International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2019: Volume 2 [1st ed.] 9783030574529, 9783030574536

Table of contents :
Front Matter ....Pages i-xvii
Front Matter ....Pages 1-1
Identification of Telltale Signature by Using Method of Adaptive Neuro-Fuzzy Systems (Denis Korochentsev, Anna Pavlenko, Roman Goncharov)....Pages 3-11
Hierarchical Quasi-Neural Network Data Aggregation to Build a University Research and Innovation Management System (Andrey Krasnov, Svetlana Pivneva)....Pages 12-25
Formalization of Ternary Logic for Application to Digital Signal Processing (Ibragim Suleimenov, Akhat Bakirov, Inabat Moldakhan)....Pages 26-35
Neural Network Modeling Methods in the Analysis of the Processing Plant’s Indicators (Egor Ushakov, Tatyana Aleksandrova, Artem Romashev)....Pages 36-45
Safety Management Technology of Electric Networks Using Geo Information System (Viacheslav Burlov, Viktor Mankov, Alexandr Tumanov, Maksim Polyukhovich)....Pages 46-56
Vladikavkaz City Seismological Network Database (Vladislav Zaalishvili, Dmitry Melkov, Aleksandr Kanukov, Madina Fidarova, Zarina Persaeva)....Pages 57-63
Regional Attenuation Relationships: Regression vs Neural Network Analysis (Vladislav Zaalishvili, Dmitry Melkov)....Pages 64-71
Use of Neural Networks to Assess Competitiveness of Organizations (Mikhail Krichevsky, Julia Martynova, Svetlana Dmitrieva)....Pages 72-82
Methods of Didactic Design in E-Learning Sphere Based on Mind Maps (Igor Kotciuba, Alexey Shikov)....Pages 83-97
Internal Control of Efficiency of Use of Budgetary Funds (Alsou Zakirova, Guzaliya Klychova, Regina Nurieva, Almaz Nigmetzyanov, Evgenia Zaugarova, Ullah Raheem)....Pages 98-123
Enterprise Architecture Modeling in Digital Transformation Era (Igor Ilin, Anastasia Levina, Alexandra Borremans, Sofia Kalyazina)....Pages 124-142
Key Digital Technologies for National Business Environment (Nikolay Pavlov, Sofia Kalyazina, Irina Bagaeva, Victoria Iliashenko)....Pages 143-157
Operational and Information Technologies Within the Enterprise Architecture: Mining Industry Case (Anastasia Levina)....Pages 158-166
Assessment of Digital Maturity of Enterprises (Igor Ilin, Daria Levaniuk, Alissa Dubgorn)....Pages 167-177
Design Theory of Network Based Smart Self-Contained Self-Rescuer with Sensor Technology (Valery Matveykin, Valery Samarin, Vladimir Nemtinov, Boris Dmitrievsky, Praveen Kumar Praveen)....Pages 178-186
Features of the Process of Digital Transformation of the Economy in Russia (Roman Ivanichkin, Pavel Kashirin, Sergey Sysoev, Oleg Shabunevich, Uwaila Osarobo James)....Pages 187-197
Spatial and Temporal Databases For Decision Making and Forecasting (Ielizaveta Dunaieva, Ekaterina Barbotkina, Valentyn Vecherkov, Valentina Popovych, Vladimir Pashtetsky, Vitaly Terleev et al.)....Pages 198-205
Front Matter ....Pages 207-207
Liquid Organic Waste Purification on the Example of Beet-Sugar Production Using Cavitation Hydrodynamic Generators (Valeriy Mishchenko, Alexey Semenov, Valentin Yatsenko, Tatyana Stepanova)....Pages 209-224
Experimental Calculation of the Main Characteristics of Thermoelectric EMF Source for the Cathodic Protection Station of Heat Supply System Pipelines (Vladimir Yezhov, Natalia Semicheva, Aleksey Burtsev, Nikita Perepelitsa)....Pages 225-237
Modeling Using Conformal Mapping of a Temperature Field Around a Hot-Water System for Channel-Free Laying (Aleksandr Loboda, Sergei Chuikin, Elena Plaksina, Lyudmila Gulak)....Pages 238-246
Development of Gas Supply Systems Using Butane-Based Gas-and-Air Mixtures (Nataliya Osipova, Sergey Kuznetsov, Svyatoslav Kultyaev)....Pages 247-257
Justification of the Choice of the Generation Capacity (Dmitrii Vasenin, Marco Pasetti, Olga Sotnikova, Tatyana Makarova)....Pages 258-265
Reorganization of System of Sanitary Purification of Municipal Solid Waste and Management of Its Disposal (Yelena Sushko, Irina Ivanova, Yelena Golovina, Anastasiya Parshina)....Pages 266-275
The Convex Fuzzy Sets and Their Properties with Application to the Modeling with Fuzzy Convex Membership Functions (Djavanshir Gadjiev, Ivan Kochetkov, Aligadzhi Rustanov)....Pages 276-284
Automation of the Construction Process by Using a Hinged Robot with Interchangeable Nozzles (Erik Grigoryan, Anna Babanina, Kirill Kulakov)....Pages 285-297
Acting Stresses in Structural Steels During Elastoplastic Deformation (Alexander Scherbakov, Anna Babanina, Kirill Graboviy)....Pages 298-311
Passive Probe-Coil Magnetic Field Test of Stress-Strain State for Welded Joints (Alexander Scherbakov, Anna Babanina, Alexander Matusevich)....Pages 312-323
Vertical Distribution of Fine Dust During Construction Operations (Svetlana Manzhilevskaya, Lubov Petrenko, Valery Azarov)....Pages 324-331
Monitoring Methods for Fine Dust Pollution During Construction Operations (Svetlana Manzhilevskaya, Lubov Petrenko, Valery Azarov)....Pages 332-340
Approximate Analytical Method for Solving the Heat Transfer Problem in a Flat Channel (Anton Eremin, Kristina Gubareva)....Pages 341-351
Stress-Strain State in Structure Angular Zone Taking into Account Differences Between Intensity Factors (Lyudmila Frishter)....Pages 352-362
Investigation of Thin Films by Using Superminiature Eddy Current Transducers (Alexey Ishkov, Vladimir Malikov)....Pages 363-370
Mathematical Modelling of Heat Transfer in Open Cell Foam of Different Porosities (Olga Soloveva, Sergei Solovev, Rishat Khusainov, Ruzil Yafizov)....Pages 371-382
Numerical Investigation of the Catalyst Granule Shapes Influence on Dehydrogenation Reaction (Sergei Solovev, Olga Soloveva, Rishat Khusainov, Alexandr Lamberov)....Pages 383-390
Assessment of the Fire Situation of a Certain Building Using Fenix+ (Marina Avdeeva, Anton Byzov, Karina Smyshlyaeva, Natalia Leonova)....Pages 391-400
Determination of the Reduced Areas of Destruction of Elements of Hazardous Production Facilities (Ekaterina Kutuzova, Vladimir Yusupdzhanov)....Pages 401-407
Integral Assessment of Anthropogenically Transformed Water Reservoirs Stability for Changes in Mode Parameters (Ekaterina Primak, Kseniya Odinokova, Nina Rumyantseva, Tatyana Kaverzneva, Sergey Efremov)....Pages 408-418
Ceramic Material Development for Phosphate Ions Removal from Local Eutrophicated Aquatic Ecosystems (Anastasiya Kolosova, Evgeniy Pikalov, Oleg Selivanov)....Pages 419-425
Ceramic Bricks Production Basing on Low-Plasticity Clay and Galvanic Sludge Addition (Anastasiya Kolosova, Evgeniy Pikalov, Oleg Selivanov)....Pages 426-431
Polymer-Ceramic Proton Exchange Membranes for Direct Methanol Fuel Cells (Alexandra Chesnokova, Tatyana Zhamsaranzhapova, Sergey Zakarchevskiy, Yuriy Pozhidaev)....Pages 432-439
Improving the Reliability of Current Collectors of the Municipal Vehicles (Valery Alisin)....Pages 440-449
Filler Impact on the Properties of Energy-Efficient Polymer Glass Composite Material (Irina Vitkalova, Anastasiya Uvarova, Evgeniy Pikalov, Oleg Selivanov)....Pages 450-456
Charge Composition Development for Heat-Resistant Ceramics (Anastasiya Uvarova, Irina Vitkalova, Evgeniy Pikalov, Oleg Selivanov)....Pages 457-463
Sanitary and Hygienic Assessment of Ceramic Bricks Containing Galvanic Sludge (Anastasiya Kolosova, Evgeniy Pikalov, Oleg Selivanov)....Pages 464-470
Mathematical Modeling and Synthesis of an Electrical Equivalent Circuit of an Electrochemical Device (Yevgeny Gerasimenko, Alla Gerasimenko, Yuri Gerasimenko, Dmitry Fugarov, Olga Purchina, Anna Poluyan)....Pages 471-480
Correlation Analysis of the Morbidity and Pollution Using GIS (Olga Burdzieva, Vladislav Zaalishvili, Aleksandr Kanukov, Tamaz Zaks)....Pages 481-491
GIS Simulation of the Geological Objects’ Soil Conditions: Strong Motion Banks and Databases (Vladislav Zaalishvili, Aleksandr Kanukov, Dmitry Melkov, Konstantin Kharebov, Madina Fidarova)....Pages 492-501
Extremum Seeking Control for the Catalytic Oxidation of Ammonia in Non-stationary Conditions (Eugeny Vasiljev, Sergey Tkalich)....Pages 502-514
Method of Infrared Reflectors Choice for Electrotechnical Polymeric Insulation Energy-Efficient Drying (Evgeny Dulskiy, Pavel Ivanov, Anatoliy Khudonogov, Viktor Kruchek, Alena Khamnaeva, Marina Divinets)....Pages 515-529
Study of the Tank Stress-Strain State with Settlement Near the Wall (Aleksandr Tarasenko, Petr Chepur, Alesya Gruchenkova)....Pages 530-536
Numerical Optimization of Film Cooling System with Injection Through Circular Holes (Nicolay Kortikov)....Pages 537-541
Modeling of Wear Processes in a Cylindrical Plain Bearing (Aleksandr Dykha, Viktor Artiukh, Ruslan Sorokatyi, Volodymyr Kukhar, Kirill Kulakov)....Pages 542-552
Modern Method of Computer Simulation of Structures and Physical Properties of Composite Materials (Milana Chantieva, Khizar Dzhabrailov, Rinat Gematudinov, Dmitriy Suvorov)....Pages 553-561
Remote Sensing of the Earth from Space to Determine the Economic Damage from Forest Fires (Mikhail Shahramanyan, Andrey Richter, Marina Danilina, Alexander Ovsianik, Stanislav Chebotarev)....Pages 562-576
Modeling of Cold-Formed Thin-Walled Steel Profile with the MBOR Fire Protection (Marina Gravit, Marina Lavrinenko, Yurij Lazarev, Artem Rozov, Anna Pavlenko)....Pages 577-592
Determining the Coefficient of Mineral Wool Vapor Permeability in Vertical Position (Kirill Zubarev, Vladimir Gagarin)....Pages 593-600
Optimizing the Temperature Stress for the Furnace Volume of a Fire-Tube Boiler (Svetlana Ovchinnikova, Denis Abornev, Michael Kalinichenko, Andrey Kalinichenko, Aleksandr Sekisov)....Pages 601-610
Temperature of Surface Layers of the Earth (Andrey Ponomaryov, Aleksandr Zakharov)....Pages 611-620
The Depth of Building Drainage in Sandy Soil (Svetlana Kaloshina, Sergei Beliaev, Dmitrii Zolotozubov)....Pages 621-630
Modeling Change of Water Content in Wood at Atmospheric Drying (Maria Zaitseva, Julia Nikonova, Gennady Kolesnikov)....Pages 631-637
Study of Aerosol Motion in Granular and Foam Filters with Equal Porosity of the Structure (Olga Soloveva)....Pages 638-649
Estimation of Portland Cement Reduction Using Polycarboxylate Based Admixture (Liliya Kazanskaya)....Pages 650-660
Hydromorphological Substantiation of Channel Stability of Navigable Rivers in Engineering Water Transport Regulation of River Runoff (Gennady Gladkov, Michail Zhuravlev, Viktor Katolikov)....Pages 661-675
Bioindication for the Search of Microorganisms-Destructors (Grigorii Kozlov, Mikhail Pushkarev, Artemiy Kozlov, Elizaveta Perepelitsa)....Pages 676-684
Probabilistic Models of the Functioning of Composite Structures with Thin-Sheet Cladding and Material-Energy-Saving Heat Insulation (Victor Bobryashov, Nikolay Bushuev)....Pages 685-697
Structural Features of Thermoplastic Marking Material with Dispersed Filler (Yuri Vasiliev, Victor Talalay, Andrey Kochetkov, Elena Surnina, Vasily Ratkin, Lyudmila Kozyreva)....Pages 698-707
Optimization of Thin-Shell Structure Covers from Position of Their Space Stability (Sergey Gridnev, Olga Sotnikova, Leonid Salogub, Vladimir Portnov)....Pages 708-720
Correction to: International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2019 (Vera Murgul, Viktor Pukhkal)....Pages C1-C1
Back Matter ....Pages 721-723

Citation preview

Advances in Intelligent Systems and Computing 1259

Vera Murgul Viktor Pukhkal   Editors

International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2019 Volume 2

Advances in Intelligent Systems and Computing Volume 1259

Series Editor Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Advisory Editors Nikhil R. Pal, Indian Statistical Institute, Kolkata, India Rafael Bello Perez, Faculty of Mathematics, Physics and Computing, Universidad Central de Las Villas, Santa Clara, Cuba Emilio S. Corchado, University of Salamanca, Salamanca, Spain Hani Hagras, School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK László T. Kóczy, Department of Automation, Széchenyi István University, Gyor, Hungary Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA Chin-Teng Lin, Department of Electrical Engineering, National Chiao Tung University, Hsinchu, Taiwan Jie Lu, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia Patricia Melin, Graduate Program of Computer Science, Tijuana Institute of Technology, Tijuana, Mexico Nadia Nedjah, Department of Electronics Engineering, University of Rio de Janeiro, Rio de Janeiro, Brazil Ngoc Thanh Nguyen , Faculty of Computer Science and Management, Wrocław University of Technology, Wrocław, Poland Jun Wang, Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

The series “Advances in Intelligent Systems and Computing” contains publications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all disciplines such as engineering, natural sciences, computer and information science, ICT, economics, business, e-commerce, environment, healthcare, life science are covered. The list of topics spans all the areas of modern intelligent systems and computing such as: computational intelligence, soft computing including neural networks, fuzzy systems, evolutionary computing and the fusion of these paradigms, social intelligence, ambient intelligence, computational neuroscience, artificial life, virtual worlds and society, cognitive science and systems, Perception and Vision, DNA and immune based systems, self-organizing and adaptive systems, e-Learning and teaching, human-centered and human-centric computing, recommender systems, intelligent control, robotics and mechatronics including human-machine teaming, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, Web intelligence and multimedia. The publications within “Advances in Intelligent Systems and Computing” are primarily proceedings of important conferences, symposia and congresses. They cover significant recent developments in the field, both of a foundational and applicable character. An important characteristic feature of the series is the short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results. ** Indexing: The books of this series are submitted to ISI Proceedings, EI-Compendex, DBLP, SCOPUS, Google Scholar and Springerlink **

More information about this series at http://www.springer.com/series/11156

Vera Murgul Viktor Pukhkal •

Editors

International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2019 Volume 2

123

Editors Vera Murgul Peter the Great St. Petersburg Polytechnic Saint Petersburg, Russia

Viktor Pukhkal Saint Petersburg State University of Architecture and Civil Engineering Saint Petersburg, Russia

ISSN 2194-5357 ISSN 2194-5365 (electronic) Advances in Intelligent Systems and Computing ISBN 978-3-030-57452-9 ISBN 978-3-030-57453-6 (eBook) https://doi.org/10.1007/978-3-030-57453-6 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

This book presents a collection of the latest studies in the field of the sustainable development of urban energy systems and new strategies for the transportation sector. The international scientific conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2019 took place in Voronezh State Technical University on November 28–30, 2019, in the city of Voronezh. This annual scientific event brought together guests and participants from throughout Russia and different foreign countries. As traditionally, the main topics to discuss were sustainable energy technologies, building energy modeling, energy efficiency in transport sector, electrical energy storage; energy management and life cycle assessment in urban systems and transportation. The objective of the conference was the exchange of the latest scientific achievements, strengthening of academic relations with leading scientists of the European Union, creating favorable conditions for collaborative researches and implementing collaborative projects, encourage young scientists, doctoral and postgraduate students in their scientific and practical work related to the field of new energy technologies. The newest equipment and devices for HVAC-systems were demonstrated, and the latest technologies of thermal protection of buildings were shared. Over more than 250 papers were submitted for the conference. All papers passed scientific and technical review. Finally, 136 papers were accepted. Within the framework of technical review, all papers were thoroughly checked for the following attributes: compliance with the subject of the conference; plagiarism (acceptable minimum of originality was 90%); acceptable English language. At the same time, papers were checked by a technical proofreader (for the quality of images, absence of Cyrillic, etc.). Scientific review of each paper was made by at least three reviewers. If the opinions of the reviewers were radically different, additional reviewers were appointed.

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Preface

Live participation in the conference was an indispensable condition for the publication of a paper. The book is intended for a broad readership: from policymakers tasked with evaluating and promoting key enabling technologies, efficiency policies and sustainable energy practices, to researchers and engineers involved in the design and analysis of complex systems. All the participants and organizers express their gratitude to Springer publishing office and to the editing group of journal Advances in Intelligent Systems and Computing for publishing the proceedings of the conference. Vera Murgul Viktor Pukhkal

Organization

Scientific Committee Samuil G. Konnikov

Iurii Tabunschikov

Antony Wood

Viktor Pukhkal

Sergey Anisimov Marianna M. Brodach

Igor Surovtsev Daniel Safarik

Full Member of the Russian Academy of Sciences, Ioffe Physical-Technical Institute of the Russian Academy of Sciences Corr. Member of RAASN, Honorary Member of the International Ecoenergetic Academy of Azerbaijan, ASHRAE fellow member, REHVA fellow member, corr. member of VDI, member of ISIAQ Academy, Winner of the 2008 Nobel Peace Prize as a Member of the Intergovernmental Panel on Climate Change Executive Director (CTBUH), Visiting Prof. of Tall Buildings, Tongji University, Shanghai, China, Studio Ass. Prof., Illinois Institute of Technology, Chicago, the USA Head of the Department of Heat and Gas supply and Ventilation, Saint Petersburg State University of Architecture and Civil Engineering Wroclaw University of Science and Technology, Professor, Poland Moscow Architectural Institute (State Academy), Vice President of Russian Association of Engineers for Heating, Ventilation, Air-Conditioning, Heat Supply and Building Thermal Physics “ABOK”, ASHRAE member, REHVA Fellow Member, Member of the Editorial Board of REHVA Journal Head of the Department of Innovation and Building Physics Voronezh State Technical University Director (CTBUH China Office), Editor (CTBUH Journal), Chicago, the USA

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Aleksander Szkarowski

Alexander Solovyev

Dietmar Wiegand Luís Bragança

Zdenka Popovic Marco Pasetti Valerii Volshanik Mirjana Vukićević Sang Dae Kim

Alenka Fikfak

Milorad Jovanovski Škoda, Radek

Paulo Cachim Aires Camões Michael Tendler

Christoph Pfeifer

Antonio Andreini Pietro Zunino

Organization

Head of the Construction Networks and Systems Division Department of Civil & Environmental Engineering and Geodesy, Koszalin University of Technology, Koszalin, Poland Head of the Research Laboratory of Renewable Energy Sources Lomonosov Moscow State University, Full member of Russian Academy of Natural Sciences Technische Universität Wien TU Wien Director of the Building Physics & Technology Laboratory, Guimaraes, University of Minho, Portugal Belgrade University of Belgrade, Faculty of Civil Engineering, Serbia Università degli Studi di Brescia UNIBS, Italy Moscow State University of Civil Engineering Faculty of Civil Engineering, University of Belgrade, Serbia Chief Editor (International Journal of High-rise Buildings), Emeritus Professor, Department of Civil, Environmental and Architectural Engineering, Korea University, Seoul, South Korea University of Ljubljana: Faculty of Civil and Geodetic Engineering (Department of Town & Regional Planning) Biotechnical Faculty (Department of Landscape Architecture), Slovenia Faculty of Civil Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia Czech Technical University in Prague, Faculty of Mechanical Engineering, Department of Nuclear Energetics Technická Department of Civil Engineering, University of Aveiro, Portugal Director of the Materials of Construction Laboratory, Guimarães, University of Minho, Portugal Currently Professor of Fusion Plasma Physics at the Royal Institute of Technology, Stockholm (KTH) and Senior Science Expert and member of the External Management Advisory Board of the ITER Organization, Kungliga Tekniska Högskolan, Sweden Professor of Process Engineering of Renewable Resources, University of Natural Resources and Life Sciences, Vienna, Austria The University of Florence, UNIFI, Italy DIME Universitá di Genova, Genoa, Italy

Organization

Olga Kalinina Tomas Hanak Vera Murgul Darya Nemova Norbert Harmathy

Igor V. Ilyin

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Peter the Great St. Petersburg Polytechnic University, Russia Faculty of Civil Engineering, Brno University of Technology, Czech Republic Peter the Great St. Petersburg Polytechnic University, Russia Peter the Great St. Petersburg Polytechnic University Budapest University of Technology and Economics, Department of Building Energetics and Building Services Peter the Great Saint-Petersburg Polytechnic University, Russia

Contents

Digital Technologies and Neural Networks Identification of Telltale Signature by Using Method of Adaptive Neuro-Fuzzy Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Denis Korochentsev, Anna Pavlenko, and Roman Goncharov

3

Hierarchical Quasi-Neural Network Data Aggregation to Build a University Research and Innovation Management System . . . Andrey Krasnov and Svetlana Pivneva

12

Formalization of Ternary Logic for Application to Digital Signal Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ibragim Suleimenov, Akhat Bakirov, and Inabat Moldakhan

26

Neural Network Modeling Methods in the Analysis of the Processing Plant’s Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Egor Ushakov, Tatyana Aleksandrova, and Artem Romashev

36

Safety Management Technology of Electric Networks Using Geo Information System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Viacheslav Burlov, Viktor Mankov, Alexandr Tumanov, and Maksim Polyukhovich Vladikavkaz City Seismological Network Database . . . . . . . . . . . . . . . . Vladislav Zaalishvili, Dmitry Melkov, Aleksandr Kanukov, Madina Fidarova, and Zarina Persaeva

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Regional Attenuation Relationships: Regression vs Neural Network Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vladislav Zaalishvili and Dmitry Melkov

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Use of Neural Networks to Assess Competitiveness of Organizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mikhail Krichevsky, Julia Martynova, and Svetlana Dmitrieva

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Contents

Methods of Didactic Design in E-Learning Sphere Based on Mind Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Igor Kotciuba and Alexey Shikov Internal Control of Efficiency of Use of Budgetary Funds . . . . . . . . . . . Alsou Zakirova, Guzaliya Klychova, Regina Nurieva, Almaz Nigmetzyanov, Evgenia Zaugarova, and Ullah Raheem

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Enterprise Architecture Modeling in Digital Transformation Era . . . . . 124 Igor Ilin, Anastasia Levina, Alexandra Borremans, and Sofia Kalyazina Key Digital Technologies for National Business Environment . . . . . . . . 143 Nikolay Pavlov, Sofia Kalyazina, Irina Bagaeva, and Victoria Iliashenko Operational and Information Technologies Within the Enterprise Architecture: Mining Industry Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 Anastasia Levina Assessment of Digital Maturity of Enterprises . . . . . . . . . . . . . . . . . . . . 167 Igor Ilin, Daria Levaniuk, and Alissa Dubgorn Design Theory of Network Based Smart Self-Contained Self-Rescuer with Sensor Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 Valery Matveykin, Valery Samarin, Vladimir Nemtinov, Boris Dmitrievsky, and Praveen Kumar Praveen Features of the Process of Digital Transformation of the Economy in Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Roman Ivanichkin, Pavel Kashirin, Sergey Sysoev, Oleg Shabunevich, and Uwaila Osarobo James Spatial and Temporal Databases For Decision Making and Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 Ielizaveta Dunaieva, Ekaterina Barbotkina, Valentyn Vecherkov, Valentina Popovych, Vladimir Pashtetsky, Vitaly Terleev, Aleksandr Nikonorov, and Luka Akimov Materials Science and Engineering for Energy Systems Liquid Organic Waste Purification on the Example of Beet-Sugar Production Using Cavitation Hydrodynamic Generators . . . . . . . . . . . . 209 Valeriy Mishchenko, Alexey Semenov, Valentin Yatsenko, and Tatyana Stepanova Experimental Calculation of the Main Characteristics of Thermoelectric EMF Source for the Cathodic Protection Station of Heat Supply System Pipelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 Vladimir Yezhov, Natalia Semicheva, Aleksey Burtsev, and Nikita Perepelitsa

Contents

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Modeling Using Conformal Mapping of a Temperature Field Around a Hot-Water System for Channel-Free Laying . . . . . . . . . . . . . . . . . . . . 238 Aleksandr Loboda, Sergei Chuikin, Elena Plaksina, and Lyudmila Gulak Development of Gas Supply Systems Using Butane-Based Gas-and-Air Mixtures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Nataliya Osipova, Sergey Kuznetsov, and Svyatoslav Kultyaev Justification of the Choice of the Generation Capacity . . . . . . . . . . . . . . 258 Dmitrii Vasenin, Marco Pasetti, Olga Sotnikova, and Tatyana Makarova Reorganization of System of Sanitary Purification of Municipal Solid Waste and Management of Its Disposal . . . . . . . . . . . . . . . . . . . . . . . . . 266 Yelena Sushko, Irina Ivanova, Yelena Golovina, and Anastasiya Parshina The Convex Fuzzy Sets and Their Properties with Application to the Modeling with Fuzzy Convex Membership Functions . . . . . . . . . 276 Djavanshir Gadjiev, Ivan Kochetkov, and Aligadzhi Rustanov Automation of the Construction Process by Using a Hinged Robot with Interchangeable Nozzles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 Erik Grigoryan, Anna Babanina, and Kirill Kulakov Acting Stresses in Structural Steels During Elastoplastic Deformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298 Alexander Scherbakov, Anna Babanina, and Kirill Graboviy Passive Probe-Coil Magnetic Field Test of Stress-Strain State for Welded Joints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312 Alexander Scherbakov, Anna Babanina, and Alexander Matusevich Vertical Distribution of Fine Dust During Construction Operations . . . . 324 Svetlana Manzhilevskaya, Lubov Petrenko, and Valery Azarov Monitoring Methods for Fine Dust Pollution During Construction Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332 Svetlana Manzhilevskaya, Lubov Petrenko, and Valery Azarov Approximate Analytical Method for Solving the Heat Transfer Problem in a Flat Channel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 Anton Eremin and Kristina Gubareva Stress-Strain State in Structure Angular Zone Taking into Account Differences Between Intensity Factors . . . . . . . . . . . . . . . . 352 Lyudmila Frishter Investigation of Thin Films by Using Superminiature Eddy Current Transducers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363 Alexey Ishkov and Vladimir Malikov

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Mathematical Modelling of Heat Transfer in Open Cell Foam of Different Porosities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 Olga Soloveva, Sergei Solovev, Rishat Khusainov, and Ruzil Yafizov Numerical Investigation of the Catalyst Granule Shapes Influence on Dehydrogenation Reaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383 Sergei Solovev, Olga Soloveva, Rishat Khusainov, and Alexandr Lamberov Assessment of the Fire Situation of a Certain Building Using Fenix+ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 Marina Avdeeva, Anton Byzov, Karina Smyshlyaeva, and Natalia Leonova Determination of the Reduced Areas of Destruction of Elements of Hazardous Production Facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 Ekaterina Kutuzova and Vladimir Yusupdzhanov Integral Assessment of Anthropogenically Transformed Water Reservoirs Stability for Changes in Mode Parameters . . . . . . . . . . . . . . 408 Ekaterina Primak, Kseniya Odinokova, Nina Rumyantseva, Tatyana Kaverzneva, and Sergey Efremov Studying Ceramic Bricks Production Possibility Basing on Low-Plasticity Clay and Galvanic Sludge Addition . . . . . . . . . . . . . . 419 Anastasiya Kolosova, Evgeniy Pikalov, and Oleg Selivanov Ceramic Bricks Production Basing on Low-Plasticity Clay and Galvanic Sludge Addition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426 Anastasiya Kolosova, Evgeniy Pikalov, and Oleg Selivanov Polymer-Ceramic Proton Exchange Membranes for Direct Methanol Fuel Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 Alexandra Chesnokova, Tatyana Zhamsaranzhapova, Sergey Zakarchevskiy, and Yuriy Pozhidaev Improving the Reliability of Current Collectors of the Municipal Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 440 Valery Alisin Filler Impact on the Properties of Energy-Efficient Polymer Glass Composite Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 450 Irina Vitkalova, Anastasiya Uvarova, Evgeniy Pikalov, and Oleg Selivanov Charge Composition Development for Heat-Resistant Ceramics . . . . . . 457 Anastasiya Uvarova, Irina Vitkalova, Evgeniy Pikalov, and Oleg Selivanov Sanitary and Hygienic Assessment of Ceramic Bricks Containing Galvanic Sludge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464 Anastasiya Kolosova, Evgeniy Pikalov, and Oleg Selivanov

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Mathematical Modeling and Synthesis of an Electrical Equivalent Circuit of an Electrochemical Device . . . . . . . . . . . . . . . . . . . . . . . . . . . 471 Yevgeny Gerasimenko, Alla Gerasimenko, Yuri Gerasimenko, Dmitry Fugarov, Olga Purchina, and Anna Poluyan Correlation Analysis of the Morbidity and Pollution Using GIS . . . . . . 481 Olga Burdzieva, Vladislav Zaalishvili, Aleksandr Kanukov, and Tamaz Zaks GIS Simulation of the Geological Objects’ Soil Conditions: Strong Motion Banks and Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . 492 Vladislav Zaalishvili, Aleksandr Kanukov, Dmitry Melkov, Konstantin Kharebov, and Madina Fidarova Extremum Seeking Control for the Catalytic Oxidation of Ammonia in Non-stationary Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502 Eugeny Vasiljev and Sergey Tkalich Method of Infrared Reflectors Choice for Electrotechnical Polymeric Insulation Energy-Efficient Drying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515 Evgeny Dulskiy, Pavel Ivanov, Anatoliy Khudonogov, Viktor Kruchek, Alena Khamnaeva, and Marina Divinets Study of the Tank Stress-Strain State with Settlement Near the Wall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Aleksandr Tarasenko, Petr Chepur, and Alesya Gruchenkova Numerical Optimization of Film Cooling System with Injection Through Circular Holes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537 Nicolay Kortikov Modeling of Wear Processes in a Cylindrical Plain Bearing . . . . . . . . . 542 Aleksandr Dykha, Viktor Artiukh, Ruslan Sorokatyi, Volodymyr Kukhar, and Kirill Kulakov Modern Method of Computer Simulation of Structures and Physical Properties of Composite Materials . . . . . . . . . . . . . . . . . . 553 Milana Chantieva, Khizar Dzhabrailov, Rinat Gematudinov, and Dmitriy Suvorov Remote Sensing of the Earth from Space to Determine the Economic Damage from Forest Fires . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 562 Mikhail Shahramanyan, Andrey Richter, Marina Danilina, Alexander Ovsianik, and Stanislav Chebotarev Modeling of Cold-Formed Thin-Walled Steel Profile with the MBOR Fire Protection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 577 Marina Gravit, Marina Lavrinenko, Yurij Lazarev, Artem Rozov, and Anna Pavlenko

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Determining the Coefficient of Mineral Wool Vapor Permeability in Vertical Position . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 593 Kirill Zubarev and Vladimir Gagarin Optimizing the Temperature Stress for the Furnace Volume of a Fire-Tube Boiler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 601 Svetlana Ovchinnikova, Denis Abornev, Michael Kalinichenko, Andrey Kalinichenko, and Aleksandr Sekisov Temperature of Surface Layers of the Earth . . . . . . . . . . . . . . . . . . . . . 611 Andrey Ponomaryov and Aleksandr Zakharov The Depth of Building Drainage in Sandy Soil . . . . . . . . . . . . . . . . . . . 621 Svetlana Kaloshina, Sergei Beliaev, and Dmitrii Zolotozubov Modeling Change of Water Content in Wood at Atmospheric Drying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 631 Maria Zaitseva, Julia Nikonova, and Gennady Kolesnikov Study of Aerosol Motion in Granular and Foam Filters with Equal Porosity of the Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 638 Olga Soloveva Estimation of Portland Cement Reduction Using Polycarboxylate Based Admixture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 650 Liliya Kazanskaya Hydromorphological Substantiation of Channel Stability of Navigable Rivers in Engineering Water Transport Regulation of River Runoff . . . 661 Gennady Gladkov, Michail Zhuravlev, and Viktor Katolikov Bioindication for the Search of Microorganisms-Destructors . . . . . . . . . 676 Grigorii Kozlov, Mikhail Pushkarev, Artemiy Kozlov, and Elizaveta Perepelitsa Probabilistic Models of the Functioning of Composite Structures with Thin-Sheet Cladding and Material-Energy-Saving Heat Insulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 685 Victor Bobryashov and Nikolay Bushuev Structural Features of Thermoplastic Marking Material with Dispersed Filler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 698 Yuri Vasiliev, Victor Talalay, Andrey Kochetkov, Elena Surnina, Vasily Ratkin, and Lyudmila Kozyreva

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Optimization of Thin-Shell Structure Covers from Position of Their Space Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 708 Sergey Gridnev, Olga Sotnikova, Leonid Salogub, and Vladimir Portnov Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 721

Digital Technologies and Neural Networks

Identification of Telltale Signature by Using Method of Adaptive Neuro-Fuzzy Systems Denis Korochentsev , Anna Pavlenko(B)

, and Roman Goncharov

Don State Technical University, Pl. Gagarina, 1, Rostov-on-Don, Rostov Region 344002, Russia [email protected], [email protected], [email protected]

Abstract. The article is devoted to the problem of using the method of adaptive neuro-fuzzy networks to assess the informativeness of the telltale signature of the object of protection. In ANFIS, a fuzzy system is used to represent knowledge in an interpreted form, as well as the ability to train a neural network to optimize the parameters of a fuzzy system. The training data base was based on the results of the previous study, which consisted in building a decision support subsystem for identifying the set of telltale signature of a protected object based on expert judgment. It contains information about the informativeness of each group of telltale signature and is used in the process of learning a neural network. Constantly changing the parameters of the membership functions when learning a neuro-fuzzy system allows you to more accurately configure the system to solve the task. The study showed the possibility of using the method of adaptive neuro-fuzzy networks in the process of evaluating the informativity of the telltale signature. Keywords: Telltale signature · ANFIS · Neural network · Fuzzy logic

1 Introduction Competitive intelligence is an accessible method of obtaining information, which is the basis for the strategic planning process and necessary for making strategic decisions when doing business. Intelligence involves obtaining and processing information about a competitor in order to gain an advantage over him. Such information may include not only data on financial, property, management resources, but also information on intellectual property and utility models. To effectively counteract competitive intelligence in relation to the developed products, it is necessary to analyze their telltale signatures in order to further reduce the information content of the required features. In this regard, there is a need to develop a system for assessing the information content of the telltale signatures of the object under study. A feature of an object that allows you to detect and recognize the object of informatization, to which the feature belongs, is called a telltale signature. Comparison of the received parameters allows you to refer the object of protection to a certain class, kind, and type and, using the means of technical recognition of sources, to certain object, i.e. to make recognition of this object. The method of adaptive neuro-fuzzy systems was proposed to use for the system of identification of telltale signatures of the object. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 3–11, 2021. https://doi.org/10.1007/978-3-030-57453-6_1

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2 Materials and Methods Adaptive neuro-fuzzy inference system (ANFIS) is a hybrid system that combines fuzzy logic and neural network methods to take advantage of the main advantages of these methods: fuzzy logic takes into account the inaccuracy and uncertainty of the simulated system, while neural network allows the system to adapt the initial rules of the fuzzy system to obtain a final ANFIS model that will fit the task. The structure of the adaptive neuro-fuzzy system consists of 5 blocks: – a rule base containing fuzzy If-Then rules; – a knowledge base that stores membership functions of fuzzy sets used in If-Then rules; – a decision block that produces output based on If-Then rules; – a fuzzification interface that converts clear data into degrees of belonging to linguistic terms; – a defuzzification interface converts the fuzzy result into a crisp output of the system. It is known that the number of z rules of a neuro-fuzzy system directly depends on the characteristics of the system by the ratio: z = un

(1)

where n is the number of inputs of the neuro-fuzzy system; u is the number of linguistic terms for the input variable. In this regard, as the optimal number of inputs of the neuro-fuzzy system was chosen the number of types of telltale signatures (visual signal, acoustic and radio signals, and material signal), described by three linguistic terms: {‘Low’, ‘Medium’ ‘High’}. Then the number of rules of the neuro-fuzzy system z = 81. In the preparation of training data, we used the achievements of the previous study, the result of which was a subsystem of decision support for the identification of a set of telltale signatures of the object. Normalized input data, which describe the informativeness of twenty common telltale signatures, as well as the result of the subsystem based on their analysis, were taken as initial information for the development of the system. The result for each type of telltale signatures was calculated as a normalized sum of the values of information content of the telltale signatures that make up this type. Table 1 shows part of the training data for the adaptive neuro-fuzzy system. With integrated knowledge for different combinations of information content of telltale signatures available in the database, it is possible to build a logical inference system that will provide automatic processing of this knowledge. As a consequence, it is possible to create a computer system that will allow you to create new knowledge without the need to conduct additional experiments [1]. The developed adaptive neuro-fuzzy system uses Takagi-Sugeno [2] fuzzy rules, which have the form: R: IF x1 is Ai1 AND x2 is Aj2 THEN z is f (x1 , x2 ) where A1 , A2 ,…, An - are the fuzzy sets used to fuzzify each parameter.

(2)

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Table 1. Training data for neuro-fuzzy system. Input data

Result

Visual

Acoustic

Radio signals

Material

0.49

0

0.64

0.34

0.43

0.59

0

0

0.33

0.42

0.5

0

0.49

0.68

0.46

0.31

0.49

0

0.56

0.37

0.56

0

0

0.63

0.42

0.68

0

0.67

0.45

0.6

0.68

0

0

0.27

0.45

0.46

0

0

0.49

0.4

For example, to find the informative character structure of the object, fuzzy rules can be of the form: R1: IF visual is “Low” AND acoustic is “High” AND radio is “High” AND material is “Medium” THEN z is f1 = p1 x1 + q1 x2 + r1 Adaptive neuro-fuzzy model is usually represented as a six-layer feedforward neural network [3], the structure of which is presented in Fig. 1.

Fig. 1. Structure of adaptive neuro-fuzzy system.

The first layer of the adaptive neuro-fuzzy system is called the input layer. The neurons of this layer transfer the input data to the second layer without converting [4–6].

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The second layer, the fuzzification layer, determines the degrees of membership of the input value to the fuzzy sets A1 , A2 ,…, An . This layer is adaptive, and each node has an activation function [7]: O1k = µAi (X)

(3)

where x is the input value of the node k; Ai is the fuzzy set describing the linguistic variables; µAi is a function of belonging to Ai . Typically, the membership function µAi selects a bell-shaped function that has the form [8]: µ (x; b, c, d)

1  x - c 2b ,   1+

(4)

d

where b is the steepness coefficient of the membership function; c-coordinate of the maximum of the membership function; d is the concentration coefficient of the membership function. Each neuron of the third layer (the rules layer) calculates the degree of wk membership, which determines how fuzzy the rule corresponds to the input value. The output of each neuron is the product of all incoming signals and is determined as [9–12]: wk = µA1i (x1 ) × µAj2 (x2 )

(5)

Layer 4 is called the normalization layer. Each neuron in this layer receives input data from all neurons in the rule layer and calculates the normalized degree of membership of a given rule, which determines the contribution of a given fuzzy rule to the result. The output of the k-th layer 4 neuron is determined as [13, 14]: wk wk = n

j = 0 wn

,

(6)

where n is the total number of fuzzy rules. Layer 5 is the defuzzification layer. Each neuron in this layer is connected to the corresponding normalization neuron of the fourth layer, and also receives initial inputs: x1 , x2 ,…, xn (visual, acoustic, radio signal, material telltale signatures). The defuzzification neuron calculates the weighted value of a given rule as: Wk fk = Wk (pk x1 + qk x2 + rk ),

(7)

Layer 6 is represented by one neuron, which calculates the sum of outputs of all defuzzification neurons and produces the overall ANFIS output [15]. Thus, the parameters of the neuro-fuzzy system regulated by the neural network include: {bk , ck , dk } - parameters of prerequisites of the system, which are nonlinear parameters of the bell-shaped membership function; {pk , qk , rk } - parameters of the consequences of the system, coefficients of the polynomial of the first degree.

Identification of Telltale Signature

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3 Research Results The algorithm inputs four variables describing the informativeness of each type of telltale signatures (Fig. 2).

Fig. 2. General scheme of neuro-fuzzy network.

The process of teaching a neural network is a change in the internal parameters of the network to more accurately match the task. The neural network parameters are updated using a hybrid optimization method that combines the method of back propagation of error for the parameters of the perquisites and the method of least squares for the parameters of the consequences of the system. The neuro-fuzzy system has a training error of about 3.5% after 100 epochs of teaching (Fig. 3). After that, the system begins testing with a test file containing data that was not used in the process of system training. A fuzzy system trained with the ANFIS method has a generalization error of about 10%.

Fig. 3. Dependence of the neural network teaching error on the number of epochs.

Figure 4 shows the input data membership functions after neural network training.

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Fig. 4. Post-training input membership functions.

Figure 5 shows the structure of the neuro-fuzzy system. The system is able to calculate the result for the entire range of input values. Figure 6 shows a graphical representation of the fuzzy output of the system based on the generated fuzzy rules for the input values {visual = 0.59; acoustic = 0; radio signal = 0; material = 0.33}. The system decided that the informative character structure for these input values is 0.406, while the actual result is 0.42. The error of this decision does not exceed the stated 10% (Fig. 6).

Identification of Telltale Signature input visual

inputmf

rule

outputmf

output

low medium high

acoustic

low medium high

radiosignal

low medium high

low

material

LogicalOperations

medium

and

high

Fig. 5. Detailed structure of the neuro-fuzzy system.

Fig. 6. Graphical representation of neuro-fuzzy inference.

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4 Conclusion Thus, the study allows us to conclude that it is possible to build a neuro-fuzzy system of identification of telltale signatures on the basis of data obtained from the previous study, and to ensure the accuracy of decision-making of about 90% of the real values. This will allow you in the future to reduce the costs of certification of the object of informatization for activities that are mainly aimed at identifying informative telltale signatures of objects of protection. ANFIS allows you to present the results in a readable form and provides the finding of suitable values of the membership function for a fuzzy system. The developed algorithm in the form of a ready-made program can be used by security specialists of both large and small enterprises, which need information protection.

References 1. Mrzygłód, B., Gumienny, G., Wilk-Kołodziejczyk, D.: Application of selected artificial intelligence methods in a system predicting the microstructure of compacted graphite iron. J. Mater. Eng. Perform. 28, 3894–3904 (2019). https://doi.org/10.1007/s11665-019-03932-4 2. Buragohaın, M.: Adaptive network based fuzzy inference system (ANFIS) as a tool for system identification with special emphasis on training data minimization. A thesis submitted in partial fulfilment of the requirements for the degree of doctor of philosophy, Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati, Guwahati, India (2008) 3. Kriesel, D.: A Brief Introduction to Neural Networks (2007) 4. Amiri, A.M., Nadimi, N., Yousefian, A.: Comparing the efficiency of different computation intelligence techniques in predicting accident frequency. In: IATSS Research (2020). https:// doi.org/10.1016/j.iatssr.2020.03.003 5. Venugopal, C., Devi, S., Rao, K.: Predicting ERP user satisfaction–an adaptive neuro fuzzy inference system (ANFIS) approach. Intell. Inf. Manag. 2(7), 422–430 (2010). https://doi. org/10.4236/iim.2010.27052 6. Yildiz, A., Yarar, A., Kumcu, S.Y., Marti, A.I.: Numerical and ANFIS modeling of flow over an ogee-crested spillway. Appl. Water Sci. 10, 90 (2020). https://doi.org/10.1007/s13201020-1177-4 7. Sharifian, S., Madadkhani, M., Rahimi, M., Mir, M., Baghban, A.: QSPR based ANFIS model for predicting standard molar chemical exergy of organic materials. Pet. Sci. Technol. 37, 1–8 (2019). https://doi.org/10.1080/10916466.2018.1496100 8. Oubehar, H., Selmani, A., Ed-Dahhak, A., Lachhab, A., Archidi, M.E.H., Bouchikhi, B.: ANFIS-based climate controller for computerized greenhouse system. Adv. Sci. Technol. Eng. Syst. J. 5, 8–12 (2020). https://doi.org/10.25046/aj050102 9. Al-Hmouz, A., Shen, J., Al-Hmouz, R., Yan, J.: Modeling and simulation of an adaptive neuro-fuzzy inference system (ANFIS) for mobile learning. IEEE Trans. Learn. Technol. 5, 226–237 (2012). https://doi.org/10.1109/TLT.2011.36 10. Ata, R., Koçyigit, Y.: An adaptive neuro-fuzzy inference system approach for prediction of tip speed ratio in wind turbines. Expert Syst. Appl. 37, 5454–5460 (2010). https://doi.org/10. 1016/j.eswa.2010.02.068 11. Azar, A.T.: Adaptive neuro-fuzzy systems. Fuzzy Systems. IN-TECH, Austria (2010). https:// doi.org/10.5772/7220

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12. Razavi, R., Sabaghmoghadam, A., Bemani, A., Baghban, A., Chau, K.W., Salwana, E.: Application of ANFIS and LSSVM strategies for estimating thermal conductivity enhancement of metal and metal oxide based nanofluids. Eng. Appl. Comput. Fluid Mech. 13, 560–578 (2019). https://doi.org/10.1080/19942060.2019.1620130 13. Sujatha, K., Vaisakh, K.: Implementation of adaptive neuro fuzzy inference system in speed control of induction motor drives. J. Intell. Learn. Syst. Appl. 2(2), 110–118 (2010). https:// doi.org/10.4236/jilsa.2010.22014 14. Tay, K., Muwafaq, H., Ismail, S., Ong, P.: Electricity consumption forecasting using adaptive neuro-fuzzy inference system (ANFIS). Univ. J. Electr. Electron. Eng. 6, 37–48 (2019). https:// doi.org/10.13189/ujeee.2019.061606 15. Penghui, L., Ewees, A., Beyaztas, B., Qi, C., Salih, S., Al-Ansari, N., Bhagat, S., Yaseen, Z., Singh, V.: Metaheuristic optimization algorithms hybridized with artificial intelligence model for soil temperature prediction: novel model. IEEE Access 8, 51884–51904 (2020). https:// doi.org/10.1109/ACCESS.2020.2979822

Hierarchical Quasi-Neural Network Data Aggregation to Build a University Research and Innovation Management System Andrey Krasnov(B)

and Svetlana Pivneva(B)

Russian State Social University, Str. Wilhelm Pik, 4 Building 1, Moscow 129226, Russia [email protected], [email protected]

Abstract. An approach to the formation of numerical values of metadata generated on the basis of the method of semantic decomposition of numerous indicators characterizing the research and innovation activities of the university, as well as their combination based on the method of hierarchical quasi-neural network aggregation, is considered. The developed methods are necessary for monitoring the state of scientific and innovative activities of the university, as a first step in building its management system. The aim of the work is to develop a method of hierarchical aggregation of data based on their presentation in the form of a quasineural network structure, the input of which is the data itself, and the output is a set of metadata or indicators of the state of the scientific and innovative activity of the university, characterizing the degree of data compliance with their planned criteria indicators. The leading approach includes: semantic decomposition of data into elementary aggregates; formation of aggregate metadata in the form of indicators characterizing the degree of compliance of aggregated data with planned criteria indicators. Keywords: Scientific and innovative activity · Semantic decomposition · Metadata · Hierarchical · Quasi-neural network · Aggregation · Interactions · Synergism

1 Introduction Any university that implements a higher education program, by its organization and activities, refers to complex organizational systems [1]. At present, the description and study of complex systems operating with big data is carried out on the basis of the AHP (Analytic Hierarchy Process) methods: analysis (decomposition) and subsequent synthesis (aggregation) of their hierarchical entities (for decision making, planning, conflict resolution and in neural synthesis) [2]. However, as practice has shown, even with a balanced system of indicators (organizations and universities), there are no formal methods for decomposing and aggregating data [3]. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 12–25, 2021. https://doi.org/10.1007/978-3-030-57453-6_2

Hierarchical Quasi-Neural Network Data Aggregation

13

In the theory of systems for aggregation, the methods of linear and nonlinear transformations of their phase vectors are widely used, as well as the apparatus of the theory of continuous groups, which allows to reduce the dimensionality of the description of both static systems, for example, in problems of clustering and pattern recognition, and dynamic systems, for example, in control and identification problems. It should be noted that, despite the developed mathematical apparatus, both for AHP [4] and for aggregation of dynamical systems [3], the corresponding decomposition and aggregation methods are quite complicated. Also important is the fact that in many cases it is impossible to introduce relations of dominance of individual indicators of the scientific and innovative activity of the university. Therefore, the work laid the foundation for simpler methods for decomposing technology, production, and business objects based on the IDEF standard and hierarchical aggregation of decomposed entities based on quasi-neural network technology. The aim of this work is to develop a method of hierarchical aggregation of data based on their presentation in the form of a quasi-neural network structure, the input of which is the data itself, and the output is a set of metadata or indicators of the state of the university’s research and innovation activity, which characterizes the degree of data compliance with planned criteria indicators.

2 Related Work For the first time, the idea of using an eigenvector to solve the so-called leader problem is known from the work of C. Berge, who proposed it for processing simple structures. Independently, Brook, Burkov in the USSR and Saaty in the USA [4] proposed a model for hierarchical ordering of relations between different data. Saaty and his followers developed the idea of using their own vector as a vector of priorities in a powerful methodology for system analysis of hierarchical process (AHP). Special issues of two journals are devoted to the method of analyzing hierarchies. In 1986, two reviews were published that presented data on most of the papers published by that time on AHP. The number of applied articles with solutions to problems from different fields on the basis of AHP is measured in thousands. Since 1988 (every two years), an International Symposium on the IAI (International Symposium on Analytic Hierarchy Process, ISAHP) has been held. The axiomatic substantiation of the method of analyzing hierarchies was first given in [4], where a number of general theorems are given that determine the operational capabilities of the AHP, showing the convenience of pairwise comparisons and the eigenvector method when evaluating relations, and the stability of the eigenvector to small perturbations in the data is investigated. Saaty and Vargam in [4] studied interval estimates by modeling under the assumption that all points of the interval are uniformly distributed. Using the Kolmogorov – Smirnov test, they showed that the components of the eigenvector satisfy the truncated normal distribution. The possibility of extending the central limit theorem to the distribution of the components of the eigenvector as limit average values of the dominance of each alternative over other alternatives along paths of all lengths was confirmed. It was shown how alternatives are selected according to the product of their priorities.

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A. Krasnov and S. Pivneva

The fundamental scale for measuring the results of paired comparisons used at the AHP was obtained on the basis of the basic relationships of the model of nervous excitation, which lead to the well-known psychophysiological law “stimulus-response”. The effectiveness of this scale has been tested in many applications [5]. In our study, we entirely borrow Saaty’s ideas about pairwise comparing objects, using the truncated normal distribution of object parameters, and also the psychophysical law “stimulus-response”, which led us to use the quasi-neural network approach for data aggregation. It should be noted that in the education system, the Saaty model has not received wide practical distribution in comparison with other applications. However, there are approaches to the adaptation of universities and higher education in general based on the theory of complex systems, especially critical conclusions from the study of complexity, where AHP can be used [1]. From this perspective, in, a systematic review of the literature is carried out to support the process of the analytical hierarchy for decision-making for sustainable development, which allows us to identify gaps and ways for future research [6, 7]. Handbook (Handbook on Constructing Composite Indicators, 2008) provides a guide to the construction and use of composite indicators, for policy-makers, academics, the media and other interested parties. While there are several types of composite indicators, this Handbook is concerned with those which compare and rank country performance in areas such as industrial competitiveness, sustainable development, globalization and innovation. Since 2004, QS World University Rankings among universities has become the world’s most popular source of comparative data on university performance. For example, Lomonosov Moscow State University (Russia) took 84th place in the QS ranking hierarchy (QS, 2020). In this regard, in Russian education, as well as in the former republics of the USSR, methods have been widely used to streamline the performance of universities on the basis of rating assessments [8–10]. Therefore, in this work, we detail the method of quasi-neural network aggregation of scientific and innovative data, which is necessary to build a system of operational and tactical management of scientific and innovative activities of the university. The methods developed by us complement the AHP methodology, since they borrow such approaches as: pair relations of objects; truncated normal distribution; description of fuzzy data. In this case, the pair relations of objects in the form of priorities of dominance are presented in the form of pair interactions by analogy with the construction of potentials of interactions of objects of continuous media in physics. At the same time, we are trying to use the simplest and most understandable data aggregation mechanism that provides systemic synergy.

3 Methodology 3.1 Quasi-Neural Network Aggregation Model In this model, it is assumed that all N balanced indicators S1 , S2 , . . . , SN related to the data on the scientific research and innovation activity (SRIA) of the university are

Hierarchical Quasi-Neural Network Data Aggregation

15

assigned specific values expressed in numerical scales: number (of publications, events, etc.), points, interest, monetary units, etc. For each indicator, upper S1∗∗ , S2∗∗ , . . . , SN∗∗ and lower S1∗ , S, . . . , SN∗ criteria values Sn∗∗ = max{Sn }, Sn∗ = min{Sn }, ∀n ∈ 1, N are usually set. We break (decompose) all indicators into groups or elementary aggregates (A, B, C, …) of data according to the attributes of semantic (semantic) homogeneity, functionality and purpose. For each elementary aggregate, we form vectors (the vectors of three aggregates are given):   STA = (SA1 , SA2 , . . . , SAK ); STB = (SB1 , SB2 , . . . , SBP ) SCT = SC1 , SC2 , . . . , SCQ , (1) whose components correspond to functionally homogeneous groups of indicators of the scientific and innovative activity of the university (K + P + Q = N). A discrete dynamic model for observing the state of the university’s SRIA or its subdivisions is presented in the form: F(t) = Sm (t) + H(t), m = 1, 2, . . . , M ,

(2)

where t is the discrete time; Sm (t) is the vector of the planned state for the m-th direction of the SRIA; H(t) is the interference vector determined by normal truncated distributions. In accordance with (2), it is believed that the state of the university’s SRIA, directly related to the m-th direction and measured in the form of the vector F or a set of indicators corresponding to it, is close to their planned criteria values determined by the vector Sm distorted by the interference H. The operational-tactical control of the SRIA should be based on the principle of automatic control of a set of indicators so as to minimize the influence of interference H and keep the vector F as close as possible to the selected vector Sm (m = 1, 2, …, M) of criteria indicators. In real conditions of the university’s activity, the interference intensities from the observation model considered above (2) are unknown. For example, the monograph has been accepted for publication, but has not yet been published. Or, the money should have come to the university account, but delayed. Under these conditions, we assume that all the components H n (n = 1, 2,…, N) of the vector H of the interference from (2) are independent and distributed according to the normal symmetrically truncated law for any m-th (m = 1, 2, …, M) directions of the SRIA:     Fn − Smn 2 1 ∼ exp − (3) , ∀n ∈ 1, N , pm (H n ) = hmn h2mn dispersions of which are generally not known. We assume that: 2  k k )2 θ , m = 1, 2, . . . , M , (Fn − Snm m K −1 K

2 θm = h2mn = 2σmn

k=1

(4)

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A. Krasnov and S. Pivneva

and each n-th indicator of the m-th direction of the SRIA has an empirical dispersion up to an unknown parameter. Moreover, in each m-th state, the vector F from (2) is completely determined by the likelihood function:  2  N  N   F − S 1 1 n mn ∼ exp − pm (F|θm ) = , m = 1, 2, . . . , M . (5) × √ 2 2 θm2 σmn θ m σmn n=1 n=1 We find parameter estimates θm∗ by maximizing likelihood functions. Then, based on conditions ∂pm ( F|θm )/∂θm = 0 (Handbook, 2008), we obtain: θm∗2

2 N  1  Fn − Smn = , m = 1, 2, . . . , M . 2 N σmn

(6)

n=1

The decision to assign the observation vector F to any of the directions or classes   (“j” or “k”) described by the corresponding likelihood functions pj F|θj and pk (F|θk ), we will make on the basis of pairwise comparison of the maximum likelihood ratios kj with the ratio of a priori probabilities Pj and Pk hypotheses “j” and “k”: pk ( F| θ∗k ) = kj = pj ( F|θ∗j )



θ∗2 j

N2

θ∗2 k

 N   2 N2 N   Fn − Sjn 2  Fn − Skn Pj = / > . (7) 2 2 Pk σjn σkn n=1 n=1

By condition (7), the state of the vector F is assigned to the class for which kj takes the maximum value. For the common case of identical a priori probabilities (Pk = Pj ), instead of (7), an equivalent but simpler condition for choosing a hypothesis (k-th or j-th) is true: 1

2  N Fn −Skm 2 n=1 σkm

1+

1

>

2  N Fn −Y jn 2 n=1 σkm

1+

, k, j = 1, 2, . . . , M .

(8)

Based on (8), we introduce the indicators:

 I (F, Sm ) =

1 N F −S 2 n mn 1+ 2 σmn n=1

, m = 1, 2, . . . , M ,

(9)

defining fuzzy degrees of closeness (0 ≤ I ≤ 1) of the vector F of the state of the SRIA 2 from (5). A bracket to areas defined by the vector Sm and dispersion σmn 

the criteria I (F, Sm ) means averaging over all n ∈ 1, N  ∗∗ ∗∗  ∗∗ T and S = S∗ = In what follows, we choose Sm = S∗∗ m m = S1 , S2 , . . . , SN m  ∗ ∗ T ∗ S1 , S2 , . . . , SN as criteria vectors. Moreover, generalizing (9), we will use the indicators:

 I ∗∗ (F, Sm ) =

1 1+

N n=1

λmn

2 (Fn −S∗∗ mn ) 2 σmn

,

N  n=1

λmn = 1, m = 1, 2, . . . , M .

(10)

Hierarchical Quasi-Neural Network Data Aggregation

17

where are the significance of the relevant indicators of the SRIA. Using the idea (minimizing the distance to the ideal is equivalent to maximizing the distance to the anti-ideal) of (Chiang, 2010), we introduce the indicators: N



 I ∗ (F, Sm ) =

λmn (

n=1 N

1+

Fn −S∗mn ) 2 σmn

λmn

n=1

2

(Fn −S∗mn )2 2 σmn

,

N 

λn = 1, m = 1, 2, . . . , M .

(11)

n=1

Indicators (10, 11) correspond to fuzzy measures of similarity (difference) of the ∗ vector F with the corresponding vectors S∗∗ m (Sm ) and grow monotonically asymptotically to 1 as all the components of the SRIA indicator vector approach the upper criteria values or move away from the lower ones criteria values for any m-th mode of operation. The latter case is typical when an increase in the effectiveness of the university’s functioning is achieved due to the growth of its indicators (energy capacity, capital intensity, number of publications, intelligence, etc.). We will assign to the group of elementary aggregates A, B, C, … data along with their group indicators IA , IB , IC , … weights μA , μB , μC , . . . that verify the group values of the aggregates to describe the state of the SRIA. A set of indicators and significance factors form a numerical description of metadata of the first hierarchy level (see Fig. 1). At the second hierarchical level, elementary aggregates A, B, C, D, E are combined into aggregates ABC and DE, and form metadata of the second hierarchical level in the form of indicators IABC and IDE , as well as coefficients μABC and μDE of their significance (μABC + μDE = 1). Aggregation at subsequent hierarchical levels and the formation of metadata is carried out by analogy with the above procedure of the directed graph of Fig. 1. Moreover, the functioning of the graph practically corresponds to the functioning of a neural-like or quasi-neural network of direct distribution.

4 Practical Results of Application of Quasi-Neural Network Aggregation of Metadata 4.1 Aggregate Interaction Models Let us consider the following practical results of applying the model of quasi-neural network aggregation of metadata for various levels of aggregation, taking into account interactions of aggregates. Suppose that two elementary aggregates A and B are combined. In the absence of their interaction, the known average weighted result is usually used: IAB = μA IA + μB IB We take into account the interaction of these elementary aggregates: IAB =

μA IA + μB IB − εAB μA μB IA IB , μA + μB − εAB μA μB

(12)

18

A. Krasnov and S. Pivneva

εAB =

1, for interaction aggregates; μAB = μA + μB − μA μB , μA + μB + μC = 1 0, for otherwise. (13)

F1A, F2A, …,FNA

А

…

B

F1C, F2C, …, FNC

C

АBС

…

F1E, F2E, …, FNE

D

E

DE

АBСDE

Fig. 1. Graph of the first, second and third hierarchical levels of the quasi-neural network parametric aggregation.

Suppose that an elementary aggregate C with metadata μc , Ic is added to a paired aggregate AB with metadata described by the tuple μAB , IAB . Then, taking into account interactions for the triple aggregate ABC, based on (13), we recursively obtain: IABC =

μAB IAB + μC IC − μAB μC IAB IC = μAB + μC − μAB μC

μA IA + μB IB + μC IC − μA μB IA IB − μA μC IA IC − μB μC IB IC + 1 − μA μB − μA μC − μB μC + μA μB μC (14) μA μB μC IA IB IC 1 − μA μB − μA μC − μB μC + μA μB μC The first term in (14) corresponds to pairwise interactions of elementary aggregates, and the last term to their triple interactions. The obtained recursive model of the dependence of the interaction potential of three aggregates through their pairwise interaction is similar to the interaction of molecules in continuum physics. The following is an example of a simpler dependency.

Hierarchical Quasi-Neural Network Data Aggregation

19

Consider the synergistic effect I AB from the interaction of elementary aggregates: IAB =

μA IA + μB IB − μA μB IA IB μA IA + μB IB − = μA + μB − μA μB μ A + μB μA μ B (μA IA + μB IB − IA I B ) μ A + μB

(15)

Thus, the maximum synergistic effect I AB = 0.14 is achieved at μA = μB = 0.5 and I A = I B = 0.5. In the general case, it is possible feedbacks in a graph discussed in Fig. So, in Fig. 2 shows graphs of elementary and pairwise subsystems with feedbacks.

Fig. 2. Graphs of elementary and pairwise subsystems with feedbacks.

In accordance with (12), the outputs of subsystems are related to their inputs by the equations: IX 1 − μFeedback (1 − μFeedback IX ) IAB = 1 − μFeedback (1 − μFeedback IA )

IY Feedback = IAB Feedback

(16)

It follows from (16) that feedback increases the synergy of subsystems. So, in Fig. 3 shows an example of the response IY Feedback of the elementary subsystem to the input action IX at different values of the feedback coefficient μFeedback . Figure 4 shows the surface of the synergistic effect IAB = IAB (IA , IB |μFedback = 1) and IAB = IAB (IA , IB |μFedback = 1 ) for the case when μA = μB = μFeedback = 0.5. The partial indicator (potential) I ∗ or fuzzy description of metadata associated with the quantitative normalized value x of any single indicator F of the research or innovation activity of a faculty member will be evaluated in accordance with (11), for example, as: I ∗ = x/(1 + x)

(17)

20

A. Krasnov and S. Pivneva Subsystem response with feedback 1.00 0.90 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10 0.00 0.00

0.99 0.90 0.50 0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Fig. 3. The responses of the elementary subsystem to the input action for various values of the feedback coefficient.

Synergistic effect surface 0.30 0.25

ΔIAB

0.20 0.15 0.10 0.05 0.00 0.05 0.20 0.35 0.50 0,85 0,90 0,95 1,00

0,80

0,75

0,70

0,60

0,55

0,50

0,45

0,40

0,35

0,30

0,25

0,15

0,10

0,05

0.95

0,20

0.80

IB

0,65

0.65

IA

Fig. 4. The surface of the synergistic effect for the pair aggregated subsystem with feedback.

  2 . So, for the number of publications x = F 2 (F = 1,2,…,N); for cash x = F 2 /Fplan With increasing x, the potential I * grows and asymptotically tends to 1. We estimate the potential of the department (chair/faculty) of the university as the average value of the potentials Ik∗ of all K employees of the department I ∗ = 1 K 1 K ∗ k=1 Ik = K k=1 xk /(1 + xk ). K So, for example, if the department has K = 10 employees and 4 of them have F = 3 collective articles, then the potential of each employee for this indicator will be   Ik∗ = 32 / 1 + 32 = 0.9. If the remaining 6 employees do not have articles, then the department’s potential for this indicator will be I ∗ = (4 ∗ 0.9)/10 = 0.36.

Hierarchical Quasi-Neural Network Data Aggregation

21

We will aggregate the potentials of various areas of the university’s SRIA taking into account the significance μm of each m-th direction. Then it is possible to apply model (10) using the partial potentials < I ∗ >m as arguments:

∗ I Σ =

1 1+

N

μm (I ∗ m

, − 1)2

N 

μm = 1, m = 1, 2, . . . , M

(18)

n=1

n=1

The effect of the interaction of partial potentials I ∗ m is implicitly presented in model (18) due to its strong nonlinearity. It is interesting to compare the aggregation results based on models (12), (13), and (18). For this, Table 1 shows the values of ISc and IIn of the potentials of the effectiveness of scientific and innovative activities of 12 faculties of one of the Russian universities with the same significance of these activities, i.e. μSc = μIn = 0.5. The generalized 

 productivity of the SRIA is determined by the aggregated potentials IΣ(12) , IΣ(13) , 

IΣ(18) , respectively. As follows from (12), the potential I12 does not take into account the interaction (ε = 0). In adjacent columns, ratings of R faculties are presented. Table 1. The results of scientific and innovative activities. I Sc I In I (12) R(12) I (13) R(13) I (18) R(I98) μ

0.5 1

0.5 4

5

6

9

1 0.58

0.98 0.780

2

3

3

0.851

2

0.919

10 2

2 0.95

0.97 0.960

1

0.973

1

0.998

1

3 0.85

0.54 0.695

5

0.774

5

0.895

5

4 0.76

0.02 0.390

9

0.515

9

0.663

9

5 0.77

0.49 0.630

6

0.714

6

0.865

6

6 0.38

0.81 0.595

8

0.691

8

0.826

8

7 0.68

0.9

0.790

2

0.849

3

0.947

3

8 0.83

0.38 0.605

7

0.702

7

0.829

7

9 0.63

0.15 0.390

9

0.489

10

0.699

10

10 0.32

0.1

0.210

12

0.269

12

0.611

12

11 0.48

0.16 0.320

11

0.401

11

0.672

11

12 0.72

0.84 0.780

3

0.838

4

0.951

4

It can be seen from the table that in the linear model, aggregated potentials that do not take into account interaction do not make it possible to distinguish between the faculty states (column 4, lines 1, 2, and 4, 9). At the same time, models (12) and (18) give the same good results (columns 6 and 10).

22

A. Krasnov and S. Pivneva 1 0.9

〈I〉In

R=2 R=3 R=4

0.8

R=1

0.7 0.6 0.5

R=5

0.4 0.3 0.2 0.1 0

R = 12

〈I〉Sc

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Fig. 5. 2D presentation of scientific and innovative activities of university’s faculties.

Figure 5 shows a 2D representation of the metadata of the SRIA University’s faculties, clearly reflecting its status. All the above models, taking into account interaction, allow you to make managerial decisions, for example, to organize assistance to those departments of the university that have sufficiently high scientific potentials, but have not yet achieved success in innovation.

5 Hierarchy of SRIA and Its 3D Presentation Consider an example of a hierarchy of description of the SRIA based on metadata generated by indicators of its activity and effectiveness. Scientific activity is formed by indicators defined over 3 years, such as: – – – –

the number of publications with the Russian Science Citation Index (RSCI); the number of publications at conferences; the number of reports on internal research, including initiative; the number of applications for grants (RFBR, RSF, Ministry of Education and Science, etc.). The scientific result is formed by such indicators defined over 3 years, such as:

– – – –

the number of publications in Web of Sciences and Scopus; the number of monographs; the number of dissertations defended; the amount of funding for grants won. Innovative activity is formed by indicators defined over 3 years, such as:

– the number of applications for RID (patents, licenses) related to ongoing research; – the number of new technologies in the form of educational methods, multimedia educational aids in disciplines, programs, etc.;

Hierarchical Quasi-Neural Network Data Aggregation

23

– the number of exhibitions held with the exhibits; – the number of design decisions based on the results of scientific research. An innovative result is formed by indicators defined over 3 years, such as: – the number of patents and licenses received related to the results of ongoing research and educational activities; – the number of textbooks created according to the results of scientific activities (articles, monographs); – the number of innovation centers and technology parks; – the amount of funding for concluded business contracts. A visual representation of the considered hierarchy of the description of the SRIA of the digital faculty is shown in Fig. 6. Fact data about scientific and innovative activities ofthe digital faculty

Research direction

Scientific activity

Scientific result

Innovative direction

Innovative activity

Innovative result

RISC publications

Ws, Ss publications

READ Applications

Patents and Licenses

Publ. of conferences

Monographs

New technologies

Study guides

Internal reports Research

Protected Dissertations

Exhibitions with an exhibit.

Centers, technology parks

Grant Applications

Grants Won

Design solutions

Contractagreement

Fig. 6. Metadata hierarchy of the scientific and innovative activities of the digital faculty.

In Fig. 7 is a 3D visualization diagram of metadata corresponding to the above hierarchy of the SRIA description. As can be seen from the figure, 3D visualization of metadata does not mix semantically different areas of research and innovation (scientific, innovative and financial areas), but shows their relationship and development dynamics in different spaces.

24

A. Krasnov and S. Pivneva Scientific result

Innovative result

2019 2018

2019

2017

2018

Scientific activity Grants Won

2017

Innovative activity

Contractagreement

Fig. 7. 3D visualization of the SRIA metadata.

6 Results An explicit form of indicators of elementary aggregates is obtained in the work, having the form of fuzzy measures of similarity of the analyzed data and their criteria values normalized to unity. The dependences of indicators of aggregates of the upper level of the hierarchy on indicators of aggregates of the lower level, taking into account their interactions, are also obtained. The synergistic effect of the introduction of interactions of aggregates, bursting into the growth of indicators of the upper levels of the hierarchy, is proved. The levels of semantic decomposition and hierarchical aggregation of metadata of scientific and innovative activities of the university in the form of scientific activity, scientific result, innovative activity, innovative result are proposed. 3D visualization of the metadata dynamics of the research and innovation activities of the university is proposed.

7 Discussion In practical terms, the results obtained are useful for building systems for monitoring the status of research and innovation activities of universities that automatically generate a small amount of metadata characterizing the state of the university as a whole, based on the current values of its numerous indicators. The practical use of the considered approach in a number of Russian universities (Moscow State Technical University named after K.G. Razumovsky, Oriole State University, and Russian State Social University) has shown its effectiveness. For example, 3D visualization of the dynamics of metadata of research and innovation activities allows university leaders to quickly conduct a visual figurative analysis of their development, and if necessary, access data from the lower level of their hierarchical description. In theoretical terms, the results complement the AHP methodology, as they are based on: pairwise interactions of indicators characterizing various multiple entities of scientific and innovative activity; the truncated normal distribution of interference masking these entities; their hierarchical aggregated description in the form of fuzzy measures of similarity between real indicators of research and innovation activity with criteria indicators. At the same time, a synergistic effect was revealed: the interaction of indicators leads to their growth during the transition from the

Hierarchical Quasi-Neural Network Data Aggregation

25

lower level of the hierarchy to a higher level, which is quite consistent with developing systems.

8 Conclusions The results obtained in the work and their testing in a number of Russian universities make it possible to consider hierarchical quasi-neural network data aggregation as a sufficiently effective tool for constructing a university scientific and innovation management system based on monitoring of its many indicators. These specific indicators were not considered in the work, but already from the review given in the first part of the work, it is clear that their choice plays an important role. Nevertheless, with the right choice of such indicators, it is equally important to skillfully use their values. The method proposed in the work just allows us to rely on the values of a set of indicators linked by a hierarchy of relations of their meta descriptions, which is built on an ascending principle - the relationships of upper level metadata are built taking into account the interactions of lower level metadata. This allows you to implement a systematic approach in assessing the state of scientific and innovative activities of the university, since it is with a systematic approach that the property of the system is not explained by the sum of the properties of its constituent parts.

References 1. Pinheiro, R., Young, M.: The university as an adaptive resilient organization: a complex systems perspective. Theory Method High. Educ. Res. 3, 119–136 (2017). https://doi.org/10. 1108/S2056-375220170000003007 2. Saaty, T.L.: Decision making with the analytic hierarchy process. Int. J. Serv. Sci. 1(1), 83–98 (2008). https://doi.org/10.1504/IJSSCI.2008.017590 3. Demetrius, K., Patricia, K.: Applying the balanced scorecard to education. J. Educ. Bus. 80(4), 222–230 (2005). https://doi.org/10.3200/JOEB.80.4.222-230 4. Saaty, T.L.: Axiomatic foundation of the analytic hierarchy process. Manage. Sci. 32(7), 841–855 (1986). https://doi.org/10.1287/mnsc.32.7.841 5. Ishizaka, A., Labib, A.: Analytic hierarchy process and expert choice: benefits and limitations. OR Insight 22(4), 201–220 (2009). https://doi.org/10.1057/ori.2009.10 6. Palomares-Montero, D., Garcia-Aracil, A.: What are the key indicators for evaluating the activities of universities? Res. Eval. 20(5), 353–363 (2011). https://doi.org/10.3152/095820 211x13176484436096 7. Federico, F., Guimarães, P.A., Dániel, V., Sjoerd, H.: Research excellence indicators: time to reimagine the ‘making of’? Sci. Public Policy 45(5), 731–741 (2018). https://doi.org/10. 1093/scipol/scy007 8. Kühne, Conny, Böhm, Klemens: Assessing the suitability of an honest rating mechanism for the collaborative creation of structured knowledge. World Wide Web 17(1), 85–104 (2012). https://doi.org/10.1007/s11280-012-0193-1 9. Qiu, C., Squicciarini, A., Rajtmajer, S.: Rating. mechanisms for sustainability of crowdsourcing platforms. In: CIKM 2019 Proceedings of the 28th ACM International Conference on Information and Knowledge Management, Beijing, China, pp. 2003–2012 (2019). https:// doi.org/10.1145/3357384.3357933 10. Kao, C.: Weight determination for consistently ranking alternatives in multiple criteria decision analysis. Appl. Math. Model. 34(7), 1779–1787 (2010). https://doi.org/10.1016/j.apm. 2009.09.022

Formalization of Ternary Logic for Application to Digital Signal Processing Ibragim Suleimenov1

, Akhat Bakirov1(B)

, and Inabat Moldakhan2

1 National Academy of Engineering of the Republic of Kazakhstan, Bogenbai Batyr, 80,

050010 Almaty, Republic of Kazakhstan [email protected] 2 Almaty University of Power Engineering and Telecommunications, Baytursynov St, 126/1, 050013 Almaty, Republic of Kazakhstan

Abstract. In this article, an abelian group G = (−1,0,1) is considered. In addition, advantages of using this group for digital signal processing were demonstrated. The main of ones are a natural form of representation of negative numbers, as well as natural digital form of slowly changing signals. This group is isomorphic to multiplicative group formed by three cubic roots of unity. This isomorphism can be used in implementation of computer systems in which physical representation of logical variables is carried out through a phase of a signal. This multiplicative group may turn out a very promising for development of computer systems where information about value of a logical variable (whatever is meant by this term) is embedded in the phase of the oscillating signal. The oscillating signals are the most promising object for implementation of quantum, optical and nanocomputing systems, since the implementation of stable states (or stable currents) that correspond to classical approaches to the creation of computer technology is problematic here. Keywords: Ternary logic · Digital signal processing · Next generation computing systems

1 Introduction In works [1, 2], it was noted that ternary logic has quite definite advantages compared to binary. At least when it comes to digital signal processing. Particularly, in the cited works it was shown that number of operations that must be done in order to convert the signal to digital form decreases at least one and a half times if we switch from binary to ternary logic. There is no doubt that in modern conditions reduction in a number of operations carried out by electronic devices becomes a very urgent task due to the fact that such concepts as the Internet of things [3], Big Data [4], etc. are becoming more common. All systems, that to some extent meet ideas of these concepts, anyway are integrated with telecommunication networks, which function in the near future, will finally go to “digital”. An effectiveness of any electronic systems depend on a number of operations © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 26–35, 2021. https://doi.org/10.1007/978-3-030-57453-6_3

Formalization of Ternary Logic for Application

27

that they must perform in order to solve a particular task, especially in conditions when the “digitalization” [5, 6] of the economy becomes a reality. It is also appropriate to emphasize that from the point of view of electronic implementation, de facto a ternary logic does not lose the advantages a binary one has. This becomes apparent when considering electronic circuits with bipolar power. Indeed, it has already become a commonplace to say that an advantage of digital signal processing (and digital electronics in general) is its high resistance to noise. In order to distinguish between logical zero and logical unity, it is enough to set a certain threshold value. If a signal value is less than a certain threshold, then it is interpreted as a logical zero, and vice versa, if it is greater than a given threshold, then it is interpreted as a logical unity. Obviously, if consider electronic circuits with both a positive and a negative power source, then transition to ternary logic does not fundamentally change anything. In the same way as it used to be within traditional “digital” approach, it is possible to separate out a negative and a positive threshold voltage level. As a result, a circuit will have all the same advantages, with the only difference, which is in use of unipolar power supply instead of bipolar one. All these considerations sufficiently reflected in the world literature [7, 8] are true. However, it is necessary to emphasize one more fact, which did not find sufficiently consistent reflection in works cited above. More precisely, ternary logic is a natural tool for digital processing of slowly changing signals (an accurate definition of this term will be provided below). In current conditions, humanity will face slowly changing signals repeatedly. In this regard, solar energy systems based on Sun navigation are a typical example [9, 10]. Moreover, all signals that so-called “smart houses” will be supplied with, as well as other systems that are somehow connected with the concept of the Internet of Things [3], will operate with relatively slow changing signals. Since any industrially applicable systems controlled by electronic equipment, one way or another, have a certain response rate. In other words, we are obviously talking about signals whose rate of change will not exceed a certain threshold. Mathematically, models of this kind of signals are functions with ε-coverage. This class includes functions satisfying the following requirements. It is permissible to choose such subinterval of signal variation range u0 when a value of signal ui+1 on the (i + 1)-th bit will differ from the value of signal ui on the i-th bit no more than u0 . If the signal on the i-th bit corresponded to a discrete level with number j, then the signal on the (i + 1)-th bit will correspond to the level with signals numbered with j − 1, j, j + 1. Ternary logic uses a “trit” concept [11, 12]. It has been formed by analogy with the concept of “bit”. In essence, they have the same etymology. It was not widely used just because ternary logic does not have one yet. The main reason is historical related to special aspects of interaction between technical and humanitarian disciplines in twentieth century [13]. According to above, it is easy to see that information on a slowly changing signal, i.e. on a signal whose rate of change is limited, is exactly equal to N trit. In a mentioned equality N is a number of bits into which signal with ε-cover is divided.

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It is easy to see that a scope of this information is much smaller than a scope of information formally corresponded to a slowly changing signal even without detailed mathematical calculations. It is true if signal is digitized using binary logic and even more so using standard approaches to the implementation of analog-digital converters [14, 15]. In this case, a number of units of information (bit) per bit is obviously related to a number of subintervals into which the signal is split. Obviously, this indicator is connected with an amount of information significantly exceeding one that trit contains. Thus, there is a quite wide class of issues where ternary logic has undisputed advantages. It is appropriate to emphasize that we are not contrasting ternary logic with binary but vice versa. We claim that in prospect the most advanced digital systems will need to be formed with ability to move from one kind of logic to another. Such formulation of the question is even more relevant because within the modern mathematical logic, highly non-trivial logics are also considered [16, 17]. Their formulation is significantly different from Aristotle and Boole logic. There is every reason to believe that further improvement of digital systems will imply flexible platforms related to restructuring of the basis itself, i.e. to restructuring the logic on which they are implemented. Thus, there is every reason to develop the formal apparatus of trinary logic, basing on an analogy with binary. In this paper, the first step of a large-scale program is implemented. Its ultimate objective is development of flexible digital platforms allowing to switch from one type of logic to another, depending on a nature of a problem being solved. There is no need to prove that the approach is also fully consistent with current trends aimed at creating artificial intelligence systems for various purposes. Obviously, a prototype of any artificial intelligence system i.e. human intelligence is capable of selectively responding to a nature of any problem being solved, also at the level of choosing the “logic” that is most appropriate for a set target.

2 Ternary Logic: Creation a Basic Abelian Group There is a set consisting of three elements −1, 0, +1. G = (−1, 0, 1)

(1)

The set can be endowed with an addition operation according to the rules below. 1 + 1 = −1

(2)

(−1) + (−1) = 1

(3)

(−1) + 1 = 1 + (−1) = 0

(4)

0 + a = a + 0 = a, ∀a ∈ G

(5)

Formalization of Ternary Logic for Application

29

In order to show that the set where addition operations mentioned above are satisfied is a group is enough to check a feasibility of the axiom of the group, which are as follows. A nonempty set G = ∅, endowed with a binary algebraic operation “+” is called a group shown in [18] if the following three axioms are satisfied. 1. The existence of a neutral element e (zero) a+e =e+a =a

(6)

2. The existence of a symmetric (inverse) element: ∀a ∈ G, ∃˜a ∈ G; a˜ + a = e

(7)

3. Associativity: for ∀a, b, c ∈ G takes place a + (b + c) = (a + b) + c

(8)

moreover, if, for G elements, the commutativity condition is satisfied ∀a, b ∈ G, a + b = b + a

(9)

then such group is called Abelian. Satisfaction of the axiom (6) directly corresponds to one of the rules (5) defining the set considering G = (−1,0,1). Satisfaction of the axiom (7) follows directly from relations (2), (3), indicating an existence of an inverse element for any nonzero element in G = (−1,0,1). Direct check allows verifying that an addition operation determined in considered way satisfies the associative axiom.   1˜ + 1˜ + 1 = 1˜ + 0 = 1˜ (10)   1˜ + 1˜ + 1 = 1 + 1 = 1˜

(11)

In expressions (10) and (11), a symbol of an inverse element is carried out in accordance with the notation −1 ↔ 1˜

(12)

This is for convenience of ternary notation, it will be clear from the following. Thus, an object defined by relations (2)–(5) mentioned above is indeed the group in a sense, which the classical theory of algebras gives to this term [18]. Moreover, this one is also a ring in a sense of the theory of algebras (which is also directly verified basing on the axioms of the ring).

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It is appropriate to emphasize that, in accordance with views of modern mathematics, axioms are not “truths that do not require proof”. The axiom list de facto is a list of properties that a studied object is endowed with. It can be done arbitrarily [19]. The only important thing is an internal logical consistency. However, this requirement also allows quite definite discrepancies in regard with problems existing in logical foundations of mathematics [20] and discrepancies in understanding of the term “logic” itself. The group, according to modern concepts, is an object that satisfy the axioms of the group. In other words, the object defined above can be considered as a group on the same grounds as a group with two elements 0 and 1 and built basing on Boolean algebra and which is a basis for the modern “digital world”. Note that the addition rules defined above look somewhat unusual, but their “unusual” is no more than the “unusual” of widespread Boolean algebra. From the point of view of mathematics, familiar to a student, the rules (2) and (3) look no more awkward than those do, which are commonly used in all areas of infocommunication technologies: 1+1=0

(13)

1+0=0+1=1

(14)

Moreover, modern mathematics (if we say a little exaggerated) allows giving a mean to anything. In accordance with rule (2) a sum of two units gives minus one, cannot be considered as something obviously illogical.

3 Applied Interpretation of Meaning of G Group in Terms of Digital Signal Processing The presented addition rules have a transparent meaning if we refer to the issue of digital signal processing. Use of ternary logic in signal digitizing involves splitting into groups of three, as it is shown in Fig. 1. In this figure, groups are selected. These groups correspond to different digits of a ternary form of representing a number. 1 0 -1 1 0 “+1”

"-1”

"-1”

“+1”

-1

1 0 -1 1 0 -1

Fig. 1. To the interpretation of rules of adding ternary logic in terms of digital signal processing.

Formalization of Ternary Logic for Application

31

According to the rules of ternary logic and the proposed notation for the inverse unit, integers should be written as a . . . bc ↔ a · 3n + . . . + b · 31 + c · 30

(15)

where the letter designations correspond to one of the elements of the G set, more precisely, its mapping to the triple (−1,0,1). According to the rule (15), a ternary number is converted to decimal. An example of such conversion for a particular combination of ternary logic symbols is given by the following entry: ˜ ↔ 1 · 33 − 1 · 32 + 0 · 31 + 1 · 30 = 27 − 9 + 1 = 35 1101

(16)

Figure 1, together with the ternary representation of integers (15), (16), shows that rules (2) and (3) have a well-defined, transparent interpretation. If transition is made from level in a selected triple to an overlying level, then the signal goes to the lowest level of the triple lying higher (which corresponds to transition to the next digit of ternary number). We emphasize that it is the ternary notation of a number that determines the convenience of switching from the notation −1 to the notation 1˜ - in order to be able to write a certain number through a sequence of characters, by analogy with a binary representation. In a binary representation, two characters 1 and 0 are used. Three characters 1, 0 and 1˜ are used here, the last one corresponds to −1. The rules for operating with group elements in these notations are presented in Table 1. Table 1. Rules for adding symbols of ternary logic in the used notation. 1˜ 0 1 1˜ 1 1˜ 0 0 1˜ 0 1 1 0 1 1˜

Note that there is also a well-defined nuance associated with the interpretation of the logical variables used. Indeed, binary logic allows a transparent interpretation within classical mathematical logic. This is expressed, in particular, in the fact that the logical unit is assigned “truth”, and the logical “zero” value. Thanks to this approach, it becomes possible to match the standard rules of mathematical logic with operations on logical variables. Thus, the logical operation “EXCLUSIVE OR” has a direct mapping in Boolean algebra, which is expressed by the well-known formula (13). At first glance, such comparison seems problematic for ternary logic. However, as noted above, modern logic operates with more complex objects than those that directly derive from Aristotelian logic. In particular, it is pertinent to note that

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the character of the G group introduced above correlates both with the representations of trialektics and the representations of dialectic positivism [21, 22]. Moreover, as noted in the cited works, as well as in [23, 24], the need has long been ripe for the creation of other nontrivial logics, in particular, due to the fact that classical Aristotelian logic is not able to describe many phenomena that occur in the real world.

4 Opportunities for Using Ternary Logic in Next Generation Computing Systems Note that Abelian G group considered above is isomorphic to the multiplicative G1 group, which is formed by three elements representing three cubic roots of unity. These elements, obviously, can be mapped to the elements of the above group according to the following rules     2π 2π ↔ 1; exp −i ↔ −1; 1 ↔ 0 (17) exp i 3 3 the addition operation with an operation of multiplication. This isomorphism is important because in modern conditions, approaches to digital signal processing must inevitably transform. First of all, we are talking about systems that can be implemented on the basis of nanotechnology. As a number of studies performed in this area and summarized in [25] clearly show, it is extremely difficult to implement computer systems based on the ideas that K.E. Shannon expressed at the beginning of the last century. Remind that these ideas are based on the representation of binary variables through a high and a low (zero) signal level, and the execution of logical operations in one way or another comes down to commuting keys. Shannon’s main achievement he noted and which subsequently became the basis for all computer technologies is in correspondence between logical operations and ordinary keys that include and respond to an electric current. Depending on whether two keys are connected in parallel or in series, such electric circuit will perform either a logical operation “AND” or a logical operation “OR”. These well-known facts should be recalled, since they unambiguously show that the concept of “state” is a basic concept in modern digital signal processing. Current flows or it does not - this corresponds to a logical unit or logical zero. However, for nanoscale systems to perform logical operations, the use of oscillating processes would be much more preferable [25]. In any case, this is much easier than trying to provide for such systems a certain fixed state, the change of which will correspond to the logical operation. The same can be said about current trends, which are already clearly visible in connection with the creation of optical/quantum information processing systems [26]. Obviously, for optics to realize the “High” and “Low” signal levels i.e. using Shannon’s basic ideas directly is quite problematic. The use of oscillating signals is also much more efficient here. Specifically in this regard isomorphism mentioned above is of interest. Indeed, the group indicated above actually means that for performing logical operations within the framework of the ternary logic, three signals with phase shifted relative to each other by

Formalization of Ternary Logic for Application

33

2π 3

can be used (Fig. 2). Each of these signals can be associated with one of the elements of the group corresponding to the ternary logic.

2π/3

2∙2π/ 3

3∙2π/ 3

4∙2π/ 3

5∙2π/ 3

6∙2π/ 3

Fig. 2. Illustration for the use of ternary logic group elements in computing systems.

In particular, this means that arithmetic summation operations, taking into account an existence of negative numbers, based on the ternary logic can be performed using the signal phase rotation operation. Thus, possibilities for digital signal processing are expanding significantly, it is quite possible that this can become the basis for quantum and optical computers. Strictly speaking, the logic should no longer be necessarily binary or ternary, the only question is what will be the resolution of used systems regarding to phase shifts. However, there is every reason to believe that the ternary logic is the most convenient, since actually we are talking about the same three-phase electrical signals that have been used in electrical engineering for a long time. The isomorphism presented above shows that it is possible to switch to the use of such signals for arithmetic operations. In fact, the isomorphism mentioned above says that ternary logic, the conveniences of which are undeniable, in particular the natural possibility of using negative numbers, can be realized in a rather simple way – using the logic elements that ensure phase rotation.

5 Conclusion Thus, there is every reason to introduce the group G = (−1, 0, 1) corresponding to the ternary logic. The advantages of this group compared to the group that corresponds to binary logic are at least in possibility of natural representation of negative numbers of any bit capacity and in natural means for translating slowly changing signals into digital form. This group is isomorphic to the multiplicative group formed by three cubic roots of unity. This multiplicative group may turn out a very promising for development of computer systems where information about value of a logical variable (whatever is meant by this term) is embedded in the phase of the oscillating signal. The oscillating signals are the most promising object for implementation of quantum, optical and nanocomputing systems, since the implementation of stable states (or stable currents) that correspond to classical approaches to the creation of computer technology is problematic here.

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References 1. Merrill, Jr., R.D.: Ternary logic in digital computers. In: Proceedings of the SHARE Design Automation Project, pp. 6–11 (1965). https://doi.org/10.1145/800266.810759 2. Keshavarzian, P., Navi, K.: Universal ternary logic circuit design through carbon nanotube technology. Int. J. Nanotechnol. 6(10–11), 942–953 (2009). https://doi.org/10.1504/IJNT. 2009.027557 3. Tan, L., Wang, N.: Future internet: the internet of things. In: 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE), vol. 5, pp. 376–380 (2010). https://doi.org/10.1109/icacte.2010.5579543 4. McAfee, A., Brynjolfsson, E., Davenport, T.H., Patil, D.J., Barton, D.: Big data: the management revolution. Harv. Bus. Rev. 90(10), 60–68 (2012) ´ 5. Afonasova, M.A., Panfilova, E.E., Galichkina, M.A., Slusarczyk, B.: Digitalization in economy and innovation: the effect on social and economic processes. Polish J. Manage. Stud. 19, 22–32 (2019). https://doi.org/10.17512/pjms.2019.19.2.02 6. Sokolenko, L.: Digitalization as a vector of economic systems development & accounting system modernization. Account. Finan. 3, 40–48 (2019) 7. Klein, M., Mol, J.A., Verduijn, J., Lansbergen, G.P., Rogge, S., Levine, R.D., Remacle, F.: Ternary logic implemented on a single dopant atom field effect silicon transistor. Appl. Phys. Lett. 96(4), 43–107 (2010). https://doi.org/10.1063/1.3297906 8. Priya, A.S., Kumar, A.S.: Optimization of 1-Bit ALU using ternary logic. Int. Res. J. Eng. Technol. 6(9), 1605–1610 (2019) 9. Hollabaugh, C.: U.S. Patent No. 9,568,218. U.S. Patent and Trademark Office, Washington, DC (2017) 10. Palkin, G., Tereshkova, L., Gorbunov, R.: Evaluating efficiency of methods for automatic orientation solar panel batteries to position with maximum output electrical power. In: 2019 International Ural Conference on Electrical Power Engineering (UralCon), pp. 109–115. IEEE (2019). https://doi.org/10.1109/uralcon.2019.8877673 11. Mirzaee, R.F., Daliri, M.S., Navi, K., Bagherzadeh, N.: A single parity-check digit for one trit error detection in ternary communication systems: gate-level and transistor-level designs. J. Multiple Valued Logic Soft Comput. 29, 3–4 (2017) 12. Shrivastava, Y., Gupta, T.K.: Design of low-power high-speed CNFET 1-trit unbalanced ternary multiplier. Int. J. Numer. Model. Electron. Netw. Devices Fields 33(1), e2685 (2020). https://doi.org/10.1002/jnm.2685 13. Altmann, J.: Natural-science/technical peace research. In: Information Technology for Peace and Security, pp. 39–60 (2019) 14. Kim, J., Jang, T.K., Yoon, Y.G., Cho, S.: Analysis and design of voltage-controlled oscillator based analog-to-digital converter. IEEE Trans. Circ. Syst. I Regul. Papers 57(1), 18–30 (2009). https://doi.org/10.1109/TCSI.2009.2018928 15. Fard, A., Gupta, S., Jalali, B.: Digital broadband linearization technique and its application to photonic time-stretch analog-to-digital converter. Opt. Lett. 36(7), 1077–1079 (2011). https:// doi.org/10.1364/OL.36.001077 16. Blasiak, Jonah: Representation theory of the nonstandard Hecke algebra. Algebras Represent. Theor. 18(3), 585–612 (2014). https://doi.org/10.1007/s10468-014-9502-y 17. Delanghe, R., Sommen, F., Soucek, V.: Clifford algebra and spinor-valued functions: a function theory for the Dirac operator. Springer Science & Business Media, p. 53 (2012) 18. Fuchsbauer, G., Kiltz, E., Loss, J.: The algebraic group model and its applications. In: Annual International Cryptology Conference, pp. 33–62. Springer, Cham (2018) 19. Bennett, B., Düntsch, I.: Axioms, algebras and topology. In: Handbook of Spatial Logics, pp. 99–159. Springer, Dordrecht (2007)

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20. Ernest, P.: What is our first philosophy in mathematics education? Learn. Math. 32(3), 8–14 (2012) 21. Suleimenov, I., Massalimova, A., Bakirov, A., Gabrielyan O.: Neural networks and the philosophy of dialectical positivism. In: MATEC Web Conference, p. 214 (2018). https://doi. org/10.1051/matecconf/201821402002 22. Suleimenov, I.E., Gabrielyan, O.A., Bakirov, A.S., Vitulyova, Y.S.: Dialectical understanding of information in the context of the artificial intelligence problems. In: IOP Conference Series: Materials Science and Engineering, p. 630 (2019). https://doi.org/10.1088/1757-899x/630/1/ 012007 23. Laubner, B.: The structure of graphs and new logics for the characterization of polynomial time (2011) 24. Cintula, P., Noguera, C.: Implicational (semilinear) logics I: a new hierarchy. Archiv. Math. Log. 49(4), 417–446 (2010). https://doi.org/10.1007/s00153-010-0178-7 25. Mun, G., Suleimenov, I., Zezin, A., Abilov, Z., Dzhumadilov, T., Izmailov, A., Khutoryanskiy, V.: Complexation with the participation of polyelectrolytes: theory and prospects of use in nanoelectronics (monograph). Library of nanotechnology (2009) 26. Yoshikawa, J.I., Hashimoto, Y., Ogawa, H., Serikawa, T., Shiozawa, Y., Okada, M., Takase, K.: Optical quantum information processing and storage. In: Quantum Communications and Quantum Imaging XVI. International Society for Optics and Photonics, vol. 10771, pp. 107710Q (2018). https://doi.org/10.1117/12.2320476

Neural Network Modeling Methods in the Analysis of the Processing Plant’s Indicators Egor Ushakov(B)

, Tatyana Aleksandrova , and Artem Romashev

Saint Petersburg Mining University, Saint Petersburg, Russia [email protected]

Abstract. The paper analyzes the geological and mineralogical features of a pyritic polymetallic deposit. The use of Kohonen neural networks in solving the problem of technological typification of this type of ore is justified, since the flotation process is essentially a multifactorial and nonlinear object. The associative method of analyzing phenomena is more direct and visual than the “implicit” setting of connections or regularities in the form of a formalized mathematical model of a narrow range of phenomena. In the case of Kohonen neural network modeling, the image of a multidimensional space on a single plane in the form of a two-dimensional grid, on which the trend of changes in the processed ore mixture can be applied, is more adequately perceived by the operator. To achieve higher reliability in the identification of topological Kohonen maps for diagnostic purposes a methodology is proposed, which includes the interpretation of calculated average values of studied parameters of all neurons, using the method of factor analysis, design of selected neurons on the plane of the main components Fi – Fj and applying on them the physical values of the vectors of the measured parameters and contour lines of output functions. The developed technology can be introduced at the plant online with the help of express data analysis control, which allows you to promptly change the reagent modes in order to achieve higher metal recovery and better quality of the resulting concentrates. Keywords: Pyrite polymetallic ores · Flotation · Neural network modeling

1 Introduction The processing plant accumulates a huge amount of information based on the quality indicators of its work. Processing efficiency depends on the handling and interpretation of the data. Also, typification, classification and regression analysis of such arrays allows to identify the “weak points” and develop new technologies for ores of different genesis [1–4]. Polymetallic ores are the most favorable object for the development of the principles of technological typification of processed raw materials, since even in the conditions of an undeveloped system of automation of flotation operations, the plant necessarily provides shift reports for at least three controlled elements. These three elements are © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 36–45, 2021. https://doi.org/10.1007/978-3-030-57453-6_4

Neural Network Modeling Methods in the Analysis of the Processing

37

simultaneously reflected in each of the resulting concentrates. Taking into account the possibility of calculating the ratios between the metal contents in the ore, it is possible to form a fairly representative multidimensional information space, which can be analyzed using neural network modeling methods. The application of the ratio of metal content in the ore was successfully used in the development of the classification of technological flotation schemes of, for example, pyritic copper and copper-zinc ores [5]. The geological and mineralogical features of the pyritic polymetallic deposit are reviewed in the literature [6–12, 14, 15]. In [7, 8] it is noted that when searching for the interconnection between the geological and mineralogical features of the deposit and the results of the flotation process, in addition to the material characteristics of ores – mineral, chemical, granulometric composition and textural and structural properties, the electrochemical properties of ore minerals also have an influence. Meanwhile the latter play a dominant role in ore processing. For specialists in the field of classical flotation, the main link in the development of the classification of processed raw materials is a set of preliminary studies, which includes mineralogical, fractional, granulometric analyses of the ore, as well as some studies of the physical properties of the minerals included in the ore. This approach to creating a system of technological classification is not acceptable, since it does not provide an online mode because of the constant variability of the type of ore mixture processed at the plant.

2 Materials and Methods Forming a statistical array when performing an audit of a processing plant. For the analysis, an array of results of shift work of the plant obtained during the processing was formed. The statistical array consisted of 342 observations. The statistical evaluation of the generated data array is shown in Table 1. Zn/Cu refers to the polymetallic factor, the value of which decreases with an increase in the proportion of copper-zinc ores in the processed ore mixture; MeCu and MeZn are the sum of the content of the metals Cu, Pb, Zn in the copper and zinc concentrate (the sericitic factor). A decrease in the values of the Me parameter indicates an increase in the sericitic component in the initial ore mixture. The Pb content in the copper concentrate [bPb(Cu)] is considered as a factor of electrochemical oxidation that affects the technological parameters of flotation.

3 Results According to Table 1, an important conclusion can be made about the significant variability of all the parameters under consideration. We have shown that it is not possible to explain this observed pattern using the traditional methods of basic statistics. Therefore, we applied the Kohonen neural network modeling method. The classification of the array of initial observations of input parameters was carried out using the 12:12-24:1 Kohonen neural network model KSOM [13], 12 × 2 format. The initial data was divided into learning – 172, control – 85 and test – 85 samples. The following were accepted as input observations: gCu, gZn, αCu, αPb, αZn, bPb(Cu), bZn(Cu), bCu(Zn), αZn/αCu, αCu/αPb, MeCu, MeZn.

38

E. Ushakov et al. Table 1. Statistical evaluation of the analyzed parameters.

Parameter

Type codes Average Minimum Maximum Std. dev.

Cu concentrate yield, %

gCu

6.17

2.92

10.30

1.27

Zn concentrate yield, %

gZn

5.54

0.69

14.05

2.03

Section productivity, t/h

G

2230

316

3959

579

Cu contents in ore, %

aCu

1.60

0.87

2.32

0.23

Pb contents in ore, %

aPb

0.88

0.18

2.04

0.37

Zn contents in ore, %

aZn

3.41

1.00

7.87

1.14

Cu contents in concentrate, %

bCu(Cu)

23.44

17.39

30.23

2.23

Pb contents in Cu concentrate, %

bPb(Cu)

5.88

0.53

14.15

2.40

Zn contents in Cu concentrate, %

bZn(Cu)

3.56

1.00

7.52

1.12

Cu contents in Zn concentrate, %

bCu(Zn)

1.55

0.63

6.26

0.74

Pb contents in Zn concentrate, %

bPb(Zn)

2.05

0.27

8.37

1.32

Zn contents in concentrate, %

bZn(Zn)

51.87

29.66

59.87

4.72

Cu recovery in Cu concentrate, % ECu(Cu)

89.11

51.88

95.94

5.21

Pb recovery in Cu concentrate, %

EPb(Cu)

45.00

2.43

95.00

20.1

Zn recovery in Cu concentrate, %

EZn(Cu)

6.87

0.57

16.15

2.76

Cu recovery in Zn concentrate, %

ECu(Zn)

5.08

1.21

23.54

2.59

Pb recovery in Zn concentrate, %

EPb(Zn)

13.52

1.57

70.12

9.94

Zn recovery in Zn concentrate, %

EZn(Zn)

83.12

24.00

95.31

8.41

Cu contents in tails, %

tCu

0.09

0.04

0.31

0.04

Pb contents in tails, %

tPb

0.16

0.02

0.63

0.07

Zn contents in tails, %

tZn

0.30

0.10

1.29

0.18

Selectivity (εCu + εZn)

Sel

172

110

191

10.9

Ratio of Zn to Cu in ore

Zn/Cu

2.14

0.81

4.52

0.68

Ratio of Cu to Pb in ore

aCu/Pb

2.14

0.69

8.11

0.97

The sum of contents of the metals MeCu Cu, Pb, Zn in Cu concentrate

32.9

26.2

41.2

2.45

The sum of contents of the metals MeZn Cu, Pb, Zn in Zn concentrate

55.5

32.8

62.8

4.36

The topological map of Kohonen is shown in Fig. 1. On the map, according to the numbers of identified elements of the Kohonen grid “0–23”, the number of observations of neurons for each element is marked.

Neural Network Modeling Methods in the Analysis of the Processing

39

9

10

20

17

21

12

13

7

21

19

14

6

13

12

13

13

16

14

7

8

15

37

9

16

Fig. 1. Kohonen topological map.

4 Discussion To achieve higher reliability in the identification of topological Kohonen maps for diagnostic purposes a methodology is proposed. It includes the interpretation of calculated average values of studied parameters of all neurons, using the method of factor analysis, design of selected neurons on the plane of the main components Fi – Fj and applying on them the physical values of the vectors of the measured parameters and contour lines of output functions. The component load matrix is defined and presented in Table 2. The presented matrix reflects the input variables that were used in the analysis. According to the Kaiser criterion, only four factors with eigenvalues greater than 1 are identified. Table 2. The component load matrix (highlighted: main components (>0.700).

gCu gZn aCu aPb aZn bPb(Cu) bZn(Cu) bCu(Zn) Zn/Cu aCu/Pb MeCu MeZn Total variance Proportion of the whole

Factor 1

Factor 2

Factor 3

Factor 4

0.058 0.965 0.286 0.885 0.932 0.167 0.229 -0.514 0.957 -0.783 0.270 0.075 4.623 0.385

0.949 0.150 0.901 0.231 0.137 0.387 0.268 -0.409 -0.051 -0.429 0.028 0.016 2.384 0.199

0.040 -0.135 0.156 0.175 0.239 -0.056 0.386 -0.714 0.198 -0.246 0.261 0.955 1.873 0.156

0.238 0.116 0.184 0.280 0.196 0.853 0.719 -0.150 0.148 -0.259 0.897 0.220 2.429 0.202

The first component reflects the two main parts of the processed ore mixture. In the positive direction of the mathematical vector, high loads of gZn (+0.965), APB (0.885), AZN (0.932), and AZN/ACU (0.957) are recorded due to the development of the polymetallic factor. In the opposite direction of the mathematical vector, a large negative load of the copper factor αCu/αPb (−0.783) is recorded, which indicates strengthening

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in the Cu-Zn component. The high content of copper in zinc concentrate (−0.514) is evidence to the fine dissemination in these ores. The second component has a maximum positive load of the content of copper in the ore (+0.901) and on the parameter gCu (+0.949). This direction is identified as the strengthening of the factor of disseminated Cu-Zn ores. In the opposite direction of the mathematical vector, the negative load of the copper content in zinc concentrate (-0.409) is fixed, which allows the identification of the development of the factor of poor emulsive disseminated ores. The first two components reflect the two main parts of the processed ore mixture. The third and fourth components additionally display subtypes connected with the development of sericitization and electrochemical oxidation processes in the deposit. Eigenvalues of the components (Table 3) indicate that the first and second components describe the examined multifactorial space by 74%. All four components describe a 94% variation in the initial characteristics. Table 3. Eigenvalues of the components. Eigenvalue (array on FA sta) highlighted: main components Components

Eigenvalue

% of variability

Accumulative value

1

6.92

57.70

2

1.97

16.39

8.89

74.09

3

1.36

11.37

10.26

85.46

4

1.05

8.78

11.31

94.24

6.92

Accumulative % 57.70

The multidimensional factorial space is designed on the plane of the Fi – Fj components. For example, Figs. 2 and 3 presents projections of a multifactorial space on the plane F1–F3, to which contour lines of copper and zinc recovery and the content of metals in concentrates are applied. Numbers of elements of the Kohonen grid are placed near the points. Additionally, physical vectors of initial characteristics are plotted on the planes in accordance with their loads on mathematical vectors (Table 2). In the figures the observations of the Kohonen grid are combined into four clusters: • A cluster of polymetallic ores in the direction of the vectors αZn, αPb, αZn/αCu, gZn; • A cluster of Cu-Zn ores composed of disseminated ores with unbound inclusions that generally do not have high conductivity, for example, due to the insulating effect of intergranular layers that do not create any intense natural electric fields. This cluster is fixed by the positive direction of the bPb/Cu vector; • A cluster of Cu-Zn ores composed of inclusions with associated sulfide secretions that have high conductivity. The most favorable in this regard are ores composed of minerals such as pyrite, pyrrhotine and copper sulfides. This cluster is fixed at lower values of the bPb/Cu vector; • A cluster of poor finely disseminated sulfur pyritic copper ores with the development of sericitization and electrochemical oxidation processes.

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Fig. 2. Projection of a multifactorial space on the plane F1–F3, with applied copper extraction contour lines.

Fig. 3. Projection of a multifactorial space on the plane F1–F3, with applied zinc extraction contour lines.

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According to the developed technological classification, the identified enrichment curves are shown in Fig. 4 and 5.

Fig. 4. Evaluation of the dependence of εCu-βCu, with applied contour lines of Cu content in the ore.

Limit curves of enrichment are naturally observed when the content of copper in the ore increases. The decrease in technological indicators in the copper cycle during processing of polymetallic ores can only be explained by the imperfection of the applied reagent mode, when the number of depressors supplied increases with an increase in the zinc content in the ore. When the ratio of finely disseminated Cu-Zn ores in the processed ore mixture increases, it naturally worsens the technological indicators in the copper cycle. The most difficult-to-recover type of processed ore mixture are poor finely disseminated sulfur pyritic copper ores. Marked on the flotability curves of copper (Fig. 4) the low extraction of 81.3% of copper in the observed element of the Kohonen grid numbered “7” can only be explained by a significant violation of the reagent mode in the copper cycle, since this element according to the classification carried out (Fig. 3) belongs to the cluster of polymetallic ores. The main factor in increasing zinc recovery in the processing of polymetallic ores is an increase in the metal content in the ore (Fig. 5). The main factor in reducing the quality of the zinc concentrate is an increase in the content of copper in it. This is evident when examining a cluster of finely disseminated Cu-Zn ores in Fig. 5 and is due to the location of the cluster on the F1–F3 plane (Fig. 3) in the direction of the bCu/Zn vector, which characterizes the development of inclusions with associated releases of high-conductivity sulfides. A decrease in the quality of zinc concentrate in this case is accompanied by an increase in metal recovery.

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Fig. 5. Evaluation of the dependence of εZn–βZn, with applied contour lines of Zn content in the ore.

The technological interpretation of the topological map of Kohonen is shown in Fig. 6. 1

2

3

12

1,60 1,43 5,01 13

5

6

1,64 0,96 3,83 14

1,63 0,84 3,24 15

1,67 0,89 3,34 16

1,42 0,50 2,22 17

1,80 1,08 4,24

1,65 0,91 3,23

8

9

1,52 0,66 3,43

1,50 1,08 4,47

18

19

1,63 0,95 3,62 20

1,70 0,88 3,11

1,83 0,81 2,74

1,39 0,44 2,00

1,57 1,19 5,06

1,69 1,59 5,17

1,73 0,70 2,44

21

Polymetallic ore

1,76 1,06 4,50

10

11

Polymetallic ore

disseminated Cu-Zn ore

1,66 1,64 5,96

7

disseminated Cu-Zn ore

Polymetallic ore

1,62 1,18 4,42

4

22 Sericitization

0

1,55 0,84 3,57

1,53 0,73 2,08

1,57 0,88 3,37 23 Sulfur pyritic poor finely disseminated copper ore

1,61 0,78 2,87

1,15 0,25 1,40

Fig. 6. Technological interpretation of the Kohonen topological map. The figure shows the contents of Cu, Pb and Zn in the ore sequentially.

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The developed approach of technological classification of processed raw materials allows us to trace the changing trend on the topological map of Kohonen (Fig. 7). The topological map shows the trend of the ore mixture processing sequence during 18 shifts. 0

1

2

3

4

5

6

7

8

Polymetallic ore 13

10

11

finely disseminated Cu-Zn ores

disseminated Cu-Zn ore

12

9

Beginning

14

Start

15

16

17

18

19

20

21

22

23

Sulfur pyritic poor finely disseminated copper ore

Fig. 7. Observation of a changing trend on the Kohonen topological map.

According to the presented trend, it is hardly possible to count on adequate actions of operational personnel to manage flotation operations. This observation confirms the reason for the observed large variability of technological indicators.

5 Conclusion As a result of the research, the complexity of the processed pyritic polymetallic ore of the deposit is shown. The use of Kohonen neural networks in solving the problem of technological typification of pyritic polymetallic ores is justified, since the flotation process is essentially a multifactorial and nonlinear object. It is shown that Kohonen maps are a visual arrangement of multiparametric information, can be used to detect differences in the system behavior modes, abnormal modes can be detected and unexpected data observations can be discovered, the subsequent interpretation of which leads to new knowledge about the system under study. The interpretation of the Kohonen map carried out using the factor analysis methodology allowed us to identify four main clusters of subtypes of the processed ore mixtures of the deposit. The developed technology can be implemented at the plant online with the help of express data analysis control,

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which allows you to promptly change the reagent modes in order to achieve higher metal recovery and better quality of the resulting concentrates. Acknowledgement. The research was carried out under the grant received from Russian Foundation of Fundamental Research № 20-55-12002.

References 1. Nikolaeva, N., Aleksandrova, T., Romashev, A.: Effect of grinding on the fractional composition of polymineral laminated bituminous shales. Miner. Process. Extr. Metall. Rev. 39(4), 231–234 (2018). https://doi.org/10.1080/08827508.2017.1415207 2. Kuznetcov, V.V., Aleksandrova, T.N.: Methods for efficiency evaluation of flotation recovery of precious metals from sulphide raw materials. In: Topical Issues of Rational use of Natural Resources - Proceedings of the International Forum-Contest of Young Researchers 2018, pp. 211–216 (2019) 3. Nikolaeva, N., Romashev, A., Aleksandrova, T.: Degree evaluation of grinding on fractional composition at destruction of polymineral raw materials. In: IMPC 2018 – 29th International Mineral Processing Congress, pp. 474–480 (2019) 4. Alexandrova, T.N.: Key directions in processing carbonaceous rocks. Zapiski Gornogo instituta 220, 568–572 (2016). https://doi.org/10.18454/pmi.2016.4.568 5. Aleksandrova, T.N., Arustamyan, K.M., Romanenko, S.A.: The mathematical analysis methods application in estimation of the international practice of copper-zinc and pyriticpolymetallic ores selective flotation. Obogashchenie Rud 5(371), 21–27 (2017) 6. Zimin, A.V., Arustamyan, M.A., Solovyova, L.M.: Classification of technological schemes of flotation of pyritic copper and copper-zinc ores. Gorny J. 11, 28–33 (2012) 7. Abdullin, A.A., Bespaev, H.A., Votsalevsky, E.S.: Deposits of Lead and Zinc in Kazakhstan. Almaty (1997) 8. Sveshnikov, G.B.: ElectroChemical Processes in Sulfide Deposits. Leningrad University Press, Leningrad (1967) 9. Titov, D.V.: The use of geophysical methods for evaluating the technological properties of ores of Pyrrhic-polymetallic deposits. Proc. Tomsk Polytechn. Univ. 4(309), 40–47 (2006) 10. Romanenko, S.A., Ushakov, E.K.: Development of technological typification of copper-zinc pyrrhotite-containing ores on the example of the Prior Deposit. In: Materials of the XXIV International Scientific and Technical Conference Scientific Bases and Practice of Processing of Ores and Technogenic Raw Materials, pp. 66–71. Yekaterinburg (2019) 11. Romanenko, S.A.: Effectiveness of multi-sensor ionometry systems and neural network modeling methods application in flotation processes laboratory studies. Obogashchenie Rud 1, 18–22 (2013) 12. Heikkinen, S., Mashevsky, G.N.: Algorithmic base for controlling the flotation process. Ore Dressing 6, 32–37 (2005) 13. Kohonen, T.: Samoorganizuyushchiyesya Karty: Adaptivnyye i Intellektualnyye Sistemy (Self-organizing Maps: Adaptive and Intelligent Systems). BINOM. Laboratoriya znaniy, Moscow (2010) 14. Mashevskiy, G.N., Romanenko, S.A.: Copper-pyrite ores flotation cleaning cycle mathematical model. Obogashchenie Rud 4, 27–33 (2014) 15. Mashevskiy, G.N., Petrov, A.V., Romanenko, S.A., Sufyanov, F.S.: Development of ore types processing classification principles on the basis of flotation process parameters control and neural network modeling. Obogashchenie Rud 4, 36–42 (2012)

Safety Management Technology of Electric Networks Using Geo Information System Viacheslav Burlov , Viktor Mankov , Alexandr Tumanov , and Maksim Polyukhovich(B) Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, St. Petersburg, Russia [email protected]

Abstract. Sustainable safe functioning of electric power networks ensures uninterrupted supply of electricity to consumers within the limits of acceptable (standardized) indicators of its quality. Meteorological factors influence the process of power transmission through power lines. The impact of hydrometeorological phenomena and processes is associated with losses in energy transmission, short-term and long-term power supply disruptions, and direct damage to infrastructure facilities. Due to the need to predict weather conditions and timely response, this study proposes a general approach to the synthesis of the power supply management system and the geo information system. Managing the process of uninterrupted electric power supply requires the formation of processes with predefined properties. The concept of management based on synthesis fulfills these requirements. The use of a geo information system eliminates interruptions in the supply of electricity to consumers. It is shown that the basis for controlling the process of required power supply is a person’s decision. Keywords: Safety · Management · Technology · Geo information system · Electricity

1 Introduction Power industry is one of the most important sectors of the Russian economy. The mode of operation of the electric power system is determined by the needs for electricity, as well as the current hydrometeorological conditions [1]. In general, the following types of meteorological factors affecting power transmission can be distinguished: – – – – –

rude wind; glaze-ice and rime deposition; thunderstorms; hailstorm; precipitation event (rain, snow, mixed precipitation);

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 46–56, 2021. https://doi.org/10.1007/978-3-030-57453-6_5

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– – – – – – – – –

47

thermal effect (heat, frost); solar radiation; hydrological phenomena (hanging dam, flash flood, seasonal flood); complexes of adverse events: a combination of rude wind and glaze-ice and rime deposition; a combination of rude wind, hail and rain; a combination of hail and rain; a combination of rude wind and rain; a combination of rude rain and snowfall (snowstorm).

The weather dependence of the electric power industry is determined by a significant number of infrastructure objects exposed to weather and climatic factors: overhead power transmission lines, transformer substations, heating mains, etc. The impact of hydrometeorological phenomena and processes is associated with losses in electric power transmission, short-term and long-term power supply disruptions, and direct damage to infrastructure facilities. For energy organizations, these types of losses are complicated by the system of applying mulcts on the part of energy consumers in the event of power outages or the supply of energy of inadequate quality. The types of losses in electric power system under the influence of meteorological factors are considered. Two types are distinguished: – damage to infrastructure facilities (lines and poles of electric power transmission lines); – power outage. Electric power transmission lines are most exposed to such meteorological factors as: rude wind; glaze-ice and rime deposition; thunderstorms. Operational experience shows that damage to electric power system is uneven throughout the year. The distribution of the causes of the power outages is seasonal [2, 3]. Fall of trees due to a larger crown occurs in the summer-autumn period. Insulation depreciation more often occurs in the spring and summer. Thunderstorms occur on two thirds in the summer, and ice deposit occur in the winter [4]. Wind speed above the calculated value leads to damage most often in spring and autumn. Birds cause emergency situations during periods of active flights: in spring and autumn [5]. The main part of production downtime caused by blackouts is one day or less [6]. According to modern estimates, the reason for power outages of cases is due to natural factors, of which in which the largest part is weather conditions [7–9]. The most dangerous impact on the energy sector is caused by wind and precipitation, lightning. Depending on the duration of the outage, consumers of electricity have losses of different scales. In addition, losses from interruptions in energy supply also depend on the type of consumer. In St. Petersburg for the 1st quarter of 2019, the undersupply (loss) of electric energy to consumers due to emergency outages amounted to 51499 kWh. At the same time, 30 outages occurred under the influence of natural phenomena, and 32 outages from falling trees (branches) due to atmospheric phenomena. Of the total amount, these reasons account for about 28%.

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Thus, it is obvious that the influence of climatic factors on energy losses is significant. This fact leads to the problem of ensuring the required quality of electric power supply to consumers (consummation by an object of the electric power complex of its purpose) [10]. One way to solve the problem is to create geo information systems (GIS). GIS is a unified system of cartographic information, including digital data about each specific locality. A distinctive feature of GIS is the presence of a connection between different points of space with the provision of typical information from external sources [11]. Telemetry objects are some objects of the electric power system (equipment, line, etc.) for which, using a variety of sensors, electrical, technical [12] and climatic parameters are measured. Currently, the creation of Smart Grid system is one of the priority areas for the development of information technologies in the energy industry [13, 14]. The basic functions of such a system include instant recording of emergency situations in the power system [15] and warning staff about the approximating of power supply parameters to critical values [16]. Analysis of meteorological parameters is very important to increase productivity and minimize interruptions in the power system.

2 Methods The implementation of power supply conditions is based on an appropriate management process. The technology of such management is reduced to the transformation of information and activity resources in the interests of achieving the goal of the activity. The main functions of the electric power system: – reliability of power supply; – the quality of electricity supplied to the consumer; – safety of electrical installations. The accomplishment of these functions is ensured by a combination of technical means and respective organizational measures. It is proposed to use the GIS of power supply management as a means of ensuring the environmental economy within the framework of the sustainable development paradigm [17]. This system is based on forecasting the performance of meteorological indicators: – – – – –

wind load; intensity of thunderous characteristics; precipitation (rain, snow, thick fog, hoarfrost, dew, etc.); temperature; solar radiation.

In this study, the issues of forecasting these indicators are considered. These indicators are the main structural elements in the formation of information support for the power supply management system.

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As a result of the development of a managerial decision, an impact is made on the electric power industry object. Management results and environmental data are sent to the surveillance subsystem. The geo information monitoring system forms a closed selforganizing system. The integration of the power management system and GIS led to the creation of a GIS for electric power supply management. The activity of such a system should provide a guaranteed result - the supply of electricity to consumers. The basis of activity is the decision of the decision maker (DM) [18]. Therefore, an independent scientific and practical interest is an adequate mathematical model of the decision of the DM, aimed at the rational management of power supply. Also worth noting is that in the proviso of the dynamics of changes in environmental characteristics under paradigm of sustainable development of territories, it is required to have a model for the formation of GIS geodata. This implies the problem of integrating the two processes: – the process of geodata formation (in this research, the characteristics of wind load indicators, thunderstorms, precipitation, temperature, solar radiation); – decision making process. The process of geodata generation in energy management is based on predicting the climatic characteristics of the territory. No-break power supply process control requires the formation of processes with predetermined properties [18]. This study presents a synthesis-based control concept that can meet these requirements. Providing sustainable power supply management for geographically dispersed objects is based on the use of data from GIS. Receiving and processing data is the most important and time-consuming stage of creating such information systems. The method of obtaining data on climatic indicators of the environment is considered the most promising and economically feasible in the management of sustainable electricity supply. GIS data must be used to shape the decision by the DM. This raises the problem of establishing a relationship between the GIS data and the decision-making model of the DM in the interests of guaranteed achievement of the goal of the activity. Without the methodological foundations of solving the problems of power supply management in the form of the conditions for the existence of the process, it is impossible to guarantee the achievement of the goal of the activity [10]. The basis of the activity is the decision of man. A person carries out his activities on the basis of a model. Therefore, in order to carry out activities in an adequate hydrometeorological setting, it is necessary to have an adequate mathematical model of human decision [18]. The aim of this work is to select and justify the conditions for guaranteed achievement of the goal of power supply management based on the synthesis of a mathematical solution model. Obtaining the conditions for the existence of the power supply management process allows constructive technology to be built. The technology for managing the safety of electric networks is the transformation of information and activity resources of DM in the interests of achieving the goal of the activity.

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In the process of activity, a person operates with the categories “system”, “model” and “purpose” [10]. Under the model of the object is understood the description or representation of the object corresponding to it and allowing to obtain characteristics about this object. Thus, a solution is a model of the process with which a person works. A process is an object in action with a fixed purpose. For synthesis, it is necessary to apply the natural science approach (NSA), based on the object integrity maintenance law (OIML) [10]. To create the conditions guaranteeing the achievement of the goals of the activity, the NSA should be used in the management of electric power supply. This approach is determined by the integration of the properties of the “human reasoning”, “outworld” and “cognition” [18]. NSA implemented by the Russian scientific and pedagogical school “System integration of public administration processes”. NSA is based on the principle of three-component cognition, which consists in the fact that a person carries out the development of solutions at three levels of representation of the situation: 1. Abstract level (forms a condition for the existence of the process). 2. Abstract-concrete level (forms causal relationships). 3. Specific level (forms the conditions for the implementation of causal relationships). Understanding the conditions for the existence of the process allows a person to be guaranteed to achieve the goal of activity. Using the decomposition method, the solution can be divided into three elements: “situation”, “solution” and “information and analytical work”. These elements correspond to “object”, “purpose” and “activity”. Using the method of abstraction, the “object” (“situation”) is identified with the frequency of manifestation of the problem in front of the person – tPM . “Purpose” (“solution”) is identified with the frequency of neutralization of the problem (average time for an adequate response to the problem) by a person tPN . “Activity” (“information and analytical work”) is identified with the frequency of identifying the problem (average time to recognize the situation) - tPI . Let us to introduce an additional value of “T”, which represents the average time to complete the target task (supplying consumers with electricity). These elements are presented in Fig. 1 (a) an average time of hazard occurrence (problem manifestation); b) an average problem identification time; c) an average time to neutralize the problem; d) the average time to complete the target task). Temporal characteristics are justified by the fact that only temporary resources for humans are irreplaceable. In the study, let us to move from the absolute values of time (tPM , tPI , tPN , T) to the frequency (intensity) of the occurrence of the corresponding events (λ, ν1 , ν2 , ζ+ ). To clarify the description, let us to introduce the following notation: λ = 1/tPM (inverse of the average time the problem manifested), ν1 = 1/tPI (inverse of the average time to identify the problem), ν2 = 1/tPN (inverse of the average time to neutralize the problem), ζ+ = 1/T (inverse of the average time to accomplishment of target task). Let us to introduce an additional parameter ζ- (frequency of disruption of the power supply process).

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The DM during management can perform two functions: – identify (recognize) the problem; – neutralize (use the power supply resources) problem. This management process can be represented in the form of the following graph (Fig. 2). This diagram shows two circuits. The first circuit (a) is a power supply management system consisting of sequential controls elements. For the sustainable functioning of an electric power complex facility, constant and timely monitoring of meteorological parameters is required. For this, GIS (b) is integrated into the power supply management system. Such integration provides DM with information on the state of the environment at the moment and in the near future. Two modes of functioning of electric power network are considered (Fig. 3): 1) Uninterruptible power supply; 2) The occurrence of interruptions in the process of power supply as a result of exposure to meteorological factors.

a)

ΔtPM

b)

ΔtPI

c)

ΔtPN

d)

t

t

t

T Fig. 1. Time diagram.

t

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GIS

1

λ

2

b)

-

ζ+

ζ

ν1

ν2

4

3

Fig. 2. State graph of the process of forming a management decision.

1

1) 2)

1

4 2

3

4

Fig. 3. Modes of functioning of electric power network.

The entered assumptions allow the use of the Kolmogorov-Chapman system of differential equations [18]. The solution of this linear algebraic system of equations is the following relations: P1 = (ζ− · ν1 · ν2 )/(λ · ζ− · ν1 + λ · ζ− · ν2 + ζ+ · ν1 · ν2 + λ · ν1 · ν2 + ζ− · ν1 · ν2 ),

(1)

P2 = (λ · ζ− · ν2 )/(λ · ζ− · ν1 + λ · ζ− · ν2 + ζ+ · ν1 · ν2 + λ · ν1 · ν2 + ζ− · ν1 · ν2 ),

(2)

P3 = (λ · ζ− · ν1 )/(λ · ζ− · ν1 + λ · ζ− · ν2 + ζ+ · ν1 · ν2 + λ · ν1 · ν2 + ζ− · ν1 · ν2 ),

(3)

P4 = (ζ+ · ν1 · ν2 + λ · ν1 · ν2 )/(λ · ζ− · ν1 + λ · ζ− · ν2 + ζ+ · ν1 · ν2 + λ · ν1 · ν2 + ζ− · ν1 · ν2 ).

(4)

These ratios determine the probability of the power supply control system being in the corresponding states. An indicator of the effectiveness of a power management system is the probability that each threat to the power management system will be identified and neutralized. This indicator is determined by the ratio: P4 = (ζ+ · ν1 · ν2 + λ · ν1 · ν2 )/(λ · ζ− · ν1 + λ · ζ− · ν2 + ζ+ · ν1 · ν2 + λ · ν1 · ν2 + ζ− · ν1 · ν2 ).

(5)

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3 Results Let us to consider the threat of glaze-ice on the wire. Glaze-ice is the formation on the wires of a layer of solid atmospheric precipitation in the form of clean ice, hoarfrost, melted snow and a combination of these precipitations. Most often, ice on wires and cables is observed at an air temperature close to 0 °C, when thaws are replaced by cold spell. Let us to compose an algorithm of actions according to Fig. 2. 1-2. When analyzing the GIS-data, a decrease in the ambient temperature to 0 °C was predicted for 3 h. (180 min.). 2-3. The DM predicts the formation of glaze-ice on the wire of the power line (25 min.). 3-4. Given the meteorological conditions (wind speed, atmospheric temperature) and the characteristics of the wire (wire diameter, wire resistance), preventive heating of the wire is carried out (60 min.). 4-1. The object fulfilled its purpose (supplying consumers with electricity) (1440 min.). The value of the preventive heating current is determined by the expression: (6) where v – wind speed, m/s; TA – atmospheric temperature, °C, ε = 0.6 – constant radiation, d – wire diameter, cm., R+1 – resistance 1 m of wire at +1 °C. Thus, let us to obtain the following values: λ = 1/180 = 0.006. ν1 = 1/25 = 0.04. ν2 = 1/60 = 0.02. ζ+ = 1/1440 = 0.0007. Let us to substitute the predicted values in the expression (5) and determine the indicator of the effectiveness of the functioning of the power supply control system for various values of the frequency of the failure of the power supply (Fig. 4). If ζ− = 1/10 = 0.100, then P4 If ζ− = 1/20 = 0.050, then P4 If ζ− = 1/30 = 0.033, then P4 If ζ− = 1/40 = 0.025, then P4 If ζ− = 1/50 = 0.020, then P4 If ζ− = 1/60 = 0.008, then P4

= 0.15. = 0.26. = 0.34. = 0.41. = 0.47. = 0.68.

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0.8 0.7 0.6 P4

0.5 0.4 0.3 0.2 0.1 0

0.008

0.020

0.025

0.033

0.050

0.100

-

ζ

Fig. 4. The dependence of the probability P4 on the frequency ζ− .

4 Discussion This study describes the development of technology for managing the stable functioning of the electric power system based on the use of GIS. The synthesis of the power supply management system and the GIS is based on the mathematical model of the managerial decision obtained by converting the “managerial decision” by the methods of decomposition, abstraction, and aggregation. As a result, the concept of “managerial decision” was transformed into an aggregate – a mathematical model of a managerial decision of the following form: P = f(λ, ν1 , ν2 , ζ+ , ζ− ),

(7)

where P is an indicator of the effectiveness of the implementation of management decisions. In order for the control object fulfills its purpose (supplying consumers with electricity), the following relationship should be fulfilled: (tPI + tPN )/tPM < 1.

(8)

In general, the research proposes the construction basics of technology for managing electrical networks based on the appliance of GIS. The presented simulation of safety management processes provides an opportunity to apply a guaranteed approach to the management of power supply processes in organizations. In the future, it is planned to complicate the simulation by including additional external factors.

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References 1. Su, Y., Kern, J.D., Denaro, S., Hill, J., Reed, P., Sun, Y., Characklis, G.W.: An open source model for quantifying risks in bulk electric power systems from spatially and temporally correlated hydrometeorological processes. Environ. Model. Softw. 126, 104667 (2020). https:// doi.org/10.1016/j.envsoft.2020.104667 2. Maliszewski, P.J., Larson, E.K., Perrings, C.: Environmental determinants of unscheduled residential outages in the electrical power distribution of Phoenix, Arizona. Reliab. Eng. Syst. Saf. 99, 161–171 (2012). https://doi.org/10.1016/j.ress.2011.10.011 3. Castillo, A.: Risk analysis and management in power outage and restoration: a literature survey. Electr. Power Syst. Res. 107, 9–15 (2014). https://doi.org/10.1016/j.epsr.2013.09.002 4. Cerrai, D., Koukoula, M., Watson, P., Anagnostou, E.N.: Outage prediction models for snow and ice storms. Sustain. Energy Grids Netw. 21, 100294 (2020). https://doi.org/10.1016/j. segan.2019.100294 5. Maricato, L., Faria, R., Madeira, V., Carreira, P., de Almeida, A.T.: White stork risk mitigation in high voltage electric distribution networks. Ecol. Eng. 91, 212–220 (2016). https://doi.org/ 10.1016/j.ecoleng.2016.02.009 6. Adoghe, A.U., Awosope, C.O.A., Ekeh, J.C.: Asset maintenance planning in electric power distribution network using statistical analysis of outage data. Int. J. Electr. Power Energy Syst. 47(1), 424–435 (2013). https://doi.org/10.1016/j.ijepes.2012.10.061 7. Mukherjee, S., Nateghi, R., Hastak, M.: A multi-hazard approach to assess severe weatherinduced major power outage risks in the U.S. Reliab. Eng. Syst. Saf. 175, 283–305 (2018). https://doi.org/10.1016/j.ress.2018.03.015 8. Mankov, V., Efremov, S., Monashkov, V.: Grounding device for electrical networks and electrical installations in the arctic regions. In: 4th International Scientific Conference on Arctic: History and Modernity, vol. 302. Institute of Physics Publishing, Saint Petersburg (2019). https://doi.org/10.1088/1755-1315/302/1/012066 9. Idrisova, J.I., Kaverzneva, T.T., Rumyantseva, N.V., Skripnik, I.L.: Neural network modeling of safety system for construction equipment operation in permafrost zone. In: 4th International Scientific Conference on Arctic: History and Modernity, vol. 302. Institute of Physics Publishing, Saint Petersburg (2019). https://doi.org/10.1088/1755-1315/302/1/012128 10. Polyukhovich, M., Burlov, V., Mankov, V., Bekbayev, A.: Electric power supply management of the construction site in the interests of facilitating electrical safety. In: 2019 International Scientific Conference on Energy, Environmental and Construction Engineering, vol. 140. EDP Sciences, Saint Petersburg (2019). https://doi.org/10.1051/e3sconf/201914008006 11. Feng, M., Shaw, S., Fang, Z., Cheng, H.: Relative space-based GIS data model to analyze the group dynamics of moving objects. ISPRS J. Photogram. Remote Sens. 153, 74–95 (2019). https://doi.org/10.1016/j.isprsjprs.2019.05.002 12. Ferreira, E.F., Barros, J.D.: Faults monitoring system in the electric power grid of medium voltage. Procedia Comput. Sci. 130, 696–703 (2018). https://doi.org/10.1016/j.procs.2018. 04.123 13. Pei, Y., Zhang, H., Gu, X., Wang, H.: Research on power grid information model based on artificial intelligence. In: ICCNEA 2019, pp. 321–328. State Grid Shaanxi Electric Power Company, Xi’an (2019). https://doi.org/10.1109/iccnea.2019.00067 14. Luo, F., Zhao, J., Dong, Z.Y., Chen, Y., Xu, Y., Zhang, X., Wong, K.P.: Cloud-based information infrastructure for next-generation power grid: conception, architecture, and applications. IEEE Trans. Smart Grid 7(4), 1896–1912 (2016). https://doi.org/10.1109/TSG.2015.2452293 15. Bagdadee, A.H., Zhang, L.: Power quality improvement provide digital economy by the smart grid. In: 1st International Conference on Materials Science and Manufacturing Technology 2019, vol. 561. Institute of Physics Publishing, Tamil Nadu (2019). https://doi.org/10.1088/ 1757-899x/561/1/012097

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16. Shrestha, M., Johansen, C., Noll, J., Roverso, D.: A methodology for security classification applied to smart grid infrastructures. Int. J. Crit. Infrastruct. Prot. 28, 100342 (2020). https:// doi.org/10.1016/j.ijcip.2020.100342 17. Russkova, I., Dolgikh, N., Salkutsan, V., Logvinova, Y.: Russia’s arctic is as an object of environmental monitoring. In: 4th International Scientific Conference on Arctic: History and Modernity, vol. 302. Institute of Physics Publishing, Saint Petersburg (2019). https://doi.org/ 10.1088/1755-1315/302/1/012028 18. Burlov, V., Andreev, A., Gomazov, F.: Mathematical model of human decision - a methodological basis for the realization of the human factor in safety management. In: 9th Annual International Conference on Biologically Inspired Cognitive Architectures, pp. 112–117. Elsevier B.V., Prague (2018). https://doi.org/10.1016/j.procs.2018.11.018

Vladikavkaz City Seismological Network Database Vladislav Zaalishvili1,2(B) , Dmitry Melkov2 , Aleksandr Kanukov2 Madina Fidarova2 , and Zarina Persaeva2

,

1 North Ossetian State University after K. L. Khetagurov, Vatutina 44-46, 362025 Vladikavkaz,

North Ossetia - Alania, Russia [email protected] 2 Geophysical Institute of Vladikavkaz Scientific Center, Markov Street, 93a, 362002 Vladikavkaz, Russia

Abstract. A database containing the titles of the records of all seismic events recorded by the network of stations of the Geophysical Institute “Vladikavkaz” and “Karmadon Parametric Test Site” was created. The application of the event sampling procedure makes it possible to select records registered simultaneously by several stations for their subsequent analysis and processing. To process the received data of the Karmadon parametric test site network, a special program for editing events in the SEV format was developed. It allows calling utility programs for their subsequent processing. Utilities for viewing and editing adb file headers, adb file converter to text format. Such data structuring allows not only finding the necessary records from the data bank, but also performing more complex operations using SQL queries. The created replenished database of seismic records and events when it is filled with a large amount of data can become an object that belongs to the category of big data. Keywords: Database · Seismic catalog · Earthquakes · Seismic data processing

1 Introduction The city of Vladikavkaz is located in the zone of high seismic hazard. The southern part of the city is located in a zone with an intensity of 8 points, and the north of 7 points (with a probability of a possible exceedance of this intensity by 2% for 50 years) [1]. In connection with the need to study and subsequent analysis of poorly understood manifestations of the features of the active faults effect on the situation in the city and in order to study the influence of various types of soils and their physical condition on the seismic effect [2–7] in the territory of the city of Vladikavkaz in 2003 it was decided to organize a local network of seismological observations. In August 2004 a local network of seismic observations was organized in areas with different soil conditions directly on the urban territory of Vladikavkaz [8–13].

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 57–63, 2021. https://doi.org/10.1007/978-3-030-57453-6_6

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The main purpose of the Karmadon Parametric Test Site local network, which serves as a source for the created database, is to observe and forecast dangerous geological processes in the form of endogenous (volcanic activity, earthquakes, etc.) and exogenous processes (avalanches, glaciers, landslides, etc.). Thus, the operation of the network involves not only the application of standard procedures for determining the parameters of earthquakes, but also the processing of accumulated large data arrays. After the network was modernized in 2006, the recording time was significantly increased due to the use of high-capacity flash cards, the sampling frequency was increased, and the accurate time service was established due to the use of GPS. In 2012, with the support of the Main Directorate of the Ministry of Emergencies of the Russian Federation for North Ossetia-Alania, equipment was installed in the area of the Kolka glacier bed and later on May 19, 2012 the installation and start of a seismic station was completed by a group of climbers led by O.N. Ryzhanov at an altitude of 2970 meters above sea level. The station operates in continuous mode, which also significantly increased the flow of received and analyzed data. The next stage of network development includes the improvement of technologies for the collection, processing and visualization of large data arrays.

2 Methods To organize the data obtained, quickly search for the necessary records, perform a number of operations on with records (analysis of the network, selecting events, etc.), software was developed that automatically entered data on the time and date of the registrar’s operation into the MS Access database (up to a millisecond), type of record and path to the corresponding file. The program runs on Windows 98-Windows 10, C++ programming language. The procedure can be performed in two modes: entering data contained in separate archiving folders (Fig. 1 a) and also searching and entering data in the specified directory (Fig. 1 b).

Fig. 1. General view of the ADB2DB program: a) data input mode of individual archiving folders; b) search and data entry mode.

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Such data structuring allows not only to find the necessary records from the data bank, but also to perform more complex operations using SQL queries, etc. An important point in processing records of any local network of seismological observations is the selection of events. An event is considered identified if it is registered by at least N stations (for example, three), and the turn-on time of the recorders falls into a certain time interval (time window) dt. The developed program “Event Selection” allows one to search for records that satisfy these conditions. The general view of the “Event Selection” program is shown in Fig. 2. The window is divided into several areas: calendar, text area, SQL string.

Fig. 2. “Event Selection” Window.

The program is similar to the program “adb-slct” of the software package of the center “Geon”, while it has several advantages: – graphical interface; – there is no need to create a *.lst file (a text file containing a list of archiving folders) - data on files is taken directly from the “ADBDB” database, the period is selected using the calendar; – there are no restrictions on the number of files, events can be sampled both for a month and for a year; – the ability to select events separately for calibration records and detection records; – the ability to open and copy files directly from the program window (if the system has a program assigned to open *.adb files); – the ability to automatically copy selected entries to a separate directory for each event. In addition, the program package includes utilities for viewing and editing the headers of adb files (Fig. 3), adb file converter in text format.

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Fig. 3. The window of the program “Header Editor”.

Number of records

The “Delta-Geon” seismic signal recorder is a next-generation registrar in comparison with “Alfa-Geon” SSR; the use of high-capacity memory cards allowed to increase the recording duration of each event. In addition, it becomes possible to download information for longer periods of time (at some stations of the regional network equipped with Alfa-Geon RSS, memory overflow may occur if data are not downloaded on time). Nevertheless, as can be seen from the table, the number of archiving folders for each station, which characterizes the regularity of downloading the information, corresponds to the frequency of downloading information once a week. Figure 4 presents a diagram showing the distribution of the total number of records by month for the period from the end of 2017 to the end of 2018. 1565 1362 1094 883 853 934 908 789 511

916 674

1021 627

239 116 109 133 118 117 107 114 112 84 47 95 104 102 103

1600 1400 1200 1000 800 600 400 200 0

Fig. 4. The distribution of the records number of the local urban network of seismic observations “Delta-Geon” by month; “Record type 0” —detection record; “Record type 2” – calibration.

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To process the obtained data of the network of the Karmadon parametric test site, the WINADB-SEV program was developed, intended for editing events in the SEV format and allowing calling utility programs for their subsequent processing - utilities for viewing and editing adb file headers, adb file converter to text format. Such data structuring allows not only to find the necessary records from the data bank, but also to perform more complex operations using SQL queries.

3 Results The next step was the development of a telemetric data transmission system that will allow to replenish the database with records of seismic events in a mode close to real time. The Delta-03 supports the ability to exchange information over TCP/IP, which allows the recorder to be directly connected to Ethernet local networks. For Kolka station, a satellite communication channel was chosen based on iDirect stations used to organize data transfer via Ethernet/IP technology via satellite communication channels in hardto-reach areas. The seismological telemetry network created on the basis of the “Delta-03” SSR is built according to the radial scheme, in the center of which is the Central Information Gathering Station that is built on the basis of a personal computer [8]. From this point, the user has access to any field observation point. The user can set or check the exact time, change the operating modes of the “Delta-03” seismic signal recorder, copy the accumulated seismological information or prepare the data storage (Flash disk or RAM disk) remotely for receiving new seismological information. When connecting to the provider line, it should be noted that the authentication protocol is not used by the registrar. The developed replenished database of seismic records and events when it is filled with a large amount of data can become an object that belongs to the category of big data. Big Data - a series of approaches, tools and methods for processing structured and unstructured data of huge volumes and significant diversity to obtain human-perceived results that are effective in continuous growth, distribution across multiple nodes of a computer network, alternative to traditional database management systems [14–16]. This series includes the means of massively parallel processing of indefinitely structured data, primarily, solutions of the NoSQL category, MapReduce algorithms, software frameworks and libraries of the Hadoop project. Hadoop is a project of the Apache Software Foundation, a freely distributed set of utilities, libraries and a framework for developing and running distributed programs running on clusters of hundreds and thousands of nodes. It is used to implement search and contextual mechanisms of many highly loaded websites, including Yahoo! and Facebook. It was developed in Java as part of the MapReduce computational paradigm, according to which the application is divided into a large number of identical elementary tasks that can be performed on cluster nodes and naturally reduced to the final result. NoSQL (not only SQL, not only SQL), in computer science, is a term that denotes a number of approaches aimed at implementing database storages that differ significantly from the models used in traditional relational DBMSs with access to data using SQL. It is applied to databases in which an attempt is made to solve the problems of scalability

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and availability due to atomicity data consistency. One of the most powerful NoSQL implementations is the Couchbase Server.

4 Discussion The created database contains the headers of the records of all events, the application of the procedure for selecting events allows user to select records registered simultaneously by several stations for their subsequent analysis and processing. However, the compact location of the stations, which is important for such studies (according to RSN 65-87, those earthquakes are subject to processing at which the distance between the registration points is less than 0.1 hypocentral) does not allow us to determine the parameters of recorded earthquakes (coordinates of the epicenter, magnitude, and etc.) therefore, the use of data from other seismological observation networks in the form of catalogs is a necessary component of this kind of data bank. One data source is the Karmadon parametric test site. The event sampling procedure will provide the matching of the selected records to seismic catalog data. Since the database includes all records registered by the urban network, information on industrial explosions will also be very interesting and important for subsequent studies. A telemetric data transmission system has been developed that will allow replenishing the database with records of seismic events in a mode close to real time. The “Delta-03” recorder supports the ability to exchange information over TCP/IP, which allows the recorder to be directly connected to Ethernet local networks. For Kolka station, a satellite communication channel was chosen based on iDirect stations used to organize data transfer via Ethernet/IP technology via satellite communication channels in hard-to-reach areas. The developed replenished database of seismic records and events when it is filled with a large amount of data can become an object that belongs to the category of big data. Acknowledgments. The study was carried out with the financial support of The Russian Foundation for Basic Research in the framework of the scientific project No. 19-35-90127.

References 1. Zaalishvili, V.B.: Some problems of the practical implementation of seismic microzoning. Factors forming the intensity of an earthquake. Geol. Geophys. Russ. South 3, 3–39 (2014). https://doi.org/10.23671/vnc.2014.3.55444 2. Gyuricza, C., Smutný, V., Percze, A., Pósa1, B., Birkás1, M.: Soil condition threats in two seasons of extreme weather conditions. Plant Soil Environ. 61(4), 151–157 (2015). https:// doi.org/10.17221/855/2014-pse 3. Weigong, C.: Study on computer-aided fault tree construction for geological disasters. In: First International Workshop on Database Technology and Applications, vol. 2, pp. 606–609 (2009). https://doi.org/10.1109/DBTA.2009.50 4. Kharebov, K., Zaalishvili, V., Zaks, T., Baskaev, A., Arkhireeva, I., Gogichev, R., Maisuradze, M., Chitishvili, M.: Influence of soils on impact parameters of seismic effect. In: Advances in Engineering Research, pp. 164–168 (2019). https://doi.org/10.2991/ciggg-18.2019.31

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5. Parada, S., Chotchaev, K., Berger, M., Magkoev, T., Bekuzarova, S., Burdzieva, O., Zaks, T., Komzha, A.: Sodium geochemistry in terrigenous complexes in connection with problem of gold content. In: Advances in Engineering Research, pp. 243–249 (2019). https://doi.org/10. 2991/ciggg-18.2019.46 6. Loudon, T.V.: Knowledge-based systems and geological survey. Zeitschrift der Deutschen Geologischen Gesellschaft 155(2–4), 225–246 (2005). https://doi.org/10.1127/zdgg/155/200 5/225 7. Krogh, L., Greve, M.H.: Evaluation of world reference base for soil resources and FAO soil map of the world using nationwide grid soil data from Denmark. Soil Use and Manage. 15, 157–166 (2006). https://doi.org/10.1111/j.1475-2743.1999.tb00082.x 8. Zaalishvili, V., Chotchaev, K., Melkov, D., Kanukov, A., Magkoev, T., Gabeeva, I., Dzobelova, L., Shepelev, V.: Complex Analysis of geological data and use of velocity model of MMS on central caucasus sections. In: vances in Engineering Research, pp. 319–324 (2019). https:// doi.org/10.2991/ciggg-18.2019.61 9. Rogozhin, E., Milyukov, V., Zaalishvili, V., Ovsyuchenko, A., Mironov, A., Gorbatikov, A., Melkov, D., Dzeranov, B.: Characteristics of modern horizontal movements in central sector of greater caucasus according to GPS observations. In: Advances in Engineering Research, pp. 250–254 (2019). https://doi.org/10.2991/ciggg-18.2019.47 10. Svalova, V., Zaalishvili, V., Ganapathy, G., Nikolaev, A., Melkov, D.: Physical fields as derivative of deformation of rock massif and technology of their monitoring. Geol. Geophys. Russ. South 9(2(32)), 109–126 (2019). https://doi.org/10.23671/vnc.2019.2.31981 11. Burdzieva, O., Zaalishvili, V., Chotchaev, K., Melkov, D., Dzeranov, B.: Engineeringgeological and hydrogeological features of the dzuarikau-tskhinval gas pipeline installation and environmental aspects of its operation in high seismicity conditions. Mater. Sci. Eng. 012-021 (2019). https://doi.org/10.1088/1757-899x/663/1/012021 12. Giorgobiani, T.: The conditions for the formation of the alpine folded system of the Greater Caucasus and the characteristic features of its structure. Geol. Geophys. Russ. South 1, 43–57 (2019). (In Russian) https://doi.org/10.23671/vnc.2019.1.26787 13. Chernov, Y., Chernov, A., Chitishvili, M.: Models of strong ground movements for probabilistic detailed seismic zoning of the territory of North Ossetia-Alania. Part I. Geol. Geophys. Russ. South 3, 161–178 (2019). https://doi.org/10.23671/vnc.2019.3.36753 14. Berra, F.: Geological maps and 3D digital visualization of geological objects: tools for improving students’ education in Earth Sciences. Rendiconti 45, 89–94 (2018). https://doi.org/10. 3301/ROL.2018.34 15. Alcaraz, M., Vázquez-Suñé, E., Velasco, V., Diviu, M.: 3D GIS-based visualisation of geological, hydrogeological, hydrogeochemical and geothermal models. Zeitschrift der Deutschen Gesellschaft für Geowissenschaften 167(4), 377–388 (2016). https://doi.org/10.1127/zdgg/ 2016/0093 16. Clifford, L.: Big data: how do your data grow? Nature 455(7209), 28–29 (2008). https://doi. org/10.1038/455028a

Regional Attenuation Relationships: Regression vs Neural Network Analysis Vladislav Zaalishvili1,2(B)

and Dmitry Melkov1,2

1 Geophysical Institute of Vladikavkaz Scientific Center, Markov Street, 93a,

362002 Vladikavkaz, Russia [email protected] 2 North Ossetian State University after K. L. Khetagurov, Vatutina 44-46, 362025 Vladikavkaz, North Ossetia - Alania, Russia

Abstract. Neural networks are applied now in many fields. It is de facto efficient and flexible tool for analysis, which could be applied where other traditional approaches are impossible. It also gives new knowledge on the basis of data analysis. In this paper, traditional regression approach is considered in comparison with neural network for regional attenuation model assessment - peak ground acceleration (PGA) variation with magnitude and hypocentral distance. Such a simple set of parameters is not usual for neural networks, but simple, and result differences are clear. Dataset was prepared on the base of K-net network data. Records of stations with Vs 30 > 700 m/s were used. Accelerations have wide dispersion, and both of the approaches gave different results: when regression is forced by a given form of linear combination, neural network is more flexible. For example, it was found that for magnitude M = 4, in close distances R > 10 km PGA(R) curve is close to M < 4 curves, and for R > 10 km has the same manner as M > 4 curves. So M = 4, R = 10 km is some kind of “point of inflection” between near field and far field zones. Keywords: Accelerogram · Attenuation relationship · Neural network · Regression

1 Introduction Various spheres of human activity are associated with the generation and accumulation of a huge amount of data, which can contain the most important practical information. This actualizes the problems of automating the extraction of knowledge from a wide variety of sources. Increased speed of calculators and sensors can significantly expand the applicability of modern scientific results in the field of data mining. Today, algorithms built on the basis of neural networks show decent results in such areas as computer vision, speech recognition, natural language processing, and others. So wide application of neural network is due to success of Deep Learning approach. It’s convenient to apply it for seismic loadings assessment. The main parameter is a Peak Ground Acceleration (PGA). It depends on earthquake magnitude, epicentral distance, and depth of the source. In this work traditional regression analysis compared with neural network [1–22]. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 64–71, 2021. https://doi.org/10.1007/978-3-030-57453-6_7

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2 Methodology In 2006, deep learning was presented in the form of a multilayer neural network, the first layer of which revealed the main features of the image, and the subsequent layers built a generalized image of the object in the form of a combination of simple primitives [23]. Nowadays, it is applied for many different problems. Typically, the process of learning a deep neural network is divided into two steps. In the first step, a single-layer network is trained, and in the next step, weights are compared between the network layers by minimizing the classification error. This approach reduces the complexity of training a network with a large number of parameters due to optimization between layers. A deep neural network is an artificial neural network with several hidden layers [24]. Additional layers allow you to build abstractions of ever higher levels, which makes it possible to form a model for recognizing complex objects in the real world. Usually deep direct networks are used (Fig. 1), however, recent studies have shown the successful use of deep architectures in recurrent networks [25]. In tasks related to image processing, convolutional neural networks are mainly used because of their greatest effectiveness.

Fig. 1. Neural network model scheme used in analysis.

Deep neural networks learning can be done using the back propagation algorithm. Thus, several rules for setting weights can be used. For example, the stochastic gradient descent algorithm: w(t + 1) = wij (t) + η +

δL δwij

(1)

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where η is a constant for regulating the magnitude of the current step, L is a loss function. The choice of the loss function can be determined by the class of the machine learning task (with teacher, without teacher, with reinforcement) and activation function. Here we use leaning with teacher. Consider the theory of learning neural networks in the context of teaching with a teacher based on the results published in [7]. The model of teaching with a teacher consists of three interconnected components, which are described in mathematical terms as follows: 1. Environment: characterized by a probability distribution of PX (x) with randomly and independently occurring cases of x; 2. Teacher: generates the desired response d for each of the input vectors x obtained from the external environment, in accordance with the conditional distribution function PX (d | x). Neither the characteristic of the medium PX (x), nor the classification rule PX (d | x) are known. However, it is known that both functions exist, i.e., there is a joint probability distribution PX (d, x) = P (x) · PX (d |x).

(2)

The desired response d and the input vector x are related by the following relation: d = f (x, v),

(3)

where v is the noise, that is, the noise of the teacher data is initially assumed. 3. Learning machine: a neural network is capable of implementing many input-output mapping functions described by the relation y = F (x, w),

(4)

where y is the actual response generated by the trained machine in response to the input signal x; w is a set of free parameters (synaptic weights) selected from the parameter space W.

3 Dataset and Attenuation Relationship The success of machine learning greatly depends on the representativeness of the source data. In recent decades, the number of information technologies that affect all spheres of human activity, including seismology, has been growing rapidly. The use of digital stations once made it possible to automate the processing of earthquake records and create powerful databases. Currently, information storage volumes and computing speeds are growing exponentially. At the same time, in many regions of the world, the number of stations recording strong movements is increasing. To solve the problems of engineering seismology, the locations of stations are chosen so as to cover all possible soil conditions of the territory. Data on engineering and geological conditions are an integral part of modern seismological databases. A similar database was created at the Geophysical

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a)

b)

c) Fig. 2. Magnitudes (a), hypocentral distances (b) and peak ground accelerations (PGA) distribution in dataset.

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Institute of the Vladikavkaz Scientific Centre of the Russian Academy of Sciences and includes data from k-net networks (Japan) and a number of other networks from around the world. Records of stations with Vs 30 > 700 m/s were used (587 records). Distribution hystograms and curves for investigated parameters are shown in Fig. 2. One can see that magnitudes are normally distributed and hypocentral distances and peak acceleration are close to lognormal. So, the simplest regression equation could be: log PGA = C1 + C2 M + C3 log R

(5)

where PGA – peak ground acceleration; M – magnitude, R – hypocentral distance; C1 , C2 , C3 – regression coefficients. Regression for this form gives the next coefficients: C1 = 0.83, C2 = 0.27, C3 = −0.46 with standard deviation σ: 0.39 (for log PGA) and coefficient of determination: 0.22. Regression was made by Sklearn package by LinearRegression function. Next improvement of equation is usually in the next form (taking into account geometrical spreading and attenuation) [26]: log PGA = C1 + C2 M + C3 log R + C4 R

(6)

with regression coefficients C1 = 1.5639, C2 = 0.1570 C3 = −0.2084 C4 = −0.0015, standard deviation σ: 0.30 (for log PHA) and coefficient of determination: 0.19.

4 Results and Discussion Obtained curves for regression and neural network are presented in Fig. 3. Data analysis was performed by TensorFlow (Keras was used) for neural model, presented in Fig. 1. Data were split into train and test subsets with test_size = 0.33. standard deviation σ: 0.3943.5 (for PGA). Curve for M = 4 obtained by neural network differ from others: in close distances R > 10 km PGA(R) curve is close to M < 4 curves, and for R > 10 km has the same manner as M > 4 curves. So M = 4, R = 10 km is a some kind of “point of inflection” between near field and far field zone, due to nonlinear effects in geological medium [27–31]. Comparison of both regression and neural network analysis with initial data are shown in Fig. 4. One can see that neural network is more close to initial data. It must be noted that data presented in Fig. 4 is just a part of a whole dataset, for which regression was calculated (3.9 < M < 4.1). While this magnitude 4 is prevalent in the dataset (Fig. 2a), other parts and predefined for of regression curve predefined such regression curve form in this region. Obtained results show advantages and perspectives of neural network application for regional attenuation calculation which is basis for seismic hazard assessment. Main disadvantage of neural network is inability of direct physical interpretation of results, but can be used as powerful tool for numerical simulation experiments.

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a)

b) Fig. 3. Attenuation curves, obtained by regression analysis (a) and neural network (b).

Fig. 4. Data for M = 4 and corresponding results of regression analysis and neural network modeling.

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References 1. Abramson, N., Braverman, D.: Learning to recognize patterns in a random environment. IRE Trans. Inf. Theor. 8(5), 58–63 (1962). https://doi.org/10.1109/TIT.1962.1057775 2. Abramson, N., Braverman, D., Sebastian, G.: Pattern recognition and machine learning. IRE Trans. Inf. Theor. 9(4), 257–261 (1963). https://doi.org/10.1109/TIT.1962.1057775 3. McCulloch, W.S., Pitts, W.: A logical calculus of the ideas immanent in nervous activity. Bull. Math. Biophys. 5(4), 115–133 (1943). https://doi.org/10.1016/s0092-8240(05)80006-0 4. Hebb, D.O.: The organization of behavior: a neuropsychological theory. Brain Res. Bull. 50(5–6), 437 (1999). https://doi.org/10.1016/s0361-9230(99)00182-3 5. Rosenblatt, F.: The perceptron: a probabilistic model for information storage and organization in the brain. Psychol. Rev. 65, 386–408 (1958). https://doi.org/10.1037/h0042519 6. Rosenblatt, F.: Principles of Neurodynamics. Brain Theor. Spartan, 245–248 (1962). https:// doi.org/10.1007/978-3-642-70911-1_20 7. Widrow, B., Hoff, M.E.: Adaptive switching circuits. WESCON Conf. 4, 96–104 (1960). https://doi.org/10.21236/ad0241531 8. Steinbuch, K.: Die lernmatrix. Kybernetik (Biological Cybernetics) 1, 36–45 (1961). https:// doi.org/10.1007/bf00293853 9. Rosenblatt, F.: Perceptron simulation experiments. Invest. Reporters Editors Conf. 42(3), 301–309 (1960). https://doi.org/10.1109/JRPROC.1960.287598 10. Minsky, M., Papert, S.: Perceptrons. MIT Press, Cambridge (1969). https://doi.org/10.7551/ mitpress/11301.001.0001 11. Kohonen, T.: Correlation matrix memories. IEEE Trans. Comput. C-21(4), 353–359 (1972). https://doi.org/10.1109/tc.1972.5008975 12. Anderson, J.A.: A simple neural network generating an interactive memory. Math. Biosci. 14, 197–220 (1972). https://doi.org/10.1016/0025-5564(72)90075-2 13. Grossberg, S.: Adaptive pattern classification and universal recoding: I. Parallel development and coding of neural feature detectors. Biol. Cybern. 23, 121–134 (1976). https://doi.org/10. 1007/bf00344744 14. Kohonen, T.: Self-organized formation of topologically correct feature maps. Biol. Cybern. 43, 59–69 (1982). https://doi.org/10.1007/bf00337288 15. Kohonen, T.: The self-organizing map. Neurocomputing 21, 1–6 (1998). https://doi.org/10. 1109/5.58325 16. Hopfield, J.J.: Neural networks and physical systems with emergent collective computational abilities. Proc. Natl. Acad. Sci. 79, 2554–2558 (1982). https://doi.org/10.1201/978042950 0459-2 17. Fukushima, K., Miyake, S., Ito, T.: Neocognitron: a neural network model for a mechanism of visual pattern recognition. IEEE Trans. Syst. Man Cybern. 13, 826–834 (1983). https:// doi.org/10.1109/tsmc.1983.6313076 18. Hubel, D.H., Wiesel, T.N.: Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J. Physiol. 160(1), 106–154 (1962). https://doi.org/10.1113/jphysiol. 1962.sp006837 19. Rumelhart, D., Hinton, G., Williams, R.: Learning representations by backpropagating errors. Nature 323, 533–536 (1986). https://doi.org/10.1038/323533a0 20. Granichin, O., Volkovich, V., Toledano-Kitai, D.: Randomized algorithms in automatic control and data mining. Springer (2015). https://doi.org/10.1007/978-3-642-54786-7 21. Angelini, L., Carlo, F., Marangi, C., Pellicoro, M., Nardullia, M., Stramaglia, S.: Clustering data by inhomogeneous chaotic map lattices. Phys. Rev. Lett. 85, 78–102 (2000). https://doi. org/10.1103/physrevlett.85.554

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22. LeCun, Y.: Backpropagation applied to handwritten zip code recognition. Neural Comput. 1(4), 541–551 (1989). https://doi.org/10.1162/neco.1989.1.4.541 23. Hinton, G.E., Osindero, S., Teh, Y.-W.: A fast learning algorithm for deep belief nets. Neural Comput. 18(7), 1527–1557 (2006). https://doi.org/10.1162/neco.2006.18.7.1527 24. Schmidhuber, J.: Deep learning in neural networks: an overview. Neural Netw. 61, 85–117 (2015). https://doi.org/10.1016/j.neunet.2014.09.003 25. Baccouche, M., Mamalet, F., Wolf, C., Garcia, C., Baskurt, A.: Sequential deep learning for human action recognition. In: 2nd International Workshop on Human Behavior Understanding (HBU). Lecture Notes in Computer Science, vol. 7065, pp. 29–39. Springer, Amsterdam, Netherlands (2011). https://doi.org/10.1007/978-3-642-25446-8_4 26. Ambraseys, N.N.: The prediction of earthquake peak ground acceleration in Europe. Earthq. Eng. Struct. Dyn. 24, 467–490 (1995). https://doi.org/10.1002/eqe.4290240402 27. Zaalishvili, V.B.: Measurement and recording equipment for seismic microzoning. Meas. Tech. 58(12), 1297–1303 (2016). https://doi.org/10.1007/s11018-016-0888-2 28. Shempelev, A.G., Zaalishvili, V.B., Kukhmazov, S.U.: Deep structure of the western part of the Central Caucasus from geophysical data. Geotectonics 51(5), 479–488 (2017). https:// doi.org/10.1134/S0016852117050053 29. Zaalishvili, V.B., Morozov, F.S., Tuaev, G.E.: Integrated Instrumental monitoring of hazardous geological processes under the kazbek volcanic center. Int. J. GEOMATE 15(47), 158–163 (2018). https://doi.org/10.21660/2018.47.20218 30. Chotchaev, K.O., Zaalishvili, V.B., Magkoev, T.T., Melkov, D.A., Nikolaev, A.V., Svalova, V.B., Arkhireeva, I.G., Dzeranov, B.V.: Physical fields as derivative of deformation of rock massif and technology of their monitoring. In: Advances in Engineering Research 182. VIII All-Russian Science and Technology Conference “Contemporary Issues of Geology, Geophysics and Geoecology of the North Caucasus” (CIGGG 2018), pp. 62–67. Vlaikavkaz (2019). https://doi.org/10.2991/ciggg-18.2019.12 31. Chotchaev, K.O., Zaalishvili, V.D., Shempelev, A.G., Melkov, D.A., Burdzieva, O.G., Parada, S.G., Dzeranov, B.V., Dzhgamadze, A.K.: Geodynamic situation in central caucasus and structural complexes on depth section of genaldon profile. In: Advances in Engineering Research 182. VIII All-Russian Science and Technology Conference “Contemporary Issues of Geology, Geophysics and Geoecology of the North Caucasus” (CIGGG 2018), pp. 325–331, Vladikavkaz (2019). https://doi.org/10.2991/ciggg-18.2019.62

Use of Neural Networks to Assess Competitiveness of Organizations Mikhail Krichevsky(B)

, Julia Martynova , and Svetlana Dmitrieva

Saint Petersburg State University of Aerospace Instrumentation (SUAI), 67, Bolshaya Morskaya Street, Saint Petersburg 190000, Russia [email protected]

Abstract. The paper contains the proposal to apply the neural networks for the assessment of enterprise competitiveness. Machine learning methods, including neural networks and simulink, were used for the solution of the task. To assess competitiveness, neural networks that give an answer in the form of assignment to a particular class were used. The example base necessary for neural network training was formed using the Monte Carlo method. Toy Dataset that plays a decisive role in understanding the algorithm operation was used as such a database. The availability of the synthetic data sample makes it easy enough to evaluate whether the algorithm was trained in the necessary rule or not. It is difficult to carry out such an assessment using real data. The calculations obtained showed the ability to form competitiveness assessments using the proposed methods. The method proposed for assessing competitiveness can find application in other management tasks, for example, selecting personnel for a vacant position, choosing a company development strategy, assessing credit risk, etc. Keywords: Neural networks · Company’s competitive · Simulink process

1 Introduction The paper is aimed at the demonstration of neural networks in solving traditional management tasks. The analysis of the term “competitiveness” leads to the conclusion that there is no generally accepted definition yet. Each researcher refers to different aspects of competition and considers different interpretations of the term. This approach results in the availability of numerous definitions of the same term. Basically, competitiveness (CT) means the ability to compete and maintain market positions. When assessing the CT at the level of countries, industries, companies, products, it should be considered that countries, industries and products do not compete but depend on activities of companies that have their own economic interests. The country assessment of CT is covered by a certain point of view. The Global Competitiveness Index (GCI) is a global study and the accompanying country rating based on the economic CT. The index is calculated according to the methodology of the World Economic Forum [1]. A similar approach is based on the combination of statistical © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 72–82, 2021. https://doi.org/10.1007/978-3-030-57453-6_8

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data and results of the survey of executives of the world’s largest companies. This study has been conducted since 2004 and currently represents the most comprehensive set of CT indicators for most countries of the world. The GCI is composed of a large number of variables that detail the CT of countries of the world with different levels of economic development. The variables are combined into twelve indicators that determine the national CT, including the quality of institutions, infrastructure, macroeconomic stability, healthcare and education, efficiency of the market of goods and services, etc. The situation is different with enterprise CT. Numerous definitions and explanations of the term do not allow to clearly identify the factors with the greatest influence. For example, the CT factors monitored by the company are product quality; staff qualification; pre-sales and after-sales service, availability of service centres; company image, etc. The presence of a significant number of publications about CT does not allow to make a clear conclusion about the factors and types of CT and classification methods [2, 3].

2 Methods 2.1 Machine Learning Research work with any data implies the creation of an observation model and its subsequent application in classification, forecasting, etc. Machine learning means a class of artificial intelligence (AI) methods. Their characteristic feature is not a direct solution of the task, but training during solving. The main problem of use of ML methods includes the development of a solution based on the assessment of the assignment of the observation object to a particular class. ML methods used for data handling represent an AI subset. According to the definition given in [4]. ML is a method that forms a model based on data. Data means information, such as documents, audio, images, etc. Thus, a model is the final output of machine learning that is suitable for tasks related to intelligence, in particular, in situations where physical laws or mathematical equations make it impossible to build a model. The process of model formation based on training data is shown in Fig. 1. Training

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Fig. 1. Formation of a model based on training data.

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The vertical arrows in Fig. 1 define the learning process, and the horizontal arrows indicate the use of the model. It must be emphasized that the data for building the model and its applications are different. Machine learning teaches computers to do what is natural for a person: learn by doing. ML algorithms use computational methods to “study” information directly from data, without relying on a predetermined equation as a model. Algorithms adaptively improve their performance as the number of samples available for training increases [5]. ML applies the theory of statistics when building mathematical models since the main task is to form the data sample inference. Computer science has a dual role. First, training requires effective algorithms to solve optimization tasks, as well as to store and process a great amount of data that are usually available. Secondly, following the model study, its presentation and algorithmic solution for inference should also be effective. For certain applications, the effectiveness of the training algorithm or logical inference, i.e. its spatial and time complexity, can be as important as the forecast precision [6, 7]. The name of ML implies that the described method analyses data and finds the model by itself, not with human assistance. This process is called “learning” because it resembles learning using data for searching a model. Therefore, the data used in ML are called training data. 2.2 Neural Networks A neural network (NN) is a black box that reflects the situation with a completely unknown process, based on observations (examples). There are known inputs and outputs, but the base of examples is required for training the network [8]. Consider a network consisting of 5 input elements and 3 output elements (Fig. 2). For simplicity, only 3 input elements are shown. The output y of the first (previously, output) layer is the input to the next layer. In this way, the first output layer becomes the hidden one. The composite system is now a two-layer system, and it is described by the two matrix transformations y = Vx and o = Wy, where the weight matrices of the hidden and output layers have a dimension of (4 * 5) and (3 * 4), respectively. In general, a neural network is a machine that simulates the method of processing of a specific task by the brain [9]. The network is implemented using electronic components or simulated by the program running on the computer. Due to training and generalization capabilities, neural networks can be expressed as a mathematical representation of the human brain’s architecture. MatLab 2018b software product is used in this paper for NN design and simulation.

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2.3 Simulink Module Following the creation of the CT assessment model using neural network technology, we can transfer to a new module – Simulink. This module represents a block diagram of the environment for simulation and model-based design. It supports system-level design, simulation, automatic code generation, as well as on-going testing and verification of embedded systems. Simulink provides a graphic editor, customizable block libraries, and solvers for modelling and simulating dynamic systems. The Simulink module is integrated with MATLAB, which allows to include MATLAB algorithms into models and export simulation results to MATLAB for further analysis. The main function of Simulink is to simulate the behavior of system components over time. The simplest form of the task implies maintenance of the clock frequency, determination of the block simulation order, and distribution of output data calculated in the block diagram to the next block. In fact, Simulink is a simulation environment for dynamic systems, but it can also be used for static systems. It allows to create the type of block diagrams. The block may represent a physical device, system or function; the input/output ratio gives full characteristics of the block. An example of such blocks is a megaphone used for voice amplification. The sound at the megaphone input is amplified at the output. A megaphone is a block; input is a sound wave in its source; output is an amplified sound wave (as heard by others).

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3 Results 3.1 Neural Network We apply the neural network approach to the assessment of the enterprise CT. Classical works on competition, for example, [10], describe three types of strategies for the company’s competitive behavior in the industry: 1. Competitive differentiation strategy means the creation of a unique product in the industry. 2. Competitive cost leadership strategy or price leadership means the company’s ability to achieve the lowest cost level. 3. Competitive focusing strategy or leadership in the niche means focusing all company’s efforts on a specific narrow group of consumers. The first strategy requires unique product properties, highly qualified workforce, the ability to create high-quality product reputation, the ability to maintain the competitive advantage of the product (patents). This strategy requires large investments in the development of unique properties. The cost leadership strategy makes it necessary to unify and simplify the product to facilitate its production and increase output. It may also require high initial investments in technology and equipment for cost minimization. It implies careful monitoring of labour processes, product design and organizational structure. The third strategy is recommended for small companies. This strategy is effective in case of market saturation, presence of strong players in the segment, a high level of production cost or cost non-competitiveness compared to the industry’s leading companies. We assume the following factors affecting the enterprise CT: X1 – investments; X2 – technology; X3 – product quality; X4 – staff qualification; X5 – organizational structure; X6 – marketing; X7 – market share. According to the authors, this set of factors is sufficient for the purpose of the study because it covers the main aspects of CT and does not contradict the generally accepted trends [10]. To create a base of examples used in ML to build a model, two approaches can be used: • use of real data; • use of “toy” datasets. No real data are available for the current study yet, so let’s review the second method. In ML it is important to learn how to correctly apply toy datasets since algorithm training based on real data is difficult and may fail [11]. Toy datasets play a crucial role in understanding the algorithm operation. A simple synthetic data sample makes it easy enough to assess whether the algorithm learned the necessary rule or not. It is difficult to carry out such an assessment using real data. We use the Monte Carlo method to form a synthetic data sample. For drawing, we accept a range of 1 to 10 points for each factor, taking into account classes. For each class selected, we draw 10 factor values. As

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a result, the whole data table will consist of 30 rows and 8 columns (columns 1–7 are factor values; column 8 is a class name). The fragment of the drawing data is shown in Table 1. Table 1. Fragment of the drawing data. X1

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First 5 observations 8.15 8.82 5.55 3.64 9.82 6.82 3.79 1 7.30 7.80 6.17 4.36 8.05 3.58 3.47 1 8.79 7.72 5.16 5.39 8.42 3.63 1.89 1 9.70 8.77 6.23 6.57 7.69 5.80 2.05 1 9.65 9.56 5.05 6.76 8.49 6.48 2.40 1 Last 5 observations 2.50 5.25 8.03 3.37 2.10 9.49 2.31 3 3.95 6.77 7.31 1.97 3.16 8.13 3.99 3 2.05 6.72 7.06 1.12 3.14 9.16 1.75 3 1.25 4.23 7.13 2.16 3.93 7.81 2.04 3 1.20 4.91 7.31 1.17 3.35 9.47 1.00 3 Note. 1 – cost leadership strategy; 3 – focus strategy

The drawing data are used to form a neural network. The two-layer neural network created in the MatLab program with the selected number of neurons corresponding to the task is shown in Fig. 3.

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Fig. 3. Neural network in MatLab.

The initial dataset of 30 objects is divided into 3 parts in the proportion of 70%, 15% and 15%: • Training sample (20 objects), used to train the network; • Validation sample (5 objects), used to assess the generalization ability of the network and stop the training process if generalization is not improved;

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• Testing sample (5 objects), used for independent measurement of network characteristics during and after training. A number of training outcomes is given below. Figure 4 shows three learning curves corresponding to training, validation and testing samples.

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In Fig. 4 the vertical axis of the graph shows the cross-entropy value that assesses the network behavior based on the target and output values. Minimization of crossentropy leads to good-quality classifiers. The horizontal axis shows the number of training epochs. We see that the network generalization worsens in the 20th epoch, so the network completed training for this period of time. To determine the assignment of an enterprise-object to a specific class of the three selected ones, we save the neural network in the MatLab working space under the net1 name and then transfer to its input through the command window the object parameters, for example, for object No. 1: km1 = [7.30; 7.80; 6.17; 4.36; 8.05; 3.58; 3.47], which is known to be assigned to the first class. The model created in the form of the NN assigns the object to the same class: >> yfit = net1 (km1) yfit = 1.0000 0.0000 0.0000.

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Now let’s take a completely new object that is not known to the network trained, in particular, km2 = [1.0; 2.0; 3.0; 4.0; 5.0; 6.0; 7.0]. The result of the neural network solution is shown below: >> yfit = net1 (km2) yfit = 0.1426 0.0015 0.8558.

The network assigned this object to the third class. 3.2 Simulink Simulink processes data of three categories (Fig. 5): • Signals – inputs and outputs of blocks calculated during simulation. • States – internal values representing the block dynamics, which are calculated during simulation. • Parameters – values that affect the block behavior and defined by the user.

Constant

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Fig. 5. Block diagram of CT assessment.

The system input is any of the vectors defining the class of CT. For example, when km2 = [1.0; 2.0; 3.0; 4.0; 5.0; 6.0; 7.0] signal is transferred to the input and the system is simulated, the structure is formed at the output. Figure 6 contains the graph with three lines corresponding to three output values: 0.1426; 0.0015; 0.8558 (see the command window above). According to the graph, the largest signal corresponds to the third class.

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0.9 0.8 0.7 0.6

Pattern Recognition Neural Network 1 Pattern Recognition Neural Network 2 Pattern Recognition Neural Network 3

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In addition to generation of output signals, the Simulink module can give a detailed structure of a neural network, the composition of its blocks, the arrangement of individual elements. For example, Fig. 7 shows the components of the first layer of NN.

p{1}

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Fig. 7. Components of the first network layer.

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4 Discussion The use of machine learning methods that create a data-based model shows the possibility of obtaining quantitative results in management tasks using artificial neural networks. The tasks of assessment of enterprise competitiveness was selected as typical management problems. For the solution of this problem, neural networks were applied, and the network in the form of a two-layer perceptron was created. To train the network using the Monte Carlo method, the toy database was simulated. It is better suitable for verification of the main provisions of the theoretical study than real data. The trained neural network demonstrated the ability to classify companies with different levels of competitiveness. The task was solved up to the stage of simulation using the Simulink module included in the MatLab software product. The simulation results showed the same results that were obtained using neural networks. However, the use of the Simulink module provides wider opportunities for studying the fine and detailed structure of the network architecture.

5 Conclusion The study showed the possibility of the transfer to quantitative methods in management. The solution of management tasks using neural networks, as described in the paper, creates the prerequisites for management quantification, i.e. the transfer of management tasks to obtaining quantitative solutions. Such prospects are provided during the use of machine learning, which is a subset of artificial intelligence. The analysis conducted during the work complies with the direction of the program “Digital Economy of the Russian Federation”. Each of directions of development of the digital environment and key institutions takes into account the maintenance of existing conditions for the creation of breakthrough and promising end-to-end digital platforms and technologies. The basic end-to-end digital technologies under the Program include neural technologies and artificial intelligence, therefore, the study conducted using such technologies is a step towards a digital economy. The neural network approach makes it possible to obtain solutions in the form of assignment to a pre-determined class, i.e., the solutions are formed as a set of discrete classes. This method assumes that the developer has a database of examples for training a neural network. In this study, the toy database was used as such rules. It showed better effectiveness for verification of the main provisions compared to real data. This approach can be extended to other management tasks that require a quantitative solution, in particular, the selection of the variant of strategic development of the company, staff selection, credit risk assessment, etc.

References 1. The Global Competitiveness Report. World Economic Forum. https://www.weforum.org/rep orts/the-global-competitveness-report-2018. Accessed 21 Feb 2020 2. Zelga, K.: The importance of competition and enterprise competitiveness. World Sci. News 72, 301–306 (2017)

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3. Shpak, N., Seliuchenko, N., Kharchuk, V.: Evaluation of product competitiveness: a case study analysis. Organizacija 52(2), 107–125 (2019). https://doi.org/10.2478/orga-2019-0008 4. Kim, P.: MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence. Seoul, Soul-t’ukpyolsi (2017) 5. Ferreira, A.M., Cavalcante, C.A., Fonte, C.H.: Patterns recognition in energy management. Compr. Energy Syst. 5, 537–580 (2018). https://doi.org/10.1016/B978-0-012-809597-3.005 29-0 6. Liu, Y., Zhao, T., Ju, W.: Materials discovery and design using machine learning. J. Materiomics 3(3), 159–177 (2017). https://doi.org/10.1016/j.jmat.2017.08.002 7. Zarra, T., Galang, M., Ballesteros, F.: Environmental odour management by artificial neural network – a review. Environ. Int. 133, 105189 (2019). https://doi.org/10.1016/j.envint.2019. 105189 8. Kecman, V.: Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models. The MIT Press, Cambridge (2001) 9. Haykin, S.: Neural Networks and Learning Machines. PHI Learning, New York (2010) 10. Porter, M.: Competitive Strategy Techniques for Analyzing Industries and Competitors. Alpina Publisher, Moscow (2020). (in Russ) 11. Zadeh, R., Ramsundar, B.: TensorFlow for Deep Learning. Beijing. O’Reilly, Sebastopol (2018)

Methods of Didactic Design in E-Learning Sphere Based on Mind Maps Igor Kotciuba(B)

and Alexey Shikov(B)

Saint Petersburg National Research, University of Information Technologies, Mechanics and Optics, Kronverksky Prospect, 49, 197101 Saint Petersburg, Russia [email protected], [email protected]

Abstract. This article explains the mind maps usage according to e-didactics, solving different problems of e-didactics. Main advantages and disadvantages of mind maps according to advantages and disadvantages of computer tools of education, typical structure of the training program’s step, and also methods of construction and analysis of a mind map for didactic projection are given. The article also discusses how to control the process of learning outcomes’ writing using technologies of mind maps with evaluation of disciplines connected with associations of constructed mind map and evaluation of strength of interdisciplinary connections, how to describe the descriptions of competencies in accordance with educational standards, detail competencies and elementary learning outcomes, find different categories of competencies and evaluate their relationship. Algorithm for constructing and analyzing a mind map for the didactic design is presented. The article provides statistical data confirming the effectiveness of using the proposed method for constructing and analyzing mind maps during different stages of didactic design. Keywords: E-didactics · Mind maps · Didactic projection · Didactic design

1 Introduction Electronic training has become ingrained in the everyday learning process not only of schools but also companies involved in personnel development. The relevance of its development and implementation is determined by the fact that “almost all instructionally effective methods of training are related to the implementation of the principles of individual training, the implementation of which in mass training systems necessarily presupposes creation of computer training technologies (CTT) on the basis of different types of automated training and adaptive training systems (ATS). The utilization of CTT is becoming one of the leading indicators in the evaluation of academic teaching staff performance” [1, 2]. Unfortunately, most remote training technologies are underpinned by a trivial process of presenting educational content to students and their subsequent testing, by the results of which the decision is made whether the educational material is successfully © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 83–97, 2021. https://doi.org/10.1007/978-3-030-57453-6_9

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acquired. This kind of scheme of programmed training is the only approach pedagogy can offer today for implementation in e-training. In other words, a technological approach on which pedagogues have worked for more than 30 years turned out to be a dead end. The development of mass training technologies did not manage to solve the problem of the lack of common methodology. Pedagogical technologies (training technologies etc.) themselves cannot be referred to as technologies meeting their general scientific definition, for they have no step-by-step description, and therefore they cannot be implemented through ICT tools. The inability of modern pedagogy to present training processes in accordance with the requirements of modern information technology has engendered the e-learning (edidactics, computer learning) problem as a problem of formalizing pedagogical knowledge and its presentation in accordance with ICT requirements. It is in the aspect of developing e-learning, i.e. presentation of training procedures in a way ensuring their implementation through ICT tools that the procedures of using mind maps in the process of electronic training presented below should be considered.

2 Related Works The process of working with knowledge is greatly facilitated by the use of different visual models. Their main purpose in pedagogy is related to the efficient transfer of knowledge, including the rate of perception of the material by students and the quality of its memorization. Researches [3–5] show a positive impact on the efficiency of training in various spheres due to the use of visual models in teaching. One of the promising visual models is a mind map model offered by the psychologist T. Buzan. The mind map approach was first voiced in 1974 when the book “Use Your Head” was published, the author of “The Mind Map Book” (1995). According to modern estimates mind maps are used almost worldwide by more than 250 million people. The following main spheres of application of mind maps can be listed: – – – – – –

planning; training; presentations; brainstorming; memorizing; decision making.

In addition, the purpose of mind maps is determined as to effectively structure and process information and do reasoning using creative and intellectual potential. There are various basic areas of using mind maps, among them both a person’s private life and the educational sphere, professional life, and business. Probably the most extensive scope of application for mind maps is in education, because their use contributes to the absorption of significant amounts of information through activating radiant thinking, and also renders a considerable support to pedagogic activities, representing a tool for visualization of a student’s thoughts. According to modern researches the mind map method [6–10] enables:

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– an in-depth analysis of students’ personalities and identification of reasons for their cognitive and emotional problems; – development of corrective programs; – monitoring students’ cognitive and personal changes in the educational process; – encouragement of students’ creativity; – contribution to the formation of common cultural competences in the process of group activities of drawing up mind maps, i.e. teamwork, the ability to talk and write logically and coherently; – formation of competences related to perception of information, its processing and exchange (keeping abstracts, drawing up summaries, reporting, preparation of essays, analytical reviews with the use of content analysis, participation in substantive discussions etc.); – training process implementation within shorter periods due to accelerated perception of information; – development of all types of memory (including short-term, long-term, image, semantic memories); – enhanced control in intellectual activity. Training within shorter periods is attained with the use of the following advantages of mind maps: – visibility of training materials presented on a mind map; – structuring of and reduction in information volumes required for acquisition; – designation of interrelations between facts, ensuring a deeper understanding of the subject; – convenience of conducting and visualizing “brainstorms”. Based on this, the following classification of mind maps by their options can be offered: – in the process of training they facilitate work on drawing up summaries and abstracts, encourage acquisition of large volumes of information through activating radiant thinking, enable to spend less time in preparing for exams; – in the process of teamwork the “mind maps” manifest themselves as a convenient means of organizing brainstorms, developing plans of ongoing projects, presenting the performed work; – in the teaching process mind maps graphically represent the relationship between the studied concepts, enable students to focus their attention, visibility to be attained, the material of lectures to become considerably simpler due to a significant reduction of the physical volumes of information; – in the sphere of correctional pedagogy mind maps enable better understanding of students’ personalities, identification of the causes of their cognitive difficulties, analysis of the personality changes in students, allow students with limited abilities to render their thoughts using a special sign system and then teachers to form special programs for correction of these difficulties. The direction of knowledge control is also becoming a significant area of using mind maps. As noted in [11, 12], mind maps can be used for “active formation of in-depth

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knowledge of the subject, as well as the control of knowledge.” The paper [13] discussed below is devoted to the methods of knowledge control underlain by mind maps, and to their automated analysis in order to assess the acquisition of the learning material. Often, when considering the mind map method, a similar technique called the Shatalov system (the method of reference signal or milestones) is mentioned. The Shatalov system is based on the method of the reference signal or milestones. Presenting educational material, V.F. Shatalov would mark on the blackboard the content of a topic using key concepts joined into frames, connected by arrows, and singled out by underlining. The Shatalov “memory cards” created in this way significantly differed from a conventional abstract by systemic nature, precision, well-thought-out bonds. A special feature of this form of training also consisted in students’ studying during the class only, it was sufficient for them just to look at a “memory card”, and all the material of the class was quickly displayed in their memory. But V.F. Shatalov’s method had no clear rules for drawing up “memory cards”. Tony Buzan’s mind map method differs from V.F. Shatalov’s system in that it determined the precise rules of drawing up mind maps. The following may be referred to as the drawbacks of mind maps: – individual aspects of their perception and usage frequency by people accustomed to linear ways of information representation – poor formalization of mind maps, which makes it difficult to analyze them automatically and extract knowledge from the brainstorm or a training session conducted by means of them; – subjective nature of the designed mind maps in case they are created by a teacher, for in this case they reflect the teacher’s professional views, and any qualified teacher imparts his own position to the interpretation of the subject [11, 12]. There are basic laws for drawing up mind maps: 1. Work with an emphasis on the following: – the need to denote the central image of a mind map, the image of a problem to be solved; – frequent work with graphic images; – the use of several (three or more) colors for the central concept; – the use of volume when working with a mind map, including the use of raised characters; – resorting to synesthesia (simultaneous perception with several sense organs); – work with varied thicknesses of links, sizes of characters, scale of images; – balanced positioning of concepts on a mind map; – balanced distances between mind map concepts of different levels. 2. The use of associations: – an option to apply arrows as links between the concepts of a mind map; – the active use of the color palette;

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– an option to resort to information encoding. 3. The requirements to transparency in the formulation of thoughts – – – – – – – – –

the principle of using only one word at a certain line; work with block letters; positioning important concepts over certain lines; rough correspondence of the length of the line and the length of a certain key concept; interconnection of links and joining them with the central concept of a mind map; displaying connections of a higher order in the form of bold and smooth lines; using separate lines to highlight blocks of crucial information; aiming at the utmost clarity of any applied images; aiming at the horizontal arrangement of characters and the list to draw up a mind map.

4. Building a personal style when drawing up a mind map. On the basis of the laws for drawing up mind maps the following structural features can be highlighted: – the central image represents the problem to be solved; – associations arising during the consideration of the problem to be solved are designated in the form of images of a higher level; – several associations of the second level can be connected with each of the major associations; – a hierarchy of thoughts must be observed; – the numerical sequence of their presentation can be used. Jointly with mind maps additional visual models can be used as well as conceptual maps that are graph structures indicating the types of links between concepts. Currently, research is being conducted in the use of mind maps in other fields as solving other problems allows their potential to be revealed as well as in e-learning process [13–16]. For example, the research [13] suggests a method of automated analysis of students’ mind maps used for the assessment of the learning material acquisition. Particular attention in the paper is given to the method of drawing up a student’s mind map aimed at identifying the correct understanding of bonds between the studied objects, which could then be interpreted in tests, as well as in the development of automated analysis methods of mind maps relying on the instruments of graph theory and the methods of syntactic analysis. The paper [15] is devoted to the discussion of mind maps in a problem of long-term monitoring of the content acquisition process by students. It is noted that mind maps can find their application within the framework of the training strategy, “I know - I want to know – I’ve learnt”, “Before and After”. A pedagogue can analyze the students’ mind maps, both manually and in automatically, at different stages of the given training strategy, including analyzing new emerging association concepts

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of the mind map and emerging/varying links between them in the long run. This kind of approach facilitates the process of individual and teamwork with a mind map, enables the teacher to compare mind maps of students with his own mind map, and to monitor changes in mind maps before, during and after the studying of a discipline. This method which includes incorporating constant visualization of the knowledge acquisition process in a discipline will significantly contribute to a prompter transition from one training step to the other.

3 Materials and Methods Computer training aids (CTA) widely used in modern education have in comparison with a teacher as training control subjects both advantages and disadvantages. The comparison of them is displayed in the following table (Table 1). Table 1. CTA advantages and disadvantages of possible mind map. CTA pluses and minuses of and possible mind map CTA’ advantages/options of mind maps

- Individualization of training in large groups; - Automation of information processing at high rate and with minimum mistakes; - Broad options for visualization of objects under study; - Independent student’s work with the object being studied due to the timely recording of the results of student’s interaction with the object of study; - An option to promptly obtain and analyze information on the directions and results of a student’s activity to evaluate the quality of performed operations - An option to construct individual, subjective mental models; - An option to automate work with a mind map [13]; - A high potential of visual tools for representing knowledge in construction of a mind map (the “use colors” principle); - An option to control training based on timely inspection of a mind map by the teacher [14]; - An option of mind maps’ analysis in order to control knowledge

CTA’ disadvantages/options of mind maps

- A limited option to analyze students’ answers (only using syntactic analysis); - A limited option to register and control students’ activity-related, personality characteristics of students - The availability of students’ answers syntactic analysis (for example, by analyzing a student’s association concepts by a pre-determined association database discussed in [13]); - An option to control and analyze such characteristics when working with a mind map as the amount of time spent on the job completion, the quantity of utilized colors and the diversity of link layers that allow the personality and activity characteristics of a student to be assessed

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Now let us consider the options of mind maps as a means of solving teacher’s problems as a training control subject (see Table 2). Table 2. Disadvantages of a teacher as a subject of learning process control and opportunities of mind maps. Disadvantages of a teacher as a subject of learning process control and opportunities of mind maps Disadvantages of a teacher

Opportunities of mind maps

- Limited opportunities in small study group in most educational institutions; - low information processing speed; - Relatively low opportunities for visual representation of knowledge about objects studied

- Expanding opportunities for learning process individualization; - higher information processing speed due to the element of automated analysis; - high audiovisual potential

The analysis conducted above allows to make a conclusion that a mind map may be considered a computer training technology and can as well solve problems of a teacher as a subject of learning process control. Some specific teacher-student interaction is also characteristic for so-called “programmed learning”. Such a program (or scenario) is based on a “learning step”, a typical structure which includes the following four frames: 1. 2. 3. 4.

Information Exercise Examination Control (a rule for transition to the next step).

First three frames of such a program are offered to a student, while the last one is necessary in order to choose the next learning step. Teacher’s participation in this case is necessary for evaluation of students’ progress and their psychological status. A teacher sometimes also may take part in building transitions from one learning step to another. As it was claimed earlier, mind maps can be used both for presenting new information and controlling knowledge acquisition. Now let’s consider their use within four frames of a teaching program (see Table 3). Thus, mind maps usage may increase the efficiency of teacher-student interaction within all the frames of a teaching program. Computer training technologies (CTT) are defined as a final result of interaction between pedagogy and informatics during the e-learning process design, in which both separate functions of learning process control and corresponding procedures are represented as software products and realized by computer hardware and software [1, 2]. The term “information training technology” (ITT) is also used in this situation. ITT is defined as a certain way of organizing a learning process based on using computers and

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other information resources. These two terms are connected but still somewhat different. Information training technologies have to include computer training technologies, which becomes an important prerequisite of a contemporary learning process. Table 3. Mind mapping opportunities according to the frames of a teaching program. Mind mapping opportunities according to the frames of a teaching program Frame

Opportunities of mind maps

Information

Visual representation of information in a tree form with different colors reduces the time used for acquisition of education material (mind map as reference abstract)

Exercise

Drawing mind maps allows a student to build and/or specify links and relations between objects studied on a previous step

Examination

A mind map created by a student can be analyzed manually or automatically in order to control the correctness of understanding of relations between studied objects both immediately and in a long term [13, 14]

Control

Mind maps allow decision-making support for a teacher in transition from one learning step to another, as in [13]

Information training technologies mean achieving specific goals of training and active engagement of students in the development of educational content. They also promote creativity in mastering a profession. As it was noted earlier, among the main application areas of mind maps there are both planning and creative thinking. Therefore, they can be successfully applied for ITT design. Since the development of radiant thinking and creativity stems from the goals and visual tools of drawing up mind maps, we will not dwell in this area of using mind maps for ITT design. Instead, we will concentrate on the opportunities of mind maps in planning educational activities. Different modern researches are acquainted with problems of didactic design [17– 19]. Russia’s accession to the Bologna Process has resulted in significant changes in the education and has made numerous researchers focus on competence approach. It is advisable first to allocate competence standard components with minimal levels of their formation results, and later determine the components of the competence standard in the form of disciplines (modules) on the basis of the principle of interdisciplinarity. Didactic design is also connected with the principle of decomposition at the design stage of an educational project [20], which is the process of separating the overall objective of the educational program into separate sub-tasks. It should be mentioned that subject specific competences are structural while narrowsubject ones are interdisciplinary. This specificity leads to the relevance of systematizing

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the process of formation and monitoring of certain categories of competencies that have to be formed based on a list of interrelated disciplines. This, in turn, requires analyzing the formation of competencies through the prism of the disciplines within which they are formed, which once again shows the special role of interdisciplinary connections [21]. Also, the rules of learning outcomes’ writing have to be integrated [13]. Thus, a conclusion can be made that an important role in both curriculum design and in monitoring the basic competencies formation is taken by consideration the goals of studying the academic disciplines and fixation of interdisciplinary connections. The procedure of decomposition is an important aspect of this consideration. In [13] a detailed algorithm of ITT design is presented. The core of this algorithm is determined by setting and further implementing the didactic task in the learning process. Let us consider the individual steps of the algorithm: – The learning objective formulation of a given academic discipline; – Selection and structuring of learning content in accordance with a specific objective; – Building the structure of a syllabus. As it was described above, the algorithm for constructing a mind map begins with the definition of its central image which represents the problem to be addressed. Further, concepts or associations of the first level are generated and represented in connection with the central image. Each of the first level associations can also be specified by the concepts of lower levels. The algorithm of building and analyzing a mind map for didactic design includes the following steps: 1. identification of the central image which represents didactic problem in the educational process; 2. determination of the associations of the first level which are the objectives of the studying for certain academic disciplines; 3. further specification of objectives of academic disciplines; the contents of each discipline should be also included; 4. determination of interdisciplinary connections; 5. visualization of the built mind map; 6. evaluation of strength of interdisciplinary connections. Especial attention should be given to steps №№ 4, 5, 6 of this algorithm. Articles [15, 22] examine the problem of using mind maps in generating interdisciplinary connections. The main attention in this article is paid to the relevance of the development of software that would enable a learner to associate concepts from different mind maps, according to the principle “from the specific to the general”, which, in turn, allows to interconnect multiple mind maps through these concepts. The paper identifies the main challenges of development of “composite” mind maps: – difficulties of visualizing a set of associations, connecting several mind maps; – difficulties of visualizing the connections linking associations of various levels with several mind maps.

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There are some existing software solutions that allow to solve these issues, for instance, by means of tabs; but [15] also suggests some new functions: – mapping relationships with lines of varying thickness (including the possibility to change the thickness of connection built earlier) and type (dashed, double, and so on); – using hyperlinks between associations; – combining associations between multiple maps in the form of hyperedges; – automatic changing lines to hyperlinks if associations are far from each other; – hiding and disclosing concepts of different branches of a mind map on any given association level (possibility to collapse entire levels of association); – automatic display of terms recurring within one mind map or a set of mind maps. All of the considered functionality increases the effectiveness of the mind map visualization for the didactic design as it reflects the specific subject area. Specifically, a “composite” mind map appears which, among other things, displays interdisciplinary connections. Along with the construction of the mind map for didactic design it is crucial to conduct its analysis in order to support expert’s decision-making. Especially, the following functionality should be provided: - Automated assessment of interdisciplinary connections strength. It can be provided in the form of a report in which the most related mind maps of disciplines are designated. The strength of the connection is defined by the number of connecting associations. This mind mapping-based approach can also support the work of an expert on the formation of a list of interdisciplinary teaching and cognitive tasks or competence-oriented tasks. The competence approach leads to expansion of the relevance of the interdisciplinary connections principle. It means that it is necessary to purposefully strengthen connections between certain disciplines that were earlier “farther” from each other by building new interdisciplinary connections. Visual representation of academic disciplines’ content in the format of the mind maps and automated assessment of interdisciplinary relations strength would greatly facilitate this process and form the following recommendations to an expert working with such models: – in case of a small number of associations or their absence it is necessary to continue the work on the connection and specification of the corresponding maps, if it is essential to fix or enhance interdisciplinary communication; – in case of a large number of associations it is necessary to consider combining corresponding concepts into a single training unit or combining the relevant “branches” of these maps into one for easier visualization. In addition, during the didactic designing process an expert may face the problem of fixing the new interdisciplinary connections, that are “distant” from each other. Some of the concepts of the “composite” mind map may become linked to each other through various chains of other associations. To find the length of the shortest connection between two remote associations (which is the shortest semantic relationship between two learning objects among those pointed out by an expert) we offer to perform the following steps:

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– represent a “composite” mind map as a directed graph. According to the laws of mind map building associations diverge from the central image and from the images of a higher level, therefore in the simplest case the mind map will be an oriented tree, or an acyclic graph; – perform the analysis of a “composite” mind map using a breadth-first search algorithm. This algorithm, which is one of the basic graph searching algorithms, allows to determine the shortest path length in an unweighted graph. This is the way in which there is the smallest number of edges, which is adequate for a “composite” mind map, which is a directed unweighted graph.

4 Results The empirical study was connected with such several steps as: 1. Constructing a mind map according to the rules of learning outcomes’ writing to describe all the competences of educational standard. 2. Evaluation of disciplines connected with associations of constructed mind map. 3. Evaluation of interrelated disciplines. 4. Evaluation of strength of interdisciplinary connections. 5. Algorithm for constructing and analyzing a mind map for the didactic design is presented below using activity diagram (Fig. 2). The version of a mind map describing learning outcomes and their interconnection is shown in Fig. 1.

Fig. 1. Mind Map of interconnected learning outcomes.

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Fig. 2. Algorithm for constructing and analysis of a mind map for the didactic design.

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Fig. 3. Mind Map in a tool of visual representing of a “composite” mind map.

The version of a “composite” mind map with automatic changing lines to hyperlinks if associations are far from each other in different subjects is given in Fig. 3. The empirical study’s results and evaluation of time spending on different stages of didactic design are given in Fig. 4.

Fig. 4. Experience.

5 Conclusions An option of using mind maps for didactic design of computer training technologies is considered. The proposed methods allow to realize the main advantages of mind maps for supporting e-didactics. Mind mapping significantly reduces the time spent on

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didactic design due to the powerful potential of visualization, as well as the proposed methods for determining the interdisciplinary connections and their strength. The proposed recommendations will support the formation of a list of interdisciplinary teaching and cognitive tasks or competence-oriented tasks. These methods can be widely used for e-learning at all levels of the educational process.

References 1. González-García, N., Sánchez-García, A.B., Nieto-Librero, A.B., Galindo-Villardón, M.P.: Attitude and learning approaches in the study of general didactics a multivariate analysis. Revista de Psicodidáctica 24(2), 154–162 (2019). https://doi.org/10.1016/j.psicoe.2019. 03.001 2. Selzer, M.N., Gazcon, N.F., Larrea, M.L.: Effects of virtual presence and learning outcome using low-end virtual reality systems. J. Displays 59, 9–15 (2019). https://doi.org/10.1016/j. displa.2019.04.002 3. Aykas, V.: An application regarding the availability of mind maps in visual art education based on active learning method. Procedia Soc. Behav. Sci. 174, 1859–1866 (2015). https:// doi.org/10.1016/j.sbspro.2015.01.848 4. Wu, T.-T., Chien, A.-C.: Combining e-books with mind mapping in a reciprocal teaching strategy for a classical Chinese course. J. Comput. Educ. 116, 64–80 (2018). https://doi.org/ 10.1016/j.compedu.2017.08.012 5. Bystrova, T., Larionova, V.: Use of virtual mind mapping to effectively organise the project activities of students at the university. Procedia-Soc. Behav. Sci. 214, 465–472 (2015). https:// doi.org/10.1016/j.sbspro.2015.11.724 6. Buzan, T.: Brain map of words to help us read minds. J. NewScientist 230, 15 (2016). https:// doi.org/10.1016/s0262-4079(16)30798-9 7. Buran, A., Filyukov, A.: Mind mapping technique in language learning. Procedia-Soc. Behav. Sci. 206, 215–218 (2015). https://doi.org/10.1016/j.sbspro.2015.10.010 8. Rosciano, A.: The effectiveness of mind mapping as an active learning strategy among associate degree nursing students. J. Teach. Learn. Nurs. 10, 93–99 (2015). https://doi.org/10. 1016/j.teln.2015.01.003 9. Simonova, I.: Concept of e-learning reflected in mind maps of university students. ProcediaSoc. Behav. Sci. 116, 1394–1399 (2014). https://doi.org/10.1016/j.sbspro.2014.01.404 10. Noonan, M.: Mind maps: enhancing midwifery education. J. Nurse Educ. Today 33, 847–852 (2013). https://doi.org/10.1016/j.nedt.2012.02.003 11. Wette, R.: Using mind maps to reveal and develop genre knowledge in a graduate writing course. J. Second Lang. Writ. 38, 58–71 (2017). https://doi.org/10.1016/j.jslw.2017.09.005 12. Fu, Q.-K., Lin, C.-J., Hwang, G.-J., Zhang, L.: Impacts of a mind mapping-based contextual gaming approach on EFL students’ writing performance, learning perceptions and generative uses in an English course. J. Comput. Educ. 137, 59–77 (2019) 13. Kotciuba, I.Yu., Shikov, A.N.: Automatic analysis of the mind maps of the pupils applied to the assessment of assimilation of a training material. J. Pedagogical Inf. 3, 25–31 (2014) 14. Yeong, F.M.: Incorporating mind-maps in cell biology lectures – a reflection on the advantages and potential drawback. Procedia-Soc. Behav. Sci. 103, 485–491 (2013). https://doi.org/10. 1016/j.sbspro.2013.10.364 15. Kaysarova, D.V., Kotciuba, I.Yu.: Using mind maps to form interdisciplinary connections. J. Distance Virtual Learn. 11, 117–122 (2014) 16. Simonova, I.: E-learning in mind maps of czech and kazakhstan university students. ProcediaSoc. Behav. Sci. 171, 1229–1234 (2015). https://doi.org/10.1016/j.sbspro.2015.01.236

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Internal Control of Efficiency of Use of Budgetary Funds Alsou Zakirova1(B) , Guzaliya Klychova1 , Regina Nurieva1 , Almaz Nigmetzyanov2 , Evgenia Zaugarova3 , and Ullah Raheem1 1 Kazan State Agrarian University, Karl Marx, 65, 420015 Kazan, Russia

[email protected] 2 Kazan branch of the Russian State University of Justice,

2nd Azinskaya street, 7A, 420088 Kazan, Russia 3 Saint-Petersburg State Economic University, Sadovaya, 21, 191023 St. Petersburg, Russia

Abstract. One of the main directions of increasing the efficiency of the agroindustrial complex is the organization of a rational state policy on management, control and support of this industry. The issues related to the organization of state support are the main in solving the problems of increasing the efficiency of agricultural production and increasing the competitiveness of domestic products. Absence of scientifically grounded recommendations on the organization of the account and control of the state subsidies has caused necessity of development of algorithm of the internal control of budgetary funds. The aim of the article is justification of theoretical provisions and development of practical recommendations aimed at development of internal control of targeted use of budgetary funds in organizations. The objectives of the research: to determine the main directions of financing of organizations; to model the structure and determine methodological and analytical procedures of internal control of budgetary funds to ensure their targeted and effective use in organizations. In the article, such methods as analysis of scientific and theoretical sources, system approach, method of comparative analysis, generalization were used. The results presented in the article allow providing the necessary control and analytical information to the system of efficiency management of state subsidies use; revealing in due time the facts of non-target and ineffective use of budgetary funds in organizations. Keywords: Internal control · Budget funds · State aid · Subsidies · External control · Efficiency · Control environment · Control procedures

1 Introduction Agriculture is a strategically important sector for any country, the development of which depends heavily on the specifics of its sectoral characteristics. These features are the main factors that make agriculture very different from other sectors of the economy. Despite strong dependence on natural and climatic conditions, geographical location of farms, seasonality of the main production cycle and involvement of biological assets in © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 98–123, 2021. https://doi.org/10.1007/978-3-030-57453-6_10

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it, as well as other sectoral features, agriculture should provide sufficient food security in the country and serve as a source of growth of the main domestic gross output [1, 2]. In addition, agriculture provides many other sectors of the country with means of production and raw materials, while being their main consumer. Taking into account the multifunctionality and importance of the agricultural sector, we can say that it is intended to solve not only economic issues, but also social problems of the country [3]. International practice shows that in many countries with developed agro-industrial complex there is an effective system of state regulation of the industry by providing state support and subsidizing the costs of production [4–6]. The main essence of such measures is that the system of subsidizing is able to create advantages of some economic entities over others by increasing competitiveness and increasing production volumes due to the effective use of budget funds, as well as motivate agricultural organizations to perform such actions, which they would not do without assistance [7–10]. Nowadays, for domestic agricultural organizations receiving budget funds is one of the main opportunities that can stabilize their activity, improve financial and economic condition [11, 12]. We consider that subsidizing of agricultural organizations is the main component of the strategy of development of social and economic condition of each region and country as a whole. We believe that the main task of the government in providing state support is to ensure stability in the industry and promote domestic products to a competitive level. In the modern economy the implemented priority programs on development of agriculture of Russia contain the idea of priority directions of investment of branches of agrarian sector using the mechanism of subsidizing and granting other forms of the state aid. The state regulation of agriculture should be carried out through the regulation of investment activity of this branch, because investment is the only solution to the problems of the branch by expanding its production potential and introduction of scientific and technical process in the activity [13, 14]. State regulation of investment activity in agriculture should be reduced to determining the optimal boundary of interference in the mechanisms of economic relations between market participants, redistribution of functions between centralized budgets and other investors, a stable increase in capital and resource allocation and the choice of levers to regulate investment processes (Fig. 1). The state can influence the activity of agrarian enterprises in two ways: by adopting laws and implementing agricultural development programs, i.e. by administrative method, and by providing money and other means, i.e. economic method. Let us consider these methods in more detail (Fig. 2). Administrative methods of impact include: implementation of control actions over observance of legislation by agricultural producers in organization of production cycles, sale of products, control over rational use of land and other natural resources, over observance of state standards for product quality, etc. Financial methods include: 1. Budgetary resources (government subsidies, grants, subventions). These funds can be provided for one head of livestock or a unit of land area if they compensate current costs of agricultural production, or in the form of direct government investment if

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Pursuing flexible tax, credit and depreciation policies

Expanding leasing opportunities

Ensuring science-based pricing

Targeted public funding for innovative projects

Stimulation of entrepreneurial activity and provision of benefits to investors Prioritizing investment and capital investment

Fig. 1. Mechanism of state impact on the activities of agricultural organizations.

Methods of government impact on agriculture

Administrative

Financial

Economic

Credits

Price Taxes

Customs

Fig. 2. Methods of state impact on agriculture.

they are of investment nature. In some cases the state provides funds to cover the costs of using the means of production in order to maintain a certain level of income of the organization [15–17]. 2. Insurance. This method consists in compensation of a part of expenses for insurance premiums payment [18, 19]. 3. Debt restructuring, i.e. ensuring conditions allowing the enterprise to repay the public debt, if any. Usually such debts are connected with the debt on payment of taxes to the budget or with payments to state non-budgetary funds [20, 21]. Credit methods of influence include payments, compensations and contributions to the share capital of commercial banks, in which the organization’s credits were granted [22]. The state has the right to provide preferential crediting or compensation for reimbursement of part of interest on credits. The price method consists in setting certain prices for certain types of products to exclude the monopoly and maintain the income of agricultural enterprises.

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In addition to price regulation to stimulate the development of agrarian enterprises, it is also possible to propose a more effective system of state subsidy of production costs. Insufficient financial support from the state reduces the ability of domestic enterprises to compete independently with foreign organizations. The reason for this is the fact that foreign agricultural organizations regularly receive subsidies for reimbursement of production costs, which allows to speak about the application of protectionism policy in these countries in relation to national agriculture [23–25]. Finally, the customs method, which consists in the establishment of customs duties on imported and exported agricultural products by the state. The development of preferential crediting in agriculture is another perspective direction of state regulation of agrarian enterprises. The development of this direction allows many domestic organizations to attract new borrowed funds to expand production. We believe that it is necessary to pay great attention to the creation of the system of state agricultural bank and cooperative credit organizations, as well as to constantly encourage the participation of commercial banks in lending to agricultural enterprises, through the provision of state guarantees for loan repayment.

2 Materials and Methods The main direction of financing of agricultural organizations of the Republic of Tatarstan are: support of development of elite seed production, financing of a part of expenses of agricultural commodity producers on payment of insurance premium accrued under the contract of agricultural insurance in the field of plant growing and animal breeding; cofinancing of expenditure obligations of subjects of the Russian Federation on rendering of untied support to agricultural commodity producers in the field of plant growing; support of pedigree farming; support of pedigree farming in the field of plant growing. Let us consider a more detailed analysis of the volumes of financing by each direction, which developed in 2017–2019 in the Republic of Tatarstan, in Table 1. Table 1. Main directions of financing agriculture in the Republic of Tatarstan from the federal and regional budgets in 2017–2019, thousand rubles. Types of government aid

2017

2018

2019

1. Subsidies to compensate for part of the cost of purchasing elite seeds

81390.50

119918

198601.80

2. Grants to cover part of the cost of laying and maintaining perennial fruit and berry plantations

11559.50

35626.30

72575.30

3. Subsidies for risk management in crop production sub-sectors

52149.30

42625.20

229033.7

4. Subsidies for soil fertility improvement and involvement of unused lands of agricultural lands in agricultural turnover

8123968.4

3431470.3

4838158.8

(continued)

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Types of government aid

2017

2018

2019

5. Subsidies for part of flax production costs

7000.00

–

–

6. Grants to help achieve the targets of regional agricultural development programmes

–

1733948.50 –

7. Subsidies to increase the productivity of dairy cattle

612419.00

2345280.30 1235084.00

8. Contribution to the authorized capital of Joint – Stock Company “Head Breeding Enterprise “Elita” for the purpose of acquisition of analytical system for estimation of raw milk quality

26000.00

–

9. Grants to support livestock breeding

681821.00

612661.80

10. Subsidies for reimbursement of part of 8785.10 agricultural producers’ expenses for payment of insurance premiums under agricultural insurance contracts in the field of animal husbandry

521638.5

14681.80

14759.20

11. Veterinary and sanitary improvement activities

163700.00

272562.40

158700.00

12. Subsidies to compensate for part of the cost of raising the brood stock of sheep and goats

1700.00

2586.20

3000.00

13. Animal husbandry support subsidy

32829.00

107900.00

228601.60

71245.6

72867.7

14. Grants for prevention of animal diseases and protection of the population from diseases common to humans and animals 15. Grants to support farmers’ farms

582885.5

636727.30

966054,9

16. Grants to support agricultural consumer cooperatives

150000.00

430513.6

536189.6

17. Support for citizens holding personal subsidiary farms

474666

451098.5

495007.1

18. Renovation of agricultural machinery park

3115365.10 1285276.80 1880056.20

19. Means aimed at development of land reclamation 400228,6 for agricultural purposes

729722.8

538841.3

20. Funds aimed at developing social and engineering infrastructure

1350635.20 631404.70

494662.00

Total government support

15690919.7 13053409.3 12574855

* The table is based on the data of consolidated annual reports of agricultural organizations of the Ministry of Agriculture and Food of the Republic of Tatarstan.

As can be seen from Table 1, government support for the main sectors of agricultural production has increased from 2017 to 2019. Thus, subsidies for reimbursement of part of the cost of purchasing elite seeds increased by 6.3 times, subsidies for raising the productivity of dairy cattle increased by 2 times. At the same time, funds allocated for the development of social and engineering infrastructure decreased 2.7 times.

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The key problem of the state policy aimed at stabilizing the agrarian sector and raising domestic agricultural products to a competitive level remains the improvement of the mechanism for the provision and use of budgetary funds. Efficient and well-constructed mechanism of subsidizing can significantly affect the increase of food security of the country. In this regard, it is important to achieve such a course of action that every ruble invested by the state in agricultural production will contribute to the increase in profits. Efficiency of state investments in the development of agricultural organizations, carried out in the form of subsidizing production costs, requires constant monitoring and analysis of technological processes related to the receipt and use of budgetary funds, control of their targeted use and compliance with the established procedure of accounting and disclosure of information on state subsidies in reporting to the legislation requirements [26, 27]. Organization of the internal control system in agricultural organizations is a rather complicated process, combining several consecutive stages (Fig. 3). Critical analysis and comparison of the objectives of the organization's functioning, defined for the previous business conditions, the previously established strategy, tactics and capabilities Elaboration and documentation of a development concept of the organization corresponding to the modern conditions, approval of activities contributing to the effective implementation of this concept. Performance analysis and improvement of the functioning management structure Development of standard control procedures to assess the rationality of performed business operations, development of measures contributing to the efficient and economical use of the organization's resources Organization of the internal control service and identification of ways for its continuous improvement in an environment of continuous development of the organization and changing external environment Forecast assessment of the effectiveness of the internal control system

Fig. 3. Consistent stages of the internal control system in agricultural organizations.

The internal control system of an agricultural organization combines control and management functions, the implementation of which is aimed at increasing the efficiency of operational and financial activities and improving the performance of agricultural industries [28, 29]. With regard to budgetary funds, internal control can be interpreted as a system of management control exercised by a specially organized independent service subordinated to the top management or owners of agricultural organizations in order to assess the targeted use of budgetary funds [30, 31]. The main task of such service is the implementation of internal audit procedures for the formation of management reporting on

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Internal budgetary control system

the movement of budgetary funds in order to assess their effectiveness and intended use [32–34]. The peculiarity of the organization of the internal control system of operations related to receipt and use of budgetary funds is the composition and content of the procedures applied and the sequence of their application aimed at assessing the targeted use of government subsidies. In the course of the research the main functional directions of the internal control system of the targeted use of budgetary funds in agricultural organizations are grounded (Fig. 4).

Ensuring the effective functioning of the organization as a whole, individual industries and structural subdivisions through the rational and economical use of budgetary funds Ensuring rational and targeted use of budgetary funds received Maintenance of property and resources acquired from budgetary resources Compliance with laws and regulations governing the receipt, use and recognition of budgetary resources Ensuring that the organization has an effective budget accounting system adapted to international financial reporting standards

Fig. 4. Main directions of internal control system for targeted use of budgetary funds.

The main tasks of control over the targeted use of budgetary resources should include: 1. verification of correctness and timeliness of execution of documents on acceptance and use of budget funds; 2. control over settlements with suppliers and contractors, debts to which are planned to be paid from the budget funds in accordance with the concluded contracts; 3. control over compliance with the terms and conditions of subsidizing; 4. control over the targeted use of allocated funds, assessment of purposefulness and reasonableness of the expenses made; 5. control over the correctness and reasonableness of allocation of budgetary funds to income and to capital; 6. verification of correctness of registration of facts of economic life in accounting accounts related to receipt and use of budget funds.

3 Results In the paper the model of internal control with the use of classical approaches and foreign experience of formation of internal control systems is developed, in which elements of internal control of target use of budgetary funds are allocated (Fig. 5).

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International Standards on Auditing

Intra-company standards and internally established procedures for the organization of internal control

Compliance with legal requirements Achievement of objectives and original purpose Verification of the reliability and authenticity of internal and external documents and reports Risk management to minimize or eliminate risks

Control procedures

legislative regulation

Internal control system of the organization

Monitoring

Subsystem structure

Subsystem of internal control over the targeted use of budget funds and internal management reporting on their use Information support for control procedures consisting in the selection and processing of information required for management reporting on the budgetary situation An organizational environment whose essence is the selection of qualified staff and the establishment of a well-functioning internal control service that aims to assess the reliability of budget data Subsystem objects: operations connected with reception and use of budgetary funds; procedures of recognition of budgetary funds in accounting; operations on disclosing the information on state grants in the reporting of the organization, etc.

Fig. 5. Internal control model of targeted use of budgetary funds.

The internal control system consists of five elements (Fig. 6). An element of the internal control system “Control environment”. In the practical activity of the internal control service of any commercial organization the most laborintensive work when assessing the internal control system is the assessment of the control environment. This is due to the fact that the control environment is closely connected with the analysis of the management system, in particular, the structure of management at all levels, the distribution of rights, duties and responsibilities, the procedure for justifying and making managerial decisions, the structure of document circulation and the norms of registration of the main planning, reporting and financial documents. The control environment unites the position, awareness and actions of representatives of the management structure with regard to the internal control system of the audited entity, as well as understanding of the significance and importance of such system within the organization. The elements of the control environment which are aimed

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Control environment Risk assessment process

Control procedures Internal Control System Monitoring of controls

Information System

Fig. 6. Elements of the internal control system.

at maintaining discipline and order are the basis for creating an effective internal control system. We believe that in organizing the internal control of the targeted use of budgetary funds the reliability of the following elements should be considered when assessing the control environment: 1. if the conditions for the provision of these funds are met, the level of complexity of issues raised and discussed with the management of the organization, related to the effective use of budgetary funds, etc.; 2. management’s approach to identifying risks of inefficient or improper use of budget funds; risks associated with failure to meet the conditions for granting budget funds and risks of incorrect and biased assessment and recording of these funds in the accounts of accounting, as well as management of these risks, their minimization or prevention; management’s position and actions with regard to disclosure of information on state subsidies in the accounting (financial) statements; 3. organizational structure in relation to budgetary funds, i.e. the system under which the organization’s activities are planned, implemented, monitored and monitored in order to achieve the integrity and other ethical values of the organization and to maintain them in the performance of operations associated with the expenditure of budgetary funds, as well as the use of current and non-current assets acquired from these amounts; 4. the opinion of management and employees on the level of professional knowledge required to perform operations related to their receipt and use, and recognition in accounting and reporting; 5. participation of owner’s representatives at performance of relevant operations with state subsidies. Here, it is possible to consider such qualities of owners as experience in substantiation of necessity of budget funds to this organization, high professional qualities and competence of goals in relation to means of state aid;

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6. distribution of responsibility and authority in the course of operations on receipt, use and recognition of budgetary funds in the accounting, selection of specialists with appropriate qualification and experience in this field; 7. Human resources policies and practices related to the recruitment of new recruits; training, education, advice to staff members to upgrade their skills and abilities for operations related to the receipt and use of government grants. “Control procedures” element of the internal control system. The methods and rules that complement the control environment as well as the accounting system include control procedures developed by the management structure of the organization for the achievement of certain objectives. The following groups of control procedures can be distinguished by their economic focus: 1. control procedures and methods aimed at checking the efficiency of economic activities, efficiency of transactions and projects, achievement of initially set economic, financial and operational indicators; 2. control procedures and methods aimed at verification of reliability and accuracy of accounting (financial) reporting and objectivity of accounting. Internal control can be carried out through the following procedures: 1. documentation of the verification procedures; 2. confirmation of conformity of the data contained in various documents with their actual existence; 3. authorization of transactions and projects; 4. delineation of powers and responsibilities; 5. procedures related to verification of actual presence of property and their compliance with the data contained in the documents of the organization, inventory; 6. verification of access restrictions for unauthorized persons and physical safety of property; 7. oversight to ensure a comprehensive assessment; 8. procedures related to the computer processing of data as well as information systems; 9. control over compliance with subsidy terms. To control compliance with the subsidy terms, we suggest using the expert opinion of the Internal Control Department (Table 2).

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Table 2. Expert opinion of the internal control department on compliance with subsidy terms (proposed form). Expert opinion of the internal control department on compliance with subsidy conditions Shakhtar LLC, Atni District, Republic Tatarstan

Date of compilation 14.09.2019

Name of the sub-program under which the state subsidy was allocated: «Development of crop production sub-industry, processing and sale of crop production» Classification group of budget funds: monetary form, operational government subsidies Direction of the state subsidy: subsidy from the budget of the Republic of Tataristan for reimbursement of expenses on purchased original and elite seeds The name of the crop: spring wheat, the variety “Bezenchukskaya 380” elite Quantity: 3 tons; Actual costs of seed acquisition: 31 thousand rubles Amount of financing: 31 thousand rubles Terms and conditions of the state subsidy: 1. Confidence that Shakhtar LLC of the Atninsky District of the Republic of Tatarstan will produce spring wheat for at least five years after the end of the reporting year in which the subsidy was received 2. Lack in the respect of LLC Shakhtar, Atninsky district of the Republic of Tatarstan, the fact of liquidation or bankruptcy 3. Providing the forecast estimate of production efficiency and calculation of winter wheat reserves for the coming 3 reporting years 4. Submission of all supporting documents confirming the existence of expenses related to the acquisition of seeds Grounds for the emergence of confidence (uncertainty) in meeting the conditions of the subsidy: 1. Under condition 1: report and memo of deputy directors for financial and operational department 2. On condition 2: balance sheet and report on financial results of the organization of annual and quarterly accounting reports of the current year 3. Condition 3: a business plan for the requested period 4. According to condition 4: estimates, invoices Commission’s conclusion: on the basis of the examined documents there is a reasonable assurance that the organization will meet all conditions related to the provision of state subsidy and it will be received

The signatures: Chairman of the Commission_______ Commission members____________ Chief ExecutiveOfficer____________

An element of the internal control system “Risk Assessment Process”. The most responsible stage of the internal control system is the implementation of procedures for assessing risks of a business entity. At this stage it is necessary to identify risks; assess them in order to determine the probability of occurrence of any negative impact on the operational or financial activity and significant misstatement of the financial statements of the organization; develop measures or control procedures aimed at their elimination or minimization. Consider the main types of risks (Table 3).

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Table 3. Major risks in the internal control system. Risks of a business entity

Risks of an internal control officer

Immediate risk

Control risk

Business continuity risk

Non-detection risk

Risk of independence

Risk of sampling error

May arise due to industry specifics, environmental conditions and other specific business conditions that cannot be inspected and justified by internal controls

Concludes the risk that the control procedures used will not confirm or identify significant risks or errors

Risks related to the fact that a business entity will cease its financial and economic activity within the next 12 months after the reporting year

Due to the fact that the control procedures used by the internal control officer will not reveal significant misstatements or errors

Due to the fact that the findings of the internal control officer with regard to the evaluation of the financial and economic activities of the entity will be contrary to reality due to the dependence of the economic entity on management

Occurs if the internal control staff member’s conclusion, based on a sample selected by him or her, differs from that justified by the application of identical internal control procedures of the General Assembly as a whole

To assess the risks of financial and economic activities of agricultural organizations, including the identification of risks associated with the inefficient and ineffective use of budgetary funds, we propose to conduct a rapid analysis, which is aimed at identifying external and internal risks, weaknesses and strengths of the organization, etc. We believe that it would be advisable to conduct such an analysis in two aspects: internal risk assessment (primary analysis) and external risk assessment (secondary analysis). When assessing internal risks that may arise in an organization, it is important to analyze the main elements of the established procedure for operating and financial activities, the organization of accounting and preparation of accounting (financial) statements. Based on such analysis, it is possible to identify weaknesses of the organization and various threats that may have a negative impact (Table 4). After a preliminary analysis and filling out the proposed document in the column “Mark on the presence (absence)” of the characteristic elements will be signs “+” or “−”. In the course of the preliminary initial analysis of the activities of Shakhtar LLC, the strengths and weaknesses were examined, and the prospects and possible threats to the organization’s activities were evaluated.

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Table 4. Initial analysis of agrarian organization activities to identify internal risks, including those related to the use of budget funds, the internal control system on the example of Shakhtar LLC, Atni District, RT (proposed form of a working document). Elemental characteristics

Mark of presence (absence)

Strength Sides A

Wide range of offered agricultural products

+

Possibility of wholesale and retail sale of products

+

High quality products

+

High level of funding

+

High level of power supply

+

Qualified staff

−

Availability of information system and automated programs + In terms of budgetary resources:

X

Availability of various projects of innovative and modernization character, which may serve as a basis for attracting subsidies

−

Positive credit history

+

Positive story about previously attracted budget funds

+

The level of profitability of production for the previous reporting period is higher than the average among the entities located in one economic zone

−

The weak Sides (B) Absence of free access to external market

Promising opportunities (C)

−

Unqualified staff

+

Small range of agricultural products

−

High selling expenses

+

Bad credit history

−

In terms of budgetary resources:

X

Lack of proposed projects that merit fundraising

+

Bad history with regard to previously raised budget funds

−

The level of profitability of production for the previous reporting period is lower than the average among the subjects located in one economic zone, or a negative value of this indicator

+

Development of retail and wholesale outlets

+

Possibility of expanding the product range

+

Staff training and retraining

+ (continued)

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Table 4. (continued) Elemental characteristics

Mark of presence (absence)

Cooperation on exchange of raw materials and products with other organizations

−

Ability to import own products

+

Information and technological support of all elements and departments of production

+

In terms of budgetary resources:

X

The possibility of developing and presenting various projects within the framework of the state program, which may deserve to attract budgetary funds

+

Possibility to develop measures aimed at increasing the efficiency of budget funds use

+

Possibility to develop measures aimed at minimizing costs and maximizing profits

+

Possible threats (E) Increase in production and commercial costs due to changes in the currency exchange rate

+

Decrease in product competitiveness

+

Drop in consumer demand due to new interchangeable products

+

Threats associated with adverse climatic conditions

−

Threats related to the subject’s industry-specific features (e.g., animal deaths due to diseases, etc.)

−

In terms of budgetary resources:

X

Non-fulfillment of subsidy conditions due to various factors and situations

+

Incorrect recognition of budget funds, resulting in − miscalculation of revenues and expenses and misstatement of accounts Misuse and misappropriation of funds

+

Among the weaknesses we can single out the low level of highly qualified personnel in the sphere of accounting in the organization, as well as keeping the values of profitability indicators at the level below average among enterprises with the same production sectors. All this determines the presence of possible threats, which may come in the short term: the risks of decreasing competitiveness and assortment of output products, threats, connected with branch peculiarities and dependence of the organization on the branch of animal industries, etc. It is also worth mentioning the strengths of the organization,

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which are high level of stock and energy supply, availability of high quality products, etc. We believe that due to such indicators the organization has an opportunity to further expand wholesale and retail outlets, increase the range and competitiveness of products. With regard to budgetary funds, we would like to note that the main drawback of the organization is the lack of real promising projects to expand the range and improve the competitiveness of products, projects of innovative and modernization character, which may become the basis for attracting additional amounts of budgetary funds. It should also be noted that in the previous reporting periods there were circumstances that led to failure to meet the subsidy terms, but no facts of misuse of subsidies were revealed. Thus, it is possible to note the following internal risks existing in the organization: 1. with regard to budget funds, there are risks of failure to meet the conditions of subsidizing, as in the previous reporting periods such cases occurred. This may lead to improper use of budget funds, as well as contribute to the fact of non-compliance with legislative requirements when accepting subsidies for accounting purposes; 2. high level of commercial expenses, which can increase the cost of products and reduce profits in the organization; 3. the lack of real projects for the innovative development of the organization and the expansion of production entails a risk that the budget funds will not be received in the future; 4. low level of availability of highly qualified personnel in the sphere of accounting and reporting, which is an element of the control environment and can adversely affect the reliability of the data of the accounting (financial) reporting or entail significant errors in reflecting the facts of economic life of various kinds in the accounting. According to Table 4, it is possible to calculate the average aggregate level by studying the weaknesses and possible threats of the company’s activity, which are attributed to the group of inherent risk factors of an economic agent. For calculation it is supposed to estimate the presence of each element of weaknesses and possible threats in 1 point and calculate the internal risk factor. So, let’s calculate the total number of points for the primary analysis of internal risks as a whole: 6(+)A − 1(−)A + 4(−)B − 4(+)B + 5(+)C − 1(−)C − 5(+)E + 2(−)E = 6 points (1) In the group of weak (B) parties out of 8 categories there are 4 positive ones, therefore the total sum of points for the categories belonging to the risk group is 4. In the group of possible risks (E) for the organization there are 5 threat categories, which is equal to 5 points. Thus, the total risk and threat assessment, equal to 9 b (4(B) + 5(E)), exceeds the total amount of the primary analysis elements (6 b), which indicates a high level of inherent risk of a business entity. In this case the internal risk ratio is 1.5. In our opinion, it is acceptable to apply the following internal risk assessment scale:

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0 < K < 0.5 - low level; 0.51 < K < 0.9 - average level; K > 1.0 - high level, which testifies to the high level of internal risks at Shakhtar LLC, RT Atnu District. Besides internal risks, there are also risks of political, social and technological nature, which are manifested from the external environment of the subject. We believe that in order to assess such risks, it is necessary to carry out a secondary analysis, or assessment of external risks. Based on the data of the preliminary secondary analysis of Shakhtar LLC activities in the Atni district of RT (Republic Tatarstan), the assessment of political, economic and social factors that may affect the organization’s activities was made. Among all the factors, as it was revealed, the most significant impact can be made by economic factors associated with the unstable economic situation in the country and around the world. It is also important to assess social factors, as they predetermine the level of consumer demand for manufactured products. Thus, let us note the main external risks: 1) constant change of exchange rates, which may lead to significant changes in the amount of costs for the purchase of raw materials, fixed assets and other types of property necessary to ensure production processes; 2) lack of labor force and highly qualified personnel; 3) with regard to income and expenses on ordinary types of activity, the organization has the risk of occurrence of large amounts of costs associated with the organization of sales process, as well as the risk of revenue shortfall due to various circumstances. The primary and secondary analyses to identify internal and external risks provide detailed information by risk category and average risk level. Based on the results of the analysis, it is possible to determine in what areas it is necessary to carry out activities to reduce and completely eliminate risks. We believe that such analysis serves not only as a procedure in the internal control system, but also as methodological and information support in the further work of accountants and managers aimed at improving the profitability of sales in agricultural organizations. The main feature of the proposed step-by-step process is that the first stage is the assessment of the business of the investigated organization, which will allow to analyze the economic and financial and economic conditions of its activities, on the basis of which it is assumed to identify weaknesses, and, consequently, to identify possible risks.

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On the basis of primary and secondary risk analysis, we propose to organize the process of risk assessment and decision making system for their minimization (Fig. 7).

Identification of risk factors based on primary and secondary Business valuation of an analysis organization

Evaluation and Development of monitoring of a strategic plan the effectiveness Materiality of the strategic assessment of to minimize or eliminate plan identified risk identified risks

Fig. 7. Risk assessment process and decision making systems to address risks (proposed option).

An element of the internal control system “Monitoring of controls” (Fig. 8). In order to assess the reliability and objectivity of the internal control system in an organization, such an element of this system as monitoring or evaluation of controls should be justified and organized. We believe that the main purpose of this element is to evaluate the achievement of the objectives of the internal control system and their effectiveness. Monitoring of the controls should be carried out by an internal or external auditor by assessing the reliability of the other four elements of the internal control system. If state subsidies are considered separately, monitoring of means of control should be carried out within the framework of assessment of correctness and objectivity of adoption and recognition of budgetary funds in the organization, compliance of the procedure of their accounting with the requirements of legislative and regulatory acts, assessment of completeness and reliability of control procedures applied in this area and the system of assessment of risks that may arise in relation to budgetary funds. As a result of the implementation of the proposed model for monitoring the internal control system of budgetary funds, we believe that the following measures should be taken: 1) development and implementation of measures for correction of the disturbed actions; 2) organization of the system of control over implementation of corrective actions; 3) periodic submission of reports on implementation of these corrective actions to the Internal Control Service.

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MONITORING THE INTERNAL CONTROL SYSTEM (ICS) FOR THE PURPOSEFUL USE OF BUDGETARY RESOURCES

Assessment of the effectiveness of the organization of ICS

Assessment of the effectiveness of the ICS

Evaluation of the established policy for the implementation of control procedures over budgetary resources

Testing the evidence of the functioning of the ICS obtained during the control procedures for a certain period

Reliability assessment of control environment elements in relation to the budget funds

Inspection of the reliability (unreliability) of the evidence collected during the verification process

Assessment of compliance of ICS organization norms and procedures with legislative and regulatory requirements

Assessment of completeness, objectivity and sufficiency of the application of selected control procedures in respect of the budget funds Reconsideration of the materiality of the risks identified during the audit

Fig. 8. Monitoring of the internal control system of targeted use of budgetary funds (proposed form).

The element of the internal control system “Information system related to the preparation of accounting (financial) statements”. The information system created by the management staff to establish and calculate certain economic indicators should be based on accounting data and the internal control service and supported by various technical and software tools existing in the organization, as well as highly qualified data processors (Fig. 9). In terms of budgetary resources, in our view, the information system should provide: 1. availability of complete information on receipt and use of budgetary funds for objective disclosure in financial statements; 2. effective transfer of information on budget funds from management structures to officials and workers in order to understand their importance and ensure their conservation, effective and targeted use; 3. Informing managers and officials about any revealed facts of unfair or incompetent spending of budgetary funds, their incorrect recording in the accounts of accounting and other facts of violations related to them in a detailed manner and with proposals for their elimination or adjustment; 4. protection of information contained in internal documents against unauthorized access.

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Control of software licenses availability

Automatic reconciliation of data on the same operations contained in different information systems

Protecting the corporate network from external unauthorized access

Approval of information resources sup-ported by the information technology structural unit

APPLIED

Approval of a list of software recognized as compatible with other information systems

GENERAL

Accounting for the actions of officials entitled to access the information system in question

Automatic reconciliation of data on different indicators contained in one information system Limiting the characteristics of the information to be entered Control of the initiation of operations Control the numbering of input documents

Change Accounting System Ensuring security on your local network

Fig. 9. Classification of information system control means.

4 Discussion The most important element of the effective functioning of the system of budget financing and implementation of state policy in the field of regulation of agriculture, raw materials and foodstuffs is the systematization of state financial control exercised by state legislative bodies and executive authorities. State financial control over state subsidies in agricultural organizations consists in detecting violations in the organization of economic processes for the acceptance and use of such funds and their reflection in the company’s accounts and financial statements. The effectiveness of such control depends to a greater extent on the clarity of the requirements and provisions of regulatory and legislative acts with regard to the procedure for the adoption and use of budgetary funds, the establishment of the nature and measure of responsibility for each type of violation and non-compliance with the established conditions, as well as the determination of sanctions corresponding to each violation that resulted in damage or distortion of material data. In the system of state financial control it is common to distinguish between state, budgetary and financial control and departmental control. The system of state control is aimed at checking and revealing drawbacks in the sphere of observance and fulfillment of obligations to the state by economic entities.

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In this system the most important objects of control are tax and customs obligations of companies, as payments received under these obligations are the main component of the revenue part of the state budget. The system of budgetary and financial control is aimed at checking the legality and efficiency of the formation, receipt and use of budgetary funds. Here one can divide directly financial and credit and administrative control. While financial and credit control is responsible for the target, economic and efficient expenditure of real state funds, administrative control is aimed at the evaluation of the activities of subordinate structures for the organization of events contributing to the expenditure of funds of this nature. The main purpose of departmental control is control over compliance with the requirements and conditions of legislative bodies prescribed in official legislative acts, which arise when business entities receive budget financing. In our opinion, such type of control is the most important in the current conditions, since the funds of state aid may significantly affect the financial position of organizations. The main task of departmental control is to provide conditions that facilitate the fulfillment of all requirements for the receipt of public funds and their targeted use. Control of agricultural organizations in this part is the most important part of the control function, since the provision of food security of the country depends on the efficiency and purposeful use of budgetary funds. The main method of departmental control carried out in respect of economic entities is inspection of documentation, which was drawn up in the course of receipt of budgetary funds. On the basis of such documents the facts of fulfillment of presentation conditions, completeness of facts of economic life, correctness of their reflection in accounting accounts and expenditure channels are considered for the purpose of evaluation of purposefulness and efficiency of use. When performing control functions, in our opinion, first of all it is necessary to take into account the principle of hierarchical affiliation, i.e. control should be carried out gradually and depending on the level of affiliation of the controlled body. The main documents considered in the course of departmental audit of budgetary funds are: accounting (financial) statements of agricultural organizations, documents that contain calculations of subsidy limits, primary documents of the organization, which were drawn up when accepting monetary funds or other type of property as a state subsidy, etc. In addition to the documents listed at the request of a departmental body, other documents may be subject to inspection if the content of information in the previously requested documents is doubtful or there is a contradiction between several documents, or the information is insufficient for a comprehensive and complete assessment of compliance of an agricultural organization with the conditions and procedure for receiving and using subsidies. Field inspections may also be carried out in such cases. There are three groups of methods of documentary inspection of state financial control: 1. verification of individual documents, which can be carried out through formal, regulatory, arithmetic and substantive verification; 2. verification in respect of interrelated documents, carried out through counterverification and mutual control; 3. verification of documents reflecting the same type of operations, combining such methods as control comparison of balances, methods of quantitative and in-kind

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accounting, recalculation of production volumes, raw materials, property and chronological analysis of performed operations. In the process of departmental financial audit of agricultural organizations for compliance with the conditions and requirements of subsidies may be drawn up “Act of departmental financial audit for compliance with the conditions and requirements of subsidies” (Table 5). An act of departmental financial audit on compliance with subsidy conditions and requirements may be drawn up based on the results of a scheduled, unscheduled and field audit. We believe that the application of this form summarizes all the information about the audit and is a confirmation of state financial control of budgetary funds provided to the agricultural organization. We believe that two types of conclusions can be justified in this opinion: positive and negative. In case of non-detection of significant violations or revelation of violations that do not have a significant impact on the reporting indicators and do not entail the fact of improper use of budgetary funds, the conclusion is positive. In case the audit team detects significant violations which may result in the improper use of subsidies or the violation itself consists in the non-targeted use of funds, the conclusion should be negative, which will express an opinion on the presence of significant distorting violations. In our opinion, such irregularities can be classified as such: 1. reflection in the documents of transactions or facts of economic life causing doubts, in case of confirmation of doubts after additional control measures or fictitious actions that were not actually performed; 2. total failure to comply with the conditions for granting subsidies or submission of documents specifying the fact of their implementation while they are not actually implemented; 3. there are significant discrepancies in the value of interrelated documents; 4. forgery of documents, i.e., preparation of documents much earlier or much later than the operation performed; 5. identification of documents that do not correspond to the actually performed facts; 6. absence of documents, confirming the fact of purchase, acquisition or construction of objects, material and production stocks, raw materials, compensated at the expense of amounts of budget funds, i.e. misuse of funds; 7. revealing of the facts of purchase, acquisition or construction of the objects, material and production stocks, raw materials at the expense of the budget funds at the expense of the sums of budget funds, i.e. false and fictitious documents. In case of detection of the abovementioned violations, the act shall contain a negative opinion with the expression of an opinion on improper use of budgetary funds or on the presence of a high probability of occurrence of such a case or on a significant probability of data distortion in the reports of the organization. If such opinion is drawn up, the departmental body has the right to take measures and sanctions in case of noncompliance with the conditions and requirements of subsidies and to impose a measure of responsibility and punishment on officials, as well as to demand return of state subsidies.

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Table 5. Act of the departmental financial inspection on compliance with the conditions and requirements of subsidies (Proposed form). Act of departmental financial audit on compliance with subsidy conditions and requirements Departmental agency conducting the inspection Ministry of Agriculture and Food of Republic Tatarstan Reviewer Group Leader

Valiyev R.A.

Inspection period

From 14.03.2020 to 16.03.2020

Name of the organization to be audited

Branch of LLC “Set Ile” - “Laishevo” of Laishevo district of Republic Tatarstan

Controlled period

2019 reporting year

Targeted government subsidy

Buying mineral fertilizers

Date of receipt of notification of subsidy

10.09.2019 year

Date of actual subsidies received

01.10.2019 year

Amount of funding

400 000 rubles

Date of control operation

Content of the control operation

Verifiable documents

Special notes

Final evaluation

14.03.2020

Verification of compliance with subsidy conditions

Expert opinion of the internal control department on fulfillment of subsidy conditions, agreement on receipt of state subsidy

1. Under condition 2 “Provision of calculations on planned indicators of crop production” it was partially performed, namely, calculations are not presented for all types of crop production

Non-compliance or partial compliance with the subsidy conditions may be evidence of non-compliance with legal requirements when subsidies are accepted for accounting purposes

(continued)

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Act of departmental financial audit on compliance with subsidy conditions and requirements 14.03.2020

Formal verification of documentation on receipt of state subsidy and purchase of mineral fertilizers

Budget 1. Incomplete painting, bill of filling of lading, details in bill purchase book, of lading №34 invoices, dated warehouse 20.09.2019 cards, payment 2. Lack of entries related to the order, etc. purchase of mineral fertilizers in the purchase book

Based on the results of the formal verification of the documentation, no materially distorting violations were detected

Final report: Based on the results of the departmental financial audit of LLC «Set Ile» “Laishevo” Branch of the Laishevo District of the Republic of Tatarstan for compliance with the conditions and requirements for granting state subsidy for compensation of expenses on purchase of mineral fertilizers in the amount of 400,000 rubles (Notice on granting subsidy from 10.09.2019 according to the Resolution of the Ministry of Agriculture of the Republic of Tatarstan “On granting state subsidies to agricultural organizations for 2019”), violations were detected: 1. Incomplete fulfillment of the condition of granting, requiring from the organization in the presentation of the calculated data on the planned indicators of crop production for 2019, which consists in the presentation of data not on all types of crop production, produced in this organization; 2. Incomplete filling of details in the bill of lading № 34 of 20.09.2019 Expression of opinion on materiality of violations: The violations revealed in the course of the audit are immaterial and do not affect the distortion of data in the statements. The state subsidy was used for its intended purpose in full. As a whole, the organization has met the conditions and requirements of the subsidy, and corrective notes have been made on the revealed violations The head of the inspection team: Date of Act:

Signature, printout

Valiyev R.A.

5 Conclusions Thus, operations related to the receipt and use of budgetary resources require special control to ensure their targeted and efficient use. The peculiarity of the organization of the internal control system of operations related to receipt and use of budgetary funds consists in the composition and content of the procedures applied and the sequence of their use. Organizations of the agro-industrial complex are characterized by a low level of efficiency of the internal control system functioning, which is connected with inadequate understanding and perception of the meaning of the control function, as well as with the lack of methodological and practical support for the organization of such a system. In this connection, the article substantiated the main functional directions of the internal

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control system of budgetary funds in agricultural organizations, argued the model, tasks, elements of such system; determined the procedure and stages of analysis of agricultural organization’s activity to reveal internal risks including those related to budgetary funds. In the course of the research, each element of the internal control system in relation to budgetary funds was structured, the monitoring model and the risk assessment process were substantiated. It was proposed to carry out primary and secondary analysis of various factors in order to identify risks, the sequence and structure of such analysis was justified. Systematization of state financial control exercised by state legislative bodies and executive authorities is the most important element of effective functioning of the system of budget financing and implementation of state policy in the field of regulation of agriculture, raw materials and food. Effective control procedures for compliance with the conditions and requirements of subsidies will make it possible to identify violations that may lead to further misuse of funds.

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Enterprise Architecture Modeling in Digital Transformation Era Igor Ilin , Anastasia Levina(B)

, Alexandra Borremans , and Sofia Kalyazina

Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, 195351 St. Petersburg, Russia [email protected]

Abstract. In the context of digitalization, different enterprises require complex vision of their various aspects: business, information systems, technological infrastructure. This is one of the top-management baseline needs in order to plan company development in technology implementation. Different digital technologies, also known as Industry 4.0 technologies, should be considered as tools for complex transformation of the listed enterprise aspects. The goal of the current research in to represent an enterprise meta-model and demonstrate how different digital technologies transform it. Enterprise Architecture approach is chosen as a method for this research and models representation. The impact of emerging technologies such as Big Data, Cloud Computing, IoT, Blockchain, Digital Twins and Artificial Intelligence on the on IT infrastructure, IT architecture, Technological and Production architecture, as well as Business architecture of a production enterprise is shown. The results of the analysis are combined into a comprehensive metamodel that describes the possible development of a modern enterprise within the framework of the Industry 4.0 concept. Keywords: Enterprise architecture · Digital transformation · Industry 4.0 · Meta-model · Archimate · Emerging technologies

1 Introduction The digital transformation of business consists in deeply transforming the business and operating model of an organization using breakthrough technologies. Digital transformation involves changing the business structure, business development strategy, corporate culture, sales system, team and process management in general. The technologies associated with digital transformation are a feature of the concept of Industry 4.0 and are designed to ensure the interaction of people and technologies and increase consumer involvement in production. The Industry 4.0 paradigm is related to the Internet of things (IoT), cyber physical systems (Cyber Physical System, CPS), information and communication technology (ICT), enterprise architecture (Enterprise Architecture, EA), and corporate integration (Enterprise Integration, EI) [1]. Industry 4.0 aims to increase value, manage knowledge, achieve a higher level of operational efficiency and productivity, as well as a higher level of automation. The concept Industry 4.0 includes the use of technical devices, such as sensors, networks, servers, designed to implement technologies. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 124–142, 2021. https://doi.org/10.1007/978-3-030-57453-6_11

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It is possible to consider nine fundamental technologies that represent the concept of Industry 4.0 - autonomous robots, simulation, horizontal and vertical system integration, industrial Internet of things, the cloud, additive manufacturing, Big Data and analytics, cybersecurity, augmented reality. These technologies allow to increase the flexibility, efficiency of processes and ultimately increase the competitiveness of the company. The collection and comprehensive assessment of data from various sources (sensors on equipment, enterprise and customer management systems, and others) are used to support decision-making, equipment adjusts its parameters. Accordingly, the business model of the company is changing [2]. Optimal support for solving a wide range of problems is provided by mobile, context-sensitive user interfaces and user-oriented assistance systems. New digital technologies are creating new value chains and new products tailored to the needs of the end user. Accordingly, the company’s profit and investment attractiveness are growing. Successful digital transformation requires incorporating technology into the enterprise architecture [3]. Their application requires a change in the organizational structure of the company, increasing its flexibility. Requirements for competencies are changing: they are expanding and involve lifelong learning. Flexible methods of product development are applied, which in turn also involves a change in the organizational structure and business model. The capabilities of technologies for personifying offers and taking into account user experience also involve changing tasks and working methods [4]. One of the key technologies discussed is the Internet of Things (IoT). Its use involves the use of Internet-oriented architecture. The IoT connects billions of devices to the Internet and allows to use the data to analyze, plan, manage and make smart decisions. IoT is widely used in such areas as transport, smart city, smart home appliances, smart healthcare, e-government, e-education, retail, logistics, agriculture, industrial production, business process management [5]. The IoT architecture consists of sensors, actuators, cloud services, protocols, communication layers, users, developers, and the corporate layer. Service Oriented Architecture (SOA) is an approach used to create an architecture based on the use of system services. The application of this approach in IoT reduces the time of product development and facilitates the marketing process [6]. The basic architecture distinguishes three layers: perception, network and application layers. The level of perception has sensors for perceiving and collecting information about the environment (physical parameters, information about other intelligent objects). The network layer organizes the connection to other intelligent objects, network devices and servers, transfers and processes data from sensors. The application layer provides the user with applications in which the IoT can be deployed, for example, smart homes, smart cities, smart health [7]. A five-layer architecture is now being offered, which additionally includes processing and business levels. Five levels are perception, transportation, processing, applications and a business level. The transport layer transmits sensor data from the perception level to the processing level and vice versa through networks such as wireless, 3G, LAN, Bluetooth, RFID and NFC. The processing layer (middleware) stores, analyzes and processes the data coming from the transport layer. It provides services to the lower layers and uses technologies such as databases, Cloud Computing and Big Data processing

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modules. The business layer manages the entire IoT system, including applications, business models, user privacy [8]. A key role is played by middleware between things and the application layer, the main purpose of which is the abstraction of functionality and communication capabilities of devices. Currently, large amounts of data are being generated daily at an unprecedented rate from diverse sources (e.g., healthcare, government, social networks, marketing, finance) [9]. This is due to many technological trends, including the IoT, the spread of Cloud Computing, and the spread of smart devices. Big Data is used in complex systems such as intelligent network systems, healthcare systems, retail systems, government systems. Large data sets consist of structured and unstructured data, open or closed, local or remote, general or confidential, complete or incomplete, etc. [10, 11]. Blockchain technology is promising for Internet interaction systems such as smart contracts, government services, IoT, and security services. The blockchain is characterized by decentralization, persistency, anonymity and auditability, which allows to ensure traceability and transparency of data, lower operating costs. On the basis of blockchain and smart contracts, new e-business models are being implemented [12]. It is based on model, distributed autonomous corporations (DAC), through which the calculations go. The blockchain is also suitable for Big Data analytics, taking into account the increased capabilities for protecting confidential information. In addition, blockchain and smart contracts are able to optimize the operation of devices with Artificial intelligence (AI) and reduce the number of errors and their illegal actions [13]. Cloud Computing-based architectures are seen as promising in areas such as connecting people and devices, heavy data usage, service space, and self-learning systems. Currently, Cloud Computing uses a two-tier application architecture where external nodes, such as user devices, use the service offered by the cloud and the business logic and database logic are located in the cloud. In general, cloud architecture is divided into levels: datacenter (hardware), infrastructure, platform, application. Each of them can be considered as a service for the layer above and as a consumer for the layer below. A promising is the distributed architecture of Cloud Computing. The use of Cloud Computing improves the accuracy and efficiency of IoT, as well as end-to-end security in networks through encryption and authentication mechanisms. Also, cloud infrastructure enhances the processing capabilities of Big Data. The abstraction of infrastructure, platforms, and software was initially offered as services (IaaS, PaaS, and SaaS) in the cloud, but the service space is becoming wider. For example, Acceleration-as-a-Service (AaaS) for applications, or Container-as-a-Service (CaaS) as an alternative virtualization technology, or Function-as-a-Service (FaaS), where the server application is used only when a request is received, is suggested. The cloud is also promising for machine learning. The Cognitive Computing model is planned in the next generation clouds, in which cognitive systems will rely on machine learning algorithms and generated data, acquire knowledge, model problems and determine solutions [14]. The Digital Twin allows to significantly expand the capabilities of cloud-based analytical services used in the concept of Industrial Internet of Things. Information from real sensors is compared with the readings of virtual sensors of a Digital Twin, which allows one to identify anomalies and establish the causes of their occurrence. A Digital Twin

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is used to evaluate, predict, analyze the performance of a product or process throughout the entire life cycle of a product, to reduce investment errors in physical prototypes and resources. Due to multiphysics modeling, data analytics, and machine learning, Digital Twins can demonstrate the impact of design changes, various usage scenarios, environmental conditions, and other factors on the product or process and eliminate the need for physical prototypes, which reduces development time and improves quality result. AI is used to support decision-making based on recommendations, machine learning and data mining. AI systems include Artificial neural networks (ANN), fuzzy expert systems, evolutionary. Each AI method has its own strengths and weaknesses. The advantages of these technologies can be combined together to create hybrid intelligent systems that can work in a complementary manner [15]. This allows the hybrid system to take common sense into account, extract knowledge from raw data, use human-like reasoning mechanisms, solve the problems of uncertainty and inaccuracy, and learn to adapt to a rapidly changing and unknown environment. This article is organized as follows: Sect. 2 describes methodological base of the research and existing knowledge on the topic. Section 3 presents the results of conducted research and application of emerging technologies in meta-model of production enterprise. Section 4 presents a conclusions of the findings in the context of IT, modern enterprises and its architecture.

2 Methodology The research methodological base includes: 1. Enterprise architecture as an integrated approach to the integration of heterogeneous elements (business processes, functional structure, organizational structure, information systems and technologies, digital technologies, manufacturing technologies, assets) into an effective business system [16]. 2. Service-oriented approach as a means of harmonizing (aligning) the requirements and capabilities of business and IT elements of a single system. One of the main functions of a service-oriented architecture is the creation of a broad architectural model that defines the goals of applications and approaches that will help achieve these goals [17]. Enterprise architecture is designed to improve the management and functioning of complex enterprises and their information systems. Enterprise architecture is understood as a set of heterogeneous elements in the interaction that make up the internal structure of business management - from strategy, goals, business model, to business and technological processes, organizational structure, information systems, production equipment and IT infrastructure [18]. Traditionally, the following layers of enterprise architecture are distinguished: the business layer (describes the activity of the enterprise and its development), the application layer (describes applications, data and their relationships) and the technology layer (describes hardware and system software). Service-oriented enterprise architecture (SOA) allows to implement high-quality and efficient company work through a service approach to enterprise business processes. The enterprise architecture, on the one

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hand, must be stable, but on the other hand, it must be flexible and adaptive to changing business environment conditions, the emergence of new technologies and tasks. Digital transformation of the industry involves the use of new digital technologies and requires the optimal organization of the enterprise structure and business processes [19]. The architectural approach can become the basis of business management and its automation. When building enterprise architecture as an integrated enterprise management model, interconnected and interdependent layers are distinguished. The multilevel structure of the enterprise architecture model determines the relationship between the main components of the system. There are a number of well-known approaches to corporate architecture. For example, the International Standard for Corporate Architecture, TOGAF offers an enterprise architecture design and development methodology - Architecture Development Method (ADM) [20]. TOGAF ADM distinguishes 3 levels: business architecture, information system architecture, technological architecture. In particular, it considers IT architecture: applications, data, equipment. The latest version of the Archi 4.0 modeling tool, using the ArchiMate modeling language, based on the TOGAF methodology, has a new group of elements (the “physical layer”), which involves a description of not only the IT infrastructure, but also the material infrastructure complex. A meta-model is being developed as a basis (see Fig. 1). Its construction begins with the definition of a mission, vision, and goal of the enterprise. When describing IT infrastructure, it is taken into account that new technologies put forward new requirements for IT architecture and IT infrastructure, including in terms of the correspondence between IT support and technological processes. When constructing a model of enterprise architecture in this article, technological processes as a subsystem and requirements for automation of production, included in the description of information systems, will be distinguished. The following levels are highlighted in this model: strategic level, business level, IT architecture, technological level, IT infrastructure.

Enterprise Architecture Modeling in Digital Transformation Era

Fig. 1. A meta-model of an enterprise.

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3 Results Consider the technologies described above and imagine their application in a manufacturing enterprise using the example of a meta-model. 3.1 Big Data Representation Big Data is a type of data that is either extremely large, fast or complex to the point that it is too hard or even impossible to handle it while using traditional methods [21]. Big Data can be either structured or unstructured. Structured data is usually numeric, already organized and stored in company’s databases. Unstructured data includes data that comes from different sources, such as, for example, social media. This data is unorganized and quite hard to navigate. The findings within that data can vary drastically and therefore may be utilized for different purposes. Almost every department can benefit from company’s usage of Big Data, Sales and R&D alike. Figure 2 shows the main principals of Big Data usage in an industrial company. Since Big Data processing requires specific methods, there is a need for some adjustments in IT-architecture and IT-infrastructure. The presented model shows how IT-architecture is expanded by adding a Big Data application. That application has several modules such as Data Lake software, ETL, Data Mart, and analytical software. Data Lake software is used for compiling incoming data from ERP, MES, and automated process control system already present in the company. Data Mart forwards processed data to a BI-system for further analysis. IT-infrastructure expansion requires additional servers and databases for the aforementioned applications. The model shows how Data Lake collects data from various internal and external sources, compiles it into raw data and forwards it to ETL. ETL, in turn, clears that data to make further handling easier. That clear data then gets to Data Warehouse which is used for processing. Lastly, data flows to the Analytical Database where it’s analyzed by specialized software. As is evident, these components provide users with data management and data analyzing services. Usage of Big Data will allow the company to make better decisions, as they will have more data to base their decisions on, as well as improve customer service and increase productivity in the company overall. 3.2 Cloud Computing Representation Cloud Computing refers to providing of required computing services that vary from data storage to additional computing power [22]. Companies opt to not having their own IT-infrastructure and instead rent out whatever they need from cloud service vendors. Still, introduction of Cloud Computing into the company’s usage requires some adjustments to be made in company’s architecture as shown in Fig. 3. As IT-architecture is expanded by a Cloud Computing application, it will work closely exchanging data with ERP and forwarding data to BI for analysis. IT-infrastructure will undergo some changes, as well. A virtual data center needs to be created, it will include virtual web server and database server. These servers will be used to access physical web and database servers in Cloud Computing vendor’s datacenter.

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The use of Cloud Computing services will allow the company to access data at any time regardless the device as long as it has required access. Also, using Cloud Computing services will be massively beneficial as it will help the company to lower the costs and avoid difficulties of maintaining its own IT-infrastructure. Not only will Cloud Computing service help decrease the amount of money spent on expensive equipment and software, it will also protect the company’s data from unauthorized access.

Fig. 2. Big Data representation in meta-model.

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Fig. 3. Cloud Computing representation in meta-model.

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3.3 IoT Representation The Internet of Things, or IoT, refers to physical devices around the world that have access to the internet, and use it to collect and share data [23]. Almost any physical object can be modified into an IoT device if it has capability to connect to the internet and can be controlled via that connection. Figure 4 shows how using IoT requires significant changes in technological architecture and IT-infrastructure of the company. As Smart Facility is implemented within technological architecture, data from its accompanying smart equipment, that will a part of company’s IoT device system, will flow with the usage of REST API to the Data Acquisition Gateway. Data Acquisition Gateway is added to the IT-infrastructure to collect data from all the IoT devices utilized in the company. IT-architecture, however doesn’t require a lot of expansion other than the addition of an IoT platform. This platform will exchange data back and forth with ERP and MES, as well as forwarding some of the data to BI for analysis and company’s automated process control system for watchful control. The Internet of Things will help the company in accessing more data about the products they manufacture, as well as various internal systems of the company, that, in turn, will provide the management with means to implement changes that would improve company’s overall performance. 3.4 Blockchain Representation Blockchain is a distributed database that stores information about all transactions of system participants in the form of a continuous sequential chain of blocks [24]. A block contains a certain set of records, and each new block that is added to the end of the chain will duplicate all the information from previous blocks. The main principles of blockchain technology are transaction anonymity, security and availability. The distributed ledger provides control of data integrity, and also makes it impossible to replace or delete transactions or their contents retroactively, which ensures that there are no disagreements between contractors regarding the actual status of fulfillment of obligations. Today, blockchain technology is mainly used for operations with cryptocurrency, although the potential for its use is much wider. Figure 5 shows an example of the implementation of blockchain technology in enterprise architecture. A key element of blockchain technology is a distributed database or distributed ledger in which some enterprise data is stored. Access to this database is carried out according to a special blockchain network protocol through the node application. Directly, users get access to blockchain technology through a blockchain platform that provides a number of services, including storage, distributed access and data processing. However, blockchain technology itself is practically useless for the enterprise. In order to benefit from the use of this technology, it is necessary to integrate it with existing systems. It is believed that the most appropriate is the integration of the blockchain platform with the ERP system. Such integration will allow the ERP system to exchange data on suppliers, partners, transactions with the blockchain platform, and receive data on transactions carried out on the blockchain platform in response.

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Fig. 4. IoT representation in meta-model.

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Fig. 5. Blockchain representation in meta-model.

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Thus, the use of blockchain technology is most appropriate if necessary, to carry out distributed control of assets and liabilities, the status of which dynamically changes depending on the onset of certain conditions. 3.5 Digital Twins Representation Digital Twin is a digital analogue of a physical object or device that simulates internal processes, technical characteristics, and behavior of a real object in various environmental conditions [25]. To ensure accurate modeling throughout the product’s life cycle or its production, Digital Twins use data from sensors installed on physical objects to record the object’s performance in real time, operating conditions and changes over time. Using this data, Digital Twins are improved and constantly updated in accordance with changes in the physical counterpart throughout the product life cycle. Thus, there is a closed feedback in a virtual environment, which allows companies to constantly optimize their products, production and increase productivity with minimal cost. This interaction cycle can be clearly seen in Fig. 6. An industrial sensor records the performance of real physical objects and transmits them to the Digital Twins software. All transferred data is stored in a Digital Twins database. Based on the data obtained, a digital model or Digital Twin is generated, which the user accesses through the appropriate application. In addition to obtaining a digital model in the application, it is possible to diagnose the model, conduct various types of analysis, modify the model, and make a forecast for the future. To ensure continuous aggregation, online processing of operational data, as well as for quick response to changes, it is necessary to integrate the application with ERP and MES systems. This integration allows companies, using data obtained from Digital Twins of products and production, to not only test the characteristics of products, but also avoid costly downtime and predict when preventative maintenance is required. A constant flow of relevant information makes it possible to speed up production operations, to make them more efficient and reliable. Thus, Digital Twins technology can unprecedentedly increase the productivity and reliability of a product or process, while reducing operating costs.

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Fig. 6. Digital Twin representation in meta model.

3.6 Artificial Intelligence Representation Artificial intelligence (AI) is an artificially created system designed to reproduce some features of human intelligence, such as planning, training, reasoning, problem solving, data manipulation and use, perception, control and manipulation of objects and, to a lesser extent, social intelligence and creativity [26]. AI is a powerful data processing tool and can find solutions to complex problems faster than traditional algorithms. Artificial intelligence technologies today find application in various fields, including the fact that they are becoming increasingly popular in enterprises. Traditionally, the company uses artificial intelligence for statistical process control, analysis of the types and consequences of potential failures, analysis of measuring systems, pricing and inventory management, as well as for productive equipment maintenance. Figure 7 shows how AI techniques may be implemented in the enterprise architecture. The AI application is supported at the IT infrastructure level by a number of software components that implement various classes of AI methods, including machine learning. Directly, the AI application is in close integration with the MES and ERP systems, since the data of the accounting system and the consolidation of data on the operation of equipment or technological processes are sources of data with which the AI works and

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Fig. 7. AI representation in meta-model.

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on the basis of which it is trained. In turn, the AI application transmits to the specified systems some created work algorithms, suggestions for solving problems, etc. Thus, AI technologies will be able to support the production process by controlling important operations, including those that people usually track. 3.7 Meta-model and Emerging Technologies Figure 8 presents an overall model of company’s architecture with implementation of all the technologies mentioned earlier. It is important to note that, first of all, all applications and platforms have integration across the enterprise at the organizational (ERP) and production (MES) levels. In addition, most applications also function much more efficiently when integrated with each other. The introduction of technologies such as the Internet of things and Digital Twins implies the generation of a huge array of data that needs to be processed, which means that there is a logical need for Big Data tools [27]. Big Data application is also used to analyze transaction information coming from blockchain platform. Cloud Computing allows Big Data application to use its additional computing power to make data processing faster and easier. Using blockchain technology helps to keep data from IoT devices safe and make all production processes more transparent. When creating Digital Twins, data from the Internet of things application and AI algorithms are used. In addition, AI algorithms make it possible to improve the mechanisms of the blockchain platform, Big Data processing, as well as the processes of collecting and processing information by the Internet of things application. Thus, the application of all these technologies together has a powerful synergistic effect, which will achieve maximum benefits for the enterprise.

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Fig. 8. Enterprise meta-model including emerging technologies.

4 Conclusion The need for a radical transformation of the business can be caused by both internal factors and external ones. In this study, we examined how all aspects of the enterprise management system are changing in the context of digital transformation.

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The reengineering of the enterprise’s activities allows us to rethink the business, its structure, management system, the relationship between the elements in order to build an effective and manageable system based on world standards and management tools. A recognized tool for integrated change management in an organization is the enterprise architecture - a systematic approach to the design and development of enterprises. From the perspective of this approach, this study examined a number of models that demonstrate changes in the organization caused by the introduction of Industry 4.0 technologies. This study showed that the enterprise architecture provides the possibility of a deep analysis of the relationships between various aspects of the organization in the context of the implementation of various types of technologies. Acknowledgments. The reported study was funded by RSCF according to the research project № 19-18-00452.

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Key Digital Technologies for National Business Environment Nikolay Pavlov(B) , Sofia Kalyazina , Irina Bagaeva , and Victoria Iliashenko Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, St. Petersburg 195251, Russia [email protected]

Abstract. Digitalization is an important trend in all spheres of life and in all countries of the world. Digital technology is widely used to increase the productivity and efficiency of all processes. It is important to correctly determine the role and place of digital technologies in order to use them most effectively. This article analyzes the role of digital technologies in economic development using the method of expert assessments and identifying the main trends and influencing factors for key digital technologies. The selected set of variables was included in the questionnaires, which were filled out by experts. A procedure to summarize the opinions of experts using the capabilities of augmented intelligence for processing expert survey data was conducted. Of further interest is the analysis of expert responses to understand the degree of technology appreciation. Based on the analysis, it is planned to build a model to align the requirements of key sectors of the Russian business to digital technologies. Keywords: Digitalization · Digital technologies · Augmented intelligence · Expert assessments

1 Introduction The digital economy is positioned as a system of economic, social and cultural relations based on the use of digital information and communication technologies. Countries that are world economic leaders are actively using digital technology to increase productivity and efficiency of the economy as a whole and individual enterprises. Digitalization is becoming an integral part of all processes of public life and determines the change of basic technologies used to implement business activities [1, 2]. Gradually, digital technologies become a reality in the economies of countries, everyday life, various fields of economic activity, in international relations (examples are in the researches of the authors [3]). The widespread adoption of digital technologies (the Internet of things, the Industrial Internet, big data, blockchain, cloud computing, machine learning, artificial intelligence, mobile communications, etc.) is one of the most important conditions for the development of national economies of all countries [4, 5].

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 143–157, 2021. https://doi.org/10.1007/978-3-030-57453-6_12

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Plans for the development of the Russian economy until 2020 have not been fully implemented [6]. Currently, a new stage of planning is underway, identifying promising areas and activities that ensure stable development in the future. Digitalization is becoming the main trend in the world [7]. Thus, for the development of the Russian economy, it is important to determine the role of various digital technologies, and for the correct distribution of resources to support them, one should take into account not only the current state of the phenomena studied, but also the prospects for the development of economic sectors in the future. Therefore, determining the importance of digital technology for the Russian economy is not an easy complex task, for the solution of which expert methods are mainly suitable. They are very diverse [8]. It is known that traditional statistical methods for determining the average score and building the confidence interval are unsuitable here [9–11]. Due to the complexity of such tasks and their multifactorial nature [12–14], there is no single method applicable for all situations. Therefore, it is proposed to use a general approach. The task arises of developing an expert survey procedure that would extract useful information from these surveys at a certain level of confidence in the results. This task itself can be attributed to one of the new digital technologies – Augmented Intelligence, which takes on the intellectualized routine work of processing information for decisionmaking. This article is devoted to the description of expert interviewing procedures for obtaining an assessment of the importance of the digital technologies development in the Russian Federation for a period of medium-term planning of approximately 3 years. The objective of the study is to highlight the spectrum of digital technologies that are most significant, according to experts, for the development of the digital environment of Russian business.

2 Methodology The proposed method for assessing the importance of digital technologies for the Russian economy is based on expert assessments of the components of the cognitive model. Based on the study results, the features of the method application are discussed. Approach tested in Pavlov’s dissertation [15, 16]. At the first stage, the task of determining the importance of digital technology is decomposed into a cognitive map of the Fig. 1 form. The construction of such a map is not difficult, since its components are quite obvious, and their interconnection is stable. Then, using the brainstorming method on the basis of literature analysis [17–19], sets of variables characterizing each factor are determined. As a result, the following analysis sections were identified: Trends: – – – – –

Integration of economic, cultural, R&D areas Disaggregated data aggregation Strengthening security, network localization Analytics - a source of competitive advantage Different human-machine interface

Key Digital Technologies for National Business Environment Digital Transformation in the The Importance of Digital Technologies

Priorities in the Russian Federation

Favorable factors in the Russian Federation

•

The Importance of Industries

Risks in the Russian Federation

Fig. 1. Cognitive map of the digital technology importance.

– – – – –

Improving Cloud Strategies Development of social networks Personification Personnel training in digital technology The role of leadership in digital transformation

Adverse factors: – – – – – – – – –

Raw material model of the economy Level of corruption Low domestic demand Centralization of management and distribution of finance Pandemic Slowdown of the global economy; global crisis forecast Decrease in private investment Sanction pressure Instability of the energy market

Favorable factors: – – – – –

Stability of the domestic political situation Export potential (agriculture) Implementation of national projects Low external debt Stimulating role of counter sanctions

Digital technology considered: – Machine learning and deep learning

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Edge Analytics PaaS Augmented Reality Augmented Intelligence Immersive Workspace Synthetics Data Digital Ops Blockchain IoT Drones 3D printing 5G

The choice of industries was made on the basis of data on the share in the turnover of the Federal State Statistics Service of the Russian Federation. – – – – – – – – – – – – – – – – – – – – – – – –

Agriculture, forestry, hunting, fishing and fish farming Mining Manufacturing Production and distribution of electricity, gas and water Construction Wholesale and retail trade; repair of motor vehicles, motorcycles, household goods and personal items Hotels and restaurants Transport and communications Financial activities Operations with real estate, rental and provision of services Public administration and military security; social insurance Education Health and social services Provision of other utility, social and personal services Household activities Priorities for the development of the Russian economy are reflected in [20]. Relaxation of tax pressure on small and medium-sized businesses Supporting domestic demand Decrease in state regulation in production Attracting large investors Refusal of excess budget surplus Sustainable natural population growth Acceleration of technological development of the country Ensuring accelerated implementation of digital technologies in the economy and social sphere

An expert survey consists in filling out survey tables: 1.

The levels of development of digital technologies in the Russian Federation at the present stage are indicated on a scale from 0 (the technology is completely absent) to 1 (the technology is maximally developed).

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2.

The degree of manifestation of digital technology trends in the Russian Federation is indicated from 0 (does not appear) to 1 (appears to the maximum extent). 3. The degree of manifestation of adverse factors is indicated from 0 (not manifested) to 1 (manifested as much as possible). 4. The degree of manifestation of favorable factors is indicated from 0 (not manifested) to 1 (manifested as much as possible) 5. The importance of economic development priorities is indicated from 0 (completely unimportant) to 1 (importance is maximum). It can be seen that the estimates are classical fuzzy quantities. 6. A table is filled out to assess the impact of digitalization trends on popularity and adherence to one or another digital technology on a scale of −1 (strong negative impact) to 1 (strong positive). 7. A table is filled out of the influence of adverse factors on the importance of economic sectors on a similar scale. It is appropriate to explain here that unfavorable factors (for example, a pandemic) can have both an adverse effect (on tourism) and a stimulating effect (on medicine). 8. A table is filled out of the influence of adverse factors on the importance of economic sectors on a similar scale. 9. A table of the influence of the priorities of the Russian economy development on the importance of economic sectors on a similar scale is being filled out. 10. Finally, a table is filled out of the role of digital technologies in the sectors of the Russian economy. Thus, the impact estimates are extended fuzzy values ranging from −1 to 1. Although the estimates are matrix-like and have a rather large dimension, filling them out does not take much time, since the presentation used is clear and allows to cover the whole problem as a whole, comparing the power of various bonds. Next, the results are calculated. Here are formulas for one expert: Itr i =

1 Tr j ∗ tij J

(1)

j

where Itri is i-th technology out of I, determined by the development trend of the Russian economy; Trj – importance j-th trend out of J, tij – influence matrix values. Inegk

 l

Negl ∗ nlk =

1 L

(2)

where Inegk – importance of the k-th sectors of the Russian economy out of K, determined by the adverse factors; Posj – importance of the first factor out of L, nlk – influence matrix values. 1 Iposk = Posr ∗ prk , (3) R r where Iposm – importance of economic sectors of the Russian Federation, determined by the favorable factors; Posr – importance of the r-th factor out of R, pnr – influence

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matrix values. Ipr k =

1 Pr j ∗ ris , S s

(4)

where Iprk – importance of economic sectors of the Russian Federation, determined by the priorities of its development; Prs – importance of the s-th priority out of S, ris – influence matrix values. The total importance of industries is defined as Iotr k =

1 (Inegk + Iposk + Ipr k ) 3

(5)

The importance of digital technology, determined by the importance of industries, is defined as Itoi =

1  Iotr j ∗ oik K

(6)

k

where Itechi – importance of digital technology is determined by the importance of the Russian economy; Techj – current level of digital technologies development in the Russian Federation, j-th out of J,erij – influence matrix values. The resulting importance of digital technology is defined as It i =

1 (Itr + Itoi ) 2 i

(7)

These are absolute values. Since the ultimate goal of the study is the distribution of resources according to the priorities of the development of digital technologies, we should move on to relative importance indicators in the range from 0 to 1, which can be interpreted as follows: values from 0 to 0,25 are or low importance; from 0,25 to 0,5 – medium importance, from 0,5 to 0,75 – high importance, from 0,75 to 1 – key importance. Isi =

Iti max(It i )

(8)

Thus, we got fuzzy estimates of the relative importance of the digital technologies development in the Russian Federation, according to one expert. To summarize the estimates at each step, average estimates were used. This is due to the fact that they are less susceptible to random deviations of estimates and, accordingly, are more reliable. The next step is to summarize the opinions of experts. In Fig. 2 shows the ranges of Isi values for 11 experts surveyed.

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Fig. 2. Summary of responses from all experts.

The shaded area shows the range of relative ratings among experts. Opinion refers to a certain category of importance if the resulting range is for the most part in one of the indicated ranges or occupies more than half of it. It can be seen that the opinions of experts vary greatly. However, certain particular conclusions can already be drawn from these results. Machine learning, PaaS, and IoT are of high-key importance. Blockchain technology is medium-high. Estimates for other sectors were contradictory. This may indicate an unformed understanding of the role of new technologies or a strong difference in expert opinion. To extract additional information from the data obtained, a cluster analysis of experts is carried out according to their absolute estimates of Iti, since they summarize their opinions. Clustering is carried out by the far neighbor estimation method (with full coupling), the square of the Euclidean distance is used as a measure of distance. This allows to more clearly identify groups of similar research elements.

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The result of cluster analysis is presented in Fig. 3.

Fig. 3. The result of a cluster analysis of experts on their absolute assessments.

It can be seen that according to the similarity of answers, 2 groups stand out clearly: 1, 3, 5, 4, 7, 2, 11 and 6, 8, 9,10. However, in the first group, a rather isolated group of experts 2 and 11 can be distinguished. Therefore, three groups will be considered: 1 (1, 3, 5, 4, 7), the results of which are presented in Fig. 4; 2 (2, 11; Fig. 5); 3 (6, 8, 9, 10; Fig. 6). It’s clear that the estimates vary greatly between groups. In groups 1 and 3, high grades prevail, and in group 3 they are more uniform. Group 2 gives various assessments of the importance of different technologies. To assess the reliability of the estimates, the absolute estimates in each group were studied. The scope of these estimates was determined. The result is shown in Fig. 7.

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Fig. 4. Expert group 1.

It can be seen that the experts of group 2 (marked in dark) showed a certain pessimism. They do not believe that digital technology is of high absolute importance. Zero ratings are especially indicative, which show the absolute unimportance of a particular technology. Thus, their relative estimates, which reflect the priorities, turned out to be just a reflection of the small difference between equally unimportant estimates, which caused their wide scatter.

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Fig. 5. Expert group 2.

Group 3 (their assessments are marked with the lightest color), on the contrary, showed excessive optimism. That is why their relative estimates are biased to key importance. Here, zero ratings may indicate a certain underestimation of certain industries. Finally, group 1 (marked in green) occupies an intermediate position, avoiding the features noted in other groups. Therefore, we can assume that their estimates are the most reliable.

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Fig. 6. Expert group 3.

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Fig. 7. The range of absolute assessments given by experts of the importance of various industries.

3 Results 3.1 Research Result Thus, the final conclusion about the importance of the digital technologies development is based on Fig. 4. Table 1 shows the role determined by the analysis in the development of the economy for each digital technology considered. It can be seen that a consensus solution has been identified for most technologies. The remaining inconsistency of estimates can be solved by the traditional Delphi method [11]. According to the results obtained, the priority of the development of digital technologies becomes visible. 3.2 Applicability of the Proposed Method The authors think that the proposed peer review process has several advantages: – the structure of the relationship of factors is highlighted in the problem. It is simple enough and does not cause contradictions; – questions to experts are quite specific, which allows to hope for the reliability of answers to them;

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Table 1. Role in the digital economy development. Digital technologies

Role

Machine learning and deep learning Important Edge Analytics

Important-key

PaaS

Key

Augmented Reality

Contradictory, not low

Augmented Intelligence

Key

Immersive Workspace

Key

Synthetics Data

Important

Digital Ops

Key

Blockchain

Medium-important

IoT

Important

Drones

Medium-important

3D printing

Medium-important

5G

Important-key

– the apparatus of fuzzy values is used for calculations, which corresponds to a different degree of influence of variables on the result; – using averaged estimates reduces the risk of emissions; – absolute assessments are used to analyze experts, and relative assessments are used to identify priorities; – the method allows to deeply analyze the results of an expert survey, extracting useful information from them. Thus, this article is an example of the use of augmented intelligence to help process expert survey data. 3.3 Further Perspectives To extract additional useful information from the collected data, it is possible to analyze the responses for each of the components of the cognitive map. Some estimates of both the initial values and the interaction matrices of factors may be similar, and on other particular issues a strong variety of opinions is possible. The identification of the most differing particular answers will allow to focus the Delphi method precisely on the most dissimilar particular estimates. Having obtained the results of the proposed method, it is useful to understand the reasons for the differences of opinion. Discarding the assumption of expert incompetence, it can be assumed that the difference in the estimates is due to the novelty of the technology and the incomplete clarity of its capabilities.

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4 Discussion The results of such studies will serve as the basis for identifying end-to-end technologies for the key sectors of the economy discussed in this article. On this basis, it is proposed to build models for aligning the requirements of key sectors of Russian business with digital technologies that provide efficient digital environment for selected industries. This will allow you to target the development of technology in accordance with the requirements of stakeholders in a particular area.

5 Conclusion In this article, the method of expert estimates of complex forecasts, which is characterized by a deeper analysis of the collected data based on modern methods of artificial intelligence was considered. The results obtained made it possible to determine an expert assessment of the importance of digital technologies used in Russia, the connection of technology applicability with the trends and development trends of the Russian business environment and with key sectors of the Russian economy. Acknowledgment. The reported study was funded by RSCF according to the research project № 19-18-00452.

References 1. Ponomarev, O., Svetunkov, S.: The impact of digital economy at the entrepreneurial capital. In: Proceedings of the International Conference on Digital Technologies in Logistics and Infrastructure (ICDTLI 2019), St. Petersburg, Russia (2019). https://doi.org/10.2991/icdtli19.2019.75 2. De la Boutetière, H., Montagner, A., Reich, A.: Unlocking Success in Digital Transformations. McKinsey Co., New York (2018) 3. Zaychenko, I., Smirnova, A., Borremans, A.: Digital transformation: the case of the application of drones in construction. In: MATEC Web of Conferences, vol. 193, p. 05066 (2018) 4. Revenko, L., Revenko, N.: Global trends and national specifics of the development of a digital economy. Int. Trends Mezhdunarodnye Protsessy 15(4), 20–39 (2017) 5. McMaster Digital Transformation Research Centre. https://mdtrc.mcmaster.ca/. Accessed 28 Apr 2020 6. Khitskov, E.A., Veretekhina, S.V., Medvedeva, A.V., Mnatsakanyan, O.L., Shmakova, E.G., Kotenev, A.: Digital transformation of society: problems entering in the digital economy. Eur. J. Anal. Chem. 12(5b), 855–873 (2017) 7. Gimpel, H., Röglinger, M.: Digital transformation: changes and chances–insights based on an empirical study (2015) 8. Divina, T.V., Petrakova, E.A., Vishnevsky, M.S.: The main methods of analysis of expert assessments analysis (2019). https://doi.org/10.24411/2411-0450-2019-11072 9. Churchill, G.A., Iacobucci, D.: Marketing Research: Methodological Foundations, 10th edn. South-Western/Cengage Learning, Mason (2010)

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10. Malhotra, N.K.: Marketing Research: An Applied Orientation, 6th edn. Pearson, London (2010) 11. Linstone, H.A., Turoff, M.: The Delphi Method: Techniques and Applications. AddisonWesley, Boston (1975) 12. Bergmann, M.: An Introduction to Many-Valued and Fuzzy Logic: Semantics, Algebras, and Derivation Systems. Cambridge University Press, Cambridge (2008) 13. Borg, I., Groenen, P.J.: Modern Multidimensional Scaling: Theory and Applications. Springer, Heidelberg (2005) 14. Giarratano, J.C., Riley, G.: Expert Systems: Principles and Programming. Brooks/Cole Publishing Co., Belmont (1989) 15. Pavlov, N.: Product lifecycle management (2016) 16. Klimin, A.I., Pavlov, N.V., Efimov, A.M., Simakova, Z.L.: Forecasting the development of big data technologies in the Russian Federation on the basis of expert assessments. In: Proceedings of the 31st International Business Information Management Association Conference, IBIMA 2018: Innovation Management and Education Excellence through Vision 2020, pp. 1669– 1679 (2018) 17. Ilin, I.V., Koposov, V.I., Levina, A.I.: Model of asset portfolio improvement in structured investment products. Life Sci. J. 11(11), 265–269 (2014) 18. Borremans, A.D., Zaychenko, I.M., Iliashenko, O.Yu.: Digital economy. IT strategy of the company development. In: MATEC Web of Conferences, vol. 170, p. 01034 (2018) 19. Ilin, I., Iliashenko, O., Iliashenko, V.: Approach to the choice of Big Data processing methods in financial sector companies. In: MATEC Web of Conferences, vol. 193, p. 05061 (2018) 20. Kosorukov, O.: Forecast of separate indicators for socio-economic development of the Russian federation up to 2020. World Appl. Sci. J. 18(C), 18 (2012)

Operational and Information Technologies Within the Enterprise Architecture: Mining Industry Case Anastasia Levina(B) Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, 195351 St. Petersburg, Russia [email protected]

Abstract. Effective automation and digitalization of the business requires approaches to the formation of an integrated management system, including the IT architecture. A modern enterprise is a complex system of management technologies, operational and information technologies, the synergistic effect of the use of which allows creating an effective and flexible business structure. The aim of this paper is to present an architectural model for the integration of management technologies, operational and information technologies. The development of such a model is especially relevant in the context of the ongoing digital transformation of the business, since the introduction of digital technologies in industrial enterprises will affect both elements of business and IT architectures, as well as elements related to production technologies. The methodological basis for the integration of technologies is the architectural and process approaches. Keywords: OT vs IT · Operational and information technologies · Reference functional model · Digital transformation · Mining reference model

1 Introduction Under current trends in the digitalization of enterprises (within the framework of Industry 4.0), underestimating the role of IT architecture and the need for its design in the early stages of creating an enterprise can be detrimental to business. The role that management systems has become comparable to the value of the operations they control. Trends in digitalization and automation require enterprises (especially industrial) to efficiently, systematically and consistently introduce new methods of working with data, technologies, devices, systems and applications into existing management architectures [1]. The need to consider the enterprise management system as a single complex of business and business processes, information flows and data flows, information systems and technologies determines the role of the architectural approach in the formation and reform of management systems to improve business efficiency due to its internal structure. As such an integrated approach to the formation of a balanced and effective management system in the professional community of business analysts and IT solutions © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 158–166, 2021. https://doi.org/10.1007/978-3-030-57453-6_13

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implementers, there is an enterprise architecture concept, which proposes to consider the enterprise’s activity model as a unity of heterogeneous elements in their interconnection and interdependence [2–4]. At present, when the management and implementation of a business is not possible without IT support, the enterprise architecture model provides the necessary comprehensive vision of all aspects of the management system and allows you to combine business and IT management components into a single system [5]. Existing approaches and models of enterprise architecture do not pay due attention to the technologies of the main activity, which determine the special structure of technological processes and technological infrastructure. Technological processes, as well as business processes, are an object of automation in a modern enterprise, and therefore should be included in the composition of factors that shape the requirements for IT architecture [1]. It is possible to balance the requirements of business and technological processes (operational and managerial technologies) for an enterprise’s IT architecture by expanding the existing model of enterprise architecture, supplementing it with a cut of production technologies and linking it with other elements of the architecture. The aim of this work is the formation of an architectural model for the integration of management technologies, operational and information technologies. The development of such a model is especially relevant in the context of the ongoing digital transformation of the business, since the introduction of digital technologies in industrial enterprises will affect both elements of business and IT architectures, as well as elements related to production technologies. This requires an exhaustive presentation of all components of the enterprise management system within the framework of a single system of enterprise architecture models.

2 Materials and Methods The methodological basis of the study are: • An architectural approach to the design of an enterprise management system, including its IT architecture; • Process approach to enterprise management; The central concept of business engineering is the concept of enterprise architecture. The enterprise architecture model is designed to combine the management technology of various aspects of the business together in order to create an integrated management system. The architecture of the enterprise in its modern sense appeared as an answer to the problems of aligning the requirements of business and IT infrastructure (according to [4–7]). The development of information technology has made IT systems an integral part of almost any enterprise. The use of information systems and technologies in business reduces the operational time, increases the efficiency of operations, and increases the effectiveness of decision support systems. The answer to the problems of matching business requirements and IT capabilities was the concept of enterprise architecture. Currently, enterprise architecture is widely used as a systematic management approach, meaning by this term the totality of various elements of the management structure and the relationships between them (various definitions can be found in [4–8]).

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The process approach has long been widely used both in business management and automation [9, 10]. The proven and generally recognized methodology for the implementation of information systems based on the process approach is that the following steps are successively implemented [10]: 1. 2. 3. 4. 5.

Inspection of enterprise processes; Analysis of enterprise processes; Reengineering of enterprise processes, if necessary; Formation of requirements for IT support services; Development of information systems in accordance with the requirements of the processes.

This automation methodology meets the principles of a systematic approach to the design of an enterprise management system: elements of a management system (processes and information systems) are designed in interconnection and interdependence with each other and can subsequently be modified depending on changing requirements [11–14].

3 Results 3.1 Management, Operational and Information Technologies Within the Enterprise Architecture The enterprise’s processes for creating an integral client product can be divided into two groups: the first group – processes aimed at building the product itself, which can be used for its functional purpose, the second group – processes that create additional product value. An analysis of the existing definitions of business and technological processes suggests that, explicitly or implicitly, the concept of “technological process” appeals to the ability of an enterprise to create a product itself that meets the requirements for its functional use, the concept of “business process” to the ability to create a consumer product values [1]. The following definitions need to be introduced: An operational (technological) process is a set of interrelated activities aimed at creating a product using a certain technology that can fulfill its functional purpose. A production process is a set of interrelated technological, auxiliary and natural processes aimed at the manufacture of certain types of products in a given quantity and a given property, in a given quality and assortment at specified times. A business process is a stable, focused set of interrelated activities aimed at creating the consumer value of a product. In the introduced definitions, a clear distinction is made between the concepts of technological, production and business process. The first is aimed at creating individual products and is determined by the technologies of a particular type of activity, the second - at creating a complete consumer product in accordance with business requirements (formulated in the production program, production plan, etc.), the third – at creating consumer value. The definitions also show the inextricable relationship of these concepts.

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The first type of processes relies on production technologies, the second – on a combination of production technologies and process control technologies, the third – on management technologies. The proposed terminology is applicable not only to industrial enterprises, but also to enterprises of other fields of activity. The proposed separation of processes into technological, production and business processes is actively used in the design of information systems [10] and is reflected in the allocation of various levels of information systems: industrial control systems, MES, ERP & BI (Fig. 1). However, a clear terminological difference between the types of processes in the design of information systems is not proposed - this is done in the present work (see definitions above).

Fig. 1. Process types vs information systems levels.

A separate role in the context of this paper is played by the types of technologies used in the implementation of activities and the management of the activities of a modern enterprise: management technologies, operational technologies, information technologies. Taking into account the trends of the concept of the fourth industrial revolution, the issue of the integration of operational and information technologies (OT vs IT) is often raised in scientific and professional publications [2]. It is necessary to include management technologies in this circuit: the integration of these three technologies among themselves and their coordinated application are one of the key factors for a successful transition to a new way of doing business [1, 11, 12]. In this regard, it is important to precisely define the terminology in relation to types of technologies for the purposes of this work: Management technologies are a set of techniques and methods for implementing the management function at the enterprise, including the generation of information necessary for making management decisions, making and monitoring the implementation of such decisions.

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Operational technologies (for manufacturing enterprises – production technologies) are a set of techniques and methods for implementing the core business of the enterprise (production of goods or the provision of services). It is important to note that the term operational technologies in the context of the fourth industrial revolution often refers to the production technologies used at industrial enterprises. In the pre-sent work, this term is used in a broader sense and includes technologies for the implementation of the main activities of any enterprise, not only industrial. Information technology (also information and communication technology, IT, ICT) are a set of techniques and methods for using automated means of computer and communication technology to collect, store, process, analyze, transfer and use data. (The definition is based on an analysis of terminology proposed in [10, 15, 16]). In Fig. 2, the structure of management technologies is reflected in the business system, in operational technologies - in the production and technological system, in information technology - in the information system. Figure 3 reflects the integration model in a single complex of management technologies, operational and information technologies. 3.2 Mining Industry Case This section describes an example of the integration of operational and information technologies of a mining enterprise based on an architectural approach. The mining industry of Russia is in constant development. This industry makes a significant contribution to the country’s economy; therefore, the efficiency of enterprises in this industry is a direct interest of both business and the state. A modern mining enterprise is a highly automated facility that requires large investments in research on the development of effective business management solutions, as well as in IT infrastructure facilities. The implementation of operational mining technologies involves the creation and operation of colossal volumes of production infrastructure (a mine, a mining plant, a transport and logistics infrastructure serving the infrastructure, utilities, etc.). In modern conditions, all objects of this infrastructure require proper automation, which allows you to receive data on the technological and production processes implemented at these objects in real time, makes it possible to quickly process and analyze them, which ultimately allows you to take timely and effective solutions for managing processes and the whole complex. The formation of the IT architecture of the mining enterprise in the proposed example occurred according to the following algorithm: 1) The functions of the mining enterprise have been identified (operating technologies and management technologies); 2) The classes of information systems that automate the selected functions and form the IT architecture (information technology) are defined. The analysis of the activities of mining enterprises and the development of an approach to functionally oriented design of their architecture was carried out in cooperation with Russian mining companies, design institutes and IT consulting companies involved in the design and automation of mining enterprises and wide known models [17].

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As a result, a list of functions of the mining enterprise was highlighted and a reference functional model was developed (Fig. 2).

Financial management

Accounting and reconciliation

IT Management

Marketing and sales

Customer relationship management

Personnel Management

Logistics

Land management

Product Lifecycle Management

Preparation for deposit development

Value chain

Optimization of production operations Production planning

Sort and mixing Mining Intramine transportation

Engineering Engineering design Research work

Warehousing

Waste management

Melting

devDepo elo sit pm ent

Rights management

Affinage

Exploration Product processing

Object definition

Manufacturing execution management

Enrichment

Processing

Enterprise management

Strategic management

Infrastructure production support

Fleet management

Material management

Asset Management Production management

Fig. 2. Reference model of mining business functions.

The reference model, shown on the Fig. 2, consists of 3 levels of functions: enterprise management and manufacturing execution management levels represent management technologies of the enterprise, value chain level – operation technologies. Both of them need a certain IT support by the information systems of a certain hierarchy and functionality level: ERP, MES, SCADA systems [15, 16]. Value chain functions fulfil a certain part of a final product on a particular stage of the operations, while management functions support the operation throughout the whole lifecycle. The appropriate levels of IT systems for each functional module of the IT architecture of the mining enterprise are shown in Table 1. The model of functions of a mining enterprise and its IT architecture proposed in Table 2 can be considered as a reference model for automation and a basis for the requirements for the functional structure of the information systems.

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№

Mining enterprise functions

Level of IT systems

1.

Object definition

–

2.

Exploration

MES (incl. BIM, GIS)

3.

Rights management

ERP

4.

Research work

MES (incl. BIM)

5.

Engineering design

MES (incl. CAD, BIM)

6.

Engineering

MES

7.

Production planning

MES

8.

Optimization of production operation

MES

9.

Mining

MES – operations management SCADA – technological processes real-time management

10.

Intra-mine transportation

MES – operations management SCADA – technological processes real-time management

11.

Sort and mixing

MES – operations management SCADA – technological processes real-time management

12.

Enrichment

MES – operations management SCADA – technological processes real-time management

13.

Melting

MES – operations management SCADA – technological processes real-time management

14.

Affinage

MES – operations management SCADA – technological processes real-time management

15.

Product processing

MES – operations management SCADA – technological processes real-time management

16.

Warehousing

MES – operations management and planning SCADA – real-time management

17.

Waste management

MES – operations management SCADA – technological processes real-time management

18.

Fleet management

MES

19.

Material management

ERP – strategic management MES – tactical control (continued)

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(continued) №

Mining enterprise functions

Level of IT systems

20.

Infrastructure production support

MES – operations management SCADA – real-time management

21.

Assets management

ERP MES

22.

Production management

MES – operations management SCADA – technological processes real-time management

23.

Logistics

ERP – strategic management and planning MES – operations management and planning

24.

Accounting and reconciliation

ERP – strategic management and planning MES – operations management and planning SCADA – real-time management

25.

Customer relationship management

ERP

26.

Marketing and sales

ERP

27.

Financial management

ERP

28.

Personnel management

ERP

29.

IT management

ERP

30.

Product lifecycle management

ERP MES

31.

Land management

ERP

32.

Strategic management

BI ERP

4 Conclusion and Discussion This paper proposes a model for integrating management technologies, operation-al and information technologies within a single enterprise management system. The model is generic, but it is of particular relevance for industrial enterprises. The application of the developed model is demonstrated by the case of the mining industry. The paper proposes a reference model of the functional structure of a mining enterprise and a reference set of functional modules of the corporate information system. Such a model with a certain adaptation to the conditions of a particular enterprise is the basis for the enterprise management system, including its IT architecture. For example, a mining enterprise often does not independently implement the entire cycle of creating the final product – the functions associated with the design of the enterprise are performed by specialized engineering companies. In this case, this part of the functions and modules of information systems, that automate them, will be implemented in an engineering company. But even in this case, it is important to ensure the continuity of the value

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chain, including the possibility of integrating information systems of various enterprises that create this value. The direction of further research in terms of technology integration in enterprise architecture will be the development of industry reference models. It is also important to research end-to-end digital technologies of specific industries and develop approaches to their implementation into the enterprise architecture model.

References 1. Levina, A., Borremans, A., Burmistrov, A.: Features of enterprise architecture designing of infrastructure-intensive companies In: Proceedings of the 31st International Business Information Management Association Conference, IBIMA, 2018, pp. 4643–4651 (2018) 2. Adina, A., Iacob, M.-E., Wombacher, A., Hiralal, M., Franck, T.: Enterprise Architecture 4.0 – a vision, an approach and software tool support. In: 2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC), 2018, pp. 1–10 (2018). https://doi.org/ 10.1109/EDOC.2018.00011 3. Janssen, T.: Enterprise Engineering: Sustained Improvement of Organizations. Springer, Heidelberg (2015) 4. Lankhorst, M.: Enterprise Architecture at Work: Modelling, Communication and Analysis, 3rd edn. Springer, Heidelberg (2013) 5. The Open Group, TOGAF Version 9.2. http://pubs.opengroup.org/architecture/togaf92-doc/ arch/. Accessed 21 Apr 2020 6. Op’t Land, M., Proper, E., Waage, M., Cloo, J., Steghuis, C.: Enterprise Architecture. Creating Value by Informed Governance. Springer, Heidelberg (2008) 7. Zachman, J.: The Zachman Framework for Enterprise Architecture. Zachman International (2005) 8. Hoogervorst, J.A.P.: Practicing Enterprise Governance and Enterprise Engineering: Applying the Employee-Centric Theory of Organization. Springer, Heidelberg (2018) 9. Weske, M.: Business Process Management: Concepts, Languages, Architectures, pp. 305– 343. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-73522-9 10. Laudon, K.C., Laudon, J.P.: Management Information Systems: Managing the Digital Firm. Pearson, London (2017) 11. Ilin, I., Levina, A., Lepekhin, A., Kalyazina, S.: Business Requirements to the IT Architecture: a case of a healthcare organization. In: Energy Management of Municipal Transportation Facilities and Transport, pp. 287–294 (2018). https://doi.org/10.1007/978-3-030-19868-8_29 12. Ilin, I.V., Frolov, K.V., Lepekhin, A.A.: From business processes model of the company to software development: MDA business extension, In: Proceedings of the 29th International Business Information Management Association Conference, pp. 1157–1164 (2017) 13. Anisiforov, A., Dubgorn, A., Lepekhin, A.: Organizational and economic changes in the development of enterprise architecture. In: E3S Web of Conferences, vol. 110, p. 02051. EDP Sciences (2019). https://doi.org/10.1051/e3sconf/201911002051 14. Zaychenko, I.M.: Analysis of digital business transformation tools. In: Proceedings of the 33rd International Business Information Management Association Conference, pp. 9677–9682 (2019) 15. IEC 62264-1:2013, Enterprise-control system integration. Part 1: Models and terminology’, ISO (2013) 16. IEC 62264-3:2007, Enterprise-control system integration. Part 3: Activity models of manufacturing operations management’, ISO (2007) 17. The Open Group, The Exploration & Mining Business Capability Reference Map: Concepts and Definitions. https://publications.opengroup.org/c143. Accessed 21 Apr 2020

Assessment of Digital Maturity of Enterprises Igor Ilin , Daria Levaniuk , and Alissa Dubgorn(B) Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, 195251 St. Petersburg, Russia [email protected]

Abstract. The paper covers the issue of enterprise digital maturity assessment. This issue is relevant for modern enterprises being in the process of digital transformation. The tendency of the information community towards a qualitative change in organization management determines the development of the economy, increasing labor efficiency and improving the quality of life. Enterprises need to understand how to conduct business in changing conditions, what strategies and management methods to use in order to further maintain their competitiveness. Knowledge of the enterprise digital maturity level allows implementing and improving existing processes in order to become more attractive from the digital point of view. The paper represents a detailed analysis of enterprise maturity assessment methodologies as well as their key points, main advantages and limitations. Describing the basics of the project management approach, a rationale for the transition from process maturity assessment to digital assessment was proposed. The main purpose of the paper is to analyze existing approaches to assessing the digital maturity of an enterprise, determine their applicability and limitations, and identify further research. Keywords: Digital maturity · Digital transformation · Digital technologies · Enterprise development · Enterprise assessment models · Company culture and strategy · Business models development · Business process development

1 Introduction In the 21st century, it has become technologically possible to make a quantum leap in the development of many industries. But digital transformation requires an adequate level of enterprise reengineering. Therefore, it is important to understand its readiness to implement some technological projects. In turn, the degree of readiness is largely determined by the maturity of the business - the plan for the transition of the enterprise to digital models of implementing activities will depend on this. This paper represents an analysis of approaches to determining the maturity and digital maturity of an enterprise, to determine the limitations of existing approaches, to identify key factors that (in accordance with these approaches) determine the readiness of an enterprise for digital transformation processes. Fast-growing companies and world leaders are forced to resort to digitalization, the integration of modern technological products and services, the transformation of all © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 167–177, 2021. https://doi.org/10.1007/978-3-030-57453-6_14

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processes and operational activities, cooperation, as well as improving the quality of customer service in order to maintain their competitiveness [1]. It includes the introduction of modern technologies and approaches into the company’s business processes. This means not only a change of equipment to a new high-tech, but also a purposeful change in management approaches, company culture and partnership, and gaining customer focus. The analysis of activities, the compilation of work algorithms makes it possible to increase the speed of work, to optimize existing business processes and create new ones, thereby securing the company’s reputation as modern and progressive in the global market. As each company refers to its own development stage and has a specific business processes system, there is no single algorithm for the digital transformation. It is necessary to conduct a comprehensive analysis of the use of information technology in the activities of the company, considering both internal processes and interaction with the environment, customers, competitors and partners.

2 Materials and Methods The paper is based on the analysis of existing approaches to the assessment of maturity and digital maturity and summarizes the data obtained from various sources. This section will briefly describe the methods that companies use in project management and strategy development. 2.1 Digital Maturity Definition The concept of “digital maturity” helps to understand what processes and models are in need for transformation, as well as at what stage of development the company is currently located. In this paper there are several descriptions of this term: Digital maturity is about adapting the organization to compete effectively in an increasingly digital environment. It is about implementing new technologies by aligning the company’s strategy, workforce, culture, technology, and structure to meet the digital expectations of customers, employees, and partners. Digital maturity is, therefore, a continuous and ongoing process of adaptation to a changing digital landscape [2]. Digital maturity is a combination of two separate but related dimensions. The first, digital intensity is investment in technology-enabled initiatives to change how the company operates – its customer engagements, internal operations, and even business models [3]. Firms maturing in the second dimension, transformation management intensity, are creating the leadership capabilities necessary to drive digital transformation in the organization. Transformation intensity consists of the vision to shape a new future, governance and engagement to steer the course, and IT/business relationships to implement technology based change [4]. Digital maturity represents a systematic way for an organization to transform digitally [5]. Hence the term specifically reflects the status of a company’s digital transformation. It describes what a company has already achieved in terms of performing transformation efforts and how a company systematically prepares to adapt to an increasingly digital

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environment in order to stay competitive. Digital maturity goes beyond a merely technological interpretation simply reflecting the extent to which a company performs tasks and handles information flows by IT, but also reflects a managerial interpretation describing what a company has already achieved in terms of performing digital transformation efforts including changes in products, services, processes, skills, culture and abilities regarding the mastery of change processes [6]. There is no general approach to assessing digital maturity. But in the described terms there are similar statements that define the “digital maturity” term. To sum up, digital maturity determines the ability of company’s processes to adapt to environment of new digital technologies implementation. 2.2 Maturity Models The digital maturity of a company directly depends on the overall maturity of the company, and the digital models are based on the maturity process models of the companies. By defining a company’s maturity model, it becomes possible to analyze the process’s readiness for changing not only in the management of processes, but also in a digital environment. Evaluation of maturity model levels helps to understand better how digital maturity levels can depend on enterprise maturity. The maturity of the company can be represented in the form of stages, which also have some variability, but have common features. In Russia various maturity models are used to assess enterprise maturity level: • • • • • •

SW SMM; integrated CMMI model; standard ISO 15504; Maturity Model COBIT 4.1 (COBIT Process Assessment Model, PAM); ORMZ model (PMI community); model SPICE (Software Process Improvement and Capability determination) etc.

For compiling a general picture of existing methodologies let us consider in more detail some of them for determining the maturity of companies. CMM and CMMI Models. The most popular model is the CMM (Capability Maturity Model for Software), which describes the maturity of software development processes in enterprises, developed by the Software Engineering Institute (USA). The success of the idea lies in the simplicity of understanding, the practicality of applying the model, and effective promotion from one level to another with significant changes in the quality of products. This model is focused on optimizing price-quality compliance. In the process of development, the model was finalized and received the name CMMI (Capability Maturity Model Integration), which differs in some details, but retains the basic principles of CMM, discreteness of gradations of maturity, focus on the project business (see Table 1) [7].

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CMMI

1

Initial

Initial

2

Repeatable Repeatable

3

Defined

Defined

4

Managed

Quantitatively managed

5

Optimizing Optimizing

The integration of models resulted in a five-level methodology for determining the maturity of enterprises. • • • • •

Level 1 - Initial. Level 2 - Managed. Level 3 - Defined. Process engineering. Level 4 - Quantitatively Managed. Level 5 - Optimized (Optimizing).

Having determined the maturity level of the company in the field of digital transformation, it is already possible at the first stage to form a list of changes in the organization to adapt it in a changing world both in the external and internal environment. Achieving the desired level is possible only with a clear description of the further strategy for achieving the required state. Disadvantages: – The need to “align” all the processes of organizations to the requirements of the SMM, even though the processes of the organization did not require the fulfillment of certain requirements. – The standard began to be used as a selection criterion for participation in tenders for software development or in outsourcing projects. The demand for certified organizations has created a proposal for “quick and painless certification”. Advantages – A quality model specifically related to the software development process; – CMM is a large, multi-stage quality standard covering the entire software development cycle: from design to implementation. It is suitable for optimizing and improving the quality of released software. Maturity Model COBIT 4.1. International Standard ISO/IEC 15504. Initially, in practice, it turned out to be difficult to implement and did not give a definite understanding of the state of the company. So, processes could have signs of different levels, not even going in a row, which happened with attributes, making it difficult to assess the level at which the company is located. This led to the loss of the holistic look of its digital maturity [8].

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The model was improved and began to be based on the international standard ISO/IEC 15504 “Information technology - process assessment”. International Standard defines process evaluation as a complete process optimization program or as part of process capabilities. Process optimization means a continuous increase in productivity and the application of rational methods in an organization. Determining the capabilities of processes according to the standard is the correct representation of potential opportunities from ongoing processes. This standard also involves five levels of digital maturity of the company, which directly depends on the maturity of the processes taking place inside. Level 0. Incomplete process. When processes are underway, but have not yet reached it. There is no single base for systematic approaches to standard processes. Level 1. Implemented process. Achieving processes at the final stage of their appointment without the use of special management methods. Level 2. Managed process. The processes to be carried out are planned in advance, then subsequently regulated. Process monitoring is carried out, the compliance of the developed product or service with the intended goals is checked. Level 3. Installed process. A base of basic processes is being formed, which are standardized and have common control algorithms. The described processes are used at all stages of the project, but are individually finalized during the execution for the purpose of the developed product. Level 4. Predictable process. The results of the processes at this stage are predicted and known in advance. Achieving certain results is easily managed and controlled. Level 5. The optimizing process. Predictable processes are constantly improving to achieve business goals. The levels are arranged in such a way that it is impossible to skip or skip one of them, the transition through the levels is carried out in order. If the company decides to skip several levels, then the simultaneous implementation of several optimization tools can lead to unpredictable consequences, jeopardizing the entire project activity of the company. Each maturity level forms the basis for the rational and efficient implementation of processes at the following levels. Nevertheless, organizations can use and receive benefits from the implementation of processes characteristic of higher maturity levels in comparison with the achieved ones. All changes associated with maturity need not be consistent. At every level implementation process, implementation management, work product management, definition, deployment, measurement, control, innovation, optimization processes are at different levels of achievement. Levels are determined by the achievement of process attributes. N - Not achieved - 0%–15% achievement. H - Partially achieved - 15%–50% achievement. B - Mostly achieved - 50%–85% achievement. P - Fully achieved - 85%–100% achievement.

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COBIT focused on the audit of IT processes than on the audit of specific functions or applications. Disadvantages: – An excess of poorly defined terms, unnecessary “formal” reasoning used to explain obvious things, and superficiality of presentation; – The hierarchy of management goals plays a decorative role: no specific tasks associated with this hierarchy are posed and no special teaching methods are used; – No holistic view of company maturity. Advantages: – Flexible and convenient assessment tool, compatible with the international standard ISO 15504; – Ability to supply processes with attributes of ISO 15504; – Certification Requirements (including Audit); – Requirements for the Appraiser and His Experience. The maturity methodologies of process approaches are constantly changing and new models are emerging such as SGMM, Model OPM3 (Project Management Institute, PMI), BPMM, etc. All approaches have their own characteristics and various criteria but most of them have 5 determined levels of maturity. By this way, digital maturity models have the same specification [9].

3 Results 3.1 Digital Maturity Models There is a close connection between the transition from the process level of maturity to a digital one. The company’s readiness for technological transformation is determined by assessing the level of compliance with fundamental processes and their management, methods of using the accumulated information. By determining the maturity level of the management system, it can characterize the stage of the company’s readiness for digital transformation, identify the company’s potential for development, and choose the direction of modernization and growth. The company which is operating effectively achieves a stable state in the global market and has a high index of readiness for digital transformation [10]. Moreover, leadership of such companies is able to identify weaknesses that need improvement and innovation through IT technology, organize monitoring of changes in the environment, increase satisfaction of the needs and expectations of stakeholders, and structure goals. An analysis of existing and popular maturity models is the basis for creating a digital maturity model. This article discusses one of the proposed models (Table 2). This model as well as the maturity model of the company describes levels of digital maturity of companies, provides a description of the state of processes, technologies, also the level of organization of employees in the company. Thus, it allows to accurately determine the stage at which the company is currently located and whether it was preparing for digital changes.

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Table 2. Digital maturity model. Maturity level

Processes

Technology

Employees

Level 5

Development of processes for autonomous decision-making by systems; Development of processes for regular forecasting and planning of future production

Integration with external data of suppliers and customers; The use of artificial intelligence systems

Development of a culture of continuous improvement and innovation; Implementation of responsible persons for the corresponding direction of predictive analytics and adaptability

Level 4

Development of audit processes of historical and current data and the use of the obtained information for optimization; Introducing procedures for regular optimization initiatives

Real-time implementation of systems for analyzing activities that automatically perform analytics, generate warnings and recommendations; The introduction of digital counterparts for testing prototyping and optimization

Organization of cross-functional sessions and data exchange sessions to work on current problems and optimization methods based on new data; Attracting additional data analysts

Level 3

Formalization of data flow control processes Creation of processes for the active exchange of knowledge and data between all project participants; Creation of a cross-functional data exchange network

Improving data accuracy, reducing the amount of useless information; Implementation of data mining systems; Integration of data exchange systems

Training employees to work with system data, various devices and interfaces; Development of “Digital” skills; Developing a Knowledge Management Culture

Level 2

Formalization of the implementation processes of the “digital plant” Outsourcing processes for connectivity

Study of the directions of integration of existing systems and technologies with future elements of the “digital factory” Formation of a single information space and data flows, connection of systems

Involvement of employees in the development of the target vision; Separation of roles and areas of responsibility, attraction of employees with competencies in business, IT and production

Level 1

Elimination of paper forms and media, execution of processes through system interfaces Data Automation

Implementation of basic production and enterprise management systems; System Integration for Automatic Data Transfer

Trained employees and their areas of responsibility

Level 0

No direct impact on processes

Creating infrastructure for subsequent implementations of industrial Wi-Fi, local area networks

No additional digital competencies required for employees

Based on the previously described methodologies, a model of digital maturity of companies, by analogy with the process, includes 5 levels [11]: • Level 0. Basic infrastructure. Technologies that do not produce business effects in themselves, but are necessary for the introduction of advanced technologies. • Level 1. Computerization. The process is automated by some IT system. Data entry into the system is carried out manually. • Level 2. Connectivity. The operational data of the process enters the system automatically, without human intervention. Integrated related systems. The control action is carried out remotely.

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• Level 3. Transparency. Key process indicators are visualized and tracked in real time. • Level 4. Predictability. Predictive systems have been introduced to predict the future state. • Level 5. Adaptability. Systems have been introduced that have a corrective effect on equipment independently or as part of a corporate system to maximize efficiency. To achieve the highest level or transition from one to another, two approaches have been singled out. 3.2 Replication of Existing Tools It is assumed that the company uses basic digital tools that give positive results, or there are developments for future implementation with a high level of versatility that can be applied to most standardized enterprise processes. Stage 0. Preparation. At this stage, there is an analysis of all the digital tools that are already used in the company or can be offered for implementation, a description of their potential effect, analysis and distribution by maturity levels, the formation of technical conditions. Stage 1. Determination of the current maturity level by units, digital technologies used in production. During the stage, a list of tools used at the enterprise, their effectiveness, as well as the definition of new ones in accordance with maturity levels is determined, parameters for evaluating the success of their implementation are highlighted. The distribution of technologies by maturity levels can be represented as follows: • • • • •

Level 1. Computerization Level 2. Connectivity Level 3. Transparency Level 4. Predictability Level 5. Adaptability

The result is an understanding of the level of digital maturity, determining the degree of success of planned implementations and existing tools. Stage 2. Formation of the target level of maturity of the unit and the mapping of the transition to it. Based on the previously compiled register of instruments, a basis is formed for moving to a new level and is framed in the form of a roadmap for implementation (usually for 3–5 years). The quantitative results of achieving the target level for each of the departments of the company are outlined. This approach requires the transformation of processes in individual production sections of the enterprise. It should be remembered that they can simultaneously have different levels of maturity. Thus, a transformation takes place based on the replication of digital tools that have been introduced and need to be further developed, or have been considered by management as planned implementations with a definite result for the enterprise.

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3.3 The Process Approach to Creating a Digital Transformation Program A second approach is proposed for the improvement and implementation of IT technologies in enterprises, which is based on a detailed analysis of processes up to operational activities. New modern technologies are taken as the basis of optimization. At levels 1–3, groups of processes are defined, from which sequences of business chains with input and output data are formed, a deep decomposition of all business processes occurs. This allows you to determine the boundaries of the enterprise’s business, the relationship of processes and functional features. To write the technical specifications for the implementation of the software, compile a user manual, and formulate standard operating procedures at levels 4–5, a detailed analysis of the steps of each process and the actions of the user group contained in the business model takes place [12]. Stage 0. Identification of the main processes for digital transformation. Includes analysis of end-to-end business processes, IT infrastructure of the company, discussion of the company’s activities and its goals with senior management. The implementation of the stage gives a detailed description of the existing processes and the level of use of IT technologies in them, identifying potentially problematic places. Stage 1. Advancing optimization measures. Evaluation of the current labor costs of processes and their efficiency, comparing the data obtained with world market leaders, identifying priority areas for development and optimization hypotheses [13]. As a result, the company receives a detailed report on the course of business processes, a comparative assessment of process activities with international practices, and quantitative indicators of the cost of optimization processes. Stage 2. Evaluation and detailed study of the proposed optimization solutions. It contains the development of top-level business processes to-be models, the definition of functional requirements for IT systems. Also, at this stage, a ranked list of initiatives to improve the company’s activities is being formed taking into account the assessment of the effect of their implementation. Stage 3. Formation of the optimization program. A to-be model of business processes is compiled in accordance with the selected modeling methodology, an optimization program and a pool of recommendations for automating specific processes are formed, all functional and non-functional requirements for the implemented IT systems are written, and a quantitative business case for each project is developed and calculated [14]. Thus, the output is a detailed program for digital transformation of the main processes to increase the efficiency of the enterprise.

4 Discussion It is possible to present the advantages and disadvantages of each of the approaches in the form of a Table 3: It should be noted that both approaches are practically applicable and are chosen by the company depending on its transformation tasks and the level of digital maturity. One more feature can be noted - this is the application of the described approaches to digital transformation at the same time, analyzing both the instrumental basis of the company and internal business processes.

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Advantages

Disadvantages

Replication of existing tools + Quick start of digital asset transformation; + Intensive use and development of existing digital tools; + Transparency and comprehensibility of the expected effects due to the lower degree of unknown

— Potential loss of benefits associated with insufficient diving; — High requirements for the quality of existing tools and implementation team; — Amount of problems may not be resolved

The process approach to creating a digital transformation program + Detailed study of a wide range of processes; + Orientation to real problems; + Potentially high effects if significant labor-intensive processes are detected that could potentially be automated; + Revision and updating of the process model; + Third-party effects expressed in detecting organizational problems

— High complexity of the stages, especially the stage of the diagnostic examination; — High qualification requirements of the methodologists conducting the research and the methods used; — Significant distraction of employees at the stages of diagnosis; — Delaying the start of digital transformation until the end of the diagnosis

5 Conclusion To achieve enterprise strategic goals and results, to determine an effective strategy, it is necessary to understand the state of maturity of the company. There are special methodologies that provide an assessment and description of models of digital maturity, divided into appropriate levels. This paper examined several models having 5 maturity levels. It can also be noted that CMM (CMMI) is based on three basic principles that also apply to the ISO 15504 standard. The maturity of an enterprise is determined by five levels, which depend on the specific criteria applied to both the developing and implementing systems of the company. The objective of each organization is to move from a lower level to a higher one in order to maintain competitiveness, increase productivity and improve the quality of developed products or services. An analogy of the process model of the enterprise maturity level with the digital one was carried out in this paper. Five levels of digital maturity are defined, and digital transformation campaigns are also considered. A number of differences between them were noted in the paper. The replication approach of the tools and developments used is considering the formation of a digital transformation program “from top to bottom”, as well ad considering existing technologies and adapting them to some specific tasks. In this case, the effect is

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obtained in any case, so technologies that have positive results are used. However, problematic points may be missed with such principles, the elimination of which requires development completely from scratch, which leads to significant costs. The process approach is defined in the opposite way to the “bottom – up” approach as a more fundamental. It identifies problems that need to be addressed. To do this, we have to do a detailed analysis of the enterprise’s business process model and diagnose the levels at which they are located. Thus, knowledge about the level of digital maturity, assessment of readiness for digital transformation, application of certain approaches to optimize activities help management in making managerial decisions for successful business development.

References 1. Gileva, T.: The digital maturity of the enterprise: the method of assessment and management. Bull. USPTU Sci. Educ. Econ. Ser. Econ. 1(27), 15 (2019) 2. Kane, G.C., Palmer, D., Phillips, A.N., Kiron, D., Buckley, N.: Achieving digital maturity. Adapting your company to a changing world. research report. MIT Sloan Manag. Rev. 59(1) (2017) 3. Dubgorn, A., Abdelwahab, M.N., Borremans, A., Zaychenko, I.: Analysis of digital business transformation tools. In: Proceedings of the 33rd International Business Information Management Association Conference, IBIMA 2019: Education Excellence and Innovation Management through Vision 2020, pp. 9677–9682 (2019) 4. Westerman, G., Tannou, M., Bonnet, D., Ferraris, P., McAfee, A.: The digital advantage: how digital leaders outperform their peers in every industry. MIT Center Dig. Bus. Capgemini Consult. 2, 2–23 (2011) 5. Zaychenko, I., Smirnova, A., Kriukova, V.: Application of digital technologies in human resources management at the enterprises of fuel and energy complex in the far north. In: Advances in Intelligent Systems and Computing, vol. 983, pp. 321–328 (2019). https://doi. org/10.1007/978-3-030-19868-8_33 6. Teichert, R.: Digital transformation maturity: a systematic review of literature. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 67(6), 1673–1687 (2019). https:// doi.org/10.11118/actaun201967061673 7. Silkina, G.: From analogue to digital tools of business control: Succession and transformation. In: IOP Conference Series: Materials Science and Engineering, vol. 497, no. 1, p. 012018 (2019). https://doi.org/10.1088/1757-899x/497/1/012018 8. Afanasenko, I.D., Borisova, V.V.: Digital Logistics: Textbook for universities. Publishing house “Peter”, Bern (2018) 9. Lipaev, V.V.: Software Engineering: Methodological Foundations. Directmedia Publishing House (2015) 10. Moorthy, V.: CMMI High Maturity Hand Book. CreateSpace Independent Publishing Platform (2015) 11. Ilin, I.V., Koposov, V.I., Levina, A.I.: Model of asset portfolio improvement in structured investment products. Life Sci. J. 11(11), 265–269 (2014) 12. Van Haren, P.B.: COBIT® 5 - A Management Guide (2012) 13. Digital Maturity Model. Achieving digital maturity to drive growth. Deloitte Development LLC (2018). https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Tec hnology-Media-Telecommunications/deloitte-digital-maturity-model.pdf. Accessed 15 Apr 2020 14. Tarasov, I.V.: Approaches to developing a strategic program of company’s digital transformation. In: Strategic Decisions and Risk Management, pp. 182–191 (2019)

Design Theory of Network Based Smart Self-Contained Self-Rescuer with Sensor Technology Valery Matveykin1,2 , Valery Samarin1 , Vladimir Nemtinov2 Boris Dmitrievsky2 , and Praveen Kumar Praveen3(B)

,

1 Corporation «Roshimzaschita», 19 Morshanskoe Highway, Tambov 392000, Russia 2 Tambov State Technical University, 106 Sovetskaya Street, Tambov 392000, Russia 3 AGG Lifesciences and Safety Solutions LLP, 1102 Lodha Supremus, Powai,

Mumbai 400072, India [email protected]

Abstract. The article describes the use of a Self-Contained Self-Rescuer and the results obtained in the field tests of the SCSR (Model SHS-30E) manufactured by Corporation Roshimzaschita, performed in the mines of India. The results state that a 30-min duration SCSR can run for longer periods of time. Actual time of protection varies from person to person depending on their breathing pattern, physical and respiratory health. In the case of emergency, it is difficult to assess the actual time of protection of miners who are making self-rescue to the surface, the fresh air base or to the Refuge Chamber from the workplace in a mine. A Rescue Team does not always have data on the condition of the miners stuck underground in case of emergency. To prepare for these situations, such a SCSR is required that can be used in case of underground emergencies and can provide its users with navigation guidelines, health parameter monitoring and help the rescue team to reach the miner. The SCSR presented in the article allows solving the aforementioned safety problems, which is becoming a necessity and can be observed by the field tests at the Mines Rescue Station, M/s Western Coalfields Limited, Nagpur, India. Keywords: Self-Contained self-Rescuer · Wearable devices · Wi-Fi · Miners · Rescue · Fatigue · Cardio-respiratory health · Network · PPE

1 Introduction A Self-Contained Self-Rescuer (commonly known as SCSR) is an apparatus being used by miners to evacuate from the underground mines in the case of emergency. Various types of SCSRs, extensively discussed in paper [1], are available on the market, and the most common type is a Chemical Oxygen based SCSR in which Potassium Superoxide (KO2 ) is used to generate Oxygen (O2 ) and to scrub Carbon Dioxide (CO2 ) as well. It has got a long shelf-life and can be used up to 10 years. It can be a bodily worn apparatus, © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 178–186, 2021. https://doi.org/10.1007/978-3-030-57453-6_15

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or it can be placed at strategic locations inside the mines, so that it can be used in case of emergencies. This apparatus is being used globally in underground mines including India. In India, this apparatus and its working principle is governed by Indian Standard IS 15803:2008 and the guidelines defined by Directorate-General of Mines Safety (DGMS) (The Regulatory Authority for Mines in India as per the Mines Act 1952). Similar type of apparatus, but containing unique enhancements, Model SHS-30E is being manufactured by Corporation Roshimzaschita, Tambov, Russian Federation which has been approved by DGMS (India) and complies with the Indian Standard IS 15803:2008. It is a 30-min duration SCSR. Currently, SHS-30E is the lightest SCSR, available on the market in its category. It weighs only 1.8 kg and the nearest competitor - 2.5 kg, providing 700-grams lighter weight. With the results in Table 1, it can be noted that despite of its low weight, it is not only successfully achieving the purpose, but exceeding the requirement [1–3]. With the advancement in the technology and changes in the dynamics of human working behavior and the nature of work which is being performed by the miners, a new intuitive, smart like latest hi-tech gadgets, SCSRs need to be designed in such a way, that they can virtually communicate with the user, understand their requirements and stress levels during an escape in case of emergency, and act as a companion to miners during their most difficult times, by at the same time comply with all the norms and the standards for SCSRs. The aim of this paper is to give a detailed description of the Novel SCSR apparatus based on SHS-30E and assumptions postulated to design such Novel SCSR from the results and the experience of its field tests at the Mines Rescue Station, M/s Western Coalfields Limited, Nagpur, India.

2 Assumptions for the Design of New IOT and Network Based Smart SCSR Leak Tightness Indicator Leak Tightness Indicator: • Currently, SCSRs are having a thermal gel like leak tightness indicator which is normally placed on the upper cover part of the SCSR, which changes its color when SCSR is opened but this indicator is not sufficient enough as it will not be able to tell anything about the leak tightness of the cartridge. • Cartridge leak tightness indicator is required in order to be sure about the leak tightness of the apparatus. It will help in saving the time of the miners and the regular expenses which is being made for laboratory tests based on random sampling. • With this random sampling there is still a chance that some leaked apparatus is still put on service and can cost life of the miner. Leak tightness indicator for cartridge can help in mitigating the risks of miners’ life. Rated Duration of SCSR: • Since each miner will be using the SCSR differently, i.e. the duration of SCSR will be different for different miner, therefore, a mechanism with the help of medical parameter monitoring devices and software-aided technology needs to be developed

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which will help in the assessment of the duration of the SCSR. Currently, while escaping with the SCSR, no one knows how far he can travel or how much breathing gas is left inside the SCSR. • Recently, it has been tested at the Mines Rescue Station, M/s Western Coalfields Limited, Nagpur as per Indian Standard and results have been excellent. There were seven subjects and different exercises have been performed. Results obtained from the tests are below [2–4]; • With the above Table 1, it can be determined that the same SCSR will give different duration safety to different miners. Quality of Gas • Measurement of the quality of the gas generated by the Chemical product i.e. Potassium Superoxide will be measured with the help of Oxygen and CO2 sensors, so that asphyxiation cannot happen due to SCSR. Many times, the air keeps coming from the SCSR, but it contains more than 3% of Carbon Dioxide and it can cause asphyxiation to the miner. • Measurement of temperature of the breathing gas, as we know the reaction between KO2 , and CO2 and H2 O are exothermic in nature and generates a lot of heat and it can burn the throat of the miners. Let’s have a look on the chemical reactions which is happening inside the cartridge; 1. 2. 3. 4. 5. 6. 7. 8. 9.

2KO2 +H2O = 2KOH+3/2O2 +9.4 kcal; 2KO2 +CO2 = K2 CO3 +3/2O2 +43.1 kcal; 2KOH+CO2 = K2 CO3 +H2 O+33.7 kcal; KOH+3/4H2 O = KOH.3/4H2 O+16.57 kcal; KOH+H2 O = KOH.H2 O+20.0 kcal; KOH+2H2 O = KOH.2H2 O+33.8 kcal; 2K2 CO3 +1/2H2 O = K2 CO3 .1/2H2 O+7.6 kcal; K2 CO3 +3/2H2 O = K2 CO3 .3/2H2 O+22.77 kcal; K2 CO3 +3H2 0+CO2 = KHCO3 +33.8 kcal.

Let’s combine the principal reactions: 4KO2 +3H2 O+2CO2 =2(K2 CO3 .3/2H2 O)+3O2 +131.82 kcal. Breathing Resistance: Measurement of breathing resistance also needs to be measured as miners feeling higher breathing resistance will not be able to the escape or they might feel thirsty or they will get tired immediately. A Wearable Device to Monitor Cardio-Respiratory Health and Fatigue of the wearer: There have been technological advancements in recent past and wearable technology is growing at a rapid speed. Such devices have been available on the market which can monitor the Cardio-Respiratory Health on the go but not quite popular with the mining industry [5–9].

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Table 1. Field Trial Results of SCSR SHS-30E, manufactured by Corporation Roshimzaschita. Age Height Weight Duration Type of Reason for (in in cm in kg in Exercise as termination Years) minutes per IS of exercise 15803:2008

Pulse per minute

Blood pressure mmHg

Before After Before After trial trial trial trial

28

178

61

52

Treadmill

Generation 80 of oxygen ceased

80

110/70 120/70

31

171

73.9

49

Treadmill

Generation 88 of oxygen ceased

88

120/70 124/84

40

168

71

76

Mines

Generation 80 of oxygen ceased

80

110/70 112/74

25

172

78.2

58

Mines

Generation 84 of oxygen ceased

80

120/80 110/70

25

176

66.5

82

Mines

Generation 70 of oxygen ceased

78

108/80 120/78

32

178

88.1

66

Mines

Generation 74 of oxygen ceased

80

110/70 120/78

39

172

77.6

204

Idle No Work

Generation 80 of oxygen ceased

80

110/70 120/74

• Cardio-Respiratory Health and fatigue of the miner can be measured with a wearable device which is capable to monitor Electrocardiogram, Heart Rate, Breathing Rate, Skin Temperature, Activity and Body Position. • It will check the level of stress of the miner while escape; • It will check the level of panic of the miner and will also monitor the cost of oxygen in case of panic and stress. • It will check the activity and the body position of the miner like the miner is lying, he is moving upright or his body is bent and in case of severity it can raise alarm as well. Network and the Analysis Software: • A mathematical model needs to be designed to analyse all the data obtained from various sensors and the historical data of the miner and also the data obtained from the laboratory results on the chemical product on the generation of useable Oxygen and the Carbon Dioxide which can be scrubbed by the chemical product;

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• All these data will be transferred to the surface of the mine or to the rescuers to analyse the situation of rescue or self-rescue and accordingly it will be conveyed back to the miners. • It can be a Wi-Fi based network system with the Global Positioning Navigation System for the mines with guiding notifications from the surface given by the dispatcher or the rescue team. Major Regulatory and the Requirement as per Indian Standard IS 15803:2008 (Table 2).

3 Design Theory of a New Self-Contained Self-Rescuer A smart SCSR will be a network and micro-processor based programmed SCSR which will diagnose the health of SCSR itself and in case of fault it will generate alarm when it is bodily worn or kept inside the mine but not in use for escape. A general flow diagram of the system is presented in Fig. 1. The SCSR is used in case of emergency to escape, it monitors the health of the miner which includes cardio-respiratory system, stress, level of panic and also monitor its own health and can let the user know about the quality of the gas being generated and all these data will be transferred to the surface via a Wi-Fi network [1–4]. Table 2. Minimal Requirement by SCSR 30 min Duration. Sl. No.

Parameter

Remarks

1.

Oxygen content

Always greater than 21%

2.

Carbon dioxide content

Always smaller than 3% at any point of time during the use of the apparatus and average CO2 for the rated duration of the apparatus will not exceed 1.5%

3.

Temperature of the breathing gas

Temperature of the breathing gas will not exceed 55 °C

4.

Breathing resistance

1. Sum of the inhalation and exhalation resistances will be maximum 16 mbar and the individual breathing resistance for inhalation or exhalation will be max 10 mbar when running at 35 l/min 2. At 70 l/min it will not exceed 20 mbar

5.

Leak tightness

Change in pressure will not be more than 0.3 mbar when tested as per the method for 1 min

6.

Duration

1. At 35 l/min 30 min 2. At 10 l/min 90 min 3. 10 min at heavy work

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Fig. 1. Flow diagram of the system.

Flow Diagram of the System Including SCSR, Human, Physiological System and Indicators and Alarms with the Regulatory Requirements (Fig. 1).

4 Technical Design, Technology and System 1. The Human: It will be the main constituent of the whole system. The entire system will depend upon how he/she behaves underground while trying to escape and the level of aerobic energy the one has and the behavior of their cardio-respiratory system. Everyone on this earth has a signature respiratory system and it can’t be generalized, therefore designing a general absolute product is a challenge. As we can see from the Table 1, exercise for mines. All the subjects have been put on same exercise and all of them started same way and they travelled through the same area but the duration of SCSR varies person to person and a 30-min duration SCSR has worked for 58 min to 82 min. So, we can confidently say that consumption and performance of chemical product is dependent upon the human who is using it. 2. The SCSR: The second constituent of the system, as described earlier it generates oxygen and scrubs Carbon Dioxide (CO2) in a closed cycle operation through Potassium Superoxide (KO2). Please refer the various chemical reactions mentioned above happening inside the cartridge. With the above, reactions we can see that apart from the generation of Oxygen, it generates a lot of heat. In SCSR, this heat is being used in the cartridge to promote ventilation inside the cartridge and while the heat in breathing gas is being minimised through the path of travel of the breathing gas and the temperature of the breathing gas is maintained at 35–450C. Production of heat is the primary indicator in SCSR which tells that reaction has initiated. 3. The Wearable Device for the Monitoring of Cardio-Respiratory Health and Fatigue with its Indicator: This would act as the bridge between the two; The SCSR and The Human. It will be a micro-processor-based programmed system with sensors which will have the health indicators from the human. It will be comprised of various types of sensors which will monitor Skin Temperature, Heart Rate, Electrocardiogram,

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Breathing Rate, and Body Position for the miners and Oxygen Sensor and Temperature Sensor to measure the quantity and quality of the breathable gas. The device shall be intuitive to calculate the fatigue on the basis of monitored heart rate and oximetry. 4. Indicators and Alarms: The data obtained by physiological sensors will be sending information to a separate device attached to the SCSR which will have electronic displays for the metrices in the form of indicators and the alarms which may be a graphical indication or three different coloured lights viz; 1. Green 2. Yellow and 3. Red with various types of beep sounds (Table 3). The same display will be used in all the conditions viz: • When the SCSR is put on the belt; • When the SCSR is being used breathing. Implications of the Indicators as per conditions. Table 3. Indicators and Alarms on SCSR. Sl. No. Colour code When SCSR is put on the belt

When the SCSR is being used for breathing

1

Green

SCSR is ready to use

Breathing gas is appropriate to breath and respiratory condition of the user is normal Rate of flow of the volume of breathing gas is normal

2

Yellow

SCSR needs maintenance

Breathing gas is appropriate to breath and respiratory condition of the user is normal Rate of flow of the volume of breathing gas is low

3

Red

SCSR needs to be discarded from Breathing gas might be toxic or the service and sent back to the contains high CO2 , high temperature, or high breathing manufacturer resistance Rate of flow of the volume of breathing gas is remarkably low or negligible Note: If the Red light persists to glow there will be a final beep alarm to replace the SCSR If the Red light persists to glow and there will be multiple beeps the user is in respiratory problem Dispatcher and rescuers in either of the case would be alarmed of the situation

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5. Data Analysis and Monitoring Station: There will be an analysis station which will automatically analyse the data received from different sensors and the Physiological Indicator System and allows the dispatcher and the rescuer to decide on the command needs to be given and the action needs to be performed. It will have real time data of all the parameters, like the functioning of SCSR, ECG, Heart Rate, Skin Temperature, Breathing Rate Indications, Breathing Gas Flow indications, etc. [10–15]. Software and the Mathematical Model: For all the above functions, a software needs to be designed based on a failsafe mathematical model. The software will be capable of to directly interact with the sensors. It will bring Intuition to the SCSR. It will be able to run on computers or on Android or IOS as an app.

5 Conclusion With increase in the awareness of safety and health consciousness, personal protective equipment (PPE) is widely being used in various industries which are prone to accidents. A lot of efforts are being made to make PPEs smart like our smart phones, smart homes and office appliances. So, that more safety can be provided to humans at work. SCSR is one of the PPE being used in coal mines. Current design and technology of the SCSR has evolved through a lot of phases which are being manufactured and used in coal mines. There have been technological advancements in terms of chemistry and SCSR has become lighter in weight and other technical parameters have also become better in terms of breathing. Smart SCSR is still under the development and research. It can be seen on the belts of the miners in near future. It will increase the chances of rescuing the miners and it will help the miners to use the SCSR effectively. The SCSR Model SHS-30E manufactured by Corporation Roshimzaschita has proved its excellent performance during the field tests at the Mines Rescue Station, M/s Western Coalfields Limited, Nagpur, India and can be successfully applied to tackle the aforementioned safety issues at the mines.

References 1. Matveykin, V.G., Nemtinov, V.A., Dmitrievsky, B.S., Praveen, P.K.: Development and implementation of network based underground mines safety, rescue and aided rescue system. J. Phys: Conf. Ser. 1278(1), 012017 (2019). https://doi.org/10.1088/1742-6596/1278/1/012017 2. IS 15803:2008 Respiratory protective devices - Self contained closed circuit breathing apparatus chemical oxygen (KO2) type, self generating, self rescuers – Specification (Indian Standard for Self Contained Self Rescuer) (2008) 3. Directorate General of Mines Safety (Regulatory Authority for Mines in India) Technical Circulars on SCSR 4. Petrocelli, A.W.: Peroxides, Superoxides, and Ozonides of Alkali and Alkaline Earth Metals, Chapter 4 (Superoxides of the Alkali and Alkaline Earth Metals) (1966) 5. Dmitrievsky, B.S., Bashkatova, A.V., Terekhova, A.A.: Simulation of the melting process in an electric arc furnace. Int. Trans. J. Eng. Manag. Appl. Sci. Technol. 10(6) (2019) 6. Nemtinov, V.A., Nemtinova, Y.V.: On an approach to designing a decision making system for state environmental examination. J. Comput. Syst. Sci. Int. 44(3), 389–398 (2005)

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7. Tabekina, N.A., Chepchurov, M.S., Evtushenko, E.I., Dmitrievsky, B.S.: Solution of task related to control of swiss-type automatic lathe to get planes parallel to part axis. J. Phys: Conf. Ser. 1015(5), 052030 (2018) 8. Buller, M.J., Tharion, W.J., Cheuvront, S.N., Montain, S.J., Kenefick, R.W., Castellani, J., Latzka, W.A., Roberts, W.S., Richter, M., Jenkins, O.C., Hoyt, R.W.: Estimation of human core temperature from sequential heart rate observations. Physiol. Meas. 34, 781–798 (2013) 9. Tharion, W.J., Buller, M.J., Karis, A.J., Hoyt, R.W.: Development of a remote medical monitoring system to meet soldier needs. In: Marek, T., Karwoswki, W., Rice, V. (eds.) Advances in Understanding Human Performance: Neuroegonomics, Human Factors, Design, and Special Populations, pp. 491–500. Taylor and Francis Group, Boca Raton, FL (2010) 10. Tharion, W.J., Lieberman, H.R., Montain, S.J., Young, A.J., Baker-Fulco, C.J., DeLany, J.P., Hoyt, R.W.: Energy requirements of military personnel. Appetite 44, 47–65 (2005) 11. Krol, O., Sokolov, V.: Modelling of spindle nodes for machining centers. J. Phys. Conf. Ser. 1084, 012007 (2018). https://doi.org/10.1088/1742-6596/1084/1/012007 12. Mokrozub, V.G., Nemtinov, V.A., Mokrozub, A.V.: Procedural model for designing multiproduct chemical plants chemical and petroleum. Engineering 53(5–6), 326–331 (2017) 13. Krol, O., Sokolov, V.: Parametric modeling of gear cutting tools. In: Advances in Manufacturing II. Lecture Notes in Mechanical Engineering, vol. 4, pp. 3–11 (2012). https://doi.org/ 10.1007/978-3-030-16943-5_1 14. Nemtinov, V.A., Nemtinova, Y.V., Borisenko, A.B., Nemtinov, K.V.: Construction of concentration fields of elements in 3D in groundwater of an industrial hub using GIS technologies. J. Geochem. Explor. 147(PA), 46–51 (2014) 15. Borisenko, A.B., Karpushkin, S.V.: Hierarchy of processing equipment configuration design problems for multiproduct chemical plants. J. Comput. Syst. Sci. Int. 53(3), 410–419 (2014). https://doi.org/10.1134/S1064230714030046

Features of the Process of Digital Transformation of the Economy in Russia Roman Ivanichkin(B)

, Pavel Kashirin , Sergey Sysoev , Oleg Shabunevich , and Uwaila Osarobo James

Russian University Peoples Friendship FGAOU IN (RUDN University), St. Miklukho-Maklaya, 6, Moscow 117198, Russia [email protected]

Abstract. This article considers the process of digital transformation on the economy and society in the Russian Federation. Digital transformation is a total technological shift that is already obvious and undeniable. A statistical analysis of the process of digital transformation of the economy and how society faces this process is the main substrate of this study, the purpose of which is to show the level of growth of digital transformation in business and companies, as well as in human capital in Russia. The digital transformation process is perceived differently by governments and people in general. This article presents some strategies and projects created by the Russian Government to ensure digitalization in all sectors of the economy and society. The article highlights the main directions of creating conditions contributing to the formation of the ecosystem of the digital economy of Russia. Digital transformation of business, digital transformation of the government, and digital transformation of the labor market are considered as such conditions. Keywords: Digitization · Digital culture · Innovation · E-commerce · Internet · Digital economy · Technology · ICT · Digital transformation · Business

1 Introduction Digital transformation in Russia has been a top priority at the highest level of leadership, and a number of digital initiatives have been implemented in the country at the national and subnational levels. Developing artificial intelligence, robotics, production of drones, as well as developing a technological infrastructure at the service of government and society are some of the strategies of the Russian government. Russia has been promoting a commitment to the transformation of its economy, with the Skolkovo Technological Park in Moscow as the leader of change. The country is particularly interested in modernizing the traditional sectors that have underpinned its GDP, such as the energy industry or heavy industry, and in entering emerging areas such as the Internet of things.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 187–197, 2021. https://doi.org/10.1007/978-3-030-57453-6_16

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From a business point of view, many companies see digital transformation as a greater opportunity for new businesses. In the public sector transformation, Russia has adopted global best practices and achieves a degree of success in developing a robust national broadband infrastructure, extensive mobile penetration, and E-government service delivery, as well as in launching digital adoption in education, health care, culture, and social service. Digital transformation has a significant impact on economic and social processes, primarily on economic growth, the labor market, and the quality of services.

2 Statistical Analysis Several hundred Russian companies from key economic sectors, including finance, telecommunciations, metal industry, energy, transport as well as retail. The survey respondents were companies’ top management, managers responsible for digital transformation as well as managers of functional blocs within companies where some or other digital technologies are being tested or already used. Respondents could choose several options. As the graph shows, at the 2019, the Big Data analysis and predictive analytics show the higher percent. Even the efforts of the government to increase the use of AI, the graphic show that only the 28% of respondents they use this technologies in their business (Fig. 1).

80% 70%

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OpƟcal ArƟficial Internet of character intelligence Things (IoT) recogniƟon (AI) (OCR) Share of respondents

Fig. 1. Digital technologies used by business companies in Russia in 2019* [1].

Digital technologies in telecommunications companies are the key element in the era of digital transformation. Following graphic show the digital technologies used by telecommunication in Russia 2019 (Figs. 2, 3, 4 and 5).

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120% 100%

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Fig. 2. Share of telecommunications business companies in Russia using digital technologies in 2019*, by type [1].

ArƟficial intelligence (AI)

5%

Internet of Things (IoT)

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20%

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50%

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Share of respondents

Fig. 3. Share of retail business companies in Russia using digital technologies in 2019*, by type [1].

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Law firms (search, contract draŌing) Pricing and promoƟon Finance and accounƟng Social media presence LogisƟc opƟmisaƟon, supply chain, procurement Fraud detecƟon Others Human resources Risk management and analysis Real-Ɵme operaƟons management Knowledge accumulaƟon Customer insights PredicƟve analyƟcs (supply and provision forecasƟng) Customer services Work with clients (e.g. personalizaƟon) Research and developement 0%

5%

10% 15% 20% 25% 30% 35% 40% 45%

Share of companies

Fig. 4. Share of companies using artificial intelligence (AI) technology in Russia in 2019, by field [2].

90

82.7

80 70 60 50 40 30 20

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3.3

0 Virtualized infrastructure market*

SoŌware as a service (SAAS) market

Web hosƟng market, excluding cloud web hosƟng

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Market value in billion Russian rubles

Fig. 5. Value of the infrastructure market of the Russian internet (RuNet) in 2018, by type of market (in billion Russian rubles) [3].

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Russian internet markets, of course, face to global competition. This is perhaps the main factor that explains in the case of the, software, hosting and domain market, why its value is so low. Other factors such as the price, security and privacy of the data, and the conditions that are established for customers, can directly influence (Figs. 6, 7, 8, 9 and 10).

14

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Fig. 6. Russian information technology market turnover in 2017, by sector (in billion U.S. dollars) [4].

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Fig. 7. Cloud technology market size in Russia from 2014 to 2020 (in billion Russian rubles) [4].

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12 10.5 10 8.8 7.6

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0 2013

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Fig. 8. Annual sales turnover of the Russian software industry from 2013 to 2018, by market* (in billion U.S. dollars) [4].

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Fig. 9. Value of services exported by the telecommunication, computer, and information industry from Russia from 2008 to 2018, by type of services (in million U.S. dollars) [2].

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Marketplace for self-employed Notary services Online sales and delivery of alcohol Search for legal informaƟon Telemedicine Online access to own medical records Online jobs, including for persons with limited mobility Internet services adapted for ciƟzens with health limitaƟons Free online courses Online sale and delivery of medicines Online government services 0%

5%

10%

15%

20%

25%

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Share of respondents

Fig. 10. Opinion poll on the most popular internet services in Russia in 2019* [1].

The process of digital transformation leads to a great demand for professionals in this area and the opening of job offers in this regard. Here are some important facts about how Russia faces this challenge (Figs. 11, 12, 13, 14, 15 and 16). 1600.0% 1362%

1400.0% 1200.0% 1016% 1000.0% 781%

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Fig. 11. Growth rate of open vacancies demanded for jobs in the digital industry in Russia from 2010 to 2019* [5].

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90%

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Distributed Project manager Neural network specialist developing system administrator soluƟons based on machine learning

Share of respondents

Number of vacancies per thousand job postings

Fig. 12. Survey on the most demanded professions in digitalization across business companies in Russia in 2019* [1].

3 2.5 2

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Fig. 13. Number of open vacancies in the information technology (IT) sector Russia in 2018, by job position* (per 1,000 job postings) [1].

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40% 36% 35% 31% 30% 25% 20% 15% 10%

9% 4%

5% 0% Less than a year

1-3 years

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Fig. 14. Distribution of vacancies in the information technology (IT) sector in Russia in 2018, by required years of experience [6].

Fig. 15. Median salary of specialists in the information technology (IT) sector in Russia in 2018, by years of experience and city* (in 1,000 Russian rubles) [6].

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The quantity of distance learning and online degrees in most disciplines is large and increasing rapidly. Online learning gives educators an opportunity to reach students who may not be able to enroll in a traditional classroom course and supports students who need to work on their own schedule and at their own pace. In Digital Russia show some results of spending in the graphic below [7].

Foreign languages

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Medicine

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Finance

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PainƟng

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9%

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38% 0%

5%

10%

15%

20%

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Fig. 16. Distribution of spending on online education in Russia in 2018, by course topic [8].

3 Conclusion The Russian Federation is on the threshold of positioning itself as a new world leader in the digital economy. Russian internet economy shows significant growth despite economic crisis and political environment. Information and Technologies (IT) industry in Russia has a huge potential both for established business models and disrupting technologies. Although many government initiatives are questionable for benefit of the Internet, government investments provide a strong impact on internet business and infrastructure. Russian internet remains one of the most active parts of the Russian economy. Its influence on other economy sectors keeps growing. Russian internet is a unique collaboration of cultural and scientific achievements, which provide innovative products and unlimited opportunities for Russian society. IT in Russia is following common trends in worldwide web and creates it’s own trends for international online business. Today, the country has good opportunities and it needs to use the existing technological foundations, human resources, and the widespread use of information and communication technologies to ensure significant progress in the use of digital technologies to meet the development challenges. It is to make maximum use of the opportunities of the digital revolution, to improve legislation that ensures

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the formation of competition among organizations, to promote the skills of workers in accordance with the requirements of the new economy and to ensure the accountability of institutions. One of the directions of development of digitalization of the economy is to improve the efficiency of the labor market. Digital transformation of the Russian economy will have an increasing impact on different industries. As the main drivers of the long-term economic growth based on strengthening of process of digitalization it should be noted the multiple-factor increase in operational productivity of companies due to promotion of Industry 4.0 in the economy, optimization of production and logistic operations, increase in efficiency of research and development and use of resources by means of installation of advanced IT systems [9]. According to the statistics collected, Russia is moving towards the digital age rapidly. More and more businesses and companies are committed to change. The Russian government is focused on creating strategies and optimizing existing ones so that this progress will increase in the coming years, thus achieving a digital society throughout the nation. Although there are still those who resist change, it is considered that more than 90% of big and small businesses, as well as companies from both the private and public sectors have entered the digital age.

References 1. Statista 2020. http://statista.com. Accessed 02 May 2020 2. Ershova, T.V., Hohlov, Y.E., Shaposhnik, S.B.: Methodology for digital economy development assessment as a tool for managing the digital transformation processes. In: 2018 Eleventh International Conference “Management of Large-Scale System Development”, pp. 1–3. MLSD. IEEE (2018) 3. Kapranova, L.D.: The digital economy in Russia: its state and prospects of development. Econ. Taxes Law 11(2), 58–69 (2018) 4. RusSoft, 15th Annual Survey of the Software Development Export Industry of Russia. http:// russoft.org. Accessed 02 May 2020 5. Nissen, V., Lezina, T., Saltan, A.: The role of IT-management in the digital transformation of Russian companies. Forsait 12(3), 53–61 (2018) 6. Borremans, A.D., Zaychenko, I.M., Iliashenko, O.Y.: Digital economy. IT strategy of the company development. MATEC Web Conf. 170, 01034 (2018) 7. Online Education. https://www.encyclopedia.com/finance/finance-and-accounting-magazi nes/online-education. Accessed 05 May 2020 8. ROSCONGRESS. https://roscongress.org/en/materials/doklad-o-razvitii-tsifrovoy-ekonom iki-v-rossii-konkurentsiya-v-tsifrovuyu-epokhu-strategicheskie-vyz/. Accessed 29 Apr 2020 9. Korobeynikova, E.V., Ermoshkina, C.N., Kosilova, A.F., Sheptuhina, I.I., Gromova, T.V.: Digital Transformation of Russian Economy: Challenges, Threats, Prospects (2018)

Spatial and Temporal Databases For Decision Making and Forecasting Ielizaveta Dunaieva1 , Ekaterina Barbotkina1 , Valentyn Vecherkov1 Valentina Popovych1 , Vladimir Pashtetsky1 , Vitaly Terleev2 , Aleksandr Nikonorov2(B) , and Luka Akimov2

,

1 Research Institute of Agriculture of Crimea, Kievskaya, 150,

295453 Simferopol, Crimea, Russia 2 Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya Str. 29,

195251 St. Petersburg, Russia [email protected]

Abstract. The work describes the list of spatio-temporal databases of information necessary for analyzing the state of the territory, changes forecasting and decisions making, especially in terms of the energy strategies appliance and energy management. Description of sources of information, stages of processing the primary data (paper media, remote sensing data, Excel, MS Access databases), storage and visualization options using both desktop GIS and online services are given. Examples for study area of the Klepininsky rural settlement of the Krasnogvardeisky district of the Republic of Crimea using GIS technologies and online satellite monitoring services are given. Keywords: Spatial and temporal databases · Forecasting · Energy management

1 Introduction Presence of long-term spatial information about the territory, possibility of its visualization and comparison is necessary tool for making managerial decisions and analyzing the development of situation in future. This decisions could be the part of the efficient energy management. At the moment, there are quite a lot of opportunities to assess the territory, both using online services such as Vega-Science (IKI RAS) [1], OneSoil [2], EOS Crop Monitoring [3–5], and using GIS software products. Integral part of territory assessment is accumulated range of information and its reliability. Availability of observational data, archival materials, and remote sensing data allows verifying estimates and obtaining objective information about the territory. Therefore, creation and storage of spatial and temporal information about territories is relevant.

2 Materials and Methods To obtain spatio-temporal information and create databases, QGIS 2.18 software with plug-ins for processing was used, as well as Vega-Science and EOS Crop Monitoring © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 198–205, 2021. https://doi.org/10.1007/978-3-030-57453-6_17

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services. To refine methodology for collecting information, the territory of the Klepininsky rural settlement of the Krasnogvardeisky district of Crimea was used. The initial data for assessment of the territory are: 1) databases of meteorological information; 2) soil characteristics, data on the content of elements in soil, soil moisture, etc.; 3) terrain features; 4) borders of districts (Crimea_adm.shp file); 5) borders of rural settlements - Crimea_hoz.shp; 6) medium and high spatial resolution images (Landsat 8 Oli/Tirs, Sentinel). The following describes the stages of databases creating and materials for their creation. It is necessary to have spatial information in the form of raster geobases of data and databases in tabular format for subsequent use in simulation modeling of crop growth in order to analyze potential yields and assess the territory by the availability of food resources. For agro-ecological assessment of the territory, it is necessary to perform the following steps and form the following databases.

3 Results and Discussions 3.1 Database of Morphometric Characteristics of Relief It is possible to obtain characteristics in several ways: to analyze the terrain using topographic maps and to construct DEM by processing contours, using DEM data from remote sensing data, such as SRTM (90 m spatial resolution for Crimea) (see Fig. 1), UAV survey data and more.

Fig. 1. Map of the processed terrain SRTM and slope of the territories with soil types.

Relief data are used to solve the following problems: determining soil erosion and identifying areas that are most susceptible to it, determining slopes and shading of slopes, which is important when developing planting schemes for orchards and vineyards, as well as when calculating runoff from the territory - determination of soil moisture distribution over the territory and more. Terrain processing is carried out using the Morphometric analysis plug-in: slopes, exposure, shadow relief (Fig. 1 - right). Depending on the steepness of the slopes, three technological groups of soils can be distinguished: 1 arable land on watersheds and drive-separated plateaus with steepness of slopes up to 3°; 2 - arable land on slopes with steepness from 3 to 5°; 3 - arable land on slopes with steepness over 5°. According to the analysis in the study area, 98% of soils belong to the first group and 2% to the second.

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3.2 Land Use Database To create database, it is necessary to map the land use of the territory in GIS environment. To do this, we will use open source software QGIS 2.18. For convenience of territory mapping, we load additional modules (plug-in) through the Modules tab - Manage modules and select QuickMapServices, Rectangles Ovals Digitizing, OpenLayers modules. Than create new shape-file and set the file parameters (Type - Polygon), select the Projected coordinate system WGS 84/UTM zone 36 N and save it with the name LU. Using the QuickMapServices module, through visual de-encryption using satellite data (Yandex, Google, Bing, etc.), we digitize and select land categories. Assign land categories by figures in the file attribute Table in the “Type” column. Assign land categories to plots in the following order: 1- agricultural land; 2 - residential land; 3 - industrial land, energy, transport, communications, broadcasting, television vision, computer science, land for space activities, defense, security, and other special purpose land; 4 - land for protected areas and objects; 5 -forest land; 6 - land for water resources; 7 - reserve lands. Next, fill land use database with necessary information, namely the characteristics of land plots. First of all, it is necessary to calculate the objects area in calculator, which is launched from attribute table, and create the Area field, type - with tenths (real), length 10, accuracy - 2. After that, go to the Field Calculator and prescribe the expression $area (area is calculated in map units in the metric coordinate system, if necessary to transfer in ha, we additionally prescribe converting in expression). If necessary, you can add cultivated crops to this database with indication of growing season (example of land use database is in Fig. 2).

Fig. 2. Land use of the territory with information database for the period 2014–2019 (left - QGIS, desktop version of geodatabase; right - Vega-Science - online geodatabase).

Database can be organized in GIS environment, Excel tables (with subsequent conversion to GIS environment), in other software tools, for example, Microsoft Access [6] and using the online services OneSoil, Crop Monitoring, Vega-Science.

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3.3 Database of Soil Characteristics Development of soil characteristics database of the territory is based on the use of soil cover map 1970 [7] and agrochemical surveys data (soil moisture, soil hydrological constants, content of macro- and microelements in soil). Soil map is created by binding paper map material in GIS environment and digitizing soil differences and entering the corresponding information in the attribute Table. To bind a map in QGIS it is need to launch the Modules tab – «raster Binding». To start binding, load the raster file, to be bound, into the data view. It can be in any common image format (*.gif, *.jpeg, *.tif, etc.), to do this select File/Open raster. If raster is bound to other layers (vector or raster), you must first load necessary layers into main QGIS window. Then, instead of entering coordinates from keyboard, map button C is selected to set coordinates of control points, in this case coordinates of control points are taken from the map, which can contain any other layers that are open in main program window. For convenience information, obtaining on specific territories in GIS environment, it is possible to perform spatial and attributive requests, in this case, for example, along the borders of rural settlement. If there are point data on soil moisture reserves or macro or micronutrients in soil, you can interpolate the data and obtain spatial information throughout the territory. Agrochemical information is stored in Excel tables indicating GPS coordinates of the sampling points and, if necessary, is converted to the *.csv format, which is read by QGIS program. Example of calculation is shown in Fig. 3.

Fig. 3. Interpolation of moisture content in soil in layer of 0–100 cm.

3.4 Database of Meteorological Parameters To assess agro-resource potential of the territory it is necessary to analyze average longterm values of meteorological parameters according to reference information [8] and

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long-term archival series of observations, as well as the availability of current meteorological information as downloaded from open archives such as NOAA, rp5.ru, NCEP (directly or through the VEGA-Science service [9]), GPM, and others, as well as data from automated weather stations (for example, Sokol-M) [10, 11]. Long-term average temperature and precipitation data in spatial form can be represented by interpolation (IDW) with contours creation, using interpolation module and contour module (see Fig. 4). At the same time, if it is necessary to present data in tabular form and load it into agrohydrological model, meteorological data can be extracted from remote sensing data using Zonal Statistic tool in object shapefile for pilot area or DN values from raster, convert raster to polygon will create vector record for each cell of the raster.

Fig. 4. IDW interpolation of long-term average annual precipitation for the period 1986–2005 for part of territory of the Klepininsky rural settlement.

3.5 Database of Vegetation Indices Vegetation state of the territory and yield potential can be estimated using vegetation indices, which can be obtained by processing bands (ratio of reflection and absorption of different wavelengths and their combinations) of satellite data using both local GIS and online services. Figure 5 presents calculation of vegetation indices NDVI and NDDI using the raster calculator in QGIS 2.18.23 program (in Raster calculation expression fits the formula by which the calculation will be performed). Using Earth remote sensing data allows analyzing and comparing territories with each other, this is especially relevant when information on areas/regions is not available in the public access. So, methods of automatic classification allow to determine the area under specific crops, to determine the potential yield and, accordingly, to assess the economic and social situation in the region/district. In the framework of joint work with IKI RAS, the methodology for identifying winter crops according to remote sensing data was improved [12].

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Fig. 5. Calculation of vegetation indices NDVI and NDDI using the raster calculator in QGIS 2.18.23.

In this paper, we compare the information on cultivated crops by Klepininsky rural settlement for 2019, contained in the crop classification map of EOS Crop Map service and the actual crop structure data (see Fig. 6).

Fig. 6. Comparison of EOS Crop Map classification with land cover for 2019 data.

The analysis showed that the EOS Crop Map service data are 60% consistent with the existing land use structure.

4 Conclusions Described approaches allow creating data geobase over multi-year period and to analyze them both in GIS environment and using online services. Presence of vector masks of the territory (depending on required scale of detail – region, rural settlement, field) allows creating a spatial request for information and obtaining information for making a decision in the field of hydraulic engineering, as well as in practical agriculture and in studies of environmental impact factors [13–21]. Also proposed approaches allows to build an efficient energy management. Acknowledgements. The reported study was funded by RFBR according to the research projects No. 19-016-00148-a, No. 19-04-00939-a.

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Vega-Science: “Vega” IKI RAS. http://sci-vega.ru. Accessed 13 Feb 2020 OneSoil. https://onesoil.ai. Accessed 13 Feb 2020 EOS Crop Monitoring. https://eos.com/cropmap/. Accessed 13 Feb 2020 Dunaieva, I., Mirschel, W., Popovych, V., Pashtetsky, V., Golovastova, E., Vecherkov, V., Melnichuk, A., Terleev, V., Nikonorov, A., Ginevsky, R., Lazarev, V., Topaj, A.: Adv. Intell. Syst. Comput. 983, 236–246 (2019) Vecherkov, V., Melnichuk, A., Dunaieva, I.: Materials of the IV Interregional with International Participation Scientific-practical Conference «Trends, Directions and Prospects for the Development of Economic Relations in Modern Economic Conditions», pp. 236–239 (2019) Vecherkov, V., Dunaieva, I., Terleev, V.: Week of Science SPbPU: Proceedings of a Scientific Conference with International Participation, Institute of Civil Engineering: In 3 parts, pp. 171– 174 (2019) Krupsky, N.K., Polupan, N.I.: Atlas of Soils of the Ukrainian SSR. Soil map of the Republican project institute of land management «UkrZemProekt». Map of soils of the «Ukrainian SSR» (1979) Prytkov, A.I., Adamenko, T.I.: Agroclimatic Handbook of the Crimea (1986–2005). Taurida, Simferopol (2011) Loupian, E.A., Proshin, A.A., Burtsev, M.A., Balashov, I.V., Bartalev, S.A., Efremov, VYu., Kashnitskiy, A.V., Mazurov, A.A., Matveev, A.M., Sudneva, O.A., Sychugov, I.G., Tolpin, V.A., Uvarov, I.A.: Current problems in remote sensing of the Earth from space. Moscow 12(5), 263–284 (2015) Dunaieva, E., Pashtetskiy, V., Nuriakhmetov, R.: Updated database of meteorological parameters obtained at the Sokol-M meteorological station located in the Orekhovsky rural settlement of the Republic of Crimea. Certificate of registration of the database RU 2020620167, 01.29.2018. Application No. 2020620041 dated 10.01.2020 Dunaieva, I., Pashtetskiy, V., Nuriakhmetov, R.: Database of meteorological parameters obtained at the Sokol-M automated station located in the Saki region of the Republic of Crimea. Certificate of registration of the database RU 2020620166, 01/29/2018. Application No. 2020620042 dated 10.01.2020 Dunaieva, Ie.A., Elkina, E.S., Plotnikov, D.E., Bartalev, S.A., Vecherkov, V.V., Golovastova, E.S.: Taurida herald of the agrarian. Sciences 4(16), 18–31 (2018) Terleev, V.V., Mirschel, W., Badenko, V.L., Guseva, IYu.: Eurasian Soil Sci. 50(4), 445–455 (2017) Terleev, V., Petrovskaia, E., Sokolova, N., Dashkina, A., Guseva, I., Badenko, V., Volkova, Y., Skvortsova, O., Nikonova, O., Pavlov, S., Nikonorov, A., Garmanov, V., Mirschel, W.: MATEC Web Conf. 53, 01013 (2016) Degtyareva, O., Degtyarev, G., Togo, I., Terleev, V., Nikonorov, A., Volkova, Y.: Procedia Eng. 165, 1619–1628 (2016) Nikonorov, A., Terleev, V., Pavlov, S., Togo, I., Volkova, Y., Makarova, T., Garmanov, V., Shishov, D., Mirschel, W.: Procedia Eng. 165, 1741–1747 (2016) Terleev, V., Petrovskaia, E., Nikonorov, A., Badenko, V., Volkova, Y., Pavlov, S., Semenova, N., Moiseev, K., Topaj, A., Mirschel, W.: MATEC Web Conf. 73, 03001 (2016) Chusov, A., Maslikov, V., Molodtsov, D., Manukhina, O.: Adv. Intell. Syst. Comput. 692, 1046–1054 (2018) Fedorov, M.P., Maslikov, V.I., Badenko, V.L., Chusov, A.N., Molodtsov, D.V.: Power Technol. Eng. 51(4), 365–370 (2017)

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20. Umanets, V., Kalitova, L., Kalitov, D., Chusov, A., Umanets, E.: International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, vol. 1, no 5, pp. 135–144 (2015) 21. Il’ina, K., Gavrilova, N.M., Bondarenko, E.A., Andrianova, M., Chusov, A.N.: Mag. Civil Eng. 76, 241–254 (2017)

Materials Science and Engineering for Energy Systems

Liquid Organic Waste Purification on the Example of Beet-Sugar Production Using Cavitation Hydrodynamic Generators Valeriy Mishchenko , Alexey Semenov(B) , Valentin Yatsenko , and Tatyana Stepanova Voronezh State Technical University, Moscow Avenue, 14, Voronezh 394026, Russia [email protected]

Abstract. The authors presented a mechanism for optimizing the results of studies of an integrated system for treating waste beet sugar production using cavitation hydrodynamic generators, a chemical treatment, and an ozonation system. As a result of the research, the synergy effect was confirmed when using the cavitator in conjunction with other methods of exposure. Also, the authors established the optimal modes for the selected types of exposure and processing environment. The scale of the problem is shown - more than 2 trillion tons of world beet sugar production waste and the alternative possibilities of using this cleaning system are described. The main problem of cleaning these wastes is the presence of saponin in them, which is a natural toxic substance that can cause hemolysis of red blood cells and is a depressing factor for the development of aquatic organisms when these wastes enter their environment. The emphasis of cleaning is shifted towards the maximum removal of saponins from the solution. Based on the purification performed and the use of control measurements by determining light absorption coefficients (transparency), a purification result was obtained that meets basic requirements, including European standards for wastewater treatment quality. The possibility of applying this technique to expand the number of optimization factors is shown. Keywords: Water purification · Sugar industry waste · Cavitation · Ozonation · Purification · Clarification · Spectrophotomerism

1 Introduction The problem of clean water is becoming every year an increasingly hot topic, the amount of available fresh water in areas of human activity is rapidly decreasing. One of the factors that significantly affect the availability of drinking water is the wastewater discharge of insufficiently treated or completely untreated into the ecosystem of human life. Especially dangerous are water with organic contamination that can not only cause outbreaks of infectious and other diseases, but also have a cumulative effect. Decades this policy of appeasement has led humanity to the brink of existence, so there © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 209–224, 2021. https://doi.org/10.1007/978-3-030-57453-6_18

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was a need to review existing approved technologies and standards to improve the quality of water purification for drinking and industrial purposes. In the production of sugar in sugar beet factories use large amounts of water. It is used for pre-processing of incoming sugar beet, hydraulic, cooling systems. Water is used for dissolving various reagents needed for manufacturing processes, etc. In the sugar industry in the form of production wastes are mainly waste water, which are purified through a biological treatment fields of a filtration, which occupies an area of tens, and sometimes hundreds of times greater than the area of the sugar factory. Considering the composition of wastewater, the following technological features. Conveyer-washing water is purified in the sump, and then returned to the production cycle. The resulting residue pumps is supplied to the seal in earthen ponds, where the filtered water is fed by gravity to the fields of filtration, and the accumulated dewatered sludge is discharged and stored on the earthworks on the perimeter of the fields. At the same pollutants seep into the soil and then into groundwater. The water of the second category is sent to the cooling pond, where it comes to the washing and transport of the beets. In most enterprises, no cooling tower, so after filling the cooling pond of any excess water and condensate are directed to the fields of filtration. The waste water of the third category (diffuse, bagasse, sewage etc.) are the most polluted, as they contain large amounts of dissolved organic substances. Thus, the dissolved sugar contributes to the formation of various organic acids, and beet saponin causes foaming of aqueous solutions and poses a threat of toxic poisoning to organisms. Therefore, drain purifying this category the most important for the environment and requires a more careful approach. Another significant drawback of outdated technology is the insufficient degree of sludge dewatering and, as a result, the large area occupied by the filtration fields with very low quality wastewater treatment. But often in most sugar factories the discharge of the third category effluent to small filtering fields is carried out without any preliminary treatment, which causes enormous environmental damage due to the infiltration of effluents into groundwater. Therefore, the need has ripened for introducing recycled water supply into the technological process with a fully closed cycle, for this it is necessary to monitor the quality of the waters used in the technological processes and look for methods that allow their reuse to indicators that would allow its use in a closed technological cycle. This type of water contains in its composition mineral and organic substances in large quantities. The following conclusions can be made. World sugar production in 2019 increased to 181 million tons. [1] Of the total sugar production in the world, sugar beets account for about 40% [4], i.e. in 2019, approximately 72.4 million tons of sugar was obtained from sugar beets. Given that from 1 ton of sugar beet, approximately 150 kg of sugar is obtained, i.e. 500 million tons of sugar beets were processed. With a coefficient of 1.7 m3 of wastewater per 1 ton of sugar beet, this amounts to about 820 million m3 of wastewater for 2019. The total volume of wastewater discharged throughout human life is more than 2 trillion tons (Table 1). When water is used by sugar factories, there are acceptable indicators of water [2], when they are taken from a water source. Data on these indicators are shown in Table 2.

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Table 1. Average annual consumption and water withdrawal rates for sugar beet production. CONSUMPTION Recycled, sequentially used water Fresh water Including: 1. Technical 2. Drinking for needs: • production: • household. LEAD Total amount of wastewater, including to be purified from pollution: 1. Production 2. Household 3. Does not require purification

WATER RATE M3 / T BEET 20 2,49 1,64 0,05 0,05 1,7 1,62 0,08 0

Table 2. Permissible water indicators. INDICAOR Temperature ˚С Color Smell Transparency, cm Suspended Substances, mg / L PH reactive media COD m^2 / l BOD5 m^2 / l Solids, m2 / l Hardness, m2 - equiv / l:: 1. general; 2. carbonate.

MAXIMUM VALUE 25 Without color Without smell 15 120 6,5-8,5 200 150 1000 15 8

As already noted, the wastewater of a sugar factory contains a large amount of various impurities. The indicators of these waters are given in Table 3 [3]. Transport and washing waters contain a large amount of sediment and suspended solids. Before discharging these waters into sedimentation tanks, mechanical impurities are partially removed in various ways (Table 4). Vehicle wash water plants for the manufacture of sugar contains both biological and chemical contamination, which consist mainly of mineral salts, sugars, microorganisms. 1 g of beet chips contains 5,7 × 〖10〗ˆ10 different microorganisms [4]. Many purified vehicle washing water of sugar factories great attention is paid to water clarification [5], and the issue of microbiological pollution is not considered. Contact was made to optimize the technology for purifying vehicle washing water of the sugar factory as from suspended solids and a variety of microbial contamination. The choice of means and methods of water purification are based on three factors: economic

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INDICATOR Temperature˚С Color Smell Transparency, cm The content of suspended solids, m2 / l pH of the medium Dissolved oxygen, m2 / l BPCCON m2 / l COD m2 / l Solids, m2 / l Content, m2 / l 1. Nitrogen organic compounds 2. Ammonia and ammonium salts 3. Nitrites, nitrates 4. Hydrogen sulfide 5. Sulfates 6. Phosphates 7. Chlorides 8. Saponin Total hardness m2 - equiv / l

VALUE OF INDICATORS 12-28 Taupe Musty, putrid 0 666-49948 7,5-8,9 0 3248-7636 4547-10110 3760-10133 18-136 3,5-22,4 Traces 1,9-13,5 9,8-131 1,2-16,0 17-198 5-12 8,3-32,8

Table 4. Regulatory characteristics of transport-washing waters. INDICATOR Content in water, m2 / l: 1. Suspended Substances 2. Dry residue 3. The residue after calcinations 4. Total nitrogen 5. Ammonia and ammonium salts 6. Sulfates 7. Phosphates 8. Chlorides

pH COD, m2O2 / l BPK5, m2O2 / l

TRANSPORT WASHING WATER 1971-22820 462-3648 185-1128

1200-8500 450-3500 150-1000

150-300 300-2500 150-1250

9,4-27 2,1-12

10-30 2-12

10-30 2-12

74-101 2,8-12,1 18,5-126 6,0-7,3 611-5394 470-4150

10-100 2-9 20-140 10-12 600-5200 400-4000

1-100 2-9 15-135 10-12 600-5200 400-4000

viability, ease of use and innovation. The last factor was due to the need to promote new breakthrough technologies, which, contrary to classical methods on the verge of combining technologies will give a qualitatively better result. Therefore, the applied technology: - Cavitation generator, as the factor of energy-cost-effective technological stages of the treatment process directly have a significant effect on the purified substrate, and also due to the synergistic effect that increases the efficiency of subsequent process

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steps. In the process of hydrodynamic generators water appear the high-energy effects (cold boiling or cavitation), which not only contribute to effective water treatment but may result in changes to its structure, enhancing physical-chemical and biological activity [6]. Cavitation is a process of violation of the homogeneity of the water layer with the formation and collapse of gas bubbles and their clusters. Previously, we studied the influence of water subjected to cavitation, the growth of fish, the destruction of dafny, on the blood of dogs [7]. – Chemical treatment of the optimal ratio of the reagent, as factor the most effective impact. – Ozonation and mechanical filtration, as a factor in the final oxidation treatment and mechanical separation of the precipitate, allowing to obtain the highest result of purification of water [8].

2 Materials and Methods The basis of the study solution was taken as untreated sewage pereslavskogo sugar factory. As mechanical purifying using a standard drum filter BF50 (capacity up to 50 m3 /h) with filter cell 40 microns. And then a carbon filter. Purification was carried out 2 times – preliminary and final after all the purifying procedures. As primary purifying systems were selected as follows: – Cavitation generator. Inventor design Nazarov Oleg Vladimirovich. The rotary type. The motor is 2.5 kW, the volume of the working chamber 19 * 10–3 m3 , the rotation speed of 2800 Rev/min With the cavitation number of 0.03. – Chemical treatment: (NH4)2SO4 (ammonium sulphate) and NaOCl (sodium hypochlorite). Reagents prepared in the form of aqueous solutions with different concentrations. – Ozonation. Used ozonator Altay 100, with a capacity of 0.3 C. ozone. The studies were conducted at initial solution of one party, while constantly keeping all parameters except modified. The accuracy of the provided 5-fold repetition of the measurements at each change. The definition of the procedure of purification was based on the literature research and comparative experimental database for key parameters. Originally applied cavitator were studied in the optimal time of cavitation. Initially, the use of the cavitator is justified by several factors: direct exposure to the sample, a

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change in the structure of the investigated sample with the aim of enhancing subsequent processing stages. Further method of purification has been defined the use of chemical reagents and finding the optimal ratio of the number entering, as the main active chemical compounds was chosen (NH4)2SO4 (ammonium sulphate) and NaOCl (sodium hypochlorite). The choice of these components was based on previous studies on the effectiveness of water purification of organic inclusions. The finishing stage of treatment is ozonation, which allows to fully oxidize the hydrolyzed compound of the preceding stage and the maximum display the remaining compounds in the sludge or completely oxidized to simple compounds (CO2, H2O). Chosen the optimal time of ozonation. To ensure purity of the experiment was conducted subsequent finishing mechanical treatment. As control devices the following items: Determination of the coefficient of light absorption (transparency) Spectrophotometer V-1100, which is a stationary tabletop laboratory device consisting of optomechanical and electronic units mounted in the housing. Spectrophotometer V-1100 constructed according to the single-beam scheme. The device uses a monochromator with a diffraction grating. A halogen lamp was used as a radiation source, and a photodiode as a receiver. The meassurement results are displayed on a multi-line graphic display. Control pH, ORP - pH 150 m. Temperature control - alcohol thermometer. Voltage and current control - universal multimeter. Table scales portioned CAS SWN-15 The analysis of the chemical composition of the test water according to the main necessary indicators after the purification was carried out in a certified laboratory of the sanitary-epidemiological station of the Voronezh region.

3 Results Carrying out cavitation processing. The cavitator of the inventor Nazarov Oleg Vladimirovich was used. Processing medium temperature (initial) 220 C. Electricity consumption 2.5 kW/h, working chamber volume 19 * 10–3 m3 , rotation speed 2800 rpm. With cavitation number 0.03. With cavitation with an increase in processing time, an increase in water temperature of more than 50% is observed. These changes correlate well with studies performed for tap water. The main focus of the study was the task of purifying the test composition and making optimal changes for subsequent exposures; therefore, when recording changes in pH, ORP, temperature, and absorption coefficients at various wavelengths, the latter was chosen for optimization. Distilled water was used as a reference solution. 5-fold repeatability of measurements with recording the average value [8] (Fig. 1). To determine the optimum values of time of cavitation by polynomial construction will make the corresponding functions and carry out a mathematical study describing the process.

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Time, min

Polynomial (300 nanometers)

Polynomial (800 nanometers)

Polynomial (500 nanometers)

Fig. 1. The dependence of the absorption coefficient at different wavelengths in the time of cavitation.

1) Function of the absorption coefficient at 300 nm. y = 0, 0002x2 − 0, 008 x + 0, 5452. Necessary condition for an extremum of functions of one variable. The equation f 0(x*) = 0 is a necessary condition for an extremum of functions of one variable, i.e. at the point x* the first derivative must vanish. It emits a stationary point XC, in which the function is increasing and not decreasing. A sufficient condition for an extremum of functions of one variable. Let f0(x) is twice differentiable in x belonging to the variety of D. If the point x* the condition: f  0(x∗) = 0, f  0(x∗) > 0, then the point x* is a point of local (global) minimum of the function. If at the point x* the condition: f  0(x∗) = 0, f  0(x∗) < 0, then the point x* is a local (global) maximum. Solution. Find the first derivative of the function: y = 0.0004 · x − 0.008. The computed values of the function at the endpoints of the interval f (20) = 0.465 f (0) = 0.545200000000000 f (25) = 0.470200000000000, fmin = 0.465, fmax = 0.545

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Find the intervals of increase and decrease. The first derivative. f  (x) = 0.0004 · x − 0.008. Find the zeros of the function. To do this, equate the derivative to zero 0.0004 · x − 0.008 = 0. Location: x1 = 20.0. In a neighborhood of the point x = 20.0 derivative of a function changes sign from (−) to (+). Hence, the point x = 20.0 - point minimum. Thus, the optimal time for cavitation to changes in the optical density at a wavelength of 300 nm is 20 min. 2) Function of the absorption coefficient at 500 nm Y = 0, 0006x2 − 0, 0189 x + 0, 6951, fmin = 0.68, fmax = 3.973. The computed values of the function f (15.75) = 0.546. Use sufficient condition for an extremum of functions of one variable. Find the second derivative: y = 0.0012. Calculated: y (15.75) = 0.0012 > 0 means the point x = 15.75 the minimum point of the function. Thus, the optimal time for cavitation to changes in the optical density at a wavelength of 500 nm is 15.75 min. 3) Function of the absorption coefficient at 800 nm y = 0, 0012x2 − 0, 0393 x + 0, 9942. Use sufficient condition for an extremum of functions of one variable. Find the second derivative: y = 0.0024 y (16.375) = 0.0024 > 0 means the point x = 16.375, the minimum point of the function. Thus, the optimal time for cavitation to changes in the optical density at a wavelength of 800 nm is 16.375 min. Where y – optical density, x is the time of ozonation. The main task of purification – decomposition of organic compounds to carbon dioxide and water, or removing the sediment, the presence of these organisms and the biological mass is most clearly

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reflected in the visible region of the spectrum. Was made of the absorption spectral analysis at different wavelengths in the visible spectrum. Represented the difference between the measurements is in the range of wavelengths from 300 to 800 nm, which is the main visible wavelength range. Ranging from the ultraviolet region to the infrared. The most visible part of the spectrum is 545 nm, however, the difference of the absorption coefficients at the extremes (300–800 nm) also indicates a change in the chemical composition of the investigated solution, and the observed trend of decreasing absorption coefficient at the visible wavelength indicates the destruction of the biomass present colored compounds and compounds causing opalescence in the solution. The most dangerous substance in the test solution is saponin, so removing it from the solution of the most priority. All saponins have in common the aglycone - oleanolic acid and spectrophotometry in the visible region of the highest absorption coefficient is determined for wavelengths 285–320 nm. So as the other biological substances in solution, have staining in the rest region of the visible spectrum and so require removal. Therefore, optimizing the time of cavitation takes into account the absorption spectra of the entire visible spectrum, but priority is given to changes in the wavelength of 300 nm. Given the minor effect of color reflected in the upper wavelengths of the optimum determined values of the degree of absorption at 300 nm – time cavitation 20 min. The holding stage chemical treatment if the initial solution and of the solution identified as optimal for cavitation. The use of different dosages of (NH4)2SO4 (ammonium sulphate) and NaOCl (sodium hypochlorite). Thus the conditions for chemical purification was determined identical stages of cavitation. The exposure time of all solutions with the addition of chemicals was 120 min. The surface changes of optical density for stage chemical purifying, respectively, of the initial solution [8] (Figs. 2, 3, 4, 5, 6 and 7).

Fig. 2. Change in the optical density of the solution at 300 nm in a different dosage of chemicals for the initial solution.

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Fig. 3. Change in the optical density of the solution at 500 nm in different dosages of chemicals for the initial solution.

Fig. 4. Change in the optical density of the solution at 500 nm in a different dosage of chemicals for the initial solution.

The findings of the chemical treatment. Building surfaces were tested using scatter plots of the approximation results.

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Fig. 5. Change in the optical density of the solution at 300 nm in a different dosage of chemicals for cavitation treated solution.

Fig. 6. The change in the optical density of the solution at 500 nm in a different dosage of chemicals for cavitation treated solution.

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Fig. 7. Change in the optical density of the solution at 800 nm in a different dosage of chemicals for cavitation-treated solution.

Subsequent differentiation shows the following values of optimal dosages to reduce the optical density. For wavelength 300 nm. The starting solution (NH4)2SO4 - 3,854% and NaOCl – 7,345%. Pre-cavitation of the treated solution (NH4)2SO4 - 3.6% and NaOCl – 6,495%. For a wavelength of 500 nm The starting solution (NH4)2SO4-4,183% and NaOCl – 7,975%. Pre-cavitation of the treated solution (NH4)2SO4-4,012% and NaOCl – 7,342%. For the wavelength of 800 nm. The starting solution (NH4)2SO4 - 3,912% and NaOCl – 4,156%. Pre-cavitation of the treated solution (NH4)2SO4 - 3,632% and NaOCl – 7,117%. Analyzing obtained data, we see the following patterns. The difference of changes of optical density for pre-treated water cavitation the chemical effects in the area of optimum values of the dosages of (NH4)2SO4 and NaOCl is 12.2%, which also shows the relevance of cavitation and the order of the product manufacturing operations. Using the priority value of the optical density at a wavelength of 300 nm (for a more complete elimination of saponins), the optimal dosages defined by (NH4)2SO4 - 3.6% and NaOCl – 6,495% for treatment after cavitation. Organoleptic description of the results of optimal chemical dosing. For the initial solution after cavitation for 20 min, and chemical treatment with doses of (NH4)2SO4 - 3.6% and NaOCl – 6,495%, we obtain the following figures.

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Dull beige color. Is the sharp smell of chlorine is observed at the bottom of the dark gray-green precipitate. On the surface of the liquid is observed foaming. Ph = 4,7. Ozonation. In previous studies it was obtained the optimal results for cavitation and chemical treatment solution. The optimal result for optical density at 300 nm as the most interesting content of saponin was determined by the following parameters: • time cavitation for 20 min; • the dosage of (NH4)2SO4 - 3,6%; • the Dosage Of NaOCl - 6,495%. Conducted ozonization of the resulting solution (Fig. 8).

Fig. 8. Dependence of optical density at various wavelengths during ozonation of a pre-chemically and cavitation-treated solution.

Mathematical study of the obtained dependencies. 1) Absorption coefficient function at 300 nm y = 0.00006x2 − 0.0039x + 0.0629

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x1 = 32.5. Calculate function values f (32.5) = −0.000475. We use a sufficient condition for the extremum of a function of one variable. Find the second derivative: y = 0.00012 We calculate: y (32.5) = 0.00012 > 0 , then the point x = 32.5 is the minimum point of the function. Thus, the optimal cavitation time for changes in optical density at a wavelength of 300 nm is 32.5 min. 2) Absorption coefficient function at 500 nm y = 0.00004x2 − 0.0032x + 0.066 y = 810 − 5 We calculate: y (40) = 8.0 10(−5) > 0 means the point x = 40 is the minimum point of the function. Thus, the optimal cavitation time for changes in optical density at a wavelength of 500 nm is 40 min. 3) Absorption coefficient function at 800 nm

y = 0.0001x2 − 0.0079x + 0.211 Find the second derivative: y = 0.0002 We calculate: y (39.5) = 0.0002 > 0, that means the point x = 39.5 is the minimum point of the function. Thus, drawing conclusions from the above, we obtain the following optimal processing values:

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• • • •

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cavitation time 20 min; dosage of (NH4) 2SO4 - 3.6%; dosage of NaOCl - 6.495%; ozonation time 32.5 min.

The resulting solution was analyzed according to the parameters necessary for assessing water quality before discharge into the ecosystem. The data obtained show the water quality is not worse than the source, and in most respects even exceeds the source water taken for production (Table 5). Table 5. The final indicators of the water to be treated water for an optimal technological regime of treatment. INDICATOR Temperature˚С Color Smell Transparency, cm Suspended Substances, mg / L PH reactive media COD m2 / l BOD5 m2 / l Solids, m2 / l Hardness, m2 - equiv / l: 1. general; 2. carbonate.

MAXIMUM VALUE 25 Without color Without smell 25 70 6,5-7,5 210 190 1200 12 6

4 Conclusion The work done is individual for a given solution and its ratio of organic inclusions, however, certain trends discussed in the article will be adequate and applicable to similar organic solutions and ultimately will determine the ultimate universal concept and approach to the treatment of both wastewater and others liquids requiring various types of exposure. The optimization method for processing the test solution can be expanded and can be applied for optimization according to other studied factors, including the economic component, which will allow us to approach the optimal method of wastewater treatment by the optimal ratio of all significantly affecting parameters.

References 1. Dubrovskaya, O.G., Kulagin, V.A., Kurilina, T.A.: Intensification of biological wastewater treatment processes of the food complex companies on the basis of hydro-thermodynamic cavitation. J. Sib. Fed. Univ. Eng. technol. 11(5), 584–590 (2018). https://doi.org/10.17516/ 1999-494X-0057

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2. Gude, V.G.: Synergism of microwaves and ultrasound for advanced biorefineries. Resour. Effi. Technol. 1, 116–125 (2015). https://doi.org/10.1016/j.reffit.2015.10.001 3. Wang, H., Fu, P., Li, J., et al.: Separation-and-recovery technology for organic waste liquid with a high concentration of inorganic particles. Engineering 4, 406–415 (2018). https://doi. org/10.1016/j.eng.2018.05.014 4. Van den Berg, F., Lyndgaard, ChB., Sørensen, K.M., Engelsen, S.B.: Process analytical technology in the food industry. Trends Food Sci. Technol. 31, 27–35 (2013). https://doi.org/10. 1016/j.tifs.2012.04.007 5. Cravotto, G., Cravotto, C.H., Veselov, V.V.: Ultrasound- and Hydrodynamic-cavitation assisted extraction in food processing. In: Reference Module in Food Science (2019). https://doi.org/ 10.1016/B978-0-08-100596-5.22956-9 6. Kim, I., Lee, I., Jeon, S.H., Hwang, T., Han, J.-I.: Hydrodynamic cavitation as a novel pretreatment approach for bioethanol production from reed. Biores. Technol. 192, 335–339 (2015). https://doi.org/10.1016/j.biortech.2015.05.038 7. Vatin, N.I., Chechevichkin, V.N., Chechevichkin, A.V., Shilova, Y., Yakunin, L.A.: Application of natural zeolites for aquatic and air medium purification. Appl. Mech. Mater. 587–589, 565–572 (2014). https://doi.org/10.4028/www.scientific.net/AMM.587-589.565 8. Petkovšek, M., Zupanc, M., Dular, M., et al.: Rotation generator of hydrodynamic cavitation for water treatment. Sep. Purif. Technol. 11830, 415–423 (2013). https://doi.org/10.1016/j.sep pur.2013.07.029

Experimental Calculation of the Main Characteristics of Thermoelectric EMF Source for the Cathodic Protection Station of Heat Supply System Pipelines Vladimir Yezhov(B)

, Natalia Semicheva , Aleksey Burtsev , and Nikita Perepelitsa

Southwest State University, 50 let Oktyabrya Street, 94, Kursk 305040, Russia [email protected]

Abstract. The scientific paper considers the design of an experimental thermoelectric power source for cathodic protection station of heat network pipelines from electrochemical corrosion; It allows you to utilize lower-grade heat with subsequent direct conversion into electricity in thermoelectric converters which are made of two metals with different thermionic properties using the effect of thermoelectricity. In this case, the generated electric current can be used as an autonomous power supply for the cathodic protection station. The experimental technique has been developed, as well as experimental studies have been performed with the subsequent analysis of the main characteristics of thermoelectric generator. Keywords: Thermoelectricity · Power supply · Efficiency · Autonomy · Pipeline

1 Introduction At present, thermoelectric modules are actively used in such high-tech areas as telecommunications, space, high-precision weapons, medicine, etc. Thermoelectric modules are also actively used in household appliances: portable refrigerators, freezers, drinking water and soft drinks coolers, compact air conditioners, etc. Thermoelectricity is the phenomenon of direct conversion of heat into electricity in conductors, as well as the reverse phenomenon of direct heating and cooling of the soldered junctions of two conductors by let-through current. The transition of thermal energy into electrical energy occurs in thermoelectric converters. A thermoelectric converter is a pair of conductors made of different materials connected at one end. When one of the junctions of an element is heated more than the other, a thermoelectric effect occurs [1]. Thermoelectric converters are used to produce electricity by directly converting heat into electricity. When a thermoelectric module connected to an electrical circuit is heated, electricity is generated. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 225–237, 2021. https://doi.org/10.1007/978-3-030-57453-6_19

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Thus, one of the main tasks ensuring the large-scale application of thermoelectricity is the development of thermal batteries made of cheap and affordable materials [2].

2 Experimental An experimental set-up has been developed to solve this problem [3]. There have also been conducted experiments on the basis of which a method for calculating the main characteristics of thermoelectric elements has been developed. Heated air from an electric heater was used as a heat transfer medium (operating environment) in the experimental set-up. Experiments on the study of heat transfer between the thermoelectric section and the pipeline were carried out in the following sequence: – turning on an electric air heater (hot air gun) with an adjustable flow rate of heated air, followed by heating until a steady-state condition is reached; – installation of verified multimeters at the inlet and outlet of the thermoelectric generator; – recording of multimeter output (current strength, voltage, resistance, temperature); – recording of anemometer output relative to the velocities at the outlet of thermoelectric sections. The number of thermal emission elements – 400 pcs. Air heater power – 2500 W. Hot air flow rate = 400 l/min (24 m3 /h). The length of the pipeline is 0.5 m. Outer diameter d1 of the pipe and the wall thickness δ1 are 59 mm and 3 mm respectively. (d2 = 50 mm – inner diameter) according to GOST 3262-75. Heat exchange surface area of thermoelectric sections Fh = 0.02 m3 /h. Coefficient of steel thermal conductivity λ1 = 20 W/m°C. Air supply volume is 107 m3 /h. Fan power is 14 W. The temperature of inside air in the laboratory room tv = 28 °C. The main characteristics of thermal emission elements made of chromel and copel are: – thermoelectric coefficient α = 12,97 · 10−3 V/K; – Q-factor Z = 2,8 · 10−3 K−1 ; – electric conductivity coefficient σ = 8 · 104 Om−1 · m−1 . TEC1-12705 semiconductor elements dimensions – 40 × 40 × 6 mm. The number of n and p elements – 400 pcs. Nominal voltage – 12 V, current strength – 4.3–4.6 A. Optimal temperature range of operation – from 55 to 83 °C. Internal resistance – 2.5–2.8 Om. Cooling capacity – 50–60 W. The scheme of the experimental set-up with metal thermoelectric converters made of chromel and copel is shown in Fig. 1. The blue arrows in the scheme show cold air streams coming through the slits by either creating flue effect or by the installed axial fan. The red arrows indicate the direction of hot air flow from the heater.

Experimental Calculation of the Main Characteristics

227

Fig. 1. Scheme of experimental set-up: 1 – protective casing; 2 – axial fan; 3 – slit for air intake; 4 – space for the movement of cold air; 5 – thermoelectric sections; 6 – steel pipes; 7-mounting ring.

3 Evaluation Experiment 1 was conducted without the use of thermal insulation and cooling system reckoning in order to determine heat loss from the pipe where the thermoelectric generator had been installed (Table 1). Table 1. Experimental data without the use of thermal insulation. No.

Temperature t1, °C

Temperature t2, °C

Voltage, V

Current strength, mA

1

70

45

0,32

59,4

2

130

60

0,35

67

3

220

100

0,39

73,3

4

290

130

0,41

84,5

5

300

150

0,43

90,5

6

360

180

0,46

95,3

The use of thermal insulation in experiment 2 (Table 2) allowed us to increase the generated thermal electromotive force (further as the text goes EMF) and current strength by 25–28%. This was made possible by a more equilibrium distribution of temperature field across the surface of thermoelectric converters and cutting off the heat flow from the pipe surface.

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V. Yezhov et al. Table 2. Experimental data with the use of thermal insulation.

№

Temperature t1, °C

1

70

2

130

3

220

4

290

5 6

Temperature t2, °C 45

Voltage, V

Current strength, mA

0,4

74,3

60

0,55

105,3

100

0,7

131,6

130

0,8

164,9

300

150

0,88

185,2

360

180

1,1

227,9

In experiment 3, a tube axial fan was used to increase cooling intensity. The lack of thermal insulation did not affect the growth of the experimental set-up capacity by another 17.5%. The data are given in Table 3. Table 3. Experimental data without the use of thermal insulation and with the installation of a tube axial fan. № Temperature Temperature Temperature Temperature Speed, Voltage, Current t1, °C t2, °C tin1, °C tin.2, °C m/s V strength, mA 1

70

45

28,3

29,4

4,10

0,47

78,4

2

130

60

28,4

41,3

4,10

0,5

87,1

3

220

100

28,3

42,9

4,10

0,62

96,8

4

290

130

28,3

44,3

4,10

0,66

107

5

300

150

28,3

45,3

4,10

0,68

120,5

6

360

180

28,4

46,5

4,10

0,7

125,8

Experiment 4 has shown a significant increase in the capacity of the experimental set-up due to the use of thermal insulation and axial fan. As can be seen from Table 4, Table 4. Experimental data using thermal insulation and tube axial fan. № Temperature Temperature Temperature Temperature Speed, Voltage, Current t1, °C t2, °C tin1, °C tin.2, °C m/s V strength, mA 1

60

45

28,3

29,4

4,10

0,45

40

2

120

60

28,4

31,4

4,10

0,6

80

3

220

100

28,3

33,2

4,10

0,93

170

4

260

130

28,3

34,4

4,10

1,2

215

5

320

150

28,3

35,6

4,10

1,56

279,5

6

410

180

28,4

36,9

4,10

2,03

363,35

Experimental Calculation of the Main Characteristics

229

the indicators grew on average by 2.3 times, and at peak load conditions by 2.9 times. At the same time, the thermoelectric converters did not overheat – the temperature of discharge air through the axial fan remained in the range of 41.3–46.5 °C. Also, the experimental data are shown in the form of graphs (Figs. 2 and 3). Installing the protective casing in experiment 5 (Table 5), slightly reduced the capacity of the set-up. This is due to a decrease in the area, intensity and rate of heat removal from the thermoelectric sections. On average, the decline was equal to 29.4%. Table 5. Experimental data using thermal insulation and protective casing. №

Temperature t1, °C

Temperature t2, °C

Current strength, mA

Voltage, V

1

65

45

0,36

66,8

2

130

60

0,53

101,5

3

190

95

0,68

127,8

4

260

120

0,86

177,2

5

320

140

1,2

252,6

6

410

170

1,6

331,5

450

2.50

410

400 350 300

260

250

1.56

1.50

220 1.20

200 150 100

2.03 2.00

320

120 0.45

50

60

0

29.40 1

1.00

0.93 0.60

31.40 2

Temperature t1,

0.50

33.23 3

34.42 4

35.65 5

Temperature tin.2,

36.93 6

0.00

Voltage, V

Fig. 2. Voltage dependence on temperature difference between cold and hot junctions.

230

V. Yezhov et al.

450

363.35 350.00

400 350

320 260

250

220

200

0

250.00 215.00

200.00

170.00

150

50

300.00

279.50

300

100

400.00

410

150.00

120

100.00

80.00

60

50.00

40.00 29.40 1

31.40 2

temperature t1,

33.23 3

34.42 4

35.65 5

temperature tin.2,

36.93 6

0.00

current, mA

Fig. 3. Dependence of current strength on temperature difference between cold and hot junctions.

When developing thermoelectric generators, you can use not only metal converters, but also semiconductor elements (Peltier elements). Due to their compact 40 × 40 mm size and 6 mm thickness they can contain up to 400 semiconductor elements. But the essential difference between Peltier elements and metal converters is the need for external intensive cooling. To confirm the theoretical calculations, an experimental set-up was made based on semiconductor thermoelectric converters. The experimental set-up is shown in Fig. 4. The blue arrows indicate the flow of cold air coming through the slits by either creating flue effect or by the installed axial fan. The red arrows show the direction of hot air flow from the heater. The experiment having been conducted (Table 6), the dependence of the generated thermal EMF on the use of intensive cooling was confirmed. When the temperature reached 110 ◦ C (maximum operating temperature), the experimental set-up power attained a maximum, then as a result of oversaturation and the inability of both the passive and active cooling system to cope with the heat coming from the hot side, the electrical performance began to decline. Graphs were constructed to visualize the experiment, (Figs. 5 and 6).

Experimental Calculation of the Main Characteristics

231

Table 6. Experimental data using Peltier elements with thermal insulation and axial fan as cooling means. №

Temperature t1, °C

Temperature t2, °C

Temperature tv1, °C

Temperature tv.2, °C

Speed, m/s

Voltage, V

Current strength, mA

1

60

45

28,3

29,4

4,00

1

159

2

70

55

28,4

40,6

4,00

1,05

164

3

80

60

28,3

51,7

4,00

1,1

170

4

90

75

28,3

62,8

4,00

1,25

176

5

100

90

28,3

73,9

4,00

1,34

183

6

110

100

28,4

85,0

4,00

1,50

190

7

120

110

28,4

96,1

3,95

1,44

187,4

8

130

120

28,4

107,2

3,92

1,3

181,3

9

140

135

28,4

118,3

3,92

1

168,1

10

150

140

28,4

129,4

3,92

0,95

165,9

11

160

155

28,4

140,4

3,91

0,8

159,4

Fig. 4. Experimental set-up with Peltier elements: 1 – protective casing; 2 – elements’ cooling system; 3 – axial fan; 4 – the pipe element with thermal insulation; 5 – 40 × 40 mm Peltier elements; 6 – fastening elements; 7 – slit for cold air intake.

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1.6

180 1.5

160

1.44

1.34

1.3

1.25

140 120

1.05

1

1.1

107.2

100

118.3 1

0.95

96.1

90 73.9

70 51.7

0.4

40.6

40 29.4

20

1

0.6

62.8

60

1.2

0.8 0.8

85.0

80

60

129.4

120 110

1601.4 140.4

140

130

100 80

150

0.2 0

0 1

2

3

4

5

temperature t1,

6

7

8

temperature t2,

9

10

11

voltage, V

Fig. 5. Dependence of the voltage generated by Peltier elements on the temperature of hot and cold junctions.

Calculation of the thermoelectric generator №1 main parameters. The calculation is observed according to the method [4]. The data from Table 4 p. 2 is used as the data source. Hot junction temperature, °C: t1hc =

120 + 60 = 90 ◦ C. 2

Cold junction temperature, °C: tBcl =

28, 4 + 31, 4 ≈ 30 ◦ C. 2

Thermophysical properties of air at pressure P = 1,013 · 103 Pa are determined by reference data [4] at temperature: t1 = 90 ◦ C: λ1 = 0, 0313 W/m2 · ◦ C, v1 = 22, 10 · 10−6 m2 /s, Pr 1 = 0, 69. Internal pipe diameter d1 = 0,05 m.

Experimental Calculation of the Main Characteristics 180

195.0

190.0

160

187.4

160 183.0

120

176.0

100

110 100

170.0 90

80 159.0 60

140.4

140 129.4

107.2 96.1

168.1

170.0

165.9

73.9

165.0 159.4

62.8

40.6 40

185.0

175.0

51.7

60

190.0

180.0

118.3

85.0

80

164.0 70

150 181.3 130

140 120

233

160.0 155.0

29.4

150.0

20

145.0 140.0

0 1

2

3

4

temperature t1,

5

6

7

8

9

temperature t2,

10

11

current, mA

Fig. 6. Dependence of the current generated by Peltier elements on the temperature of hot and cold junctions.

External pipe diameter d2 = 0,059 m. Thermophysical properties of air at pressure P = 1,013 · 103 Pa are determined by reference data [4] at temperature: t2 = 30 °C: λ2 = 0, 0267 W/m2 · ◦ C, v2 = 16, 0 · 10−6 m2 /s, Pr 2 = 0, 701. Reynolds criterion 1 Re1 = w1v·d , 1 4,1·0,05 Re1 = 22,1·10−6 = 9276.

(1)

Under the Reynolds calculation criterion, the performance is turbulent, hence the Nusselt criteria equation will have the form: Nuhc

0,43 Nuhc = 0, 037 · Re0,8 1 · Pr 1 , 0,8 0,43 = 0, 037 · 9276 · 0, 69 = 47, 1.

(2)

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Calculation of heat transfer coefficient coming from the air to the inner wall of the pipe α1, W/m2 · °C: α1 = Nu1 · λd11 , 2 ◦ α1 = 47, 1 · 0,0313 0,05 = 29, 5 W/M · C.

(3)

Grasgof’s criterion 

Gr = g

· d23 · 

Gr = 9, 81 · 0, 0593 ·

1 273+t

  ·(t −tX )

2  v2  1 ·(90−30) 273+90

(16·10−6 )2

, (4)

= 13, 0 · 106 .

Nusselt criteria equation: , Nu2 = 0, 5 · (Pr · Gr)0.25  20,25 6 Nu2 = 0, 5 · 0, 701 · 13 · 10 = 15, 5.

(5)

Calculation of heat transfer coefficient [5, 6] coming from the outer surface of the pipe to the thermoelectric sections α2 W/m2 · °C: α2 = Nu2 · λd22 , 2 ◦ α2 = 15, 5 · 0,0267 0,059 = 7 W/M · C.

(6)

Calculation of heat transfer coefficient, W/(m°C): K1 = K1 =





 1 + (α1 ·d1 )



1 2·λ

1   d ·Ln d2 + 1

 1    0,059 1 1 1 + 2·20 ·Ln 0,05 + (7·0,059) (29,5·0,05)

1

,

(α2 ·d2 )

(7)

= 0, 32 W/M2 · ◦ C.

Linear heat flow, W/m: (8) The amount of heat released from the 300 mm open line at this temperature difference is Qh = 60, 3 × 0, 3 = 18, 1 W. At a temperature of 120 °C, we determine the main parameters of the generated electrical power: – voltage, V U = 0,6 V

Experimental Calculation of the Main Characteristics

235

– current, mA: I = 80 mA According to the procedure given in [7]. The auxiliary coefficient is calculated by the formula:

m=



m=

  1 + 0, 5 · Z · t1hc + t2cl ,

(9)

1 + 0, 5 · 2, 8 · 10−3 · (90 + 30) = 1, 08.

Resistance of thermionic converter, Om: R=

  α· t1hc −t2cl ·N ,    I · 1+0,5·Z· t1hc +t2cl −1

−3 ·(90−30)·400 12,97×10  √ 0,08· 1+0,5·2,8·10−3 ·(90+30)−1

R1 =

(10)

= 9493, 1 Om.

Electric power being transferred to the external circuit, W   (2·N ·α)2 · t1hc −t2cl · m 2, R (m+1)   2 2·400·12,7·10−3 ·(90−30) 1,08 · = 9493,1 (1,08+1)2

P=

P=

(11) 0, 163 W.

Performance factor, %: η= η=

0,163 18,1

P Qh

× 100%,

(12)

× 100% = 0, 9%.

According to the present procedure, when calculating thermoelectric generator parameters using metal thermoelectric converters efficiency at average temperature of hot = 295 ◦ C and cold junctions tBcl = 28,4+36,9 = 33 ◦ C will be 1.32%, t1hc = 410+180 2 2 which is 1.46 times more than the initial efficiency. Calculation of the thermoelectric generator №2 main parameters [7]. The data from Table 6 p. 1 is used as the source data. At 60 °C temperature we determine the main indicators of electricity generated by one Peltier element: – voltage, V U = 1, 44 V – current, mA: I = 187 mA

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Auxiliary coefficient:

m = 1 + 0, 5 · 2, 8 · 10−3 · (90 + 30) = 1, 08. Thermoelectric converter resistance, Om: R1 =

3, 7 × 10−3 · (90 − 30) · 280 

 = 811 Om. 0, 187 · 1 + 0, 5 · 2, 8 · 10−3 · (90 + 30) − 1

Electric power output to external circuit by one thermoelectric converter of Peltier element, W  2 2 · 280 · 3, 7 · 10−3 · (90 − 30) 1, 08 = 0, 032 W. P= · 811 (1, 08 + 1)2 Performance factor, %: η=

0, 032 × 100% = 0, 18%. 18, 1

To determine the power of the element cooling system, it is necessary to calculate the cooling power of one Peltier element, W: Qo , εmax

Po =

(13)

Cooling capacity of the thermal element taking into account losses is determined from the expression [7, 8]: Qo =

3, 7 · 10−3

Qo = α · Tx · I − 0, 5I 2 R − λ(T − Tx ), · 30 · 0, 187 − 0, 5 · 0, 1872 · 811 − 0, 5(90 − 30) = −44, 1 W. (14)

The maximum cooling coefficient of the reverse cycle of the thermoelement, in which the role of the working substance is performed by the electronic gas and there is no irreversible loss, is defined by the formula [8]: T

εmax = εmax =

30 90−30

Po =

Tx T −Tx

·

·

M − Tx M +1

1,08− 90 30

−44,1 −046

1,08+1

,

= −0, 46,

(15)

= 95, 9 W.

The amount of heat that hot junction emits will be more than the heat that cold junction absorbs by the amount of electricity costs: 

Qh = Po + Qo , Qh = 95, 9 + (−44, 1) = 51, 8 W. 

(16)

For this design value it is necessary to select the cooling system for Peltier element.

Experimental Calculation of the Main Characteristics

237

4 Conclusions 1. The designs of thermoelectric generators for heat supply systems using both metal and semiconductor converters have been proposed. 2. The experimental method has been developed. 3. The experimental studies with the subsequent analysis and calculation of the main parameters of heat and mass transfer with the help of laboratory set-up being used for thermoelectricity generation have been presented. 4. The dependence of the generated electric power and the thermoelectric generator on the cooling system design has been established. 5. Peltier elements can be used in low-potential heat recovery systems with temperatures up to 800 c, and an active cooling system must be provided. 6. The thermoelectric converters made of chromel-copel pairs can be used at temperatures above 1500c, in these circumstances, the use of a passive cooling system is sufficient.

References 1. Ezhov, V.S., Semicheva, N.E., Burcev, A.P., Perepelica, N.S., Ermakov, D.A., Burcev, A.P.: Mezhdunarodnaya nauchno-prakticheskaya konferentsiya. Sovremennye problemy v stroitel’stve: postanovka zadach i puti ih resheniya, 225–233 (2019) 2. Ezhov, V.S., Semicheva, N.E., Burcev, A.P., Zenchenkov, V.I., Ermakov, D.A.: Izvestiya Yugo-Zapadnogo gosudarstvennogo universiteta 23(2), 74–84 (2019) 3. Yezhov, V., Semicheva, N., Pakhomova, E., Burtsev, A., Brezhnev, A., Perepelitsa, N.: International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018, vol. 2, pp. 670–678. Springer Nature Switzerland AG (2018) 4. Salova, T.Y.: Processy diffuzii i teplomassoperenosa. SPbGAU, Sankt-Peterburg (2018) 5. Bajkov, V.I., Pavlyukevich, N.V., Fedotov, A.K., SHnip, A.I.: Teplofizika: neravnovesnye processy teplomassoperenosa. Vyshejshaya shkola, Minsk (2018) 6. Vidin, Y.V., Zlobin, V.S., Ivanov, D.I.: Nestacionarnyj teploperenos v neodnorodnyh konstrukciyah krivolinejnoj konfiguracii. SFU, Krasnoyarsk (2016) 7. Novotel’nova, A.V., Asach, A.V., Tukmakova, A.S., Samusevich, K.L.: Metody issledovaniya teploprovodnosti, elektroprovodnosti i koefficienta Zeebeka. ITMO, Sankt-Peterburg (2019) 8. Pozdeev, A.G., Kotlov, V.G., Kuznecova, Y.A.: Dinamicheskie teploobmenniki. PGTU, Joshkar-Ola (2019) 9. Lokonova, V.D., Kolomiec, M.A.: Termoelektricheskij modul’ pel’t’e: ustrojstvo, princip dejstviya, harakteristiki Volgodonskij inzhenerno-tekhnicheskij institut Filial Nacional’nogo issledovatel’skogo yadernogo universiteta "MIFI", g. Volgodonsk 1(05), 49–52 (2018) 10. SHishov, K.A., SHiryaev, P.P.: Issledovanie zavisimosti vyhodnoj moshchnosti termoelektricheskoj batarei ot vneshnej nagruzki MGTU im. N.E. Baumana 7, 70–71 (2017)

Modeling Using Conformal Mapping of a Temperature Field Around a Hot-Water System for Channel-Free Laying Aleksandr Loboda , Sergei Chuikin(B)

, Elena Plaksina , and Lyudmila Gulak

Voronezh State Technical University, 20-Letiya Oktyabrya Str., 84, Voronezh 394006, Russia [email protected]

Abstract. The article deals with the development of methods for mathematical modeling of a temperature field around a hot-water system for channel-free laying by means of conformal mapping. A major disadvantage of the existing numerical methods for designing temperature fields around pipelines of heat supply systems is a high likelihood of errors due to instability of suggested solutions and convergence problems that still remained unaddressed. These solutions can be made more accurate by using analytical calculation methods, e.g., the conformal mapping method. An essential characteristic of a model in question is a possibly accurate analytical solution for designing temperature fields and streamlines. The implementation of various available functions in symbolic mathematical packages (in particular, linear-fractional ones) retains a high accuracy in numerical studies of the models. Using mathematical models for designing streamlines and temperature fields by means of the theory of conformal mappings, a solution can be obtained that is as identical as possible to the analytical one, which would ultimately enable us to improve the accuracy of the results. These results can be employed in design and reconstruction of heat supply systems. Keywords: Heat losses · Heat supply · Temperature field · Conformal mapping · Heat supply networks · Channel-free laying · Energy-saving · Energy-efficiency

1 Introduction Increasingly demanding requirements for energy-efficiency of modern centralized heating systems are making it necessary to reduce heat loss while heat energy is transported. A considerable amount of heat loss is one of the major limiting factors for the use of centralized heat systems while deciding on a heat supply option. Therefore a great deal of attention in design and reconstruction of heat supply systems should be paid to the accuracy of determining heat losses in pipelines. Currently, underground channel-free pipeline laying has become most commonly used in construction of urban heat systems. According to the existing methods [1], corresponding heat losses can be identified both by means of aggregated indicators and more accurate mathematical models based on © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 238–246, 2021. https://doi.org/10.1007/978-3-030-57453-6_20

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design of temperature fields in soils surrounding pipelines. In accordance with the regulatory documents [2], heat losses by a single pipeline can be given by the following formula. τ − tH (1) Q=  4heq dion 1 1 2π λi ln diin + 2π λso ln don where ton is the temperature of the outside air, °C; don is the external diameter of the pipeline, m; λso is the thermal conductivity of soil, Watt/(m·°C); heq is the equivalent depth of the pipe laying, m (heq = h + (λso /α), α is the heat exchange coefficient from the soil surface up to the air, Watt/(m2 ·°C)); dion . diin are the diameters of the external and internal i-th layers of insulation, m; λi is the thermal conductivity of the i-th layer of isolation, Watt/(m·°C); τ is the average temperature of a heat carrier, °C. Figure 1 shows a temperature field around a single pipeline and streamline (a thermal flow direction).

Fig. 1. Scheme of a temperature field and streamlines (thermal flow directions) of a single pipeline [2].

In [2] it is noted that the resistance of soil, (m·°C)/Watt is determined using the Forchheimer equation that takes the following form: ⎛ ⎞    2heq 2 2heq 1 Rso = ln⎝ + − 1⎠. (2) 2π λso don don In practice single-pipe heating systems are uncommon. Two-pipe systems with supply and return pipelines are most commonly used (Fig. 2). Thus as the temperatures of the supply and return pipelines are not identical and their temperature fields interact, it was suggested that additional thermal resistance was introduced [1, 2].   2 1 2h ln 1 + , (3) R0 = 2π λso b

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where b is the distance between the axis of the pipes, m; h is the depth of the pipe laying (the distance from the soil surface to the axis of the pipes), m.

a)

b)

Fig. 2. Scheme of the heat supply system for two-pipe channel-free laying: a) a calculation scheme of the distribution of the soil temperature at a random point [2]; b) a scheme of the temperature field around a two-pipe heating system [5]; T so is the soil temperature; T fe is the temperature of the supply pipeline; T re is the temperature of the return pipeline; b is the distance between the axes of the pipes; h is the depth of the pipe laying; A is a random point with the coordinates xA and yA .

Considering a mutual influence of the supply and return pipelines, the total heat loss is determined as the sum of the losses of the two pipelines that can be given by the following formulas [1, 2] (τ1 − ton )R2 − (τ2 − ton )R0 , R1 R2 − R20 (τ2 − ton )R1 − (τ1 − ton )R0 Q2 = , R1 R2 − R20

Q1 =

(4) (5)

where Q1 and Q2 are the heat losses of the supply and return pipelines respectively, Watt/m; τ1 and τ2 is the temperature in the supply and return pipeline, °C; R1 and R2 is the thermal resistance of the supply and return pipeline including that of the soil and insulation, (m·°C)/Watt. In the meantime, the temperature field of a two-pipe heating system for channel-free laying can be designed using the following dependence:   x2 + (y + h)2 Q1 Q2 (x − b)2 + (y + h)2 ln + ln , (6) tx,y = ton + 2π λso 2π λso x2 + (y − h)2 (x − b)2 + (y − h)2 where x and y are the coordinates of the point where the temperature is determined, m (the coordinate axes go through the centre of the supply pipeline). The results of a more accurate numerical modeling of the temperature field of a two-pipe heating system are given, e.g., in [3, 4]. In this case, the thermal regime of the pipelines is investigated by means of a method based on solving a differential heat equation in cylindrical coordinates with a number of assumptions (the results of designing the temperature field are shown in Fig. 3b).

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While solving the equations used in the above studies, a considerable number of calculations is required. Errors in these calculations might affect the accuracy of the desired temperature and the correctness of the final picture of streamlines (thermal flow directions). The mathematical models employed in this method are investigated using numerical methods. Therefore developing models that are as identical as possible to analytical ones is increasingly important. One of the approaches to the practical issues arising in heat supply and ventilation systems [4, 5] is the one based on methods of the theory of functions of a complex variable. One of these methods is the conformal mapping method. Among other things, it can be employed in order to calculate plane harmonic vector fields, i.e., those whose vectors are parallel to some plane X [6–8]. The main objective of conformal mapping is to design functions that map one area onto another. Let us consider in more detail the features of the application of this method in modeling the temperature field around a heat pipe for channel-free laying.

2 Materials and Experiments While looking at the simplest case of designing a temperature field in the soil around a pipeline, several restrictions should be made. Firstly, a pipeline must be considered homogeneous (without several layers), whereas in fact, a pipeline is a multi-layer structure that consists of one or more layers of heat and water insulation and a pipeline itself, with each of the layers possibly having different thermal and physical properties. Secondly, a thermal flow (heat loss) of a pipeline should be considered constant and even in length. A picture of the temperature fields emerging in soil by an individual pipe can obviously be obtained from the picture for a concentric circular ring due to a conformal (and even a linear fractional) mapping of a half-plane with a circular cut onto such a ring as shown in Fig. 3.

Fig. 3. Conformal (linear fractional) mapping of the half-plane with a circular cut w onto a ring.

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Inside the ring, the isotherms are naturally seen as circles (with the same center shared by the two circles enclosing the ring) and the streamlines (heat distribution) as radii. In Fig. 3, the points A(0, −i(h − r)) and B(0, −i(h + r)) denote the surface points of the transformed pipeline located on the axis OY. The axis goes through the center of the circle of the pipe with the coordinates (0, −ih) and the origin is at point 0. The points A* and B* are located on the inner circle of the ring. The point 0*(0, i/b) lies on the outer surface of the ring, the point C*(0, i/(2b)) is the center of the ring being transformed. Note. For a complete description of the picture, it is necessary to understand the intensity of a temperature drop along the radii considering the thermal resistance of the soil. As a matter of fact, this can be found out by means of an experiment in the soil (e.g., on a section from the surface to the pipe corresponding to an individual radius on the ring being modeled). The rates of temperature change at all the radii can be considered identical (at least in the initial version of the model), hence the information about an individual section will allow the whole picture to be restored (Fig. 4).

Fig. 4. Scheme of the isotherm and streamlines of a single pipeline of a heating network using conformal mapping.

As was previously noted, in fact, single-pipe heat supply systems are uncommon. For two pipes in the soil there are a lot of different particular tasks. E.g., the depths h1, h2 of the laying of pipes, the radii r1, r2 of these pipes as well as the temperatures T1, T2 on the surface of the pipes are normally considered in the model. The simplest problem involves two pipes where all the parameters (h, r, T) are identical. A half-plane with two such round cuts can be conformally mapped onto a (large) circle with two round (small) cuts (of the same radius) arranged symmetrically (“a mask with eyes”). It can be shown that these cuts can be arranged in the same diameter (Fig. 5).

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Fig. 5. Conformal (fractional linear) mapping w of the half-plane with two circular cuts onto the circle with two round (small) cuts (of the same radii).

It is also possible when two pipes with the same cross section are located at different depths. Such a problem (Fig. 4) obviously comes down to the above problem (Fig. 5) with a few corrections to be made. Normally, the diameters of the return and supply piping may not coincide and can be at different depths. This formulation of the problem can also be reduced to linear fractional transformations.

Fig. 6. Conformal (fractional linear) mapping w of the half-plane with two circular cuts at different laying depths onto the circle with two round cuts.

The problem regarding the fields in the “mask with eyes” appears to be an easier one to investigate due to the limitations of such an area (as opposed to an unlimited half-plane with cuts).

3 Results Following the fractional linear transformation w 1 = ω, z − jb

(7)

the points A, B and 0 (Fig. 3) are transformed into the internal points of the circle of the ring A*, B* and 0* respectively, i.e., A : −i(h − r) →

i , h−r+b

(8)

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B : −i(h + r) → 0:0→

i , h+r+b i . b

(9) (10)

Following the transformation the start of the coordinates 0 lies in the external surface of the ring with the coordinates 0*(i/b) with the centre of the circle of the transformed pipeline at the point C*(i/(2b)). Then if

b = h2 − r 2 , (11) the distance A∗ C ∗ =



 1 1 − , h − r + b 2b

(12)

 1 1 − . 2b h + r + b

(13)

equals the distance ∗



∗

B C =

Considering the variant shown in Fig. 6 with the limitations we get a1 + a2 = a = const, r1 = r2 = r, h1 < h2 , and an extra condition a2 < h22 − h21 , it can be shown that

 ∀t ∈

h2 − h12 0, 2 2a

(14)

∃! b > 0,

where the scheme in Fig. 6 is employed. Therefore the mapping ω=

1 , z − (t + ib)

(15)

transforms the half-plane with two identical cuts into a circle with two identical cuts.

4 Discussion In fact, while calculating heat losses in pipelines of heat supply systems using methods based on enlarged parameters or solving a system of complex differential equations, there might be errors that affect correctness of the desired solution. Its accuracy can be improved by means of analytical calculation methods and the conformal mapping method

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is certainly one of these. A limited number of approximate functions are normally used in computer calculations using this method making the solution, in effect, an analytical one. An important characteristic of the model in question is a possibility of an accurate analytical solution to designing temperature fields and streamlines. The implementation of linear fractional functions in packages of symbolic mathematics retains a high accuracy in numerical study of models. It should be noted that the above problem of describing temperature fields in a large circle with two small circular cuts obviously requires elaborate numerical modeling - not only qualitative considerations based on conformal mappings. In numerical modeling, issues related to the difference in the radii of two pipes and the temperatures on their surfaces seem to become of less importance.

5 Conclusions The existing methods of mathematical modeling of temperature fields in soil around pipelines of heat supply systems for channel-free laying based on the solution of complex systems of differential equations normally involve an overwhelmingly large number of computer calculations. As a result, they become more likely to contain some errors, e.g., those associated with their instability or with convergence issues that still remain unaddressed. By means of mathematical models for designing streamlines and temperature fields using on the theory of conformal mappings, a solution that is as identical as possible to the analytical one can be obtained, which would enable the accuracy of the results to be improved.

References 1. Arefiev, N., Mikhalev, M., Zotov, D., et al.: Physical modeling of suspended sediment deposition in marine intakes of nuclear power plants. Procedia Eng. 117(1), 32–38 (2015). https:// doi.org/10.1016/j.proeng.2015.08.120 2. Riso, Ch., Riccardi, G., Mastroddi, F.: Nonlinear aeroelastic modeling via conformal mapping and vortex method for a flat-plate airfoil in arbitrary motion. J. Fluids Struct. 6, 230–251 (2016). https://doi.org/10.1016/j.jfluidstructs.2016.02.002 3. Khabakhpasheva, T.I., Kim, Y., Korobkin, A.A.: Generalised Wagner model of water impact by numerical conformal mapping. Appl. Ocean Res. 44, 29–38 (2014). https://doi.org/10.1016/ j.apor.2013.10.007 4. Vranayova, Z., Kaposztasova, D.: Hot water tanks from the point of view of temperature and energy confrontation. In: E3S Web of Conferences, vol. 45, p. 00099 (2018). https://doi.org/ 10.1051/e3sconf/20184500099 5. Wojtkowiak, J., Ole´skowicz-Popiel, C.: Investigations of hot water temperature changes at the pipe outflow. In: E3S Web of Conferences, vol. 22, p. 00186 (2017). https://doi.org/10.1051/ e3sconf/20172200186 6. Chappelear, J.E., Hirasaki, G.J.: A model of oil-water coning for two-dimensional, areal reservoir simulation. Soc. Petrol. Eng. J. 16(02), 65–72 (1976). https://doi.org/10.2118/498 0-pa

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7. Eilerts, C.K., Sumner, E.F.: Integration of partial differential equations for multicomponent, two-phase transient radial flow. Soc. Petrol. Eng. J. 7(02), 125–135 (1967). https://doi.org/10. 2118/1499-pa 8. Korovin, I.S., Tkachenko, M.G.: Intelligent oilfield model. Procedia Comput. Sci. 101, 300–303 (2016). https://doi.org/10.1016/j.procs.2016.11.035

Development of Gas Supply Systems Using Butane-Based Gas-and-Air Mixtures Nataliya Osipova(B)

, Sergey Kuznetsov , and Svyatoslav Kultyaev

Yury Gagarin Saratov State Technical University, Politekhnicheskaya Str., 77, Saratov 410052, Russia [email protected]

Abstract. The paper presents research on the use of butane-based gas-and-air mixtures to supply gas to consumers. It discusses the conditions ensuring an excess pressure in the butane tanks for natural regasification of the liquid-gas phase. We recommended the initial levels of filling tanks with gas, taking into account the possible maximum heating of ground and underground tanks. We determined the vapor production capacity of underground tanks. We established that a decrease in temperature in a tank is observed upon intensification of evaporation in the tank with a low value of the wetted surface area, which results in the formation and growth of an ice coat on the tank. We recommended the butane-based gas mixture composition, taking into account deviations in the Wobbe Index and the maximum flame propagation rate. We determined the dew point temperature for the gas-and-air mixture, which is recommended for use in gas supply systems. Keywords: Gas mixture · Butane · Excess pressure · Vapor production capacity · Gas tank filling level · Interchangeable gases · Wobbe index · Flame propagation rate

1 Introduction Despite the high rates of gasification and the development of a gas pipeline system connected to a unified gas supply system using main-pipeline natural gas, gasification of remote regions is carried out predominantly in the autonomous mode (using only liquefied/compressed natural gas (LNG, CNG) and liquefied petroleum gas (LPG)) or in the form of combined gasification (by building both gas pipelines and autonomous gasification facilities) [1]. Additionally, a factor advocating autonomous gasification is the presence of gas (gas condensate) fields in the region, based on which local systems with a developed network of gas pipelines are created, being isolated from the unified gas supply system. For those regions that have neither regional gas supply systems nor gas (gas condensate) fields, only autonomous gasification is recommended. The analysis of scientific publications showed that the most suitable systems, in this case, are autonomous gas supply systems using gas-and-air mixtures based on liquefied petroleum gases, so-called “propane-air” and “butane-air” systems. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 247–257, 2021. https://doi.org/10.1007/978-3-030-57453-6_21

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In turn, the above systems can also be used as backup fuel, ensuring uninterrupted gas supply to facilities in case of sudden drops in gas pressure in the system, the appearance of water condensation in pipelines, “rotating” disconnections of consumers from the unified gas supply system [2]. Gas-and-air mixture supply systems have several advantages, including when comparing them with the systems of liquefied petroleum gas supply using the propane-butane mixture: – operation regardless of the climatic features of the region and the terrain; – gasification of standalone facilities, regardless of the distance from the intensively build-in area; – creating a private gas supply system not included in the common gas network of the community; – absence of fractional nature of gas evaporation in the tank when choosing “propaneair” or “butane-air” systems, that is inherent to the propane-butane mixture and determines the variable gas composition fed to combustion in gas-consuming equipment; – no need to use “summer” and “winter” mixtures for year-round operation of the gas supply system; – no need to replace burners of gas-consuming upon its subsequent conversion to natural gas, to prevent the flashback and flame lift-off phenomena. In this case, the gas supply is carried out using a mixture of propane or butane with air; and, unlike systems operating with the propane-butane mixture, these systems fully meet the condition for main-pipeline natural gas without reconfiguring the consumer gas-consuming equipment and re-laying the existing gas supply networks. In the field of providing consumers with gas-and-air mixtures, there are scientific studies by N.N. Osipova, F.C. Costa, the Giproniigaz Institute, the World LPG Association (WLPGA), the Argonne National Laboratory [3]. It should be noted that these papers were focused on propane gas as the main component of the mixture, as the start of propane regasification occurs at a temperature of −42 °C, and the minimum excess vapor pressure of 0.1 MPa in the tank is provided at −20 °C, that allows us to recommend the above gas to be used in almost all climatic operation areas; the excess pressure in the tank (1.6 MPa) when heated to maximum temperatures (+45 °C) is also ensured by propane; therefore, the maximum pressure and the gas tank filling level are designed for filling the same with propane fraction (no more than 85%). This approach to the analysis of gas-and-air mixture supply systems focusing on the main component – propane – results in overestimating the performance parameters, the measured values of the actual excess pressure in tanks, the initial and residual levels of tank filling with gas, and not quite correct choice of the tank unit volume for a group facility. The development of autonomous gas supply systems using liquefied petroleum gases leads to an increase in the share of butane consumption in the household supply market [4]. The wider use of butane in gas supply systems is supported by the fact that the price of butane is 20% lower than that of propane.

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The development of recommendations for the use of gas supply systems with butanebased gas-and-air mixtures requires solving the following problems: – ensuring the required and sufficient conditions for stable regasification of butane in the tank; – substantiating the gas-and-air mixture composition that meets the interchangeability conditions of combustible gases; – determining the properties of the butane-based gas mixture, that provide operation without condensation. Thus, to develop recommendations for expanding the use of technical butane for household gas supply to consumers, further research is required.

2 Materials and Methods To develop recommendations on establishing operating modes of butane tanks, it is required to determine the conditions for generating excess pressure in the tank. The partial pressure of saturated butane vapor, according to the Antoine correlation, is calculated using the following formula: Pb (t) = 10

Bb b +t

Ab − C

(1)

where Ab , Bb , Cb are constants of the Antoine equations correlation. The diagram (Fig. 1) shows the pressure values generated in the tank depending on the butane liquid phase temperature.

Fig. 1. Temperature dependence of butane vapor pressure.

As shown by the diagram in Fig. 1, at negative ambient temperatures, the vacuum is formed in the tank; the pressure in the tank becomes equal to the atmospheric one at a temperature of 0 °C. Excess pressure is generated in the area of positive temperatures.

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The maximum pressure of 0.37 MPa is provided in the tank at a temperature of 40 °C. This fact restricts the use of butane tanks on the ground in the operation practice at sub-zero outdoor temperatures. For stable regasification of the vapor phase, the vapor phase pressure shall exceed the atmospheric one to create excess pressure in the tank. The analysis of climate data shows that soil has a positive temperature potential throughout the year and, in some climatic zones, it can be used as a heat source during heat transfer and regasification of the liquid-gas phase. The soil mass in moderately cold and moderately warm climatic operation zones has a positive temperature potential and can be used as a heat source for natural butane regasification in underground tanks. Given that the tanks for operation in the climate conditions of the Russian Federation are manufactured with a high neck (0.6 m), the laying depth with a standard tank diameter of 1.2 to 1.4 m shall be about 1.8 to 2.0 m. At this depth, the temperature of the soil mass ranges from 4.2 °C to 8.0 °C, which ensures an excess pressure of 0.12 to 0.14 MPa in the underground tank, which is sufficient for the normal functioning of the shut-off and control valves of the underground butane tank. Thus, when operating underground butane tanks in moderately cold and moderately warm zones, the required excess pressure is formed in the tank for natural regasification of the butane liquid phase. In accordance with the rules for the safe operation of liquefied petroleum gas tanks, the recommended level of filling with the liquid phase shall not exceed 85%. The above fact is due to a high volume expansion coefficient when heating gas in a ground tank. At the same time, this filling level is set for a gas with a higher coefficient of volume expansion: propane. Therefore, a butane tank will not be filled completely at maximum heating, resulting in inefficient use of the LPG tank. It should be noted that the filling level for ground and underground tanks shall be adapted differentially due to different maximum heating temperatures. To calculate volume expansion in the ground tanks, one shall adapt the limit temperature of plus 55 °C; for underground tanks, plus 40 °C. Due to lower temperature heating from the soil mass, underground tanks can have a high filling level. To determine the level of filling the tank with liquefied gas with a high content of butane fractions, let us use equilibrium diagrams and carry out their analysis. The level of filling the tanks with the liquid phase is highly influenced by the season; therefore, the dynamics of filling the tank with gas shall be considered, taking into account the year-round use of the LPG tank. The tank filling level is calculated based on the following correlation: k=

bυbt , υ t max

(2)

f

where υft max ; υbt are the specific volume of liquid at the time of filling at maximum and actual temperatures of liquid butane, m3/kg; b is the butane content in liquefied petroleum gas, % (by weight). To determine the possible tank filling level, we made calculations for ground and underground installations of LPG tanks for butane. The LPG temperature at the tank filling time ranged from −10 °C to the maximum one with the respective installations of tanks.

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The calculation results are presented in diagrams (Fig. 2).

Fig. 2. Justification of the level of filling tanks with butane: 1 – an underground tank, 2 – a ground tank.

The analysis of the diagrams (Fig. 2) showed that, regardless of the initial temperature, the filling of the butane underground tank capacity can be increased as compared with the ground one. For example, the limit ground tank filling level at a liquefied gas temperature of +20 °C is 89%, whereas the filling level of an underground tank can be 95% under the same conditions. The difference in filling levels at different temperatures is from 4.7% at a liquefied gas temperature of −10 °C to 15% at a liquefied gas temperature of plus 40 °C. Therefore, when operating underground tanks in various climatic zones within the temperature range from −10 to +10 °C, the recommended level of filling the tank with butane is from 89% to 93%. The gas vaporization process in the tank occurs in the form of a constant repetition of a cycle, the first stage of which is gas cooling due to the internal energy of the liquid phase, and the second stage is the heat transfer from the environment. Let us assume that, at time τ, all vaporized gas is supplied to the consumer. In this case, the heat spent on evaporation will lower the temperature of the liquid phase in the tank, °C: t1 =

rG cp (G − G)

(3)

where r is the latent vaporization heat, kJ/kg; G is the amount of vaporized gas, kg; cp is the gas heat capacity at constant pressure, kJ/(kg·°C); G is the total weight of gas in the tank, kg. The amount of vaporized gas in an underground tank due to heat influx can be calculated using the following formula:   Fmix kPb tb − tgr G= , (4) rb Pat

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where Fmix is the wetted surface area of the tank, sq m; k is heat transfer coefficient from the soil mass to the liquid phase [4, 5], kJ/sq m·°C; tb is the butane liquid phase temperature, °C; tgr is the soil temperature, °C. The supplied heat will increase the liquid phase temperature in the tank:   kFmix tb − tgr t2 = (5) cp (G − G) When splitting the gas evaporation process into minor time intervals, the total change in the liquid phase temperature at time τ will be determined as follows: t = −t1 + t2 ,

(6)

where t1 is the temperature change due to gas cooling, °C; t2 is the temperature change due to the heat transfer from the environment, °C.

3 Results To determine the designed vapor production capacity of underground tanks based on butane, we carried out the following calculations using the following initial data: – – – –

the geometric volume of the tank: 5.0 m3 , 2.5 m3 , 1.5 m3 , 1.0 m3 : the level of filling the tank with butane: 90%, 50%, 35%, 20%; climatic operation zones: moderately cold, moderately warm; the butane liquefied phase temperature: −15 °C.

The calculation results are presented in diagrams in Fig. 3. As can be seen from the diagrams (Fig. 3), the positive temperature potential of the soil provides natural regasification of the product. The lowest vapor production capacity is provided by a 1.0 m3 tank in a moderately cold zone: 0.62 kg in hour (0.23 m3 in hour); the highest one, by a 5.0 m3 tank operated in a moderately warm zone: 13.98 kg in hour (5.13 m3 in hour). The tank filling level also has a significant impact on its vapor production capacity: the larger the wetted surface area involved in heat transfer, the greater the amount of gas evaporated due to natural regasification of the product. Tanks of 1.0 m3 provide evaporation from 0.66 kg in hour to 3.85 kg in hour, depending on the tank filling level. The low vapor production capacity of 1.0 m3 tanks does not allow recommending such tanks for gas supply to a group of consumers, leaving their main use for gas supply of individual residential buildings. To determine the change in the gas-liquid phase temperature in the tank, we carried out calculations using formulas (3), (4), (6). The calculation results of temperature changes per 1 kg of vaporized gas in underground tanks, given the level of filling with the liquid phase, are presented in Table 1. The analysis of Table 1 suggests that the temperature drop of the liquid phase in the tank increases with emptying the tank. At the same time, the heat influx to the wetted tank surface from the soil mass remains stable. With the gas regasification in the tank,

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Fig. 3. Vapor production capacity of underground tanks filled with butane.

not exceeding its natural evaporative capacity, the resulting temperature is positive and decreases with emptying the tank. With the gas regasification in excess of its natural evaporation capacity, the resulting temperature becomes negative, which indicates the insufficient wetted surface of the operated tank. This fact leads to the growth of an ice coat around the tank and stops the gas evaporation in the tank. Therefore, for tanks with a volume of 1.0 m3, the minimum filling level should be not less than 30%; for tanks with a volume of 1.5 m3, at least 25%. When using gas-and-air mixtures for supplying gas to consumers, burners of gasconsuming equipment shall be adapted for main-pipeline natural gas. This fact is due to

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N. Osipova et al. Table 1. Temperature change in a tank when the liquid phase of butane is gasified. Tank volume, m3 Tank filling level with the liquid phase, % 90

80

70

60

50

40

30

20

Temperature drop of the gas-liquid phase in an underground tank during butane evaporation 5.0

0.09 0.10 0.12 0.13 0.16 0.20

0.27

0.41

2.5

0.18 0.20 0.23 0.27 0.32 0.41

0.54

0.81

1.5

0.27 0.31 0.35 0.41 0.49 0.61

0.82

1.23

1.0

0.45 0.51 0.58 0.68 0.81 1.02

1.36

2.04

Temperature rise of the gas-liquid phase in an underground tank during heat exchange with the environment 5.0

0.97 0.97 0.97 0.97 0.97 0.97

0.97

0.97

2.5

1.12 1.12 1.12 1.12 1.12 1.12

1.12

1.13

1.5

1.10 1.10 1.10 1.10 1.10 1.10

1.10

1.10

1.0

1.32 1.32 1.32 1.32 1.32 1.33

1.33

1.33

Temperature change of the gas-liquid phase in the underground reservoir during the regasification process 5.0

0.88 0.87 0.85 0.83 0.81 0.77

0.70

0.56

2.5

0.94 0.92 0.89 0.85 0.80 0.72

0.58

0.31

1.5

0.82 0.79 0.75 0.69 0.61 0.48

0.28 −0.13

1.0

0.87 0.82 0.74 0.65 0.51 0.31 −0.03 −0.71

the calorific value and the density of flammable vapors of pure butane that is different from natural gas. Given the prospective gasification of communities with main-pipeline natural gas, it is required to foresee the composition of the butane-and-air mixture, which shall be fully compliant with the conditions of natural combustible gases for industrial and household purposes. The permissible deviation of the Wobbe Index from the rated value shall be no more than 5% with fluctuations in the Wobbe Index values within the range of 41.2 to 54.5 MJ/m3 [5]. An additional condition for the interchangeability of gases is the maximum deviation of the flame propagation rate by no more than 15 to 20%. Compliance with the above conditions will allow burning gas without flame lift-off and flashback, with the gas combustion completeness close to 100%. To develop recommendations for using butane as the main component of the gasand-air mixture, more research is needed in the following fields: – adapting the gas mixture as an interchangeable combustible gas for supplying gas to consumers without replacement of gas-consuming equipment when converting it to natural gas;

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255

– reducing the dew point temperature affecting the condensate generation in gas distribution pipelines for hydrate-free reduction of the gas-and-air mixture. The criterion for interchangeability of combustible gases is the Wobbe Index. Such interchangeability is determined by the possible use of an alternative gas without violating the normal operation of gas burners and their design solutions. The Wobbe Index of the butane-air gas mixture is calculated using the following formula:  w Ql b · kb0 , (7) W0 =   0 /ρ ρb kb0 + ρair kair air   0 are the volume concenwhere Qlw b is the net calorific value of butane, MJ/m3; kb0 ; kair tration of butane and air in the gas-and-air mixture, %; ρb , ρair are the specific density of butane and air, kg/cu nm. According to calculations, the butane content in the gas-and-air mixture shall be not less than 48% and not more than 54% [5]. In this case, the gas-and-air mixture fully complies with the requirements for combustible gases interchangeability in terms of the Wobbe Index. At the same time, for normal operation of gas-consuming devices, interchangeable gases shall differ in the maximum flame propagation rate by no more than 15 to 20%. The normal maximum flame propagation rate of a gas-and-air mixture in a pipe with a diameter of 25.4 mm, at a temperature of 20 °C and a pressure of 101.3 kPa is calculated using the following formula:   L V1l1w1 + V2l2w2 + . . . + Vnlnwn , (8) W = V1 + V2 + . . . + Vn where L is the content of composite gas in the combustible mixture, providing the maximum flame propagation rate, %; V1 , V2 …..Vn are the content of simple gases in the combustible mixture, %; w1 , w2 …wn are the maximum flame propagation rates for simples gases in the combustible mixture, m/s; l1 , l2 … ln are the content of simple gases in the mixtures providing the maximum flame propagation rate, %. The actual maximum flame propagation rate, given the content of inert admixtures (carbon dioxide and nitrogen) in gas, can be calculated approximately, by using the following formula: Wd = W (1 − 0.01N2 − 0.012CO2 ),

(9)

where W is the maximum flame propagation rate of the combustible mixture, m/s; N2 , CO2 are the content of nitrogen and carbon dioxide in a composite gas, %. To determine the maximum flame propagation rate of a butane-based gas-and-air mixture, we carried out the relevant calculations. As a butane-and-air mixture was considered as an alternative to natural gas, given the prospective gasification with mainpipeline natural gas, we compared the maximum flame propagation rates for natural gas and the gas-and-air mixture of the recommended composition.

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For the purpose of calculation, we considered natural gas of the following composition: CH4–8 7%, C2 H6 – 5.0%, C3 H8 – 1.6%, C4 H10–0 .7%, C2 H15 – 1.8%, N2–3 .0%, CO2 – 0.5%. The composition of the recommended gas mixture: C2 H6 – 2.0%, C3 H8 – 3.0%, C4 H10–4 8%, air (O2 (21%) + N2 (79%)) – 47%. According to our calculation, the normal maximum flame propagation rate for natural gas is 0.7 m/s, whereas that of the butane-and-air mixture, 0.83 m/s. The difference in maximum rates was 18.75%, which meets the recommended limit for interchangeable combustible gases: 15 to 20%. Therefore, the recommended gas-and-air mixture meets the requirements for flammable gases interchangeability, given the recommended ranges of maximum flame propagation rates. As mentioned above, the use of gas-and-air mixtures reduces the dew point temperature, which has a favorable effect on the hydrate-free operation of gas supply systems. Table 2 presents the dew point temperatures of the recommended gas-and-air mixtures based on butane. Table 2. Dew point temperatures when using a butane-based gas-and-air mixture of the recommended composition. Pressure, MPa Dew point temperature, °C Butane content in the gas-and-air mixture (recommended), (%)

Butane 100%

Lower limit 48% Upper limit 54% 0.304 (3.0 at)

17

11

30

0.203 (2.0 at)

−3

1

18

0.101 (1.0 at)

−20

−18

−1

As follows from Table 2, the use of the gas-and-air mixture significantly reduces the dew point temperature. Thus, the use of technical butane provides the water vapor concentration in the gas phase even at −1 °C, and with increasing pressure, it partially covers the positive temperature range, which excludes completely the use of technical butane even in the warm season. The use of a gas-and-air mixture shifts the line of vapor phase saturation with water vapor, allowing to take the butane vapor phase from an underground tank at positive temperatures and to transport it with decreasing temperature to the values below zero, bypassing the hydrate formation zone at any recommended butane content in the gasand-air mixture [6–8]. This fact makes the use of gas-and-air mixtures attractive for supplying gas to consumers in year-round operation. The use of gas-and-air mixtures shifts the dew point temperature by more than 10 °C over the entire pressure range of gas-and-air mixture generated in an underground tank.

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4 Conclusions 1. We have considered the required conditions for providing excess pressure in underground butane tanks to ensure natural regasification of the liquid phase. We found that the natural regasification of gas in underground tanks occurs only at positive temperatures of the surrounding soil mass in moderately cold and moderately warm climatic zones. The minimum amount of gas equal to 0.66 kg in hour is generated by a 1.0 m3 tank in a moderately cold climate zone at a filling level of 20%. The maximum natural evaporation capacity is provided by a 5.0 m3 tank in a moderately warm climate zone: 14.73 kg in hour at a filling level of 90%. The temperature drop of the liquid butane phase when taking vapors depends on the amount of vaporized gas as compared to the amount of the remaining liquid phase of gas in the tank and, for tanks of various volumes, and it averages 1.1 to 1.3 °C upon evaporation of the calculated amount of gas per hour. 2. The recommended composition of the butane-based gas-and-air mixture for supplying gas to consumers is 48 to 54% butane and 52 to 46% air, respectively. This composition meets the condition for the combustible gases interchangeability, remaining within 5% of the Wobbe Index fluctuations and within the permissible limits of 15 to 20% in terms of the normal maximum flame propagation rate. 3. The use of “butane-air” mixtures reduces the water vapor condensation temperature by 10 or more degrees relative to the vapor phase of technical butane, which has a positive effect on gas consumption modes in the cold season.

References 1. Ondeck, A., Drouven, M., Blandino, N., Grossmann, I.E.: Multi-system shale gas supply chain planning with development and resource arrangements. Comput. Chem. Eng. 1274, 49–70 (2019). https://doi.org/10.1016/j.compchemeng.2019.05.004 2. Yang, J., Sun, W., Cai, J., Mao, H., Fang, R.: Development of supply-demand balance and distribution software of gas system for iron and steel industry. Procedia Eng. 152011, 5143– 5147 (2011). https://doi.org/10.1016/j.proeng.2011.08.954 3. Yu, W., Song, S., Li, Y.: Gas supply reliability assessment of natural gas transmission pipeline systems. Energy 1621, 853–870 (2018). https://doi.org/10.1016/j.energy.2018.08.039 4. Sukharev, M.G., Kosova, K.O., Popov, R.V.: Mathematical and computer models for identification and optimal control of large-scale gas supply systems. Energy 1841, 113–122 (2019). https://doi.org/10.1016/j.energy.2018.02.131 5. Yu, W., Wen, K., Min, Y.: A methodology to quantify the gas supply capacity of natural gas transmission pipeline system using reliability theory. Reliab. Eng. Syst. Saf. 175, 128–141 (2018). https://doi.org/10.1016/j.ress.2018.03.007 6. Ahmadvand, H., Goudarzi, M., Foroutan, F.: Gapprox: using gallup approach for approximation in big data processing. J. Big Data 6(1), 20 (2019). https://doi.org/10.1186/s40537-019-0185-4 7. Romano, A.A., Scandurra, G.: “Nuclear” and “nonnuclear” countries: Divergences on investment decisions in renewable energy sources. Energy Sources Part B Econ. Plann. Policy 11(6), 518–525 (2016). https://doi.org/10.1080/15567249.2012.714843 8. Sadorsky, P.: Renewable energy consumption and income in emerging economies. Energy Policy 37(10), 4021–4028 (2009). https://doi.org/10.1016/j.enpol.2009.05.003

Justification of the Choice of the Generation Capacity Dmitrii Vasenin1(B) , Marco Pasetti2 , Olga Sotnikova1 and Tatyana Makarova1

,

1 Voronezh State Technical University, 20th Anniversary

Oktyabrya Street, 84, Voronezh 394006, Russia [email protected] 2 Department of Information Engineering, University of Brescia, Via Branze, 38, 25123 Brescia, Italy

Abstract. The energy system of our country has a complex structural organization due to unequal resources distribution. At the same time, the balance of energy generation, allocation and consumption in terms of territory to achieve energy security of regions and opportunity of intersystem exchange of power flow and energy during normal and accident modes for increasing productivity of energy consortium. An electrical grid plays an important role in supply and connecting functions in the power system. The latest computer and communication technologies make it possible to create an efficiently functioning network that can be equipped with modern information and diagnostic nodes, a control automation system for all elements involved in the production, transmission and distribution of electrical energy. Our research work is devoted to the creation of an intelligent energy system with an active adaptive network. Our research work highlights the main aspects of creating a calculation methodology and substantiating the criteria for selecting generating capacity in the development and technical re-equipment of existing energy systems. Keywords: Energy saving · Energy safety · Energy sources · Power grid · Power supply system · The unified electric power system · Transmission and allocation of energy

1 Introduction There are lots of scientific works devoted to the assessment of energy conservation system structure. They can contain economic feasibility of the connection to the centralized power supply or examine the possibility of using small local power supplies. The utility of centralized and decentralized power supply is considered according to electricity rates and diesel fuel costs [1–4]. This approach can help to find out where it is necessary to undertake a detailed assessment of using one or another technically feasible and economically permissive energy supply option. At the local level particular options of power supply of each consumer, order of energy sources input, necessary investments and © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 258–265, 2021. https://doi.org/10.1007/978-3-030-57453-6_22

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equipment configuration are determined. Research findings for different regions allow to form some suggestions about promising areas in technical progress of small-scale power generation and to estimate the possibilities of introducing. Calculational and comparison techniques of alternative power supply options should be chosen according to the production cost, financing terms, investment performance and overall performance. Choosing of an optimal solution should be based on the comprehensive consideration of technical, environmental, reliability and economic factors of the system. The aim of the research is criteria development for the choice of an optimal way for a power supply system and on the basis of that to create a structure of generating capacity in case of development or modernization of power supply systems with all facts above being considered. We have responded to the same challenge earlier for justification of the heat supply system structure considering various degree of system centralizing and decentralizing and cost estimation during the functioning of the system [5, 6].

2 Materials and Methods Existing modern methods of calculating the optimization of the strategy for the development of power pools are considered. It is shown that in current methods fuel costs are considered more than operation mode and reliability of the equipment. Environmental factor and financing terms are almost not considered. The analysis of scientific literature data has shown that there is no one single criteria that includes all factors determining system performance in general. Task formulation: to find the most effective way of power supply system development that can meet demands for electric and heat power at the territory considering the fuel mix, localization and emissions. Political, economic, technical and other investment risk evaluation also plays an important role. There is no one criteria that can consider all that facts. That is why the comparison of the development strategies effectiveness on a multicriteria basis is suggested. The most effective option should be the best according to all criteria.

3 Results The main criteria are the following: – criteria of maximum specific economy-wide effect:

max E = max{E · τ/ R} i, i = 1, 2 . . . ,

(1)

where (2)

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The following notation is accepted here: Rit – cost estimate of the results in i-option, in t-year; Cit – cost estimate of all kinds of costs; αt – modular ratio of costs in t-year; τ – risk ratio of long-term investments; – criteria of the best performance of internal efficiency for the power pool:

max P = max{P · τ/ R} i. , i = 1, 2 . . . . P=

t=tk t=tn

Pit (1 + βp )1−t

(3) (4)

where Pit – disposable income of the power pool in i-option development in t-year; βp - minimal acceptable return; – criteria of the best return on investments: max  P = max{ P · τ/ K} i, i = 1, 2 . . . , .

(5)

where  P - net profit increase (after tax payment, charges, etc.). These criteria consider the effectiveness of using installed capacity and investment performance conditions. Cost function can be described as a sum of its parts: C = Cps + Cf + Cen + Cl + Crel ,

(6)

where Cps – modular ratio of costs of the construction and operation of power plants without fuel factor; Cf – fuel costs of heat and electric power production; Cen – environmental costs; Cl – costs of power supply lines construction Crel – reliability costs. Cps =

n 

[akh

h=1

+ach

E 

E 

∗

J I     ∗ Keji Nejih − Nejih

E=1 j=1 i=1

J I   ∗ ∗ (αeji keji Nejih + Ceji Nejih Tjih ,

E=1 j=1 i=1

where h = 1…h – optimization period development (development period is set to one year); e – the number of load centers; j – the number of plants installed in load center; i – the number of aggregate types, using in the plant;

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Keji - specific investments in plant construction; Nejih - installed capacity, MW; akh - modular ratio of investments; ach - modular ratio of current costs; αeji - depreciation charge index; Ceji modular ratio of power production costs (without fuel factor). Cl can be evaluated in the following way:

where kee - specific investments in power supply lines αee - depreciation charge index. Electric flux direction for the connection between load centers and systems can’t be determined beforehand, so there are two opposed electric fluxes N_(ee´h) and N_(e´eh) for each territory. In the optimal plan one of the fluxes is equal to zero, that provides an optimal solution. The first step in fuel factor determining is fuel consumption calculating. It is based on the optimal composition of generating capacity at every instant. Choosing of the equipment composition consists of two stages: – the first stage is to determine a schedule of the power pool potential load, growth rate of load and equipment composition; – the second stage is to optimize load allocation between aggregates for the existing schedule. Optimal load allocation between aggregates is based on cost minimization, including fuel costs, environmental costs and non-delivered energy costs connected with the ways of equipment redundancy. In that case the target function of load allocation between aggregates within a day is the following: (9)

Optimum of the target function is determined considering the following limitations: n Nit = Nsyst t ; (10) i=1

Ni syst ≤ Ti ≤ Ni max , n i=1

QitT +

n i=1

 QitPVK = Qsyst t ,

(11) (12)

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D. Vasenin et al. PVK QiPVK ≤ QiPVK min ≤ Qit max ,

(13)

T QiTmin ≤ QitT ≤ Qmax ,

(14)

where Nit , Ni max , Ni min – current, maximum and minimal capacity of the aggregate, respectively. PVK , Q PVK , Q T , Q T , Q T QiPVK max – minimal, current and maximum thermal min , Qit i max i min it load of turbines or peaker heating boiler; Ci – fuel cost; Bk – maximum acceptable fuel flow; E  V DPVK  Q T + DPVK Q PVK – non-delivered energy costs of the related Dct i ct t ct t power connected with operating modes of the aggregates; Pi – fee ratio for emissions of i- source; mi – specific value of i-source emissions; per Ei , Qit Qi - related power production; Bitn = Bitres + Bittrn – additional fuel costs connected with switching the equipment to standby mode and transition processes. The value of potential energy loss because of changing of operation modes can be determined in the following way: ni   m ni m m Cnj Pj qj m − rj Nm T , (15) V = m−ri +1

where Npi – available system capacity; T – a period under review (calculation period); m - the number of combinations from n according to m; Cnj nj – a number of aggregates, necessary for the base-load provision in j-interval with no back-up; rj – a number of aggregates, which can be used for compensation of system power reduction caused by crashes; Pi , Qi – operating and crash probability. It can be evaluated in the following way:       Pi = − K12 ϕ1 + K22 ϕ2 + . . . + Kn2 ϕn , (16) where K1 K2 . . . Kn – working capacity indexes of certain operating modes; ϕ1 ϕ2 . . . ϕn – weight probabilities of the operating modes defined by the expression Cf =

m S j=1

S=1

24 t=1

Bjsti Cjsti .

(17)

Where S is a number of seasons in a year. :, a C …. - the number of days in the corresponding season. Environmental costs can be calculated in the following way

ϕ

Cen = P1jt M jt + P2jt Mjt .

ϕ

Where M jt , Mjt – limit emissions and emissions in excess of limit in t-year;

(18)

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P1jt P2jt – limit and in excess of limit emission requirements. The reliability of the power supply was provided by bringing all options to the same level by using certain reserve capacity (emergency, repairing and load). Frame 1. Input of basic data, energetic and load characteristics, forming of development options Frame 2. Allocation of load among units and choosing of operating units

Frame 3. Fuel cost calculation

Frame 4. Cost calculation Cps, Cl, Cen

Frame 5. Reserve calculation R and reliability costs

Frame 6. Calculation of efficiency criteria

No

All options are considered

No

All loads are considered

Frame 7. Comparison of all options using efficiency criteria and choosing the best option

Results recording Fig. 1. The algorithm of optimization scheme realization.

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Reliability costs are determined in the following way: (19) – investments, performance factors and amortization of investments; where Cserv – costs of standby sets service; Clost – lost energy costs. An algorithm of choosing an optimal solution based on submitted concept (Fig. 1).

4 Discussion The implementation of the given algorithm, which is based on a hierarchical approach to the selection of optimization criteria for the generating capacity of the energy system, and the use of innovations in electronic technologies will reduce many technological restrictions, environmental and terrorist threats, lower the cost of energy networks and the energy resource itself. Most of the work on upgrading electrical networks should be included in the concept of “smart grids”, and other additional resources and opportunities should also be used. The implementation of territorial and temporary models of demand for electricity and the development of algorithms for the interchangeability of resource capacities remain urgent issue [7–10]. The proposed criteria for choosing the optimal path for the development of the power supply system made it possible to create on their basis an algorithm for choosing the structure of generating capacities in cases of development or modernization of energy pools. The use of the obtained solutions can help to find the most efficient energy supply for consumers in certain regions, provide the best indicator of reliability and economical operation, and achieve minimum energy consumption.

5 Conclusion In recent decades, Smart Grid technology has been developing in many countries. Smart power supply networks are actually modernized power supply networks that use information and communication systems and technologies to collect information on energy production and energy consumption, which can automatically increase efficiency, reliability, economic benefits, as well as sustainability of electricity production and distribution. The use of the obtained algorithms allows solving the issues of the most efficient energy supply to consumers in certain regions of our country, ensuring the best reliability and cost-effectiveness of operating energy facilities, while minimizing electricity tariffs.

References 1. Valenzuela, J., Wang, J.: A probabilistic model for assessing the long-term economics of wind energy. Electr. Power Syst. Res. 81(4), 853–861 (2011). https://doi.org/10.1016/j.epsr.2010. 11.015

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2. Aivarez, E.A., So ler Guitart, J., et al.: Design and control strategies for a hydrokinetic smart grid. Int. J. Electr. Power Energy Syst. 95, 137–145 (2018). https://doi.org/10.1016/j.ijepes. 2017.08.019 3. Carrizosa, M.J., Lamnabhi—Lagarrigue, F., et al.: Optimal power flow in multi-terminal hvdc grids with offshore wind farms and storage devices. Int. J. Electr. Power Energy Syst. 65, 291–298 (2015). https://doi.org/10.1016/j.ijepes.2014.10.016 4. Baloch, M.H., Wang, J., Kaloi, G.S.: Stabiliti and nonlinear controller analysis of wind energy conversion system with random wind speed. Int. J. Electr. Power Energy Syst. 79, 75–83 92016). https://doi.org/10.1016/j.ijepes.2016.01.018 5. Aghili, S.J., Hajian-Hoseinabadi, H.: Reliability evaluation of repairable systems using various fuzzy-based methods – a substation automation case study Aghili. Int. J. Electr. Power Energy Syst. 85, 130–142 (2017). https://doi.org/10.1016/j.ijepes.2016.08.010 6. Zeng, Q., Peng, D.: Frequency-hopping based communication network with multi-level qoss in smart grid: code design and performance analysis. IEEE Trans. Smart Grid 3(4), 1841–1852 (2012). https://doi.org/10.1109/TSG.2012.2214067 7. Kyritsis, A., Tselepis, S., et al.: Evolution of py systems in Greece and review of applicable solutions for higher penetration levels. Renewable Energy 109, 487–499 (2017). https://doi. org/10.3390/en12122441 8. Yip, S.-C., Hew, W.-P., et al.: Detection of energy theft and defective smart meters in smart grids using linear regression. Int. J. Electr. Power Energy Syst. 91, 230–240 (2017). https:// doi.org/10.1016/j.ijepes.2017.04.005 ˇ 9. Rejic, Ž.B., Cepin, M.: Estimating the additional operating reserve in power systems with installed renewable energy sources. Int. J. Electr. Power Energy Syst. 62, 654–664 (2014). https://doi.org/10.1016/j.ijepes.2014.05.019 10. Zhu, H., Huang, G.H.: Dynamic stochastic fractional programming for sustainable management of electric power systems. Int. J. Electr. Power Energy Syst. 53, 553–563 (2013). https:// doi.org/10.1016/j.ijepes.2013.05.022

Reorganization of System of Sanitary Purification of Municipal Solid Waste and Management of Its Disposal Yelena Sushko , Irina Ivanova(B)

, Yelena Golovina , and Anastasiya Parshina

Voronezh State Technical University, Moscovskiy Prospect, 14, Voronezh 394026, Russia [email protected]

Abstract. The present research is aimed to elaborate recommendations on sanitary purification and disposal of solid waste. Today all large cities endure a hard situation with municipal solid waste management; the placement of waste recycling plants (WRP) and waste transfer stations and the choice of a waste disposal technology are still remaining urgent problems. More than 20 methods of waste neutralization and disposal have been known by this day. Each of these methods includes 5–10 kinds of techniques, technological schemes, major equipment, types of facilities. Many issues that concern elaboration of recommendations on realignment of sanitary purification system in cities have to deal with the problems of disposal and recycling of some industrial wastes. Developments regarding systems of recycling municipal solid waste in cities will have much stronger economic effect if this problem is considered together with the issues of recycling a part of industrial and medical waste. Keywords: Sanitary purification · Solid waste · Recycling · Disposal

1 Introduction Amendments to the Federal Law of the Russian Federation dated June 24, 1998 № 89-FL “On Production and Consumption Wastes” and other legislative acts launched a new waste management system in the Russian Federation, particularly in the Voronezh region. This system implies the responsibility of regions for the collection and disposal of municipal solid waste and the priority of its recycling. According to the federal state statistical data, approximately 1200 types of waste of hazard classes I-V with weight of 7,579,683.25 tons were generated in economic entities of the observed region during 2019, which is 83,300 tons more than in 2018 [1]. 78.3% (5.93 million tons) of total amount of generated waste are non-hazardous and low-hazardous. The total number of entities referring to economic or other activities that produce waste is 4311 units (Table 1). According to economic activity organization, the Voronezh region is an industrial and agricultural entity. The main sources of waste production in the Voronezh region are machine engineering, electric power, chemical industry, animal husbandry © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 266–275, 2021. https://doi.org/10.1007/978-3-030-57453-6_23

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Table 1. Characteristics of production of manufactural and consumption waste for 2019. Waste class of hazard for the environment

Waste generation for 2019, tons

Class I

94.283

Class II

261.044

Class III

1 645 990.7

Class IV

1 070 391.207

Class V

4 862 946.016

Totally

7 579 683.25

and agricultural stock processing. 4/5 of the total industrial output accounts for these sectors. There are 9 sugar factories in the Voronezh region. The amount of waste produced in the Voronezh region is annually increasing. Waste recycling, reuse and disposal prevail over other waste management activities in the region. Approximately 300 license holders carry out waste management activities with waste of hazard classes I–IV. Like in the previous year, wastes from agricultural stock processing (beet pulp), animal husbandry (manure) and crop production (sunflower husk) rank first in volumes among industrial wastes that are being disposed or reused, in respect that the agricultural sector is prevalent in the economy of the region [2]. Animal and chicken manure that are used as fertilizers enriching soils with nitrogen and other nutrients should comply with the requirements of current regulations and contain no pathogenic microflora. Animal husbandry enterprises that observe the rules on collecting and neutralizing manure and have a license for these types of activities, use it as a fertilizer added to soil. The standards of accumulating municipal solid waste (MSW) are constantly changing, they reflect the state of supplying population with goods, but at the same time they largely depend on local conditions. Various factors influence the accumulation of municipal solid waste; the key factors are below: – the degree of improvement of households (the presence of garbage chutes, heating systems, energy for cooking, water supply and sewage); – development of a network of catering and domestic services; – the level of production of mass-market products and trade culture; – the level of coverage of cultural-and-social and public institutions by household cleaning and sweeping; – climatic conditions. The methods of waste processing and neutralization are divided into disposal (aimed at solving sanitary-hygienic tasks) and recycling (aimed at solving sanitary-hygienic and economic problems). In terms of technological principle, they are divided into:

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– – – – –

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biological; chemical; thermal; mechanical; combined.

The choice of processing technology is determined by the solution of the main task: sanitary cleaning of the city from municipal solid waste. When choosing a particular technology, one should take into account technical, economic, environmental, climatic and social factors [3]. When choosing a technology, the following factors and criteria must be considered: Technical and economic factors: 1. 2. 3. 4. 5.

The technology should be the cheapest in terms of reduced expenditures. Maximum use of valuable components of MSW. Environmental factors: The technology for MSW recycling should be environmentally friendly. End products of recycling (compost, ash, RDF, etc.) should make no harm to the environment.

Climatic and social factors: • the presence of favorable climatic and social conditions; • to select the most reasonable technology for recycling and disposal of MSW in the city of Voronezh, the following technologies are considered: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Storage. Burning with heat recovery. Composting. Production of RDF + composting. Composting + burning of non-compostable fractions. Assortment + aerobic composting (Project “Scarabey”, option I). Assortment + anaerobic composting (Project “Scarabey”, option II). Assortment + anaerobic composting + burning (Project “Scarabey”, option III). Pyrolysis (Project “RAMET”). Steaming and generation (Consortium “RCR Group”).

The result of a working process of MSW enterprises is the production of the following useful components shown in Table 2. The calculation is carried out for a productivity of 300 thousand tons per year. 1. 2. 3. 4.

Storing. Burning with heat recovery. Composting. RDF production + Composting.

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Table 2. The amount of valuable components extracted from MSW using various technologies for recycling of waste with productivity of 300 thousand tons per year. Name of disposed products

Units of measurement

Technology

Black metals

T

0

10500

10500

10500

Non-ferrous metals

T

0

0

3000

1

2

3

4

5

6

7

8

9

10

10500

12000

12000

12000

12000

12000

3000

3000

4500

4500

4500

4500

4500

Plastics

T

0

0

0

0

0

10500

10500

10500

0

10500

Glass

T

0

0

0

14400

0

14400

14400

14400

14400

14400

Compost

T

0

0

180000

90000

180000

90000

90000

90000

0

0

RDF

T

0

0

0

108000

0

0

0

0

0

0

Paper

T

0

0

0

0

0

69000

69000

69000

0

0

Textile

T

0

0

0

0

0

9000

9000

9000

0

0

Wood

T

0

0

0

0

0

3000

3000

3000

0

0

Pyrocarbon

T

0

0

0

0

18750

0

0

15000

6000

0

Steam (14 atm.)

Gcal/year

0

450000

0

0

129000

0

0

900000

0

0

Electric power

MW-h

0

0

0

0

0

0

6600

6600

0

21000

Neutralized slag

T

0

0

0

0

0

0

0

12000

4200

0

5. 6. 7. 8.

Composting + burning of non-composted fractions. Sorting + aerobic composting (“Scarabey” option I). Sorting + anaerobic composting (“Scarabey” option II). Sorting + anaerobic composting + burning (“Scarabey” option III).

2 Materials and Methods Large organizations producing the biggest amount of I hazard class wastes (mercurycontaining wastes) are located in three municipalities: Voronezh Urban District, Novovoronezh Urban District and Rossoshansky District. Due to the lack of organizations dealing with the disposal of mercury-containing and other hazard class I wastes in the Voronezh region, the collection and transportation of these wastes was organized for further neutralization outside the region. Application of the technology of using waste in the production cycle or its secondary use is gaining wider spread in the Voronezh region [4]. The development of infrastructure for sorting (separate collection) and utilization (use) of production and consumption waste is the priority issue. For instance, there are organizations in the Voronezh region that perform activities on plastic, polyethylene and polypropylene waste disposal. The technology of recycling plastic products consists in preliminary grinding, further granulation and final production of recycled polypropylene that is applicable for further use as a raw material.

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The handling of waste referring to hazard class II, for instance used batteries, is also an urgent problem. Their disposal is carried out by disassembling, discharge of electrolyte, grinding, crushing and granulation. During the process of disposal, the separation of solid fractions from paste-like lead-containing mass occurs with the formation of secondary raw materials applicable for further use [5]. A new direction in oil waste disposal is being developed: oil sludge (exhausted waste containing oil products) is disposed by adding agent “Ekonaft” to it and blending oil and petroleum oil waste in a mixing tank until the mineral filler “PUN” is formed that can further be used in the process of manufacturing materials for road construction. In addition, waste oils are disposed with the use of special equipment involved in mastic production. As the result, finished product is obtained. In the Voronezh region, there is the only enterprise engaged in the disposal of used railway sleepers and recycling of used car tires. Building waste recycling is performed with the use of a mobile crushing facility. When crushing building materials in such a facility, a new raw material is produced, which is subsequently used as an additive when manufacturing concrete products and performing asphalt laying. OOO “Ekoresurs” is a promising company capable of utilizing such types of waste as rubber products, car tires, exhausted oil products, sludge, oily waste, paints and varnishes, paper, cardboard, wood waste, medical and food waste. For waste disposal, the low-temperature pyrolysis method is used. OOO “Novator” performs the disposal of soil waste containing products of petroleum origin, which further are used in the construction, reconstruction and repair of roads after processing and strengthening with inorganic binders. It became possible to utilize waste generated at one of the large enterprises of Voronezh producing synthetic rubbers with obtaining a final product called “Polikrosh”, which is used for the production of rubber goods. OOO Production Group “Smesi i Ogneupory” processes iron scrap and mixtures of refractory materials, metallurgical slag, kiln scrap and other similar types of waste by crushing the incoming raw material with the addition of binders and forming bricks intended for refractory facing. OOO “Voronezhvtorma” provides services on collection and removal of waste paper, glass waste and polyethylene waste in the city of Voronezh and municipal areas. In addition, the organization has a license for the collection and transportation of waste tires. Activities on plastic, polyethylene and polypropylene waste recycling is an actively developing direction of hazard class IV waste disposal. The ratio of waste generated in Voronezh (by hazard class) is shown in Fig. 1. After receiving a license for waste management activities, a company is capable of disposing construction waste remained after building dismantling with a view to further use it in house or road construction. A promising area in waste neutralization is the use of pyrolysis facilities capable of recycling such types of waste as rubber products, car tires, waste petroleum products, sludge, oiled waste, paints and varnishes, paper, cardboard, wood waste, medical and food waste.

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1% 10%

9% class I, II III class IV class V class unnown

80%

Fig. 1. The ratio of waste produced in Voronezh (by hazard classes).

3 Results Several organizations of the Voronezh region got licenses for waste management activities specified by collection, transportation, processing and disposal of waste tires, pneumatic chambers, rubber conveyor belts, etc. with further recycling of these wastes into rubber crumb, which is transferred to enterprises for the use in manufacturing rubber products. Municipal solid waste is still produced in large amounts and include consumption wastes from office and domestic premises of companies and enterprises, which are compositionally similar to municipal solid wastes, garbage from cleaning wholesale and retail enterprises, cultural and sports and other institutions. In 2019, according to the data of directorate of Federal Service for Supervision of Natural Resource Usage “Rosprirodnadzor” in the Voronezh Region, MSW management operators accepted 722,525.49 tons of MSW for burial, while economic entities produced 134,394.9 tons of MSW. The smallest total index determines the optimal technology for neutralization and disposal of MSW for Voronezh. Figure 2 represents an integrated assessment of technologies for MSW recycling in the city of Voronezh.

90 80 70 60

E D C B A

50 40 30 20 10 0

1

2

3

4

5

6

7

8

9

10

Fig. 2. Integrated assessment of technologies for MSW recycling in Voronezh.

1. 2.

Storing. Burning with heat recovery.

272

3. 4. 5. 6. 7. 8. 9. 10.

Y. Sushko et al.

Composting. RDF production + Composting. Composting + burning of non-composted fractions. Sorting + aerobic composting (“Scarabey” option I). Sorting + anaerobic composting. Sorting + anaerobic composting + burning (“Scarabey” option III). Pyrolysis RAMET. Steaming and generation.

A - Reduced expenditures for capital construction and operation of facilities. B - Maximum use of valuable components of MSW. C - The technology for MSW recycling should be environmentally friendly. D - Final products of recycling (compost, ash, RDF, etc.) must not be harmful to the environment. E - Climatic factor. A summary table of emissions of harmful substances into the atmosphere when applying different technologies of MSW disposal was compiled (Table 3). Table 3. Summary table of emissions of harmful substances into the atmosphere under application of different technologies of MSW disposal. Hazard class

Amount of emissions, t/year

1

–

2

0.652

143.387

3

1.080

79.114

1+2

0.652

159.737

1

2 0.109

3

4

5

6

7

8

9

10

–

–

–

–

–

–

–

–

8.184

8.184

150.744

8.184

8.184

89.584

148.3

7.245

252.483

252.483

279.233

252.483

252.483

267.613

252.483

79.114

8.184

8.184

150.744

8.184

8.184

89.584

148.3

7.245

1. Storing

2. Burning with heat recovery

3. Composting

4. RDF production + Composting

5. Composting + burning of non-composted fractions

6. Sorting + aerobic composting (“Scarabey” option I)

7. Sorting + anaerobic composting. (“Scarabey” option II

8. Sorting + anaerobic composting + burning (“Scarabey” option III)

9. pyrolysis RAMET

10. Steaming and generation

4 Discussion For 10 years, in accordance with the statutory order of the administration of the Voronezh region dated 18.06.2008 № 513 “On approving the procedure for maintaining the regional cadaster of production and consumption waste of the Voronezh region”, the Department of Natural Resources and Ecology of the Voronezh Region collects information provided by local governments of municipal and urban districts, as well as enterprises engaged in waste management. The collection and processing of this information allowed systematizing all available information on their location, area, types of buried waste.

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According to the cadaster data, in 2019, 305 unlicensed waste disposal facilities operated in the region (including 298 authorized and 7 unauthorized landfills) and 17 licensed solid municipal waste landfills. The State Register of Waste Disposal Facilities formed by Rosprirodnadzor includes 17 MSW landfills. Waste disposal at other facilities, including authorized landfills, in accordance with Article 12 of the Federal Law of the Russian Federation of June 24, 1998 No. 89-FZ “On Production and Consumption Wastes” entails fines and a five-fold payment for negative impact on the environment. Amount of money is received as a payment for negative environmental impact due to waste disposal. According to the requirements of federal legislation, the Voronezh region is now transferring to a new waste management system. In 2019, the department continued to implement measures on creating intermunicipal waste recycling clusters in the region. On the territory of the Semiluksky municipal district of the Voronezh region, nearby the existing MSW landfill OOO “Kaskad”, the construction of a waste sorting complex with a capacity of 440 thousand tons per year under one-shift working schedule was completed. The Law on the Federal Budget for 2019 and target period 2019–2020, the Voronezh Region was granted with a federal subsidy for erecting facilities for MSW processing (sorting), which amounted 79.361 million rubles. The money was collected by means of ecological dues payed by manufacturers and importers of goods that are advised for disposal after losing their consumer properties. In the framework of the agreement “On the provision of subsidies to the budget of the constituent entity of the Russian Federation from the federal budget” concluded between the government of the Voronezh region and the Ministry of Natural Resources of Russia, three waste sorting complexes were built for inter-municipal waste recycling clusters. The operation of waste sorting complexes will allow sorting out of waste up to 26% of useful fractions that can be repeatedly used, as well as extend the lifetime of MSW landfills and prevent the formation of unauthorized landfills. In addition to the selected regional MSW management operator in the Voronezh inter-municipal cluster, in October 2019, based on the results of competitive selections, regional waste management operators were selected for remaining seven inter-municipal waste recycling clusters. As part of the development of the regional component of the national Ecology project, the Department sent proposals to the Ministry of Natural Resources of Russia on including measures for the rehabilitation of 24 unauthorized landfills with a total value of 1,028.7 million rubles into the federal project “Clean Country”, and measures for building 16 waste sorting complexes with a total value of 1037 million rubles into the federal project “Formation of integrated MSW management system”. The order of the Department of Housing and Utility Services and Energy of the Voronezh Region approved the standards for the accumulation of MSW in the territory of the Voronezh Region for the Voronezh Inter-municipal waste recycling cluster. The work on calculating the standards for the accumulation of MSW for the remaining clusters is going on.

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On the territory of the Russian Federation, in accordance with Article 12 of the Federal Law “On Production and Consumption Wastes”, a list of types of production and consumption wastes was approved by order of the Government of the Russian Federation dated July 25, 2017 № 1589-r, which includes useful components, which are prohibited to be buried. Today, the following types of waste are not to be buried on an MSW landfill: scrap metal, fluorescent lamps, LED lamps, mercury-containing devices. Waste sorting complexes belonging to clusters will send raw materials for processing. In the Voronezh region, there is a number of specialized enterprises possessing facilities capable for processing and disposal of waste that is considered recyclable: polymers, paper, glass, metal, etc. Among the main aims of waste recycling is to reduce the amount of landfill waste, improve the environmental situation, and manufacture new products. Regional responsibilities for the collecting, sorting and transferring secondary resources for recycling will be executed by the regional operator within the clusters. Considering the priority of state policy aimed at using waste as potential resources and the ban on the disposal of waste containing useful fractions, the regional annual event “Decade of collection of secondary material resources” was held. In the framework of cooperation with potential investors under implementation of measures in the field of waste management, the department permanently and comprehensively analyzes all applications and forms a list of investment and commercial proposals. Investment projects in the field of waste management coming to the department are entered into the updated register of commercial and investment offers, which today contains information on 150 organizations that have proposed projects for the Voronezh region that comply with environmental legislation and key directions of the state policy of the Russian Federation in the field of waste management [6–8]. Activities of the program “Environmental safety of the Voronezh urban district” are the following: – – – – – – – –

– –

experiment on organization of a system of separate municipal waste collection; design of a waste recycling complex; construction of a waste recycling complex; development of average annual standards for the formation (accumulation) of municipal solid waste for social facilities, educational, medical institutions, etc.; development of a system for the collection and processing of spent petroleum products; preparatory work on building an industrial site for recycling car tires; development of a system for collection, placement, neutralization and disposal of those waste, the owner of which is not known; specification of the list, locations and amounts of ownerless waste, as well as those waste, the owner of which for any external reasons is not able to ensure their proper recycling and disposal; preparation of a conclusion on determination of ownerless waste management that is proper in terms of economy and environment; placement, neutralization, disposal of ownerless waste.

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5 Conclusion Today, waste disposal in special landfills remains the world’s prevailing method of MSW treatment. World’s most advanced countries averagely apply this method in more than 58% cases, Russia – approximately in 97%. The main disadvantages of this method are: – – – –

the need for large areas for landfills; irretrievable loss of valuable components of MSW; negative impact on the environment; the search for new landfills entails the significant increase in waste removal distances.

Closed MSW landfills should be rehabilitated in order to prevent environmental pollution, and for the purposes of land restoration and possible production of biofuel (biogas). The lack of selective waste collection leads to the need for the next 15–20 years to focus on methods that allow sorting waste, extracting valuable components and preparing the sorted part for thermal or biological decomposition. The choice of recycling technology is determined through the economic and environmental comparison of various options that depend on certain conditions (MSW composition, ability to sell the final product, prices of fuel, raw materials, territorial capabilities, environmental friendliness of technologies and end products, etc.).

References 1. Chen, Z., Yu, G., Wang, Y., Wang, X.: Fate of heavy metals during co-disposal of municipal solid waste incineration fly ash and sewage sludge by hydrothermal coupling pyrolysis process. Waste Manag. 10915, 28–37 (2020). https://doi.org/10.1016/j.wasman.2020.04.048 2. Silva, R.V., De Brito, J., Lynn, C.J., Dhir, R.K.: Use of municipal solid waste incineration bottom ashes in alkali-activated materials, ceramics and granular applications: a review. Waste Manag. 68, 207–220 (2017). https://doi.org/10.1016/j.wasman.2017.06.043 3. Rokni, M.: Design and analysis of a waste gasification energy system with solid oxide fuel cells and absorption chillers. Int. J. Hydrogen Energy 43, 5922–5938 (2018). https://doi.org/ 10.1016/j.ijhydene.2017.10.123 4. de Pauli, A.R., Espinoza-Quiñones, F.R., et al.: Integrated two-phase purification procedure for abatement of pollutants from sanitary landfill leachates. Chem. Eng. J. 33415, 19–29 (2018). https://doi.org/10.1016/j.cej.2017.10.028 5. Zhipeng, T., Bingru, Z., Chengjun, H., et al.: The physiochemical properties and heavy metal pollution of fly ash from municipal solid waste incineration. Process Saf. Environ. Prot. 98, 333–341 (2015). https://doi.org/10.1016/j.psep.2015.09.007 6. Romano, A.A., Scandurra, G.: “Nuclear” and “nonnuclear” countries: divergences on investment decisions in renewable energy sources. Energy Sources Part B Econ. Plan. Policy 11(6), 518–525 (2016). https://doi.org/10.1080/15567249.2012.714843 7. Masini, A., Menichetti, E.: The impact of behavioural factors in the renewable energy investment decision making process: conceptual framework and empirical findings. Energy Policy 40, 28–38 (2012). https://doi.org/10.1016/j.enpol.2010.06.062 8. Sadorsky, P.: Renewable energy consumption and income in emerging economies. Energy Policy 37(10), 4021–4028 (2009). https://doi.org/10.1016/j.enpol.2009.05.003

The Convex Fuzzy Sets and Their Properties with Application to the Modeling with Fuzzy Convex Membership Functions Djavanshir Gadjiev1

, Ivan Kochetkov2

, and Aligadzhi Rustanov2(B)

1 Department of Mathematics, Lee campus, Florida South Western College, 8099 College

Parkway, Fort Myers, FL 33919, USA [email protected] 2 Moscow State University of Civil Engineering, Yaroslavskoe Shosse, 26, Moscow 129337, Russia [email protected]

Abstract. The convex fuzzy sets are discussed in terms of the extension principle of Fuzzy logic sets in cases, when characteristic function is not one-to one. The new fuzzifying extension theorem is introduced to apply the concepts of the fuzzy sets to the non-convex fuzzy sets. This theorem enables to find the crossover points of the fuzzy sets, which gives new outlook to the modeling of the nonconvex fuzzy sets in terms of the convexity of the fuzzy sets. The power fuzzy convex sets and their properties are established in the article here to show the convexity of all level cuts of the sub-sets of the fuzzy set. There were presented the properties of the quasi-convex fuzzy sets, which indicates the support plane of the fuzzy sets, where the characteristic function is quasi-convex at the support point. Furthermore, there were introduced the properties of the quasi-convex fuzzy sets, where the convexity of the fuzzy sets can be achieved at the mid-point of the suggested interval of uncertainty, where the support point is located. There were presented the properties of the quasi-convex fuzzy sets, where the extension principle to apply the fuzzy categories can be utilized. There were presented the various types of the constructed convex membership functions based on the new convexity properties established in the article here. Keywords: Fuzzy sets · Convex fuzzy sets · Quasi-convex fuzzy sets · Support plane · Support point · Characteristic function · Convex membership function

1 Definitions and Main Principles of the Fuzzy Sets Definition 1.1. Let U be a set, called the universe, where the elements of the universe are x ∈ U. If F ⊂ U, then membership in subset of F of U is called a characteristic function.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 276–284, 2021. https://doi.org/10.1007/978-3-030-57453-6_24

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A membership of the characteristic function is based on the set {0, 1}, where value 1 indicates the membership, while the value of 0 indicates the non-membership, such that:

Definition 1.2. If the set of F is defined on the real closed interval [0, 1], then F is identified as the fuzzy set [1, 2]. Based on the definition we can define the fuzzy set as it is: Definition 1.3. A fuzzy set F is a set, which is defined by the set of ordered pair: . If , where T [0, 1] is a family of the closed intervals, then this type of the fuzzy set is called the interval-closed valued fuzzy set. Equivalent fuzzy sets: Two fuzzy sets are equivalent if and only if:

Support of the fuzzy set: The support of the fuzzy set is a set with the non-zero membership function: . Crossover point of the fuzzy sets: , where , are the crossover points of F. The elements of Singleton of the fuzzy set: as support is a singleton. A fuzzy set with the only point , when Height of the fuzzy set: The height of a fuzzy set is the least upper bound of a membership function:

F is normalized if and only if and . In all other cases a fuzzy set is sub-normalized fuzzy set. -level fuzzy set: The -level fuzzy set is a subset, where elements are the entries of a fuzzy set to the . least degree of If the inequality is strict, then is a strict –level fuzzy set. Hence, we will define the fuzzy set in terms of the level sets as it is: There is existed level fuzzy set there as it is: (1) Based on (1) we may re-define the standard fuzzy set as the union of the standard fuzzy subsets: (2) The (2) is the union of the fuzzy subsets, which is called a decomposition of the fuzzy sets based on -level fuzzy sets.

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Now we introduce the following decomposition theorem of the fuzzy sets: Theorem I: If F ∈ F(X ) is the union of –level sets: (3) where Proof: Let let us represent

, then F(X ) is called the fuzzy power set of X . , where . The representation in terms of the sum as the sum of supporting subsets:

where 0 is the empty set ∅: and , are , where . the -level cut sets of . Thereafter, Corollary 1: For F = F(X ), a cardinality of fuzzy set of F is the following: F| . The relative cardinality is F = ||X |. Definition: The inclusion of the fuzzy sets satisfies the following condition: . Given fuzzy sets F1 , F2 ∈ F(X ), F1 ⊆ F2 if If inequality is strict, then the inclusion is strict as well.

2 The Convexity of Fuzzy Sets Definition 2.1. A fuzzy set is convex if and only if there is the following inequality holds: (4) Because the convexity of a fuzzy set is given at the point of x ∈ R, which is the element of fuzzy set, then we may represent the concept of the quasi-convexity, which meant the convexity at the point: Definition 2.2. Let F be non-empty fuzzy convex set in R and let . The fuzzy set is a quasi-convex if for each elements there is the following inequality holds: (5) The theorem below shows that the convexity of the fuzzy sets is determined by the convexity of its level cuts. . Theorem 2: If F is the non-empty convex fuzzy set in R and The fuzzy set is quasi-convex if and only if the level

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cut set

is quasi-convex for each . Proof: If is an element of the support of the fuzzy set, then there exists neighborhood around , where . , and . The strong quasiSuppose that there exists convexity leads us to the inequality:

However, . This result contradicts the local convexity at x. There is presented Extension rule, originally defined by Zadeh, which lets apply fuzzy set theory on the mathematical applied problems. The Extension rule can be applied to the membership functions, which are not one-to-one functions. In such scenario the Extension rule suggests that the fuzzy image by the fuzzy arguments can be obtained at the support of the membership function. Extension rule: Let’s consider mapping from domain of X to a range of . If F ⊂ X , then a fuzzy subset about domain of X has the image by the characteristic . function of of the fuzzy variable: Part 1: If is one-to-one mapping, then (6) Part 2: If is not one-to-one mapping, then there is the following rule applies: (7) The following theorem lets evaluate characteristic function at two points in a case, when the fuzzy membership function is not one-to one. Based on this theorem we can locate the element of the fuzzy set, which corresponds to the support of the fuzzy set, which, eventually, proves the case 2. . Consider Theorem 3: Let F be non-empty quasi-convex fuzzy set on , such that ζ < η. , then there exists such that for Part 1: If . Then at . , then for . Then Part 2: If for . and . Next, using contradiction, let Proof: Suppose . and membership function is strictly Since ζ is the convex combination of . However, this result quasi-convex, we obtain that . Therefore, . contradicts that The part 2 is proved by using similar contradiction. Next theorem is for the strictly quasi-convex fuzzy sets over the given interval and the mid-point of this interval is the convex combination of the other two pints.

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Theorem 4: Let F . Let

be non-empty strictly quasi-convex fuzzy set on and δ > 0, where δ is very small. Next, let , such that λ < ε < μ. , then for . If , then Part 1: If for . , then for . If , then Part 2: If for . and . Using contradiction, let Proof: Part 1: Let . Since ε is convex combination of , then using definition of the strictly . However, this results convex fuzzy sets we obtain . Therefore, bring us to contradiction, since, there was supposed that . and . Using contradiction. Let . Part 2: Let and using the definition of the strictly conSince μ is a convex combination of , which contradicts to vex fuzzy sets we have . Therefore, . We must mention, that the concept of the strictly quasi-convex fuzzy sets can be utilized in the extension principle to enhance it to find the support of the fuzzy set with the following theorem given below: be a strictly quasiTheorem 5: Let F is a nonempty convex set in X . Let is the support convex. If is the point of the strictly quasi-convex fuzzy set, then . point of . The convexity of the Proof: Let us assume that there exists . We assumed that is the support point set of F lead us to for of . By the convexity at the point we have is strictly quasi-convex and , hence we some γ ∈ (0, 1). Because for each δ ∈ (0, 1). However, here we have got obtain that the contradiction of the support point of . Hence, the proof is completed.

3 Fuzzy Convex Sets and Analytical Representation of the Convex Fuzzy Sets The Fuzzy sets can be presented in various ways such as modeling by type 1 to type 2, when type 2 has the six modifications in terms of the analytical representation. Type1: Discrete form of the fuzzy sets, where the fuzzy sets are in the form of discrete . pairs Type 2: Analytical representation, when the fuzzy sets are described as the parametric or piecewise functions, such as: I.

Convex membership functions with sink:

The Convex Fuzzy Sets and Their Properties with Application to the Modeling

II.

Smoothed sink convex membership:

Alternatively, smoothed convex membership functions can be given as it is:

III.

Concave membership

IV.

Piece-wise Convex membership L-functions:

V.

Convex Fuzzy membership smoothed L-functions:

Alternative smoothed L-function:

VI.

Membership S-function by Zadeh:

with flanks for modeling:

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VII. Fuzzy membership convex functions represented by the smoothed concave function:

VIII. Smoothed convex membership function:

For t > 1, We must note that the construction and, further, utilization of membership functions with analytical representations I–VIII is enormously important process as the fundamental key factor to approach the various modeling techniques in the theory and applications of the control systems. The process of building of a membership function is a vital step in the theory of control systems. The modeling types I through VIII is highly useful, when the parameters of the prospective constructed membership function are following the parameters presented at the prospective analytical representation of the membership function in the form of type I to type VIII. If the membership function is chosen and, then approximated to match the parameters of modeling with type I–VIII, then such estimated model is called as the modeling type of human phenomena problems [3–9].

4 Conclusion The linguistic problems with further representation of the linguistic elements in the form of the fuzzy convex sets give the ample opportunities to represent the fuzzy convex sets analytically with graphical representation of the various types of concave membership functions. The fuzzifying category is enhanced enormously by the extension principle, which gives broad opportunities to apply fuzzy modeling category to the vast variety of the functions, which are not convex and/or not one-to-one. The theoretical verification in terms of the newly proved theorems to support the extension principle were given in this article here. There was presented Theorem 1, which has proven that the convexity of the level cut fuzzy sets is the convex power fuzzy set in the form of the union of level-cut fuzzy sets. The Corollary 1 of Theorem 1 describes the concept of the cardinality and relative cardinality of the power fuzzy sets. The Theorem 2 proves that the fuzzy quasi-convex properties of the fuzzy sets need to be applied to each level cut of the fuzzy sets. Furthermore, this theorem illustrated that all level cut of the fuzzy sets is quasi-convex. The Theorem 3 empowered the extension principle to utilize fuzzy properties to the functions, which are not one-to-one. Moreover, the theorem 3 lets locate the fuzzy argument of the universe of the fuzzy sets, where the support plane can be determined.

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The Theorem 4 considered the opportunity to show that the quasi-convexity of the fuzzy sets occurs at the mid-point of the interval of uncertainty of the fuzzy argument. This theorem establishes new enhancement to the extension principle for the non-convex and not one-to-one functions. The Theorem 5 lets find the support of the quasi-convex fuzzy sets by locating the point, where the fuzzy set is strictly quasi-convex. This theorem is the new enhancement to the extension principle, which enables to locate the support plane of the fuzzy sets. There were shown the analytical and/or possible graphical representation of the various types of the analytical representation of the fuzzy convex sets set by modeling type I through type VI. Utilizing the analytical representation of the modeling of the fuzzy sets with type I to type VI modeling provides us with sufficient information to visualize the fuzzy sets by the characteristic functions and corresponding fuzzy curves. The problems, where we need to construct the analytical representation of the characteristic functions direct to the broad manifolds of the applied and engineering problems. Further application of the properties of the convex fuzzy sets and fuzzy analytical modeling of the types 2 from I to VIII directs to the application of the heuristic processes. The modeling of the heuristic processes gives engineers and researchers in applied sciences magnitude of the opportunities from discovering the new analytical modeling of the construction of the convex fuzzy sets to visualizing fuzzy sets in terms of the applied mathematics and engineering context. Furthermore, the utilization of the constructed heuristic fuzzy set model is the vivid example of the application of the theoretical fuzzy logic mathematical tools in real engineering and environmental problems. These types of the application of the theoretical models in construction of the analytical model of the membership functions are in great demand in the various fields of the natural phenomena and human innovation activity. Moreover, the construction of the heuristic fuzzy set modeling is strongly required to be based on the precise mathematical tools with reference to the problem to be solved. It is important to mention that the fuzzy sets with the corresponding membership function have been analyzed within the concepts of the modern Analysis in the article here. Moreover, new properties of the convex fuzzy sets are established in the article here. The convex fuzzy set and their properties can be utilized for modeling purposes to model human phenomena activities, e.g. such as modeling of the convex fuzzy sets to represent natural and human phenomena problems, involving factors such as a temperature, volume, frequency, age, degree, or pressure, or any other forms of the human activity or natural phenomena problems.

References 1. Gadjiev, D.D., Kochetkov, I., Rustanov, A.: Aggregation of the fuzzy logic sets in terms of the functions of the triangular norm and triangular co-norm. IOP Conf. Series 403, 012187 (2019). https://doi.org/10.1088/1755-1315/403/1/012187 2. Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. J. Fuzzy Sets Syst. 1, 3–22 (1978)

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3. Zimmerman, H.J.: Fuzzy Set Theory and Its Application, Second Revised Edn. Kluwer Academic Publishers, Boston (1993) 4. Aliev, R.A., Fazlollahi, B., Aliev, R.R.: Soft Computing and Its Applications in Business and Economics. Springer, Heidelberg (2004) 5. Yager, R.R., Filev, D.P.: Essentials of Fuzzy Modeling and Control. Wiley, Hoboken (1994) 6. Mamdani, E.H.: Applications of fuzzy logic to approximate reasoning using linguistic systems. J. IEEE Trans. Comput. C-26, 1182–1191 (1977) 7. Aliev, R.A.: Fuzzy experts systems. In: Aminzadeh, F., Jamshidi, M. (eds.) Soft Computing: Fuzzy Logic. Neural Networks and Distributed Artificial Intelligence, pp. 99–108. PTR Prentice Hall 8. Cerruti V. Graphs and fuzzy graphs. J. Fuzzy Inf. Decis. Process. 95 (1982) 9. Aliev, R.A., Aliev, R.R.: Soft Computing and Its Application. World Scientific, New Jersey (2001)

Automation of the Construction Process by Using a Hinged Robot with Interchangeable Nozzles Erik Grigoryan1

, Anna Babanina1(B)

, and Kirill Kulakov2

1 Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya Street, 29, Saint

Petersburg 195251, Russia [email protected] 2 Moscow State University of Civil Engineering, Yaroslavskoe Shosse, 26, Moscow 129337, Russia

Abstract. The article describes a method of automating the construction process by using a hinged robot in construction. Some problems such as the mobility of the 3D printing device have been solved. With increasing mobility of the device there will be increased not only the speed of construction, but also the need for high-class concrete. The main purpose of the experience is to provide a method of feed solution in the terms of use articulated robot manipulator with possibility of timely dosages in difficult conditions so that replenishment of the solution could occur on the construction site or close to it. The main idea is to use nozzles that have certain capabilities for construction. The first nozzle is a system of capturing brick blocks fed by the conveyor, and their further movement to the desired point. The other nozzle is a mobile extruder. The system is able to create a concrete thread with great precision which can be used as a masonry mortar and as a solution for printing the frame of the building. Keywords: Hinged robot · Construction process · Interchangeable nozzles

1 Introduction To date, a large number of studies are carried out to study the automation of the construction process, including the introduction of construction 3D printer. Nevertheless, despite the rapid rate of increase in labor productivity, the construction industry lags behind other areas in which automation technologies have been introduced [1, 2]. Other industrial sectors, such as the automotive industry, have already fully undergone changes in the values of improving product quality and productivity with the advent of new technologies [3, 4]. The method of full or partial automation of masonry structures has the possibility of remote updating and modification, so this system has prospects for further research. Digital design and planning tools such as CAD, BIM, Revit, etc. are already quite well developed and are gaining all the need to use, while automated manufacturing © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 285–297, 2021. https://doi.org/10.1007/978-3-030-57453-6_25

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methods are still not able to be fully used in practice, they also need development and research. Awareness of this fact of the prospective use of such technology has led to an increase in research activities in this area in recent years [5–7]. The main problem of printing structures using selective layer-by-layer deposition by extrusion is the low mobility and poor weather resistance of printing equipment [8, 9]. These disadvantages are applicable to mass construction on construction sites. At the moment, the printing of structural elements takes place in spacious and equipped rooms, after which the element is transported to the construction site. This method of automation is not optimal, complex and often economically unprofitable for developers, as we are talking about trivial forms of the building. The issue of mobilization of construction 3D printer remains relevant to this day. Most of the already known and proposed approaches to the creation of additive concrete based on extrusion can’t meet the requirements of large-scale mass construction, in addition, with the increase in the dimensions of structural or non-structural components, respectively, the cost of machines increases. For economic reasons, a great advantage would be the maximum use of existing equipment with the need to modify it (nozzles for different types of work). A big broken in the development of 3D technology in construction is the need to adapt the concrete mixture under the narrow opening of the extrusion head. In addition, it should be noted that construction with concrete printing can increase the cost of materials, as in practical application, the need for a concrete mixture of a higher and more expensive class, unlike traditional mixtures, will increase. Obviously, with increasing mobility of the device, capable of layer-by-layer deposition by extrusion, will increase not only the speed of construction of buildings and the efficiency of resources spent on the construction of large structures, but also the need for high-class concrete. The main purpose of the experience is to provide a method of feed solution in the terms of use articulated robot manipulator with possibility of timely dosages in difficult conditions so that replenishment of the solution could occur on the construction site or close to it. Such operations will help to automate the process of construction of stone structures, increase its speed and availability. The task is to show in theory the possibility of practical application of this method of supplying the solution. In a simplified form, an extrusion 3D printer can be represented as a print head working in conjunction with a positioning system that moves the head precisely along the print path. Obviously, the larger the dimensions of this device, the larger the object it will be able to build (increases the printing radius). The printing process is carried out in such a way that the motors installed on both sides of the device, with the help of toothed belts, move the extruder along the programmed “path”, thereby layer by layer creating a previously designed object. In most cases, the 3D printer uses two fixed motors that drive two belts to move the extruder head on two axes, but it is worth considering that this system is used to create relatively small objects that require high accuracy (Fig. 1). The disadvantages of this positioning system are obvious. Stationary industrial robots are very limited in working space. The maximum range of the working space is around 4–5 m [9], making it ineffective in dealing with large-scale objects in the field of construction, besides, this device has no ability to move that allows it to be used in the

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Fig. 1. Core XY 3D printer positioning system.

construction industry. In the case of objects with sufficiently large dimensions, the positioner does not need such accuracy, so one motor with significant weight and power will be enough. To move the extruder requires a convenient system that can control the head with good accuracy. The design of the “engine-belt” has only one axis of movement, which is not convenient for working with objects of large scale. Moreover, the movement of the extruder head must not only be precise, but also fast enough to realize economical printing speed. The French company XtreeE [9] offered its model of industrial robots for 3D printing with complex shapes. To increase the working space, the company uses several robots at the same time, placed at different points at the required distance (Fig. 2). This system has the same principles of 3D printing, but has a large radius of coverage. This structure of the relationship between the positioner and the extruder head is necessary to create large-scale objects. But the disadvantage of the xtreel robot is the inability to work with a solution consisting of a large filler. Moreover, the design is not able to work with a solution of low class and quality. An interesting 3D printer concept was implemented by Apis Cor. The peculiarity of the design consists in the presence of a rotary mechanism located in the Central axis of the robot base. The rotary manipulator has a horizontal telescopic boom to move the print head. During the solution feeding process, the boom grows with the printing object. The technology is designed to erect simple structures outside the Earth, for space companies such as Space X, or the state Corporation NASA. The disadvantage of this equipment is the restriction on the height of the structure and the final location of the object. After completion of the construction of the manipulator in the case of the construction of the building with the maximum allowable radius and close to this value, the robot is inside the building, which causes difficulties in its further extraction. In addition, to print a building more than one floor, it is necessary to move it to the second, which also causes difficulties, since the weight of this device is quite impressive. In addition, the bearing

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Fig. 2. The concept of the proposed 3D printer.

capacity of the overlap will have to be determined taking into account the weight of the printing robot. Obviously, all designs are based on concepts used in other industries to drive the extruder head. These methods can obviously be explained from a logical point of view, technologies have already been applied in practice and are in increasing demand among users and investors. But the construction industry is much more complex and large-scale in terms of the area of work. Most of the known specific projects are not able to be fully implemented in this area for several reasons: • • • • • •

rough environment: site irregularities, weather conditions, scale of work; need for regular maintenance; conservative attitude of the construction industry to technology; diversity of work performed; the absence of a large number of people classified in the work with robots; therefore, it is important to use a specific manipulator having several nozzles that are able to perform different types of work. Ease of operation and maintenance is also important. The technology should be simple and clear. Therefore the purpose of adaptation works is; • to make a frequently used technique suitable for printing specific drive modifications or individual components; • to allow the concrete mortar not only to build walls, but also to serve as a seam of brickwork. Thus, the proposed scheme in the article will help to solve the problem not only with structures created exclusively by a 3D printer, but also to automate the traditional process of construction – walls of brickwork. For several years, employees of the Dresden technical University have been researching and modifying the boom drive in order to optimize the accuracy of the robot’s

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positioning. In the end, the necessary data were obtained, with the help of which optimized drive components, algorithm and control systems can be implemented, allowing to reduce oscillations up to 95% and increase positioning accuracy.

2 Materials and Methods 2.1 The Device that Was Used for Testing the Method of Solution’s Feeding In the course of the research as articulated robot manipulator was used the equipment of company Mitsubishi. The model of the test robot is RV-2AJ. This model is able to fully perform all the necessary processes for the project. On the example of this robot, you can see the possibility of practical application of the proposed process. In addition, the robot is equipped with pneumatic grips, the work of which can be used in different ways. Technical characteristics of the used articulated robotic arm: • • • • • •

model: Mitsubishi Robot RV-2AJ; type of robot: Articulated; number of joins: 5; payload: 2.0 kg; repeatability: ±0,02 mm/s; arm reachable radius: 482 mm.

Since it is first necessary to carry out tests on miniature devices only similar in characteristics to the actual ones, a full-bodied brick with a scale of 1:10 relative to the size of the brick used in construction was chosen as a building material. The fine aggregate solution was presented with a gypsum-based solution that has a relatively similar solidification rate and fluidity. Moreover, this type of solution on properties strongly does not differ from water-cement. The result of this study is a theoretical proof that the use of the manipulator as a masonry and mortar feeding device is possible with the help of replaceable nozzles and only with the use of one pair of pneumatic grips. The task also includes the selection of the most optimal mechanism capable of interacting with robots and at the same time to be able to replace others in a timely manner. Moreover, the design should include the possibility of timely dosing in the field. The work includes several stages: • ability to create algorithms using a special programming language, which is suitable for controlling the robot, on a stationary computer; • creation of a drawing of the optimal working system for supplying a sufficiently thin and accurate jet of mortar capable of stopping work at a certain time without unnecessary residues of the concrete mixture; • create a drawing of gripping brick claws, customized to a specific size and weight of the brick (in this case – work with a brick having a size of 1:10 relative to the real); • calculation of viscosity of liquids, optimal speed of solution supply and extruder head movement;

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• testing with mock-UPS of building components to illustrate the feasibility of using this technology on a real construction site; • calculation of the percentage of components entering the extruder feed mixture. 2.2 Robot Control Using a Programming Language The initial stage of the study is to connect the articulated robot arm to a stationary computer, and later control it with the help of the desired programming language. After connecting to the computer using the licensed computer program COSIROP, you must select one of the proposed programming languages. MELFA BASIC IV was used in this study. After setting the desired position of the x, y, z axes, it is necessary to set the initial position of each brick. The test was carried out taking into account that the initial position of each brick will remain unchanged with the help of conveyor feed technology. The final position of each brick is indicated by calculation depending on the shape of the future structure, this requires the dimensions of one of them (width, height and length). Obviously, the higher the quality of the robot manipulator, the less error it has, since the model Mitsubishi RV-2AJ has an average level of quality, inaccuracy in the work was appropriate, so you should sometimes make a check for an offset from the initial level (Fig. 3).

Fig. 3. Training manipulator.

The final stage of the first stage is to write a program with which the robot moves and performs the necessary actions. The MOV command in this language means the command to move from one point to another, and the OVRD command is the speed

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of the manipulator head as a percentage of the maximum speed (OVRD 10–10% of the maximum speed). Teams such as HOPEN and HCLOSE operated pneumatic grips, opening and closing them respectively. The last important command is DLY, which means a pause in seconds that the robot will make before it starts a new task. After the correct algorithm is compiled, it is necessary to specify a cycle of these actions with an offset depending on the brick layer. The model of the manipulator used was created for training purposes, not for construction work, so many of the necessary sensors were missing (optical), but for working with bricks on a scale of 10:1, the manipulator was completely suitable for testing.

3 Results and Discussion 3.1 Drawing of the Solution Supply Mechanism The stage of creating a mechanism capable of transforming the simple installation of two grips that can move only in two opposite directions is the main one in the development of this device. Therefore, the design used a system acting on the principle of a crank mechanism (CM), which is designed to convert the reciprocating motion of the pistons into rotational motion (Fig. 4). Based on the possibility of using CM in the case of the grips of the manipulator, it was found that the method of feeding the solution by rotation is the most optimal among other possible. Pneumatic grips are only capable of reciprocating, so it is obvious that the device will be appropriate for this test.

Fig. 4. Crank mechanism.

After selecting the necessary system by which the solution will be supplied, it is necessary to reduce the number of pistons to two (only two grips) and install them on different sides to be able to perform the necessary functions. The work consisted in measuring the distance and dimensions of two pneumatic grips (Fig. 5). Later, the necessary measurements were transferred to AUTOCAD. The drawing reflects the exact dimensions of the rotating head of the manipulator. For comparison, a photo of this part of the robot arm was taken, reflecting the actual type of grips (Fig. 6).

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Fig. 5. Drawing pneumatic tongs of the manipulator.

Fig. 6. Photo of the drawn component.

After transferring the exact dimensions to the program, a prototype of a replacement mechanism was designed, capable of performing an accurate supply of concrete mix with timely dosing (Fig. 7). The device was designed exclusively to work with the

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articulated robot used in this work. It is worth noting that to work with manipulators of other manufacturers, the size and final appearance of the extruder will be different depending on the performance and capabilities of the robot model.

Fig. 7. A prototype of the extruder, the feed solution using a rotating screw.

This drawing was created using the computer program AUTOCAD 2018. This is a graphical program that allows you to create not only flat drawings, but also objects in 3D, which can then be displayed on 3D printing. Algorithm of actions when creating a three-dimensional object: it is necessary to enable computer-aided design (CAD), in the mode of operation to choose 3D modeling. According to the available working drawings, using the “modeling” tab, simple geometric shapes are created, into which you can divide this object. Using the “edit” tab and the “move”, “copy” tools in space, the resulting shapes must be arranged according to the drawing. Using point-to-point binding, it will be more convenient to create a final volumetric object. The ViewCube tool, located in the upper right corner, helps to bypass the object from all sides, and eliminate possible inconsistencies. The main components of the solution supply system are shown in Fig. 8. Elements of the water-cement mortar supply system: 1. 2. 3. 4. 5. 6.

Thermal insulator. A rotary screw with a specific pitch. The extruder nozzle. The direction of rotation of the screw. The level of water solution. The body of the extruder.

3.2 Drawing of the Mechanism Which Grabs a Brick Creation of the replaceable mechanism capable to seize a brick without its further damages passed by the same principle, as the above-mentioned system of giving of a solution.

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Fig. 8. Extruder printing device.

Moreover, this component, due to the lack of complex components, was created specifically for the model used in the experiment of the articulated robotic arm. Figure 7 shows the distances between the skeleton grips, which is attached to the main capture device. It is also worth Recalling that the device was created exclusively for this model of manipulator (Fig. 9).

Fig. 9. Prototype of the device of capture of a brick (drawing).

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This element is attached to the base of the tongs. With its help, the brick is transferred to the desired position, it is only necessary to specify it in the program that controls the manipulator. The pneumatic Tong in the RV-2AJ manipulator has a pressure sensor and regulator. An appropriate amount of pressure is applied to lift and carry heavier objects. This system was implemented using 3D printing technology, and later fixed on the basis of tongs. 3.3 The Main Properties of the Concrete Mixture Used as a Mortar for Masonry • Mobility: the mobility grade is determined according to the main purpose of the solution. As in work the laying from a full-bodied brick, ceramic stones, concrete stones or stones from easy breeds recommended according to Russian state standard GOST 28013-98 the mark on mobility PK3 with depth of immersion of a cone of 8–12 cm is used. • General technical conditions for clay, which is part of the solution: the content of clay particles smaller than 0.4 mm should be from 30 to 80%, the size of more than 0.16 mm-no more than 30%. Granulometric composition of clay is determined by Russian state standards GOST 21216.2 and GOST 21216.12. • Water-holding capacity of mortar mixtures should be not less than 90%. • Delamination of freshly prepared mixtures should not be higher 10%. • The temperature of the mortar mixture should, depending on the climate, correspond to the Table 1. Table 1. The effect of ambient air temperature on the temperature of the mixture. Average daily outdoor temperature, °C

Solution mixture temperature, °C Masonry material Brick

Stone

Wind speed, m/s Less than 6

Over 6

Less than 6

Over 6

Less than −10 °C

10

10

10

15

From −10 °C to −20 °C

10

15

15

20

Less than −20 °C

15

20

20

25

• The time to increase the percentage of strength depends on the outside temperature according to Table 2. Taking into account all the above properties, you can choose the optimal brand of solution suitable for its use as a masonry mortar. There was carried out a research to detect the influence of the percentage of the system consisting of sand, cement and fly ash on the static and dynamic yield stresses. Based on 15 experiments with a different percentage of solution components, there was

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The period of curing, days

A fraction of the 28-day strength achieved under optimal hardening conditions, (%) −3 °C

0 °C

+5 °C

+10 °C

+20 °C

+30 °C

1

3

5

9

12

23

35

2

6

12

19

25

40

55

3

8

18

27

37

50

65

5

12

28

38

50

65

80

7

15

35

48

58

75

90

14

20

50

62

72

90

100

28

25

65

77

85

100

selected the most optimal composition, which contains 16% cement, 22% sand, 25% fly ash, 33% water and 4% silica powder. In this case, the static yield strength will be higher than 5000 Pa, and the dynamic - more than 250 Pa, which will allow the fresh solution to withstand the load of the subsequent applied layers. Therefore, theoretically, this system can be used in real conditions.

4 Conclusion In this study, a construction automation system was proposed through the use of replaceable nozzles for timely dosing in the field. The system consists of 2 nozzles: a brick Tong system and an extruded cement mortar supply system for both gluing brick layers and printing the supporting frame of the building. An important component in the work was the creation of a replaceable system of supply of mortar mixture using the principle of crank mechanism, as it was necessary to choose the most suitable system of supply of solution not only for the robot manipulator used in this work, but also for other models of robots.

References 1. Konikov, A.I.: Perspective directions in the field of construction management information systems. Ind. Civ. Eng. 6, 64–69 (2019). https://doi.org/10.33622/0869-7019.2019.06.64-69. (in Russian) 2. Dalenogare, L.S., Benitez, G.B., et al.: The expected contribution of Industry 4.0 technologies for industrial performance. Int. J. Prod. Econ. 204, 383–394 (2018). https://doi.org/10.1016/j. ijpe.2018.08.019 3. Wu, P., Wang, J., Wang, X.: A critical review of the use of 3-D printing in the construction. Autom. Constr. 68, 21–31 (2016) 4. Farhan, N.A., Sheikh, M.N., Hadi, M.N.S.: Investigation of engineering properties of normal and high strength fly ash based geopolymer and alkali-activated slag concrete compared to ordinary Portlandcement concrete. Constr. Build. Mater. 196, 26–42 (2019). https://doi.org/10. 1016/j.conbuildmat.2018.11.083

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5. Chousidis, N., Ioannou, I., Batis, G.: Utilization of Electrolytic Manganese Dioxide (EMD) waste in concrete exposed to salt crystallization. Constr. Build. Mater. 158, 708–718 (2018). https://doi.org/10.1016/j.conbuildmat.2017.10.036 6. Grigoryan, E., Babanina, A., Eropkin, A.: Concrete mixture grout for printing extruder. E3S Web Conf. 135, 03072 (2019). https://doi.org/10.1051/e3sconf/201913503072 7. Ardiny, E., Witwicki, S., Mondada, F., Construction automation with autonomous mobile robots: a review. In: 2015 3rd RSI International Conference on Robotics and Mechatronics (ICROM), Tehran, pp. 418–424 (2015). https://doi.org/10.1109/icrom.2015.7367821 8. Roychand, R., De Silva, S., Law, D., Setunge, S.: Micro and nano engineered high volume ultrafine fly ash cement composite with and without additives. Int. J. Concr. Struct. Materials 10(1), 113–124 (2016). https://doi.org/10.1007/s40069-015-0122-7 9. Melenbrink, N., Werfel, J.: Autonomous sheet pile driving robots for soil stabilization. In: 2019 International Conference on Robotics and Automation (ICRA), pp. 339–345 (2019). https:// doi.org/10.1109/icra.2019.8793546

Acting Stresses in Structural Steels During Elastoplastic Deformation Alexander Scherbakov1

, Anna Babanina2(B) , and Kirill Graboviy3

1 Saint Petersburg State University of Architecture and Civil Engineering, Vtoraya

Krasnoarmeiskaya Street, 4, Saint Petersburg 190005, Russia 2 Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya Street, 29, Saint

Petersburg 195251, Russia [email protected] 3 Moscow State University of Civil Engineering, Yaroslavskoye Shosse, 26, Moscow 129337, Russia

Abstract. The destruction of welded metal structures is most often preceded by plastic deformation in stress concentration zones. Therefore, the detection of such zones when assessing the technical condition of metal structures where plastic deformation has occurred or is occurring is an important scientific and practical task. In the study, mechanical tests were carried out to obtain the dependence of the values of the magnetic field strength Hp (σ) in the controlled zone under cyclic uniaxial tension of the samples under elastic and plastic deformation. Graphic dependencies of values are obtained. According to the research results, the relationship between the structure, magnetic and mechanical parameters is revealed, which allows a reliable assessment of the structural state of the metal and the operating stresses in welded joints and elements of welded metal structures using other methods of the passive flux-gate control method. Keywords: Elastoplastic deformation · Structural steels · Graphic dependencies · Mechanical tests

1 Introduction During the manufacture, installation and subsequent operation of welded metal structures of building machines, structural changes occur in the metal of welded joints and metal structural elements, some of which are sources of dangerous zones of stress concentration. A decrease in the reliability and safety of welded metal structures is possible when acting stresses in the hazardous areas of the stress concentrations are higher than the permissible stresses or plastic deformation occurs to one degree or another. Therefore, obtaining accurate information in the process of monitoring the technical condition of welded metal structures of building machines and assessing the residual life requires both the development of new methods and the improvement of existing methods and techniques of control tools [1–5]. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 298–311, 2021. https://doi.org/10.1007/978-3-030-57453-6_26

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When assessing the structural state and indirectly measuring the acting stresses in products made of ferromagnetic materials, magnetic control methods are often used based on the relationship between the structural, magnetic, and mechanical parameters of the metal [6, 7]. But such control can be complicated by the fact that often during the technical diagnosis of welded metal structures the structural state of the metal, chemical composition and magnetomechanical background of the metal of structural elements and welded joints remain unknown. As a rule, the destruction of welded metal structures is most often preceded by plastic deformation in stress concentration zones, therefore, the detection of such zones when assessing the technical condition of metal structures where plastic deformation has occurred or is occurring is an important scientific and practical task, since this helps to increase the reliability and safety of the operating constructions. The solution to this complex problem requires extensive experimental research on structural steels with different initial structures and chemical composition, including the structure after cold plastic deformation. The aim of the article is to identify the relationship between the structure, magnetic and mechanical parameters, which will allow a reliable assessment of the structural state of the metal and the acting stresses in welded joints and elements of welded metal structures.

2 Methods and Materials Mechanical tests to obtain the dependence of the magnetic field strength value Hp (σ) in the controlled zone during cyclic uniaxial tension of the samples under elastic deformation were carried out using low-carbon steel 08ps, St3 and low-alloy 10CrSiNiCu. The test samples were subjected to various types of processing (in order to obtain a coarse-grained structure): • • • • •

factory as-received condition; factory as-received condition + annealing at 900 and 1050 °C; to obtain a fine-grained structure: factory as-received condition + thermal cycling; factory as-received condition + rolling for the degree of deformation ε = 50%.

It should be noted that, depending on the initial structure of the chemical composition, magnetic and mechanical background of the samples, the initial values of the magnetic field strength Hp (before applying an external load) on the surface of the sample in different zones can vary significantly both in sign and magnitude. This was taken into account when the experimental studies were carried out. The dependence of the scattering magnetic field strength on the acting stresses Hp (σ) was obtained on samples in an artificially created stress concentration zone, which was created by reducing the crosssectional area in the central part of the sample by 20% due to the creation of lateral radius grooves. Mechanical tests in the plastic region of deformation were carried out using samples of low-carbon steel 08ps and low-alloy steel 10CrSiNiCu, preliminarily rolled to a degree

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of deformation ε = 50% during elastoplastic deformation. In this case, the influence of the chemical composition and structural state of steels on the magnetic parameter Hp was studied, depending on the magnitude of the acting stresses.

3 Results and Discussion 3.1 Area of Elastic Deformation The obtained dependences of the magnetic field strength value Hp (σ) in the controlled zone under cyclic uniaxial tension of the samples under elastic deformation are shown in Fig. 1, 2, 3, 4 and 5. It should be noted that, regardless of the initial structure and chemical composition of the steels, after the first loading-unloading cycle of the samples, the greatest changes in the magnetic parameter Hp from the magnitude of the acting stresses were observed. In all the studied steels, with an increase in the operating stresses σ, the values of Hp decrease during tension and increase during unloading, as a result of which a magnetic hysteresis loop is formed during loading and unloading of the samples. But after the first cycle of elastic loading and unloading of the samples, the magnetic hysteresis loop is not closed, and the final values of the magnetic parameter Hp after unloading do not coincide with the initial values before loading. Regardless of the steel under study, the second loading-unloading cycle contributes to the closure of the magnetic loop.

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205 200

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175

100 80 0

50

100

150

a)

200

250 300 s , MPa

170

0

25

50

75

100

125

s , MPa

b)

Fig. 1. Dependence of the magnetic field scattering H p from uniaxial tensile stresses σ of steel samples in the as-received condition: a - 10CrSiNiCu; b - 08ps.

At the third and subsequent loading and unloading of the samples, the values of Hp (σ) observed during the second cycle are practically repeated. In all cases, the increment

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1 2 3

205 200 195

нагружени 1 loading е нагружени 2 loading е нагружени 3 loading е

11ра згр. unloading 22ра згр. unloading

1 2 3

260 250

н1агружени loading е н2агружени loading е н3агружени loading е

11разгр. unloading 22разгр. unloading

240 230

190 185 180

220 210

175 170 165 160

200 190 180

155 150 145

170 160 150

140 135 0

25

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100 125 150 175 200 225

140 0

25

50

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100 125 150 175 200 225

s , MPa

s , MPa

b)

a)

Fig. 2. Dependence of the magnetic field strength H p from uniaxial tensile stresses σ of steel samples: a - 10CrSiNiCu in the as-received condition + thermal cycling; b - 08ps after rolling at ε = 50%. Нр, А/m

205

115

нагружени е 11 loading разгр . 11 unloading 2 нагружени е 2 loading разгр . 22 unloading нагружени е 33 loading

200 195

Нр, А/m н агружени е 1 loading р азгр. 1 unloading н агружени е 2 loading 2 unloading р азгр. н агружени е 3 loading

105 95

190 185

85

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65

170 55

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160 0

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a)

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Fig. 3. Dependence of the magnetic field H p on uniaxial stresses tensile σ of steel samples: a 08ps after annealing at 900 °C; b - St3 in the as-received condition.

of the scattering magnetic field strength Hp is proportional to the change in the acting stresses σ. Therefore, regardless of the initial values of Hp of the chemical composition of the steels, after the first loading-unloading cycle, the initial magnetic prehistory of the samples is completely erased, as a result of which the increase in the number of cycles

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190 185 180

11loading нагружение 11unloading разгр. 22loading нагружение разгр. 22unloading нагружение 33loading

195 190 185 180 175 170

175 170 165 160

165 160 155

155 150

150 145 140 135 130 125

145 140 135 130 125 0

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practically does not change the nature of the course of the Hp (σ) curves, and thus increases the degree of reliability of the measurements. Thus, the coercive force Hc for steels Cr70, 09Mn2Si, 15CrSiNiCu, 25CrSiNiCu decreased in the elastic region of deformation with an increase in the effective tensile

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stresses, which indicates the identity of the magnetic parameters recorded by the devices depending on the structural changes in the studied steels. During mechanical tests, the influence of the initial structure on the change in Hp values from the acting stresses σ was evaluated. Samples with an equilibrium and coarsegrained structure in the as-received condition + annealing at 900 °C showed a strong influence of this structure on the dependence of Hp on the acting stresses, in contrast to samples in the factory as-received condition, i.e., a finer-grained structure. In this case, the course of the Hp (σ) curves was qualitatively preserved. One of the typical dependences of the scattering magnetic field strength Hp on uniaxial tensile stresses σ for 08ps coarse-grained steel is shown in Fig. 3a. The figure shows that more equilibrium structures correspond to smaller changes in the intensity of the scattering magnetic field from cycle to cycle. In this case, with an increase in the acting stresses, a decrease in the Hp values occurs, with a decrease in the acting tensile stresses during unloading of the sample, the Hp values increase. But even in this case, after the first cycle, the initial magnetic background of the sample is erased. Similar dependences Hp (σ) are inherent in low-alloy steel 10CrSiNiCu. In the presence of a nonequilibrium fine-grained structure of steel, the amplitude of Hp values increases compared to the coarse-grained structure of the samples in the state of factory as-received condition and after high-temperature annealing. A typical Hp (σ) dependence for 10CrSiNiCu steel after thermocyclic treatment is shown in Fig. 2a. It can be seen from the figure that, for 10CrSiNiCu steel, an increase in the effective stresses leads to significant fluctuations in the values of Hp for all loading-unloading cycles, but, as in the previous cases, a significant hysteresis is observed after the first cycle and a characteristic dependence of Hp (σ) increases and decreases in the controlled section of stresses. Thus, the fine-grained structure of 10CrSiNiCu steel, which has higher strength characteristics, in particular, σt, in contrast to coarse-grained steel, also corresponds to a larger shift in the burst of increasing Hp values towards higher stresses. Carrying out preliminary cold plastic deformation of samples significantly affects the dependence Hp (σ) in 08ps and 10CrSiNiCu steels (Fig. 2b and 4a respectively) under elastic tensile deformation, which is significantly different during the first loading and unloading of samples. In a subsequent cycle, the magnetic hysteresis loop becomes much narrower. But in this case, too, there is a decrease in the Hp values during loading of the sample and their increase during unloading. The erasure of the magnetic background of the samples occurs after the first loading-unloading cycle. The dependence Hp (σ) for 10CrSiNiCu steel has a similar character. Since many elements of welded metal structures work in compression, it is important to evaluate the effect of stresses on the change in the magnetic parameter Hp during elastic deformation by compression. A typical curve of the dependence of Hp on the acting stresses σ during compression of samples of St3 steel in the as-received condition is shown in Fig. 5. In this case, as in tension, during the first loading-unloading cycle an open loop of magnetic hysteresis is formed. However, upon compression, an increase in the effective stresses leads to an increase in the values of Hp, and upon a decrease, their decrease, i.e., in contrast to tension. After the second loading-unloading cycle, the branches of the magnetic hysteresis loop come closer and the difference in the final and initial values of Hp is eliminated, which in turn indicates that the initial magnetic

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background of the metal is erased. At the third loading, the curve Hp (σ) is identical to the curve at the second loading. It must be emphasized that what is common for structural steels during their elastic deformation after removal of the magnetic background is that the increment of the Hp values is proportional to the change in the acting stresses, both during tension and compression. Since plastic deformation can occur in both weakened and unrefined sections of metal structures, it is of interest to assess the effect of acting stresses in unrefined (Fig. 2a) and in weakened (Fig. 2b) sections of samples after preliminary cold plastic deformation. In this case, the initial values of the magnetic parameter Hp were equal before testing. From Fig. 2b, it can be seen that a weakened cross section with higher stresses corresponds to more significant values of Hp, which indicates the presence of a relationship between the magnitude of the acting stresses and a change in the parameter Hp. Thus, the most dangerous zone of stress concentration in elements and welded joints of metal structures at the same values of Hp will be the one in which the Hp increment will be higher during loading (unloading). Therefore, during elastic deformation of the studied steels, regardless of their initial structure and chemical composition, the Hp increments are proportional to the change in the acting stresses, and the magnetic hysteresis loop formed after the first loadingunloading cycle is most often not closed. In the second and subsequent cycles, the branches of the magnetic hysteresis loop approach each other, and the difference between the final and initial values of Hp becomes insignificant, which increases the degree of reliability of the results of subsequent measurements. Grinding grain size in structural steels with increasing acting stresses increases the values of Hp. Thus, coarse-grained equilibrium structures obtained after annealing at 900 and 1050 °C correspond to insignificant changes in Hp under cyclic loading, while fine-grained structures obtained during thermal cycling are characterized by sharper changes in Hp from cycle to cycle. It should be emphasized that the violation of the proportionality Hp (σ) indicates the approach of the acting stresses to the values of the yield strength (see Fig. 3a). Thus, the presence of correlations Hp (σ) helps to identify the most dangerous zones of stress concentration in welded joints and elements of operated welded metal structures in assessing their technical condition. It should be noted that critical welded metal structures are operated at a voltage of less than 0.5σt. Considering the above, by the nature of the change in Hp (σ) during the stepwise cyclic loading of metal structural elements, the following problems can be solved: • determine the sign of stresses acting in stress concentration zones (in welded joints and structural elements) (tension or compression), followed by their comparison with the calculated values; • determine the degree of danger of the identified stress concentration zones, as well as indirectly the level of acting stresses. • Assessing the degree of danger of stress concentration zones, it is necessary to take into account the increment H p obtained by stepwise loading and unloading of the structure (structural elements), taking into account that the higher the increment, the greater the acting stresses and the greater the degree of danger of the identified

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stress concentration zones. In danger zones of stress concentration, the level of acting stresses can be determined by the nature and magnitude of the change in H p (σ): • violation of the proportionality of the change in the values of H p (σ) corresponds to the limit of proportionality for a given steel grade; • stresses below the proportionality limit (if there is no violation of the proportionality of the change in H p (σ), then the acting stresses are below the proportionality limit); • stresses above the proportionality limit when deviating from the proportional change in H p (σ). 3.2 Area of Plastic Deformation The tension of the samples in the plastic region of deformation, in contrast to the deformation of samples in the elastic region, showed the opposite picture: with increasing stresses σ, the intensity of the scattering magnetic field Hp increased (Fig. 6). This is characteristic both for coarse-grained samples (in the as-received condition, after annealing at 900 and 1050 °C), and for fine-grained (after thermal cycling) and deformed (after cold plastic deformation) studied steels. Figure 6 shows typical dependences of Hp on the acting stresses σ during uniaxial tension of samples with a coarse-grained structure obtained as a result of high-temperature annealing (as-received condition + annealing at 1050 °C). The figure shows that after the Hp values decrease to the minimum in the elastic region, they begin to rise in the region of plastic deformation. With complete unloading of the samples under study, magnetic hysteresis is observed, while the final values of Hp do not coincide with the initial values. The tension of samples with a finer-grained structure (as-received condition + annealing at 900 °C) somewhat changes the dependence Hp (σ) in both elastic and plastic regions. So, for the studied steels during loading, the minimum value of the Hp value shifts toward higher stresses (Fig. 7). It must be emphasized that when the higher load is removed in the initial stage, there is a greater delay in the Hp tension than for coarser-grained samples obtained after annealing at 1050 °C. Moreover, the final values of Hp do not coincide with the initial ones. The tensile deformation of the samples with an even finer-grained structure (asreceived condition) is marked by an even larger shift of the minimum Hp values towards higher effective stresses σ and a more pronounced magnetic hysteresis Hp during unloading of the samples in the plastic region (Fig. 8), which is especially clearly observed for low-alloyed steel 10CrSiNiCu (Fig. 8b). A typical dependence of the magnetic field strength on the stresses Hp (σ) for 10CrSiNiCu fine-grained steel in the as-received condition + thermal cycling is shown in Fig. 9. The presence of a fine-grained structure shifts the minimum values of Hp under tension to even higher values of the acting stresses, while the parameter Hp remains constant almost until complete unloading while maintaining the staged change in Hp (σ) beyond the elastic limit. In this case, a sharp shift in the minimum Hp values of 10CrSiNiCu steel towards higher stresses is largely due to the presence of a fine-grained structure obtained in the process of thermal cycling, compared with other structural states.

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Removing the external load (unloading the samples) practically does not change the magnitude of the magnetic parameter Hp until the acting stresses of the order of 150–200 MPa are reached. The complete removal of the external load does not lead to final values of the initial values of the scattering magnetic field strength Hp. The same dependence Hp (σ) is also observed for steels that underwent preliminary cold plastic deformation by a degree of deformation ε = 50% (Fig. 10). In this case, a displacement of the minimum Hp to the region of higher stresses is also observed; during unloading,

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constant Hp values are maintained. Consequently, with a decrease in the grain size for all the studied steels under uniaxial tension, a shift of the minimum Hp values to the region of higher acting stresses is observed.

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The presence of a fine-grained structure in the metal, as well as the structure after cold plastic deformation, leaves the Hp values during unloading almost constant. It should be noted that the change in the shape of the magnetic hysteresis loop substantially depends on the type of previous treatment. So, for samples annealed at 1050 °C, the decrease in Hp values begins immediately after the external load is removed, while in samples with a fine-grained structure or after cold plastic deformation, the Hp values remain at the initial level. The same dependence of the change in the magnetic hysteresis loop upon magnetization of a ferromagnet in strong magnetic fields is observed after annealing and after hardening [8], which indicates the identity of the processes of magnetization of ferromagnetic materials both in strong magnetic fields and in a weak magnetic field of the Earth, but in the presence of action stresses. Therefore, the established relationship between the parameter Hp and the acting stresses σ during tension of samples from low-carbon and low-alloy steels with different initial structures shows that upon elastic deformation by tension with an increase in σ above a certain value, the values of Hp decrease, while in the plastic region they increase, and the minimum values of Hp with decreasing grain size, shifts toward higher acting stresses. Нр, А/m

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Reducing stresses (unloading) leads to a delay in the change in the values of the magnetic parameter Hp, which is why a magnetic hysteresis loop is formed. With a decrease in the initial grain size of structural steel, there is an ever-increasing delay in the values of the parameter Hp for the very fine-grained structure, which is observed almost until the samples are completely unloaded. The same picture is observed when unloading laboratory samples that underwent preliminary cold plastic deformation, which indicates irreversible magnetization of the samples in a weak magnetic field of the Earth.

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To increase the reliability of the results of experimental studies of welded metal structures of building machines, it is of interest to assess the effect of multiple unloadingloading of metal structural elements in stress concentration zones operating in the plastic deformation region observed under real operating conditions of construction machines. The experimental studies of multiple loading-unloading of samples in the plastic deformation region showed a different nature of the dependence of the Hp (σ) curve (Fig. 11). Нр, А/m

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The course of the Hp curves for large and less significant degrees of deformation is somewhat different: for large degrees of deformation, the values of Hp remain almost unchanged until the samples are completely unloaded, and for zones with small degrees of deformation, significant changes in Hp are observed in the elastic region of deformation. The diverse nature of the change in the magnetic parameter Hp during unloading of the objects of study allows us to assess the degree of plastic deformation of the metal in the zones of stress concentration, which characterizes the danger of the identified zones.

4 Conclusion The conducted experimental studies during cyclic elastoplastic deformation of lowcarbon steels 08ps, St3 and low-alloy steel 10CrSiNiCu allowed us to establish the following:

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• passive fluxgate control of the surface of welded metal structures with a fluxgate transducer (after deformation, deformation-thermal, and thermal treatments) allows without preliminary surface preparation to reveal stress concentration zones by anomalous deviation of the magnetic parameter H p ; • when samples are stretched in the elastic region of deformation, an increase in stresses σ leads to a decrease in the magnetic parameter H p , and a decrease in stresses leads to an increase in these values; • by the nature of the change in the parameter H p during cyclic elastic deformation, one can judge the sign of stresses (tension, compression); • the first loading-unloading cycle in the elastic region of deformation erases the magnetic and mechanical background of the samples; the magnetic hysteresis loop in the initial and final values of H p does not close. The second and subsequent cyclic loading makes it possible to close the magnetic hysteresis loop and the convergence of its ascending and descending branches, which increases the degree of reliability of the subsequent measurement results; • loading of samples in the region of Hooke’s law corresponds to a proportional increment of the magnetic parameter H p and a change in the acting stresses. The lack of proportionality indicates the excess of the acting stresses of the proportionality limit of the metal, the increment of the H p values (modulo) slows down, and the greater the closer the acting stress to the yield strength of the metal; • higher stresses correspond to more significant changes in the H p parameter of the plastic deformation region, which makes it possible to assess the degree of danger of the identified stress concentration zones in the metal structures of construction machines; • when samples are stretched in the plastic region of deformation with an increase in acting stresses, an increase in H p values is observed; when external load is removed, H p decreases. In the stress concentration zone undergoing plastic deformation, it is possible to assess the degree of plastic deformation and the acting stresses: at small degrees of deformation, the change in H p under loading is insignificant, with a further increase in the acting stresses, the increase in H p increases, then the growth of H p slows down, a three-stage character of the change in the H p values with increasing acting stresses; • samples with a fine-grained structure and after cold plastic deformation during unloading in the plastic region show a stronger magnetic hysteresis than for steels with a coarse-grained structure: an increase in the width of the magnetic hysteresis loop indicates an increase in the degree of danger of the stress concentration zone, which must be taken into account during the technical diagnosis of welded elements of metal structures; • the presence of stress concentration zones in elements with a weakened cross-section (including general and local zones of corrosion damage) leads to a sharp change in H p values both during loading and unloading, which is likely due to higher acting stresses due to weakening of the controlled section due to corrosion wear. In this case, a higher (modulo) increment of the parameter H p corresponds to higher acting voltages, which determine the most dangerous of the studied zones.

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According to the research results, the relationship between the structure, magnetic and mechanical parameters is revealed, which allows a reliable assessment of the structural state of the metal and the acting stresses in welded joints and elements of welded metal structures using other methods of the passive flux-gate control method.

References 1. Potapov, Y., Polikutin, A., Panfilov, D., Okunev, M.: Comparative analysis of strength and crack resistance of normal sections of bent elements of T-sections, made of rubber concrete, cauton reinforcement and concrete. MATEC Web Conf. (2016). https://doi.org/10.1051/mat ecconf/20167304018 2. Lyushinskiy, A.V., Fedorova, E.S., Roshan, N.R., Chistov, E.M., Golov, R.S.: Diffusion welding of 12Cr18Ni10Ti steel to palladium alloy foil. Weld. Int. (2017). https://doi.org/10.1080/095 07116.2017.1318505 3. Pan, Z.H., Zhou, J.L., Jiang, X.: Investigating the effects of steel slag powder on the properties of self-compacting concrete with recycled aggregates. Constr. Build. Mater. 200, 570–577 (2019). https://doi.org/10.1016/j.conbuildmat.2018.12.150 4. Nedeljkovic, M., Ghiassi, B., Laan, S., Li, Z.M., Ye, G.: Effect of curing conditions on the pore solution and carbonation resistance of alkali-activated fly ash and slag pastes. Cem. Concr. Res. 116, 146–158 (2019). https://doi.org/10.1016/j.cemconres.2018.11.011 5. Scherbakov, A., Monastyreva, D., Smirnov, V.: Passive fluxgate control of structural transformations in structural steels during thermal cycling. E3S Web Conf. 135, 03022 (2019). https:// doi.org/10.1051/e3sconf/201913503022 6. Romano, A.A., Scandurra, G.: “Nuclear” and “nonnuclear” countries: divergences on investment decisions in renewable energy sources. Energy Sources Part B Econ. Plan. Policy 11(6), 518–525 (2016). https://doi.org/10.1080/15567249.2012.714843 7. Masini, A., Menichetti, E.: The impact of behavioural factors in the renewable energy investment decision making process: conceptual framework and empirical findings. Energy Policy 40, 28–38 (2012). https://doi.org/10.1016/j.enpol.2010.06.062 8. Sadorsky, P.: Renewable energy consumption and income in emerging economies. Energy Policy 37(10), 4021–4028 (2009). https://doi.org/10.1016/j.enpol.2009.05.003

Passive Probe-Coil Magnetic Field Test of Stress-Strain State for Welded Joints Alexander Scherbakov1

, Anna Babanina2(B)

, and Alexander Matusevich3

1 Saint Petersburg State University of Architecture and Civil Engineering,

Vtoraya Krasnoarmeiskaya Street, 4, Saint Petersburg 190005, Russia 2 Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya Street, 29,

Saint Petersburg 195251, Russia [email protected] 3 Moscow State University of Civil Engineering, Yaroslavskoye Shosse, 26, Moscow 129337, Russia

Abstract. The most common destruction places of welded metal structures are the welded seam and the heat-affected zone. These zones are stress concentrators, even if there are no defects. Equally important is the goal of preventing corrosion damage while improving the reliability and safety of welded metal structures. The most promising is the passive probe-coil magnetic field test method, which allows a complete examination of the alleged places of corrosion damage without surface preparation. The study is dedicated to identifying the most dangerous zones and places of the welded joint, and which of them must be controlled in the first place. The aim of the paper is to develop a methodology for assessing the stressstrain state of welded joints, taking into account the structural and mechanical heterogeneity of the metal. Correlations between the values of magnetic parameter H p and the acting stresses σ in the controlled zones under uniaxial elastic tension of the samples are determined. A metallographic analysis of welded joints of structural steels was carried out. It was revealed that the most dangerous area of the welded joint in metal structure is the fusion zone of the weld and the base metal with the overheating area. Keywords: Thermocyclic treatment · Probe-coil magnetic field test · Steel · Magnetic field · Dispersion · Ferromagnet · Magnetic parameter

1 Introduction Welded metal structures in construction machines are made of sheet rolled metal of mild low-alloy steel without heat treatment of metal after welding. The supplied structural steel metal has a ferrite-pearlite structure, and the rolling texture depending on the thickness of the sheets used. Welded joints of such steels in all cases have structural and mechanical heterogeneity. The modes and technology of welding steels are determined by both the type of structure and the conditions of its operation, as well as by the nature of the heat treatment before and after welding. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 312–323, 2021. https://doi.org/10.1007/978-3-030-57453-6_27

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The properties of metal structures can significantly deteriorate due to structural changes in the metal (grain growth, the formation of quenching structures, temper brittleness of the metal, etc.) [1, 2]. The influence of these factors on the strength and durability of structural elements is considered in many fundamental works [3, 4]. However, factors affecting the performance of welded joints, as well as residual stresses, defects, etc., can be commensurate with the stress concentration [5–7]. Therefore, a lot of experimental work has been devoted to studying the influence of these factors on the reliability and operation safety of welded metal structures [3, 4]. The stress concentration is understood as the local stress increase in areas of a sharp change in the cross section of the deformable body [8]. In welded metal structures stress concentrators can be structural and technological cuts, sharp transitions of welds to the base metal, various defects of the weld and heat affected zones, structural discontinuities, structural and mechanical heterogeneity of the metal of the welded joints. Therefore, when choosing welding materials and welding modes, specialists always strive to ensure that the properties of different zones and sections of the welded joint are not lower than the properties of the base metal. The strength of the welded joint should also be identified with the strength of the base metal of the weakest section. The most desirable is achieving the uniformity of mechanical properties throughout the welded joint, which is not always possible. In order to increase the operability of welded metal structures, it is necessary to take into account the effect of welding on the continuity of sections when developing its technology. Welding effect on heterogeneity, on the appearance of residual stresses, and thereby on the destruction possibility of metal structures during long-term operation should be considered as well. Usually, the change in the stress-strain state of the structure and properties of the metal during welding is closely related to the formation and crystallization conditions of the weld pool, as well as to the ongoing structural transformations. Currently, this issue has not been sufficiently studied, therefore, the calculation methods for determining the stress-strain state of the metal give the greater the error, the closer to the fusion line the zone or section in question is located. The following factors have a significant impact on the reliability and performance of welded joints and elements of welded metal structures: • • • • • • •

structural heterogeneity of welded joints; shape complexity of the welded metal structure; increased dispersion of metal properties; the presence of residual stresses in the elements and nodes of welded structures; diffusion processes taking place in the welding seam; the presence of temperature fragility ranges; relatively low operating temperatures of welded structures.

The most common destruction places of welded metal structures are the welding seam and the heat-affected zone. These zones are stress concentrators even in the absence of defects, since a sharp temperature drop appears during cooling of the welding zone, which leads to a change in the metal structure in the weld zone and the heat-affected zone, the appearance of various foreign inclusions, and the appearance of thermal stresses and

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cracks. Therefore, the following question arises: which zones and places of the welded joint are the most dangerous, and which of them must be controlled in the first place. Thus, assessing the danger degree of the main zones and sections of the welded joint in welded metal structures is of scientific and practical interest. This implies the purpose of the research, which is to develop a methodology for assessing the stress-strain state of welded joints, taking into account the structural and mechanical heterogeneity of the metal.

2 Materials and Methods For the experimental studies, flat welded samples of St3 steel with a thickness of 2, 4 and 8 mm were used, a significant part of samples was reinforced. The values of the stray magnetic field strength Hp were measured in the weld zone during stops while conducting mechanical tests. The values were also measured in the fusion zone with the overheat section and in the base metal zone. Since real welded metal structures work under conditions of elastic deformation, it is important to trace the Hp changing due to the acting stresses in the welded joint during low-cycle elastic deformation. Tests on welded samples without removing the thickening of the welding seam showed that a significant change in the magnetic parameter Hp took place in the fusion zone of the base metal with the weld, which could indicate the presence of higher acting stresses in this control zone. The presence of such a local zone of stress concentration, in our opinion, is caused by several factors. Those factors are, first of all, the presence of technological stress concentrators (small radii of the transition from the weld to the base metal), and the influence of structural and mechanical heterogeneity of the metal in the fusion zone with the overheating section obtained by crystallization, or their combined effect. In order to exclude the technological concentrator effect of welded joints during mechanical tests, samples with removed thickening were studied. In order to conduct microstructural analysis, a set of instruments was used, such as a profilometer (determines the degree of corrosion) and an ultrasonic thickness gauge (provides thickness measurement with an accuracy of 0.01 mm with unilateral access to the structure). The grain size was determined by the secant method (Glagolev method) [9] according to the results of 5–9 measurements at 650-fold magnification. Data metallographic studies were processed mathematically. Reliable identification of stress concentrating zones, i.e. places of corrosion wear, especially in enclosed box-shaped elements of welded structures, is a very difficult task, since traditional methods and means of non-destructive testing are aimed at finding a specific defect. When using ultrasonic thickness gauges to find corrosion damage, preliminary preparation of the control surface is required in order to reliably contact the piezoelectric transducer with the metal. The most promising is the passive probecoil magnetic field test, which allows a complete examination of the alleged places of corrosion damage without surface preparation. In order to assess the effect of corrosion damage on magnetic properties, studies were carried out on samples of mild steel St3, which have various corrosion damages.

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3 Results and Discussion Typical correlations between the Hp values and the acting stresses σ in the controlled zones under uniaxial elastic tension of the samples are shown in Fig. 1. It can be seen that, regardless of the control zone, significant changes in the Hp parameter are observed during the first loading-unloading cycle. With an increase in the operating stresses σ, a decrease in the magnetic field strength Hp occurs, and when the external load is removed, Hp increases. With a cyclic change in the operating stresses as a result of the application and removal of external loads, a magnetic hysteresis loop is formed. The first loadingunloading cycle is not able to close the magnetic hysteresis loop (the final values of Hp after unloading do not coincide with the initial values). The second and subsequent cycles of elastic deformation close the loop of magnetic hysteresis.

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0

Нр , A/m

40 0

25

50

75 100 125 150 175 200 225 250

? , MPa

b)

Fig. 1. The correlation between the stray magnetic field and internal stresses in a welded joint made of steel St3 with removed thickening: a - in the fusion zone of the base metal with a weld; b - in the zone of the base metal.

In the second cycle, the Hp values during loading and unloading of the samples practically approach each other, which is noticeable according to the arrangement of the branches of the magnetic hysteresis loop, while the final Hp values practically coincide with the initial ones. Therefore, regardless of the magnetic background of the metal, a change in the Hp values from σ develops identically starting from the second loading cycle. Thus, the obtained correlations Hp (σ) are in full agreement with the experimental data obtained in the field of elastic deformation of samples made of structural steels. After analyzing the function Hp (σ) (Fig. 1), it is determined that the smallest changes in Hp during the second and third loading are inherent in the base metal zone. In the fusion zone with the overheating section and in the weld zone, a more significant change in Hp is observed, which indicates the presence of higher acting stresses. Therefore, such

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a change in the magnetic parameter as a function of the acting stresses is probably related to the structure of the welded joint. It, in turn, is determined by the initial structure of the materials being welded, the nature of the physical effect on it, and the completion degree of the phase and structural transformations occurring during welding. The largest number of structural changes during welding is observed in metals undergoing polymorphic transformations. Regardless of the presence or absence of a polymorphic transformation in a metal in a welded joint, three following main areas can be distinguished: – 1) the temperatures of melting and the beginning of intensive grain growth; – 2) the temperatures of the beginning and end of the phase transformation during heating; – 3) tempering temperatures of the hardened base metal before welding and the recrystallization beginning of the treatment. The first is the zone where the metal was heated to a temperature above the solidus line and was in a liquid or solid-liquid state, the second zone is affected by heat, where the heating temperature was sufficient for complete or partial phase transitions and recrystallization. The third is the zone of mechanical and thermomechanical effect, where the metal heating temperature and its residence time at this temperature are insufficient for various processes of phase transformations and recrystallization to occur. In this area of the welded joint, changes caused by plastic and elastic deformation of the metal under the influence of welding stresses are preserved. In the region of the base metal, welding results in stresses that are not accompanied by plastic deformation of the metal. It should be emphasized that the largest changes in the chemical composition of the metal, its heterogeneity, as well as the formation of defects in the welded joint (pores, hot and cold cracks) are observed in the weld metal and the fusion zone. The conducted metallographic analysis of welded joints of structural steels showed that they contain various zones of structural changes during welding. These zones are common for mild low alloy steels. The microstructure of the weld and the fusion zone of the St3 steel specimen after mechanical tests in the elastic region of deformation are shown in Fig. 2. It can be seen that the weld metal has a characteristic dendritic structure, which dimensions, shape, degree of chemical uniformity and directionality are determined by the welding conditions and the properties of metal being welded. Since the metal in this zone is heated to a temperature above the liquidus line, this determines the intensive development of chemical reactions and metallurgical processes between the weld metal and atmospheric gases, as well as welding materials (electrode coatings, fluxes, and protective gases). It should be noted that a columnar zone with a predominant orientation is formed in all metals and alloys crystallizing under nonequilibrium conditions due to dendritic growth. In this case, the boundaries between the crystals, which form as the solid phase crystal lattices advance into the melt, are usually also elongated in the direction of growth (Fig. 3). When welding thin sheets butt to butt (Fig. 3, right), the spatial crystallization pattern is replaced by a flat one, that is, the curvilinear growth axes of crystallites are located in parallel planes. Moreover, the small volume of the weld pool and the large curvature

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Fig. 2. Microstructure of butt welded joint made of St3 steel in the welding seam zone and fusion zone, × 200.

Fig. 3. The growth paths of crystallites in the weld pool with crystallization schemes: on the left – spatial; on the right – flat.

of the surface being melted are the reason that the columnar crystallites in the weld are more misoriented than in ingots, which is shown in Fig. 3. A fusion zone adjoins the weld metal, which is clearly visible in Fig. 2, where the metal was heated to a solid-liquid state. The width of the fusion zone depends on the composition of the metal and the temperature regime of heating and cooling, i.e., on the position of the nonequilibrium temperatures of the liquidus and solidus. The most significant changes in the chemical composition and properties of the metal are observed in this particular zone, both due to the characteristics of crystallization and to diffusion processes.

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Thus, a change in the perlite structure in these zones in mild steels caused by high cooling rates leads to a decrease in ductility and an increase in the strength of the weld metal (Fig. 4). The overheating section, where the temperature of steel heating varies from Ac3 to the solidus line, is very important. This zone is characterized by the fact that complete structural and phase transformations common for steel can occur in the metal of this zone. The distinctive coarse-grained microstructure of the considered St3 steel for the overheating section is shown in Fig. 5.

Fig. 4. The correlation between cooling rate and mechanical properties of the welding seam metal.

Fig. 5. The microstructure of the butt weld made of St3 steel in the overheating zone, × 200.

The microstructure of the base metal is shown in Fig. 6. It can be observed that the structure of the base metal is finer-grained than in the weld and fusion zones with an overheating area (Fig. 2 and 5), and therefore has enhanced mechanical properties. The lower mechanical properties of the metal in the weld and fusion zones with the

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overheating area are probably due to the larger grain size in comparison with the base metal. It was determined [10] that the yield strength, strength, hardness, fatigue and impact strength increase with a decrease in grain size. Consequently, the zones and areas with the highest acting stresses are the weld and the fusion zones with the overheating area. But it is necessary to take into account reduced working acting stresses in the weld zone in real structures caused by the thickening of the seam (in our case, the thickening is removed), while such compensation is not provided for the fusion zone, which allows us to consider it the most dangerous. It should be emphasized that the fusion zone and the adjacent overheat area are also places of the possible formation of hot and cold cracks. For mild low-alloy steels, a significant grain growth is observed in the heating zone above 1000 °C, especially during electroslag and gas welding, which significantly reduces the mechanical properties of the steels.

Fig. 6. The butt weld microstructure made of St3 steel in the base metal zone.

It should be noted that the most dangerous area of the welded joint of welded metal structures is the weld’s fusion zone and the base metal with the overheating area, which is confirmed by experimental studies. This danger is aggravated by the occurrence of dangerous radii of transition from the weld metal to the base metal (0.4–0.8 mm on average) during welding. This contributes to metal damage and crack development in a small volume of the heat-affected zone. Dangerous zones and places, where the operating stresses are determined for the subsequent strength calculation, are identified by the maximum increments of the magnetic parameter Hp. The smallest changes in the magnetic field strength Hp were observed at the section of complete recrystallization of the metal having the finest-grained structure. During long-term operation, welded metal structures are exposed to aggressive corrosive environments, as a result of which corrosion damage is formed. The most typical defects in case of corrosion damage are general and local areas of reduced cross section of structural elements and the appearance of stress concentrators, which are especially significant in case of local corrosion damage. One of the important prerequisites for developing methods for controlling corrosion damage is considered to be the fact that any type of corrosion develops in the stress

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concentrating zones, which subsequently are destruction causes of protective coating of metals and the subsequent corrosion development in these areas. Given the above, the goal of preventing corrosion damage is an important part of improving the reliability and safety of welded metal structures. Corrosion damage can be both local and general. The most promising is the passive probe-coil magnetic field test method, which allows a complete examination of the alleged places of corrosion damage without surface preparation. The results of the effect of the acting internal stresses σ on the change in the magnetic parameter Hp in zone 1 with local corrosion damage and in adjacent zone 2 without damage and having a cross-sectional area much larger than in zone 1 are shown in Fig. 7. Measuring the Hp values under tension was carried out after each loading step until the effective stresses in zone 1 were close to the yield strength σy. Then, the stretching of the sample was stopped and the test sample was unloaded stepwise, as during loading, while measuring the magnetic parameter Hp in zones 1 and 2. It was shown that both in zone 1 and in zone 2, the Hp values decrease under step loading, and their values increase during step unloading (Fig. 7). At the same time, in zone 1, which has a smaller cross section, a sharper decrease and increase in Hp values occur during loading and unloading, respectively. Thus, for example, when the external load increases from 150 to 250 kg, the Hp value in zone 1 decreases from 202 to 155 A/m,

Нр , А/м Hp, A/m

240 230

1

1'

220 210 2'

200

2

3

190 180 170 160

3'

150 4'

140 130 120

4

110 100 90

Р 0,2

80 0

50

100

150

200

250

300

350

400

Px10, Р х10, Н N

Fig. 7. Correlation between the stray magnetic field H p on the applied load in zones 1 (with local corrosion damage) and 2 (without damage).

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their difference Hp (modulo) is 47 A/m (points 3 and 3’). At the same time in zone 2 Hp decreases from 220 to 213 A/m (points 1 and 1’), while the difference in the values of Hp (modulo) in this zone is 7 A/m. When the load decreases from 250 to 150 kg, the magnetic field strength in zone 1 increases from 115 to 147 A/m, their difference Hp is 32 A/m (points 4 and 4’). At the same tine in zone 2, Hp increases from 207 up to 210 A/m (points 2 and 2’), while the difference in Hp values in this zone is 3 A/m. A sharp change in the Hp values in zone 1 is due to higher acting stresses (caused by the weakening of the cross section) at the same loads. Consequently, higher increments Hp (modulo) of the Hp parameter in the zone of stress concentration 1 indicate higher effective stresses than in the concentration stress zone 2. Thus, the degree of danger of the identified zone is not determined by the initial value of Hp, which in our case is slightly higher (223 A/m) in less hazardous zone 2 than in more dangerous zone 1 (214 A/m). The degree of danger is determined by the magnitude of the increment (modulo) of Hp values during step loading or unloading of samples. It should be noted that an increase (decrease) in the effective stresses with an increase (decrease) in the external loads on the sample leads to a decrease (increase) in the Hp values in the controlled zones. Moreover, most importantly, a higher (modulo) Hp increment corresponds to higher effective stresses determining the most dangerous of the studied zones, which had initial Hp parameter values close in magnitude. It is also necessary to point out that the initial Hp value in the local corrosion damage zone was slightly lower than in the zone without damage. But even in this case, in the process of loading and unloading the sample, it is possible to determine the zone of corrosion damage by a higher increment of Hp values. In this regard, it becomes possible to evaluate the current stresses during the stepwise loading and unloading of the sample. When a sample is stretched in the elastic strain range, where Hooke’s law is fulfilled, equal Hp increment values correspond to equal increments of the external load P, that is, in this case, the acting stresses are less than the proportionality limit σpr. An increase in the acting stresses above the proportionality limit violates the linear dependence Hp (σ) Нр, А/m

Нр, А/m

–5

loading loading

– 10

–5

unloading unloading

– 15 – 20 – 25 – 30 – 35 – 40 – 45 – 50 – 55 – 60 – 65 – 70 – 75 – 80 – 85

0

25

50

75

10 0

1 25

a)

150

1 75

2 00

225

6 – 7 –8 – 9 – 10 – 11 – 12 – 13 – 14 – 15 – 16 – 17 – 18 – 19 – 20 – 21 – 22 – 23 – 24 –

25 0

27 5

P, kg

0

25

50

75

loading

unloading

loading

unloading

10 0

12 5

1 50

1 75

2 00

22 5

25 0

2 75

P, kg

b)

Fig. 8. The correlation between the stray magnetic field and the applied loads: a – in an area with general corrosion damage; b – in the area without damage.

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(in our case, at P > 300 kg), and therefore the acting stresses are above the proportionality limit. Consequently, it is possible to determine not only the zone of local corrosion damage, but also indirectly estimate the magnitude of the acting stresses under low-cycle loading of the samples. The presence of general corrosion is characterized by a difference in Hp values compared to areas that do not have such damage (Fig. 8).

4 Conclusion Based on the results of the studies, a methodology for assessing the stress-strain state of welded joints was developed, taking into account the structural and mechanical heterogeneity of the metal. Thanks to experimental studies, it was found that the most dangerous area of the welded joint in metal structure is the fusion zone of the weld and the base metal with the overheating area. In this regard, it is firstly necessary to control the fusion zone of the weld with the base metal and the overheating area when diagnosing welded joints of metal structures, and secondly, the weld. Identifying zones of corrosion damage and determining the effective stresses in them does not yet guarantee reliable and safe operation of welded metal structures. Not only the strength calculation of welded metal structures is required, but also taking into account the dynamics of the development of corrosion damage, and therefore determining the actual stress-strain state of welded metal structures working in aggressive corrosive environments is relevant.

References 1. Scherbakov, A., Monastyreva, D., Smirnov, V.: Passive fluxgate control of structural transformations in structural steels during thermal cycling. In: E3S Web of Conferences, vol. 135, p. 03022 (2019). https://doi.org/10.1051/e3sconf/201913503022 2. Eilerts, C.K., Sumner, E.F.: Integration of partial differential equations for multicomponent, two-phase transient radial flow. Soc. Petrol. Eng. J. 7(02), 125–135 (1967). https://doi.org/ 10.2118/1499-pa 3. Korovin, I.S., Tkachenko, M.G.: Intelligent oilfield model. Procedia Comput. Sci. 101, 300– 303 (2016). https://doi.org/10.1016/j.procs.2016.11.035 4. Kolbin, V.V.: Generalized mathematical programming as a decision model. Appl. Math. Sci. 8(70), 3469–3476 (2014). https://doi.org/10.12988/ams.2014.44231 5. Konikov, A.I.: Perspective directions in the field of construction management information systems. Ind. Civil Eng. 6, 64–69 (2019). https://doi.org/10.33622/0869-7019.2019.06.64-69. (In Russian) 6. Raychaudhuri, D.: Very small aperture terminal (VSAT) systems for digital satellite communication: an overview. IETE J. Res. 36(1), 24–34 (1990). https://doi.org/10.1080/03772063. 1990.11436 7. Wang, L., Liu, Y., Yin, Z.: A hybrid TDMA/CSMA-based wireless sensor and data transmission network for ors intra-microsatellite applications. Sensors 18(5), 1537 (2018). https://doi. org/10.3390/s18051537 8. Pinaev, S.A.: Application of polymer-cement corrosion protection for different strength concrete of reinforced concrete elements. In: IOP Conference Series, Materials Science and Engineering (2018). https://doi.org/10.1088/1757-899X/463/3/032012

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9. Potapov, Y., Polikutin, A., Panfilov, D., Okunev, M.: Comparative analysis of strength and crack resistance of normal sections of bent elements of T-sections, made of rubber concrete, cauton reinforcement and concrete. In: MATEC Web of Conferences (2016). https://doi.org/ 10.1051/matecconf/20167304018 10. Radulova, G.M., Slavova, T.G., Kralchevsky, P.A., Basheva, E.S., Marinova, K.G., Danov, K.D.: Encapsulation of oils and fragrances by core-in-shell structures from silica particles, polymers and surfactants: the brick-and-mortar concept. Colloids Surf. A-Physicochem. Eng. Aspects 559, 351–364 (2018). https://doi.org/10.1016/j.colsurfa.2018.09.079

Vertical Distribution of Fine Dust During Construction Operations Svetlana Manzhilevskaya1(B)

, Lubov Petrenko1

, and Valery Azarov2

1 Don State Technical University, Sq. Gagarina, 1, Rostov-on-Don 344010, Russia

[email protected] 2 Volgograd State Technical University, Lenin Avenue, 28, Volgograd 400005, Russia

Abstract. The study of the dynamics of particles is very important for a proper understanding of air cleaning and sampling the fine dust pollution where the most essential particles are particles with the sizes 2,5–10 µm. This article summarizes the results of the study of the fine dust distribution and concentration released during construction production. During many construction processes performing, a large amount of dust pollution is released. It includes concentrations of different particle sizes. Special attention should be paid to fine dust particles, since air pollution in the work area affects the health of the construction workers. The buildings under construction along Magnitogorskay Street 1 and 1A in Rostovon-don were selected as the objects under the study. The measurements of the fine dust distribution on the construction site were made using an electric dust aspirator PU-3E/12 which is designed for sampling in absorption devices to further determine the concentration of dust. The dispersion composition of the dust formed during the dustiest construction works was described by a logarithmic-normal distribution. The functional analysis of the amount of fine dust PM2,5 and PM10 released during the local construction allows us to determine the most dangerous construction works that affect the total environmental pollution in the working and sanitary protection areas. This helps to determine the risk of various diseases in workers, local construction personnel, and the population of the residential area. Keywords: Environment security · Dust pollution · Logarithmic-normal distribution · Dusty construction processes · Vertical direction distribution · Fine dust · Working area pollution

1 Introduction The study of the dynamics of particles is very important for a proper understanding of air cleaning and sampling the fine dust pollution where the most essential particles are particles with the sizes 2,5–10 µm. Aerodynamic properties of these particles vary considerably over this range. The often remarkable persistence of dust clouds in still air is due to the fact that, for a small particle, the air resistance opposing its motion, even at very low velocity, equals the gravitational force, so that after accelerating under © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 324–331, 2021. https://doi.org/10.1007/978-3-030-57453-6_28

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gravity for a short distance, the particle attains a constant falling or terminal velocity. For example, a particle with the diameter of 2 µm falls at 1.28 × 10−4 m/s [1]. The particle falling velocity depends on the diameter of the particles and increases up to the size of 60 µm. The large particles accelerate through appreciable distances under gravity and attain much higher terminal velocities. For example, a particle with the size of 1 mm falls at 6.8 m/s. The great differences in terminal velocities state the fact that the air cleaning method of the removing particles of 1 mm diameter by passing the dust-polluted air through a settling chamber is not actual for the fine particles. The fine dust particles are rapidly stopped by air resistance at high velocities, their motion being almost solely due to air movements. Fine dust in working space may be effectively controlled by effective methods of building site and working space organization. Basically, air-cleaning equipment provides means of impressing forces on dust particles so that they cross the flow lines of the gas passing through the cleaner and impact on a collector. The forces may be impressed in various ways; by a sudden change of air direction in the inertial separator and in some types of fibrous filter, by centrifugal action in the cyclone, or by application of a high voltage in the electrostatic precipitator. The fine dust pollution removing methods must take into account the indoor climate conditions, such as humidity, temperature, because the standard terms and conditions are bad in restriction of air pollution. Particles smaller than 10 µm, falling under gravitational forces, rapidly reach their terminal velocity due to drag forces, which also limit their range when they are projected horizontally. Large particles of dust or grit, however, accelerate rapidly under gravity, and when projected horizontally travel appreciable distances before the horizontal component of velocity is destroyed [2]. During many construction processes performing, a large amount of dust pollution is released. It includes concentrations of different particle sizes. Special attention should be paid to fine dust particles, since air pollution in the work area affects the health of the construction workers.

2 Materials and Methods The study of the fine dust distribution and concentration released during construction was conducted in two stages during the full-scale investigation. At the first stage, the concentration of dust in the atmospheric air was determined; at the second stage, dust collection was investigated. The buildings under construction along Magnitogorskay Street 1 and 1A in Rostovon-don were selected as the objects under the study. A 3-factor experiment was performed in full-scale conditions. The concentration of fine dust particles was the important parameter for optimization. The variable factors were considered, they were the distance from the working area of the construction process and the humidity of the atmospheric air. The following response functions were selected: concentrations of PM2.5 and PM10 , assigned to the highest non-recurrent MAC in the working zone, and the velocity of particle deposition.

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According to the fact that all technological processes of repair and construction works are performed in accordance with state standards, i.e. the conditions are met under which the temperature and relative humidity must be at least +10 and 40%, respectively, the full-scale measurements of the dust concentration and the content of PM2.5 and PM10 were carried out in the spring and summer period. The conditions of sampling are shown in Fig. 1. Working area

1

2

3

4

5

6

1

sampling point

Fig. 1. The location map of air sampling points from the source of dust formation in the air of the working area during repair and construction works performing.

The measurements of the fine dust distribution on the construction site were made using an electric dust aspirator PU-3E/12 which is designed for sampling in absorption devices to further determine the concentration of dust pollution in the working area. The duration of air sampling to determine single concentrations is 20 min at regular intervals during working hours on the construction site. On a tripod, at a height of 1.5 m from the ground, a filter holder was installed, which is connected with a flexible hose to the aspirator. The velocity of wind is 7–8 m/s. The system was checked for tightness of the connection, the filter was inserted into the filter holder, and the aspirator was programmed for a specific speed and time of sampling. During the selection process, records are made for each filter, indicating the filter number, location, sampling conditions, speed, and duration of the selection. The following Table 1 gives the devices and equipment used in the study of dust pollution in the working area. The determination of the single concentration of dust particles PM2.5 and PM10 , was performed by the aspirating the test air at a flow rate of 0.25 dm3 /min for 20 min. Air samples were taken at the level of the adult breathing zone 1.5 m from the groundsimultaneously at 5–6 points on the leeward side.

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Table 1. The devices and equipment used in the study of dust pollution in the working area. №

Devices and equipment

Application

1

Electric dust aspirator

The determination of the dust content of the working area air

2

Set of rubber tubes

The tubes joint with the device

3

High-accuracy weighing machine

The filters weighing

4

Filters

The determination of the dust content of the working area air

5

Microscope

The conduct of disperse composition of dust

3 Results and Discussion The analysis of the dispersed composition of dust was performed according to the scheme: 1. The distribution of particle mass by diameter was constructed. 2. The distribution of the geometric shape coefficient and correlation dependences were determined. 3. The covariance values of the cross section of the pass function were determined. 4. Experimental studies were conducted to determine statistical indicators of the dynamic form coefficient. 5. According to the results of the diameters of particles in dust pollution the density of particles in the air was analyzed. 6. The results were drawn graphically in the form of differential size distribution curves. As a result of the analysis in integral curves, each point of which showed the relative content of particles D as a percentage, the size of these points was greater or less than the given size Dp. The limits of permissible error of measurements during the analysis were 15% (the error in the selection of samples was 10%, the error of measurement tools was 5%). Analysis of the dispersed dust composition determined the main physical and chemical properties of the dust released during construction processes. The analysis of dust particle size distribution in the working area included the theoretical researches of log-normal distribution [3] and fundamental researches of some foreign and Russian scientists [4–14]. The logarithmic-normal distribution is considered to be the most reasonable for analytical description of the results of dispersed dust analysis. The function of the passage D(d) and the density ω(d) of the logarithmically normal distribution of the fine dust particle is:    log d 1 (log d − log d50 )2 exp − d log d , (1) D(d ) = √ 2log 2 σ 2π log σ −∞

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where d50 – the median of the distribution; log d – the standard deviation of the logarithms of diameters [15]. Let’s consider the results of a survey of the dustiness of the atmospheric air and the air of the working area during construction work. The composition of the investigated repair and construction works and the results of the degree of dustiness of the processes are presented in Table 2. In the process of examination the measurement of disperse composition and concentration of dust was conducted. The dust dispersion was determined by microscopic method. Table 2. The composition of the dusty construction processes and results of research. №

Repair and construction processes

PM10 , mcg/m3

PM2.5 , mcg/m3

1

Plastering

25

5

*

2

Insulating

3

Mobilization works

4

Shuttering

5

Arrangement of bored piles

6

Scaffold

7

Reinforcing

8

Carcassing

10

High dust content (HDC)

Medium dust content (MDC)

5

1

*

30

10

*

4

2

20

6

*

8

2

*

7

1.4

Slightly dust content (SDC)

*

*

2

*

9

Walling

17

3.4

*

10

Flooring

21

6.3

*

11

Collecting of waste

28

11.4

*

12

Painting

21

8.9

*

13

Finishing

23

9.2

*

14

Waterproofing

16

6

*

15

Lagging

19

6.5

*

16

Roofing

11

3.3

17

Concreting

23

7.2

* *

Analysis of the results of the dispersed composition of dust entering the air at different times showed that the experimental points were plotted on a probabilistic logarithmic, double logarithmic coordinate grid. The Figs. 2, 3 and 4 show the integral functions of the particles as results of the distribution by diameter.

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D(dp),% 99.99 99.97 99.9 99.7 99 98 97 95 90 80 70 60 50 40 30 20 10 5 2 1 0.5 0.25 0.1 0.04 0.01 1

2

10

20

100

Dp, μm

Fig. 2. The results of analysis for construction processes with high dust content (HDC). D(dp),% 99.99 99.97 99.9 99.7 99 98 97 95 90 80 70 60 50 40 30 20 10 5 2 1 0.5 0.25 0.1 0.04 0.01 1

2

10

20

100

Dp, μm

Fig. 3. The results of analysis for construction processes with medium dust content (MDC).

According to Fig. 2 the particle mass size is up to 24 µm and the proportion of fine dust particles PM2.5 and PM10–0 .35% and 6% respectively. According to Fig. 3 the particle mass size is up to 20 µm and the proportion of fine dust particles PM2.5 and PM10–0 .35% and 6% respectively.

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S. Manzhilevskaya et al. D(dp),% 99.99 99.97 99.9 99.7 99 98 97 95 90 80 70 60 50 40 30 20 10 5 2 1 0.5 0.25 0.1 0.04 0.01 1

2

10

20

100

Dp, μm

Fig. 4. The results of analysis for construction processes with slightly dust content (SDC).

According to Fig. 4 the particle mass size is up to 24 µm and the proportion of fine dust particles PM2.5 and PM10–0 .4% and 43% respectively. A graphical representation of the results of the dispersion analysis, presented as integral curves, showed the distribution of particle mass by diameter in Figs. 2, 3 and 4. The dispersion composition of the dust formed during the dustiest construction works was described by a logarithmic-normal distribution.

4 Conclusions 1. A dispersed analysis of dust particles released during repair and construction works was carried out. The integral functions of the distribution of the mass of dust particles by diameter were constructed. The analysis shows that this distribution is truncated logarithmically normal. This analysis of the dispersed composition of the dust selected during construction work allowed us to calculate theoretically the proportion of fine dust PM2.5 and PM10 . 2. The functional analysis of the amount of fine dust PM2.5 and PM10 released during the local construction allows us to determine the most dangerous construction works that affect the total environmental pollution in the working and sanitary protection areas. This helps to determine the risk of various diseases in workers, local construction personnel, and the population of the residential area next to the construction production. In addition, it is possible to implement measures that significantly reduce the dust pollution of the atmosphere at performing design works, especially in job and construction plans performing.

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References 1. Hu, M., Fan, B., Wang, H., Qu, B., Zhu, S.: Constructing the ecological sanitation: a review on technology and methods. J. Cleaner Prod. 125, 1–21 (2016). https://doi.org/10.1016/j.jcl epro.2016.03.012 2. Manzhilevskaya, S.E., Azarov, V.N., Petrenko, L.K.: The pollution prevention during the civil buildings construction. In: MATEC Web Conference, vol. 196, pp. 1–7 (2018). https://doi. org/10.1051/matecconf/201819604073 3. Ilyichev, V., Emelyanov, S., Kolchunov, V., Bakayeva, N., Kobeleva, S.: Estimation of indicators of ecological safety in civil engineering. Procedia Eng. 117, 126–131 (2015). https:// doi.org/10.1016/j.proeng.2015.08.133 4. Shvartsburg, L.E., Butrimova, E.V., Yagolnitser, O.V.: Energy efficiency and ecological safety of shaping technological processes. Procedia Eng. 206, 1009–1014 (2017). https://doi.org/ 10.1016/j.proeng.2017.10.586 5. Menzelintseva, N.V., Karapuzova, N.Y., Mikhailovskaya, Y.S., Redhwan, A.M.: Efficiency of standards compliance for PM(10) and PM(2.5). Int. Rev. Civil Eng. 7(6), 1–8 (2016). https:// doi.org/10.15866/irece.v7i6.9750 6. Bespalov, V.I., Gurova, O.S., Samarskaya, N.S.: Main principles of the atmospheric air ecological monitoring organization for urban environment mobile pollution sources. Procedia Eng. 150, 2019–2024 (2016). https://doi.org/10.1016/j.proeng.2016.07.286 7. Zuo, J., Rameezdeen, R., Hagger, M., Zhou, Z., Ding, Z.: Dust pollution control on construction sites: awareness and self-responsibility of managers. J. Cleaner Prod. 166, 312–320 (2017). https://doi.org/10.1016/j.jclepro.2017.08.027 8. Zhao, Y., Song, X., Wang, Y., Zhao, J., Zhu, K.: Seasonal patterns of PM10, PM2.5, and PM1.0 concentrations in a naturally ventilated residential underground garage. Build. Environ. 124, 294–314 (2017). https://doi.org/10.1016/j.buildenv.2017.08.014 9. Li, C.Z., Zhao, Y., Xu, X.: Investigation of dust exposure and control practices in the construction industry: implications for cleaner production. J. Cleaner Prod. 227, 810–824 (2019). https://doi.org/10.1016/j.jclepro.2019.04.174 10. Yi, W., Chi, H.-L., Wang, S.: Mathematical programming models for construction site layout problems. Autom. Constr. 85, 241–248 (2018). https://doi.org/10.1016/j.autcon.2017.10.031 11. Wu, Z., Zhang, X., Wu, M.: Mitigating construction dust pollution: state of the art and the way forward. J. Cleaner Prod. 112(2), 1658–1666 (2016). https://doi.org/10.1016/j.jclepro. 2015.01.015 12. Telichenko, V.I., Slesarev, M.U., Kuzovkina, T.V.: The analysis of methodology of the assessment and expected indicators of ecological safety of atmospheric AIR IN the Russian Federation for 2010–2020 years. Procedia Eng. 153, 736–740 (2016). https://doi.org/10.1016/j.pro eng.2016.08.235 13. Hong, J., Hong, T., Kang, H., Lee, M.: A framework for reducing dust emissions and energy consumption on construction sites. Energy Procedia 158, 5092–5096 (2019). https://doi.org/ 10.1016/j.egypro.2019.01.637 14. Ryzhova, L.V., Titova, T.S., Gendler, S.G.: Ensuring environmental safety during the construction and operation of tunnels in residential areas. Procedia Eng. 189, 404–410 (2017). https://doi.org/10.1016/j.proeng.2017.05.064 15. Tian, J., Gang, G.: Research on regional ecological security assessment. Energy Procedia 16, 1180–1186 (2012). https://doi.org/10.1016/j.egypro.2012.01.188

Monitoring Methods for Fine Dust Pollution During Construction Operations Svetlana Manzhilevskaya1(B)

, Lubov Petrenko1

, and Valery Azarov2

1 Don State Technical University, Sq. Gagarina, 1, Rostov-on-Don 344010, Russia

[email protected] 2 Volgograd State Technical University, Lenin Avenue, 28, Volgograd 400005, Russia

Abstract. The development of the measures in the environment and labor safety in construction production put more attention not only to the risks of harming the employee, but also to such subtle and little noticeable phenomena as dust and vibration. The technological processes on construction sites, in construction production, carry a hidden threat. Also, the dust released during construction works is a threat to residents of nearby construction sites that do not have the means to remove dust. The most dangerous dust pollution is fine dust pollution of dust particles with sizes of 0.5–10 µm (PM0,5 -PM10 ). This article discusses a method for suppressing dust emission on a construction site. The results of the effectiveness of the developed equipment, including fog formation, were obtained in the course of field measurements during many technological processes on the construction site in Rostov-on-Don. These results show that the amount of fine dust PM2.5 PM10 pollution reduces under the influence of water fog gun with a magnetic nozzle equipment using. The concentration of particles in the air reduces almost by 2 times, depending on the height of the equipment’s impact. The reducing of the sanitary protection zone size and the additional costs for removing fine dust in the working area allow the contractor to save money allocated for dust suppression on the construction site and direct them to environmental protection measures during infill construction. Keywords: Environment security · Dust pollution · Dusty construction processes · Dust control equipment · Fine dust · Working area pollution

1 Introduction The development of the measures in the environment and labor safety in construction production put more attention not only to the risks of harming the employee, but also to such subtle and little noticeable phenomena as dust and vibration. These factors are hardly noticeable, but over time, when their actions accumulate from day to day, the employee may have serious health problems, and this is the danger. In this article, we will consider a new method of dust suppression in the construction production and on the construction site. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 332–340, 2021. https://doi.org/10.1007/978-3-030-57453-6_29

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The technological processes on construction sites, in construction production, carry a hidden threat [1–3]. Also, the dust released during construction works is a threat to residents of nearby construction sites that do not have the means to remove dust. The most dangerous dust pollution is fine dust pollution of dust particles with sizes of 0.5– 10 µm (PM0,5 -PM10 ) [4]. In this regard, it became necessary to capture and suppress fine particles, which are the most dangerous. The dry filtration is not always desirable, especially when dusts are tacky or deliquescent. The resistance of bag filters then rises rapidly, and the bags are also difficult or impossible to clean. Electrostatic precipitators, too, are unsuitable when particles are corrosive, whilst dry dusts often constitute an explosion hazard. For these and other reasons, given in Table 1, wet type dust collectors can find wide application in the construction production. They operate on the principle that dust, once captured and surrounded by a large droplet, is more easily removed from the particles stream, either in the chamber in which contact has been made or in a subsequent cleaner (e.g. cyclone) [5]. Table 1. The comparison of dry and wet dust collection equipment. Dry collection

Wet collection

Advantages 1. Recovery of dust in the dry state (when it is 1. Cooling of dust particles at high of value) temperatures before passing to a secondary collector 2. Corrosion uncommon 3. A following collector (e.g. bag filter) does 2. May reduce the quantities of acid dust particles not have to deal with wet particles 3. Explosion unlikely 4. Often low capital cost. Although running costs may be higher than for dry collectors the overall costs may be less when intermittent usage only is required Disadvantages 1. Dust may be a hazard or nuisance during disposal 2. Possibility of explosion 3. Not generally suitable for sticky or corrosive materials

1. Cooling may cause trouble by reducing the particles velocity, the loss of buoyancy giving rise to particle fall-out close by 2. Disposal of large quantities of liquid 3. Often high power requirements 4. Possibility of corrosion engendered by use of liquid

Although large particles are effectively removed from a dust cloud by impingement on a surface of large area, smaller particles demand smaller targets and a high relative velocity between particle and target. The small target is achieved by atomization of the fluid, which is usually water. For an example of the dust-scavenging properties of droplets we can compare with the increase in clarity of the atmosphere after rain; the equipment involved is similar to this acting in industrial dust control devices. Inertia and

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interception effects are undoubtedly the important contributors to the efficiency of the usual type of wet cleaner [6]. The dust clouds released into space during construction work have a fairly wide field of influence, so it is necessary to suppress the source of dust. For this purpose, the best solution is fine water droplets. Falling under high pressure in the area of distribution or occurrence of dust, the droplets envelop the dust particles and settle with them. This very effective solution is implemented in wet type dust collectors, namely in dust suppression guns or, due to the resulting effect, they are also called fog guns.

2 Materials and Methods There are various types of designs for wet-type dust collectors, where the state of the liquid phase can be represented as a combination or separately of jets, drops, foam and film [7, 8]. The process of dust collection using this equipment occurs by collision of liquid droplets in the form of fog, such as in a fog gun, with dust particles. This action is the main one for the dust deposition process. When the particles of a large fraction connect with the water drops under the action of inertia, they are precipitated together with them on the surface. The particles of fine dust do not have sufficient kinetic energy and in the process of equipment exposure they bend around the drop and remain in the air in most cases. The number of precipitated particles under the influence of drops depends on the mass of the particles and their velocity relative to the drop. The diameter of the drop and the environmental conditions are also important factors [9]. The results of the research show that the using of standard wet-type dust collectors can precipitate the particles with a diameter of more than 1 µm [10–13]. The diameter of the precipitated particles can be decreases under conditions of fog formation. The particle precipitation on droplets is also facilitated by the interaction of electric charges of particles and drops. This is due to the fact that the particles of fine dust carry a charge that is obtained at the time of their formation and accumulate it during movement, depending on the speed. The degree of interaction between the electric charges of particles and droplets depends on the speed of their movement. An important factor is the water temperature. During the formation of a dust stream, the particles must be cooled by fog’s drops, since this causes a greater possibility of condensation of the fog on the dust particles under the action of polarizing diffusion. Under such conditions, the particles grow in size, and the possibility of their precipitation increases. The process of dust precipitation with the help of the fog gun must be implemented with following characteristics: 1. The water flow rate is 0.2–0.6 L per m3 ; 2. The hydraulic resistance is 400–600 Pa. In such conditions, the degree of precipitation for particles larger than 1 µm will be 95–99% and for particles smaller than 1 µm it will be 45–50%. The efficiency of the precipitation of the dust particles produced from construction processes with the wet type dust collectors using depends on the flow rate of the liquid, the diameter of water drops, the rate of formation of drops and the pressure in the installation.

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In this regard, during the operation of the equipment, the pressure of the liquid entering the spray nozzles should be monitored. In accordance with the task of developing measures and cost-effective means to the fine dust pollution reducing, a device was developed that represents a dust precipitation fog gun consisting of a frame, water supply pipes, a fan, a filter, a pneumatic pump and a nozzle system. This equipment is also additionally equipped with sources of a constant electromagnetic field that allow you to give the water flow physical properties that can attract fine dust particles. The equipment configuration is shown in Fig. 1.

Fig. 1. The equipment configuration: 1 – filter, air pump and nozzle system, 2 – water supply pipes and fan, 3 – frame.

There are sources of the electromagnetic field around the nozzles, inside the body of the equipment. They ensure the impact from all sides of the liquid flow. A round-shaped electromagnetic field source with a hole is mounted on the section that is close to the nozzles, so that the body of the field source covers this section of the tube along the entire diameter. Under the pressure created by the pump, water enters the tube system and passes through the area affected by the electromagnetic field. The water flow, exposed to a constant electromagnetic field, acquires new physical properties at the output, and becomes able to attract small particles. A water particle passing through an electromagnetic field as a liquid stream becomes charged. The equipment must be connected to the central water supply system. Water, passing through the filter with the help of a pump, is supplied under pressure through internal tubes to the nozzles (up to 0.1 mm in diameter). The air flow and water flow are mixed under the high pressure, as well as changes in the physical properties of water particles due to the influence of a constant electromagnetic field source. The result is a cloud consisting of fine water drops that settle in the impact sector and act effectively not only

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in relation to large dust particles, but also effectively attract the smallest dust particles that pose the greatest threat to human health. The practical results of using the equipment were taken at construction site. The samples of fine dust particles PM2.5 -PM10 were taken from during different construction processes during their production. The experiment took place at the construction sites of in Rostov-on-Don. The purpose of this experiment was to find out the humidity degree of atmospheric air when dust pollution was at the level of MPC (maximum permissible concentration) and the distance from the working area. The sampling was performed at different distances from working area during construction processes performing. The sampling points of the experiment were located at the distance 10 m, 20 m, 30 m, 40 m and 50 m from the working area of different types of dusty construction processes. The optimization parameters in the calculations and analysis were the concentration of fine dust particles PM10 and PM2.5 , according to MPC and the dust particles the fall rate. The fine dust measuring instrument was particle counter Handheld 3016. According to the results of experiment, the statistical data processing was performed.

3 Results and Discussion

loading, MPC

Figures 2, 3, 4 and 5 show the dependences of the dust concentration content at different atmospheric humidity. The experiment showed that the dust concentration decreases with increasing air humidity as a result of its humidification by the fog gun equipment. The fine dust particles, connecting with fog drops, increased in size and precipitated. 7 6 5 4 3 2 1 0

b a 35

40

50 60 70 80 percentage of moisture

90

95

Fig. 2. The changes in the concentration of fine dust in a time of the air humidification by spraying water from a fog gun equipment with a magnetic nozzle in a time of the production of plastering works a) warm time; b) winter time.

The dynamics and the efficiency of the collection of particles depends on the dimensionless parameter К

(1)

where dp2 – the particle diameter, DS is the collector diameter, and U is their relative velocity.

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loading, MPC

6 5 4 3

b

2

a

1 0

38

40

50 60 70 80 percentage of moisture

90

98

Fig. 3. The changes in the concentration of fine dust in a time of the air humidification by spraying water from a fog gun equipment with a magnetic nozzle in a time of the production of insulation works a) warm time; b) winter time.

loading, MPC

8 6 4

b

2

a

0

33

40

50

60

70

80

90

95

percentage of moisture Fig. 4. The changes in the concentration of fine dust in a time of the air humidification by spraying water from a fog gun equipment with a magnetic nozzle in a time of the production of drilling works a) warm time; b) winter time.

loading, MPC

6 5 4 3

b

2

a

1 0

33

40

50 60 70 80 percentage of moisture

90

95

Fig. 5. The changes in the concentration of fine dust in a time of the air humidification by spraying water from a fog gun equipment with a magnetic nozzle in a time of the production of shuttering works a) warm time; b) winter time.

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The equation for the impaction parameter is written as NI =

S , DS

(2)

where S is the range of a particle of diameter DS , projected at a velocity of U . NI differs from K by a factor of 2. Equation (2) may be rewritten as NI =

xf , DS g

(3)

where f is the terminal velocity of the dust particle which has a velocity of x relative to the collecting drops. We can invert this expression for impaction parameter creating so that a high collection efficiency is indicated by a small value of DxfS g . The equations show that, for a high collection efficiency, the collecting drops should be small and that the relative velocity between a drops and a dust particle should be high. These are conflicting fact in so far as a small water drop, even when projected at a high velocity, rapidly takes up the motion of the surrounding gas and dust particles. Very fine drops therefore provide a poor collecting system unless they contact the dust close to their point of generation, whilst very large drops are inefficient, in addition to requiring excessive volumes of water. The liquid rate feed is very important factor. If it is too highly concentrated, the coalescence drop occurs. On the other hand, too small a quantity of drops gives inadequate sweeping of the dust. Generally, the liquid rate should be about 0.1% by volume [14, 15]. Figure 6 shows the curves of relating collision efficiency with drop size, when drops are falling in still air. 100 10µm

Efficiency,%

5µm 3µm 10

Size of the dust particle 2µm

1 10

100 1000 Diameter of the water drops, µm

10000

Fig. 6. Dust collection efficiency of water drops during the pollution prevention at the construction site.

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4 Conclusions The amount of fine dust PM2.5 -PM10 pollution reduces under the influence of water fog gun with a magnetic nozzle equipment using. The results show, that the concentration of particles in the air reduces practically by 2 times, depending on the height of the equipment’s impact. This significantly changes the total amount of air pollution in the working areas and sanitary protection zones, as magnetized water further increases this effect of collecting and precipitating dust particles. The reducing of the sanitary protection zone size and the additional costs for removing fine dust in the working area allow the contractor to save money allocated for dust suppression on the construction site and direct them to environmental protection measures during the infill construction.

References 1. Li, T., Wen, X.: Local ecological footprint dynamics in the construction of the Three Gorges Dam. Resour. Conserv. Recycl. 132, 314–323 (2018). https://doi.org/10.1016/j.resconrec. 2017.05.006 2. Shvartsburg, L.E., Butrimova, E.V., Yagolnitser, O.V.: Energy efficiency and ecological safety of shaping technological processes. Procedia Eng. 206, 1009–1014 (2017). https://doi.org/ 10.1016/j.proeng.2017.10.586 3. Telichenko, V.I., Slesarev, M.U., Kuzovkina, T.V.: The analysis of methodology of the assessment and expected indicators of ecological safety of atmospheric air in the Russian federation for 2010-2020 years. Procedia Eng. 153, 736–740 (2016). https://doi.org/10.1016/j.proeng. 2016.08.235 4. Manzhilevskaya, S.E., Azarov, V.N., Petrenko, L.K.: The pollution prevention during the civil buildings construction. MATEC Web Conf. 196, 2035–2043 (2018). https://doi.org/10.1051/ matecconf/201819604073 5. Ilyichev, V., Emelyanov, S., Kolchunov, V., Bakayeva, N., Kobeleva, S.: Estimation of indicators of ecological safety in civil engineering. Procedia Eng. 117, 126–131 (2015). https:// doi.org/10.1016/j.proeng.2015.08.133 6. Hu, M., Fan, B., Wang, H., Qu, B., Zhu, S.: Constructing the ecological sanitation: a review on technology and methods. J. Clean. Prod. 125, 1–21 (2016). https://doi.org/10.1016/j.jcl epro.2016.03.012 7. Bespalov, V.I., Gurova, O.S., Samarskaya, N.S.: Main principles of the atmospheric air ecological monitoring organization for urban environment mobile pollution sources. Procedia Eng. 150, 2019–2024 (2016). https://doi.org/10.1016/j.proeng.2016.07.286 8. Ryzhova, L.V., Titova, T.S., Gendler, S.G.: Ensuring environmental safety during the construction and operation of tunnels in residential areas. Procedia Eng. 189, 404–410 (2017). https://doi.org/10.1016/j.proeng.2017.05.064 9. Zhao, Y., Song, X., Wang, Y., Zhao, J., Zhu, K.: Seasonal patterns of PM10, PM2.5, and PM1.0 concentrations in a naturally ventilated residential underground garage. Build. Environ. 124, 294–314 (2017). https://doi.org/10.1016/j.buildenv.2017.08.014 10. Tian, J., Gang, G.: Research on regional ecological security assessment. Energy Procedia 16, 1180–1186 (2012). https://doi.org/10.1016/j.egypro.2012.01.188 11. Yi, W., Chi, H.-L., Wang, S.: Mathematical programming models for construction site layout problems. Autom. Constr. 85, 241–248 (2018). https://doi.org/10.1016/j.autcon.2017.10.031 12. Zuo, L., Rameezdeen, R., Hagger, M., Zhou, Z., Ding, Z.: Dust pollution control on construction sites: Awareness and self-responsibility of manager. J. Clean. Prod. 166, 312–320 (2017). https://doi.org/10.1016/j.jclepro.2017.08.027

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13. Wu, Z., Zhang, X., Wu, M.: Mitigating construction dust pollution: state of the art and the way forward. J. Clean. Prod. 112(2), 1658–1666 (2016). https://doi.org/10.1016/j.jclepro. 2015.01.015 14. Li, C.Z., Zhao, Y., Xu, X.: Investigation of dust exposure and control practices in the construction industry: Implications for cleaner production. J. Clean. Prod. 227, 810–824 (2019). https://doi.org/10.1016/j.jclepro.2019.04.174 15. Hong, J., Hong, T., Kang, H., Lee, M.: A framework for reducing dust emissions and energy consumption on construction sites. Energy Procedia 158, 5092–5096 (2019). https://doi.org/ 10.1016/j.egypro.2019.01.637

Approximate Analytical Method for Solving the Heat Transfer Problem in a Flat Channel Anton Eremin

and Kristina Gubareva(B)

Samara State Technical University, Molodogvardeyskaya St., 244, 443100 Samara, Russia [email protected]

Abstract. The use of velocity and temperature distributions in moving fluids is of theoretical and practical significance. Designing efficient heat exchange equipment, development of modes of thermal and thermomechanical processing of products, determination of heat losses in pipeline systems is related to the need to determine the velocity and temperature fields in the flows of fluids and gases. This article presents the development results of an approximate analytical method for mathematical modeling of heat transfer process in laminar flows. The main provisions of the method are demonstrated using the example of solving the heat exchange problem in a plane parallel channel. The combined use of the thermal balance integral method and location method allowed obtaining a simple in form analytical solution of the problem under study. Note that accuracy of the solutions obtained depends on the number of approximations performed, i.e. on the number of N (points of a spatial variable), in which the initial differential equation is satisfied exactly. So, already at N = 2, a ratio error is not more than 10% in the range of changes along the longitudinal coordinate 0.1 ≤ η < ∞ and at N = 10 decreases to 1%. Analytical form of the resulting solutions allows one to analyze isotherm fields inside the channel, to calculate the dimensionless values of the average mass temperature, the Nusselt number, etc. Keywords: Heat transfer in fluids · Collocation method · Integral heat balance method · Approximate analytical solution · Isotherms · Nusselt criterion · Average mass temperature

1 Introduction For mathematical description of heat and mass transfer processes in moving media, the classical laws of continuum mechanics are used, such as the Navier – Stokes equations, equation of continuity, energy equation [1, 2]. When the dependencies of fluid physical properties on temperature and pressure are added, these equations form a closed system of equations that describes the convective transfer and fluid dynamics. The use of accurate analytical methods to solve these problems is possible only in several simple cases. For example, when solving some boundary value problems for flat bodies and bodies with central axial symmetry, the following methods are used: method of separation of variables (Fourier), Green function method [3, 4]; methods of integral transformations © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 341–351, 2021. https://doi.org/10.1007/978-3-030-57453-6_30

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with finite and infinite integration limits (Hankel, Laplace, Legendre transformations, etc.) [5, 6]. Such solutions are usually expressed by complex analytical dependencies, infinite series containing special functions, which significantly limits their practical use. Currently numerical methods for studying heat and mass transfer processes in flows of fluids and gases are widely used. Modern software products allow one to automatically build calculation grids, solve systems of linear equations and offer a wide range of tools for analyzing the results obtained. However, analytical solutions have some significant advantages compared to numerical solutions. In particular, the solutions obtained in the analytical form allow performing parametric analysis of the system under study, parametric identification, the setting on the programming of measuring devices, planning of control actions on production processes, etc. Consequently, approximate analytical methods for mathematical modeling of heat transfer processes in moving fluids have been developed: various modifications of the integral heat balance method [8–11]; the Ritz method [12–14], the Kantarovich method [15]; the Galerkin method [16–19], etc. This article presents the development results of an approximate analytical method for solving one – dimensional heat and mass transfer problems that allows one to get simple-form solutions with sufficient accuracy for engineering applications. The main provisions of the method are considered on the example of solving the heat transfer problem in a plane parallel channel.

2 Mathematical Statement of the Problem As a particular example of using this method, let’s consider the problem in a stable flow of incompressible fluid in a flat channel with width h (Fig. 1). To derive a differential equation describing this process we assume the following assumptions: 1) steady-state, stable flow; 2) incompressible fluid; 3) constant thermal physical properties; 4) laminar mode of fluid flow; 5) internal heat sources; and energy dissipation are not taken into account. Under these assumptions, the process of non – stationary heat transfer is described by Navier – Stokes equations combined with the energy and continuity equation is as follows

ρ

∂T + ω · ∇T = a∇ 2 T ; ∂τ

(1)

∂ω + ρω · ∇ω = −∇P + μ∇ 2 ω; ∂t

(2)

div ω = 0 .

(3)

In is known that the heat exchange process does not have any effect on the flow of the fluid with when physical properties of the fluid are constant. In this case, the fluid moves as if the flow were isothermal.

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y y

h

ωx(y)

x

0

x

Fig. 1. Scheme of heat transfer.

Introduce the coordinate system as shown in Fig. 1. In this case, Eq. (2) taking into account (3) is as follows d 2 ωx (y) p =− 2 dy μl

(4)

where x, y – longitudinal and transverse spatial coordinates, respectively; ωx – projection of the velocity vector on the axis Ox; p/l = const – pressure drop on the section of the channel length l; μ – dynamic viscosity. Given that the flow velocity on the channel surface is zero (ωx (h) = ωx (0) = 0), we obtain the known law of velocity distribution in a flat channel from the solution of the equation of motion.   ph2 y  y 2 . (5) − ωx (y) = 2μl h h Let us find an average flow rate determined by the formula h ωcp

Q = = hB

wx (y)Bdy

0

hB

=

ph2 12μl

(6)

where Q – volumetric flow rate; B – channel width. The energy Eq. (1) taking into account the found velocity profile ωx (y) and ωcp will be   y  y 2 ∂T (x, y) ∂ 2 T (x, y) − =a (7) 6ωcp h h ∂x ∂y2 Consider the problem of heat exchange in a flat channel for the case when the channel inlet temperature is T0 , one of its surfaces is heat insulated, and the other one maintains a constant temperature TCT .

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The boundary conditions for Eq. (7) are formulated as T (0, y) = T0 ; T (x, 0) = TCT ;

∂T (x, h) =0 ∂y

(8)

Problem (7), (8) can be presented in a dimensionless form. To do this, introduce the following dimensionless parameters: =

ωcp h T − TCT y x ;ξ= ;η= ; Pe = , T0 − TCT h Peh a

(9)

where  – dimensionless temperature; ξ, η – dimensionless transverse and longitudinal coordinates, respectively; Pe – Peclet number. Problem (8), (11) taking into account the introduced notations will be 6(ξ − ξ2 )

∂ 2 (η, ξ) ∂(η, ξ) = ; ∂η ∂ξ2

(10)

(0 , ξ) = 1;

(11)

(η, 0) = 0;

(12)

∂(η, 1) = 0. ∂ξ

(13)

3 Method Description The method presented in this article for obtaining approximate analytical solutions to non – stationary heat conduction problems consists is satisfying the differential equation of the Sturm – Liouville boundary value problem in a given number of points of a spatial variable. Obtaining a solution is limited only by the possibility of separating variables in the initial differential equation. The solution to problem (10)–(13), according to the method of separation of variables, can be found as follows (η, ξ) = ϕ(η)ψ(ξ),

(14)

Substituting (14) in (10) we find

where ν – some constant.

∂ ϕ(η) + νϕ(η) = 0; ∂η

(15)

∂ 2 ψ(ξ) + 6(ξ − ξ2 )νψ(ξ) = 0, ∂ ξ2

(16)

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The solution of Eq. (15) is known and has the form ϕ(η) = A exp(−νη),

(17)

where A – unknown coefficient. Substituting (14) in (12), (13) we get ∂ ψ(1) = 0; ∂ξ

(18)

ψ(0) = 0.

(19)

Solving the Sturm – Liouville boundary value problem (16), (18), (19) accepted as n+2 

ψ(ξ) =

bi ξi ,

(20)

i=0

where bi (i = 0, n + 2) – unknown coefficients. It should be noted that the relation (20) satisfies the boundary condition (18). The ratio (18) allows one to introduce another boundary condition ψ(1) = const = 1

(21)

Substituting (20) in (21), we find b0 = 0. We require that the relation (20) satisfies the boundary condition (18) and Eq. (19) at two points (with a step ξ = 1/2, starting from the point ξ = 0). Substituting (20), limited to four terms of the series, in the rations (18), (19) and Eq. (16), with respect to points of ξ = 0; 0, 5 relatively unknown coefficients bi (i = 0, 4) we obtain a system of four algebraic linear equations. From solution of this system we find: b1 = −

5ν + 32 ; 4ν − 32

b2 = 0; b3 =

(23)

31ν − 32 ; 4ν − 32

b4 = −

(22)

11ν − 16 . 2ν − 16

(24) (25)

Let us find the integral of the weighted residual of the Eq. (15) 1 0

n+2 n+2  ∂2  i 2 i bi ξ + 6(ξ − ξ )ν bi ξ d ξ =0 . ∂ ξ2 i=0

i=0

(26)

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Calculating the integrals in (26), taking into account the found values of coefficients bi (i = 0, 4) relative to the eigenvalues νk , we obtain an algebraic equation of the second degree 39ν2 − 898ν + 2240 = 0;

(27)

From the solution of Eq. (27) we get two eigenvalues ν1 = 20, 179373; ν2 = 2, 846267.

(28)

Substituting (17), (20) in (14), for each eigenvalue we will have partial solutions k (η, ξ) = Ak exp(−νk )

n+2 

bi (νk ) ξi .

(29)

i=0

To fulfill the initial conditions, its residual is formed, and also the residual orthogonality is required for each eigenfunction, i.e. 1  n−1 0

k=0

Ak

n+2 





bi (νk ) ξi − 1 ψj (νj , ξ)d ξ =0 · (j = 1, 2; n = 2 )

(30)

i=0

Calculating the integral in (30), for finding Ak (k = 0, 2) we obtain a system of two algebraic linear equations. Its solution is A1 = −0, 91778; A2 = 1, 209014.

(31)

After integration constants had been found, the solution to the boundary value problem (10)–(13) can be found from (29). Graphs of the temperature distribution along spatial variables, compared to the numerical solution, are shown in Fig. 2, 3. Their analysis shows that at η ≤ 0.3, the error of the solutions obtained exceeds 10%. Thus, the solution obtained can only be used for digital calculations of temperature fields in a fluid. To improve the accuracy of the solution, it is necessary to increase the number of terms of the series (20). To get additional equations in order to determine unknown coefficients bi to increase the number of coordinate ξ points, in which should perform Eq. (16). And, in particular, taking the number of such points equal to 10 (with step ξ = 1/10, starting from the point ξ = 0), with respect to unknown coefficients bi we get 12 equations (two more are added as a result of substitution in Eq. (19)). After determining the unknown bi (i = 0, 12) from the solution of this system of equations, the further course of the solution is repeated. Figure 2, 3 shows that already in the 10th approximation at η ≥ 0.1, the solution obtained practically coincides with the numerical one. Analysis of Fig. 2 allows one to make a conclusion about the convergence of the proposed method.

Approximate Analytical Method for Solving the Heat Transfer Problem

1

– FDM – 2nd approx. – 6th approx. – 10th approx.

0.8

0.1 0.3

Θ

0.6

347

0.4 0.2

η = 0.6

0

0.2

0

0.4

0.6

ξ

0.8

1.0

Fig. 2. Temperature distribution in coordinate.

0.8 0.3

0.64

Θ

0.48

0.32

0.5

0.16 0

ξ = 0.1 0.1

0.48

0.86

η

1.24

1.62

2.0

Fig. 3. Temperature change in time.

4 Determination of the Heat Transfer Coefficient The average mass temperature can be found by formula h T (x) =

ωx (y)T (x, y)dy

0

h 0

ωx (y)dy

1 = h ωcp

h ωx (y)T (x, y)dy. 0

(32)

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Taking into account dimensionless parameters, relation (32) can be reduced to a dimensionless form T (x) − TcT  (η) = =6 T0 − TcT

1  (η, ξ)(ξ − ξ2 )d ξ.

(33)

0

The Nusselt criterion is determined according to the ratio Nu =

1 ∂ (η, ξ) αh = , λ ∂ξ  (η)

(34)

where α – heat coefficient on the surface. The limit value of the Nusselt number (η → ∞) in the 10-th approximations was Nu∞ = 2, 42 (exact value Nu∞ = 2, 43). Graphs of changes in the Nusselt criterion and the average mass temperature along the length of the channel are shown in Fig. 4. 1.0

2.88

0.8

2.76

0.6

Θ

Nu

3

2.64

0.4

Θ Nu

2.52

0.2 Nu∞

2.4

0

0.6

1.2

η

1.8

2.4

3.0

0

Fig. 4. Distribution of the average mass temperature and the Nusselt criterion along the length of the flat channel.

5 Analysis of the Isotherms The temperature distribution functions obtained according to the described method have a simple analytical form, which makes it possible to study the heat transfer process in the fields of isotherms. The results of constructing isotherms using are shown in Fig. 5. The analysis shows that isotherms occur on the surface of the body (at a point ξ = 0) and spread along the longitudinal coordinate η. It should be noted that for each isotherm, two characteristic coordinates (where it appears and disappearscan) can be determined.

Approximate Analytical Method for Solving the Heat Transfer Problem

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1.0 0.5

0.8

0.4

0.3

0.2

0.6

ξ

Θ=0.1

0.4 0.2 0

0

0.1

0.2

η

0.3

0.4

0.5

Fig. 5. Distribution of isotherms in a flat channel (A = 1).

6 Discussion of the Results A method for obtaining high-precision approximate analytical solutions to heat transfer problems by directly satisfying the differential equation of a boundary value problem in a given number of points of a spatial variable has been developed on the basis of combined use of the method of separation of variables and orthogonal methods of weighted residuals. Obtaining a solution is only limited by the possibility of separation of variables in the initial differential equation. Moreover, practically no restrictions are imposed on the form of the differential equation of the boundary value problem obtained after separation of variables. In this connection, the method can be applied to problems that do not allow obtaining solutions using classical exact analytical methods. Acknowledgment. The reported study was funded by RFBR, project number 20-38-70021 and the Council on grants of the President of the Russian Federation as part of the research, project number MK-2614.2019.8.

References 1. Landau, L.D., Lifshitz, E.M.: Fluid Mechanics, 2nd edn. Pergamon Press, Headington Hill Hall (1987) 2. Kays, W.M., Crawford, M.E.: Convective Heat and Mass Transfer, 2nd edn. McGraw–Hill, New York (1993) 3. Sneddon, I.N.: Fourier Transforms. Dover Publications, New York (1995) 4. Cherati, D.Y., Ghasemi-Fare, O.: Analyzing transient heat and moisture transport surrounding a heat source in unsaturated porous media using the Green’s function. Geothermics 81, 224– 234 (2019). https://doi.org/10.1016/j.geothermics.2019.04.012 5. Tranter, C.J.: Integral Transforms in Mathematical Physics. Methuen, London (1966)

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6. Tsoi, P.V.: System Methods for Calculating Boundary-Value Problems of Heat and Mass Transfer, 3rd edn. Publishing House MPEI, Moscow (2005) 7. Christie, I., Griffiths, D.F., Mitchell, A.R., Zienkiewicz, O.C.: Finite element methods for second order differential equations with significant first derivatives. Int. J. Numer. Meth. Eng. 10(6), 1389–1396 (1976) 8. Layeni, O.P., Johnson, J.V.: Hybrids of the heat balance integral method. Appl. Math. Comput. 218(14), 7431–7444 (2012). https://doi.org/10.1016/j.amc.2012.01.001 9. Mitchell, S.L., Myers, T.G.: Improving the accuracy of heat balance integral methods applied to thermal problems with time dependent boundary conditions. Int. J. Heat Mass Transf. 53(17–18), 3540–3551 (2010). https://doi.org/10.1016/j.ijheatmasstransfer.2010.04.015 10. Mitchell, S.L., Myers, T.G.: Application of standard and refined heat balance integral methods to one-dimensional Stefan problems. SIAM Rev. 52(1), 57–86 (2010). https://doi.org/10.1137/ 080733036 11. Novozhilov, V.: Application of heat-balance integral method to conjugate thermal explosion. Therm. Sci. 13(2), 73–80 (2009). https://doi.org/10.2298/tsci0902073n 12. Dutta, S., Sil, A.N., Saha, J.K., Mukherjee, T.K.: Ritz variational method for the high-lying non-autoionizing doubly excited 1,3Fe states of two-electron atoms. Int. J. Quantum Chem. 118(14), e25577 (2017). https://doi.org/10.1002/qua.25577 13. Lotfi, A., Yousef, S.A.: A generalization of ritz-variational method for solving a class of fractional optimization problems. J. Optim. Theory Appl. 174(1), 238–255 (2017). https:// doi.org/10.1007/s10957-016-0912-3 14. Falk, R.S.: Ritz method based on a complementary variational principle. Revue francaise d automatique, informatique, recherché operationnelle 10(8), 39–48 (1976). https://doi.org/10. 1051/m2an/197610r200391 15. Kantorovich, L.V.: A method for the approximate solution of partial differential equations. Doklady AN SSSR 2(9), 532–534 (1934) 16. Rao, T.D., Chakraverty, S.: Modeling radon diffusion equation in soil pore matrix by using uncertainty based orthogonal polynomials in Galerkin’s method. Coupled Syst. Mech. 6(4), 487–499 (2017). https://doi.org/10.12989/csm.2017.6.4.487 17. Nourgaliev, R., Luo, H., Weston, B., Anderson, A., Schofield, S., Dunn, T., Delplanque, J.R.: Fully-implicit orthogonal reconstructed discontinuous Galerkin method for fluid dynamics with phase change. J. Comput. Phys. 305, 964–996 (2016). https://doi.org/10.1016/j.jcp.2015. 11.004 18. Belytschko, T., Lu, Y.Y., Gu, L.: Element free Galerkin methods. Int. J. Numer. Methods Eng. 37(2), 229–256 (1994). https://doi.org/10.1002/nme.1620370205 19. Arnold, D.N., Brezzi, F., Cockburn, B., Marini, D.: Unified analysis of discontinuous Galerkin methods for elliptic problems. SIAM J. Numer. Anal. 39(5), 1749–1779 (2001). https://doi. org/10.1137/s0036142901384162 20. Letelier, M.F., Hinojosa, C.B., Siginer, D.A.: Analytical solution of the Graetz problem for non–linear viscoelastic fluids in tubes of arbitrary cross–section. Int. J. Therm. Sci. 111, 369–378 (2017). https://doi.org/10.1016/j.ijthermalsci.2016.05.034 21. Bennett, T.D.: Correlations for the Graetz problem in convection. Int. J. Heat Mass Transf. 136, 832–841 (2019). https://doi.org/10.1016/j.ijheatmasstransfer.2019.03.006 22. Eremin, A.V.: Study of thermal exchange with liquid flowing in a cylindrical channel. In: International Science and Technology Conference, pp. 1–5 (2019). https://doi.org/10.1109/ EastConf.2019.8725422 23. Eremin, A.V., Kudinov, V.A., Stefanyuk, E.V.: Heat exchange in a cylindrical channel with stabilized laminar fluid flow. Fluid Dyn. 53, 29–39 (2018). https://doi.org/10.1134/s00154 62818040171

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24. Kudinov, V.A., Eremin, A.V., Kudinov, I.V.: The development and investigation of a strongly non–equilibrium model of heat transfer in fluid with allowance for the spatial and temporal non-locality and energy dissipation. Thermophys. Aeromech. 24(6), 901–907 (2017). https:// doi.org/10.1134/s0869864317060087 25. Fedorov, F.M.: Boundary Method for Solving Applied Problems of Mathematical Physics. Nauka, Novosibirsk (2000) 26. Eremin, A.V., Kudinov, I.V., Dovgyallo, A.I., Kudinov, V.A.: Heat exchange in a liquid with energy dissipation. J. Eng. Phys. Thermophys. 90(5), 1234–1242 (2017). https://doi.org/10. 1007/s10891-017-1679-6 27. Kudinov, I.V., Kudinov, V.A., Kotova, E.V., Eremin, A.V.: On one method of solving nonstationary boundary-value problems. J. Eng. Phys. Thermophys. 90(6), 1317–1327 (2017). https://doi.org/10.1007/s10891-017-1689-4 28. Petuhov, B.S.: Heat Transfer and Resistance During Laminar Fluid Flow in Pipes. Energy, Moscow (1967)

Stress-Strain State in Structure Angular Zone Taking into Account Differences Between Intensity Factors Lyudmila Frishter(B) National Research University Moscow State University of Civil Engineering, Yaroslavsko-Ye Shosse 26, Moscow 129337, Russian Federation [email protected]

Abstract. Angular zones where elements of structures and constructions are connected are characterized by complex stress-strain states and are an object of relevant theoretic-numerical and experimental research. Geometrically non-linear shape of boundaries – cut-outs, cuts, as well as the finite discontinuity of predefined forced deformations, emerging into the boundary of elements connection, results in appearance of the stress-strain state singularity. This paper considers local stress-strain state in the apex zone of an angular cut-out on the boundary of a plane domain. The novelty of research stems from the fact that the stress-strain state in neighborhood of the apex of an angular cut-out on the domain boundary is characterized by limit values of stresses and deformations, similar to stress intensity factors used with force criteria in fracture mechanics. A procedure is described for obtaining the expressions for displacements and stresses in neighborhood of the angular cut-out apex using stress intensity factors and deformation intensity factors for a variety of homogeneous boundary conditions. Differences are determined between expressions of stresses and displacements written using the stress and deformation intensity factors, which supports the practical relevance of the paper for carrying out experiments and determining critical values of stress and deformation intensity factors. Keywords: Stress-Strain state · Angular zone of domain boundary · Stress intensity factors · Deformation intensity factors

1 Introduction The stress-strain state of composite structures in the zones of element connection, under the action of forced deformations which are rupturing along the line (surface) of elements contact, is characterized by a power-type singularity. The stress-strain state in the zone of irregular point on the domain boundary under the action of forced deformations, particularly, temperature deformations, is determined by solution of the homogeneous boundary value elasticity problem. Solution of the homogeneous elasticity problem in neighborhood of irregular point on the singular line is reduced [1–4] to solution of © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 352–362, 2021. https://doi.org/10.1007/978-3-030-57453-6_31

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∂ the plane deformation problem: σx = 0, σy = 0, τxy = 0, τxz = τyz = 0, ∂z ≈ 0, σzz = ν(σxx + σyy ) and of the out-of-plane deformation problem: εxz = 0; εyz = 0; W = 0; nz = 0, εx = εy = εz = εxy = 0, U = V = 0. The power singularity of the stress-strain state is defined by geometry of the domain boundary shape – cut-out, cut. The order of stress-strain singularity depends on eigenvalues of the homogeneous elasticity problem [1, 5–9], which depend on the boundary shape, type of boundary conditions, mechanical characteristics of the domain material, and have a range of values [5, 8–10]. In fracture mechanics, for an ideal mathematical cut singular stresses are characterized by stress intensity factors [1, 5, 8–15]. The aim of the paper is to determine the stress-strain state in the angular cut-out zone of an arbitrary solution of the domain boundary using intensity factors of stresses and deformations as limit values of stresses and deformations, as well as to determine the ratios of stress and deformation intensity factors for various homogeneous boundary conditions.

2 Problem-Solving Method 2.1 Problem Statement. Plane Deformation Case A V-shaped domain with the symmetrical solution 2α in neighborhood of the apex of the angular cut-out domain boundary is considered [1, 5, 8, 9]. The displacement solution of the homogeneous boundary value elasticity problem for plane deformation in the polar coordinate system [1, 5, 8–11, 15]: is written as: ur = r λ f (θ ), uθ = r λ g(θ )

(1)

where f (θ ), g(θ ) are unknown functions of the angle θ to be determined, and λ is the unknown parameter. Substitution of ratios (1) into Lame’s equations results in expressions for displacements, deformations and stresses in neighborhood of irregular point on the domain boundary [1, 8, 9, 15, 16]: r−λ ur = Acos[(1 + λ)θ] + B sin[(1 + λ)θ ] + Ccos[(1 − λ)θ ] + D sin[(1 − λ)θ ], r−λ uθ = Bcos[(1 + λ)θ ] − A sin[(1 + λ)θ] + ν2 Dcos[(1 − λ)θ ] − ν2 C sin[(1 − λ)θ ], r1−λ εr = λ[Acos[(1 + λ)θ ] + B sin[(1 + λ)θ ] + Ccos[(1 − λ)θ] + D sin[(1 − λ)θ]], r1−λ εθ = [−λAcos[(1 + λ)θ ] − λB sin[(1 + λ)θ] + C(1 − ϑ2 (1 - λ))cos[(1 − λ)θ ] + D(1 − ϑ2 (1 - λ)) sin[(1 − λ)θ ], r1−λ εrθ = [−2λAsin[(1 + λ)θ] − 2λB cos[(1 + λ)θ ] + (1 − λ)(v2 − 1)Csin[(1 − λ)θ] + (1 − λ)(v2 − 1)D cos[(1 − λ)θ ]], μ−1 r1−λ σθ = − 2λAcos[(1 + λ)θ ] − 2λB sin[(1 + λ)θ ] − (1 + λ)(1 − ν2 ) Ccos[(1 − λ)θ ] − (1 + λ)(1 − ν2 )D sin[(1 − λ)θ] (2)

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μ−1 r1−λ τrθ = − 2λAsin[(1 + λ)θ] + 2λB cos[(1 + λ)θ ] − (1 − λ)(1 − ν2 ) C sin[(1 − λ)θ ] + (1 − λ)(1 − ν2 )D cos[(1 − λ)θ ], μ−1 r1−λ σr = 2λ{(A cos[(1 + λ)θ ] + B sin[(1 + λ)θ ] 3−λ 3−λ + k−λ C cos[(1 − λ)θ ] + k−λ Dsin[(1 − λ)θ ]}, E where μ = 2(1+ν) , E, ν are the shear modulus, elasticity modulus, and Poisson’s ratio −2λ of the domain material, correspondingly, ν2 = 3+λ−4ν 3−λ−4ν , 1 − ν2 = k−λ , k = 3 − 4ν, λ are the eigenvalues of the homogeneous boundary value problem, in the general case, complex numbers, and factors A, B, C, D are arbitrary constants to be determined. We consider limit values for stresses and deformations, which are called stress and deformation intensity factors, correspondingly, similar to stress intensity factors in fracture mechanics [1, 9, 12–15]. By satisfying particular homogeneous boundary conditions for the domain cut-out, expressions for unknown factors A, B, C, D are written using the stress and deformation intensity factors which have differences. The strain-stress states in the form of (2) are written using the limit values of stresses and deformations in neighborhood of irregular point on the domain boundary, and ratios for the stress and deformation intensity factors are obtained.

2.2 Domain Stresses Intensity Factors Let us denote the limit values of stresses in neighborhood of irregular point on the domain boundary as: KσI = lim μ−1 r 1−λ σθ, θ = 0

(3)

KσI I = lim μ−1 r 1−λ τr θ, θ = 0

(4)

r→0

r→0

By finding the ratios for A and C factors in expression (2) for stresses σθ , we pass on to the limit when θ = 0: lim μ−1 r 1−λ σθ, θ = 0 = −2Aλ − (1 + λ)(1 − ν2 )C.

r→0

By finding the ratios for factors B and D in expression (2) for shear stresses τr θ we pass on to the limit when θ = 0: lim μ−1 r 1−λ τrθ,

r→0

θ =0

= 2λB + (1 − λ)(1 − ν2 )D.

Taking into account notations (3), (4), the ratios for factors A and C, B and D will be written as −2Aλ − (1 + λ)(1 − ν2 )C = KIσ ,

(5)

2λB + (1 − λ)(1 − ν2 )D = KIσI .

(6)

Taking into account notations (3), (4), boundary conditions and ratios (5), (6), factors A and B, C and D are written using stress intensity factors.

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2.3 Domain Deformations Intensity Factors Let us denote the limit values of deformations in neighborhood of irregular point on the domain boundary as: KεI = lim r 1−λ εθ, θ = 0

(7)

KεI I = lim r 1−λ εrθ, θ = 0

(8)

r→0

r→0

By determining the ratios for factors A and C in expression (2) for deformations εθ we pass on to the limit when θ = 0: −

lim r 1−λ εθ, θ = 0 = λ− [−A +

r→0

(1 + λ− − 4ν) C] k −λ

(9)

By determining the ratios for factors B and D in expression (2) for angular deformations εr θ we pass on to the limit when θ = 0: +

lim r 1−λ εr θ,

r→0

θ =0

= 2λ+ B + (1 − λ+ )(1 − ν2 )D

(10)

Taking into account notations (7), (8), the ratios for factors A and C, B and D will be written as: λ− [−A +

(1 + λ− − 4ν) C] = KIε k −λ

2λB + (1 − λ)(1 − ν2 )D = KIεI

(11) (12)

Taking into account notations (9), (10), boundary conditions and ratios (11), (12), factors A and C, B and D are written using deformation intensity factors. Note that the ratios for factors B and D obtained using the limit values of shear stresses (6) and angular deformations (12), are the same. Let us consider two cases of homogeneous boundary conditions and obtain their ratios of stress and deformation intensity factors. 2.4 Homogeneous Boundary Conditions for Stresses Stress-Strain State Representation Using Stress Intensity Factors. Let us consider homogeneous boundary conditions in the form of: σθ = τrθ = 0 when θ = ±α.

(13)

After satisfying the boundary conditions (13), two homogeneous systems of linear equations are obtained relative to unknown constants A, B, C, D. The determinant of the first system of linear equations has the form of: λ sin 2α + sin 2λα = 0 or sin 2λα = −λ sin 2α.

(14)

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If λ is the root of characteristic Eq. (14), then in the stress-strain equation written as (2) summands with factors A and C (B = D = 0) are retained. Let us denote the root system of Eq. (14) as λ− i . The determinant of the second system of linear equations has the form of: −λ sin 2α + sin 2λα = 0 or sin 2λα = λ sin 2α.

(15)

If λ is the root of characteristic Eq. (15), then in the stress-strain equation written as (2) summands with factors B and D (A = C = 0) are retained. Let us denote the root system of Eq. (15) as λ+ i . Taking into account boundary conditions (12), we obtain the ratios for unknown factors:   (1 − λ− ) sin (1 − λ− )α    C, A =  (16) k − λ− sin (1 + λ− )α   (1 + λ+ ) sin (1 − λ+ )α     D. B = (17) k − λ+ sin (1 + λ+ )α Taking into account notations (3), (4) of the ratios (5), (6), factors A, C, B, D will be written as: A=

(1 − λ) sin[(1 − λ)α] Kσ , 2λ[(λ − 1) sin[(1 − λ)α] + (λ + 1) sin[(1 + λ)α]] I

(18a)

C=

(k − λ) sin[(1 + λ)α] Kσ , 2λ[(λ − 1) sin[(1 − λ)α] + (λ + 1) sin[(1 + λ)α]] J

(18b)

B=

(1 + λ) sin[(1 − λ)α] Kσ , 2λ[(λ + 1) sin[(1 − λ)α] − (1 − λ) sin[(1 + λ)α]] I I

(18c)

D=

(k − λ)sin[(1 + λ)α] Kσ . 2λ[(λ + 1) sin[(1 − λ)α] − (1 − λ) sin[(1 + λ)α]] I I

(18d)

Taking into account factors (18a, 18b, 18c, 18d) of displacement in neighborhood of the cut-out apex, the domain boundaries will be written as:         1 − λ− sin 1 − λ− α       KIε cos 1 + λ− θ     − − − − − λ − 1 sin 1 − λ α + λ + 1 sin 1 + λ α 2λ         v2 k − λ− sin 1 + λ− α       KIε cos 1 − λ− θ }     − − − − − − λ − 1 sin 1 − λ α + λ + 1 sin 1 + λ α 2λ         1 + λ+ sin 1 − λ+ α +          KIε I sin 1 + λ+ θ + r−λ { +  + + + + 2λ λ + 1 sin 1 − λ α − 1 − λ sin 1 + λ α       v2 (k − λ+ )sin 1 + λ+ α           KIε I sin 1 − λ+ θ } + + + + + + 2λ λ + 1 sin 1 − λ α − 1 − λ sin 1 + λ α

− ur = rλ {

(19a)

Stress-Strain State in Structure Angular Zone

357

        − 1 − λ− sin 1 − λ− α           KIε sin 1 + λ− θ − − − − − 2λ λ − 1 sin 1 − λ α + λ + 1 sin 1 + λ α         v2 k − λ− sin 1 + λ− α       KIε sin 1 − λ− θ }     − − − − − − λ − 1 sin 1 − λ α + λ + 1 sin 1 + λ α 2λ         1 + λ+ sin 1 − λ+ α +          KIε I cos 1 + λ+ θ + r−λ { +  + + + + 2λ λ + 1 sin 1 − λ α − 1 − λ sin 1 + λ α       v2 (k − λ+ )sin 1 + λ+ α         KIε I cos 1 − λ+ θ }   + 2λ+ λ+ + 1 sin 1 − λ+ α − 1 − λ+ sin 1 + λ+ α −

uθ = rλ {

(19b) Stress-Strain State Representation Using Deformation Intensity Factors. For the same homogeneous boundary conditions: σθ = τrθ = 0 if θ = ±α, taking into account notations (7), (8), of ratios (9), (10), the unknown factors of stress-strain state in the form of (2) will be written in the form of:

C=

(k − λ) sin[(1 + λ)α] Kε , λ((1 + λ − 4ν) sin[(1 + λ)α] − (1 − λ) sin[(1 − λ)α]) I

(20a)

A=

(1 − λ) sin[(1 − λ)α] Kε , λ((1 + λ − 4ν) sin[(1 + λ)α] − (1 − λ) sin[(1 − λ)α]) I

(20b)

B=

(1 + λ) sin[(1 − λ)α] Kε , 2λ[(λ + 1) sin[(1 − λ)α] − (1 − λ) sin[(1 + λ)α]] I I

(20c)

D=

(k − λ)sin[(1 + λ)α] Kε . 2λ[(λ + 1) sin[(1 − λ)α] − (1 − λ) sin[(1 + λ)α]] I I

(20d)

Taking into account intensity factors (20a, 20b, 20c, 20d) of displacement in neighborhood of the cut-out apex, the domain boundaries will be written as: 





 

   1 − λ− sin 1 − λ− α −        KIε cos 1 + λ− θ   ur = rλ { −  − − − − 1 + λ − 4ν sin 1 + λ α − 1 − λ sin 1 − λ α λ

        k − λ− sin 1 + λ− α         KIε cos 1 − λ− θ }   − − − − − 1 + λ − 4ν sin 1 + λ α − 1 − λ sin 1 − λ α λ         1 + λ+ sin 1 − λ+ α +        KIε I sin 1 + λ+ θ   + r−λ { +  + + + + λ + 1 sin 1 − λ α − 1 − λ sin 1 + λ α 2λ       (k − λ+ )sin 1 + λ+ α         KIε I sin 1 − λ+ θ }   + + + + + + λ + 1 sin 1 − λ α − 1 − λ sin 1 + λ α 2λ

+

(21a)

       1 − λ− sin 1 − λ− α      K ε cos 1 + λ− θ    { − uθ = r 2λ μ λ− − 1 sin 1 − λ− α + λ− + 1 sin[(1 + λ)α] I         v2 k − λ− sin 1 + λ− α      KIε cos 1 − λ− θ }      − 2λ− μ λ− − 1 sin 1 − λ− α + λ− + 1 sin 1 + λ− α −λ−



358

L. Frishter         1 + λ+ sin 1 − λ+ α         KIε I sin 1 + λ+ θ   2λ+ λ+ + 1 sin 1 − λ+ α − 1 − λ+ sin 1 + λ+ α       v2 (k − λ+ )sin 1 + λ+ α         KIε I sin 1 − λ+ θ }   + 2λ+ λ+ + 1 sin 1 − λ+ α − 1 − λ+ sin 1 + λ+ α + + r−λ {

(21b) Displacements in neighborhood of the point of the cut-out apex including the point itself, are unique in the solution domain of the linear elasticity problem. Let us equate the displacement values for this domain written using the stress and deformation intensity factors. We obtain the final ratios for stress and deformation intensity factors in the form of:       2[(1 + λ− ) sin 1 + λ− α + (λ− − 1) sin 1 − λ− α σ        KεI ,   (22a) KI =  1 + λ− − 4ν sin 1 + λ− α − 1 − λ− sin 1 − λ− α KIσI = KIεI .

(22b)

In case of the out-of-plane deformation problem, the solution in neighborhood of irregular point on the domain boundary is written by analogy as: w = r λ1 [D1 sin λ1 θ + D2 cos λ1 θ ], μ−1 r 1−λ1 τxz = λ1 {−D1 sin[(1 − λ1 )θ] + D2 cos[(1 − λ1 )θ]},

(23)

μ−1 r 1−λ1 τyz = λ1 {D1 cos[(1 − λ1 )θ] + D2 sin[(1 − λ1 )θ]}, where D1 , D2 are the arbitrary constants to be determined, where λ1 are the eigenvalues of the homogeneous boundary value problem. By denoting K1I I I =

lim μ−1 r 1−λ1 τyz, θ = 0 , K2I I I =

r→0

lim μ−1 r 1−λ1 τxz, θ = 0

r→0

(24)

factors D1 and D2 are written, whereas the stress and deformation intensity factors are numerically the same. 2.5 Homogeneous Boundary Conditions for Displacements Stress-Strain State Representation Using Stress Intensity Factors. Let us consider homogeneous boundary conditions in the form of:

uθ = uθ = 0 when θ = ±α

(25)

After satisfying the boundary conditions (13), two homogeneous systems of linear equations are obtained relative to unknown constants A, C, B, D. The determinant of the first system of linear equations has the form of: λ sin 2λα = − sin 2α, k = 3 − 4ν. k

(26)

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If λ is the root of characteristic Eq. (26), then in the stress-strain equation written as (2) summands with factors A and C (B = D = 0) are retained. Let us denote the root system of Eq. (26) as λ+ i . The determinant of the second system of linear equations has the form of: λ sin 2λα = − sin 2α, k = 3 − 4ν. k

(27)

If λ is the root of characteristic Eq. (27), then in the stress-strain equation written as (2) summands with factors B and D (A = C = 0) are retained. Let us denote the root system of Eq. (27) as λ− i . Taking into account boundary conditions (25), we obtain the ratios for unknown factors:       − + − sin 1 − λ α + cos 1 − λ α    D   C, B = − ν2 (28) A = −ν2 sin 1 + λ− α cos 1 + λ+ α Taking into account boundary conditions (25), we obtain the ratios for unknown factors:    sin 1 + λ− α     KIσ   C= (1 + λ− )(ν2 − 1) sin 1 + λ− α + 2ν2− λ sin 1 − λ− α , (29a)    − (3 − 4ν + λ) sin 1 − λ− α      Kσ ,  A= 2λ{(1 + λ− ) sin 1 + λ− α + (3 − 4ν + λ) sin 1 − λ− α } I    −(3 − 4ν − λ) cos 1 + λ+ α       Kσ , D= 2λ{(1 + λ) cos 1 + λ+ α + (3 − 4ν + λ) cos 1 − λ+ α I I    (3 − 4ν + λ) cos 1 − λ+ α      Kσ .  B= 2λ{(1 + λ) cos 1 + λ+ α + (3 − 4ν + λ) cos 1 − λ+ α I I

(29b) (29c) (29d)

Taking into account the obtained factors (29a, 29b, 29c, 29d), displacements and stress-strain states in the form of (2) in neighborhood of the cut-out apex of the domain boundary are written. Stress-Strain State Representation Using Deformation Intensity Factors. Let us consider the same homogeneous boundary conditions for displacements in the form of:

uθ = uθ = 0 when θ = ±α. Taking into account boundary conditions (25), and ratios for factors A and C, B and D in the form of (28), the values of unknown factors A, C, B, D are written using the deformation intensity factors in the form of:    − (3 − 4ν + λ) sin 1 − λ− α     K ε , (30a)   A= − λ {(3 − 4ν + λ) sin 1 − λ− α + (1 + λ− − 4ν) sin 1 + λ− α I

360

C=

L. Frishter

   (3 − 4ν − λ) sin 1 + λ− α     K ε , (30b)   λ− {(3 − 4ν + λ) sin 1 − λ− α + (1 + λ− − 4ν) sin 1 + λ− α I

Factors B and D have the form of (29c), (29d). Displacements in neighborhood of the point of the cut-out apex including the point itself, are unique in the solution domain of the linear elasticity problem. Let us equate the displacement values for this domain written using the stress and deformation intensity factors. We obtain the final ratios for stress and deformation intensity factors in the form of:       2{(1 + λ− ) sin 1 + λ− α + (3 − 4ν + λ) sin 1 − λ− α } σ      K ε , (31a)  KI = {(1 + λ− − 4ν) sin 1 + λ− α + (3 − 4ν + λ) sin 1 − λ− α I KIσI = KIεI .

(31b)

3 Results A procedure is described for obtaining the stress-strain state (2) in neighborhood of the angular cut-out apex on the domain boundary using stress intensity factors (3), (4) and deformation intensity factors (7), (8) for a variety of homogeneous boundary conditions (13), (25). Unknown factors of stress-strain state (2) are determined using stress intensity factors in the form of (18a, 18b, 18c, 18d) and deformation intensity factors (20a, 20b, 20c, 20d) for boundary conditions (13), as well as in the form of (29a, 29b, 29c, 29d), (30a, 30b) for boundary conditions (25). Ratios for stress and deformation intensity factors in the form of (22a, 22b), (31a, 31b) are obtained, demonstrating their differences.

4 Discussion The apex zone of the angular cut-out on the domain boundary includes several subdomains: domain of plastic deformations where finite deformations must be taken into account, domain of elastic deformations (linear and non-linear) for which the singular stress-strain state (2) with the power singularity is written in the framework of the elasticity problem using stress and deformation intensity factors. If the zone of non-linear material properties is small, a neighborhood exists in neighborhood of irregular point on the boundary where the stress-strain state expressions (2) are reasonably accurate to define the distribution of stresses and deformations, which is confirmed by experimental research of solutions in this area [14–19]. In this paper, the stress-strain state is determined for such a zone of irregular point on the domain boundary, taking into account the stress and deformation intensity factors.

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5 Conclusions The difference between stress and deformation factors for normal stresses and linear deformations under various homogeneous boundary conditions is determined by the influence of Poission’s ratio, the angle of solution of the domain boundary cut-out, hence by the minimum eigenvalue of the homogeneous boundary value problem. Intensity factors for shear stresses and angular deformations are the same. In the general case of the stress-strain state in neighborhood of the cut-out apex on the domain boundary, it is impossible to speak of proportionality of the stress and deformation intensity factors, which must be taken into account when their values are determined by experiment.

References 1. Parton, V., Perlin, P.: Methods of the Mathematical Theory of Elasticity. Nauka, Moscow (1981) 2. Parton, V., Morozov, E.: Elastic-Plastic Fracture Mechanics: Special Problems of the Fracture Mechanics. LENAND, Moscow (2017) 3. Chobanyan, K., Gevorkyan, S.: The behavior of the stress field near the angular point of the separation line in the problem of plane deformation of a composite elastic body. Bull. Acad. Sci. Armen. SSR. Mech. 24(5), 16–24 (1971) 4. Aksentyan, O.: Features of the stress-strain state of the plate in the neighborhood of the edge. Appl. Math. Mech. 31(1), 178–186 (1967) 5. Kondratyev, V.: Boundary value problems for elliptic equations in domains with conical or corner points. Trans. Moscow Math. Soc. 16, 209–292 (1967) 6. Ilyushin, A.: Continuum Mechanics. LENAND, Moscow (2014) 7. Morozov, E., Nikishkov, G.: Finite Elements Method in Fracture Mechanics. Knizhny dom Librokom, Moscow (2017) 8. Timoshenko, S., Gudyer, J.: Theory of Elasticity. Nauka, Moscow (1975) 9. Cherepanov, G.: Mechanics of Brittle Failure. Nauka, Moscow (1974) 10. Kuliev, V.: Singular Boundary Value Problems. Nauka, Moscow (2005) 11. Vardanyan, G., Frishter, L.: Analysis of the stress-strain state in the vicinity of an irregular point on a special line of the region using elements of dimension theory. Int. J. Comput. Civil struct. Eng. 3, 75–81 (2007) 12. Matviyenko, Yu.: Fracture Mechanics Models and Criteria. Fizmatlit, Moscow (2006) 13. Denisyuk, I.: Stress state close to a singular line of the interface boundary. Bull. Russ. Acad. Sci. Solid Mech. 5, 64–70 (1995) 14. Makhutov, N., Moskvichev, V., Morozov, E., Goldstein, R.: Unification of computation and experimental methods of testing for crack resistance: development of the fracture mechanics and new goals. Ind. Lab. Diagn. Mater. 83(10), 55–64 (2017). https://doi.org/10.26896/10286861-2017-83-10-55-64 15. Razumovsky, I.: Interference-Optical Methods of Deformable Solid Mechanics. MGTU named after N. Bauman, Moscow (2007) 16. Frishter, L.: Photoelasticity-based study of stress-strain state in the area of the plain domain boundary cut-out area vertex. In: Murgul, V., Popovic, Z. (eds.) EMMFT 2017, Advances in Intelligent Systems and Computing, vol 692, pp. 836–844. Springer, Heidelberg (2017). org/https://doi.org/10.1007/978-3-319-70987-1_89 17. Frishter, L.: Capabilities for stress-strain state generation within a stress concentration zone using the photoelasticity method. In: EMMFT 2018, pp. 692–700. Springer, Heidelberg (2018). https://doi.org/10.1007/978-3-030-19756-8_65

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18. Pestrenin, V., Pestrenina, I., Landik, L.: The stress state near a singular point of a flat composite design. TGU Bull. Math. Mech. 4, 80–87 (2013) 19. Tihomirov, V.: Determination of Stress Intensity Factors by the Method of Photoelasticity in Three-Dimensional Problems of Fracture Mechanics. Development of Methods of Experimental Mechanics. IMASH RAN, Moscow (2003)

Investigation of Thin Films by Using Superminiature Eddy Current Transducers Alexey Ishkov1(B)

and Vladimir Malikov2

1 Altay State Agricultural University, Krasnoarmeyskiy avenue, 98, 656049 Barnaul, Altai Region, Russia [email protected] 2 Altai State University, Lenina avenue, 61, 656049 Barnaul, Altai Region, Russia

Abstract. The article describes the results of studies of Ni, Al and Ag ultrathin films obtained by the resistive thermal evaporation method and having the characteristic dimensions of islands of 700–1000 nm with a film thickness of about 500 nm. The research objective was the development of subminiature eddy-current transducer designed for studying thin films. Timeliness is subject to the need to assess and predict safe operation life of products manufactured using thin films. A subminiature surface eddy-current transducer of the transformer type was developed. On the basis of eddy-current transducer, a software and hardware complex was developed to control the eddy-current transducer. The hardware and software complex provided the opportunity to make local studies of the electrical conductivity of non-ferromagnetic thin films by the method of eddy currents. In the course of the study, it was possible to develop an algorithm for finding changes in the average amplitude of the output signal, which allows concluding about the electrical conductivity of the thin film. The results of testing of Al, Ag and Ni films were presented, and the electrical conductivity values of the samples were obtained. The study of the kinetics oxidation of nanofilms oxygen in the air at 25 °C is presented. Keywords: Ultrathin films · Eddy-current transducer · Voltage on the measuring coil

1 Introduction Nowadays, nano-objects provide a promising research for the identification of new fundamental properties of the materials and their potential technological applications. Much effort is devoted to understand the physical and chemical properties of materials, which can serve as model catalyst systems. Consequently, fundamental studies have been carried out on a range of heterogeneous catalyst, for example, metal islands grown on thin films [1–3] or on single-crystals surfaces [4, 5]. Although the main microscopic steps governing nucleation and growth of the films are now understood, detailed characterization of these processes has proven difficult. Earlier, empirical and theoretical studies of Pd over single crystals MgO, investigated © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 363–370, 2021. https://doi.org/10.1007/978-3-030-57453-6_32

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defect nucleation [6] when nucleation centers occupy minority of sites. On the other hand, the results of nucleation kinetics over thin films controlled by random nucleation [7], each atomic site is potentially a nucleation center. In this study, we build upon many experimental and theoretical studies [8] have been carried out to understand these processes. The present object of studies in various fields of engineering is Ni, Al and Ag alloys. The alloy has high durability and heat transmission; it is easy to process, possesses metallike properties and due to the low density and high durability, it can significantly reduce the weight of the product with strength characteristics similar to heavier materials. An important difference between a thin metal film and a similar metal in the normal state is the difference in electrical conductivity. The differences in conductivity may be great. Therefore, it is extremely important to create a gage system that allows to measure the conductivity of a thin metal film. According to the results of studies [9–11], it is reasonable to measure electrical conductivity of thin films using the eddy current control method. This method provides the use of an eddy current transducer with energizing and measuring windings. Analysis of the electromagnetic field distribution appeared in a thin film by means of an eddy current transducer allows us to make a conclusion on electrical conductivity of the film. The use of the eddy current method provides the high performance of control, the possibility of checking without direct contact of the ECT and the surface of the thin film to be checked, the simplicity of the ECT design, and the weak dependence of the control results on environmental conditions [12]. The requirements for non-contact and highly precise online thickness measurement of metal films has increased rapidly with the development of industrial automation, semiconductor industry, and micromechanical technology. The main techniques for metal thickness measurement with eddy current sensors can be classified as single-frequency eddy current [12], pulsed eddy current (PEC) [13] and multi-frequency eddy current (MEC) [14] sensors based on the types of excitation signals. In the single-frequency eddy current technique, the sensor coil is excited with a sinusoidal signal and the eddy currents are distributed in a fixed depth. It is the most traditional method and is the basis of other methods. Due to the small thickness of thin films (100–2000 μm), only a few models on the market allow to study their conductivity. In particular, this is due to the range of operating frequencies required for the study of thin films, which is 1–10 MHz. The aim of the study is to develop a measuring system based on the eddy current transducer designed to measure the conductivity of thin metal films capable of localizing the electromagnetic field in small areas of the object of control.

2 Material Choices and Design Subminiature ECT [15–17] is designed for experimentally local studies of titanium-alloy plates and weld seams. The developed subminiature ECT represents a core wrapped with the following windings: energizing, measuring and compensation. ECT consists of a core wrapped with the energizing, measuring and compensation windings. Both the

Investigation of Thin Films by Using Superminiature Eddy Current Transducers

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windings and the core are impregnated with a compound. They are enclosed in a washer of corundum. This equates to increase the mechanical stability of the transducer. The developed device allows, in particular, to determine the electrical conductivity, which allows to draw some conclusions about the properties of the test films. Thin alloy films prepared by pulsed (200–250 ms), vacuum sputtering (10−3 –10−4 Pa) at temperatures of 3000–3200 °C alloy (0,005–0,008 g), of the evaporated from the belt surface heater (1 × 15 × 0,05 mm) on pre-the annealed substrate in a vacuum chamber installation ALA-TOO type IMASH 20–75. Conductivity(σ) nanofilms found contactless eddy currents developed by us with the use of sub-miniature eddy-current transducer. To test different conductive materials, a developed transducer is used, which is connected to a personal computer via a sound card that is used as a generator and as a signal transducer. The signal thus is sent directly to the energizing winding. The software is able to control the quantity of a signal applied to the energizing winding and also allows to read the voltage values from the measuring winding, which, taking into account the calibration, are converted into conductivity values. ECT winding coils consist of a copper wire with the thickness of 5 μm. The core is made of ferrite 2000NM3 with an initial magnetic permittivity value of 2000 and has a pyramidic shape. Characteristics of the developed transducer make it possible to achieve high localization of the control, namely, to localize the field within 2500 μm2 . The developed system provides a significant depth of penetration of the field into the prototype system up to values of ~5 mm (at frequencies of 500 Hz.) The software coded in C++ for Windows allows controlling the signal on the energizing winding and receiving the signal from the measuring winding. With the help of the software it is possible to effectively control the signal, which is applied directly to the energizing winding. Also with this software it is possible to receive a signal directly from the measuring winding. The impressed voltage can be controlled using a special mixer built into the Windows. With the help of this mixer, the frequency and amplitude parameters of the generator sinusoidal signal are set. In turn, the sound card makes it possible to extend the signal bandwidth, which is applied directly to the energizing winding. The generation unit controls the generator, which transmits a signal of frequency f1 to the energizing windings of eddy current transducers, these ETCs create an electromagnetic field that induces eddy currents in an electrically conductive test object. The voltage in the form of signals C1 and C2 carries information about the substrate and the thin film, respectively. Screen and the difference values of the averaged amplitudes of the two signals C1 and C2 are displayed. The surface of the films was examined using the NEOPHOD 32 optical microscope. In particular, it was used to study the structure of the surface of films after passing the synthesis wave.

3 Experimental Results The studies of the signals of the designed transducer were carried out on samples representing thin films of such metals as Al, Ag, and Ni obtained after condensation during gas phase in vacuum on glass substrates.

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Introduced voltage, mV

Figure 1 presents the initial data - measured values of the voltage on the measuring coil of the ECP, in the absence and in the presence of the Al film. Area 1 (N = 150–600) corresponds to the signal in the absence of the object of control - decompensation of the ECP. Area 2 (N = 620–1190) corresponds to the signal in the presence of the film.

180 170 160 150 140 130 120 110 100

3

1 2

0

300

600

900

1200 N

1500

1800

2100

Fig. 1. Voltage on the measuring winding of ECT (Al film). 1—signal without object of control, 2—signal in the presence of the film under study.

Introduced voltage, mV

Figure 2 shows a diagram of an algorithm that allows you to calculate the electrical conductivity of the film by the value of the difference between the signal with the film and the signal from the substrate. 155 145 ∆U1, Area 1

135

∆U2, Area 2

125 115 105 0

200

400

N

600

800

1000

Fig. 2. Determination of the averaged signal amplitude, U1—the signal span without the object of control, U2—in the presence of the Al film on the glass base surface.

In the area 1 the averaged amplitude of the signal is equal to 29 mV, in the area 2–3 - 10.8 mV. The difference between the EMF amplitude in the area 1 and the EMF amplitude in the area 2 () is 18.2 mV.  for Ag film is 8.31 mV and for Ni film - 21.35 mV.

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In Fig. 3 and Fig. 4 the results of measuring the response of Ag and Ni films, are presented respectively.

Intoduced voltage, mV

220 200 180 160 140 120 100 0

500

1000

1500

N

Introduced voltage, mV

Fig. 3. Voltage on the measuring winding of ECT (Ag film).

190 180 170 160 150 140 130 120 110 100 700

1200

1700

2200

N Fig. 4. Voltage on the measuring winding of ECT (Ni film).

For Al and Ag films, the voltage applied by the eddy currents is less than the decompensation, and consequently in Fig. 1 and Fig. 3 we see a decrease in the signal amplitude. For a Ni film, the contribution of eddy currents is much greater than the decompensation, as a result of which we see an increase in the signal amplitude in Fig. 4. Based on the data obtained and in accordance with the experimentally obtained equation f(x) = 0.0809x − 0.3696 based on samples of films with known electrical conductivity the conclusion on the electrical conductivity of the films under study may be drawn (Table 1).

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8.31

0.161

Al 18.2

0.5114

Ni 21.35

0.956

Investigation of the kinetics oxidation of nanofilms oxygen in the air at 25 °C was carried out contactless visually-optical method by photographing them at different time intervals and determining the decreasing area of the film. The picture (Fig. 5) shows the oxidation kinetics of alloy nanofilms Ni and Ag in a ratio of four to one, in the air.

c

a

d

1 0.8

b

α

0.6 0.4 0.2 0 0

500

1000 1500 2000 2500 3000 3500 4000

t, c Fig. 5. Kinetics of alloy nanofilms Ni and Ag. 1 – Ni film, 2 – Ag film.

The radial growth velocity of the island was by two orders of magnitude less than the propagation speed of the synthesis wave and was 0.028 mm/s, and the area growth velocity of the embryo (island) was by an order of magnitude less, which is 0.0034 mm2 /s. Table 2 gives the calculated front propagation velocity and the growth velocity of islands, determined by the size and time of moving objects on two consecutive frames.

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Table 2. Front propagation velocity and the growth velocity of islands. Thin film system

r1 - radius of the first island, μm

r2 - radius of the first island, μm

Reaction front velocity, mm/s

Radial growth velocity of islands, mm/s

Ni Ag

Area growth velocity of islands, mm2 /s

9.55

27.95

1.03

0.028

0.0034

8.26

24.41

0.91

0.015

0.0025

These results allow us to conclude that the synthesis wave is formed more by increasing the number of islands, rather than by increasing their area. The subsequent development of islands indicates a sequence of other reactions that lead to the final phase composition of the thin film. All changes can be traced by examining the surface microstructure as shown in Fig. 5.

4 Conclusions The results of the experiment showed the effectiveness of the proposed method of controlling the electrical conductivity of thin films with electrical conductivity from 0.1 to 1 MSm/m. To achieve this goal, we used developed ultra-miniature eddy current transducers with a filtering system for the received signal. The measuring system includes: software, hardware, ECT and allows to produce hardware and software processing of the received signal in order to improve the accuracy of measuring the electrical conductivity of thin films. In the course of the work, it was possible to create an algorithm to find the change in the average amplitude of the output signal, the magnitude of which makes it possible to infer the parameters of the film, in particular the electrical conductivity. The air oxidation of the nanofilms obtained in the Ni and Ag system at the temperature of 25 °C studied by means of a contactless optical method is a topochemical reaction, described by the Erofeev-Kolmogorov equation with the following constants: k (0.07– 12.5) · 10−2 and n 0.26–0.98 depending on the film specific electrical conductivity. The kinetic parameters of the synthesis wave and islands were determined, as well as their dimensions. It was established that the synthesis wave velocity is 1.03 mm/s, the radial growth of the island is 0.028 mm/s. Distribution of islands by size shows that the average diameter of the islands in the unit area is 1.164 μm.

References 1. Stiehler, C., Pan, Y., Schneider, W.D.: Electron quantization in arbitrarily shaped gold islands on MgO thin films. Phys. Rev. B Condens. Matter Mater. Phys. 88, 1–8 (2013). https://doi. org/10.1103/PhysRevB.88.115415 2. Shao, X., Cui, Y., Nilius, N.: Growth of two-dimensional lithium islands on CaO (001) thin films. J. Phys. Chem. 116, 17980–17984 (2012). https://doi.org/10.1021/jp306328c 3. Nolte, P., Stierle, A., Kasper, N., Jin-Phillipp, N.Y.: Reversible shape changes of Pd nanoparticles on MgO (100). Precursor J. Catal. 286, 1–5 (2012). https://doi.org/10.1021/ nl2023564

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4. Wang, H.F., Ariga, H., Dowler, R., Sterrer, M.: Surface science approach to catalyst preparation—Pd deposition onto thin Fe3 O4 111 films from PdCl2 . Nano Lett. 11, 4697–4700 (2011). https://doi.org/10.1016/j.jcat.2011.09.026 5. Nolte, P., Stierle, A., Kasper, N., Jin-Phillipp, N.Y.: Combinatorial high-energy x-ray microbeam study of the size-dependent oxidation of Pd nanoparticles on MgO (100). Phys. Rev. B Condens. Matter Mater. Phys. 77, 11–15 (2008). https://doi.org/10.1103/PhysRevB. 77.115444 6. Xu, L., Campbell, C.T., Jonsson, H.: Kinetic Monte Carlo simulations of Pd deposition and island growth on MgO (100). Surf. Sci. 601, 3133–3142 (2007). https://doi.org/10.1016/j. susc.2007.05.027 7. Renaud, G.: Real-time monitoring of growing nanoparticles by in situ small angle grazing incidence X-Ray scattering. In: AIP Conference Proceedings, vol. 748, pp. 63–71 (2005). https://doi.org/10.1063/1.1896476 8. Baara, F., Chemam, A.: Nucleation and growth kinetics of palladium nanoparticles on thin films of MgO (100). Rev. Sci. Technol. Synthèse 34, 10–17 (2017) 9. Yurkov, V., Ryzhii, V.: Effective interactions and the nature of Cooper instability of spin polarons in the 2D Kondo lattice. JETP Lett. 88(5), 370–377 (2008). https://doi.org/10.1134/ S0021364008180069 10. Abramchuk, S., Kramarenko, E., Stepanov, G., Nikitin, L.V., Filipcsei, G., Khokhlov, A.R., Zrínyi, M.: Novel highly elastic magnetic materials for dampers and seals: Part I. Preparation and characterization of the elastic materials. Polym. Adv. Technol. 18(11), 883–896 (2007). https://doi.org/10.1002/pat.924 11. Li, W., Ye, Y., Zhang, K.: A thickness measurement system for metal films based on eddycurrent method with phase detection. IEEE Trans. Indust. Electr. 64(5), 3940–3949 (2017). https://doi.org/10.1109/TIE.2017.2650861 12. Ribeiro, A.L., Ramos, H.G.: Liftoff insensitive thickness measurement of aluminum plates using harmonic eddy current excitation and a GMR sensor. Measurement 45(9), 2246–2258 (2012). https://doi.org/10.1016/j.measurement.2012.04.025 13. Kral, J., Smid, R., Ribeiro, A.L.: The lift-off effect in eddy currents on thickness modeling and measurement. IEEE Trans. Instrum. Meas. 62(7), 2043–2049 (2013). https://doi.org/10. 1109/TIM.2013.2247713 14. Yin, W.L., Xu, K.: A novel triple-coil electromagnetic sensor for thickness measurement immune to lift-off variations. IEEE Trans. Instrum. Meas. 65(1), 164–169 (2016). https://doi. org/10.1109/TIM.2015.2479106 15. Dmitriev, S., Malikov, V.: The steel defects investigation by the eddy current method. IOP Conf. Ser. Mater. Sci. Eng. 698, 1–7 (2019). https://doi.org/10.1088/1757-899x/698/6/066045 16. Dmitriev, S., Ishkov, A., Grigorev, A., Shevtsova, L., Malikov, V.: Scanning the layered composites using subminiature eddy-current transducers. In: Advances in Intelligent Systems and Computing, vol. 982, pp. 701–708 (2020). https://doi.org/10.1007/978-3-030-19756-8_66 17. Malikov, V.N., Dmitriev, S.F., Katasonov, A.O., Sagalakov, A.M., Ishkov, A.V.: Subminiature eddy-current transducers for studying steel to dielectric junctions. In: AIP Conference Proceedings, vol. 2053, pp. 1–9 (2018). https://doi.org/10.1063/1.5084495

Mathematical Modelling of Heat Transfer in Open Cell Foam of Different Porosities Olga Soloveva(B)

, Sergei Solovev , Rishat Khusainov , and Ruzil Yafizov

Kazan State Power Engineering University, Krasnoselskaja street, 51, Kazan 420066, Russia [email protected]

Abstract. In this work, a detailed numerical simulation of the gas flow through a heated open cell foam material was carried out. For this, several models of porous media were created with several values of porosity and the same surface area. Numerical studies were carried out in the ANSYS Fluent software package. The calculations used the SST turbulence model. The validity of the use of this model was confirmed based on direct numerical calculations performed on several models with a detailed breakdown of the grid (60 million cells). Good agreement was found between the results of calculations using DNS obtained on a detailed grid and a relatively rough network with the SST turbulence model. While maintaining the surface area of the material, porosity only affects the pressure drop while keeping the heat transfer characteristics. Creating heat exchangers from porous structures while maintaining thermal characteristics and low hydrodynamic resistance will be useful when using forced convection. Keywords: Heat transfer · Numerical simulation · Open cell foam

1 Introduction Open cell foam materials have great potential for enhancing heat transfer and are used in heat engineering systems, which leads to a constant study of gas and liquid flows in these materials to improve the overall characteristics of the system [1–3]. Recently, convective heat transfer in channels and pipes that are entirely or partially filled with a porous medium has been studied in detail. Research results are used to create and design new heat exchangers. In [4–7], heat transfer in a porous medium – liquid system was studied, boundary conditions on the wall, stationary and non-stationary processes, the effect of thermal scattering, and various forms of filling a tube with a porous material. Extensive studies were carried out using methods for filling various volumes with a porous medium to enhance heat transfer [8, 9]. Ceramic porous media exhibit excellent mechanical and heat transfer properties. These materials are widely used in various industries related to high-temperature and aggressive environments, ranging from highstrength insulation panels to catalysts and heat exchangers. The heat transfer process inside a porous medium is a combination of the thermal conductivity of the structure itself, the thermal conductivity of the liquid, convection and radiation inside the porous © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 371–382, 2021. https://doi.org/10.1007/978-3-030-57453-6_33

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material. Numerous empirical and analytical dependencies were established, as well as correlations obtained on the basis of numerical simulation for evaluating the thermal conductivity of porous media [10, 11]. Recent studies on this topic can be found in the works of Kumar and Topin [12–14]. Metallic porous media perform well during the removal and further transfer of heat to the cooling gas; therefore, porous structures can be used in the development of more efficient refrigeration machines. Open cell foam materials can be an alternative or a valuable modification of microchannel heat exchangers due to the possibility of flexible adjustment of surface area and porosity parameters. In recent years, more and more works have appeared using real structures of the porous medium obtained by micro-tomography [15, 16]. From numerical modelling, preliminary knowledge about the morphology, properties of solids and liquids should be well known as the initial data for the corresponding models. However, in practical engineering applications, most of this data is not available from standard tables or literature, since small changes in the composition, processing parameters and conditions of use of materials can lead to significant changes in their properties. As a result, the method of numerical modelling will mainly be limited to the study of such aspects as the effect of changes in the structure of the porous medium and verification of existing models. Currently, there is a demand for accurate models of convective heat transfer in porous media that would allow the creation of compact and efficient heat exchangers. The heat transfer properties of porous structures are more dependent on geometric parameters and operating conditions: porosity, surface area, fibre thickness, fabrication material, mass flow rate, pressure drop and temperature. Geometric models of porous structures are sets of intersecting spheres. Depending on the method of construction, the structure can be ordered and disordered. An ordered structure is created based on a cubic lattice, and a disordered structure is created by “filling” with spheres randomly located inside a given volume. Using models with a disordered structure is closer to reality since open cell foam media have a random arrangement of cells in space, there is no transparency in such a structure. The geometry of the random porous structure used in this work was created by the discrete element method (DEM).

2 Problem Formulation The gas flow through the heated open cell foam material is considered for three models with variable porosity ε = 0.8, ε = 0.85, ε = 0.9 and fixed surface area F = 0.003 m2 . It is necessary to determine the effect of the porosity of the medium on the hydrodynamics and the intensity of heat transfer. The computational domain is a cubic structure, inside of which there is an equilateral porous insert with a linear size of 20 mm with attached nozzles 10 mm and 30 mm long, respectively. Such dimensions are due to the need to ensure the remoteness of the input and output boundaries for the desired convergence of the numerical calculation. An example of the computational domain is presented in Fig. 1.

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Fig. 1. An example of a calculation model for a structure with porosity ε = 0.8.

The number of mesh cells is in the range of 17 to 20 million cells. The value of the discrepancy in the calculations was 10−6 . The following parameters were set at the boundaries of the region: temperature on the surface of the porous structure Twall = 400 K and air temperature at the inlet and outlet Tin = Tout = 300 K. At the outlet, atmospheric pressure was set; the values of the flow velocity at the inlet to the computational domain are presented in Table 1 and correspond to the range of Reynolds numbers from 100 to 1000. For each porosity with equal Reynolds numbers, the velocities were obtained, which are also presented in Table 1. v=

Rep εμ , ρdp

(1)

where dp - is the average diameter of the partition between the filter cells, ε - the porosity of the medium, υ - is the average gas flow rate, ρ - the gas density, μ - the dynamic viscosity coefficient. Physical properties of air ρ = 1.225 kg/m3 , μ = 1.7894 · 10−5 Pa s. Table 1. The values of the flow velocity at the inlet to the computational domain. Re

v, m/s v, m/s v, m/s (ε = 0.8) (ε = 0.85) (ε = 0.9)

100

1.298

1.633

2.189

200

2.594

3.264

4.378

300

3.892

4.897

6.568

400

5.189

6.53

500

6.48

8.16

10.94

600

7.784

9.794

13.136

700

9.082

11.427

8.757

15.325 (continued)

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v, m/s v, m/s v, m/s (ε = 0.8) (ε = 0.85) (ε = 0.9)

800 10.379

13.059

17.515

900 11.676

14.691

19.704

16.32

21.89

1000 12.97

It is generally accepted that the laminar flow regime in porous structures is observed only under the condition Re < 1, in cases where 1 < Re < 5 the features of the geometry determine the flow regime. And in case of Re > 5, a transitional flow regime appears with a further transition to a turbulent regime. In our calculations, the Reynolds number varied in the range from 20 to 1000, which corresponds to the turbulent flow regime. The SST model of turbulence was used in the calculations; the legitimacy of using this model was checked based on direct numerical calculation performed on several models with detailed grid breakdown (60 million cells). Good agreement was found between the results of calculations using DNS obtained on a detailed mesh and a relatively coarse mesh with an SST turbulence model.

3 Models and Methods In the approximation of the stationary flow of an incompressible gas, the equation of conservation of mass in the control volume takes the form: ∂ ρvi = 0, ∂xi where xi and xj - velocity and coordinates in the i direction. Momentum conservation equation:    ∂  ∂vi ∂P ∂ μ − ρvi vj = , ∂xj ∂xj ∂xj ∂xi P - static pressure, vi , xj - velocity and coordinate in the j direction. Energy equation:    ∂T ∂  ∂ λ , ρvi cp T = ∂xi ∂xi ∂xi

(2)

(3)

(4)

where cp - is the heat capacity of gas, λ - is the coefficient of thermal conductivity of air, T - is the temperature of the gas.

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Fig. 2. An example of streamlines in the model with porosity ε = 0.9 for Re = 500.

4 Results Numerical modelling is carried out in the ANSYS Fluent software package (v. 19.0) based on the solution of the system of Eqs. (2–4) using the control volume method. An example of a picture of gas flow lines in the computational domain for Re = 100 presented in Fig. 2. In Fig. 3 shows the curves of the pressure drop versus velocity for the porosity of the medium ε = 0.8, ε = 0.85 and ε = 0.9. The graph shows that while maintaining the surface area, the pressure drop of the structure with higher porosity is less. The authors of [17] proposed an expression for the pressure drop in an open cell foam material obtained based on experimental studies. (5) τ = 1 + 1.2175

1 − 0.971(1 − ε)0.5 (1 − ε)

0.5

·

(1 − ε) , ε

(6)

where p - the pressure drop; L - the thickness of the porous medium; τ - tortuosity of open cell foam material; ε - porosity; dh - hydraulic diameter; μ - coefficient of dynamic viscosity of the gas; v - velocity; ρ - density. The nature of the curves of change in pressure drop depending on the flow rate calculated from experimental expressions (5–6) repeats the character of the curves of numerical calculation. Aforementioned indicates the admissibility of using this model for hydrodynamic and thermal calculations. The discrepancy between the calculated and experimental graphs becomes more extensive with increasing porosity of the medium

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Fig. 3. The graph of pressure drop versus velocity.

since formulas (5–6) are not universal and were written for the structure of a specific geometry. Figure 4 shows a graph of the change in heat flux versus velocity. The heat flux is constant for different values of the porosity of the medium in the case of convective heat transfer since the surface area is the determining parameter.

Fig. 4. Change in heat flux versus flow rate.

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Fig. 5. Change in air temperature at the exit from the calculation area.

Figure 5 shows the change in average air temperature at the output boundary of the computational domain. Temperature curves for the porosity of 0.8 and 0.85 deviate insignificantly in the range of gas velocities from 1 to 11 m/s. With increasing flow velocity, a higher value of the porosity of the medium provides a lower of the air temperature at the outlet boundary. For porosity of 0.9, the temperature curve is much higher, starting from a velocity of 4 m/s, ending with 11 m/s. The temperature field in the plane of the central section is shown in Fig. 6. It can be seen that at a certain distance from the porous insert, the temperature field is equalised. Therefore, there is a sufficient thickness of open cell foam material at which heat removal becomes insignificant.

Fig. 6. The temperature field of the gas flow in cross-section at ε = 0.9 for Re = 500.

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From the known value of the heat flux, surface area, as well as the temperature values on the surface of the porous structure and at the output boundary of the computational domain, the average heat transfer coefficient can be calculated. α=

q , twall − tout

(7)

where q - the heat flux density, twall - the average wall temperature, tout - the average air temperature. q=

Qwall , F

(8)

where Qwall - the heat flux on the surface of the porous structure, F - the surface area of the porous structure. The curves of changes in the heat transfer coefficient are shown in Fig. 7; the heat transfer coefficient does not change for different values of the porosity of the medium, which is associated with an equal amount of the surface area, which is crucial.

Fig. 7. Change in heat transfer coefficient depending on the velocity.

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Fig. 8. Change in the Nusselt number depending on the flow rate.

When calculating the Nusselt number, the characteristic size is the hydraulic diameter of the porous structure: Nu =

α · dh , λ

(9)

where dh - the hydraulic diameter of the porous structure, λh - the coefficient of thermal conductivity of air. Since in our case, the heat transfer and thermal conductivity coefficients remain unchanged, and the hydraulic diameter increases with increasing porosity of the medium, the Nusselt number is higher for a structure with higher porosity, as shown in Fig. 8. Figure 9 presents a comparison of the results of numerical calculation and the results obtained based on an empirical formula (10) for small Reynolds numbers from 20 to 80. The graphs show good agreement between the results for porosity ε = 0.9. We can conclude that this dependence can only be used for structures with high porosity. If Re > 100 the empirical dependence ceases to work since expression (10) is valid for a narrow range of Reynolds numbers (20 < Re < 80).   0.37 4(1 − ε) 0.5 · 0.26 Re Pr , (10) Nu = 1 − e−(1−ε)0.04 where Re - the Reynolds number, Pr - the Prandtl number, ε - the porosity of the medium.

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Fig. 9. Comparison of the results of numerical calculation and empirical dependence (10) for the Nusselt number.

5 Conclusion Models of porous structures with porosities ε = 0.8, ε = 0.85 and ε = 0.9 with the same surface area are constructed. Numerical calculations of the airflow through a porous structure heated to 400 K are carried out. Studies have shown that the thermophysical parameters do not change while maintaining the surface area with increasing porosity of the medium, however, the hydrodynamic characteristics of the flow change, and with greater porosity, the pressure drop is lower. It can be concluded that it is possible to create heat exchangers from porous structures with preserving the thermophysical characteristics and low hydrodynamic resistance, which will be beneficial in cases when forced convection is used. The semi-empirical dependence for the Nusselt number, which showed good agreement with the results of a numerical study, can be applied at low Reynolds numbers (Re < 100) and only for the value of porosity ε = 0.9. The results obtained in this study can serve as the basis for creating the equation for the Nusselt number over the entire range of Reynolds number and porosities. Acknowledgments. The reported study has been funded by RFBR according to research project No. 19-07-01188.

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References 1. Siavashi, M., Bahrami, H.R.T., Aminian, E.: Optimization of heat transfer enhancement and pumping power of a heat exchanger tube using nanofluid with gradient and multi-layered porous foams. Appl. Therm. Eng. 138, 465–474 (2018). https://doi.org/10.1016/j.appltherm aleng.2018.04.066 2. Du, S., He, Y.L., Yang, W.W., Liu, Z.B.: Optimization method for the porous volumetric solar receiver coupling genetic algorithm and heat transfer analysis. Int. J. Heat Mass Transf. 122, 383–390 (2018). https://doi.org/10.1016/j.ijheatmasstransfer.2018.01.120 3. Hamadouche, A., Azzi, A., Abboudi, S., Nebbali, R.: Enhancement of heat exchanger thermal hydraulic performance using aluminum foam. Exp. Thermal Fluid Sci. 92, 1–12 (2018). https://doi.org/10.1016/j.expthermflusci.2017.10.035 4. Dehghan, M., Jamal-Abad, M.T., Rashidi, S.: Analytical interpretation of the local thermal non-equilibrium condition of porous media imbedded in tube heat exchangers. Energy Convers. Manag. 85, 264–271 (2014). https://doi.org/10.1016/j.enconman.2014.05.074 5. Dehghan, M., Valipour, M.S., Keshmiri, A., Saedodin, S., Shokri, N.: On the thermally developing forced convection through a porous material under the local thermal non-equilibrium condition: an analytical study. Int. J. Heat Mass Transf. 92, 815–823 (2016). https://doi.org/ 10.1016/j.ijheatmasstransfer.2015.08.091 6. Mahmoudi, Y., Karimi, N.: Numerical investigation of heat transfer enhancement in a pipe partially filled with a porous material under local thermal non-equilibrium condition. Int. J. Heat Mass Transf. 68, 161–173 (2014). https://doi.org/10.1016/j.ijheatmasstransfer.2013. 09.020 7. Kuznetsov, A.V., Nield, D.A.: Local thermal non-equilibrium effects on the onset of convection in an internally heated layered porous medium with vertical through flow. Int. J. Therm. Sci. 92, 97–105 (2015). https://doi.org/10.1007/s11587-014-0219-3 8. Chen, Y.Y., Li, B.W., Zhang, J.K., Qian, Z.D.: Influences of radiative characteristics on free convection in a saturated porous cavity under thermal non-equilibrium condition. Int. Commun. Heat Mass Transfer 95, 80–91 (2018). https://doi.org/10.1016/j.icheatmasstrans fer.2018.04.001 9. Mendes, M.A.A., Ray, S., Trimis, D.: An improved model for the effective thermal conductivity of open-cell porous foams. Int. J. Heat Mass Transf. 75, 224–230 (2014). https://doi. org/10.1016/j.ijheatmasstransfer.2014.02.076 10. Mendes, M.A.A., Ray, S., Trimis, D.: Evaluation of effective thermal conductivity of porous foams in presence of arbitrary working fluid. Int. J. Therm. Sci. 79, 260–265 (2014). https:// doi.org/10.1016/j.ijthermalsci.2014.01.009 11. Ranut, P.: On the effective thermal conductivity of aluminum metal foams: Review and improvement of the available empirical and analytical models. Appl. Therm. Eng. 101, 496–524 (2016). https://doi.org/10.1016/j.applthermaleng.2015.09.094 12. Kumar, P., Topin, F., Vicente, J.: Determination of effective thermal conductivity from geometrical properties: application to open cell foams. Int. J. Therm. Sci. 81, 13–28 (2014). https://doi.org/10.1016/j.ijthermalsci.2014.02.005 13. Kumar, P., Topin, F.: Simultaneous determination of intrinsic solid phase conductivity and effective thermal conductivity of Kelvin like foams. Appl. Therm. Eng. 71(1), 536–547 (2014). https://doi.org/10.1016/j.applthermaleng.2014.06.058 14. Kumar, P., Topin, F.: Thermal conductivity correlations of open-cell foams: extension of Hashin-Shtrikman model and introduction of effective solid phase tortuosity. Int. J. Heat Mass Transf. 92, 539–549 (2016). https://doi.org/10.1016/j.ijheatmasstransfer.2015.08.085 15. Chen, S., Gong, W., Yan, Y.: Conjugate natural convection heat transfer in an open-ended square cavity partially filled with porous media. Int. J. Heat Mass Transf. 124, 368–380 (2018). https://doi.org/10.1016/j.ijheatmasstransfer.2018.03.084

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16. Cunsolo, S., Oliviero, M., Harris, W.M., Andreozzi, A., Bianco, N., Chiu, W.K., Naso, V.: Monte Carlo determination of radiative properties of metal foams: comparison between idealized and real cell structures. Int. J. Therm. Sci. 87, 94–102 (2015). https://doi.org/10.1016/ j.ijthermalsci.2014.08.006 17. Inayat, A., Klumpp, M., Lammermann, M., Freund, H., Schwieger, W.: Development of a new pressure drop correlation for open-cell foams based completely on theoretical grounds: Taking into account strut shape and geometric tortuosity. Chem. Eng. J. 287, 704–719 (2016). https://doi.org/10.1016/j.cej.2015.11.050

Numerical Investigation of the Catalyst Granule Shapes Influence on Dehydrogenation Reaction Sergei Solovev1,2(B) , Olga Soloveva1 , Rishat Khusainov1 and Alexandr Lamberov2

,

1 Kazan State Power Engineering University, Krasnoselskaja Street 51, Kazan 420066, Russia

[email protected] 2 Kazan Federal University, Kremlevskaja Street 18, Kazan 420008, Russia

Abstract. In the work, by means of numerical modeling, the influence of the size and shape of the catalyst granules in the fixed-bed reactor for the dehydrogenation of ethylbenzene to styrene on its efficiency is studied. ANSYS Fluent 19.0 software was used to solve a written system of equations. Many component properties parameters are taken from the database of the used software. The granular layer is based on the discrete element method (DEM). The granules are in the shape of a circle, trefoil, and quatrefoil and have a size of 3 mm in diameter. The length of the studied granules is 3 mm, 6 mm and 9 mm. The effect of the granule size and their shape on the concentration of product yield in a wide range of gas velocities is compared. Variants of the catalyst granules shape that provide the highest values of the reaction product output are determined. The output concentration of the product is estimated for industrial reactors and laboratory plants. Keywords: Fixed bed reactor · Granules · Computational fluid dynamics

1 Introduction Researchers are optimizing the catalyst bed chemical reactors by numerical simulation with the use of computational fluid dynamics (CFD) since in most cases hydrodynamics affect the course of a chemical reaction [1–6]. Most of the work is devoted to studies of catalytic processes in a reactor with an ordered arrangement of granules, however, in reality, the granules are arranged in random order. The authors of [7] studied catalytic processes in a fixed catalyst bed with a random arrangement of granules. The influence of the layer geometry on the radial velocity, and as a consequence on heat and mass transfer, was studied in [8–11]. There are restrictions on the use of this model in the case when the layer is formed by just a few granules. In this case, axial symmetry is not observed and local phenomena can be overlooked. A detailed study is possible using three-dimensional modeling, as shown in [12]. The consideration of local features is shown in [13], where a full three-dimensional geometry is used. In contrast to averaged models, modeling allows one to study processes in reactors regardless of their size and shape, and also to consider both large-scale and local © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 383–390, 2021. https://doi.org/10.1007/978-3-030-57453-6_34

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phenomena in them. The process of methanol decomposition in a microreactor was experimentally and numerically studied in [14]. In the chemical industry, there is a problem of overheating in the contact zones of granules and on their surface, which is associated with the exothermicity of the reaction. One of the solutions to this problem is the use of foam material, which acts as the basis for the deposition of the catalyst. In [15], flow through a layer created by porous cubes was studied. The presence of local porosity (in addition to the total porosity of the layer) leads to an increase in convection and a decrease in overheating. We studied the process of dehydrogenation of ethylbenzene to styrene in a granular catalyst bed, and a mathematical model of the reaction was constructed. The granular layer is based on the discrete element method (DEM) as models of granules, cylinders, shamrocks and quatrefoils of different sizes were chosen. The effect of the granule size and their shape on the concentration of product yield in a wide range of gas velocities is compared. The output concentration of the product is estimated for industrial reactors and laboratory plants.

2 Problem Formulation and Solution Methods 2.1 Catalyst Shapes and Chemical Reaction The investigation in this paper are based on studies [16, 17], where the ethylbenzene to styrene dehydrogenation process in a fixed-bed reactor for cylindrical garnishes of different sizes was considered. The ethylbenzene dehydrogenation reaction is primary, and the following equation describes proceeds with the heat absorption and an increase in the volume of gaseous products C6 H5 CH2 CH2 ↔ C6 H5 CH = CH2 + H2 −124.8 kJ/mol.

(1)

Activity indicators are styrene yield to missed ethylbenzene (activity - A), and decomposed ethylbenzene (selectivity - S) is calculated based on chromatographic analysis data. The formula (2) calculates the activity A=

Cout C8H8 in Cin C8H10 + CC8H8

× 100,

(2)

in where Cout C8H8 is a mass fraction of styrene at the outlet (% mass.), CC8H10 is mass fraction in of ethylbenzene in raw materials (% mass.), CC8H8 is a mass fraction of styrene in raw materials (% mass.). Figure 1, α shows an example of constructing a packing of cylindrical catalyst granules with a diameter of 3 cm for a model of a laboratory reactor. The bed height is 45 mm, the diameter of the granules is 3 mm, and the length of the granules is 6 mm. Figures 1b and c show options for constructing packages of catalyst granules having the shape of a trefoil and quatrefoil in cross section. The diameter of the cross-section of the figures is 3 mm. Such granules have a larger surface area, which can contribute to an increase in the yield of the reaction product. We want to use numerical simulation to determine the changes in the yield of the reaction product depending on the shape of the granules.

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Fig. 1. The examples of the catalyst bed.

2.2 Numerical Simulation The described problem was solved by the finite volume method with grid partitioning of the considered reactor domain. The flow is considered stationary. For a multicomponent gas phase, the conservation laws of mass, momentum, and energy are satisfied. The mass conservation equation ∇ · (ρv ) = 0,

(3)

where ρ is the density, v is the velocity. The momentum conservation equation ∇ · (αρv v) = −∇p + ∇ · τ¯¯ + ρ g ,

(4)

where p is the pressure, τ¯¯ is the stress tensor. The mass conservation equation for the i-th component of the gas mixture ∇ · (ρv Yi ) = −∇ · Ji + Ri ,

(5)

where Yi is the mass fraction for the i-th component of gas mixture, Ri is the net rate of production of i-th species by chemical reaction, Ji is the diffusion flux of i-th species, which arises due to gradients of concentration and temperature. ∇T , Ji = −ρDm,i ∇Yi − DT ,i T

(6)

where T is the temperature, Dm,i is the mass diffusion coefficient, DT ,i is the temperature diffusion coefficient. The energy conservation equation   ∂p ∇ · (ρv h) + ∇ · Jq = + τ¯¯ : v, ∂t

(7)

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where h =

N 

Yi hi is the gas enthalpy, and

i=1

Jq = λ∇T +

N 

hi Ji ,

(8)

i=1

where λ is the thermal conductivity of mixture, N is a number of components in the mixture. For chemical reactions, the term Ri in Eq. (6) is Ri = Mi

NR 

Ri,r ,

(9)

r=1

where Mi is the molecular mass for i-th component, NR is a number of reactions involving the i-th component of the mixture. Ri,r = υr kr

N   ηr Cj ,

(10)

j=1

where υr is the stoichiometric coefficient, Cj is the concentration of the j-th component of mixture, ηr is the rate exponent for reactant j-th species in reaction, kr is the reaction rate constant. kr = Ar e−Er / RT ,

(11)

where Ar is the pre-exponential coefficient, Er is the activation energy. For the numerical solution of the problem, we divide the entire domain under consideration into finite elements of a triangular shape, the dimensions of which are sufficient to determine the specific factors of the phenomenon under study. We selected the method of cutting part of the granules with the formation of small gaps as a way to neutralize the problems with contact points between granules. This fact imposes cell size restrictions when meshing. We use a uniform grid, with 1.0e−04 m selected as the primary cell size. Near the surface of the granules and at the contact points, we carried out thickening with a mesh size of 2.5e−05 m and 5.0e−05 m. Such a grid partition avoids sharp cell bending. To simulate the processes of hydrodynamics and heat and mass transfer in a reactor, boundary conditions are set in the computational domain. We established the boundary conditions using the mechanisms of the computational laboratory reactor and solver used at all boundaries of the computational domain. The boundary conditions in the CFD model are set in accordance with the calculations obtained in the laboratory reactor. On the surfaces, the conditions for the impermeability of the walls are set. On the outer wall, a temperature value is set equal to the value of the heated walls of the reactor. In place of the gas flow in the reactor model, we establish the conditions for the mass flow of gas. At the site of the reactor model, conditions were established for “external pressure” outside the considered region for gas escape.

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The considered flow of the gas phase (at a temperature of 600 °C) is considered to be a multicomponent ideal incompressible gas consisting of raw materials (ethylbenzene and water steam) and reaction products (styrene and hydrogen). At the inlet to the reactor, the gas mixture consists only of ethylbenzene and steam in a mass ratio of 1:2. The flow rate of the gas mixture is considered from 2.18 · 10−5 up to 1.056 · 10−3 kg/s corresponds to the average gas velocity in the reactor cross-section from 0.1 m/s to 5 m/s. In this case, the Reynolds number Rep = vdp ρ/μ is in the range from 2 to 115. We performed the calculations for a laminar gas flow model. We use the software ANSYS Fluent 19.0 to solve the written system of equations. Many parameters of the component properties are from the database of the used software. We take the physicochemical properties of the components according to the polynomial dependence on temperature.

3 Results Consider a model of a laboratory reactor for a granulated catalyst bed for the dehydrogenation of ethylbenzene to styrene 4.5 cm in height and 2.8 cm in diameter. In this case, for example, in industrial radial-type reactors, the average gas velocity can be of the order of 3 m/s. Therefore, we will carry out calculations for a wide range of gas velocities. Figure 2 presents the results of numerical calculations of the reaction product (styrene) output for the entire investigated range of gas velocity and catalyst granule lengths and shapes. For granules with a length of 3 mm, it is evident that the product output is maintained at an order of 70–75% in the gas velocity range up to 1.5 m/s. Further, there is a decline in values of up to 40%. For the case of granules with a length of 6 mm calculations show that maintaining a substantial product output is possible only up to gas velocities of 0.5 m/s, then a decrease is observed. Calculations for granules with a length of 9 mm show a significant decrease in the product output from a gas velocity of 0.1 m/s. Then we will carry out a comparative analysis of granules with different crosssectional shapes. The best results show trefoil granules. Such granules more densely fit into a fixed catalyst bed and provide a large surface area of the entire bed. Moreover, the differences in the graphs have similar behavior for all values of the length of the catalyst particles.

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Fig. 2. Calculated activity depending on gas velocity.

4 Conclusion For all constructed models of a granular catalyst bed, we calculated the reactor operation parameters. We carried out the calculations for a wide range of gas velocity (0.1–3.0 m/s), consisting of a mixture of steam, ethylbenzene, and reaction products (styrene and hydrogen). We choose such a wide range of gas velocities for a comparative analysis of the operating parameters of the reactor under consideration, both in laboratory tests at low velocities and in the industrial operation of the catalyst at high velocities. Thus, the catalyst granule length has a significant effect on the yield of the reaction product for the process of ethylbenzene dehydrogenation to styrene. Larger granules show better efficiency because they form a layer with the largest surface area and lowest porosity. At the same time, the voids formed in the packaging of such granules have small volumes and do not contribute to the formation of through gas flows without contact with the catalyst surface. The change in the efficiency of the catalyst when the size of the granules is evaluated.

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Acknowledgments. This work was supported by the Ministry of Science and Higher Education of the Russian Federation under the state contract No. 074-11-2018-030.

References 1. Jiang, Y., Khadilkar, M.R., Al-Dahhan, M.H., Dudukovic, M.P.: CFD modeling of multiphase flow distribution in catalytic packed bed reactors: scale down issues. Catal. Today 66(2–4), 209–218 (2001). https://doi.org/10.1016/s0920-5861(00)00642-8 2. Gunjal, P.R., Kashid, M.N., Ranade, V.V., Chaudhari, R.V.: Hydrodynamics of trickle-bed reactors: experiments and CFD modeling. Ind. Eng. Chem. Res. 44(16), 6278–6294 (2005). https://doi.org/10.1021/ie0491037 3. Gunjal, P.R., Ranade, V.V.: Modeling of laboratory and commercial scale hydro-processing reactors using CFD. Chem. Eng. Sci. 62(18–20), 5512–5526 (2007). https://doi.org/10.1016/ j.ces.2007.01.078 4. Solov’ev, S.A., Egorov, A.G., Lamberov, A.A., Egorova, S.R., Kataev, A.N.: Effect of the design of a feedstock injection device in a fluidized-bed reactor on the efficiency of the reaction using the dehydrogenation of iso-paraffins in a fluidized chromia–alumina catalyst bed as an example. Catal. Ind. 8(1), 48–55 (2016). https://doi.org/10.1134/s207005041601013x 5. Soloveva, O.V., Solovyev, S.A.: Investigation of the influence of heated catalyst feeding system on the intensity of temperature-dependent chemical reaction in the fluidized bed apparatus. In: IOP Conference Series: Materials Science and Engineering, vol. 158, no. 1 (2016). https://doi.org/10.1088/1757-899x/158/1/012086 6. Soloveva, O.V., Solovev, S.A., Egorova, S.R., Lamberov, A.A., Antipin, A.V., Shamsutdinov, E.V.: CFD modeling a fluidized bed large scale reactor with various internal elements near the heated particles feeder. Chem. Eng. Res. Des. 138, 212–228 (2018). https://doi.org/10. 1016/j.cherd.2018.08.011 7. Calis, H.P.A., Nijenhuis, J., Paikert, B.C., Dautzenberg, F.M., Van Den Bleek, C.M.: CFD modelling and experimental validation of pressure drop and flow profile in a novel structured catalytic reactor packing. Chem. Eng. Sci. 56(4), 1713–1720 (2001). https://doi.org/10.1016/ s0009-2509(00)00400-0 8. Küfner, R., Hofmann, H.: Implementation of radial porosity and velocity distribution in a reactor model for heterogeneous catalytic gasphase reactions (TORUS-Model). Chem. Eng. Sci. 45(8), 2141–2146 (1990). https://doi.org/10.1016/0009-2509(90)80088-v 9. Bey, O., Eigenberger, G.: Fluid flow through catalyst filled tubes. Chem. Eng. Sci. 52(8), 1365–1376 (1997). https://doi.org/10.1016/s0009-2509(96)00509-x 10. Giese, M., Rottschäfer, K., Vortmeyer, D.: Measured and modeled superficial flow profiles in packed beds with liquid flow. AIChE J. 44(2), 484–490 (1998). https://doi.org/10.1002/aic. 690440225 11. Winterberg, M., Tsotsas, E., Krischke, A., Vortmeyer, D.: A simple and coherent set of coefficients for modelling of heat and mass transport with and without chemical reaction in tubes filled with spheres. Chem. Eng. Sci. 55(5), 967–979 (2000). https://doi.org/10.1016/ s0009-2509(99)00379-6 12. Dixon, A.G., Nijemeisland, M.: CFD as a design tool for fixed-bed reactors. Ind. Eng. Chem. Res. 40(23), 5246–5254 (2001). https://doi.org/10.1021/ie001035a 13. Freund, H., Zeiser, T., Huber, F., Klemm, E., Brenner, G., Durst, F., Emig, G.: Numerical simulations of single phase reacting flows in randomly packed fixed-bed reactors and experimental validation. Chem. Eng. Sci. 58(3–6), 903–910 (2003). https://doi.org/10.1016/s00092509(02)00622-x

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14. Pohar, A., Belaviˇc, D., Dolanc, G., Hoˇcevar, S.: Modeling of methanol decomposition on Pt/CeO2/ZrO2 catalyst in a packed bed microreactor. J. Power Sources 256, 80–87 (2014). https://doi.org/10.1016/j.jpowsour.2014.01.051 15. Das, S., Deen, N.G., Kuipers, J.A.M.: Multiscale modeling of fixed-bed reactors with porous (open-cell foam) non-spherical particles: hydrodynamics. Chem. Eng. J. 334, 741–759 (2018). https://doi.org/10.1016/j.cej.2017.10.047 16. Solovev, S.A., Khusainov, R.R., Nasretdinova, D.R.: Numerical investigation of the granule size effect on the reaction product yield in a catalyst fixed bed. In: IOP Conference Series: Materials Science and Engineering, vol. 618, no. 1 (2019). https://doi.org/10.1088/1757-899x/ 618/1/012096 17. Solovev, S.A., Soloveva, O.V., Gilmurahmanov, B.S., Lamberov, A.A.: Numerical simulation of a flow mixer for a radial type chemical reactor. In: IOP Conference Series: Earth and Environmental Science, vol. 421, no. 7 (2020). https://doi.org/10.1088/1755-1315/421/ 7/072017

Assessment of the Fire Situation of a Certain Building Using Fenix+ Marina Avdeeva(B)

, Anton Byzov , Karina Smyshlyaeva , and Natalia Leonova

Peter the Great St. Petersburg Polytechnic University, Polytechnic Street, 29, 195251 St. Petersburg, Russia [email protected]

Abstract. Fire is a dangerous phenomenon that accompanies humanity throughout its history. Each person and each enterprise should be prepared for a fire situation and to get out of such a situation with minimal damage. To exclude their occurrence, it is necessary to deal with fire risk assessment and preparation of measures that are aimed at reducing fire risk. The article is devoted to the current problem: the use of simulation methods to reproduce various emergencies and their further assessment and forecasting. In this regard, the task of modeling emergency situations is set, the software tool “Fenix+” is used to find a solution. It allows one to build a drawing of a building, and use a graphic editor to recreate the structure of an object of any complexity. Using this software, a three-dimensional model of the building is built. One of the most dangerous emergency scenarios is presented. The calculated values of indicators are obtained, such as: evacuation time, evacuation routes, evacuation exit capacity, critical temperature, smoke of the room, individual risk. Calculation and analysis of values of these indicators allows assessing the need for implementation of additional fire prevention measures. Keywords: Management · Technosphere safety · Modeling · Simulation · Emergency · Fire · Evacuation · Risk · Smoke · Fenix+ · Life safety · Life and health

1 Introduction Due to the high growth of emergencies of a natural and man-made nature, and also gradual increase in the number and scale of emergencies, it is necessary to anticipate possible threats, risks and dangers using methods for predicting and preventing them. Fire is a dangerous phenomenon that accompanies humanity throughout its history. With the development of technology and industry, the problem of fires is becoming more and more widespread, as a result even the smallest mistake can lead to fires and irreversible consequences, and therefore the relevance of the problem of ensuring fire safety is undeniable in our time. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 391–400, 2021. https://doi.org/10.1007/978-3-030-57453-6_35

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Each person and every enterprise should be prepared for a fire situation and to get out of such a situation with minimal damage. In order to exclude their occurrence, it is necessary to deal with fire risk assessment and preparation of measures that are aimed at reducing fire risk. The calculation of time and escape routes during fires in buildings and premises is an important point in assessing fire risk. According to estimates for 2018, the number of fires in Russian Federation is 132.4 thousand. This is 7 thousand less than in 2017, and 18 thousand less than in 2014. These statistics show a clear downward trend in the number of fires across the country. The reason for this is tightening of fire control standards, improvement of fire prevention systems from the technical side, refractory materials used in construction, etc.

2 Problem Setting Having analyzed the approaches of modern scientists [1–6] to solving the problems of liquidation of emergency situations, we can conclude that they are based on outdated technologies. The solution to this problem is presented by the authors through the use of information technologies based on the use of mathematical methods and simulation models. Due to the fact that parameters describing the process of occurrence of an emergency situation contain random variables, mathematical description of this process in the framework of deterministic models is difficult to implement. This entailed the need to use the simulation method for this purpose. Thus, the process of an emergency in the building acts as the object of modeling. Before constructing a simulation model, the authors of the article conducted a study of the input and output parameters characterizing the process of an emergency. Moreover, it is proposed to consider the flow of events W as disturbances. The output parameters are indicators representing a vector whose components are: tevac – evacuation time, Lesc – escape routes, Pcap - evacuation exit capacity, T - critical temperature, D - smoke in the room, Qr - individual risk.

3 Methods The methods of research and individual risk assessment currently used have a number of disadvantages (along with advantages): they make it possible to describe the process only in a generalized way, idealizing and simplifying its elements. A completely new stage of methodological and instrumental support includes various solutions, initially tested not on real objects and people, but on their analogues, in other words, models. As a result, implementation of timely decisions requires preliminary estimates of final results using simulation, which is purposed to create simulation models of systems in question and conduct simulation experiments with these models. Thanks to simulation, one can bring the model as close as possible to the real situation. The need to use other research methods along with imitation is not excluded. They are part of a directed experiment with the model.

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At the moment, one of the most effective methods is the use of computer modeling and programming in the calculation of evacuation. The “Fenix+” program allows to simulate an object, and the integrated FDS (Fire Dynamics Simulator) program allows to program the spread of fire throughout the study area. “Fenix+” is a program developed by MST and designed to assess fire risk. The calculation of fire risk in the program is based on the appendix to the order of the Ministry of Emergencies of Russia dated 30.06.09, No. 382 [6]. “Fenix+” allows to build a drawing of protection object, for which, during the simulation of a fire situation, it calculates fire risk and evacuation time. A graphical editor built into the program allows to accurately recreate the structure of an object of any complexity. The program implements a model of human behavior used by seeking the shortest way to the exit, bypassing obstacles and eliminating the possibility of a collision with other people. At the end of the fire risk assessment, the program presents a fire safety report, which is designed in accordance with GOST. The selected program gives the opportunity to pre-think about the layout of the internal space of the object, what materials will be used during construction and decoration, the maximum number of people in the room for a successful and timely evacuation. A key feature of this technique is the fact that it is possible to simulate the situation repeatedly, selecting necessary parameters, without financial loss, in contrast to applied modeling. To obtain the initial data on which basis the calculations are carried out, one should use the building design documentation, fire safety declaration and reference sections of normative documents on fire safety. In some cases, an actual site survey may be required to collect baseline data [7, 8]. The restaurant building belongs to category f 3.2 according to its intended purpose. This category includes dining rooms, clubs, restaurants, cafes. The object’s working time is 8:00–23:00, 7 days a week. A one-time flow of guests varies from 70 to 140, depending on the day of the week and time. The building occupies 2 floors, each measuring 26 × 11 m. The total area is 572 m. Both floors can be divided into a hall, a kitchen and administrative premises. The building has two exits - the main one from the avenue and the service exit to the well of the house. On the ground floor there are 3 fire extinguishers and 3 buttons “turn on the means and systems of fire automatics”. The second floor is equipped with 3 fire extinguishers and 2 power buttons and fire automatics systems. Every 5 years, the contents of the fire extinguishers are recharged, every 10 years occurs a complete replacement. Smoke and fire detectors are located throughout the floor area. This article discusses one scenario of a fire situation for which the indicators highlighted in the emergency modeling task will be obtained. In the quality of the scenario, we will consider a certain course of development of a fire hazard situation in which the place of burning and the nature of its development will be taken into account.

4 Results The authors of this article have implemented a model of the object under consideration for the first floor. It is presented below (Figs. 1 and 2).

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Fig. 1. Three-dimensional model representing the general view of the building.

Fig. 2. Model representing the ground floor plan.

The calculation is carried out for the scenario in which the highest parameters of fire hazard factors are displayed. At the same time, it is important not to exclude the fact that there are blocked evacuation exits, faulty fire warning systems. On the constructed three-dimensional model of the building, experiments were conducted to model the evacuation of people. At the same time, the area of the fire was determined and people were arranged. Table 1. Estimated values of the time of evacuation and the number of evacuated people. Evacuation start time

Evacuation time

Total number of people

The number of the evacuated people

5.3

176.6

140

140

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The following results were obtained: Table 1 shows the calculated values of evacuation time and the number of evacuated people, Table 2 presents the values of individual fire risk. Table 2. Calculated values of individual fire risk. Scenario

Fire AUP frequency, compliance Qn, i year−1 coefficient, Kan,i

Likelihood of human presence, Ppr,i

Probability of people evacuating, Pe,i

Fire Individual protection risk, Qr,i system compliance coefficient, Kfps,i

Scenario 1

4*10−2

0.458

0.1

0.870

0.900

2.376*10−3

A map of temperature distribution when modeling a fire in a building is presented below (Fig. 3 and 4), as well as distribution of smoke from the source of fire (Fig. 5), and evacuation routes that were recorded during the simulation (Fig. 6 and 7) (Table 3).

Fig. 3. Map of the temperature distribution when modeling a fire on the ground floor of the building.

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Fig. 4. Map of the temperature distribution during a fire simulation on the second floor of the building.

Fig. 5. Smoke levels in various areas of the floor.

Assessment of the Fire Situation of a Certain Building Using Fenix+

Fig. 6. Evacuation routes on the first floor of the building.

Fig. 7. Evacuation routes on the second floor of the building.

397

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Name

Temperature

Visibility

O2

CO2

CO

HCl

Heat flow

Floor 1 Outside the premises Door 1

not blocked

31.67

not blocked

not blocked

not blocked

not blocked

not blocked

Door1_1

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Door1_2

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Door1_3

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Door1_4

not blocked

31.76

not blocked

not blocked

not blocked

not blocked

not blocked

Door 9

27.49

23.56

not blocked

not blocked

not blocked

not blocked

not blocked

Door9_1

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Door9_2

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Door9_3

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Door9_4

27.49

23.56

27.49

not blocked

not blocked

not blocked

not blocked

Registrar 1

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Registrar 2

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Registrar 3

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Registrar 4

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Registrar 5

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Registrar 6

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Registrar 7

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked (continued)

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Table 3. (continued) Name

Temperature

Visibility

O2

CO2

CO

HCl

Heat flow

Floor 1 Outside the premises Registrar 8

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Registrar 13

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

Registrar 14

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

not blocked

5 Discussion Calculation and assessment of the time of evacuation in the case of an emergency allows analyzing: the ways of leaving the room or building, the total time when people can leave the facility, the load on the fire exits with the maximum number of people, the effectiveness of the evacuation schemes of the facility. By analyzing these parameters, one can create the optimal evacuation scheme by distributing the load on the fire exits. As a result of modeling the fire situation at the object of protection, vivid illustrations of dynamics of development of dangerous fire factors were obtained, namely: a map of distribution of temperature and visibility, calculated values of individual fire risk. Based on the results obtained, the authors of this article made proposals for implementation of additional fire prevention measures for the object of modeling.

6 Conclusions 1. The authors set the task of simulation of emergencies in order to obtain the values of output indicators during the development of this situation. 2. The authors conducted a simulation of emergency situations on the constructed three-dimensional model of the building. 3. The authors obtained the numerical values of the indicators defined in the modeling problem. 4. Based on the experiments conducted on the constructed building model, it can be concluded that the use of simulation techniques greatly facilitates the task of conducting a large number of experiments, allows obtaining adequate results, as well as saving time spent working on the problem

References 1. Koshmarov, Y.A.: Consideration of the fire in terms of physical model, forecasting of dynamics of the fire, distribution to the room, zoning of areas. Academy GPS of the Ministry of Internal Affairs of the Russian Federation, Moscow (2000)

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2. Brushlinsky, N.N.: Reduction of fire risks, the techniques of reduction of fire risk and major factors affecting fire risks. Fire risks: the basic concepts. National Academy of Sciences of Fire Safety, Moscow (2004) 3. Burlov, V.G., Grobitski, A.M., Grobitskaya, A.M.: Construction management in terms of indicator of the successfully fulfilled production task. Mag. Civ. Eng. 63(3), 77–91 (2016). https:// doi.org/10.5862/MCE.63.5 4. Puzach, S.V., Smagin, A.V., Lebedchenko, O.S., Abakumov, E.S.: New ideas of calculation of necessary time of evacuation of people and of efficiency of use of the portable filtering self-rescuers at evacuation on the fires. Academy GPS of the Ministry of Internal Affairs of the Russian Federation, Moscow (2007) 5. Korol’chenko, A.Y.: Fire-and-explosion hazard of substances and materials and means of their suppression: the reference book in 2 volumes, Moscow (2004) 6. Burlov, V., Grachev, M.: Development of a mathematical model of traffic safety management with account for opportunities of web technologies. Transp. Res. Procedia 20, 100–106 (2017). https://doi.org/10.1016/j.trpro.2017.01.023 7. Fenix+/Fenix+ 2 Program for determination of size of individual fire risk, version x.1.74 Methodical management (2018) 8. Sharkhun, S.V., Sirina, N.F.: Modern high-rise construction and its fire hazard. Technosphere Saf. 4, 37–42 (2015)

Determination of the Reduced Areas of Destruction of Elements of Hazardous Production Facilities Ekaterina Kutuzova(B)

and Vladimir Yusupdzhanov

Peter the Great Saint Petersburg Polytechnic University, 29 Politekhnicheskaya Street, 195251 Saint Petersburg, Russia [email protected]

Abstract. The article analyzes aspects of application of the reduced damage areas for individual elements of hazardous production facility. Methods for determining the reduced damage area by shrapnel, shock wave and combined damage are reviewed, namely the Destruction Laws using which it is possible to calculate the potential damage areas. The Coordinate Destruction Law expresses the dependence of the destruction probability on the removal of the explosion epicenter from the element of hazardous production facility. The Destruction Digital Law expresses the dependence of the destruction probability of the element of hazardous production facility on a number of explosions. A method for determining the Coordinate Destruction Laws and reduced damage areas for elements of hazardous production facility is proposed. The identification of vulnerable elements for each hazardous production facility is made on the grounds of the event with the following content: the object is damaged, which may be different for the same object under various conditions. Therefore, the Coordinate Destruction Law and reduced damage areas should be calculated for different levels and possible scenarios of accidents. Based on experience and theory, the reduced damage areas during the explosion of various amounts of explosives occurred in an open area are determined. Keywords: Hazardous production facility · The Coordinate Destruction Law · The Destruction Digital Law · Reduced damage areas

1 Introduction A high level of industrial safety is achieved by the development and implementation of Industrial Safety Management System (hereinafter referred to as the ISMS) at hazardous production facilities. The ISMS is a structured set of managerial decisions, norms and procedures by means of which risk prevention activities and industrial safety requirements are carried out and developed. Managerial decisions, norms and rules are developed in the following ISMS documentation: © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 401–407, 2021. https://doi.org/10.1007/978-3-030-57453-6_36

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a) Policy Statement of Operating Organizations in the Field of Industrial Safety; b) Provision on the Industrial Safety Management System; c) Provision on Production Control over Compliance with Industrial Safety Requirements at Hazardous Production Facilities; d) Planning Documents to Reduce Risk of Accidents at Hazardous Production Facilities; e) Industrial Safety Declaration; f) Other documents ensuring the ISMS functioning stipulated by the Regulation on the Industrial Safety Management System [1]. The actual continuity of this article is determined by the need to calculate the potential damage areas that are formed by shrapnel during an explosion or by combined damage by both shrapnel and a shock wave, as there are no requirements in the methods on analyzing and evaluating risks effectiveness for calculating these damage areas. Herefrom, the task is to determine the method for calculating the reduced damage areas for elements of hazardous production facility.

2 Materials and Methods The calculations of probable areas of damage by shrapnel and combined damage are proposed to be carried out according to the following Destruction Laws: The Coordinate Destruction Law (CDL) expresses the dependence of the destruction probability on the removal of the explosion epicenter from the element of hazardous production facility (hereinafter referred to as the HPF). This dependence is described by G(x, z) function; The Destruction Digital Law (DDL) expresses the dependence of the destruction probability of the element of hazardous production facility on a number of explosions. This dependence is described by G(n) function [2]. The graphic representation of G(x, z) function is the surface (Fig. 1). Let’s consider the structure of this function. G(x, z) function is positive, since this function expresses the probability of the object’ damage. In the object’s vicinity, it is possible to distinguish an area of reliable defeat Qr within which G(x, z) = 1 [3]. Outside this area, there is an area of unreliable defeat Qu . The object is not necessarily damaged if a burst happens within this area and 0 < G(x, z) < 1. Within its limits, G(x, z) is a monotonically decreasing function. Fortwo bursts occurring  in the same direction from the object’s center at a distance I1 = x21 + z21 and I2 = x22 + z22 with I1 < I2 , inequality G(x1 , z1 ) > G(x2 , z2 ) holds true. This follows from the fact that the probability of the object’s damage can only decrease as a burst recedes into the distance from it. The area around the object, with a burst within which one can expect its damage, is called an area of Qd dangerous bursts [4]. Outside the area of unreliable defeat, there is an area of safe bursts Qs . The bursts within this area do not damage the object, and G(x, z) = 0.

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403

Fig. 1. Function graph of the Coordinate Destruction Law.

Thus, the Coordinate Destruction Law is expressed by the following function [3]: ⎧ ⎨ 1 with (x, z) ∈ Qr ; G(x, z) = G(x, z) with (x, z) ∈ Qu ; (1) ⎩ 0 with (x, z) ∈ Qs . The Destruction Digital Law describes the damaging effect of shrapnel, which defeat in some cases makes accumulation of damage. Accumulation of damage means the phenomenon than an object can be damaged only by the joint action of two or more shrapnel, none of which individually damages an object [2]. G(n) dependence is a function of an integer argument; therefore, it can be graphically represented as a series of ordinates corresponding to different n values (Fig. 2) [5]. For visual representation, the vertices of these ordinates are connected by lines. Let’s consider the structure of this function. G(n) function is positive. This follows from the fact that this function expresses the probability of the object’s damage. In the absence of hits, the object cannot be damaged, i.e. G(0) = 0. With an unlimited increase in the number of hits, the object’s damage becomes reliable, i.e. G(∞) = 1. With an increase in the number of hits the probability of the object’s damage cannot become less, since the Destruction Law is a non-decreasing function, i.e. if n2 > n1 , then G(n2 ) ≥ G(n1 ) [3]. For a certain class of objects, the Destruction Digital Law can be expressed by an exponential function. This class includes objects with no accumulation of damage. Such objects consist of aggregates (compartments) that are sharply different in their vulnerability: when hit into one aggregate, the object is damaged reliably; when hit into others, the object isn’t damaged at all. Consequently, the object’s damage is achieved by

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Fig. 2. Function graph of the Destruction Digital Law.

shrapnel that hit the vulnerable aggregate (element), i.e. the probability of the object’s damage is numerically equal to the probability of shrapnel hitting the vulnerable sections [4]. If the explosions are independent and the probability of damage from explosion to explosion does not change and is equal to p, then the probability of the object’s damage with n hits into it will be equal to the probability of the object’s damage with at least one shrapnel. Such a probability, as known, is determined by the following formula [3] G(n) = 1 − (1 − p)n

(2)

The Destruction Laws are full characteristics of explosions’ damaging effects, but they are inconvenient for practical use, since the functions expressing these laws are complex. Therefore, it becomes necessary to use a simpler description of explosions’ damaging effects instead of the Destruction Law. The explosions’ damaging effects is characterized by the damage area S. Damage area S means such a site around the element of HPF, where an explosion can cause damage to the element of HPF. Damage area S is a random variable [2]. Here is an explanation of the aforesaid. We divide the area around the element of HPF into k elementary sites with a size of Si = x*z and number them in the following order i – 1, 2, 3 … k. It is believed that an explosion with equal probability can occur within any elementary site. If the element is damaged during an explosion within i elementary site, this site belongs to the damage area. Since HPF element’s damage during an explosion is a random event, then the belonging of i elementary site to the damage area S will be a random value. Therefore, as a numerical characteristic of explosion damaging effect, the mathematical expectation of the area is used, where an explosion can damage the element of HPF. This area is called the reduced damage area Sd [5].

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405

Random variable is the damage area S corresponding to the sum of the elementary sites: k Si (3) S= i=1

Since the dimensions of i elementary site are small, the probability of hitting during an explosion within this site is constant and equal to G(xi, zi). If this site does not belong to the damage area, then the probability of this event is equal to 1 – G(xi , zi ). The mathematical expectation of the damage area’s increment will be determined by the following formula [3] M [Si ] =

k i=1

Si pi = Si G(xi , zi ) + 0[1 − G(xi , zi )] = Si G(xi , zi )

(4)

The mathematical expectation of the damage area according to the Theorem on Mathematical Expectation of Sum of Random Variables is determined by the following formula [5] M [S] =

k i=1

Si G(xi , zi )

or speaking about infinitesimal quantities, by the formula [5]   ∞ M [S] = Sd = G(x, z)dxdz −∞

(5)

(6)

3 Results This means that the element of HPF can be located both in cover positions and outside them, depending on the location conditions. Cover positions include buildings and structures, fundamental and protective structures. Determining the Coordinate Destruction Laws and the reduced damage area for the specified conditions can be made according to the following method [5]. 1. For each HPF, the content of the phrase the object is damaged is established, that is, which j elements’ damage (aggregates, mechanisms, personnel) of the object deprives it of the ability to perform its functions. Such elements are called vulnerable elements of the object. The dimensions, manufacturing material, shielding by various details (protection), and possibility of its hitting with each of the damaging factors are determined for each j vulnerable element. 2. Damaging i factors that can disable the object in question are established. The Coordinate Destruction Law Gi (x, z) is calculated for each of them based on the parameter with the help of which it is possible to quantify the actuating quantity of i factor on the object. The parameters are: – density of the slaughter shrapnel  (x, z) per unit of the object’s vulnerable area; – overpressure pf for evaluation of the air shock wave [5].

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Based on experience and theory, the dependence of the parameters value with the distance from the explosion is established as follows:  (x, z) = f (x, z); (7) pf = (x, z). By calculation or on the basis of experimental data, a relationship between the probability of object W damage and the value of a striking factor parameter is established as follows:  W = g(); (8) Wdis.ex. = ϕ(pf ) etc.; these dependencies are called damage functions [5]. Using dependency (7) and damage function (8), the values of the function expressing the Coordinate Destruction Law of the object Gi (x, z) are calculated. 3. The function of the Coordinate Law of Combined Damage as a result of the object’s impact by all the damaging factors G(x, z) is calculated. If we take the result of impact of each damaging factor as an independent event, then the probability of the object’s damage with at least one damaging factor will be determined by the following formula: I (9) G(x, z) = 1 − [1 − Gi (x, z)] i=1

where I is the number of damaging factors [5]. 4. The reduced damage area is determined by the formula (6) and the values of reduced dimensions of the individual elements of HPF are calculated by the following formulas:

2md =

Sd ; 2ld = Sd : 2md , λ

(10)

where: λ = 2ld : 2md

4 Discussion The identification of vulnerable elements for each HPF is made on the basis of the content of the object is damaged event. This event’s content for the same object in different conditions may be different [4]. Therefore, the Coordinate Destruction Law and reduced damage areas should be calculated for different levels and possible scenarios of accidents. Based on experience and theory, the reduced damage areas during the explosion of various amounts of explosives occurred in an open area are determined. The values of these areas are listed in Table 1 [2].

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Table 1. The reduced damage areas during the explosion occurred in an open area. No. Amount of explosive, kg The reduced damage area, m2 1

0.05

162.20

2

0.5

352.00

3

1.5

509.40

4

3.5

677.50

5

6

812.20

6

9

930.90

7

12

1,025.60

8

18

1,175.50

9

24

1,295.00

10

32

1,426.60

5 Conclusions Thus, the article analyzes the Destruction Laws, as well as methods for determining the reduced area damaged by shrapnel, shock wave, and combined damage. The aspects of application of the reduced damage areas for individual elements of hazardous production facility were under discussion [6, 7]. In addition, a method for determining reduced damage areas for elements of a hazardous production facility is proposed. Based on experience and theory, the reduced damage areas during the explosion of various amounts of explosives occurred in an open area are determined.

References 1. Burlov, V.G., Lepeshkin, O.M., Lepeshkin, M.O., Gomazov, F.A.: The control model of safety management systems. In: IOP Conference Series: Materials Science and Engineering, vol. 618(1) (2019). https://doi.org/10.1088/1757-899x/618/1/012088 2. Bobrikov, A.: Evaluation of the Effectiveness of Fire Damage by Missile Strikes and Artillery Fire. Galea Print, St. Petersburg (2006) 3. Kashutin, V.: Probability Theory. Kalinin Military Artillery Academy, Leningrad (1971) 4. Ventsel, E.: Probability Theory and Its Engineering Application. Nauka, Moscow (1988) 5. Averianov, M.: Theoretical Foundations of Artillery Fire Control. Kalinin Military Artillery Academy, Leningrad (1978) 6. Borisova, M., Byzov, A., Efremov, S.: Assessment of the maximum possible number of victims of accidents at hazardous production facilities for insurance purposes. In: IOP Conference Series: Materials Science and Engineering, vol. 666(1) (2019). https://doi.org/10.1088/1757899x/666/1/012096 7. Tumanov, A., Venevsky, S.: Elaboration of theoretical methods for assessment of isolated and combined physical damage effects of technogenic accident while transporting radiological materials by multimodal transport. In: IOP Conference Series: Materials Science and Engineering, vol. 582(1) (2019). https://doi.org/10.1088/1757-899x/582/1/012038

Integral Assessment of Anthropogenically Transformed Water Reservoirs Stability for Changes in Mode Parameters Ekaterina Primak1 , Kseniya Odinokova1 , Nina Rumyantseva2(B) Tatyana Kaverzneva2 , and Sergey Efremov3

,

1 Russian State Hydrometeorological University,

Malookhtinsky Pr., 98, Saint-Petersburg 195196, Russia 2 Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, Saint-Petersburg 195251, Russia [email protected] 3 St. Petersburg State Marine Technical University, 3 Pilotskaya Str, Saint-Petersburg 190000, Russia

Abstract. The integral assessment of stability of the lakes in the south part of Karelia North Lake District for changes in natural and anthropogenic mode parameters is analyzed based on the point-index assessment (PIA) method and composite indicators method (CIM). The article estimates the state of these anthropogenically transformed water reservoirs in terms of physicogeographical, morphological, hydrological characteristics as well as changes in water quality parameters. The integral indices were developed to assess stability of water reservoirs for changes in mode parameters. The integral indicators were built based on composite indicators method. Following the results of assessment of water reservoirs stability for changes in natural and anthropogenic mode parameters based on the PIA method, the stability of Lake Vygozero corresponds to stability Class I, that is the maximum one; the stability of Lake Segozero, to stability Class II that is above intermediate one; and the stability of Lake Ondozero, to stability Class III that is intermediate one. Following the results of assessment of water reservoirs stability for changes in natural and anthropogenic mode parameters based on the CIM method, the stability of Lake Vygozero corresponds to stability Class III, that is the intermediate one; the stability of Lake Segozero and Lake Ondozero corresponds to stability Class II, that is above intermediate one. Keywords: Integral indicators · Natural parameters · Anthropogenic parameters

1 Introduction. Stability Concept Currently, it is difficult to select water bodies that would not be affected by external anthropogenic impacts. Human activities have a significant impact on landscapes leading, among other things, to changes in quality of the aquatic environment. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 408–418, 2021. https://doi.org/10.1007/978-3-030-57453-6_37

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Assessment of ecosystem stability for changes in mode parameters is extremely important to prevent and mitigate the negative effects of anthropogenic factors on water bodies. It is reasonable to divide all approaches to examination of the geosystem stability into two groups. The first group can include all concepts of stability and variability of geosystems as a fundamental (basic) property of real-world objects in close relation to the idea of the system invariance. The second one includes studies of the geosystem stability for anthropogenic impacts of different nature. For ecology, the “stability” concept has many meanings. Therefore, different publications refer to numerous terms that describe different categories of stability: resilience, inertness, invariance, vulnerability, stable equilibrium, and impact resistance. Definition of the stability is rather complex, therefore, there are many approaches to description of this concept and study of this property of the ecosystem. However, there is still no single, clearly defined method for integral assessment of the state and resistance of ecosystems to impacts. In view of this, different definitions were considered thereby highlighting the variety of terms used during assessment of stability. Ecosystem resistance to impacts is ecosystem ability to save its properties and mode parameters as quasi-constant ones under conditions of existing internal and external disturbances. Ecosystem vulnerability is ecosystem loss of ability to save its properties and mode parameters as quasi-constant ones under conditions of existing internal and external disturbances. Resilience is natural ecosystem ability to return to the former state of stable equilibrium after temporary impact on it. According to A. M. Lyapunov, the stability is the most demanding requirement of global ecosystem stability. Community stability is brought into correlation with stability of certain positive stationary solution of model equations system – equilibrium point or boundary cycle that is with certain equilibrium position of the ecosystem in multidimensional space of its characteristics [1]. According to Yu. M. Svirezhev, the (hierarchic) stability assumes retention of population structure due to stabilization action of the whole community or ecosystem. In other words, any system consists of “fragments”; each fragment can be, from time to time, stable or unstable. However, instability of one “fragment” can be stabilized by other “fragment” which is hierarchically higher. In the view of V. F. Shuyskiy, the most efficient way is to use quantitative indices which take into account not fixed values of quantitative characteristics of biosystems and their set periodicity but the degree of their variableness over the period of monitoring. Within his publication, V. F. Shuyskiy makes reference to modeling of stability and justifies the advantage of this method by the fact that we can handle not with the expectation of constancy of quantitative characteristics, but with the constancy of the mode in which these characteristics change. According to V. F. Shuyskiy, “the most reasonable measure of resistance to impact on any biosystem is level of impact at which changes caused by such impact lose their reversibility”.

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V. B. Sochava (1978) associated the stability concept with the concept of natural geosystem invariant. Speaking about the invariant concept that came to geographic research from physics, Sochava presented some geosystem properties that remain unchanged during various dynamic processes taking place in the geosystems. According to I. N. Rosnovskiy, the system stability means its ability to retain its properties and mode parameters under conditions of existing internal and external disturbances. Within this article, the water body stability for changes in mode parameters is understood as its ability to retain its properties and mode parameters under conditions of existing external and internal loads [2]. The study is aimed at integral assessment of stability of anthropogenically transformed water reservoirs for changes in mode parameters based on the point-index assessment method and composite indicators method.

2 Water Bodies Stability Assessment Methods The methods for assessment of ecological system stability are based on presentation of the environmental object as a complex multi-parameter system, i.e. its qualities and properties are characterized by a set of initial parameters [3]. The fundamental properties and parameters of the assessment are physical-geographical and climatic conditions as well as the nature of the anthropogenic impact. The water body stability was assessed based on two methods: the point-index assessment (PIA) method and composite indicators method (CIM). 2.1 Point-Index Assessment The point-index assessment is a reconnaissance stage required for justification and selection of assessment parameters, building of rating scales, understanding of the assessment results; however, it is often insufficient for objective assessment of the stability of the studied water body. The parameters of stability and vulnerability of aquatic ecosystems are combined into an expert point-index system which takes into account the regional features of water bodies and enables to conduct a comparative assessment of the vulnerability of aquatic ecosystems to impacts within the limits of changes in their parameters. In the course of the assessment, the indices and then the categories of the corresponding assessment factors are sequentially summarized in the tables. The stability points are found by the sum of the categories; then points of trophicity or water quality are added to them, thereby determining the type of stability. The resulting sum is used to determine the class and subclass of the water reservoir stability [4]. Assignment to a certain class of stability is the final stage of the work and allows to identify more or less stable water bodies and analyze the spatial-temporal changes in the stability of water reservoirs and channels. According to some authors, this approach is the result of indirect assessment of stability since any emergent property cannot be measured in principle [5, 6].

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2.2 Composite Indicators Method This is a multicriteria assessment or assessment of the state and impact on natural ecosystems by building composite indicators based on a set of representative assessment criteria. The multicriteria assessment implies the need for a procedure of information convolution. The integral assessment includes a stage associated with integration of previously heterogeneous (multicriteria) assessments taking into account their weight in a common assessment [7]. Building of the integral indicator is based on the composite indicators method (CIM) or the randomized composite indicators method (RCIM) using incomplete, inaccurate, and non-numerical information. The stages are implemented either for several levels of information convolution or all assessment parameters are united into single initial classification model. The first case is preferable as it permits to take into account nonequilibrium of the levels during determination of the integral indicator of the stability. For the second case, non-equilibrium of the initial parameters during convolution can be only taken into account [7]. Development of the integral indicator can be divided into several stages: At the first stage, the reasonable set of criteria of the state of biota and abiotic environment is selected. At the second stage, we get rid of the dimensions of the initial characteristics so that the value equal to 0 would correspond to the best conditions for each criterion and equal to 1 would correspond to the worst conditions (or vice versa). Thus, the initial criteria in various measurement scales are reduced to dimensionless scales. For the criteria of the first type, the function will be as follows: 0, at xi ≤ mini,  qi = qi (xi ) =

xi − mini maxi − mini

λ

, at(mini , < xi ≤ maxi ),

(1)

1, at xi > maxi For the criteria of the second type, the function will be as follows: 0, at xi ≤ mini , qi = qi (xi ) = {(

maxi −xi λ ) at(mini < xi ≤ maxi ), maxi − mini

(2)

0, at xi > maxi where qi is transformed value of the criterion; xi is current value of the criterion; mini is minimum (background, permissible, safe, maximum permissible, other) value of the criterion; maxi is maximum value of the criterion, λ is a parameter which determines the particular type of the function. The qi always changes within the range from 0 to 1. Thus, the initial criteria in various measurement scales are reduced to dimensionless scales; then, it is possible to carry out mathematical operations to obtain the integral indicator of the ecosystem state.

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At the third stage, the integral indicator type I (qi , wi ) is selected to be built in such a way that it depends not only on qi indicators but on their signification determined by wi weight coefficients. As the equation for the integral indicator, define linear convolution of indicators as follows: Ii =

n 

qi wi, i = 1, . . . n

(3)

i=1

At the fourth stage, introduce assessments of wi weight coefficients. With equal weights of all initial parameters, the weight shall be described by the following formula: wi = 1/n

(4)

Then, at the fifth stage, calculate I for the left and the right boundaries of each class. At the sixth stage, test the developed integral index. Comparison of the state of ecosystems using integral methods allows to quantitatively assess the spatial-temporal features of their dynamics, degree of their anthropogenic transformation, degree of permissible impact on them.

3 Characteristics of Examined Water Bodies 3.1 Lake Vygozero Lake Vygozero (Vygozero water-storage reservoir) is a water reservoir in the European part of Russia, the Republic of Karelia. It refers to the basin of the White Sea. As far as the lake was included in the route of the White Sea – Baltic Sea Canal since 1932, it was transformed into a water-storage reservoir of long-term flow regulation at the Vyg River waterhead ascent. The water level in the lake rose by 7 m resulted in flooding of large areas and increase of the water reservoir area by almost twice from 560 km2 to 1,250 km2 . A large amount of organic and mineral substances – mainly woody and grassy residues, surfaced peat bogs and eroded soils – entered the water reservoir from the flooded area. Lake Vygozero existed in its native state until 1931. As a result of economic development, the water reservoir suffered significant anthropogenic changes. Among such changes were the construction of the White Sea – Baltic Sea Canal in 1932 and the erection of the Segezha Pulp and Paper Mill (Segezha PPM) on the northern shore of Lake Vygozero in Segezha in 1939. The consequences of the lake transformation into the water-storage reservoir reflected in its hydrochemical conditions, as well as caused changes in the lake’s flora and fauna [8]. 3.2 Lake Segozero Lake Segozero is located in the European part of Russia, in the Republic of Karelia. It refers to the basin of the White Sea.

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When the dam was built at the source of the Segezha River at Popov Porog in 1957, the lake turned out to be backwater, the water level increased by 6.3 m. The catchment area is 7,480 km2 . Before creation of the water-storage reservoir for over-years storage, the lake area was 753 km2 (782 km2 with islands), and the water edge was at the altitude of 113.7 m. In terms of the water surface area, Lake Segozero is on the 5th place in the Republic of Karelia and on the 16th place in Russia. The water reservoir is used for timber-rafting and shipping. There are small settlements on the lake banks: Popov Porog (where the HPP is located), as well as Padany, Termany, Pogost on the west bank, Karelian Maselga and Velikaya Guba on the southeast one. The main anthropogenic changes on the lake were observed after its damming accompanied by a significant increase in the water level. The changes reflected in the macrophytes and biota composition, however, the lake water is still of good quality. The lake is still oligotrophic. The Segozerskoye trout farm operates on the lake [9]. 3.3 Lake Ondozero Ondozero is a lake-reservoir in the central part of the Republic of Karelia. It refers to the basin of the Vyg River flowing into the White Sea. The lake area is 182 km2 . The lake length is 30 km, the width is 13 km, the average depth is 3.3 m, the maximum depth is 8 m. The water storage volume is 0.6 km3 . The total area of 54 islands located within the lake is 10.6 km2 . The Ondozero ranks no. 15 in the Republic of Karelia and no. 70 in Russia in terms of the water surface area. The Vyg River tributary — the Onda River — flows through the lake. The Onda River flow is dammed with a timber-floating dam in the river headwaters, and the lake is transformed into the water-storage reservoir. The lake is used for hydropower industry (regulation of the Vygsky Cascade which consists of five hydroelectric power plants: Ondskaya, Palokorgskaya, Matkozhnenskaya, Vygostrovskaya, Belomorskaya), for the needs of the local population, commercial and recreational fishing. The lake is exposed to small anthropogenic pollution; the water characteristics are mostly close to natural state [10].

4 Results of Assessment of Water Reservoirs Stability for Changes in Natural and Anthropogenic Mode Parameters 4.1 Assessment of Water Reservoir Stability Based on PIA Method Lake Vygozero • Category 6 according to physicogeographical and morphometric characteristics; • Category 1 according to the first group of hydrological characteristics (level and temperature conditions); • Category 2 according to the second group of hydrological characteristics (water exchange conditions);

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• Water quality corresponds to Class III and is mesotrophic by the trophic status. Vulnerability class is IB. Type of vulnerability by water quality: Class III of water quality corresponds to 5 points. The sum of points for the vulnerability family and the vulnerability type by water quality is 9 points. The water reservoir is referred to stability Class I, therefore, it has maximum stability for changes in the natural and anthropogenic mode parameters. Lake Segozero • Category 1 according to physicogeographical and morphometric characteristics; • Category 2 according to the first group of hydrological characteristics (level and temperature conditions); • Category 2 according to the second group of hydrological characteristics (water exchange conditions); • Water quality corresponds to Class II and is mesotrophic by the trophic status. Vulnerability class is IA. Type of vulnerability by water quality: Class II of water quality corresponds to 8 points. The sum of points for the vulnerability family and the vulnerability type by water quality is 16 points. The water reservoir is referred to stability Class II, therefore, it has above intermediate stability for changes in the natural and anthropogenic mode parameters. Lake Ondozero • Category 6 according to physicogeographical and morphometric characteristics; • Category 1 according to the first group of hydrological characteristics (level and temperature conditions); • Category 3 according to the second group of hydrological characteristics (water exchange conditions); • Water quality corresponds to Class II and is mesotrophic by the trophic status. Vulnerability class is IIA. Type of vulnerability by water quality: Class II of water quality corresponds to 8 points. The sum of points for the vulnerability family and the vulnerability type by water quality is 21 points. The water reservoir refers to stability Class III, therefore, it has intermediate stability for changes in the natural and anthropogenic mode parameters. 4.2 Assessment of Water Reservoir Stability Based on CIM Method Within the study, an integral index was developed to assess the water reservoirs stability for changes in natural and anthropogenic mode parameters. The integral indicators were built based on composite indicators method. The following indicators were chosen as the basis of the classification model to build the integral index in order to assess the water reservoir stability for changes in the natural mode parameters: surface area, km2 ; volume, km3 ; maximum depth, m; average water temperature in summer, °C; duration of freezing period, months; vertical mixing, the number of times per year; water exchange coefficient; amplitude of level

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fluctuations, m; the presence of seasonal stratification, points; flow conditions, points; nature of damming, points. Indicators to assess the water reservoir stability for changes in the anthropogenic mode parameters: dissolved oxygen, percentage of saturation; BOD5 , mgO2 /l; COD, mgO2 /l; color, deg.; degree of acidification, pH; transparency, m; the average biomass of phytoplankton during the growing season. Lake Vygozero. Following the results of assessment of the stability for changes in the mode parameters based on the CIM method, it was found that Lake Vygozero has intermediate stability, Class III, for changes in the natural mode parameters and for changes in water quality and eutrophication. Lake Segozero. Following the results of assessment of the stability for changes in the mode parameters based on the CIM method, it was found that Lake Segozero has above intermediate stability, Class II, for changes in the natural mode parameters and for changes in water quality and eutrophication. Lake Ondozero. Following the results of assessment of the stability for changes in the mode parameters based on the CIM method, it was found that Lake Ondozero has above intermediate stability, Class II, for changes in the natural mode parameters and for changes in water quality and eutrophication. Figures 1 and 2 show the results of assessment of the water reservoir stability for changes in the natural mode parameters and for changes in water quality based on the PIA and CIM methods.

Fig. 1. Results of assessment of transformed lakes stability for changes in natural mode parameters and for changes in water quality based on PIA method.

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Fig. 2. Results of assessment of transformed lakes stability for changes in natural mode parameters and for changes in water quality based on CIM method.

5 Conclusion The studied Lake Vygozero, Lake Segozero and Lake Ondozero are anthropogenically transformed water reservoirs. For the water bodies under consideration, the main sources of anthropogenic impacts and contamination are Segezha PPM and HPP. The assessment of stability for changes in natural and anthropogenic mode parameters of the water bodies was performed using two methods. Following the results of the stability assessment based on the PIA method: – Lake Vygozero corresponds to stability Class I, i.e. has maximum stability for changes in the parameters and modes; – Lake Segozero corresponds to stability Class II, i.e. has above intermediate stability for changes in the parameters and modes; – Lake Ondozero corresponds to stability Class III, i.e. has intermediate stability for changes in the parameters and modes. Following the results of the stability assessment based on the CIM method: – Lake Vygozero corresponds to stability Class III, i.e. has intermediate stability for changes in the parameters and modes; – Lake Segozero corresponds to stability Class II, i.e. has above intermediate stability for changes in the parameters and modes; – Lake Ondozero corresponds to stability Class II, i.e. has above intermediate stability for changes in the parameters and modes.

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The integral indices was developed within the study to assess the water reservoirs stability for changes in natural and anthropogenic mode parameters. The integral indicators were built based on composite indicators method. The point-index method is the reconnaissance stage required for justification and selection of assessment parameters, building of rating scales, understanding of the assessment results; however, it is often insufficient for objective assessment of the stability of the studied water body. The composite indicators method enables to develop scales of integral assessment of the system properties based on the existing classifications according to the larger list of criteria selected by a researcher at his own discretion as the case may be. In addition, the CIM method enables to trace the spatial-temporal dynamics of changes both between the classes and within one class.

References 1. Rozenberg, G.S., Zinchenko, T.D.: The sustainability of aquatic ecosystems: an overview of the problem. Arid Ecosyst. 4(4), 234–243 (2014). https://doi.org/10.1134/S20790961140 40106 2. Shashulovskaya, E.A., Mosiyash, S.A.: Some approaches to the assessment of the ecological state of different-type reservoirs based on the relationship among their main hydrochemical parameters. Povolzhskiy J. Ecolo. 3, 371–383 (2019). https://doi.org/10.35885/1684-73182019-3-371-383 3. Dmitriev, V.V., Fedorova, I.V., Birykova, A.S.: Approaches to assessment and GIS mapping of sustainability and environmental well-being of geosystems. Part IV. Integrated assessment of ecological well-being of terrestrial and aquatic ecosystems. Vestnik of Saint-Petersburg University 7(2), 37–53 (2016). https://doi.org/10.21638/11701/spbu07.2016.204 4. Tretyakov, V., Dmitriev, V., Sergeev, Yu., Kulesh, V.: Monitoring of an aquatic ecosystem ecological status and assessment of its resistance to anthropogenic impacts by results of simulation. In: 19th International Multidisciplinary Scientific Geoconference SGEM 2019 Conference proceedings, pp. 485–492. (2019). https://doi.org/10.5593/sgem2019/5.1/ s20.061 5. Amaro Medina, D.R., Dmitriev, V.V.: Approaches to assessment and GIS-mapping of sustainability and environmental well-being of geosystems. Integral assessment of ecological status of fluvial systems. Vestnik of Saint Petersburg University 64(2), 162–184 (2019). https://doi. org/10.21638/spbu07.2019.201 6. Burlov, V.G., Lepeshkin, O.M., Lepeshkin, M.O., Gomazov, F.A.: The control model of safety management systems. In: IOP Conference Series: Materials Science and Engineering, vol. 618(1) (2019). https://doi.org/10.1088/1757-899x/618/1/012088 7. Dmitriev, V.V., Ogurtsov, A.N., Hovanov, N.V., Osipov, G.K., Kulesh, V.P., Sergeyev, Yu.N., Fedorova, I.V.: Integral assessment of condition and sustainability of socio-ecologicaleconomic systems. In: Landscape Modelling and Decision Support. Innovations in Landscape Research, pp. 49–78 (2020). https://doi.org/10.1007/978-3-030-37421-1_4 8. Litvinenko, A.V., Filatov, N.N., Bogdanova, M.S., Karpechko, V.A., Litvinova, I.A., Salo, Y.A.: Anthropogenic transformation and economic use of Lake Vygozero. Water Resour. 41(4), 454–463 (2014). https://doi.org/10.7868/S0321059614040105

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9. Filatov, N.N., Litvinenko, A.V., Bogdanova, M.S.: Water resources of the Northern economic region of Russia: the state and use. Water Resour. 43(5), 779–790 (2016). https://doi.org/10. 7868/S0321059616050059 10. Bulavina, A.S.: Features of river runoff formation in the lake-river water collection systems in the western part of the White Sea. Arct. Environ. Res. 17(3), 161–172 (2017). https://doi. org/10.17238/issn2541-8416.2017.17.3.161

Studying Ceramic Bricks Production Possibility Basing on Low-Plasticity Clay and Galvanic Sludge Addition Anastasiya Kolosova , Evgeniy Pikalov , and Oleg Selivanov(B) Vladimir State University named after A.G. and N.G. Stoletovs, Gor’kogo, 87, 600000 Vladimir, Russia [email protected]

Abstract. The research objective was to develop new ceramic material containing lanthanum compound. The resulting material can be used for phosphate ions removal from local eutrophicated aquatic ecosystems. The release of lanthanum compound in the developed ceramic material occurs not only from its surface, but also from the depth due to the additional porosity of the ceramic sample produced with the chalk introduction into the charge composition, thus providing the increase of the developed material service life. Compressive strength and porosity of the developed samples were determined using standard methods for ceramic products. Phosphate ions concentrations changes in aqueous model solutions in contact with the developed ceramic material were determined by capillary electrophoresis. The ceramic samples toxicity was determined applying the method of Daphnia magna Straus mortality. The optimal material composition has been developed, its physical and mechanical characteristics have been determined, and the binding ability of the developed ceramic material with lanthanum compound with respect to phosphate ions has been studied. The results on the developed material toxicity and its complete environmental safety are presented. It was proposed to use this clay for the production of ceramic material, containing lanthanum compounds, for small natural and artificial water bodies: ponds, pools, aquariums, decorative reservoirs, fountains, etc. Keywords: Eutrophication · Phosphate ions · Lanthanum compound · Low plasticity clay

1 Introduction It is wildly known that one of the main elements contributing to the process of the aquatic ecosystems eutrophication is phosphorus of biogenic origin. Its concentration increase in natural water bodies occurs due to both accumulation of natural organic matter, dead aquatic plants, fallen leaves, products of fish and waterfowl, and to the intensive pollution of water bodies with organic substances contained in the agricultural enterprises waste waters. Large amounts of phosphorus get into the water bodies with household © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 419–425, 2021. https://doi.org/10.1007/978-3-030-57453-6_38

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effluents in the form of phosphorus-containing compounds - the basis of synthetic detergents - which are difficult to remove from water [1–3]. The result of these negative processes is active water weeding, overgrowing with blue-green algae of both natural and artificial water bodies. Toxins from blue-green algae significantly threaten invertebrates, fish, and other aquatic animals. The microflora species composition of water bodies changes greatly, the number of useful microorganisms decreases but the amount potentially dangerous microorganisms increases. Microbial and other self-purification processes in water bodies are suppressed but their degradation accelerates. Phosphate pollution of water in marine and freshwater aquariums, water basins reproducing natural aquatic ecosystem for fish and marine animals, occurs due to the intensive feeding of hydrobionts, which causes the inhibition of calcium producing organisms’ development [3–5]. The modern methods used to eliminate these harmful phenomena for aquatic ecosystems are not perfect. The application of various protective agents: copper sulfate, polyacrylamide, various coagulants, adsorbents - causes the death of aquatic organisms and fish, so the search and development of new effective means and materials is an urgent task. This report presents the research dealing with the purification of local eutrophicated aquatic ecosystems from phosphate ions using ceramic material containing lanthanum compound.

2 Materials and Methods The clay from Suvorotskoye deposit of the following composition was used for the research (wt.%): SiO2 = 67.5; Al2 O3 = 10.75; Fe2 O3 = 5.85; CaO = 2.8; MgO = 1.7; K2 O = 2.4; Na2 O = 0.7. According to the composition, aluminum oxide content is insignificant, it indicates clay low plasticity [6–8]. Thus it can hardly be used as a raw material in the construction industry for the production of high-quality ceramic products and the range of its application is rather limited. Such clay can be used for the construction ceramic products (bricks, tiles) production only after its modification with various additives [9–11]. The authors propose to use this clay for the production of ceramic material, containing lanthanum compounds, as a kind of bottom soil for small natural and artificial water bodies (ponds, pools, aquariums, decorative reservoirs, fountains, etc.) that are subject to eutrophication, in order to remove phosphate ions from water. Lanthanum carbonate La2 (CO3)3 (TU 6-09-4770-79) was applied as an additive to the charge for binding phosphate-ions. The fine-disperse chalk of M5 brand (TU 5743-001-22242270-2002) containing CaCO3 of at least 98.0 wt.% was used as a gas-forming additive to increase the material porosity, Prior the research, the clay was dried, crushed, and the fraction of max 0.63 mm particle size was selected for further experiments. The prepared clay was mixed with the specified amounts of lanthanum carbonate. The material samples were made in cubes of 50 mm side using semi-dry pressing technology at the molding humidity of 8 wt.% at a specific pressing pressure of 20 MPa and a firing temperature of 1100 °C. The samples were produced and tested in series of three samples each. Compressive strength (σcmp , MPa) and porosity (P, %) of the developed samples were determined using standard methods for ceramic products. Phosphate ions concentrations

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changes in aqueous model solutions in the in contact with the developed ceramic material were determined by capillary electrophoresis using “Kapel-104” device. The ceramic samples toxicity was determined applying the method of Daphnia magna Straus mortality under the influence of toxic substances in the aqueous extract from the studied ceramic samples, compared to the controlling culture in samples without toxic substances (control).

3 Results At the first research stage, the impact of the chalk content on the physical and mechanical properties of the resulting ceramic material was studied. The results of the experiments are shown in Fig. 1 and 2. The data in Fig. 1 demonstrates that the increase of the chalk content in the charge causes the decrease in ceramic material strength and increase of its porosity. It depends on the fact that chalk is basically represented by calcium carbonate, which decomposes at the temperature range of 900–1000 °C, causing the formation of carbon dioxide and voids in the material. At the same time, when the chalk content exceeded 5 wt.%, strength characteristics weaken considerably, so for further experiments it was decided to use charge compositions with chalk content of 5 wt.%.

Fig. 1. Dependence of the studied ceramics properties on the chalk content in the charge.

The second stage of the research was devoted to the influence of lanthanum carbonate content on the ceramics properties produced on the basis of the chalk containing charge. The results of determining the samples properties from the developed compositions are presented in Fig. 2. According to the data presented in Fig. 2, the increase of the lanthanum carbonate content in the charge causes the ceramic samples porosity increase, since additional carbon dioxide is released during the decomposition of lanthanum carbonate. Meanwhile, the samples strength characteristics slightly change.

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Fig. 2. Dependence of ceramics properties produced from charge, containing 5 wt.% of chalk from lanthanum carbonate content.

At the third research stage, ceramic material samples were placed in aqueous model solutions with phosphate ions concentration of 5 mg/l. The experiments were carried out in static mode during 14 days at 1:10 ratio of ceramic material, containing lanthanum carbonate, and model solution. Model solutions were sampled for testing the changes in phosphate ions concentrations in 3, 7, 11, 14 days. The research results dealing with determining the changes in phosphate ions concentrations in aqueous model solutions contacting ceramic material are shown in Fig. 3.

Fig. 3. Changes in phosphate ions concentrations of aqueous model solutions contacting ceramic material.

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The resulting data revealed that the smallest decrease in phosphate ions concentration occurred when the model solution was contacting the sample of the charge containing 2 wt.% of lanthanum carbonate (composition 1). Such insignificant effect can be explained by the small amount of lanthanum compound formed in the ceramic material during firing, which is not enough for phosphate ions binding in the model solution as insoluble compounds. Phosphate ions content in the model solution contacting the sample, made from the charge containing 4 wt.% of lanthanum carbonate (composition 2), decreased by more than 2 times. Almost complete purification of the model solution from phosphate ions occurred during the experiments with the samples of the charge containing 6 and 8 wt.% of lanthanum carbonate (compositions 3 and 4). A slight decrease in phosphate ions concentration in the aqueous media, contacting ceramic samples during the first seven days, can be explained by the processes occurring in the material when immersing into the water. Lanthanum compounds in the sample surface layers and on the pores surface interact with water and form an adsorbed layer of lanthanum hydroxide. Lanthanum hydroxide in turn reacts with carbon dioxide dissolved in water to form lanthanum carbonate. All these processes occur gradually and phosphate ions are absorbed more effectively alongside the formation of sparingly soluble compounds simultaneously with the increase of lanthanum carbonate amount formed in the material surface layers. At the fourth stage of the research, the toxicity of ceramic material samples was determined. Extracts from samples were prepared by leaching the pieces of ceramic material samples with cultivation water at the ratio of 1:10. The resulting mixture was stirred and kept during 16 h. Biotesting was performed at pH = 7.2–7.6, temperature of 20 ± 2 °C, and dissolved oxygen content of at least 6 mg/dm3. Toxicity of each sample was determined three times. The results of aqueous extracts toxicity study from samples based on the compositions are shown in Fig. 4.

Fig. 4. Dynamics of Daphnia death in aqueous extracts of different charge composition.

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The study of the acute toxic effect of aqueous extracts from the developed ceramic materials samples on Daphnia magna Straus by their mortality (the acute toxicity criterion was 50% or more Daphnia death during 96 h) showed that the sample based on the charge containing lanthanum carbonate in an amount of 8 wt.% (composition 4) was the most toxic. The ceramic material samples based on the charge containing lanthanum carbonate 2–6 wt.% did not cause the death of 50% of Daphnia during 100 h of exposure, indicating no toxicity of these samples and environmental safety for living organisms.

4 Conclusions According to the research results the ceramic material produced from the low-plasticity clay of the Suvorotskoye deposit with the addition of 6 wt.% lanthanum carbonate and 5 wt.% of chalk, has shown its effectiveness in removing phosphate ions from aqueous model solutions, creating prerequisites for its use in real conditions for purifying local eutrophied aquatic ecosystems. The release of lanthanum compound in the developed ceramic material occurs not only from its surface, but also from the depth due to the additional porosity of the ceramic sample produced with the chalk introduction into the charge composition, thus providing the increase of the developed material service life. Herewith as a result of prolonged action, lanthanum compound concentration fluctuations decrease allowing for gradual binding of phosphate ions in the aquatic ecosystem without harming hydrobionts, in contrast to the liquid specimen with lanthanum, when significant risk of immediate introduction of high dose of lanthanum occurs. The developed material can be used as a bottom soil or decorative water ceramics, as it is not toxic and can be recommended as an environmentally safe material.

References 1. Hamdi, N., Srasra, E.: Removal of phosphate ions from aqueous solution using Tunisian clays minerals and synthetic zeolite. J. Environ. Sci. 24(4), 617–623 (2012). https://doi.org/ 10.1016/S1001-0742(11)60791-2 2. Yu, Y., Chen, J.P.: Key factors for optimum performance in phosphate removal from contaminated water by a Fe–Mg–La tri-metal composite sorbent. J. Colloid Interface Sci. 445, 303–311 (2015). https://doi.org/10.1016/j.jcis.2014.12.056 3. Okada, K., Ono, Y., Kameshima, Y., Nakajima, A., MacKenzie, K.J.D.: Simultaneous uptake of ammonium and phosphate ions by compounds prepared from paper sludge ash. J. Hazard. Mater. 141(3), 622–629 (2007). https://doi.org/10.1016/j.jhazmat.2006.07.017 4. Luo, L., Duan, N., Wang, X.C., Guo, W., Ngo, H.H.: New thermodynamic entropy calculation based approach towards quantifying the impact of eutrophication on water environment. Sci. Total Environ. 603–604, 86–93 (2017). https://doi.org/10.1016/j.scitotenv.2017.06.069 5. Yang, Y., Wang, J., Qian, X., Shan, Y., Zhang, H.: Aminopropyl-functionalized mesoporous carbon (APTMS-CMK-3) as effective phosphate adsorbent. Appl. Surf. Sci. 427(Part B), 206–214 (2018). https://doi.org/10.1016/j.apsusc.2017.08.213 6. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Energy efficiency improving of construction ceramics, applying polymer waste. Adv. Intell. Syst. Comput. 983, 786–794 (2019). https://doi.org/10.1007/978-3-030-19868-8_77

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7. Shakhova, V.N., Berezovskaya, A.V., Pikalov, E.S., Selivanov, O.G., Sysoev, É.P.: Development of self-glazing ceramic facing material based on low-plasticity clay. Glass Ceram. 76(1–2), 11–15 (2019). https://doi.org/10.1007/s10717-019-00123-4 8. Kolosova, A., Sokolskaya, M., Pikalov, E., Selivanov, O.: Production of facing ceramic material using cullet. In: E3S Web of Conferences, vol. 91, p. 02003 (2019). https://doi.org/10. 1051/e3sconf/20199102003 9. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Development of environmentally safe acid-resistant ceramics using heavy metals containing waste. In: MATEC Web of Conferences, vol. 193, pp. 03035 (2018). https://doi.org/10.1051/matecconf/201819303035 10. Shakhova, V.N., Vitkalova, I.A., Torlova, A.S., Pikalov, E.S., Selivanov, O.G.: Receiving of ceramic veneer with the use of unsorted container glass breakage. Ecol. Ind. Russia 23(2), 36–41 (2019). https://doi.org/10.18412/1816-0395-2019-2-36-41 11. Shakhova, V., Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Development of composite ceramic material using cullet. In: MATEC Web of Conferences, vol. 193, p. 03032 (2018). https://doi.org/10.1051/matecconf/201819303032

Ceramic Bricks Production Basing on Low-Plasticity Clay and Galvanic Sludge Addition Anastasiya Kolosova , Evgeniy Pikalov , and Oleg Selivanov(B) Vladimir State University named after A.G. and N.G. Stoletovs’, Gor’kogo, 87, 600000 Vladimir, Russia [email protected]

Abstract. The research objective was to assess the possibility of producing ceramic bricks based on low-plasticity clay available in the Vladimir region with the addition of galvanic sludge. The experimental results for studying physical and mechanical properties of ceramic bricks based on the developed composition, including low-plasticity clay of the Suvorotskoye deposit in the Vladimir region and galvanic sludge from the local enterprise, are presented. The following material properties determined according to the standard methods were considered: density, compressive strength, porosity and water absorption. Additionally, the results of material toxicity assessment using the determination method for Daphnia magna Straus mortality under the impact of toxic substances in water extract from the studied ceramic samples are presented. Due to the drastic decrease in strength characteristics and high toxicity of the resulting material, boric acid was introduced into the charge. This component choice is stipulated by the fact that even small amount of boric acid causes the formation of a vitreous phase during firing, thus increasing ceramics density and strength, and simultaneously hindering the heavy metals migration. As a result, strength characteristics were improved for the samples produced with the galvanic sludge introduction, and their toxicity was reduced reaching a satisfactory level. Thus, the developed composition based on the clay and galvanic sludge in the specified quantities with the addition of boric acid as a modifier can produce environmentally friendly high quality ceramic bricks. Keywords: Building ceramics · Low-plasticity clay · Galvanic sludge · Environmental safety

1 Introduction In terms of product yield, the construction materials production is one of the leading industries in Russia and construction products are of high demand at the market. The construction materials industry determines the effectiveness of the construction complex development, which ensures the growth of all regional economic sectors due to the © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 426–431, 2021. https://doi.org/10.1007/978-3-030-57453-6_39

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construction of industrial facilities. Besides it contributes to the solution of a number of social problems, such as updating housing funds and determining housing prices. One of the main wall construction materials is ceramic brick, though recently cheaper, but less durable and environmentally friendly materials are more often used. In this regard, it is necessary to develop technologies allowing high-quality ceramic bricks production at low cost [1–3]. Meanwhile it should be noted that construction bricks in Russia are mainly produced at the enterprises of relatively small production capacity basin on local raw materials. Therefore, it will be relevant to consider the possibility of producing ceramic bricks using local raw materials of poor quality, as well as secondary raw materials thus simultaneously solving the problem of industrial waste recycling [4–6]. The research objective was to assess the possibility of producing ceramic bricks based on low-plasticity clay available in the Vladimir region with the addition of galvanic sludge, which utilization is one of the most important problems for the region. Therefore, it is necessary to study the effect of the galvanic sludge in the ceramics composition on the principle physical and mechanical properties of the resulting material and choose the best charge composition ensuring high quality of products. Since galvanic sludge contains heavy metals and is an environmentally harmful waste of 2–3 hazard class [5–7], it was necessary to make experiments confirming environmental safety of the resulting ceramic material.

2 Materials and Methods The clay from Suvorotskoye deposit of the following composition was used for the research (wt.%): SiO2 = 67.5; Al2 O3 = 10.75; Fe2 O3 = 5.85; CaO = 2.8; MgO = 1.7; K2 O = 2.4; Na2 O = 0.7 [8, 9]. Aluminum, calcium, and magnesium oxides in the clay composition indicated it low plasticity. Galvanic sludge from the industrial enterprise “Avtopribor Plant” (Vladimir) after the waste water treatment of electroplating processes with the 60 to 70% moisture was introduced into the charge. The sludge contains the following compounds (wt.%): Zn(OH)2 ≈ 11.3%; SiO2 ≈ 7.08%; Ca(OH)2 ≈ 16.52%; Cr(OH)3 ≈ 9.31%; (Fe2+ )Cr2 S4 ≈ 4.17%; CaCO3 ≈ 40.25%; CaO ≈ 3.45%; ZnO ≈ 2.41%; Cu(OH)2 ≈ 2.38%; Ni(OH)2 ≈ 2.62%; Mn(OH)2 ≈ 0.64%; Pb(Oh)2 ≈ 0.14% [5]. Relatively large amount of zinc and chromium compounds in the composition confirms this sludge toxicity. Prior the research, the materials were dried, crushed, and the fraction of max 0.63 mm particle size was selected for preparing raw material mixture used in the experiments. The samples were prepared applying semi-dry pressing technology at the molding charge moisture of 8 wt.%, under specific pressing pressure of 15 MPa and firing temperature of 1050 °C. The material samples were made in series in the cubes shape of 50 mm side. Every series consisted of three samples. To assess physical and mechanical properties of ceramic materials samples, density (ρ, kg/m3 ), compressive strength (σcmp , MPa), porosity (P, %) and water absorption (WA, %) have been determined in compliance with the standard methods. Ceramics toxicity has been determined according to death Daphnia magna Straus method under the impact of toxic substances in the water extract from the studied samples.

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3 Results The results of determining the samples physical and mechanical properties produced after the introduction of sludge (GS) into the charge in different proportions are shown in Fig. 1 and 2. The data in Fig. 1 shows that the increase of galvanic sludge in the charge causes density and strength decrease of the resulting ceramic material. It depends on the fact that the galvanic sludge composition includes compounds decomposing at high temperatures with the formation of gases and water vapor accompanied by the formation of pores and voids in the sample depth, so the material porosity and water absorption increase. It is proved by the data in Fig. 2. During the experiment on toxicity determination for all the studied compounds, over 50% of Daphnia death was recorded, thus indicating high ratio of heavy metals migration.

Fig. 1. The studied samples density and compressive strength.

In this regard, it has been decided to limit the galvanic sludge amount to 2.5 wt.% and add boric acid to the charge as a modifying additive. This component choice is stipulated by the fact that even small amount of boric acid causes the formation of a vitreous phase during firing, thus increasing ceramics density and strength [10–12], and simultaneously hindering the heavy metals migration [5].

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Fig. 2. The studied samples porosity and water absorption.

The experimental results on compositions with different amounts of boric acid (BA), introduced separately or combined with galvanic sludge into the charge, are shown in Table 1. Table 1. Physical and mechanical properties of modified ceramic bricks. Sample

Content, wt.% BA

Density, kg/m3

Compression strength, MPa

Porosity, %

GS

Water absorption, %

1

–

1

2090.3

21.6

5.9

6.3

2

–

2

2139

22.1

5.2

5.4

3

2.5

1

2051.6

21.2

8.2

9.7

4

2.5

2

2089.3

21.8

7.7

8.9

5

2.5

–

1996.9

13.0

9.1

10.1

The results of toxicity determining in samples produced basin on the compositions indicated in Table 1 are shown in Fig. 3. According to Fig. 3, the increase of boric acid content (compositions 1 and 2) causes material toxicity increase, and, consequently, this component increase is not advisable. The introduction of 2 wt.% of boric acid into the charge composition combined with galvanic sludge (composition 4) makes it possible to produce ceramic material with satisfactory toxicity.

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Fig. 3. Toxicity assessment of the studied compositions.

4 Conclusions Thus, the research results prove the possibility of producing high-quality ceramic bricks based on low-plasticity clay from the Vladimir region Deposit with the introduction of 2.5 wt.% of galvanic sludge from the enterprise “Avtopribor Plant” PLC (Vladimir) and 2 wt.% of boric acid. In comparison with the check composition produced only on the basis of the studied clay, the developed composition allows manufacturing the material characterized by the increased strength (from 14.3 to 21.8 MPa). At the same time, toxic waste from the local industrial enterprise can be applied to the production of environmentally safe construction material.

References 1. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Energy efficiency improving of construction ceramics, applying polymer waste. Advances in Intelligent Systems and Computing, vol. 983, pp. 786–794 (2019). http://doi.org/10.1007/978-3-030-19868-8_77 2. De Silva, G.H.M.J.S., Hansamali, E.: Eco-friendly fired clay bricks incorporated with porcelain ceramic sludge. Constr. Build. Mater. 228, 116754 (2019). https://doi.org/10.1016/j.con buildmat.2019.116754 3. Rehman, M.U., Ahmad, M., Rashid, K.: Influence of fluxing oxides from waste on the production and physico-mechanical properties of fired clay brick: a review. J. Build. Eng. 27, 100965 (2020). https://doi.org/10.1016/j.jobe.2019.100965 4. Cusidó, J.A., Cremades, L.V.: Environmental effects of using clay bricks produced with sewage sludge: leachability and toxicity studies. Waste Manag. 32(6), 1202–1208 (2012). https://doi.org/10.1016/j.wasman.2011.12.024 5. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Development of environmentally safe acid-resistant ceramics using heavy metals containing waste. MATEC Web Conf. 193, 03035 (2018). https://doi.org/10.1051/matecconf/201819303035 6. Arsenovic, M., Radojevic, Z., Stankovic, S.: Removal of toxic metals from industrial sludge by fixing in brick structure. Constr. Build. Mater. 7, 7–14 (2012). https://doi.org/10.1016/j. conbuildmat.2012.07.002

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7. Magalhães, J.M., Silva, J.E., Castro, F.P., Labrincha, J.A.: Physical and chemical characterisation of metal finishing industrial wastes. J. Environ. Manage. 75(2), 157–166 (2005). https://doi.org/10.1016/j.jenvman.2004.09.011 8. Perovskaya, K., Petrina, D., Pikalov, E., Selivanov, O.: Polymer waste as a combustible additive for wall ceramics production. E3S Web Conf. 91, 04007 (2018). https://doi.org/10. 1051/e3sconf/20199104007 9. Shakhova, V.N., Vitkalova, I.A., Torlova, A.S., Pikalov, E.S., Selivanov, O.G.: Receiving of ceramic veneer with the use of unsorted container glass breakage. Ecol. Ind. Russia 23(2), 36–41 (2019). https://doi.org/10.18412/1816-0395-2019-2-36-41 10. Abi, C.B.E.: Effect of borogypsum on brick properties. Constr. Build. Mater. 5930, 195–203 (2014). https://doi.org/10.1016/j.conbuildmat.2014.02.012 11. Kolosova, A., Sokolskaya, M., Pikalov, E., Selivanov, O.: Production of facing ceramic material using cullet. E3S Web Conf. 91, 02003 (2019). https://doi.org/10.1051/e3sconf/201991 02003 12. Shakhova, V.N., Berezovskaya, A.V., Pikalov, E.S., Selivanov, O.G., Sysoev, É.P.: Development of self-glazing ceramic facing material based on low-plasticity clay. Glass Ceram. 76(1–2), 11–15 (2019). https://doi.org/10.1007/s10717-019-00123-4

Polymer-Ceramic Proton Exchange Membranes for Direct Methanol Fuel Cells Alexandra Chesnokova , Tatyana Zhamsaranzhapova , Sergey Zakarchevskiy , and Yuriy Pozhidaev(B) Irkutsk National Research Technical University, 83, Lermontov Str., 664074 Irkutsk, Russia [email protected]

Abstract. Proton-exchange composite membranes based on poly(vinyl alcohol)/BEA zeolite for direct methanol fuel cell were obtained. Poly(vinyl alcohol) was crosslinked with sulfosuccinic acid and doped with BEA zeolite. Proton conductivity, ion-exchange capacity, water uptake, swelling ratio, methanol permeability and mechanical properties of membranes were tested. An increase in the zeolite content leads to an increase in ion-exchange capacity and a decrease in water uptake and methanol permeability of membranes. The proton conductivity temperature dependence of composite membranes in the range from 30 to 80 °C and a 100% of relative humidity was studied. The best result was demonstrated by the membrane containing 25% BEA (proton conductivity −23.2 mS cm−1 , the activation energy −26 kJ mol−1 K−1 ). The tensile strength increases with the addition of zeolite in 4 times, and the elongation at break decreases in more than 5 times (25% BEA sample) as compared to the membrane without additives. Keywords: Direct methanol fuel cells · Proton-exchange composite membranes · Poly(vinyl alcohol) · Zeolite · Proton conductivity · Water uptake

1 Introduction Energy sources of the future should be environmentally acceptable and energy efficient. Thus, the development and application of electrochemical energy sources as fuel cells are great of importance [1, 2]. Direct methanol fuel cells (DMFCs) are promising owing to the highest energy conversion efficiency, and environmental safety [3, 4]. Direct methanol fuel cells (DMFCs) enables the conversion of the chemical energy stored in liquid methanol fuel to electrical energy, with water and carbon dioxide as byproducts. Compared to hydrogen fueled PEMFCs, DMFCs present several intriguing advantages [5, 6]. Membranes for operation in DMFCs must have high proton conductivity and ion-exchange capacity, low swelling ratio and methanol permeability, good chemical and mechanical stability [7]. A commercially available membrane Nafion meets these requirements. However, it is costly [8].

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 432–439, 2021. https://doi.org/10.1007/978-3-030-57453-6_40

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In recent years, alternative proton conducting membranes have been proposed. One of the alternative materials is poly(vinyl alcohol) (PVA) [1, 9]. Poly(vinyl alcohol) is a water soluble, semi-crystalline, fully biodegradable and non-toxic polymer. It is extensively used in paper coating, textile sizing, drug release and flexible water-soluble packaging films [9]. The non-toxicity of PVA, excellent film forming property, high oxygen and aroma barrier, good biocompatibility and high transparency have contributed to further stimulate the market growth of PVA in packaging with end-use segment exceeding more than 30% of the global market of PVA [10]. However, the undesirable properties of PVA, including poor solvent resistance, insufficient strength and the low heat stability, have restricted its wide applications [9]. PVA-based membranes crosslinked with SSA [10] showed proton conductivity values in the range of 10−3 to 10−2 S·cm−1 and demonstrate excellent electrochemical characteristics [1]. However, the PVA/SSA membranes can operate efficiently at low temperature as dehydratation process occurring at the temperature above 80 °C can cause problems with proton transfer. A great number of alternative strategies have been investigated for the development of proton conducting membranes in dehydrating environments, i.e., high temperatures and reduced relative humidity, such as composite organic–inorganic membranes [11]. The composite membranes are characterized by the incorporation of nanometric scale inorganic fillers, in which the filler-polymer interaction can range from strong (covalent and ionic bonds) to weak (physical interactions). The addition of an inorganic material in the polymer membrane often increase the chemical and mechanical stability and improve water uptake at higher temperatures increasing the membrane working temperature [12]. Beydaghi H. et al. [13] have developed organic–inorganic nanocomposite membranes based on PVA/SBA-15-propyl-SO3H, in which –SO3H groups were introduced by co-condensation as hydrophilic inorganic modifier. With addition of nanoporous silica, the nanocomposite membranes show higher water uptake and proton conductivity. Navarra M. A. et al. [14] have investigated the effect of a functionalized silica filler, having a –SO3H end-group, on cross-linked PVA membranes. It was demonstrated the inorganic compound effect in improving the stability of the membranes and in reducing the crystalline phase of the polymer matrix. Silica particles positive effect on the retention of the absorbed liquid phase (i.e., water) has been investigated by IR spectroscopy and 1H NMR. Conductivity values of the membranes were found to be in the order of 10−2 – 10−1 S cm−1 . Fuel cell tests on using the developed composite membranes as electrolytes have shown current and power levels which are comparable with those obtained in the same working conditions by adopting conventional membrane separators (i.e., Nafion 117). In this study, we have prepared PVA/SSA/BEA zeolite membranes and investigated their physicochemical properties (proton conductivity, ion-exchange capacity, water uptake, swelling ratio and mechanical properties) toward application in DMFC.

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2 Experimental 2.1 Synthesis of Membranes A 10% PVA solution was dissolved in distilled water at 90 °C for 6 h with constant stirring. Sulfosuccinic acid (SSA) (10 wt%) was added to PVC solution. The resulting mixture was stirred for 1 h at 40 °C, then BEA zeolite (1, 3, 5, 25%) was added and homogenized. To obtain a modified form of BEA zeolite, it was previously treated with a 0.5 M solution of sulfuric acid at a temperature of 70 °C for 4 h. The control sample was without zeolite. Membranes were formed by solvent casting method on a polyethylene terephthalate film. After evaporation of the solvent, the membranes were kept in an oven at 100 °C for 1 h. 2.2 Ion Exchange Capacity The ion-exchange capacity was determined by the method of reverse titration. The membrane samples were preliminary kept at 0.05 M NaOH for 24 h, then titrated by 0.05 M HCl using phenolphthalein as an indicator. 2.3 Water Uptake The samples were kept in a vacuum oven for 24 h at a temperature of 80 °C. The resulted membranes were than cooled and weighed. Distilled water and membrane samples were placed in a round bottom flask equipped with a reflux condenser so that they were completely covered with water and did not contact each other and the walls of the flask. The flask was placed in a thermostat and kept at temperatures of 30 and 100 °C for 24 h. After that the membrane samples were removed from the water, dried with filter paper and weighed. Water uptake was calculated as a percentage of dried sample weight using the formula: B = [(m1 – m)/m]100, where m, m1 is the mass of dried and wet sample, respectively, g. The average value of three experiments was taken as the result and rounded to 0.1%. 2.4 Proton Conductivity and Mechanical Properties of Membrane The proton conductivity of ion exchange membranes was investigated by impedance spectroscopy in the temperature range of 30–80 °C at 75% relative humidity on a Z3000 instrument (Elins, Russia) in C/membrane/C symmetrical cells. The measurements were conducted in the frequency range of 500–5 kHz. The mechanical properties of the membranes were studied on a Shimadzu AGS-X universal testing machine. Test specimens were prepared in the form of a rectangle of a 25 × 60 mm size. The specimens were tested in the dry state and conditioned prior at 23 °C and 50% relative humidity for 24 h. The tests were conducted at a crosshead speed of 1 mm min-1. The continuous measurement of the load and elongation of the specimens was performed in an automated mode. The modulus of elasticity was determined using the dedicated software.

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3 Results and Discussion PVA was used as a polymer matrix for membrane synthesis. Bare PVA have good electro isolating properties. Various sulfonating agents such as concentrated sulfuric acid, sulfosuccinic acid, sulfophthalic acid, sulfoacetic acid and chlorosulfonic acid can be used to provide proton conductive properties to PVA [10, 15–20] to make it suitable for DMFC application. However modified PVA have excellent water solubility, thus the crosslinking of the polymer is required [9, 21]. There are different methods for PVA crosslinking, including physical, chemical and radiation methods [1]. Variety of chemical reagents as sulfosuccinic acid, poly(acrylic acid), glutaraldehyde has been employed for cross linking PVA. PVA and sulfosuccinic acid were used as the main matrix and as the source of ionogenic groups, respectively, in order to get crosslinked PVA–SSA esters through the esterification reaction between the hydroxyl groups of PVA and the carboxylic acid groups of SSA (Fig. 1) [14, 22].

Fig. 1. The scheme of PVA-SSA etherification reaction.

The BEA type zeolite additive modificated with sulfuric acid solution was introduced into polymeric PVA-SSA matrix in the form of powder. As BEA is a high silica zeolite, it determines its acid resistance. The BEA zeolite is an aluminosilicate with large pores, it was first synthesized using the tetraethyl ammonium cation as a structure-forming agent [23]. Ion-exchange capacity (IEC) of a membrane determines the ability displace ions included to the membrane structure by oppositely charged ions present in the surrounding solution. IEC values for PVA/SSA/BEA membranes with a content of BEA 1%, 3%, 5% and 25% are 1.5, 2.4, 2.8 and 2.9 mmol/g, respectively. The IEC for the membrane without zeolite additive was 0.95 mmol/g. Therefore, doping of the membrane with BEA zeolite leads to a significant increase in the ion-exchange activity of the membranes. Water uptake (WU) of membranes plays an important role in the process of proton migration, and also influences on the mechanical properties of membranes. It was observed, the zeolite content increase in the membrane composition, lead to water uptake

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decreasing. The greatest decrease in WU was observed for the PVA/SSA/BEA membrane with a zeolite content of 25% BEA. When the membrane is wet, its linear dimensions increased by 2–5%, and the thickness increase by 13–29% depending on BEA content. The swelling ratio values change with an increase in the zeolite content which correlates well with the amount of water uptake. An increase in the zeolite content leads to a decrease in the swelling ratio of the membranes. One of the main characteristics of membranes is proton conductivity, which was determined by impedance spectroscopy in the temperature range from 30 to 80 °C at 100%. The introduction of BEA zeolite in the composition of PVA/SSA membranes leads to an increase in the proton conductivity (Table 1). The enhance of composite membrane proton conductivity by doping with ceramic fillers has been noted in a number of studies [1, 24]. It is known that ion-exchange membranes consisting of a dispersed zeolite phase and a continuous PVA phase are characterized by the formation of additional proton transport channels along the polymer-ceramic interface [1]. According to the temperature dependence of proton conductivity, the activation energy (Ea) of the proton transfer process was calculated using the Arrhenius equation. Compared to Nafion (Ea is 22.8 kJ/mol), the activation energy for PVA/SSA/BEA composite membranes is slightly higher and has values of 26–27 kJ/mol (Table 1), except of the PVA/SSA/5% BEA membrane (Ea is 16 kJ/mol) (Table 1), which is significantly lower than for Nafion. Therefore, the zeolite content has a significant effect on both proton conductivity and activation energy. The mechanical properties of the membranes were investigated. At a temperature of 23 °C and a relative humidity of 50% the tensile strength of membranes is increased with BEA zeolite content. When compared with a membrane without additives, the tensile strength increases with the addition of 25% BEA zeolite in 4 times and the elongation at break decreases in more than 5 times (Table 1). Table 1. Proton conductivity, activation energy and mechanical analysis of membranes. Membrane

Proton conductivity (mS sm−1 )

Activation energy (kJ mol−1 K−1 )

Modulus of elasticity (MPa)

Tensile strength (MPa)

Relative elongation to break (%)

PVA/SSA

10.9

23

52

3

290

PVA/SSA/BEA (1%)

18.7

27

50

4

91

PVA/SSA/BEA (3%)

11.9

26

42

5

87

PVA/SSA/BEA (5%)

8.6

16

34

10

54

PVA/SSA/BEA (25%)

23.2

26

22

12

52

In addition to high proton conductivity, the basic requirement for the PEM’s for DMFC application is high methanol permeation resistance. It was found that the

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methanol permeability of PVA/SSA/BEA membranes decreased with increasing BEA content. Zeolite particles block part of the hydrophilic polymer channels in the composite membranes structure, providing a low level of methanol permeability. Methanol permeability for the PVA/SSA membrane is found to be 2.27 × 10−6 cm2 S−1 , which reduces to 6.91 × 10−7 cm2 S−1 for PVA/SSA/BEA(25%) membrane.

4 Summary Biodegradable proton-exchange composite membrane poly (vinyl alcohol)/BEA zeolite for direct methanol fuel cell were prepared. Polyvinyl alcohol was crosslinked with sulfosuccinic acid to improve its physicochemical properties and introduce ionogenic SO3 H groups to the membrane structure. Proton conductivity, ion-exchange capacity, water uptake, swelling ratio, methanol permeability and mechanical properties of membranes were investigated. The ion-exchange capacity of the membranes increases with an increase in the zeolite content. An increase in the zeolite content in the membrane leads to a decrease in water uptake and methanol permeability. The temperature dependence of the composite membranes proton conductivity in the range from 30 to 80 °C and 100% RH was studied. The best proton conductivity value (23.2 mS cm−1 ) was demonstrated by a membrane containing 25% BEA. Acknowledgments. The reported study was funded by RFBR, project number 18-08-00718. A. Chesnokova acknowledges financial support of INRTU (grant No 04-fpk-19).

References 1. Maiti, J., Kakati, N., Lee, S.H., Jee, S.H., Viswanathan, B., Yoon, Y.S.: Where do poly(vinyl alcohol) based membranes stand in relation to Nafion® for direct methanol fuel cell applications. J. Power Sources 216, 48–66 (2012). https://doi.org/10.1016/j.jpowsour.2012. 05.057 2. Dunn, S.: Hydrogen futures: toward a sustainable energy system. Int. J. Hydrogen Energy 27(3), 235–264 (2002). https://doi.org/10.1016/S0360-3199(01)00131-8 3. McNicol, B.D., Rand, D.A.J., Williams, K.R.: Direct methanol-air fuel cells for road transportation. J. Power Sources 83(1–2), 15–31 (1999). https://doi.org/10.1016/S0378-775 3(99)00244-X 4. Sun, H., Wang, W., Koo, K.-P.: The practical implementation of methanol as a clean and efficient alternative fuel for automotive vehicles. Inter. J. Engine Res. 20(3), 350–358 (2019). https://doi.org/10.1177/1468087417752951 5. Joghee, P., Malik, J., Pylypenko, S., O’Hayre, R.: A review on direct methanol fuel cells – In the perspective of energy and sustainability. MRS Energy Sustain. 2 (2015). https://doi.org/ 10.1557/mre.2015.4 6. Adamson, K.-A., Pearson, P.: Hydrogen and methanol: a comparison of safety, economics, efficiencies and emissions. J. Power Sources 86(1–2), 548–555 (2000). https://doi.org/10. 1016/S0378-7753(99)00404-8 7. Wang, Y., Chen, K.S., Mishler, J., Cho, S.C., Adroher, X.C.: A review of polymer electrolyte membrane fuel cells: technology, applications, and needs on fundamental research. Appl. Energy 88, 981–1007 (2011). https://doi.org/10.1016/j.apenergy.2010.09.030

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8. Dhanapal, D., Xiao, M., Wang, S., Meng, Y.: A review on sulfonated polymer composite/organic-inorganic hybrid membranes to address methanol barrier issue for methanol fuel cells. Nanomaterials 9(5), 668 (2019). https://doi.org/10.3390/nano9050668 9. Wong, C.Y., Wong, W.Y., Loh, K.S., Daud, W.R.W., Lim, K.L., Khalid, M., Walvekar, R.: Development of poly(vinyl alcohol)-based polymers as proton exchange membranes and challenges in fuel cell application: a review. Polym. Rev. 60(1), 171–202 (2020). https://doi. org/10.1080/15583724.2019.1641514 10. Ghorbel, N., Kallel, A., Boufi, S.: Molecular dynamics of poly(vinyl alcohol)/cellulose nanofibrils nanocomposites highlighted by dielectric relaxation spectroscopy. Compos. Part A Appl. Sci. Manuf. 124, 105465 (2019). https://doi.org/10.1016/j.compositesa.2019.05.033 11. Oliveira, P.N., Catarino, M., Müller, C.M.O., Brandão, L., Tanaka, P.D.A., Bertolino, J.R., Pires, A.T.N.: Preparation and characterization of crosslinked PVAL membranes loaded with boehmite nanoparticles for fuel cell applications. J. Appl. Polym. Sci. 131(18), 40148 (2013). https://doi.org/10.1002/app.40148 12. Tripathi, B.P., Shahi, V.K.: Functionalized organic-inorganic nanostructured N-p-carboxy benzyl chitosan-silica-PVA hybrid polyelectrolyte complex as proton exchange membrane for DMFC applications. J. Phys. Chem. B 112(49), 15678–15690 (2008). https://doi.org/10. 1021/jp806337b 13. Beydaghi, H., Javanbakht, M., Badiei, A.: Cross-linked poly(vinyl alcohol)/sulfonated nanoporous silica hybrid membranes for proton exchange membrane fuel cell. J. Nanostruct. Chem. 4(2), 1–9 (2014). https://doi.org/10.1007/s40097-014-0097-y 14. Navarra, M.A., Fernicola, A., Panero, S., Martinelli, A.A., Matic, A.: Effect of functionalized silica particles on cross-linked poly(vinyl alcohol) proton conducting membranes. J. Appl. Electrochem. 38, 931–938 (2008). https://doi.org/10.1007/s10800-008-9498-2 15. Tutgun, M.S., Sinirlioglu, D., Celik, S.U., Bozkurt, A.: Investigation of nanocomposite membranes based on crosslinked poly(vinyl alcohol)–sulfosuccinic acid ester and hexagonal boron nitride. J. Polym. Res. 22, 47 (2015). https://doi.org/10.1007/s10965-015-0678-6 16. Kakati, N., Das, G., Yoon, Y.S.: Proton-conducting membrane based on epoxy resinpoly(vinyl alcohol)-sulfosuccinic acid blend and its nanocomposite with sulfonated multiwall carbon nanotubes for fuel-cell application. J. Korean Phys. Soc. 68(2), 311–316 (2016). https://doi.org/10.3938/jkps.68.311 17. Tomas, M., Remis, T., Gholami, F.: The determination of effective diffusion coefficient from the electrochemical impedance spectra of composite poly (vinyl alcohol) membranes. Environ. Prog. Sustain. Energy 38(5), e13195 (2019). https://doi.org/10.1002/ep.13195 18. Ajith, C., Deshpande, A.P., Varughese, S.: Proton conductivity in crosslinked hydrophilic ionic polymer system: competitive hydration, crosslink heterogeneity, and ineffective domains. J. Polym. Sci. Part B: Polym. Phys. 54(11), 1087–1101 (2016). https://doi.org/10.1002/polb. 24012 19. Li, H.Q., Liu, H.J., Wang, H., Yang, H., Wang, Z.Z., He, J.: Proton exchange membranes with cross-linked interpenetrating network of sulfonated polyvinyl alcohol and poly(2-acrylamido2-methyl-1-propanesulfonic acid): excellent relative selectivity. J. Membr. Sci. 595, 117511 (2010). https://doi.org/10.1016/j.memsci.2019.117511 20. Zhou, T., Li, Y., Wang, W.W., He, L., Cai, L., Zeng, C.: Application of a novel PVA-based proton exchange membrane modified by reactive black KN-B for low-temperature fuel cells. Intern. J. Electrochem. Sci. 14, 8514–8531 (2019). https://doi.org/10.20964/2019.09.16 21. Boroglu, M.S., Celik, S.U., Bozkurt, A., Boz, I.: The synthesis and characterization of anhydrous proton conducting membranes based on sulfonated poly(vinyl alcohol) and imidazole. J. Memb. Sci. 375(1–2), 157–164 (2011). https://doi.org/10.1016/j.memsci.2011.03.041 22. Kim, D.S., Park, H.B., Rhim, J.W., Lee, Y.M.: Proton conductivity and methanol transport behavior of cross-linked PVA/PAA/silica hybrid membranes. Solid State Ionics 176(1–2), 117–126 (2005). https://doi.org/10.1016/j.ssi.2004.07.011

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23. Rodionova, L.I., Knyazeva, E.E., Konnov, S.V., Ivanova, I.I.: Application of nanosized zeolites in petroleum chemistry: synthesis and catalytic properties (review). Pet. Chem. 59(4), 455– 470 (2019). https://doi.org/10.1134/S0965544119040133 24. Marcos-Madrazo, A., Casado-Coterillo, C., García-Cruz, L., Iniesta, J., Simonelli, L., Sebastián, V., Encabo-Berzosa, M.M., Arruebo, M., Irabien, A.: Preparation and identification of optimal synthesis conditions for a novel alkaline anion-exchange membrane. Polymers 10(18), 913 (2018). https://doi.org/10.3390/polym10080913

Improving the Reliability of Current Collectors of the Municipal Vehicles Valery Alisin(B) Mechanical Engineering Research Institute of the Russian Academy of Sciences, 4, M. Kharitonyevskiy lane, Moscow 101990, Russia [email protected]

Abstract. The article is devoted to extending the life of contact strips for collecting pantographs in electric traction vehicles by choosing the elemental composition of nanostructured crystals of partially stabilized zirconia for inserts. The effect of doping zirconia crystals with rare-earth elements on tribological properties is experimentally investigated. The hardness of the sample and crack resistance are evaluated by the method of kinetic micro-indentation. It has been established that alloying zirconia crystals is an effective method of increasing strength properties. Crystal samples were selected that showed the highest characteristics of crack resistance and hardness. Tribological tests of selected samples under dry sliding conditions were carried out on laboratory friction machines. The wear rate of surfaces for steady-state friction is directly proportional to the nominal pressure. The morphology and mechanism of wear of the friction surfaces after testing are investigated. The appearance of unevenly distributed films of secondary structures on the friction surface is shown. The use of zirconia inserts in contact strips will increase the wear resistance and allowable load on the prefabricated pantograph, which will reduce the potential of the arc discharge. A predicted elemental composition of zirconia-based material for a contact strip sleeve is proposed. Keywords: Electrical contact · Current collectors · Ceramic materials · Tribological tests

1 Introduction Efficiency and performance capabilities of municipal electrically propelled vehicles depend on the reliability and resource of current-collecting devices, in which the sliding electric contact bushings have the smallest service life. Bushings are manufactured of graphite-based materials. They have high electrical conductivity, good anti-friction properties, but also a very low wear resistance [1]. Wear-out of electrical contacts leads to disfunction and functional loss of the entire power transmission system. Electrical contact wear-out processes are diversified, however abrasive wear-out is the basic type of sliding contact wear-out [2]. The work [3] is dedicated to study of the electrical contact wear-out mechanism, which analyzed the degradation of the electrical contact resistance © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 440–449, 2021. https://doi.org/10.1007/978-3-030-57453-6_41

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associated with the wear-out process. It has been established that final polishing with aluminium oxide particles improves the contact electrical properties. The work [4] has analyzed the worn-out surfaces and wear debris through scanning electron microscopy method and energy dispersion spectrometer, and also considered the mechanism of contact surfaces wear-out. The work [5, 6] considers the wear-out phenomenon that arises in self-conjugated metal copper sliding contacts with a high current density in a damp carbon dioxide environment. The work [6] primarily proposes the models for calculating the wear-out rate, which can be utilized for approximate forecasting of wear-out of the contact wire and the pantograph strip. Impact of dynamic loads on the electrical contact operation has been studied in the work [7]. It has been established that the service life consists of three basic stages: plastic deformation stage; zero wear-out stage; measurable wear-out stage. Experimental observations of the wear-out pattern enabled to formulate the forecast method for the engineering analysis of impact wear-out. The work has elaborated the model of this subsurface mechanism which is further combined with the models of surface mechanisms in order to obtain the general model of the contact system sliding wear-out. The impact of surface microhardness has been studied in the work [8]. The work [9] presents the carbon composite reinforced with carbon fiber/copper mesh with a good electrical conductivity and wear resistance, which was manufactured using the chemical evaporation, impregnation and carbonation method. The outcomes have demonstrated that the composite wear resistance is significantly affected by the fiber orientation during current friction. The work [10] has analyzed the factors affecting the electrical contact resistance in the carbon nano-tube additive, the carbon nano-tube density, the electrical load, the frequency and amplitude of the load, of the vibrating load. The work discusses the role of carbon nano-tubes in reducing the electrical contact resistance in terms of lubrication and damping. The work [11] makes emphasis on the wear-out, friction and electrical properties of the newly elaborated disc-to-disc contact design for sliding electrical contacts. Different types of graphite and copper, as material combination, the contact different operating parameters and, in particular, different directions of the electric current, that is, the disk polarity, have been studied under the actual contact conditions in a special tribological test facility. The work [12] has studied the impact of transient resistance on the electrical contact wear-out. The works [13, 14] have considered the impact of electric current on friction and wear-out in sliding contacts of the composite material relative to a metal. It is demonstrated that this effect is similar to the contact lubrication, however there are certain differences in the tribological pattern of the materials with a plastic binder. Similar results are obtained in the work [15], which has considered the impact of humidity, speed, and service life on the friction and electrical properties. The basic outcomes of both tribological and electrical studies can be associated with the properties of self-lubricating layers. The paper [16] presents the outcomes of the work and tribological mechanisms in the new design of the electric sliding contact in terms of the sliding speed, standard force and electric current throughout the 24-h experiments. Tribo-film formation in almost all contacts, which leads to the temperature reduction at the contact has been established. It is known [17] that the solid lubricant films are applied to the friction surface using the magnetron sputtering method in order to increase the contact wear resistance. Ionic fluids have been used in the work [18] for lubricating the copper sliding electrical contacts with the purpose to reduce

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the energy dissipation and improve the reliability and durability of the sliding electrical contact. Standard deviation has been introduced for assessing the stability of conducting and tribological pattern. Characterization and analysis of lubricants and worn surfaces enabled to established that electrical conductivity and tribological pattern of various lubricants are associated with the lubricant nature and the protective film formed on worn surfaces. Wear resistance of electrical contacts in case of boundary lubrication with lubricating oil blending has been studied in the work [19]. It has been established that the anti-wear efficiency depends on the film formation at the boundary surface, which also acts similar to the insulating barrier for electric current. Arc discharge has a significant impact on the wear-out of electrical contacts [20]. The arc discharge process has been recorded by a high-speed camera. The accumulated energy of the arc discharge has been assessed. Experimental outcomes demonstrate that the wear-out rate of the contact strip is approximately directly proportional to the arc discharge accumulated energy in logarithmic coordinates. It is underlined that the standard force increase can suppress the arc discharge and reduce the contact wear-out. The contact strip in collecting pantographs of the electric traction vehicles, in particular, trolleybuses, contain a casing with a chute for the contact wire matching the contact wire shape. Application of the plate-shaped bushings made of partially stabilized zirconium dioxide, located along the casing working surface is promising in order to preserve the contact high electrical conductivity and increase the resistance to abrasive wear-out of the contact strip. Location of bushings on strip working surface is executed at a distance that enables to reduce the fracture caused by the load generated by the friction forces between the bushing and the contact wire. Quantitative value of this distance is conditioned by the design peculiarities of the current collection elements in railway and municipal vehicles. Effectiveness of the proposed design when using the partially stabilized zirconium dioxide under the wire icing conditions consists in maintaining the operability of the current collector owing to the fact that the bushing hardness is much higher compared to that of ice. This enables to scrape off the ice crust. Application of the partially stabilized zirconium dioxide enables to increase significantly the resource (durability) of the friction pair with a higher level of tribological and strength properties. However, the tribological properties of the zirconium dioxide-based material have not been studied enough. The work objective is to study the tribological features of nanostructured crystals in partially stabilized zirconium dioxide doped with rare earth elements under conditions of sliding friction without lubrication.

2 Materials and Methods The hardness and crack resistance tests have been conducted on a kinetic microhardness tester pursuant to the international standard ISO/DIS 14577 -1:2002 “Metallic materials - Instrumented Indentation Test for Hardness and Materials Parameters”. The device positioning accuracy makes 0.1 μm. The maximum force makes 10 N. During these tests, the kinetic microhardness tester was set up for indenting (the most versatile and convenient for the Vickers pyramid indent) using U. Oliver’s and G. Farra’s method (power law of the indentation curve approximation).

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Tribological experiments have been conducted on the testing facility for friction pairs with the reciprocal motion. The plane-to-plane interface with the reciprocal motion of samples is used as a model friction assembly for studying the friction coefficients. Samples out of ceramics and crystals are manufactured in the form of plates with a size of 10 × 10 × 4 mm or less, that eases the manufacture of test samples, which is especially important for the zirconium dioxide-based crystal materials that are hard for processing. Besides, it ensures the constancy of average contact pressure values. The installation layout is submitted in Fig. 1.

Fig. 1. Installation layout for sample testing for friction.

On the base 1, a slider 2 is mounted on which a movable sample 3 is fixed. A fixed sample 4 is fixed in the holder 5. When the slider 2 is reciprocating, the friction force is transmitted to the sample 4, which is registered by the meter 7 through the rod 6. Test sample holder consists of two interconnected disks with a gap between their end surfaces for improving the uniformity of load distribution on the friction surface. Whereby the cylindrical protrusion with a tapered tip is provided on the inner side of the disk located from the loading element side. Besides, through threaded holes are made on this disk surface. Blind stepped hole for accommodating the cylindrical projection and conical tip of the first disk is made on the inner side of the second disk located from the counter sample holder side. While the second disk surface is provided with holes for accommodating threaded fasteners which interconnect the disks. Groove for accommodating and mounting the test sample is made on the second disk outer surface. Whereby the fasteners are placed in the second disk holes with a gap. And the height of the cylindrical protrusion of the first disk makes possible free rolling of the first disk relative to the second one. Presence of gaps and selection of height for the cylindrical protrusion that exceeds the hole depth ensures free rolling of the upper disk relative to the lower one. The method for investigating the tribological properties of Partially Stabilized Zirconia crystals is based on the narratives of interaction between surfaces under friction, which are based on the solid discrete contact model and the hypothesis of the

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dual adhesive and deformation nature of external friction. Dimensionless parameters are assumed as the basic tribological properties: f – friction coefficient, J - wear-out intensity, ε - relative wear-out resistance of the tested materials: f = F/P; J = h/L; ε = Je /Ji

(1)

where F is the friction force, P is the load; h is the value of worn-out material on the friction path L; Je is the wear-out intensity of the sample selected as a reference one from among the tested n samples, Ji is the wear-out intensity of the i-th sample (i = 1…n, n is the number of tested samples).

3 Outcomes The strength and tribotechnical properties of Partially Stabilized Zirconia crystals have been studied depending on the Y2 O3 content and the type and concentration of doping agents in rare earth element oxides. It has been established that crystal doping with Tb, Ce-Nd oxides results in an increase in their bending strength, and CeO2 + Er2 O3 doping results in almost a twofold increase in wear resistance (Table 1). Table 1. Strength and tribotechnical properties of Partially Stabilized Zirconia crystals with various compositions. ZrO2 -3 mol%Y2 O3 + doping agent

K1s MPa*m0.5

Hardness, Hv

Friction coefficient, f

Wear-out intensity, J

Without impurity

10.9–11.3*

12.8

0.23

2.52*10−9

Ce-Nd

11.43

13.8

0.69

2.25*10−8

Ce-Er

12.8

12.8

0.12

1.22*10−9

Ce

9.9

12.7

0.21

1.39*10−9

Pr

10.6

15.9

0.20

1.29*10−9

A set of tribological studies of Zr02-based crystal samples with different Y203 content (up to 35 mol%) has revealed a certain relationship between the friction and wearout properties and the stabilizing agent amount. In particular, using the tribotechnical test patterns under the load-speed modes (p = 5.0 MPa, v = 2.0 m/s) enabled to reveal the downward trend in the intensity of wear-out of crystal samples in parallel to increase in Y203 in the scope of its low concentrations (up to 3.5…4.0 mol%). The most important features of mechanical properties of the mating parts surface layers are hardness, modulus of elasticity and coefficient of non-recoverable deformations, which is often referred to in the reference sources as the plasticity coefficient, which is not correct, since it also takes into consideration the energy costs related to crack formation. Studies of the coefficients of irreversible losses for Partially Stabilized Zirconia crystals afford ground for concluding that the crystals containing the stabilizing

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Fig. 2. Prints on a Partially Stabilized Zirconia crystal with 2.8% Y2 O3 under the load of 7 N and 0.5 N.

additive of 2.8% Y2O3 represent the practical interest for utilization of Partially Stabilized Zirconia crystals in friction assemblies. Experiments show, that crack formation starts during micro-indentation from a certain threshold value, whereby the crack formation start depends on the sample orientation, since all crystals are characterized with a strongly pronounced anisotropy of mechanical properties. Experiments with sequential loading of fragmental samples from 0.2 to 9 N have been conducted (Table 2). It has been established that no cracks are formed up to the load of 7 N. Figure 2 presents the print photos. Table 2. The micro-indentation outcomes. Load, (N)

HV, Vickers (micro)

E, (GPa)

Wplast, (μJ)

Kp

HV*Kp

0.2

1795.4

253.82

0.04

0.561

1007

0.5

1597.6

224.72

0.14

0.562

894

1

1720.9

204.66

0.38

0.517

889

2

1577.1

204.91

1.07

0.518

817

3

1785.8

208.51

2.05

0.529

944

4

1575.2

185.97

3.01

0.503

792

5

1543.1

179.38

4.20

0.494

762

6

919.96

138.24

6.14

0.470

431

7

874.29

130.85

7.76

0.463

405

Contact pressure most strongly affects the wear-out resistance of current collectors from amongst the operational factors. It has been experimentally established that in most cases the intensity of surface wear-out for the steady-state friction mode under normal operating environment is directly proportional to the nominal pressure. Deviations from the direct proportionality which have been observed during experiments are conditioned either by non-completion of the surface aging process or by the modification of the physical-mechanical properties of the surface layer materials in the mating surfaces under the impact of their heating owing to the heat released during the surface friction. Therefore, experimental evaluation of the elemental wear-out

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law must always be accompanied by specifying the applicability limits for the resulting dependence.

4 Discussion Experiments have revealed that the tribological properties of zirconium dioxide crystals vary greatly depending on the crystal chemical composition. With their high hardness, they differ favorably from other ceramic materials and crystals characterized with high crack resistance. Tribological properties significantly depend on the type of secondary structures that are developed on the friction surface. Crystals derived from a melt represent the non-equilibrium, metastable material from the thermodynamical point of view, which is evidenced by the phase analysis data. Thus, for the scope of compositions corresponding to the content of yttrium oxide from 8 to 35 mol%, the conditions for synthesis from a melt are such that the crystals contain only the cubic phase, since, as is obvious from the state diagram, the temperature of the polymorphic transition of the cubic-tetragonal phase decreases sharply in parallel with increase in the yttrium oxide content. The rate of temperature decrease in the crystals after growing is high, and the cation diffusion coefficients in zirconium dioxide-based materials are very low (especially under the temperatures below 1000 C), which leads to the situation when the phase composition corresponding to high temperatures is preserved in the crystals. Crystal synthesis technological modes, in particular, the crystal growth rate can also influence the phase composition and, respectively, the wear-out properties. Study of the friction surface morphology and identification of the wear-out leading mechanisms - destruction of surface layers in the samples with different content of stabilizing agent - are of interest for analyzing the relationship between the friction parameters and wear-out of Partially Stabilized Zirconia crystals with their chemical composition and synthesis conditions. Microhardness has been studied as well as x-ray structural and electron microscopic analysis of the friction surfaces in crystal samples with different stabilizing oxide content have been conducted for this purpose. Even visual examination of friction surfaces after testing demonstrates the partial change compared with their initial state, which is associated with the formation of secondary structure films. Formation of secondary structure films can be due to a number of physical and chemical processes, such as: counter-body material friction transfer, incomplete removal of wear debris from the friction zone, their adhesion on the friction surface of samples, partial or complete oxidation of the transferred material, etc. Uneven distribution of secondary structures films over the surface is observed. Change in the microhardness of surface layers after tribological tests is noted as well. It should be noted that a spread of microhardness values is observed on the friction surface which is conditioned both by spread of the initial surface hardness and the microstructural irregularity of the surface films. In general, this spread falls within the range between the initial microhardness of the base material and the minimum microhardness of the film – Ninit. – Nfilm min . Indirect assessment of thickness of h films formed during test based on microhardness measurement, x-ray structural analysis and electron microscopy enables to conclude that it falls within the range of 1,0 ≤ h ≥ 3,5 μm. Unfortunately, x-ray structural analysis of the sample friction surfaces has not enabled

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Fig. 3. Secondary structures on the friction surface of samples with different Y2 03 content: a 2%, b - 4%, c - 8%, d - surface area without secondary structures films, 100X.

to evaluate the phase composition of the formed films, which is conditioned by their small thickness and uneven distribution over the friction surface. Taking into consideration that the x-ray penetration depth makes h < 4.0 μm, thickness of the films can be assumed to be less than this limit. Figures 3 present photos of electron microscopic examination of the samples friction surfaces with 2, 4, and 8 mol% of Y2 03 under various magnification values. Films can be seen on the mating surfaces (light areas). Moreover, the overall pattern of film distribution over the surface, the level of film uniformity, as well as the area of the film individual sections vary for samples with different concentrations of the stabilizing agent. So, the film is not uniform for samples with Y2 03 content of 2.0 mol%, it consists of separate sections which in the lump are oriented in the sliding direction. More dark areas of the sample base material are visible between the film islands. At Y2 03 of 4 mol%, the film is also not uniform, nevertheless, an increase in the area of the film individual sections and the area occupied by the film as a whole is observed.

5 Conclusions Study of the strength and tribotechnical properties of Partially Stabilized Zirconia crystals depending on the Y2 03 content and the type and concentration of doping impurities of rare earth element oxides has revealed that they are characterized with high strength properties, low friction coefficient and high wear-out resistance. It is demonstrated that doping with impurities of rare earth element oxides represents the effective method for increasing their strength and tribotechnical properties. Crystals containing a stabilizing

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additive of 2.8% Y2 03 represent the practical interest for utilization of Partially Stabilized Zirconia crystals in friction assemblies. The crystals of ZrO2 -2.8 mol% Y2 03 + 1weight% CeO2 compositions present the greatest interest in terms of plasticity criterion (coefficient of irreversible losses) from among the Partially Stabilized Zirconia crystals doped with rare-earth elements.

References 1. Kragelsky, I.V., Alisin, V.V., Chichinadze, A.V., Myshkin, N.K.: Professional Engineering. Friction and wear of electric contacts. London and Bury St. Edmunds, UK (2001) 2. Grandin, M., Wiklund, U.: Wear phenomena and tribofilm formation of copper/coppergraphite sliding electrical contact materials. Wear 398, 227–235 (2018). https://doi.org/10. 1016/j.wear.2017.12.012 3. Isard, M., Lahouij, I., Montmitonnet, P., Lanot, J.-M.: Third-body formation by selective transfer in a NiCr/AgPd electrical contact Consequences on wear and remediation by a barrel tumble finishin. Wear 426–427, 1056–1064 (2019). https://doi.org/10.1016/j.wear.2018. 11.022 4. Tu, C., Chen, Z., Xia, J.: Thermal wear and electrical sliding wear behaviors of the polyimide modified polymer-matrix pantograph contact strip. Tribol. Int. 42(6), 995–1003 (2009). https://doi.org/10.1016/j.triboint.2009.02.003 5. Argibay, N.J., Sawyer, W.: Asymmetric wear behavior of self-mated copper fiber brush and slip-ring sliding electrical contacts in a humid carbon dioxide environment. Wear 268(3–4), 455–463 (2010). https://doi.org/10.1016/j.wear.2009.08.036 6. Wei, X., Meng, H., He, J., Jia, L., Li, Z.: Wear analysis and prediction of rigid catenary contact wire and pantograph strip for railway system. Wear 442–443, 203118 (2020). https://doi.org/ 10.1016/j.wear.2019.203118 7. Senouci, A., Frene, O., Zaidi, H.: Wear mechanism in graphite–copper electrical sliding contact. Wear 225–229, 949–953 (1999) 8. Kurosaki, K., Setoyama, K., Matsunaga, O., Yamanaka, S.: Nanoindentation tests for TiO2, MgO, and YSZ single crystals. J. Alloy. Compd. 386, 261–264 (2005). https://doi.org/10. 1016/j.jallcom.2004.05.016 9. Wang, P., Zhang, H., Yin, J., Xiong, X., Deng, C.: Effects of fibre orientation on wear behavior of copper mesh modified-carbon/carbon composite under electric current. Tribol. Int. 116, 310–319 (2017). https://doi.org/10.1016/j.triboint.2017.07.011 10. Jang, I., Joo, H.G., Jang, Y.H.: Effects of carbon nanotubes on electrical contact resistance of a conductive Velcro system under low frequency vibration. Tribol. Int. 104, 45–56 (2016). https://doi.org/10.1016/j.triboint.2016.08.019 11. Poljanec, D., Kalin, M.: Effect of polarity and various contact pairing combinations of electrographite, polymer-bonded graphite and copper on the performance of sliding electrical contacts. Wear 426–427, 1163–1175 (2019). https://doi.org/10.1016/j.wear.2019.01.016 12. Grandin, M., Wiklund, U.: Friction, wear and tribofilm formation on electrical contact materials in reciprocating sliding against silver-graphite. Wear 302, 1481–1491 (2013). https:// doi.org/10.1016/j.wear.2013.02.007 13. Myshkin, N., Konchits, V.: Friction and wear of metal-composite electrical contacts. Wear 58, 119–140 (1992) 14. Bucca, G., Collina, A.: Electromechanical interaction between carbon-based pantograph strip and copper contact wire: a heuristic wear mode. Tribol. Int. 92, 47–56 (2015). https://doi.org/ 10.1016/j.triboint.2015.05.019

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15. Echeverrigaray, F., de Mello, S., Leidens, L., Boeira, C., Figueroa, C.: Electrical contact resistance and tribological behaviors of self-lubricated dielectric coating under different conditions. Tribol. Int. 143, 06086 (2020). https://doi.org/10.1016/j.triboint.2019.106086 16. Kalin, M., Poljanec, D.: Influence of the contact parameters and several graphite materials on the tribological behaviour of graphite/copper two-disc electrical contacts. Tribol. Int. 126, 192–205 (2018). https://doi.org/10.1016/j.triboint.2018.05.024 17. Wang, P., Yue, W., Lu, Z., Zhang, G., Zhu, L.: Friction and wear properties of MoS2-based coatings sliding against Cu and Al under electric current. Tribol. Int. 127, 379–388 (2018). https://doi.org/10.1016/j.triboint.2018.06.028 18. Cao, Z., Xia, Y., Liu, L., Feng, X.: Study on the conductive and tribological properties of copper sliding electrical contacts lubricated by ionic liquids. Tribol. Int. 130, 27–35 (2019). https://doi.org/10.1016/j.triboint.2018.08.033 19. Zhao, H., Feng, Y., Zhou, Z., Qian, G., Zhang, X.: Effect of electrical current density, apparent contact pressure, and sliding velocity on the electrical sliding wear behavior of Cu–Ti3AlC2 composites. Wear 44–445, 203156 (2020). https://doi.org/10.1016/j.wear.2019.203156 20. Chen, X., Yang, H., Zhang, W., Wang, X., Zhou, Z.: Experimental study on arc ablation occurring in a contact strip rubbing against a contact wire with electrical current. Tribol. Int. 61, 88–94 (2013). https://doi.org/10.1016/j.triboint.2012.11.020

Filler Impact on the Properties of Energy-Efficient Polymer Glass Composite Material Irina Vitkalova , Anastasiya Uvarova , Evgeniy Pikalov(B) and Oleg Selivanov

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Vladimir State University named after A.G. and N.G. Stoletovs, 600000 Vladimir, Russia [email protected]

Abstract. This paper presents the research results of the influence of the filler amount impact on the basic physical, mechanical and operational properties of energy-efficient polymer composite material for external and internal wall cladding of buildings and structures. The raw material mixture contains sheet window glass cullet used as filler and non-plasticized polyvinyl chloride waste dissolved in methylene chloride used as binder. Products based on this mixture can be produced by cold pressing method followed by heat treatment at the methylene chloride boiling point. Judging by the research results, it was discovered that the increase in the filler content causes the increase of its density, thermal conductivity, water absorption, total and open porosity alongside frost resistance reduction. The compressive and bending strength is enhanced by increasing the filler content up to 40 wt%, but further increase of the cullet amount causes its decline due to the lack of the binder. Basing on the received dependences, the chosen filler content equaled 40 wt%, as it provides not only maximum strength for this composition, but also allows producing material with energy-efficient thermal characteristics. Water absorption and frost resistance at the stated filler contents are at the level allowing to use the developed composite material both for interior and exterior walls cladding combining the functions of the facing and insulating layers at multi-layer walls constructing. Keywords: Cullet · Non-plasticized polyvinyl chloride waste · Methylene chloride · Polymer glass composite material · Energy efficiency

1 Introduction Construction industry is one of the most actively developing branches in the modern world. Enterprises producing construction materials and products are among the largest scale plants, and their products in recent years remain among the most popular items. The main trends in the construction materials and products manufacturing are the improvement of the main operational properties, the expansion of the raw material base and product range, as well as cost and energy intensity reduction. At the same time, special © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 450–456, 2021. https://doi.org/10.1007/978-3-030-57453-6_42

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attention is paid to the strength and frost resistance increase, water absorption reduction, ensuring fire and environmental safety, durability and besides recently more attention is paid to energy efficiency [1]. In this regard, the processes of construction materials production are currently developing, equipment, technologies and compositions of raw mixtures are being improved in order to increase productivity and quality, but reduce their cost. The range and assortment of the products manufactured by construction industry enterprises is also expanding [2–4]. Both traditional natural materials, including ceramics, glass, mineral binders (primarily cement), wood and metal, and synthetic materials, including polymers, rubbers, organic binders (bitumen, tar, etc.) and various kinds of composite materials are widely used in this industry. Most construction materials and products are characterized by their high density, and, therefore, create a load on the foundation and supporting structures. Besides, these materials are characterized by poor bending and tensile strength, as well as by low resistance to aggressive environments. These disadvantages can be minimized through the use of polymer composite materials, where polymer binders provide low weight and chemical resistance, and fillers increase strength characteristics [5–7]. In addition, composite materials, including polymers, allow combine energy efficiency and strength with other performance characteristics [8, 9]. It should be noted that polymer composite materials have certain disadvantages such as aging phenomenon and polymer binder combustibility, which reduce their effectiveness for construction. However, these disadvantages can also be leveled by applying non-flammable fillers and special additives in polymer binders (flame retardants, stabilizers, etc.). Another disadvantage of polymer composite materials is their relatively high cost, which can be reduced by using cheap fillers, including waste-based or secondary polymer raw materials as binders [8–10]. The research authors have previously experimented with developing a method for facing composite material production where non-plasticized polyvinyl chloride (NPVC), obtained by dissolving consumption waste of this polymer in methylene chloride was the binder, and cullet waste was used as the filler. Finally, it was proved that the highest compressive strength and the lowest water absorption of the developed material can be obtained at the ratio of NPVC: methylene chloride in a binder solution equal to 1:2 at the introduction of filler 40 wt% and at the pressing pressure of 8 MPa [9]. The research objective was to study the dependence of the basic physical, mechanical and operational properties of the developed energy-efficient composite material on the amount of filler in the raw material mixture and to determine the amount of filler ensuring product high quality and the material properties meet the requirements for facing materials.

2 Materials and Methods The raw material mixture composition for the production of the developed polymer composite material included polymeric thermoplastic binder, dispersed filler and solvent. To produce thermoplastic binder, PVC waste was used, which comes from the production of building profiles (docking profiles and skirting boards) and finishing wall

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panels. These waste and polymer type were chosen due their large scale production and high demand, as well as large waste accumulation of NPVC [11, 12]. It is worth mentioning that NPVC is characterized by its strength, low water absorption and it refers to hard combustible substances, which is important for facing materials, besides it refers to non-thermo stable polymers [9, 11]. It means that its dissolving and cold processing will eliminate the possibility of product destruction during the production process. Waste comprising window sheet glass (hereinafter-cullet) of the following composition (by weight. %): SiO2 = 73.5; CaO = 7.4; MgO = 1.9; Na2 O = 11.1; K2 O = 5.2; Al2 O3 = 0.9 [9] was used as a filler. The choice of cullet, similar to the binder, is explained by the considerable amount of these wastes formed as a result of household glass consumption, and large scale production of glass [13–15]. Cullet as a material for composite materials production differs by its strength, moisture resistance and incombustibility, and therefore can be used to cladding materials production. First grade technical methylene chloride (MC) in compliance with GOST 9968-86 with 98,8% of the basic substance content was used to transfer thermoplastic binder into a liquid state. This solvent has good solvent capacity associated with a small molar volume, which allows the solvent molecules penetrate easily between the polymer molecules and accelerates the dissolution process. The high volatility and low boiling point of methylene chloride facilitate solvent removal during heat treatment. Methylene chloride advantages also include low flammability, low toxicity (4 hazard class) and low cost compared to most solvents. During the research, the developed ceramics samples were manufactured applying cold pressing technology [9]. NPVC and cullet were pre-crushed with less than 0.63 mm particle size fraction and dried to a constant mass. Afterwards NPVC was mixed with the MC at the ratio of 1:2 to prepare binder solution, which in turn was mixed with a given amount of filler to produce homogeneous raw mixture. Composite material samples were formed from the resulting raw material mixture at a specific pressure of 8 MPa, which were subjected to heat treatment at the temperature of 45–50 °C for 45 min to remove the solvent. Samples of each composition of the raw mixture were made in five samples batches. To define the dependence of the developed composite material properties on the filler content and to evaluate the research results, the produced samples were tested applying standard methods for construction materials regarding density (ρ, kg/m3 ), water absorption (WA,%), open (Pop , %), closed (Pcl , %) and total (Ptot , %) porosity, frost resistance (FR, cycles), compressive (σcs , MPa) and bending (σbs , MPa) strength, thermal conductivity (λ, W/m·o C).

3 Results As the data, received as the result of experimental studies, proves the density and thermal conductivity of the developed material (see Fig. 1, a) almost linearly increases alongside the increase of the cullet content, which depends on the fact that cullet density and thermal conductivity (2470–2500 kg/m3 and 0.6–0.7 W/(m·o C), respectively) is significantly higher than that of NPVC (1350–1430 kg/m3 and 0,15–0.175 W/(m·o C), respectively). It should be noted that the filler content does not exceed 65 wt%, thermal conductivity

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of the material is lower than 0.46 W/(m·o C) and the resulting material in compliance with GOST 530-2012 can be classified as conditionally effective. But at the filler content of less than 50 wt% the thermal conductivity of the material is reduced to values corresponding to the effective thermal characteristics of the products (0.24 < λ < 0.36). Herewith it should be noted that the introduction of less than 35 wt% into the resulting raw mixture, binder excess occurs, which makes product processing difficult and finally causes shape deterioration and lowers strength characteristics [9]. In addition, it should be considered that binder amount increase enhances solvent amount in the raw mixture composition, thus increasing heat treatment time for its removal and the overall energy intensity of the production. The dependence of the compressive and bending strength on the filler amount in the raw material mixture (see Fig. 1, b), proves that these properties reach their maximum at the cullet content of 40 wt% as part of the raw material mixture, but further increase in the filler amount causes the properties decrease. Such dependencies nature is explained by the fact that with the cullet content increase up to 40 wt%, the filler enhances the strength of the resulting material, forming a frame from the cullet particles interconnected through the layers of NPVC [11]. At the higher cullet content due to the binder amount reduction, the layers thickness is insufficient to form a strong frame. Simultaneously with the decrease of the layers thickness cullet particles, not interconnected through the layers of NPVC appear, thus manifesting drastic decrease of strength characteristics, the material stratification the along the height of the product and edges shedding.

Fig. 1. Relation of density and thermal conductivity (a), material compressive and bending strength (b) and filler amount.

The research results additionally determined that the cullet content increase in the raw mixture composition causes the increase of the total and closed porosity of the developed polymer composite material but the closed porosity decreases (see Fig. 2a). The pores in the developed material are formed primarily due to the air bubbles appearing at the phase section boundary in the filler-binder system during mixing, which remain at

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the subsequent production stages of the products and in the products themselves thanks to imperfect adhesion of the binder to the filler particles and high binder viscosity, preventing air bubbles removal from material depth. Pores in the material are also formed as a result of solvent boiling and volatilization processes. In case of small filler amount, the surface area of the phase contact in the filler – binder system is negligible, but binder amount is sufficient to fill most pores and voids in the material depth and to transfer almost all remaining pores into the closed ones. If the filler content is increasing up to over 45 wt% the number of the formed pores is growing, and the binder amount is not enough to fill the pores and transfer them to the closed porosity [9]. Water absorption and frost resistance dependency of the developed material on the filler content in the composition of the raw mixture (see Fig. 2, b) defines that absorption rises almost linearly alongside the filler amount increase, which is associated with increased total and open porosities of the material (see Fig. 2a). In turn, water absorption increase and formation of the developed porous structure causes linear decrease of frost resistance alongside the increase of the open pores proportion. It is worth noting that water absorption of finishing and facing materials should be over 2% but less than 5% for the socle tiling and less than 9% for the facades or not more than 16% in case of interior walls facing. Frost resistance of external materials is to resist over 40 cycles for facades facing and over 50 cycles for the socle facing. Consequently, the developed material suits interior cladding with all considered filler contents, but for facade cladding the content is to be less than 65 wt% and for socle facing - not exceeding 45 wt%.

Fig. 2. Dependence of porosity (a), water absorption and frost resistance (b) of the material on the filler amount.

According to the research results, the selected filler amount in the raw mixture composition equaled 40 wt%, thus allowing after methylene chloride removal to produce facing composite material consisting of 33.3 wt% of NPVC and of 66.7 wt% of cullet, and also allowing achieve the best combination of studied properties of the developed

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material for using such products as facing and energy-efficient products thus combining functions of facing and heat-insulating layers in multilayered walls. In case of low-rise construction, it is possible to use the developed composition for producing material that can additionally be used for wall construction from one material without separation into functional layers and will meet all basic requirements for strength, frost resistance and energy efficiency.

4 Conclusions The research results proved that cullet introduction the amount of 40 wt% into the raw mixture as a filler allows producing of polymer composite material possessing basic physical, mechanical and operational properties make it possible to use this material in the of facing tiles production. Raw mixture composition beside cullet also includes 20 wt% of NPVC waste and 40 wt% of methylene chloride. The specified raw mixture composition provides the degree of composite material filling equal to 66.7 wt%. Herewith the material density is relatively low, reducing the load exerted on the supporting structures by the facing products. Thermal conductivity of the developed material (0.295 W/m·o C) allows attributing it to the group of energyefficient materials. It makes them meet modern heat engineering standards and rational consumption of building materials during construction and repair work. The material strength characteristics (σcs = 15.5 MPa and σbs = 3.7 MPa) are comparable to the ceramic brick brand M150 (σcs = 15 MPa and σbs = 2.8 MPa), so the developed material can be used in case there is no high mechanical load on the coated surface during operation. Water absorption (3.8%) and frost resistance (52%) of the material meet the requirements for external and internal materials for wall cladding of buildings and structures. Thus, the basic physical and mechanical characteristics of the material allow applying such products for tiling internal walls, facades and socles of buildings and structures.

References 1. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: The use of polymer and glass waste to obtain a self-glazing facing ceramic. Ecol. Ind. Russ. 23(11), 38–42 (2019). https://doi.org/ 10.18412/1816-0395-2019-11-38-42 2. Shubbar, A.A., Sadique, M., Kot, P., Atherton, W.: Future of clay-based construction materials – a review. Constr. Build. Mater. 210, 172–187 (2019). https://doi.org/10.1016/j.conbuildmat. 2019.03.206 3. Schiavoni, S., D’Alessandro, F., Bianchi, F., Asdrubali, F.: Insulation materials for the building sector: a review and comparative analysis. Renew. Sustain. Energy Rev. 62, 988–1011 (2016) 4. Konuklu, Y., Ostry, M., Paksoy, H.O., Charvat, P.: Review on using microencapsulated phase change materials (PCM) in building applications. Energy Buildings 106, 134–155 (2015). https://doi.org/10.1016/j.enbuild.2015.07.019 5. Sarde, B., Patil, Y.D.: Recent research status on polymer composite used in concrete-an overview. Mater. Today Proc. 18(7), 3780–3790 (2019). https://doi.org/10.1016/j.matpr.2019. 07.316

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6. Yan, L., Kasal, B., Huang, L.: A review of recent research on the use of cellulosic fibres, their fibre fabric reinforced cementitious, geo-polymer and polymer composites in civil engineering. Compos. B Eng. 92, 94–132 (2016). https://doi.org/10.1016/j.compositesb.2016. 02.002 7. Fang, H., Bai, Y., Liu, W., Qi, Y., Wang, J.: Connections and structural applications of fibre reinforced polymer composites for civil infrastructure in aggressive environments. Compos. B Eng. 164, 129–143 (2019). https://doi.org/10.1016/j.compositesb.2018.11.047 8. Hameed, A.M., Hamza, M.T.: Characteristics of polymer concrete produced from wasted construction materials. Energy Procedia 157, 43–50 (2019). https://doi.org/10.1016/j.egypro. 2018.11.162 9. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: The development of energy efficient facing composite material based on technogenic waste. Adv. Intell. Syst. Comput. 983, 778– 785 (2019). https://doi.org/10.1007/978-3-030-19868-8_76 10. Kashyap, S., Datta, D.: Reusing industrial lime sludge waste as a filler in polymeric composites. Mater. Today Proc. 4(2), 2946–2955 (2017). https://doi.org/10.1016/j.matpr.2017. 02.176 11. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Energy efficiency improving of construction ceramics, applying polymer waste. Adv. Intell. Syst. Comput. 983, 786–794 (2019). https://doi.org/10.1007/978-3-030-19868-8_77 12. Sadat-Shojai, M., Bakhshandeh, G.-R.: Recycling of PVC wastes. Polym. Degrad. Stab. 96, 404–415 (2011). https://doi.org/10.1016/j.polymdegradstab.2010.12.001 13. Mohammadinia, A., Wong, YCh., Arulrajah, A., Horpibulsuk, S.: Strength evaluation of utilizing recycled plastic waste and recycled crushed glass in concrete footpaths. Constr. Build. Mater. 197, 489–496 (2019). https://doi.org/10.1016/j.conbuildmat.2018.11.192 14. Kolosova, A., Sokolskaya, M., Pikalov, E., Selivanov, O.: Production of facing ceramic material using cullet. In: E3S Web of Conferences, vol. 91, p. 02003 (2019). https://doi.org/10. 1051/e3sconf/20199102003 15. Shakhova, V.N., Vitkalova, I.A., Torlova, A.S., Pikalov, E.S., Selivanov, O.G.: Receiving of ceramic veneer with the use of unsorted container glass breakage. Ecol. Ind. Russ. 23(2), 36–41 (2019). https://doi.org/10.18412/1816-0395-2019-2-36-41

Charge Composition Development for Heat-Resistant Ceramics Anastasiya Uvarova , Irina Vitkalova , Evgeniy Pikalov(B) and Oleg Selivanov

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Vladimir State University named after A.G. and N.G. Stoletovs, 600000 Vladimir, Russia [email protected]

Abstract. This article presents the results of the charge composition development for heat-resistant ceramics production based on low-plasticity clay with the addition of 10 wt. % of cerium oxide and 5 wt. % of boric acid as functional additives. It has been stated that self-glazing effects on the surface and ceramic particles glazing in the products depth are observed during joint introduction of these additives. These effects occur as boric acid, being a strong flux, forms a vitreous phase and reduces liquid-phase sintering temperature of ceramics. This vitreous phase based on borosilicates includes cerium oxide, as well as silicon, aluminum, calcium and magnesium oxides, which are characterized by high melting points, chemical resistance and heat resistance. This vitreous phase is represented in the structure of the material in the form of the layers between the ceramic particles and forms a single frame possessing low thermal coefficient of linear expansion, which contributes to the compaction, open porosity reduction, material strength characteristics and heat resistance increase. The advantages of cerium oxide are the reduction of the difference between thermal coefficients of linear expansion between the amorphous and crystalline phases in the material, as well as the ability of this substance to serve as a catalyst for hydrocarbons and soot oxidation when heated. The obtained results allow using the obtained ceramics for lining thermal units and flue channels operated at high temperatures and in aggressive environments, alongside the production of self-cleaning walls without interrupting thermal units operation. Keywords: Heat-resistant ceramics · Low-plasticity clay · Boric acid · Cerium oxide · Self-glazing · Thermal coefficient of linear expansion

1 Introduction Heat-resistant ceramics is characterized by its strength, hardness, chemical stability and primarily by the ability to withstand stresses in the material at sharp temperature changes during repeated heating to high temperatures with subsequent cooling without destruction and preserving its operational properties. Products made of heat-resistant ceramics are used in lining furnaces and stokes, in the production of various kiln furniture, insulators in electric heating devices and piezoelectric sensors. Lately heat-resistant ceramics © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 457–463, 2021. https://doi.org/10.1007/978-3-030-57453-6_43

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has been increasingly widely used in the production for various branches of mechanical engineering, including internal combustion engines and gas turbines, machine tools, electronics, energy, aviation and aerospace industry [1–3]. Simultaneously with the listed application, heat-resistant ceramics products are also used in the household both for lining thermal installations (ovens, fireplaces, etc.) and for making kitchen utensils (coffee makers, stewing braziers, frying pans, etc.). Regarding its composition, heat-resistant ceramics basically refers to the oxide (based on pure oxides), oxide-free (based on carbides, nitrides, borides and silicides) or to the silicate and aluminosilicate ceramics based on the compounds containing such metals as aluminum, lithium, zirconium, beryllium, titanium, magnesium, yttrium, etc. [4–6]. Oxide and oxygen-free compounds of these metals [5, 7, 8], as well as various silica raw materials are mainly used as raw material for heat-resistant ceramics production. Natural clay raw material as the main component for heat-resistant ceramics production is rarely used but for refractory clays, which can comprise up to 70 wt. % of the charge composition. The application of all these compounds in the heat-resistant ceramics composition is mainly explained by high melting temperatures and strength, accompanied with low thermal coefficient of linear expansion (TCLE). To make the products from heat-resistant ceramics, semi-dry and plastic molding, slicker casting and thermoplastic bundles casting are used, followed by firing at temperatures from 1100 to 1700 °C, depending on the sintering temperature of the charge components [1, 7, 8]. The research objective is to develop the charge composition for the ceramics production with high strength and heat resistance characteristics at low firing temperature. An additional task was the introduction of low-plasticity clay as the main charge component, which application on the one hand reduces ceramics production cost, and on the other hand expands the usage of low-demand natural raw materials. Low demand for low-plasticity clay is stipulated by poor strength and crack resistance characteristics of the products on its basis, so for its effective use it is necessary to introduce functional additives thus improving the resulting ceramics quality. The research authors have previously developed the charge compositions based on low-plasticity clay, allowing produce wall [9] and facing products [10–12] including acid-resistant items [13]. In the mentioned researches strength and crack resistance increase was achieved through the combined introduction [10, 11, 13] of glass-forming additives and fluxes, allowing obtain the effects of ceramic particles glazing in depth and products surface self-glazing. This article suggests the possibility to obtain vitreous phase at the reduced firing temperature using cerium oxide and boric acid to increase strength and heat resistance.

2 Materials and Methods The principle charge component was low-plasticity clay from Suvorotskoye deposit of the Vladimir region of the following composition (wt. %): SiO2 = 67.5; Al2 O3 = 10.75; Fe2 O3 = 5.85; CaO = 2.8; MgO = 1.7; K2 O = 2.4; Na2 O = 0.7. The clay plasticity index equals 5.2, and, consequently, it refers to the low-plasticity type in compliance with GOST 9169-75. This clay low plasticity is explained by the presence

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of aluminum, calcium and magnesium oxides [9] which belong to refractory oxides and increase clay fire resistance. Moreover, silicon and aluminum oxides contained in this clay in relatively large quantities, reduce TCLE, its low values increase ceramics thermal stability, and sodium and potassium alkaline oxides increasing TCLE, are presented in minimal quantities. Thus, the clay composition justifies its introduction into heatresistant ceramics manufacturing. To form the vitreous phase and to achieve self-glazing and glazing effects, cerium oxide (STO 00203789-060-2013) of 99.8% main substance mass fraction and boric acid of brand B grade 2 (GOST 18704-78) of 98.6% main substance mass fraction were introduced into the charge. Cerium oxide was chosen due to its refractoriness and ability to perform as a soot catalyst when heated, allowing to apply the resulting ceramics as self-cleaning lining. Boric acid was chosen as it is a strong flux able of significant temperature reduction for formation of the vitreous phase and liquid-phase sintering [10–12]. During the research, the developed ceramics samples were manufactured using semidry pressing technology [9, 10]. Prior the experiments, the clay was dried to a constant mass and crushed for fraction selection of particle size less than 0.63 mm. Further the clay, cerium oxide and boric acid were mixed dry first, and then with water to produce the molding mass of 8 wt. % humidity. The samples were made from the molding mass at a specific pressing pressure of 15 MPa. The molded samples were fired at the maximum temperature of 1050 °C. Samples based on the studied compositions were made in batches of three samples each. To determine the properties dependence on the charge composition and to assess the research results, the following characteristics have been determined according to the standard methods for ceramic materials: compressive (σcmp , MPa) and bending (σbnd , MPa) strength, heat resistance (HR (1000 °C - water), heating shifts), acid resistance (AR, %), density (p, kg/m3 ) and open porosity (Popn , %).

3 Results At the first stage of experimental study, the influence of cerium oxide and boric acid content on the main properties of the developed ceramics – compressive strength and heat resistance was studied. As the received data demonstrate (see Figs. 1 and 2), the applied additives contribute to the considered properties improvement, and self-glazing and glazing effects are observed when they are co-introduced. As it was stated in earlier researches [10–12], the formation of vitreous phase during firing, especially in the presence of self-glazing and glazing effects, causes the strength increase of the resulting ceramics as the vitreous phase forms layers between the ceramic particles, connecting them into a strong and solid frame. This explains almost linear increase of the developed ceramics strength with the introduction of up to 10 wt. % cerium oxide and up to 5 wt. % boric acid. Further increase of these additives amount causes vitreous phase excess and layers thickness increase.

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Fig. 1. Dependence of the developed ceramics compressive strength on cerium oxide and boric acid (BA) content.

Fig. 2. Dependence of developed ceramics thermal stability on cerium oxide and boric acid (BA) content.

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As a result, the vitreous phase starts to perform not as a binder, but as a separate phase, characterized by fragility and according to the additivity rule reduces the material strength as a whole. This explains the reduced distance between the straight lines in Fig. 1, their alignment at the introduction of more than 10 wt. % cerium oxide and gradual decrease of the line for 10 wt. % boric acid below line for 5 wt. % boric acid. Moreover the excess of the vitreous phase causes product deformation and their faces melting, and it is also worth considering that additives introduction increase, especially cerium oxide, increases the cost of the developed ceramic material. Thermal stability increase caused by additives introduction can be explained by several reasons. Firstly, we must note that during the firing boric acid forms the melt interacting with the silica within the clay, forming borosilicates [12], which are characterized by high resistance, especially at high contents of silicon oxide and small quantities of alkaline oxides. The composition of the applied low-plasticity clay impacts contributes to it. Refractory aluminum, calcium and magnesium oxides, also contained in the lowplastic clay, partially pass into the vitreous phase during firing, additionally increasing its heat resistance. Besides it is also worth considering that boron-containing phases contribute to the material formation with low TCLE and consequently contributes to its thermal stability [4, 14]. In addition, it is known that the cerium oxide introduction increases glass thermal expansion coefficient, but at the same time it facilitates the difference reduction between the coefficient of amorphous and crystalline areas in the material [15], thus increasing the developed ceramics thermal stability. Depending on the nature of determined dependencies, it was decided to introduce up to 10 wt. % cerium oxide and 5 wt. % boric acid into the charge, avoiding the formation of vitreous phase excess the during firing and in turn reaching maximum compressive strength and heat resistance, as well as keeping the required shape of the products. At the second stage of experimental research, a set of basic properties of the developed ceramics was determined depending on the content of cerium oxide in the charge containing 5 wt. % of boric acid. As the result (see Table 1) it was stated that cerium oxide increased amount causes the increase of all examined properties except open porosity, which on the contrary decreases. Table 1. The developed ceramics characteristics. Characteristics

Cerium oxide content, wt. % 0

2

4

6

8

10

Density, kg/m3

1974.9 2016.3 2077.1 2169.7 2316.1 2366.6

Compressive strength, MPa

25.8

31.4

38.6

48.4

62.6

70.2

Bending strength, MPa

6.0

8.6

11.9

16.4

22.9

26.3

Open porosity, %

2.2

2.0

1.9

1.7

1.4

1.2

Heat resistance (1000 °C - water), heating 9 shifts

26

59

90

106

112

Acid resistance, %

74.8

88

95.4

96.9

98.4

61.6

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As in the case of the compressive strength and heat resistance dependencies discussed above, the impact mechanism of the applied additives on other properties indicated in the table includes liquid-phase sintering of the material and self-glazing effect observed in the samples. Liquid-phase sintering and vitreous phase in the ceramics depth cause the decrease of total porosity and material compaction, but sample surface self-glazing transfers most open pores into closed ones. The acid resistance increase depends on the fact that the basis of the resulting vitreous phase comprises borosilicates, which differ not only in high temperature resistance, but also in high chemical resistance [12, 13]. Cerium oxide, a part of the vitreous phase, also increases chemical resistance. Boron oxide can reduce chemical resistance if its content exceeds 13% [13], but its amount is much lower in the developed composition. Thus, the charge composition, including 10 wt. % of cerium oxide and 5 wt. % of boric acid, and allowing reach the maximum strength and heat resistance for this composition corresponds to the research objective best.

4 Conclusions The research resulted in the development of the charge composition, allowing obtaining heat-resistant ceramics based on low-plasticity clay through the addition of 10 wt. % cerium oxide and 5 wt. % boric acid. Alongside heat resistance, the resulting ceramics is characterized by high strength, density, acid resistance and low open porosity. The developed composition will promote low-plasticity clays application, which are practically not used in the ceramic industry because of poor strength and crack resistance of the resulted products. Cerium oxide introduction into the charge increases the refractoriness and chemical resistance of the resulting ceramic material. Besides cerium oxide reduces the difference between the TCLE of amorphous and crystalline phases in the ceramics depth, which in turn reduces the internal stresses occurring in the material during temperature fluctuations due to unequal volume extensions, and thus contributing to increased heat resistance by maintaining the ceramic material strength and integrity as the result of heating up to high temperatures with subsequent cooling. The boric acid contributes to the vitreous phase formation during firing and reduces of liquid-phase sintering temperature of ceramics. The presence of vitreous phase based on borosilicates increases developed ceramics strength, heat resistance and chemical resistance. The self-glazing effect makes it possible to use the resulting ceramics for lining thermal units and flue channels operated at high temperatures and in aggressive environment, providing self-cleaning walls without stopping the thermal units, where cerium oxide will perform as a catalyst for the soot and hydrocarbons oxidation when heated.

References 1. Ferraris, E., Vleugels, J., Guo, Y., Bourell, D., Kruth, K.P., Lauwers, B.: Shaping of engineering ceramics by electro, chemical and physical processes. CIRP Ann. 65(20), 761–784 (2016). https://doi.org/10.1016/j.cirp.2016.06.001

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2. Rakshit, R., Das, A.K.: A review on cutting of industrial ceramic materials. Precis. Eng. 59, 90–109 (2019). https://doi.org/10.1016/j.precisioneng.2019.05.009 3. Farooqui, M.N., Patil, N.G.: A perspective on shaping of advanced ceramics by electro discharge machining. Procedia Manuf. 20, 65–72 (2018). https://doi.org/10.1016/j.promfg.2018. 02.009 4. Wang, X., Wang, J., Wang, H.: A heat-resistant organic adhesive for joining Al2O3 ceramics in air and argon atmospheres. J. Manuf. Processes 26, 67–73 (2017). https://doi.org/10.1016/ j.jmapro.2017.01.014 5. Wang, D., Mao, Z.: Microscopic observations of wear of heat-resistant ceramics. Wear 167(1), 87–89 (1993). https://doi.org/10.1016/0043-1648(93)90059-U 6. Wu, J., Hu, C., Xu, X., Zhang, Y., Lu, C., Wang, D.: Preparation and thermal shock resistance of cordierite-spodumene composite ceramics for solar heat transmission pipeline. Ceram. Int. 42(12), 13547–13554 (2016). https://doi.org/10.1016/j.ceramint.2016.05.147 7. Otitoju, T.A., Okoye, P.U., Chen, G., Li, Y., Okoye, M.O., Sanxi, L.: Advanced ceramic components: materials, fabrication, and applications. J. Ind. Eng. Chem. 85, 34–65 (2020). https://doi.org/10.1016/j.jiec.2020.02.002 8. Mishra, R., Ningthoujam, R.S.: High-Temperature Ceramics. Materials Under Extreme Conditions, pp. 377–409 (2017). https://doi.org/10.1016/b978-0-12-801300-7.00011-5 9. Sukharnikova, M.A., Pikalov, E.S., Selivanov, O.G., Sysoev, É.P., Chukhlanov, V.Y.: Development of a batch composition for the production of construction ceramic based on raw material from vladimir oblast: clays and galvanic sludge. Glass Ceram. 73(3-4), 100–102 (2016). https://doi.org/10.1007/s10717-016-9834-7 10. Shakhova, V.N., Vitkalova, I.A., Torlova, A.S., Pikalov, E.S., Selivanov, O.G.: Receiving of ceramic veneer with the use of unsorted container glass breakage. Ecol. Ind. Russ. 23(2), 36–41 (2019). https://doi.org/10.18412/1816-0395-2019-2-36-41 11. Shakhova, V., Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Development of composite ceramic material using cullet. MATEC Web Conf. 193, 03032 (2018). https://doi.org/10.1051/ matecconf/201819303032 12. Shakhova, V.N., Berezovskaya, A.V., Pikalov, E.S., Selivanov, O.G., Sysoev, É.P.: Development of self-glazing ceramic facing material based on low-plasticity clay. Glass Ceram. 76(1-2), 11–15 (2019). https://doi.org/10.1007/s10717-019-00123-4 13. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Development of environmentally safe acid-resistant ceramics using heavy metals containing waste. MATEC Web Conf. 193, 03035 (2018). https://doi.org/10.1051/matecconf/201819303035 14. Awasthi, A., Subhash, G.: Deformation behavior and amorphization in icosahedral boronrich ceramics. Prog. Mater Sci. 112, 100664 (2020). https://doi.org/10.1016/j.pmatsci.2020. 100664 15. Krainova, D.A., Zharkinova, S.T., Saetova, N.S., Raskovalov, A.A., Kuz’min, A.V., Eremin, V.A., Sherstobitova, E.A., Pershina, S.V., Dyadenko, M.V., Zhang, X., Jiang, S.: Influence of cerium oxide on properties of glass–ceramic sealants for solid oxide fuel cells. Russ. J. Appl. Chem. 90(8), 1278–1284 (2017). https://doi.org/10.1134/S1070427217080146

Sanitary and Hygienic Assessment of Ceramic Bricks Containing Galvanic Sludge Anastasiya Kolosova , Evgeniy Pikalov(B)

, and Oleg Selivanov

Vladimir State University named after A.G. and N.G. Stoletovs’, Gor’kogo, 87, 600000 Vladimir, Russia [email protected]

Abstract. The research objective was to perform sanitary and hygienic assessment of ceramic bricks containing low-plasticity clay from the deposit located in the Vladimir region with the addition of galvanic sludge from the local enterprise. To ensure good strength characteristics of ceramic bricks and reduce heavy metals migration from them, boric acid was introduced into the charge. The results of the environmental safety assessment of ceramic bricks based on the composition, developed by the authors of the article. Sanitary and chemical studies were conducted to determine the heavy metals migration into the water and ammonium acetate extracts of samples with minor chipping that imitate the material depletion. Additionally, radiological testing of natural radionuclides activity contained in the studied material was conducted. Since the developed material is odorless and does not contain any organic substances, biocidal and odorometric studies were not carried out. The results of determining the Daphnia magna Straus mortality under the toxic substances influence in the water extract from the studied samples were taken for the sanitary-toxicological assessment of the material. The research results confirm the environmental safety of the ceramic bricks based on the developed composition under conventional operating conditions, which exclude its long-term contact with the acidic environments. Keywords: Building ceramics · Environmental safety · Galvanic sludge · Heavy metals compounds · Heavy metals migration · Maximum permissible concentrations

1 Introduction The enterprises efficiency in all industries is associated with ensuring large scale production of high-quality products at minimal expenditure of raw materials and energy resources, which are provided, on the one hand, by low-waste technologies, and on the other - by expanding the raw material base. Resource base expanding is possible in case of using low-quality materials or secondary resources, thus contributing to the development of low-waste technologies. Another way to reduce the raw materials cost is to use the regional raw material base as much as possible, since it reduces the transportation expenses. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 464–470, 2021. https://doi.org/10.1007/978-3-030-57453-6_44

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Thus, the production process including the recycling of industrial waste from local enterprises is very topical now [1–3]. However, it is worth considering that waste from a number of industries contains toxic components which are harmful for the environment and humans [4–6]. Therefore, additional studies are necessary to confirm the environmental safety of the materials and products containing industrial waste in compliance with the required sanitary and hygienic requirements. The research objective was to perform sanitary and hygienic assessment of ceramic bricks containing low-plasticity clay from the deposit located in the Vladimir region with the addition of galvanic sludge from the local enterprise. Considering that the construction brick in the Vladimir region is produced at relatively small-scale enterprises, dependent on local raw materials and operating under the conditions of shortage of nearby high-quality clay deposits, the important issue is to consider the possibility of producing ceramic bricks using local low-grade clay, with the introduction of galvanic sludge as secondary raw material. The production composition of the studied bricks was previously developed by the article authors and provides high quality products manufacturing [7]. Preliminary environmental assessment of ceramic bricks was performed applying the method of Daphnia magna Straus mortality under the impact of toxic substances present in the water extract from the tested samples, which confirmed the environmental material safety. However, additional comprehensive research is required. To achieve the research objective, the sanitary and hygienic indicators of different compositions containing various components separately and jointly introduced into the charge were studied, allowing determine the environmental safety of each component and confirm the environmental safety of the developed composition as a whole.

2 Materials and Methods The main component of the raw mixture for ceramic bricks production was the clay from Suvorotskoye deposit in the Vladimir region of the following composition (wt%): SiO2 = 67.5; Al2 O3 = 10.75; Fe2 O3 = 5.85; CaO = 2.8; MgO = 1.7; K2 O = 2.4; Na2 O = 0.7 [8– 10]. The above composition shows that the clay does not contain any toxic components and can be considered environmentally safe. The sludge formed as a result of waste water chemical treatment from electroplating plants of “Zavod” Avtopribor” PLC (Vladimir) was also introduced into the charge. The sludge was a pasty product of the moisture from 60 to 70%. The sludge composition included the following compounds (wt%): Zn(OH)2 ≈ 11.3%; SiO2 ≈ 7.08%; Ca(OH)2 ≈ 16.52%; Cr(OH)3 ≈ 9.31%; (Fe2+ )Cr2 S4 ≈ 4.17%; CaCO3 ≈ 40.25%; CaO ≈ 3.45%; ZnO ≈ 2.41%; Cu(OH)2 ≈ 2.38%; Ni(OH)2 ≈ 2.62%; Mn(OH)2 ≈ 0.64%; Pb(OH)2 ≈ 0.14% [4, 7]. The sludge composition contains heavy metals compounds that are hazardous for the environment and human health [11–13]. In this regard galvanic sludge belongs to the 2nd or 3rd hazard class. To ensure good strength characteristics of ceramic bricks and reduce heavy metals migration from them, boric acid was introduced into the charge, corresponding to GOST

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18704-78 [1, 9, 14]. According to the impact degree on human body, boric acid is a moderately dangerous substance (3rd hazard class). Thus, the components introduced into the charge are toxic, therefore, it is necessary to make sanitary and hygienic assessment of the material produced using these components. This assessment was carried out in compliance with the methods and requirements established under the guidelines of MU 2.1.674-97 “Sanitary and hygienic assessment of construction materials, containing industrial waste”. Firstly, sanitary and chemical tests were conducted to detect and quantify the released chemicals into the environment. Taking into account high density of the studied material (from 1996.9 to 2139 kg/m3 ) and, consequently, the relatively insignificant migration of chemicals into the air, their migration degree into one-day aqueous and ammonium-acetate extracts from samples with minor chips was studied to simulate minor material wear. The model media allows creating conditions similar to migration under the influence of adverse environmental factors: acid rain, seasonal temperature changes, and mechanical disruption of material density, which often occurs in real conditions. The maximum permissible concentrations (MPC) of substances in the water bodies for drinking and cultural-domestic water supply were used as criteria for the toxic substances migration from the tested samples to the aquatic environment. Quantitative determination of heavy metals in aqueous extracts from the samples was performed using atomic absorption spectrometer (AAS) “Quantum-Z. ETA-T”. Additionally, radiological studies were carried out using a dosimeter-radiometer MGK-01-10/10 to determine the specific activity of natural radionuclides contained in ceramic bricks based on the developed composition. It depends on natural radioactive isotopes often contained by waste in significantly higher concentrations than traditionally used materials, so for the comprehensive ecological and hygienic expertise, radioactivity testing on is mandatory. The samples were produced from the studied material in compliance with the previously developed technology by the authors basing on semi-dry pressing method. Clay and galvanic sludge were pre-dried reaching the constant mass and crushed for the further selection of particle size fraction of max 0.63 mm. Then all the charge components were first mixed dry, and then water was added and molding mass was produced of 8 wt% humidity. Ceramic samples were manufactured from the resulting mass under the pressing pressure of 15 MPa and maximum firing temperature of 1050 °C for determining sanitary and hygienic parameters.

3 Results The research included sanitary and hygienic studies of the samples produced on the basis of the compositions given in Table 1. The samples were produced and tested in batches of three samples each, and their physical and mechanical characteristics were determined using standard methods.

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Table 1. Samples composition for testing. Composition № Components amount, wt% Galvanic sludge Boric acid 1

–

1

2

–

2

3

2.5

1

4

2.5

2

5

2.5

–

Heavy metals compounds contained in galvanic sludge cause the greatest danger for the environment and human health [11–13], so sanitary and chemical studies consisted in determining their migration from samples. Simultaneously the heavy metals of the highest concentration in the galvanic sludge composition were considered: zinc, chromium, copper and nickel. The tests results are presented in Table 2. Table 2. Results of determining heavy metals migration into test media. Sample

Metal concentration, mg/l

Metals MPC in water bodies for potable and household purposes, mg/l

In extract on distilled water (pH = 7.2)

In ammonium acetate extract (pH = 4.8)

Sample 3

0.001

0.129

1

Sample 4

0.002

0.262

1

Sample 5

0.0008

0.249

1

Sample 3

0.001

0.715

0.1

Sample 4

0.008

0.172

0.1

Sample 5

0.006

1.694

0.1

Sample 3

0.046

0.092

0.05 for Cr6+

Sample 4

0.010

0.051

0.05

Sample 5

0.921

2.680

0.05

Sample 3

0.124

0.674

1

Sample 4

0.056

0.328

1

Sample 5

0.782

1.872

1

Copper

Nickel

Chromium

Zink

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According to the data in Table 1, the heavy metals migration from all the tested samples in neutral environment is significantly less than the established MPC and these samples can be considered safe for standard operating conditions. In the acidic media, sample 4 demonstrated the lowest heavy metals migration, although chromium migration in it approaches the established MPC, and nickel migration significantly exceeds the permissible value. Therefore, long-term contact with the acidic media must be avoided for ceramics based on the tested samples. Likewise, the data from Table 1 shows that separate introduction of galvanic sludge (sample 5), results in the ceramics, characterized by the lowest environmental safety, for both neutral and acidic environments. At the same time, the copper ions migration is effectively blocked, and nickel chromium and zinc ions migration significantly exceeds the migration of these metals in the analyzed samples 3 and 4. Thus, boric acid introduction contributes to the immobilization of heavy metal ions in the ceramic material, which can be explained by the fluxing action of this charge component. On the one hand, the fluxing effect is manifested in the vitreous phase formation, including some heavy metal ions, which at the same time almost completely lose their migration ability into the neutral environments. On the other hand, the vitreous phase contributes to the ceramic particles coating and reduces the material porosity, making it difficult for ceramic grains to contact tested media and reducing such contact area. Samples measurements made during radiological studies showed that the average gamma radiation dose near the samples surface is 0.045 mSv/hour, which corresponds to the radiation safety standards. Since the charge components and the material produced from it do not contain organic substances and compounds, and are odorless, the biocidal and odorometric studies were not carried out. For the sanitary and toxicological assessment of the material, the results of determining Daphnia magna Straus mortality under the effect of toxic substances in the aqueous extract of the studied samples were taken, which were previously carried out and also confirmed the environmental safety of samples 1, 2 and 4 [7]. These results also prove that boric acid facilitated heavy metals immobilization in the ceramic material. However, it is worth considering that boric acid introduction in the amount of more than 2 wt% initiates the decrease of the material environmental safety depending on its low toxicity. Special attention is to be paid to the galvanic sludge introduction in the amount of more than 2.5 wt% not allowing the production of the environmentally safe material using boric acid in the mentioned above amounts. It is possible only if additional fluxing and glass-forming components are used, which make possible the increase of both boric acid and galvanic sludge amount. Basing on this considerations boric acid amount is limited to 2 wt% in this research, and galvanic sludge amount – to 2.5 wt%, allowing the use of low-compound charge composition including low cost raw material components. Thus, according to the previous research results conducted by the authors and current research results, samples 1 and 2 containing boric acid, as well as the sample 4 containing galvanic sludge, can be considered low-toxic.

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4 Conclusions The research results proved that ceramic bricks based on the composition containing no more than 2.5% galvanic sludge and 2% boric acid can be considered the safest for the environment and human health in operating conditions excluding long-term contact with acidic environments. This composition possesses high strength (21.8 MPa) and can be recommended for the ceramic bricks production for internal load-bearing layers during the construction of multi-layer walls, in order to avoid the impact of aggressive environmental factors. Herewith anthropogenic waste from the local enterprise is recycled in the production of environmentally friendly construction material. Moreover, the production of highquality products using low plasticity clay becomes possible. Thus, simultaneously the tasks of both resource saving and environmental protection are being solved.

References 1. Shakhova, V.N., Vitkalova, I.A., Torlova, A.S., Pikalov, E.S., Selivanov, O.G.: Receiving of ceramic veneer with the use of unsorted container glass breakage. Ecol. Ind. Russia 23(2), 36–41 (2019). https://doi.org/10.18412/1816-0395-2019-2-36-41 2. Rehman, M.U., Ahmad, M., Rashid, K.: Influence of fluxing oxides from waste on the production and physico-mechanical properties of fired clay brick: a review. J. Build. Eng. 27, 100965 (2020). https://doi.org/10.1016/j.jobe.2019.100965 3. Al-Fakih, A., Mohammed, B.S., Liew, M.S., Nikbakht, E.: Incorporation of waste materials in the manufacture of masonry bricks: an update review. J. Build. Eng. 21, 37–54 (2019). https://doi.org/10.1016/j.jobe.2018.09.023 4. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Industrial waste utilization in the panels production for high buildings facade and socle facing. E3S Web Conf. 33, 02062 (2018). https://doi.org/10.1051/e3sconf/20183302062 5. Magalhães, J.M., Silva, J.E., Castro, F.P., Labrincha, L.A.: Role of the mixing conditions and composition of galvanic sludges on the inertization process in clay-based ceramics. J. Hazard. Mater. 106(2–330), 169–176 (2004). https://doi.org/10.1016/j.jhazmat.2003.11.011 6. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Energy efficiency improving of construction ceramics, applying polymer waste. Adv. Intell. Syst. Comput. 983, 786–794 (2019). https://doi.org/10.1007/978-3-030-19868-8_77 7. Pikalov, E.S., Selivanov, O.G., Chukhlanov, V.Y., Sukharnikova, M.A.: Application of regional technogenic wastes in the production of ceramic products. Ecol. Ind. Russia 21(6), 24–29 (2017). https://doi.org/10.18412/1816-0395-2017-6-24-29 8. Kolosova, A., Sokolskaya, M., Pikalov, E., Selivanov, O.: Production of facing ceramic material using cullet. E3S Web Conf. 91, 02003 (2019). https://doi.org/10.1051/e3sconf/201991 02003 9. Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Development of environmentally safe acid-resistant ceramics using heavy metals containing waste. In: MATEC Web of Conferences, vol. 193, p. 03035 (2018). https://doi.org/10.1051/matecconf/201819303035 10. Shakhova, V.N., Berezovskaya, A.V., Pikalov, E.S., Selivanov, O.G., Sysoev, É.P.: Development of self-glazing ceramic facing material based on low-plasticity clay. Glass Ceram. 76(1-2), 11–15 (2019). https://doi.org/10.1007/s10717-019-00123-4

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11. Shakhova, V., Vitkalova, I., Torlova, A., Pikalov, E., Selivanov, O.: Development of composite ceramic material using cullet. In: MATEC Web of Conferences, vol. 193, p. 03032 (2018). https://doi.org/10.1051/matecconf/201819303032 12. Bocanegra, J.J.C., Mora, E.E., González, G.I.C.: Encapsulation in ceramic material of the metals Cr, Ni, and Cu contained in galvanic sludge via the solidification/stabilization method. J. Environ. Chem. Eng. 5(4), 3834–3843 (2017). https://doi.org/10.1016/j.jece.2017.07.044 13. Pérez-Villarejoa, L., Martínez-Martíneza, S., Carrasco-Hurtadob, B., Eliche-Quesadac, D., Ureña-Nietod, C., Sánchez-Sotoe, P.J.: Valorization and inertization of galvanic sludge waste in clay bricks. Appl. Clay Sci. 105–106, 89–99 (2015). https://doi.org/10.1016/j.clay.2014. 12.022 14. Perovskaya, K., Petrina, D., Pikalov, E., Selivanov, O.: Polymer waste as a combustible additive for wall ceramics production. E3S Web Conf. 91, 04007 (2018). https://doi.org/10. 1051/e3sconf/20199104007

Mathematical Modeling and Synthesis of an Electrical Equivalent Circuit of an Electrochemical Device Yevgeny Gerasimenko , Alla Gerasimenko , Yuri Gerasimenko , Dmitry Fugarov(B) , Olga Purchina , and Anna Poluyan Don State Technical University, Gagarina Square, 1, Rostov-on-Don 344010, Russia [email protected]

Abstract. The given research is aimed at the mathematical modeling and synthesis of the electrical equivalent circuit of an electrochemical device as an element of an electrical circuit. Mathematical modeling is completed in the result of a systematic study of the concentration and electric fields in a two-electrode electrochemical system. The object of study is considered to be linear with constant parameters. The object sizes are considered to be insignificant that’s why the electric current density on the electrodes surface is assumed to be equally distributed. Diffusion in the electrolyte becomes the limiting stage of electrode processes in the system with a finite mass transfer rate. The Laplace operator method is used as a research method, it is used to calculate the voltage at the electrodes of an electrochemical device. The mathematical model of an electrochemical device has been developed in the run of the system study and an electrical equivalent circuit has been synthesized, which contains infinite number of parallel branches including active and reactive elements. Besides, analytical formulas have been obtained that can be used in the process of calculation individual discrete parameters on these branches. In case of engineering calculations, the number of branches in the electrical equivalent circuit can be limited with the finite number, specified by accuracy of the calculations. It should be also mentioned that as a result of the study, it has become possible to synthesize all kinds of particular characteristics of an electrochemical device as well as the opportunity to study the dynamics of various transition processes in it. Keywords: Boundary conditions · Electrolyte concentration · Electric potential surge · Nernst equation · Electrical equivalent circuit

1 Introduction For the purpose of rigorous calculation and study of electrochemical devices’ dynamics, their advanced mathematical models are required [1]. The latter may only be obtained as a result of dynamical system study of electric and mass transfer in them. An important aspect of this study is the closed relation between concentration and electric fields with the help of the processes occurring at the electrode - electrolyte interface of electrode © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 471–480, 2021. https://doi.org/10.1007/978-3-030-57453-6_45

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processes. The ultimate goal of an electrochemical device system research is to obtain its mathematical model as an element of an electrical circuit [2]. An electrochemical device that consisted of two identical plane-parallel electrodes was studied [3]. Current I(t) flows through this device, while current density is uniformly distributed on the surface of electrodes. The electrodes area is s, and the distance between the electrodes is . The limiting stage of electrode process kinetics molecular is  hyperbolic diffusion in electrolyte that occurs with constant rate V = D τ where D is diffusion coefficient and [tau] is relaxation constant. Let us consider spatiotemporal concentration field of electrolyte C (x; t) as monadic, with the x coordinate normal to electrodes surfaces. Coordinates x = 0 and x =  correspond to the electrodes (Fig. 1).

U(t)

s -

+

+ - - + I(t)

0

l

X

Fig. 1. Geometry of an electrochemical device.

In relation to concentration field of the electrolyte C (x; t) the following initial boundary value problem [4] is set [5] in the interval [0; ]: ∂ 2C ∂ 2C ∂C +τ 2 =D 2 ∂t ∂t ∂x

(1)

C(x; 0) = C0

(2)

∂C (x; 0) = 0 ∂t

(3)

I (t) ∂C (0; t) = N ∂x s

(4)

Mathematical Modeling and Synthesis of an Electrical Equivalent Circuit

∂C I (t) (l; t) = N ∂x s

473

(5)

where N > 0 is the kinetic constant [5, 6] of the electrode reaction; C0 is the initial concentration of electrolyte.

2 Materials and Methods The problem (1)–(5) can be easily solved using the Laplace operational method [6]. Let ◦ ◦ ◦ ◦ there be correspondences C(x; t) = C (x; p), I (t) = I (p). ◦

◦

◦

In relation to the image C (x; p), we get the following boundary problem: ◦

C0 (τ · p + 1) d C (x; p) p(τ · p + 1) ◦ − C (x; p) = − 2 dx D D ◦

(6)

◦

d C (0; p) I (p) =N dx s ◦

(7)

◦

d C (l; p) I (p) =N dx s

(8)

General solution of a differential Eq. (6) has the following structure: (9) ◦

˜ Where C(x; p) is the general solution of a homogeneous differential equation. ◦

˜ p) p(τ · p + 1) ◦˜ d 2 C(x; C(x; p) = 0 − dx2 D

(10)

is some partial solution of the initial inhomogeneous Eq. (9). In order to solve (10) let us compose a secular equation: k2 −

p(τ · p + 1) =0 D

(11)

Roots of Eq. (11):  k1,2 = ±

p(τ · p + 1) D

make it possible to write the general solution of (10) as:   ◦ p(τ · p + 1) p(τ · p + 1) ˜ x + B(p)ch x C(x; p) = A(p)sh D D where A(p) and B(p) are arbitrary constants of integrating that are to be defined.

(12)

(13)

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Partial solution of Eq. (6) can be written as: (14) Insertion of (12) and (13) into (9) leads to the following result:   ◦ p(τ · p + 1) p(τ · p + 1) C0 x + B(p)ch x+ C (x; p) = A(p)sh D D p

(15)

Coefficients A(p) and B(p) can be found from boundary conditions (7) and (8). To do so, let us differentiate (15) by x: ◦

d C (x; p) = dx



    p(τ · p + 1) p(τ · p + 1) p(τ · p + 1) x + B(p)sh x (16) A(p)ch D D D

From (16) with x = 0, we have:  ◦ d C (0; p) p(τ · p + 1) = A(p) dx D

(17)

Collating (7) and (17) leads to the following result: ◦

I (p)

A(p) = N  s p(τ ·p+1) D

(18)

Insertion of (18) and x = l into (16) results in:    ◦ ◦ d C (l; p) N I (p) p(τ · p + 1) p(τ · p + 1) p(τ · p + 1) = ch l + B(p) sh l dx s D D D Collating (8) and (19), we define coefficient B(p).  ◦ p(τ ·p+1) l I (p)sh D 2  B(p) = N  p(τ ·p+1) p(τ ·p+1) l s ch D D 2

(19)

(20)

◦

General solution C (x; p) set by expression (15) with regard to (18) and (20) gets the following form:    ◦ p(τ ·p+1) N x − 2l (p)sh I ◦ D C0  +  (21) C (x; p) = p p(τ ·p+1) l s p(τ ·p+1) ch D D 2 In any electrochemical system at the electrode-electrolyte interface there is a surge [7] of electric potential that is uniquely defined with accepted allowances by the value

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of electrolyte concentration on the interface surface. This dependence is set by Nernst equations that are defined in the case studied by the following linear relations [8]: − (t) = g0 + g1 C(0; t)

(22)

+ (t) = g0 + g1 C(l; t)

(23)

where [delta] − (t) is the potential surge on the cathode; [delta] + (t) − s the potential surge on the anode; g 0 > 0, g 1 > 0 are parameters of linear approximation of the Nernst equation. Applying the Laplace transformation to relations (22) and (23), we obtain the following operator dependencies [9, 10]: (24) (25) Voltage U(t) at the electro-chemical device is calculated using the 2-d Kirchhoff’s Law: (26) where is the resistance of the electrolyte column between the plates. Here [gamma] is specific conductivity of the electrode. From the 2-d Kirchhoff’s Law we get: U (t) = + (t) − − (t) + I (t)re

(27) (28)

Let us insert (24) and (25) into (27). ◦  ◦ ◦ ◦ U (p) = g1 C (l; p) − C (0; p) + I (p)re ◦

(29)

◦

We get C (0; p) and C (l; p) from (21):

 ◦ l sh p(τ ·p+1) N I (p) C0 D 2  + · C (0; p) = p s p(τ ·p+1) l ch p(τ ·p+1) D D 2  ◦ l sh p(τ ·p+1) ◦ N I (p) C0 D 2  + · C (l; p) = p s p(τ ·p+1) p(τ ·p+1) l ch D D 2 ◦

From (29), using (30), (31), we obtain:  l 2Ng1 sh p(τ ·p+1) ◦ ◦ D 2  U (p) =  · I (p) + r I (p) l s p(τ ·p+1) ch p(τ ·p+1) D D 2

(30)

(31)

(32)

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3 Results Synthesis of an electrical equivalent circuit. The obtained correlation (32) is the basis for synthesis [11–13] of an electrical equivalent circuit. ◦

Coefficient I (p) of the first summand in (32) is the diffusion-hyperbolical impedance:  l 2Ng1 sh p(τ ·p+1) D 2  Z(p) =  · (33) p(τ ·p+1) l s p(τ ·p+1) ch D D 2 The value inverse to it, i.e., conductivity, is expressed as:   p(τ · p + 1) p(τ · p + 1) l s cth Y (p) = 2Ng1 D D 2

(34)

Let us decompose [2] the hyperbolic function included into (34) into the following sequence:   ∞ 2 p(τ · p + 1) l p(τ · p + 1) l 1 cth =  · 2 + (35) p(τ ·p+1) 2 2 D 2 D π p(τ ·p+1) 2 l +k l k=1 4Dπ D Inserting the last decomposition into (34) and omitting intermediate calculations, we obtain: Y (p) =

2s 2 2s ∞ s g1 Nl p + g1 Nlτ p + 2 2 2Ng1 l p2 + 1 p + 4k 2π D k=1

τ

(36)

l τ

Conductivity Y(p) defined by formula (36) meets requirements of physical feasibility using passive electric elements [14]. Let us show that each member of the series in formula (36) can be modeled using the electrical circuit (Fig. 2) [15,16].

Lk Ck

rk

(1)

rk(2)

Fig. 2. Substitution branch electric drawing.

Impedance of the circuit shown in Fig. 2 has the form:     (1) (2) (1) (2) (2) p2 Lk Ck rk + rk + p Lk + Ck rk rk + rk   Zk (p) = . (2) pCk pLk + rk

(37)

Mathematical Modeling and Synthesis of an Electrical Equivalent Circuit

Accordingly, conductivity of the branch is given by expression:   (2) pCk pLk + rk     Yk (p) = (1) (2) (1) (2) (2) p2 Lk Ck rk + rk + p Lk + Ck rk rk + rk

477

(38)

Let us reduce expression (38) to (36): p2 Yk (p) =

1

(1) (2) rk +rk

+p

  (1) (2) Lk rk +rk   p2 + p (1) (2) Lk Ck rk +rk

(2)

r  k  (1) (2) Lk rk +rk

+

(2)

(39)

r  k  (1) (2) Lk Ck rk +rk

Comparing the corresponding coefficients in (36) and (39), we obtain the system of equations for determining parameters of an electrical equivalent circuit branch: ⎧ 1 2s ⎪ (1) (2) = g1 Nl , ⎪ ⎪ rk +rk ⎪ ⎪ (2) ⎪ r ⎪ ⎪  k  = 2s , ⎪ (1) g1 Nlτ ⎪ ⎨ Lk Ck rk +rk(2) (1) (2) (40) Lk +Ck rk rk   = 1, ⎪ ⎪ (1) (2) τ ⎪ L C +r r ⎪ k k k k ⎪ ⎪ (2) ⎪ ⎪ rk 4k 2 π 2 D ⎪ ⎪ ⎩ L C r (1) +r (2)  = l 2 τ . k

k

k

k

Solving the latter system of equations leads to the following results: Ck =

sl ; 2g1 Nk 2 π 2 D

(41)

(1)

g1 N 4k 2 π 2 τ D 2sl

(42)

(2)

2g1 Nk 2 π 2 τ D sl

(43)

Lk =

2g1 Nk 2 π 2 τ 2 D sl

(44)

rk = rk =

Taking into account the structure of expressions (32) and (30), we obtain a complete electrical equivalent circuit of an electrochemical device (Fig. 3).

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C1

C2

Ck

r1(1)

r2(1)

rk(1)

rg

L1

r1(2)

L2

r2(2)

Lk

rk(2)

Fig. 3. Electrical equivalent circuit of an electrochemical device.

4 Discussion In this scheme, resistance rg that models ohmic losses in the process of electrode polarization is calculated as follows: rg =

g1 Nl s

(45)

With initial data: s = 0.01 m2 ; l = 0.01 m; g1 = 0.025 V/(Kmol/m3 ); N = 5.45 (Kmol/m3 )m·A−1 ; τ2 = 1·10−6 s ; γ = 35 −1 ·m−1 ; D = 1.65·10−6 m2 ·s−1 we obtain the following values of electrical equivalent circuit parameters: re = 0.029 ; rg = 0.136 ; (1) (2) C1 = 22.52 F; r1 = 4.44·10−8 ; r1 = 4.44·10−8 ; L1 = 4.44·10−8 μH; (1) (2) C2 = 5.63 F; r2 = 1.775·10−7 ; r2 = 1.775·10−7 ; L2 = 1.775·10−7 μH; (1) (2) C3 = 2.50 F; r3 = 3.99·10−7 ; r3 = 3.99·10−7 ; L2 = 3.99·10−7 μH. If a scientific calculation is needed for a transient current process with given input voltage, calculation result is represented as a partial sum of an infinite series. The number of summands in partial sum of the series is determined by a predetermined current calculation error. In engineering calculations of transient current, an electrochemical device with a finite number of parallel branches with reactive elements is used.

5 Conclusions 1. Rigorous scientific calculations of an electrochemical device are possible only in case of a system study of its physical fields (concentration and electrical ones).

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2. A mathematical model of an electrochemical device as an element of an electric circuit can be built after calculating operating voltage at its electrodes. 3. The electrical equivalent circuit of an electrochemical device contains an infinite number of parallel branches containing active and reactive elements. 4. When calculating the current in an external circuit of an electrochemical device connected to a voltage source, there is the problem of numerical inversion of the integral Laplace transformation for a complex transcendental expression. 5. The obtained expression for operating impedance of an electrochemical device makes it possible to synthesize all kinds of its particular characteristics and to study the dynamics of any transition process.

References 1. Solomentsev, K.Yu.: Interference elimination in digital controllers of automation systems of oil and gas complex. J. Phys: Conf. Ser. 1015, 032179 (2018). https://doi.org/10.1088/17426596/1015/3/032179 2. Fugarov, D.D.: Magnetodielectric AC measuring transducer for automation systems in oil refineries. J. Phys: Conf. Ser. 1333, 062020 (2019). https://doi.org/10.1088/1742-6596/1333/ 6/062020 3. Kim, Y., Yang, C.: Electret formation in transition metal oxides by electrochemical amorphization. NPG Asia Mater. 12, 1 (2020). https://doi.org/10.1038/s41427-019-0187-x 4. Oda, K., Saitoh, H., Hoaki, Y., Shimoda, H., Hirao, T., Ichiyoshi, W., Takase, S., Shimizu, Y.: A lithium-ion conductive Li1.5Al0.25Ga0.25Ti1.5(PO4)3 solid electrolyte for electrochemical device. Solid State Ionics 346, 115212 (2020). https://doi.org/10.1016/j.ssi.2019.115212 5. Poluyan, A.Yu.: Solution of task on the minimum cost data flow based on bionic algorithm. J. Phys: Conf. Ser. 1333, 032056 (2019). https://doi.org/10.1088/1742-6596/1333/3/032056 6. Minakshi, M., Mitchell, D.R.G., Jones, R.T., Pramanik, N.C., Jean-Fulcrand, A., Garnweitner, G.: A hybrid electrochemical energy storage device using sustainable electrode materials. ChemistrySelect 5(4), 1597–1606 (2020). https://doi.org/10.1002/slct.201904553 7. Gerasimenko, Y.Y., Kucherenko, S.M., Lipkin, S.M., Lipkin, M.S.: Potential step study of intercalation processes. Electrochem. Soc. Trans. 58(14), 89–94 (2014). https://doi.org/10. 1149/05814.0089ecst 8. Poluyan, A.Yu.: Application of bionic and immune algorithms for the solution of ambiguous problems of transportation routing. J. Phys: Conf. Ser. 1333, 032057 (2019). https://doi.org/ 10.1088/1742-6596/1333/3/032057 9. Fugarov, D.D., Gerasimenko, Y.Y.: Methods for revealing hidden failures of automation system for technological processes in oil and gas sector. J. Phys: Conf. Ser. 1118, 012055 (2018). https://doi.org/10.1088/1742-6596/1118/1/012055 10. Baumann, A.E., Burns, D.A., Liu, B., Thoi, V.S.: Metal-organic framework functionalization and design strategies for advanced electrochemical energy storage devices. Commun. Chem. 2(1), 86 (2019). https://doi.org/10.1038/s42004-019-0184-6 11. Poluyan, A.Y.: Adaptive algorithm of selecting optimal variant of errors detection system for digital means of automation facility of oil and gas complex. J. Phys: Conf. Ser. 1015, 022013 (2018). https://doi.org/10.1088/1742-6596/1015/2/022013 12. Carré, C., Gunkel-Grillon, P., Serres, A., Jeannin, M., Sabot, R., Quiniou, T.: Laboratory and in-situ investigations for trapping Pb and Ni with an unusual electrochemical device, the calcareous deposit in seawater. Sci. Rep. 9(1), 3400 (2019). https://doi.org/10.1038/s41598019-40307-0

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13. Pound, B.G.: The use of electrochemical techniques to evaluate the corrosion performance of metallic biomedical materials and devices. J. Biomed. Mater. Res. Part B Appl. Biomater. 107(4), 1189–1198 (2019). https://doi.org/10.1002/jbm.b.34212 14. Regu, T., Ambika, C., Karuppasamy, K., Jeon, J.-H., Jeong, Y.-T., Vikraman, D., Raj, T.A.B., Kim, H.-S.: Al2O3-incorporated proton-conducting solid polymer electrolytes for electrochemical devices: a proficient method to achieve high electrochemical performance. Ionics 25(11), 5117–5129 (2019). https://doi.org/10.1007/s11581-019-03075-5 15. Wang, W., Fu, Y., Lv, Q., Bai, H., Li, H., Wang, Z., Zhang, Q.: Miniaturized device with a detachable three-electrode system and vibration motor for electrochemical analysis based on disposable electrodes. Sens. Actuators, B: Chem. 297, 126719 (2019). https://doi.org/10. 1016/j.snb.2019.126719

Correlation Analysis of the Morbidity and Pollution Using GIS Olga Burdzieva(B)

, Vladislav Zaalishvili , Aleksandr Kanukov , and Tamaz Zaks

Geophysical Institute of the Vladikavkaz Scientific Centre of the Russian Academy of Sciences, 93a Markova Str., Vladikavkaz 362002, Russia [email protected]

Abstract. The article considers the environmental pollution of the urbanized area with heavy metals and explores their effect on the oncological incidence of the population. Using modern GIS technologies, the content of heavy metals in soils of the city of Vladikavkaz was interpolated according to the available results of laboratory studies of soil testing and the corresponding maps were constructed. According to the results of the studies, a linear dependence of the oncological morbidity of the population on the content of heavy metals in soils is obtained. The reliability coefficient of approximation R2 = 0.14 indicates that the contribution of the content of heavy metals in soils to the total incidence of oncology in the population can be up to 14% of the total contribution of all factors that form the final value of the incidence. It was found that the following elements have the greatest impact in decreasing order: arsenic, mercury, and cadmium. Keywords: Ecology · Urban territory · Pollution · Heavy metals · Morbidity · Regression analysis

1 Introduction In addition to harmful influence to nature, environmental pollution leads to various diseases of the population living in the contaminated area, including cancer. In the Republic of North Ossetia-Alania, environmental pollution occurs mainly due to enterprises of non-ferrous metallurgy and vehicles [1–8]. The capital of the republic the city of Vladikavkaz is exposed to the greatest pollution. The main stationary sources of pollution and the largest number of vehicles are located there. In rural areas of the republic, the condition of atmospheric air is stably satisfactory due to the absence of large industrial enterprises and a large number of vehicles. Besides that the considered territory is characterized by high seismic hazard [9–16]. In addition to its direct destructive impact, an earthquake can cause an environmental disaster in the territories where industrial enterprises that are producing or processing hazardous chemicals are located.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 481–491, 2021. https://doi.org/10.1007/978-3-030-57453-6_46

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2 The Incidence of Neoplasms in the City of Vladikavkaz According to the Zonation of Urban Clinics Anthropogenic environmental pollution has a pronounced effect on the formation of population health. The steady increase in the flow of toxic substances into the environment primarily affects the health of the population. Assessing the significance of environmental pollution according to the biological responses of the human body, according to health indicators, is more objective than comparing the concentrations of individual pollutants with hygiene standards, since it integrally takes into account the influence of all, including unidentified pollutants, their integrated and combined effect on the human body [17–27]. Previously, we created the incidence rate map by the generally accepted method of territorial polyclinic zonation. This method involves the calculation of the incidence of the population for each individual clinic [28–32]. The calculation was made for the adult population, by calculating the ratio of the number of newly registered cases of cancer in various locations to the number of people served by this clinic [33–36]. The obtained value was divided by a thousand, which made it possible to find out the number of diseased people per thousand of the population. From polyclinics No. 1, 3, 4, 5, 7 data was selected on the incidence of malignant tumors in various regions of the city of Vladikavkaz. The resulting material designed in the form of a database was superimposed on a digital map-scheme of city development. In other words, in GIS technologies, the place of residence of the patients (streets, buildings, their numbers) were applied to the map of the existing buildings, thus forming a real distribution of the incidence of malignant tumors over the city area. The incidence values for different years were obtained, as well as the average value for several years, which was applied to the map (see Fig. 1).

Correlation Analysis of the Morbidity and Pollution Using GIS

Fig. 1. The incidence of neoplasms in the city according to zonation of urban clinics.

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3 Methods As it was mentioned above, there are four polyclinics serving the adult population at the place of residence in Vladikavkaz. Accordingly, there are only four polygons with calculated incidence for the entire territory. To conduct regression and correlation analyzes the incidence of the population on a uniform grid of 500 by 500 m was calculated. The task of constructing such a grid in the form of a shape-file often arises in ArcGIS. Such a grid, for example, can be used as a coordinate grid. The easiest way to solve this problem is realized by using the Create Fishnet utility from the Feature Class toolbox. This utility is located in the ArcToolbox section and the following fields are filled in for its use: • In the Output Feature Class window, the name of the output mesh shape-file is set. To make it easier to specify the extreme points the name of the layer for which the grid is being built can be loaded. • In the Cell Size field, the grid width and height are set (in our case, 500 m). • The Number of Rows/Columns field the number of grid cells is set. The result of using the utility is a shape-file in which each cell has a polygon type. By adding an additional field to each polygon, using additional tools in ArcGIS the necessary parameters can be calculated. In our case, it was necessary to calculate the number of adults living within each such polygon, the number of newly registered cases of cancer and based on these data, calculate the incidence according to the constructed grid. This task is solved using the Spatial Join utility from the Analysis Tools of Overlay section. Using a spatial join, a comparison is made between the rows of the Join Features table and the Target Features based on their spatial location. According to the default parameters, all attribute values of join objects are connected to the attributes of the target objects and their copies are created in the output object class. The user can specify which attributes will be added to the output feature class by making changes to the parameter Field Map of Join Features. Two new fields, Join_Count and TARGET_FID, are always added to the output feature class. Join_Count is a counter showing the number of join objects corresponding to each target object (TARGET_FID). If for the Join Operation parameter value JOIN_ONE_TO_MANY is set, more than one row can be matched for each target in the output class. The JOIN_FID field is necessary to determine which target object (TARGET_FID) was joined to this or that object. A value -1 in the JOIN_FID field indicates that there are no objects corresponding to a given spatial relation to the target object. All target objects of the source class are saved to the output feature class if JOIN_ONE_TO_ONE was selected for the Join Operation parameter and the Keep All Target Features option was set. After testing this utility, we get a new layer at the output, which in the Join Count column contains the statistics we need. The constructed incidence map is presented in Fig. 2.

Correlation Analysis of the Morbidity and Pollution Using GIS

Fig. 2. Map of the incidence of the population of Vladikavkaz.

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As can be seen from the constructed maps, it is not possible to unambiguously identify areas with high incidence rates in one area. Analyzing the constructed maps, it can be assumed that the territory of the city is not large enough to show differences in the incidence of the population, due to the distance to the epicenters (core) or sources of pollution.

4 Results There are close correlation between the value of the obtained amount of metals and their content in the body of a person working in production. In particular, chemical workers have noted an accelerated development of pathology of bioelectric and contractile function of the heart, atherogenic changes in blood serum, neurocirculatory dystonia, myocardial dystrophy, atherosclerosis, and chronic heart failure. When considering the situation with the population not working in such industries, but living in a halo of their distribution, it should be noted that there is a direct relationship between chemical pollution of the environment and an increase in the frequency of allergies, bronchopulmonary pathology, thyroid hyperplasia, caries, and a violation of neuropsychic and physical development. Ecological conditionality of congenital malformations and malignant tumors, which are markers of chronic exposure to xenobiotics, is also noted. Since sampling was carried out at certain points in the city, the Interpolation tool was used to obtain a map of the content of heavy metals in the soils along the city. An example of such a map is shown in Fig. 3. The result of the calculation is a map in the form of a raster layer. To calculate the average value of the content of heavy metals in each cell for which the incidence rate was calculated using the tool “Spatial join”, it is necessary that the layers are in the shape file format. To do this, a layer consisting of points was created, to which data on the concentration of heavy metals at this point were assigned as attribute information. Then, using the tool “Spatial join”, the average value of all points included in the polygon was calculated, for which the incidence value was calculated.

Correlation Analysis of the Morbidity and Pollution Using GIS

Fig. 3. The population incidence map of Vladikavkaz.

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5 Discussions In 2014, the state-financed institution “Directorate for the Implementation of Environmental Programs and Environmental Education” and the Open Joint-Stock Company “Sevosettingeoekomonitoring” conducted studies to assess the state of soil pollution, including pesticides and radioactive substances, and prepared environmental maps with geopathic zones. Comparison of these data with the data of our studies showed good agreement. Thus, based on our data, a very voluminous table was compiled, consisting of 124 rows, each of which contains information on the incidence of the population within each of the sectors and on the average values of the content of the following elements in the soil of the city: cadmium, antimony, manganese, vanadium, lead, arsenic, mercury, copper, nickel, zinc, chromium. According to the results of the studies, a linear dependence of the oncological incidence of the population on the content of heavy metals in soils was obtained. The reliability coefficient of approximation R2 = 0.14 indicates that the contribution of the content of heavy metals in soils to the total incidence of oncology in the population can be up to 14% of the total contribution of all factors that form the final value of the incidence. It was found that the following elements have the greatest impact on public health in decreasing order: arsenic, mercury and cadmium.

6 Conclusion 1. Correlation and regression relationships between the oncological morbidity of the population and the content of heavy metals in soils have been established. 2. For the analysis, the territory of Vladikavkaz city was divided into 118 identical sites, for each of which the oncological incidence of the population was calculated. 3. An assessment of the number of residents living on each of the sites based on the area and number of storeys of private houses, the area, the number of entrances and number of storeys for multi-story buildings and the average population density has been made. 4. Using modern GIS technologies, the heavy metals content in the soils of the city of Vladikavkaz was interpolated according to the available results of laboratory tests of soil testing and the corresponding maps were constructed. 5. The content of the following elements in city soils was studied: cadmium, antimony, manganese, vanadium, lead, arsenic, mercury, copper, nickel, zinc, chromium. 6. Based on the processing of the results of the studies, a linear dependence of the oncological morbidity of the population on the content of heavy metals in soils is established. 7. The reliability coefficient of the approximation R2 = 0.14 indicates that the contribution of the content of heavy metals in soils to the total incidence of oncology can be up to 14% of the total contribution of all factors that form the final value of the incidence. 8. It has been established that the following elements: arsenic, mercury and cadmium have the greatest negative impact on the incidence of the population in descending order.

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16. Parada, S.G., Chotchaev, Kh.O., Berger, M.G., Magkoev, T.M., Bekuzarova, S.A., Burdzieva, O.G., Zaks, T.V., Komzha, A.L.: Sodium geochemistry in terrigenous complexes in connection with problem of gold content. Adv. Eng. Res., 243–249 (2019). https://doi.org/10.2991/ciggg18.2019.46 17. Balée, W.: The Research Program of Historical Ecology. Annu. Rev. Anthropol. 35, 75–98 (2006). https://doi.org/10.1146/annurev.anthro.35.081705.123231 18. Patz, J., Campbell-Lendrum, D., Holloway, T., Foley, J.: Impact of regional climate change on human health. Nature 438, 310–317 (2005). https://doi.org/10.1038/nature04188 19. Rogozhin, E.A., Milyukov, V.B., Zaalishvili, V.B., Ovsyuchenko, A.N., Mironov, A.P., Gorbatikov, A.V., Melkov, D.A., Dzeranov, B.V.: Characteristics of modern horizontal movements in central sector of greater caucasus according to gps observations. Adv. Eng. Res., 250–254 (2019). https://doi.org/10.2991/ciggg-18.2019.47 20. Svalova, V.B., Zaalishvili, V.B., Ganapathy, G.P., Nikolaev, A.V., Melkov, D.A.: Landslide risk in mountain areas. Geol. Geophys. Russ. South 9(2(32)), 109–126 (2019). https://doi. org/10.23671/vnc.2019.2.31981 21. Zaalishvili, V.B., Chotchaev, Kh.O., Melkov, D.A., Kanukov, A.S., Magkoev, T.T., Gabeeva, I.L., Dzobelova, L.V., Shepelev, V.D.: Complex analysis of geological data and use of velocity model of mms on central caucasus sections. Adv. Eng. Res., 319–324 (2019). https://doi.org/ 10.2991/ciggg-18.2019.61 22. Masselot, P., Chebana, F., Ouarda, T., Bélanger, D., St-Hilaire, A., Gosselin, P.: A new look at weather-related health impacts through functional regression. Sci. Rep. 8, 15241 (2018). https://doi.org/10.1038/s41598-018-33626-1 23. Myers, S., Patz, J.: Emerging threats to human health from global environmental change. Annu. Rev. Environ. Resour. 34, 223–252 (2009). https://doi.org/10.1146/annurev.environ. 033108.102650 24. Hobbs, R., Cramer, V.: Restoration ecology: interventionist approaches for restoring and maintaining ecosystem function in the face of rapid environmental change. Annu. Rev. Environ. Resour. 33, 39–61 (2008). https://doi.org/10.1146/annurev.environ.33.020107.113631 25. Ellis, E.: Ecology in an anthropogenic biosphere. Ecol. Monogr. 85(3), 287–331 (2015). https://doi.org/10.1890/14-2274.1 26. Burdzieva, O.G., Zaalishvili, V.B., Chotchaev, Kh.O., Melkov, D.A., Dzeranov, B.V.: Engineering-geological and hydrogeological features of the Dzuarikau-Tskhinval gas pipeline installation and environmental aspects of its operation in high seismicity conditions. Mater. Sci. Eng., 012–021 (2019). https://doi.org/10.1088/1757-899x/663/1/012021 27. Giorgobiani, T.V.: Conditions of formation of the alpine folded system of the Greater Caucasus and unique features of it’s structure. Geol. Geophys. Russ. South 1, 43–57 (2019). https://doi. org/10.23671/VNC.2019.1.26787 28. Chernov, Y.K., Chernov, A.Y., Chitishvili, M.I.: Models of strong ground motions for probabilistic detailed seismic zoning of the territory of North Ossetia-Alania. Geol. Geophys. Russ. South 3, 161–178 (2019). https://doi.org/10.23671/VNC.2019.3.36753 29. Beriev, O.G., Zaks, T.V., Kanukov, A.S.: Investigation of ecogeophysical and meteorological factors of the environment of Vladikavkaz. Geol. Geophys. Russ. South 3, 27–39 (2017). https://doi.org/10.23671/VNC.2017.3.9503 30. Driscoll, D., Lindenmayer, D.: Framework to improve the application of theory in ecology and conservation. Ecol. Monogr. 82(1), 129–147 (2012). https://doi.org/10.1890/11-0916.1 31. Byerly, H., Balmford, A., Ferraro, P., Wagner, C., Palchak, E., Polasky, S., Ricketts, T., Schwartz, A., Fisher, B.: Nudging pro-environmental behavior: evidence and opportunities. Front. Ecol. Environ. 16(3), 159–168 (2018). https://doi.org/10.1002/fee.1777 32. Ferguson, J.M., Reichert, B.E., Fletcher, R.J., Jager, H.I.: Detecting population–environmental interactions with mismatched time series data. Ecology 98(11), 2813–2822 (2017). https:// doi.org/10.1002/ecy.1966

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GIS Simulation of the Geological Objects’ Soil Conditions: Strong Motion Banks and Databases Vladislav Zaalishvili1,2(B) , Aleksandr Kanukov2 , Dmitry Melkov2 Konstantin Kharebov2 , and Madina Fidarova2

,

1 North Ossetian State University after K.L. Khetagurov, Vatutina 44-46, 362025

Vladikavkaz, North Ossetia - Alania, Russia [email protected] 2 Geophysical Institute of Vladikavkaz Scientific Center, Markov Street, 93a, 362002 Vladikavkaz, Russia

Abstract. Evaluation of the soil conditions influence on the seismic effect of possible earthquakes includes determination of physical and mechanical conditions of soils and simulation of the effects considering the soil stratum. Thereat mathematical models are based on some assumptions and idealizations. Otherwise strong motion databases and banks give real instrumental data on site effect. The article considers the investigation of soil conditions and their simulation in an indissoluble connection based on the procedure of seismic hazard assessment of the soils of Vladikavkaz. The results of strong-motion databases use (for example, K-NET) for selecting seismic records according to the fundamental characteristics of earthquakes (magnitude, source depth, epicentral distance) and soil conditions of the corresponding stations based on the greatest similarity of the ground models are given. The seismic intensity increments for soils widespread in the territory of Vladikavkaz are obtained. For clay soils with a thickness of about 20 m with the presence of soils of soft plastic consistency, the increment is 1 point relative to the distribution of clay soils of semi-solid consistency with a thickness of up to 5 m. For pebbles with a filler >30%, the increment is 0 points and with a filler 30%, the increment is 0 points and with a filler Fcr = 1.9; the significance level of the zero hypothesis is 5%; the numbers of degrees of freedom to the explained dispersion dfe = 9; the number of degrees of freedom of the explained dispersion for the remainder dfr = 115). The compliance of this model and the initial dependences of process parameters are confirmed by Figs. 1, 2 and 3. It should be noted that the non-stationarity of the obtained characteristics stated above and the object of set forth by the research as the extreme control system cause the sufficiency of high-quality coincidence of real and simulated (calculated) dependences i.e., the requirement of utility of the found dependences f(·) and g(·) for the calculated forecasts of the extent of conversion to a model it is not produced.

3 System of Extreme Control 3.1 General Function Diagram of the System The functional diagram of a synthesizable system is shown in Fig. 4; it includes the object of control, i.e., the ammonia oxidation process, and two contours of control [15–17]. The contour of temperature T stabilization compensates the autothermal effect arising at the variations of α, i.e., it supports T at its technologically reasonable value T = Tmax = 880 °C by means of temperature control of ammoniac-air mix TAMM at the input of the reactor. In this contour the standard discrete PI-controller is used with the sampling period Td = 10 s. The extreme regulation contour provides the maintenance of an extent of conversion α at the, greatest possible level for the current conditions, by the organization of search and operation movements by two coordinates, namely, the operating influences ν and γ [18]. The fluctuations of content ϕ = ±0.05 of oxygen in air and the fluctuations of volume Qair = ±1,500 m3 /h of air at the input of the reactor were used in the system research using the simulation process. Ensuring the ν ≥ 0.8 m/s restriction is provided by the conventional control of v with uv cut-off at the top level. Restriction of β = [QNH3 /QAMM ] ≤ 0.11 with growing QNH3 is provided by the increase of Qair that allows to keep the maximum productivity of the reactor at the increased content of oxygen in air. Besides those specified above, the restrictions for the ranges of the operating influences have been provided: 0.8 m/s ≤ ν ≤ 1.5 m/s; 1.6 ≤ γ ≤ 2.4; 80 °C ≤ TAMM ≤

E. Vasiljev and S. Tkalich ΔQai r = ±1,500 m3/h

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Fig. 4. Function chart of a control system.

220 °C. It should be noted that the reliable performance of restrictions assumes an application of the forecasting models based, in particular, on the neural network technologies [11, 19]. The executive mechanisms in all three control paths v, γ and T are presented by the first order inertia links. 3.2 Extremum Search Algorithm The two-coordinate discrete controller is used in the system realizing the alternate change of the operating influences of uv and uγ with an odd number of steps for purpose of maintenance of value α at the maximum level ed. The definition of the direction of the movement is carried out by the combination of the operation and trial steps made in accordance with the ratios (indexes v and γ are omitted): un = un−1 +  u · sign  αn · sign  un−1 ;

(9)

where un = u[nT d ]; αn = α[nT d ], αn = αn −αn-1 ; un-1 = un−1 −un−2 , u – some minimum-hardware increment of control perceived by the executive mechanisms and causing the change α detected by the conversion extent sensor (Fig. 5). The specified approach to the choice of an increment u is defined by the fact that the continuous nature of the technological process which is characterized by a slow drift of parameters causes the irrelevance of a traditional problem of th1 extremum speed search and puts the problem of its deduction in the forefront [20, 22]. The loss of the

Extremum Seeking Control for the Catalytic Oxidation of Ammonia un-1,v

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Fig. 5. Block diagram of an algorithm of search of an extremum.

self-oscillatory movement (a roving loss) arising at the same time will be minimum at the hardware value u and when the quasistatic operating mode of the extreme regulation contour is provided [22, 23]. This mode can be provided with the obviously bigger choice of Td in comparison with the time of the transition processes in the system. In case this condition cannot be realized, e.g., because of the contradiction to the requirements of the Kotelnikov’s theorem, then the system stability can be provided by the transition to the continuing control mode. 3.3 System Operability Test Using the Imitating Model

γ=2

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An inspection of operability of the synthesized system of extreme control was carried out primarily for the autonomous modes of regulation by each coordinate γ and ν separately. In Fig. 6 the trajectory of the movement to an extremum α and its deduction by means of the operating influence of ν are shown at the constant γ = 2 and T = 880 °C values. The dependence ν(t) is shown in the separate diagram (Fig. 6a) and corresponds to the preset mode of an extremum area bypass. The point numbers 1,2,3,… in Figs. 6a, 6b would serve for an evident comparison of the conditions of a system in a time domain and in the space of ν and α coordinates.

0.986

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Fig. 6. Search and deduction of an extremum at one-dimensional control: a) the variation of gas flow velocity; b) changes of the conversion extent.

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Gas flow velocities v, (m/s) Oxygen/ammonia proportion, γ

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The results of the system simulation in the full-function mode of search and the deduction of an extremum in both coordinates γ and ν are shown in Fig. 7 and they also confirm its working capacity and efficiency. 7

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Fig. 7. The search movements of system in the field of an extremum: a) in the space of coordinates γ and ν; b) in time t.

The roving losses do not exceed 0.1% (see Fig. 7a in which the step of lines of equal level makes 0.02%), and on the real device it will be defined by the sensitivity of sensors. It should be noted that for the accepted uγ and uν values the function of extent of conversion α(γ, v) in the field of an extremum has a narrow comb-like extrapolation form (Fig. 7a) leading to the increased number of steps of its bypass – in our case considered here it consists of 36 steps making a total time cycle lasting 6 min. The cycle duration can be reduced by 2–3 times by a rotation of the system coordinates γ0v, having focused one of them along a comb axis of and having applied the quasigradient methods of search. However, if the speed of α drift exceeds 1% per hour, then the transition to a continuing mode will be a more radical decision.

4 Conclusion As a result of the solution of a task of the ammonia catalytic oxidation process control the following conclusions can be made: – the process discussed above is the multidimensional object with the extreme inputoutput characteristic whose position in the space of coordinates changes because of non-stationarity of the technological process parameters; – to achieve the controlled process of oxidation at least two adjustable values should be used: the extent of conversion supported at the greatest possible value and the temperature in the contact zone stabilized at the constant level; – the operating values can be the oxygen/ammonia proportion, the temperature of ammoniac-air mix and gas flow velocity in the reactor; – the most wide-known representation of the of catalytic oxidation process by the isothermal model of ideal replacement does not answer an objective of the extreme control and the transition to a regression model is desirable in the coordinates of the

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adjustable parameters elected above. The creation of such model with high degree of adequacy is possible on the basis of a passive experiment; – the surface of criterion function of the process has narrow comb-like form. For the reduction of bypass time of this surface it is expedient to transform the initial system in the operating coordinates to the equivalent system in which one of coordinates is focused along a crest of function of the purpose; – a low speed of parametrical drift of ammonia oxidation process allows solving an objective of the control on the basis of the self-oscillatory controller which is carrying out a task of the deduction of an extremum by combination of trial and operating movements in the space of the system coordinates.

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12. Pura, J., Wieci´nski, P., Kwa´sniak, P., Zwoli´nska, M., Gierej, M.: Investigation of the degradation mechanism of catalytic wires during oxidation of ammonia process. Appl. Surface Sci. 388(B), 670–677 (2016). https://doi.org/10.1016/j.apsusc.2016.05.071 13. Xu, J., Chen, G., Guo, F., Xie, J.: Development of wide-temperature vanadium-based catalysts for selective catalytic reducing of NOx with ammonia: review. Chem. Eng. J. 353, 507–518 (2018). https://doi.org/10.1016/j.cej.2018.05.047 14. Beskov, V.S., Vanchurin, V.I., Brunshtein, E.A., Golovnya, E.V., Yashchenko, A.V.: Simulation of the ammonia oxidation process over an oxide monolith catalyst. Catal. Ind. 2(3), 266–269 (2010). https://doi.org/10.1134/s2070050410030104 15. Podvalny, S.L., Vasiljev, E.M.: A multi-alternative approach to control in open systems: origins, current state, and future prospects. Autom. Remote Control 76(8), 1471–1499 (2015). https://doi.org/10.1134/s0005117915080123 16. Podvalny, S.L., Vasiljev, E.M.: Multi-alternative control of large systems. In: 13th International Scientific-Technical Conference on Electromechanics and Robotics “Zavalishin’s Readings”. MATEC Web of Conferences, vol. 161, 02003 (2018). https://doi.org/10.1051/ matecconf/201816102003 17. Dartmann, G., Almodaresi, E., Barhoush, M., Bajcinca, N., Kurt, G.K., LGjcken, V., Zandi, E., Ascheid, G.: Chapter 2: Adaptive control in cyber-physical systems: distributed consensus control for wireless cyber-physical systems. In: Song, H., Rawat, D.B., Jeschke, S., Brecher,C., Xhafa, S.E.F. (eds.) Cyber-Physical Systems. Foundations, Principles and Applications, pp. 15–30. Academic Press (2017). https://doi.org/10.1016/b978-0-12-803801-7.000 02-x 18. Moses, M., Banerjee, S.: Biologically inspired design principles for Scalable, Robust, Adaptive, Decentralized search and automated response (RADAR). In: IEEE Symposium on Artificial Life (ALIFE), IEEE, Paris (2011). https://doi.org/10.1109/alife.2011.5954663 19. Tkalich, S.A., Burkovsky, V.L., Kravets, O.Ja.: Comparison of the neural net training algorithms for the emergencies forecasting of technological processes. In: IOP Conference Series: Materials Science and Engineering. International Workshop “Advanced Technologies in Material Science, Mechanical and Automation Engineering”, Krasnoyarsk Science and Technology City Hall of the Russian Union of Scientific and Engineering Associations, vol. 537, 032040. Institute of Physics and IOP Publishing Limited (2019). https://doi.org/10.1088/ 1757-899x/537/3/032040 20. Jin, Z.: Chapter 12: The system dynamic adaptability concern. In: Jin, Z. (ed.) Environment Modeling-Based Requirements Engineering for Software Intensive Systems, pp. 217–239. Morgan Kaufmann (2018). https://doi.org/10.1016/b978-0-12-801954-2.00012-1 21. Zeigler, B.P., Muzy, A., Kofman, E.: Chapter 24: Open research problems: systems dynamics, complex systems. In: Zeigler, B.P., Muzy, A., Kofman, E. (eds.) Theory of Modeling and Simulation, 3rd edn., pp. 641–658. Academic Press (2019). https://doi.org/10.1016/b978-012-813370-5.00035-3 22. Wang, L., Chen, S., Zhao, H.: A novel fast extremum seeking scheme without steady-state oscillation. In: Proceedings of the 33rd Chinese Control Conference. IEEE, Nanjing (2014). https://doi.org/10.1109/chicc.2014.6896460 23. Shanhe, J., Zhicheng, J.: An improved HPSO-GSA with adaptive evolution stagnation cycle. In: Proceedings of the 33rd Chinese Control Conference. IEEE, Nanjing (2014). https://doi. org/10.1109/chicc.2014.6896444

Method of Infrared Reflectors Choice for Electrotechnical Polymeric Insulation Energy-Efficient Drying Evgeny Dulskiy1(B) , Pavel Ivanov1 , Anatoliy Khudonogov1 , Viktor Kruchek2 , Alena Khamnaeva1 , and Marina Divinets1 1 Irkutsk State Transport University, Irkutsk 664074, Russia

[email protected] 2 Emperor Alexander I St. Petersburg State Transport University, St. Petersburg 190091, Russia

Abstract. The article describes the proposed method of choosing the shape of effective infrared reflective devices during the design of energy-efficient hardware complexes for drying polymer insulation of electrical equipment, based on the comparative calculation of radiation viewfactors, using computer-aided engineering analysis technologies. Theoretical calculations on the use of infrared radiation to heat various surfaces are presented as justification of the necessity to choose reflector shapes. The paper analyzes the basic methods of calculating the angular radiation coefficients, identifies the advantages and disadvantages of each. The proposed technique is based on the construction of 3D models of infrared emitters with reflective devices of various shapes, which are located above the copper backing. In this case, the copper backing acts as a recorder of thermal fields. First of all, viewfactors were taken as selection criteria, depending on the shape of the reflective device and its relative position with regard to the emitter. A half-cube method was chosen as a method of calculating viewfactors due to its relative simplicity and high accuracy. The second criterion was the distribution of the thermal fields of heating of the irradiated surface and the reflector itself. The technique consists in a stepwise assessment of these criteria. As a result of the calculations, a trapezoidal reflector with an expansion angle of 150° has the best performance. The proposed technique gives clear and demonstrable results in terms of choosing the effective forms of infrared reflective devices, allowing one to quickly configure heating modes. Keywords: Polymeric insulation · Infrared radiation · Infrared heating · Radiation reflector · Radiation viewfactors · Energy efficiency

1 Introduction One of the most important tasks of railway transport in Russia is the necessity to ensure reliable operation of traction rolling stock. A long-term analysis of the reliability of the traction rolling stock shows that the most damageable element is an electric machine, namely insulation. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 515–529, 2021. https://doi.org/10.1007/978-3-030-57453-6_49

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The technology and technique of hardening the insulation of electric equipment for traction rolling stock using infrared (IR) radiation, proposed by scientists of Irkutsk State Transport University, can improve the performance of repair procedures, as well as significantly reduce the cost of electricity when drying polymer insulation. A methodology of designing energy-efficient hardware systems for drying polymer insulation of electrical equipment of traction rolling stock is proposed as part of the research and development work No. AAAA-A19-119010990009-3 on the topic “Improving the reliability of power equipment of traction rolling stock”. This article focuses on the selection of effective reflectors of infrared (IR) radiation. The use of infrared radiation in the process of drying of polymer insulation during the manufacture and repair of electrical equipment of traction rolling stock can significantly reduce energy costs and increase the productivity of repair procedures [1–3]. At the same time, the energy efficiency of the drying process, in particular, heating, can be further improved by correctly selecting devices, reflecting thermal radiation. The use of reflective devices together with infrared emitters can significantly reduce the loss of thermal reflection flux, especially from the rear side of the emitter, reflecting and redistributing it in the right direction. Similar reflective devices are also called reflectors in a production environment. The effectiveness of the reflective devices depends primarily on the reflectivity of the surface and the material from which it is made. The energy of the reflected radiation depends on the angle at which the energy of the incident radiation is transferred to the surface, as well as on the direction in which the reflected energy is considered [4]. At the stage of formation of the reflected flux, losses are associated with a change in the spectral composition of the reflected flux by the selectively reflecting surface of the emitter, which affects the value of the integrated reflected flux. A quantitative assessment of the process of reflection of the stream at wavelength λ is determined by the spectral reflection coefficient, Pλ =

Φpλ Φλ

(1)

where Φpλ is the reflected thermal flux, Φλ is the incident flux of thermal radiation. If the monochromatic flux Φpλ incident on the reflector and the spectral reflection coefficient for the same wave unit Pλ are known, then the reflected part of this flux is Φpλ = Pλ Φλ

(2)

Since any complex radiation flux is the sum of the fluxes composing it, it is obvious that the total reflected flux Φρ is equal to the sum of its components: λ2

Φρ = ∫ ϕλ ρλ d λ λ1

(3)

Reflectors, as a rule, are made of materials that have a low heat capacity (steel, aluminum), and their surface is polished almost to a specular gloss, forming a mirror

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Fig. 1. Diffuse (left) and mirror (right) reflective surfaces.

surface (Fig. 1, right). However, to minimize manufacturing costs, it is possible to use ordinary steel as reflectors, forming a diffuse surface (Fig. 1, left). When choosing a reflector, its optimal shape is important. At the design stage of the irradiators, it is necessary to take into account the geometric shape of the reflector in order to minimize the loss of infrared radiation during operation. A comparative analysis of the dependence of the distribution of the flux of infrared radiation incident on the surface of a copper plate and the temperature of its surface on the shape of the reflector was conducted in the article, using computer technology for engineering analysis.

2 Materials and Methods The first option considered was a standard trapezoidal ECR-type reflector, see Fig. 2. The calculations showed that reflectors of various shapes form IR radiation fluxes on the heated surface, which differ not only in density, but also in the nature of its distribution in the working area. To evaluate the effectiveness of the geometric dimensions of the reflectors in [5], it was proposed to use a criterion (4) where l is the width of the working area in the vertical direction; q p inc (x)dx and q  inc (x)dx are the flux densities of the incident radiation from the reflector and the total radiation from the reflector and IR emitter.

Fig. 2. The general view of the trapezoidal ECR-type reflector.

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The shape of the reflector allows one to control the formation of IR radiation fluxes on the irradiated surface, which differ not only in density, but also in the nature of its distribution. For clarity, comparing the shapes of reflectors by this criterion, we summarize all the results in Table 1. Table 1. The value of the criterion kef for various forms of reflectors.

The shape of IR emitters

Parameter value 0.212

0.138

0.182

0.193

0.175

0.244

The table shows the calculation results for the case of heating with an FSF-type IR emitter with a power of 500 W of a steel plate 3 mm thick at a distance of 50 mm. As can be seen from the table, the trapezoidal reflector with rounding on the sides has the best result; the trapezoidal reflector with an angle of 150º is in second place. The proposed criterion is universal and suitable for evaluating the effectiveness of reflectors of various shapes. As part of the research, another technique is proposed for choosing the shape of reflectors that takes into account the distribution of the thermal field and the distance to the irradiated object based on the use of the finite difference method. From a mathematical point of view, the shape of the reflector affects the value of viewfactors, which, in turn, is affected by the relative position of the emitters above the irradiated surface, the geometry of the reflector and the irradiated surface. The flux of infrared radiation emitted by each elementary area dA1 of the surface of the infrared emitter, and irradiating the elementary area dA2 of a steel plate can be

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determined from the Lambert law dq12 = M1 ·

cos ϕ1 dA1 d Ω π

(5)

where M 1 is the radiancy of the infrared emitter per segment of the frontal part of the armature winding, W/mm2 ; dΩ is the solid angle (Fig. 3) dΩ =

cos ϕ2 dA2 r2

(6)

r is the axis of the solid angle dΩ (distance between the source and receiver of infrared radiation), mm; ϕ 1 , ϕ 2 are angles between normals n1 , n2 and axis r. Given the formula, the Lambert law will be written as dq12 = M1

cos ϕ1 cos ϕ2 dA1 dA2 π r2

(7)

The second part of this expression is the mutual radiation surface, showing the effective part of the elementary surface area dA1 of the infrared emitter, which radiates only to the elementary surface area dA2 of the frontal segment of the winding dH12 =

cos ϕ1 cos ϕ2 dA1 dA2 . π r2

(8)

Fig. 3. Spatial distribution of infrared radiation.

Knowing the mutual radiation surface, it is possible to determine the fraction of radiation that has left the elementary surface area dA1 on the elementary surface area dA2 , which is viewfactors dFϕ12 =

cos ϕ1 cos ϕ2 dH12 1 1 ∫ ∫ = = dA1 dA2 dA1 dA1 A1 A1 A2 π r2

(9)

Defining viewfactors is a time consuming process. For viewfactors, the following equality holds true: dFϕ12 · A1 = dFϕ21 · A2

(10)

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The following basic methods are used for calculating viewfactors [6–11]: (1) a direct adaptive integration method; (2) the Monte-Carlo method; (3) a semi-cube point method. The essence of the direct adaptive integration method is to calculate the integrals between each pair of elementary surface sites Ai and Aj (Fig. 4). The amount of radiated thermal flux transmitted between the two surfaces will depend on how much of the radiation from each surface falls on the other surface. As shown in Fig. 4, the radiation propagating from the surface Ai to the surface Aj will be equal to   cos ϕ1 · cos ϕ2 · Aj qij = Mi · Ai · (11) = Mi · Ai · Fij r2 where qij is the thermal flux between the surface Ai and Aj , W; M is the energy radiancy, W/mm2 ; Ai , Aj are surface areas, mm2 ; r is the distance between surfaces, mm; F ij are viewfactors between surfaces Ai and Aj .

Fig. 4. The definition of viewfactors between two surfaces.

Since viewfactors are exclusively geometric, the following equality holds true: Ai · Fij = Aj · Fji .

(12)

In this case, the equation of heat transfer by radiation is of the form qij = Ai · (Mi − Gi ),

(13)

where G is the heat flux in the opposite direction. For G, two expressions independent from each other can be formed: (a) the incident radiation to the surface should be equal to the radiation emitted by all other surfaces that irradiate this surface Ai · Gi =

N  j=1

Mj · Aj · Fji =

N  j=1

Mj · Ai · Fu ,

(14)

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Or Gi =

N 

Mj · Fij ,

(15)

j=1

where N is the number of surfaces involved in the calculations; (b) another expression for G Gi =

Mi − εi · Eni Mi − εi · Eni = ρi 1 − εi

(16)

where E ni is the radiation power, W, εi is emissivity, ρ is the reflection coefficient. After repositioning of the terms, we obtain Mi = Eni −

1 − εi · qi . Ai · εi

(17)

Substituting this equation into Eq. (14), we obtain the main equation for the problems of thermal radiation of a diffusely gray body      Ai · δij − 1 − εj · Ai · Fij (18) · qj = Ai · δij − Ai · Fij · {Eni }. Aj · εj For problems of thermal radiation of a black body, that is, with εi = 1, this equation takes the form  (19) qj = Ai · δij − Ai · Fij · {Eni }, It can be seen from the equation that the net thermal flux of radiation from the black surface represents the difference between the emitted radiation and the received one, that is, there is no reflection in this case. The thermal flux from the surface A1 to A2 is calculated as   Aj cos ϕj , (20) qij = Mi · (Ai · cos ϕi ) · π · r2 where ϕ ij are the angles between the normals ni , nj and the axis r (Fig. 3). In Eq. (20), the first term in brackets is the projection A1 of the normal to the connecting line, and the second term is the solid angle at which the surface A2 is visible from the center of the surface A1 . Viewfactors in this case are defined as

cos ϕ · cos ϕ  j i · Aj , Fij = (21) π · r2 Substitute Eqs. (21) into (19) qij = Mi · Ai · Fij .

(22)

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When calculating by this method, the areas of the emitted surfaces are divided into faceted surfaces. The more complex the geometry, the more faceted surfaces and, accordingly, more complex calculations. For example, Fig. 5 presents the order of finding faceted surfaces for the case of the IR radiation heating of a segment of the frontal part of the electric transport engine armature winding in the process of drying [1].

Fig. 5. The order of constructing faceted surfaces.

The formula for finding viewfactors, taking into account Fig. 5, is written as

(23)

where dA1a and dA1b are the areas of surface elements of faceted surfaces, respectively, mm2; dF ϕ12 is the average angular radiation ratio of the surface 1 to the surface 2 (Fig. 5); dF ϕ1a2a , dF ϕ1a2a , dF ϕ1a2a , and dF ϕ1a2a are, respectively, angular radiation ratios of the surface elements of the faceted surface mesh 1 and 2. The fastest and most accurate method in calculations of viewfactors is the half-cube point method. This method is a modification of the unit radius sphere method proposed by Nusselt [6]. Let us consider it first. If you build a semisphere of a single radius over the elementary platform of dA1 (Fig. 6), the viewfactors between dA1 and some surface of A2 will be equal to dF1−2 =

cos β2 dA2 1 1 · ∫ cos β1 = · ∫ cos β1 d ω1 . π A2 S2 π A2

(24)

Note that dω1 is the projection of dA2 onto the surface of the semisphere, since d 1 =

dAs cos β2 dA2 = dAs = , 2 r s2

(25)

where r is the radius of a single semisphere. With this in mind, viewfactors are calculated as dF1−2 =

1 · ∫ cos β1 dAs . π As

(26)

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However, dAS cosβ1 is the projection of dAs onto the semisphere base. Therefore, the integration of cosβ 1 dAS gives the projection Ab of the surface AS on the basis of the semisphere, or dF1−2 =

1 Ab · ∫ cos β1 dAs = . π As π

(27)

Fig. 6. The geometric scheme for determining viewfactors by the unit radius sphere method.

The main disadvantage of this method is the great difficulty in projecting the surface A2 on the semisphere. For this purpose, as well as to increase the speed of calculating viewfactors, in the half-cube method, the sphere is replaced by a cube (Fig. 7). Viewfactors have been already predefined for its sections of faces 1. When projecting the surface A2 on the surface of the cube, we find the sum of all viewfactors of the sections of the faces of the half-cube 2, on which the projection of the surface A2 falls, although the quality of the calculation is lost for complex geometry. The sum of these viewfactors gives the angular coefficient of the entire surface. The half-cube method is also used in the calculation of viewfactors in the specialized solver “MSC SindaRad” [12]. This solver makes it possible not only to calculate viewfactors, but also to visualize the calculation results. Consider the proposed method when choosing effective reflectors in the design of industrial units. The methodology of choosing reflectors is a stepwise comparison and evaluation of each model compared with others. At the preparation stage, the model is divided into a finite element mesh, properties and loads are set. When setting up the operation of thermal radiation, the reflection and absorption coefficients of objects are set. Next, the model is calculated to determine the distribution of temperature fields. At first, viewfactors with visualization are calculated. At this stage, the angular element of the reflector is selected and its reflectivity is evaluated, as shown in Fig. 9.

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Fig. 7. The geometric scheme for determining the viewfactors by the half-cube method.

What we estimate directly is the reflection zone on the irradiated object (in this case, on a steel plate).

3 Results For the calculation, 3D models of reflectors of the analyzed forms were developed, similar to those presented in Table 1. A similar FSF [13] 500-watt IR emitter and a 3 mm-thick steel plate located 50 mm away from the emitter were selected for the method in question. The general view of the 3D models is presented in Fig. 8. The colors on the visualized model show the locations of the reflected radiation from the selected element at the reflector’s corner. The red indicates the maximum hit, blue - no hit. Accordingly, with the color palette it is possible to assess the concentration of reflected rays. The results of the remaining calculations are presented in Fig. 10. Visualization of the calculation of viewfactors allows one to evaluate the irradiation zone, the intensity of infrared radiation, taking into account the maximum and minimum. Thus, the concentration zone is clearly visible in the a-c models. Also in models b, in, d, one can clearly see the boundary of the action of the thermal field (Fig. 10), which will allow choosing the distance between irradiators when designing. The next step is to evaluate and compare thermal fields in calculated models using the MSC Sinda solver [12, 14]. The main task of the reflector, as mentioned earlier, is to reduce the loss of IR radiation by redirecting and/or focusing the flux on the irradiated object. Thus, the final thermal field can be a reliable parameter, characterizing the effectiveness of the reflector performance [15].

Method of Infrared Reflectors Choice а)

b)

c)

d)

e)

f)

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a – flat, b – trapezoidal ECR (expansion angle is 150º), c – trapezoidal (expansion angle is 120º), d – semicircular (radius is 130 mm), d – rectangular, e – trapezoidal with a rounding of 60 mm radius

Fig. 8. 3D models of reflectors with an infrared emitter and a steel platform.

Fig. 9. Calculation results of viewfactors in Sinda Rad for a flat reflector.

The calculation analyzed the thermal fields of the steel plate, reflector and model as a whole (Figs. 11 and 12).

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а)

b)

c)

d)

e)

f)

a – flat, b – trapezoidal ECR (expansion angle is 150º), c – trapezoidal (expansion angle is 120º), d – semicircular (radius is 130 mm), d – rectangular, e – trapezoidal with a rounding of 60 mm radius

Fig. 10. Visualizing the calculation of viewfactors for all variants of reflectors.

As can be seen from Fig. 11, the distribution of isotherms in models is generally similar, but the temperatures of their boundaries differ. Thus, one can see that in the models b and f the shape of the reflector provides the maximum temperature on the surface of the plate.

Method of Infrared Reflectors Choice a)

b)

c)

d)

e)

f)

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a – flat, b – trapezoidal ECR (expansion angle is 150º), c – trapezoidal (expansion angle is 120º), d – semicircular (radius is 130 mm), d – rectangular, e – trapezoidal with a rounding of 60 mm radius

Fig. 11. Visualization of the calculation of the thermal field of the plates for all design cases.

The next step is to compare the heating temperatures in reflectors of different shapes to assess the effectiveness of the reflection of the infrared radiation. The results of the remaining calculations are presented in Fig. 12. Analyzing the results of the calculation, it is clear that models b and f have the lowest heating temperature.

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b)

c)

d)

e)

f)

a – flat, b – trapezoidal ECR (expansion angle is 150º), c – trapezoidal (expansion angle is 120º), d – semicircular (radius is 130 mm), d – rectangular, e – trapezoidal with a rounding of 60º radius

Fig. 12. Visualization of the calculation of the thermal field of model reflectors.

4 Conclusions Based on the research results, we can conclude that the best results in terms of the directional concentration of thermal radiation, the highest heating of the irradiated surface and the smallest heating of the reflector itself were shown in specimens b and f, which have a trapezoidal shape with an angle of 150º and with a rounding with a radius of 60 mm. Thankfulness. The article was published at the expense of the state task on the topic “Improving the reliability of power equipment of traction rolling stock”. Acknowledgments. Thus, the proposed method of selecting effective IR radiation reflectors, based on the calculation of radiation viewfactors, allows one to select optimal forms of reflectors, depending on the geometric features of the design of winding electrical equipment exposed to drying, the power of the emitters, the material and the quality of the reflector surface.

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References 1. Khudonogov, A., Dulskiy, E., Ivanov, P.: Basis for local methods of insulation hardening of traction rolling stock electrical machines. In: Murgul, V., Popovic, Z. (eds.) EMMFT 2017. AISC, vol. 692, pp. 109–119. Springer, Cham (2018). https://doi.org/10.1007/978-3-31970987-1_12 2. Dulskiy, E., Khudonogov, A., Khudonogov, I., Astrakhantsev, L., Ivanov, P., Tuigunova, A.: Modeling of the oscillating mode of the IR-energy supply in the technology of restoration of insulating fingers of electric motors of locomotives. In: Murgul, V., Pasetti, M. (eds.) EMMFT-2018 2018. AISC, vol. 982, pp. 546–555. Springer, Cham (2020). https://doi.org/ 10.1007/978-3-030-19756-8_52 3. Dulskiy, E.Y., Ivanov, P.Y., Khudonogov A.M.: A functional approach to the analy-sis of technological processes of using thermal radiation in the process of repairing insulation of electric locomotive equipment. In: IOP Conference Series: Materials Science and Engineering, Volume 760, International Conference on Transport and Infrastructure of the Siberian Region (SibTrans-2019), vol. 760. IOP Publishing (2020). https://doi.org/10.1088/1757-899x/760/1/ 012019 4. Cosson, B., Schmidt, F., Le Maoult, Y.: Infrared heating stage simulation of semi-transparent media (PET) using ray tracing method. Int. J. Mater. Form. 4, 1–10 (2011). https://doi.org/ 10.1007/bf01900836 5. Tan, M.: On choosing a rational form of reflector for a heater with gas-discharge radiation sources. Herald of the Bauman Moscow State Technical University. Ser. Mech. Eng. 2, 117– 120 (2008). https://doi.org/10.1007/s12289-010-0985-8 6. Pueyo, X.: Diffuse interreflections. Techniques for form-factor computation: a survey. Vis. Comput. 7, 200–209 (1991) 7. Slater, M.: A comparison of three shadow volume algorithms. Vis. Comput. 9, 25–38 (1992). https://doi.org/10.1007/bf01901026 8. Aguerre, J.P., Fernandez, E., Beckers, B.: Importance-driven approach for reducing urban radiative exchange computations. Build. Simul. 12, 231–246 (2019). https://doi.org/10.1007/ s12273-018-0482-4 9. Li, B., Chen, H., Ning, B.: Uniform deterministic discrete method for radiative view-factors in complex geometric systems. J. Therm. Sci. 4, 100 (1995). https://doi.org/10.1007/bf0265 3192 10. Pellegrini, V.: Monte Carlo approximation of form factors with error bounded a priori. Discrete Comput. Geom. 17, 319–337 (1997). https://doi.org/10.1145/220279.220310 11. Monteix, S., Schmidt, F., Maoult, Y.L., Yedder, R.B., Diraddo, R.W., Laroche, D.: Experimental study and numerical simulation of preform or sheet exposed to infrared radiative heating. J. Mater. Process. Technol. 119(1–3), 9–97 (2001). https://doi.org/10.1016/s09240136(01)00882-2 12. Sinda Advanced Thermal Simulation Solution. https://www.mscsoftware.com/product/sinda. Accessed 25 Mar 2020 13. Elstein infrared Emitters http://www.elstein.com/en/elstein-products/infrared-systems/. Accessed 25 Mar 2020 14. Gumenuk, A.: Patran-Sinda-MSC thermica – specialized complex for orbital thermal analysis the design of the spacecraft. Cadmaster 2, 50–58 (2014) 15. Michael, F.M.: Radiative Heat Transfer. Academic Press, Oxford (2013). https://doi.org/10. 1016/c2010-0-65874-3

Study of the Tank Stress-Strain State with Settlement Near the Wall Aleksandr Tarasenko1

, Petr Chepur1

, and Alesya Gruchenkova2(B)

1 Industrial University of Tyumen, Volodarskogo str. 38, 625000 Tyumen, Russia 2 Surgut Oil and Gas Institute, Entuziastov str. 38, 628405 Surgut, Russia

[email protected]

Abstract. In the paper, the authors investigate numerically the stress-strain state of the RVS-20000 storage tank when the settlement zone is located near the tank wall. A numerical model of the tank has been developed in accordance with the actual geometric dimensions, taking into account all structural elements and maximum operating loads. When modeling local settlement in order to take into account the spatial work of the soil, the Pasternak model of the soil base was used. The tank stress-strain state was calculated with the values of the radius of the settlement zone from 1 to 10 m. The choice of this interval is due to the fact that in more than 92% of cases, tanks with local bottom settlement fall into this range of values. The dependences of the maximum acting stresses in the wall of the VST on the position of the area of inhomogeneity in the soil base are established. The boundary of the edge effect zone from the VST wall is established. If the center of the area of inhomogeneity is located in this zone, it is necessary to conduct an additional analysis of the SSS of the tank metal structures when assigning the maximum settlement. Keywords: Vertical steel tank · Area of inhomogeneity · Stress-strain state

1 Introduction Vertical steel tanks (VSTs) for oil storage are one of the most critical facilities for the long-distance transportation of hydrocarbons. The analysis of the causes of the accidents on VSTs showed that uneven settlements caused by local inhomogeneity of the soil base cause the destruction of vertical steel tanks in 46% of cases [1–5]. Local base settlements develop as a result of changes in the structure of the soil mass under the influence of operational loads and the own weight of the soil, as well as additional factors, such as thawing of ice layers in frozen soil, and a change in the level of groundwater [6–8]. Normative documents regulate the number of wells drilled during surveys: for tanks with a volume of more than 5000 m3 - at least 5 wells, for tanks with a volume of less than 5000 m3 - 4 wells. Considering that the base area of modern tanks can reach 7000 m2 , engineering and geological sections constructed according to surveys do not always fully reflect the actual soil composition of the natural base, which leads to the appearance of settlement zones during operation [9, 10]. Within the bottom area, local inhomogeneity © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 530–536, 2021. https://doi.org/10.1007/978-3-030-57453-6_50

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can be located in its central part and near the VST wall (Fig. 1). In the first case, the area of inhomogeneity is outside the boundary effect from the wall and this problem can be solved by the analytical method, and in the second case, the inhomogeneity area is near the wall and is affected by the cylindrical stiffness of the wall, so it is possible to determine the tank SSS parameters only by numerical methods [11–13]. Thus, the authors set the task of investigating the stress-strain state of RVS-20000 with the location of the inhomogeneity area in the vicinity of the wall by a numerical method.

Fig. 1. The local inhomogeneity of the base is located in the central part of the bottom (a), near the wall (b): 1 - tank wall, 2 - artificially compacted soil base; 3 - local inhomogeneity, R - radius of the tank, r - radius of a circle inscribed in the area of local inhomogeneity.

2 Methods To solve the problem in the ANSYS software package [1], a numerical model of the RVS-20000 tank was developed, which is as close to the real design as possible and consists of the following structural parts: the central part of the bottom, annular plates, walls, stiffening ring in the upper belt, a beam frame and a fixed roof. In the developed model, the maximum operational loads were simultaneously applied: the weight of the stored fluid P, the excess pressure Pex , the vacuum pressure Pvac , the weight of the snow cover and the fixed roof equipment Psn.+eq. [13]. When creating a numerical model of the tank for constructing a mesh in the central part of the bottom, annular plates, walls, stiffening ring and sheet roofing, we chose a shell quadrangular four-node end element with six degrees of freedom SHELL181; in the supporting beams of the fixed-roof frame - a linear two-node beam element with six degrees of freedom BEAM188; in the connecting beams of the roof - a two-node FE with six degrees of freedom BEAM4 [14]. The simulation was performed in a nonlinear setting to analyze the appearance of zones with limiting values of stresses and strains. The selection of materials and the indication of their properties for the created model was carried out in the Engineering Data module for managing materials associated with the

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analysis unit. 09G2S steel was chosen in the library of nonlinear materials for nonlinear analysis (General Nonlinear Materials). To take into account physical nonlinearity, the experimentally obtained stress-strain curve for 09G2S steel was approximated by a dependence consisting of 4 segments: the first segment corresponds to the proportionality limit, the second - to the yield strength, the third - to the yield segment, and the fourth - to the ultimate tensile strength (Table 1). To simulate the elastic fixing of the bottom of the tank in contact with the settlement area and the base of the VST, the “elastic support” boundary condition was introduced. In order to take into account the spatial work of the soil, the Pasternak model of the soil base was used [15, 16], accounting for the discrete bed coefficients that determine the deformation characteristics of the base. For the area of inhomogeneity, we introduced the bed coefficient k1 , and k2 - for the base of the tank, outside the area of inhomogeneity. Table 1. Elastic-plastic characteristics of 09G2S steel. Characteristics σpl, εpl, MPa % 320

σy, εy, MPa %

0.0016 325

σy.s, εy.s, MPa %

0.0036 373

σut, εut, MPa %

0.01501 470

0.021

σpl , εpl – stresses and strains corresponding to the proportionality limit; σy , εy - stresses and strains corresponding to the yield strength; σy.s. , εy.s. - stresses and strains corresponding to the yield segment; σut , εut - stresses and strains corresponding to the ultimate tensile strength.

3 Experimental Part Figure 2 presents the design scheme for conducting a numerical experiment. The area of inhomogeneity is characterized by the following geometrical parameters: radial size – r, distance from the wall to the center of the area of inhomogeneity – X. In the first case, the distance from the wall to the center of the area of inhomogeneity is equal to the radius of the settlement zone – X = r, in the second case – X = r + 2 m, in the third – X = r + 4 m, in the fourth – X = r + 6 m, in the fifth – X = r + 8 m, in the sixth case – X = r + 10 m. The calculation of the SSS of the tank was carried out at the following values of the radius of the settlement zone - 1, 2, 4, 6, 8, 10 m. For simulating the prepared artificially compacted base of the tank, outside the area of inhomogeneity, the bed coefficient k2 = 2·108 N/m3 was set. The bed coefficient k1 set for the area of inhomogeneity varied from 0.3 MN/m3 to 5 MN/m3 . The minimum value of k1 is chosen based on the fact that in the case of a k1 value of less than 0.3 MN/m3 , the solution convergence is lost when calculating, which corresponds to the absence of soil in the settlement zone.

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Fig. 2. Design scheme: 1 - tank roof; 2 - tank wall; 3 - bottom annular plate; 4 - central part of tank bottom; 5 - stiffening ring; 6 - tank soil base with bed coefficient k2; 7 - local soil base inhomogeneity with bed coefficient k1; R - tank radius, m; r - radius of local base inhomogeneity area; X - distance from wall to inhomogeneity area center; δ - bottom thickness; w - vertical component of settlement.

4 Results and Discussions Based on the results of calculations of the numerical model of RVS-20000, diagrams of the distribution of maximum stresses in the tank wall (Fig. 3) were obtained for various geometric sizes and locations of the inhomogeneity area at the base. Based on the results of a numerical experiment, we established the dependences of the maximum equivalent stresses in the RVS-20000 wall for given radii of the settlement zone on the position of local inhomogeneity relative to the VST wall for the case of the maximum allowable settlement (Fig. 4). Based on the results of processing the obtained dependences, the boundary of the zone of action of the edge effect from the VST wall was established in the presence of an area of inhomogeneity at the base (Fig. 5). According to the results of processing the obtained dependences, expression (1) was obtained, which allows us to determine the boundaries of the zone of the edge effect from the wall of the VST, with the maximum allowable settlement: X = r + 3.0323 · ln(r) + 1.8956

(1)

X – distance from the wall to the center of the inhomogeneity area of the soil base, m; r – inhomogeneity area radius, m. The analysis of graphical dependences showed that when the radius of the inhomogeneity area is 1 m, the stresses in the wall do not reach the permissible ([σ] = 188 MPa),

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Fig. 3. Maximum equivalent stresses in the wall of RVS-20000 at δ = 6 mm, r = 10 m, X = 8 m.

Maximum equivalent stresses in RVS-20000 wall σequiv, MPa

400 350 300

Boundary of edge effect zone from wall r = 10 m

250

r=8m

200

r=6m

150

r=4m

100

r=2m r=1m

50 0

r+2 r+4 r+6 r+10 r+8 0r 2 4 6 8 10 Distance from VST wall to inhomogeneity area center X, m

Fig. 4. Dependences of the maximum equivalent stresses in the wall of the RVS-20000 on the position of the area of inhomogeneity.

even with the closest possible location to the wall. In addition, it was found that at a certain location of the inhomogeneity area, a moment comes at which the maximum equivalent stresses in the tank wall begin to increase. The increase in stresses in the wall is explained by the appearance of the edge effect from the cylindrical shell of the VST. For each radial size of the local inhomogeneity of the soil base, a cut-off segment is constructed that characterizes the boundary of the edge effect zone from the VST wall at the maximum permissible settlement. Thus, according to the results of processing the obtained data, the dependence of the boundary of the edge effect zone on the radius of the inhomogeneity area was established. Within this zone, the maximum permissible settlement should be less than the limit according to the requirements of the technical documentation. If the center of

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Local inhomogeneity area radius r, m Distance from VST wall to inhomogeneity area center X, m

1

3

5

7

9

0 2 4 6

Edge effect zone from wall

8 10 12 14 16 18

Boundary of edge effect zone Х = r +3.0323ln(r)+1.8956

20

Fig. 5. Boundary of the edge effect zone from the tank wall.

the inhomogeneity area is located in this zone, it is necessary to conduct an additional analysis of the SSS of the tank metal structures when assigning the maximum settlement.

5 Conclusions A finite element model of the RVS-20000 tank was developed in the ANSYS software package with a maximum degree of detail of structural elements. A design scheme was developed and the contact problem of the interaction of the RVS-20000 tank with a soil base based on the Pasternak model, taking into account the deformation of the soil outside the area of inhomogeneity, was solved. Dependences of the maximum acting stresses in the wall of the VST on the position of the area of inhomogeneity in the soil base were established. A dependence was obtained that allows us to determine the boundary of the edge effect zone from the wall of the VST.

References 1. Tarasenko, A., Chepur, P., Gruchenkova, A.: Determining deformations of the central part of a vertical steel tank in the presence of the subsoil base inhomogeneity zones. J. AIP Conf. Proc. 1772, 060011 (2016). https://doi.org/10.1063/1.4964591 2. Tarasenko, A.A., Chepur, P.V.: Aspects of the joint operation of a ring foundation and a soil bed with zones of inhomogeneity present. Soil Mech. Found. Eng. 53(4), 238–243 (2016). https://doi.org/10.1007/s11204-016-9392-6 3. Terzeman, J.V., Teregulov, M.R.: Analysis of the stress-strain state of the toroidal transition connecting the wall and the bottom of the tank. J. Phys: Conf. Ser. 1425, 012001 (2020). https://doi.org/10.1088/1742-6596/1425/1/012001

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4. Vasiliev, G.G., Salnikov, A.P., Katanov, A.A., Likhovtsev, M.V., Ilin, E.G.: Optimizing the desktop processing of the terrestrial laser scanning data in assessing the stress-strain state of tanks. J. Pip. Sci. Tech. 3(2), 112–117 (2019). https://doi.org/10.28999/2514-541X-2019-32-112-117 5. Latypova, L.A., Lukyanova, I.E.: Calculation of the stress-strain state of a vertical steel tank with a volume of 5000 m3 under horizontal seismic impact in the ANSYS software complex. J. Oil Gas Bus. 1(17), 113–119 (2019). https://doi.org/10.17122/ngdelo-2019-1-113-119 6. Gorban, N.N., Vasiliev, G.G., Leonovich, I.A.: Analysis of existing approaches to modeling cyclic loading of the oil tank wall of marine terminals. J. Oil Ind. 3, 110–113 (2019). https:// doi.org/10.24887/0028-2448-2019-3-110-113 7. Yudakov, V.A., Fan, S.D., Fan, I.A., Teregulov, M.R., Bagdasarova, Y.A.: Improving the operational reliability of vertical steel tank bottoms for oil and petroleum products. J. Oil. Bus. 8(608), 59–65 (2019). https://doi.org/10.30713/0207-2351-2019-8(608)-59-65 8. Lukyanova, I.E., Mikhailova, V.A., Kantemiov, I.F., Yakshibaev, I.N.: Study of ignition of binding substances used in foundations of tanks. J. IOP Conf. Ser. Earth Env. Sci. 1(378), 012019 (2019). https://doi.org/10.1088/1755-1315/378/1/012019 9. Gorelov, A.S.: Heterogeneous Soil Bases and Their Influence on Work Vertical Steel Tanks. Nedra, Saint Petersburg (2009) 10. Gorban, N.N., Vasiliev, G.G., Leonovich, I.A., Salnikov, A.P.: Study of the functioning models of tank farms of marine terminals in the Russian Federation. J. Oil Ind. 1, 77–80 (2020). https:// doi.org/10.24887/0028-2448-2020-1-77-80 11. Tarasenko, A., Chepur, P., Gruchenkova, A.: The use of a numerical method to justify the criteria for the maximum settlement of the tank foundation. J. AIP Conf. Proc. 1899, 060003 (2017). https://doi.org/10.1063/1.5009874 12. Tarasenko, A.A., Konovalov, P.A., Zekhniev, F.F., Chepur, P.V., Tarasenko, D.A.: Effects of nonuniform settlement of the outer bottom perimeter of a large tank on its stress-strain state. Soil Mech. Found. Eng. 53(6), 405–411 (2017). https://doi.org/10.1007/s11204-017-9420-1 13. Slepnev, I.V.: Stress-Strain Elastic-Plastic State of steel Vertical Cylindrical Tanks with Inhomogeneous Base Settlement. Moscow Engineering and Building Institute, Moscow (1988) 14. Bruyaka, V., Fokin, V., Soldusova, E., Glazunova, N., Adeyanov, I.: Engineering Analysis in ANSYS Workbench. Samara State Technical University, Samara (2010) 15. Korobkov, G.E., Zaripov, R.M., Shammazov, I.A.: Numerical Modeling Stress-Strain State and Stability of Pipelines and Tanks in Difficult Operating Conditions. Nedra, Saint Petersburg (2009) 16. Korobkov, G.E.: Numerical Modeling of Stress-Deformed State and Stability of Pipelines and Tanks in Complicated Operating Conditions. Nedra, Saint Petersburg (2009)

Numerical Optimization of Film Cooling System with Injection Through Circular Holes Nicolay Kortikov(B) Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, St. Petersburg 195251, Russia [email protected]

Abstract. This work is devoted to studying the capabilities of the IOSO NS GT 2.0 software package using the example of optimizing a film cooling system with injection through circular holes. The maximum value of the film cooling efficiency was determined on the basis of a single software package that includes a program for calculating cooling efficiency and a search algorithm within the optimization environment. The search for the global maximum of film cooling efficiency was carried out first by varying two, and then five main system parameters. This allowed us to determine the optimal values of the parameters at which the cooling efficiency when blowing the curtain through a series of circular holes increases by 30%. This change is caused by an increase in the blowing parameter to a value equal to 1.236 in the case of normal (to the plate surface) coolant supply for conditions typical of the operation of gas turbine blades (turbulence intensity is 10%). Keywords: Optimization · Film cooling · IOSO technology

1 Introduction An increase in the initial temperature of the gas at the turbine inlet poses the problem of ensuring the operability of the elements of gas turbine units (GTU), which are exposed to high gas temperatures in combination with high external loads. This problem is solved, on the one hand, by improving structural materials and the manufacturing technology of gas turbine parts in contact with a high-temperature working fluid, and on the other, by developing and implementing various cooling systems. Of all the elements of the high-temperature path, the turbine blade operates under the most stressful conditions [1, 2]. The blades of the first stage of the high-temperature turbine have a developed convective-film cooling scheme in which the cooler is fed through rows of perforations to the surface of the blade (Fig. 1,a). To create competitive samples in the field of gas turbine engineering [3–5], it is necessary to combine mathematical models [6] and software systems [7–9] with search methods [10, 11] for the most effective technical solutions within the framework of the optimization environment. Moreover, to solve optimization problems, it is necessary to solve the problem of integrating various programs within the framework of one project. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 537–541, 2021. https://doi.org/10.1007/978-3-030-57453-6_51

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Fig. 1. Nozzle blade with convection-film cooling (a); design scheme of film cooling of the plate (b).

Currently, a large number of commercial software packages are known that declare the ability to organize a search for a global optimum for functions with a large number of variables [7, 12, 13]. Among the most promising are the algorithms of IOSO technology [14]. During the optimization process in IOSO, at each iteration, the response surfaces of optimization criteria and constrained parameters are constructed. To build a response surface, adaptive regression analysis algorithms are used; evolutionary self-organization algorithms with structurally parametric approximation; neural network algorithms. The IOSO NX GT 2.0 program [14] is able to find a global extremum for functions with hundreds of independent variables. The IOSO NM and IOSO PM programs are aimed at multicriteria optimization and parallelization of the calculation process. The tabular and graphical forms of presentation of the optimization results allow us to analyze the solutions obtained and determine the direction of further research. Verification of the program code is possible either analytically using a function with a known position and value of the global maximum, or based on comparison with experimental data in a problem for which there is a global maximum in the behavior of the objective function (film cooling efficiency). In this work, IOSO NX GT 2.0 verification was carried out on the basis of integration with the adiabatic wall temperature calculation program [15] when the curtain was blown onto the plate through perforations (Fig. 1,b) in order to increase the film cooling efficiency of gas turbine blades.

2 Problem and Method The appearance of the maximum value for the efficiency η of cooling the plate with a gas curtain when blowing through perforations (Fig. 2 and 3) is associated with various effects on the flow and heat transfer of the following factors (M is the injection parameter, DR is the ratio of the densities of the main and secondary flows, Tu1 is the degree of turbulence of the main stream, α is the angle of blowing of the curtain, P¯ = P/d is the relative step between the perforation holes (d is the diameter of the hole), L/d is relative cooling tube length, x/d is the dimensionless longitudinal coordinate).

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In [15], to calculate the efficiency η¯ averaged over the width of the plate, the dependence (1) was proposed: η¯ = η(M ¯ , DR, Tu1 , α, P/d , L/d , x/d )

(1)

It was obtained as a result of a generalization of experimental data, and its practical use is associated with the sequential calculation of twenty algebraic relations. Figure 2 shows a nonmonotonic change with increasing x/d and an increase in the injection parameter from the values M = 0.2 to M = 2.5. The position of the maximum efficiency practically does not change and is located at a distance of 4–5 calibers from the injection site (calculated by the diameter of the perforation hole).

Fig. 2. The effect of the injection parameter on the change in the efficiency of film cooling along the plate: (a) - low ratio of the densities; (b) - high ratio.

With blowing parameters from M = 0.2 to 0.6 the maximum efficiency increases due to an increase in the flow rate of the cooler. The highest efficiency peak η¯ = 0.385 is achieved with a blowing parameter value of M = 0.6. For injection parameters above M = 0.6 the peak of efficiency first decreases, and then, with the injection parameter M = 1.0 a local maximum is reached. A further increase in the blowing parameter causes a distinct separation of the jet. Efficiency far from the place of blowing is stabilized in the vicinity of the value η¯ = 0.12. At higher blowing parameters, the efficiency peak decreases, and the minimum efficiency occurs at M = 1.7. Figure 3 shows the width-averaged efficiency at a small angle of injection and two different hole spacings P/d = 2 and 5, respectively. With a small step of holes P/d = 2 (Fig. 3, a), the averaged efficiency is much higher than the values at P/d = 5, which is associated with a large specific consumption of cooler per unit area of the protected plate. The highest maximum now occurs at M = 0.5 and reaches a value of η¯ = 0.53. In the case of P/d = 2, the position of the maximum is clearly visible with a further decrease in efficiency at a large distance from the blowing place than with P/d = 5 (Fig. 3, b).

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Fig. 3. The effect of hole spacing on film cooling performance: P/d = 2.0 (a); P/d = 5.0 (b).

3 Results The calculation results are presented in Table 1. First, the search for the maximum film cooling efficiency was carried out when only two parameters P¯ and M were changed in the ranges: 2 ≤ P¯ ≤ 4 and 0.5 ≤ M ≤ 3 if the values of other parameters were constant: Tu1 = 1.5%; α = 350; DR = 1.095; x/d = 5, Red = 1000. In the future, the search for the maximum cooling efficiency was carried out on a broader basis, namely, by varying five independent parameters at once: 1.0% ≤ Tu1 ≤ 10%; 300 ≤ α ≤ 900; 1.1 ≤ DR ≤ 2.87; 2 ≤ P¯ ≤ 4 and 0.5 ≤ M ≤ 3.0. Table 1. Results of numerical optimization of a film cooling system. First case (two variables)

Second case (five variables)

Design variables

Effectiveness Design variables

M

0.5

0.295

P/d

2.0

Effectiveness

M

1.236 0.414

P/d

2.0

Tu1

0.1

α

1.57

DR

1.18

4 Discussion In the first case, the calculation results indicate that the greatest value of the film cooling efficiency η¯ = 0.295 and is achieved at M = 0.5 and P¯ = 2.0. These values correspond to the experimental data [15, 16], while the discrepancy of 15% can be explained by some difference in the initial data in the experiment and calculation. The search results for the global maximum when varying five variables indicate an increase in the maximum value cooling efficiency to a value equal to η¯ = 0.414 at Tu1 = 10%; α = 900; DR = 1.18; P¯ = 2.0 and M = 1.236.

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5 Conclusions It is shown that IOSO NX GT 2.0 is a reliable tool for finding the optimal solution to one function of the target (efficiency of cooling). This algorithm can be successfully used in combination with various application programs. As an example, a search was made for a global maximum of efficiency and optimal parameter values for a film cooling system, as applied to operating conditions of gas turbine blades.

References 1. Krivonosova, V., Lebedev, A., Simin, N., Zolotogorov, M., Kortikov, N.: Experimental and numerical analysis of high temperature gas turbine nozzle vane and film cooling effectiveness. In: Turbo Expo – 2011, GT- 45294, Proceedings of ASME, Vancouver, pp. 1–9 (2011) 2. Kortikov, N.N., Kuznetsov, N.B., Sadovnikova, T.Y.: Improvement of approaches for simulating the thermal state of perforated blades used in high temperature gas turbines. Therm. Eng. 59(1), 13–19 (2012). https://doi.org/10.1134/50040601512010065 3. Li, S., Yang, S., Han, J.: Effect of coolant density on leading edge showerhead film cooling using PSP measurement technique. In: ASME Paper GT-94189, pp. 1–11 (2013) 4. Sakai, E., Takahashi, T., Funazaki, K., Salleh, H., Watanabe, K.: Numerical study on flat plate and leading edge film cooling. In: ASME Paper GT-59517, pp. 1–13 (2009) 5. Lee, K.D., Choi, D.W., Kim, K.Y.: Optimization of ejection angles of double-jet film-cooling holes using RBNN model. Int. J. Therm. Sci. 73, 69–78 (2013) 6. Lapshin, K.L.: Optimization of the Flow Parts of Steam and Gas Turbines. Polytechnic University Publishing, St. Petersburg (2011) 7. User Guide STAR-CCM+ 10.06. Optimate+. CD-adapco (2015) 8. HEEDS MDO (2019). http://www.mdx.plm.automation.siemens.com. Accessed 3 Apr 2020 9. Pinter, J.D.: Nonlinear optimization with GAMS/LGO. J. Global Optim. 1, 79–101 (2007) 10. Hadrick, J.K., Metzger, D.E., Taxuchi, D.I.: The use of formal optimization methods in the design of a gas film cooling system. AIAA J. 16(12), 149–155 (1978) 11. Lee, K., Kim, S., Kim, K.: Numerical analysis of film-cooling performance and optimization for a novel shaped film-cooling hole. In: ASME Paper GT-68529, pp. 1–11 (2012) 12. Egorov, I.N., Kretinin, G.V., Leshchenko, I.A. Kuptzov, S.V.: IOSO optimization toolkit - novel software to create better design. In: 9th AIAA/ISSMO Symposium and Exibit on Multidisciplinary Analysis and Optimization. AIAA paper AIAA-5514, Atlanta, pp. 1–12 (2002) 13. Egorov, I.N., Kretinin, G.V., Fedechkin. K.S.: Multi-level robust design optimization fan. In: Workshop CEAS, Vrije Universiteit Brussels (VUB), Brussels, Belgium, pp. 1–11 (2010) 14. IOSO NS GT vers. 2.0: IOSO Technology Center, Moscow, 2001–2003. http://www.iosotech. com. Accessed 3 Apr 2020 15. Baldauf, S., Scheurlen, M., Schulz, A., Wirtig, S.: Correlation of film cooling effectiveness from thermographic measurements at engine like conditions. In: Proceedings of the ASME. Turbo Expo, Amsterdam, The Netherlands, pp. 1–14 (2002) 16. Pakhomov, M.A., Terekhov, V.I., Khalatov, A.A., Borisov, I.I.: Film cooling effectiveness with injection through circular holes embedded in a transverse trench. Thermophys. Aeromech. 22(3), 329–338 (2015). https://doi.org/10.1134/S0869864315030075

Modeling of Wear Processes in a Cylindrical Plain Bearing Aleksandr Dykha1 , Viktor Artiukh2(B) , Ruslan Sorokatyi1 Volodymyr Kukhar3 , and Kirill Kulakov4

,

1 Khmelnytsky National University, Str. Instytutska 11, Khmelnytsky 29000, Ukraine 2 Peter the Great St. Petersburg Polytechnic University, Str. Polytechnicheskaya 29,

195251 St. Petersburg, Russia [email protected] 3 Pryazovskyi State Technical University, Str. Universytetska 7, Mariupol 87500, Ukraine 4 Moscow State University of Civil Engineering, Yaroslavskoe Shosse, 26, Moscow 129337, Russia

Abstract. One of the most important and significantly affecting the behavior of technical systems is the wear process of elements. The use of numerical modules of application programs is carried out using the simulation and analysis of the physical processes occurring in the wear process. Numerical models should be based on the use of a unified mathematical apparatus and a methodological approach to describe the behavior of various types of technical tribosystems. Models should describe the wear process as a non-stationary random process. The paper analyzes the shaping of the wear surface of a radial plain bearing operating under conditions of skew axis of the shaft and sleeve. The problem was solved by the method of triboelements in the environment of the finite element package ANSYS. The combined use of triboelement and finite element methods has removed a number of restrictions in the calculation models. As a result of the calculation analysis, the presence of a transition wear zone was revealed and experimentally confirmed, quantitative parameters were determined, and the mechanism of its formation was explained. A comparative analysis of the results of numerical modeling and experiment shows a good agreement between qualitative and quantitative laws. The proposed complex algorithm for the numerical solution of the contact wear in a rally bearing is recommended for use in engineering calculations of the wear of various machines and mechanisms. Keywords: Plain bearing · Wear · Profile formation · Simulation · Triboelement method

1 Introduction The problem of wear of radial plain bearings with misalignment of shaft and bush axes was considered elsewhere [1–8]. It should be noted that the authors of [1–3] paid insufficient attention to the wear mechanism of surface-profile formation at the initial © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 542–552, 2021. https://doi.org/10.1007/978-3-030-57453-6_52

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moment of tribojoint operation. Furthermore, wear governing factors were considered to be determined values. In works [4, 5], the efficiency of plain bearings with thin onelayer [4] and multilayer [5] antifriction coatings with misaligned shaft and bush axes was considered stochastically; however, during the construction of the model, it was assumed that the elastic deformation of the coating is described by the Vinkler model, which reduces the applicability of the obtained results to thin coatings. At the same time, successful solutions are known that use to determine the changing face geometry of wear, including for the shaft and bush of sliding bearings, the finite element method (FEM) [9–11], artificial neural networks [12] and dynamic approximation of jointed surfaces using superformula [13, 14]. Such approaches make it possible to comprehensively take into account the effect of antifriction coating thickness [15, 16], changes in wear surfaces geometry and stress-strain state to determine the main parameters of the wear model. The aim of the work is to analyze the formation of wear-surface geometry in a radial plain bearing with misaligned shaft and bush axes. The method of triboelements with the ANSYS finite-element modeling package [9] was used to solve the problem. The joint application of the methods aims to extend the possibilities of the method of triboelements via using the findings of finite-element analysis of the stress-strain state of tribojoint elements as data for determining parameters of the triboelements model of wear. The joint application of these methods made it possible to eliminate some of the limitations in the calculation models. In works [17–24] the experimental design approaches for solving wear-contact problems for sliding bearings is proposed. On the basis of direct and inverse wear-contact tasks, algorithms are presented for calculating bearing wear and identifying the parameters of their wear laws. At the same time there are difficulties in the engineering implementation of the solutions obtained. Thus, for a more accurate calculation of the shape of the worn surface of sliding bearings, numerical calculation methods are needed. Methods of computer modeling the behavior of tribosystems should take into account the physical mechanisms of the wear process and determining factors.

2 Calculation Model and Mathematical Model A contact of a rigid shaft of R1 radius with a cylindrical elastic antifriction layer of ε thickness in engagement with a rigid bush (Fig. 1) was considered. The shaft is positioned at angle α to the bush. The axis z is directed along the bearing axis. The bearing wear and contact pressures depend on the position of contact points. It is taken that only the antifriction layer is worn. General theses of the algorithm for the solution of wear contact problems using the method of triboelements with ANSYS package are discussed in [9]. Thus, the interaction algorithm of the wear calculation module by the triboelement method with the ANSYS complex can be represented as follows. 1. Building on the basis of the ANSYS complex a geometric model of a technical system, including tribo-conjugates.

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Fig. 1. Calculation model.

2. Building by means of the calculated finite-element model of the system and triboconjugation. 3. Saving the set of coordinates of the nodes of the finite elements of the tribological conjugation located on the wear surface. 4. Using the solver of the ANSYS complex, taking into account a given set of input parameters, the stress-strain state of the elements of the technical system, including the elements of tribo-conjugation, is determined. 5. Using the obtained decision results, the parameters of the wear model are determined in the wear calculation module. The parameters are the values of the components of the transition probability matrix for each node of the finite element that has come into contact. 6. In the module for calculating wear, a mathematical average of the amount of wear is determined for each node of the finite element located on the wear surface. 7. Using the module for calculating wear, the amount of wear is determined, and a set of new coordinates of the nodes of the finite elements located on the wear surface is determined. In order to solve wear contact problems in a spatial setting, one should take into consideration that, in this case, a cubic spline of the worn surface is constructed. At each iteration of wear determination, a cubic spline of the worn surface is constructed, the geometry of which takes into account the wear of the previous step. The calculation scheme allowed us to build a parameterized calculation model in the preprocessor of the ANSYS package (Fig. 2). The contact interaction of elements of the tribojoint was simulated as a rigid–compliant contact. Shaft 2 (Fig. 2), which is rigid, was taken as a target surface. Antifriction layer 1 was taken as the contact surface. On the contact surface of the antifriction layer, the geometric position of the triboelements was determined. SOLID186 twenty-node spatial elements were used to generate a mesh of the finiteelement model of the antifriction layer. Surface–surface contact elements were used

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to obtain a shaft–antifriction element friction pair. The target surface is described by TARGE170 elements and the contact surface is described by CONTA174.

Fig. 2. Calculation model: 1. antifriction element, 2. rigid shaft.

Wear was considered to be a random Markov-type process with a discrete time and state. At the moment of time t = 1, the probabilities of TE in a given state were   finding by the transition-probability found as the product of the vector of initial states π j   matrix (TPM) Wij :      πj (t = 1) = πj (t = 0) Wij , i, j = 1, 2, . . . , KC (1)     where πj (t = 0) is the vector of initial states; πj (t = 1) is the vector of unconditional of finding TEs in ith states i = 1, …, KC at the moment of time t − 1; and  probabilities of TE states at a moment Wij is the transition-probability matrix. The   probabilities of time t > 1 were found as the product πj (t − 1) of the vector of unconditional probabilities at the moment (t − 1) by TPM that specifies the behavior of TE at the moment t as follows:      i, j = 1, 2, . . . , KC πj (t) = πj (t − 1) Wij , (2)   Components of the vector of initial states πj (t = 0) were determined based on the assumption that, at the initial moment of time, the TE was in the first state as follows:   πj (t = 0) = [1, 0, 0, . . . 0]. (3) The accumulation of tribodamage refers to cumulative damages; therefore, to describe the TE behavior, the TPM with singular upward jumps and absorbing state [17], which accounts for the mechanical essence of wear, namely, the subsequent damage of material layers, as follows: ⎡ ⎤ 0 ... 0 w11 (t) w12 (t) 0  ⎢ 0 w22 (t) w23 (t) 0 . . . 0 ⎥  ⎥. (4) Wij = ⎢ ⎣ ... ... ... ... ... ...⎦ 0

0

0

0 ... 1

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The absorbing state is taken to mean the state of total wear of the antifriction layer. According to [18], components wij (t) were found as follows: wij (t) ∼ = λI (t) t, i = j ,

(5)

where the intensity of wear flow λ1 (t) = V1 (t)/h; t is the period of time that governs the loading cycle; h is the wear value that is found from the condition of ordinary nature of flow; V1 (t) is the wear rate at the moment of time t. The value of h is chosen from the condition that the probability of occurrence of a wear value more than h per a loading cycle is negligibly small. Wear values are found via the mathematical expectation mt of finding TE as follows: zt = (mt − 1) h, where the mathematical expectation mt =

KC

i πi (t),

(6) i = 1, 2, . . . , KC ; πi (t) is

i=1

unconditional probabilities of TE states; h = ε/(KC − 1). It was assumed that, at the initial moment of time, all elements were in state 1. The following power dependence was used as a function of wear rate versus contact pressures and sliding velocities: VI = Kw Vp(φ, φ0 (t))γ ,

(7)

where V1 is the wear rate, Kw is the coefficient of wear rate, V is the sliding velocity of shaft on antifriction layer, p(ϕ, ϕ0 , (t)) is contact pressures, and γ is the exponent.

3 Numerical Performance Numerical analysis was performed for the following parametric values: Q = 300 N; ε = 2.6·10−3 m;  = 2.0·10−4 m; R1 = 1.12·10−2 m; Vcp = 0.95 m/s; KC = 5; Kw = 1·10−12 m2 /N. Calculation results were used to build contact pressure distributions on the surface (Fig. 3) for the initial moment of time, for the moment that corresponds to active geometry variation (0.75 ks) and the period of stationary wear of tribojoint elements (9 ks). An analysis of time variation of contact pressures (Fig. 4) and maximum wear (Fig. 5) has shown the basic processes of geometry formation of the wear surface to occur at the initial moment of time before 1.5–2.0 ks. At this time, the wear becomes stationary, which is evinced by almost all linear dependences of maximum pressure (Fig. 4) and maximum wear (Fig. 5). An analysis of the shape of the contact pressure distribution on the surface at the initial moment of time in the absence of wear (Fig. 3a) shows that maximum contact pressures that act along of axis of load application drop linearly from the maximum on the bush face to zero in the exit zone from the contact of the shaft with the bush. The beginning of wear results in variations in the surface geometry of the shaft–bush contact, and an increase in the area of contact interaction, and a substantial decrease in maximum contact pressures. Here, the contact pressures rise near the contact surface boundaries (Fig. 3b). Therefore, in the beginning of the wear, upon wear surface formation, contact pressures tend to be equalized both in axial and radial directions.

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Fig. 3. Contact pressure distribution on the surface at an angle of misalignment of the shaft and bush axes of 0.5° at the following moments of time: (a) 0 ks; (b) 0.75 ks; (c) 9 ks.

This behavior of the contact pressures at the initial moment of wear is attributed to the fact that, retaining continuity of the shaft–bush contact and provision of the equality of the values of shaft point movements under the action of the applied forces and under wearing requires the uniform bush wear along the contact axis, which is provided by the equalized contact pressures (Fig. 3c). In this case, the calculation model assumes a constancy of the axes misalignment angle during wear, which governs the above mechanism of the kinematic bush–shaft interaction. The additional degrees of freedom that govern the possibility of varying the angle of axis misalignment and taking into account nonuniform contact pressures and, consequently, wear (maximum at the bush face and zero in the contact exit zone) in the direction of the plane of load application would result in the increasing angle of mutual misalignment of the axes of the tribojoint elements.

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The wear surface increases along the boundaries of the wear contact interaction owing to new contact elements of the unworn surface due to elastic deformation of the bush. As a result, a transitional wear zone arises on the boundaries of the interaction zone (Fig. 6b), which is characterized by a nonlinear dependence of the wear values in the direction of the plane of load application. At the initial stage of contact surface geometry formation, contact pressures substantially drop. Here, the shape of pressure distribution on the surface tends to be uniform in both the axial and radial directions (Fig. 3c). The linear mode of the time dependences of maximum contact pressures and wear (Figs. 4, 5) during this period makes it possible to conclude that the system starts operating under stationary wear conditions.

Fig. 4. Maximum contact pressures vs. wear time at misalignment of shaft and bush axes: (1) 0.35°; (2) 0.5°; (3) 0.75°.

Fig. 5. Maximum wear vs. wear period at misalignment of shaft and bush axes: (1) 0.35°; (2) 0.5°; (3) 0.75°.

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Fig. 6. (a) Wear surface and (b) transitional zone for axis misalignment angle 0.5° and wear time 9 ks.

Fig. 7. Samples upon testing (axis misalignment is 0.5°, test time is 9 ks).

4 Results and Discussion In order to validate the calculation results, we conducted experiments when a bush is worn by a rigid shaft with mutual axis misalignment at the geometrical and force

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friction parameters that correspond to the calculation analysis. A composite material based on Flubon 15 fluoroplastic was used as a material for the sample to be worn. The choice of the material is caused by its triboengineering characteristics to provide stable operation under unlubricated friction with a low coefficient of friction and absence of wear of the second element of the tribojoint. The tests were carried out at a shaft rotation frequency of 800 rpm. A transitional wear zone between the worn and unworn surface can be seen on the pictures of the cut specimen (Fig. 7) upon testing. The results of measurement of the transitional zone for different misalignment angles of shaft and bush angles are shown in the table. A comparison of the wear surfaces and dimensions of the transitional zones obtained via calculations and experiments demonstrates good quantitative and qualitative consistency (Table 1). The width of the transitional zone, as evidenced by the experimental findings and results of numerical analysis depends on the mutual misalignment angle of shaft and bush axes. A decrease in the misalignment angle results in the increasing width of this zone. Table 1. Width and length of wear area. Axes misalignment angle, grade

0.35

Wear surface length (experiment/calculation), mm

14.52/14.50 11.68/11.75 9.15/9.25

Width of transitional zone in the direction of bush axis 0.72/0.75 (experiment/calculation), mm

0.50 0.55/0.50

0.75 0.30/0.25

A general analysis of the data obtained in experimental studies and numerical simulation has shown good consistence of quantitative and qualitative results.

5 Conclusions The paper discusses the findings of the study of wear surface geometry formation in plain bearings with misaligned shaft and bush axes. The calculation analysis made it possible to reveal and experimentally confirm the presence of a transitional wear zone, determine its quantitative parameters, and explain the mechanism of its origination. A comparative analysis of the numerical simulation and experimental data shows good consistency of qualitative and quantitative regularities. Data analysis shows that, for the given scheme of wear contact interactions, the initial wear period is the period of the active formation of the wear surface geometry. Large contact pressures that arise from the mutual misalignment of tribojoint element axes govern the high surface wear rate and the rapid increase in the surface of wear contact interaction. This, in its turn, leads to a rapid decrease in actual contact pressures. In this case, the contact pressures are equalized in the axial and radial directions. Newly appeared contact surface spots start to wear, a result of which a transitional wear zone is shaped. In the small period of time of surface geometry formation, the tribosystem is worn under stationary conditions.

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Acknowledgments. The reported study was funded by RFBR according to the research project №19-08-01241a. The authors declare that there is no conflict of interest regarding the publication of this paper. This research work was supported by the Academic Excellence Project 5-100 proposed by Peter the Great St. Petersburg Polytechnic University.

References 1. Chernets, M.V.: Prediction of the life of a sliding bearing based on a cumulative wear model taking into account the lobing of the shaft contour. J. Frict. Wear 36(2), 163–169 (2015). https://doi.org/10.3103/S1068366615020038 2. Soldatenkov, I.A.: Evolution of contact pressure during wear of the coating in a thrust sliding bearing. J. Frict. Wear 31(2), 102–106 (2010). https://doi.org/10.3103/S1068366610020029 3. Goryacheva, I.G., Mezrin, A.M.: Simulation of combined wearing of the shaft and bush in a heavily loaded sliding bearing. J. Frict. Wear 32(1), 1–7 (2011). https://doi.org/10.3103/s10 68366611010053 4. Dykha, A., Sorokatyi, R., Makovkin, O., Babak, O.: Calculation-experimental modeling of wear of cylindrical sliding bearings. East. Eur. J. Enterp. Technol. 5(1), 51–59 (2017). https:// doi.org/10.15587/1729-4061.2017.109638 5. Mezrin, A.M.: Determining local wear equation based on friction and wear testing using a pin-on-disk scheme. J. Frict. Wear 30(4), 242–245 (2009). https://doi.org/10.3103/S10683 66609040035 6. Artiukh, V., Belyaev, M., Ignatovich, I., Miloradova, N.: Depreciation of bearing blocks of rollers of roller conveyers of rolling mills. IOP Conf. Ser. Earth Environ. Sci. 90, 012228 (2017). https://doi.org/10.1088/1755-1315/90/1/012228 7. Maruschak, P.O., Panin, S.V., Zakiev, I.M., Poltaranin, M.A., Sotnikov, A.L.: Scale levels of damage to the raceway of a spherical roller bearing. Eng. Fail. Anal. 59, 69–78 (2016) 8. Nikitchenko, A., Artiukh, V., Shevchenko, D., Larionov, A., Zubareva, I.: Application of nonlinear dynamic analysis for calculation of dynamics and strength of mechanical systems. In: Murgul, V., Pasetti, M. (eds.) EMMFT-2018 2018. AISC, vol. 983, pp. 496–510. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-19868-8_49 9. Sorokatyi, R.V., Dykha, A.V.: Analysis of processes of tribodamages under the conditions of high-speed friction. J. Frict. Wear 36(5), 422–428 (2015). https://doi.org/10.3103/S10683 6661505013X 10. Bharat, V., Prasad, B.D., Krishnaprasad, N.J., Venkateswarlu, K.: Evaluation of contact stresses in bearings made of Al – Beryl Metal Matrix composites by finite element method. Procedia Mater. Sci. 5, 598–604 (2014). https://doi.org/10.1016/j.mspro.2014.07.305 11. Solomonov, K.N.: Application of CAD/CAM systems for computer simulation of metal forming processes. Mater. Sci. Forum 704–705, 434–439 (2012) 12. Saridakis, K.M., Nikolakopoulos, P.G., Papadopoulos, C.A., Dentsoras, A.J.: Identification of wear and misalignment on journal bearings using artificial neural networks. Proc. Inst. Mech. Eng. Part J J. Eng. Tribol. 226(1), 46–56 (2011). https://doi.org/10.1177/135065011 1424237 13. Anishchenko, O.S., Kukhar, V.V., Grushko, A.V., Vishtak, I.V., Prysiazhnyi, A.H., Balalayeva, E.Y.: Analysis of the sheet shell’s curvature with Lame’s superellipse method during superplastic forming. Mater. Sci. Forum 945, 531–537 (2019). https://doi.org/10.4028/www.scient ific.net/MSF.945.531 14. Anishchenko, A., Kukhar, V., Artiukh, V., Arkhipova, O.: Application of G. Lame’s and J. Gielis’ formulas for description of shells superplastic forming. MATEC Web Conf. 239, 06007 (2018). https://doi.org/10.1051/matecconf/201823906007

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15. Anishchenko, A., Kukhar, V., Artiukh, V., Arkhipova, O.: Superplastic forming of shells from sheet blanks with thermally unstable coatings. MATEC Web Conf. 239, 06006 (2018). https:// doi.org/10.1051/matecconf/201823906006 16. Cao, J., Qin, L., Yu, A., Huang, H., Li, G., Yin, Z., Zhou, H.: A review of surface treatments for sliding bearings used at different temperature. In: Chowdhury, M.A. (ed.) Friction, Lubrication and Wear. IntechOpen (2019). https://doi.org/10.5772/intechopen.86304 17. Sorokatyi, R., Chernets, M., Dykha, A., Mikosyanchyk, O.: Phenomenological model of accumulation of fatigue tribological damage in the surface layer of materials. In: Uhl, T. (ed.) IFToMM WC 2019. MMS, vol. 73, pp. 3761–3769. Springer, Cham (2019). https://doi.org/ 10.1007/978-3-030-20131-9_371 18. Dykha, A.V., Kuzmenko, A.G.: Solution to the problem of contact wear for a four-ball weartesting scheme. J. Frict. Wear 36(2), 138–143 (2015). https://doi.org/10.3103/S10683666150 20051 19. Levandovskiy, A.N., Melnikov, B.E., Shamkin, A.A.: Modeling of porous material fracture. Mag. Civ. Eng. 1, 3–22 (2017). https://doi.org/10.18720/MCE.69.1 20. Efremov, D.B., Gerasimova, A.A., Gorbatyuk, S.M., Chichenev, N.A.: Study of kinematics of elastic-plastic deformation for hollow steel shapes used in energy absorption devices. CIS Iron Steel Rev. 18, 30–34 (2019) 21. Artiukh, V., Mazur, V., Kargin, S., Zakharova, L.: Adapters for metallurgical equipment. MATEC Web Conf. 170, 03028 (2018). https://doi.org/10.1051/matecconf/201817003028 22. Maksarov, V.V., Keksin, A.I.: Forming conditions of complex-geometry profiles in corrosionresistant materials. IOP Conf. Ser. Earth Environ. Sci. 194(6), 062016 (2018). https://doi.org/ 10.1088/1755-1315/194/6/062016 23. Pestryakov, I.I., Gumerova, E.I., Kupchin, A.N.: Assessment of efficiency of the vibration damping material «Teroson WT 129». Constr. Unique Build. Struct. 5(44), 46–57 (2016) 24. Dykha, A.V., Kuzmenko, A.G.: Distribution of friction tangential stresses in the CourtneyPratt experiment under Bowden’s theory. J. Frict. Wear 37(4), 315–319 (2016). https://doi. org/10.3103/s1068366616040061

Modern Method of Computer Simulation of Structures and Physical Properties of Composite Materials Milana Chantieva1(B)

, Khizar Dzhabrailov1(B) and Dmitriy Suvorov2

, Rinat Gematudinov2

,

1 Moscow Technical University of Communications and Informatics,

Aviamotornaya Str., 8a, Moscow 111024, Russia [email protected] 2 Moscow Automobile and Road Construction State Technical University (MADI), Leningradsky Avenue, 64, Moscow 125319, Russia [email protected]

Abstract. The optimal direction of scientific research in the study of the structural and physical properties of composite materials is presented in article. A plan for experimental and theoretical work has been developed. Methods of modeling the structure of composite materials using a computer are shown. In this case, the software should provide an end result aimed at calculating the required values. The problem of calculation and a research of physical properties of concrete taking into account their structural features are of great theoretical and practical interest. Creation of new manufacturing techniques of construction materials demands theoretical justifications, and often and strict analytical dependences. Also presented is the latest direction in the study of building composite materials, which has the term “computer material science”, which studies the properties of composite materials based on computer modeling. All this led to the fact that many researchers began to use idea of the composition nature of the structure of materials that creation of the uniform theory of structuration and properties of construction materials demanded. It led to emergence of the new direction in construction science called “Construction materials science”. Keywords: A filtration · Granulometric properties of composites · Modeling of the structure of composite materials · Computer modeling of the structure of composites · Computer materials science · Mathematical modeling · A cluster · Composite swore · Structure of composite materials

1 Introduction It is known that experimental methods for studying the structure of composite materials have several disadvantages. The ability to realize the analytical dependence of the components of composite materials on the properties of the binder and their concentration was impossible. With the advent of powerful algorithmic programming languages, it became possible to use a computer to search for a composite with desired properties [1]. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 553–561, 2021. https://doi.org/10.1007/978-3-030-57453-6_53

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2 Purpose and Solution of a Task Using this method will allow you to implement a set of random elements of composite materials. The structure of the composite can be investigated using the theory of “leakage” —the study of the properties of the connected components of random graphs, the modeling of the composite structure, and this reduces to a digital model that will be stored in the computer’s memory. So, it will be possible to study the processes of percolation and fluid seepage into composite materials [2].

3 Method of Selection of the Composition of Composite Materials When considering composite materials, the development of the structure is replaced by modeling the process of randomly filling the volume, where the simulation process is transferred to a computer using algorithms. The tasks of such modeling include: – study of the development of the structure of the composite. – identification of the relationship of the properties of elements. Analytical studies during the formation of the structure were carried out using aggregate density. Such a process took place over time, where each element of the packed element was exposed to a certain point in time, chosen randomly [3]. By criterion of the accepted model when performing a condition:  2   2 s  x(t) − xi t 0 ≥ R(t) − R t 0 , 0 ≤ t ≤ t0 i=0

(1)

Process of filling will continue until in the set area there is no Poisson point left meeting this condition (1). In time interval [t0, t0 + dt] number of spheres which can be packed equally: dn = αe − Ndt.

(2)

The number of the expected Poisson points is equal: N = αV[R(t) + R(t0)]sdt,

(3)

where V - the volume of the s-dimensional sphere of single radius; V =

π s/2 .  T 1 + 2s

(4)

The number of the packed spheres above during T(R) will be expressed by R radius as:   0 −aV ∫t [R(t)+R t 0 ]2

0 n(R) = α ∫t 0 ≤T (R)

dt 0

(5)

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Let’s enter also a concept of function of density of packings ρ (R) as volume of spheres R radius above in the single volume of packing:   0 −aV ∫t [R(t)+R t 0 ]2

0 ρ(R) = αV ∫t 0 ≤T (R)

dt 0

(6)

The extreme value of function of density for equal spheres is equal: t0

s −aω ∫0 (2R) dt 0 ρ = αω ∫∞ 0 R e s

(7)

Using a computer allows you to obtain models, as well as calculate structural and physical characteristics using programs that combine random-fill model algorithms and computational algorithms [4–6].

4 The Development of a Composite Material Structure-Modeling Algorithm Based on the analysis of the algorithms, the “PACKAGING” algorithm is developed. The algorithm “PACKING” allows you to get a package with a filling density of 0.35… 0.4. Modeling is performed by filling balls with distributed diameters in the ranges of 0.06– 0.12, 0.12–0.25, 0.25–0.35. Checking the coordinates of the packed sphere is carried out under the condition:   1 − Rmin > x(k) > Rmin , k = 1, 2, 3 (8) that is check of hit of coordinate of the center of the sphere in the packed volume is carried out: Rmin ≤ Ri ≤ Rmax ,

(9)

that is hit of radius of the played sphere in 1 particle size distribution set by the block: x(k) ⊂ Vi (10) Vi ⊂ Vj that is check of a condition not of crossing of the packed sphere Vi volume from Vj which is earlier packed by volume: 3 [x(k) + Ri ] < 1

3k=1 (11) k=1 [x(k) − Ri ] > 0

5 Development of a Porosity Model for a Composite Material Based on Its Mathematical Structure Model When studying the physical properties of a liquid and the properties of a composite, models of the layer structure are used. In the practice of hydraulic calculations, the

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capillary model was widely used. Since the simplicity of hydraulic dependences obtained based on this model satisfies the coincidence with experience with the introduction of a minimum number of correction empirical coefficients. Namely, its tortuosity coefficient T, which shows the relative elongation of the capillary, which occurs due to the curvature of the trajectory of the liquid at a filler concentration [7]. T=

1 N Ti i=1 N

(12)

The S(T) there is less, the material is more uniform. At the same time the absolute size of a mean square deviation depends not only on degree of uniformity of material, but also on absolute value of average size of coefficient of tortuosity. These deviations in coarse-grained material most often happen more, than in finely porous (fine-grained), therefore the mean square deviation of S(T) can be useful only for comparison purposes materials with approximately identical structures. Generally, objective assessment of uniformity of structure is the relative size of a mean square deviation - the attitude of an average quadratic deviation towards average value of coefficient of tortuosity that is variation coefficient. S(T ) = S(Tot )η¯ T

(13)

S2 2 1 N (Ti − T )2 ;S = i=1 N −1 T¯

(14)

Sv = Φα =

If Ti is average value of coefficient of tortuosity in i-m the direction, then for N case = 3 it is possible to write down:  (T 1 − T )2 + (T 2 − T )2 + (T 3 − T )2 Φa = (15) 1, 41T The smallest length (Fig. 1) of a capillary of li between points of A and B is found how length of a way of liquid, on the shortest geodetic curve expression (16) will register in the form suitable for calculation for the COMPUTER       



x − xj + y − yj + y − y x − x 1 n j j   Rj [arcsin 1 − − ] T (x, y) = 1 + j−1 l0 R2j R2j (16) where xj , yj are coordinates j-and spheres R radius. Calculation of dispersion and autocorrelation function of coefficient of tortuosity was carried out by means of the scheme on the known formulas of the theory of probabilities (Fig. 2). Here k = 1, 2… — number of sections of a sample on an axis x, i = 1, 2… — number of capillaries in k section. Then the Dx (k) value is averaged on number of section Dx (A) =

1 N Dk k=1 N

(17)

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B rj O

A oi

α C D

Fig. 1. Scheme of calculation of length of the minimum capillary.

1

K

0.5

t 0 0

0.1

0.2

0.3

0.4

0.5

0.6

Fig. 2. Dispersion (a) and correlation function of coefficient of tortuosity (b).

The x y function symbol means that the calculations were carried out along the OH axis. The autocorrelated functions obtained for various types of structures show a certain value of the dependence of the tortuosity coefficient (correlation) in a narrow interval equal to the average statistical diameter of the packed particles in the mixture. The

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claimed methodology, and the values of tortuosity coefficients, statistical characteristics can be used in hydraulic calculations of the movement of gases and liquids through granular layers. It was previously noted that the task of studying the concentration hollow characteristics of a composite material consists of two tasks: modeling the structure of the composite material and the problems of studying concentration hollow characteristics and determining their particle size distribution. For this, it is necessary to analyze the hollow characteristics of this composite, depending on its concentration and structural properties. Thus, we can turn to electrical analogy in calculating the properties of composite materials. The task of mathematical modeling is to calculate the electrophysical characteristics of a composite material. Use of the theory of “the effective environment” when imposing outputs of the theory of “course” to it will allow to model concentration characteristics of electro physical properties of a system the di-electrician-conductor, generally, and composition material on the basis of polymeric knitting, in particular [8].   1 k − (VKOH − VKOH (18) )2 β B= 2 where Vkon is volume concentration of the carrying-out phase (sand); Big advantage is the universality of exponents (critical indexes the) of q, s, t and communication between them following from the general theory of phase transitions: q = t (1/s − 1)

(19)

The formula Landaue-ra-Bruggemana is more convenient: (20) The potential difference between the plates of two spheres is shown in Fig. 3.

Z

Z

R dψ R dψ

R

dψ r

X

dφ r φ

rdφ dS Y

Fig. 3. to a conclusion of expression (20) in the dipolar (bispherical) system of coordinates.



ashη X = chη−cosξ ; Y = ρcosϕ sinϕ Z = ρsinϕ; ρ = chη−cosξ

(21)

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Thus, the conductivity between two spherical inclusions in homogeneous effective environment can be written down as  dS , (22) g = γ0 1(ψ) s Since on ϕ corner the value of length of an arch of current does not change, expression (23) can be rewritten: dS = R2 sinψd ψd ϕ

(23)

Corners of  P1M1O and  C1O1P1 are equal as formed by mutually perpendicular parties L1 − R1 cosψ1 C1 P1 R(ξ ) = tgψ1

C1 P1 =

(24) (25)

Taking into account expression (25) for (26) we will receive:  π sin2 ψ 2 d ψ1 , g1 = γ0 R1 2π 0 ψ1 (L1 − R1 cosψ1 )  π sin2 ψ d ψ1 , (26) g2 = γ0 R22 2π 0 ψ2 (L2 − R2 cosψ2 ) In the described computer CritConc program the latest approaches to computer modeling were applied. Besides, modern approaches to programming allowed to reduce as much as possible operating time of programs and also to simplify its interface. Obtaining results using simulation on a computer requires a large number of reimplementations for various random packaging. In this regard, the correct choice of the number of implementation in many respects contributes to the successful conduct of experiments with the developed model (Fig. 4).

R(Ом х 10n )

4.5 4 3.5 3 2.5 2 1.5 1 0.5

V кон

0 0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

Fig. 4. Dependence of the “seeming” resistance on Vkon .

0.4

0.45

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6 Comparison of Experimental Data with Data Obtained from Modelling For descriptive reasons works of the program for modelling of porous structure in composite material in Fig. 5. its working area with pseudo-three-dimensional interpretation of distribution of a crack is presented. Authors should use the forms shown in Table 3 in the final reference list.

Fig. 5. Result of modelling of a crack in composite structure.

Average concentration dependences of hollowness of composite material in subcritical and postcritical areas are given in Fig. 5 experimental (a curve 1) and model (a curve 2) when using filler with a radius of 0.03–0.175, measured in shares to cube edge length.

7 Conclusion On the basis of optimum direction of researches, the plan of experimental and theoretical researches will contain the following items: 1. To prove and learn methods for developing a mathematical model on a composite. 2. To develop an algorithm and the program of modeling of structure of composite material 3. On the basis of theory conclusions of “percolation (infiltration)” to develop the mathematical model connecting the filtering properties of composite material and its concentration and granulometric properties. In the described computer program “Crit Conc» , the latest approaches to computer modelling were applied. Besides, modern method to programming allowed to reduce as much as possible operating time of programs and to simplify its interface.

References 1. Ilyukhin, A.V., Chantieva, M.E., Gematudinov, R.A., Shukhin, V.V.: Cluster structures and the theory of percolation in computer materials science of construction composite materials. Bull. Moscow Automob. Road State Tech. Univ. (Moscow Administrative Road Inspectorate) 4(27), 97–101 (2011)

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2. Lyukhin, A.V., Chantieva, M.E., Gematudinov, R.A., Hakimov, Z.L.: Development of a method of calculation of fractional composition of the filtering materials. Bull. Moscow Automob. Road Instit. (State Tech. Univ.) 4(19), 117–123 (2009) 3. Ilyukhin, A.V., Chantieva, M.E.: Use of the porous permeable ceramics received by method of the burning-out additives as the filtering elements of ceramic filters for water purification. Bull. Moscow Automob. Road State Tech. Univ. (Moscow Administrative Road Inspectorate) 2(21), 75–79 (2010) 4. Chantieva, M.E., Iluhin, A.V., Dzhabrailov, Kh.A., Gematudinov, R.A.: Software optimization methods for composite materials. In: 2019 Systems of Signals Generating and Processing in the Field of on Board Communications, pp. 1–4. Moscow, Russia (2019). https://doi.org/10. 1109/sosg.2019.8706771 5. Dzhabrailov, K., Gorodnichev, M., Gematudinov, R., Chantieva, M.: Development of a control system for the transportation of asphalt mix with the maintenance of the required temperature. In: Popovic, Z., Manakov, A., Breskich, V. (eds.) TransSiberia 2019. AISC, vol. 1116, pp. 354– 364. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-37919-3_35 6. Gorodnichev, M., Dzhabrailov, K., Gematudinov, R.: Information system for obtaining parameters high-frequency vibrations of road-construction machines. Conference of Open Innovations Association, FRUCT 24, 619–623 (2019) 7. Marsov, V.I., Gematudinov, R.A., Seleznev, V.S., Dzhabrailov, K.A.: Systems of signals generating and processing in the field of on board communications. In: SOGS, 8706718 (2019). https://doi.org/10.1109/sosg.2019.8706718 8. Gematudinov, R.A., Romanov, K.S., Chantieva, M.E., Shukhin, V.V.: Optimal control of the pneumatic system in the process of dosing bulk materials. Vestnik MADI (GTU) 4(23), 110–113 (2010)

Remote Sensing of the Earth from Space to Determine the Economic Damage from Forest Fires Mikhail Shahramanyan1 , Andrey Richter2 , Marina Danilina1,3(B) Alexander Ovsianik1 , and Stanislav Chebotarev1

,

1 Finance University under the Government of the Russian Federation,

Leningradsky prosp. 49, 125993 Moscow, Russia {MAShakhramanyan,AIOvsyanik,SSChebotarev}@fa.ru, [email protected] 2 IRS “AEROCOSMOS”, Gorokhovskij per. 4, 105064 Moscow, Russia [email protected] 3 Russian Economic University, Stremyanny per. 36, 117997 Moscow, Russia

Abstract. The article describes the methodology of the rapid assessment of economic damage from forest stand loss as a result of forest fires, during and at the end of the fire hazard season. To achieve this goal, the following tasks are solved: identification of forest burns on space images; determination of the location of forest fires (coordinate reference); determination of the area of forest burned down in the current year; damage assessment in physical terms. A block diagram is presented and the steps of the algorithm for calculating the amount of damage from wood loss are described. Modis products are considered as a “material” for monitoring. The results of the economic damage assessment on the example of emergency with varying forest tax parameters are presented. The methodology for express assessment of economic damage from the loss of wood caused by forest fires, and its main stages are described. Modis information products and the main forest tax parameters in the monitoring of forest fires used in the methodology are presented. As a result of the research, estimates of economic damage were obtained for various images describing different emergencies: the European part of Russia, July–August 2010; Transbaikalia, Irkutsk Region, Far East, April 2012; Southern Siberia, Transbaikalia, Urals, April 2015; Krasnoyarsk Territory, Irkutsk Region, Buryatia, Transbaikalia, Yakutia, July–September 2019 Damage estimates are presented using the example of forest fires in 2019 in Krasnoyarsk Territory under different conditions: for different forest-taxing machines, with varying forest-tax categories, the level of wood quality and dominant tree species. Keywords: Economic loss · Forest fires · Remote sensing · Space · Earth

1 Introduction Currently, a large amount of information is being received from artificial Earth satellites, which can be used to assess damage from forest fires. In particular, from space images, © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 562–576, 2021. https://doi.org/10.1007/978-3-030-57453-6_54

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it is possible to obtain data on the coordinates of forest burns, the area of the burnt forest and its type. However, not all incoming information can be used to solve this problem. From space images of the earth’s surface with a resolution of 1 × 1 km, obtained from satellites of the NOAA series, it is impossible to estimate with a high degree of accuracy the area of relatively small burned forest areas. Large burns with an area of more than 20 ha can be determined from satellite imagery of the earth’s surface with a resolution of 150 × 150 m, obtained from the satellite and from satellite data EOS (TERRA), with a spatial resolution of 250 × 250 m. When using high-resolution space images (not less than 35 × 35 m), the accuracy of determining the area of forest burns is 1 ha. Since the purpose of the methodology is to obtain an express assessment of damage, such accuracy should be consistent with the task. Thus, to solve the above problem, it is necessary to use high-resolution or medium-resolution satellite images, depending on the required accuracy of the results. Forest fires are divided according to the type of burning into lower and upper fires and by the strength of burning into strong, medium and weak. Ground fires damage only the lower part of tree trunks and this type of fire cannot be detected from outer space, especially if the burning force was low [1]. During horse fires, the upper part or the whole tree burns down, therefore this type of fire is recorded from space. During horse fires, all wood dies or completely depreciates, therefore, to calculate the damage from fires, we accept that after the fire, the loss of wood is 100%.

2 Description of the Technique 2.1 The Source Data for the Calculations The source data for the calculations are the following: • space images with a spatial resolution of up to 250 m, which provide the identification of the area (ha) and the location of forest burns (geographical coordinates); • topographic maps M 1: 200 000, which determine the type and type of burned forest, the height, thickness and density of the burned forest vegetation; • cost of 1 cubic m of standing timber, which depends on the region, remoteness of the forest from roads, etc. and to a lesser extent on the type and species composition of the forest. 2.2 Cartographic Information Requirements Cartographic information should contain data on the type and species of the burned forest, the height, thickness and density of the burned forest vegetation. This information is displayed on topographic maps M 1: 200 000 or forest taxation maps or plans. 2.3 Determination of the Cost of 1 Cu. m of Standing Timber Minimum standing timber rates are approved by Decree of the Government of the Russian Federation. They are differentiated by administrative regions, which, depending on forest and economic conditions, are grouped into five groups.

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The amount of the fee depends on the species of wood (for example, pine is more expensive than aspen), the quality of raw wood (the most expensive is commercial thick wood, the cheapest is woodcutter), and the rate of fees, determined by the distance of haulage (the smaller it is, the higher the price). A total of seven forest tax categories are provided. The ratio of the cost of wood in the first and seventh category is quite significant and equal to 1: 0.27 [2]. 2.4 Flowchart of the Methodology The flow chart for calculating the damage - Fig. 1 [3].

Fig. 1. The flowchart of the algorithm for calculating the amount of damage from wood loss as a result of forest fires using space data.

The location of forest fires is determined by the coordinates obtained when forest fires were detected during a fire hazard period using ground or remote data. Terrestrial data are contained in Aviation Conservation reports, local authorities. When forest fires are detected according to remote sensing data, information from the NOAA satellite is used by AVHRR equipment. Fires are recognized by the “FIRE DETECTION” program. The geographical coordinates of the fire centers, the area of the burning forest, the distance from the settlements are determined. Forest burns can be identified directly from satellite images of medium and high spatial resolution (250 × 250 m and above). To do this, the image is loaded into the ERDAS Imagine viewer so that 2 (0.6–0.7 μm) spectral channel (Resource-O and SPOT) is colored red, 3 (0.8–0.9 μm) spectral channel is green and 1 (0.5–0.6 μm) spectral channel - in blue. When synthesized in such colors, forest burns have the following decryption features. It is known that the main deciphering sign of fresh burns after strong ground and wild horse fires is a dark gray and dark tone in the panchromatic channel, uneven, most often wedge-shaped borders.

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The first sign is due to the black burning surface, resulting from the complete burnout of the soil (moss) cover, adolescent and undergrowth, as well as carbonization of fallen leaves. The uneven nature of the edge of the burns is associated with different types and intensity of fires during the day, uneven fire maturation of plantation types, different categories of areas encountered along the path of fire spread, and finally, the direction of the wind during their operation. When forest burns are recognized by multi-zone images, the forest burn tone changes depending on the spectral channel. In the green (0.5–0.6 μm) section of the spectrum, burns are practically invisible, have the same gray tone as coniferous forests. In the second spectral channel (the red part of the spectrum), forest burns are slightly lighter than the coniferous forests surrounding them. Burns are clearly distinguishable in the third spectral channel (near infrared part of the spectrum) and have an almost black tone, in contrast to forests with a gray image tone. The first two spectral channels, along with the third, must be used to separate forest burns from other natural objects, such as coniferous forests, light forests, peat bogs, clearings, and swamps. When synthesizing spectral channels as described above, forest burns have a dark lilac tone (reddish-purple R = 0.647, G = 0.153, B = 0.522), while coniferous forests are displayed in a darker lilac tone with a slight green tint (R = 0.451, G = 0.336, B = 0.464). Woodlands have a lighter shade than forest burns and differ from the latter in a perfectly monotonous texture. Cuttings, like light forests, have a light lilac tone of the image, but the correct borders. Plowed peat bogs are dark lilac, almost black and have regular borders. Deciphering signs of burns allow visual identification of burns in space images, but it is likely that small areas of the burned forest will be missed, and automatic determination of the exact geographical coordinates and areas of burns is possible only using digital image processing methods. 2.5 The Main Stages of the Methodology 1. The choice of fragments of satellite images of areas where there are supposedly burns from forest fires. 2. The selected fragments are imported into ERDAS IMAGINE 8.2, where the radiometric correction of the selected images is carried out, transforming them into a geographical projection and combining them with the M 1: 200000 or 1: 500000 map. 3. Recognition of forest burns by the ISODATA classification method (cluster analysis) without training. 40 classes are set in order to reduce the methodological classification error caused by “overlapping” classes in case of insufficient quantity. When using the 20 classes, fire burns combine or overlap with objects (water, swamp soils, peat bogs, light forests) closely lying in the spectral field of signs, which significantly distorts the real picture. 4. Class identification by analyzing their spectral curves. So, the spectral curve corresponding to the class of water decreases with increasing wavelength from the visible (0.5–0.6 μm) to the near infrared (IR) range (0.8–1.1 μm), the spectral curves of

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5.

6.

7.

8.

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plant objects fall from green (0.5–0.6 μ) to the red (0.6–0.7 μ) section of the spectrum and increase sharply towards the near IR range (0.8–1.1 μ), the spectral curves of soils exposed to vegetation, as well as clouds, rocks, asphalt pavements etc. grow monotonously with increasing wavelength and differ from each other in different reflection intensities. The spectral curve of forest burns is similar to the spectral curves of dark coniferous forests and wet marsh vegetation, i.e. falls from the first to the second spectral channel and increases slightly to the third channel. For a more visual representation of the spectral distribution of objects, you can use the data representation in red (X axis) and near IR channel (Y axis), where it is clear that burners and locations of cinder have the lowest brightness values both on the X axis and the Y axis, for excluding water bodies. Creating a “mask” from classes corresponding to burns and locations of cinder. In the raster editor, the transparency of all classes is turned on, except for classes that correspond to cinder and locations of cinder. A layer containing only classes of burners and locations of cinder is superimposed on a previously prepared raster topographic map. This determines the geographical location of the burned areas. After identification, the class corresponding to the forest burning is assigned a red color, the class corresponding to the location of cinder is assigned a yellow color. Determination of the area of the burned forest. To calculate the area of the burned forest, it is necessary to transfer the image from the geographical projection to the map projection, for example, to the Transverse Mercator projection with a description of the spheroid according to the Krasovsky model and Pulkovo data. Then add the “area” function in the Raster editor and get the area of forest burns in hectares. Next, a table is compiled containing the geographic coordinates of each burnout. Characterization of a burned forest. The characteristics of a burned forest are obtained by forest taxation or simply topographic maps. On the map, a symbolic sign indicates: type of forest (coniferous, deciduous, mixed), forest species (pine, maple, spruce, etc.), the height and thickness of trees in meters, the distance between trees in meters. Determination of the volume of burned wood. The resulting mask is superimposed on a topographic map in M 1: 200000 or a forest map in 1: 500000 and tree species affected by the fire are determined. Then, using the calculated burning area and the characteristics of the forest cover according to the topographic map on the site of this burning before the fire (tree density, average tree trunk thickness, average tree height), the volume of burned wood was determined. Calculation Model: π d 2h , s= V1 = 12



100 l

2 , VΓ a = V1 s, V = V = V1 sSg , U = CV

(1)

V1 [ha] - volume of wood of one tree (tree model - cone), r [m] - radius, d - diameter (thickness) [m], h [m] - tree height; s is the number of trees per 1 ha, l [m] is the distance between trees, Vga [m3 ] is the volume of wood per 1 ha, V [m3 ] is the volume of wood over the entire burning area, Sg [ha] is the burning area according to satellite data, U [p] - damage in rubles, C - cost of 1 m3 of wood.

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2.6 The Output of the Methodology is the Assessment of the Loss of Wood Loss from Fires, Expressed in Rubles The accuracy of the damage assessment depends on the accuracy of the recognition of burns on space images, which affects the value of the area of the burned forest. In a fire, not only the forest burns, but also the adjacent swamps, on which there is light forest and grass cover. Space images show both forest and swamp burns in a characteristic tone, therefore, after recognizing and applying a “mask” to the map, it is necessary to select areas that are not related to forest vegetation and calculate areas that do not correspond to the forest. 2.7 Selection of Information Products in the Field of Forest Fire Monitoring As a “material” for monitoring, we consider MODIS products. Due to the wide range of applications for Modis images, >240 different information products have been released so far. Product identifiers correspond to their classification system. So, the Terra satellite system corresponds to the products * MOD *, Aqua - * MYD *. So, the Terra satellite system corresponds to the products * MOD *, Aqua - * MYD *. The products of the level differ according to the processing level: Level0 (zero level_ - primary data in *.pds format; Level1A (first level) - the result of unpacking data in *.hdf format; Level1B (second level) - reduction of data to different spatial resolutions (MOD021KM, 1-36 - to 1 km; MOD02HKM, 1-7 - to 500 m; MOD02QKM, 1-2 - to 250 m; MOD02OBC - on-board calibration data); Level1C (third level) - physical quantities on a regular grid W, for which a specific nomenclature is used. Products with ID = * hHHvVV * (tiles, images I) are formed as arrays of images on a regular grid W. Images are stored in a sinusoidal projection with the coordinates of the points (x, y), where x = R ∗ λ ∗ cos(ϕ), y = R ∗ ϕ

(2)

Figure 2 shows the grid W in the coordinates (λ, ϕ), the partition w1 (a) and (λ’, ϕ’), where λ’ = x, ϕ’ = y for R = 1, the partition w2 (b). The grid is divided into 36 cells horizontally (HH, h = 0…35) and 18 cells vertically (VV, v = 0…17). The relations are:     ymax − y x − xmin ,v = (3) h= T T     (ymax − y)mod T (x − xmin )mod T i= − 0.5 + 1, v = − 0.5 + 1 (4) T T R = 6371007.181 m - radius of the Earth’s sphere; T = 1111950 m - width and height of tiles; xmin = −20015109 m - the western boundary of the projection; ymax = 10007555 m, northern boundary of the projection; w = T/1200 = 926.62543305 m - the actual cell size of the Modis sinusoidal grid “1 km”; i and j are the row and column numbers of matrix I of size d = [d1 d2 d3], where d1 is the number of channels, i = 1…d2, d2 = 1200, j = 1…d3, d3 = 1200.

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h=17 h=18

v=0 *h22v02*

h=16

h=19

h=0

h=35

v=16 v=17

h

v

a

b Fig. 2. Diagram of the layout of products of the form * hHHvVV *: a) w1; b) w2.

Figure 3 shows an overlay of a map of the land and Russia on w1–w2 markups. For each product, methods and algorithms for processing primary data are regularly improved, i.e. Various product versions called collections are created. In particular, the Collections: 1 - data created in the first year of operation of the MODIS camera (2000– 2001); 2 - data obtained on the basis of Collection 1, as well as captured during the period November 2000–December 2002; 3 - processed data from Collections 1 and 3, as well as modern data, etc. Table 1 - Modis information products for the task of monitoring forest fires. Data is stored in *.hdf format - a universal hierarchical format for storing scientific data. Image processing, including reading *.hdf data, is carried out in various software tools, such as in Matlab (libraries mapping toolbox, image processing toolbox, etc.) or Python (libraries pymodis, pillow, etc.). In particular, in Matlab, metadata is read by the

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Fig. 3. Overlay of a world map (contours of states) and a map of the Russian Federation (contours of subjects) on the breakdown: a) w1; b) w2.

function S = hdfinfo (str), where S is the structure, and images by the function I = hdfread (str, sds_name), where I is the image, str = ‘path \ id.hdf’ is the path and file name, sds_name - layers, each of which corresponds to a mono-or multi-channel image I. The program developed as part of the methodology works for the following Modis products (Fig. 4): I) M [O, Y] D021KM - hyperspectral image with a spatial resolution of 1 km (products of the first processing level); II) M [O, Y] D14 - data on fires obtained from the corresponding images M [O, Y] D021KM (products of the second processing level); III) M [O, Y] D14A [1, 2] - 8-day fire data composites, issued every 8 days based on M [O, Y] D14 (products of the third level of processing); IV) M [O, Y] D13A [1–3] - 16-day composites of data on vegetation indices (products of the third level of processing); V) MCD12C1 - types of underlying surface.

570

M. Shahramanyan et al. Table 1. MODIS products applicable in forest fire monitoring.

Monitoring objects

Terra

Aqua

Calibrated satellite images MOD021KM, MOD02HKM, MOD02QKM

MYD021KM, MYD02HKM, MYD02QKM

Forest fires, burns, burners MOD14, MOD14A1, MOD14A2, MOD14CRS, MOD14CMQ, MOD14C8Q

MYD14A1, MYD14A2, MYD14CRS, MYD14CMQ, MYD14C8Q

Earth temperature

MOD11_L2, MOD11A1, MOD11A2, MOD11B1, MOD11B2, MOD11B3, MOD11C1, MOD11C2, MOD11C3, MOD21, MOD21A1D, MOD21A1N, MOD21A2

MYD11_L2, MYD11A1, MYD11A2, MYD11B1, MYD11B2, MYD11B3, MYD11C1, MYD11C2, MYD11C3, MYD21, MYD21A1D, MYD21A1N, MYD21A2

Vegetation indices

MOD13A1, MOD13A2, MOD13A3, MOD13C1, MOD13C2, MOD13Q1, MOD44B (MOD15*, MOD16*, MOD17*, MOD43*, MOD44*)

MYD13A1, MYD13A2, MYD13A3, MYD13C1, MYD13C2, MYD13Q1 (MYD15*, MYD16*, MYD17*, MYD44*)

Cloudy, smoky

MOD35_L2, MOD06_L2, MODATML2,

MYD35_L2, MYD06_L2, CLDMSK_L2_VIIRS_SNPP, CLDPROP_D3_VIIRS_SNPP, CLDPROP_L2_MODIS_Aqua, CLDPROP_L2_VIIRS_SNPP, CLDPROP_M3_VIIRS_SNPP

Fig. 4. Correspondence in the method of input images Modis of different types (I–V) and processing schemes.

3 Forest Tax Parameters in the Monitoring of Forest Fires The following interconnected groups of forest taxation parameters were used in the methodology [4–6]: 1) Rate of payment per unit volume of wood of forest stands;

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2) Varieties of wood and classification of forest vegetation; 3) Forest tax areas and state entities; 4) The geographical coordinates of regions and entities and their coordinates on a regular grid. The first group includes: Nu - number of forest tax area, Np - number of forest plantation species, t - forest tax category (takes natural values from 1 to 7), L [km] - logging distance, Nq and q - wood quality, C [p/m3 ] - fee rate, rubles for 1 dense m3 of wood. The parameters are regulated in [4] and other documents, the pay rate is determined depending on u, p, t and q, and the values of r and C depend on t. The second group includes: Np and p - number and species of forest stands, k belonging to deciduous (k = 1) or coniferous (k = 2), d [m] - diameter of the tree trunk at the base, D [m] - diameter crowns, l [m] - the distance between the trees, H [m] the height of the tree. There are minimum (Lmin , dmin , Dmin , lmin , Hmin ), average (Lm , dm , Dm , lm , Hm ) and maximum (Lmax , dmax , Dmax , lmax , Hmax ) values depending on p and other forest tax parameters. For example, r and l depend on the intrinsic (on the germination of s, life expectancy τ [years], etc.) and improper (ecological state, climatic conditions, etc.) rock parameters. The third group includes: Nu and u - number and forest tax area, Nu ‘and u’ - forestry, NU and U - subject of the Russian Federation, NU ‘and U’ - municipal region, NuU relations between regions u and U. We consider, in total ~340 forest tax areas and ~85 subjects of the Russian Federation. The fourth group includes: Xu and XU - vectors of the geographical coordinates of forest tax regions and constituent entities of the Russian Federation (longitudes λ and latitudes ϕ of turning points of polygons of regions); Xmin u and Xmax u are the minimum and maximum coordinates of the regions u, Xmin U and Xmax U are the regions of U; NW are the numbers of cells (rows h and columns v) of the grid W to which the coordinate vectors XW correspond, in also Xmin W, Xmax W; NWu and NWU are the relationships between cell numbers and region numbers u and U. The main species of forest plantations p (Np): birch (1), beech (2), hornbeam (3), oak (4), spruce (5), elm (6), cedar (7), maple (8), linden (9), larch (10), white alder (11), black alder (12), aspen (13), fir (14), pine (15), poplar (16), ash (17). Minor breeds: horse chestnut, eucalyptus, Himalayan cedar, quince, bird cherry, elderberry, etc. Wood quality q (Nq): large commercial wood without bark (1), medium commercial wood without bark (2), small commercial wood without bark (3), wood in bark (4). Table 2 shows the ratio of the first group of parameters using the example of the Kaliningrad forest-tax area (Nu = 1), larch (Np = 10). Table 3 shows the ratio of the second group of parameters given for the main tree species. Different dominant tree species (Np) correspond to different types of forests (product MCD12C1): 1) Evergreen coniferous forests (NK = 1) - Np = 5, 7, 10, 14, 15; ξ = I; 2) Evergreen deciduous forests (NK = 2) - in countries with tropical and subtropical climates; 3) Small-leaved forests (NK = 3) - Np = 1, 13, 11, 12; ξ = II-III; 4) Broadleaved forests (NK = 4) - Np = 2, 3, 4, 6, 8, 9, 17; ξ = I; 5) Mixed forests (NK = 5) Np = 1, 5, 13, 15; ξ = I, II; 6) Forest-steppe (NK = 8) - Np = 4, 9, 17; ξ = I, II. Classes of height ξ: I - H ≥ 20 m, D ≥ 10 m; II - 10 m ≤ H≤20 m, 5 m ≤ D ≤10 m; III - H ≤ 10 m, D ≤ 5 m.

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M. Shahramanyan et al. Table 2. Rates of payment per unit volume of wood forest stands. t Lmin , m

Lmax , m

C, p/1 m3 Nq = 1

Nq = 2

Nq = 3 Nq = 4

1 0

10

204.3000 145.2600 72.5400 6.8400

2 10

25

185.7600 131.7600 65.8800 4.5000

3 25

40

157.5000 112.5000 56.3400 4.5000

4 40

60

120.9600

86.0400 43.9200 3.4200

5 60

80

92.3400

65.8800 33.1200 3.4200

6 80

100

74.3400

53.4600 26.4600 1.6200

7 100

–

56.3400

39.9600 19.6200 1.6200

Table 3. Parameters of tree species. Np H, m

d, m

D, m

l, m

7–12

τ, years

k

1

20–30 1–1.5

6–30

150–300

1

2

25–30 1.2–1.7 10–15 6–30

400–500

1

3

7–12

100–200

1

4

30–40 1–1.5

15–25 6–30

500–1000 1

5

30–35 1–1.8

6–10

6–30

300–400

2

6

25–30 1.3–1.8 15–25 6–30

300–400

1

7

30–40 1.4–2

6–30

400–500

2

8

20–30 0.8–1.2 10–14 6–30

200–300

1

9

20–30 0.8–1.2 12–15 6–30

300–400

1

400–900

2

50–100

1

12 20–30 0.3–0.9 10–14 6–30

100–150

1

13 25–35 0.5–1

10–12 6–30

80–100

1

14 20–40 1–1.5

7–10

6–30

150–200

2

15 20–40 0.6–1.2 8–15

6–30

300–500

2

16 40–45 1–1.2

3–5

10–30 80–100

17 25–35 1–1.2

20–30 10–30 150–200

0.5–0.6 5–10

10 30–40 0.8–1

4–5

6–30

10–15 6–30

11 15–20 0.5–0.8 7–10

6–30

1 1

The ratio of the third group of parameters on the example of forest tax areas: u - Zheleznodorozhny, Nu = 5; U - Komi Republic, NU = 7; B (A) - Syktyvkar (Syktyvkar), Kortkerossky (Kortkerossky, Lokchimsky, Storozhevsky (except Nivshersky and Syvyudarsky forestries), Koygorodsky (Kazhimsky, Koygorodsky), Priluzsky (Letsky and Priluzsky) Syktyktyktyvktyvtyktyks, Syktty (Sysolsky), Udor (Yertomsky,

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Mezhdurechensky, Udor), Ust-Vymsky (Aikinsky, Chernamsky) A - forestry enterprises (forestry, forest parks), B - municipal areas of the subject.

4 Economic Damage Assessment by the Example of Forest Fires in 2019 in the Krasnoyarsk Territory The observation area is the section Q = h22v02, covering parts of the constituent entities of the Russian Federation Krasnoyarsk Territory (NU = 8), the Republic of Sakha (NU = 9), as well as small parts of Tomsk (NU = 10), Irkutsk Region (NU = 11), Khanty-Mansiysk Autonomous Okrug (NU = 12) (Fig. 5).

Fig. 5. The observation area on the w2 partition.

As material, we take images of the form (III) and (IV) (see Fig. 4). Assessment of economic damage U [mln. p.] in a program developed on the basis of the methodology, with various settings for forest tax parameters: Table 5 - forest tax regions included in section Q; Table 6 - forest tax discharge for the First East Siberian forest tax region; Table 7 - the quality of wood for the area and VII forest tax category; Table 8 - the dominant tree species for this region and category with the quality of wood “wood in the bark” (Table 4). Table 4. Experiment Material. Period of observation

Products Modis (ID)

t1 – June 26, 2019

MOD13A1.A2019177.h22v02.006.2019194004523.hdf MOD14A1.A2019177.h22v02.006.2019186004419.hdf

t2 – July 4, 2019

MOD13A2.A2019185.h22v02.006.2019210003902.hdf MOD14A2.A2019185.h22v02.006.2019194004015.hdf

t3 – July 12, 2019

MOD13A1.A2019193.h22v02.006.2019210003902.hdf MOD14A1.A2019193.h22v02.006.2019202001927.hdf

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In all cases, the adjustment of geometric parameters giving a minimum amount of damage (second group of forest tax parameters): H = 10 m, d = 5 dm, l = 30 m (geometric parameters for a rare small-leaved forest, homogeneous in composition). Other non-configurable parameters are averaged. Table 5. Variation of the forest tax area (subject of the Russian Federation). u

t1, million roubles t2, million roubles t3, million roubles

First East Siberian region

4.1

20.0

10.2

The second East Siberian region 3.6

17.4

8.9

Third East Siberian region

3.0

14.6

7.5

Fourth East Siberian region

4.8

23.3

11.9

Fifth East Siberian region

5.4

26.2

18.0

Sixth East Siberian region

3.7

13.4

9.2

Table 6. Variation of the forest tax discharge. t

t1, million roubles t2, million roubles t3, million roubles

Rank I

6.8

Rank II

5.6

27.2

13.9

Rank III

5.2

25.2

12.9

Rank IV

4.0

19.4

9.9

Rank V

3.1

15.0

7.7

Rank VI

2.6

11.9

6.1

Rank VII 1.9

8.9

4.6

32.7

16.8

Table 7. Variation in wood quality. q

t1, million roubles t2, million roubles t3, million roubles

Large commercial wood without 3.5 bark

16.9

8.6

Medium timber without bark

2.5

12.2

6.2

Small business wood without bark

1.3

6.3

3.2

Firewood in the bark

0.1

0.3

0.2

Remote Sensing of the Earth from Space

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Table 8. Variation of tree species. p

t1, million roubles t2, million roubles t3, million roubles

Cedar

0.1

0.3

0.2

Spruce 0.2

0.7

0.4

Fir

0.9

4.2

2.1

Larch

3.0

14.2

7.3

5 Results The methodology for express assessment of economic damage from the loss of wood caused by forest fires, and its main stages are described. Modis information products and the main forest tax parameters in the monitoring of forest fires used in the methodology are presented. As a result of the research, estimates of economic damage were obtained for various images describing different emergencies: the European part of Russia, July– August 2010; Transbaikalia, Irkutsk Region, Far East, April 2012; Southern Siberia, Transbaikalia, Urals, April 2015; Krasnoyarsk Territory, Irkutsk Region, Buryatia, Transbaikalia, Yakutia, July–September 2019. Damage assessments are presented on the example of forest fires in 2019 in the Krasnoyarsk Territory under various conditions: for different forest-taxon rabons, with varying forest-tax discharge, the level of wood quality and the dominant tree species.

6 Conclusion Space monitoring allows you to register emergency zones (floods, forest fires, drought, etc.), evaluate their consequences and have a relatively low cost compared to aerial photography. The methodology for the express assessment of the economic damage of vegetation losses from natural disasters according to satellite imagery has been developed. To obtain an express assessment of damage from vegetation loss (forestry and agricultural) as a result of an emergency, it is necessary: to identify the centers of emergency on satellite images; determine the location of the foci (coordinate reference); determine the area of the affected areas at a given point in time; estimate the damage in physical terms.

References 1. Shahramanyan, M.A., Doroshenko, S.G., Epikhin, A.V., Reznikov, V.M., Shcherbenko, E.V.: Methods for thematic processing of satellite images during monitoring of natural emergencies. Civ. Secur. Technolo. Bull. FC “VNIIGOCHS” 4(6), 8–39 (2004) 2. Shaptala, V.G., Radotsky, V.Y., Shaptala, V.V.: Basics of emergency modeling: textbook; under the general. Shaptala V.G. (ed.) BSTU, Belgorod (2010)

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3. Richter, A.A., Shahramanyan, M.A.: Basics of Emergency Modeling: A Monograph. Lambert Academic Publishing, Moscow (2018) 4. Galeev, A.A., Bartalev, S.A., Ershov, D.V., Krasheninnikova, Y.S., Lupyan, E.A., Mazurov, A.A.: Construction of an adaptive fire detection algorithm. Curr. Probl. Remote Sens. Earth Space 5(1), 58–68 (2008) 5. Sevko, O.A.: Landscape taxation with the basics of park management: a course of lectures on the discipline of the same name for students of specialty 1-75 02 01 “Garden and park construction”. BSTU, Minsk (2009) 6. Nikiforchin, I.V.: Forest taxation: a workshop for the preparation of bachelors in the field of 250100 “Forestry”. SPbGLTU, SPb (2013)

Modeling of Cold-Formed Thin-Walled Steel Profile with the MBOR Fire Protection Marina Gravit(B)

, Marina Lavrinenko , Yurij Lazarev , Artem Rozov , and Anna Pavlenko

Peter the Great St. Petersburg Polytechnic University, 29 Politechnicheskaya St, St. Petersburg 195251, Russia [email protected]

Abstract. The article presents the results of the wide-scale fire tests of light thin-walled steel structures (LTWS) for a fire protection efficiency of a structural fire-protection. Cross sections of steel constructions are composite. They consist of cold-formed galvanized C-shaped profiles lined with the basalt roll MBOR material. Then there is a numerical investigation by the finite element method in the Elcut PC. As a result, temperature-time curves of steel constructions are obtained under the mode of a standard fire both in experimental tests and in numerical studies. The results show good convergence of the finite element method to the experimental data. The influence of a facing layer thickness of the basalt roll MBOR material on the fire resistance to the fire influence on LTWS is estimated. Some groups of a fire protection efficiency of a structural fire protection are determined. It was found that the fire resistance of LTWS increased from 45 to 75 min due to the facing with rolled fire-resistant mineral wool materials. Keywords: Cold-Formed Thin-Walled steel profile · CFS · Light Thin-Walled steel structures · LTWS · Thin-Walled sections · Fire resistance limit · Fire-Resistant efficiency · Fire resistance of steel structures · Galvanized profile · Fire test

1 Introduction Cold-formed thin-walled steel profile constructions are widely spread in low-height construction. These constructions are produced by tens of factories with an automatic production line. Light thin-walled steel constructions are perfect at technical and economic indicators. Extensive architectural features let to work precisely, flexibly and effectively in case of a dynamically changing market. Metal structures in residential and non-residential construction are considered to be one of the most advanced in the world. Generally, a framework of the building consists of Sigma-, C- and Z- profiles. They are made with a galvanized high-strength structural steel. A typical LTWS column is shown in the Fig. 1. A steel column is left unprotected or faced with flame retardants, while a cavity is either left empty or filled with insulation material like the fire-proof plate «EUROLit» (Fig. 2). A cold-formed steel is a light material with a high strength-to-weight © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 577–592, 2021. https://doi.org/10.1007/978-3-030-57453-6_55

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Fig. 1. A typical LTWS column.

ratio. A protective facing made it possible to increase the ability of steel to resist flame effects in fire conditions, despite the fact that it loses its structural strength quickly in a high-temperature environment [1].

1. Roll material MBOR; 2. Flame retardant compound «Plazas»; 3. Cold-formed galvanized LTWS profile; 4. Fire-proof plate «EURO-Lit» Fig. 2. Fire protection of structures of LSTC profiles.

There are various types of facing are available for columns, for example, gypsum board (GPB), mineral thermal insulation wool, concrete tile, ceramic material, plaster, brick and etc. [2, 3]. A fire resistance of thin-walled bars is very important question in the modern world. There are numerous studies of these structures but, despite the facts, this question is actual for nowadays. A fire protection material is a fireproof compound or material that have a fire-resistant efficiency and specially designed for a fire protection of various objects. A fire-resistant efficiency of a fire protection material for steel construction is characterized by the time (in minutes) from the beginning of the fire test to reaching the critical temperature of a standard sample of a steel construction with a fire-resistant cover.

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Specialized research centers have been established in all developed countries of the world. They are engaged in research of a fire resistance of building structures. Fire tests of individual structures and building fragments are carried out at specially equipped ranges. The researches of such authors as Vatin N.I., Garifullin M.R., Gravit M.V. [4–9], Naser M.Z. [10, 11], Chen W., Ye J. [12–15], Dias Y. [16] made a great contribution for solution of theoretical, technical and practical problems in calculations of a fire resistance of structures made of a cold-rolled galvanized profile. Dias Y. [17] made full-scale tests on the fire resistance of LTWS walls. They were made of a stiffened channel section web (SCS web) with using mathematical models based on the results of a fire tests. Also, LTWS walls were made of a new profile with a hole in the reinforced wall (SCS) and welded profile walls (HFS). As a result, it was found that the influence of the bar’s geometry on the fire resistance of LTWS walls is minimal. Meanwhile, Kesawan S. and Mahedran M. [18, 19] discovered that the fire resistance of HFC-profiled LTWS walls is better than ordinary LSTC-profiled LTWS walls. Excellent fire resistance results are demonstrated due to the geometric characteristics of the HFC profile. Cold-formed steel walls (CFS walls) with plasterboard facing are widely spread in modern buildings. There is a great importance of a fire resistance of such walls. Most of the published works are devoted to the study of characteristics of such walls. Chen W., Ye J., i Zhao Q. [20, 21] made an experimental study of nonbearing CFS walls under four different fire conditions in a laboratory. Ariyanayagam A.D. analyzed the disadvantages of plasterboard joints according to the fire resistance class of a single-layer and double-layer plasterboard facing [22]. Furthermore, experimental studies on a fire resistance of building structures based on LTWS are still to be conducted. An influence of mineral wool facing on a fire resistance of such structures is unknown. Possibly, LTWS column faced with basalt roll materials can have good fire-resistant characteristics due to the low thermal conductivity [23, 24]. Some researches of a fire-resistant effectiveness of basalt roll materials were conducted in the laboratory of JSC TIZOL (Russia), f.e.: 1. Experimental studies of the C-shaped profiles with the fire-resistant basalt roll MBOR material; 2. Modeling of a thermal impact at LTWS building with the fire-resistant material MBOR. The basis of a fire protection coating is the basalt fire protection roll MBOR material. This material is a staple canvas made of basalt super-thin fibers. It stitches by knitting and stitching method and covers with an aluminum foil on one side. The results of numerical studies of cold-formed galvanized steel profiles with a fire protection made of thermal insulation plates made of the basalt MBOR-F wool are described in this survey. The fire-retardant efficiency and behavior of LTWS-profiles were determined with linear finite element models developed in the Elcut PC and verified from fire tests.

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2 Methods 2.1 Methods According to ISO 834-1:1999 LTWS profile prototypes with a fire protection made of heat-insulation plates, which made of the basalt MBOR-F wool. Tests of such prototypes are carried out with normative documents under a four-sided thermal effect according to the standard temperature mode. This method allows to determine an actual efficiency of the fire protection compound criteria. Criteria are equal to the time from the beginning of the thermal effect to the limit stage of the prototype. The prototype gets the limit stage when the heating temperature of the structure cross section is critical. Stand equipment includes: – Testing furnace with fuel supply and combustion system. The furnace design is shown in the Fig. 6; – Devices for the prototype installation on the furnace; – Measuring and recording systems. The standard temperature mode is created in the testing furnace during the test process. The mode characterized by the equation: T - T0 = 345 log(8t + 1)

(1)

Where: t – time from the beginning of the test, min; T – temperature in the oven (corresponding to the time t), °C; T0 – temperature in the oven before heating (ambient temperature), °C; Building structures based on the cold-formed galvanized steel profiles with a fire protection have been investigated without static load. It has been made for determination of the steel thin-walled structures behavior and fire resistance improvement. The test object is a rod structure of a composite section. This structure made of two C-shaped profiles with bolted mounting. First prototype is 2AS 150 × 75 × 16,8 × 1,6 mm. Second prototype is 2AS 380 × 125 × 29,9 × 3,5 mm. Steel columns heating time depends on two factors: a metal thickness and a thickness of a fire protection. It works when all other conditions, like heating scheme and temperature mode, are equal. So, normal I-section columns with minimal metal thickness were selected for determination the warm-up time. Then thickness was increased according to the I-section assortment. Facing structure of the prototype is a single-layer covering made of the MBOR-F plates consisting of basalt fibers. Structure schemes for testing and main geometric characteristics of the profile are shown in the Fig. 3 and the Fig. 4. There were four prototypes with the length of 1700 ± 10 mm for the tests. The term of reduced metal thickness (tred ) is used for comparison of metal structures. It is defined

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Fig. 3. First prototype: a) with fire-resistant material MBOR-8F lining; b) with fire-resistant material MBOR-20F lining.

Fig. 4. Second prototype: a) with fire-resistant material MBOR-8F lining; b) with fire-resistant material MBOR-16F lining.

as the ratio of the cross-sectional area to its heated perimeter for each prototype test. It is demonstrated by the formula 2:  tred = S P (2) Where: S – cross-sectional area of the metal structure, mm2, P - heated part of the perimeter of the structure, mm. The reduced thickness of the metal structure is calculated by the formula (2). tred = 1.01 mm (for the first prototype). tred = 2.35 mm (for the second prototype). There are thermocouples with an electrode diameter of no more than 0.75 mm for measuring the temperature of prototypes. Thermocouples are placed in the middle section

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of the sample on the inner surfaces of the walls of the structure. The method of attachment is shown in the Fig. 5.

Fig. 5. Thermocouple installation place on the site.

Fig. 6. The furnace for the fire tests.

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The standard curve of the standard fire mode according to ISO 834 was programmed in the furnace. The prototypes are placed vertically in the furnace. Temperature of the furnace was regulated using the thermocouples. So, temperature changes of the open surface of each prototype is close to the values of the standard fire curve. These tests continued until the structures reached the critical temperature Tcr = 500 °C. The fire effect stops when the object of research reaches the limit stage (Figs. 7 and 8).

Fig. 7. First prototype: a) – before test; b) – in process; c) – after test.

Fig. 8. Second prototype: a) – before test; b) – in process; c) – after test.

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2.2 Finite Element Method Steel structure models both with and without fire protection were developed in the «ELCUT» PC and were tested according to the fire tests. The boundary conditions of the models consider correspond to the boundary conditions of the experimental program. The cross section of the first (a, c) and the second prototype (b, d) is symmetrical. The origin point place passes through the center of symmetry of the cross section, which is divided into a grid of the finite elements. The general view of the finite element model is shown in the Fig. 9.

(a) Test 1

(b) Test 2

(c) Test 3

(d) Test 4

Fig. 9. Finite element model’s grid of calculated cross sections.

The system is evenly heated by an external heat flow. All energy is used to increase the system’s temperature taking into account its heat capacity. Heating stops when an external borders temperature equalizes with an external environment temperature, which corresponds to the set temperature in the furnace.

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3 Results 3.1 The Results of the Experiment According to ISO 834-1:1999 The structural fire protection is not collapsed at the end of the fire test. The basalt roll material retains its thermal insulation properties and integrity throughout the experiment. The time of getting the limit stage of the prototype is the prototype test’s result. The dependence «time of fire impact – temperature of the structure» is defined for steel structures with different thickness of a metal and a fire-protection. This dependence is shown in the Fig. 10, 11, 12, 13.

Fig. 10. Test 1. First prototype MBOR-16F.

Fig. 11. Test 2. First prototype MBOR-20F.

Estimation of a fire protection efficiency. The results of the fire tests of getting critical temperature (500 °C) is shown in the Table 1.

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Fig. 12. Test 3. Second prototype MBOR-8F.

Fig. 13. Test 4. Second prototype MBOR-20F.

Table 1. The results of the fire tests. tred , mm

MBOR-F, mm

Tcr , °C

Time (min)

Fire-retardant efficiency group

1.01

16

500

32:12

6

37:08

6

37:33

6

47:02

5

20 2.35

8 16

500

The Figs. 10, 11, 12, 13 describe that time from the beginning of the fire test to reaching the critical temperature is 33 min for the prototype with 1.01 mm. reduced metal thickness and 16 mm. basalt MBOR-16F material thickness. This criterion corresponds to

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the 6th fire-retardant efficiency group. The same prototypes with 20 mm. basalt MBOR20F material thickness reached the same condition after 37 min. It also corresponds to the 6th fire-retardant efficiency group according to the Russian classification in GOST R 53295-2009 «Fire retardant compositions for steel constructions. General requirement. Method for determining the fire-retardant efficiency» (First group – more than 150 min; Second group – more than 120 min; Third group – more than 90 min; Fourth group – more than 60 min; Fifth group – more than 45 min; Sixth group – more than 30 min; Seventh group – more than 15 min). Prototypes with 2.35 mm. reduced metal thickness and 8 mm fire-resistant facing MBOR-8F plates reached the critical temperature after 39 min. This criterion corresponds to the 6th fire-retardant efficiency group. Same prototypes with 16 mm fire-resistant facing MBOR-16F plates reached the same condition after 49 min. It corresponds to the 5th fire-retardant efficiency group. 3.2 Modeling Results Modeling of the temperature distribution for the time corresponding to the cross-section heating close to the critical temperature is shown in the Fig. 14. This modelling is based on the results of the fire tests.

(a) Test 1

(b) Test 2

(c) Test 3

(d) Test 4

Fig. 14. Temperature gradient for the first and the second prototypes.

The fire-resistance construction’s estimation performs by comparison the results of the fire tests. These fire tests based on the determination of the time when the steel

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construction gets the critical temperature. The results of the tests are shown in the ELCUT PC. An Estimate temperature indicator received from the theoretical research. It compared with the results of the standard fire tests made by the company «Andrometa», Russia. The Q value is taken as the deviation of the Tpr parameter from the Tcr. It calculates in percent and it can be calculated by the formula (3):  (3) Q = ((Tpr - Tcr ) Tcr ) · 100% Where: Tcr – Critical temperature, °C; Tpr – Temperature after modeling, °C; Q – Deviation of the modeling results from the experiment, %. The values of the obtained temperatures and their correlation with the fire tests are presented in the Table 2. Table 2. Temperature correlation with the fire tests. tred , mm

MBOR-F

Tpr , °C

Tcr ,°C

Time (min)

1.01

16

603.2

500

32 37

25.2

500

37

−18.7

47

−11.5

2.35

20

626.6

8

423.3

16

450.5

Q, % 20.6

Fig. 15. Test 1. First prototype MBOR-16F.

The data presented in the Table 2 and in the Fig. 15, 16, 17, 18 show a significant difference between the modelling temperature and actual results of the fire tests. First

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prototype consists of two C-shaped profiles. Its modelling temperature is 603.2°C (for MBOR-16F) and 626°C (for MBOR-20F) that differ by 20% and 25% for each other. So, second prototype differs from experimental data by 18.7% (for MBOR-8F) and 11.5% (for MBOR-16F) respectively.

Fig. 16. Test 2. First prototype MBOR-20F.

Fig. 17. Test 3. Second prototype MBOR-8F.

The results of the calculations describe satisfactory convergence with the results of the fire tests. A significant divergence between calculated and experimental data may be due to the fact that integrity of structural fire protection joint zones was violated. It is about the first prototype with MBOR-16F and MBOR-20F facing. The numerical calculations of the first prototype differ less by 10% with the fire tests in case of warming up the prototypes to the critical temperature Tcr = 700 °C. And the second prototype differs by 25.3% and 14.3% respectively when MBOR-8F and MBOR-16F fire protection are used in the tests. It is shown in the Table 3.

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Fig. 18. Test 4. Second prototype MBOR-16F.

Table 3. Temperature correlation with the fire tests. tred , mm

MBOR-F

Tpr , °C

Tcr ,°C

Time (min)

1.01

16

752.0

700

48

7.4

20

747.2

50

6.7

8

522.7

50

−25.3

16

599.7

69

−14.3

2.35

700

Q, %

4 Discussion There are four tests of the light steel thin-walled structures with a structural fire protection in this statement. Experimental researches of the limits of fire resistance of LSTC profile constructions with the roll basalt MBOR fire-protection material are analyzed. There are values of the fire protection efficiency for C-shaped steel rods with using of the thermal insolated basalt wool’s MBOR-F plate (8, 16, 20 mm thickness) are calculated in this statement. It is determined that the fire-retardant efficiency of light steel thin-walled constructions was increased from two to four times after the fire tests. An estimation of the possibility of using theoretical methods for calculation of the fire resistance of structures is very important question. The modeling of a fire resistance of LTWS building is completed in the ELCUT program. This modeling based on experimental data. So, the reliability of the calculation model has been confirmed. Nevertheless, further studies of the behavior of light steel thin-walled structures in a high-temperature environment are considered to be appropriate. Acknowledgments. The authors express their gratitude to the management of «TIZOL» company for providing fire experiments and to the specialists of «Andrometa» LTD company for providing technical and informational support.

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References 1. Chen, W.: Improved fire resistant performance of load bearing cold-formed steel interior and exterior wall systems. Thin-Walled Struct. 72, 145–157 (2013) 2. Terekh, M., Tretyakova, D.: Primary energy consumption for insulating. In: E3S Web of Conferences, vol. 157, p. 8 (2020) 3. Zemitis, J., Terekh, M.: Optimization of the level of thermal insulation of enclosing structures of civil buildings. In: MATEC Web of Conferences, vol. 245 (2018) 4. Gravit, M.V.: Software packages for calculation of fire resistance of building construction, including fire protection. In: IOP Conference Series: Materials Science and Engineering, vol. 456, no. 1 (2018) 5. Gravit, M., Dmitriev, I., Lazarev, Y.: Validation of the temperature gradient simulation in steel structures in SOFiSTiK. In: Advances in Intelligent Systems and Computing, vol. 983, pp. 929–938 (2019) 6. Gravit, M.V., Nedryshkin, O.V.: Full-scale tests for the simulation of fire hazards in the building with an atrium. In: Advances and Trends in Engineering Sciences and Technologies IIIProceedings of the 3rd International Conference on Engineering Sciences and Technologies, ESaT 2018, pp. 375–380 (2019) 7. Shukhardin, A.: Fire simulation of light gauge steel frame wall system with foam concrete filling. In: Advances in Intelligent Systems and Computing, vol. 982, pp. 836–844 (2020) 8. Vatin, N.: Simulation of cold-formed steel beams in global and distortional buckling. Appl. Mech. Mater. 633, 1037–1041 (2014) 9. Garifullin, M.: Buckling analysis of cold-formed c-shaped columns with new type of perforation. In: Advances and Trends in Engineering Sciences and Technologies - Proceedings of the International Conference on Engineering Sciences and Technologies, ESaT 2015, pp. 63–68 (2016) 10. Degtyareva, N.: Combined bending and shear behaviour of slotted perforated steel channels: Numerical studies. J. Constr. Steel Res 161, 369–384 (2019) 11. Naser, M.Z., Degtyareva, N.V.: Temperature-induced instability in cold-formed steel beams with slotted webs subject to shear. Thin-Walled Struct. 136, 333–352 (2019) 12. Chen, W., Ye, J., Zhao, Q.: Thermal performance of non-load-bearing cold-formed steel walls under different design fire conditions. Thin-Walled Struct. 143, 106242 (2019) 13. Chen, W.: Thermal behavior of external-insulated cold-formed steel non-load-bearing walls exposed to different fire conditions. Structures 25, 631–645 (2020) 14. Chen, W.: High-temperature steady-state experiments on G550 cold-formed steel during heating and cooling stages. Thin-Walled Struct 151, 106760 (2020) 15. Chen, W.: Full-scale experiments of gypsum-sheathed cavity-insulated cold-formed steel walls under different fire conditions. J. Constr. Steel Res. 164, 105809 (2020) 16. Dias, Y., Keerthan, P., Mahendran, M.: Fire performance of steel and plasterboard sheathed non-load bearing LSF walls. Fire Saf. J. 103, 1–18 (2019) 17. Dias, Y., Keerthan, P., Mahendran, M.: Predicting the fire performance of LSF walls made of web stiffened channel sections. Eng. Struct. 168, 320–332 (2018) 18. Kesawan, S., Mahendran, M.: Post-fire mechanical properties of cold-formed steel hollow sections. Constr. Build. Mater. 161, 26–36 (2018) 19. Kesawan, S., Mahendran, M.: Fire performance of lsf walls made of hollow flange channel studs. J. Struct. Fire Eng. 8(2), 149–180 (2017) 20. Chen, W., Ye, J., Li, X.: Thermal behavior of gypsum-sheathed cold-formed steel composite assemblies under fire conditions. J. Constr. Steel Res. 149, 165–179 (2018) 21. Chen, W., Ye, J., Li, X.: Fire experiments of cold-formed steel non-load-bearing composite assemblies lined with different boards. J. Constr. Steel Res. 158, 290–305 (2019)

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22. Ariyanayagam, A.D., Kesawan, S., Mahendran, M.: Detrimental effects of plasterboard joints on the fire resistance of light gauge steel frame walls. Thin-Walled Struct. 107, 597–611 (2016) 23. Musorina, T., Gamayunova, O., Petrichenko, M.: Thermal regime of enclosing structures in high-rise buildings. Vestnik MGSU 13, 935–943 (2018) 24. Musorina, T.A., Gamayunova, O.S., Petrichenko, M.R., Soloveva, E.: Boundary layer of the wall temperature field. In: Advances in Intelligent Systems and Computing, vol. 1116, pp. 429–437 (2020)

Determining the Coefficient of Mineral Wool Vapor Permeability in Vertical Position Kirill Zubarev1,2(B)

and Vladimir Gagarin1,2

1 Moscow State University of Civil Engineering, 26, Yaroslavskoye Shosse, Moscow

129337, Russia [email protected] 2 Research Institute of Building Physics of Russian Academy of Architecture and Construction Science, Moscow 127238, Russia

Abstract. Construction industry uses well-known wet cup method for determination of the coefficients of vapor permeability for different construction materials. Moreover, this experimental researches are used for vertical enclosing structures. As a result, wet cup method is used for vertical enclosing structures, whereas the experimental study is carried out for horizontal samples. We decided to compare the coefficients of vapor permeability for two types of building material positions: horizontal and vertical. For that, we constructed a new experimental device with vertical position of test sample, which has L-type section capacity and relative air humidity sensors. We carried out eight experiments with new device and the same number of experiments by wet cup method to make a comparison. Differences between the coefficients of vapor permeability of mineral wool in horizontal and vertical positions were not found. It proves the possibility that engineers can use the results of determining the coefficients of vapor permeability from classical wet cup method and apply them to vertical enclosing structures without additional refinement coefficients. Keywords: Moisture regime · Vapor permeability · Experimental study

1 Introduction Construction industry has a lot of problems with moisture transfer inside enclosing structures. This vital problem is been solving in some different directions. Firstly, new mathematical models of the moisture transfer are been developed by scientists from all over the world [1–13]. Secondly, new approaches for experimental determination moisture diffusion coefficients are being made [14–21]. Solution of moisture transfer problem improves the level of buildings heat protection and energy efficiency [22–26]. Many countries use classical well-known wet cup method, which can be described like an experiment with a cup of water. A sample of a test material is located on the top of the cup and space between a test sample and cup is filled with sealing compound, so water vapour flow can move only throw materials and be perpendicular to the surface. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 593–600, 2021. https://doi.org/10.1007/978-3-030-57453-6_56

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Scheme of the wet cup method in case of horizontal test sample position is presented (Fig. 1). A cup with the test sample of mineral wool is presented (Fig. 2).

1 – test sample, 2 – holding device, 3 – sealing compound, 4 – water, 5 – device case

Fig. 1. Scheme of the wet cup method in case of horizontal test sample position [28].

Fig. 2. A cup with the test sample of mineral wool.

The parameters of chamber, which includes the experimental device, are 23 ± 0.5 °C – the temperature of air around cup and 50 ± 3% – the relative humidity of air around cup. Size of a sample can be not less than 0.1 m (length) × 0.1 m (width) × 0.1 m (thickness) and not bigger than 0.1 m (length) × 0.1 m (width) × 0.3 m (thickness). For calculating permeability coefficients of a building material, following formulas are used. Vapor permeability resistance is determined by expression: wet cup

R=

d ein − eext − air wet cup . g μair

(1)

Determining the Coefficient of Mineral Wool Vapor Permeability

595

where ein – water vapor partial pressure inside the device, Pa; eext – water vapor partial pressure outside the device, Pa; g – moisture flow through the sample registered by scales, wet cup – air gap thickness between the water surface and the test sample, m; kg/s·m2 ; dair wet cup – vapor permeability of the air gap between the water surface and the test sample, μair kg/m· s·Pa. Vapor permeability of the air gap between the water surface and the test sample is obtained by the special graphic [28]. Water vapor partial pressure outside the device is determined by relation: eext = ϕext · Et .

(2)

where Et – saturated water vapor pressure under experimental temperature, Pa; ϕext – relative air humidity outside the device. Water vapor partial pressure outside the device can be obtained by formula: ein = ϕin · Et .

(3)

where ϕin – relative air humidity inside the device. Material vapor permeability coefficient is defined by relation: μ=

δ . R

(4)

Saturated water vapor pressure under experimental temperature can be written by analytical expression [8, 9]: 5330

Et = 1.84 · 1011 · e− 273+t .

(5)

where t – air temperature, °C. Also saturated water vapor pressure under experimental temperature can be found by the special table (Table 1) [28]. Table 1. Dependence saturated water vapor pressure on temperature of air. Temperature, °C

Saturated water vapor pressure Et , Pa

Temperature, °C

Saturated water vapor pressure Et , Pa

Temperature, °C

Saturated water vapor pressure Et , Pa

22.0

2644

23.0

2809

24.0

2984

22.1

2660

23.1

2826

24.1

3001

22.2

2676

23.2

2842

24.2

3020

22.3

2691

23.3

2860

24.3

3038

22.4

2709

23.4

2877

24.4

3056

22.5

2725

23.5

2894

24.5

3074

22.6

2742

23.6

2913

24.6

3093

22.7

2758

23.7

2930

24.7

3112

22.8

2776

23.8

2948

24.8

3130

22.9

2792

23.9

2965

24.9

3149

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K. Zubarev and V. Gagarin

2 Problem Different approaches for measuring vapor permeability coefficient exist [28]. However, more often we meet with laboratory devices, which have horizontal position of the test sample. As a result, wet cup method is used for vertical enclosing structures, whereas the experimental study is carried out for horizontal samples. The purpose of current work is comparison of the coefficients of vapor permeability for two types of building materials positions: horizontal and vertical.

3 Materials and Methods We developed a new type of an experimental equipment with vertical position of the test sample, which has L-type section capacity and relative air humidity sensors. A test sample of a construction material is positioned vertically and sealed in the window (Fig. 3, Fig. 4).

1– electronic scales, 2– water, 3– device case, 4– relative air humidity sensors, 5– test sample, 6– sealing compound,А – link between electronic scales and computer

Fig. 3. Scheme of vapour permeability coefficient measuring device in case of vertical test sample position [29].

This device allows to obtain the vapour permeability of a construction material which is positioned in vertical state. Physical principles of the device work were described in the previous article [29]. We can use formula (6) without any changes for calculation the vapor permeability coefficient of construction materials, but vapor permeability resistance have to be obtained by following relation: R=

dair ein − eext − . g μair

(6)

Determining the Coefficient of Mineral Wool Vapor Permeability

597

Fig. 4. Device for vapor permeability coefficient measurement in case of vertical test sample position.

where dair – air gap thickness between relative air humidity sensors and the test sample, m; μair – vapor permeability of the air gap between relative air humidity sensors and the test sample, kg/(m·s·Pa). As the distance between relative air humidity sensors and the sample dair is low, the expression (6) can be written as: R=

ein − eext . g

(7)

Relative air humidity inside the device is defined as the average relative air humidity along the sample height, because sensors distributed along the sample height, and can be obtained by formula: 1 ϕin = · h

h f (x)dx.

(8)

0

where h – sample height, m. f(x) – sensor reading dependence function on height, m. Taking Eqs. (2)–(4), (7) and (8) into account, we can calculate the exact value of permeability for the new device: δ·g

μ= Et · ( 1h

·

h

.

(9)

f (x)dx − ϕext )

0

4 Results and Discussion We carried out eight experiments by classical wet cup method and eight experiment by the new device for a mineral wool insulation. Results of the experiment are summed up in a table (Table 2).

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Numbers of experiments

Permeability coefficients according wet cup method μ, kg/(m·s·Pa)

Permeability coefficients according experiments by new device μ, kg/(m·s·Pa)

1

8.61·10−11

8.50·10−11

2

8.64·10−11

8.50·10−11

3

8.56·10−11

8.53·10−11

4

8.58·10−11

8.58·10−11

5

8.72·10−11

8.61·10−11

6

8.69·10−11

8.64·10−11

7

8.64·10−11

8.53·10−11

8

8.67·10−11

8.56·10−11

Average

8.64·10−11

8.56·10−11

We used statistic methods to obtain statistical differences in experimental results. Firstly, we did Shapiro Wilka test which showed us that data of permeability coefficients of classical wet cup method and new device experiment had normal type of distribution. It gave us an opportunity to use Student Parametric Method, which proved that there is no difference between permeability coefficients in horizontal and vertical positions of construction materials sample of mineral wool insulation. Thus, vapor permeability coefficient obtained by wet cup method has been used for vertical enclosing structures without additional refinement coefficients.

5 Conclusion As a result, we gave the evidence that there is no differences between permeability coefficients of a mineral wool in horizontal and vertical positions. Moreover, other scientists Kupriyanov V.N. and Petrov A.S. had discovered that the mineral wool has one of the biggest permeability coefficients from all construction materials [28]. Therefore, as we have not found differences of mineral wool coefficients, all building materials which have less value of permeability do not have differences of permeability between horizontal and vertical positions too. It proves the possibility that engineers can use the results of determining the coefficients of vapor permeability from classical wet cup method and apply them to vertical enclosing structures without additional refinement coefficients.

References 1. Bai, H., Zhu, J., Chen, X., Chu, J., Cui, Y., Yan, Y.: Steady-state performance evaluation and energy assessment of a complete membrane-based liquid desiccant dehumidification system. Appl. Energy 258, 114082 (2020)

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2. Zhang, N., Chen, X., Su, Y., Zheng, H., Ramadan, O., Zhang, X., Chen, H., Riffat, S.: Numerical investigations and performance comparisons of a novel cross-flow hollow fiber integrated liquid desiccant dehumidification system. Energy 182, 1115–1131 (2019) 3. Gvozdkov, A.: Modern solutions to improve the efficiency of air treatment in HVAC Systems. In: 9th International Conference on Environmental Engineering (ICEE 2014), vol. 258, pp. 114082 (2014) 4. Vavrovic, B.: Importance of envelope construction renewal in panel apartment buildings in terms of basic thermal properties. In: Advanced Materials Research. (Kocovce: International Conference on Advanced Building Construction and Materials (ABCM 2013)), vol. 855, pp. 97-101 (2014) 5. Lal, S., Lucci, F., Defraeye, T., Poulikakos, L.D., Partl, M.N., Derome, D., Carmeliet, J.: CFD modeling of convective scalar transport in a macroporous material for drying applications. Int. J. Therm. Sci. 123, 86–98 (2018) 6. Tang, Y.C., Min, J.C., Wu, X.M.: Selection of convective moisture transfer driving potential and its impacts upon porous plate air-drying characteristics. Int. J. Heat Mass Transf. 116, 371–376 (2018) 7. Skerget, L., Tadeu, A., Ravnik, J.: BEM numerical simulation of coupled heat, air and moisture flow through a multilayered porous solid. Eng. Anal. Boundary Elem. 74, 24–33 (2017) 8. Gagarin, V.G., Akhmetov, V.K., Zubarev, K.P.: Assessment of enclosing structure moisture regime using moisture potential theory. In: MATEC Web of Conferences, vol. 193, p. 03053 (2018) 9. Gagarin, V.G., Akhmetov, V.K., Zubarev, K.P.: The moisture regime calculation of singlelayer enclosing structures on the basis of the discrete-continuum method application. In: IOP Conference Series: Materials Science and Engineering (APCSCE), vol. 456, p. 012105 (2018) 10. Gagarin, V.G., Akhmetov, V.K., Zubarev, K.P.: The moisture regime calculation of singlelayer enclosing structures on the basis of the discrete-continuum method application. In: IOP Conference Series: Materials Science and Engineering (International science and technology conference “FarEastCon-2019”), vol. 753, p. 022045 (2020) 11. Musorina, T., Katcay, A., Petrichenko, M., Selezneva, A.: Thermal properties of conventional and high-strength concrete. In: MATEC Web of Conferences, vol. 245, p. 06005 (2018) 12. Gamayunova, O., Musorina, T., Ishkov, A.: Humidity distributions in multilayered walls of high-rise buildings. In: E3S Web of Conferences, vol. 33, p. 02045 (2018) 13. Statsenko, E.A., et al.: Moisture transport in the ventilated channel with heating by coil. Mag. Civ. Eng. 70(2), 11–17 (2017) 14. Perre, P., Pierre, F., Casalinho, J., Ayouz, M.: Determination of the mass diffusion coefficient based on the relative humidity measured at the back face of the sample during unsteady regimes. Drying Technol. 33, 1068–1075 (2015) 15. Belkharchouche, D., Chaker, A.: Effects of moisture on thermal conductivity of the lightened construction material. Int. J. Hydrogen Energy 41(17), 7119–7125 (2016) 16. Liu, Z.C., Hansen, W., Wang, F.Z.: Pumping effect to accelerate liquid uptake in concrete and its implications on salt frost durability. Constr. Build. Mater. 158, 181–188 (2018) 17. Wu, Z., Wong, H.S., Buenfeld, N.R.: Transport properties of concrete after drying-wetting regimes to elucidate the effects of moisture content, hysteresis and microcracking. Cem. Concr. Res. 98, 136–154 (2017) 18. Zvicevicius, E., et al.: Effects of moisture and pressure on densification process of raw material from Artemisia dubia Wall. Renewable Energy 119, 185–192 (2018) 19. Georget, F., Prevost, J.H., Huet, B.: Impact of the microstructure model on coupled simulation of drying and accelerated carbonation. Cem. Concr. Res. 104, 1–12 (2018) 20. Li, X.X., Chen, S.H., Xu, Q., Xu, Y.: Modeling capillary water absorption in concrete with discrete crack network. J. Mater. Civ. Eng. 30(1), 04017263 (2018)

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21. Eklund, J.A., Zhang, H., Viles, H.A., Curteis, T.: Using handheld moisture meters on limestone: factors affecting performance and guidelines for best practice. Int. J. Architectural Heritage 7(6), 207–224 (2013) 22. Hoseini, A., Bahrami, A.: Effects of humidity on thermal performance of aerogel insulation blankets. J. Build. Eng. 13, 107–115 (2017) 23. Jin, H.Q., Yao, X.L., Fan, L.W., Xu, X., Yu, Z.T.: Experimental determination and fractal modeling of the effective thermal conductivity of autoclaved aerated concrete: effects of moisture content. Int. J. Heat Mass Transf. 92, 589–602 (2016) 24. Shukla, N., Kumar, D., Elliott, D., Kosny, J.: Moisture content measurements in wood and wood-based materials-advancements in sensor calibration and low-moisture-content regime. In: Next-generation thermal insulation challenges and opportunities. (Jacksonville: Symposium on Next Generation Thermal Insulation Challenges and Opportunities), vol. 1574, pp. 66–80 (2014) 25. Suchorab, Z., Sobczuk, H., Lagod, G.: Estimation of building material moisture using noninvasive TDR sensors. In: Thermophysics 2016: 21st International Meeting 2016. (21st International Meeting on Thermophysics), vol. 1752, p. 030003 (2016) 26. Rubene, S., Vilnitis, M., Noviks, J.: Impact of external heat insulation on drying process of autoclaved aerated concrete masonry constructions. In: 2nd International Conference on Innovative Materials, Structures and Technologies, vol. 96, p. 012059 (2015) 27. Potzsch, N., Ruther, N.: Determination of the water vapour diffusion permeability of building materials in dependency on the temperature. Bauphysik 31(2), 106–109 (2009) 28. Petrov, A.S., Kupriyanov, V.N.: About operational factor influence on vapor permeability of heat-insulating materials. Int. J. Pharm. Technol. 8(1), 11248–11256 (2016) 29. Zubarev, K.P., Gagarin, V.G.: Experimental comparison of construction material vapor permeability in case of horizontal or vertical sample position. In: IOP Conference Series: Materials Science and Engineering (International Multi-Conference on Industrial Engineering and Modern technologies), vol. 463, p. 032082 (2018)

Optimizing the Temperature Stress for the Furnace Volume of a Fire-Tube Boiler Svetlana Ovchinnikova1(B) , Denis Abornev2 , Michael Kalinichenko2 Andrey Kalinichenko2 , and Aleksandr Sekisov1

,

1 I.T. Trubilin Kuban State Agrarian University,

st. Kalinina, 13, Krasnodar, Krasnodar Territory 350004, Russia [email protected] 2 North-Caucasus Federal University, st. Pushkin 1, Stavropol, Stavropol Territory 355017, Russia

Abstract. A reasonable choice of the temperature stress for the furnace volume allows providing the required value of the gas temperature at the furnace outlet, as well as the high quality of the fuel combustion process with an optimal excess air ratio. The goal of the research is to study the temperature stress for the furnace of a fire-tube boiler and its effect on the boiler’s design used for heat supply to agricultural enterprises. In order to study the effect of temperature stress and the furnace’s proportions on the ratio of heating surface areas, the design resistance is checked. Calculations for sectional water fire-tube boilers with different proportions of the furnace were performed for various thermal loads of the same furnace volume. Each heating surface was calculated using the approximate method, based on the chord method in this case. During the calculation process, the temperature of the flue gases at the exit from the heating surface was first set, and then refined by successive approximations. In order to draw up the overall balance of the boiler, another global approximation was made. The temperature determined at the exit from the last heating surface was set at the start of the calculation, i.e. in the heat balance, where it affects the loss with flue gases and the efficiency of the boiler. It was determined that the optimal values of the temperature stress for the furnace can vary greatly, depending on the selected ratio of the flue length to its diameter. Keywords: Temperature · Stress · Furnace · Fire-tube boiler

1 Introduction According to the estimates of foreign experts and our data, an energy-saving policy can provide up to 30–50% of saved energy consumed today [1–3]. At the same time, the costs of implementing these measures are 2–3 times less than the costs of increasing the fuel and energy base in order to obtain an equivalent amount of heat [4–6]. Upgrading the equipment and technologies using the latest scientific and technical achievements will provide only 10% of them. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 601–610, 2021. https://doi.org/10.1007/978-3-030-57453-6_57

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In the last century, the use of fire-tube boilers was limited due to a number of accidents caused by errors in the design and construction. Such errors indirectly indicate actual flaws in the calculation methods of designing fire-tube boilers, as well as the complexity of real thermophysical processes occurring in gas-air and water paths [7–9].

2 Materials and Methods The practical aspects of calculating the fire-tube boilers has such peculiarity as the absence of strict regulatory and calculation base. The previously mentioned peculiarities of the fire-tube boiler design cause difficulties in calculating heat transfer both in convective heating surfaces and in the furnace [10]. Most known approaches are based on the finite element method, which involves the installation of specific software and requires a significant amount of time to set the boundary conditions and perform calculations [11]. This makes impossible to use such methodologies to solve optimization problems, which require searching and calculating the large number of variants for structural schemes [12]. One of the design problems, which does not have a clear solution methodology, is the problem of properly determining the volume of the heating chamber [13–15]. The goal of the research is to study the optimal temperature stress for the furnace of a fire-tube boiler and its effect on the boiler’s design. The design of a steel water-heating boiler with a horizontal cylindrical direct-flow furnace and two passes of smoke tubes was taken as basis for the study (Fig. 1).

Fig. 1. Operational scheme of a sectional boiler.

The boiler body (1) has cylindrical shape and includes a heating chamber, front (5) and rear (3) tube plates, convection pass duct and an outer shell ring.

Optimizing the Temperature Stress for the Furnace Volume of a Fire-Tube Boiler

603

The heating chamber is cylindrical, made as a flue (2) and a backfire chamber (8) with welded tube plates (9) and (6). A burner flange is welded to the front edge of the heating chamber, and the bottom of the heating chamber is connected to the rear tube plate of the body (3) by anchor tubes (21). The bottom of the heating chamber and the rear tube plate form a plastic system that compensates the temperature extension of the fire-tube. Tube plates, fire-tube, backfire chamber and their bottoms are made of sheet steel. The convection pass duct of the boiler consists of smoke tubes (4). The pipes are grouped and welded into the tube plates. Gaps are left between the bundles of smoke tubes for inspecting and cleaning the boiler along the water side. Seamless pipes are used as smoke tubes. The geometric characteristics of the boiler are presented in Table 1. Table 1. Geometric characteristics of the boiler. Fire-tube length

LT = 3 m

Fire-tube diameter Reversing chamber diameter

DT = 1 m    2 + d2 · n Dr.c = 2 · DT ft1 , m ft1

Reversing chamber length

Lr.c = 0.4 · Dr.c , m

Fire-tube diameters of first and second ducts

dft = 0.051 m

Fire-tube wall thickness

δft = 0.0025 m

Fire-tube length of first duct

Lft1 = LT m

Fire-tube length of second duct

Lft2 = LT + Lr.c + 0.1 m

3 Results The number of fire-tubes of the first and second ducts nft1 and nft2 (pcs.) is determined according to the optimal speed condition for flue gases, which is 10 m/s. In the calculations, the initial (operational) composition of the gaseous fuel is presented in Table 2. Table 2. Operational fuel composition. CH4

C2 H6 C3 H8 C4 H10 C5 H12 C6 H14 CO2 N2

90.29 2.8

1.1

0.75

0.34

0.2

0.32 4.2

604

S. Ovchinnikova et al.

The algorithm for calculating the heat transfer in the boiler furnace is as follows: 1. 2. 3. 4. 5.

The geometric characteristics of the furnace are calculated. The temperature ϑm at the outlet of the furnace is set. The radiation properties of the combustion products are calculated. The temperature at the outlet of the furnace ϑm is calculated. The temperatures ϑm specified in paragraph 2 and calculated in paragraph 4 of this algorithm are compared. 6. The amount of heat absorbed in the furnace is calculated.

The presented calculation is performed using the method of successive approximations, which is based on the chord method in this study. The furnace’s length Lf is set as a constant and equals 3 m, and the diameter of the furnace Df varies between four following values: 0.5; 0.75; 1.0; 1.5 m. Thus, four following ratios of the furnace’s size are obtained: Lf /Df = 6; 4; 3; 2. Overall, there are 24 calculation experiments. In each experiment, a calibration calculation of the boiler is performed. During the calibration, the number of fire-tubes of the first and second ducts is determined according to the condition that the speed of the flue gases should be 10 m/s. Calculation of each heating surface is performed by the method of successive approximations. The change in the number of fire-tubes in each calculation (satisfying the condition w = 10 m/s) is taken into account when determining the diameter and length of the reversing chamber. The dimensions of the chamber must be taken into account earlier while calculating the furnace. Thus, changing the number of fire-tubes makes it necessary to further refine the thermal calculation of the furnace. All calculations and approximations were successfully automated using MS Excel. The results of the calculation experiments are summarized in tabular form (Table 3). Table 3. The results of the calculation experiments. qv , kW/m3

n1

ϑt , °C

 , °C ϑyx

η, %

L2 , m

122.3

94.3

3.42

118.9

95.0

3.47

113.4

95.5

3.55

107.5

95.9

3.67

103.2

96.2

3.87

1497

100.5

96.3

4.15

16

659

119.4

94.4

3.55

31

897

120.3

94.9

3.58

DT , m

Q, MW

L/D

n2

0.5

0.5

6

704

0.5

1

6

1266

66

31

1092

0.5

2

6

2050

142

59

1272

0.5

4

6

2762

298

114

1394

0.5

8

6

2967

611

223

1465

0.5

16

6

2630

1236

441

0.75

0.5

4

300

25

0.75

1

4

566

59

29

16

869

(continued)

Optimizing the Temperature Stress for the Furnace Volume of a Fire-Tube Boiler

605

Table 3. (continued) ϑt , °C

 , °C ϑyx

η, %

L2 , m

61

1112

116.5

95.4

3.64

118

1282

111.1

95.7

3.75

DT , m

Q, MW

L/D

qv , kW/m3

0.75

2

4

1002

133

0.75

4

4

1579

285

0.75

8

4

2056

596

228

1395

105.8

96.0

3.92

0.75

16

4

2153

1218

447

1458

101.8

96.2

4.19

1

0.5

3

159

22

15

510

115.4

94.6

3.68

1

1

3

306

54

31

743

118.2

95.0

3.70

1

2

3

567

123

62

975

117.3

95.3

3.75

1

4

3

964

272

120

1174

113.2

95.6

3.84

1

8

3

1418

579

233

1321

107.7

96.0

4.00

1

16

3

1702

1198

453

1413

103.1

96.2

4.25

1.5

0.5

2

63

18

15

314

105.9

95.0

3.96

1.5

1

2

123

45

30

522

112.3

95.3

3.97

1.5

2

2

236

108

62

754

114.5

95.4

4.00

1.5

4

2

433

247

123

981

113.3

95.6

4.06

1.5

8

2

724

544

239

1174

109.6

95.8

4.18

1.5

16

2

1041

1154

463

1316

104.7

96.1

4.40

n1

n2

The results show that in all cases the boiler efficiency is approximately the same and is about ~95–96%. The total length of the fire-tubes is determined by the following formula: Lft = Lft1 · nft1 + Lft2 · nft2 , m

(1)

The total area of convective heating surfaces is as follows: Fc = π · dft · Lft , m2 .

(2)

The total area of the radiation heating surfaces, taking into account the volume of the reverse chamber between the flue and the fire-tubes of the first duct, is as follows: FT = π · DT · Lft2 , m2 .

(3)

Total heating surface area of the boiler: Ftot = FT + Fc , m2 . Calculations for all modes are summarized in Table 4.

(4)

606

S. Ovchinnikova et al. Table 4. Calculation results for boiler indicators. qv , kW/m3

DT , m

Q, MW

L/D

0.5

0.5

6

704

0.5

1

6

0.5

2

6

0.5

4

0.5 0.5

Fc

FT

Ftot 28.1

Fc /Ftot * 100%

22.7

5.4

80.86

1266

48.9

5.4

54.4

89.99

2050

101.8

5.6

107.3

94.81

6

2762

210.3

5.8

216.1

97.33

8

6

2967

431.9

6.1

437.9

98.61

16

6

2630

887.5

6.5

894.1

99.27

0.75

0.5

4

300

21.1

8.4

29.5

71.63

0.75

1

4

566

46.1

8.4

54.6

84.55

0.75

2

4

1002

99.5

8.6

108.1

92.07

0.75

4

4

1579

207.8

8.8

216.6

95.93

0.75

8

4

2056

429.8

9.2

439.0

97.89

0.75

16

4

2153

885.7

9.9

895.6

98.90

1

0.5

3

159

19.4

11.6

31.0

62.68

1

1

3

306

44.4

11.6

56.0

79.22

1

2

3

567

96.4

11.8

108.2

89.11

1

4

3

964

204.6

12.1

216.6

94.43

1

8

3

1418

427.5

12.6

440.0

97.15

1

16

3

1702

884.1

13.3

897.5

98.51

1.5

0.5

2

63

18.2

18.6

36.8

49.34

1.5

1

2

123

40.7

18.7

59.4

68.51

1.5

2

2

236

91.6

18.8

110.5

82.94

1.5

4

2

433

198.8

19.1

217.9

91.22

1.5

8

2

724

421.7

19.7

441.4

95.53

1.5

16

1041

880.8

20.7

901.5

97.70

Analysis of the data shows that the ratio of convective areas should increase with increasing temperature stress of the furnace. However, an increase in the length/diameter ratio of the furnace leads to a decrease in the required convective areas. All calculations were performed in accordance with the condition that the speed of combustion products in fire-tubes is constant and equals 10 m/s. The results are presented in the form of four graphs for different furnace’s length/diameter ratios (Fig. 2).

Optimizing the Temperature Stress for the Furnace Volume of a Fire-Tube Boiler

607

Fс/Ftot, % 90 80

Lf/Df = 6 Lf/Df = 4 Lf/Df = 3 Lf/Df = 2

70 60 50

qv ,

0

1000

2000

kW/m

3000

3

Fig. 2. The ratio of convective areas depending on the temperature stress of the furnace, with various proportions of the furnace of the fire-tube boiler.

4 Discussion The indicator of boiler’s efficiency characterizes operating costs. During the course of calculation experiments, the efficiency was approximately the same, ~95–96% on average. The average thermal stress index of the total heating surface characterizes the metal consumption of the boiler, and, consequently, the capital costs. qf =

Q kW , Ftot m2

(5)

where Q is the nominal thermal capability of the boiler, kW. The results of calculating the temperature stress for the total heating surface are presented in Table 5. Table 5. Calculation of temperature stress of the total heating surface. qv , kW/m3 qf

DT , m Q, MW

L/D

0.5

0.5

6

704

17.8

0.5

1

6

1266

18.4

0.5

2

6

2050

18.6

0.5

4

6

2762

18.5

0.5

8

6

2967

18.3

0.5

16

6

2630

17.9

0.75

0.5

4

300

17.0 (continued)

608

S. Ovchinnikova et al. Table 5. (continued) qv , kW/m3 qf

DT , m Q, MW

L/D

0.75

1

4

566

18.3

0.75

2

4

1002

18.5

0.75

4

4

1579

18.5

0.75

8

4

2056

18.2

0.75

16

4

2153

17.9

1

0.5

3

159

16.1

1

1

3

306

17.9

1

2

3

567

18.5

1

4

3

964

18.5

1

8

3

1418

18.2

1

16

3

1702

17.8

1.5

0.5

2

63

13.6

1.5

1

2

123

16.8

1.5

2

2

236

18.1

1.5

4

2

433

18.4

1.5

8

2

1.5

16

724

18.1

1041

17.7

The results of calculating the temperature stress for the total heating surface are displayed on the graph (Fig. 3).

Fс/Ftot, % 90 80

Lf/Df = 6 Lf/Df = 4 Lf/Df = 3 Lf/Df = 2

70 60 50

qv ,

0

1000

2000

3000

kW/m

Fig. 3. Thermal stress of the total heating surface.

3

Optimizing the Temperature Stress for the Furnace Volume of a Fire-Tube Boiler

609

An analysis of the data obtained (Fig. 3) shows that the optimal temperature stress of the boiler furnaces (extremum points on the graph) increases with increasing the length/diameter ratio Lf /Df . The overall metal consumption of the boilers also increases. According to the obtained calculations and the given graphs, the results must be subjected to mathematical processing for convenient practical use. The results of studying the boiler indicators according to the temperature stress of the furnace volume are processed and systematized as follows. The coordinates of the extremum points for each length/diameter ratio of the flue are determined according to Fig. 3. The data obtained are summarized in Table 6. Table 6. Temperature stress of the furnace at maximum temperature stresses of the boiler area, depending on the proportions of the furnace. L/D qv , kW/m3 2

400

3

650

4

1000

6

2100

In order to determine the analytical correlation, these data are approximated by the least square method. In this case, the most suitable approximation type is exponential. According to the results of data processing, the following analytical correlation is obtained: opt

qv = 184.08 · e

L

0.411 DT

T

,

kV . m3

(6)

The determination coefficient R2 , which equals 0.9958, is very close to 1, which indicates a good description quality of the experimental data. The obtained analytical correlation allows calculating the optimal temperature stress of the furnace depending on its size. The required parameters are the length of the flue (Lt ) and its diameter (Dt ) in the range of the ratios Lt /Dt from 2 to 6 to optimize resource efficiency.

5 Conclusions The scientific novelty of the study is the obtaining a new analytical correlation between the optimal temperature stress of the furnace and the geometric proportions of the firetube. The obtained correlation can be recommended for use by engineering and technical personnel in the design of fire-tube boiler units or for evaluating the design efficiency of existing fire-tube boiler units.

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References 1. Ovchinnikova, S., Kalinichenko, M., Markina, N., Schneider, E.: Energy modernization of housing stock. In: E3S Web of Conferences, vol. 157, p. 06028 (2020). https://doi.org/10. 1051/e3sconf/202015706028 2. Mingming, M.G., Xue, W., Wang, C.J., Lin, Y., Chu, H.: Numerical study on the effect of separated over-fire air ratio on combustion characteristics and NOx emission in a 1000 MW supercritical CO2 boiler. Energy 175, 593–603 (2019). https://doi.org/10.1016/j.energy.2019. 03.111 3. Behzad, M.T., Rinaldi, N.F.: Dynamic modelling and optimal sizing of industrial fire-tube boilers for various demand profiles. Appl. Therm. Eng. 132, 341–351 (2018). https://doi.org/ 10.1016/j.applthermaleng.2017.12.082 4. Mikhailov, A., Vdovin, O., Slobodina, E.: Heat exchange processes in the volume of a firetube boiler with a non-water heat carrier. Omsk Sci. Bull. 3(159), 37–40 (2018). https://doi. org/10.25206/1813-8225-2018-159-37-40 5. Batrakov, P.A., Mikhailov, A.G., Ignatova, V.Y.: Fire – tube boiler optimization criteria and efficiency indicators rational values defining. J. Phys. Conf. Ser. 944, 012009 (2018). https:// doi.org/10.1088/1742-6596/944/1/012009 6. Sekisov, A.N.: Improving the efficiency of the organization of construction production based on the use of BIM-technologies. IOP Conf. Ser. Mater. Sci. Eng. 698, 066005 (2019). https:// doi.org/10.1088/1757-899X/698/6/066005 7. Sekisov, A., Serga, G.: Rotary-screw systems for rotary kilns. In: E3S Web of Conferences, Topical Problems of Architecture, Civil Engineering and Environmental Economics (TPACEE 2018), vol. 91, p. 02034 (2019). https://doi.org/10.1051/e3sconf/20199102034 8. Yu, C., Xiong, W., Ma, H., Zhou, J., Si, F., Jiang, X., Fang, X.: Numerical investigation of combustion optimization in a tangential firing boiler considering steam tube overheating. Appl. Therm. Eng. 154, 87–101 (2019). https://doi.org/10.1016/j.applthermaleng.2019.03.074 9. Akkinepally, B., Shim, J., Yoo, K.: Numerical and experimental study on biased tube temperature problem in tangential firing boiler. Appl. Therm. Eng. 126, 92–99 (2017). https://doi. org/10.1016/j.applthermaleng.2017.07.121 10. Gutiérrez Ortiz, F.J.: Modeling of fire-tube boilers. Appl. Therm. Eng. 31, 3463–3478 (2011). https://doi.org/10.1016/j.applthermaleng.2011.07.001 11. Habib, M.A., Nemitallah, M.A.: Design of an ion transport membrane reactor for application in fire tube boilers. Energy 81, 787–801 (2015). https://doi.org/10.1016/j.energy.2015.01.029 12. Tognoli, M., Najafi, B., Rinaldi, F.: Dynamic modelling and optimal sizing of industrial firetube boilers for various demand profiles. Appl. Therm. Eng. 132, 341–351. https://doi.org/ 10.1016/j.applthermaleng.2017.12.082 13. Rodriguez Vasquez, J.R., Rivas Perez, R., Sotomayor Moriano, J., Peran Gonzalez, J.R.: System identification of steam pressure in a fire-tube boiler. Comput. Chem. Eng. 32, 2839– 2848. https://doi.org/10.1016/j.compchemeng.2008.01.010 14. Fu, J., Liu, Z., Wei, L., Lin, L., Li, N., Zhou, Q., Ma, C.: Identification of the running status of membrane walls in an opposed fired model boiler under varying heating loads. Appl. Therm. Eng. 173, 115217 (2020). https://doi.org/10.1016/j.applthermaleng.2020.115217 15. Gañan, J., Al-Kassir, A., González, J.F., Turegano, J., Miranda, A.B.: Experimental study of fire tube boilers performance for public heating. Appl. Therm. Eng. 25, 1650–1656 (2005). https://doi.org/10.1016/j.applthermaleng.2004.10.008

Temperature of Surface Layers of the Earth Andrey Ponomaryov(B)

and Aleksandr Zakharov(B)

Perm National Research Polytechnic University, Perm 614000, Russian Federation {andryepab,miks}@pstu.ru

Abstract. The article presents the results of monitoring the temperature of the surface layers of the earth. Monitoring was carried out at two sites with engineeringgeological conditions typical for Perm. The geological conditions of the first site are clay soils, the second site is sandy. The first site is located in a dense urban development, the second is an unfinished part of the city of Perm. The depth of the soil massif on which the temperature was monitored was: for the first site 19 m, for the second site - 37 m. Based on monitoring results, a picture of the temperature change in the soil massif in time for both sites was obtained. In the article, the average monthly temperatures of the soil massif are plotted on both sites. The zone of fluctuations in the temperature of the soil massif is revealed depending on the temperature of the outside air. The depth of the zone of seasonal temperature fluctuations was 10 m. Monitoring determined that the temperature of the ground mass is below 10 m: for the first site +12 °C with a decrease in temperature to 10 °C to a depth of 19 m, for the second site - a constant +6–7 °C to a depth of 37 m. Keywords: Temperature · Surface · Layers · Earth

1 Introduction As a rule, the technologies based on the use of the soil thermal energy are employed for heating and cooling of buildings, at least to provide electricity and hot water. These technologies have been widely used in European and neighboring countries [1–9]. Their introduction in Russia is the point and did not found mass distribution. Quantitative assessment of subgrade temperature is one of the main factors allowing introduce process based on the use of the soil thermal energy. In particular, they are energy-efficient foundations and underground structures of buildings. Existing studies provide information on the temperature of the surface layers of soils in various countries of Europe, North America, Africa [10–14]. At the same time, no similar studies have been found for the territory of Russia. This article presents the results of monitoring the temperature fields of soils for the city of Perm. The results of these studies can also be used for predictive calculations of energy foundations in territories located at similar latitudes (58° N). The studies of temperature fields of ground bases in the city of Perm having carried out since 2009 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 611–620, 2021. https://doi.org/10.1007/978-3-030-57453-6_58

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[15–20]. Research is being carried out to quantify the soil thermal behavior for the main types of geotechnical conditions. The results of monitoring surface of the earth may also be of interest in the design of road bases and structures, modeling of seasonal soil freezing processes [21–29].

2 Geological Section of Experimental Sites Research of temperature fields of ground bases carried out for two basic types of geotechnical conditions specific to the left-bank and right-bank parts of the Perm city. Studies are being conducted at two sites: Site 1. The monitoring system is installed at the Civil Engineering Faculty PNRPU in the Sverdlovsky district of Perm (left bank of the city of Perm). Monitoring has been carried out continuously since December 2008 to the present. Site 1 is characterized by dense urban development. The development age is more than 50 years. The distance from the observation well to the nearest building is about 3 m.

Fig. 1. Geological section of experimental sites.

Following the results of geological engineering survey experimental site 1 is comprised of quaternary alluvial- dealluvial clayey soil of the total thickness of 11.6 m,

Temperature of Surface Layers of the Earth

613

with up to 60–70% of pebbles at the bottom. Quaternary soils are overlaid by a filled-up ground of the thickness of 6.0 m. Bedrock is argillites uncovered at a depth of 17.6 m. Filled-up ground is presented by clay soil of semi-solid to plastic consistency at the base with an admixture of 60–70% of construction waste (rubble, broken bricks, glass, wood). Quaternary alluvial- dealluvial deposits are mainly represented by the clay of solid to semi-solid consistency underlying the pebble with loamy sand of solid consistency (content of gravel and pebbles is 60–70%). The geological section is shown in Fig. 1a. Site 2. The monitoring system is installed on the territory of the university campus in the Leninsky district of Perm (right bank of the city of Perm). Monitoring has been carried out since August 2015. Currently monitoring data were processed till January 2019. Site 2 is located in the undeveloped area of the city. The distance to the nearest building is more than 30 m. According to the results of archival research of surrounding area site 1 is comprised of quaternary alluvial sand and clay of the total thickness of 15 m, with 25% of gravel at the bottom. Quaternary alluvial deposits are represented by fine sand, clay, and clay soils of plastic to liquid consistency. The gravel inclusion was marked from a depth of 1.0 m along the full thickness of the alluvial soils with an increase to the base up to 25%. According to the results of archive research the bedrock was uncovered at a depth of 17.0 m. The geological section is shown in Fig. 1b. According to the results of geotechnical studies sites 1 and 2 are assigned to the I and II types of geotechnical conditions, respectively, specific to Perm.

3 Monitoring of the Temperature Fields Results Studies of the temperature field distribution in the soil are carried out by installing the resistive temperature transducer (temperature sensors). Installation of resistive temperature transducer was made in a pre-drilled hole under the protective casing. To gather the data RTM 59 loggers are used for measuring, continuous recording and monitoring of temperature and other non-electrical values (frequency, pressure, flow, level, etc.), converted into electrical signals of strength, DC voltage and DC resistance. The thickness of the observed soil mass on the site 1 is 19 m. The temperature sensors are installed at intervals of 1 m. Monitoring of temperature fields has held for more than 10 years on the site 1. Summarized monitoring results (average monthly temperatures for the period from January 2009 to January 2019) are shown in Fig. 2. Under the diagram the temperature of the soil mass from a depth of 8–9 m is practically independent of the seasonal outdoor temperature fluctuations. The temperature is about 12 °C, falling to 10 °C to the depth of 19 m.

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0

3

5

7

t, °С 11

9

13

15

17

19

2 4 6 Deep, m

8 10 12 14 16 18 20

January May September

February June October

March July November

April August December

Fig. 2. Site 1. Diagram of average monthly temperatures of soil mass according to the monitoring results from 2009 to 2019.

To analyze the temperature fluctuations for several annual cycles the average monthly temperatures in September for the 2009–2018 are shown in Fig. 3. 19

September 2009 September 2010 September 2011 September 2012 September 2013 September 2014 September 2015 September 2016 September 2017 September 2018

18 17 16 t, °С

15 14 13 12 11 10

0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 Deep, m

Fig. 3. Site 1. Diagram of average monthly temperatures of soil mass in September for the 2009– 2018.

Temperature of Surface Layers of the Earth

615

Under the diagram the temperature of the soil mass from a depth of 8–9 m is constant (the difference is not more than 1 °C) during 10 years of monitoring. The thickness of the observed soil mass on the site 2 is 37 m. The temperature sensors are installed at intervals of 2 m, till a depth of 3 m interval is equal to 0.5 m. Monitoring of temperature fields has held for more than 3 years on the site 1. Summarized monitoring results (average monthly temperatures for the period from August 2015 to January 2019) are shown in Fig. 4.

0

0

2

4

6

8

t, °С 10

12

14

16

18

20

2 4 6 8 10 12

Deep, m

14 16 18 20 22 24 26 28 30 32 34 36 January May September

February June October

March July November

April August December

Fig. 4. Site 2. Diagram of average monthly temperatures of soil mass according to the monitoring results from August 2015 to January 2019.

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To analyze the temperature fluctuations for several annual cycles the average monthly temperatures in September for the 2015–2018 are shown in Fig. 5. 13

September 2016 September 2017

12

September 2018

t, °С

11 10 9 8 7 6

0

2

4

6

8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 Deep, m

Fig. 5. Site 2. Diagram of average monthly temperatures of soil mass in September for the 2015– 2018.

Analysis of monitoring results on the site 2 displays that the temperature of soil mass from a depth of 9 m is constant and equals to 6–7 °C. For further analysis the average annual temperatures of soil mass for the entire period are shown in Table 1 and Fig. 6 for both sites.

0

9.9

6.8

Deep, m

Site 1, °C

Site 2, °C

5.7

10.9

1

6.1

11.4

2

6.5

11.8

3

–

12.0

4

6.7

12.0

5

–

12.1

6

6.3

12.0

7

–

12.0

8

6.7

12.0

9

–

11.5

10

6.6

11.3

11

–

11.5

12

6.6

11.4

13

–

11.5

14

6.5

11.7

15

–

11.0

16

6.5

10.8

17

–

10.5

18

6.3

10.3

19

Table 1. Average annual temperatures of soil mass for sites 1 and 2.

7.3

–

21

7.0

–

23

6.9

–

25

6.8

–

27

6.7

–

29

6.8

–

31

6.2

–

33

6.1

–

35

6.0

–

37

Temperature of Surface Layers of the Earth 617

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A. Ponomaryov and A. Zakharov 14

Site 1

12

Site 2

t, °С

10 8 6 4 2 0

0

5

10

15

20 Deep, m

25

30

35

40

Fig. 6. Diagram of average annual temperatures of soil mass for sites 1 and 2.

4 Conclusions According to the results of the conducted studies, the following conclusions were drawn: 1. The temperature of soil mass of 2 site from a depth of 9 m is constant and equals to 6–7 °C. The temperature fall has not been recorded at depths 7–37 m, in contrast to the site 1. 2. The temperature of the soil mass for the site 2 is lower than for the site 1 on average of 4–6 °C. 3. The fixed difference of soil mass temperatures of the sites is probably explained by the presence of additional heat sources at the site 1, in particular, site 1 is characterized by dense urban development. 4. When designing power efficient foundations and underground structures the location of the object, the presence of surrounding buildings, engineering services should be taken into account.

References 1. Katzenbach, R., Vogler, M., Waberseck, T.: Large energy pile systems in urban areas. Bauingenieur (2008) 2. Katzenbach, R., Wagner, I.M.: The use of borehole heat exchangers as energy storage systems - design and efficiency. Bauingenieur (2012) 3. Adam, D., Markiewicz, R.: Energy from earth-coupled structures, foundations, tunnels and sewers. Geotechnique 59(3), 229–236 (2009). https://doi.org/10.1680/geot.2009.59.3.229 4. Katzenbach, R., Leppla, S., Waberseck, T.: Deep excavations and deep foundation systems combined with energy piles. In: Baltic Piling (2013) 5. Sanner, B.: Geothermal heat pumps technologies and development. Tech. Poszuk. Geol. 43(5– 6), 26–34 (2004) 6. Brandl, H.: Energy piles and diaphragm walls for heat transfer from and into the ground. In: Deep Found. Bored Auger Piles - Bap Iii (1998)

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7. Brandl, H., Adam, D., Markiewicz, R.: Ground-sourced energy wells for heating and cooling of buildings. Acta Geotech. Slov. 3(1), 4–27 (2006) 8. Morklyanyk, B., Shapoval, V., Khalymendyk, O., Ivaskevych, O., Lavreniuk, V.: Prospects for the use of underground structures as a source of thermal energy. Collect. Res. Pap. Natl. Min. Univ. 57, 98–112 (2019). https://doi.org/10.33271/crpnmu/57.098 9. Bogdanoviˇcs, R., Borodinecs, A., Zajacs, A., Šteinerte, K.: Review of heat pumps application potential in cold climate. In: Murgul, V., Popovic, Z. (eds.) EMMFT 2017. AISC, vol. 692, pp. 543–554. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-70987-1_58 10. Brandl, H.: Energy foundations and other thermo-active ground structures. Geotechnique 56(2), 81–122 (2006). https://doi.org/10.1680/geot.2006.56.2.81 11. Brandl, H.: Thermo-active ground-source structures for heating and cooling. Procedia Eng. 57, 9–18 (2013). https://doi.org/10.1016/j.proeng.2013.04.005 12. Brandl, H.: Geothermal geotechnics for urban undergrounds. Procedia Eng. 165, 747–764 (2016). https://doi.org/10.1016/j.proeng.2016.11.773 13. Tileu, K., Teltayev, B., Aitbayev, K., Suppes, E.: Mapping of frost penetration depth for highways in Kazakhstan. In: 16th Asian Regional Conference on Soil Mechanics and Geotechnical Engineering, ARC 2019 (2020) 14. Zhussupbekov, A., Shakhmov, Z., Lukpanov, R., Tleulenova, G., Kudryavtsev, S.: Frost depth monitoring of pavement and evaluation of frost susceptibility at soil ground of Kazakhstan. In: 19th International Conference on Soil Mechanics and Geotechnical Engineering, ICSMGE 2017 (2017) 15. Ponomarev, A.B., Zakharov, A.V.: Analysis of the interaction between energy-efficient foundations and soil mass. Soil Mech. Found. Eng. 52(4), 232–237 (2015). https://doi.org/10. 1007/s11204-015-9333-9 16. Ponomaryov, A., Zakharov, A.: Numerical simulation of the process of geothermal lowpotential ground energy extraction in Perm region (Russia). In: 18th International Conference on Soil Mechanics and Geotechnical Engineering: Challenges and Innovations in Geotechnics, ICSMGE 2013 (2013) 17. Ponomaryov, A., Zakharov, A.: Temperature of soil monitored at experimental sites in perm region (Russia). Acta Polytech. CTU Proc. 10, 38–42 (2017). https://doi.org/10.14311/app. 2017.10.0038 18. Ofrikhter, I., Zaharov, A., Ponomaryov, A., Likhacheva, N.: Modeling heat transfer process in soils. MATEC Web Conf. 251, 02048 (2018). https://doi.org/10.1051/matecconf/201825 102048 19. Ponomaryov, A., Zakharov, A.: Numerical simulation of the process of geothermal lowpotential ground energy extraction in Perm region (Russia). MATEC Web Conf. 86, 03008 (2016). https://doi.org/10.1051/matecconf/20168603008 20. Ponomaryov, A.B., Zakharov, A.V.: Numerical simulation of the process of the geothermal low-potential ground energy extraction in the perm region (Russia). Procedia Eng. 150, 2272– 2277 (2016). https://doi.org/10.1016/j.proeng.2016.07.293 21. Sakharov, I.I., Paramonov, V.N., Kudryavtsev, S.A.: The account of frost heave and thawing processes when designing road embankments in cold regions. In: Petriaev, A., Konon, A. (eds.) Transportation Soil Engineering in Cold Regions, Volume 1. LNCE, vol. 49, pp. 19–24. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-0450-1_3 22. Teltayev, B.B., Suppes, E.A.: Temperature and moisture in a highway in the south of Kazakhstan. Transp. Geotech. 21, 100292 (2019). https://doi.org/10.1016/j.trgeo.2019. 100292 23. Teltayev, B.B., Suppes, E.A.: Temperature in pavement and subgrade and its effect on moisture. Case Stud. Therm. Eng. 13, 100363 (2019). https://doi.org/10.1016/j.csite.2018. 11.014

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24. Teltayev, B.B., Liu, J., Suppes, E.A.: Distribution of temperature, moisture, stress and strain in the highway. Mag. Civ. Eng. 7(83), 234 (2018). https://doi.org/10.18720/MCE.83.10 25. Teltayev, B., Suppes, E., Liu, J.: Impact of freezing of subgrade on pavement deformation. In: 19th International Conference on Soil Mechanics and Geotechnical Engineering, ICSMGE 2017 (2017) 26. Ulitskii, V.M., Sakharov, I.I., Paramonov, V.N., Kudryavtsev, S.A.: Bed – structure system analysis for soil freezing and thawing using the termoground program. Soil Mech. Found. Eng. 52(5), 240–246 (2015). https://doi.org/10.1007/s11204-015-9335-7 27. Teltayev, B.B., Baibatyrov, A.I., Suppes, E.A.: Characteristics of highway subgrade frost penetration in regions of the Kazakhstan. In: 15th Asian Regional Conference on Soil Mechanics and Geotechnical Engineering, ARC 2015: New Innovations and Sustainability (2015). https://doi.org/10.3208/jgssp.kaz-08 28. Teltaev, B.B., Aitbaev, K.: Assessment of the non-stationary temperature field in a road construction with an underground heat pipeline by the finite element method. Int. J. Pure Appl. Math. (2014). https://doi.org/10.12732/ijpam.v93i5.6 29. Kudryavtsev, S.A.: Numerical modeling of the freezing, frost heaving, and thawing of soils. Soil Mech. Found. Eng. 41(5), 177–184 (2004). https://doi.org/10.1007/s11204-005-0005-z

The Depth of Building Drainage in Sandy Soil Svetlana Kaloshina(B)

, Sergei Beliaev , and Dmitrii Zolotozubov

Perm National Research Polytechnic University, Perm 614000, Russian Federation [email protected]

Abstract. To protect the foundations and buried parts of buildings and structures at a high level of groundwater, it is necessary to create wall drainage, which should provide reliable protection from groundwater for the entire period of exploitation of the building, and therefore be reliable and at the same time economical in the device. Therefore, it is necessary to determine the optimal depth of foundation for soils typical of many countries, and hydrogeological conditions typical of urban areas. The calculation was made in the PlaxFlow1.5. The depth was determined depending on a variable ground-water level in small, medium, and large sand. The conclusions are made to use a drainage located directly under the mortar and a drainage constructed in a separate trench. Essential aspects are identified which affect the depth of a buried drain are the width of the building; the presence or absence of underground floors; depth; the filtration coefficient of the drained soil; the level of groundwater; the presence of a waterproofing and its depth. Keywords: Building · Drainage · Sandy soil

1 Introduction The process of flooding of buildings and structures is quite dangerous, since as the groundwater level rises, capillary dampening and water saturation occurs in the soil of the base and building materials, both foundations and other underground parts of buildings [1–3]. Subsequently, there is a change in the physical and mechanical characteristics and stress-strain state of the soil, as well as a violation of the operational suitability of buildings and structures. All these factors can lead to uneven precipitation and increased precipitation of foundations of buildings and structures and, as a result, to additional deformations of building structures [4, 5]. For normal operation of foundations, basements, and buried structures, it is necessary to protect underground water. The type of protection will be determined by the topographical and hydrogeological conditions of the construction site, the level of seasonal fluctuations in groundwater, their aggressiveness towards the foundation material, as well as structural solutions of the underground part of the building [6, 7]. When the groundwater level is high, drainage of the soil is one of the most effective water protection measures that allow protecting building structures, including foundations, for the entire period of their exploitation. At the same time, a drainage system is arranged around a building or territory that is subject to protection from groundwater, © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 621–630, 2021. https://doi.org/10.1007/978-3-030-57453-6_59

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which is an engineering structure designed to intercept, receive and divert excess water [8–10]. Such drainage systems can be arranged including the use of modern geosynthetic materials [11–13]. As a protection of building structures from waterlogging, linear drainage of an imperfect type in sandy soil is considered. This is because we are considering construction sites with a deep reservoir cover, which is typical not only for Russia but also for many other countries [14–16]. When designing a drainage system, one of the most urgent tasks is to determine the necessary depth of the drains, sufficient to achieve the required minimum gap between the top of the depression curve and the floor level of the basement. During the research, the problem of determining the optimal depth of the drainage is considered on the example of designing a local drainage of an imperfect type for a 4-story residential building with a basement 14.6 m wide, located in Perms.

2 Methods Numerical modeling in the PlaxFlow1 software package was used as the main research tool for determining the optimal depth of drainage. The PlaxFlow Module is an extension of the PLAXIS program and allows you to perform a time-dependent calculation of groundwater filtration. It can also be used for joint filtration and deformation calculations that allow determining changes in pore pressures and deformations that affect each other [17, 18]. Two variants of drainage design are considered for numerical simulation: 1) Wall drainage, the design solution of which has accepted according to the patent (Nevzorov A. L., Nikitin A.V., Zaborskaya O. M. Wall drainage: Pat. 2640600 Russian Federation (2018)) in Fig. 1. 2) Separate trench drainage structure in Fig. 2. The building in question has a pile foundation. The piles have a single row arrangement with a step of 0.9 m with a cross-section of 30 × 30 cm. To simulate filtration of groundwater through the soil in between piles space, was modeled conditional dividing wall, with the characteristics of the surrounding soil mass, but with a filter factor of 3 times smaller (which takes into account the substitution of part of the ground reinforced concrete piles). Previously, the depth of the drainage was assigned based on its location under the pile’s raft, and was 2.68 m, both in the first and second versions of the drainage device. In the second variant of the drainage device the safe distance from the drainage to the outer walls of the projected building was first determined using the formula 1: lmin = b +

B h − hf + 2 tan ϕ

where b is the broadening of the foundation, m; B is the width of the drainage trench, m;

(1)

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1 is the drainage pipe; 2 is the anchor rod; 3 is the brackets; 4 is the grillage; 5 is the piles; 6 is the crushed stone or gravel; 7 is the fine sand; 8 is the basement walls; 9 is the basement floor; 10 is the light sandy loam, semisolid; H is the capacity of the aquifer; T is the excess of imperfect drains over the water barrier; h is the depth of immersion of the drainage under undervalued groundwater level; DL is the ground level Fig. 1. The wall drainage located under the grillage of the building.

h is the drainage depth, m; hf is the depth of the foundation, m; ϕ is the angle of internal friction of the soil, deg. The minimum safe distance from the drain to the exterior walls of the building was

lmin = 0.1 +

1.0 2.68 − 2.50 + = 0.91 m 2 tan 30◦

For the convenience of work and to provide some margin in case of need to increase the depth of the drainage for further design, a distance of l = 1.5 m was adopted.

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1 is the drainage pipe; 2 is crushed stone; 3 is the sand with a filtration coefficient of at least 5 m/day; 4 is the local soil; h is the depth of the drainage under the undimmed water table; b is the widening of the foundation; B is the width of the drainage trench; l is the safe distance of the drainage from the exterior walls of the projected building; hf is the depth of the foundation; DL is the ground level; WL is the groundwater level

Fig. 2. Separate trench drainage structure.

Options for possible drainage locations in the plan are shown in Fig. 3. The main characteristics of engineering and geological elements of the construction site, obtained from engineering and geological surveys, are shown in Table 1. The groundwater level according to engineering and geological surveys is recorded at a depth of 1.0 m. During periods of snowmelt and heavy rains, groundwater may rise by 0.5 m. In this regard, the calculation of the groundwater level varies from 0.5 to 1.5 m. The selection of the type and design of the drainage system is based on calculations in the PlaxFlow1.5 software package [19]. The calculation scheme is shown in Fig. 4.

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1 is the drainage pipe; 2 is the drainage well; 3 is the drainage slope; 4 is the discharge collector

Fig. 3. The plan of drainage: a) single line, b) double line.

Table 1. Main characteristics of engineering-geological elements. No

Soil name

H, m

W

IL

e

γ n , kN/m3

cn , kPa

ϕ n , deg

E, MPa

1a

Fill soil

0.3–2.5

0.132

0.82

–

–

–

–

–

1

Fine sand

8.2–12.5

0.200

–

0.68

18.42

1.0

30

22

2

Lean clay

0.4–2.6

0.219

0.20

0.72

18.62

18.0

16

11

3

Gravel

do 7.0

0.168

–

–

–

–

–

30

3 Results and Discussion As a result of solving the test problem, it is concluded that for the engineering and geological conditions specified in Table 1, a single-line type of drainage (Fig. 3, a) and its location under the pile’s raft (Fig. 1) are possible only if the groundwater is found at a depth of 2.0 m or more. Therefore, for further calculations, a two-line drainage was adopted (Fig. 3, b), located in a separate trench (Fig. 2). At the next stage, it was necessary to determine the depth of the drains, providing the required rate of drainage.

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Fig. 4. Calculation scheme implemented in PlaxFlow1. 5.

In this problem, the drainage norm is the lowest depth of the maximum predicted groundwater level from the floor mark of the basement of the building, which provides normal operating conditions for the building. For buildings with basements, it should be taken 0.3 m below the basement floor mark. In the course of numerical modeling to determine the required drainage rate, the depth of drainage was varied at the groundwater level of 0.5; 1.0; 1.5 m (Table 2). Table 2. Results of varying the depth of drains. No Drainage depth, m The amount of lowering of the groundwater level relative to the basement floor, m At groundwater level, m 0.5

1.0

1.5

1

2.8

0.00

0.00

0.27

2

3.0

0.01

0.18

0.39

3

3.2

0.12

0.22

0.44

4

3.4

0.14

0.26

0.51

5

3.6

0.17

0.34

0.67

6

3.8

0.49

0.63

0.81

The minimum values of drainage depth at different groundwater levels that provide the required drainage rate are summarized in Table 3.

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Table 3. Results of numerical and analytical calculations. No WL, m Required drainage depth at the accepted drainage rate, m

The rate of drying, m

1

0.5

3.70

0.30

2

1.0

3.50

3

1.5

2.90

Figure 5 shows the location of the depression curve.

Fig. 5. The filter field in PlaxFlow1.5 at a WL of 1.0 m and a drainage depth of 3.5 m.

To expand the scope of application of the results obtained concerning sandy soils, similar calculations were performed for the engineering-geological section presented in Fig. 4, for which medium sand was first used as geological element -1, then large sand. For medium sand and large sand, the following characteristics were adopted: – filtration coefficient kf = 10 m/day, porosity coefficient e = 0.62 – for medium-sized sand; – filtration coefficient kf = 25 m/day, porosity coefficient e = 0.62 – for coarse sand. The calculations were performed in the PlaxFlow1 software package.5. The groundwater level is assumed to be 0.5; 1.0; 1.5 m. The calculation results for medium-sized and coarse sand are shown in Table 4. On the based of calculations, we can conclude that the required drainage depth depends on the WL for different types of sandy soils, provided that the drainage rate is 0.3 m. Table 5 also shows a variant of a possible drainage device scheme. Option 1 corresponds to the method of placing the drainage directly under the pile’s raft (Fig. 1), option 2-the location of the drainage in a separate trench (Fig. 2). The results obtained

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S. Kaloshina et al. Table 4. Results of varying the depth of drains. No

Drainage depth, m

The amount of lowering of the groundwater level relative to the basement floor, m Medium-sized sand

Large sand

At groundwater level, m 0.5

1.0

1.5

0.5

1.0

1.5

1

2.6

0.09

0.16

0.31

0.11

0.16

0.29

2

2.7

0.16

0.25

0.39

0.19

0.23

0.38

3

2.8

0.25

0.34

0.48

0.27

0.34

0.46

4

3.0

0.44

0.53

0.65

0.36

0.44

0.55

5

3.2

0.66

0.72

0.81

0.45

0.52

0.64

6

3.4

0.72

0.79

0.89

0.55

0.62

0.72

Table 5. Results of variation of engineering-geological conditions. No

Type of sand

GL, m

Required drainage depth at the accepted drainage rate, m

The rate of drying, m Drainage design option

1

Fine

0.5

3.70

0.30

1.0

3.50

2

3

Medium

Large

Option 2 Option 2

1.5

2.90

Option 2

0.5

2.90

Option 2

1.0

2.80

Option 1, 2

1.5

2.60

Option 1, 2

0.5

2.80

Option 1, 2

1.0

2.70

Option 1, 2

1.5

2.60

Option 1, 2

in Table 5 are valid for buildings and structures on pile foundations up to 15 m wide and a basement depth of 2.1 m.

4 Conclusions Protection of territories and individual buildings and structures from flooding is a complex process that begins with the design of the terrain of the site and ends with waterproofing of already erected structures. One of the key ways of protection is the use of drainage systems.

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The conducted research in the form of numerical modeling and their comparison with foreign works have shown that it is possible to find the optimal depth of the drainage, which will ensure the normal operation of the building or structure. The results of the research were carried out for sandy soils, which are widely distributed in different countries, and hydrogeological conditions characteristic of urbanized territories. Based on the research performed, the following conclusions can be drawn: 1. At the same rate of drainage with an increase in the groundwater level, the required depth of the drainage increases. Since the groundwater level changes depending on the time of year, when choosing the depth of the drains, it is necessary to focus on the highest groundwater level, which is typical during periods of snowmelt and heavy rains. 2. For buildings up to 15 m wide, the use of single-line drainage is possible only if the surface is covered with sandy soil, represented by medium sand or large sand, which has large filtration coefficients compared to fine sand, which also allows you to reduce the depth of the drainage and place it directly under the grillage. 3. The most significant factors that affect the depth of the drains are the width of the building; the presence or absence of a basement; its depth; the filter factor drained soil; groundwater levels; the presence of impermeable layer and its depth. 4. In sandy soils, when designing local drainage, you should consider the possibility of including it in the General drainage system, which will have a positive effect on the further improvement of the territory.

References 1. Terleev, V.V.: Hysteresis of the soil water-retention capacity: estimating the scanning branches. Mag. Civ. Eng. 1, 141–148 (2018). https://doi.org/10.18720/MCE.77.13 2. Terleev, V.: Modelling the hysteretic water retention capacity of soil for reclamation research as a part of underground development. Procedia Eng. 165, 1776–1783 (2016). https://doi.org/ 10.1016/j.proeng.2016.11.922 3. Bukhartsev, V.N., Petrichenko, M.R.: Nonsteady filtration in a uniform soil mass. Power Technol. Eng. 46, 198–200 (2012). https://doi.org/10.1007/s10749-012-0331-z 4. Ponomaryov, A.B., Kaloshina, S.V., Zakharov, A.V., Bezgodov, M.A., Shenkman, R.I., Zolotozubov, D.G.: Results of geotechnical modelling of the influence of construction of the deep foundation ditch on the existing historical building. In: 15th Asian Regional Conference on Soil Mechanics and Geotechnical Engineering, ARC 2015: New Innovations and Sustainability (2015). https://doi.org/10.3208/jgssp.atc19-01 5. Nevzorov, A.L., Nikitin, A.V., Zaruchevnyh, A.V.: The underpinning of historical buildings foundations in Arkhangelsk city. In: 14th Asian Regional Conference on Soil Mechanics and Geotechnical Engineering (2011) 6. Tóth, J.: A theoretical analysis of groundwater flow in small drainage basins. J. Geophys. Res. 68, 4795–4812 (1963). https://doi.org/10.1029/jz068i016p04795 7. Barron, O.V., Barr, A.D., Donn, M.J.: Effect of urbanisation on the water balance of a catchment with shallow groundwater. J. Hydrol. 485, 162–176 (2013). https://doi.org/10.1016/j. jhydrol.2012.04.027

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8. Schilling, K.E., Jindal, P., Basu, N.B., Helmers, M.J.: Impact of artificial subsurface drainage on groundwater travel times and baseflow discharge in an agricultural watershed, Iowa (USA). Hydrol. Process. 26, 3092–3100 (2012). https://doi.org/10.1002/hyp.8337 9. Kolymbas, D., Wagner, P.: Groundwater ingress to tunnels - the exact analytical solution. Tunn. Undergr. Sp. Technol. 22, 23–27 (2007). https://doi.org/10.1016/j.tust.2006.02.001 10. Howard, A.D.: Theoretical model of optimal drainage networks. Water Resour. Res. 26, 2107–2117 (1990). https://doi.org/10.1029/WR026i009p02107 11. Ponomaryov, A., Zolotozubov, D.: Several approaches for the design of reinforced bases on karst areas. Geotext. Geomembr. 42, 48–51 (2014). https://doi.org/10.1016/j.geotexmem. 2013.12.002 12. Ponomaryev, A.B., Kleveko, V.I., Zolotozubov, D.G.: Experience of geosynthetical material application for karst danger reduction of building base. In: 9th International Conference on Geosynthetics - Geosynthetics: Advanced Solutions for a Challenging World, ICG 2010 (2010) 13. Ponomaryov, A., Zolotozubov, D.: Technique of reinforced soil base calculation under fall initiation in ground mass. In: 18th International Conference on Soil Mechanics and Geotechnical Engineering: Challenges and Innovations in Geotechnics, ICSMGE 2013 (2013) 14. Wafa, F.F., Abu Rizaiza, O.S., Mirza, W.H., Khan, M.Z.A.: Impact of groundwater pollution on concrete structures. Concr. Int. 10, 54–58 (1988) 15. Abu-Rizaiza, O.S., Sarikaya, H.Z., Ali Khan, M.Z.: Urban groundwater rise control: case study. J. Irrig. Drain. Eng. 115, 588–607 (1989). https://doi.org/10.1061/(ASCE)0733-9437 16. Herrmann, H., Bucksch, H.: Groundwater flow model. In: Dictionary Geotechnical Engineering/Wörterbuch GeoTechnik (2014) 17. Zhao, L., You, G.: Stability study on the northern batter of MBC Open Pit using Plaxis 3D. Arab. J. Geosci. 11(6), 1–11 (2018). https://doi.org/10.1007/s12517-018-3454-1 18. Chanmee, N., Bergado, D.T., Hino, T., Lam, L.G.: Analysis and simulations of erosion protection designs using the PLAXIS 2D and Slide programs. In: 15th Asian Regional Conference on Soil Mechanics and Geotechnical Engineering, ARC 2015: New Innovations and Sustainability (2015). https://doi.org/10.3208/jgssp.tc302-10 19. Galavi, V.: Groundwater flow, fully coupled flow deformation and undrained analyses in PLAXIS 2D and 3D. (2010). https://doi.org/10.3208/jgssp.tc302-10j.1746-1561.2005.tb0 7343.x10.1111, https://doi.org/10.3208/jgssp.tc302-10j.1746-1561.2005.00038.x

Modeling Change of Water Content in Wood at Atmospheric Drying Maria Zaitseva(B)

, Julia Nikonova(B)

, and Gennady Kolesnikov

Petrozavodsk State University, 33 Lenin Ave., Petrozavodsk, Resp. Karelia 185035, Russia [email protected], [email protected], [email protected]

Abstract. Objective: to develop a methodology for predicting changes in the water content in wood during atmospheric drying, taking into account the fast and slow stages of this process. Research methods: mathematical modeling, applied analysis of results, comparison with experimental data known from the literature, synthesis in order to better understand the regularities of drying. Results: a twoparameter model is developed, in which a phenomenological approach is used, focused on obtaining averaged estimates of wood moisture during atmospheric drying. Causal relationships are not detailed, but are taken into account in an integral form. Calculation formulas are obtained, the use of which simplifies the procedure for predicting changes in the water content in wood during atmospheric drying. The adequacy of the model and the reliability of the calculation results are confirmed by their consistency with the experimental data known in the literature. Research prospects can be focused on adapting the model to other drying methods in order to reduce the energy and time spent on a given technological process. Keywords: Wood · Drying rate · Drying time

1 Introduction Drying of wood is a necessary link in the technology of its further use. There are many drying methods, of which atmospheric drying is the least energy intensive and, at the same time, the longest. The duration of atmospheric drying depends on a number of conditions and can be, for example, 24 weeks [1]. In this regard, there is a problem of predicting changes in wood moisture during atmospheric drying. It should be noted that this problem is relevant not only for improving the technology of wood drying at the stage of its preparation for further use. Obviously, in the regime of atmospheric drying, roof trusses and other supporting and enclosing structures of wooden buildings function. Regularities of changes in wood moisture in such structures are necessary, first of all, for specialists in the field of protection of unique monuments of wooden architecture [2, 3]. Theoretical aspects directly related to the problem of drying, including atmospheric drying, taking into account the effect of equilibrium moisture of wood as a capillaryporous material, are most fully presented in the monograph [4]; applied issues are considered, for example, in articles [5, 6]. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 631–637, 2021. https://doi.org/10.1007/978-3-030-57453-6_60

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A one-parameter model of wood drying was proposed in [7], which, however, did not take into account the influence of the fast and slow drying stages (although the fast and slow stages of moisture transfer were taken into account when impregnated). The adequacy of the results obtained in this work indicates the practical feasibility of developing a drying model taking into account the fast and slow stages of moisture transfer. Such an improvement, from a physical point of view, is objectively due to differences in the regularities of transfer of free and bound moisture in wood [8]. Thus, in order to get a more complete understanding of the drying process of wood, it is advisable to develop a two-parameter model, which takes into account the two above stages of the process under consideration. We will develop a two-parameter model based on the logic of inductive conclusions, based on the analysis of particular premises and their mutual influence within the framework of a generalized mathematical model. In other words, we are transforming a one-parameter model of wood drying [7] into a two-parameter model.

2 One-Parameter Model of Wood Drying It is known that the relative moisture of wood Cb1 , depending on the initial moisture Cb0 and the drying time t, can be determined using the formulas [7]: Cb1 = Cb =

Cb0 (Cb + 0.01) Cb0 + 0.01 e−ϑ −1 Cb0

+ e−ϑ − 1

ϑ=

t τ

(1) (2) (3)

Here τ is the model parameter, measured in units of time. From a formal point of view, the parameter τ is necessary to write relation (2) in a dimensionless form. The physical (technological) meaning of this parameter is discussed below. The relative moisture of the wood was determined by us, by analogy with [5], as the ratio Cb1 =

mass of water in wood mass of water in wood + mass of dry wood

(4)

The conversion of relative moisture to absolute moisture, equal to the ratio of the mass of water in wood to the mass of dry wood, can be performed according to well-known formulas [4]. The value of the function Cb (Cb0 ) (1), which corresponds to specific values of τ and ϑ, depends on the initial moisture Cb0 , however, the initial moisture, in turn, depends on the species and age of the wood, storage conditions, and a number of other factors. For example, with decreasing atmospheric moisture and with increasing temperature, the drying rate increases, which is modeled by a decrease in parameter τ. Given these circumstances, parameter τ can be called a technological parameter. If the initial relative

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Fig. 1. Graph of the Cb (Cb0 ) function.

moisture of the wood does not exceed 0.5 (which corresponds to an absolute moisture of 100%), then we can assume that the parameter τ is equal to the times t, during which the initial moisture of the wood decreases approximately by half (see Fig. 1). To determine the value of τ, we perform an experiment on drying the sample, reducing its relative moisture, for example, from Cb0 = 0.38 to Cb1 = 0.19. We experimentally determine the time t for the implementation of this process. Substituting the measurement results of Cb1 and t in (1), we obtain the equation from which we find τ. Parameter τ is measured in units of time. In this experiment, τ = t. Then ϑ = 1, Cb =

e−1 −1 Cb0 + e−1 − 1

(5)

The graph of the function Cb (Cb0 ) is shown in Fig. 1. The rate of the drying process decreases monotonically over time. The dependence of rate on time is determined by analogy with [7], differentiating relation (1) with respect

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to time t. After the transformations we get:    dCb1  Cb0 Cb (1 − Cb ) = |Vd | =  dt  τ(Cb0 + 0.01)

(6)

In relation (6), the speed modulus was used to visually reflect the tendency for a decrease in the drying rate with an increase in the duration of this process. This question is considered in more detail below, using the two-parameter model as an example (see Fig. 3).

3 Two-Parameter Model of Wood Drying Consider a model with weight coefficients, constructed taking into account the fast and slow stages of moisture transfer. Summarizing relation (2), we write the equation for determining the relative moisture in the following form: Cb2 = w1

e−ϑ1 −1 Cb0

+ e−ϑ1 − 1

+ w2

e−ϑ2 −1 Cb0

+ e−ϑ2 − 1

(7)

Here, where ϑ1 = t/τ1 , ϑ2 = t/τ2 . The adjusted value of relative moisture, by analogy with (1), we find by the formula Cb3 =

Cb0 (Cb2 + 0.01) Cb0 + 0.01

(8)

The indices 1 and 2 at ϑ and τ relate, respectively, to the above two stages of drying (fast and slow). The model parameters τ1 , τ2 and weights w1 , w2 = 1 − w1 are determined experimentally. To minimize the volume and duration of the experiments, it is advisable to focus on the fast drying stage using the relations t = τ1 , ϑ2 /ϑ1 = τ1 /τ2 = t/τ2 . Substituting these relations into formula (7), we obtain an equation from which τ2 can be found, if w1 is previously assigned, w2 = 1 − w1 is calculated, and Cb2 and t = τ1 are determined from the experiment. To clarify the obtained value of τ2 , formula (8) is used. The value of Cb0 is assumed to be known. A more detailed consideration of the issue raised is beyond the scope of this paper. To get a clearer understanding of the prospects for further research, we consider the application of the above formulas to the analysis of experiment of the atmospheric summer drying of wood with the initial relative moisture Cb0 = 0.54, i.e. 54%, known from the literature [1]. Using the weight coefficients w1 = 0.45 and w2 = 0.55 in formula (7), we obtain for the three options τ1 and τ2 the numerical results shown in Fig. 2. We determine the rate of the drying process by differentiating relation (6) with respect to time. In this case, sufficient accuracy provides numerical differentiation:    Cb3    (9) Vd ≈  t  In relation (9), as in (6), the absolute value of rate was used to visually reflect the regularity of a decrease in the drying rate with an increase in the drying time; Cb3 = Cb3,i+1 − Cb3,i ; t = ti+1 − ti ; i = 0..23. Figure 3 shows the results of calculations by formula (9) if t is equal to one week (for the same initial data as in Fig. 2).

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Fig. 2. Calculated wood moisture during atmospheric drying (summer, 24 weeks).

Fig. 3. Change in the rate of decrease in wood moisture.

4 Discussion and Conclusion The modeling results (Fig. 3) show that in the interval 0 < t < 10 weeks, the drying rate decreases rapidly. This means that the initial stage of drying is most effective according to the criterion of energy consumption per unit mass of water removed from the wood. In the interval 10 ≤ t ≤ 15 weeks, there is a point at which the drying rate is almost independent of the drying parameters. If 15 < t < 24 weeks, then the rate decreases, but very slowly; this stage is the least efficient according to the criterion of energy consumption and drying time.

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The modeling results (Figs. 2 and 3) do not contradict the experimental data known from [1, p. 5]. In addition, the drying rate trends predicted by formula (7) (Fig. 3) do not generally contradict the experimental data from [9, p. 2001, Fig. 2, c]. Using the proposed approach (in other words, taking into account relations (1)–(7)), modeling of drying features in other conditions can be performed. For example, a modeling of the known [9] experimental dependences of the rate of moisture removal on time at the temperature of the drying agent can be performed. The realism of this assumption is justified by the fact that the dimensionless variables ϑ1 = t/τ1 and ϑ2 = t/τ2 indicated above (formula (5)) relate, respectively, to the above two stages of drying (fast and slow). Indeed, with increasing temperature, the drying rate increases, which is modeled by a decrease in the parameter τ in formula (2) or a decrease in the parameters τ1 and τ2 in formula (5). Summarizing, we note as a conclusion the following. 1. A method for predicting changes in the water content in wood during atmospheric drying is proposed. The method was built using mathematical modeling, applied analysis of results and comparison with experimental data known from the literature, in other words, the approach used for system analysis, including synthesis and analysis, was used to better understand the regularities of drying. 2. As a tool for applied analysis, a model is proposed in which a phenomenological approach is used when choosing an empirical formula, focused on obtaining averaged moisture estimates taking into account the fast and slow stages of drying. 3. The adequacy of the model and the reliability of the calculation results are confirmed by their consistency with the experimental data known in the literature. 4. The practical significance of the considered method lies in the possibility of its use for predicting changes in wood moisture during drying, depending on the values of technological parameters and weight coefficients. 5. Research prospects can be focused on adapting the model to other drying methods in order to reduce the energy and time spent on a given technological process.

References 1. Visser, R., Berkett, H., Spinelli, R.: Determining the effect of storage conditions on the natural drying of radiata pine logs for energy use. NZ J. Forest. Sci. 44(3), 1–8 (2014). https://doi.org/ 10.1186/1179-5395-44-3 2. Kozlov, V., Kisternaya, M.: Biodeterioration of historic timber structures: a comparative analysis. Wood Mat. Sci. Eng. 9(3), 156–161 (2014). https://doi.org/10.1080/17480272.2014. 894573 3. Bertolin, C., de Ferri, L., Grottesi, G., Strojecki, M.: Study on the conservation state of wooden historical structures by means of acoustic attenuation and vacuum microbalance. Wood Sci. Technol. 54(1), 203–226 (2019). https://doi.org/10.1007/s00226-019-01150-8 4. Patyakin, V.I., Tishin, Yu.G., Bazarov, S.M.: Technical Hydrodynamics of Wood. Lesnaya Promyshlennost, Moscow (1990) 5. Kizha, A.R., Han, H.S.: Moisture content in forest residues: an insight on sampling methods and procedures. Curr. For. Rep. 3(3), 202–212 (2017). https://doi.org/10.1007/s40725-0170060-5

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6. Berner, M.O., Scherer, V., Mönnigmann, M.: Controllability analysis and optimal control of biomass drying with reduced order models. J. Process Control 89, 1–10 (2020). https://doi.org/ 10.1016/j.jprocont.2020.03.002 7. Kantyshev, A.V., Zaitseva, M.I., Kolesnikov, G.N.: Model of wood impregnation after incomplete drying as an additional energy management tool. J. Phys. Conf. Ser. 1333(3), 032033 (2019). https://doi.org/10.1088/1742-6596/1333/3/032033 8. Vrublevskaya, V.I., Matusevich, V.O., Kuznetsova, V.V.: Substantiation of the interaction mechanism of wood components and water. Lesnoy Zhurnal (Russ. For. J.) 357(3), 152–163 (2017). https://doi.org/10.17238/issn0536-1036.2017.3.152 9. Nigay, N.A., Kuznetsov, G.V., Syrodoy, S.V., Gutareva, N.Y.: Estimation of energy consumption for drying of forest combustible materials during their preparation for incineration in the furnaces of steam and hot water boilers. Energy Sources Part A Recovery Util. Environ. Eff. 42(16), 1997–2005 (2020). https://doi.org/10.1080/15567036.2019.1604910

Study of Aerosol Motion in Granular and Foam Filters with Equal Porosity of the Structure Olga Soloveva(B) Kazan State Power Engineering University, Krasnoselskaja str., 51, Kazan 420066, Russia [email protected]

Abstract. This paper consider a comparison of granular and open cell foam filters based on the models of filters with different sizes of granules and cells. For all models, the porosity parameter of the medium remained fixed (ε = 0.44). Due to the random location of the cells to eliminate errors, the calculation results for each sample were averaged over the calculations of five different geometries with the same parameters. The results of numerical calculations are in a good agreement with the experimental data of the pressure drop value in the filters. It was found that open cell foam material shows the maximum pressure drop, and the efficiency of particle deposition in the model of open cell foam filter is higher in comparison with the model of granular filter. The largest cell size provides the maximum value of the filter quality factor in the case of open cell foam material, the reverse pattern is observed in the case of granular filter. Keywords: Filtration · Efficiency · Porosity · Quality factor

1 Introduction Filtration today plays an important role both in industry and in life [1, 2]. For fine cleaning, the most common are fibrous, open cell foam, membrane and wicker filters. Fiber filters are widely used due to the high particle deposition efficiency, but create a large pressure drop due to fast clogging, which is accompanied by cleaning or replacement costs. Granular filters are also a fairly common type, since they have a low manufacturing cost and low environmental resistance [3]. Such filters are used in wastewater and drinking water treatment [4, 5]. Granular filters are used in industry for filtering various gases, where the use of a different type of filters seems impossible due to high temperatures or the presence of chemical active components in the filtered substance [6]. In chemical production, a granular filter is preferred due to its high heat resistance, corrosion resistance, and low cost of filter material [7, 8]. Granular filters are divided into several types: with a fixed, moving and fluidized bed. Filtration here includes various mechanisms, such as particle capture, inertial deposition, diffusion, gravitational and electrostatic attraction [9]. The most widely used are fixed-bed filters.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 638–649, 2021. https://doi.org/10.1007/978-3-030-57453-6_61

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A lot of factors can influence the filtration efficiency; pressure drop, flow rate, size, shape and packing method of granules make the greatest contribution to particle deposition [10–16]. Some studies suggest a new type of granular filter arrangement that uses two layers of granules of different sizes. With such a system, the filtered medium first enters the layer with large granules, which cannot catch small particles, but at the same time has a low pressure drop. After this the filtered medium gets to a layer consisting of small granules, which effectively capture small particles [17, 18]. A possible replacement for granular filters are open cell foam filters. The open cell foam material consists of intersecting cells distributed randomly in the volume. The main parameters that determine the geometry of these media are the diameter of the cells and the distance between them. High porosity provides a low pressure drop and good medium strength. Porous media also have a developed surface area, which is a great advantage when using open cell foam material as a matrix for the deposition of various chemical catalysts. For example, polyurethane porous media can be used to remove heavy metal ions, for example, lead from water [19–21]. Since it is possible to set and adjust the size and shape of the pores, it is possible to obtain open cell foam material with such parameters as are necessary for a particular task [22–24]. Porous structures are used in the automotive and aerospace industries, as they have high strength with respect to their weight [25]. Porous media can be used in microelectronics, where it is not possible to make large radiators for heat removal [26]. Studies of the flow of liquids and gases through porous media have intensified in the last 30 years. Until recently, there were several flow models in porous media. Darcy’s law, according to which the pressure drop per unit length is proportional to the product of the fluid velocity and dynamic viscosity and inversely proportional to permeability [27]. The following model shows the dependence of permeability on the square of the cell diameter [28]. Another flow model tells us that permeability is a function of the area of the largest hole in the cell [29]. There are almost as many motion models as the studies themselves, but the development of technological progress helps us to improve the methods of study. Today, the most accurate research method can be called direct numerical simulation. All laws and models described earlier do not take into account all the features of geometry and give approximate data. Numerical modeling takes into account all the features of geometry and the Navier-Stokes equations are solved for each step of the calculation. The main difficulty in numerical calculations is the creation of a reliable geometric model of the fluid or gas flow region; in some studies, the creation of a porous medium is based on a set of rectangular prisms [30]; in others, researchers resorted to using an ordered model, which is a set of tetracaidecahedrons in which a cell was generated [31]. There is also a method of magnetic resonance imaging (MRI) or computed tomography to study the flow of fluid inside a porous medium [32–34]. Granular and open cell foam filters are the most promising at the moment. Evaluation of the quality parameter can answer the question of which filter to use more preferably depending on the specific technological cycle.

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2 Problem Formulation The choice of filter depends on the parameters of the technological cycle. An increase in the efficiency of particle deposition is usually accompanied by an increase in the resistance of the medium. To compare the models of granular and open cell foam filters, the medium porosity parameter ε = 0.44 was recorded. Since it is not possible to change the porosity of a granular filter, models of open cell foam filters with the same porosity as those of a granular filter were created. The geometries of the created filters are shown in Fig. 1, and filter parameters can be seen in Table 1.

Fig. 1. Models of granular (a) and open cell foam (b) filters.

The geometries of the computational domain are shown in Fig. 2. Models are the inverse filter matrix with nozzles attached at both ends. Thickness of the filter part, length of the nozzles and diameter of the entire tube are 40 mm each.

Fig. 2. The geometry of the computational domain of granular (a) and open cell foam (b) filters.

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Table 1. Filter parameters for ε = 0.44. Filter

Cell size of porous medium d c , mm

Granular – 1

4

Granular – 2

5

Granular – 3

6

Open cell foam – 1

4

Open cell foam – 2

5

Open cell foam – 3

6

700

9.082

800

10.379

900

11.676

1000

12.97

Fig. 3. Tubes with open cell foam material used for the experiment.

To verify the accuracy of the numerical calculation, experimental studies of the gas flow in granular and open cell foam material were carried out. The granular filter for the experiment was a flask with glass balls, a model of an open cell foam filter was printed on a 3D printer as the inverse matrix of a computer model of a porous medium (Fig. 3).

3 Results The hydrodynamic calculation carried out in the ANSYS Fluent software package (v. 19.0) based on the solution of the Navier-Stokes equations by the finite element method shows that an open cell foam filter with the porosity of 0.44 equal to the porosity in a granular filter model has a higher hydrodynamic resistance. A sharp increase in pressure drop is associated with the complex structure of an open cell foam material (Fig. 4).

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The change in the particle deposition efficiency for the case of an open cell foam filter depending on the particle diameter for three cell sizes is shown in Fig. 5. The minimum cell size allows us to achieve the maximum value of the particle deposition efficiency while maintaining the porosity of the medium. The geometry of a porous medium with a random arrangement of cells in space introduces a change in the gas flow field and the particle trajectory.

Fig. 4. The change in pressure drop depending on the average flow rate: 1 – numerical calculation for the model of a granular filter, 2 – numerical calculation for the model of an open cell foam filter, 3 – experimental data for the case of a granular filter, 4 – experimental data for the case of an open cell foam filter.

Figure 5 (a) shows the averaged values of efficiency over three geometries of porous media. In the case of a granular filter, the scatter in the values of the particle deposition efficiency for granules of different sizes is not so significant. The particle deposition efficiency in the granular filter in Fig. 5 (b) is also represented by averaged values. From Fig. 5 (a) and (b), it can be concluded that the granule size in the granular filter does not significantly contribute to the change in the deposition efficiency, while in the case of an open cell foam filter, the cell size can be selected with the desired efficiency and pressure drop.

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1.00 0.95

E

0.90

open cell foam filter 1 2 3

0.85 0.80 0.75 0.70 0.0000000

0.0000005

0.0000010

0.0000015

0.0000020

dp, m

a 1.0

E

granular filter

0.8

1 2 3

0.6

0.4

0.2 0.000000

0.000005

0.000010

0.000015

0.000020

dp, m

b Fig. 5. Efficiency of particle deposition for the case of open cell foam filter (a) and granular filter (b) and fixed porosity (ε = 0.44) depending on the particle diameter with three characteristic sizes of cells of porous structure dc, mm: 1–4, 2–5, 3–6.

Figure 6 demonstrates the dependence of the pressure drop on the size of granules and cells in the filter model. The pressure drop in the granular filter changes insignificantly, in an open cell foam filter it changes non-linearly and decreases with increasing pore size.

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9000 8000

1 2

7000

p, Pa

6000 5000 4000 3000 2000 1000 0

4.0

4.5

5.0

5.5

6.0

dc, m Fig. 6. The change in the value of the pressure drop depending on the size of the granules and cells: 1 – open cell foam filter, 2 – granular filter.

An important characteristic in filtration is the filter quality factor, which is defined as the ratio of the particle deposition efficiency to the pressure drop. Figure 7 (a) shows that the quality factor is determined by the particle deposition efficiency for the case of a granular filter and takes the maximum value for filter models with granule sizes dc = 4 mm and dc = 5 mm. With the increase in granule size, the filter quality factor decreases significantly. The opposite picture is observed in the case of open cell foam material (Fig. 7 (b)). The largest cell size provides the highest filter quality factor, since in this case the resistance of the medium becomes decisive.

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0.012 granular filter

0.010

Qf

1 2 3

0.008 0.006 0.004 0.002 0.000 0.000000

0.000005

a

0.000010

0.000015

0.000020

dp, m

0.00022 0.00020

Qf

open cell foam filter

0.00018

1 2 3

0.00016 0.00014 0.00012 0.00010 0.0000000

0.0000005

0.0000010

0.0000015

0.0000020

dp, m

b Fig. 7. Change in the quality factor of a granular filter (a) and open cell foam filter (b) depending on the particle size for three cases of cell diameter dc, mm: 1–4, 2–5, 3–6.

Figure 8 shows particle trajectories for a granular and foam filter. With equal particle sizes dp = 0.1 μm and a flow velocity of 2 m/s, the efficiency of particle deposition in an open cell foam filter is higher than for a granular filter (80% of settled particles for a foam filter and 32% of settled particles for a granular filter).

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Fig. 8. Trajectories of motion of particles of the same size dp = 0.1 μm: a – granular filter, b – open cell foam filter.

4 Conclusion In this work, we studied the change in pressure drop, particle deposition efficiency, and filter quality factor for two models of a porous medium: a granular and foam filter. Parametric calculations were carried out at a fixed porosity of the models for three different cell diameters (granules). The calculation results are averaged over five geometries for each model. Experimental studies of the gas flow in a porous medium were carried out to verify the calculation. The calculation results showed that for the case of a granular filter, a change in the size of the granules introduces a slight change in the value of the particle deposition efficiency. For an open cell foam filter, the diameter of the cell is critical. The quality factor of a granular filter takes maximum values for the diameter of granules dc = 4 mm and dc = 5 mm, in a foam filter, the maximum is observed at a cell diameter dc = 6 mm. Studies of hydrodynamics in two filter models allow to conclude that in the case where an increase in the differential pressure of the medium is expensive and critical in production, preference should be given to granular filters. For technological processes in which a high degree of purification is required, open cell foam filters with a small cell diameter should be used.

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Acknowledgments. This work is supported by the Russian Science Foundation under grant № 19-71-00100.

References 1. Jaeger, H.M., Nagel, S.R., Behringer, R.P.: Granular solids, liquids, and gases. Rev. Mod. Phys. 68, 1259 (1996). https://doi.org/10.1103/revmodphys.68.1259 2. Cai, J., Dong, H., Fu, W.: Study on particle flow in shaft moving beds. J. Northeast. Univ. Nat. Sci. 28, 1599 (2007) 3. Tien, C., Ramarao, B.V.: Macroscopic description of fixed-bed granular filtration. In: Brenner, H. (ed.) Granular Filtration of Aerosols and Hydrosols. Butterworth Series in Chemical Engineering, Boston, MA, pp. 17–45 (1989). https://doi.org/10.1016/b978-1-85617-458-9. x5000-3 4. El-Hedok, I.A., Whitmer, L., Brown, R.C.: The influence of granular flow rate on the performance of a moving bed granular filter. Powder Technol. 214, 69–76 (2011). https://doi.org/ 10.1016/j.powtec.2011.07.037 5. Altmann, J., Rehfeld, D., Träder, K., Sperlich, A., Jekel, M.: Combination of granular activated carbon adsorption and deep-bed filtration as a single advanced wastewater treatment step for organic micropollutant and phosphorus removal. Water Res. 92, 131–139 (2016). https://doi. org/10.1016/j.watres.2016.01.051 6. Hsu, C.J., Hsiau, S.S.: A study of filtration performance in a cross-flow moving granular bed filter: the influence of gas flow uniformity. Powder Technol. 274, 20–27 (2015). https://doi. org/10.1016/j.powtec.2015.01.006 7. Hsu, C.J., Hsiau, S.S., Chen, Y.S., Smid, J.: Investigation of the gas inlet velocity distribution in a fixed granular bed filter. Adv. Powder Technol. 21, 614–622 (2010). https://doi.org/10. 1016/j.apt.2010.04.001 8. Xiao, G., Wang, X., Zhang, J., Ni, M., Gao, X., Luo, Z., Cen, K.: Granular bed filter: a promising technology for hot gas clean-up. Powder Technol. 244, 93–99 (2013). https://doi. org/10.1016/j.powtec.2013.04.003 9. Smolders, K., Baeyens, J.: Elutriation of fines from gas fluidized beds: mechanisms of elutriation and effect of freeboard geometry. Powder Technol. 92, 35–46 (1997). https://doi.org/ 10.1016/s0032-5910(97)03214-2 10. Çarpinlio˘glu, M.Ö., Özahi, E.: A simplified correlation for fixed bed pressure drop. Powder Technol. 187, 94–101 (2008). https://doi.org/10.1016/j.powtec.2008.01.027 11. Kuo, Y.M., Huang, S.H., Lin, W.Y., Hsiao, M.F., Chen, C.C.: Filtration and loading characteristics of granular bed filters. J. Aerosol Sci. 41, 223–229 (2010). https://doi.org/10.1016/j. jaerosci.2009.09.011 12. Solovev, S.A., Soloveva, O.V., Popkova, O.S.: Numerical simulation of the motion of aerosol particles in open cell foam materials. Russ. J. Phys. Chem. 92, 601–604 (2018). https://doi. org/10.1134/s0036024418030275 13. Choi, J.H., Choi, K.B., Kim, P., Shun, D.W., Kim, S.D.: The effect of temperature on particle entrainment rate in a gas fluidized bed. Powder Technol. 92, 127–133 (1997). https://doi.org/ 10.1016/s0032-5910(97)03225-7 14. Wey, M.Y., Chen, K.H., Liu, K.Y.: The effect of ash and filter media characteristics on particle filtration efficiency in fluidized bed. J. Hazard. Mater. 121, 175–181 (2005). https://doi.org/ 10.1016/j.jhazmat.2005.02.005 15. Liu, K.Y., Wey, M.Y.: Filtration of nano-particles by a gas–solid fluidized bed. J. Hazard. Mater. 147, 618–624 (2007). https://doi.org/10.1016/j.jhazmat.2007.01.058

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16. Soloveva, O.V., Solovev, S.A., Khusainov, R.R.: Evaluation of the efficiency of prefilter models using numerical simulation. J. Phys. Conf. Ser. 1399, 022059 (2019). https://doi.org/ 10.1088/1742-6596/1399/2/022059 17. Soloveva, O.V., Solovev, S.A., Khusainov, R.R., Shubina, A.S.: Investigation of the effect of material’s cell size with the fixed porosity on the efficiency of aerosol particle deposition. J. Phys. Conf. Ser. 1158, 042023 (2019). https://doi.org/10.1088/1742-6596/1158/4/042023 18. Soloveva, O.V., Solovev S.A., Khusainov R.R.: Evaluation of the efficiency of prefilter models using numerical simulation. J. Phys. Conf. Ser. 1399, 022059 (2019). https://doi.org/10. 1088/1742-6596/1399/2/022059 19. Paenpong, C., Pattiya, A.: Filtration of fast pyrolysis char fines with a cross-flow moving-bed granular filter. Powder Technol. 245, 233–240 (2013). https://doi.org/10.1016/j.powtec.2013. 04.044 20. Yang, G., Zhou, J.: Experimental study on a new dual-layer granular bed filter for removing particulates. J. China Univ. Min. Technol. 17, 201–204 (2007). https://doi.org/10.1016/s10061266(07)60072-8 21. McBrayer, R.L., Wysocki, D.C.: Polyurethane Foams Formulation and Manufacture. Program Division, Technomic Publishing Company, Incorporated (1998) 22. Gunashekar, S., Abu-Zahra, N.: Characterization of functionalized polyurethane foam for lead ion removal from water. Int. J. Polym. Sci. 2014, 7 (2014). https://doi.org/10.1155/2014/ 570309 23. Merentsov, N.A., Balashov, V.A., Bokhan, S.A., Nefed’eva, E.E., Tezikov, D.A., Groshev, V.V.: Modeling and calculation of flow filter. IOP Conf. Ser. Earth Environ. Sci. 224, 012041 (2019). https://doi.org/10.1088/1755-1315/224/1/012041 24. Gu, D., Schüth, F.: Synthesis of non-siliceous mesoporous oxides. Chem. Soc. Rev. 43, 313– 344 (2014). https://doi.org/10.1039/c3cs60155b 25. Ariga, K., Vinu, A., Yamauchi, Y., Ji, Q., Hill, J.P.: Nanoarchitectonics for mesoporous materials. Bull. Chem. Soc. Jpn 85, 1–32 (2011). https://doi.org/10.1246/bcsj.20110162 26. Li, W., Wu, Z., Wang, J., Elzatahry, A.A., Zhao, D.: A perspective on mesoporous TiO2 materials. Chem. Mater. 26, 287–298 (2013). https://doi.org/10.1021/cm4014859 27. Hwang, J.J., Hwang, G.J., Yeh, R.H., Chao, C.H.: Measurement of interstitial convective heat transfer and frictional drag for flow across metal foams. J. Heat Trans. 124, 120–129 (2002). https://doi.org/10.1115/1.1416690 28. Boomsma, K., Poulikakos, D., Zwick, F.: Metal foams as compact high performance heat exchangers. Mech. Mater. 35, 1161–1176 (2003). https://doi.org/10.1016/j.mechmat.2003. 02.001 29. Boomsma, K., Poulikakos, D.: The effects of compression and pore size variations on the liquid flow characteristics in metal foams. J. Fluids Eng. 124, 263–272 (2002). https://doi. org/10.1115/1.1429637 30. Hilyard, N.C., Collier, P.: A structural model for air flow in flexible PUR foams. Cell. Polym. 6, 9–26 (1987) 31. Mills, N.J.: The wet Kelvin model for air flow through open-cell polyurethane foams. J. Mater. Sci. 40, 5845–5851 (2005) 32. Du Plessis, P., Montillet, A., Comiti, J., Legrand, J.: Pressure drop prediction for flow through high porosity metallic foams. Chem. Eng. Sci. 49, 3545–3553 (1994). https://doi.org/10.1016/ 0009-2509(94)00170-7 33. Boomsma, K., Poulikakos, D., Ventikos, Y.: Simulations of flow through open cell metal foams using an idealized periodic cell structure. Int. J. Heat Fluid Flow 24, 825–834 (2003). https://doi.org/10.1016/j.ijheatfluidflow.2003.08.002

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34. Hoferer, J., Lehmann, M.J., Hardy, E.H., Meyer, J., Kasper, G.: Highly resolved determination of structure and particle deposition in fibrous filters by MRI. Chem. Eng. Technol. 29, 816– 819 (2006). https://doi.org/10.1002/ceat.200600047. Industrial Chemistry-Plant EquipmentProcess Engineering-Biotechnology 35. Lehmann, M.J., Hardy, E.H., Meyer, J., Kasper, G.: MRI as a key tool for understanding and modeling the filtration kinetics of fibrous media. Magn. Reson. Imaging 23, 341–342 (2005). https://doi.org/10.1016/j.mri.2004.11.048 36. Charvet, A., Du Roscoat, S.R., Peralba, M., Bloch, J.F., Gonthier, Y.: Contribution of synchrotron X-ray holotomography to the understanding of liquid distribution in a medium during liquid aerosol filtration. Chem. Eng. Sci. 66, 624–631 (2011). https://doi.org/10.1016/j.ces. 2010.11.008

Estimation of Portland Cement Reduction Using Polycarboxylate Based Admixture Liliya Kazanskaya(B) Emperor Alexander I, St. Petersburg State Transport University, Moskovskij, 9, 190031 Saint-Petersburg, Russia [email protected]

Abstract. Influence of the mineralogical composition of Portland cement on the water-reducing effect of polycarboxylate based admixture is shown in the paper. It is shown that the value of reduction of Portland cement quantity due to reduction of mixing water significantly depends on the mineralogical composition of Portland cement of the same strength class. It is shown that the influence of the mineralogical composition can be reduced by introducing water in two steps. Polycarboxylate based admixture must be entered with the second portion of the mixing water. It is stated that such a double-batch with water and admixture allows obtaining significant savings of Portland cement per 1 kg of admixture in concrete based on Portland cement with high amount of C3 A and R2 O. The results of quantity reduction of Portland cement of CEM42.5I strength class per 1 kg of the polycarboxylate based admixture depending on the way of admixture introduction were obtained on the basis of experimental data using 14 mixtures. Keywords: Portland cement · Polycarboxylate based admixture · Superplasticizer · Cement quantity reduction

1 Introduction Use of concrete compositions with low Portland cement quantity per 1 MPa of strength is an important issue meanwhile it is necessary to ensure the production of concrete with the required technical characteristics [1–4]. There are various technological techniques to reduce the Portland cement quantity and maintain or improve the technical properties of concrete [5, 6]. Modern technological techniques are aimed to obtain multi-component concretes [7–11]. One of the important components of concrete is the polycarboxylate based admixture (superplasticizer). The superplasticizer can also be called water-reducing admixture if it is used to reduce water quantity in fresh concrete. However, the problem of compatibility of superplasticizer and cement must be taken into account when preparing high-performance concrete. Reduction of the plasticizing (or water-reducing) effect of superplasticizer in some fresh concrete mixtures is understood as the compatibility problem [1, 12]. This study aims to assess the reduction of Ordinary Portland cements that is used widely. Assessment of water-reducing effect of polycarboxylate superplasticizer and © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 650–660, 2021. https://doi.org/10.1007/978-3-030-57453-6_62

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assessment of Portland cement reduction per 1 kg of superplasticizer are the objectives of the study. It is necessary to state the conditions when superplasticizer provides significant Portland cement savings. The following main tasks of the study can be formulated on the basis of the review of published results. Influence of the mineralogical composition of Portland cement on the water-reducing effect of polycarboxylate based admixture must be studied. The value of reduction of Portland cement quantity due to reduction of mixing water depending on the mineralogical composition of Portland cement of the same strength class is necessary to estimate. The procedure for the introduction of superplasticizer to reduce the amount of water should be determined. The results of quantity reduction of Portland cement of CEM42.5I strength class per 1 kg of the polycarboxylate based admixture depending on the way of admixture introduction and mineralogical composition of Portland cement will be obtained on the basis of experimental data using 14 mixtures. Thus, the comparison of the properties of two of CEM42.5I strength class will be carried out to determine the reduction of Portland cement amount and method for determining the effectiveness of the superplasticizer will be proposed.

2 Related Research Review Polycarboxylate-based superplasticizers are used to produce modern types of concrete. It is possible to highlight the following problems that are solved through the superplasticizer introduction: increase of workability of fresh concrete [1, 12–16], increase of early and normative strengths [1, 17–20], reduction of cement quantity [21–24], increase of the rheological activity of mineral additives [25–29], improvement of fibers distribution in the concrete structure [3, 30–32]. The dependence of the plasticizing effect of polycarboxylate admixture on the cement composition can be occur not only in the rapid loss of workability but also in the phenomenon of “re-liquefaction” when the workability of fresh concrete does not decrease over time, but, on the contrary, increases [9, 25]. The manifestation of this effect often occurs in fresh concrete with high workability and leads to the segregation of the mixture during transportation or in zero slump fresh concrete and leads to the fast solidification of fresh mixture. Deterioration of workability of fresh concrete leads to the discontinuity of structure of hardened concrete and to the reduction of its technical properties, primarily compressive strength. Compatibility of polycarboxylate superplasticizers and Portland cement was considered in the literature [17, 33–35]. High values of plasticizing or water-reducing effect of superplasticizer without reducing the concrete strength in the required time of hardening should be understood as good compatibility of superplasticizer and cement. For example, the high strength of concrete at the age of 12-24 h is necessary for precast structures and this should be taken into account when assessing the compatibility of superplasticizer and cement [1, 14]. The appearance of undesirable effects such as rapid setting of fresh concrete mixture or, conversely, its re-liquefaction with the introduction of water-reducing admixtures

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based on polycarboxylate is associated with the influence of chemical and mineralogical compositions of cements since the admixtures themselves have a constant chemical composition [14, 29, 34, 35]. Influence of tricalcium aluminate quantity on the water-reducing effect of superplasticizer as well as the influence of the alkali metal oxides is stated in paper [14, 33]. For example, it is shown that Portland cement should have the reduced amount of C3 A that should be no more than 6.3% and the alkaline oxides (R2 O) should be no more than 0.79% in order to ensure compatibility cement with superplasticizer. As compatibility the author of the paper [33] means obtaining high water-reducing effect of superplasticizer in zero slump fresh concrete with a low water-to-cement ratio that is used for responsible transport constructions. Other factors that determine the insufficient reduction of water demand of fresh concrete with the introduction of polycarboxylate modifiers exist in addition to the content of C3 A. One of which is the content of alkali metals. Recently, an increase of the content of alkali metals in cements is observed due to the decrease in irretrievable kiln dust removal from furnaces and improvement of the efficiency of dust collection devices. Kiln dust captured from the flue gases of the furnaces contains an average of 4–7 times more alkali metals compared to clinker [5]. The dust returned to the furnace increases the content of alkali metals in the clinker which can affect the properties of fresh concrete. It should be noted that regulatory documents in transport construction strictly regulate the C3 A amount up to 7% and R2 O up to 0.8% in Portland cement. Polycarboxylate superplasticizers have high water reducing with Portland cement of the normalized quantity of C3 A and R2 O. However, the study of the possible water reduction when using polycarboxylate superplasticizers with ordinary Portland cement where the C3 A and R2 O may vary within wide ranges is contemporary task. Significant reduction in water demand can be used in order to reduce Portland cement quantity. Published data on influence of properties of ordinary Portland cement so as to reduce its amount per 1m3 in equally-strong concretes through the use of superplasticizers is not enough. However, reducing the Portland cement consumption is an important task to decrease the construction cost and develop green concrete technologies [36–40]. This study aims to assess the reduction of Ordinary Portland cements that is used widely. Assessment of water-reducing effect of polycarboxylate superplasticizer and assessment of Portland cement reduction per 1 kg of superplasticizer are the objectives of the study. It is necessary to state the conditions when superplasticizer provides significant Portland cement savings. Additional knowledge is needed on the mutual influence of Portland cement and superplasticizers on the properties of fresh concrete, hardening processes and physical and technical properties of concrete for the effective use of these admixtures in the production of concrete and reinforced concrete.

3 Materials and Methods for Proposed Work Reducing the water demand in fresh concretes of equal workability is one of the ways to increase the concrete strength. Therefore, experimental studies have been conducted

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to estimate the influence of the mineralogical composition of Portland cement on the water-reducing effect of admixture. Based on the above, two Portland cements were chosen for the study. The mineralogical compositions of cements are presented in Table 1. Table 1. Mineralogical compositions of cements. Designation

C3 S C2 S C3 A C4 AF R2 O

CEM 42.5I (OPC-1) 62.8 14.6 5.9

13.5

0.63

CEM 42.5I (OPC-2) 63.4 15.4 8.1

11.2

0.90

The alkaline oxide quantities in these cements are 0.63% and 0.9%, the tricalcium aluminate quantities are 5.9% and 8.1% accordingly. The polycarboxylate superplasticizer Stachement 2280 was selected for the experiments. The admixture was introduced with mixing water. The water-reducing effect of the admixture was estimated as reduction of water demand in percentage of the initial water demand of fresh concrete and was determined on fresh concrete with equal slump that was 7 cm.

4 Research Results and Discussion When comparing the water-reducing effect of the superplasticizer, it was found that it depends on the type of Portland cement, in particular, strongly depends on the cement mineralogical composition according to Fig. 1. The obtained data confirm the results published in papers [1, 33]. This allows concluding that the water reducing effect of the superplasticizer decreases with increase of C3 A amount. Water-reducing effect, %

30 25

OPC-1

20 15

OPC-2

10 5 0 0,3

0,6 0,9 Superplascizer quanty, %

Fig. 1. Water-reducing effect of the admixture depending on the type of cement.

Four laboratory mixes using OPC-1 and four mixes using OPC-2 were made to assess the possible reduction of water demand: one control composition without superplasticizer and three compositions with superplasticizer (SP) quantity of 0.3%, 0.6% and 0.9% of cement mass (Tables 2 and 3).

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L. Kazanskaya Table 2. Evaluation of Portland cement reduction (opc-1).

No

SP, %

OPC, kg/m3

SP, kg/m3

W/C

S, cm

Compressive strength at 28 days, MPa

Cement reduction, kg/m3

Cement reduction per 1 kg of SP, kg

1

0

450

0

0.4

7

62.3

–

–

2

0.3

416

1.25

0.4

7

62.8

3

0.6

357

2.14

0.4

7

63.5

93

43.5

4

0.9

336

3.02

0.4

7

62.5

114

37.7

34

27.2

The fresh concretes had equal workability with 7 cm slump and the same waterto-cement ratio (W/C) equal to 0.4. Fine and coarse aggregates, while maintaining the necessary ratio between them, were added to the fresh concrete mixture after the superplasticizer introduction in order to achieve the initial workability with 7 cm slump (S). Calculated - experimental method of selection of concrete composition was used. Table 3. Evaluation of Portland cement reduction (opc-2). No

SP, %

OPC, kg/m3

SP, kg/m3

W/C

S, cm

Compressive strength at 28 days, MPa

Cement reduction, kg/m3

Cement reduction per 1 kg of SP, kg

1

0

450

0

0.4

7

60.5

–

–

2

0.3

427

1.28

0.4

7

61.9

23

18.0

3

0.6

390

2.34

0.4

7

62.8

60

25.6

4

0.9

368

3.31

0.4

7

60.3

82

24.8

From the analysis of Tables 2 and 3 it can be concluded that the cement reduction per 1 kg of the admixture increases with the increase of admixture quantity but this dependence is not linear. The greatest cement reductions can be achieved on OPC-1. This was to be expected since higher water-reducing effect of the admixture was obtained on this Portland cement. Comparative assessment of Portland cement savings per 1 kg of admixture is shown in Fig. 2. The quantity of C3 A and R2 O in Portland cement should be taken into account to obtain significant reduction of water demand when using polycarboxylate admixture that one can see in Figs. 1 and 2. Reduced water demand leads to the increase of concrete strength that it can be used to reduce the cement in the production of concrete with the same strength.

Cement reducon per 1 kg of SP, kg

Estimation of Portland Cement Reduction 50 45 40 35 30 25 20 15 10 5 0

655

43,5 37,7 27,2

25,6

24,8

18

0,3 OPC-1

0,6 OPC-2

0,9 SP quanty, %

Fig. 2. Comparative assessment of Portland cement savings per 1 kg of admixture.

Further, the way of superplasticizer introduction was investigated in the paper. The mixing water was introduced in two stages. At the first stage the water of 60% quantity of the total mixing water was introduced and then the water in amount of 40% of the total mixing water was introduced. The superplasticizer was introduced at the second stage in order to reduce the influence of C3A and R2O on the water-reducing effect of the superplasticizer. Similar compositions as in Tables 2 and 3 were used. The results are presented in Tables 4 and 5. Table 4. Evaluation of Portland cement reduction (opc-1) at two-stage superplasticizer introduction. No

SP, %

OPC, kg/m3

SP, kg/m3

W/C

S, cm

Compressive strength at 28 days, MPa

Cement reduction, kg/m3

Cement reduction per 1 kg of SP, kg

1

0

450

0

0.4

7

62.3

–

–

2

0.3

411

1.23

0.4

7

63.1

39

31.7

3

0.6

353

2.12

0.4

7

63.8

97

45.7

4

0.9

332

2.99

0.4

7

62.4

118

39.5

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Table 5. Evaluation of Portland cement reduction (opc-2) at two-stage superplasticizer introduction. No

SP, %

OPC, kg/m3

SP, kg/m3

W/C

S, cm

Compressive strength at 28 days, MPa

Cement reduction, kg/m3

Cement reduction per 1 kg of SP, kg

1

0

450

0

0.4

7

60.5

–

–

2

0.3

419

1.25

0.4

7

62.2

31

24.8

3

0.6

365

2.19

0.4

7

63.4

85

39.0

4

0.9

346

3.11

0.4

7

60.9

104

33.4

Cement reducon per 1 kg of SP, kg

It is stated that the fresh concrete mix had better workability using the water introduction in two steps and introduction of superplasticizer with second part of water. Fine and coarse aggregates, while maintaining the necessary ratio between them, were added to the fresh concrete mixture after the superplasticizer introduction in order to achieve the initial workability with 7 cm slump (S). The compositions were recalculated to 1 m3 . Comparative assessment of Portland cement savings per 1 kg of admixture depending on Portland cement type and the way of superplasticizer introduction is shown in Fig. 3.

50 45 40 35 30 25 20 15 10 5 0

45,7

43,5

39

37,7

39,5 33,4

31,7 27,2

24,8

25,6

24,8

18

0,3

0,6

OPC-1

OPC-2

OPC-1 (2 stages)

OPC-2 (2 stages)

0,9 SP quanty, %

Fig. 3. Comparative assessment of Portland cement savings per 1 kg of admixture depending on way of superplasticizer introduction.

One can see in Fig. 3 that two-stage water introduction and introduction of superplasticizer with second part of water lead to greater cement saving per 1 kg of admixture especially for Portland cement with non-normalized mineralogical composition. The value of reduction of Portland cement quantity due to reduction of mixing water significantly depends on the mineralogical composition of Portland cement of the same strength class.

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It is shown that the influence of the mineralogical composition can be reduced by introducing water in two steps. Polycarboxylate based admixture must be entered with the second portion of the mixing water. It is stated that such a double-batch with water and admixture allows obtaining significant savings of Portland cement per 1 kg of admixture in concrete based on Portland cement with high amount of C3 A and R2 O. However, it should be noted the following pattern. The water-reducing effect of the superplasticizer increases significantly with the increase of the superplasticizer amount as shown in Fig. 1. Meanwhile, the maximum reduction of Portland cement per 1 kg of superplasticizer was obtained at amount of 0.6% and not at amount of 0.9% which corresponds to the maximum water reduction. On the basis of the above-mentioned it should be noted that it is necessary to pay attention to the way of superplasticizer introduction as well as to the selection of the concrete composition.

5 Conclusion There are various technological techniques to reduce the Portland cement quantity and maintain or improve the technical properties of concrete. One of these is the use of polycarboxylate based admixture (superplasticizer). Reducing water demand can be used to reduce Portland cement amount in concretes with the same strength. Additional knowledge is needed on the mutual influence of Portland cement and superplasticizers on the properties of fresh concrete, hardening processes and physical and technical properties of concrete for the effective use of these admixtures in the production of concrete and reinforced concrete. The conditions under which significant water-reducing effect can be achieved are stated in the paper. The results of quantity reduction of Portland cement of CEM42.5I strength class per 1 kg of the polycarboxylate based admixture depending on the way of admixture introduction and mineralogical composition of Portland cement were obtained on the basis of experimental data using 14 mixtures. One can conclude that significant reduction of Portland cement quantity was observed using superplasticizer of amount equal to 0.6% and the cement with mineralogical composition including R2 O equal to 0.63% and C3 A equal to 5,9%. The savings of such cement was 43.5 kg per 1 kg of superplasticizer. At the same amount of superplasticizer the Portland cement reduction was 25.6 kg per 1 kg of superplasticizer for the cement with mineralogical composition including R2 O equal to 0.9% and C3 A equal to 8.1% that was 40% less. Considering these results it is necessary to pay attention to the choice of Portland cement with the necessary mineralogical composition. Various ways of superplasticizers introduction are effective methods for significant reduction of cement that was shown in this paper. It is shown that it is possible to reduce the influence of the mineralogical composition of Portland cement by introducing mixing water in two stages. It was stated that two-stage mixing is effective for Portland cement of non-normalized mineralogical composition. Cement savings can increase from 25.6 kg to 36 kg for Portland cement of non-normalized mineralogical composition.

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Further studies should continue to study the ways of admixtures introduction in order to save Portland cement and develop green concrete technology.

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Hydromorphological Substantiation of Channel Stability of Navigable Rivers in Engineering Water Transport Regulation of River Runoff Gennady Gladkov(B)

, Michail Zhuravlev , and Viktor Katolikov

Admiral Makarov State University of Maritime and Inland Shipping, St. Petersburg 198035, Russia [email protected]

Abstract. The paper is devoted to the problems of regulating the hydrological and channel regimes of large navigable rivers, which are currently subject to the anthropogenic influence of engineering factors. Such factors include the construction of retaining hydraulic structures - dams, dredging for the needs of river and sea transport in transit of navigable rivers, free excavation of river alluvium - the production of non-metallic building materials by various subsoil users. Another argument that cannot be ignored today is the climate-related change in the characteristics of river water runoff and alluvium runoff from the territory of the river basin. In different geographical and climatic situations, the interaction of various influence factors and their possible combinations turned out to be different. The degree of occurring changes in the hydromorphology of river channels was also different. The following should be noted as important: such changes on the rivers turned out to be objectively significant, they can be instrumentally measured using special geodetic and hydrometric instruments, have a one-way irreversible character and affect the economic conditions of various water users at a considerable distance from their location. The scientific interest of this work is limited to the field of river transport and problems of land hydrology. The bulk of the materials of this study was obtained on the basis of their own research on free and regulated rivers used in Russia, in a number of former republics of the USSR and abroad to provide shipping by inland river and coastal navigation. Keywords: Hydromorphological rationale · Channel stability · River flow regulation · Land hydrology

1 Introduction In 2019, 110 years have passed since the creation of the Interdepartmental Commission to draw up a plan of work to improve and develop water communications in the Russian Empire. The Interdepartmental Commission and its permanent chairman, Professor Timonov V.E., already in their works laid the foundations of state policy in the field of improving and arranging waterways in Russia. The main idea laid down in the © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 661–675, 2021. https://doi.org/10.1007/978-3-030-57453-6_63

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Commission Plan was to create a network of latitudinal and meridional waterways in the country, which should provide all-Russian, inter-district and intra-district communications. In addition, such a network should include not only the main rivers along which large inhabited and industrial centers are located, but also small rivers for which the role of access roads was assigned. A lot of time has passed since the start of the work of the Interdepartmental Commission. The hydromorphological situation on the waterways in Russia has substantially changed, new means and ways of communication have arisen, as well as other problems that Russian engineers of that time could not even think about. However, many thoughts and ideas of that time, taking into account modern realities, deserve unconditional attention and careful study today. Currently, the operating network of inland waterways in Russia is 101.7 thousand km. Most of these routes have a developed infrastructure for the organization and maintenance of shipping. In the regions of the Russian Federation, where there are exploitable inland waterways, about 90% of the gross domestic product is created and 80% of the country’s population lives. At the same time, the share of inland water transport in the Russian Federation accounts for less than 1.5% of the total volume of transportation of cargo and freight turnover of all types of transport [1], while in Germany - 11%, the Netherlands - 34%, France - 10% of freight turnover with a steady growth trend in river traffic, primarily cargo in containers. Moreover, the ratio of the length of inland waterways, railways and roads is in the European part of Russia - 1:1:8, in Germany - 1:6:92, in France - 1:6:190 and in the Netherlands - 1:0.5:23. Inland water transport in the post-perestroika period has reduced almost five times the volume of traffic in the main range of cargo, which led to the loss of industry positions in the transport system of Russia. Passenger transportation by inland water transport decreased by more than eight times - from 103.0 million people up to 12.7 million people a year. The weakening of the competitive position of inland water transport is largely due to a decrease in the production potential of the industry. A significant reduction in river traffic in the last years of the last century is associated with a general drop in the volumes of production and consumption of industrial and agricultural products during the recession of the Russian economy in the 90 s. The deterioration of transport indicators of inland waterways [2] has become the main reason for the loss of traditional cargo flows in water transport. Significantly worsened indicators characterizing the quality of shipping conditions on the inland waterways of Russia. To date, on a large number of sections of waterways for various reasons, there has been a decrease in the size of ship passages. There are significant infrastructural restrictions on shipping on main waterways. The development strategy of the inland water transport of the Russian Federation for the period until 20301 ) provides for a significant reduction in the share of the length of waterways that limit the capacity of the Unified Deep Water System of the European part of Russia, as well as a significant improvement in the quality parameters of inland waterways paths in general. Therefore, for the successful implementation of the tasks in different shipping sections of 1 Order of the Government of the Russian Federation of 02.29.2016 No. 327-r.

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waterways, depending on the characteristics of the hydromorphological regime, various scientific and approaches and engineering solutions should be applied. Currently, the capacity on the Unified Deep Water System in a number of transit highways is limited, first of all, by insufficient dimensions of the waterway in certain sections of the Volga-Baltic and Volga-Don waterways, in transit shipping sections of the Kama, Belaya, Volga, Vyatka, Upper and Lower Don, as well as on a number of other navigable rivers. Moreover, on free and regulated areas of navigable rivers, degradation processes develop in different ways. The main difficulties for navigation on regulated rivers are sections of waterways located in the lower pools of hydroelectric facilities. Due to the interception of solid runoff by under-pore structures of hydroelectric facilities in these areas, irreversible erosion processes develop, bottom marks and water level marks decrease. Changes in the characteristics of the river flow and channel as a result of the regulation of runoff by hydroelectric facilities appear almost immediately after putting the complex of water-supporting structures into operation, or rather, they begin to affect even in the process of blocking the river channel. The most favorable case from the point of view of the subsequent operation of the cascade of hydroelectric facilities during river transport locks is the complex nature of the solution to this problem, when the structures are erected as soon as possible, along the entire length of the watercourse - from the source of the river - and to its mouth. In this case, the riverbed turns into a cascade of regulating pools, which are used simultaneously and solve transport problems along the entire length of the river. With shipping, as a rule, in such cases there are no problems. An example is the small Moselle River in Germany in the region of Koblenz, where a cascade of 14 low-pressure hydroelectric facilities was built and is currently widely used. There are still a number of such projects that have been quite successfully implemented on inland waterways in Western and Eastern Europe. In our country, in previous years, whole water transport systems were also built Vyshnevolotskaya, Tikhvinskaya, Mariinskaya, Severo-Dvinskaya, Seversko-Donetsk and others. Some of them, such as, for example, Seversko-Donetsk, have been in operation for the present time one hundred and more years; others ceased to exist after the loss of freight traffic, and one of them, Mariinskaya, after its reconstruction was the basis of the modern Volga-Baltic waterway of the Unified Deep Water System of the Russian Federation. The intensity of hydromorphological changes in the characteristics of the river flow and the river channel in the lower pool of the hydroelectric facilities varies over time. The most active erosion processes in the lower pools occur in the initial period after the dam blocked the river channel. Over time, the intensity of reformation fades, but erosion processes are spreading downstream of the river. In a whole series of cases, the situation in the lower pools of hydroelectric facilities (for example, the Ob river below the Novosibirsk hydroelectric station, the Volga river below the Nizhny Novgorod hydroelectric facility, etc.) is aggravated as a result of intensive mining of non-metallic building materials. Erosion processes below hydroelectric facilities occur on all regulated rivers, regardless of the geographical position of the river, its water content and soil composition of bottom sediments [3, 4]. As a result of this, irreversible changes in the hydrological and

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channel regimes took place everywhere in the lower pools of hydroelectric facilities, which led to a violation of the conditions of navigation and affected the interests of all water users and the environmental situation in the basins of large navigable rivers. Another group of waterways is free rivers, the hydromorphological regime of which has so far been changed in unsupported conditions due to various engineering measures being carried out on them. On some navigable rivers, this was facilitated by a significant over-exaggeration of rifts while achieving guaranteed navigable depths. However, in the vast majority of cases, the prevailing effect was the extraction of non-metallic building materials from channel quarries on the hydrological and channel regimes of rivers. To date, a number of navigable rivers of the Russian Federation (Vyatka, Belaya, Oka, Ufa, Vychegda, Tom, Upper Lena, Upper Don, etc.) have manifested adverse environmental consequences of engineering activities carried out earlier on the waterways. The main reasons for these changes are due to a progressive decrease in the bottom marks and water level marks. The changes in the river regime are most pronounced in the low-water period of time, at low water consumption. In modern conditions, there is no prospect of building new large hydropower facilities for complex use in urban areas, and there is no possibility of filling a number of existing reservoirs to design levels. In this regard, it is necessary to study options for restoring the level regime of navigable rivers to improve the quality of water resources in the adjacent territories and ensure shipping on inland waterways using relatively inexpensive and efficient channel low-pressure navigational facilities. Among such priority tasks in the industry should be the construction of a low-pressure hydroelectric facility on the Volga near the town of Gorodets to solve the problem that has dragged on so far since the 80 s of the last century, from the moment the Cheboksary reservoir was filled to a temporary mark. The second object, from the point of view of the severity of shipping on the Unified Deep Water System today is the Bagaevsky hydroelectric facility in the Lower Don. Next up is the problem on Kama, where on the site located in the lower pool of the Tchaikovsky hydroelectric facility to Kambarka, which, like the Volga cascade, was not filled up to the design marks, in this case, the Nizhnekamsk reservoir. Next - the lower pool of the Novosibirsk hydroelectric facility on the Ob, Vyatka, Upper Lena, Upper Don, waterways of the North Dvina basin, where shipping has almost ceased to exist today. Only a listing of the main and burning problems would take up a significant part of this narrative. However, we need to talk about possible solutions and the scientific justification of the challenges. So far, we have not touched on questions about the modern pace of hydro-construction in our country, which, according to the most conservative estimates, today are several times behind the pace of work that took place in the Russian Empire at the turn of the 19th and 20th centuries. In modern conditions, the idea of creating cascades of low-pressure structures to restore the violated level regime on navigable rivers [5] can be claimed and successfully developed in the interests of a wide range of water users. Along with providing shipping, such projects will contribute to improving the hydrological and channel regimes of watercourses, improving the quality of water and the conditions for the economic use of floodplain areas, developing fisheries, small-scale energy, water tourism and other industries in the adjacent territories.

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Formulating the basic requirements that, in our opinion, should be submitted at present when justifying, designing, and constructing low-pressure structures, whose main goal is to restore the lost level regime in the interests of a wide range of water users, including for ensuring transit shipping. In accordance with environmental requirements, the designed structures should not block the river floodplain, and should also ensure the free passage of water and bottom sediment runoff in spring flood, while preserving the natural volume of annual runoff of bottom channeling sediments and the habitat of aquatic biota. The construction of low-pressure structures will contribute to restore water levels for shipping and other water users during the low-water period, and will also create conditions for improving the water regime and the environmental situation in the river basin. With such a formulation of the question, the number of potential participants in the water sector who are interested in implementing new investment projects for transport locks in waterways can significantly increase. The construction of such structures can be recommended in the lower pools of hydroelectric facilities, as well as in sections of free rivers, subject to the influence of anthropogenic factors and engineering impact on the river regime. In these cases, the application of traditional methods of ensuring shipping conditions - the deepening and straightening of bottom - is not effective enough. Measures to straighten the river bottom activate erosion processes and cannot lead to the restoration of low water markings in principle, and dredging, moreover, will contribute to additional erosion and a further decrease in low-water water levels. The use of traditional methods of maintaining navigable passages - track work - within the established values of hydraulically permissible navigable depths, is advisable to be kept on free rivers, where the water levels in the long-term period have not changed [6]. In natural conditions, the river flow transports entrained and suspended sediment in the riverbed. Bottom sediments during their movement downstream of the river create a variety of dynamically stable channel forms that determine the modern appearance of the river channel and its floodplain. Therefore, the planned layout and the main structural solutions of the designed hydroelectric facilities should be selected in such a way as to ensure the transit passage of bottom sediments through the target of the structure, taking into account the laws of their movement. In this case, the choice of the location of the low-pressure hydroelectric facility, the location of the culverts and navigable canals, as well as the design of the spillway gates should be based on the analysis of the dynamics of average channel forms and macro forms of the riverbed. Many years of experience in the successful operation of low-pressure hydroelectric facilities built at the beginning of the last century show that the designers and builders of these structures in previous years had a sufficient idea of the mechanism of movement of river sediments and took this into account in their work. Meanwhile, at the time of engineering and hydrometeorological surveys, the composition of the design work does not provide for the study of the laws of movement of bottom sediments, there are no data on the particle size distribution of bottom sediments, as well as calculations of the annual runoff of bottom sediments and an analysis of the dynamics of middle channel forms in the section. Such omissions lead to a significant decrease in the quality of design studies.

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In modern projects of hydroelectric facilities, the location of the spillway structure is chosen in such a way as to ensure efficient and hydraulically beneficial passage of water through the structure’s target to all phases of the water regime, as well as taking into account the construction technology. The regularities of the development of the channel process and the conditions of transport of bottom sediments are not taken into account. Such objects, implemented in practice without sufficient hydromorphological substantiation of design decisions, subsequently create significant difficulties in the operation of culverts and shipping facilities of the hydroelectric facility. In order to ensure reliable operation of new low-pressure hydroelectric facilities on navigable rivers, it is necessary to develop sections related to the study of the laws of the riverbed processes and flow parameters of bottom sediments at the site of the main hydroelectric facility as part of the design work. This will require special field work and a modern hydromorphological analysis of the channel process within the framework of engineering and hydrometeorological surveys. An assessment of the mechanism for passing bottom sediments through the hydraulic system target under design conditions should be carried out on the basis of materials from mathematical and physical modeling of river bottom deformations and motion parameters of bottom sediments in channels. These issues need to be addressed already in the early stages of design, which will allow for taking hydromorphological requirements into account when preparing the main design decisions. At the same time, such issues as the choice of the construction target, the permissible degree of tightness of the channel in the construction target, the designation of the weir threshold and the normal retaining water level, the geometric parameters of the water supply and drainage channels, the operation mode of the storage reservoir, etc. must be reasonably decided. For the implementation of projects of low-pressure hydroelectric facilities on navigable rivers, it is necessary to develop engineering and technical solutions for the provision of shipping, water and river sediment passage through the construction target, based on the use of modern materials and technologies, as well as to improve the regulatory and technical base necessary for the design, construction, building and operation of such hydropower facilities, taking into account the characteristics of the hydrological regime of the river and the specifics of the development of the channel process. The indicated shortcomings of the modern technology for designing hydroelectric facilities on navigable rivers in terms of its hydromorphological justification are due to the imperfection of the existing regulatory framework in the field of design activity. According to the authors of this work, there is an urgent need to create a special Code of Rules for the design of such structures, in which the issues of accounting for the channel process under conditions of anthropogenic impact on the hydrological and channel regimes of navigable rivers should be developed at the modern level in the field of river hydromorphology. The key problem of the hydroelectric facility is the problem of passing through its target bottom channel-forming sediments, taking into account the patterns of their transport in this section under natural conditions, without changing the natural annual flow of bottom sediment. In these conditions, it is necessary to give a new meaning to the concept of “stability of the river channel on the construction site.” At the same time, as a result of the construction of a low-pressure hydroelectric facility, not only the

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instantaneous “hydraulic” stability of the river bottom and the cross section of the channel should be ensured, but also the long-term dynamic stability of the channel formation processes at the construction site, taking into account the artificial regulation of runoff in the construction target. To ensure long-term dynamic stability of the channel formation processes in the zone of influence of the designed hydraulic facility for the period of its operation, a number of scientific problems must be solved. These include issues such as establishing the value of channel-forming water discharge in a given section of the river channel, as well as forecasting the forms of bottom sediment movement in the lower pool and forecasting accumulation of bottom sediment in the higher pool of the low-pressure hydroelectric facilities under design conditions. The most important of them is the problem of reliable estimation (calculation) of the flow rate and annual runoff of bottom channel-forming sediments in the area, both in natural conditions and in design conditions. The value of the annual runoff of bottom sediments characterizes the intensity of all hydromorphological processes in the riverbed section and, accordingly, determines the methods and mechanisms for passing bottom sediments through the target of the hydraulic facilities under design conditions. Due to the complexity of these problems, the development of a mechanism for passing bottom sediments should be carried out on the basis of mathematical and physical modeling of deformations of the river bottom and motion parameters of bottom sediments in culverts. Therefore, one of the main tasks in this case is the problem of choosing a reliable formula for the flow of bottom sediments in specific hydromorphological and hydraulic conditions. This problem is mainly devoted to the discussion of this article.

2 Methods and Materials The river flow in a channel with a moving bottom, under conditions of dynamic equilibrium, is characterized by the statistical stability of the main indicators of the hydrological and channel regimes. At the same time, for a considerable time, the characteristics of liquid and solid runoffs and the main morphometric parameters of the channel remain unchanged. This allows you to predict the development of the channel process in the future and carry out business activities taking into account the predicted data. In [7] the conditions of the statistical stability of the flow channel are formulated in the form L U1 < U < U2 , 0

∂ ∂ U2 dl ≈ 0, ∂l ∂t

L If dl ≈ 0

(1)

0

where U is the average flow velocity; U1 and U2 are its lower and upper limits, respectively; L is the length of the section; If is the friction bias. The channel flow regulates the movement of water and the characteristics of sediment transport, using the degrees of freedom at its disposal. Transformations in the flow structure consist in the reconstruction of the velocity field along the depth and width of the flow, the change in the slopes of the free surface, and the characteristics of turbulence.

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All these changes are explicitly or indirectly related to the parameters of the bottom waves and the conditions of sediment transport. To assess the effects of the interaction of the flow and the channel, a system of calculated dependences is proposed below, which establish the relationship between the Shezy coefficient and the flow depth and the flow velocity and a model for describing the characteristics of sediment transport. To ensure stability under the conditions of anthropogenic impact on the channel process, the set of criteria for statistical stability should be supplemented on the basis of sufficiency considerations. It should be borne in mind that with a certain degree of impact, as long as the condition of speeds is valid, the flow will be able to respond to changes that occur. However, the flow-channel system in this case will be in a recovery state different from the initial steady state. In this case, the uniformity of the hydraulic row can be broken. In the case of engineering intervention in the natural course of the channel process development, the flow reacts to artificial changes in its channel. Its reaction is manifested at different levels of the flow-channel system and, depending on the degree of influence, can receive a different spatial-temporal orientation. Usually, in the initial period, these processes proceed more intensively in the relatively short section. Then, over time, the intensity of changes decreases, but the influence spreads up and down the river from the place of work. In such cases, it is customary to talk about a change in the stability of the river channel. The flow response to artificial changes in the channel is always directed towards increasing its stability. However, such interconnections are realized in the flow-channel system only within certain limits, depending on the degree of engineering intervention, and operate until the flow is able to regulate the characteristics of its channel. Therefore, when designing engineering water transport measures on rivers [4] in order to ensure the stability of the channel, it is necessary to supplement the system of Eqs. (1) with the following expressions 

L

I /I ≈ 1 and 0

∂ qs dl ≈ 0 ∂l

(2)

The first expression in (2) establishes the need to maintain water levels when designing engineering measures in the riverbed; the second is due to the need to maintain sediment runoff conditions in the section. The joint implementation of (1) and (2) creates the necessary and sufficient conditions for ensuring the statistical stability of river channels during engineering intervention in the natural course of the channel process development. When designing the hydrological regime of the river flow under altered conditions, i.e. after the creation of a low-pressure hydroelectric facility, it is necessary to ensure that the conditions recorded in expressions (2) are maintained in all possible modes of its operation - both when the spring flood is passed and during the low-water period, under conditions of backwater. It should be noted that when designing hydroelectric facilities with high pressures, this is almost never possible, which poses many problems in the process of their subsequent operation in practice. As a research apparatus for solving such problems, as a rule, the results of mathematical and hydraulic modeling of the designed structures are used. In research and

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design practice, hydraulic calculations are usually performed using a hydrodynamic model based on solving the system of equations in the shallow water approximation by the finite element method. The modern apparatus [8] makes it possible to solve with a sufficient degree of reliability the problem of the distribution of average on vertical velocities in river flows and to model the influence of the designed measures on the speed regime and water levels. However, certain issues of river hydraulics that characterize the internal structure of a turbulent suspension transport flow, the parameters of large-scale turbulence, the movement of driven sediments and channel transformations in such models are not solved by definition, or are solved unsatisfactory. In this regard, when designing critical structures at water bodies, additional hydraulic studies are carried out on large-scale models. The methodology for designing and constructing rigid spatial hydraulic models was developed at the State Hydrological Institute during the course of many years of experimental research. To date, it has been successfully tested [9] when conducting research on hydraulic structures and engineering activities at water bodies. When modeling channel reformation in rivers, the task is to perform hydraulic calculations of the characteristics of the water flow and sediment transport parameters (bottom deformations) as a result of solving the known system of equations of water motion, continuity and deformation by given initial and boundary conditions by numerical methods. This system of equations with five unknowns is closed with the help of two additional calculated dependences - the law of hydraulic resistance in the form of the formula of the Shezy coefficient and the formula of sediment discharge. Therefore, the quality of hydraulic calculations and channel forecasts to a large extent depends on the reliability of estimating energy losses along the length and parameters of sediment transport in the deformable channel. The following section of this paper is devoted to these key problems.

3 Results The most thorough study in the field of estimating the flow energy loss in natural riverbeds with a deformable bottom was carried out by [7, 10]. Later works and generalizations of other authors [11–13] provide practical recommendations that can be applied in solving river hydraulics equations by numerical methods with the aim of modeling sediment transport and calculating channel deformations in rivers. In rivers with relatively large soils, the main resistance to the movement of water is exerted by a loose flow around the soil particles of river alluvium at the bottom of the flow. In practice, the calculation formulas are used for the Shezy coefficient, constructed as a function of the dimensionless size of the bottom sediments N/d. Preference is usually given to well-known calculated dependences having the structure of the formulas of A. P. Zegdz and Manning-Strickler, which give fairly close results. In rivers with sandy bottom sediments, the share of energy losses prevails due to the detached flow around ridges at the bottom of the river. The existence of feedback in the flow moving channel system made it possible to obtain [10, 11, 13] a number of new promising formulas for the Shesi coefficient as a function of the flow velocity and dimensionless flow depth as applied to the conditions of water movement in the

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streaky dells, on rifts, and in river bends. The calculated dependences obtained have been extensively tested according to field observations on rivers and experimental hydraulic research materials. The established by such way values of the Shezy coefficients are used further when performing hydraulic calculations, on the one hand, to calculate the friction force in the equation of motion of a viscous incompressible fluid. As a result of solving the equation of motion, the value of the channel filling is calculated, the average speed and direction (in the 2D setting) on the vertical are determined. Based on these data, the local slope of the free surface can be determined both on the vertical and on the computational element (in the 2D model), and within the boundaries of the entire computational section as a whole (in the 1D model). Further, the magnitude of the energy loss along the length, estimated by the Chesi formula, is used to solve the deformation equation as part of the sediment discharge formula when calculating the shear stress at the bottom of the river flow. In one of the latest works of the authors of this study [13], as a result of a modification of the calculation formula of L. van Rijn [14], a new model of sediment transport in rivers was obtained and tested according to two hundred and ninety-six measurements on rivers. In total, more than 30 different formulas of sediment discharge in rivers and their possible modifications were investigated. Table 1. General characteristic of a sample of measurement data for calibration of a sediment transport model. Average flow speed m/s, from/to

Average depth, m, from/to

Average diameter of bottom sediments mm, from/to

Slope of free

Water temperature, deg, C°

Number of measurements

Author, source

surface 0 /00 , from/to

0.5/2.50

1.0/20.0

0.1/2.0

–

–

226

L. van Rijn, [14]

0.09/2.77

0.06/7.3

0.25/93.2

0.003/11.0

1.1/24.7

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Taking into account the results of studies of Ribberink [15], the final calculated dependence for the fractional calculation of the flow rate of different-grained soil in rivers is written as √  2.4 n  1 − ξi Θci /μΘi βi , (3) qs = AHUFr 2.4 √ ρs /ρ − 1 i=1 An analysis of a number of well-known and approved methods [16] allowed the authors to distinguish the relative fraction of granular roughness in calculations, the  so-called “ripple” is factor in product μΘi , where Θi = H · I /di (ρs ρ − 1) the value is the mobility coefficient of an individual soil fraction. The parameter μ in this case is calculated in accordance with well-known recommendations by the formula μ = (Ks /Ks )1/4 = (Ks /(Ks + Ks ))1/4 .

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In this case, the effective height of the roughness protrusions at the bottom of the ridge flow is calculated depending on the average particle diameter Ks = dm + 1.6Sdm ,  βi (di − dm )2 . The parameters of the ridge resistance of the river where Sdm =  bottom depend on the size of the bottom ridges Ks = 10h2D /LD , and the bottom waves themselves - length (LD ) and height (hD ) - are calculated in accordance with the recommendations  of M. Yalin according to the formulas LD = 5H and hD = H · 1/6 · (1 − Θcm Θm )(1 − Fr 2 ). The value of the critical value of the mobility coefficient of the average particle size of the soil in the mixture is calculated by the formula of the author [13], obtained depending on the dimensionless particle diameter as a result of the processing of experimental data by V. S. Knoroz [17]. The calculated dependencies are written as  1/ 3 2 d Θcm = 0.026 · [(D∗ + 1.3)/(D∗ − 0.72)]2 , Where D∗ = ρ  g ν

(4)

The conditions for the shift of heterogeneous soil particles at the bottom are estimated for each fraction depending on the average diameter of the soil particles in the mixture by introducing a correction factor that takes into account the effect of “shading” of an individual soil particle in the mixture - the so-called “hiding/exposure-factor”. B. Zengen in his work [16] performed an analysis of the research results of I.V. Egiazarov on the problem of assessing the stability of a particle of heterogeneous soil at the bottom of the river flow and taking into account the experimental data of several other authors (Ashida-Egiazarov-Zengen), proposed a system of calculated dependences for the value of the critical value of the mobility coefficient ξi = Θci /Θcm depending on the range of values di /dm . Comparison of the calculated values of the sediment discharge costs with field data indicate their satisfactory coincidence. The correlation coefficient in the regression equation was 0.887. The value of the free term in the modified formula of L. van Rijn was equal to A = 0.0014. The value of the angular coefficient b in the regression equation according to the results of testing the model turned out to be 0.997, which allowed us to keep the initial value of the exponent set by the author unchanged in formula (3).

4 Discussion The resulting model will have certain limitations in its practical use for modeling channel sediment transport and forecasting channel reformation at sections of navigable rivers, improved by means of dredging, straightening, as well as in solving practical problems related to regulating water flow and runoff of river deposits with low-pressure hydraulic facilities. In this case, the following main problems can be expected, which can lead to deterioration in the quality of the model operation in practical conditions. It should be noted that almost all currently applied sediment discharge formulas have similar disadvantages. At this stage of the research, the authors tried to anticipate these difficulties, and, if possible, assess their danger. m the known problems of deterministic-type calculation formulas qs ∼  IOne of Θ − Θc is that, due to the high degree of dependence of the predicted sediment

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discharge rate on the water flow speed, such calculation formulas turn out to be the least accurate in the field of weak sediment transport, i.e. starting almost from the moment of the particle shift of the river alluvium at the bottom of the flow. Criterion values, evaluating the beginning of the shift of soil particles at the bottom of the flow, are determined by experimental data in hydraulic chutes with a bed without a ridge. Therefore, experimenters are subsequently led to introduce into the calculation discharge formula a large number of different coefficients, as was done in this case, in order to bring the model to a more adequate description of the real process in the river channel. The situation was approximately the same in the case under consideration, when according to testing the presented model (3) in 30 cases out of 296 gave zero sediment discharge in calculations, while in real conditions (according to measurement data) its value was nonzero. When calculating sediment discharge based on the available data sample (see Table 1 above) according to the well-known Meyer – Peter and Müller formula [18] in a similar interpretation with the value of the critical magnitude of the mobility coefficient according to Shields [19], the number of calculation points in the total data sample volume amounted to 81. In all other cases of test calculations performed [13], including at earlier stages of work, the use of the critical tangential stress value in the calculations according to V.S. Knoroz (4) gave obviously better results than according to the well-known Schilds estimate. Another important point that you need to pay attention to when using new calculated dependences in calculation practice is that most of the calculated sediment discharge formulas obtained in laboratory and field conditions were substantiated and tested for quasi-uniform water movement. In real conditions, with unsteady movement of water in the case of regulation of runoff by hydroelectric facilities, large values of local accelerations will occur. It should be expected that these processes will be weaker on low-pressure hydroelectric facilities. In any case, it will be obvious that when modeling sediment transport under conditions of unsteady movement of water in the river, the parameters of the bottom ridges, when changing, following the changing kinematics of the river flow, will lag in time from the change in the velocity field of the river flow. The new formulas of the Shezy coefficient, constructed as a function of the flow velocity [13], of course, will to some extent compensate for this time lag in the calculations, however, the time lag in the calculations will definitely take place. Concern is caused by problems associated with an attempt to isolate from the amount of energy loss along the length of the relative fraction of granular roughness. A chain of calculations based on the use of the original hypothesis of G. Einstein and the calculation formulas of M. Yalin in the interpretation of B. Söngen [16] seems cumbersome. Under conditions of quasi-uniform water movement, it gives quite satisfactory results, however, with an unsteady process, which we will always deal with while continuously regulating water discharge in the cascade of hydroelectric facilities, this approach cannot be considered quite satisfactory. It has already been noted above that it is necessary to take into account the inertia of the rearrangement of the ridged topography of the bottom in the process of changing the value of river runoff.  m When calculating sediment discharge by the formula of the form qs ∼ Θ I − Θc , it seems more expedient to calculate the relative fraction of the granular roughness of the alluvial bottom surface using one of the well-known and tested formulas of the

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Shesi coefficient, such as the Manning-Strickler or A. P. Zegdzh formula. Preliminary test calculations performed in the framework of this work showed the efficiency of this approach. However, for this it is necessary to conduct an additional special study with the use of new experimental data [20, 21].

5 Conclusion Currently, in many parts of the waterways, the carrying capacity is limited by the insufficient dimensions of the shipways. At the same time, on free and regulated sections of navigable rivers, a decrease in the size of the waterway occurred for various reasons. On regulated rivers, the main problems with ensuring navigable conditions arise on the sections of waterways located in the lower pools of hydroelectric facilities. In these areas, due to the interception of solid runoff by sub-porous structures of hydroelectric facilities, irreversible erosion processes develop, bottom marks and water level marks decrease. Similar processes associated with the violation of uniformity of hydrological series appeared on a number of free navigable rivers as a result of mass production of non-metallic building materials from river beds. These changes adversely affected the conditions for ensuring the safety of shipping and facilities of the coastal infrastructure of water transport, and affected the quality of water resources and the environment. One of the possible options for restoring the violated level regime and improving the conditions for maintaining waterways in such sections of navigable rivers is the construction of relatively inexpensive and efficient channel low-pressure navigable facilities. The construction of such structures on waterways will require the improvement of the hydromorphological justification of design decisions. To ensure reliable operation of new low-pressure hydroelectric facilities on navigable rivers, it is necessary, as part of the design work, to develop sections related to the study of the patterns of channel processes and the parameters of bottom sediment runoff at the site of the main hydroelectric facilities. This will require special field studies and a modern hydromorphological analysis of the channel process within the framework of engineering and hydrometeorological surveys. An analysis of the current practice of maintaining navigable passages and navigable hydraulic structures on inland waterways indicates that to date there is an urgent need to create a special Code of Practice for the design of low-pressure hydroelectric facilities, in which the issues of accounting for the channel process under conditions of anthropogenic impact on hydrological and channel regimes of navigable rivers should be developed at the modern level of knowledge in the field of river hydromorphology, based on new methodological approaches and the use of modern methods of physical and mathematical modeling. At the same time, the objectives of creating low-pressure hydroelectric facilities on waterways should be not only issues of improving navigational conditions, but also ensuring long-term dynamic stability of channel formation processes in the influence zone of retaining structures during operation, as well as maintaining and improving the habitat of aquatic biota.

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References 1. Van Hulten, M.: Prospects for the development of inland water transport in Europe. GeoJournal 1(2), 7–23 (1977). https://doi.org/10.1007/bf00220117 2. Gladkov, G.L.: Ensuring the conditions of navigation on inland waterways. J. Transp. Russ. Fed. Sci. Transp. Sea River Transp. 1, 8–14 (2014) 3. Babi´nski, H.: Mi˛edzynarodowa Droga Wodna E40. Stan i mo˙zliwo´sci zagospodarowania, ˙ ´ Global Compact w Polsce, Raport Zegluga Sródl˛ adowa – Wisła, Rozdz. II, Bezpiecze´nstwo ekologiczne, pp. 212–217 (2015) 4. Gladkov, G.L., Chalov, R.S., Berkovich, K.M.: Gidromorfologiya rusel sudokhodnykh rek: Monografiya. 2nd. Lan’, St. Petersburg (2019) 5. Gladkov, G.L., Katolikov, V.M., Shurukhin, L.A.: Construction of low-pressure hydroelectric facilities on navigable rivers. J. Transp. Russ. Fed. 5(78), 39–42 (2018) 6. Gladkov, G.L., Zhuravlev, M.V., Sokolov, Y.P.: The Content of Inland Waterways. Track Works, 2nd edn. red. Lan’, St. Petersburg (2019) 7. Chanson, H.: Fundamentals of open channel flows. Environ. Hydraul. Open Channel Flows, 11–34 (2004). https://doi.org/10.1016/b978-075066165-2/50034-5 8. Aleksyuk, A.I., Belikov, V.V., Borisova, N.M., Fedorova, T.A.: Numerical modeling of nonuniform sediment transport in river channels. Water Resour. 45(1), 11–17 (2018). https://doi. org/10.1134/S0097807818050275 9. Klaven, A.B., Kopaliani, Z.D.: Experimental Studies and Hydraulic Modeling of River Flows and Channel Processes. Nestor-Historiy, St. Petersburg (2011) 10. Antropovskii, V.I.: Hydraulic resistance of different-type river channels with manifestations of karst and suffosion processes. Water Resour. 30(6), 650–652 (2003). https://doi.org/10. 1023/b:ware.0000007591.55657.09 11. Sukhodolov, A.N., Nikora, V.I., Katolikov, V.M.: Flow dynamics in alluvial channels: the legacy of Kirill V. Grishanin. J. Hydraul. Res. 49(3), 285–292 (2011). https://doi.org/10. 1080/00221686.2011.567760 12. Stewart, M.T., Cameron, S.M., Nikora, V.I., Zampiron, A., Marusic, I.: Hydraulic resistance in open-channel flows over self-affine rough beds. J. Hydraul. Res. 57(2), 183–196 (2019). https://doi.org/10.1080/00221686.2018.1473296 13. Gladkov, G.L., Zhuravlev. M.V.: Hydraulic resistance to water flow and sediment transport in rivers. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova 11(6), 1044–1055 (2019). https://doi.org/10.21821/2309-5180-2019-11-61044-1055 14. Rijn, V., Leo, C.: Sediment transport, part 1: bed load transport. J. Hydraul. Eng. 110(10), 1431–1456 (1984). https://doi.org/10.1061/(ASCE)0733-9429(1984)110:10(1431) 15. Ribberink, J.S.: Mathematical modelling of one dimensional morphological changes in rivers with non-uniform sediment. Delft University of Technology, Report 87(2) (1987) 16. Söhngen, B., Kellermann, J., Loy, G.: Modelling of the Danube and Isar Rivers morphological evolution. Part I: Measurements and formulation. In: Proceedings of 5th International Symposium On River Sedimentation, Karlsruhe, vol. 3, pp. 1175–1207 (1992) 17. Collis-George, N., Youngs, E.G.: Some factors determining water-table heights in drained homogeneous soils. J. Soil Sci. 9(2), 332–338 (1958) 18. Meyer-Peter, E., Muller, R.: Formulas for bed-load transport. In: Proceedings of 2nd Meeting of the International Association for Hydraulic Structures Research, pp. 39-64. Delft (1948) 19. Shields, A.: Anwendung der Ahnlichkeitsmechanik und der Turbulenzforschung auf die Geschiebe Bewegung. Diss, Berlin (1936)

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20. Yang, S.-Q.: Sediment transport capacity in rivers. J. Hydraul. Res. 43(2), 131–138 (2005). https://doi.org/10.1080/00221686.2005.9641229 21. Hasegawa, K., Hirose, K., Meguro, E.: Experiments and analysis on alternating mainstream change in the bifurcated channel in mountain rivers. Proc. Hydraul. Eng. 47, 679–684 (2003). https://doi.org/10.2208/prohe.47.679

Bioindication for the Search of Microorganisms-Destructors Grigorii Kozlov , Mikhail Pushkarev(B) , Artemiy Kozlov , and Elizaveta Perepelitsa Saint-Petersburg State Institute of Technology, 26 Moskovsky Prospect, 190013 St. Petersburg, Russia [email protected]

Abstract. The work is devoted to the substantiation of soil sampling points for the selection of promising strains-destructors of organic pollutants using bioindication to reduce the volume of routine microbiological studies, by excluding samples taken in environmentally friendly locations and focusing on samples from environmentally “dirty” points. The paper presents the results of research carried out in 2018–2019. In the course of work, 11 points were studied in obviously environmentally friendly and environmentally unfriendly locations on the territory of Krasnodarskiy krai (Anapa, Novorossiysk and Gelendzhik district) and, respectively, 14 points in obviously environmentally friendly and environmentally unfriendly locations in the North-West region (Saint-Petersburg, suburbs and Leningrad oblast) of Russia. Pinus brutia var. Pityusa (STEVEN) SILBA, 1985 for Krasnodarskiy krai; Pinus sylvestris L., 1753 and Quercus robur L., 1753 for the North-West region of Russia were used as indicator plants. As an indicator – a joint test criterion for zero asymmetry and excess of distribution of the maximum length of needles of Pinus brutia var. Pityusa (STEVEN) SILBA, 1985; Pinus sylvestris L., 1753; weight of acorns of Quercus robur L., 1753. The proposed method showed the simplicity of primary data collection and high sensitivity. Low requirements for the accuracy of primary measurements (as opposed to fluctuating asymmetry) allow future automatization of the process using a smartphone camera and the use of the method not only to search for promising strains-destructors, but also to develop a mobile application for assessing the local environmental situation for a wide range of users. Keywords: Bioindication · Asymmetry · Excess · Pinus sylvestris L., 1753 · Pinus brutia var. Pityusa (Steven) Silba, 1985 · Quercus robur

1 Introduction The soils of cities with a long industrial history are a promising reservoir for the selection of highly effective destructors of organic pollutants [1]. However, the determination of sampling points from which crops are isolated is usually based on expert assessment © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 676–684, 2021. https://doi.org/10.1007/978-3-030-57453-6_64

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(taking into account soil contamination, etc.), but microbiological manipulations are quite complexity and lengthy, so it is desirable that their effectiveness is higher. It is more logical to pre-map the area by the degree of contamination in order to select the most polluted places that contain, respectively, the most promising destructors. However, if we take the content of pollutants as a function, then their determination or assessment of the total toxicity of soil samples for the selection of promising soil samples is hardly appropriate due to the greater complexity than the actual selection of strainsdestructors. The bioindication method is simpler, but the use of fluctuating asymmetry [2–4] can also be more complexity than the main study: first, it requires measuring several parameters of the option; second, it requires high accuracy, for example, when determining the length of pine needles, the authors of the work [2] used a microscope and made measurements with an accuracy of 0.025 mm. Thus, it is necessary to automate the process based on available hardware – ideally a smartphone or tablet, otherwise the complexity of the auxiliary study is higher than the main one. The solution is to use image recognition technology and measure the parameters of bio-objects with subsequent calculations, but this requires a parameter that does not require high accuracy of primary data. In principle, we can improve the accuracy of data collection, but we will need high-resolution cameras, as well as close-ups. In this case, the complexity of the study will not radically decrease. In this regard, we decided to measure only one maximum parameter of the object of observation (reduces the requirements for measurement accuracy) and calculate the asymmetry and excess of the distribution of this parameter. It is convenient to compare different locations using a joint test criterion for zero asymmetry and excess [5].  2  2 Ec As +n (1) k=n 6 24 where n - is the sample size; As - is the asymmetry; Ec - is the excess. This approach is also convenient when an unpaired needle or leaf blade is used as a bioindicator, but an object such as a spruce or larch. In this work, we measured the asymmetry and excess of indicator plant parameters in obviously highly polluted and clean locations in the South (Pinus brutia var. pityusa (Steven) Silba, 1985) and in the North-West of Russia (Pinus sylvestris L., 1753) to justify the isolation reservoirs of strains. The choice of objects is due, first, to the fact that the length is a one-dimensional value, and secondly – the image fits significantly more needles than leaf blades at the same resolution of the photo.

2 Materials and Methods The research used fallen needles of Pinus brutia var. pityusa (Steven) Silba, 1985, Pinus sylvestris L., 1753, as well as a mass of acorns of Quercus robur. Measurements were made with a ruler with an accuracy of 1 mm. The values of unbiased sample estimates of asymmetry and excess were calculated using Excel using formulas (1) and (2): As =

 xi − x¯ 3 n Sx (n − 1)(n − 2)

(2)

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 xi − x¯ 4 n(n + 1) 3(n − 1)2 Ec = − Sx (n − 1)(n − 2)(n − 3) (n − 2)(n − 3)

(3)

where n - is the sample size; Sx - is the mean square deviation; x¯ - arithmetic mean; xi option.

3 Results and Discussion We conducted a survey of a number of natural and man-made locations for which organic and inorganic pollutants are known to be polluted in order to confirm the sensitivity of the method and test the method’s ability to search for local pollutants of greatest interest in terms of identifying the most polluted areas for soil sampling. The Black Sea coast of the Caucasus was surveyed in resort and industrial settlements, as well as various locations of Saint-Petersburg and the Leningrad region for which are known (according to literature data) in works [6]. In research on bioindication, the authors use different sample sizes - so in work [7] a sample size equal to 120 is used, while other researchers took a sample size equal to 1500 [2]. Thus, the experimental determination of the sample size for a consistent estimation of values is relevant. The example of a herbarium collected in the Sergievka Park in Peterhof town shows (Fig. 1) that sample values vary very widely depending on the sample size for small sample sizes and stabilize around the general values at n ≥ 750 for As and n ≥ 1250 for Ec. Before these values, although Ec begins to fluctuate around the general value at n ≥ 200, and As - almost immediately, but the amplitude of these fluctuations is very large. 2.5

Values As and Ec

2

The esmate fluctuates around its general value, but the amplitude of the fluctuaons is large

1.5

Sample size, sufficient for calculaon Ec (n=1250)

1

Ec

0.5 0

-0.5 -1

0

500

1000

1500

2000

Sample size, sufficient for calculaon As (n=750)

2500 As

Sample size (n), pieces

Fig. 1. Dependence of sample estimates of asymmetry and excess of the distribution of the maximum length of needles of Pinus sylvestris L. Place of collection of the herbarium – Peterhof town, Sergievka Park (59.892764, 29.835802).

Thus, in order to avoid getting a false positive or false negative result, it is necessary to analyze the dependence of the selective value on the sample size and assess whether the sample size is sufficient to obtain a consistent estimate or not.

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Tables 1 and 2 present data on the asymmetry and excess of the distribution of the maximum length of needles of Pinus brutia var. pityusa (Steven) Silba, 1985, collected in various locations of the Russian Black Sea coast of the Caucasus and the North-West, obtained taking into account the consistency check. We took the average value of the parameter calculated from the values stabilized near the general value (Fig. 1). At the same time, in an industrial location, the asymmetry and excess are very far from zero values, and in a recreational zone they are almost zero. Table 1. Black Sea coast of the Caucasus. Pinus brutia var. pityusa (Steven) Silba, 1985, 2018. Place of collection of the herbarium

Coordinates

As

Ec

k

Air pollution

Nearby sources of atmospheric pollution

12 Kirova street, Divnomorskoe village

44.503260, 38.131534

3.50·10−3

4.18·10−2

7.49·10−5

Very low

Passenger vehicles

107 Ostrovsky street, Gelendzhik

44.554463, 38.098462

1.60·10−3

−1.48·10−2

9.57·10−6

Very low

Passenger vehicles, M-4 Don highway (1.5 km)

2 Revolution street, Gelendzhik

44.563549, 38.077029

−1.27·10−1

7.69·10−1

3.47·10−2

Low

Marina for pleasure boats (250 m)

29 Schmidt street, Gelendzhik

44.574558, 38.080482

−6.62·10−1

1.23

1.36·10−1

Low

Highway M-4 Don (600 m downhill)

19 D. Sabinina street, Gelendzhik

44.578780, 37.987373

−1.37·10−1

1.03·10−1

3.60·10−3

Low

Passenger vehicles, Gelendzhik airport (1.5 km)

1 Golubaya Buhta street, Gelendzhik

44.575775, 37.985020

2.11·10−1

1.43

9.31·10−2

Low

Passenger vehicles, Gelendzhik airport (1.8 km)

16 Phistashkovaya street, Gelendzhik

44.582197, 37.989663

6.69·10−3

7.06·10−1

2.08·10−2

Low

Passenger vehicles, airport (1.6 km)

Anapa-7, airport

45.004609, 37.339007

−1.86·10−1

−1.04·10−1

6.28·10−3

Low

Passenger vehicles, Anapa airport (300 m)

1 Sovetov square, Anapa

44.895456, 37.316388

2.34·10−1

−1.03·10−1

9.63·10−3

Low

Anapa sea station (600 m)

86 Lenin street, Tsemdolina village

44.755796, 37.725496

3.82·10−1

2.27

2.39·10−1

High

A-290 highway (nearby), industrial zone (400 m)

2 Moskovskaya street, Novorossiysk

44.728243, 37.757406

−1.17

4.02 10−1

9.07·10−1

High

E97 highway (nearby), port (1 km)

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Since the sample size at which the sample estimate stabilizes near the general value is different, it is convenient to take n = 1 to apply formula (1) to the problems of this study. The industrial location is represented by the city of Novorossiysk, the selection of herbarium was made near the highway with busy traffic near the commercial sea port. The asymmetry values are stabilized at a value close to −1.17; the excess is about 4.02. Another industrial location-Cement valley near Novorossiysk gives the following values of asymmetry and excess: As = 3.82 × 10−1 ; Ec = 2.29. Thus, it is obvious that the asymmetry and excess of this distribution is very large, and the distribution is far from normal. For Gelendzhik city there is a pronounced dependence of the amount of asymmetry and excess on the degree of environmental well-being. In the selection point of the herbarium – the area of a busy highway (respectively, the contamination of benzopyrene), the asymmetry is 6, and the excess is 1.5 times higher than on the sea shore. Thus, local pollution is very clearly monitored, although according to the state report on the condition of the environment in the Krasnodarskiy krai [6] environmental pollution in the resort city of Gelendzhik is negligible. Further, to test the sensitivity to local pollution, measurements were made in locations that provide the best air circulation. Gelendzhik is a closed bay surrounded by mountains, where the airport, seaport and the Federal highway “Don” are located. The Blue bay area and the village of Divnomorskoye, which have almost open coasts (the bay is very small, and there is an open coast in Divnomorskoye), were examined as cleaner locations. In the “Blue bay” location, the asymmetry and excess are stabilized at a value equal to the modulus of about 0.1; in the case of an open coast, they tend to zero values. The well-known fact that the main role in ensuring environmental well-being belongs to air circulation, it is confirmed by data on the resort city of Anapa located on a flat area. There are also small (no higher than 0.25 to the modulus) values of asymmetry and excess of distribution of needles of Pinus brutia var. pityusa (Steven) Silba, 1985, even in the area of such a source of pollution as the international airport. Thus, this method is very sensitive and can be used to search for local contamination spots, where soil samples should be taken to isolate promising destructors. A convenient way to assess the degree of difference between the distribution and the normal law is the joint criterion formula (1) at n = 1 (for convenience, since the sample size at which the value of the selective indicator is stabilized near the general value is different), the values of which are also shown in Table 1. At the same time, we accept k values of the order of 10−3 or lower as exceptionally clean locations. Points where the k values are of the order 10−2 are considered clean, and points of the order 10−1 or more are considered environmentally dirty locations. This method of bioindication is very informative, because it allows us to identify spots of local pollution – so there are locations that can be attributed to the reference level of cleanliness in Gelendzhik (location-107 Ostrovsky street), where k is 7.3 times lower than in the village of Divnomorskoe and to those whose contamination is very significant (location - 29 Schmidt street). However, the most “dirty” location of Gelendzhik is 7 times “cleaner” than Novorossiysk.

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However, such a convenient (large length of needles) indicator plant grows only in the southern region of Russia. Therefore, the next step was to test the method on other plants - indicators. Table 2. Saint Petersburg and Leningrad region. Pinus sylvestris L., 1753. 2019. Place of collection Coordinates of the herbarium

As

Bank of the 59.946407, 29.573989 1.47·10−1 Chernaya Rechka, Leningrad region, Lomonosovsky district, village Bolshaya Izhora,

Ec

k

Air pollution Nearby sources of atmospheric pollution

3.61·10−1

9.03·10−3

Very low

Highway (200 m)

Primorskoe sh., house 84, Leningrad region, Lomonosovsky district, village Bolshaya Izhora,

59.944524, 29.572829 3.24·10−1

−3.85·10−1

2.37·10−2

Low

Highway (nearby)

Oranienbaumskoe sh., Sergievka Park, Saint-Petersburg, Peterhof

59.892764, 29.835802 −1.13·10−1

5.10·10−2

2.24·10−3

Very low

–

Oranienbaumskoe sh., Park Sergievka, beach R. Cristatel’ka, Saint-Petersburg, Peterhof,

59.892370, 29.836504 4.88·10−2

3.19·10−1

4.65·10−3

Very low

Campfire location (nearby)

18 Stepan Razin street, Saint-Petersburg, Peterhof

59.887401, 29.844458 4.00·10−1

5.50·10−1

3.93·10−2

Low

Stove heating (nearby)

45 Avrova street, Alexandria Park, Saint-Petersburg, Peterhof

59.866860, 29.922673 3.08·10−1

6.25·10−3

1.58·10−2

Low

Road, railway (near)

12 Diveevskaya street Saint-Petersburg, Peterhof

59.897373, 29.866355 5.97·10−1

5.22·10−1

7.07·10−2

Low

Highway (400 m, downhill) treatment facilities (600 m)

147 Primorsky av., Park of the 300th anniversary of SPb, Saint-Petersburg

59.981077, 30.202672 7.83·10−1

1.17

1.59·10−1

High

Western high-speed diameter (500 m)

Shosseynaya str., 58, Leningrad region, Vsevolozhsky district, Yanino-1

59.939226, 30.600066 5.31·10−1

7.92·10−1

7.31·10−2

Low

Plant for mechanized processing of household waste 2

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Pinus sylvestris L., 1753, widely used as a bioindicator, almost everywhere growing in the North-West of Russia (the parameter is the maximum length of needles), as well as for urban areas, especially the old city, where pine is not used as an ornamental plant, the indicator was a mass of acorns of Quercus robur in abundance represented in the park locations of Saint-Petersburg. The results presented in Table 2 indicate that it is possible to detect local contamination even from a single house with stove heating or a campfire used by vacationers. The cleanest of the considered locations are the coast village of Bolshaya Izhora and the park area of Old Peterhof. These locations are characterized as exceptionally clean. The clean is the area of cottage development of the park zone and the coast of Old Peterhof, residential development next to the highway in Bolshaya Izhora, as well as, strange as it may seem at first glance, the territory of the garbage processing plant, StPSUE Plant for mechanized processing of household waste - 2. This apparent discrepancy can be explained by the fact that the enterprise is significantly (more than 500 m) removed from a busy highway, the presence of green spaces Table 3. Saint-Petersburg. Quercus robur. 2019 year. Place of collection of the herbarium

Coordinates

As

Ec

k

Air Nearby pollution sources of atmospheric pollution

Dubkovskoe 60.089547, 29.938870 4.33·10−1 5.96·10−1 4.60·10−2 Low highway, Park “Dubki” Saint-Petersburg, city of Sestroretsk

–

19, 25 line, 59.933997, 30.257468 1.38·10−1 4.47·10−1 1.15·10−2 Low Vasilyevsky island, house 19, garden “Vasileostrovets”, Saint-Petersburg

Highway (nearby)

59.850981, 30.037416 4.30·10−1 7.00·10−3 3.08·10−2 Low

Highway (nearby)

3zh Frontovaya street, Orlovsky Park, Strelna village, Saint-Petersburg

17 Ushakovskaya 59.982975, 30.307175 4.92·10−1 1.80 nab., Stroganov Park, Saint-Petersburg

1.76·10−1 High

Highway (nearby)

59.721500, 30.417900 4.65·10−1 2.13

2.25·10−1 High

Highway (nearby)

41 Oktyabrsky av., Oktyabrsky Boulevard, Saint Petersburg, Pushkin

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between the highway and the territory of the enterprise, as well as the fact that the main technological process of waste processing is composting. Consideration of the location located at a similar distance from the highway, next to the treatment facilities (biotechnological waste water treatment) in Old Peterhof shows a practical coincidence of the values of k. The dirtiest location (from the ones considered) is the 300th anniversary of St. Petersburg Park. This is due to the fact that they are close to the most important sources of pollution – urban highways. The results obtained for Quercus robur (Table 3) are similar to the results for Pinus sylvestris L., 1753 – the observed values of bioindicators clearly coincide with the known data on contamination of examined locations, but a smaller sample size is required to obtain consistent estimates of asymmetry and excess (Fig. 2).

3 2.5

Ec

1.5

Sample size, sufficient for calculaon Ec (n=230)

1 0.5 0 -0.5 -1

-1.5

10 30 50 70 90 110 130 150 170 190 210 230 250 270 290 310 330

Volumes As and Ec

2

As

Sample size, sufficient for calculaon As (n=250)

Sample size (n), pieces Fig. 2. Dependence of the acorn mass asymmetry and excess on the sample size. Place of collection of the herbarium - Saint Petersburg, garden “Vasileostrovets” (59.933997, 30.257468).

In general, it can be stated that the gradation of ecological well-being at the herbarium collection point by the value k, adopted for Pinus brutia var. pityusa (Steven) Silba, 1985, can be applied to Pinus sylvestris L., 1753, and Quercus robur, which makes it possible to map the same location for different species, if the main species is not present at the required control point. Given the same density, the mass of acorns can be replaced by the area of their projection on the plane, which is also easy to measure relatively accurately when photographing with a smartphone camera and image recognition.

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4 Conclusions Asymmetry and excess used as indicators of Pinus sylvestris L., 1753, Pinus brutia var. pityusa (Steven) Silba, 1985, Quercus robur is a fairly sensitive tool for detecting environmental pollution and, consequently, identifying locations that are promising for searching for organic pollutant destructors. When using the studied indicators, comparable results are obtained, which allows us to use of “interchangeability” in cases where the main plant-indicator is not in the desired location. When processing experimental data, it is necessary to investigate the dependence of the sample estimate on the sample size and use a sample size that is consistent with the estimate. Acknowledgment. The work was performed within the State task of the Ministry of Science and Higher Education of the Russian Federation (785.00. X6019).

Authors’ Contribution. All the authors read and approved the final manuscript. The role of the authors in the work was distributed as follows: Kozlov G. V.-idea, herbarium collection and data generalization, checking calculations, discussion, writing the paper. Pushkarev M.A. - data processing (Table 2), discussion of results, editing of the paper. Kozlov A.G. - herbarium collection and primary data processing on Pinus brutia var. pityusa (Steven) Silba, 1985 (Table 1) within the framework of a training research project. Perepelitsa E.S. - collection of herbarium and primary processing of data on Quercus robur (Table 3, partially Table 2) as part of the course work on the discipline “Biological statistics”.

References 1. Kozlov, G., Pushkarev, M., Mokhna, V.: Phenatrene biodestructors isolated from soils of large cities. In: E3S Web of Conferences, vol. 135, p. 01052 (2019). https://doi.org/10.1051/e3sconf/ 201913501052 2. Chudzinska, E., Pawlaczyk, E.M., Celinski, K., Diatta, J.: Response of Scots pine (Pinus sylvestris L.) to stress induced by different types of pollutants – testing the fluctuating asymmetry. Water Environ. J. 28, 533–539 (2014). https://doi.org/10.1111/wej.12068 3. Ivanov, V.P., Ivanov, Y.V., Marchenko, S.I., Kuznetsov, V.V.: Application of fluctuating asymmetry indexes of silver birch leaves. Russ. J. Plant Physiol. 62(3), 340–348 (2015). https://doi. org/10.1134/s1021443715030085 4. Reimchen, T.E.: Parasitism of asymmetrical pelvic phenotypes in stickleback. Can. J. Zool. 75, 2084–2094 (1997). https://doi.org/10.1139/z97-843 5. Bowman, K.O., Shenton, L.R.: Omnibus test contours for departures from normality based on √ b1−− b1 and b2. Biometrika 62(2), 243–250 (1975). https://doi.org/10.2307/2335355 6. Serebritsky, I.A.: Report on the environmental situation in Saint-Petersburg in 2018. Sezamprint LLC, Saint Petersburg (2019) 7. Kashparova, E., Levchuk, S., Morozova, V., Kashparov, V.: A dose rate causes no fluctuating asymmetry indexes changes in silver birch (Betula pendula (L.) Roth.) leaves and Scots pine (Pinus sylvestris L.) needles in the Chernobyl Exclusion Zone. J. Environ. Radioact. 211, 105731 (2020). https://doi.org/10.1016/j.jenvrad.2018.05.015

Probabilistic Models of the Functioning of Composite Structures with Thin-Sheet Cladding and Material-Energy-Saving Heat Insulation Victor Bobryashov1

and Nikolay Bushuev2(B)

1 TSNIISK Named After Koucherenko V.A. Research Center of Construction Joint Stock

Company, 2nd Institutskaya St., 6, Moscow 109428, Russia 2 Moscow State University of Civil Engineering, 26, Yaroslavskoye Shosse, Moscow 129337, Russia [email protected]

Abstract. The models of the operation of enclosing composite structures using the theory of stochastic processes are considered. It is established that they are stationary. Numerical characteristics of random processes are given on the example of snow impacts, including taking into account entropy scientific approaches. The hierarchy of failures of non-mechanical origin in assessing the indoor climate is given. The use of the proposed models, building rules, standards, instructions, recommendations is advisable for thermal protection of buildings and structures, since resistance to impacts can reduce emissions into the environment by about 130 kg/m2 , if their parameters are fulfilled according to SP 50.13330.2012 “Thermal protection of buildings”. The introduction of 30 million M2 of structures per year reduces the equivalent fuel consumption by about 3.9 × 106 tons. The proposed models of energy-saving structures are the most environmentally friendly of all traditional solutions. They have no analogues in environmental friendliness and emissions of toxic substances into the environment. Keywords: Polymer composite materials · Probability distributions · Strength

1 Introduction Impacts on the building envelope are random sequences of stochastic processes [1–6]. The response to the effects of snow, wind, ice, temperature and humidity is a random variable. Therefore, it is necessary to create fencing models that take into account these complex impact processes. The loading of layered structures with effective thermal insulation was estimated based on the theory of stochastic processes and the theory of emissions of random functions [1–4, 6]. Particular attention is paid to stationary random narrow-band, broadband,

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 685–697, 2021. https://doi.org/10.1007/978-3-030-57453-6_65

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ergodic processes. It is shown (1) that the centering of processes as the difference between a random function and its mathematical expectation X 0 (t) = X (t) − mx (t)

(1)

it leads loads, creep, relaxation and other to stationary processes. Since the centered processes have positive and negative values, therefore, the mathematical expectation and variance for them are “zero”. Actions according to (1) make it possible to remove strict restrictions on the development of mathematical expectation mx(t) and variance Dx(t) in time. Then the basis for classification is only a correlation, normalized function of the process [1, 3], their invariance with respect to any time shifts indicates the stationary nature of random processes, which can be narrow-band, broad-band. If the correlation, normalized function tends to zero for a long duration of the process in time, then the random process is ergodic and its characteristics can be obtained from one implementation by time averaging. Note that from the point of view of the physics of the process, the correlation normalized function determines the internal structure of the random process [2, 3]. The problem of choosing the laws of distribution of influences and bearing capacity in the framework of the scientific triad: “mathematical model - algorithm - computer program” [7] is considered and discussed. The development of probabilistic models of the functioning of enclosing structures should be preceded by the creation of deterministic mathematical models - the basis for a comparative assessment of the reliability of structures. The deterministic solution raises a number of significant objections based on the random nature of the effects and properties of materials that develop over time. The possibility of using the theory of “infinitely divisible laws” for sums of independent random variables, Lindeberg conditions [2] - conditions that must be imposed on members so that their functions converge to a certain distribution law. Moreover, the conditions of convergence lead to different laws, and the main thing is that a fixed law is not necessarily “normal” [2, 4, 8]. The conditions for convergence to the laws of extreme values of Gumbel, WeibullGnedenko, Fischer-Tippet, Poisson, Gauss-Laplace and Pearson are given. Particular attention is paid to the method of analyzing experimental results by the method of numerical characteristics, which does not depend on the type of probability distributions. Numerical characteristics are widely used in assessing the reliability of structures using the “moment method” and in determining the safety index [2, 3]. The question of convergence of impacts, parameters of strength to a certain distribution in accordance with the “criteria of agreement” of Pearson, Kolmogorov, Smirnov is discussed. In some cases, they cannot serve as a “measure” for choosing the distribution of laws without taking into account the physical nature of the consequences and reactions (force, bearing capacity).

2 Materials and Methods The load can be specified according to one-dimensional asymmetric, symmetric laws or in the form of a random process, strength - according to one-dimensional laws of probability distribution or in the form of random variables. In the latter case, the authors

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have not yet found an analytical solution, but the authors investigated the experimental result under the influence of a constant load and response in the form of a random process to many implementations [8, 9]. It is necessary to analytically establish the type, form, parameters of the probability distributions of impacts and strength, which do not “contradict” the experimental results. It is desirable to have probability distributions with interpretability properties (the ability to give constants a certain meaning), a limited number of parameters, ease of use, etc. [1]. For comparison, various models of the functioning of structures are considered - symmetric, asymmetric, models of random (non-stationary), stationary (broadband) processes. A detailed analysis of scientific works [1, 2, 5, 7–9], the authors’ own research on probabilistic physical models allow us to make proposals for assessing impacts, bearing capacity and, accordingly, choose models that should take into account the following scientific facts for the proposed research option: – climatic effects on the building envelope are the sum of constant static, variable pulsating effects, including temperature outside and from the premises, solar radiation, humidity effects; – numerous processing of random load implementations [10–12, 14] showed that random influences and random responses (non-stationary) practically known in construction can be reduced to stationary if the process is reduced to a centered one and the theorem known in probability theory is used that centered the process is characterized only by a correlation function. This removes the strict condition about the constant of mathematical expectation, and if the experimental values of the correlation function relative to the main diagonal are approximately the same, then the process is stationary; – under the conditions indicated above, it becomes possible to apply the theory of spectral representations, the method of canonical decompositions of functions, the theory of emissions for stationary processes. The goal is to establish the type of process (narrow-band, broadband, ergodic, “white noise”) and theoretically determine the values of extrema, the laws of distribution of voltage amplitudes, the number of zeros per unit time (effective frequency of the process), the irregularity coefficients of the process, the broadband coefficients (width of the energy spectrum); – according to the found characteristics of irregularity, broadband, a random process can be simplified using well-known methods of schematization of random processes (rain-rain method, extremum method, full-cycle method); Numerous processing of random load implementations performed by the author and other authors [8, 10, 11] showed that random effects and random responses (non-stationary), can be reduced to stationary if the process is reduced to centered. We use the theorem that a centered process is characterized only by a correlation function. This removes the strict condition on the constant of mathematical expectation, and if the experimental values of the correlation function with respect to the main diagonal are approximately the same, then the process is stationary;

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– under the above conditions, it becomes possible to apply the theory of spectral representations, the method of canonical decompositions of functions, the theory of radiation for stationary processes. The goal is to establish the type of process (narrowband, broadband, ergodic, “white noise”) and theoretically determine the values of the extrema, the laws of the distribution of voltage amplitudes, the number of zeros per unit time (effective frequency of the process), the unevenness of the process, the coefficients of broadband (width of the energy spectrum); – according to the found characteristics of irregularity, broadband, the random process can be simplified using well-known methods of schematization of random processes (rain-run method, extremum method, full-cycle method). A feature of the functional purpose of light building shells with effective thermal insulation is the presence of several absolute, functional limit states [6]. Many authors and research groups from foreign countries, in addition to limit states for bearing capacity and deformability, introduce limit states for fire hazard, lighting, etc. Some proposals include up to 17 signs of a failure in air quality (microclimate of buildings). Fire hazard suggestions include flammability, smoke, toxicity, fire spread, and more. Failures “parameter - tolerance field” [12] are also taken into account. In addition, the features of the theory of reliability of structures should be taken into account [7, 13, 14]: – there is no organization to collect information about failures and their intensity; – inadequate control over the reliability of services at enterprises of production structures; – the presence of technological internal stresses in the manufacture of facing structures. This is not a complete list of faults and their scientific interpretation, which must be understood, since the experience of their implementation in construction lasts no more than 50 years. Their use in important special areas, for example, in translucent shelters, racks of pulse voltage generators, hydroacoustics, meteorological shelters, leads to the concept of failure of dielectric, vibration-absorbing and other characteristics. Much scientific work must be done on the classification of failures. Unfortunately, in scientific approaches to the classification of failures of building shells there is no consensus. Materials on this issue are not systematized and are far from accepted terminological assessments, where failure is considered a violation of the operational state of the technical system. It is clear that each element of the system can be considered as a single one. In this regard, the building envelope in the building system, apparently, can be considered as functionally connected (by the principle of maintaining operability) in a parallel circuit due to multi-span. And their failure occurs after the failure of all elements. The concept of malfunctioning of enclosing structures should include those functional parameters that lead to a decrease in the efficiency of only operational indicators. However, other functional parameters (for example, depletion of the paint resource, corrosion of fillers, drains, etc.) lead to the concept of a defect or to the concept of the criticality of failures depending on their consequences, as is accepted in the norms of ISO, IEC and others. In some works [1], not only the above parameters of the enclosing structures are normalized, but also the microclimate of buildings and residential premises (temperature difference, amplitude of temperature

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fluctuations on the inner surface of the enclosure, illumination, etc.). This leads to the concept of environmental disruptions. Therefore, an extended concept of probabilistic models of climatic effects is proposed [1, 4], associated with a subgroup of ergonomic indicators. Technological processes affect the choice of a model of functioning, reliability and bearing capacity of structures. The indicated reliability indicators are achieved in the manufacture of structures. Therefore, the most important for the effective functioning of structures with effective thermal insulation is the input control of raw materials, selective control of characteristics during acceptance tests, process control, and much more. Without solving these problems, obtaining high-quality wall structures and ensuring their reliability becomes problematic. By the model of the functioning of enclosing structures, we mean the probabilistic ratio of stresses proportional to loads and strength, which describe the conditions of failure-free operation or functional parameters, as the solution of formula (2) - the product of the integral stress function by the density of the distribution of strength [5, 6, 13]:  ∞ (2) Pf = [1 − FS (r)] · fR(r) dz −∞

To assess the reliability or probability of failure, it is necessary to establish the laws of distribution of influences and the bearing capacity of building envelopes. This problem was solved with the help of a probabilistic analysis of impacts in different regions of the Russian Federation and bearing capacity at all plants of the USSR and the Russian Federation producing sandwich pagnels. In total, more than one hundred thousand tests were summarized and analyzed, including tests conducted in foreign countries (68 thousand for sheet metal). Thus, research has a significant basis as a source of reliability, standardization of the parameters of building envelopes and the creation of their models.

3 Results and Discussion The basic principles of reliability are described in [2]. According to [5], the choice of the probability distribution function is performed for constant and temporary Gaussian influences with an admissible nonzero probability. Negative values - according to the logarithmically normal distribution, the Weibull, Pearson type III distributions, and the extreme Humbel values. The first understanding of these proposals was stated by the authors in connection with the development of SNiP “Reliability of building structures. Basic Provisions for Calculation” (draft 1990) and introduction [5]. It was published in the collection of scientific articles TsNIISK “Actual problems of research.” on the theory of constructions”, part 1, 2009 with the aim of further developing the method of limit states. When assessing impacts, it was found that [8, 10, 11] in the field of scientific analysis, the main impact scheme is underestimated - a complex “random process of time”, which is an obvious fact that needs to be developed. After analyzing numerous publications, the authors formulated mathematical algorithms for assessing the effects of snow, wind, humidity, temperature, solar radiation, etc. Published in various sources [8–11]. The selection of suitable, adequate probabilistic models mentioned above met the requirements of yuri.

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Estimating the real climatic effects and experimental results taking into account entropic scientific approaches, the authors establish that these are mainly analytical models of the so-called “exponential type”. It is necessary to analyze this single model of a wide class of effects according to [13].      χ − Xy α α  (3) exp − P(χ ) = 2λ(1/α) λσ  where α is the exponent, set approximately according to the “K − χ” diagram using the experimental ordered variational distribution series, and the values of the entropy coefficient Ke are determined by the formula: (4) Counter excess χ is established from the expression √ χ =1 ε

(5)

Where ε is the kurtosis of the distribution. Models of an “exponential type” of a general form (proved by the authors’ studies) were introduced based on physical considerations and completeness of calculations. At the same time, the average periods of atmospheric impact repeatability at the highest annual values within one year, fifty, one hundred years were taken with reliability indices β from 2.8 to 5.2 (according to Eurocodes), sensitivity coefficient αS = 0.8 (for prevailing loads), reliability classifications according to [14] - low, medium, high risk, taking into account economic, social, environmental consequences. The proposals of the CIB, the Structural Safety Committee, Ellingwood (USA), according to the standards of the American Concrete Institute (ACI 318-83), as well as metal structures (β = 3.1; β = 3.2), respectively, are considered. The scientific considerations adopted above are fully correlated with [12] regarding the use of physical methods for calculating reliability. As an example, let us consider a model of snow loads for the Kolyma UGKS districts about the annual water reserves in the snow cover of the Debina, Ortukan, Khaltynyh - (forest), Omek-gan, Maduna, Ola-4, shallow - (forest). They were presented by the authors in the form of a random process lasting 44 years (Fig. 1, 2). Analyzing the results, we notice that for the period 1950–1951. In the snow cover there are significant excess water supplies from the average level. As a result, it turned out that the average variability in the “forest” (CS4 = 0.423) is greater than in the “field” (CS4 = 0.305). An attempt to present the excess as abnormal and exclude from the estimates of the average value, asymmetry, excess was not convincing. It is difficult to imagine that the variability in the “forest” is greater than in the “field”, given the movement of snow due to the influence of the wind.

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Оrtuкаn-480, field

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100 0 300

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200 100 0

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Fig. 1. Snow cover – field.

Fig. 2. Snow cover – forest.

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For the purpose of a deeper analysis of probabilistic random influences (sequences), we establish the value of the mathematical expectations of snow loads q¯ , as well as the index of the non-uniformity of the random process.  θ = N0 Ne (6) where N0 is the number of intersections by ascending branches of the process of level q¯ ; Ne is the number of extrema of the same process, according to the procedure proposed by the authors in [11]. Add to theabove the value of the coefficient of broadband random process of snow loads μ = Ne N0 , the reciprocal of θ. On average, for all implementations, μ is more than 0.93. Applying the elements of correlation functions according to the algorithm [1–3], we have: (7) n  mx (tk ) =  Dx (tk ) =



i=1 xi (tk )

n 2 i=1 [xi (tk )]

n

(8)

n mx (tl )] [

2

n n−1

(9)

Here is the correlation function reflecting the internal structure of the snow load for its four realizations in the “field”, in the “forest”. Dividing (7) into the product of the standards that  are established from (9), we obtain the values of normalized correlation functions ρx t, t I . (10) Changes by years in the “forest”, “field” are presented in Figs. 3, 4. They indicate that the process of exposure in the “forest” for four implementations is stationary, close to “ergodic”, which can be estimated by the average values of the process for one implementation in time, in contrast to the “field” process, which is stationary in the “broad sense” according to the scientific interpretation in [1–3]. The invariance of the processes of influence with respect to the change in the normalized functions ρx t, t I ., shown in Fig. 5, the spectrum of which is constant in time, i.e. the exposure process in this parameter is close to “white noise”. Interesting, significant is the coincidence of the maximums of snow cover in the “forest” and in the “field” in the area of 53–55 years. The correlation functions (Fig. 5) vary uniformly in time and are independent of the magnitude of the shift along the time axis.  The correlation between the cross sections of the exposure process is significant ρx t, t I > 0.6. Here we do not consider special issues related to the basic properties of stationary random processes that are devoted to x spectral decompositions, including in complex

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p`x(t)

1 0.8 0.6 0.4 0.2 0

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Fig. 3. Normalized correlation function of the snow cover in the “forest” according to 4 realizations: Omeck-gan-540, Madown-522, Ola-4, Shallow-water-57 (1948–1985).

1

p`x(t)

0.8 0.6 0.4 0.2 0

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Fig. 4. Normalized correlation function of the snow cover in the “field” according to 4 realizations: Debin-325, Ortukan-480, Khatynnakh-782, Kulu-668 (1948–1985). a) 1941-1985

b) 1948-1985 p`x(t)

p`x(t)

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years 41

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Fig. 5. The invariance of the processes of influence of normalized functions.

form. These questions are examined in detail in the works of V.I. Tikhonova, B.V. Gnedenko [2], V.S. Pugacheva [1], E.S. Wentzel [3], A. N. Kolmogorov, where close attention

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is paid to the work of N. Wiener-Khinchin. In the authors’ work, special attention, preference is given to the correlation theory of random functions, because they can clearly be determined based on experimental test results, as shown above. The values of the correlation, normalized functions are not given below only for technical reasons. In the work of B.V. Gnedenko emphasizes that the use of a correlation theory based on the determination of the first and second points cannot replace the probability distribution of parameters. Therefore, we will further consider the probabilistic characteristics of snow impacts using the Omeck-gan-540 meteorological station (forest) as an example, the experimental and theoretical statistical probabilities of snow cover are given in Table 1 and Fig. 6. The best approximation of equalizing frequencies is Gram-Charlier type B. Table 1. Experimental and theoretical statistical the probability of snow cover of the weather station Omeck-gan-540 (forest). № x

Expfrequencies Theoretical equalization frequencies for distributions Gram-Charlier Gram-Charlier Pearson Gauss-Laplace Poisson type A type B type VII

1

110.25 11

8.96

10.73

6.29

6.72

9.67

2

140.75 14

13.66

15.11

11.47

10.57

13.23

3

171.25

7

8.04

5.65

10.42

9.87

9.06

4

201.75

3

2.33

2.61

4.89

5.47

4.13

5

232.25

0

1.75

2.22

1.51

1.79

1.41

6

262.75

3

1.27

1.23

0.39

0.35

0.39

16

Statistical Probabilities, n

14 12

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Gram Charlie type A

Gram Charlie type B

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Gauss-Laplace

Poisson

Fig. 6. Experimental and theoretical probabilities of the snow cover of the weather station Omeckgan-540 (forest).

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4 Conclusion 1.

2.

3.

4.

5.

6.

7.

8.

The problematic issues of the functioning of models of composite building envelopes with thin-sheet surface cladding and material and energy-saving thermal insulation under random exposure to wind, snow, aggressive environments and other loads are considered. Impacts on building envelopes are random processes of random sequences. Reaction to the effects of random variables. It is established that the impact on the building envelope is mainly interpreted as a random stationary process (narrowband, ergodic, broadband, “white noise”) of the so-called “exponential” type, in contrast to the arcsine, bimodal, Cauchy and others. It is shown that, by centering the processes, the difference between a random function and its mathematical expectation X 0 (t) = X (t) − mx (t) can lead to relaxation, creep and damage to stationary, which reduces the stringent restrictions on the development of mathematical expectations mx (t) of the variance of the process over time. Therefore, to evaluate the process, only the correlation function normalized by variances of the process is used - the latter determines the internal structure of the random process. In addition to GOST 23486, 21562, 4.220, developed by the authors, the classification of failures of mechanical and non-mechanical origin is given priority. Close attention is paid to the hierarchy of failures of non-mechanical origin. They are most important for the class of structures under consideration. It is noted that one of the main features of composite walling is the presence of several functional limit states. Their far from exhaustive classification is given, especially for special structures whose interpretation is far from perfect. There are no legislative bodies in the construction complex for registering failures and, therefore, for assessing and preventing them. Along with other researchers, probabilistic models are proposed as a relationship between stresses and bearing capacity. Offers of Boloatin, Rzhanitsyn, Kapura, Fredentol, Shpet, Gnedenko and others. It is proved that the calculated values of the influence of strength are sufficient for its reliability (confidence probability of no more than P = 0.99 and a quantile value of 2.58). To assess the load and response, the entropy “k-chi” indicators are used for the diagrams of the ordered variational distribution series. The “k-chi” diagram in rectangular coordinates allows you to approximately determine the exponent of the exponent type. Accepted by the authors on the basis of physical considerations and completeness of calculations with average recurrence periods of atmospheric effects for one year, twenty five, fifty and one hundred years with a reliability index β according to Eurocodes, GOST R ISO 2394 from 2.8 to 5.2. A detailed assessment of the load of enclosing structures from snow impacts is given for eight districts of the UGKS (Kolymsky) in the “forest” and “field”. Presented as a random process (random sequence) in 44 years. The calculation results are presented separately in the “forest” and in the “field”. Using elements of the theory of correlation, the developed calculation method established the parameters of a random process - correlation, normalized correlation functions. They are

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presented in the form of graphs showing that the process of snow exposure of the implementations is stationary, close to ergodic. 9. The invariance of the processes of action by changing the normalized functions ρx (t, t1 ) is noted. Their spectrum is almost constant in time, that is, the process of exposure in this parameter is close to “white noise”. Normalized correlation functions develop identically and do not depend on the magnitude of the shift along the time axis. 10. As an example of eight implementations, experimental and theoretical stochastic estimates of the snow cover of the Omek-gan-540 meteorological station (forest) are calculated using Gram-Charles type A and B, Pearson type VII, Gauss and Poisson. They are clearly shown in Fig. 6 and confirm the hypothesis of distributions of “exponential type”. 11. The article discusses and analyzes problematic issues, hypotheses, suggestions, correlation considerations regarding probabilistic models of the functioning of building envelopes. Their standardization, development of recommendations, guidelines, instructions, technical regulations, SNiPs, Code of practice, methodological recommendations, the implementation of which would allow to achieve results that correspond to the main quality indicators corresponding to the best foreign analogues.

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12. Simankina, T., Kibireva, I., Mottaeva, A., Gusarova, M.: Application of the PERT method in scheduling of construction of apart-hotel for energy consumption economy. In: Advances in Intelligent Systems and Computing, vol. 983, pp. 138–145 (2019). https://doi.org/10.1007/ 978-3-030-19868-8_13 13. Lebedeva, I.V.: The history of the development of domestic standards of snow loads. Bull. SRC “Construction” 3(14) (2017) 14. Bobryashov, V.M., Bobryashov, V.V., Bushuev, N.I.: A probabilistic assessment of the random loading of energy-saving building envelopes. Bull. Res. Center “Building”/Stud. Theory Struct. 3(14) (2017)

Structural Features of Thermoplastic Marking Material with Dispersed Filler Yuri Vasiliev1(B)

, Victor Talalay1 , Andrey Kochetkov2 , Elena Surnina3 Vasily Ratkin3 , and Lyudmila Kozyreva3

,

1 Moscow State Automobile and Road Engineering University,

64 Leningradsky Prospect, Moscow 125319, Russia [email protected] 2 Perm National Research Polytechnic University, 29 Komsomolsky Prospect, Perm, Perm Territory 614990, Russia 3 Saratov State Technical University named after Gagarin Yu.A., 77, Polytechnic st., Saratov 410054, Russia

Abstract. Objective: development of compositions and methods for combining components together to obtain functionally stable heterogeneous composite materials for road marking based on petroleum polymer resins (PPR) and modified dolomite filler. The methodological basis of the work is the modern experience of leading domestic and foreign researchers in the field of creating effective polymeric materials for road marking. The paper used methods of quality control of materials for road marking, as well as modern methods for the study of composites: infrared spectroscopy, thermogravimetric analysis, optical spectroscopy, determination of the specific surface by the Koseni-Farman method, test methods for road surfaces, etc. For static processing, the Excel software package was used. Thermoplastic formulation can be specially selected for different climatic conditions: softer thermoplastic is suitable for very cold climates; medium hard thermoplastic is suitable for temperate climates; high hardness thermoplastic is suitable for hot climates. In order to give increased adhesion bonds between the filler and the polymer, we used modification (sizing) with an AGM-9 organosilane. In this case, the silicon-functional group reacts with the filler, and the organofunctional group reacts with the resin. It is proved that when modified with organosilane of the AGM-9 grade, there is an increase in adhesion bonds between the filler and the polymer. Keywords: Scientific and technical support · Production · Road marking materials · Polymer base · Tests · Thermoplastics · Marking paint · Application

1 Introduction Nowadays, road marking is an effective means of organizing the movement of vehicles, contributing to increased road safety, as well as an increase in vehicle speeds and © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 698–707, 2021. https://doi.org/10.1007/978-3-030-57453-6_66

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throughput of roads. According to the UN, the presence of markings on the road surface can reduce the number of accidents by almost 20%. The use of road marking made of composite materials based on thermoplastics in comparison with traditional paints and varnishes can increase the service life by 5–10 times depending on the intensity of the traffic flow. Despite the higher cost of thermoplastics, their share in road construction is growing from year to year and reaches 30% in the regions of the Russian Federation with developed road infrastructure. The issues of creating new types and methods of using road marking were dealt with at the Federal Road Agency, MADI, OJSC GIPRODORNII, FSUE ROSDORNII, OJSC SOYUZDORNII and other organizations. Known works of 3M firm (USA), scientists and specialists from France, Finland, Sweden, Canada and other countries [1–10]. However, to date, the task of creating and correcting the formulations of effective marking coatings for specific application conditions has not been solved. Among the promising technical solutions to this problem is the production of thermoplastic marking materials based on petroleum polymer resins (PPR). Their application provides the required indicators of uniformity and durability of the marking and their compliance with the requirements of regulatory documents [1–3]. The marking properties and its service life are largely determined by the effectiveness of formulation development and the technology of production of the materials used. Moreover, the marking material must have such qualities that would allow to preserve the marking properties and the required service life in the most diverse conditions of its operation, which to a large extent corresponds to modern polymer-based composite materials. Therefore, the task of developing formulations for marking roads, ensuring their high performance, as well as methods of scientific support of their production is relevant. The study of the physicochemical properties of materials based on a polymer is carried out depending on the composition consist and their structure based on infrared spectrometry [2].

2 Research Methods Objective: development of compositions and methods for combining components together to obtain functionally stable heterogeneous composite materials for road marking based on petroleum polymer resins and modified dolomite filler, methods for their refinement for specific climatic and road conditions. The methodological basis of the work is the modern experience of leading domestic and foreign researchers in the field of creating effective polymeric materials for road marking. The paper used methods of quality control of materials for road marking, as well as modern methods for the study of composites: infrared spectroscopy, thermogravimetric analysis, optical spectroscopy, determination of the specific surface by the Koseni-Farman method, test methods for road surfaces, etc. For static processing, we used the Excel software package. It is assumed that the thermoplastic formulation can be specially selected for different climatic conditions: softer thermoplastic is suitable for very cold climates; medium hard thermoplastic is suitable for temperate climates; high hardness thermoplastic is suitable for hot climates.

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3 Results of Study When analyzing the components of a composite thermoplastic for road marking, methods for increasing the strength characteristics of a composition were studied. This possibility arises when using filler modifiers – substances that increase the adhesion of fillers and the matrix of the composite [1–9]. Therefore, when conducting the selection of effective components, the characteristics and compatibility of thermoplastic components were investigated. First of all, this refers to the matrix part of the composite – petroleum polymer resin [1–3]. Modification of the petroleum polymer resin with maleic acid (A.A. Artemenko method) is manifested by an increased acid number up to 2.4 mg KOH/g compared with unmodified samples. This indicates that during the modification process, maleic acid was grafted onto macromolecules of a petroleum polymer resin. The spectrum of the petroleum polymer resin filled with microdolomite is a superposition of the spectra of microdolomite and the petroleum polymer resin, which indicates the absence of chemical interaction between the components of the system. Filling was carried out by heating the resin to temperatures in the range 180 °C– 200 °C with continuous mixing for 30 min. As a result, an increase in the peak of the C=O bond is observed in the spectrum, caused by partial oxidation of the resin upon heating. Obviously, to reduce the effect of oxidation, it is advisable to mix the composite at lower temperatures. In order to give increased adhesion bonds between the filler and the polymer, we used modification (sizing) with an AGM-9 organosilane. For this, a water-alcohol solution of AGM-9 was prepared in the proportion of H2 O:C2 H5 OH:AGM-9 = 20:10:1. The degree of adhesion of an organosilane with a particulate filler is mainly related to the topography and surface characteristics such as porosity, wettability and adsorbed moisture. Substituted alkoxysilanes (SAS) or AGM-9 ((3-aminopropyl)triethoxysilane, H2 N(CH2 )3Si(OC2 H5 )3 ) are modifiers that are used in the form of aqueous and aqueousalcoholic solutions, aqueous emulsions, as well as in pure form. In this case, two types of treatment are used: pre-treatment of the filler, which consists in active mixing with organosilane or its solution and further drying; its introduction by mixing the filler with an organic film former at different stages of the process. The first treatment option is better due to the good distribution of the modifier on the surface of the filler. The compatibility of the modifier with organic film formers is determined by the nature of the functional group included in their composition. The formation of bonds first occurs as a result of the hydrolysis of the hydrolyzable part. Then, the processes of formation of organo-oligomers and the interaction of their hydroxyl groups with hydroxyl groups of the OH of the filler surface are carried out simultaneously with the formation of covalent bonds. Water is a by-product of the polycondensation reaction. At the interface, only one bond of the silicon atom with the filler surface is formed. This structure allows the use of new bonds as a connecting bridge between the organic matrix (resin) and inorganic filler, which usually do not chemically react with each other. In this case, the silicon-functional group reacts with the filler, and the organofunctional group reacts with the resin. After condensation with the hydroxyl groups of the filler

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surface, the remaining groups retain the ability to form hydrogen bonds or to condense with each other. Thus, due to the combination of covalent and hydrogen bonds, organosilane modifies the inorganic surface, giving it the characteristics of organofunctional. Figure 1 shows the dynamics of the wetting of dolomite powder MD40 with a solution of organosilane AGM-9.

Fig. 1. Process of wetting and impregnating thin sections of dolomite with 10% solution of AGM-9 in ethanol.

After the filler treated with the organosilane solution was dried, it was mixed with the resin, and the organofunctional groups of the modified MD interacted with the carboxyl groups of the treated resin. Accordingly, it can be argued that the adhesion between the mineral particles of the filler and the petroleum polymer resin in this case occurs not only by flowing the adhesive into pores and cracks on the surface of the substrate with subsequent solidification (microrheological mechanism of adhesion), but also due to the formation of strong chemical bonds. Polycondensation occurred with OH groups contained in microdolomite, with the release of a simple aliphatic diethyl ether CH3 CH2 OCH2 CH3 . When a sizing filler is introduced into the composition of a petroleum polymer resin, the coupling of the sizing agent to the macromolecules of the polymers included in the resin takes place. After treatment with the AGM-9 modifier, particles of dolomite – filler from neutral become active, which is manifested in an increase in their dispersibility and degree of the polymer filling. This becomes possible due to the formation of a chemical bridge from the bonds “dolomite – silane – resin”.

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Relative elongation, %

The formation of cross-linking bridges leads to the fact that the volume of the composite, consisting of a matrix – petroleum polymer resin and a filler sizing with silane – dolomite, forms a spatially cross-linked structure. At an elevated temperature and active mixing of the ingredients during the preparation of the mixture in the proportion of 70% dolomite: 30% petroleum polymer resin No. 1, a rapid evolution of carbon dioxide CO2 occurs, the sources of which are charged carbonate groups CO3 2− . Due to the rapid progress of the cross-linking reaction, neutral CO2 molecules turn the composite into a porous material, and oxygen ions oxidize the resinous part, which manifests itself in the darkening of the entire mass. The dynamic characteristics of the composite are presented in Fig. 2. 4 3,5 3 2,5 2 1,5 1 0,5 0 0

1

2

3

4

5

6

7

Tension stress, MPa Composition 1

Composition 1М

Fig. 2. Elastic characteristics of the composition 1 with unmodified and modified dolomite.

From the above experimental data, it is possible to draw a well-founded conclusion that the obtained composite material is hard and brittle and is not suitable for use in road marking. The results obtained, at first glance, suggest that the sizing of dolomite with organosilanes is impractical due to the receipt of a highly cross-linked and brittle structure. However, the effect of increasing strength as a result of the formation of a spatially cross-linked structure allows to suggest the possibility of using this effect to improve the properties of the composite. In fact, the result obtained is similar to the process of formation of ebonite – a vulcanization product of rubber with a large amount of a crosslinking agent – sulfur. Often the cross-linked structure of ebonite excludes the presence of elasticity, but at the same time gives high strength. Avoiding the achievement of high strength of the composition due to the formation of a highly cross-linked structure (its critical state), in this work, we propose the use of a combined combination of modified and unmodified microdolomite in a ratio of 10–15:85–90, respectively. In this case, the formation of a structure is achieved, which is a rare grid (by analogy with rubber), which has increased strength and, at the same time, sufficient elasticity, providing good performance.

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Interlayer shear strength, MPa

The dependence of the strength on the content of the modified AGM-9 dolomite is shown in Fig. 3. The dependence of the elongation of the composite on the content of the modified dolomite is shown in Fig. 4. 7,5 7 6,5 6 5,5 5 4,5 4

0

5

10

15

20

25

Content of modified dolomite, % Composition 1

Composition 2

Composition 3

Elongaon at rupture, %

Fig. 3. Dependence of strength on the content of the modified AGM-9 dolomite.

7 6 5 4 3 2 1 0 0

5 10 Content of modified dolomite, % Composition 1 Composition 2

15

20

25

Composition 3

Fig. 4. Dependence of the elongation of the composite on the content of the modified dolomite.

4 Discussion of Results Studies show that the best result is obtained when using a mixture of modified and unmodified dolomite in a ratio of 10–15:85–90. The content of the resin, which is the binder in the thermoplastic road marking, is a factor on which the wear resistance and thermal expansion coefficients of the composite depend. Considering that the marking is applied to asphalt concrete, which has different temperature expansion coefficients, the deformation characteristics of the marking should exceed the similar properties of asphalt concrete.

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Therefore, with a strong adhesion of the thermoplastic and the road surface with changes in the temperature of the external air, the material ruptures if its temperature coefficient turns out to be less than that of asphalt concrete. As a result, there are irregularities in the continuity, which leads to the destruction of road markings. It is believed that the adhesion of the thermoplastic to the road surface is directly proportional to the durability of the marking. This explanation is rather controversial, since it is difficult to imagine that physical and chemical bonds can arise quite quickly in places of rupture. This is due to the fact that foreign thermoplastics have greater elasticity compared to domestic ones and respond better to crack formation in asphalt concrete. The developed compositions 1 and 2 in comparison with the analogue have increased adhesion to asphalt concrete and elasticity in the temperature range from −10 °C to 20 °C. These indicators allow us to conclude that the developed material has the best resistance under operating conditions, especially at low temperatures. Comparative characteristics of the developed formulations are presented in Table 1. Table 1. Comparison of the characteristics of the developed formulations with analog. Parameters

Composition “Crater” Composition 1 Composition 2

Melt flow rate V, g/s (at T = 180 °C) 4.8–5.2

5.0–5.5

4.5–5.2

Softening point Ts , °C

110–112

115–120

105–115

Whiteness, %

80–83

80–82

80–85

σpr at 20 °C, MPa

2.4–3.2

3.5–4.0

2.6–3.0

σpr at 0 °C, MPa

7.5–9.5

9.8–11.3

7.8–8.4

σpr at −10 °C, MPa

14.5–19.0

22.0–25.0

15.6–19.4

at 20 °C

3.5

5

6

at 0 °C

2

3

3.5

Elongation in tension E, %:

at −10 °C

1

2

2.5

Stickiness

Non-sticky

Non-sticky

Non-sticky

Adhesion at T = 20 °C, MPa

1.2–1.5

2.4–2.7

2.0–2.3

Curing time, min

15–17

8–10

12–15

A comparison of the operational characteristics of the developed compounds with an analogue to the resistance to the effects of automobile wheels with various treads (including studded ones) was carried out at the Karusel-2 test site of the Moscow Automobile and Road State Technical University (MADI) (Moscow), Fig. 5 and 6. Each wheel was mounted on its own rod and rolled in test mode at a speed of 90 km/h, running into the tested samples of road thermoplastic. After one thousand cycles, a visual evaluation of the test samples was performed.

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Fig. 5. View of the test site for road materials for repeated exposure of the wheel.

Fig. 6. Installation of samples at the test section.

The state of the samples of marking material on the route of the test site after the tests is presented in Fig. 7.

Fig. 7. Samples of marking material on the route of the test site after testing: I – composition “Crater”; II – composition 1; III – composition 2.

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Field tests showed that after passage in the amount of 1000 cycles, samples II and III were practically not deformed and did not become contaminated, while sample I was contaminated. The macro roughness of the worn part increased from 0.2 to 1.2 mm. The wear rate of road marking samples (the current average scatter of vertical marks) decreased by approximately 5–12%. Further field tests at the test site (4000 passes) showed that the developed composition of the marking thermoplastic is more resistant to repeated loads in operating conditions. Macro roughness was evaluated using a 3D model (digital) based on photographs of tested samples (Fig. 8, Table 2).

Fig. 8. Condition of material samples after testing (3D). Table 2. Test results of the developed compounds on the test stand. Indicator

Sample 1

Sample 2

Sample 3

Pollution

Yes

No

No

Deformability

Yes

No

No

Macro roughness, mm

2.5

More then 4.0

1.5

Destruction

No

Yes

No

Field tests at the test site showed that the developed compositions of the marking thermoplastic are more resistant to repeated loads in the operating conditions.

5 Results 1. The spectrum of the petroleum polymer resin filled with microdolomite is a superposition of the spectra of microdolomite and the petroleum polymer resin, which indicates the absence of chemical interaction between the components of the system.

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2. In order to give increased adhesion bonds between the filler and the polymer, we used modification (sizing) with an AGM-9 organosilane. In this case, the siliconfunctional group reacts with the filler, and the organofunctional group reacts with the resin. It is proved that when modified with organosilane of the AGM-9 grade, there is an increase in adhesive bonds between the filler and the polymer. In this case, the silicon-functional group of organosilane reacts with the resin. To eliminate browning and embrittlement while improving the properties of the composite, it is proposed to use a mixture of modified and unmodified dolomite in a ratio of 10–15:85–90. 3. The effect of increasing strength as a result of the formation of a spatial crosslinked structure allows suggesting the possibility of using this effect to improve the properties of the composite. 4. As a result of field tests at the MADI ring test stand of the developed compositions for road marking based on the petroleum polymer resin, it was found that the developed compositions of the melts of the marking thermoplastic are more resistant to repeated loads under operating conditions (the coefficient of variation of macro roughness decreases by at least 5%).

References 1. Vozny, S.I., Evteeva, S.M., Talalay, V.V., Kochetkov, A.V.: The production technology of thermoplastics for road marking. Plastics 9–10, 45–49 (2014) 2. Evteeva, C.M., Vozny, S.M., Talalay, V.V., Krylov, V.K., Vasiliev, Yu.E., Kochetkov, A.V.: Improving the formulations and production technology of plastic materials for road marking on a polymer basis: monograph. In: Artemenko, A.A. (ed.) RATA, Saratov (2014) 3. Bazhanov, A.P., Evteeva, S.M., Vozny, S.I., Krylov, V.K., Talalay, V.V.: Improving the formulations and production technology of plastic materials for road marking on a polymer basis: monograph. In: Kochetkov, A.V. (ed.) PGUAS, Penza (2015) 4. Filatova, A.V., Dormidontova, T.V.: Research of influence of quality of materials on a road marking of highways. Procedia Eng. 153, 933–937 (2016) 5. Mirabedini, S.M., Jamali, S.S., Haghayegh, M., Sharifi, M.: Application of mixture experimental design to optimize formulation and performance of thermoplastic road markings. Prog. Org. Coat. 75(4), 549–559 (2012) 6. Taheri, M., Jahanfar, M., Ogino, K.: Self-cleaning traffic marking paint. Surf. Interfaces 9, 13–20 (2017) 7. Burghardt, T.E., Pashkevich, A., Mosböck, H.: Yellow pedestrian crossings: from innovative technology for glass beads to a new retroreflectivity regulation. Case Stud. Transp. Policy 7(4), 862–870 (2019). Corrected proof. Available online 9 July 2019 8. Gulotta, T.M., Mistretta, M., Praticò, F.G.: A life cycle scenario analysis of different pavement technologies for urban roads. Sci. Total Environ. 673, 585–593 (2019) 9. Ho, K.-Y., Hung, W.-T., Ng, C.-F., Lam, Y.-K., Kam, E.: The effects of road surface and tyre deterioration on tyre/road noise emission. Appl. Acoust. 74(7), 921–925 (2013) 10. Chen, J., Yin, X., Wang, H., Ding, Y.: Evaluation of durability and functional performance of porous polyurethane mixture in porous pavement. J. Clean. Prod. 188, 12–19 (2018)

Optimization of Thin-Shell Structure Covers from Position of Their Space Stability Sergey Gridnev(B)

, Olga Sotnikova , Leonid Salogub , and Vladimir Portnov

Voronezh State Technical University, Voronezh, Russia [email protected]

Abstract. Calculations of thin-walled concrete dome roofs of circular outline of different type under the influence of operational loadings with use of two modern program complexes are executed. Extent of influence on the intense state of strain (ISS) of dome covering of inclusion in team work of supporting ring from mass concrete and brickwork under different conditions of staying is evaluated. The analysis of features of forms of loss of stability of dome coverings together with supporting ring under different conditions of staying of dome on supporting ring is made It is investigated by the VAT of dome coverings as a part of construction from position of forecasting of possible forms of loss of stability. The technique of the solution of problem of optimization of such design with the choice of criterion and parameters of problem of optimization is constructed. use of opportunities of the Topological Optimization module of the final and element «MidasCivil» computer. Criterion function was considered dependent on thickness of dome, elastic modulus of Poisson’s ratio of material, arrow of raising of dome. Keywords: Dome coverings · Supporting ring · Final and element model · Space stability · Optimization of design · Criteria and parameters of problem of optimization · Stability loss form

1 Introduction Dome coverings are widely used for blocking of flights round or oval in respect of buildings and constructions (circuses, sports and showrooms, lobbies of metro stations, etc.). Application of dome constructions increases in connection with mass construction and recovery of cult constructions recently. Use at design of constructions of different final and element) program complexes (MidasCivil, Sofistik, Lusas, Lira, Ansys, Nastran, Algor, Danfe, Mefisto, Femap) allows to estimate adequately the intense state of strain (ISS) of designs of construction and not to allow emergence of the zones dangerous in terms of destruction and loss of stability. However questions of checks on loss of stability at design of space load-carrying structures in normative documents are stated simply, and is not provided practical recommendations about stability analysis of dome coverings in normative documents. Basis of dome coverings is the dome which represents the space design consisting of cover with vertical axis of rotation and supporting ring (the lantern ring is absent). Object © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 708–720, 2021. https://doi.org/10.1007/978-3-030-57453-6_67

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of research is the thin-walled concrete dome roof of circular outline. One of shortcomings of such constructions is the possibility of irregular shapes of loss of stability. To questions of research VAT and stability of covers in different statements it is devoted a number of works in recent years we Will note works of the Russian scientists [1], and number of publications abroad. Among the latest work on studying of loss of stability of flexible flat covers works [2], including thermoelastic [3, 4] and dynamic stability are devoted [5, 6]. And only work is devoted to optimization of covers [7]. However not enough attention is paid to issues of optimization of dome coverings in construction from position of stability unfairly and these questions demand development and detailed study, especially from engineering positions. Therefore it is obvious that development of approaches for implementation of optimum design of building constructions, in particular dome coverings, is important during creation of rational and economic designs [8, 9]. The purpose of work is creation of technique of the solution of problem of optimization of designs of dome coverings of circular outline under the influence of operational loadings as a part of construction from position of prevention of possible forms of loss of stability. The modern licensed final and element «MidasCivil» computerand the systems of through architectural and construction design of Ing+ the rated MicroFe module are for this purpose used. The task of optimization of geometrical parameters of dome covering and characteristics of material from stability position was set.

2 Experimental 2.1 Basic Provisions Object of research is the round concrete dome roof of the main hall of complex of cult construction of Annunciation Cathedral of Voronezh (Fig. 1) in the plan. This object is chosen for the purpose of further perspective design and construction of cult and spectacular constructions with dome covering in regions as normal, and with special conditions of construction, such as heavy snow load with low temperature indicators both high humidity and temperature indicators. The dome covering represents steel concrete flat cover 6 cm thick from constructive reinforcement in the form of grid of 200 × 200 mm from wire with a diameter of 10 mm. For creation of design model we use from KE library of the rated MicroFe module the shell hybrid final element and the shell final element on the basis of method of movements. At the same time the following provisions are adopted: 1. The covering of dome is simulated by elements of flat cover taking into account shift deformations on shell thickness on the basis of Reyssnera-Mindlin’s theory. 2. Geometrical nonlinearity in calculation is not considered in type of small movements of design. The final and element model from the shell elements with uniform grid for two types of brick supporting ring and mass concrete (Fig. 2) is generated. For the purpose of the choice like final element during creation of final and element (FE) model for further uses are executed pilot numerical surveys VAT of concrete smooth

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Fig. 1. The geometrical scheme of the studied dome with the main geometrical characteristics.

Fig. 2. Type of KE of the rated scheme of dome with monolithic supporting ring.

dome roof with a diameter of 16 m and with a shell thickness of 6 cm with monolithic steel concrete ring the sizes of cross-section of 60 × 60 cm. At the same time KE of method of movements and hybrid KE are used. In Tables 1, 2 and 3 characteristics of materials of the used KE of dome and supporting ring from concrete are provided, and the scheme of their arrangement is shown to Fig. 3. E - elastic modulus; ν - Poisson’s ratio; ρ - density; ρ- multiplier for material density; fss - reduction coefficient shift. rigidity of beam wall; fdp - coefficient of reduction of the turning rigidity of plate; fSb - coefficient of reduction of normal rigidity of beam wall; fP1 - coefficient of reduction of flexural rigidity of plate;

Optimization of Thin-Shell Structure Covers from Position Table 1. Summary table of materials. №

Material name

Type

1

1 (isotheres.)

Isotropic

2

2 (isotheres.)

Isotropic

Color

Table 2. Main characteristics of isotropic materials. Thickness, mm

E, kN/m2

ν

ρ, t/m3

ρ

60

3.00e+7

0.20

2.75

1.00

600

3.60e+7

0.20

2.75

1.00

Table 3. Additional characteristics of isotropic materials. № fss

fdp

fSb

fP1

fsp Cm

Ck

1

0.00 0.00 0.00 0.00 0

0.00 0.00

2

0.50 0.90 0.00 0.90 1

0.00 0.00

fsp - reduction coefficient shift. rigidity of thick plate; Cm - damping coefficient for weight; Ck - damping coefficient for rigidity.

Fig. 3. KE general lay-out from different materials.

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Calculation is executed on combination of loadings: the curb weight and snow load of dome covering with monolithic supporting ring. The analysis of results has allowed to draw conclusion on small discrepancy of results. Further when performing calculations hybrid KE are used. For illustration of the analyzed results below in Fig. 4 diagrams of distribution of meridional tension from the curb weight and snow load when using hybrid KE are shown.

Fig. 4. Diagram of distribution of meridional tension from the curb weight and snow load.

2.2 Numerical Researches VAT of Dome Covering With use of the scheme chosen as KE numerical researches of influence of compatibility works with supporting ring on deformed conditions of intense dome covering on rated combination of loadings in the following sequence are performed: 1. The analysis of the VAT of dome without interaction with the blocked construction is made at hinged staying and with rigid jamming on contour under the influence of loading from curb weight and from the curb weight and snow load; 2. The analysis of the VAT of dome taking into account interaction with monolithic supporting ring the sizes 600 × 600 of class B40 concrete (the system is considered as cover with rigid jamming) under the influence of loading from the curb weight and snow load is made; 3. The analysis of the VAT of dome taking into account monolithic supporting ring by the sizes 600 × 640(h) of lime sand brick of M250 brand on M150 brand solution (the system is considered as cover with hinged interface) under the influence of loading only from the curb weight and snow load is made; 4. The critical value of tension and vertical movement of upper point of dome from combination of loadings of curb weight and snow load are defined.

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Let’s include below some results of numerical researches. In Fig. 5 the deformed type of dome with movement of upper point from the curb weight and snow load at hinged staying is shown. We will use this movement further as criterion of approach of critical condition at stability loss.

Fig. 5. The Deformed Type of Dome from the curb weight and snow load.

The diagram of meridional tension from the curb weight and snow load is shown to Fig. 6.

Fig. 6. Diagram of meridional tension from the curb weight and snow load.

The analysis of numerical results at this stage allow to draw the following conclusions: 1. When calculating on curb weight difference in the dome VAT in interaction with supporting ring from concrete and lime sand brick on solution insignificant by consideration of tangential tension. It makes 0.5% for the minimum tangential and 0.96% for the maximum tangential voltage. 2. When calculating on curb weight difference in the dome VAT in interaction with supporting ring from concrete and lime sand brick on solution considerable by consideration of meridional tension. It makes 20.45% for the minimum meridional and 12.29% for the maximum meridional voltage. 3. When calculating on the curb weight and snow load difference in the dome VAT in interaction with supporting ring from concrete and lime sand brick on solution insignificant by consideration of tangential tension. It makes 0.3% for the minimum tangential and 0.52% for the maximum tangential voltage.

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4. When calculating on the curb weight and snow load difference in the dome VAT in interaction with supporting ring from concrete and lime sand brick on solution considerable by consideration of meridional tension. It makes 20.23% for the minimum meridional and 9.36% for the maximum meridional voltage. Thus, it is possible to draw the general conclusion that the supporting ring gets into team work with dome covering and perceives thrust. It leads to significant increase in meridional tension more for concrete supporting ring. 2.3 The Analysis of Forms of Loss of Stability of Dome Covering at Different Designs of Supporting Ring In the system of through architectural and construction design of Ing+ the rated MicroFe module forms of loss of stability and safety factors of stability of dome covering corresponding to them for the following cases have been defined by the option “Stability”: – without supporting ring; – two designs of supporting ring. At the same time curb weight remained constant, and the snow load increased to the size of critical load. Let’s give below because of limitation of volume we will give only in Figs. 7 and 8 the first forms of loss of stability of thin-walled dome at different staying of dome cover on supporting ring.

Combination - 2, form - 1; Stability Safety factor = 92.6614.

Fig. 7. The first form of loss of stability of thin-walled dome at hinged staying on brick supporting ring.

Let’s note that introduction of hinges and brick supporting ring considerably reduces the safety factor of the general stability of system and changes forms. There is possibility of loss of stability of brick supporting ring. For confirmation of the received result it is necessary to check this design model when performing natural experiment. Tough interface of dome to steel concrete supporting ring practically does not influence forms of loss of stability and has reserved coefficients on stability as the supporting ring does not lose stability.

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Combination – 2, form – 1; Stability Safety factor = 154.18.

Fig. 8. The first form of loss of stability of thin-walled dome at rigid jamming of dome in concrete supporting ring.

2.4 Optimization of Parameters of Dome Covering Optimization of the steel concrete dome representing circle with a diameter of 16 m in the plan, with initial constant thickness of 0.06 m, jammed in supporting ring or pivotally supported on brick supporting ring with constant cross-section is executed. We set task of optimization of dome covering which consists in minimization by criterion function. The greatest development for really designed structures was gained by tasks in which as optimality criterion the weight or volume at observance of conditions of durability, rigidity and stability and also different constructive restrictions is accepted. We take the weight of dome covering for criterion. We will consider criterion function in our researches dependent on the following parameters: – – – –

changeable thickness of dome; elastic modulus; poisson’s ratio; arrow of raising of dome.

We consider constants the sizes of supporting ring. We optimize geometrical characteristics and physical parameters of material of dome covers from position of their space stability. When determining criteria of critical condition at the time of loss of stability the following mechanism of loss of stability and further destruction of design of dome is accepted: – – – –

education and disclosure of radial cracks; flaking of outside fibers of protective layer of concrete; dahl reduction of thickness of concrete section of element follows; development of plastic deformations in armature and fragile destruction of concrete.

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General order of performance of numerical researches: 1. Definition of forms of loss of stability of dome without interaction with the blocked construction with hinged staying and with rigid jamming under the influence of loading from the curb weight and snow load. 2. Definition of forms of loss of stability of dome taking into account supporting ring the sizes 600 × 640(h) of lime sand brick of M250 brand on M150 brand solution under the influence of loading from the curb weight and snow load. 3. Definition of forms of loss of stability of dome taking into account monolithic supporting ring the sizes 600 × 600 of class B40 concrete under the influence of loading from the curb weight and snow load. Material of dome covering – steel concrete: E = 3.25 MPas, σ = 104 MPas, μ = 0.2. Load of dome: the curb weight of 0.55 T/m2 + the payload of 0.15 T/m2 + snow load on mark of +117 m (wind load is not considered). According to objective it is appointed the following restrictions for optimization of dome covering: – on durability max ≤ [σ]± , σeqv.

(1)

– on vertical movement of upper point of dome yult at which there is loss of stability of dome   (2) ymax ≤ yult , – on limits of change of variables of design. The arrow of rise is appointed from condition:    f= 1 6÷1 8

(3)

As criterion of loss of stability vertical movement of top of dome at the time of stability loss is accepted. For determination of this size calculation on combination of loadings to increase in snow load until approach of limit state is executed. The deformed type of dome with monolithic supporting ring is shown in Fig. 9. At the following stage with use of opportunities of the «Topological Optimization» module of the final and element «MidasCivil» by optimization we receive simple uniform reduction of shell thickness to the basis at action only of vertical uniformly distributed load and curb weight. By means of the module of final and element complex of «Parametrical optimization» influence of variables of design (shell thickness, elastic modulus and Poisson’s ratio) on movements or tension of design in the set point was estimated. The correlation analysis (Fig. 10) is made. For the complex analysis of behavior of criterion function for two variables the method of surface of response “Response surface methodology” is used. Figure 11 is the schedule of criterion function for two functions: the elasticity module - Poisson’s ratio.

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Fig. 9. The deformed type of dome at the time of approach of limit state.

Fig. 10. Schedules of variables of design (shell thickness, elastic modulus and Poisson’s ratio) on movement of the set design point.

The same schedules it is received for functions: elastic modulus - shell thickness. At the second stage the material elastic modulus, Poisson’s ratio and shell thickness varied. Schedules of relocations of the center of dome at different values of variables of design are as a result received. Further by optimization as parameter dome height in addition varied. Width of the considered dome - 16.5 m. Loading: the vertical uniformly distributed load 1ts/m2+ curb weight was accepted. In Fig. 12. vertical movements of top of dome covering are shown. At the left domes with hinged seal, on the right – with rigid are given. Increase in coordinate of X – increases rise arrow. Increase in coordinate of Y – reduction of shell thickness. In Fig. 13 vertical movements of dome covering with different arrows of rise are shown.

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Fig. 11. The schedule of criterion function for two functions: the elasticity module - Poisson’s ratio.

Fig. 12. Vertical movements of dome covering with hinged staying and tough seal rigid.

Fig. 13. The deformed type of domes with different arrows of rise (side view).

Below in Fig. 14 schedules of vertical movements of top of dome covering at change of shell thickness depending on arrow for different conditions of fixing are shown.

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Fig. 14. Vertical movement of top of dome at change of shell thickness. f = 7.5 m.

3 Evaluation The general conclusions on the performed work can be formulated as follows: 1. When calculating the VAT and checking stability of dome covering it is necessary to consider supporting ring since it gets into team work with dome covering in the rated scheme and perceives thrust. It leads to significant increase in meridional tension more for concrete supporting ring. 2. When determining forms of loss of stability of dome covering use of brick supporting ring considerably reduces the safety factor of the general stability of system and changes stability loss forms. 3. Tough interface of dome to steel concrete supporting ring practically does not influence forms of loss of stability of the dome and has reserved coefficients on stability as the supporting ring does not lose stability. 4. Use at design of methods optimum (in particular, geometrical) design of thin-walled dome coverings allows to create more rational and economic designs and to make the justified engineering decisions.

References 1. Jakšic, Z., Ladjinovi´c, D., Trivuni´c, M., Harmati, N., Vatin, N.: Masonry construction remedial measures in case of a multi-story housing facility caused by floor extension process. Procedia Eng. 117(1), 502–515 (2015). https://doi.org/10.1016/j.proeng.2015.08.252 2. Kanyukova, S., Vatin, N., Leybman, D., Sazonova, T.: Dynamic control method of design terms in underground construction. Procedia Eng. 165, 1918–1924 (2016). https://doi.org/10.1016/ j.proeng.2016.11.942

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3. Klyuev, S., Klyuev, A., Vatin, N.: Fine-grained concrete with combined reinforcement by different types of fibers. In: MATEC Web of Conferences, vol. 245 (2018). https://doi.org/10. 1051/matecconf/201824503006 4. Klyuev, S.V., Klyuev, A.V., Vatin, N.I.: Fiber concrete for the construction industry. Mag. Civil Eng. 84(8), 41–47 (2018). https://doi.org/10.18720/MCE.84.4 5. Korniyenko, S.V., Vatin, N.I., Gorshkov, A.S.: Thermophysical field testing of residential buildings made of autoclaved aerated concrete blocks. Mag. Civil Eng. 64(4), 10–25 (2016). https://doi.org/10.5862/mce.64.2, https://www.scopus.com/inward/record.uri?eid=2-s2.0-849 94577524&doi=10.5862%2FMCE.64.2&partnerID=40&md5=db0aeb0cff0a2e40ad39b6fd 791afdae 6. Kovaˇciˇc, B., Kamnik, R., Vatin, N., Ishkov, A.: The vertical displacement measurement of concrete plates with special emphasis on rough error. Procedia Eng. 165, 936–946 (2016). https://doi.org/10.1016/j.proeng.2016.11.803 7. Orlovich, R.B., Nowak, R., Vatin, N.I., Bespalov, V.V.: Strength evaluation of the Prussian vaults made from brick aggregate concrete. Mag. Civil Eng. 82(6), 95–102 (2018). https://doi. org/10.18720/MCE.82.9 8. Romano, A.A., Scandurra, G.: “Nuclear” and “nonnuclear” countries: Divergences on investment decisions in renewable energy sources. Energy Sources Part B Econ. Plann. Policy 11(6), 518–525 (2016). https://doi.org/10.1080/15567249.2012.714843 9. Marques, A.C., Fuinhas, J.A., Pires Manso, J.R.: Motivations driving renewable energy in European countries: a panel data approach. Energy Policy 38(11), 6877–6885 (2010). https:// doi.org/10.1016/j.enpol.2010.07.003

Author Index

A Abornev, Denis, 601 Akimov, Luka, 198 Aleksandrova, Tatyana, 36 Alisin, Valery, 440 Artiukh, Viktor, 542 Avdeeva, Marina, 391 Azarov, Valery, 324, 332 B Babanina, Anna, 285, 298, 312 Bagaeva, Irina, 143 Bakirov, Akhat, 26 Barbotkina, Ekaterina, 198 Beliaev, Sergei, 621 Bobryashov, Victor, 685 Borremans, Alexandra, 124 Burdzieva, Olga, 481 Burlov, Viacheslav, 46 Burtsev, Aleksey, 225 Bushuev, Nikolay, 685 Byzov, Anton, 391 C Chantieva, Milana, 553 Chebotarev, Stanislav, 562 Chepur, Petr, 530 Chesnokova, Alexandra, 432 Chuikin, Sergei, 238 D Danilina, Marina, 562 Divinets, Marina, 515

Dmitrieva, Svetlana, 72 Dmitrievsky, Boris, 178 Dubgorn, Alissa, 167 Dulskiy, Evgeny, 515 Dunaieva, Ielizaveta, 198 Dykha, Aleksandr, 542 Dzhabrailov, Khizar, 553 E Efremov, Sergey, 408 Eremin, Anton, 341 F Fidarova, Madina, 57, 492 Frishter, Lyudmila, 352 Fugarov, Dmitry, 471 G Gadjiev, Djavanshir, 276 Gagarin, Vladimir, 593 Gematudinov, Rinat, 553 Gerasimenko, Alla, 471 Gerasimenko, Yevgeny, 471 Gerasimenko, Yuri, 471 Gladkov, Gennady, 661 Golovina, Yelena, 266 Goncharov, Roman, 3 Graboviy, Kirill, 298 Gravit, Marina, 577 Gridnev, Sergey, 708 Grigoryan, Erik, 285 Gruchenkova, Alesya, 530

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 V. Murgul and V. Pukhkal (Eds.): EMMFT 2019, AISC 1259, pp. 721–723, 2021. https://doi.org/10.1007/978-3-030-57453-6

722 Gubareva, Kristina, 341 Gulak, Lyudmila, 238 I Iliashenko, Victoria, 143 Ilin, Igor, 124, 167 Ishkov, Alexey, 363 Ivanichkin, Roman, 187 Ivanov, Pavel, 515 Ivanova, Irina, 266 J James, Uwaila Osarobo, 187 K Kalinichenko, Andrey, 601 Kalinichenko, Michael, 601 Kaloshina, Svetlana, 621 Kalyazina, Sofia, 124, 143 Kanukov, Aleksandr, 57, 481, 492 Kashirin, Pavel, 187 Katolikov, Viktor, 661 Kaverzneva, Tatyana, 408 Kazanskaya, Liliya, 650 Khamnaeva, Alena, 515 Kharebov, Konstantin, 492 Khudonogov, Anatoliy, 515 Khusainov, Rishat, 371, 383 Klychova, Guzaliya, 98 Kochetkov, Andrey, 698 Kochetkov, Ivan, 276 Kolesnikov, Gennady, 631 Kolosova, Anastasiya, 419, 426, 464 Korochentsev, Denis, 3 Kortikov, Nicolay, 537 Kotciuba, Igor, 83 Kozlov, Artemiy, 676 Kozlov, Grigorii, 676 Kozyreva, Lyudmila, 698 Krasnov, Andrey, 12 Krichevsky, Mikhail, 72 Kruchek, Viktor, 515 Kukhar, Volodymyr, 542 Kulakov, Kirill, 285, 542 Kultyaev, Svyatoslav, 247 Kutuzova, Ekaterina, 401 Kuznetsov, Sergey, 247 L Lamberov, Alexandr, 383 Lavrinenko, Marina, 577

Author Index Lazarev, Yurij, 577 Leonova, Natalia, 391 Levaniuk, Daria, 167 Levina, Anastasia, 124, 158 Loboda, Aleksandr, 238 M Makarova, Tatyana, 258 Malikov, Vladimir, 363 Mankov, Viktor, 46 Manzhilevskaya, Svetlana, 324, 332 Martynova, Julia, 72 Matusevich, Alexander, 312 Matveykin, Valery, 178 Melkov, Dmitry, 57, 64, 492 Mishchenko, Valeriy, 209 Moldakhan, Inabat, 26 N Nemtinov, Vladimir, 178 Nigmetzyanov, Almaz, 98 Nikonorov, Aleksandr, 198 Nikonova, Julia, 631 Nurieva, Regina, 98 O Odinokova, Kseniya, 408 Osipova, Nataliya, 247 Ovchinnikova, Svetlana, 601 Ovsianik, Alexander, 562 P Parshina, Anastasiya, 266 Pasetti, Marco, 258 Pashtetsky, Vladimir, 198 Pavlenko, Anna, 3, 577 Pavlov, Nikolay, 143 Perepelitsa, Elizaveta, 676 Perepelitsa, Nikita, 225 Persaeva, Zarina, 57 Petrenko, Lubov, 324, 332 Pikalov, Evgeniy, 419, 426, 450, 457, 464 Pivneva, Svetlana, 12 Plaksina, Elena, 238 Poluyan, Anna, 471 Polyukhovich, Maksim, 46 Ponomaryov, Andrey, 611 Popovych, Valentina, 198 Portnov, Vladimir, 708 Pozhidaev, Yuriy, 432 Praveen, Praveen Kumar, 178

Author Index Primak, Ekaterina, 408 Purchina, Olga, 471 Pushkarev, Mikhail, 676 R Raheem, Ullah, 98 Ratkin, Vasily, 698 Richter, Andrey, 562 Romashev, Artem, 36 Rozov, Artem, 577 Rumyantseva, Nina, 408 Rustanov, Aligadzhi, 276 S Salogub, Leonid, 708 Samarin, Valery, 178 Scherbakov, Alexander, 298, 312 Sekisov, Aleksandr, 601 Selivanov, Oleg, 419, 426, 450, 457, 464 Semenov, Alexey, 209 Semicheva, Natalia, 225 Shabunevich, Oleg, 187 Shahramanyan, Mikhail, 562 Shikov, Alexey, 83 Smyshlyaeva, Karina, 391 Solovev, Sergei, 371, 383 Soloveva, Olga, 371, 383, 638 Sorokatyi, Ruslan, 542 Sotnikova, Olga, 258, 708 Stepanova, Tatyana, 209 Suleimenov, Ibragim, 26 Surnina, Elena, 698 Sushko, Yelena, 266 Suvorov, Dmitriy, 553 Sysoev, Sergey, 187

723 T Talalay, Victor, 698 Tarasenko, Aleksandr, 530 Terleev, Vitaly, 198 Tkalich, Sergey, 502 Tumanov, Alexandr, 46 U Ushakov, Egor, 36 Uvarova, Anastasiya, 450, 457 V Vasenin, Dmitrii, 258 Vasiliev, Yuri, 698 Vasiljev, Eugeny, 502 Vecherkov, Valentyn, 198 Vitkalova, Irina, 450, 457 Y Yafizov, Ruzil, 371 Yatsenko, Valentin, 209 Yezhov, Vladimir, 225 Yusupdzhanov, Vladimir, 401 Z Zaalishvili, Vladislav, 57, 64, 481, 492 Zaitseva, Maria, 631 Zakarchevskiy, Sergey, 432 Zakharov, Aleksandr, 611 Zakirova, Alsou, 98 Zaks, Tamaz, 481 Zaugarova, Evgenia, 98 Zhamsaranzhapova, Tatyana, 432 Zhuravlev, Michail, 661 Zolotozubov, Dmitrii, 621 Zubarev, Kirill, 593