Smart Technologies for Sustainable Development: Select Proceedings of SMTS 2019 [1st ed.] 9789811550003, 9789811550010

Table of contents :
Front Matter ....Pages i-xiii
Comparative Study of Pedestrian Vibration for Design of Steel Arch Bridge (Rahul Suresh, A. Sofi, K. Ganesh)....Pages 1-17
Lateral Load Analyses of Multi-storeyed Frames with and Without Shear Walls (Akash John Koshy, A. Sofi, A. R. Santhakumar)....Pages 19-35
The Diagnosis for the Lack of Remote Village Electrification Using Sustainable Energy in Labranzagrande (Alan Achenkunju John, P. Venkatesh Kumar)....Pages 37-44
Experimental Studies on the Suitability of Coconut Shell as a Filler Material in Concrete Cubes (Renuka Sai Gadekari, Sreevalsa Kolatayar, Rajesh Kumar Chitrachedu)....Pages 45-53
A Sustainable Approach to Turn Plastic Waste into Useful Construction Blocks (K. Monish, J. John Jesuran, Sreevalsa Kolathayar)....Pages 55-62
Study on Mechanical Properties of M30 Grade Concrete with Replacement of Cement by Wollastonite (D. Saranyadevi, P. Sabareeswaran, P. Paramaguru, M. Surya Prakash)....Pages 63-70
Flexural Behaviour of Auxetic Core Sandwich Beam (Ruby Vaguez, Simon Jayasingh)....Pages 71-82
Correlation Between Surface Absorption and Chloride Ion Penetration of Concrete with Nano Silica (R. Vandhiyan, E. B. Perumal Pillai, S. Lingeswari)....Pages 83-94
Prediction of Setting Time and Strength of Mortar Using Soft Computing Technique (Kiran Devi, Babita Saini, Paratibha Aggarwal)....Pages 95-102
A Study on Dynamic Behaviour of Monoblock Concrete Sleepers Using SAP2000 (P. S. Rao, A. K. Desai, C. H. Solanki)....Pages 103-109
Spatial Machines for Heterogeneous MRI Data—A Critical Review (Zabiha Khan, R. Loganathan)....Pages 111-115
Influence of Fineness of Mineral Admixtures on the Degree of Atmospheric Mineral Carbonation (C. Farsana, Bibhuti Bhusan Das, K. Snehal)....Pages 117-136
Experimental Setup for Thermal Performance Study of Phase Change Material Admixed Cement Composites—A Review (K. Snehal, Bibhuti Bhusan Das)....Pages 137-149
The Behavior of Ambad Earth Dam Under Change in Water Level and Earthquake (B. M. Bhosale, Rohan Deshmukh)....Pages 151-166
A Review on the Properties of Steel-Concrete Interface and Characterization Methods (E. P. Sumukh, Sharan Kumar Goudar, Bibhuti Bhusan Das)....Pages 167-203
Prediction of Compressive Strength and Electrical Resistivity of Mortar Mixes Containing Industrial Waste Products (Maninder Singh, Babita Saini, H. D. Chalak)....Pages 205-212
An Overview on Waste Materials Used in Engineered Cementitious Composite (Maninder Singh, Babita Saini, H. D. Chalak)....Pages 213-222
Studies on Modeling and Control of RCC Frame with MR Damper (R. Rakshita, C. Daniel, G. Hemalatha, L. Sarala, D. Tensing, S. Sundar Manoharan)....Pages 223-234
Detection of Defects in Concrete Structures by Using Infrared Thermography (Madhuraj Naik, Varadmurti Gaonkar, Ganesh Hegde, Lalat Indu Giri)....Pages 235-246
DSP-Based Implementation of MPPT Tracking and Sliding Mode Control for Photo-Voltaic Systems (Subramanya Bhat, H. N. Nagaraja)....Pages 247-259
Analysis of Resilience Performance of Water Distribution Network (A. Ariffa Parakath, T. R. Neelakantan)....Pages 261-267
Influence of Steel Fibers on Enhancing the Toughness Property on Concrete: A Simplified Approach (Meyyappan Palaniappan, Jemimah Carmichael Milton, Sathya Soroopan Ramasubramaniam, Hariharan Palvannan, Hariharasudan Sundararaj)....Pages 269-275
Behavior of Zero-Cement Mortar: An Experimental Study (Jagan Sivamani, Mohammed Sulaiman)....Pages 277-287
An Efficient Fire Detection System Using Support Vector Machine and Deep Neural Network (Archana Venugopal, Febi Justin, Linju Santhosh, Riya Binny, NG Resmi)....Pages 289-296
Engineering Properties of Heavyweight Concrete—A Review (B. P. Sharath, Bibhuti Bhusan Das)....Pages 297-314
Experimental Study on Lightweight Concrete with Copper Slag and Pumice Stone, Leca as a Partial Replacement of Aggregates (V. Praveen Jesuraj, V. Sreevidya)....Pages 315-325
Influence of Magnetic Water on Properties of Concrete Paver Blocks (R. Malathy, N. Karuppasamy, V. Adithya, P. Gokulapriya)....Pages 327-336
Floor Response Spectra: An Investigation on Hospital Building (H. D. Karthik Nadig, R. Sreekala, K. Sathish Kumar, J. Simon)....Pages 337-345
Behavior of Rectangular Footing on Geosynthetic Reinforced Crusher Dust (Bandita Paikaray, Sarat Kumar Das, Benu Gopal Mohapatra, Sweta Sarangi)....Pages 347-357
Evaluation of Pozzolanic Performance of Treated and Untreated Bagasse Ash (S. Sindhu, S. Praveenkumar, G. Sankarasubramanian)....Pages 359-367
Experimental Study on Bubble Deck Slab Using Palm Seeds (M. Iswarya, V. S. Tamilarasan)....Pages 369-376
Self-compacting Concrete: A Review (J. Abdul Bari, K. S. Krithiga)....Pages 377-386
Strength Characteristics of Red Mud and Silica Fume Based Concrete (Chava Venkatesh, Madduru Sri Rama Chand, Nerella Ruben, Chereddy Sonali Sri Durga)....Pages 387-393
Effect of Green Corrosion Inhibitors on the Properties of Mortar and Concrete (K. Kavya, S. Keerthana, T. Pradeep)....Pages 395-405
Utilizing and Optimizing Waste Resources in Paver Block (S. Janaki Raman, Shanmugasundaram)....Pages 407-416
Prediction of Strength Characteristics of Soil Using Neural Network Techniques (Amit Kumar, D. K. Soni)....Pages 417-424

Citation preview

Lecture Notes in Civil Engineering

Sanjay Kumar Shukla Srinivasan Chandrasekaran Bibhuti Bhusan Das Sreevalsa Kolathayar   Editors

Smart Technologies for Sustainable Development Select Proceedings of SMTS 2019

Lecture Notes in Civil Engineering Volume 78

Series Editors Marco di Prisco, Politecnico di Milano, Milano, Italy Sheng-Hong Chen, School of Water Resources and Hydropower Engineering, Wuhan University, Wuhan, China Ioannis Vayas, Institute of Steel Structures, National Technical University of Athens, Athens, Greece Sanjay Kumar Shukla, School of Engineering, Edith Cowan University, Joondalup, WA, Australia Anuj Sharma, Iowa State University, Ames, IA, USA Nagesh Kumar, Department of Civil Engineering, Indian Institute of Science Bangalore, Bengaluru, Karnataka, India Chien Ming Wang, School of Civil Engineering, The University of Queensland, Brisbane, QLD, Australia

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Sanjay Kumar Shukla Srinivasan Chandrasekaran Bibhuti Bhusan Das Sreevalsa Kolathayar •

•

•

Editors

Smart Technologies for Sustainable Development Select Proceedings of SMTS 2019

123

Editors Sanjay Kumar Shukla Discipline of Civil and Environmental Engineering, School of Engineering Edith Cowan University Perth, Australia Bibhuti Bhusan Das Department of Civil Engineering National Institute of Technology Karnataka Mangalore, India

Srinivasan Chandrasekaran Department of Ocean Engineering Indian Institute of Technology Madras Chennai, Tamil Nadu, India Sreevalsa Kolathayar Department of Civil Engineering National Institute of Technology Karnataka Mangalore, India

ISSN 2366-2557 ISSN 2366-2565 (electronic) Lecture Notes in Civil Engineering ISBN 978-981-15-5000-3 ISBN 978-981-15-5001-0 (eBook) https://doi.org/10.1007/978-981-15-5001-0 © Springer Nature Singapore Pte Ltd. 2021 This work is subject to copyright. All rights are reserved 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 Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

The problems caused by global warming and climate change have forced the scientists and engineers to explore materials, methods and techniques, which can bring sustainable developments in our villages, towns and cities. Attempts are being made worldwide to create new/modified materials, often called smart materials, which can help bring the developments closer to our safe and sustainable natural environment. Researchers are also focussing on making suitable improvements in design methodologies, construction techniques and maintenance strategies for achieving the goals of sustainability. Keeping all these needs and developments in mind, an International Conference on Smart Materials and Techniques for Sustainable Development (SMTS-2019) was organized from 4 to 5 April 2019 at Dr. N. G. P. Institute of Technology, Coimbatore, India. This book includes the selected papers from this conference dealing with several topics, including smart structures and materials, innovation in smart composites, green construction materials and technologies, optimization and innovation in structural design, structural dynamics and earthquake engineering, structural health monitoring system, nanomaterials, nanotechnology and sensors, smart biomaterials and materials for energy conversion and storage devices. We thank all the staff of Springer for their full support and cooperation at all the stages of the publication of this book. We do hope that this book will be beneficial to students, researchers and professionals working in the field of smart materials and sustainable development. The comments and suggestions from the readers and users of this book are most welcome. Perth, Australia Chennai, India Mangalore, India Mangalore, India

Sanjay Kumar Shukla Srinivasan Chandrasekaran Bibhuti Bhusan Das Sreevalsa Kolathayar

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Contents

Comparative Study of Pedestrian Vibration for Design of Steel Arch Bridge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rahul Suresh, A. Sofi, and K. Ganesh

1

Lateral Load Analyses of Multi-storeyed Frames with and Without Shear Walls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Akash John Koshy, A. Sofi, and A. R. Santhakumar

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The Diagnosis for the Lack of Remote Village Electrification Using Sustainable Energy in Labranzagrande . . . . . . . . . . . . . . . . . . . . . . . . . Alan Achenkunju John and P. Venkatesh Kumar

37

Experimental Studies on the Suitability of Coconut Shell as a Filler Material in Concrete Cubes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Renuka Sai Gadekari, Sreevalsa Kolatayar, and Rajesh Kumar Chitrachedu

45

A Sustainable Approach to Turn Plastic Waste into Useful Construction Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Monish, J. John Jesuran, and Sreevalsa Kolathayar

55

Study on Mechanical Properties of M30 Grade Concrete with Replacement of Cement by Wollastonite . . . . . . . . . . . . . . . . . . . . D. Saranyadevi, P. Sabareeswaran, P. Paramaguru, and M. Surya Prakash

63

Flexural Behaviour of Auxetic Core Sandwich Beam . . . . . . . . . . . . . . . Ruby Vaguez and Simon Jayasingh

71

Correlation Between Surface Absorption and Chloride Ion Penetration of Concrete with Nano Silica . . . . . . . . . . . . . . . . . . . . . . . . R. Vandhiyan, E. B. Perumal Pillai, and S. Lingeswari

83

Prediction of Setting Time and Strength of Mortar Using Soft Computing Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kiran Devi, Babita Saini, and Paratibha Aggarwal

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Contents

A Study on Dynamic Behaviour of Monoblock Concrete Sleepers Using SAP2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 P. S. Rao, A. K. Desai, and C. H. Solanki Spatial Machines for Heterogeneous MRI Data—A Critical Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Zabiha Khan and R. Loganathan Influence of Fineness of Mineral Admixtures on the Degree of Atmospheric Mineral Carbonation . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 C. Farsana, Bibhuti Bhusan Das, and K. Snehal Experimental Setup for Thermal Performance Study of Phase Change Material Admixed Cement Composites—A Review . . . . . . . . . . . . . . . . 137 K. Snehal and Bibhuti Bhusan Das The Behavior of Ambad Earth Dam Under Change in Water Level and Earthquake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 B. M. Bhosale and Rohan Deshmukh A Review on the Properties of Steel-Concrete Interface and Characterization Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 E. P. Sumukh, Sharan Kumar Goudar, and Bibhuti Bhusan Das Prediction of Compressive Strength and Electrical Resistivity of Mortar Mixes Containing Industrial Waste Products . . . . . . . . . . . . 205 Maninder Singh, Babita Saini, and H. D. Chalak An Overview on Waste Materials Used in Engineered Cementitious Composite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Maninder Singh, Babita Saini, and H. D. Chalak Studies on Modeling and Control of RCC Frame with MR Damper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 R. Rakshita, C. Daniel, G. Hemalatha, L. Sarala, D. Tensing, and S. Sundar Manoharan Detection of Defects in Concrete Structures by Using Infrared Thermography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 Madhuraj Naik, Varadmurti Gaonkar, Ganesh Hegde, and Lalat Indu Giri DSP-Based Implementation of MPPT Tracking and Sliding Mode Control for Photo-Voltaic Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Subramanya Bhat and H. N. Nagaraja Analysis of Resilience Performance of Water Distribution Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 A. Ariffa Parakath and T. R. Neelakantan

Contents

ix

Influence of Steel Fibers on Enhancing the Toughness Property on Concrete: A Simplified Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 Meyyappan Palaniappan, Jemimah Carmichael Milton, Sathya Soroopan Ramasubramaniam, Hariharan Palvannan, and Hariharasudan Sundararaj Behavior of Zero-Cement Mortar: An Experimental Study . . . . . . . . . . 277 Jagan Sivamani and Mohammed Sulaiman An Efficient Fire Detection System Using Support Vector Machine and Deep Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289 Archana Venugopal, Febi Justin, Linju Santhosh, Riya Binny, and NG Resmi Engineering Properties of Heavyweight Concrete—A Review . . . . . . . . 297 B. P. Sharath and Bibhuti Bhusan Das Experimental Study on Lightweight Concrete with Copper Slag and Pumice Stone, Leca as a Partial Replacement of Aggregates . . . . . . 315 V. Praveen Jesuraj and V. Sreevidya Influence of Magnetic Water on Properties of Concrete Paver Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 R. Malathy, N. Karuppasamy, V. Adithya, and P. Gokulapriya Floor Response Spectra: An Investigation on Hospital Building . . . . . . . 337 H. D. Karthik Nadig, R. Sreekala, K. Sathish Kumar, and J. Simon Behavior of Rectangular Footing on Geosynthetic Reinforced Crusher Dust . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 Bandita Paikaray, Sarat Kumar Das, Benu Gopal Mohapatra, and Sweta Sarangi Evaluation of Pozzolanic Performance of Treated and Untreated Bagasse Ash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359 S. Sindhu, S. Praveenkumar, and G. Sankarasubramanian Experimental Study on Bubble Deck Slab Using Palm Seeds . . . . . . . . . 369 M. Iswarya and V. S. Tamilarasan Self-compacting Concrete: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 J. Abdul Bari and K. S. Krithiga Strength Characteristics of Red Mud and Silica Fume Based Concrete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387 Chava Venkatesh, Madduru Sri Rama Chand, Nerella Ruben, and Chereddy Sonali Sri Durga

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Contents

Effect of Green Corrosion Inhibitors on the Properties of Mortar and Concrete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395 K. Kavya, S. Keerthana, and T. Pradeep Utilizing and Optimizing Waste Resources in Paver Block . . . . . . . . . . . 407 S. Janaki Raman and Shanmugasundaram Prediction of Strength Characteristics of Soil Using Neural Network Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417 Amit Kumar and D. K. Soni

About the Editors

Dr. Sanjay Kumar Shukla is an internationally recognized expert in the field of Civil (Geotechnical) Engineering. He is the Founding Editor-in-Chief of International Journal of Geosynthetics and Ground Engineering, published by Springer Nature, Switzerland. He is also the Founding Research Group Leader (Geotechnical and Geoenvironmental Engineering) at the Edith Cowan University, Perth, Australia. He holds the Distinguished Professorship in Civil Engineering at Delhi Technological University, Delhi, VIT University, Vellore, Chitkara University, Himachal Pradesh, VR Siddhartha Engineering College, Vijayawada, India, and Fiji National University, Suva, Fiji. He graduated in Civil Engineering from BIT Sindri, India, and earned his MTech in Civil Engineering (Engineering Geology) and PhD in Civil (Geotechnical) Engineering from Indian Institute of Technology Kanpur, India. His primary areas of research interest include geosynthetics and fibres for sustainable developments, ground improvement techniques, utilization of wastes in construction, earth pressure and slope stability, environmental, mining and pavement geotechnics, and soil-structure interaction. He is an author/editor of 14 books, including 7 textbooks and 258 technical articles, including 158 refereed journal papers. Shukla’s generalized expression for seismic active thrust (2015) and Shukla’s generalized expression for seismic passive resistance (2013) are being used by practicing engineers worldwide for designing the retaining structures. He has been honoured with several awards, including the most prestigious IGS Award 2018 by the International Geosynthetics Society (IGS), USA, in recognition of outstanding contribution to the development and use of geosynthetics during the 2014-2017 IGS award period. He is a fellow of Engineers Australia, Institution of Engineers (India) and Indian Geotechnical Society, and a member of American Society of Civil Engineers, International Geosynthetics Society and several other professional bodies. He is the Senior Editor of Cogent Engineering (Civil and Environmental Engineering), and serves on the editorial boards of more than 10 international journals, including ICE Ground Improvement, Soil Mechanics and Foundation Engineering, and Journal of Mountain Science.

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About the Editors

Dr. Srinivasan Chandrasekaran is a Professor in the department of Ocean Engineering, Indian Institute of Technology Madras, India. He has over 27 years of experience in teaching, research and industrial consultancy. His active research areas include dynamic analysis and design of offshore structures, development of new-generation compliant offshore platforms for ultra-deepwater oil and gas exploration, structural health monitoring of ocean structures, risk and reliability, fire resistant design of structures, use of Functionally Graded Materials (FGM) in marine risers, and Health, Safety & Environmental (HSE) management in process industries. He was a visiting fellow under the invitation of Ministry of Italian University Research (MiUR) to University of Naples Federico II for two years. He has authored about 160 research papers in peer-reviewed international journals and refereed conferences organized by professional societies around the world. Dr. Bibhuti Bhusan Das is currently serving as an Associate Professor at National Institute of Technology Karnataka, Surathkal. Before joining NITK, he served as Centre Head for National Institute of Construction Management and Research, Goa and Indore Campus. He has been working as a Post-Doctoral Research Associate and Adjunct Faculty in the department of Civil Engineering at Lawrence Technological University, Southfield, Michigan, USA. His area of research focuses on sustainability of construction and building materials such as microstructure characterization of materials, non-destructive testing of concrete structures, corrosion of reinforcement and durability studies on concrete and sustainability in construction project management. He is an Associate Member of American Concrete Institute and is a part of the International Faculty Network Committee launched by ACI Education Foundation in 2009. He is an editorial board member and reviewer to several national and international journals. Dr. Sreevalsa Kolathayar pursued M.Tech from IIT Kanpur, Ph.D. from Indian Institute of Science (IISc) and served as International Research Staff at UPC BarcelonaTech Spain. He is presently Assistant Professor in the Department of Civil Engineering, National Institute of Technology Karnataka, Surathkal, India. Dr. Sreevalsa has authored five books and eight book chapters published by CRC Press, Springer and Elsevier. He published 36 journal papers and 30 conference papers. He is Editorial Board member of two International Journals and acted as a reviewer for many international journals. His research interests include Ground Motion Attenuation & Seismic Hazard Assessment, Local Site effects & Liquefaction Susceptibility, Pseudo-dynamic approach for Seismic Loading, Disaster Risk Reduction, Geogrids and Geocells, and Water geotechnics. He is currently the Secretary Indian chapter of International Association for Coastal Reservoir Research (IACRR), and Executive Committee Member of Indian Society of Earthquake Technology. In 2017, The New Indian Express honored

About the Editors

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Dr. Sreevalsa with Edex award: 40 under 40 - South India’s Most Inspiring Young Teachers. He is the recipient of ISET DK Paul Research Award from Indian Society of Earthquake Technology, IIT Roorkee in 2018. Dr. Sreevalsa is in the roster of two technical committees of ASCE Geo-Institute. He received “IEI Young Engineers Award” by The Institution of Engineers (India), in recognition of his contributions in the field of Civil Engineering.

Comparative Study of Pedestrian Vibration for Design of Steel Arch Bridge Rahul Suresh, A. Sofi, and K. Ganesh

Abstract Crossing over has been the key component in the advancement of the street framework. Although analysts have given numerous important scientific commitments with respect to the comprehension and displaying of passerby prompted vibrations of footbridges, there is yet a need to figure out what genuine upgrades have been accomplished in structure techniques. The extension and scope of arrangement have relied upon the viable misuse of the most efficient materials accessible. This paper introduces the structure and investigation of the bridge using STAAD.Pro software. This article gives a basic diagram of the procedures proposed in the design of steel arch bridge. Focus is set on the improvement of passerby load, the structure rules and vibration countermeasures. Pedestrian vibration using different codes is also done to do a comparative study of vibrations obtained. Keywords STAAD pro · Design and analysis · Pedestrian vibration · Comparative study

1 Introduction A bridge is a method by which a street, railroad or different administrations is conveyed over a snag, for example, a stream, valley and the other street or rail route line, either with no moderate help or with just a set number of backings at advantageous areas. Extension territory in sizes from the unobtrusive limited ability to focus, say, a little waterway or the extraordinary instances of suspension, spans R. Suresh · A. Sofi (B) School of Civil Engineering, VIT, Vellore, India e-mail: [email protected] R. Suresh e-mail: [email protected] K. Ganesh L&T Infrastructure Engineering Limited, Manapakkam, Chennai, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_1

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R. Suresh et al.

across wide estuaries [1]. Appearance is normally less critical for the littler extensions; yet in all cases, the creator will think about the presence of the fundamental components, which make up the bridge, the superstructure and the substructure and the pick extents which are suitable to the specific conditions considered [2]. The utilization of steel frequently encourages the designer to choose extents that are stylishly satisfying. Bridges are an essential part of transport infrastructure [3]. Steel has been chosen in situations where concrete was the rational construction material, and poorly designed concrete bridges have been supplanted by welldesigned steel alternatives. However, the results of several recent tenders have indicated that for multispan bridges, a well-designed concrete deck is cheaper than the steel composite equivalent [4]. The primary preferred standpoint of the basic steel over other development materials is its quality and flexibility. It has higher solidarity to cost proportion in strain and marginally lower solidarity to cost proportion in pressure when contrasted and concrete. The stiffness to weight proportion of steel is a lot higher than that of cement [5]. Hence, structural steel is a productive and conservative material in extensions. Structural steel has been the normal answer for long-range spans since 1890 when the Firth of Forward cantilever connect, the world’s significant steel connect around then was finished From the modern Upset in the nineteenth century, bracket frameworks of steel created iron were produced for bigger scaffolds, yet iron did not have the elasticity to support large loads [6]. With the approach of steel, which has a high tensile strength, a lot bigger extensions were fabricated, many utilizing the thoughts of Gustave Eiffel. Bridges are arranged on the premise that how the four powers specifically shear, pressure, strain and minute are conveyed in the bridge structure. Furthermore, unlike those of road and railway bridges, users of footbridges are directly exposed to vibration, which can produce feelings of discomfort or even anxiety. In fact, pedestrian movement produces a complex system of forces, acting in three directions and varying in time and space; these depend on the characteristics of the pedestrian but are also modified by the interaction with other pedestrians and by the perception of the structural motion [7, 8].

2 Methodology The below flow chart shows the steps followed for the research work.

Comparative Study of Pedestrian Vibration for Design …

3

Data CollecƟon & Literature Analysis

Detailed Analysis & Design

ErecƟon Methodology

Pedestrian VibraƟon

3 Analysis and Design The analysis of steel arch bridge is carried out for dead loads, superimposed loads and live load live loads for pedestrian load are assigned to the model and load combinations are used as per IRC 6:2016 standards [9]. Results for maximum load cases were extracted and corresponding design has been done for the bridge.

3.1 Analysis The different member property that was used for the bridge design and analysis has been shown below (Fig. 1). The grade of concrete M35 and grade of steel of E350 are considered for the design of steel sections. The yield stress considered is 350 MPa. The unit weight of steel is taken as 78.5 kN/m3. The Modulus of elasticity considered is 2 × 105 MPa. The bridge is modelled in STAAD.Pro [10]. The different load cases and load combinations that is to be taken in the bridge analysis are shown in Table 1. Section forces are calculated for the bridge section in STAAD.Pro. The obtained force is taken for the design of the sectional member and the longitudinal member. Axial forces obtained are used for the design of column for the steel bridge hear force and bending moment of the entire bridge is shown in Fig. 2.

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Fig. 1 Cross-sectional view of the entire member section

Table 1 Load cases and Load combinations

Load cases

Load combinations

Dead load (DL)

1.35DL + 1.35SIDL + 1.5LL + 0.9WL

Super imposed dead load (SIDL)

1.35DL + 1.35SIDL + 1.15LL + 1.5WL

Live load (LL)

1.35DL + 1.35SIDL + 0.2LL + 1.5ELx

Wind load (WL)

1.35DL + 1.35SIDL + 0.2LL + 1.5ELy

Earthquake load (EL)

3.1.1

Temperature Analysis

Thermal effects have come in for close scrutiny in recent years. In the past, the effect of non-linearity of temperature distribution across the dreck depth was not

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5

Fig. 2 Shear force and bending moment

well understood so that, where thermal effet was considered, it was essentially the effect of rise or fall in the overall mean temperature of the body over a long period of time [9]. As structure became more complex and the distribution of temperature through the deck depth, particularly its nonlinear profile, began to be understood better, the need for a closer look into thermal effect arose. For this, two types of temperature analyses should be done [11, 12]. • Positive Differential Temperature The coefficient of thermal expansion is taken as 1.2 × 10−5 /°C (Fig. 3). Using the equations the extreme fibre strain and the strain gradient can be calculated. 0 Σ A − θ Σ Ay = αΣ At

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Fig. 3 IRC 6 positive temperature diagram

Fig. 4 Reverse temperature diagram

0 Σ Ay − θ Σ Ay 2 = αΣ Ayt Then the eigen stress can be calculated using the equation shown f ei = E C (0 − yθ − αt) • Reverse differential Temperature The coefficient of thermal expansion is taken as 1.2 × 10−5 /°C (Fig. 4). Using the equations the extreme fibre strain and the strain gradient can be calculated. 0 Σ A − θ Σ Ay = αΣ At 0 Σ Ay − θ Σ Ay 2 = αΣ Ayt Then the eigen stress can be calculated using the equation shown f ei = E C (0 − yθ − αt).

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3.2 Design The design of bridge is done after the analysis using STAAD. Pro. Different member property was assigned for the design of the steel bridge. In this design tube, star, bar (suspender) sections were used. During the design process, the design of deck, as well as waist slab, was done [7]. The different types of checks were also done in order to check whether the member was safe or not. When the member was so safe then the section of the members was changed in order to make it a more economical section. The section forces as well as the axial forces are taken from the STAAD analysis.

3.2.1

Erection Methodology

These are the design steps for the erection of an arch bridge • Installation of the arch frame • Installation of deck steel elements on temporary supports and adjustment up to the required position • Assembly of the deck elements (Fig. 5) • Assembly of the hangar bars and checking the length of each one • Checking of the distance between the top and bottom holes for each hangar bar • Installation of hangar bar • A bush or a cushion will be provided between the longitudinal girder and the temporary support so that there will not be any lateral movement while placing the concrete slabs [13, 14]. • Casting of the concrete slab • Removal of the temporary supports • Finishing (Fig. 6).

4 Pedestrian Vibration It is important to calculate the vibration to the design guidelines. These codes have different methods analysing the pedestrian vibrations. The different design guidelines are: • IRC:SP:56/BS5600-2 • Eurocode 5 part-2 • Sétraa (French Technical Department for Transport, Roads and Bridges Engineering and Road Safety).

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Fig. 5 Erection of arch portion of the bridge

4.1 IRC:SP:56/BS 5400-2 The fundamental natural frequency f 0 of a superstructure which exceeds 5 Hz for bridge that is not loaded in the vertical direction and 1.5 Hz for bridge that is loaded in the horizontal direction, then the vibration is deemed to be satisfied. If the superstructure fundamental natural frequency in the vertical direction is equal to or less than 5 Hz, the √ vertical acceleration (max) of any part of the superstructure shall be limited to 0.5 f 0 m/s−2 . The maximum acceleration can be calculated as shown below [15, 16]. The maximum vertical acceleration a (m/s2 ) shall be taken as follows: a = 4π 2 f 02 ys kψ where f o is the fundamental natural frequency (in Hz) ys is the static deflection (in m) k is the configuration factor see Table 2 ψ is the dynamic response factor see Fig. 7.

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Fig. 6 Erection of the deck slab and removal of temporary support

Table 2 Configuration factor k

Dynamic response factors ψ are given in Fig. 1. In the absence of more precise information, the value of δ (the logarithmic decrement of the decay of vibration due to structural damping) given in Table 2 should be used (Table 3). The natural fundamental frequency f0 is evaluated for the superimposed dead load and may be calculated from the following   f 0 = C 2 /2πl 2 (E I g/M) where g is the acceleration due to gravity (in m/s2 )

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Fig. 7 Dynamic response factor Ψ

Table 3 Logarithmic decrement of decay of vibration

Bridge superstructure

δ

Steel with asphalt or epoxy surfacing

0.03

Composite steel/concrete

0.04

L is the length of the main span (in m) C is the configuration factor see Table 4 E is the modulus of elasticity (in kN/m2 ) I is the second moment of area of the cross section M is the weight per unit length of the full cross section at mid-span (in kN/m). Table 4 Configuration factor C

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4.2 Eurocode 5 Part 2 For pedestrian vibrations in footbridge, Eurocode states that a maximum peak acceleration in all directions must be performed if the first natural frequency of the bridge deck is less than 5 Hz for vertical vibrations or less than 2.5 Hz for lateral and torsional vibrations. The allowable maximum acceleration according to Eurocode is found in Table 5 and should be fulfilled by a considerable margin due to high uncertainties in the calculation of the response [17–19]. The approach described here is only valid for timber bridges with simply supported beams or truss systems excited by pedestrians. In EC 5-2, it is stated that the model will be found in future versions of EN 1991-2. The vertical and horizontal acceleration for one person moving across the bridge will depend on the natural frequency, mass of the bridge and the damping ratio shown in the equation below:  avert,1 = ahor,1 =

for f vert < 2.5H z for 2.5H z < f vert < 5H z

200N Mζ 100N Mζ

50N for 0.5H z < f hor < 2.5H z Mζ

where avert,1 is the vertical acceleration from one pedestrian ahor,1 is the horizontal acceleration from one pedestrian M is the mass of the bridge ζ is the damping ratio of the bridge. Vertical and horizontal accelerations for a group of people is given by: avert,n = 0.23avert,1 nkvert ahor,n = 0.18ahor,1 nkhor where avert,n is the vertical acceleration of n pedestrians ahor,n is the horizontal acceleration from n pedestrians n is the number of pedestrians on the bridge Table 5 Allowable acceleration according to Eurocode

Direction of vibrations

Max accelerations (m/s2 )

Vertical

0.7

Horizontal-normal use

0.2

Horizontal-exceptional crowd loads 0.4

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Fig. 8 Relationship between the first natural frequency and the coefficient kvert and khor according too EC 5-2

k vert /k hor is the coefficient dependant on the natural frequency of the bridge and can be found in Fig. 8. The number of pedestrians should be taken as follows:

4.3 Stéra “Dynamic behaviour of footbridges” a group working for the French Technical Department prepared this design guideline for Transport, Roads, Bridges Engineering and Road Safety (Sétra). The code gives a methodology to evaluate the response of bridge structures subjected to pedestrian loading. The following steps are shown below in Fig. 6 (Fig. 9). The code provides two choices for the client to work on the design of the bridge. The client can decide what type of load or traffic, class the bridge belongs to and what type of comfort criteria is required for the bridge. The client’s traffic class is the total amount of pedestrians or the density of the pedestrian loading on the bridge. The different density or loading depends on the various classes from a large crowd (Class I) to scares crowd in remote areas (Class IV). If the client chooses a scare or lower class a more economical section can be used for the design of the bridge, thus reducing the cost and also to ensure freedom to architectural design. Well if a lower class is chosen it increases the risk of pedestrian feeling uncomfortable due to strong acceleration. But if the bridge is designed using the large crowd class then it will exceed the design concepts or the limits [20, 21]. The four categories of comfort level are like the first three for the acceptable to the last one is unacceptable vibrations. The comfort level often depends on the location and the number of people who are using the bridge. This type of bridge is used for most sensitive people like elderly, disabled people, school children, etc. The acceleration of bridge deck and comfort criteria are linked which is calculated using the different load cases which are described. The allowable acceleration is made in terms of acceleration range instead of a particular single value. The various ranges

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Fig. 9 The design procedure as defined by Sétra

of acceleration are shown in Table 6 for vibration in a vertical direction. The first three accelerations shown are of comfort criteria from maximum, average and minimum. The last is the unacceptable range and also the most uncomfortable criteria. The fundamental natural frequency can be calculated using the formula below: n2π fn = 2L 2

 EI ρS

where L is the entire span of the bridge (in m) E is the Young’s modulus of steel (in N/m2 ) I is the moment of inertia of deck (in m4 ) ρ S is the linear density of deck (in Kg/m) Table 6 Vertical vibration for comfort criteria

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Fig. 10 The design procedure as defined by Sétra

Table 7 Density of pedestrians

Class

Density d of the crowd

III

0.5 pedestrians/m2

II

0.8 pedestrians/m2

The force to be taken for modes in the vertical direction:  Fs = d × (280N )X cos 2π f v t × 10.8 ×

ξ ×Ψ n

where ζ is the damping ratio of the deck Ψ is the value of Factor from Fig. 10 d is the density of the crowd from Table 7. The acceleration under vertical load is given by: Accmax =

1 4× F 2ζ ρ Sπ

where F is the surface load that is applied ρ S is the linear density of deck (in Kg/m) ζ is the damping ratio of the deck. In both vertical and horizontal directions, there are four frequency ranges, corresponding to decreasing risk of resonance: • • • •

Range 1: maximum risk of resonance Range 2: medium risk of resonance Range 3: low risk of resonance for standard loading situations Range 4: negligible risk of resonance (Table 8).

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Table 8 Frequency range (Hz) of the vertical and longitudinal vibrations

Table 9 Frequency from different codes Fundamental Frequency (Hz)

IRC:SP:56/BS 5400-2

Eurocode 5 part 2

Stéra

3.711

1.17

3.59

Table 10 Acceleration from different codes Acceleration

IRC:SP:56/BS 5400-2

Eurocode 5 part 2

Stéra

amax < alim 0.016 < 0.963 m/s2

avert(1) < alim 0.394 < 0.7 m/s2 avert(n) < alim 0.471 < 0.7 m/s2

2.6 Hz < fn < 5 Hz Range 3 Accmax = 0 (Range 3 Low risk of Resonance)

4.4 Comparison with Different Codes The modulus of elasticity is taken as 2.05 × 108 kN/m2 , moment of inertia 0.221 m4 , acceleration due to gravity 10 m/s2 , mass of the entire bridge 31.7 kN/m, density of crowd (d) 0.5 (class III) 0.8 (class II) 1.0 (class I). The frequency is calculated as per the different codes and is shown in Table 9. After the calculation of the frequency, the acceleration is calculated [22] with which we can predict the safety of the structure or not. The calculated acceleration is shown in Table 10.

5 Conclusion In this paper, a detailed design for the steel arch bridge was explained. Also, a comparison of pedestrian vibration using different code was done. It can be concluded from the following points: • Analysis was done with different members with the loads so that the economical section can be used for bridge design which can reduce the cost project. • The different checks for the deck as well as the waist slab are done such as the shear, crack width, moment of inertia, deflection have been done.

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• The erection of the bridge has been discussed in detail so that the erection can be done without any difficulties. • Finally, the pedestrian vibration was calculated for this steel arch bridge using three different codes and was compared so that it shows more information regarding the vibration of the bridge. • The vibration obtained can now be used to check whether the bridge will fail or not. So by using this technique, we can reduce the failure of bridges that have happened in the past like the Lively bridge in Milan.

References 1. Hong R, Khudeira S (2013) Chicago’s first tied-arch bridge. Practice Period Struc Design Construct 19(3):04014011 2. Dey P, Narasimhan S, Walbridge S (2016) Evaluation of design guidelines for the serviceability assessment of aluminum pedestrian bridges. J Bridge Eng 22(1):04016109 3. Ivorra S et al (2013) Dynamic behavior of a pedestrian bridge in Alicante, Spain. J Perform Construct Facilit 29(5):04014132 4. ASCE Committee on Construction Equipment and Techniques (1989) Concrete Bridge Design and Construction in the United Kingdom. J Construct Eng Manage 115(4):618–635 5. Rao A (2006) Design and construction of the longest rope-stayed newspaper foot-bridge. J Profess Issues Eng Educ Practice 132(2):112–117 6. Štimac Grandi´c I (2015) Serviceability verification of pedestrian bridges under pedestrian loading. Tehniˇcki vjesnik 22(2):527–537 7. Ricciardelli F, Demartino C (2016) Design of footbridges against pedestrian-induced vibrations. J Bridge Eng 21(8):C4015003 8. Fujino Y, Siringoringo DM (2015) A conceptual review of pedestrian-induced lateral vibration and crowd synchronization problem on footbridges. J Bridge Eng 21(8):C4015001 9. IRC: 6-2017, Loads and stresses (revised edition) with latest amendments 10. IS:800-2007, General construction in steel 11. Benjeddou O, Limam O, Ouezdou MB (2017) The experimental and the theoretical analysis of the serviceability behavior of a deployable footbridge. Archi Civil Mech Eng 17(2):293–306 12. Qiu W-L et al (2010) Stability analysis of special-shape arch bridge. Tamkang Univ Sci Technol 13(4):365–373 13. Joshi V, Srinivasan M (2018) Walking crowds on a shaky surface: stable walkers discover millennium bridge oscillations with and without pedestrian synchrony. Biol Let 14(10):20180564 14. Barker C et al (2005) Footbridge pedestrian vibration limits-Part 1: pedestrian input. In: Footbridge 2005 international conference 15. BS-5400-1978 (Part 2), Steel, concrete and composite bridges 16. IRC:SP 56-2011, Guidelines for steel pedestrian bridges 17. EN 1991-1-5 (Part 1), Action on structures 18. EN 1993-1-1, Design of steel structures 19. EN 1994-1-1 (Part 1), Design of composite steel and concrete structures 20. Dymond BZ, Roberts-Wollmann CL, Wright WJ, Cousins TE, Bapat AV (2013) Pedestrian bridge collapse and failure analysis in Giles County, Virginia. J Perfor Construct Facilit 28(4):04014006 21. Xu C, Sugiura K, Qingtian S (2018) Fatigue behavior of the group stud shear connectors in steel-concrete composite bridges. J Bridge Eng 23(8):04018055

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22. Heinemeyer C, Feldmann M (2009) European design guide for footbridge vibration. In: Footbridge vibration design. CRC Press, pp 13–30

Lateral Load Analyses of Multi-storeyed Frames with and Without Shear Walls Akash John Koshy, A. Sofi, and A. R. Santhakumar

Abstract Multi-storeyed buildings are popping up more and more in India due to its ever-growing need for accommodation as opposed to its subsequent lack of land area. It is a known fact that as the height of the structure increases, lateral loads become a crucial part of the design. Shear walls are among one of the most common, cheap and effective methods by which lateral loads are resisted. In this paper, a study is made on multi-storeyed buildings of a symmetric plan with shear walls provided at multiple locations across the plan. The total length and thickness of walls were kept constant throughout all cases. Straight walls and L-shaped R.C.C. walls were made use of. Linear static, linear dynamic and non-linear static analyses were performed. Comparisons were made based on roof-level displacement, drift, stiffness of structure and ductility to find the best-performing configuration. Keywords Linear analyses · Pushover analysis · Storey displacements · Inter-storey drift · Ductility

1 Introduction This paper deals with the comparison of structural stability of multi-storeyed R.C.C. frames against lateral forces, when shear walls have been provided at different locations throughout the plan. The building plans taken for the study were symmetrical, and square in shape. A. J. Koshy School of Civil Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India e-mail: [email protected] A. Sofi (B) Department of Structural and Geotechnical Engineering, School of Civil Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India e-mail: [email protected] A. R. Santhakumar Civil Engineering, Anna University, Guindy, Chennai, Tamil Nadu, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_2

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Shear walls are vertical structural elements that resist in-plane lateral loads by utilizing cantilever action. Reinforced cement concrete shear walls have been taken for this study. Three building models were taken into consideration, and under each case, shear walls were provided at six different locations as straight and L-shaped flanged walls. The thickness and total length of walls were kept unchanged throughout all the different scenarios to find the influence of above-mentioned walls on the response of structures, based on their positioning alone. The variation in response, as the structure’s height and bay width were increased, was studied. All the analyses were performed using ETABS 2017. The whole procedure involves the following basic steps: Modelling, Linear analyses, Designing and Pushover analysis. Analyses were performed for Zone III, conforming to IS 1893: 2016. All members were designed utilizing IS 456: 2000 and detailed with recommendations from IS 13920: 2016. Non-linear analyses require proper modelling of structures with non-linearity introduced. The basic procedure for pushover analysis of a moment-resisting frame using ETABS is explained in [1]. The author explains the procedure for manually performing pushover analysis in [2]. From [3], shear walls can be modelled by multiple methods like single column method, fibre or frame modelling, multilayered shell modelling and shell model with fibre hinges. For modelling the wall as a shell element, both fibre and multilayered approach gave almost similar results according to [4–6]. However, proper hinge occurrence can’t be pinpointed in the multilayered model, even though it is the more accurate one. Thus, fibre hinge was chosen for analysis. [7–14] are associated with studies regarding linear analyses of structures with shear walls [13] showcases the effect of curtailment in shear walls, and reduction in the amount of steel used in frame members when shear walls are introduced is discussed in [7]. Non-linear analyses involving shear walls are performed in [15]. A general comparison between different papers regarding similar topics was obtained from [16, 17] and was helpful for the study.

2 Objective of the Study The objectives of the study include: • To analyse the structures using Equivalent static, Response spectrum and Pushover Analysis; • To find the optimum location of shear walls in each scenario.

3 Description of Models Three R.C.C. frames were considered. The base model is a symmetric, G+4 storey, R.C.C. frame with 6-m-long bays. The latter models have 11-m beam spans and double the number of storeys, respectively. Shear walls are introduced in each of

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21

Table 1 Geometrical properties of structures S.No.

Structure

Case A

Case B

Case C

1

Number of storeys

5

5

10

2

Length in X and Y direction (m)

30

55

30

3

Floor height (m)

3.5

3.5

3.5

4

Building height (m)

17.5

17.5

35

5

Slab thickness (mm)

125

125

125

6

Beam size (mm)

300,400

500,600

400,500

7

Column size (mm)

400,400

600,600

700,700

Table 2 Material properties S.No.

Material

Grade

1

Concrete (Beam, Column)

M30

2

Concrete (Slab)

M25

3

Rebar

HYSD 415

Table 3 Seismic data S.No.

Parameter

Case A

Case B

Case C

1

Seismic zone

2

Damping ratio (%)

III

III

III

5

5

5

3

Importance factor

1.2

1.2

1.2

4

Soil type

Medium soil

Medium soil

Medium soil

5

Response reduction factor

5

5

5

6

Time period

0.287 s

0.212 s

0.575 s

the above-mentioned cases at specific locations, either as straight or L-shaped walls. Detailed information regarding models is provided in Tables 1, 2 and 3.

4 Loading The load cases used for the analyses are listed below: • • • • •

Dead load (DL). Live load (LL)—Taken as 2.5 kN/m2 . Masonry load (ML)—Taken as 20 kN/m3 . Wind load (WL)—According to IS 875: 2015. Seismic Load (EL)—According to IS 1893: 2016.

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The load combinations for linear static analysis are given below: • • • • • • • •

1.5 (DL + ML) 1.5 (DL + ML + LL) 1.5 (DL + ML ± WL) 1.2 (DL + ML + LL ± WL) 1.5 (DL + ML ± EL) 1.2 (DL + ML + LL ± EL) 0.9 (DL + ML) ± 1.5WL 0.9 (DL + ML) ± 1.5EL.

Since the buildings are symmetrical, and because columns are of square section, wind and seismic analyses in only X-direction were performed. Masonry loads were applicable only for peripheral beams in all storeys, excluding the roof. In addition to the above-mentioned combinations, ones including loading by response spectrum functions were also considered for design.

5 Shear Wall Positioning The different positions at which shear walls are provided for Case A model is shown from Figs. 1, 2, 3, 4, 5, 6 and 7. The same trend is followed for the remaining two cases, i.e., B and C. Wall thickness was taken as 200 mm. Fig. 1 Core

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23

Fig. 2 Core with opening

Fig. 3 Straight-1

6 Analysis Results Equivalent static, response spectrum and pushover analysis were performed on all models.

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Fig. 4 Straight-2

Fig. 5 L-1

7 Linear Analyses Equivalent static analysis was performed based on user inputted time periods and response spectrum analysis was done for zone III. The load combination 0.9 (DL + ML) ± 1.5EL was found to be most critical for design and results displayed, corresponding to the same unless mentioned otherwise.

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25

Fig. 6 L-2

Fig. 7 L-3

8 Base Reactions Base reactions are functions of the total weight of the building. As such, all models are expected to have similar base reaction values, sparing some deviation due to addition or removal of beams and columns as required for the model considered. Figure 8 represents the comparison of base reactions.

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Base Reactions (kN) 8000 7000 6000 5000 4000 3000 2000 1000 0 CASE A MRF

CORE

CASE B CORE-OPENING

STRAIGHT-1

CASE C STRAIGHT-2

L-1

L-2

L-3

Fig. 8 Base reactions in kN

9 Top Storey Displacements The maximum lateral displacement undergone by topmost stories in each case is compared in Fig. 9. Top Storey Displacements (mm) 200 180 160 140 120 100 80 60 40 20 0 5 STOREY 6m MRF

CORE

5 STOREY 11m CORE-OPENING

Fig. 9 Top storey displacements in mm

STRAIGHT-1

10 STOREY 6m STRAIGHT-2

L-1

L-2

L-3

Lateral Load Analyses of Multi-storeyed Frames …

27

20 18 16

Elevation (m)

14

MRF CORE

12

CORE-OPENING

10

STRAIGHT-1

8

STRAIGHT-2 L-1

6

L-2 4

L-3

2 0 0

0.002

0.004

0.006

0.008

0.01

Storey drift

Fig. 10 Storey drifts for Case A

10 Storey Drift The difference in two consecutive storey displacements divided by that storey’s height gives the considered storey’s drift value. It is an important parameter in designing partition or curtain walls as they might crack due to larger drift values. Figures 10, 11 and 12 represents storey drifts in Cases A, B and C, respectively. The maximum storey drifts of different cases, from analyses, are charted in Fig. 13. It should be noted that when shear walls are provided, the maximum storey drifts occur at storeys that are near the top, in contrast to bare moment resisting frames, where it occurs at lower storey levels.

11 Stiffness Stiffness refers to the structure’s rigidity or its ability to resist displacement under the effect of a force. Maximum storey stiffness was observed at the ground floor and its variation among the different cases are charted in Fig. 14.

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20 18 16 14

MRF CORE

12

CORE-OPENING STRAIGHT-1

10

STRAIGHT-2 8

L-1 L-2

6

L-3

4 2 0 0

0.001

0.002

0.003

0.004

0.005

0.006

Fig. 11 Storey drifts for Case B 40 35 30

Elevation (m)

MRF 25

CORE CORE-OPENING

20

STRAIGHT-1 STRAIGHT-2

15

L-1 L-2

10

L-3 5 0 0

0.001

0.002

0.003

0.004

0.005

Storey drift

Fig. 12 Storey drifts for Case C

0.006

0.007

0.008

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29

Maximum storey drifts 0.009 0.008 0.007 0.006 0.005 0.004 0.003 0.002 0.001 0 CASE A MRF

CORE

CASE B CORE-OPENING

STRAIGHT-1

CASE C STRAIGHT-2

L-1

L-2

L-3

Fig. 13 Maximum storey drifts

Maximum storey stiffness (kN/m) 7000000 6000000 5000000 4000000 3000000 2000000 1000000 0 CASE A MRF

CORE

CASE B CORE-OPENING

STRAIGHT-1

CASE C STRAIGHT-2

L-1

L-2

L-3

Fig. 14 Maximum storey stiffness in kN/m

12 Non-linear Static Analysis Commonly known as pushover analysis, here, the considered building is given a user-specified lateral displacement until the structure is incapable to deform. Such an analysis gives a good idea on the pattern of building failure or hinge formation. The modelling of the structure or more precisely, the inclusion of non-linearity by means of hinges are of utmost importance here. M3, moment hinges are provided at ends of beams, and P-M2-M3 hinges are provided at the ends of columns. Shear

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Case A

0.45

DESIGN SPECTRUM

0.4

MRF

Spectral Acceleration (g)

0.35

CORE

0.3

CORE-OPENING

0.25

STRAIGHT-1

0.2

STRAIGHT-2 0.15 L-1 0.1 L-2 0.05 L-3 0 0

50

100

150

200

250

Spectral Displacement (mm) Fig. 15 Pushover curves for Case A

walls are modelled as shells itself with fibre hinges along with uniform reinforcement ratio in either direction applied. NTC 2008 was made use of, for obtaining the target displacements.

13 Pushover Curves The capacity curves for the different scenarios have been plotted against a scaled design spectrum function corresponding to Zone III as per Indian standards in Figs. 15, 16 and 17 for Cases A, B and C, respectively.

14 Performance Points The capacity curves for the different scenarios have been plotted against a scaled design spectrum function corresponding to Zone III as per Indian standards in Table 4.

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31

Case B

0.45

DESIGN SPECTRUM 0.4

MRF

Spectral Accelaration (g)

0.35

CORE 0.3

CORE-OPENING 0.25

STRAIGHT-1 0.2

STRAIGHT-2 0.15

L-1 0.1

L-2 0.05

L-3 0 0

50

100

150

200

250

Spectral Displacement (mm) Fig. 16 Pushover curves for Case B

15 Ductility It is the ability of the considered structure by which it can withstand displacements or deformations without catastrophic failure. It is one of the most important terms in earthquake engineering, in the sense, if ductility is more, then the probability of life endangerment is less. It is expressed as the ratio of displacement at performance point to the displacement at the formation of first hinge. Data regarding ductility for various cases are tabulated in Table 5.

16 Results and Discussions • Base reactions, in all cases, for every model were mostly similar. It is worthy to note that base reactions for L-3 in all cases gave the least value. There was a reduction of base reaction from bare MRF by 5.6% for L-3 followed by straight-2 by 2.28%. The general trend is similar among all cases. • A huge reduction in top storey displacements is seen throughout all models when the shear wall is provided.

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Case C 0.45 DESIGN SPECTRUM

0.4 MRF

Spectral Acceleration (g)

0.35 CORE

0.3 CORE-OPENING

0.25 STRAIGHT-1

0.2 STRAIGHT-2

0.15 L-1

0.1 L-2

0.05 L-3

0 0

50

100

150

200

250

Spectral Displacement (mm) Fig. 17 Pushover curves for Case C

– Core walls perform the best in all cases by reducing the maximum storey displacements by 85% from the base value. – In five-storeyed structures, straight walls (straight-2) perform better than L shaped walls (L-3) by 10.98%. – In ten-storeyed structures, L shaped walls (L-3) perform better than straight walls (straight-2) by 5.3%. • Storey drifts follow the same pattern as storey displacements. – Core walls outperform others by maximum drift reduction of 85.8%. – Straight walls perform better than L shaped ones at five-storeyed height and L-shaped walls perform better for ten-storeyed structure. • Stiffness follows the same trend in all cases with core walls providing maximum resistance to lateral loads. An increase in stiffness by 88% form base models were observed. • Performance points imply that core walls perform the best by providing the best shear capacity and minimum displacement. • Ductility varies differently among all the cases: – For Case A, straight walls provide maximum ductility. – For Case B, L-shaped walls provide maximum ductility. – For Case C, straight wall along periphery performs best.

Base shear (kN)

Displacement (mm)

Case C

Base shear (kN)

Displacement (mm)

13943.7

70.2

13451.3

160.17

Base shear (kN)

Case B

199.14

3322.8

Displacement (mm)

Case A

MRF

Table 4 Performance points

22087.7

44.5

16612.4

60.0

10635.8

54.52

Core

21240.7

45.8

15695.8

62.7

10218.1

57.35

Core-opening

18329.8

45.1

13650.8

75.8

6142.67

85.57

Straight-1

17258.3

43.8

13359.4

75.87

5259.8

81.92

Straight-2 82.28

16434.2

57.5

13496.8

104.94

5061.6

L-1

71.19

16406.4

57.46

13496.8

104.94

4872.9

L-2

68.72

15408.8

57.6

12606.1

102.66

4418.09

L-3

Lateral Load Analyses of Multi-storeyed Frames … 33

34

A. J. Koshy et al.

Table 5 Ductility Case

MRF

Core

Core-Opening

Straight-1

Straight-2

L-1

L-2

L-3

A

1.51

1.57

2.60

6.11

8.70

5.58

5.25

4.37

B

4.64

3.22

3.34

5.20

4.74

6.74

6.48

3.10

C

1.79

4.46

4.45

2.98

4.70

3.17

3.41

2.90

L-shaped walls follow the same trend in all cases with L-3 exhibiting lesser ductility than L-1 and L-2, giving similar values. For the longer span structure, straight-1 outperformed straight-2. Only in case 3 did core walls have greater ductility than other configurations. Thus, generally, core walls gave greater ductility for a taller building.

17 Conclusions Considering all the factors that are provided in the paper, core walls perform the best for the given structure heights. In the shorter and taller structures, core walls exhibited the best results in terms of roof level displacement, storey drift and stiffness as per linear analyses. Pushover analysis also places core walls at the apex in terms of performance points. The only area where core walls suffer is in terms of ductility. Core walls provide the least ductility in almost all cases but it makes up for that with its clearly higher shear capacity. L-shaped walls performed better than straight walls for the taller building, furthermore, it also helps in containing the torsional effects. If analyses were performed for even taller structures, L-shaped walls might prove to be even more effective than core walls. For shorter structures, straight walls performed better as opposed to L-shaped walls with respect to displacement parameters and stiffness. Straight walls provide adequate ductility in all cases and have better performance points as compared with L-shaped walls. It is a configuration that does well or performs adequately in every scenario.

References 1. Shah MD, Patel SB (2011) Nonlinear static analysis of RCC frames (software implementation ETABS 9.7). In: National conference on recent trends in engineering & technology 2. Chopra AK, Goel RK (2004) A modal pushover analysis procedure to estimate seismic demands for unsymmetric-plan buildings. Earthquake Eng Struct Dynam 33(8):903–927 3. Anwar N, Aung TH (2016) Modelling of shear walls for non-linear and pushover analysis of tall buildings 4. Debnath PP, Choudhury S (2017) Nonlinear analysis of shear wall in unified performance based seismic design of buildings. Asian J Civil Eng 4(18):633–642

Lateral Load Analyses of Multi-storeyed Frames …

35

5. Fahjan YM, Kubin J, Tan MT (2010) Nonlinear analysis methods for reinforced concrete buildings with shear walls. In: 14th European conference on earthquake engineering 6. Kubin J, Fahjan YM, Tan MT (2008) Comparison of practical approaches for modelling shearwalls in structural analyses of buildings. In: The 14th world conference on earthquake engineering 7. Husain MA, Mahmood OI (2017) Comparative study for different types of shear walls in buildings subjected to earthquake loading. Al-Nahrain J Eng Sci 20(2):358–367 8. Mishra S, Singh VK (2018) Optimization of location of shear wall in irregular multi storey building. Int J Eng Res Mech Civil Eng 3(4) 9. Sahu V, Khare GP, Sahu DK (2018) Behaviour of multistorey building with different shear wall arrangements with and without central cross shear wall. Int Res J Eng Technol (IRJET) 5(1) 10. Jaya P, Alandkar PM (2016) Drift analysis in multistoried building. Int J Eng Sci Res Technol 11. Aliya WK, Charkha SD, Determination of base shear and displacement for multi-storey building with different location of shear wall using STAAD.Pro. Int J Eng Innov Technol (IJEIT) 4(11) 12. Sud A, Shekhawat RS, Dhiman P (2014) Effect of different shear wall configurations on seismic response of a moment-resisting frame. Euro Scienti J ESJ 10(10) 13. Shekhawat RS, Sud A, Dhiman P (2014) Economical placement of shear walls in a moment resisting frame for earthquake protection. Int J Res Eng Technol 3(9):346–352 14. Maheedhar BR, Kumar MA, Nagarjuna S, Prasad CVSR (2018) Analysis and design of G + 12 storey building with shear wall effect with two basements. Int Res J Eng Technol (IRJET) 5(5) 15. Nazari YR, Saatcioglu M (2017) Seismic vulnerability assessment of concrete shear wall buildings through fragility analysis. J Build Eng 12:202–209 16. Khandelwal DN, Mhetre MS (2017) A review on optimum height and location of shear walls in high-rise buildings. Int J Innov Eng Sci 2(9) 17. Tuppad S, Fernandes RJ (2015) Optimum location of shear wall in a multi-storey building subjected to seismic behavior using genetic algorithm. Int Res J Eng Technol (IRJET) 2

The Diagnosis for the Lack of Remote Village Electrification Using Sustainable Energy in Labranzagrande Alan Achenkunju John and P. Venkatesh Kumar

Abstract This paper focuses on the analysis of electrification prospects for a remote village in Colombia. The main goal is to define the best sizing of a hybrid power plant to serve the microgrid with renewable energy resources like solar, wind, hydro, etc. The yearly average of energy potential and load consumption is the main requirement. In spite of the extension of coverage in electrification in the mentioned sectors, these have never been included in any project which contributes to accentuate the conditions of poverty. This paper is a case study of the rural area of the municipality of Labranzagrande, which does not have an energy service. Adding to this problem, its location is in the so-called isolated areas. The proposed solution to the lack of energy in homes can also be applicable for schools in whose classrooms there is no service either. Keywords Hybrid · Renewable energy · Photovoltaic · Microgrid · Remote village · Hydropower · Electrification

1 Introduction This is the analysis of the prospects for remote village electrification in the state of Boyacá Colombia, where there is the provision to build a microgrid. The objective is to develop generation systems with a hybrid power plant to serve the microgrid according to the availability of renewable energy resources [1, 2]. This case study defines the energy needs of the town to draw its consumption curve and assume its evolution over time. Various technically feasible energy solutions have been assessed for the rural area. But the rural areas are not connected with the utility grid and these systems do not satisfy the amount of required supply. For these situations, the A. A. John · P. V. Kumar (B) Department of Electrical and Electronics Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India e-mail: [email protected] A. A. John e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_3

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A. A. John and P. V. Kumar

approach of hybrid technology has been introduced. It can work fully with renewable sources as well as partially on conventional resources [3, 4]. Despite the extension of coverage in the electrification of the referred sectors, these have never been included in any project, thus contributing to accentuate the conditions of poverty.

2 Scope and Goals • To analyze and evaluate renewable energy potential mainly for resources such as Solar Radiations, Wind, and Hydro Potential at the Labranzagrande locality in the Department of Boyacá [5]. • To make the prefeasibility analysis and estimate the load demand. The planning system should follow the main goal of building an eco-friendly system that is a more pollution-free system. The system is a cost-effective analysis of a hybrid system for a sensible repayment period.

3 Area for Case Study The rural area of the municipality of Labranzagrande does not have an energy service. Adding to this problem, its location is in the so-called Isolated Areas shown in Fig. 1. Verda Guayabal is an area where there are 74 consumers unable to connect to the grid. So, the difficulty of expansion of the grid and the transportation facility difficulty lead to the proposal of a Project with Renewable Energy. A. Current Scenario The study of the current scenario of the location and the geographical features, the energy consumed by the people, and the energy potential of the area are helping to provide a verdict for the energy solutions [6]. The analysis will give a conclusion for deciding the various systems and their advantages. From this, we can easily find out feasible solutions for rural electrification. • Inside the Ministry, the Weather Change Moderation Group discourses all problems related to climate in the country, and Colombia’s hydraulic potential, solar potential, and greenhouse emissions are very low per unit of GDP (0.2 tCO2e) and per capita (1.3 tCO2e). • The Organization of Latin American Energy (OLADE) assessed that CO2 emissions from electricity generation in 2003 were 6.5 million tons. At present, 30% of CO2 emissions in Colombia are derived from the energy sector [7, 8]. The diagnosis of locations to be electrified requires a load consumption rate. Moreover, the load curve demand area should be analyzed and the energy production rate of the rural area should be calculated.

The Diagnosis for the Lack …

39

Fig. 1 Municipality map of Labranzagrande

B. Load Consumption of Labranzagrande The estimation of electricity demand for rural villages is not easy. The finest way to do it would be to study an equivalent village powered by a community with renewable resources. Then it would be convenient to measure the electricity generated and narrate it to the village we are interested in. The typical load consumption of a rural town is usually composed of a prominent peak at night corresponding to the use of lighting, a peak in the morning/noon, and a baseload is shown in Table 1. The curve demand of 96 users is shown in Fig. 2 for 24 h. The daily maximum demand for electrical usage by the people is at the peak hours between 6:00 a.m. and 8:00 a.m. and from 6:00 p.m. to 10:00 p.m. • The main goal of estimating the load consumption of the users is to determine the energy needs and the sizing of the power generation system. • The economic activities performed by the users of this area are mainly agriculture, cow farming, crop cultivation, etc. • For one user, the total load consumption per day is 5,940 W and the total capacity of electric load is 1,195 watts. • The energy consumed and the load demand assessed for the total number of users in the rural area is 74. • The total electric load consumption of users per day is 441 kWh and for one month is 13,231 kWh. Total capacity of the electric load is 88 kW.

40

A. A. John and P. V. Kumar

Table 1 Daily electrical load consumption of rural areas in Labranzagrande Load

Watts

Qty

Total Watts AC

Lamp

Use Hrs/Day

DC

Total Wh/day

60

5

300

3.8

1140.0

Water Pump

150

1

150

1.0

150.0

Blender

400

1

400

1.0

400.0

Television

60

1

60

4.0

240.0

Radio

20

1

20

8.0

160.0

200

1

200

15.0

3000.0

Phones

10

3

30

0.3

10.0

Self Consumption of the equipments

35

1

24.0

840.0

Average daily load AC

5100

Average daily load DC

840

Total Wh/day

5,940

Refrigerator

AC total connected watts

35 1160

DC total connected watts Total load watts

35 1,195

Fig. 2 Electrical load consumption curve

The initial assessment and location identification have be done for energy potential analysis. The analysis of the renewable energy potential of solar, wind, and hydraulic is necessary to estimate the range of energy production (kWh), the sizing of power capacity of generation (kW), and estimation of renewable resources exploitation in the area of study.

The Diagnosis for the Lack …

41

C. Energy Potential The analysis of the renewable energy potential of solar, wind, and hydraulic is necessary to estimate the range of energy production (kWh), the sizing of power capacity of generation (kW), and estimation of renewable resources exploitation in the area of study. The solar radiation in Labranzagrande per year is an average value of 4.75 kWh/m2 , which is shown in Fig. 3. The source for finding solar irradiation is the World Atlas which has all kinds of information about renewable energy resources. The wind resource is good only on the Pacific Coast, but for the Department of Boyacá, it is less as compared to the other departments in Colombia. The wind speed, air density, and direction are important parameters used for calculating the wind energy potential of the area (Fig. 4). The evaluation of the hydro potential throughout the Department of Boyacá receives the main attention among local resources, being one of the objectives of this work. Figure 5 shows the water flow rate of the River Cravo Sur having 20 50 m3 /sand the location for rural areas. The River Cravo Sur has a flow rate of 40 m3 /s.

4 Energy Solutions The renewable energy potential analysis of solar, wind, and hydro shows that solar and hydroelectric system is more feasible. The interconnection to the existing utility grid is the finest solution at present but for that, there are some restrictions with financial and environmental risks. The economic viability is more important to consider the expansion of the grid to tie. If we are going to build a power generation system, utilizing the renewable resources of the area is more beneficial than the grid-tie. The challenges for the grid connection are the environmental problems and distance of the users from a particular area. The energy solutions for Labranzagrande are classified along with their risks, advantages, and methods for the generation and transmission systems. The analysis of load consumption and energy potential range of the rural area head for the different energy generation solutions are classified below: 1. 2. 3. 4.

Isolated PV for Dispersed users PV–MCH Hybrid Solution without connecting to the grid. PV–MCH Hybrid Solution with connection to the grid Connect to the grid without a generation system.

The reasons for selecting hybrid solutions mainly geographically, technically, and financially are categorized below:

42

Fig. 3 Solar global horizontal irradiation of Colombia

A. A. John and P. V. Kumar

The Diagnosis for the Lack …

43

Fig. 4 Wind speed of Labarzagrande

• The main reason for selecting Photovoltaic–Microhydro Hybrid Power Plant in this area is the higher energy potential rate of Solar and Hydro. • The PV potential rate is 24.5 KW and the hydro potential rate from the River Cravo Sur is 65 MW which is really beneficial for this kind of power generation system in this area and it is also helpful for empowerment of rural areas. • The alternative solution which is available on the location is the connectivity to the main grid. The financial investment and environmental risks are high. So in order to find a better solution for this, we go for the hybrid power plant which is economically feasible and reliable to the company.

5 Conclusions The rural area of the municipality of Labranzagrande does not have an energy service. Adding to this problem, its location is in the so-called Isolated Areas. Renewable resources potential is analyzed for the rural area given the full potential range of solar and wind. The energy solutions by analyzing the potential and other criteria and simulation results in HOMER Pro which states that PV–MCH Hybrid Off-Grid System is more feasible financially and economically.

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Fig. 5 Water flow rate of Labranzagrande

References 1. Energización solar fotovoltaica para las viviendas de las Zonas Rurales no inter comunica das del Municipio de Labranzagrande Boyacá. “PROYECTO: ENERGIZACIÓN SOLAR FOTOVOLTAICA PARA LA ZONA RURAL DEL MUNICIPIO DE LABRANZAGRANDE DEPARTAMENTO DE BOYACA BENEFICIARIOS: 96 FAMILIAS” 2. Atlas Potencial Hidoenergetico de Colombia, 2015 UPME 3. http://atlas.ideam.gov.co/presentacion/ 4. http://sig.simec.gov.co/GeoPortal/Carrusel/Home 5. Electric Power Development Co., Ltd., Guideline and manual for hydropower development, vol 2 small scale hydropower. 2011 Japan International Cooperation Agency 6. Meshram S, Agnihotri G, Gupta S (2013) Modeling of grid connected DC linked pv/hydro hybrid system. Elect Electro Eng Int J (ELELIJ) 2(3) 7. Kusakana K, Munda JL, Jimoh AA (2009) Feasibility study of a hybrid PV-micro hydro system for rural electrification. IEEEAFRICON 2009, 23–25 Sept. 2009, Nairobi, Kenya 8. D-026-18 AUTOGENERACIÓN A PEQUEÑA ESCALA Y GENERACIÓN DISTRIBUIDA. http://apolo.creg.gov.co/Publicac.nsf/1c09d18d2d5ffb5b05256eee00709c02/83b41035c2c4 474f05258243005a1191

Experimental Studies on the Suitability of Coconut Shell as a Filler Material in Concrete Cubes Renuka Sai Gadekari, Sreevalsa Kolatayar, and Rajesh Kumar Chitrachedu

Abstract Globally, the consumption of concrete is raising high. The production of cement raises the carbon footprint and causes depletion of non-renewable resources. Researchers are formulating new technologies to save the resources, energy for the next generations, to reduce disposal problems and to make the product or structure economical. For this purpose, recycled waste and treated natural materials, etc., are used as a substitute for cement, aggregates, or reinforcement. This paper presents studies conducted to analyze the performance of a coconut shell as a filler. The material used in the present study was naturally available, cost-free, and non-toxic material. The strength performance of different concrete cube specimens with coconut shells in their different orientations was assessed by conducting compressive strength tests. From the results, the effective position and orientation of the shell in the concrete cube were found out. Keywords Compressive strength · Orientation · Rebound hammer · Construction · Impact value

1 Introduction There is a depletion of river sand and aggregates mined from rock quarries that are used as raw materials in manufacturing concrete. Nowadays many waste materials can be reused in manufacturing composite materials. Coconut shell is a strong, naturally available, and eco-friendly material. The untreated shell resists decay and there will be less loss in the strength even though the shells are thrown into a garden R. S. Gadekari Sree Vidyanikethan Engineering College, Tirupati, India S. Kolatayar (B) National Institute of Technology Karnataka, Mangalore, India e-mail: [email protected] R. K. Chitrachedu Ashoka Institute of Engineering & Technology, Hyderabad, India © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_4

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compost. It is a high potential material for the development of new composites because of their high strength. Agunsoye et al. [1] revealed that the crushed coconut shell can be used in casting new metal matrix composites to ameliorate the strength, resistance toward bad weather, etc. The rough texture and hardness of coconut shell provide high impact strength to the composites in which it has been used as a filler material. Keerthika et al. [2] observed that the tensile strength, hardness, breaking strength, and specific gravity of acrylonitrile butadiene rubber can be efficiently increased with the use of coconut shell powder as a filler material. Coir fiber and coconut shell powder together provide good stiffness and flexural strength [3] to pelletized polyethylene waste. Agunsosoye et al. [4] found that the rough texture of the powdered coconut shell improves the properties like the hardness of polyethylene waste and reduces the porosity by acting as a filler material. Related to innovations in pavement materials with products of coconut shell Jeffry et al. [5, 6] carried out studies on nano-charcoal coconut shell ash (NCSA) in bitumen. NCSA improved the performance of bitumen in resisting fatigue cracks and rutting. Aminah et al. [7] conducted tests and concluded that the coconut shells can produce lightweight concrete and reduce the cost of construction by replacing coarse aggregate with coconut shells. Coconut shell aggregate can be treated only for water absorption, as other treatments were not required. Kukarni and Gaikwad [8] observed no bond failure in the test specimens as there will be adequate bonding between the coconut shell aggregate concrete and the steel bars. Research work conducted by Ahlawat and Kalurkar [9] proved that the CS aggregates can be effectively used in reinforced concrete construction. The percentage increase of CS powder as a filler material in concrete gives high split tensile strength [10]. Gunasekaran et al. [11, 12] carried out various experiments to understand the behavior of coconut shells as aggregate in concrete. Some of the conclusions drawn from their research work are lower wood–cement ratio results in weaker bonds between wood and concrete matrix. The present paper discusses the direct usage of coconut shells as a filler material.

2 Materials 2.1 Coconut Shell Coconut shells were collected from Palakkad, Kerala, India. Some of the coconut shells have a small hole at its crown part, and some are without a hole. The thickness of shells varies from 2 to 4 mm, height 50 to 70 mm, and diameter 70 to 110 mm. Shells were dried in the sunlight to remove moisture from it.

Experimental Studies on the Suitability of Coconut Shell … Table 1 Mechanical properties of coconut shell

2.1.1

47

S. No.

Property

Value (%)

Reference

1

Impact value

9.01

IS: 5640–1970 [14]

2

Crushing value

2.76

IS: 2386 Part IV–1963 [15]

3

Abrasion value

1.50

IS: 2386 Part IV–1963 [15]

Physical and Mechanical Properties

Important properties like moisture content and water absorption tests were conducted to know the physical properties of the coconut shell. As there are no separate test procedures for coconut shells to find the above properties, the shells were crushed into small pieces of size 2–10 mm. Then the standard procedures available to test coarse aggregate were used. The moisture content came out to be 3.92% as per IS: 2386 Part III–1963 [13] and water absorption was 19.87%. The mechanical properties of coconut shells, like impact, crushing, and abrasion values, were found to measure the resistance of shell toward impact loads, gradually applied load and wear, respectively. The values are tabulated in the following Table 1.

2.1.2

Compressive Strength Properties

The shell is tested under the universal testing machine (UTM) with different orientations to know the maximum load taken by the shell and to study the failure pattern of the shell. The different orientations of the shell are shown in Fig. 1. After a number of trials, it is observed that the coconut shell (with hole-crown up), i.e., CSHU will take a load of about 7 kN. The load taken by shells in their different orientations is shown in Table 2. The failure of a coconut shell with a hole (Fig. 2) is safe as the crack will extend up to the hole and it stops. As there is no material at the hole the load will not pass through the other half shell. The failure of coconut shell without a hole occurs at the crown part and the failure will be sudden.

2.2 Plain Concrete A normal M25 mix has been used to cast all concrete cubes. Based on specific gravity, water absorption, the total moisture content of coarse and fine aggregates, and by considering mild exposure conditions, the proportion of mix was 1:1.821:2.766 as per IS: 10262–2009 [16]. Ordinary Portland Cement of 43 grade, river sand, and mined quarry coarse aggregates were used in casting cubes. The concrete cubes of

48

R. S. Gadekari et al.

Fig. 1 a Coconut shell (with hole-crown up) CSHU. b Coconut shell (with hole-crown down) CSHD. c Coconut shell (without hole-crown up) CSU. d Coconut shell (without hole-crown down) CSD Table 2 Load-bearing capacity of coconut shells in their different orientations

Fig. 2 Failure pattern of coconut shell with a hole

S. No

Type and orientation

Maximum load (KN)

1.

CSHU

7.29

2.

CSHD

4.12

3.

CSU

5.28

4.

CSD

2.68

Experimental Studies on the Suitability of Coconut Shell …

49

Table 3 Different concrete cubes S. No.

Type of concrete cube

1.

Normal

2.

CS infilled with concrete with a nominal cover of 25 mm

3.

Hollow shells with no nominal cover

Position of shell in the concrete cube

Designation

–

–

N

Crown up

Top

SCHUT

Bottom

SCHUB

Top

SCHDT

Crown down

Bottom

SCHDB

Crown up

Bottom

SHUB

Crown down

Top

SHDT

150 mm × 150 mm × 150 mm were cast with a nominal cover of 25 mm for concrete infilled shells and no cover for hollow shells.

3 Different Orientations of Coconut Shell in Concrete Cubes The casting of concrete cubes carried out by placing CS of both types in different orientations. Three sets of concrete cubes were cast. From the compressive testing of the coconut shell, it was clearly observed that the shell having holes had shown the best results. Due to this reason, all concrete cubes were cast by placing coconut shells with a hole. As placing a hollow concrete shell with the crown up in top portion and crown down in the bottom portion is not possible in site conditions, these two patterns were not cast. The details of different concrete cubes are given in Table 3 and are shown in Fig. 3. About 42 concrete cubes were cast with the above-specified positions and orientations to analyze the compressive strength of concrete cubes for 7 days and 28 days of curing period.

4 Results and Discussion 4.1 Rebound Hammer Test Rebound hammer test, a non-destructive test was done as per the standard procedure specified in IS: 13311 (Part 2)–1992. The compressive strength of concrete cubes was measured from the rebound number. The calibration chart given by the equipment manufacturer was used to measure the compressive strength. The results are presented in Table 4.

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Fig. 3 a CS crown down in bottom portion of cube (DB) (CS infilled with concrete). b CS crown down in top portion of cube (DT) (CS infilled with concrete or hollow CS). c CS crown up in bottom portion of cube (UB) (CS infilled with concrete or hollow CS). d CS crown up in top portion of cube (UT) (CS infilled with concrete)

Table 4 Compressive strength of concrete cubes from Rebound Hammer test S. No.

Specimen details

28 days compressive strength (MPa)

1.

N

25

2.

SCHUT

16

3.

SCHUB

24

4.

SCHDT

12

5.

SCHDB

18

6.

SHUB

26

7.

SHDT

15

From the above results, it can be seen that the cubes in which shell was in the bottom portion shown high compressive strength. The hollow shells and shells infilled with concrete gave almost the same strength. But, the failure pattern of different concrete cubes was not known with a rebound hammer test. To observe this and to find the reason behind the strength, compression tests were performed.

4.2 Compressive Strength Tests Figure 4 shows the 7-day compressive strength and Fig. 5 shows the 28-day compressive strength of different specimens as specified in Table 3. From the above comparison charts, it can be clearly seen that the specimen with crown up shell at its bottom

Experimental Studies on the Suitability of Coconut Shell …

51

Fig. 4 Compressive strength of different specimens (7 days cured)

Fig. 5 Compressive strength of different specimens (28 days cured)

portion provided higher compressive strength. The infilled shell concrete cubes did not show much good results than the hollow shell concrete cube. While testing, different failure patterns were observed. While performing the compressive strength test of concrete cubes having CS, it was observed that the shell took the load which was transferred from concrete to CS after the formation of the first crack. As discussed earlier in Sect. 2.1.2, the concrete shell can withstand up to a load of around 7 kN. It can be observed clearly that due to the presence of CS, the crack took a path as seen in Fig. 6. This indicates that the concrete cubes with CS are satisfying the serviceability criteria. The hollow shells in the concrete cube with crown up in the bottom portion showed the best results

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Fig. 6 Failure pattern of SHUB

as the shell at that position acted as filler material and are load-bearing blocks. As these blocks are cost-effective, provides an aesthetic appearance, high strength than conventional concrete cubes, and good thermal insulation, these can be used in constructing structural elements like beams and slabs.

5 Conclusion This study introduced a coconut shell which is a sustainable and low-cost material as a potential filler in concrete cubes. The effective shell orientation and its position in the concrete cube were effectively evaluated for its applicability as a filler material in structural members. It was concluded that the average compressive strength of SHUB and SCHUB concrete cubes was higher. This showed that infilling the shells with concrete does not make much sense. By placing the hollow shells in structural members, the overall cost of construction reduces as the quantity of cement, coarse and fine aggregates will be saved with the inclusion of CS. Further investigation will pave the way for the incorporation of CS in structural members like beams and slabs.

References 1. Agunsoye JO, Talabi SI, Bello SA, Awe IO (2014) The Effects of cocos nucifera (coconut shell) on the mechanical and tribological properties of recycled waste aluminium can composites. Tribol Ind 36(2):155–162 2. Keerthika B, Umayavalli M, Jeyalalitha T, Krishnaveni N (2016) Coconut shell powder as cost effective filler in copolymer of acrylonitrile and butadiene rubber. Ecotoxicol Environ Saf 130:1–3

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3. Kuburi LS, Dauda M, Obada DO, Umaru S, Dodoo-Arhin D, Iliyasu I, Mustapha S (2017) Effects of Coir Fibber loading on the physio-mechanical and morphological properties of coconut shell powder filled low density polyethylene composites. Procedia Manufact 7:138–144 4. Agunsosoye JO, Isaac TS, Samuel SO (2012) Study of mechanical behaviour of coconut shell reinforced polymer matrix composite. J Miner Mater Character Eng 11:774–779 5. Jeffry SNA, Jaya RP, Abdul Hassan N, Yaacob H, Satar MKIM (2018) Mechanical performance of asphalt mixture containing nano-charcoal coconut shell ash. Constr Build Mater 173:40–48 6. Jeffry SNA, Jaya RP, Hassan NA, Yaacob H, Mirza J, Drahman SH (2018) Effects of nanocharcoal coconut-shell ash on the physical and rheological properties of bitumen. Constr Build Mater 158:1–10 7. Aminah S, Tukiman, Sabarudin M (2009) Investigate the combination of coconut shell and grained palm kernel to replace aggregate in concrete: a technical review. In: The proceedings of national conference on postgraduate research (NCON-PGR), 1st October 2009, UMP Conference Hall, Malaysia, 2009 8. Kukarni PV, Gaikwad SKB (2013) Comparative study on coconut shell aggregate with conventional concrete. Int J Eng Innov Technol 2(12):67–70 9. Ahlawat D, Kalurkar LG (2015) Performance of coconut shell as coarse aggregate in concrete: a review. Int Res J Eng Technol 2(4):1096–1100 10. Leman AS, Shahidan S, Nasir AJ, Senin MS, Mohd Zuki SS, Wan Ibrahim MH, Azhar ATS (2017) Properties of concrete containing coconut shell powder (CSP) as a filler. IOP Conf Ser Mater Sci Eng 271(1):1–8 11. Gunasekaran K, Kumar PS, Lakshmipathy M (2011) Mechanical and bond properties of coconut shell concrete. Constr Build Mater 25(1):92–98 12. Gunasekaran K, Kumar PS, Lakshmipathy M (2011) Study on properties of coconut shell as an aggregate for concrete. Nat J Ind Concr Inst 12(2):27–33 13. IS: 2386 (Part III)–l963, Indian standard methods of test for aggregate for concrete, Part III specific gravity, density, voids, absorption and bulking 14. IS: 5640–1970, Indian standard method of test for determining aggregates impact value of soft coarse aggregate 15. IS: 2386 (Part IV)–1963, Indian standard methods of test for aggregate for concrete, Part IV mechanical properties 16. IS: 10262–2009, Indian standard concrete mix proportioning—guidelines (first Revision)

A Sustainable Approach to Turn Plastic Waste into Useful Construction Blocks K. Monish, J. John Jesuran, and Sreevalsa Kolathayar

Abstract The world economy is surging and newer technologies are evolving with the time. The construction sector is about to undergo a huge transformational change. The people of the world are looking forward to residing in houses made of sustainable materials. The people are concerned about increasing levels of greenhouse gases in the atmosphere. The cement production is accompanied by huge greenhouse gas emissions. On the other hand, waste plastics are becoming a nightmare for the people residing in developed and underdeveloped countries, as the waste management becomes difficult in those places. This research discusses a potential solution to address the above-stated issues of concern, i.e., plastic waste into construction blocks with lower cost and rapid construction phases. A study was conducted to examine the effectiveness of using LDPE (Low-Density Polyethylene), (major sources of waste and least recycled plastic) with waste materials like bottom ash, copper slag, and ceramic in different proportions to create blocks. This study compares the mechanical properties of different mix proportions of raw materials to find an optimum composition. This paper also investigates the pre-eminence of the newly developed composite block over the conventional brick in terms of economic viability, environmental sustainability, and construction superiority. Keywords LDPE · Low cost · Composites · Bottom ash · Copper slag · Ceramic

1 Introduction The Management of waste has gained a huge thrust in the developing countries like India. As per Census of India [1], the population of India is reaching 1.32 billion. Central Pollution Control Board (2015) shows that 0.143 million tons of solid wastes K. Monish · J. J. Jesuran Department of Civil Engg, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India S. Kolathayar (B) National Institute of Technology Karnataka, Mangalore, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_5

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are generated per day in the country out of which only 77% has not been processed in accordance with the guidelines which poses a serious threat to the country. Narrowing the issues to the plastic waste, the Central Pollution Control Board (2015) survey shows 15342.6 tons of plastic waste per day is produced. Out of this enormous waste is recycled and the plastic waste mainly LDPE is littered and uncollected because of its low recycling value. It is a well-known fact that India is undergoing a huge development; the people of India are shifting from their shelter from the mud-based hut to brick mortar homes. As a result of this, the demand for the brick and the cement is increasing, and the cement production is associated with greenhouse gas emission. In this paper, we are going to address the alternative solutions for the above-stated problems by using LDPE with other waste materials to develop interlockable bricks. Plastic is generally classified into two categories, namely thermoplastic and thermosetting plastic. The thermoplastic has the superiorly of being recycled without altering its property [2]. Out of the total waste produced, the thermoplastic contributes to 78% [3], and the polyethylene and PET are categorized as a thermoplastic. Of the total plastic produced in the world, LDPE comprises 17% of volume [3]. LDPE is a soft material of low cost, and it has a good ductile and impact resistance. Polyethylene terephthalate (PET) is also one of the more prevailing plastic wastes in the environment. The decomposition period for PET is higher than the LDPE. Many researchers incorporated the plastic waste into the concrete matrix. But they recommended incorporation of plastic waste below 2% of the total weight of the concrete [4]. Many research works have been done on natural residues [4–6]. Hamid and Sahrim [7], Félix et al. [8] tried to incorporate different coupling agent to increase the binding property between the plastic and the filler. Mohan [9] examined the effectiveness of using LDPE and HDPE (High-Density Polyethylene) with easily procurable materials like sand, rice husk, and sawdust, in different proportions to create the interlocking blocks.

2 Materials and Methodology 2.1 Materials 2.1.1

Low-Density Polyethylene (LDPE)

The waste plastic carry bags are procured from the Amrita Recycling Plant. It is subjected to cleaning with the water, and the cleaned plastic is shredded using the shredder machine into pieces of size varying from 2 to 50 mm. The density of the LDPE is 0.9 gm/cm3 , and the melting point is around 130 °C.

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2.1.2

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Bottom Ash

The Bottom Ash (BA) is mainly produced as a waste in the thermal power plants, and the bottom ash is mainly used as the landfill but there are many problems associated with it [10]. The density of the bottom ash was found to be 700 kg/m3 [11]. It is sieved through an 800-micron sieve to avoid the carbon content as it decreases the mechanical properties of the composite.

2.1.3

Polyethylene Terephthalate

The main source for the PET plastic is plastic bottles. The melting point of the PET was around 260 °C, and the density was around 1.38 g/cm3 . The plastic bottles are obtained from the Amrita Recycling Plant and shredded into pieces of size 5 to 50 mm.

2.1.4

Copper Slag

The copper slag is the main byproduct produced in the manufacturing process of the copper from its ore. The size of the copper slag is further reduced, and it is generated as waste. The density of the copper slag is found out to be 3.61 g/cm3 .

2.1.5

Crushed Ceramic Aggregates

Ceramic is non-recyclable. Ceramic wastes are products which have good mechanical properties. The process of manufacturing will create a lot of wastes. The causes for such generation of wastes are breakage or improper manufacturing. Ceramic materials contribute 54% of waste within the construction and demolition wastes. The ceramic is crushed and sieved through an 800-micron sieve. The density of ceramic was found to be 2.4 g/cm3 .

2.1.6

Used Engine Oil

The used engine oil is used as a coupling agent on the experimental basis. The waste engine oil poses a serious threat to the environment as it has the potential to convert the cultivable soil into uncultivable soil.

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2.2 Methodology 2.2.1

Process of Development

The molds of size 7 cm × 7 cm × 7 cm were prepared, and the molds were placed one over the other so that the resultant size of the mold will be 7 cm × 7 cm × 14 cm. The silicone spray is sprayed over the inner surface of the mold for the easy removal of the block. The composite sample consisting of different material with different compositions was prepared by hand mix, and the mix was placed in the mold in the layer and it was hand compacted. The mold is placed in the hot air oven for 3 h of time at 170 °C. The distance from the mold to the coils will be around 15 cm, and the walls of the mold are 3 cm thick. So the effective temperature inside the mold will be 105 °C. The mold was taken out, and it was subjected to mechanical compaction of about 35 MPa for about 5 min. The block was removed out of the mold and was cooled to room temperature by exposing it to outer environment for about 24 h. The resultant block has a size of about 3 cm, and for the tests purpose, the cubes of around 3 cm were cut out from the block.

3 Results and Discussion 3.1 Density The densities of BA, CA, LDPE, PET, and CS were found to be 0.7 g/cm3 , 2.4 g/cm3 , 0.93 g/cm3 , 1.32 g/cm3 , and 3.61 g/cm3 , respectively, where BA was found to be having the lowest density and CS with the highest density. The lowest density was observed in LDPE:BA (2:1) with oil of about 0.85 g/cm3 (Table 3), and the highest density was observed in LDPE:CS (2:1) with oil of about 1.54 g/cm3 (Table 4). With the addition of 10% of the coupling agent, it was evident that there was a decrease in densities in all the composite mixes.

3.2 Compression Test In India, IS: 1077 standard recommends a minimum value of 3.5 MPa for compressive strength for the brick. According to European code minimum, compressive strength for clay brick is 5 MPa. The ASTM advises a minimum of 10.7 MPa for brick for light weather area and 20.7 MPa for hard weather. Figure 1 illustrates the variation of compressive strength with respect to different ratios of the different composites which is mentioned in the Tables 1, 2, 3, 4, 5, 6, and 7.

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Fig. 1 Variation of compressive strength of blocks with respect to varying mix ratios Table 1 LDPE with bottom ash including carbon Sl No.

LDPE: BA

Avg density (g/cm3 )

Avg compressive strength (MPa)

Water absorption (%)

1

2:1

0.901

11.93

5.4

2

4:1

0.91

9.81

3.2

3

3:1

0.906

16.54

4.2

Table 2 LDPE with bottom ash Sl No.

LDPE: BA

Avg density (g/cm3 )

Avg compressive strength (MPa)

Water absorption (%)

1

2:1

0.907

23.27

4.9

2

4:1

0.921

17.56

2.9

3

3:1

0.909

31.41

3.2

Table 3 LDPE with bottom ash and oil Sl No.

LDPE: BA

Machine oil (%)

Avg density (g/cm3 )

Avg compressive strength (MPa)

Water absorption (%)

1

2:1

10

0.85

23.77

1.9

2

4:1

10

0.88

19.13

1.8

3

3:1

10

0.86

32.46

1.5

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Table 4 LDPE with ceramic Sl No.

LDPE: CA

Avg density (g/cm3 )

Avg compressive strength (MPa)

Water absorption (%)

1

2:1

1.29

15.48

7.8

2

4:1

1.21

16.7

5.1

3

3:1

1.24

20.97

5.9

Table 5 LDPE with ceramic and oil Sl No.

LDPE: CA

Machine oil (%)

Avg density (g/cm3 )

Avg compressive strength

Water absorption (%)

1

2:1

10

1.26

15.9

6.9

2

4:1

10

1.14

18.3

4.3

3

3:1

10

1.19

22.12

4.9

Table 6 LDPE with copper slag Sl No.

LDPE: CS

Avg density (g/cm3 )

Avg compressive strength (MPa)

Water absorption (%)

1

2:1

1.54

19.85

5.1

2

4:1

1.38

18.62

4.2

3

3:1

1.49

18.97

4.5

Table 7 LDPE with copper slag and oil Sl No.

LDPE: CS

Machine oil (%)

Avg density (g/cm3 )

Avg compressive strength (MPa)

Water absorption (%)

1

2:1

10

1.49

21.43

2.3

2

4:1

10

1.31

19.24

1.7

3

3:1

10

1.42

20.15

1.9

3.2.1

Low-Density Polyethylene with Bottom Ash

From Table 2, it can be inferred that (3:1) mix ratio yields the highest strength in this composite with a strength of about 16 MPa, which satisfies all the standards’ requirements except the ASTM norm in hard weather condition, and a lower compressive strength was observed for mixes with higher filler material content. This behavior can be explained due to the lack of adhesion between plastics and filler materials. By the addition of coupling agent, the strength was found to hike since the hydrophobic property of the plastic and the hydrophilic property of the aggregates tend to reduce due to the formation of an interfacial layer between plastics and fillers, thus obtaining the highest strength in the entire study.

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Table 8 LDPE with PET and bottom ash Sl No.

LDPE: PET: BA

Avg density (g/cm3 )

Avg compressive strength (MPa)

Water absorption

1

4:2:1

1.45

18.25

6.1

3.2.2

Low-Density Polyethylene with Ceramic Aggregates

From Table 5, it can be inferred that (3:1) mix ratio with the addition of 10% oil yields the highest compressive strength of about 22 MPa, and every mix with ceramic aggregates had potentially crossed 15 MPa and that every mix ratios had satisfied all the standard requirements except ASTM norm in hard weather condition.

3.2.3

Low-Density Polyethylene with Copper Slag

Table 6 highlights that (2:1) mix ratio with the addition of coupling agent yields the highest compressive strength of about 21.4 MPa, and every mix was found to satisfy the standard requirements. In this composite, the strength tends to rise proportionally to the weight of the filler material up to a limit.

3.2.4

Low-Density Polyethylene with PET and BA

The melting point of PET was high though we tried with 170 °C. The resultant block had the PET particle without being melted. The strength of that block was found to be 18.25 MPa with water absorption of 6.1 (Table 8).

3.3 Water Absorption Test The test was carried in accordance with the Indian Standard Code 3495 part 2. For all the composites, with the rise in plastic content, the water resistance was found to be increasing as the plastic owns good water resistive properties, Furthermore, the addition of the coupling agent decreases widely the water absorption due to the elimination of pores and by making the composite more finer and glossy in finish. LDPE with BA (3:1) from Table 3 tends to give the highest water resistive property, with water absorption of about 1.5%.

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4 Conclusions This study presented a potential solution to turn plastic waste into construction blocks with lower cost and rapid construction phases. It examined the effectiveness of using LDPE (Low-Density Polyethylene), which is a major source of waste and least recycled plastic, along with waste materials like bottom ash, copper slag, and ceramic in different proportions to create construction blocks by comparing the mechanical properties of different mix proportions of raw materials, and an optimum composition was arrived. The LDPE plastic and the PET plastic could be mixed in its semi-molten state. The suitable temperature for the mixing process will be around 250 °C. The best block is 3:1 of plastic and ceramic. The main problem associated with the plastic bricks is its fire resistance. The future research can be carried out with the incorporation of the fire retardant materials like compounds of bromides.

References 1. Census of India (2011) Provisional population totals. Government of India, New Delhi 2. Wahid et al (2015) Utilization of plastic bottle waste in sand bricks. J Basic Appl Scient Res 2090–4304. ISSN 3. Koranteng J (2016) Developing composites from waste plastic and sawdust, Report 4. Rahman KS et al (2013) Flat-pressed wood plastic composites from sawdust and recycled polyethylene terephthalate (PET): physical and mechanical properties. SpringerPlus 2(1):629 5. Arrakhiz FZ et al (2012) Mechanical properties of high-density polyethylene reinforced with chemically modified coir fibers: impact of chemical treatments. Mater Des 37:379–383 6. Chen RS et al (2015) Biocomposites based on rice husk flour and recycled polymer blend: Effects of interfacial modification and high fiber loading. BioResources 10(4):6872–6885 7. Hamid MRY, Sahrim AH (2011) Effect of flame retardants on wood plastic composites-HDPE based. In: Key engineering materials, vol. 471. Trans Tech Publications 8. Félix JS, Domeño C, Nerín C (2013) Characterization of wood plastic composites made from landfill-derived plastic and sawdust: volatile compounds and olfactometric analysis. Waste Manag 33(3):645–655 9. Mohan HT et al (2017) Transforming urban waste into construction blocks for a sanitation infrastructure: a step towards addressing rural open defecation. In: Global humanitarian technology conference (GHTC), 2017 IEEE. IEEE 10. Seniunaite J, Vasarevicius S (2016) Leaching of copper, lead and zinc from municipal solid waste incineration bottom ash. In: International scientific 36 conferences “environmental and climatic technologies”, October 2016 11. Kochert S et al (2009) Transforming bottom ash into fly ash in the coal fired power stations. In: World of Coal Ash conference, May 2009

Study on Mechanical Properties of M30 Grade Concrete with Replacement of Cement by Wollastonite D. Saranyadevi, P. Sabareeswaran, P. Paramaguru, and M. Surya Prakash

Abstract This paper reports effect of concrete using replacement such as wollastonite powder for cement. In the project work, the concrete grade of M30 was selected, and IS method was used for mix design. The properties of material for cement, wollastonite powder and coarse aggregate were studied for mix design. The various strengths of concrete like compressive strength and split tensile strength were studied for replacements of cement using wollastonite powder. The mix proportion has been taken as 1:1.65:2.92. Keywords Replacement of cement · Wollastonite powder · Properties of materials · Compressive strength · Split tensile strength

1 Introduction Concrete is a composite material composed of water and coarse granular material (the fine and coarse aggregate) embedded in a hard matrix of material (the cement or binder) that fills the space among the aggregate particles and glues them together. Concrete is widely used for making architectural structures, foundations, brick or block walls, pavements, bridges or overpasses, highways, runways, parking structures, dams, pools/reservoirs, etc. Nowadays, production of cement becomes environmental hazards since it releases large amount of carbon dioxide. To overcome this problem, it is very essential to D. Saranyadevi (B) · P. Sabareeswaran · P. Paramaguru · M. Surya Prakash Department of Civil Engineering, SNS College of Engineering, Coimbatore-35, Tamil Nadu, India e-mail: [email protected] P. Sabareeswaran e-mail: [email protected] P. Paramaguru e-mail: [email protected] M. Surya Prakash e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_6

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research the alternative methods. In order to fulfil the requirement of the cement, certain alternative materials must be found. Wollastonite powder is used in the concrete as alternative material. It is the product obtained from grinding the wollastonite rock. When it is introduced in concrete as a replacement material, it reduces the environmental pollution, space problem and also reduces the cost of concrete. The replacement of cement by using wollastonite powder leads to consumption of generated wollastonite powder and solve the environmental pollution problem. The chemical analysis, specific gravity, sieve analysis and compressive strength are identified for various percentages of wollastonite powder.

2 Materials Used 2.1 Cement The ordinary Portland cement of grade 43 is used in this study.

2.2 Wollastonite Powder Wollastonite Powder is basically powder grinded from wollastonite rock. Wollastonite powder generally consists of crushed wollastonite stone with most particles passed through a 90 µm sieve. As with course aggregate, this can be primary, secondary or recycled sources. Wollastonite is a naturally occurring mineral named in honour of English mineralogist and chemist Sir W. H. Wollaston (1766–1828). Wollastonite is a calcium metasilicate (CaSiO3 ) mineral [1] with particles similar to cement particles by size. The main constitutions are calcium oxide and silicon dioxide. Additional to this, it also contains iron, magnesium, manganese, aluminium, potassium and sodium (Table 1). Table 1 Chemical composition of wollastonite

Material

Composition %

CaO

45–48

SiO2

47–52

Al2 O3

3–5

Fe2 O3

1–3

MgO

3–4

Na2 O

0.08

K2 O

0.51

Study on Mechanical Properties of M30 Grade Concrete … Table 2 Physical properties of fine aggregate

Properties

65 Value

Type

Natural

Specific gravity

2.62

Fineness modulus

3.17

Zone

II

2.3 Fine Aggregate Fine aggregate was purchased which satisfied the properties of fine aggregate required for experimental work, and the sand conforms to the zone II as per the specifications of IS 383:1970 (Table 2).

2.4 Course Aggregate Course aggregates are particles greater than 4.75 mm sieve, but generally range between 9.5 and 37.5 mm in diameter [2]. They can either be from primary, secondary or recycled sources. Primary or Virgin aggregates are either Land or Marine-Won. Gravels constitute the majority of course aggregate used in concrete with crushed stone making up most of the remainder (Table 3).

3 Mixing of Materials The mix design for concrete is in the proportion of 1:1.65:2.92 for all the specimens which are to be casted and tested [3]. Table 3 Physical properties of coarse aggregate

Properties

Value

Type

Crushed

Specific gravity

2.73

Fineness modulus

2.81

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4 Material Properties 4.1 Sieve Analysis Test 4.1.1

Cement

Sieve analysis is done for cement as per IS 4031 (part I)-1996. The first step involves breaking any air-set lumps in the cement sample with finger. 100 g of cement is taken and sieved through 90-micron sieve. The percentage of weight retained is less than 10%.

4.1.2

Wollastonite

Wollastonite powder is taken and placed on top of the 90-micron sieve. Sieving is done manually for 15 min, and weight retained on sieve is found. It is noted that the percentage retained on sieve is less than 10%.

4.2 Compressive Strength Test The standard mould size of 150 mm × 150 mm is used for casting. Curing is done for 7, 14 and 28 days [4]. For concrete cubes and the compression strength test is done in compressive testing machine as per IS 516:1959 for the standard concrete and for the partial replaced samples [5].

4.3 Split Tensile Test Tensile strength is one of the basic and important properties of concrete. So, it is necessary to find the strength of the concrete at which the concrete members may crack. The standard mould size of 150 mm × 300 mm is used for casting. The specimens casted for various percentage replacement of wollastonite powder were cured and tested. Curing is done for 7, 14 and 28 days. Split tensile test is done as per IS 5816:1999 for the control concrete and for the partial replaced samples.

Study on Mechanical Properties of M30 Grade Concrete …

5 Results and Discussion 5.1 Compressive Strength of Concrete

Compressive Strength N/mm2

See Figs. 1, 2 and 3. 50 40 30 20 10 0 7 days

28 days

% Replacement of 5% of Wollastonite powder Conventional Concrete

5 % Wollastonite

Fig. 1 Replacement of 5% of wollastonite powder

Compressive Strength N/mm2

45 40 35 30 25 20 15 10 5 0 7 days

28 dyas

% Replacement of 10% of Wollastonite powder Conventional Concrete Fig. 2 Replacement of 10% of wollastonite powder

10% Wollastonite

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Compressive Strength N/mm2

45 40 35 30 25 20 15 10 5 0 7 days

28 dyas

% Replacement of 15% of Wollastonite powder Conventional Concrete

15% Wollastonite

Fig. 3 Replacement of 15% of wollastonite powder

5.2 Split Tensile Strength of Concrete See Figs. 4, 5 and 6.

Split tensile Strength N/mm2

4 3.5 3 2.5 2 1.5 1 0.5 0 7 days

28 dyas

% Replacement of 5% of Wollastonite powder Conventional Concrete Fig. 4 Replacement of 5% of wollastonite powder

5% Wollastonite

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Split tensile Strength N/mm2

4 3.5 3 2.5 2 1.5 1 0.5 0 7 days

28 dyas

% Replacement of 10% of Wollastonite powder Conventional Concrete

10% Wollastonite

Fig. 5 Replacement of 10% of wollastonite powder

Split tensile Strength N/mm2

4 3.5 3 2.5 2 1.5 1 0.5 0 7 days 28 dyas % Replacement of 15% of Wollastonite powder Conventional Concrete

15 % Wollastonite

Fig. 6 Replacement of 15% of wollastonite powder

6 Conclusion Based on the experimental study, the following results have been found: • The optimum percentage of replacement for fine aggregate by wollastonite powder of M40 grade concrete and the target mean compressive strength of the tested specimen have been studied. • By the usage of wollastonite powder, the soil scarcity can be reduced.

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• Conventional concrete shows the compressive strength of 23.2, 27.2 and 40.6 N/mm2 at 7, 14 and 28 days, respectively. • When the wollastonite is replaced for 5%, the compressive strength increases by 4.1 and 6.87% at 7 and 28 days, respectively. • When the wollastonite is replaced for 10%, the compressive strength increases by 3.47% at 28 days. • When the wollastonite is replaced for 15%, the compressive strength does not have any changes. • Conventional concrete shows the tensile strength of 2.8 and 3.44 N/mm2 at 7 and 28 days, respectively. • When the wollastonite is replaced for 5%, the tensile strength increases by 11.7 and 4.65% at 7 and 28 days, respectively. • When the wollastonite is replaced for 10%, the tensile strength increases by 3.57 and 3.77% at 7 and 28 days, respectively. • When the wollastonite is replaced for 15%, the tensile strength decreases by 2.1 and 9.88% at 7 and 28 days, respectively. • Wollastonite concrete increases the compressive and tensile strength effectively. It is advantageous to use wollastonite in concrete.

References 1. Mishra AK, Mathur R, Goel P (2007) Marble slurry dust and wollastonite-inert mineral admixtures for cement. IRC Technical papers/20207/ Indian-Highway 2. IS: 383-1970. Specification for coarse and fine aggregate from natural sources for concrete, 2nd revision. BIS, New Delhi 3. IS: 10262-2009. Recommended guidelines for concrete mix design. Bureau of Indian Standards, New Delhi, India 4. Dahiphale S, Khan K, Tikhe K (2007) Properties of concrete containing wollastonite. Int J Eng Res Mech Civil Eng. ISSN (Online) 2456-1290 5. IS: 516-1959. Method of test for strength of concrete. BIS, New Delhi 6. Mathur R, Mishra AK, Goel P (2007) Influence of wollastonite on mechanical properties of concrete. J Sci Ind Res 66:1029–1034 7. Masthanvali K, Thrimurthi Naik D (2017) Effect of wollastonite, flyash and silica fume on strength of concrete. Int J Mag Eng Technol Manag Res 4:419–428 8. Pradhan D, Dutta D (2013) Influence of silica fume on normal concrete. Int J Eng Res Appl 3(5):79–82 9. Neville AM, Books JJ (1999) Concrete technology. International Student Edition. Addison Wesley Longman Ltd. ISBN 981-840-4 10. Shetty MS (1999) Properties of concrete theory and practice, 4th edn. S. Chand & company Ltd. ISBN 81-219-0348-3

Flexural Behaviour of Auxetic Core Sandwich Beam Ruby Vaguez and Simon Jayasingh

Abstract Auxetic is a material or a structure which has gained popularity due to its enhanced properties; they are widely used in the field of biomedical, aerospace, automotive, military and textile industry. They exhibit negative Poisson’s ratio, that is, unlike unconventional materials, they become wider when uniaxially stretched and thinner when uniaxially compressed. They exhibit enhancement in physical properties like vibration absorption, shear resistance, indentation resistance, fracture resistance and lower fatigue crack propagation. In this paper, a 3D unit cell was numerically modelled to evaluate the auxetic behaviour, and parametric analysis was done to evaluate the performance of different designs of unit cell, and it was compared with the equivalent monolithic one. Various design parameters considered were the height of the vertical connecting strut and the centre and radius of the curved strut of the core. It was found that a curved strut core shows auxetic behaviour, and as the distance of the centre of the curved strut increases, the deflection of the unit cell increased. This 3D unit cell was then numerically modelled to sandwich beam with auxetic core subjected to three-point bending. The behaviour of the structure was studied numerically using Abaqus/CAE 6.14. Keywords Auxetic · Curved strut · Unit cell · Composite sandwich beam · Negative Poisson’s ratio

1 Introduction Sandwich composite structures are widely used in naval, automotive applications, aerospace and sporting due to their high-energy absorption capacity, strength to R. Vaguez (B) Structural Engineering, Vellore Institute of Technology, Vellore, India e-mail: [email protected] S. Jayasingh Department of Structural and Chemical Engineering, Vellore Institute of Technology, Vellore, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_7

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weight ratio and stiffness to weight ratio [1, 2]. A sandwich structure commonly consists of two thin high-strength face sheets and a low-density core. The advantage of this structure is that it utilizes the strength and stiffness of the face sheet and the shear, bending and buckling resistance and energy absorption of the core [3–5]. The bending behaviour of sandwich composite structures depends upon the geometry of face sheets, the material used and the topology of the core [1]. A wide range of novel materials have been used as cores in sandwich structures such as open cell and closed cell foam, honeycomb cellular foam, corrugated foam and lattice foam. Lately, auxetics have been gaining importance owing to their enhancement in physical properties like fracture resistance, shear resistance, vibration absorption, indentation resistance and lower fatigue crack propagation [5–7]. Auxetics are materials and structures with negative Poisson’s ratio, they exhibit an unusual behaviour that is under uniaxial tension, these materials and structures expand transversely, and under uniaxial compression, they contract transversely. They unlike unconventional materials become wider when uniaxially stretched and thinner when uniaxially compressed. Auxetics can be a single molecule, a crystal or a macroscopic structure. Some natural auxetic materials are α-Cristobalite (SiO2 ), Pyrolytic Graphites, single crystal such as Pyrite (FeS2 ) and some types of zeolites such as Siliceous Zeolite MFI-Silicalites [8]. In this paper, a 3D unit cell was numerically developed and subjected to uniaxial compression to investigate the Poisson’s ratio. This 3D unit cell was then numerically modelled to a sandwich structure with auxetic core subjected to three-point bending. The behaviour of the structure was studied numerically using Abaqus/CAE 6.14. The numerical approach using ABAQUS was validated based on experiment conducted by Tiantian Li and Lifeng Wang on ‘Bending behaviour of sandwich composite structures with tunable 3D-printed core materials’. In this work, mechanical testing such as the compression test and three-point bending test were performed on sandwich structures containing 3D-printed core materials with truss, conventional honeycomb and re-entrant honeycomb core to study the bending behaviour [1]. The numerical simulation was done using finite element analysis software Abaqus, and plane stress condition was assumed during simulation. The load v/s displacement graphs were plotted to compare the strength of each material [1]. The experimental approach conducted by Tiantian Li and Lifeng Wang on ‘Bending behaviour of sandwich composite structures with tunable 3D-printed core materials’ was validated using Abaqus/CAE 6.14.

2 Numerical Model 2.1 Auxetic Unit Cell The auxetic core investigated in this work is a curved structure which exhibits negative Poisson’s ratio. The 3D geometry of the core provides biaxial negative Poisson’s ratio

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responses from all directions as compared to uniaxial behaviour of 2D auxetic unit. Figure 1 shows the auxetic unit cell. The configuration of the auxetic unit cell is defined by the height of the vertical connecting strut and the centre and radius of the curved strut. All the linking struts, curved struts and vertical struts have a circular cross section of radius, r = 0.2 mm, while the struts forming the top and bottom bases have square cross section with width, d = 0.4 mm [6, 9]. The base of unit cell is of width, L2 = 2Lsin(θ) and the total height of the unit cell, H = 2a + 2Lcos(θ) and the total width of the unit cell is W = 2c + L2, where c = 1 mm [6, 9]. The dimensions have been chosen with reference to the work done by Gabriele Imblazano, Phuong Tran et al. on ‘A numerical study on auxetic core sandwich panel under blast loading’. Nine models of auxetic unit cells are created by varying the length of vertical strut from no strut to 2 mm strut and by varying the distance of the centre of the curved strut from the datum plane, from 1 to 3 mm, keeping the width of the unit cell as a constant. Figure 2 shows the design parameters considered for the parametric study. The baseline model taken is that of the model with 1 mm vertical strut and 2 mm

Fig. 1 Schematic diagram of 3D curved auxetic core

Fig. 2 Design parameters

74 Table 1 Material properties and Johnson–Cook parameters of annealed steel SS304

R. Vaguez and S. Jayasingh S. No.

Property (kg/m3 )

Input data

1.

q

2.

E (GPa)

7900

3.

m

0.3

4.

TM (K)

1673

5.

Tr (K)

293

6.

A (MPa)

310

7.

B (MPa)

1000

8.

n

0.65

9.

C

0.07

10.

e0 (s–1)

1.00

11.

m

1.00

200

distance of the centre of the curved strut from the datum plane. A static load is applied on the baseline model and displacements, strains and Poisson’s ratio are calculated numerically [10]. Geometric non-linearity is considered due to large deformations.

2.2 Material Property In the research by Gabriele Imblazano, Phuong Tran et al., the rate-dependent property of annealed steel SS304 is used [10]. Annealed steel SS304 has a reduced higher ductility and yield strength due to the annealing manufacturing process. It is utilized for both the auxetic and monolithic modelling (Table 1).

2.3 Poisson’s Ratio of Auxetic Unit Cell Poisson’s ratio is defined as the ratio of transverse engineering strain to the axial engineering strain. The auxetic unit cell is modelled in Abaqus/CAE with a uniform static loading applied at the top base, while the bottom base is being simply supported in the vertical direction. The strain, displacement and effective Poisson’s ratio are then numerically calculated. It was noticed that more the length of the vertical strut, the lower the absolute value of negative Poisson’s ratio, and more the distance of the curve centre from the datum place, more the absolute value of negative Poisson’s ratio. The value of negative Poisson’s ratio of the baseline model is found to be −1.17.

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Fig. 3 Baseline model of unit cell

2.4 Uniform Static Loading Uniform static load is applied on the nine unit cells. The top facet of the unit cells is subjected to uniform static loading, while the bottom facet is being simply supported in the vertical direction. In Abaqus/CAE, the load type is assigned as concentrated force, on each node along the width with a magnitude of 15 N, and the failure load and deflection are noted. Figure 3 shows the load applied on the model.

2.5 Auxetic Core Sandwich Beam Three models of auxetic core sandwich beam are created. The beam is created for core with no strut and curve 1 mm, core with 1 mm vertical strut and curve 1 mm and core with 2 mm vertical strut and curve 1 mm. The Auxetic core sandwich beam is modelled to have a core, of two layers of unit cell, along the width and depth, and maintaining a length of 110 mm, sandwiched between the two metallic facets. Figure 4 shows the baseline model of beam. The material property input is same as that for the unit cell. The top and bottom facets are modelled as shell elements with a thickness of 2 mm. They are meshed using quadrilateral shape mesh, and element type chosen is that of S4R type. The auxetic core is modelled with mesh element type B31. Figure 5 shows the meshed model of the auxetic unit cell. The equivalent monolithic model of same areal volume and

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Fig. 4 Baseline model of auxetic core sandwich beam

Fig. 5 Meshed auxetic unit cell

material property is created for three-point bending. For the baseline case, the monolithic beam is 4.47 mm thick. The baseline model is also meshed using S4R element type. The performances of these models under three-point bending are studied, and load versus displacement graph was obtained.

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2.6 Three-Point Bending The auxetic core sandwich beam is subjected to three-point bending, with a span length of 60 mm. The load was applied as concentrated force on the top facets, and simply supported boundary condition was applied at the bottom facets. Figure 6 shows the beam subjected to three-point loading (Fig. 7).

3 Result and Discussion The baseline model of the auxetic unit cell is first analysed in this work. The auxetic unit cell is made of a top facet, a sandwiched core and a bottom facet with 1 mm vertical strut, 1 mm curve and 9.327 mm base. Figure 8 shows the deformed baseline model. The unit cell is subjected to a uniform static load, and the failure load and deflection graph is noted. Uniform static load is applied to the other models, and the load versus deflection graphs are plotted.

Fig. 6 Three-point bending

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Fig. 7 Bending characteristics of curve 1, 2 and 3 mm unit cell

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Fig. 8 Deformed model of baseline unit cell

3.1 Effect of Length of Vertical Strut Figure 7 depicts the effect of change in length of vertical strut on the load-carrying capacity of curve 1 mm, curve 2 mm and curve 3 mm auxetic unit cell, respectively. It is observed that as the length of the vertical strut increases the load-carrying capacity decreases and deflection increases.

3.2 Effect of Curve Radius Figure 9 depicts the effect of the distance of the curve centre from the datum plane for no strut, strut 1 mm and strut 2 mm auxetic unit cells, respectively. It is seen that as the distance from the datum plane increases the load-carrying capacity decreases and the deflection also increases.

3.3 Auxetic Core Sandwich Beam Figure 10 shows the deformed model for the baseline model of auxetic core sandwich beam. It is seen that the auxetic beam gives the same behaviour as in the unit cell. That is, as the length of the strut increases, the load-carrying capacity decreases and the deflection increases, and as the distance of the curve centre increases, the deflection increases and load-carrying capacity decreases. Figure 11 shows the bending behaviour of the auxetic core sandwich beam.

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Fig. 9 Bending characteristics of no strut. Strut 1 mm and strut 2 mm unit cell

Baseline Beam Model

Monolithic Beam Model

Fig. 10 Deformed model of auxetic core sandwich beam and monolithic beam

4 Conclusion Numerical investigations of the bending behaviour of auxetic unit cell, auxetic core sandwich beam and equivalent monolithic steel plates were conducted. The composite auxetic core sandwich beam was modelled by assembling multiple layers of similar auxetic unit cells and the two top and bottom facets. The Poisson’s ratio and auxetic behaviour of the auxetic core unit cell and the auxetic core sandwich beam were controlled by changing the length of the vertical strut and the distance of the curve centre from the datum plane. The auxetic core was meshed with beam

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Fig. 11 Bending characteristics of auxetic core sandwich beam of curve 1 mm and equivalent monolithic beam

elements to reduce computational time. The baseline and parametric analyses were conducted using annealed steel SS304 for both auxetic core and the facets. Uniform static loading was applied on the auxetic unit cell and three-point bending test was done on the auxetic core sandwich beam. It was found that as the length of the strut increases the load-carrying capacity decreases and the deflection increases, hence concluding that the curved struts are the main load-carrying members. The curved struts were seen to undergo compression both longitudinally and transversely, thus proving the auxetic behaviour. On increasing the distance of the curved strut from the datum plane, it was seen that the load-carrying capacity decreases and the deflection increases; this was due to the intersecting of the curved strut as the curve radius increases. The intersecting of the struts was seen to reduce the load-carrying capacity of the entire structure. No strut and curve 1 mm auxetic unit cell was found to take 212 and 498% more load than the strut 1 mm and strut 2 mm auxetic unit cell. It was also seen that no strut and curve 1 mm beam was found to take 63.75% more load than the equivalent monolithic beam of same volume and material property.

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References 1. Li T, Wang L (2017) Bending behaviour of sandwich composite structures with tunable 3Dprinted core materials. J. Compos Struct 2. Imbalzano G, Linforth S et al (2018) Blast resistance of auxetic and honeycomb sandwich panel: comparison and parametric designs. J Compos Struct 3. Zenkert D, Nordisk I (1997) The handbook of sandwich construction. Engineering Materials Advisory Services Ltd., Cradley heath, West Midlands 4. Gibson LJ, Ashby MF (1999) Cellular solids: structure and properties. Cambridge University Press 5. Allen HG (2015) Analysis and design of structural sandwich panels: the commonwealth and international library: structures and solid body mechanics division. Elsevier 6. Imbalzano G, Tran P et al (2015) Three-dimensional modelling of auxetic sandwich panels for localised impact resistance. J Sandw Struct Mater 7. Hu LL, Zhou MZh, Deng H (2019) Dynamic indentation of auxetic and non-auxetic honeycomb cores under large deformation. J Compos Struct 8. Jin X, Wang Z et al (2016) Dynamic response of sandwich structures with graded auxetic honeycomb cores under blast loading. J. Compos Part B Eng 9. Imbalzano G, Tran P et al (2016) A numerical study of auxetic composite panel under blast loading. J Compos Struct 10. Choi JB, Lakes RS (1995) Analysis of elastic modulus of conventional foams and of re-entrant foam materials with a negative Poisson’s ratio. Int J Mech Sci

Correlation Between Surface Absorption and Chloride Ion Penetration of Concrete with Nano Silica R. Vandhiyan, E. B. Perumal Pillai, and S. Lingeswari

Abstract Durability of concrete is greatly affected by water absorption and its transportation. A less permeable concrete is more durable. Nano Silica (NS) when added to concrete can perform as a filler material and also participate in pozzolanic reaction to improve the density of concrete. In this investigation, concrete samples were made by adding NS to concrete. The compressive strength increased with increase in NS content up to 1.5%. Ultrasonic pulse velocity test showed improvement in concrete’s density with increase in NS content. Sorptivity test demonstrated the reduction of surface absorption with increase in NS. Reduced chloride ion penetration was also prominent during Rapid Chloride Penetration Test (RCPT). Relation between water absorption and current passed was found, and using this relation, prediction chart and formula were proposed. Keywords Nano silica · RCPT · Sorptivity · UPV · Surface absorption

1 Introduction Durable reinforced concrete is the need of the hour. Concrete being a porous material is susceptible to damage by infiltration of harmful substances through its external surface and their advancement through the pore system leading to various durability problems. The passage of water in the pore structure of concrete has an important role in the deterioration of concrete structure. This pore water carries various corrosive ions and directly participates in some physical and chemical deterioration processes [1]. R. Vandhiyan (B) Department of Civil Engineering, PSNA College of Engineering & Technology, Dindigul, India e-mail: [email protected] E. B. Perumal Pillai Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India S. Lingeswari Department of Civil Engineering, SSM Institute of Engineering & Technology, Dindigul, India © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_8

83

84 Table 1 Composition of nano silica

R. Vandhiyan et al. Chemical composition

Percentage (%)

SiO2

99.88

Al2 O3

0.007

TiO2

0.006

Fe2 O3

0.001

Carbon

0.03

Addition of Nano Silica (NS) to concrete improves its density and also contributes to the strength development of cement matrix [2]. The concrete with NS performs better because of its filler effect and pozzolanic reaction. The larger surface area provided by NS speeds up the rate of hydration and pozzolanic reactions. The strength and durability of concrete with NS improve due to the increased presence of Calcium Silicate Hydrate (C–S–H) formed when NS reacts with free calcium hydroxide (Ca(OH)2 ) [3]. Many studies have proved that NS improves the hydration process, compressive strength, tensile strength, and abrasive resistance, and decreases the permeability of concrete [, 4–6]. In this work, compressive strength of concrete with NS and without NS was compared with its corresponding Ultrasonic Pulse Velocity (UPV) values to show the improvement in density of the concrete with NS. Further, improvement in density and pore structure was found by conducting sorptivity test. Then, Rapid Chloride Penetration Test (RCPT) was also performed on the concrete samples to find the permeability.

2 Materials and Methods 2.1 Materials The specific surface area of NS used was 201 m2 /g, and chemical composition was 99.9% SiO2 (Table 1) in powder form. The Ordinary Portland Cement (OPC) was used as obtained from the market. River sand conforming to Zone I as per IS: 383-1970 [7] was used as fine aggregate. Broken stones of 20 mm conforming to IS: 383-1970 [7] were used as coarse aggregate. Superplasticizer with chemical base melamine formaldehyde and specific gravity 1.20 kg/l manufactured by chemical company Sika was used.

2.2 Mixing of Ingredients The NS was added in proportions of 0.5, 1, 1.5, and 2% by weight of cement in the concrete mix, and the samples were designated C1, C2, C3, and C4, respectively, and

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Table 2 Ingredients for 1 m3 of concrete Mix designation

C0

C1

C2

C3

C4

Cement (kg)

394.3

394.3

394.3

394.3

394.3

Fine aggregate (kg)

638.3

638.3

638.3

638.3

638.3

Coarse aggregate (kg)

1191

1191

1191

1191

1191

Nano silica (kg)

0

1.97

3.94

5.91

7.89

Superplasticizer (kg)

0

1.77

1.97

2.37

2.96

Water (l)

197

197

197

197

197

the base mix with 0% NS was designated C0 (Table 2). All the specimens were water cured. The mixing technique plays an important role while fine materials like NS are used. The adding of NS to mix leads to decrease in workability due to interaction between the NS and the wet cementitious mix [8]. If the superplasticizer interacts with NS first, reactivity gets reduced; to avoid this, water and other ingredients were mixed thoroughly first to ensure proper dispersion of NS. Superplasticizer was added later and mixed to have uniform dispersion [9].

2.3 Ultrasonic Pulse Velocity Test The UPV values were taken from cubes of size 150 mm × 150 mm × 150 mm before they were subjected to compression test. Application of petroleum gel on the faces of concrete and transducers ensured the acoustical coupling between them. This acoustical coupling helps the ultrasonic pulses to pass into the concrete and then get detected by the receiving transducer.

2.4 Sorptivity Tests Sorptivity test shows the concrete’s capacity to absorb and transmit water through it by capillary suction. The test was conducted as per ASTM C 1585 [10]. The cylindrical concrete specimens used were of diameter 100 mm and thickness 50 mm. The sides of the specimen were sealed with wax. The end of the specimen that should not be exposed to water was sealed using plastic sheet, and secured in place by an elastic band. The specimen was placed inside a pan with only 2 mm of the exposed surface immersed into the water. The weight of the specimen was measured 18 times up to eight days. The weight was measured at 60 s, 5, 10, 20, 30, 60 min, then every hour up to 6 h, and then once a day up to 8th day.

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2.5 Rapid Chloride Penetration Test This test was conducted in accordance with ASTM C1202 [11]. Specimen samples were cut from concrete cubes of size 150 mm × 150 mm × 150 mm, diameter of the RCPT cylindrical specimens being 100 mm, and thickness 50 mm. The sides of the specimen were sealed with wax.

3 Experimental Results and Discussion 3.1 UPV and Compressive Strength Ultrasonic pulse transmission velocity (V ) was determined at km/s by using the Equation 1 V =

L T

(1)

where L is transmission distance in kilometers and T is transmission time inside the concrete in seconds. The pulse velocity increases with increase in the age of the concrete irrespective of its composition (Fig. 1). As the age of the concrete increases, the hydration of cement also increases. Due to this, the capillary pores/voids were reduced, and so the resistance against conduction of pulse declines [12]. The samples

Fig. 1 UPV at various days of curing

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87

Fig. 2 Comparison of compressive strength

with NS have a faster pulse velocity than the sample without NS on the 7th day. Similarly, the compressive strength (Fig. 2) of samples with NS was higher on the 7th day. The compressive strengths of C3 (29.48 N/mm2 ) and C4 (29.63 N/mm2 ) samples had a very little difference of 0.5%, but the pulse velocity of C3 (3.42 km/s) and C4 (3.7 km/s) had a greater difference of 7.99%. This must be due to the presence of excess NS particles that supports the easy transmission of pulse through the concrete. The increase in compressive strength of samples containing NS must be attributed by the large quantity of tricalcium silicate (C3 S) formed during the pozzolanic reaction [13]. The free Ca(OH)2 reacts with this abundant C3 S to form C–S–H. Due to this reaction, the density and strength of the matrix improves. The presence of NS accelerates the hydration by providing more nucleation sites [14]. The pulse velocity and strength increased for all samples on the 14th day, and the concrete properties were better as the NS content increased. On the 28th day the compressive strength of sample with 2% NS (C4) was 4.41% less than the sample with 1.5% NS (C3). Also, the C3 sample had 1.47% more compressive strength than C4 sample on the 60th day. The reduction in compressive strength of C4 compared to C3 must be due to the presence of excess NS particles than the quantity required to react with Ca(OH)2 . The excess NS occupies space in the matrix without contributing to the strength [15]. But the pulse velocity was higher in C4 samples on both 14th and 60th days because the transfer of waves was supported by excess NS particles filling the nano-sized pores. Earlier studies have shown that UPV is affected by the water cement ratio, quantity of aggregates, curing temperature, and compressive strength [16, 17]. Addition of

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Fig. 3 UPV versus compressive strength

NS improves the strength of concrete and fills the voids which increases the UPV. Figure 3 clearly shows that UPV increases with increase in compressive strength. Also, it is noted that the UPV has a higher value for the same compressive strength when the concrete has a higher NS content. On 28th day, the samples C3 and C4 were in excellent class (as per IS 13311-1 [18]), and other samples were categorized as good. On 60th day, C0 and C1 were in good category, and the rest of the samples were in excellent category.

3.2 Sorptivity The amount of water absorbed increases with increase in time as expected. But the absorption was very rapid during the first 6 h after which it became slow. This can be noted from the Fig. 4, and also it shows that the water absorption decreases with increase in NS content. It is very evident that the specimen with no NS had a higher rate of absorption than the specimens with NS. Figure 5 shows that the initial rate of absorption decreases with the increase in the NS content. This shows that the presence of NS increases the density of the concrete and improves pore structure. It was observed that the secondary rate of absorption was far less than the initial rate of absorption for all the specimens. The specimen without NS has greater absorption rate compared to the specimens containing NS as seen in Fig. 6. This reinforces the fact that addition of NS reduces the porosity of concrete. The initial rates of absorption of concrete samples C1, C2, C3, and C4 were 19.87, 26.67, 32.55, and 38.04% less than that of C0 sample, respectively. The secondary rates of absorption of concrete samples C1, C2, C3, and C4 were 20.58, 20.58, 37.77, and 37.77% less

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89

Fig. 4 Water absorption with respect to time

Fig. 5 Initial rate of absorption

than that of C0 sample, respectively. The concrete with NS was absorbing less water, and water absorption is inversely proportional to the NS content in the concrete specimens. Park et al. [19] have found that permeability is influenced by the surface water absorption of concrete. This proves that the use of NS reduces the surface water absorption which in turn reduces the permeability and improves the durability of concrete.

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Fig. 6 Secondary rate of absorption

3.3 Chloride Permeability The initial current consumption by C0 was high compared to all the specimens with NS. The current readings at 30 min for C0, C1, C2, C3, and C4 specimens were 0.109 Amps, 0.092 Amps, 0.083 Amps, 0.081 Amps, and 0.075 Amps, respectively. The concrete with 0.5% NS was consuming 15.21% less current than the control specimen without NS. Similarly, initial current readings for C2, C3, and C4 were 23.50, 25.81, and 29.49% less than that of C0 specimen, respectively. Figure 7 shows that there was reduction in charge passed with increase in NS content. Also, the current reading at 30 min interval increased up to 6 h in a linear fashion for all samples, and because of this linear change, the sample with the lower initial current had the lowest charge passed. It was obvious that the concrete with higher NS had better pore structure and resistance to current flow. The chloride permeability of the concrete reduced due to the increased density of the concrete and blocking of pores by NS. The total charge passed was calculated as per ASTM C1202 [11]. The charges passed by C1, C2, C3, and C4 samples were 9.28, 14.97, 18.68, and 21.53% less than that of C0 sample, respectively. This shows that as the NS content increases the permeability of concrete decreases. Figure 8 shows the comparison of the water absorption (in sorptivity test) and current flow (in RCPT) with respect to time (6 h). The slope followed by both water absorption and current flow is similar. So the initial water absorption of the concrete directly relates to the current flow in the RCPT. This shows that the measure of water absorption can help in assessing the current consumed by the concrete sample during the RCPT.

Correlation Between Surface Absorption …

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Fig. 7 Current passed versus duration

Based on the above philosophy, a graph was plotted with water absorption in X-axis and current values in Y-axis as seen in the Fig. 9. The values for calculating water absorption at 90, 150, 210, 270, and 330 h were not recorded while conducting the experiment, so interpolation was done to obtain those values. A polynomial trend line was fitted with the plottings. Equation 2 satisfies the curve. Y = −8 × 108 X 4 + X 3 107 − 40986X 2 + 96.087X + 0.0089

(2)

4 Conclusions The experiments proved that the addition of NS has positive impact on concrete’s strength and durability. It was also ascertained that plasticizers are essential when using NS. The addition of plasticizer as the last ingredient after the thorough mixing of other components aids in better dispersion of NS and thus ensures positive results. Addition of 1.5% NS by weight of cement to the concrete gave the highest compressive strength gain of 37.85% more than the concrete without NS on 28th day. 1.5% NS concrete (C3) was 4.6% and 1.49% stronger than the 2% NS concrete (C4) on 28th and 60th day, respectively. Hence, it can be concluded that the addition of NS beyond 1.5% may lead to reduction of compressive strength of concrete. UPV test showed an increase in UPV speed with increase in NS content. The increase in UPV speed indicates the reduction in pores and increase in density of concrete due to addition of NS.

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Fig. 8 Water absorption versus current flow of a C0, b C1, c C2, d C3, e C4

Sorptivity test showed a reduction in rate of surface water absorption with increase in NS quantity in concrete. Since surface absorption is directly related to the permeability of concrete, it can be said that the permeability of concrete reduces due to the addition of NS. This supports the finding that due to addition of NS the pores in concrete reduce thus improving the pore structure. RCPT shows that chloride ion penetration was controlled by the addition of NS, and it again confirms that the presence of NS in concrete makes it less permeable to ion transportation. Current passed during RCPT can be related to the water absorption, and thus water absorption value at any given time can help predict the current flow during the same time.

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Fig. 9 Relation between surface water absorption and current flow

References 1. Ye H, Jin N, Jin X, Fu C (2017) An experimental study on relationship among water sorptivity, pore characteristics, and salt concentration in concrete. Period Polytech Civil Eng 61(3):530 2. Ehsani A, Nili M, Shaabani K (2017) Effect of nanosilica on the compressive strength development and water absorption properties of cement paste and concrete containing fly ash. KSCE J Civil Eng 21(5):1854–1865 3. Lu JX, Poon CS (2018) Improvement of early-age properties for glass-cement mortar by adding nanosilica. Cement Concr Compos 89:18–30 4. Ardalan RB, Jamshidi N, Arabameri H, Joshaghani A, Mehrinejad M, Sharafi P (2017) Enhancing the permeability and abrasion resistance of concrete using colloidal nano-SiO2 oxide and spraying nanosilicon practices. Constr Build Mater 146:128–135 5. Singh LP, Karade SR, Bhattacharyya SK, Yousuf MM, Ahalawat S (2013) Beneficial role of nanosilica in cement based materials—a review. Constr Build Mater 47:1069–1077 6. Behfarnia K, Rostami M (2017) Effects of micro and nanoparticles of SiO2 on the permeability of alkali activated slag concrete. Constr Build Mater 131:205–213 7. IS 383 (1970) Specification for coarse and fine aggregates, Bureau of Indian Standards, New Delhi 8. Rajendiran V, Stalin VK (2016) Effect of nano silica on the performance of cementitious grout for ground modification. Jpn Geotech Soc Spec Publ 2(63):2138–2143 9. Berra M, Carassiti F, Mangialardi T, Paolini AE, Sebastiani M (2012) Effects of nanosilica addition on workability and compressive strength of portland cement pastes. Constr Build Mater 35:666–675 10. ASTM C (2004) 1585-04. Standard test method for measurement of rate of absorption of water by hydraulic-cement concretes. ASTM International 11. ASTM C (2005) 1202-05. Standard test method for electrical indication of concrete’s ability to resist chloride ion penetration. ASTM International 12. Nik AS, Omran OL (2013) Estimation of compressive strength of self-compacted concrete with fibers consisting nano-SiO2 using ultrasonic pulse velocity. Constr Build Mater 44:654–662 13. Singh LP, Bhattacharyya SK, Shah SP, Mishra G, Ahalawat S, Sharma U (2015) Studies on early stage hydration of tricalcium silicate incorporating silica nanoparticles: part I. Constr Build Mater 74:278–286 14. Zhang MH, Islam J (2012) Use of nano-silica to reduce setting time and increase early strength of concretes with high volumes of fly ash or slag. Constr Build Mater 29:573–580

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15. Chithra S, Senthil Kumar SRR, Chinnaraju K (2016) The effect of colloidal nano-silica on workability, mechanical and durability properties of high performance concrete with copper slag as partial fine aggregate. Constr Build Mater 113:794–804 16. Karaiskos G, Deraemaeker A, Aggelis DG, Van Hemelrijck D (2015) Monitoring of concrete structures using the ultrasonic pulse velocity method. Smart Mater Struct 24(11):113001 17. Lin Y-C, Lin Y, Chan C-C (2016) Use of ultrasonic pulse velocity to estimate strength of concrete at various ages. Mag Concr Res 68(14):739–749 18. IS 13311-1 (1992) Non-destructive testing of concrete - Methods of Test Part 1: Ultrasonic pulse velocity, Bureau of Indian Standards, New Delhi 19. Park S-S, Kwon S-J, Jung SH, Lee S-W (2012) Modeling of water permeability in early aged concrete with cracks based on micro pore structure. Constr Build Mater 27(1):597–604

Prediction of Setting Time and Strength of Mortar Using Soft Computing Technique Kiran Devi , Babita Saini, and Paratibha Aggarwal

Abstract Soft computing techniques, i.e., linear regression, artificial neural network, genetic expression programming, etc., are being practiced for the prediction of data. In this study, artificial neural network model predicted the consistency, setting time, and compressive strength of mortar at various curing time. The eighteen distinct mix proportions of cement mortar consisting of accelerators, i.e., calcium nitrate and triethanolamine as additives and stone powder as replacement of cement were selected for the prediction of various parameters. The accelerators are used to fasten the stiffening of cementitious materials and speed up the construction work. Stone powder was used to minimize the consumption of cement and problems associated with waste to the ecosystem. The laboratory data set was used for the prediction model. The appropriate artificial neural network model constitutes mix constituents as input parameters, i.e., cement, sand, water, and additional materials. The results from ANN training in multilayer feedforward neural network were evaluated and compared with the experimental results. A graphical representation between predicted and experimental results was also drawn. Results showed that artificial neural network technique was found effective for the prediction of various parameters of cement mortar with high correlation coefficients and low values of mean absolute error and root mean squared error. Keywords Accelerators · Stone powder · Soft computing technique · Artificial neural network

K. Devi (B) · B. Saini · P. Aggarwal Civil Engineering Department, National Institute of Technology, Kurukshetra 136119, India e-mail: [email protected] B. Saini e-mail: [email protected] P. Aggarwal e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_9

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1 Introduction Concrete is a basic construction material composed of cement, aggregates, and water. Sometimes, admixtures are used to improve certain properties of cementitious materials. Among admixtures, accelerators are used to shorten the setting of cement mortar and concrete. Also, accelerating admixtures increase the rate of development of strength by accelerating heat of hydration. The use of accelerators in mortar and concrete allows early stripping of outer formworks during construction and speed up the construction work [1, 2]. On the other hand, huge amount of harmful gases are emitted during the production of Portland cement, and to reduce this, alternative materials to cement has become the need of today. Also, stone industries are causing wastes in the form of dust and slurry which have hazardous impacts on the ecosystem. To minimize the consequences of stone waste on ecosystem, it can be utilized in construction industries as partial replacement of cement [3–6]. Several techniques are being used to predict the various parameters from experimental results. Soft computing techniques have become famous among all the techniques due to their better capabilities and accuracy. Soft computing techniques consist of computational technique and algorithms to give solution for complex computational problems [7]. Artificial neural network (ANN) is a modeling tool based on non-linear statistical data which find the relation between input and output parameters [8]. ANN predictive model comprises three layers: first layer, i.e., input layer which indicates the input parameters; middle one, i.e., hidden layer, consists of neurons; and last layer, output layer, consists of output parameters or target or results. The neurons are connected with each layer in various layers. It is not mandatory that number of hidden layers should be identical to number of neurons in each hidden layer. ANN model learning consists of two stages: training in which input data values are fed in ANN input layer and results are given in the target or output layer; and testing involves one forward pass using saved weight of predictive model [9]. ANN solved many complex problems due to interconnected computing elements. ANN has many applications in various fields, i.e., aerospace, banking, industrial, medical, automotive, engineering, robotics, securities, transportation, telecommunications, defense, and credit card activity checking [10]. It has many applications in civil engineering, i.e., concrete durability, workability, concrete construction smoothness, cost analysis, and mechanical properties of concrete [11]. Intelligent prediction system, i.e., ANN model was found to be very effective for the prediction of compressive strength development of concrete [12]. The prediction of elastic modulus of normal and high strength concrete using ANN was found to be a feasible tool [13]. ANN can be used as an alternate approach to predict the compressive strength of self-compacting concrete [14]. The predictive models, i.e., linear regression (LR), ANN, and support vector regression (SVR) were used to predict the compressive strength of HPC and also proposed hierarchical classification and regression (HCR) approach to improve the performance. HCR with 4-classes SVM in first level together with single ANN had least mean absolute percentage

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error [15]. The prediction of compressive strength of high-performance concrete was done with the help of multiple regression analysis and artificial neural network model. ANN gave more accurate results with high correlation [16]. The compressive strength of mortar mixes with variant strength class was predicted using ANN technique with good precision and accuracy [17]. ANN and genetic expression programming (GEP) model predicted properties of cement mortar consisting of micro silica and gave high accurate results [18]. The compressive and flexural strength of mortar consisting of modified zeolite additives was predicted using ANN model and gave good results and correlation [19]. GEP model had potential to predict the compressive strength of mortar and also strength as input data increased the accuracy of predictive model [20]. Research significance In the present study, artificial neural network technique predicted the consistency and setting time of cement paste of various eighteen mixes consisting of calcium nitrate (CN), triethanolamine (TEA),and stone powder from Kota stone (SP). Also, prediction of compressive strength of different mortar mixes at 3, 7, and 28 days was carried out. The cement, sand, water, CN, TEA, and SP were taken as input parameters and setting time (initial (IST) and final setting time (FST)) and compressive strength as target or output. Multilayer perceptron feedforward was trained through error backpropagation algorithm in this study.

2 Methodology In the present study, data set of 18 mix proportions of cement mortar consisting of accelerators, i.e., CN, TEA, and SP were used, and detailed description was given by [2]. To predict the consistency, setting time, and compressive strength, artificial neural network technique was adopted. ANN is a computational model based on the structure and functions of biological neural networks, and complex relationship between input and output was modeled with ANN modeling tool. The WEKA 3.8.2 software was used for the prediction. Multilayer perceptron with two hidden layers of four and two neurons was constructed to train, test, and validate the experimental results. The cement, sand, water, CN, TEA, and SP were taken as input parameters, and consistency, setting time, and compressive strength of mortar at 3, 7, and 28 days in MPa was taken as output parameter. The different eighteen data sets with minimum, maximum, mean, and standard deviation of various parameters have been given in Table 1. The architecture of ANN model consist 6–2–6 where first digit indicates number of input parameters, 2 indicates the hidden nodes, and last digit indicates target output to be predicted. The example architecture of 28 days compressive strength as output parameter of predictive model has been shown in Fig. 1, and remaining targets were also similar in nature with their individual outputs. Lowest value of root mean square error (RMSE) was the criterion to stop training of ANN model. Lower values of RMSE indicated the better performance of neural

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Table 1 Statistical range of input parameters for ANN model Parameters

Min.

Max.

Mean

Std. Dev.

Cement (kg/m3 )

517.5

575

546.267

23.123

Sand

(kg/m3 )

1725

1725

1725

0

Water (kg/m3 )

322

368

348.217

13.265

CN (kg/m3 )

0

5.8

3.867

2.813

TEA

(kg/m3 )

0

0.6

0.194

0.262

SP (kg/m3 )

0

57.5

28.756

23.123

Consistency

28

32

30.278

1.153

IST (min.)

9

175

86.833

48.913

FST (min.)

30

290

187.833

81.481

3 days compressive strength (MPa)

21.62

35.8

27.979

3.729

7 days compressive strength (MPa)

27.65

40.31

33.794

3.238

28 days compressive strength (MPa)

25.92

45.48

37.316

5.149

Fig. 1 ANN predictive model

network. Regression value is used to determine the correlation between input and target in neural networks, and R-value of unity indicates strong relationships. RMSE and R-values were the standard for assessment of network performance [21].

3 Analysis of ANN Predictive Model The appropriate ANN model comprises prediction model for consistency, setting time (ST), and compressive strength (CS) of mortar consisting of accelerators and SP. In ANN model, two hidden layers with four and two neurons were constructed,

Prediction of Setting Time and Strength …

99

Predicted values

trained, and tested with the experimental data of various 18 mix proportions of mortar. The comparison of ANN predictive results was compared with laboratory results. The prediction of various parameters of cement mortar using ANN has been shown in Figs. 2, 3, 4, 5, 6, and 7, respectively. Figures 2, 3, and 4 illustrated the prediction of consistency, setting time, and comparison with the experimental results, respectively. The comparison of experimental results of strength at various ages was compared with predicted values and shown in Figs. 5, 6, and 7. The correlation coefficient, R was found near to unity for all the predictive output values. Also, RMSE and mean absolute error (MAE) were low for all parameters. The values for R, R2 , MAE, RMSE, and equation for all output values have been given in Table 2.

32.5 32 31.5 31 30.5 30 29.5 29 28.5 28 27.5 27.5

Consistency

y = 0.9936x + 0.2079 R² = 0.9987

28

28.5

29

29.5 30 30.5 Experimental values

31

31.5

32

32.5

Fig. 2 Predicted versus actual values of consistency

Fig. 3 Predicted versus actual values of IST

Initial setting time

Predicted values

200 150 100

y = 1.0032x - 1.2029 R² = 0.997

50 0

0

50

100

150

Experimental values

200

100

K. Devi et al.

Fig. 4 Predicted FST versus actual FST

350

Final setting time

Predicted values

300 250 200 150

y = 0.9911x + 2.9149 R² = 0.9998

100 50 0 0

100

200

300

400

Experimental values

Fig. 5 Predicted versus actual 3 days CS

Predicted values

40

3 Days Compressive strength

35 30

y = 0.9925x + 0.5342 R² = 0.9925

25 20 20

25

30

35

40

Experimental values

Fig. 6 Predicted versus actual 7 days CS Predicted values

45

7 Days Compressiev strength

40 35 30

y = 1.0177x + 0.1936 R² = 0.9547

25 20 20

25

30

35

40

45

Experimental values

4 Conclusions The present study signifies the possibility of neural network for the prediction of various parameters of cement mortar. The data for consistency, setting time, and compressive strength of 18 different mixes of cement mortar at various ages were collected. CN, TEA, and SP enhanced the consistency and reduced rather than diminished the setting time for all the mix proportions. The exercise of CN and SP in

Prediction of Setting Time and Strength … 50

101

28 Days Compressive strength

Predicted values

45 40 35 30

y = 1.0003x + 0.054 R² = 0.9999

25 20 20

25

30

35

40

45

50

Experimental values Fig. 7 Predicted versus actual values of 28 days compressive strength

Table 2 Results from ANN predictive model Target

R

R2

MAE

RMSE

Equation

Consistency

0.9994

0.9987

0.332

0.0429

y = 0.9936x + 0.2079 y = 1.0032x + 1.2029

Initial setting time

0.9985

0.997

1.6599

2.7949

Final setting time

0.9999

0.9998

1.516

1.88

y = 0.9911x + 2.9149

3 days compressive strength

0.9963

0.9925

0.3854

0.4517

y = 0.9925x + 0.5342

7 days compressive strength

0.9771

0.9547

0.8048

0.0567

y = 1.0177x + 0.1936

28 days compressive strength

0.9854

0.9710

0.8524

1.2466

y = 1.0668x + 1.7266

mortar enhanced the strength, while TEA decreased compressive strength. ANN model was trained, and tested results for various input parameters of cement mortar were compared with the experimental results. The neural network model had very low mean absolute error and root mean squared error for all the predictive parameters. The correlation coefficient for output parameters, i.e., target was found near to unity. Therefore, ANN predictive model for these 18 mixes gave results with high precision and accuracy. ANN predictive model can be used for the prediction of consistency, setting time, and compressive strength of cement mortar consisting of accelerating admixtures and stone waste.

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References 1. Devi K, Saini B, Aggarwal P (2018) Effect of accelerators with waste material on the properties of cement paste and mortar. Comput Concr 22:153–159 2. Devi K, Saini B, Aggarwal P (2018) Combined use of accelerators and stone slurry powder in cement mortar. Springer Nature Switzerland AG 2019, vol 21, pp 1–8 3. Khodabakhshian A, de Brito J, Ghalehnovi M, Shamsabadi EA (2018) Mechanical, environmental and economic performance of structural concrete containing silica fume and marble industry waste powder. Constr Build Mater 169:237–251 4. Rana A, Kalla P, Csetenyi LJ (2015) Sustainable use of marble slurry in concrete. J Clean Prod 94:304–311 5. Devi K, Acharya KG, Saini B (2018) Significance of stone slurry powder in normal and high strength concrete. Springer Nature Switzerland AG 2019, vol 21, pp 484–492 6. Singh H, Garg P, Kaur I (eds) (2018) In: Proceeding of 1st international conference on sustainable waste management through design. Springer Nature America 7. Naderpour H, Nagai K, Fakharian P, Haji M (2019) Innovative models for prediction of compressive strength of FRP-confined circular reinforced concrete columns using soft computing methods. Compos Struct 215:69–84 8. Eskandari H, Tayyebinia M (2016) Effect of 32.5 and 42.5 cement grades on ANN prediction of fibrocement compressive strength. Proc Eng 150:2193–2201 9. Khashman A, Akpinar P (2017) Non-destructive prediction of concrete compressive strength using neural networks. Proc Comput Sci 108:2358–2362 10. Diab AM, Elyamany HE, Elmoaty MAEA, Shalan AH (2014) Prediction of concrete compressive strength due to long term sulfate attack using neural network. Alexandria Eng J 53:627–642 11. Prasad BKR, Eskandari H, Reddy BVV (2009) Prediction of compressive strength of SCC and HPC with high volume fly ash using ANN. Constr Build Mater 23:117–128 12. Lee S (2003) Prediction of concrete strength using artificial neural networks. Eng Struct 25:849– 857 13. Demir F (2008) Prediction of elastic modulus of normal and high strength concrete by artificial neural networks. Constr Build Mater 22:1428–1435 14. Uysal M, Tanyildizi H (2011) Predicting the core compressive strength of self-compacting concrete (SCC) mixtures with mineral additives using artificial neural network. Constr Build Mater 25:4105–4111 15. Chou J-S, Tsai C-F (2012) Concrete compressive strength analysis using a combined classification and regression technique. Autom Constr 24:52–60 16. Chithra S, Kumar SRRS, Chinnaraju K, Ashmita FA (2016) A comparative study on the compressive strength prediction models for high performance concrete containing nano silica and copper slag using regression analysis and artificial neural networks. Constr Build Mater 114:528–535 17. Eskandari H, Nik MG, Eidi MM (2016) Prediction of mortar compressive strengths for different cement grades in the vicinity of sodium chloride using ANN. Proc Eng 150:2185–2192 18. Azimi-Pour M, Eskandari-Naddaf H (2018) ANN and GEP prediction for simultaneous effect of nano and micro silica on the compressive and flexural strength of cement mortar. Constr Build Mater 189:978–992 19. Onyari EK, Ikotun BD (2018) Prediction of compressive and flexural strengths of a modified zeolite additive mortar using artificial neural network. Constr Build Mater 187:1232–1241 20. Mahdinia S, Eskandari-Naddaf H, Shadnia R (2019) Effect of cement strength class on the prediction of compressive strength of cement mortar using GEP method. Constr Build Mater 198:27–41 21. Naderpour H, Rafiean AH, Fakharian P (2018) Compressive strength prediction of environmentally friendly concrete using artificial neural networks. J Build Eng 16:213–219

A Study on Dynamic Behaviour of Monoblock Concrete Sleepers Using SAP2000 P. S. Rao, A. K. Desai, and C. H. Solanki

Abstract A high-speed train is one which often operates at a speed above 200 kmph (125 mph). High-speed trains bring about new challenges in the construction of strong railway roadbeds so as to protect mechanical components of trains and track structures from damage, to improve the comfort of riding for passengers and to reduce ground vibration and noise pollution. While designing railway tracks, irregularities of the wheels and rails must be accounted for, as they may induce considerable dynamic loads. For a track structure, the most important part is a concrete sleeper. There is a continuous need for the improvement in the analytical tools for the dynamic analysis of the concrete sleepers. A 3D FEM model of the concrete sleeper is developed in SAP2000 version 18.0 software considering two conditions, that is, when sleeper is placed on-site without any constraints and when it is placed on ballast. The results obtained are finally validated with the previously done work on STRAND7 software by comparing their mode shapes. Keywords High-speed rails · Concrete sleepers · Vibration analysis · SAP2000

1 Introduction In order to maintain spacing between the rails; sleepers are tied to the rails. This helps to maintain the positioning and level of the tracks. This leads to the even distribution of dynamic loading through the sleepers onto the track structure. They also act as an electrical insulator between the two rails. The commonly used materials for the construction of sleepers are (1) Wooden sleepers, (2) Metal sleepers and (3) Concrete sleepers. Based on the design speed of train and the cost of the project, the appropriate

P. S. Rao (B) APSIT, Thane, Maharashtra, India e-mail: [email protected]; [email protected] A. K. Desai · C. H. Solanki SVNIT, Surat, Gujarat, India © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_10

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Fig. 1 Concrete sleepers [7]

material is selected for the construction of sleepers. Commonly used concrete sleepers are monoblock sleepers, reinforced twin block sleepers and prestressed sleepers. Reinforced twin block sleeper was first developed in France. The sleeper is light in weight and comprises two concrete blocks that are joined together with the rigid steel beam to restrict their lateral movement with the passage of train; see Fig. 1a. The sleepers are designed for the service life of about 50 years and can withstand varying operating frequency. It is commonly used in the countries like France, Belgium, Denmark, Netherlands, Greece, etc. Countries like United States of America, Canada, Sweden, Australia, England, Germany, China and many more have adopted ballastless technology for the high-speed rails. These countries commonly use prestressed reinforced concrete beams also known as prestressed monoblock sleepers for hauling light and heavy transits on ballastless track. The concrete sleepers are designed either as a rigid or as a flexible beam. For the operating frequency below 100 Hz, they are modelled as rigid beam, and as flexible beam for the operating frequency up to 300–400 Hz using Euler–Bernoulli or Rayleigh–Timoshenko beam theory, Tore Dahlberg, 2003 [1]. As the rails are discretely supported by the sleepers at a regular interval of 0.65 m, stiffness along the rail increases with the passage of wheel over the rails. The frequency of vibrations induced in the rails due to spacing between sleepers is given by the Eq. (1): f =

v D

(1)

where v is the train velocity and D is the span between two sleepers (0.65 m).

2 Literature Review Grabe et al. [2] studied the effect of under-sleeper pads while analysing sleeper– ballast interaction. As per their theory, in case of ballasted track structure, the presence of under-sleeper pads will increase the contact area between the angular ballast particles and the underside of the concrete sleeper. This further leads to reduction in the ballast breakdown which leads to reduction in total track settlement. They concluded with the static and cyclic load test with about one million loading that the

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use of pad will help reduce regular wear and tear of ballast and will help increase their service life. Clark et al. [3] developed prototype of railway sleepers using FEM technique, and determined its resonant frequency. The modal analysis of various components of the track structure was conducted to develop and analyse the influence of train loading on the mode shapes of the components. The numerical analysis exhibited zero tension condition near the supports. Kishore Kumar and Sambasivarao [4] studied the impact of trainload at two points on the sleeper where passing rails rest on them. The modal analysis of the sleeper in the unrestraint condition depicted that natural frequencies in unrestraint condition is lesser than the natural frequencies of the sleeper subjected to restraints representing actual in situ condition. Their study showed that in order to understand the dynamic behaviour of the sleeper condition it is necessary to analyse the interaction between the sleeper and underlying ballast. Li [5] did dynamic and static analysis on a prestressed concrete sleeper. The interaction between sleeper and ballast was analysed to study structural behaviour of the sleeper using finite element modelling. ANN was adopted to understand the behaviour of sleeper under a various support condition. The study considered the influence of movement of rail seat in the vertical direction and development of stresses at various critical locations on rail seat. Kaewunruen et al. [1] conducted experimental modal analysis of prestressed concrete sleepers to understand the influence of void in situ conditions. The frequency considered for the study ranges from 0 to 1600 Hz. The impact for this range of frequency was generated using hammer excitation technique. Bruel & Kjaer PULSE dynamic analyser captured the frequency generated by means of the hammer, and the results were further processed using the STAR Modal analysis package for various excitation frequency. Remennikov and Kaewunruen [6] conducted their study to determine the factors that lead to the development of cracks in the prestressed concrete sleepers as such cracks add to maintenance cost of the railway track. Their findings include parametric analysis of free vibration response of concrete sleeper when placed on rail pads with different properties. Based on Timoshenko beam theory, the sleeper was modelled as beam element supported by spring elements which represent ballast support to the sleepers at their base. The dynamic performance of railway track when subjected different types of rail pads was later summarized by analysing the first five mode shapes obtained through modal analysis. Kumaran et al. [7] discussed the dynamic response of prestressed concrete sleeper due to irregularities in wheel and rail, for various parametric conditions. The time history analysis of the vehicle and track was made using MSC/NASTRAN to comprehend the dynamic behaviour of sleepers. The dynamic amplification factors for deflection, ballast pressure and bending moments of track for various vehicle–track conditions at various operating frequencies were critically reviewed.

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3 Modelling of Sleeper Australian standard gauge sleeper was considered in the present work. The sleeper is having symmetricity in two directions. The span of the sleeper is 2700 mm. The top width of the sleeper is 220 mm with a base measuring 270 mm. The centre-to-centre distance between the rails is 1676 mm which represents broad gauge. The schematic representation of sleeper is shown in Fig. 2. In SAP, solid element is used to model sleeper as a solid monoblock with trapezoidal section. Springs are used to represent ballast, with the stiffness equivalent to the stiffness of ballast in vertical direction. The ends of the sleeper were restrained in all three translational directions. In free condition, it is assumed that sleepers are just lying on the layer of ballast; thus, while modelling free condition, the sleepers were resting without any constraints (Tables 1, 2 and 3).

Fig. 2 Schematic representation of trapezoidal monoblock concrete sleeper used for study

Table 1 Sleeper material properties used for validating model [6]

Sr. No.

Parameters list

Symbol

Values

1

Flexural rigidity

EIc

4.6 MN/m2

2

Ballast stiffness

kb

13 MN/m2

3

Sleeper density

S

2750 kg/m3

4

Effective stiffness

ke

17 MN/m2

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Table 2 Natural frequencies of the validated in situ sleeper study model Mode

Sleeper 1, STRAND7 (Hz)[6]

Sleeper 2, EXPERIMENTAL Study model SAP2000 (Hz) (Hz) [7]

1

122

155.22

135.88

2

314

413.70

380.65

3

607

503.85

632.95

4

997

775.67

740.85

5

1486

1168.48

1174.28

Table 3 Natural frequencies of the validated free-free condition sleeper study model Mode

Sleeper 1, STRAND7 (Hz)[6]

Sleeper 2, EXPERIMENTAL (Hz)[7]

Study model SAP2000 (Hz)

1

122

135.71

99.4

2

314

404.83

135.84

3

607

481.36

295.47

4

997

767.84

345.65

5

1486

1155.31

380.65

4 Results and Discussion The results of natural frequencies and mode shapes of the free and in situ railway concrete sleeper are given in Table 4. The lowest fundamental frequency obtained in a condition devoid of constraints on the sleeper through Eigen Frequency Modal Analysis is 99.4 Hz, while the same in an actual field condition yields 135.88 Hz by constraining the bottom and adjacent surface. This on comparing with the previous work done by various researchers shows the average percentage error is within 10%. The outcome of modal analysis in the said conditions is shown in Table 4. The current study signifies the importance of ballast–sleeper interaction based on the fact that for the in-situ condition, the frequencies are substantially higher and thereby aids to conclude that the ballast cushions the sleeper effectively. Thus, it can be summarized that actual field boundary conditions have a tremendous influence on derivation of the natural frequency and generation of dynamic mode shapes of concrete sleepers, and hence it is recommended to model the boundary conditions of the sleepers as per field condition to minimise the fatality caused by undermining the importance of ballast–sleeper interaction.

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Table 4 Change in mode shapes of concrete sleepers (in situ) Mode

Field condition

1

1st bending

Deformed shapes

Frequency (Hz) 135.88

2

2nd bending

380.65

3

3rd bending

632.95

4

4th bending

740.85

5

1st twisting

1174.28

5 Conclusion Modal analysis is one of the widely used technique for the prediction of vibration response of the concrete sleepers. These vibration parameters of concrete sleepers assist in the development of a realistic dynamic model of railway track. The results of the modal analysis for the concrete sleepers under different boundary conditions are presented in the paper. The study shows that ballast sleeper interaction had a notable influence on the natural frequency and vibration mode shape of concrete sleepers as ballast cushions sleeper effectively.

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109 500

150

FF

100

IS 50

Natural Frequency, Hz

Natural Frequency, Hz

200

0

300 200 100 0

SLP1

SLP2

SLP3

SLP1

SLP2

SLP3

1200

600 500 400

FF

300

IS

200 100 0

Natural Frequency, Hz

700

Natural Frequency, Hz

400

1000 800 600 400 200 0

SLP1

SLP2

SLP3

SLP1

SLP2

SLP3

Fig. 3 Comparative analysis of 1st, 2nd, 3rd and 4th mode for free-free (FF) and in situ (IS) sleepers conditions

References 1. Tore Dahlberg (2003) Railway Track Dynamic-A Survey”, Solid Mechanics IKP Linkoping University 2. Grabe PJ, Mtshotana BF, Sebati MM, Thunemann EQ (2016) The effects of under-sleeper pads on sleeper–ballast interaction. J S Afr Inst Civil Eng 58(2):35–41. Paper 1241 3. Clark A, Kaewunruen S, Janeliukstis R, Papaelias M (2017) Damage detection in railway prestressed concrete sleepers using acoustic emission. IOP Conf Ser Mater Sci Eng 251:012068. https://doi.org/10.1088/1757-899x/251/1/012068 4. Kishore Kumar. D and Sambasivarao K (2014) Static and dynamic analysis of railway track sleeper” International Journal of Engineering Research and General Science Volume 2, Issue 6 5. Shan Li (2012) Railway Sleeper Modelling with Deterministic and Non-deterministic Support Conditions Master Degree Project 6. Kaewunruen S, Remennikov A M (2007) Investigations of static and dynamic performance of railway prestressed concrete sleepers. http://ro.uow.edu.au/engpapers/359 7. Remennikov, A. M. and Kaewunruen, S 2005 Investigation of vibration characteristics of prestressed concrete sleepers in free-free and insitu conditions.http://ro.uow.edu.au/engpapers/ 284 8. Kumaran G, Devdas Menon, Krishnan KN (2003) Dynamic studies of rail track sleepers in a track structure system Journal of Sound and Vibration 268 485–501

Spatial Machines for Heterogeneous MRI Data—A Critical Review Zabiha Khan and R. Loganathan

Abstract Biomedical Engineering enables better quality of life to the medical conditions of people. Magnetic Field Applications in biological aspects and manipulations of tissue engineering sorted out the diagnostic solutions. MRI has become the potential emerging tool to gain capabilities to overcome obstacles of biomedical field. The Combination of Image Processing in MRI with the ability to produce targets, presents a disruptive technology which affects the criticality of healthcare. Keywords MRI · Biomedical engineering · Image processing

1 Introduction MRI (Magnetic Resonance Imaging) provides the treatment in the form of precise targeting, processing, and quantification and is widely used in medical technology to detect tissue abnormalities and tumors. It studies the human anatomy and analyzes the full body producing high spatial resolution images of soft tissue for the detection of disease. Considering many parameters to characterize the pathology using a continuous process, the extraction and analysis of large amounts of advanced quantitative imaging features is referred as “Radiomics” [1]. Radiomics can be used to build descriptive and predictive models relating to the features such as gene–protein signatures. Radiomics can provide valuable diagnostics, prognostic, or predictive information.

Z. Khan (B) Computer Science & Engineering, VTU, Belagavi, India e-mail: [email protected] R. Loganathan (B) Computer Science & Engineering, HKBK College of Engineering, Bengaluru, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_11

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2 MRI, a Diagnostic Tool!! MRI images are generated using a magnetic field approximately 10,000 times stronger than the earth’s magnetic field. It also provides maps of anatomical structure with Magnetic Resonance of hydrogen (1H) nuclei in water and lipids measured by MRI Scanner. Signal values have 4096 shades and can be represented by a pixel [2]. MRI scanner is available at 1.5T or 3T. During the process, a radio frequency pulse will be introduced resulting in spinning protons to move out of the alignment. Also, a radio antenna inside the scanner helps in detecting the signal and creating the image. MRI can confirm early stage tumor, thus correctly stratifying patients into active surveillance which ensures the appropriate treatment. SVM (Support Vector Machines) can be used as supervised learner. In SVM, every object is represented by a point in the n-dimensional space, used for regression and classification. However, consensus on which technical approaches and combination of Multiparametric MRI (Multiparametric-Medical Resonance Imaging) techniques should be used for specific clinical indications remains a challenge. Multiparametric imaging consists of the combination of T1 and T2—weighted atomic imaging and functional MR techniques including Diffusion Weighted Imaging, Dynamic Contrast Enhanced Imaging, and Spectroscopy Imaging. As reported, accuracies of Multiparametric MR Imaging techniques for different indications are inconsistent; suitable conclusions are difficult to arrive at [3].

3 MRI Protocol All scans were obtained with 1.5T MR Scanner using Integrated Endo-Rectal Pelvic Phased array coil [4]. Recent advances in MRI in detecting the cancer with multiparametric approach help in realizing MP-MRI into the real world as a diagnostic tool. MP-MRI is widely used for characterizing tumor [5].

4 Key Technologies and Challenges in Radiomics As per QIN (Quantitative Imaging Network), guidelines established by NCI (National Cancer Institute), implementation of Radiomics includes acquisition and reconstruction of standardized images, segmentation, feature extraction, and quantitative data analysis. The physiological property assessment using different techniques of MRI provides a novel approach into the microvasculature vessel permeability and volume fractions [6]. However, in the early stage development, there are innumerable problems that must be solved in Radiomics from original.

Spatial Machines for Heterogeneous MRI Data … Table 1 The table below lists the qualitative variables and their respective sources in DCE-MRI

Source

113 Variable

Scanner

Pulse sequence

Software

Image formation Input functions Software bug handling

Operator

Image parameters

5 Image Extraction to Data Analysis Authors have adopted accurate Quantitative measurement of perfusion parameters by DCE-MRI which may impact heavily on the clinical care of cancer patients. Image Data Quantification methods will reduce turnaround time leading to the optimal treatment [7]. Major sources of variability in DCE-MRI are MRI Scanner, Post Image Processing, and Operator. But each MRI scanner has its own configuration performing with Pulse Code Sequences including reconstruction schemes [8] (Table 1).

6 Quantitative Imaging Process of extracting measurable information from images to find the amount and extent of the diseases provides reproducible numerical results. An effort has been made by authors toward achieving better results for quantitative and qualitative image formation [9].

7 Advances in Image Acquisition Lot of advances in image acquisition will improve quality and resolution of imaging along with diversity in imaging modalities. Radiomics and Radiogenomics are the outcome of quantitative imaging; by incorporating the signs of informatics into medical imaging, we create a powerful driver for the precision medicine activities [10].

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8 Advances in Image Classification The labeling of images into one of a number of predefined categories can be referred as Image Classification. It is a critical step for high-level processing; also, it is the last step in the process to detect and classify the image into normal and abnormal form.

9 Deep Learning Based Image Recognition This is an unexplored area of research gaining lot of attention by the researchers nowadays. Using this approach, accelerated MRI can be produced with the help of Deep Learning which leads to shorter duration in measurements obtained from the data acquired. Currently, authors of this paper are involved in Deep Learning based image classification [11].

10 Work Done so Far Detailed critical review of research papers [1–12] has been carried out by the authors of this paper. As per the references indicated [1–12] from International and National scenario, it is observed that MRI data is surely heterogeneous. Ample research work has been carried out on medical imaging, quantitative measurements of different parameters by different techniques in MRI, Image Data Quantification, and challenges in Radiomics. Hence, further work on Deep Learning based image recognition related to Prostate Cancer is under progress [12].

11 Conclusion This paper describes different aspects of image processing techniques for MRI imaging to improve the Performance, Classification, and Accuracy in detecting tumors with preprocessing, segmentation, feature extraction, and classification overviews of image processing techniques. Future work will be extended to detect the types of tumors in MRI which may provide results efficiently involving both qualitative and quantitative labels. Acknowledgements Assistance provided by Dr. N. S. Kumar (Professor and Director R&D, GCE, Ramanagaram) was greatly appreciated.

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References 1. Niaf E et al. Kernel-based learning from both qualitative and quantitative labels: application to prostate cancer diagnosis based on multiparametric MR imaging 2. Levy MA et al. Informatics methods to enable sharing of quantitative imaging research data 3. Huang M, Yang W, Wu Y, Jiang J, Chen W, Feng Q. Brain tumor segmentation based on local independent projection-based classification 4. Guo Y et al. Deformable MR prostate segmentation via deep feature learning and sparse patch matching 5. Costouros NG et al. Microarray gene expression analysis of murine tumor heterogeneity defined by dynamic contrast-enhanced MRI 6. Lee D, Yoo J, Ye JC. Deep residual learning for compressed sensing MRI 7. Jeelani H, Martin J, Vasquez F, Salerno M, Weller DS. Image quality affects deep learning reconstruction of MRI 8. Sindhu A et al. A survey on detecting brain tumorinmri images using image processing techniques 9. Wang G, Li W, Zuluaga MA, Pratt R, Patel PA, Aertsen M, Doel T, David AL, Deprest J, Ourselin S, Vercauteren T. Interactive medical image segmentation using deep learning with image-specific fine tuning 10. Cheng R et al. Deep learning with orthogonal volumetric HED segmentation and 3D surface reconstruction model of prostate MRI 11. Ravı D, Fabelo H, Callico GM, Yang1 G-Z. Manifold embedding and semantic segmentation intraoperative guidance with hyperspectral brain imaging 12. Leynes AP, Larson PEZ. Synthetic CT generation using MRI with deep learning: how does the selection of input images affect the resulting synthetic CT?

Influence of Fineness of Mineral Admixtures on the Degree of Atmospheric Mineral Carbonation C. Farsana, Bibhuti Bhusan Das, and K. Snehal

Abstract Global carbon dioxide concentration is rising at the rate of 2 ppm every year, which had led to the demand of sustainable development. In construction industry, manufacturing of cement is the main source of global anthropogenic carbon dioxide emissions. Carbon capture and storage is a recent technology which had helped to sequester carbon dioxide from atmosphere and thus helps in reducing the greenhouse effect to a certain extent. This study mainly focuses on the atmospheric mineral carbonation of mineral admixtures like fly ash (FA), ground granulated blast furnace slag (GGBS), and silica fume (SF), which are the industrial by-products and are being treated as waste. This study also focuses on the effect of fineness of different mineral admixtures on the degree of atmospheric mineral carbonation. Fly ash with three different levels of fineness (FA, FA I, and FA II), GGBS with three different levels of fineness (GGBS, GGBS I, and GGBS II), and silica fume were mixed with activators like lime and gypsum and were left for atmospheric mineral carbonation. Mineralogical characterisations were done using X-ray diffraction (XRD), thermo gravimetric analysis (TGA), and scanning electron microscopy (SEM). Degree of carbonation of the samples was analyzed and calculated using the TGA results. From the comparative analysis of all the samples, it was found that GGBS II had highest degree of carbonation. It was also observed that calcium-based compounds like calcite, aragonite, vaterite, calcite magnesium syn, gismondine, waikarite, calcium silicate hydrate, diopside, calcium sulfate, and portlandite were formed in the samples after 45 and 90 days of atmospheric mineral carbonation. However, it was observed that with increasing levels of fineness of mineral admixtures, there was no significant change in the degree of atmospheric mineral carbonation.

C. Farsana · B. B. Das (B) · K. Snehal Department of Civil Engineering, NITK, Surathkal 575025, India e-mail: [email protected] C. Farsana e-mail: [email protected] K. Snehal e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_12

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Keywords Carbon dioxide emissions · Mineral admixtures · Atmospheric mineral carbonation · XRD · TGA · SEM

1 Introduction The world population is increasing rapidly day by day leading to industrialization, urbanization, globalization of market economy, and environmental pollution. The combined effect of all these has led to climate change, which is threatening to cause damage to human life on the earth. Global warming is major effect of the climate change. Global warming is the increase in the average temperature of the Earth’s atmosphere and oceans as a result of greenhouse gases in our atmosphere [1]. According to Intergovernmental Panel on Climate Change (IPCC), during the period 800–1200, i.e., before the industrial revolution the carbon dioxide (CO2 ) concentration remained nearly constant at about 280 ppm (parts per million). IPCC data shows that the atmospheric CO2 concentration is rising at an approximate rate of 2 ppm every year (IPCC special report on carbon dioxide capture and storage, 2005). IPCC recommends that atmospheric CO2 concentration must be reduced to the 1990 level or less in the next 20–30 years and, therefore, major CO2 -emitting industries must take decisive measures for achieving drastic cuts in CO2 emissions within this period [2, 3]. Concrete is the most widely used building material in the world because of its strength and durability, among other benefits. Concrete is used in nearly every type of construction, including homes, buildings, roads, bridges, airports, and subways [4, 5]. The production of Portland cement, which is an essential constituent of concrete, leads to the release of significant amount of CO2 and other greenhouse gases (GHGs) [6–8]. According to Gigaton throwdown initiative 2009, the cement industry contributes to about 5% of the global anthropogenic CO2 emissions [9]. Thus, it is clear that cement industries are contributing significantly to the climate change. For the sustainability of cement and concrete industries, they must take decisive measures for achieving significant reduction in CO2 emissions. Significant CO2 reduction can be achieved through replacement of cement in concrete by optimum amount of supplementary cementitious materials [6, 7, 10, 11]. Fly ashes, ground granulated blast furnace Slag (GGBS), silica fume, geopolymers, rice husks, etc,. are some of the supplementary cementitious materials available to replace cement [7, 10, 12–15]. Thermal power industries produce million tons of coal fly ash each year, which are usually disposed in the form of piles and landfills leading to the environmental as well as health issues [16–19]. Several studies show that fly ash can be used up to 25–30% replacement level to cement depending upon the quality of ash (4–5, 15). According to American Concrete Institute, the substitution of Portland cement by 25% of fly ash reduces overall CO2 emission by 30–50% [6, 15, 18, 19]. American Coal Ash Association estimates that fly ash in concrete is responsible for avoiding 12 million tons of CO2 emissions each year [1, 18]. World’s steel production is also

Influence of Fineness of Mineral Admixtures …

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increasing day by day due to the increasing needs of population. This has led to the production of slag, by-product in the manufacture of steel. Majority of slag usually remains unused. Researches report that substantial portion of the normal Portland cement in concrete can be replaced by GGBS, generally about 50% [10, 20]. While comparing with Portland cement, manufacture of GGBS requires less than a fifth of the energy and produces less than a fifteenth of the carbon dioxide emissions [10, 21]. Studies also show that as slag is rich in calcium and magnesium oxide it can be also used as a feedstock for carbon dioxide sequestration [10, 20–23]. The alternative method to control the global warming is CO2 absorption. The carbon capture and storage (CCS) is a new technology which can be achieved through geological storage, ocean storage, and storage below sea bed and through mineral carbonation [24]. Mineral carbonation is a process similar to natural weathering process. It is an exothermic reaction between metal oxides bearing materials and carbon dioxide which results in the formation of thermodynamically stable carbonate minerals [19, 24, 25]. Unlike other sequestration process, mineral carbonation provides permanent trapping of carbonate mineral where post monitoring is not essential once CO2 sequestration is done. However, the natural carbonation is a slow process. Pre-treatment like grinding is one of the ways to improve the rate of carbonation. Mineral carbonation can be achieved through direct carbonation, direct gas–solid carbonation, direct aqueous carbonation, and indirect carbonation [11, 12, 24–27]. In direct method, carbonation takes place in single step. While in indirect method, calcium and magnesium are first extracted from the mineral and then carbonated. The calcium and magnesium-bearing industrial residues like coal fly ash, steel slag, and waste concrete can be used as a feedstock for carbon dioxide sequestration [7, 12–15, 21, 24]. Carbon dioxide sequestration can be achieved economically through the mineral carbonation of calcium-bearing sulfated mixture of admixture to atmospheric conditions in open place [28]. During mineral carbonation, initially dissolution of silica and alumina occurs in the presence of calcium and sulfate which results in the formation of unstable mineral ettringite, which further decomposes to form the carbonate and sulfate minerals [29]. Thus, it seems that carbon dioxide capture and storage technology, low-temperature burning technology, and increased admixture content of cement are effective methods of reducing the carbon dioxide emissions. Considering this in view, current experimental investigation was carried out focusing on to the atmospheric mineral carbonation. Mineral admixtures like fly ash, ground granulated blast furnace slag, and silica fume, which are the industrial by-products are being used in this study. This study also presents the effect of fineness of different mineral admixtures on the degree of atmospheric mineral carbonation through advanced characterization techniques such as X-ray diffraction (XRD), thermo gravimetric analysis (TG-DTA), and scanning electron microscopy (SEM). In addition, influence of fineness of mineral admixtures such as fly ash with three different levels of fineness ranging from 2100 to 3350 cm2 /g (FA, FAI, and FAII), GGBS with three different levels of fineness ranging from 3500 to 4700 cm2 /g

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(GGBS, GGBS I, and GGBS II), and silica fume (200,000 cm2 /g) mixed with activators like lime and gypsum was left for atmospheric mineral carbonation in order to study the rate of atmospheric mineral carbonation.

2 Materials and Material Characteristics The present study was focused on to determine the potential of atmospheric mineral carbonation. The mineral admixtures used in present experiment investigation are: The class F fly ash procured from Udupi Power plant, Padubidri, Karnataka; GGBS procured from locally available sources in Jindal Steel and Power Limited, Bengaluru, Karnataka; and Silica fume procured from Manjeshwar Techno Trades, Mangalore (named as “CORNICHE SF”) confirming to ASTM C1240:2005 and IS 15388:2003 standards were used in the present study. In this study, fly ash with three different levels of fineness (FA, FA I, and FA II), GGBS with three different levels of fineness (GGBS, GGBS I, and GGBS II), and silica fume with unaltered fineness were considered. The received samples of fly ash of fineness 2162 cm2 /g and GGBS of fineness 3530 cm2 /g were named as FA and GGBS, respectively, while the grinded samples of fly ash and GGBS were named as FA I (2874 cm2 /g), FA II (3349 cm2 /g), GGBS I (3917 cm2 /g), and GGBS II (4670 cm2 /g), respectively. In order to activate the mineral admixtures for atmospheric mineral carbonation, the current study made use of activator such as hydrated lime containing small percentages of calcium oxide and gypsum; both procured from Sri Durga Laboratory Equipments, Mangalore were used. The physical properties of the materials used in present investigation are presented in Table 1. The consistency of different mixes used in present study is shown in the Table 2. Table 1 Physical properties of the received and grinded samples Sl. No.

Materials

Specific gravity

Fineness (cm2 /g)

Normal consistency (%)

1

FA

2.18

2161.86

32.00

2

FA I

2.28

2873.45

32.50

3

FA II

2.33

3349.14

33.00

4

GGBS

2.86

3529.41

35.00

5

GGBS I

2.89

3917.27

36.50

6

GGBS II

3.03

4670.03

37.00

7

SF

2.26

200,000

83.00

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Table 2 Consistency of the mixes for carbonation Sl. No.

Samples

Admixture (gms)

Lime (gms)

Gypsum (gms)

Consistency (%)

1

FA

375

15

10

34

2

FA I

375

15

10

34.5

3

FA II

375

15

10

35

4

GGBS

375

15

10

37

5

GGBS I

375

15

10

38

6

GGBS II

375

15

10

39

7

SF

375

15

10

85

3 Experimental Study 3.1 Sample Preparation The preparation of sample involves two steps, i.e., (a) grinding (ball milling) and (b) preparation of mix for atmospheric mineral carbonation. Grinding (ball milling) The received samples of fly ash (FA) and ground granulated blast furnace slag (GGBS) were subject to mechanical grinding by means of ball mill. Fly ash was grounded to the fineness of 2873.45 cm2 /g (FA I) and 3349.14 cm2 /g (FA II) after grinding for the duration of 1 h and 2 h, respectively, in ball mill. Similarly, GGBS was also grounded to the fineness levels of 3917.27 cm2 /g (GGBS II) and 4670.03 cm2 /g (GGBS III) after grinding for 21 /2 h and 5 h, respectively, in ball mill. Preparation of mix for atmospheric mineral carbonation. The seven sample mixes for atmospheric mineral carbonation were prepared by mixing mineral admixtures with lime and gypsum in the ratio of 100:4:3 [24]. Water was also added to make the paste workable. Amount of water added was determined using the consistency of the mix. Then the prepared samples were grounded into powder and kept in porcelain dish and was exposed to open atmosphere for mineral carbonation for a period of 45 days and 90 days. After 45 days and 90 days of carbonation, few grams of each carbonated sample were taken out and were tested for X-ray diffraction (XRD) and thermo gravimetric analysis (TGA) in order to check the carbonation rate. Figure 1 represents the prepared samples for atmospheric mineral carbonation.

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FA

FA1

FAII

GGBS

GGBS1

GGBSII

SF Fig. 1 Prepared samples of FA, FA I, FA II, GGBS, GGBS I, GGBS II, and SF

3.2 Analysis and Measurement of Carbonation The extent of carbonation after 45 days and 90 days of atmospheric exposure is analyzed by means of three techniques, i.e., X-ray diffraction analysis (XRD), thermo gravimetric analysis (TGA), and scanning electron microscope (SCM). XRD was used to determine the mineralogical characteristics of the received samples and the carbonated sample. The test was carried out at a deflection angle ranging from 20° to 80° at a scanning speed of 2°/min. The intensity peak data obtained from XRD were then analyzed using X-Pert High Score Plus software. XRD gave different peaks at different intensities corresponding to diffraction angles. Each peak corresponds to a specific mineral. As calcite and calcium-based compounds were present, it was concluded that the sample was carbonated.

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TGA was carried out by taking few milligram of the powdered sample in a platinum pan and was properly placed in the furnace. The sample was then heated from 50 to 100 °C at heating rate of 10°/min and from 100 to 900 °C at 20°/min in air with a purge rate of 20 ml/min. The recorder automatically records the change in weight with temperature. From the plot between weight and temperature, the weight loss was analyzed. The mass loss in the TGA curve indicates the consumption of some bound water and calcium hydrates during the decarbonation. The degree of carbonation using TGA results was analyzed based on two different methods: Method I: Based on study conducted [13], degree of CO2 sequestration can be calculated as follows: Eb =

Rloss × 100. 1 − Rloss

(1)

where Eb = CO2 sequestration efficiency of the carbonated paste (%) and Rloss = weight loss due to the decarbonation of carbonates in the carbonated paste between 500 and 900 °C (%). Method II: Based on the study conducted by [21], degree of carbonation can be calculated as follows: CO2 content (wt%) =

m500◦ C −900◦ C × 100, m105◦ C

(2)

where m500°C–900°C = weight loss of the sample between 500 and 900 °C from TGA graphs (mg) and m105°C = weight of sample at 105 °C from TGA graphs (mg). Carbonation Degree, ζ(% ) =

CO2 (wt % ) 100−CO2 (wt % )

×

MWCa (g/mol) MWCO2 (g/mol)

Atot (g/g)

× 100

(3)

where MWCa = molecular weight of Ca in g/mol, MWCO2 = molecular weight of CO2 in g/mol, and Atot = total weight of admixture per weight of paste (g/g). Morphological study was carried out by means of scanning electron microscope to analyze the microstructure of carbonated and non-carbonated samples.

4 Results and Discussions 4.1 Results of XRD Analysis The mineralogical composition of the samples was analyzed and was depicted in Fig. 2a–g, and Table 3 presents the pattern list of XRD peaks.

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Fig. 2 XRD patterns of non-carbonated and carbonated samples of a FA b FA I c FA II d GGBS e GGBS I f GGBS II g SF

Influence of Fineness of Mineral Admixtures …

Fig. 2 (continued)

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Table 3 Pattern list of XRD peaks Symbol

Compound name

Chemical formula

Q

Quartz

SiO2

M

Mullite, syn

Al4.75 Si1.25 O9.63

S

Sillimanite

Al2 SiO5

K

Kieserite

MgSO4 (H2 O)

D

Diopside

CaMgSi2 O6

τ

Moissanite 3\ITC\RG, syn

SiC

α

Calcite

CaCO3

ρ

Gypsum, syn

CaSO4 .2H2 O

ε

Gismondine

CaAl2 Si2 O8 .4H2 O

η

Calcite, magnesium, syn

(Mg0.06 Ca0.94 )(CO3

λ

Calcium silicate hydrate

Ca2 SiO4 .0.50H2 O

μ

Aragonite

CaCO3

φ

Augite

Ca(Mg0.85 Al0.15 )((Si1.70 Al0.30 )O6 )

ζ

Parawollastonite

CaSiO3

δ

Coesite

SiO2

χ

Magnetite

Fe3 O4

γ

Calcite

CaCO3



Waikarite

CaAl2 Si4 O12 .2 H2 O

σ

Grossite, syn

CaAl4 O7



Calcium sulfate

CaSO4

π

Vaterite, syn

CaCO3

ψ

Portlandite, syn

Ca(OH)2

Influence of Fineness of Mineral Admixtures …

127

From the XRD patterns of non-carbonated fly ash, it can be observed that fly ash contains minerals like quartz, mullite, sillimanite, and kieserite. It can be observed from the XRD patterns of 45 days carbonated fly ash samples (FA, FA I, FA II) that some of the quartz, mullite, sillimanite, and kieserite minerals were replaced by calcite, aragonite, diopside, gypsum, gismondine, calcium silicate hydate, and augite. But it is clear from the XRD patterns of 90 days carbonated samples of fly ash that most of the minerals found in non-carbonated samples were replaced by calciumbased compounds like calcite, calcite magnesium, aragonite, calcite magnesium syn, diopside, waikarite, and calcium sulfate (Fig. 2a–c). No significant peaks can be analyzed from the XRD patterns of non-carbonated GGBS. But after 45 days of carbonation, calcite peaks can be identified in the samples of GGBS (GGBS, GGBS I, and GGBS II). XRD patterns of GGBS samples after 90 days show more peaks with the presence of calcium-based compounds like calcite, vaterite, portlandite, and diopside (Fig. 2d–f). XRD patterns of non-carbonated silica fume show the presence of minerals such as diopside and moissanite. XRD patterns of 45 days carbonated sample of silica fume (SF) shows the presence of calcite, calcite magnesium, and coesite, while XRD patterns of 90 days carbonated sample show the presence of calcite and gismondine peaks (Fig. 2g). So it is clear from the mineralogical analysis that calcium-based compounds were formed after 90 days of carbonation which indicates that the samples were getting carbonated with time.

4.2 Results of TGA Analysis The results of thermo gravimetric analysis of the received samples of fly ash, GGBS, and silica fume are shown in Fig. 3a–c. TGA results of 45 days of carbonated samples are shown in Fig. 4a–g. TGA results after 90 days of carbonation are shown in Fig. 5a–g. From TGA test results of non-carbonated and carbonated samples, it can be observed that there is a significant weight loss between 100–200 °C, 200–500 °C, 500–900 °C. The weight loss between 100 and 200 °C was mainly due to the decomposition of moisture content in the sample [13, 21]. But it can be observed that weight loss between 200 and 500 °C was less compared to the other two. This weight loss was mainly due to the decomposition of magnesium-based carbonates and other organic compounds [21]. A significant weight loss can be observed between 500 and 900 °C, which was mainly due to the decomposition of calcium carbonates and other calcium-based compounds [13, 21, 25]. A comparative analysis of percentage weight losses of received samples was done and is depicted in Fig. 6. A comparative analysis of percentage weight losses between 500 and 900 °C for different samples with different fineness was done and is plotted in the Figs. 7, 8, and 9.

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a

17.43 25.00

6.000 17.42

20.00 17.41

4.000 15.00

2.000

17.39

TG mg

DTA uV

10.00

17.40

17.38

5.00 0.000

17.37

0.00

17.36

-2.000 -5.00

17.35 -10.00

-4.000 17.34 100.0

b

25.00

200.0

300.0

400.0 500.0 Temp Cel

600.0

700.0

800.0

900.0

0.000

17.20

20.00

17.19 -1.000

DTA uV

-2.000

17.17

10.00

TG mg

17.18

15.00

17.16 5.00

-3.000 17.15

0.00

-4.000

17.14

17.13

-5.00 100.0

c

200.0

300.0

400.0 500.0 Temp Cel

600.0

700.0

800.0

900.0

-2.00

20.10

35.00 -4.00

30.00

20.00

-6.00 -8.00

19.90 -10.00 -12.00

19.80

20.00

15.00

-14.00 19.70

-16.00 -18.00

19.60

10.00 -20.00

5.00

-22.00

19.50

-24.00 100.0

200.0

300.0

400.0 Temp Cel

500.0

Fig. 3 TGA of days received samples a FA b GGBS c SF

600.0

700.0

800.0

TG mg

DTA uV

25.00

Influence of Fineness of Mineral Admixtures … b

250.0

a

129

-2.00

34.40

10.00 220.0

40.00 200.0

-4.00 200.0

160.0

-8.00

39.40

DTA uV

-14.00

TG mg

-12.00

39.20

33.40 40.0

-20.00

38.80

-22.00 200.0

300.0

400.0 Temp Cel

500.0

600.0

700.0

800.0

100.0

d

220.0

-4.00

160.0

31.60

200.0

300.0

400.0 500.0 Temp Cel

600.0

700.0

800.0

4.000 21.80

140.0

3.000

120.0

2.000

21.60

31.40 160.0

33.20

0.0

38.60 100.0

-2.00

-2.00

20.0 -4.00

0.0

180.0

33.60 0.00

60.0

39.00 -18.00

200.0

2.00

80.0

-16.00

c

33.80

120.0 100.0

50.0

34.00

4.00

TG mg

140.0

100.0

6.00

39.60

-10.00

DTA uV

150.0

34.20

180.0

39.80

-6.00

8.00

-6.00

21.40

TG mg

DTA uV

31.20

-8.00 120.0

DTA uV

100.0

-10.00

100.0

21.20

0.000

80.0

31.00

-1.000

21.00

60.0

-12.00 80.0

60.0

1.000

TG mg

140.0

-2.000 -14.00

30.80

20.80

40.0 -3.000

40.0

-16.00

20.0

-18.00

20.60 20.0 -4.000

30.60

0.0

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4.3 Analysis of Degree of Carbonation Degree of carbonation of the samples after 45 and 90 days of carbonation was calculated based on the method suggested by Cao, W. and Yang, Q. (2015) and Huijgen,

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Fig. 5 TGA of 90 days carbonated samples a FA b FA I c FA II d GGBS e GGBS I f GGBS II g SF

W.J.J., Witkamp, G., and Comans, R.N.J. (2005) [13, 21, 25], and comparative analysis of both the methods for 45 and 90 days is depicted in Fig. 10 and Fig. 11, respectively. From the comparative analysis, it was clear that GGBS II had highest degree of carbonation followed by GGBS I and GGBS for both 45 and 90 days of carbonation.

Influence of Fineness of Mineral Admixtures …

0.8 0.6 0.4 0.2

Fig. 9 Comparison of % weight loss of non-carbonated (received) and carbonated samples of silica fume (CSF)

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% weight loss b/w 500˚C-900˚C

0

Fig. 7 Comparison of % weight loss of non-carbonated (received) and carbonated samples of fly ash (CFA, CFA I, CFA II)

% Wt loss at 500˚C-900˚C

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Fig. 6 Comparison of % weight losses of received samples of FA, GGBS, and SF

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Fig. 11 Comparison of calculated degree of carbonation of the different samples at 90 days based on the two different methods

4.4 Results of SEM Analysis The results of the morphological analysis of non-carbonated and carbonated samples using SEM were shown in Figs. 12, 13, and 14. It can be observed from the SEM results of non-carbonated samples of fly ash that it appears to be spherical in shape with smooth surface and were loosely packed. While in the carbonated samples, it can be observed that some of the particles were fused together with the other particles, and they appear to be porous in their morphology (Fig. 12). The SEM results of non-carbonated GGBS samples depict that particles appear to be crystalline in shape with lots of pores in between them. However, in the carbonated samples of GGBS, particles appear to be agglomerated which may be due to the formation of calcite minerals. It can also be noticed that less pores were present in between the particles (Fig. 13). While, in case of non-carbonated silica fume, irregurlar shaped particles were found to dispersed in the matrix. While in carbonated samples, it can be observed that the degree of reaction happens to be significant and the particles were found to be fused together with fewer pores between them (Fig. 14).

Influence of Fineness of Mineral Admixtures …

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Fig. 12 SEM results of non-carbonated and carbonated samples of fly ash

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Fig. 13 SEM results of non-carbonated samples and carbonated samples of GGBS

While comparing the SEM results of non-carbonated samples of fly ash with different fineness, there do not appear any distinct morphological differences. Both fine particles (FA I, FA II) and coarser particles (FA) of fly ash appear to be round in shape, while coarser particles had some finer particles in between them. In carbonated samples of fly ash with different fineness (FA, FA I, and FA II), a rim of carbonation products can be observed on the particles but not much difference can be noticed

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Fig. 14 SEM results of non-carbonated and carbonated samples of silica fume

SF

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with different fineness levels. In non-carbonated samples of GGBS with all levels of fineness (GGBS, GGBS I, and GGBS II), it can be observed that particles appear to be crystalline and flaky in shape. In coarser samples, bigger as well as smaller particles can be seen. While in carbonated samples, particles appear to be fused together but no significant difference can be observed with different fineness levels of GGBS.

5 Conclusions From the results and discussion, following conclusions can be drawn. Mineral admixtures like fly ash, GGBS, and silica fume get carbonated with 45 and 90 days of atmospheric mineral carbonation. With 45 days of atmospheric mineral carbonation, only few of the compounds present in mineral admixtures gets converted into calcium-based compounds. But with 90 days of carbonation, most of the compounds present in the non-carbonated samples of fly ash, GGBS, and silica fume gets converted into calcium-based compounds such as calcite, aragonite, vaterite, calcite magnesium syn, calcium silicate hydrate, gypsum, calcium sulfate, gismondine, diopside, and waikarite. Analysis using method I (according to Cao and Yang [13]) had highest degree of carbonation compared to the method II (according to Huijgen et al. [21]). GGBS II achieved degree of carbonation of 4.605%, which is highest among all the mineral admixtures. Bonded arrangement of particles found in the morphological studies of carbonated samples is mainly due to the formation of calcite and other calcium-based compounds during the atmospheric mineral carbonation. With the increase in the fineness of mineral admixtures, there is no significant change in their degree of atmospheric mineral carbonation.

References 1. Flower DJM, Sanjayan JG (2007) Greenhouse gas emissions due to concrete manufacture. Int J Life Cycle Assess 12(5):282–288

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2. IPCC (2005) IPCC special report on carbon dioxide capture and storage. Prepared by working Group III of the Intergovernmental Panel on Climate change, Metz B, Davidson O, de Coninck HC, Loos M, Meyer LA (eds). Cambridge University Press, Cambridge, United Kingdom and New York, USA 3. Mazzotti M (2005) Mineral carbonation and industrial uses of carbon dioxide, IPCC special report on carbon dioxide capture and storage. In: Eliasson B, Sutamihardja RTM (eds). Cambridge University Press, UK, pp 319–338 4. Mehta PK (2004) High performance, high volume fly ash concrete for sustainable development. In: Proceedings of the international workshop on sustainable development and concrete technology, May 20–21, Beijing, China 5. Mehta PK (2010) Sustainable cements and concrete for the climate change era—a review. In: Proceedings of the second international conference on sustainable construction materials & technologies, June 28–30, University Politecnica delle Marche, Ancona, Italy 6. Muduli SD, Nayak BD, Dhal NK, Mishra BK (2014) Atmospheric CO2 sequestration through mineral carbonation of fly ash. Greener J Phys Sci 4(1):1–6 7. Bertoz MF, Simons SJR, Hills CD, Carey PJ (2004) A review of accelerated carbonation technology in the treatment of cement-based materials and sequestration of CO2 . J Hazard Mater 112:193–205 8. Lagerblad B (2005) Report on carbon dioxide uptake during concrete life cycle-state of the art. Swedish Cement and Concrete Research Institute SE-10044, Stockholm 9. Augustine C, Byrne A, Gimon E, Goerner T, Hoffman I, Kammen DM, Kantner J, Levin J, Lipman T, Mileva A, Muren R, Paul S, Sapatari S, Thorsteinsson H, Tominks C (2009) Gigaton throwdown: redefining what’s possible for clean energy until 2020. Report, Renewable and Appropriate Energy Laboratory 10. Arivalagan S (2014) Sustainable studies on concrete with GGBS as a replacement material in cement. Jordan J Civ Eng 8(3):263–270 11. Ashraf W (2016) Carbonation of cement-based materials: challenges and opportunities. Constr Build Mater 120:558–570 12. Das BB, Pandey SP (2011) Influence of fineness of fly ash on the carbonation and electrical conductivity of concrete. J Mater Civ Eng 23(9):1365–1368 13. Cao W, Yang Q (2015) Properties of a carbonated steel slag-slaked lime mixture. J Mater Civ Eng 27(1):1–8 14. King D (2012) The effect of silica fume on the properties of concrete as defined in concrete society report 74, cementitious materials. In: Proceedings 37th conference on our world in concrete & structures, Singapore Concrete Institute, 29–31 August 2012, Singapore 15. He L, Yu D, Weizhi Lv, Wu J, Xu M (2013) A novel method for CO2 sequestration via indirect carbonation of coal fly ash. Ind Eng Chem Res 52:15138–15145 16. Mun M, Cho H (2013) Mineral carbonation for carbon sequestration with industrial waste. Energy Procedia 37:6999–7005 17. Naganathan S, Linda T (2013) Effect of fly ash fineness on the performance of cement mortar. Jordan J Civ Eng 7(3):326–331 18. Post NM (2010) Fly ash looms as the ‘new asbestos’. Green Source Magazine, April 15, 2010 19. Sann A, Uibbu M, Caramanna G, Kuusik R, Maroto-valer MM (2014) A review of mineral carbonation technologies to sequester CO2 . Chem Soc Revol 43:8049–8080 20. Suresh D, Nagaraju K (2015) Ground granulated blast slag (CGBS) in concrete—a review. IOSR J Mech Civ Eng 12(4):76–82 21. Huijgen WJJ, Witkamp G, Comans RNJ (2005) Mineral CO2 sequestration by steel slag carbonation. Environ Sci Technol 39(24):9676–9682 22. Makhdoom O, Makhdoom I (2013) Effect of components fineness of ground granulated blast furnace slag (CGBFS) on its strength efficiency in roller compact concrete mixes. Asian J Nat Appl Sci 2(3):82–89 23. Song K, Song J, Lee BY, Yang K (2014) Carbonation characteristics of alkali-activated blast furnace slag mortar. Adv Mater Sci Eng 326458:1–11

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Experimental Setup for Thermal Performance Study of Phase Change Material Admixed Cement Composites—A Review K. Snehal and Bibhuti Bhusan Das

Abstract Phase change material (PCM) is a prospective material with a caliber to store thermal energy. The hasty development in the modern world and lavish life style amplified the energy demand. Building and infrastructure are the leading energy and material consumers over the globe. Conservation of building energy associated to heating and cooling is made possible by embedding PCM in construction materials (like concrete) which has a great potential to improve the thermal comfort of the residents. The concrete coupled with PCMs has a tendency to improve the thermophysical properties like heat capacity/thermal mass and thermal insulating property besides with an ability to save energy for the development of sustainable built environment. There are so many techniques and experimental setups used by the researchers to analyze the thermal performance of PCM-admixed cementitious systems. In line to this, an attempt has been made to review the different experimental setup used by various researchers to study the thermal facets (heat capacity, thermal cycle, thermal conductivity, etc.) of PCM-doped cementitious systems Keywords Phase change material · Thermal cycle · Thermal conductivity · Heat capacity

1 Introduction The sensible heat and latent heat are the two categories of thermal energy storage techniques [1, 2]. Amongst the two thermal energy storage techniques, latent heat which is isothermal in nature possesses larger ability to store energy [3, 4]. Phase change material (PCM) is one such potential material which can store latent heat during the cycle of phase change from solid to liquid and vice versa [5–7]. The rapid K. Snehal · B. B. Das (B) Department of Civil Engineering, NITK, Surathkal 575025, India e-mail: [email protected] K. Snehal e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_13

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growth in urbanization increased the need for energy where building and infrastructure industries are the globe’s prime source for energy consumption. At this juncture, developing an energy-efficient building and construction material is of great potential. Considering this in view, introducing PCM as a latent heat storage material in chief building materials like cement composites has been suggested by researchers as a media to improve the thermal efficiency of building [5, 8, 9] by reducing heating and cooling load [4]. The several factors that influence the inside air temperature of a building includes outside climatic conditions like temperature variation, solar heat, wind speed, etc., along with other physical properties like thickness of wall, window/wall area ratio, thermal conductivity of wall, etc., and few other factors like indoor heating sources, supplementary heating/cooling system, etc. Balancing the indoor temperature differences in building plays a significant role in thermal comfort and at the same time increases the thermal effectiveness [4, 10]. Researchers had reported that PCMs have a significant potential in improving thermal mass/heat capacity [11, 12] as well as in improving the thermal resistivity by lowering the thermal conductivity [8, 13] of cement composites. Figure 1 depicts the balancing effect on indoor temperature by the influence of thermal mass. For the effective utilization of PCMs as thermal energy storage material in cementitious system, it should possess certain desirable thermodynamic, kinetic, and chemical properties [15]. Literature says PCMs integration in any form of application material will induce the temperature responses [16]. The specific heat, latent heat capacity, heat flow, thermal cycle, and thermal conductivity are the significant thermophysical properties needed to be assessed for PCM-integrated cementitious system [11]. In general PCM-doped cement composites are characterized by means of differential scanning calorimeter for analyzing the thermal performance of the material by considering the small quantity of material (~4 mg) [17]. As of to monitor real scale building adopted with PCM-integrated material is a complicated, expensive, and time-consuming procedure. In context to this, researchers have employed few other Fig. 1 Balancing indoor temperature by the influence of thermal mass (Source Saulles [14])

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feasible techniques in laboratory scale for investigating the thermal performance of cement composite materials. This paper refers to the review on different experimental setups used by various researchers to study the thermal aspects of PCM-admixed cementitious systems.

2 Experimental Setup for Thermal Performance Study Researchers had made use of various approaches to measure the thermal cycles/thermal storage capacity of PCM-integrated cementitious system, and majority of the researchers had incorporated differential scanning calorimeter (DSC) to analyze the thermal properties. However, an attempt has been made to assemble few different experimental procedure/set up adopted by the previous researchers to analyze the thermal property techniques [17–28]. The experimental setup used by Cellat et al. [18] in their study is a programmable thermo stated water bath [Huber CC, Fig. 2a] to measure the heating/cooling curves of PCM (butyl stearate) which was controlled by the temperature range of 5–35 °C at the rate of 1 °C min−1 . The procedure involved is stated by the authors; the test tube containing 10 ml of sample is taken and placed in water bath, and the change in temperature was recorded by the data logger at the interval of 10 s which was measured by T-type thermocouples (accuracy of ±5 °C). Authors have reported that as the lifespan of PCM is reliant on its thermal cycle stability the test was carried out by means of aforementioned experimental setup by subjecting the samples to heating and cooling cycles, i.e., initially by heating the sample above the PCM melting point and cooling below its freezing point. The sample was subjected to 1000 thermal cycles, and the thermal properties of each sample after the 200 successive thermal

Fig. 2 a Experimental apparatus to measure heating and cooling curves in water bath b heating and cooling curve of PCM (Source Cellat et al. [18])

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cycles were analyzed by means of differential scanning calorimeter (DSC). The Fig. 2b represents measured thermal cycles (heating and cooling curve). Farnam et al. [19] employed the longitudinal guarded comparative calorimeter (LGCC) to analyze the thermal response of PCM-included mortar specimens through heating and cooling activities, and to carry out this analysis authors have made use of PCM-based mortar specimens (LWA or an embedded tube form) of size 25.4 × 25.4 × 50.8 mm. Authors have stated that in order to yield the one-dimensional heat flow temperature gradient is produced in specimen and 2 m bars were used at the top and bottom of specimens with known thermal properties to examine the temperatures at different positions. Researchers had used two-stage cold plate (CascadeCCP-22, TECA, Chicago, Illinois) method by varying the specimen temperature from 24 to −40 °C (at the heating and cooling rate of 4 °C/h and −2°). It was also stated that to accomplish thermal equilibrium the constant temperature was maintained at 24 °C for 1 h and −40 °C for 4 h, then equilibrium was maitained for one test cycle (refer Fig. 3 for the LGCC heat flow curve). Authors also used low temperature differential scanning calorimeter (LT-DSC) to analyze the thermal properties of PCMs. The study by Gunasingh and Hemalatha [20] evaluated the inside variation of PCM (paraffin) modified concrete temperature by means of positioning the “Ktype” thermocouple before placing the concrete at the center and the sides of the mold (Fig. 4). Their experimental setup included the endemically fabricated digital thermometer with seven segmented LED display to measure the temperature and even the inside temperature of concrete cube. Lecompte et al. [21] in parallel to the analysis of thermal properties (latent heat, specific heat, phase change temperature) of PCM-based concrete by DSC, a hot plate apparatus (similar setup by Franquet et al. [22]) is also used as to evaluate the thermal

Fig. 3 LGCC heatflow curve for PCM-based mortars prepared from a Type 1 cement b Type V cement (Source Farnam et al. [19])

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Fig. 4 Experimental setup to measure the temperature by means of positioned K-type thermocouples (Source Gunasingh and Hemalatha [20])

responses as well as the thermal conductivity of the specimens (Fig. 5). The experimental setup consists of two cryothermostats and heating resistance (located at the hot side) and thermal guards (to ensure one-dimensional heat transfer). On monitoring the cryothermostat temperature and heating power, the hot and cold plate temperatures were kept in control. Hence, three K-type thermocouples were surrounded on the surface of plates to measure the temperature; in addition to that, hot plate was used to monitor the power dissipation through heating resistance, thereby allowing entire power transmission to the specimen. Authors had mentioned that specimen of size 13 * 13 * 2 or 5 cm3 (comprised of K-type thermocouple at the center placed during casting) was used which was sandwiched between hot–cold plates, and the temperatures were recorded via data logger as well as heat flux by means of flux meters. Fig. 5 Experimental setup for thermal response measurement (Source Lecompte et al. [21])

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Researchers had enforced several temperature levels so as to attain the stationary state and thus to characterize the thermal responses of specimens. The innovative experimental methodology used by Pisello et al. [17] involved coupling of two experimental appliances (Hot Disk thermal constant analyzer surrounded by environmental climatic chamber, Fig. 6) to investigate the influence of temperature fluctuation on PCM-admixed concrete. Researchers made use of Hot Disk appliance which utilizes [23] transient plane source (TPS) method to characterize the two identical samples of same material. Whereas, environment chamber (601 × 810 × 694 mm) is furnished with inbuilt thermocouples and solar stimulator to regulate air temperature, relative humidity, and radiative power. Double Nickel spiral (10 µm thick) plane was fastened between two identical samples (10 × 10 × 5 cm) which is employed as a heat source and dynamic sensor subjected electrical heating. While the entire sandwiched setup was covered by 10 cm thick polyurethane foam over four faces leaving the top and bottom faces to have a direct expose to controlled environment, the entire sandwiched setup was placed in environmental climatic chamber and subjected to hygrothermal cycle. The samples gets exposed to the developed variation in heat, probe temperature increases with increase in time. Fundamental thermal property mainly relies on the nature of surrounding samples. Authors stated that time-dependent resistance to electric heat sensed by hot disk sensor was measured as thermal conductivity and thermal diffusivity in addition to specific heat of the material. Niall et al. [24] employed an experimental setup to analyze the heating behavior of PCM (microencapsulated and impregnated lightweight aggregate form) incorporated concrete panels. Authors used the concrete panels of the size 200 mm × 200 mm × 200 mm (cured for 28 day and dried for extra 28 days) embedded with three thermocouples at a depth of 50 mm in addition to the thermocouples at front and rear faces of the panels in order to record the temperature by means of data logger (Fig. 7). Researchers introduced an artificial light source (Follow 1200 pro lamp) in order to imitate the heat energy transfer from natural light source (sunlight) to the exposed panel. While it is possible to regulate the wavelength of the emitted electromagnetic waves from pro lamp, in addition to this, insulated light box was fabricated to avoid the environmental effects (i.e., temperature discrepancy).

Fig. 6 Experimental arrangement a TPS sensor sandwiched between two identical concrete samples b concrete sample guarded by polyurethane foam c final experimental setup within environmental chamber (Source Pisello et al. [17])

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Fig. 7 Schematic representation of experimental setup of light box (Source Niall et al. [24])

The thermal properties characterized by Pisello et al. [17] of PCM-admixed concrete composites made use of in-lab analysis tool which included (a) Solar spectrophotometer and integrating sphere (Shimatzu SolidSpec-3700) in accordance to ASTM E1980–11 [29] was employed to analyze the variation in concrete optical surface finishing corresponding to the presence of PCM (refer Fig. 8a). (b) Thermal emissometer (AE1 RD1) in accordance to ASTM C1371-04a [30] was employed to characterize the thermal properties like thermal conductivity, thermal diffusivity, and specific heat (refer Fig. 8b). Whereas, authors mention that kapton-covered flat tungsten spiral probe present in the equipment (placed in a single sided alignment) performed as a source of heat and thermometer resistance, super insulating material was placed on the opposite side of the probe, with known thermal properties imputed to the large irregularity of one side surface of the specimens. Researchers had conducted experiments at ambient Fig. 8 Experimental apparatus for thermal and optical energy analysis a solar spectrophotometer b thermal emissometer c hot disk (Source Pisello et al. [17])

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Fig. 9 Experimental setup to measure heat transfer and flow (left) and encapsulated flat plate (right, Source Zalba et al. [10])

temperature condition (i.e., at about 20–22 °C) where majority of the PCM in the composites are in liquid phase. Authors reported that the experiments were repeated for three times for each sample, and mean value is considered as the final data. (c) Hot disk method in accordance to ISO 22007-2 [31] was employed to measure the thermal conductivity (refer Fig. 8c) Zalba et al. [10] made use of a closed air experimental apparatus inbuilt with fan for air movement, heating and cooling system with ability to fix the suitable temperature of air as well as a thermal storage unit to measure the airflow and temperature; Fig. 9 (left) represents the experimental setup. Authors have reported that the experiment was carried out with the flat plate encapsulate (other than any other geometry, Fig. 9 right) for the reason that PCM heat transfer would be monitored by encapsulate thickness; melting and solidification process is uniform in corresponding to the plane at the center of the plate and fall in air pressure is less. Authors stated that by means of calibrated platinum resistance thermometers (5 nos) placed in both inlet and outlet conduits of storage unit air temperature was measured and airflow via calibrated flow meter; the complete stored data were assessed through specific software. The experimental study carried out by Borreguero et al. [25] made use of an experimental setup as represented in Fig. 10. This setup comprised of aluminum hollow metallic box (10 * 6 * 3 cm) maintained at desired temperature via constant demineralized water flow using peristaltic pump from a thermostatic bath. The aluminum cell also includes an internal diffuser plate to improve liquid distribution and to endure the same temperature. Researchers made use of 3 cm thick specimen and positioned it on top of aluminum cell which was insulated with 2 cm thick cork boards. Overall eleven K-type thermocouples were utilized as a media to measure temperatures, among which nine were placed on exterior surface of the specimen and rest two were located at the inlet and outlet borders of the cell along the liquid flow direction. The signals measured by thermocouples were recorded by means of computer using NOKEVAL program. Study was carried out in two different ways (1) absorption study—varying the set point of thermostatic bath (21–40 ± 0.1 °C) and (2)

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Fig. 10 Experimental setup to study the thermal properties of gypsum boards (Source Borreguero et al. [25])

reversibility study—cyclically varying the set point of thermostatic bath (21–36 ± 0.1 °C). Dong et al. [26] studied thermal performance of hollow special ball impregnate PCM modified concrete by making use of self-designed experimental set up (Fig. 11) were PCM concrete panels of size 200 mm × 200 mm × 40 mm was used. Selfdesigned experimental model includes a two compartment wooden box separated by an internal wooden wall with 200 mm × 200 mm × 40 mm opening. A foam-made test room was positioned within the compartment (at back) built with an internal dimension of 200 mm × 200 mm × 200 mm and internal opening similar to internal wooden wall. Whereas, the front compartment was placed with hollow reflective paper coated PVC envelope in order to develop constant and stable temperature field. Researchers had placed the concrete panel in the opening of the test room with the aid of suitable sealant (to avoid air gap). They had used four K-type thermocouples (to measure temperature) among which one was placed at the center of the test room and the other two on the external and internal surfaces of the concrete panel. Finally, the

Fig. 11 Experimental setup to measure thermal performance a constituents uses b setting up of the specimen c complete experimental setup and its top view (Source Dong et al. [26])

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Fig. 12 Transient hot-bridge experimental setup (Source Saeed [27])

fourth one is used to measure the environmental temperature and positioned within the compartment where the test room was stored. Setup also consists of heating source (500 W lamp) at 500 mm distance on the front side. The temperature changes were recorded by means of data logger during the process of heating (by lamp) the sample for about three hours and then cooling (switch off the lamp) until sample reaches an environmental temperature. The study conducted by Saeed [27] on thermal conductivity measurement of PCMadmixed cementitious samples employed Transient Hot-Bridge technique (Fig. 12). Experimental setup was equipped with a kapton-insulated sensor enforced by 105 × 42 mm metal frame. The directly inserted sensor into the sample acts as a temperature probe and source of heat. Researchers depending upon the type of PCM applied a suitable current (of 0.049 A) and measurement time (55 s). The computer connected with data acquisition unit records the data, and the software (Intuitive Windows® based software) computes the thermophysical properties like thermal conductivity, heat capacity, and thermal diffusivity. The study on thermal transmission of PCM cement composites by Jeong et al. [28] utilized the calibrated hot box method (Fig. 13) which analyzes the realistic thermal performance of building components like wall. This experimental setup consists of cold and hot chambers along with a specimen-locating panel. The temperature difference between the hot and cold boxes across the placed specimen of 20 °C was created, and the temperature was recorded once the heat flow from hot to cold system reaches constant value.

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Fig. 13 Diagram representing the plan of the calibrated hot box (Source Jeong et al. [28])

3 Conclusions The following can be concluded from the above review. Among various approaches used by the researchers to measure the thermal cycles/thermal storage capacity of PCM-integrated cementitious system, differential scanning calorimeter (DSC) is used in extent to analyze the thermal properties. The hot plate method is noticed to be the relevant and easy technique to analyze thermal conductivity. However, other alternate simple and easy setup to measure the thermal cycles is also recommended by the researchers.

References 1. Mehling H, Cabeza LF (2008) Heat and cold storage with PCM. Springer, Berlin 2. Dehdezia PK, Hallb MR, Dawsona AR, Caseyb SP (2012) Thermal, mechanical and microstructural analysis of concrete containing microencapsulated phase change materials. Int J Pavement Eng 14(5):449–462 3. Sharma A, Tyagi VV, Chen CR, Buddhi D (2009) Review on thermal energy storage with phase change materials and applications. Renew Sustain Energy Rev 13:318–345 4. Zhang Y, Zhou G, Lin K, Zhang Q, Di H (2007) Application of latent heat thermal energy storage in buildings: state-of-the-art and outlook. Build Environ 42:2197–2209 5. Ling TC, Poon CS (2013) Use of phase change materials for thermal energy storage in concrete: an overview. Constr Build Mater 46:55–62 6. Bentz DP, Turpin R (2007) Potential applications of phase change materials in concrete technology. Cement Concr Compos 29:527–532

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7. Jayalath A, Mendis P, Gammampila R, Lu A (2011) Applications of phase change materials in concrete for sustainable built environment: a review. In: Proceedings of the international conference on structural engineering, construction and management, at Kandy, Sri Lanka, 1 8. Kuznik F, David D, Johannes K, Roux JJ (2011) A review on phase change materials integrated in building walls. Renew Sustain Energy Revolut 15(1):379–391 9. Rathod MK, Banerjee J (2013) Thermal stability of phase change materials used in latent heat energy storage systems: a review. Renew Sustain Energy Revolut 18:246–258 10. Zalba B, Valverde BS, Marin JM (2005) An experimental study of thermal energy storage with phase change materials by design of experiments. J Appl Stat 32(4):321–332 11. Ricklefs A, Thiele AM, Falzone G, Sant G, Pilon L (2017) Thermal conductivity of cementitious composites containing microencapsulated phase change materials. Int J Heat Mass Transf 104:71–82 12. Hunger M, Entrop AG, Mandilaras I, Brouwers HJH, Founti M (2009) The behavior of self-compacting concrete containing micro-encapsulated phase change materials. Cem Concr Compos 31:731–743 13. Thiele AM, Sant G, Pilon L (2015) Diurnal thermal analysis of microencapsulated PCMconcrete composite walls. Energy Convers Manag 93:215–227 14. Saulles DT (2012) Thermal mass explained. The Concrete Centre 15. Tyagi VV, Buddhi D (2007) PCM thermal storage in buildings: a state of art. Renew Sustain Energy Rev 11(6):1146–1166 16. Dehdezi K, Hall MR, Dowson A (2013) Thermal, mechanical and microstructural analysis of concrete containing microencapsulated phase change materials. Int J Pavement Eng 14:449–462 17. Pisello AL, D’Alessandroc A, Fabianib C, Fiorellic AP, Ubertinic F, Cabezad LF, Materazzic AL, Cotana F (2016) Multifunctional analysis of innovative PCM-filled concretes. Sustain Energy Build Procedia 111:81–90 18. Cellat K, Beyhan B, Kazanci B, Konuklu Y, Paksoy H (2017) Direct incorporation of butyl stearate as phase change material into concrete for energy saving in buildings. J Clean Energy Technol 5(1):64–68 19. Farnam Y, Krafcik M, Liston L, Washington T, Erk K, Tao B, Weiss WJ (2015) Evaluating the use of phase change materials in concrete pavement to melt ice and snow. J Mater Civ Eng 28 20. Gunasingh KC, Hemalatha G (2017) Impact of paraffin as phase change material in concrete cubes for enhancing the thermal energy storage. ARPN J Eng Appl Sci 12(15):4424–4431 21. Lecompte T, Le Bideau P, Glouannec P, Nortershauser D, Le Masson S (2015) Mechanical and thermo-physical behaviour of concretes and mortars containing phase change material. Energy Build 94:52–60 22. Franquet E, Gibout S, Tittelein P, Zalewski L (2014) Experimental, theoretical analysis of a cement mortar containing microencapsulated PCM. Appl Therm Eng 73:30–38 23. Bo H, Gustafsson EM, Setterwall F (1999) Tetradecane and hexadecane binary mixtures as phase change materials (PCMs) for cool storage in district cooling systems. Energy 24:1015– 1028 24. Niall D, West R, McCormack S, Kinnane O (2016) Thermal mass behaviour of concrete panels incorporating phase change materials. In: Sustainable built environment conference, Hamburg, German 25. Borreguero AM, Garrido I, Valverde JL, Rodríguez JF, Carmona M (2014) Development of smart gypsum composites by incorporating thermo regulating microcapsules. Energy Build 76:631–639 26. Dong Z, Cui, Tanf W, Chen D, Wen H (2016) Development of hollow steel ball macroencapsulated pcm for thermal energy storage concrete. Materials (Basel) 9(1):59

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27. Saeed RMR (2016) Thermal characterization of phase change materials for thermal energy storage. Masters theses, 7521 28. Jeong YW, Koh TH, Youm KS, Moon J (2017) Experimental evaluation of thermal performance and durability of thermally-enhanced concretes. Appl Sci 7:811 29. ASTM E1980–11. Standard practice for calculating solar reflectance index of horizontal and low-sloped opaque surfaces 30. ASTM C1371–15. Standard test method for determination of emittance of materials near room temperature using portable emissometers 31. ISO 22007-2:2015. Plastics — Determination of thermal conductivity and thermal diffusivity — Part 2: Transient plane heat source (hot disc) method

The Behavior of Ambad Earth Dam Under Change in Water Level and Earthquake B. M. Bhosale and Rohan Deshmukh

Abstract This study presents a dynamic analysis and effect of a change in water level on a zoned earth dam subjected to earthquake motion in which pore water pressure, effective stresses, and displacements are calculated. The finite element method is used in the analysis of the Earth dam. As a case study, the Ambad dam is selected, which is located on the Ambad River in Nashik district of Maharashtra and constructed of the zoned embankment, it has a total length of 0.946 km. The height of the dam is 26.85 m. In the first case of analysis, different magnitudes of earthquakes such as 5.4 and 8.8 are considered for a period of 10 s. The second case is the change in the water level like rapid drawdown and slow drawdown conditions are considered. It is concluded that the value of pore water pressure generated at the base of the core is greater than that in the upper parts of the dam, the stress increases during the earthquake and change in water-level analysis which indicates that the soil continues to weaken during this period, the horizontal displacement increases with the depth of the point of the crest and the largest horizontal displacement will be at the base of the dam at the time of the earthquake and there is an attenuation of the acceleration to some degree depending on the amplitude of the input horizontal acceleration. To improve the stability, a factor of safety, stress and its displacement in this project use the geogrid and grouting technique. Keywords Earth dam · Earthquake · Finite elements · Geotextile · Grouting

B. M. Bhosale Department of Civil Engineering, MCOERC, Nashik 422105, India R. Deshmukh (B) Civil Engineering Department, Terna Engineering College, Nerul, Navi Mumbai 400706, Maharashtra, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_14

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1 Introduction The earthen dam is the most ancient type of embankment, as they can be constructed with the natural material with a minimum of processing and embankment dam, as defined earlier, is one that is constructedusing natural materials. Before nineteenth century earth dam is a homogeneous profile and after the nineteenth century it is constructed as a zoned profile. In its simplest and oldest form, the embankment dam was constructed with low-permeability soils to a nominally homogeneous profile. The section of the dam provides a feature like neither internal drainage nor a cut-off to restrict seepage flow through the foundation. This type of dam is not having any facility to control seepage, but there was little progress in design prior to the nineteenth century. It was then increasingly recognized that in principle, larger embankment dams required two-component elements [1]. (1) An impervious water-retaining element or core of very-low-permeability of the soil is, for example, soft clay or heavily remolded ‘puddle’ clay. (2) Supporting shoulders of coarser earth fill (or rock-fills) provide structural stability. As a further enhancement to the design, the shoulders were frequently subject to a degree of simple zoning, with finer and more cohesive soils placed adjacent to the core element and coarser fill material toward either face or in some case sand filter is also provided to minimize the seepage in dam body. Present embankment dam design practice retains both principles. Compacted fine-grained silty or clayey earth fills, or in some instances, manufactured materials, like asphalt or concrete, are employed for the impervious core element. The stability of a slope of waterfront geotechnical structures such as an earthen dam, artificial river embankment, marine bunds are dependent on its geometry, pore pressure due to change in water level, soil properties, and the forces to which it is subjected to internally and externally. The pore pressure and surface water pressure are examples of such internal and external forces that may be due to the hydrostatic and hydrodynamic effect on the slope stability. Whether a slope is partially or totally submerged, the internal and external forces that affect the slope can change as the water-level changes. As a result of the water-level change, both seepage-induced pore pressures due to transient flow and stress-induced excess pore pressures develop inside the slope [2]. Excess pore pressures dissipate over time and consolidation takes place. The rate of dissipation of excess pore pressures and a decrease in seepage-induced pore pressures depend on the drawdown rate and the hydraulic conductivity and compressibility characteristics of the slope materials and earthquake acceleration. In highly permeable soils, stress-induced pore pressures mostly dissipate during the drawdown. In soils with low-permeability, seepage-induced and stress-induced pore pressures are not likely to dissipate at the same rate with the external water-level changes; consequently, totally or partially undrained soil behavior will be observed.

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In recent years, there have been rapid developments in the fields of computational methods, software design and high speed and low-cost hardware of particular relevance to slope stability analysis are the limit equilibrium and finite element methods. However, when using limiting equilibrium methods to analyze slopes, several computational difficulties and numerical inconsistencies may occur in locating the critical slip surface (depending on the geology) and hence establishing a factor of safety [3]. In general, the most important factors for slope stability analysis are (1) The geometry of slope. (2) The material properties of the soil. (3) The forces acting on the slope. The previous study considered three different examples with homogeneous and inhomogeneous slopes taking into account the effects of (a) Rapid drawdown, (b) Undrained clay soils, (c) Earthquake effect. Nomenclature γ μ ϕ c k S u EC , ES FS |u|

unit weight of soil (kN/m3 ). Poisson’s ratio. angle of internal friction. cohesion (kN/m2 ). coefficient of permeability (m/day). undrained shear strength. Young’s modulus of core and shell, respectively (MPa). factor of safety. total hypothetical displacement.

2 Methodology The paper presents the results of finite element modeling of the stability and seepage analyses of the earth dam using PLAXIS 2D software [4]. The analysis has fully coupled effects and mainly considers the interaction between the surface water and groundwater, which forms the essential component of the coupled analysis [5, 6]. The two main parameters which were varied in the study to identify the changes in the stability of the earth dam are the change in water level and earthquake effect. The stability of the dam has been checked for the following conditions: (1) (2) (3) (4)

The rapid drawdown in 10 days duration. The slow drawdown in 50 days duration. Earthquake during the low water level of the dam. Earthquake during full reservoir level of the dam.

The primary purpose and overall safety of the dam play a vital role in the design criteria. Moreover, every design criteria must fulfill the following fundamental design aspects [7]:

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Stability of embankment and foundation under critical conditions. Control of seepage and pressure in both the embankment and foundation. Safety measures to control the overtopping situation. Erosion control methods.

However, the seepage plays one of the deciding roles for the overall safety of the dam, hence the present study is attempted to study minimize the seepage and improve the stability factor. In the present study, finite element based PLAXIS 2D software is used for the analysis purpose. The finite element model is developed and validated with the previous study [8, 9] and then the parametric study is carried out by varying the parameters like modulus of elasticity, the angle of internal friction of soil, the effect of a change in water level, the effect of an earthquake, etc. Previous researchers [10] used GeoStudio software to study the effect of varying amplitude and time of earthquake on the earthen dam. Effect of seismic analysis on the earthen dam is shown in terms of effective stress, pore water pressure, total stresses, and total displacement of the dam.

2.1 Numerical Modeling The following study is carried out by Finite Element (FE) approach with a plain strain relationship. The soil of the earth dam is modeled by using Mohr–Coulomb constitutive model; properties of the model are given in Table 1. A triangular medium mesh is generated to connect all points in the geometry. Figure 1 shows the Ambad earth dam’s Google Maps location and Fig. 2 shows the Ambad earth dam section considered in the study. Table 1 Soil properties Parameters

Unit

Casing

Model

–

Mohr–Coulomb Mohr–Coulomb Mohr–Coulomb

Foundation

Hearting

Type

–

Drained

Drained

Undrained

γ (unsaturated and saturated) KN/m3

16.5, 20.5

15.8, 17.8

15.5, 17.5

E  and μ

KN/m2

2E4, 0.33

5E4, 0.3

2.5E4, 0.3

c ,

KN/m2

15

S u

13.9

15.7

ϕ, ψ

(Degree) 26.1, 1

24.22, 5

18.77, –

K

m/day

0.01

1.00E−04

0.25

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Fig. 1 Location of Ambad earth dam (Google Maps)

Fig. 2 Cross section of dam

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2.2 Ambad Earth Dam Ambad dam is located on the downstream of the Ambad river in Ambad village. This Ambad village is located in taluka Dindori, district Nashik. Ambad dam is an example of an earthen dam. The height of the dam is 26.85 m at R.D. 946 m. The dam will store 4.825 million cubic meters of water. Total irrigation potential will be 526 ha. Control Levels Top of Dam—705.15 m. Top of Hearting—704.15 m. M.W.L—703.15 m. F.R.L—701.65 m. Sill level—688.00 m. Stripped Level—678.30 m. In this study, different flow functions were considered for each case along with the high magnitude of an earthquake such as earthquake at full (high) reservoir level of the dam, the rapid drawdown in 10 days duration, the slow drawdown in 50 days, and earthquake at the low water level of the dam. The representative earth dam which was considered for the finite element analysis was 26.85 m in height with the side slope of 1 in 2.5 and 1 in 3 on the upstream side and 1 in 2 and 1 in 2.5 on downstream sides, and 1 in 1 for hearting, with 30 m deep foundation. The high reservoir level was 25 m high along with 5 m groundwater. Suitable hydraulic boundary conditions were assigned to the upstream side, before the start of the upstream face and the last portion of the subsoil part. The finite element mesh model in Fig. 3 and in Fig. 4 and Fig. 5 shows the local magnitude of 5.4, 8.8.

Fig. 3 FEM model of Ambad dam

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Fig. 4 Earthquake data of 5.4 magnitudes

Fig. 5 Earthquake data of 8.8 magnitudes

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2.3 Soil Properties Table 1 presents the soil properties used in the finite element analysis of the earth dam. Table 2 shows the axial stiffness values of Geotextile and Grouting material.

3 Results and Discussion The results of the finite element analyses by using PLAXIS 2D are depicted in Figs. 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, and 25. Figure 6 shows the total displacement; Fig. 7 gives the variation of the normal strain and Fig. 8 shows the normal stresses in the body of an earth dam and the subsoil. Figure 9 shows deformation in the earthen dam body. Stability results are expressed in the form factor of safety (FOS) for all the cases (Figs. 10 and 18). The various cases are shown along the X-axis; various cases considered during the study are Case-(1) Full Reservoir (F). Case-(2) Empty Reservoir (E). Table 2 Geotextile and grouting properties

Identification Geotextile Grouting

Fig. 6 Total displacement

Fig. 7 Normal strain

Axial stiffness (EA) (KN/m) 800 10,000

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Fig. 8 Normal stresses

Fig. 9 Deformation of dam

Fig. 10 Graph plot for the factor of safety versus various cases (magnitude-5.4)

Case-(3) Earthquake when full reservoir with Geotextile (G1). Case-(4) Earthquake when full reservoir with Grouting (G2).

3.1 Earthquake Analysis for 5.4 Magnitude From Fig. 10, it is observed that FOS has been comparatively less for full reservoir (case 1) condition than the empty reservoir (case 2) condition. In view of this situation,

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Fig. 11 Graph plot for total displacement versus various cases (magnitude-5.4)

Fig. 12 Graph plot for horizontal displacement versus various cases (magnitude-5.4)

Fig. 13 Graph plot for vertical displacement versus various cases (magnitude-5.4)

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Fig. 14 Graph plot for shear strain versus various cases (magnitude-5.4)

Fig. 15 Graph plot for mean stresses versus various cases (magnitude-5.4)

Fig. 16 Graph plot for pore water pressure versus various cases (magnitude-5.4)

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Fig. 17 Graph plot for shear strain versus mean stresses for (magnitude-5.4)

Fig. 18 Graph plot for factor of safety versus various cases (magnitude-8.8)

Fig. 19 Graph plot for total displacement versus various cases (magnitude-8.8)

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Fig. 20 Graph plot for horizontal displacement versus various cases (magnitude-8.8)

Fig. 21 Graph plot for vertical displacement versus various cases (magnitude-8.8)

Fig. 22 Graph plot for shear strain versus various cases (magnitude-8.8)

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Fig. 23 Graph plot for mean stresses versus various cases (magnitude 8.8)

Fig. 24 Graph plot for pore water pressure versus various cases (magnitude-8.8)

Fig. 25 Graph plot for shear strain versus mean stresses (magnitude-8.8)

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seismic analysis was performed on full reservoir (case 1) condition along with the use of geosynthetic and grouting material. It is observed that FOS is increased up to 2 during seismic conditions with the use of geotextile and grouting material. From Figs. 11, 12, and 13, it is observed that for case-1 total, horizontal, and vertical displacements are 0.2, 0.187, and 0.1 m resp. for an earthquake of magnitude 5.4. Similarly for case-3 and 4, total, horizontal and vertical displacements are found to be less than 0.05 m. From Fig. 14, it is observed that the maximum shear strain of 2.57% is observed in case-1 followed by 1.26% in case-2. Shear strain is less than 0.5% for both case-3 and 4. From Fig. 15, it is observed that mean stresses are 683 kPa for case-1 and for case-3 and 4 it is less than 450 kPa.

3.2 Earthquake Analysis for 8.8 Magnitude From Figs. 19, 20, and 21, it is observed that for case-1 total, horizontal, and vertical displacements are 0.42, 0.45, and 0.32 m, resp., for an earthquake of magnitude 8.8. Similarly for case-3 and 4; total, horizontal, and vertical displacements are found to be less than 0.3 m. From Fig. 22, it is observed that the maximum shear strain of 12.5% is observed in case-1 followed by 2.3% in case-2. Shear strain is less than 2.2% for both case-3 and 4. From Fig. 23, it is observed that mean stresses are 700 kPa for case-1 and for case-3 and 4 it is less than 450 kPa.

4 Conclusions [1] FEM PLAXIS 2D software is comparatively easy and user-friendly for calculating total displacement, stresses, and active pore water pressure of an earthen dam. The factor of safety is found to be greater than 1.5 for low reservoir condition and found to be less than the stipulated values for full reservoir condition after applying the different magnitudes of earthquake on the earthen dam. [2] Use of geotextile and grouting technique in the earth dam body shows that the factor of safety increases than stipulated values for both the full reservoir condition and low reservoir condition. [3] When the various earthquake conditions are applied on the earth dam, it is found that displacement, strain, stresses, and pore water pressure are increased with respect to an increase in the earthquake magnitude. [4] By using the geotextile and grouting technique in the earth dam body, the displacement, shear strain, pore water pressure, and mean stresses of an earth dam is reduced by 50–85%, 80–90%, up to 90%, and 40–50%, respectively. [5] Use of geotextile and grouting technique gives a better result for lower magnitudes of the earthquake.

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References 1. Novak P, Moffat AIB, Nalluri C, Narayanan R (2005) Hydraulic structures, 3rd ed. Taylor and Francis. ISBN No. 0-415-25071-4 2. Mehmet MB (2007) Investigation of stability of slopes under drawdown conditions. Comput Geotech 34(2):81–91 3. Hammouri NA, Malkawi AIH, Yamin MMA (2008) Stability analysis of slopes using the finite element method and limiting equilibrium approach. Bull Eng Geol Environ 67:471 4. PLAXIS 2D (2012) Tutorial manual, Delft, The Netherlands 5. Freeze AR (1971) Three dimensional, transient, saturated-unsaturated flow in a groundwater basin. Water Resour Res 7(2):347–366 6. Zhou Y, Li W (2011) A review of regional groundwater flow modelling. Geosci Front 2(2):205– 214 7. Li GC, Desai CS (1983) Stress and seepage analysis of earth dams. J Geotech Eng ASCE 109(7):946–960 8. Athani S, Shivamanth A, Solannki CH, Dodagoudar GR (2015) Seepage and stability analyses of earth dam using finite element method. In: ICWRCOE2015 9. Shivamanth A, Athani SS, Desai MK, Dodagoudar GR (2015) Stability analysis of Dyke using limit equilibrium and finite element method. Water Resour Res 4:884–891 10. Fattah MY, Alwash HH, Hadi SA (2016) Behavior of Khassa Chai Earth Dam under earthquake excitation. Eng Technol J 34, Part (A)(15)

A Review on the Properties of Steel-Concrete Interface and Characterization Methods E. P. Sumukh, Sharan Kumar Goudar, and Bibhuti Bhusan Das

Abstract The Steel-Concrete interface (SCI) is usually regarded as the weakest region, which influences both mechanical properties and durability of reinforced concrete structures. Several researchers have well explored and defined the importance of SCI on the service life of the reinforced concrete structures as it directly affects the durability. The primary objective of this paper is to report and compare a variety of published findings and microstructural analysis on the SCI in one place which appears in reinforced concrete. The information available on the occurrence, formation, properties, various characterizing and analysing techniques of SCI are reviewed for a better understanding of microstructural properties of SCI on the hardened and durability properties of reinforced concrete. It was found that the SCI exhibits significant spatial inhomogeneity along and around as well as perpendicular to the reinforcing steel. Significant factors like quantification of porosity, porous zone thickness and actions that affect the properties of SCI like wall effect, bleeding, settlement and segregation of fresh concrete which were favourable to both initiation and propagation of corrosion are described in this paper. The influence of w/c ratio, hydration age, steel orientation and mineral admixtures on the distribution profiles of hydration products and Engineering properties of SCI is also discussed. Keywords Steel-concrete interface · Porosity · Service life · Water-cement ratio · Calcium hydroxide

E. P. Sumukh (B) · S. K. Goudar · B. B. Das Department of Civil Engineering, National Institute of Technology Karnataka, Surathkal, Mangalore 575025, India e-mail: [email protected] S. K. Goudar e-mail: [email protected] B. B. Das e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_15

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1 Introduction The interface refers to a place or an area or a point, where two or more systems with different things meet and interact with or without affecting one another. In case of concrete, there exists a number of interfaces in concrete as it is being produced by the fusing several materials of different physical, morphological and chemical characteristics. These interfaces play an important role in determining the unique behaviour of concrete. The basic ingredients used for the production of concrete are cement (less than 90 μm in size), water, fine aggregates (μm to mm in size), coarse aggregates (certain mm in size), mineral admixtures such as fly ash (20–60 μm in size), silica fume (less than 0.1 μm in size), ground granulated blast furnace slag (GGBS) (20–50 μm in size), chemical admixtures such as accelerators, retarders, water-reducing admixtures, etc. These ingredients of concrete have a different range of particle sizes, shape, texture and specific gravities (varies from 1 to 3.15), which is also one of the reasons for non-homogeneity in concrete. Because of the nonhomogeneity between different ingredients, there exists a transition zone at their interfaces and is being termed as the interfacial transition zone (ITZ) [1–5]. One of the important transition zone, that is, ITZ between aggregate and cement paste was explored extensively by the research community. However, there is another transition zone in reinforced concrete between steel and concrete which has gained the attention of researchers lately and is widely called as Steel-Concrete interface (SCI). The SCI plays an important role in determining the mechanical and durability properties of reinforced concrete [5–9]. The Steel-Concrete interfacial zone is also defined as a region between steel and concrete with a slightly higher water to cement ratio, and eventually a higher porosity than the bulk paste due to the wall effect. It was also reported that there is a discontinuous layer of Ca(OH)2 present at the vicinity of Steel-Concrete interface [6, 8–12]. Page [6] in 1975 was the first person to document the existence of a dense Ca(OH)2 layer at the Steel-Concrete interface which acts as the physical barrier for corrosion initiation. The Ca(OH)2 at the vicinity of SteelConcrete interface is helpful in maintaining the pH value at a relatively higher level. Even though the Steel-Concrete interface has relatively high pH still, it is regarded as the weakest region, which influences both mechanical properties and durability of reinforced concrete structures [12–14]. Previously, it was believed that the characteristics at aggregate-cement paste interface and Steel-Concrete interface are considerably the same [5, 8]. But the recent developments in microstructure studies revealed that ITZ properties around the aggregates-cement paste interface, ITZ properties at Steel-Concrete interface and bulk cement paste differs significantly [8]. In the literature, it was observed that some of the researchers designated the interface between steel and concrete as ‘steelcement paste’ interface even though the aggregates were part of the concrete in their research investigation [8, 13]. The researchers did not mention the reason for designating the interface as ‘steel-cement paste’ interface. The authors feel that one of the possible reasons may be adhesion of cement paste to the stationary reinforcement bars in freshly compacted concrete because of the higher specific gravity of cement

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paste when compared to aggregates. The SEM images reported by many researchers reveal that the aggregates are not present within a few micrometre distance (0–40 μm) from the steel surface [5, 8, 12]. The porous nature of cement paste (up to a certain micrometre distance) at the SCI is often being referred by the research fraternity as the porous zone thickness [6–9, 12, 14]. The porosity at SCI, which is being measured as porous zone thickness (PZT) plays an important role in determining or forecasting the remaining service life of reinforced concrete structures in aggressive exposure conditions. Hence, a clear understanding of properties of SCI is need of the hour. There is a great deal of variability in reporting the properties of SCI such as measurement of PZT and hydration products near the interface. A systematic and detailed characterization of SCI is missing in the literature despite the efforts of a few researchers. Hence, the present work aims to report the published findings of the properties of SCI and characterization methods of SCI of reinforced concrete.

2 Significance and Importance of SCI Porosity or PZT at the SCI is a prime factor in forecasting the time required for corrosion initiation to corrosion cracking [8, 15–17]. Prediction of time to corrosion cracking is a key element in evaluating the service life of corroded reinforced concrete (RC) structures. For predicting the time to initial cover cracking, many recent theoretical models have introduced the porous zone thickness at the SCI as one of the important parameters. Tuutti [18] in 1980 proposed a theoretical model to predict the service life of reinforced concrete structures, which did not include the PZT parameter around the SCI. The proposed model is shown in Fig. 1. According to Tuutti’s model of service life prediction, the service life of a structure has two stages of corrosion degradation. The first stage of deterioration is corrosion initiation period (To ). During this period, the penetration of CO2 or chloride ions from the outside environment into the reinforced concrete structure takes place. These ions dissolve in concrete pore solution, also migrate through voids, cracks, and crevices of concrete and finally reach the SCI. Because of higher water to cement ratio at the SCI, moisture and oxygen supply will be abundant compared to bulk concrete which triggers the initiation of corrosion process [19]. The second stage was called as propagation period (Tcr ). Soon after the corrosion initiation, the corrosion products start to exert an expansive pressure on the concrete. As the expansive pressure exceeds the tensile strength of concrete, concrete cracking process begins which was considered as the end of service life of structures. It was observed that the actual service life of structures was considerably more than the predicted ones by Tuutti’s service life prediction model. This confusion led the researchers to investigate the SCI properties especially the PZT. Page and Treadaway [20] in 1982 reported the existence of a porous zone at the SCI. The concept of PZT at SCI was incorporated by Weyers [21] in 1998 and proposed a three-stage model for service life prediction as shown in Fig. 2. In which the

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Fig. 1 Tutti’s service life prediction model of corroded structures [18]

free expansion zone in between corrosion initiation and propagation period was introduced. In the modified service life prediction model, the propagation period, Tcr , was separated into two different periods. The first one is the free expansion period, Tfree , represents time to fill corrosion products in the porous zone adjacent to the corroding steel reinforcing bar. The second period, Tstress , represents the time in which the corrosion products exerts an expansive pressure on the surrounding concrete as the porous zone was already filled. It was proposed that some amount of corrosion products formed after corrosion initiation migrates away from the reinforcing steel through voids and crevices in the concrete and some corrosion products fill the porous zone at SCI. During this period no expansive pressure was exerted on the concrete surface, but once these pores in porous zone were completely filled by the corrosion products, further formation of corrosion products imparts expansive pressure on the concrete surface. This model assumes that with the increase in the volume of corrosion products the expansive pressure also increases linearly. This induces the tensile stresses inside the concrete. When it exceeds the tensile strength of concrete, cover cracks were generated. Once the cracks were generated, the expansive pressure exerted by corrosion products on the surrounding concrete cannot be quantified as they may discharge out from these

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Fig. 2 Three-stage service life prediction model proposed by Weyers [21]

cracks. So the generation of a cover crack in concrete represents the end of service life of the corroded reinforced concrete structures. Figure 3 shows a schematic diagram of the corrosion-cracking process as proposed by Weyers 1998. This modified service life prediction model was brought up with certain assumptions to formulate the internal radial pressure, which occurs due to the expansion of corrosion products. The basic assumption was about the expansive stresses around the steel bar was due to the uniform development of corrosion products around the steel reinforcing bar. Several models on volume expansion by corrosion [21–23] were proposed by using this assumption. But in general, the development of corrosion products around the steel reinforcement bar was not uniform as the extent of corrosion varies around the steel reinforcing bar. This variation in corrosion is mainly due to nonuniform surface exposure of steel bar to the corroding environment. Bazant [22] in 1979 suggested a mathematical model to measure corrosion initiation and corrosion-cracking time, based on Weyers’s three-stage service life prediction model [21] by considering the rate of corrosion, cover depth, steel reinforcing bars spacing, steel reinforcing bar diameter and concrete properties such as tensile strength, modulus of elasticity, Poisson’s ratio and creep coefficient. From these findings, Liu and Weyers [24] in 1998 proposed a mathematical model wherein mass loss rate of corroding steel and time to fill the porous zone around SCI before exerting the

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Fig. 3 Corrosion and cracking process [21]

expansive rate of corroding steel and time to fill the porous zone around SCI before exerting the expansive pressure were considered. Rate of corroding steel and time to fill the porous zone around SCI before exerting the expansive pressure were considered. For predicting the remaining service life of structures, a constant value of PZT was being assumed without any experimental investigation. Liu and Weyers [24] assumed the occurrence of 12.5-μm-thick porous zone and Petre-Lazar et al. [25] assumed 40-μm-thick porous zone around steel bar for modelling and testing purpose. It is also observed that a thickness of 40 μm has been adopted by many others too [15, 16, 22, 24–26] without any further experimental verification. It was also observed that a uniform distribution of PZT around the steel bar was assumed by all the previous researchers for assessing the service life prediction models [15, 16]. The recent developments in the microstructure study of SCI reveal that PZT varies from point to point along the length of reinforcing steel [8, 9, 11, 14]. Thus, assuming a steady value of PZT and uniform distribution of PZT for all kinds of concretes in modelling seems to be an oversimplification. Also, the physical condition of the Steel-Concrete interface is considered as an important factor while dealing with the chloride threshold, which in turn influences the prediction of the service life of RC structures [27]. Hence, systematic characterization and understanding about the porosity or PZT at the SCI is one of the crucial phenomena in assessing the service life of existing structures in chloride-laden environment. A slight variation in considering the porous zone

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thickness in service life prediction models leads to misinterpretation of the actual service life of RC structures. Thus, characterizing the SCI has gained the attention among the research fraternity in assessing the primary reason for the corrosion initiation, reduction in bond strength, assessing chloride threshold and modelling the remaining service life of RC structures in the chloride-laden environment.

3 Nomenclature of Steel-Concrete Interface The SCI can be classified into two main parts, one part being associated with steel and the other part being concrete. The steel part of SCI includes bulk core steel in the inner surface and towards the periphery of steel, passive film, mill scale and pre-existing native rust layers are developed on the surface of reinforcement bar. The steel part of SCI is not been discussed in the present paper as it has been discussed in previous research articles [8, 12, 13, 28–31]. The main focus of this review paper is on the concrete part of SCI, which plays an important role in service life prediction of reinforced concrete structures [5, 12, 15, 16, 24–26, 32]. The concrete part of SCI can be further divided into two zones. The zone adjacent to steel is porous concrete due to the voids in the interface and this zone is being named as porous zone [6–9, 12, 14, 33]. The area which occurs next to the porous zone after several micrometre distances from steel surface is known as bulk denser concrete region [7–9, 34, 35]. Due to the induced stresses, there is a chance of separation of concrete from the steel surface called as slip or separation. Some amount of cracks may occur in the concrete part of SCI, which helps in the ingression of harmful ions towards the surface of the steel. Red dashed lines as presented in Fig. 4 indicate preferential pathways for chloride ingress and blue dots represent adsorbed water (only shown for large pores). In between steel part and concrete part of SCI, there exist larger voids which may contain bleed water zone, larger pores, etc. Sometimes, a small amount of concrete gets attached to the steel surface called by the term concrete splatter.

4 Why the SCI Is Porous? It is now well understood that the SCI is porous and few researchers explained the occurrence of porous ITZ between steel and concrete. When the cement paste comes in contact with stationary reinforcement bar, the cement particles tends to separate from the cement paste because of the shearing forces and this phenomenon is widely recognized as the ‘wall effect’. This action forms a narrow region around the reinforcement bar with fewer cement particles and more water. Thus, water to cement ratio at the SCI was higher compared to the bulk concrete. The higher water to cement ratio and fewer cement particles at the SCI creates the porous zone [8]. Scrivener et al. [36] reported the phenomenon of wall effect on the basis of particle

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Fig. 4 Schematic illustration of steel-concrete interface (SCI) [31]

size distribution and packing of various components of concrete against the larger solid surface as shown in Fig. 5. According to this mechanism, the concrete grains or aggregates were having their own size and shape. When the aggregates come in contact with large solid surface (such as reinforcement bars), the aggregates would not cut their surface against the stationary and solid surface. During compaction, the large aggregates move away from the solid surface because of the shearing forces. Only smaller grains or aggregates remain near the interface. In a normal concrete, around 20–30% of the cement paste accumulates in the ITZ adjacent to the reinforcing steel bars. The cement particles in cement paste move away from the interface during compaction, due to which a large amount of water accumulates at the interface. The w/c ratio was significantly higher in the interface compared to that of bulk denser concrete. The high water content causes the porous nature of the SCI. Also, the grading of cement particles plays an important role in the process of hydration at the interface. At any given time of hydration, the reacted thickness of any cement grain is approximately the same. During the early ages of hydration, the smaller cement grains as well as the outer surface of the larger cement grains

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Fig. 5 Illustration of the wall effect [36]

react first. Thus, the inner core of the larger cement grains remains unreacted and coarser. As a result of all these, the hydration products and smaller cement grains are accumulated near the steel surface and the larger anhydrous material moves away from the interface due to the wall effect. Wall effect can be reduced by varying the gradation of concrete ingredients. The addition of finer materials such as mineral admixtures/fillers can make the ITZ denser, provided the particle size of fillers should be smaller than the cement particles [9]. Some of the researchers reported that the casting direction also has an impact on the porosity of SCI. For example, in horizontally placed reinforcement bars (such as beams), the casting was done from the top side or in other words perpendicular to the horizontal reinforcement [8, 11]. In such cases, bleeding occurs beneath the horizontal bars. The heavier solid particle settles downwards and the free water rises upwards during compaction. This free water moves upwards until it gets trapped below the horizontal reinforcement, which ultimately becomes a void once the water evaporates [5, 8, 9]. As a result of increased w/c ratio, the plastic viscosity increases which enhance the bleeding and reduce the concrete quality around the bottom area of horizontal reinforcement. Some of the researchers reported that the voids or gaps were in the order of millimetres. The voids under the horizontal bars can be seen in Fig. 6. The accumulation of bleeded

Fig. 6 Void formation below the horizontal bars [11]

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Fig. 7 Water accumulation pattern beneath the horizontal bar [9]

water on the underside of the horizontal cast reinforcement bar can be described by a mechanism proposed by Kenny and Katz [9]. According to this mechanism, the bleed water continues to rise upwards and accumulates under the horizontal reinforcement bar up to some extent. Then this accumulated bleed water finds a way up along the sides of the reinforcement bar by breaking the water-filled zone under the steel bar as shown in Fig. 7. This upward movement of bleed water empties the water-filled void below the horizontal bar and reduces its thickness. This upward movement of bleed water continues to rise until the hydration products prevent this movement. Once the hydration products terminate the upward movement of bleed water, the final size of the void is determined, and remains unchanged after this. According to this mechanism, the void size is independent of the volume of bleed water and the rheological properties of the mix like viscosity determine the void size before and after rising of water. The bleeding induced voids have a crescent shape or more elongated nature, which helps them to gain a better contact area with the reinforcing bars compared to air voids [31]. Water filled in bleeding induced voids were gets emptied on drying and chemical shrinkage. Emptied bleeding induced voids can be refilled by water on wetting. Accumulation of bleed water not only exists below horizontal casted bars but also takes place in between indentation on steel bars, under cover blocks, tie wires, reinforcement bar intersection junction in the reinforced concrete [31].

5 Properties of SCI As the steel-concrete interface is referred to as the weakest zone in the reinforced concrete structure, their properties are ones which decide mechanical and durability properties of reinforced concrete structures. With limited information, it is often assumed that the steel-concrete interface has a similar property as the interfacial transition zone, which is the interface between cement paste and aggregates. However, recent developments showed that the properties of SCI and ITZ of aggregate-cement paste interface are different from each other [5, 8, 9]. The properties of SCI that are being referred are porosity or PZT, hydration products such as calcium hydroxide,

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CSH, and unhydrated cement particles. The variation in porosity or PZT reported by a few previous researchers were reported systematically. Also, the hydration products formed at the SCI are discussed.

5.1 Porosity Porosity is the quality of the material being porous, or completely filled with tiny holes. It is the open empty spaces between grains or trapped in grains in a microstructure. The occurrence of small tiny openings or spaces within a material is known as porosity. Porosity has a much higher importance in the case of SCI as it is regarded as the weakest zone in the reinforced concrete structure. Porosity in the SCI arises due to the bleeding-induced defects, shrinkage and poor packing of cement grains against the reinforcing steel bars [8, 11, 13]. The packing of cement grains during the early ages of cement hydration leaves more porous zone around the reinforcing steel. Hydration products that precipitate within the porous zone is mostly the calcium hydroxide which tends to fill the voids in the porous zone and reduces porosity [11, 37]. But even in later stages of hydration, the porosity in the ITZ is still significantly more than bulk denser concrete [38], which is mainly due to the wall effect and bleeding induced defects [8]. Due to wall effect, smaller grains are accumulated at SCI. During the first day of hydration, porosity at the SCI is about 85% more than that of bulk denser concrete. It was reduced as hydration proceeds and during later ages, the percentage reduction in porosity is the same in both SCI and bulk denser concrete due to preferential precipitation [37]. Around the vertically cast reinforcement bars and the top side of the horizontally cast reinforcement bar, the precipitation of Ca(OH)2 was found to be 5 μm distant from steel surface, whereas 40 μm distant porous zone was found in the underside of the horizontal reinforcement bar [8]. Thus, the voids which remain unfilled became a permanently porous region which contributes to corrosion initiation and reducing mechanical and durability properties of concrete [8]. The porosity of the reinforced concrete also reduces after corrosion initiation due to the filling of corrosion products within the pores [12, 32]. These corrosion products initially fill the porous zone at SCI. Once these porous zones are completely filled, corrosion products start inducing expansive pressure on concrete which leads to the formation of cracks. Some of the corrosion products also tend to migrate outside through the radial cracks and exerts spalling pressure by filing the cracks [14]. Carbonation in the concrete also reduces the porosity at SCI slightly by filling the pores with carbonation product (CaCO3 ) [39]. But still, the porosity of ITZ was more than the bulk denser concrete zone. This is due to the higher initial porosity of SCI and the carbonation products largely precipitates in the cracks, pores and aggregate-cement paste ITZ when compared to that in SCI [39]. The bar geometry like ribs shape, size and indentations on the ribs have a certain influence on the properties of SCI by imparting bleeding-induced voids below the horizontally cast bars which affect the overall porosity [8, 9, 31].

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The orientation of reinforcement of bars such as vertically cast (columns) and horizontally cast (beams) members also has an influence on porosity of SCI. The ITZ properties around horizontally cast members and vertically cast members are not the same [8, 9]. A uniform and dense concrete (less porous) is usually found around the vertically cast members. Whereas in the case of horizontally cast members, two different zones, namely, upper and lower zones exist. The upper zone occurs above the reinforcement bar which is quite denser and similar to the ITZ properties around the vertically cast reinforcement bar. The lower zone occurs on the underside of the reinforcement bar which is more porous and has very low density [8, 9, 31]. Usually, a circumferential void is formed underneath the bottom half of the steel reinforcement bar that largely affects the durability properties of SCI. This void separates the steel and concrete along the bottom side of the reinforcement bar [7]. The w/c ratio of the mix also determines the extent of porosity at the SCI. The porosity of SCI increases with an increase in w/c ratio [5, 8, 13]. For a concrete of 0.49 w/c ratio, the porosity at the SCI was approximately 30%, whereas, in case of bulk concrete, approximately 8% porosity was found after the first day of hydration. Even after 7 days of hydration, the porosity adjacent to steel was more than the bulk concrete [8]. For a concrete of 0.7 w/c ratio, the porosity at the SCI was approximately 50% and at the same time porosity of bulk concrete was 12%. Similar kind of observations on the effect of w/c ratio was reported by several researchers [5, 9]. The porosity of the SCI is usually about twice or thrice the porosity of bulk denser concrete [38]. Few researchers have experimentally determined the percentage porosity at the SCI and are presented in Table 1. The effect of w/c ratio and effect of supplementary cementitious material (SCM) on the porosity of SCI can be understood from Table 1. The percentage porosity at the SCI and w/c ratio is directly proportional, as the w/c ratio increases porosity at the SCI also increases. It can be observed that the top side of horizontally cast reinforcement bars and vertically cast reinforcement shows similar porosity values at the SCI. Significant variation of percentage porosity was noticed for the bottom side of horizontally cast reinforcement bars. Kenny and Katz [9] reported that the porosity found beneath all horizontal reinforcement bar was 1.0 or very close to this value only mixes with a w/c of 0.52 and higher powder contents had a somewhat lower porosity of 0.8–0.9. The porosity above horizontal reinforcement bars and around vertical reinforcement bars ranged from 0.15 to 0.52 and from 0.24 to 0.46, respectively. The SEM images showed 0.5–2 mm voids below the horizontally cast reinforcement bars. Few researchers reported the effect of the addition of SEM’s on the percentage porosity of SCI. These reported values of SEM’s on the porosity of SCI may not be conclusive, as very few reported findings were available. A systematic approach to the effect of SEM’s on the properties of SCI is missing in the literature. Due to the addition of SCM’s, a significant reduction in percentage porosity was noticed at the SCI [7, 11]. The pozzolanic reaction due to the addition of SEM’s was predicted to be the reason for the reduced percentage porosity at the SCI [7].

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Table 1 Reported data on percentage porosity at the steel-concrete interface References Zayed [7] Soylev and Francois [11]

w/c ratio

Filler/SCM

0.45

–

–

30

22

0.45

Silica fume

10%

19

08

0.75

–

–

19

0.53

–

–

16

0.6

Limestone filler

140

16.5

0.39

–

–

15

0.39

Silica Fume

30

10

Horne et al. [8] 0.49 Kenny and Katz [9]

Filler/SCM (%)

Porosity at SCI (%) Horizontal

Vertical

Horizontal (Top)

Horizontal (Bottom)

Vertical

–

–

5

45

7

0.7

–

–

9

85

23

0.4

Powdered CaCO3

0

0.48

1

0.34

0

0.16

0.96

0.46

0.45

4

0.52

0.96

0.4

0.45

8

0.39

1

0.41

0.45

12

0.23

1

0.24

0.45

16

0.29

0.99

0.31

0.45

20

0.49

1

0.28

0.47

0

0.15

1

0.35

0.52

8

0.21

0.97

0.46

0.52

12

0.22

0.8

0.35

0.52

17

0.2

0.92

0.36

0.55

0

0.21

0.99

0.3

0.6

0

–

–

0.33

0.65

0

0.15

0.9

0.3

0.44

SCM supplementary cementitious material, w/c water to cement ratio

5.2 Porous Zone Thickness at Steel-Concrete Interface Some of the researchers reported the porosity at SCI in terms of porous zone thickness (PZT). The PZT was considered as an influencing and important parameter in service life prediction models [15, 24, 26, 32, 40]. Few researchers assumed the PZT while predicting the service life of structures in service life prediction models without any experimental investigations [24, 25]. Thoft-Christensen [26] suggested that the thickness of the porous zone was in the range of 10–20 μm and assumed 12.5 μm porous zone thickness for the service life prediction modelling. Liu and

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Weyers [24] also developed a mathematical model for the service life prediction of a structure by assuming 12.5 μm of porous zone thickness. Assuming the PZT without experimental investigation may lead to the misinterpretation of the service life of structures. Due to the developments in the microstructure study of SCI, several researchers experimentally measured the PZT at SCI by image analysis. Horne et al. [8] measured the PZT at the SCI by doing image analysis of BSE images. Only two locations, the top and bottom sides of the steel, are quantitatively analysed in their study. One or two locations around the SCI were measured by other researchers also [7, 11, 41]. This appears to be inadequate to represent the whole steel-concrete interface around the steel bar. A thorough quantitative measurement should be conducted for the entire interface area around the steel. Only two researchers Chen et al. [5] and Kenny and Katz [9] measured the PZT all around the SCI which helps to understand the variation in PZT around the entire interface. This kind of measurement of PZT all around the SCI is the need of the hour. In this regard, few researchers have experimentally determined the PZT at SCI and are presented in Table 2. The effect of w/c ratio and effect of supplementary cementitious material (SCM) on the PZT of SCI can be understood.

5.2.1

Influence of w/c Ratio on the Porous Zone Thickness (PZT)

The reinforcement bar orientation plays an important role. The PZT of vertically cast members and horizontally cast members varies significantly. There are two distinct zones for horizontally cast members, namely, horizontal top (H-Top) and horizontal bottom (H-Bottom). The variation in PZT with respect to w/c ratio of horizontal top and horizontal bottom as reported by research fraternity is presented in Fig. 8 and Fig. 9, respectively. The variation in PZT with respect to w/c ratio of vertically cast members is presented in Fig. 10. The data of PZT and w/c ratio in Figs. 8, 9 and 10 were extracted from Table 2. It is difficult to come to a common conclusion as different researchers reported different values of PZT for a similar w/c ratio. Leaving some extreme values, it can be noticed that w/c ratio and PZT are directly correlated. PZT at SCI increases as w/c ratio increases. In most of the observations, the PZT around the vertically cast reinforcement bar and above the horizontally cast reinforcement bar shows almost similar values. The bottom side of the horizontally cast reinforcement bar has PZT in the order of several hundred micrometres to a few millimetres range.

5.2.2

Influence of Adding Supplementary Cementitious Materials (SCM) or Fillers on Porous Zone Thickness

The beneficial effects of adding supplementary cementitious materials (SCM) or fillers on the microstructure properties of bulk concrete were known to us. The SCM’s also displayed a reduction in porosity of ITZ between aggregate-cement paste interfaces [36]. However, very few articles were reported the effect of SCM’s

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Table 2 Reported data on porous zone thickness at steel-concrete interface References

Zayed [7]

w/c ratio

Filler/SCM

Filler/SCM (%)

PZT (μm) Horizontal top (H-Top)

Horizontal bottom H-Bottom)

Vertical

0.45

–

–

50

50

50

0.45

Silica fume

10

35

35

40

Zhu et al. [42]

0.35

–

–

10

50

15

Liu and Weyers [24]

0.35

–

–

12.5

12.5

12.5

Christensen [26]

0.35

–

–

10

10

10

0.4

–

–

20

20

20

Zhu et al. [43]

0.43

–

–

35

60

–

0.36

GGBS

60

30

50

–

Zhu et al. [44]

0.36

GGBS

60

30

50

–

0.68

–

–

40

70

–

Horne et al. [8]

0.49

–

–

15

65

20

0.7

–

–

25

165

35

Mondal and Shah [45]

0.35

–

–

20

20

20

0.5

–

–

100

100

100

Wang et al. [17]

0.3

Silica fume

10

80

95

87

0.3

–

0

90

105

98

0.5

–

0

107

125

114

Yuan and Ji [41]

0.6

–

–

87

104

95

Angst et al. [31]

0.55

–

–

–

140

–

0.6

–

–

–

150

–

Biniam [46]

0.4

–

–

17

44

18

0.5

–

–

20

69

21

Zhao et al. [47]

0.44

–

–

65

118

–

Kenny and Katz [9]

0.40

Powdered CaCO3

0

30

268

112

0.44

0

45

280

79

0.45

4

88

245

89

0.45

8

129

299

113

0.45

12

114

311

136

0.45

16

74

287

84

0.45

20

87

304

76

0.47

0

94

320

109 (continued)

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Table 2 (continued) References

w/c ratio

Filler/SCM

0.52

Chen et al. [5]

Zacharda et al. [34]

Filler/SCM (%)

8

PZT (μm) Horizontal top (H-Top)

Horizontal bottom H-Bottom)

Vertical

81

288

135

0.52

12

77

226

118

0.52

17

85

186

85

104

264

117

0.55

0

0.6

0

0.65

0

54

296

110

88

0.5

–

–

21.5

37

–

0.45

–

–

10

19

–

0.4

–

–

9.5

15

–

0.4

–

–

40

40

40

SCM supplementary cementitious material, w/c water to cement ratio 130 120

Kenny and Katz 2015 Horne et al. 2007 Chen et al. 2018 Zhu et al. 2004 Zhu et al. 2000 Zhao et al. 2013 Yuan and Ji 2009 Biniam 2011 Christensen T. P. 2000 Mondal and Shah 2008 Liu and Weyers 1998 Wang et al. 2009 Zhu et al. 1997

Porous zone thickness (um)

110 100 90 80 70 60 50 40 30 20 10 0

0.3

0.4

0.5

0.6

0.7

0.8

0.9

w/c ratio

Fig. 8 Variation in the porous zone thickness and w/c ratio of the top side of horizontally cast reinforcement bar (H-Top)

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340 Kenny and Katz 2015 Horne et al. 2007 Chen et al. 2018 Zhu et al. 2004 Zhu et al. 2000 Angst U 2011 Zayed 1991 Zhao et al.2013 Yuan and Ji 2009 Biniam 2011 Christensen. T.P. 2000 Mondal and Shah 2008 Liu and Weyers 1998 Wang et al. 2009 Zhu et al. 1997

320 300 280

Porous zone thickness (um)

260 240 220 200 180 160 140 120 100 80 60 40 20 0

0.3

0.4

0.5

0.6

0.7

0.8

0.9

w/c ratio

Fig. 9 Variation in the porous zone thickness and w/c ratio of the bottom side of horizontally cast reinforcement bar (H-Bottom) 130 120

Kenny and Katz 2015

110

Horne et al. 2007 Zayed 1991

Porous zone thickness (um)

100

Yuan and Ji 2009

90

Biniam 2011

80

Christensen T. P 2000

70

Mondal and Shah 2008 Liu and Weyers 1998

60

Wang et al. 2009

50

Zhu et al. 1997

40 30 20 10 0

0.3

0.4

0.5

0.6

0.7

w/c ratio Fig. 10 Variation in the porous zone thickness and w/c ratio of vertically cast reinforcement bar

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on the properties of SCI especially the PZT. It can be observed from Table 2 that the addition of SCM does reduce the PZT at SCI, irrespective of reinforcement bar orientation in the reinforced concrete. However, the bottom side of horizontally cast reinforcement bars showed the least reduction in PZT due to the addition of SCM’s. It was also noticed that a higher dosage of SCM’s/filler has a better effect towards the reduction in PZT of SCI. As only a few countable reported findings were found on the effect of SEM’s on PZT, a systematic investigation is need of the hour.

5.2.3

Effect of Surface Texture of Reinforcement Bar on the Porous Zone Thickness

The surface of the reinforcing steel bar has ribs all over its length. The presence of indentations on the steel bars, reinforcement bar intersection junction, usage of cover blocks, tie wires causes the bleed water to store below them which in later stages forms the empty voids [31]. The ribs on the steel surface also have the same impact on the porous zone thickness. Along the ribs of the steel reinforcement bars at SCI, the presence of the porous zone is comparatively more with larger thickness. It was also observed that the thickness of the porous zone is larger in the zone adjacent to the curved face of the ribs (59.8 μm) when compared to that of two parallel sides of the ribs (17.1 μm) [5]. The PZT or voids at the ribs can also be influenced by the sample preparation methods such as, speed of cutter and polishing standards. Chen et al. [5] was the only author who reported the variation in PZT at the ribs. Figure 11 shows the voids or porous band at the rib of SCI.

5.3 Hydration Products at SCI 5.3.1

Calcium Hydroxide

During the hydration of cement, the bulk concrete undergoes microstructural development by hydration products. Calcium silicate hydrate gel (C–S–H gel) and calcium hydroxide denoted by Ca(OH)2 or CH are the two major products that are formed [8, 36]. These two hydration products strongly determine the physical, mechanical and durability properties of concrete. The ITZ properties around the aggregatescement paste interface, ITZ properties at steel-concrete interface and bulk cement paste differ significantly due to the variation in the formation of hydration products [7, 8]. Very few research articles report the variation in hydration products around the SCI. Baumel [48] in 1959 and Page in 1975 [6] and 2009 [19] confirmed the existence of a lime-rich and dense layer of calcium hydroxide at the SCI. Horne et al. [8] proposed an explanation for the enriched quantity of calcium hydroxide at the SCI. When the cement paste comes in contact with the stationary reinforcement bar, the cement particles tend to separate from the cement paste because of the shearing forces, forming a narrow region around the reinforcement bar with fewer cement

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Fig. 11 Porous band around the rib at the SCI [5]

particles and thus more water. The high water content and few cement particles around the reinforcement bar forms a distinct area into which calcium ions (Ca2+ ) formed by the reaction of anhydrous cement diffuses from outside the interface area to form regions enriched in calcium hydroxide. The calcium hydroxide at the vicinity of SCI is helpful in maintaining the pH value at a relatively higher level which acts as a physical barrier for corrosion initiation [19]. It was observed that the calcium hydroxide was more in the interface region adjacent to both vertically cast and horizontally cast reinforcement bars (over 5 μm distance from the steel surface) when compared to that of bulk denser concrete. Around 18% more calcium hydroxide was observed around the SCI even after 365 days of hydration when compared to bulk concrete [8]. Microstructural analysis confirms that there was no continuous or uniform layer of calcium hydroxide at any distance from the interface [8]. The w/c ratio also pose a significant impact on the concentration of calcium hydroxide at the SCI. Due to the bleeding-induced defects under the horizontally cast reinforcement bars, w/c ratio at the interface increases, which reduces the calcium hydroxide concentration. It was observed that the quantity of calcium hydroxide at the SCI decreases by about 11% when the w/c ratio increases from 0.49 to 0.7 [refer Figs. 14 and 15]. The properties of the SCI above the horizontally cast reinforcement bar were almost the same as that of vertically cast reinforcement bars under the same w/c ratio. But the degree of reaction on the top side of horizontally cast reinforcement

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Fig. 12 The distribution of calcium hydroxide in plain and silica fume admixed concrete at different distances from the steel surface [7]

Fig. 13 Effects of silica fume on the nature of the transition zone in specimens cast normal to the reinforcement axis. a porosity profiles b unreacted cement profiles [7]

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Fig. 14 Microstructural gradients in the interfacial region between cement paste and the topside (left) and bottom side (right) of horizontally cast steel at four ages in concrete with a w/c ratio of 0.49: a calcium hydroxide, b porosity, c unreacted clinker phases, and (d) undesignated hydration products (mainly C–S–H) [8]

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Fig. 15 Microstructural gradients in the interfacial region between cement paste and the topside (left) and bottom side (right) of horizontally cast steel at four ages in concrete with a w/c ratio of 0.70: a calcium hydroxide, b porosity, c unreacted clinker phases, and d undesignated hydration products (mainly C–S–H) [8]

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bar was lesser than that of vertically cast reinforcement bars due to the lesser availability of water. As a result of this, the calcium hydroxide distribution on the top side of the horizontally cast reinforcement bar was lesser than the vertically cast reinforcement bars [8]. The microstructure below horizontally cast reinforcement bar was significantly different and non-comparable with the top side of horizontally cast reinforcement bar. It was mainly affected by the bleeding induced defects, where larger voids (in the range of several hundred micrometres) filled with bleed water zones were observed [31]. These bleed water zones had a higher degree of reaction and a large quantity of calcium hydroxide precipitation was noticed [8]. The addition SCM’s showed a better distribution of the cement grains in addition to filling the available space between the cement grains. The calcium hydroxide distribution at the SCI was significantly reduced due to the addition of silica fume [7]. The distribution of calcium hydroxide in plain and silica fume admixed concrete at different distances from the steel surface can be observed in Fig. 12. For plain and silica fume concrete, the calcium hydroxide distribution profile at the SCI showed the same general trends with a reduction in the amount of calcium hydroxide from 15% in plain mixes to about 5% in silica fume admixed concrete (Fig. 13).

5.3.2

Unhydrated Particles Oranhydrous Cement Particles

The origin of ITZ occurs mainly due to the packing of the anhydrous cement grains [36]. During the hydration of cement particles, the grading of cement particles plays a vital role in the packing of hydration products. As explained before (in Sect. 4) the anhydrous cement particles largely occur in the bulk denser concrete and their degree of reaction is lesser in the early ages of hydration. The width of the zone with anhydrous cement particles decreases as hydration proceeds and at greater ages, almost all the anhydrous cement particles hydrate forming a bulk denser concrete around the ITZ [36]. The amount of anhydrous cement particles reduces as the hydration proceeds at greater ages throughout the bulk denser concrete. Lesser distribution of anhydrous cement particles was observed close to SCI [7, 8]. The anhydrous cement particle distribution gradually increases with the increase in the distance from the steel surface. The reinforcing bar orientation and the water-cement ratio also has some impact on the concentration of anhydrous cement particles. It was observed that the degree of reactivity of anhydrous cement particles increases with the increase in the w/c ratio [8, 39]. Hence the accumulation of anhydrous cement particles is found to be lesser throughout the concrete with higher w/c ratio [refer Figs. 14 and 15]. The concentration of anhydrous cement particles was found to be more on the top of horizontal cast reinforcing bars due to deficiency of water above the bar. Whereas, the concentration of anhydrous cement particles was lesser below the horizontally cast reinforcing bars due to the increased availability of water because of trapped bleed water under the reinforcement bars [8] (Fig. 16).

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Fig. 16 Microstructural gradients in the interfacial region between cement paste and vertically cast steel at four ages in concrete with a w/c ratio of 0.49: a calcium hydroxide, b porosity, c unreacted clinker phases, and d undesignated hydration products (mainly C–S–H) [8]

6 Characterization Methods of SCI 6.1 Greyscale Thresholding Method When the scanning electron microscope (SEM) images were taken in back-scattered electron (BSE) mode, greyscale thresholding technique can be used as an image

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analysis technique to characterize the SCI. This is possible when the greyscale intensity of a pixel in the SEM image corresponds to the density of the volume of matter interacting with the electron beam [49]. Reinforced concrete is having various phases and each phase is having its own unique density. Each phase that interacts with the electron beam forms its own unique grey-level intensities. This leads to a difference in the contrast level for different components as steel, aggregates, hydrates and pores or voids in BSE images of SCI [1, 5, 50]. Then the range of grey-level distribution of different components at SCI is manually assumed [5, 50]. Figure 17a shows a typical BSE image at SCI and their greyscale histograms of individual components were taken as represented in Fig. 17b. Since the steel has a higher atomic number, it appears brighter white in Fig. 17a with higher greyscale value in Fig. 17b. Pores or voids appear darker in the BSE images due to lower atomic number. Thus, the steel and pores do not overlap and hence the phase borderline between them was easy to distinguish. But the grayscale values of cement hydration products with pores and aggregates which appears in between the end phases overlap each other up to some grey-level intensities [5]. However, in the case of reinforced concrete, the porous band at the interface needs to be separated from both steel and cement hydration products. Several researchers came up with different techniques to distinguish the phase borderline between hydrates in the cement paste/concrete and pores by setting an appropriate grayscale threshold value [5, 49–52]. Yang and Buenfeld [52] produced an algorithm for bifurcating aggregate particles by a combination of greyscale thresholding. Scrivener et al. [51] suggested a tangent-slope thresholding technique to differentiate pores and hydration products. Wong et al. [50] presented an efficient method to separate pores from hydration products. Kenny and Katz [49] used the point of intersection between two Gaussians produced by greyscale levels of cement paste hydrates and pores as the threshold level that bifurcates between these phases (Fig. 18). At the point of intersection, the probabilities of components (pores and hydration products) belonging to each phase are equal. The effective and reliable method was proposed by Chen et al. [5]. He considered a greyscale value of 42, which was the tangent’s midpoint of phase changing boundary between cement paste and porous band (as shown in Fig. 19) by analysing greyscalelevel distribution at SCI. Thus, the components having pixel grey value of less than or equal to 42 were taken as pores/voids and the rest were considered as hydration products and aggregates. Then the porous zone at the SCI was well distinguished and its thickness can be measured by greyscale thresholding. Considering the BSE image in Fig. 17a, after thresholding with a grayscale value of 42, a clear image showing well-distinguished steel, porous band and cement hydration products (with small voids) was obtained as shown in Fig. 20a. This post thresholding image was rotated to align vertically and the pores were measured at various spots. By taking the mean value of all these measured values, the actual porous zone thickness of this BSE image can be quantified.

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(a) BSE image showing a typical SCI

(b) Histogram of each phase showing grayscale range from 0-255 Fig. 17 BSE image of a typical SCI and their corresponding grayscale histograms of each phase

6.2 Nanoindentation Nanoindentation (NI) is an extensively used technique which has got significance in measuring the material properties at the micron and nano levels to attain the

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Fig. 18 Selection of greyscale threshold between two Gaussians [49]

microstructure and nanostructure of materials. It allows the user to execute mechanical tests on the micro and nanoscale structure of the material. In the case of cementbased materials, their mechanical properties are mainly depending on properties and structure at microscale and nanoscales. In order to understand and improve macroscopic mechanical performances of cement-based materials, it is crucial to inspect their mechanical properties at this micro- and nanostructural level [54, 55]. This is an effectual and dominant tool to discover the material’s microstructural and nanostructural elastic properties, hardness and creep properties [34]. This technique works on a basic theme that a very tip indenter with known properties and geometry is allowed to indent on the face material and examining the mechanical performance of the material from the reaction of the tip [54, 55]. It is important that the intender which was used should be much rigid than the testing specimen. The indenter used for the cement-based materials was Berkovich tip, which has three-sided pyramid that seems much trouble-free to grind [54]. To characterize the SCI, a series of indents were made in the ITZ between steel and bulk denser concrete to attain its nanomechanical properties [34]. The samples used for performing this test should have a smooth flat surface without any undulations [54]. The load acting on the indenter was a controllable parameter and the resultant depth of penetration was noted. Normally a trapezoidal loading program with loading, holding, and unloading phase was used as shown in Fig. 22. Local Elastic properties like indentation modulus (or reduced modulus) and hardness of the SCI can be estimated by the Oliver–Pharr method [56] using the unloading division of load penetration curve (Fig. 21) [54, 55]. The indentation modulus (or reduced modulus)

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Fig. 19 Selection of greyscale threshold by the tangents midpoint of phase changing boundary between cement paste and porous band [5]

was related to Young’s modulus ‘E’ and Poisson’s ratio ‘ν’ of the specimen and was obtained by Eq. 1.   M = E/ 1 − ν 2

(1)

From the indentation statistics, another factor called hardness and was obtained by Eq. 2. H = Pmax /Ac

(2)

where Pmax is the maximum load and Ac is the contact area. Time-dependent parameters, like creep indentation parameter (CIT) and creep compliance functions can be also extracted from the load–displacement curves

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(a) After thresholding

(b) Upright rotation and porous zone thickness measurements Fig. 20 BSE image after thresholding with grey value of 42 [53]

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Fig. 21 A typical load–depth curve of the nanoindentation tests [54]

Fig. 22 Trapezoidal loading program used in a nanoindentation experiment [55]

obtained by the indentation [34]. Creep indentation parameter depends on the contact force and holding period (time), which can be obtained by Eq. 3. The relative change between the depth of indentation h1 that come across at the time t1 and depth of indentation h2 that come across time t2 . Creep compliance relates the time-dependent strain with the nominal stress. From indentation data creep compliance can be obtained by

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the Eq. 4. CIT = 100(h2 − h1 )/h1

(3)

Cc = 2h2 (t)/ [π(1 − VS2 ) P0 tan α]

(4)

where h(t) is the indentation depth corresponding to time t, P0 is the applied force/load, VS is the Poisson’s ratio of specimen and α is the angle between edge of tip and surface (In Berkovich diamond tip α = 19.7°). Based on the suitability for conducting the test and the type of specimen, nanoindentation has got some types. Grid nanoindentation was one among them conducted to achieve more number of indents on the specimen [57]. It was used to assemble the data like mechanical properties for conducting statistical analysis [58, 59]. The grid size, shape of the grid and loading history should be predefined for this technique. Grid spacing should be large enough to keep the indent away without disturbing the surrounding indentations. Generally, this type of nanoindentation was preferred to assemble and evaluate the microstructural mechanical properties of ITZ [60, 61]. This method was more suitable for homogeneous materials. To carry out nanoindentation on heterogeneous materials, statistical nanoindentation technique has been introduced. This technique involves taking plenty of arbitrary indents on a definite area of the specimen and then analyse the indentation data statistically [54, 55]. A novel method called manual indentation technique has been introduced to advance the accuracy of grid indentation method. In this approach, the indentation points should be manually selected prior to a required particular phase, so that the indenter will impact on a required phase which enhances the accuracy of the result. Since the indentation points are to be selected in advance, by the operator manually, it has got the name manual indentation technique [55]. Apart from these, there is one more technique of nanoindentation coupled with other techniques like SEM, atomic force microscopy and energy-dispersive X-ray spectroscopy (EDS) [54]. From the nanoindentation study on the SCI, it is possible to approximate the ITZ thickness due to the variation in the values of indentation modulus from the reinforced steel bar surface [57]. The main distinction between ITZ and the bulk denser concrete is the porosity, which is inversely proportional to the modulus of elasticity of ITZ. The indentation modulus shows an increasing trend with the increasing distance from the steel surface. From the past research on nanoindentation, the mean modulus of elasticity for clinker is about ~120 GPa, low-density C–S–H gel ~20 GPa, high-density C–S–H gel ~31 GPa and calcium hydroxide ~40 GPa [62]. In SCI, it was found that the calcium hydroxide was largely concentrated in the porous zone and C–S–H gel was largely concentrated in the bulk denser concrete [7, 8]. As per this distribution profile of CH and C–S–H gel, the modulus of elasticity should be more in ITZ than that in bulk denser concrete. But the actual results show the opposite trend because of the fact that the percentage of pores/voids was higher in the ITZ which was more dominant than the increased modulus of elasticity of calcium hydroxide. Similarly, the other parameter called hardness also shows the same trend

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(increases with the increase in distance measured away from the surface of steel). Time-dependent parameters, specifically the creep indentation parameter CIT and creep compliance functions, show increased values at the ITZ than that in bulk denser concrete. The mean value of creep compliance in the ITZ was two times superior to the corresponding values in bulk denser concrete [34].

6.3 Energy-Dispersive X-ray Spectroscopy (EDS) Energy-dispersive X-ray spectroscopy (EDS) was an analytical technique used for the elemental analysis or chemical characterization of a specimen. EDS systems are normally incorporated into the SEM instrument. SEM provides clear high-resolution images of the specimen by focusing an electron beam throughout the surface and perceives a secondary or backscattered electron signal which is displayed as an image. By taking these kinds of SEM images of SCI, it was possible to find the composition of hydration products at the SCI. EDS analysis of the obtained SEM images can be done on a particular spot or an area or a line profile or a 2D map. From the past studies on elemental compositions of SCI [7, 8], it was clear that the major composition of the porous zone is being calcium hydroxide crystals and C–S– H gel was the principal composition in bulk denser concrete. Hence, the distribution profiles of these two compounds will help in determining the extent of the porous zone from the face of reinforcing steel. In general, the EDS composition results of cement-based samples show calcium (Ca) and silica (Si) compositions using which Ca/Si ratio or C/S ratio can be extracted. Several researchers confirmed the existence of calcium hydroxide and C–S–H gel on the basis of calcium to silica ratio (Ca/Si ratio) [7, 8, 63–65]. Table 3 shows the Table 3 Ca/Si ratios for C–S–H gel and Ca/Si ratio quoted by previous researchers Composition

Technique used

C–S–H gel

–

Ca/Si ratio Range

–

1.2–2.3

SANS/SAXS –

1.6–2

TEM

1.65–1.9

SEM SEM TGA

Average 1.7

Bentz et al. [66]

1.75

Pellenq et al. [67]

1.7

Allen et al. [68] Garcia et al. [69] Richardson and Groves [70]

1.65 1.89–2

– Calcium hydroxide

Author

1.74 1.95–2

Rodger and Groves [71] Harrisson et al. [72] Gutteridge and Dalziel [73] Garcia et al. [69]

SEM scanning electron microscope, TGA thermogravimetric analysis, SANS small-angle neutron scattering, SAXS small-angle X-ray scattering, C–S–H calcium silicate hydrate

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values of the Ca/Si ratio, from which the occurrence of calcium hydroxide and C–S– H gel can be identified. From the past researcher’s data about Ca/Si ratio, it may be concluded that Ca/Si ratio values for C–S–H gel falls in the range of 0.8–1.75 and for calcium hydroxide falls in the range of 1.75–3.5. On this basis of Ca/Si ratio, the compositions of ITZ and bulk concrete as well as PZT can be determined.

7 Conclusions The present review paper gives an idea of general properties of steel-concrete interface, which were reported by the researcher fraternities. The characterization methods of steel-concrete interface were systematically discussed. The following are the key conclusions from the present study. • The properties of steel-concrete interface differ from the properties of aggregate cement paste interface and bulk denser concrete. • The deviation of properties of steel-concrete interface when compared to bulk denser concrete was due to the ‘wall effect’. • The properties of steel-concrete interface were found to be quite influenced by the water to cement ratio, curing period, compaction time and addition of mineral admixtures. • The porous zone thickness at the steel-concrete interface plays an important role in service life prediction models. • The porous zone thickness at the steel-concrete interface increases as water to cement ratio increases. • The addition of mineral admixtures or fine fillers reduces the porous zone thickness at the steel-concrete interface. • There is the preferential formation of calcium hydroxide at the steel-concrete interface, which acts as a physical barrier for corrosion initiation until the ingress of harmful ions at the level of steel-concrete interface. • The grey-level thresholding method of characterization may be considered the reliable and reproducible method for measuring the porosity or porous zone thickness at the steel-concrete interface.

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47. Zhao Y, Wu Y, Jin W (2013) Distribution of millscale on corroded steel bars and penetration of steel corrosion products in concrete. Corros Sci 66:160–168. https://doi.org/10.1016/j.cor sci.2012.09.014 48. Bäumel A (1959) Die Auswirkung von Betonzusatzmitteln auf das Korrosionsverhalten von Stahl in Beton. Zement-Kalk-Gips. 7:294–305 49. Kenny A, Katz A (2012) Characterization of the interfacial transition zone around steel reinforcement bar by means of the mean shift method. Mater Struct Constr 45:639–652. https:// doi.org/10.1617/s11527-011-9786-x 50. Wong HS, Head MK, Buenfeld NR (2006) Pore segmentation of cement-based materials from backscattered electron images. Cem Concr Res 36:1083–1090 51. Scrivener KL, Patel HH, Pratt PL, Parrott LJ (1986) Analysis of phases in cement paste using backscattered electron images, methanol adsorption and thermogravimetric analysis. MRS Online Proc Libr Arch 85 52. Yang R, Buenfeld NR (2001) Binary segmentation of aggregate in SEM image analysis of concrete. Cem Concr Res 31:437–441 53. Goudar SK, Das BB, Arya SB, Shivaprasad KN (2020) Influence of sample preparation techniques on microstructure and nano-mechanical properties of steel-concrete interface. Constr Build Mater 256:119242 54. Hu C, Li Z (2015) A review on the mechanical properties of cement-based materials measured by nanoindentation. Constr Build Mater 90:80–90. https://doi.org/10.1016/j.conbuildmat.2015. 05.008 55. Davydov D, Jirásek M, Kopecký L (2011) Critical aspects of nano-indentation technique in application to hardened cement paste. Cem Concr Res 41:20–29. https://doi.org/10.1016/j.cem conres.2010.09.001 56. Oliver WC, Pharr GM (1992) An improved technique for determining hardness and elastic modulus using load and displacement sensing indentation experiments. J Mater Res 7:1564– 1583 57. Xiao J, Li W, Sun Z, Lange DA, Shah SP (2013) Properties of interfacial transition zones in recycled aggregate concrete tested by nanoindentation. Cem Concr Compos 37:276–292. https://doi.org/10.1016/j.cemconcomp.2013.01.006 58. Constantinides G, Ulm F-J (2007) The nanogranular nature of C-S-H. J Mech Phys Solids 55:64–90 59. Ulm F, Vandamme M, Bobko C, Alberto Ortega J, Tai K, Ortiz C (2007) Statistical indentation techniques for hydrated nanocomposites: concrete, bone, and shale. J Am Ceram Soc 90:2677– 2692 60. Mondal P, Shah SP, Marks LD (2009) Nanomechanical properties of interfacial transition zone in concrete. In: Nanotechnology in construction, vol 3. Springer, pp 315–320 61. Li W, Xiao J, Sun Z, Kawashima S, Shah SP (2012) Interfacial transition zones in recycled aggregate concrete with different mixing approaches. Constr Build Mater 35:1045–1055 62. Nˇemeˇcek J, Králík V, Vondˇrejc J (2013) Micromechanical analysis of heterogeneous structural materials. Cem Concr Compos 36:85–92 63. Turk K, Karatas M, Ulucan ZC (2010) Effect of the use of different types and dosages of mineral additions on the bond strength of lap-spliced bars in self-compacting concrete. Mater Struct 43:557–570 64. Goudar S, Das B, Arya S (2019) Microstructural study of steel-concrete interface and its influence on bond strength of reinforced concrete BT—microstructural study of steel-concrete interface and its influence on bond strength of reinforced concrete. Adv Civ Eng Mater 8. https://doi.org/10.1520/ACEM20180133 65. Hiremath PN, Thanu HP, Basavana Gowda SN, Goudar SK (2020) Early strength development of blended concrete under different curing conditions. Emerg Mater Res 9(1):1–8 66. Bentz DP, Stutzman PE, Garboczi EJ (1992) Experimental and simulation studies of the interfacial zone in concrete. Cem Concr Res 22:891–902. https://doi.org/10.1016/0008-8846(92)901 13-A

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Prediction of Compressive Strength and Electrical Resistivity of Mortar Mixes Containing Industrial Waste Products Maninder Singh, Babita Saini, and H. D. Chalak

Abstract In the present paper, non-linear soft computing technique (neural network) has been used to predict the compressive strength and electrical resistivity of cement mortar at 7 and 28 days. Thirteen mixes of cement mortar consisting of silica fume and alccofine as subrogation of cement were selected. The training and testing data used in ANN predictive model were based on experimental results in the laboratory. Cement, silica fume, alccofine, sand and water were used as input parameters. The predicted results obtained from ANN using multilayer feedforward neural network were compared with the experimental results. Results showed that ANN technique is effective for the prediction of strength in compression and electrical resistivity of various cement mortar mixes and correlation coefficients were also high. The values of correlation coefficient (R) and R2 were higher at 28 days than 7 days results for both compressive strength and electrical resistivity. Keyword Alccofine–silica fume · Electrical resistivity · Artificial neural network · Predictive model

1 Introduction Nowadays, the environmental protection is the prime concern for the eco-friendly nature. To protect the environment, different type of efforts have been adopted, and the utilization of waste is one of those. On the earth, different type of wastes are being generated (solid, liquid, gases); the utilization of these wastes in huge quantities is M. Singh (B) · B. Saini · H. D. Chalak Civil Engineering Department, National Institute of Technology Kurukshetra, Kurukshetra 136119, Haryana, India e-mail: [email protected] B. Saini e-mail: [email protected] H. D. Chalak e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_16

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necessary for making the environment eco-friendly. As we know, the construction industry is the major field that consumes solid materials, which results in the depletion of natural resources in huge quantities. Cement is the basic need of construction industry that consumes a lot of energy during production and approximately releases 1 kg of carbon dioxide for 1 kg of the manufacturing process [1, 2]. In India, the quantity of generated industrial waste such as rice husk ash, slag, metakaolin, alccofine (AF), fly ash, marble waste and silica fume (SF), etc., is very high, so the utilization of these waste materials is the basic need for protecting environment. Electrical resistivity (ER) is a non-destructive technique, used for measuring the capability of current flow. Current flow performance of any material depends on the microstructure of the matrix. ER is directly related to the chloride penetration, corrosion risk and porosity of the matrix [2, 3]. Therefore, it is a good indicator of material durability. Numerous research investigations reported that the inclusion of fine particles size materials in concrete improved the strength and durability performance [4, 5]. In the present paper, two types of industrial wastes, i.e. AF and SF as subrogation of cement have been used. AF and SF are solid waste products in the form of ultra-fine materials. AF, a low-calcium silicate material, is an iron industry waste. In [6–9], authors have reported that the use of AF as subrogation of cement improves the workability and strength properties of mortar mix. SF is a silicon metal or alloy waste and is also known as microsilica (MS). In [10–12]. Authors reported that the use of SF as subrogation of cement improved the performance of concrete. Concrete is the third most used resource after air and water because of its strength and durability characteristics. Many developments are taking place in the construction industry based on the requirements and new evolving techniques. Therefore, modelling of properties of concrete is becoming a necessity day by day. New modelling techniques by using artificial neural networks (ANN) help in assessing the change in different properties of concrete when other materials replaced its standard ingredients. Modelling also aids in knowing the dependency of concrete properties on other factors like curing period, curing temperature, type of curing, etc. The relationships between components and concrete properties are highly nonlinear; therefore, traditional models having various properties of concrete are inadequate [13]. In early studies, linear and multivariable regression analyses were used for the modelling and statistical analysis of concrete behaviour. But, now regression analysis is considered insufficient as compared to modelling by ANN. Many researchers have used various algorithm-based models like ANN, adaptive neurofuzzy inference system (ANFIS) and multiple linear regression (MLR) for computing the strengths of concrete mixes consisting of recycled aggregates [14, 15]. Properties of concrete depend upon many factors like water–cement ratio, type of cement used, cement content, mineral admixture, etc. Nowadays all the concrete firms have a very limited budget to spend on trial mixes and mix design. Further, testing of trial mixes before and during construction consumes a lot of time that increases the cost of project, as a large amount of materials is wasted. Therefore, the application of ANN for prediction of early strength and other properties is a boon to the construction industry [16].

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Prediction of strength of high-performance concrete using neural network by several researchers is a new development in the construction field. The performance of various machine techniques was analysed and the construction of individual enacting model was done to assess the strength of high-performance concrete (HPC) [17]. In [18], the authors proposed feasibility of machine learning to study the long-term assessments of reinforced concrete (RC). Authors have also discussed the benefits of machine learning and modelling for life span assessment of RC structures in detail. In [19], the authors tried to predict the strength of HPC consisting of additives as a partial replacement. For this purpose, MRA (multiple regression analysis) and ANN models were used, and ANN results found to be more accurate with a higher correlation coefficient. Further use of regression analysis and ANN in damage prediction of concrete structures is also important for seismic risk mitigation plans. In [20], the authors used decision tree algorithms for the modelling of single-degree-of-freedom RC buildings, and numerous time history non-linear analyses were performed.

1.1 Research Significance The present study emphasizes the prediction of compressive strength (CS) and ER of cement mortar mixes consisting SF and AF as a subrogation of cement at different proportions. ANN model was trained and the results were compared with the experimental results. The least value of RMSE (root mean square error) and high value of R (correlation coefficient) and R2 were the main criteria in the assessment of the predicted model. The purpose was to establish the correlation between input and output parameters. In this study, multilayer perception to predict the CS and ER of cement mortar mixes after 7 and 28 days was used and predicted results were compared with experimental results. Cement, AF, SF, sand and water were taken as input parameters and CS and ER at 7 and 28 days were achieved as output or target.

2 Methodology In the present study, Weka 3.8.3 tool with multilayer perception (ANN model) as a soft computing technique to predict the cement mortar properties was used. ANN is a computational model-based non-linear statistical data modelling tool where the relationships between input and output parameters are modelled [21, 22]. For a multilayer perception feedforward, error backpropagation algorithm was used in this study. A total of 13 mix proportions of cement mortar containing AF and SF were used to predict the CS and ER of mortar mixes at 7 and 28 days [23]. The predicted model comprises input layer, i.e. five input parameters, one hidden layer with four neurons for compressive strength and six neurons for ER parameters and output parameters.

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In this study, to analyse the performance of ANN, the values of correlation coefficient (R), mean absolute error (MEA), R2 and RMSE values have been used.

3 Statistical Data The statistical data used in the ANN prediction model are presented in Table 1. The architectural representation of the used ANN prediction model is shown in Fig. 1a, b. The value of R was the highest and RMSE was the least for better performance of the predicted model. Table 1 Range of Input parameters for ANN model Parameters Cement

(kg/m3 )

Sand (kg/m3 ) Alccofine

(kg/m3 )

Minimum

Maximum

Mean

Standard deviation

345

375

486.538

62.617

1725

1725

1725

0 44.871

0

115

44.231

Silica fume (kg/m3 )

0

115

44.231

44.871

Water (kg/m3 )

316.25

316.25

316.25

0

7 days compressive strength (MPa)

20.17

36.07

27.298

5.865

28 days compressive strength (MPa)

24.52

39.11

32.294

5.07

7 days electrical resistivity (k cm)

17.51

28.24

23.013

3.563

28 days electrical resistivity (k cm)

21.57

33.48

28.134

3.224

Fig. 1 a Predicted ANN model for compressive strength, b predicted ANN model for electrical resistivity

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4 Predicted Model Analysis The predicted results of ANN model consist of the relationship between the input and output parameters. The performance of ANN model was evaluated in the form of correlation coefficient (R), R2 , RMSE and MAE. The relationship between predicted and experimental results of output parameters is shown in Figs. 2, 3, 4 and 5. Figures 2 and 3 show the relation between predicted and experimental CS at 7 and 28 days, respectively. Similarly, Figs. 4 and 5 show the relation between predicted and experimental ER at 7 and 28 days, respectively. The values of correlation coefficient were found near to unity for all the output parameters, whereas RMSE was low in the range of 1–2. The respective values of performance parameters R, R2 , RMSE and MAE for all targeted results are given in Table 2. The values of R and R2 were higher at 28 days results for CS and ER than 7 days. The linear equations were derived from the corelation between experimental results and predicted results (ANN prediction model) of CS and ER of cement mortar consisting of AF and SF at 7 and 28 days of water curing. These equations can be used continually to predict the CS and ER of mortar of similar quality for a limited range of industrial wastes, which are used in the present study. The prediction of these properties aid in saving time as well as money and labour. A standard equation may also be derived for the estimation of CS and ER of mortar containing AF and SF of any proportions using ANN model. Fig. 2 Predicted versus experimental 7d CS

7 days Compressive strength 41

36

31

26

y = 0.9287x + 2.6433 R² = 0.8882

21

16 16

26

36

Experimental Compressive strength (MPa)

46

210 Fig. 3 Predicted versus experimental 28 d CS

M. Singh et al. 28 days Compressive strength 44 39 34 29

y = 0.901x + 3.1659 R² = 0.8981

24 19 19

24

29

34

39

44

Experimental Compressive strength (MPa)

Fig. 4 Predicted versus experimental 7d ER

7 days Electrical resistivity 33 31 29 27 25 23 21

y = 1.141x - 2.6052 R² = 0.7704

19 17 15 15

20

25

30

Experimental electrical resis vity (kΩ-cm)

5 Conclusions The present study checks the feasibility of neural-based models for the prediction and comparison of different properties of cement mortar. The output parameters were obtained from the experimental results in the laboratory. Thirteen different mix proportions of cement mortar containing SF and AF as a subrogation of cement were taken for the modelling. The use of both finer size waste materials (SF and AF) as a replacement of cement increased the compressive strength; whereas, the filling effect of these materials enhanced the electrical resistivity of cement mortar mixes. The trained ANN model was tested and the predicted results of mix proportions were

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28 days Electrical resistivity

Fig. 5 Predicted versus experimental 28d ER

35 33 31 29 27 25

y = 0.8085x + 5.2167 R² = 0.7742

23 21 21

26

31

36

Experimental electrical resis vity (kΩ-cm)

Table 2 Values of performance parameters Target

R

R2

RMSE

MAE

Equation

7 days compressive strength

0.9425

0.8882

2.0232

1.2183

y = 0.9287x + 2.6433

28 days compressive strength

0.9477

0.8981

1.5554

1.2714

y = 0.901x + 3.1659

7 days electrical resistivity

0.8778

0.7704

2.2774

1.8376

y = 1.141x − 2.6052

28 days electrical resistivity

0.8799

0.7742

1.4868

1.1749

y = 0.8085x + 5.2167

compared with experimentally obtained results. The neural network model showed the least mean absolute error and RMSE for the predictive models. Linear relationships were derived between the predicted and experimental values of ER and CS. These equations can be used to predict the ER and CS values of mortar consisting of waste. ER is a durability property of cementitious materials that can be used to determine the porosity, corrosion resistance, etc., directly or indirectly. The correlation coefficient (R) for output parameters were found near to unity. Therefore, ANN predictive model results suggest that high precision and accuracy can be acquired by using properties parameters along with input variables.

References 1. Liew KM, Sojobi AO, Zhang LW (2017) Green concrete: prospects and challenges. Constr Build Mater 156:1063–1095 2. Gambhir ML (2004) Concrete technology. The McGraw Hill companies 3. Medeiros-Junior Ronaldo A, Lima Maryangela G (2016) Electrical resistivity of unsaturated concrete using different types of cement. Constr Build Mater 107:11–16 4. Ramezanianpour AA, Pilvar A, Mahdikhani M, Moodi F (2011) Practical evaluation of relationship between concrete resistivity, water penetration, rapid chloride penetration and compressive strength. Constr Build Mater 25:2472–2479

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5. Hassan KE, Cabrera JG, Maliehe RS (2000) The effect of mineral admixtures on the properties of high-performance concrete. Cement Concr Compos 22:267–271 6. Mustafa Sahmaran, Li Victor C (2009) Durability properties of micro-cracked ECC containing high volume fly ash. Cem Concr Res 39:1033–1043 7. Saxena SK, Kumar M, Singh NB (2018) Effect of alccofine powder on the properties of pond fly ash based geopolymer mortar under different conditions. Environ Technol Innov 9:232–242 8. Gupta S, Sharma S, Sharma D (2015) A review on alccofine: a supplementary cementitious material. Int J Mod Trends Eng Res 2:114–118 9. Gautam M, Sood H (2017) Effect of Alccofine on strength characteristics of concrete of different grades-A review. Int Res J Eng Technol (IRJET) 4:2854–2857 10. Reddy AN, Meena T (2018) A Study on compressive behavior of ternary blended concrete incorporating alccofine. Mater Today Proc 5:11356–11363 11. Mohan A, Mini KM (2018) Strength and durability studies of SCC incorporating silica fume and ultra-fine GGBS. Constr Build Mater 171:919–928 12. Pedro D, Brito JD, Evangelista L (2018) Durability performance of high-performance concrete made with recycled aggregates, fly ash and densified silica fume. Cement Concr Compos 93:63–74 13. Karein S, Mahmoud M, Ramezanianpour AA, Ebadi T, Isapour S, Karakouzian M (2017) A new approach for application of silica fume in concrete: wet granulation. Constr Build Mater 157:573–581 14. Chou JS, Tsai CF (2012) Concrete compressive strength analysis using a combined classification and regression technique. Autom Constr 24:52–60 15. Deshpande N, Shreenivas L, Sushma K (2014) Modeling compressive strength of recycled aggregate concrete by artificial neural network, model tree and non-linear regression. Int J Sustain Built Environ 3:187–198 16. Khademi F, Jamal SM, Deshpande N, Londhe S (2016) Predicting strength of recycled aggregate concrete using artificial neural network, adaptive neuro-fuzzy inference system and multiple linear regression. Int J Sustain Built Environ 5:355–369 17. Özta¸s A, Pala M, Özbay E, Kanca E, Çagˇlar N, Bhatti MA (2006) Predicting the compressive strength and slump of high strength concrete using neural network. Constr Build Mater 20:769– 775 18. Chou JS, Pham AD (2013) Enhanced artificial intelligence for ensemble approach to predicting high performance concrete compressive strength. Constr Build Mater 49:554–563 19. Taffese WZ, Sistonen E (2017) Machine learning for durability and service-life assessment of reinforced concrete structures: recent advances and future directions. Autom Constr 77:1–14 20. Chithra S, Kumar SRRS, Chinnaraju K, Ashmita FA (2016) A comparative study on the compressive strength prediction models for high performance concrete containing nano silica and copper slag using regression analysis and artificial neural networks. Constr Build Mater 114:528–535 21. Karbassi A, Mohebi B, Rezaee S, Lestuzzi P (2014) Damage prediction for regular reinforced concrete buildings using the decision tree algorithm. Comput Struct 130:46–56 22. Eskandari- Naddaf H, Kazemi R (2017) ANN prediction of cement mortar compressive strength, influence of cement strength class. Constr Build Mater 138:1–11 23. Eskandari H, Tayyebinia M (2016) Effect of 32.5 and 42.5 cement grades on ANN prediction of fibrocement compressive strength. Procedia Eng 150:2193–2201

An Overview on Waste Materials Used in Engineered Cementitious Composite Maninder Singh, Babita Saini, and H. D. Chalak

Abstract This paper presents the overview on waste materials used for making engineered cementitious composite (ECC). Micromechanics-based ECC is a superb class of high-performance fibre-reinforced cementitious products. It is a mortar-based fibre-reinforced cementitious matrix and shows ductile nature due to excessive strain hardening under tensile loading. With the growth in industry the quantity of industrial waste product on land is increasing, thus resulting in environment pollution in different ways. In the ECC mix design, huge quantity of industrial waste products have been used such as silica fume, iron ore tailings powder, blast furnace slag, crumb rubber, recycled concrete fines, fly ash, palm oil fuel ash and so on. This study reported the effect of these industrial by-products on fresh, mechanical and durability properties of ECC. The present overview signifies that the subrogation of cementitious materials and fine aggregates with the industrial waste products in ECC improves deflection capacity, strain hardening behaviour, flexural and toughness properties, drying shrinkage tensile strain and width of cracks resistance of cementitious composite. The outcome of overview depicts that the properties of ECC enhanced with the use of waste products up to some replacement level, whereas the carbon dioxide emissions decreased, which made the ECC green in nature. Keywords Engineered cementitious composite · Recycled concrete fines · Tensile strain · Fly ash · Crack width

M. Singh (B) · B. Saini · H. D. Chalak Civil Engineering Department, National Institute of Technology Kurukshetra, Kurukshetra 136119, Haryana, India e-mail: [email protected] B. Saini e-mail: [email protected] H. D. Chalak e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_17

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Fig. 1 Behaviour of normal concrete, fibre-reinforced concrete and ECC under tensile loading [8]

1 Introduction Engineered cementitious composite (ECC) is a mortar-based highly ductile nature cement matrix, which shows pseudo strain hardening behaviour in tension regime. The design model of fibre-reinforced ECC relies on fracture mechanics or micromechanics [1, 2]. ECC mainly consists of cementitious matrix and fibres. To reinforce ECC, different types of polymeric fibres have been used. Fibres across the cracks transfer the stresses and act as a bridge. ECC generally consists of 2% or less than that randomly distributed short-length fibres. The role of the cementitious composite depends on the mechanical interactions between fibre, matrix and chemical bonding [3–5]. ECC generally consists of microconstituents, because the bigger size particles affect the ductile behaviour [6]. Compressive strength and elastic modulus of ECC ranges from 20 to 95 MPa and 18 to 34 GPa, respectively. The compressive strength of ECC shows normal to high strength concrete nature, whereas the elastic modulus is less than ordinary concrete, that is, due to non-appearance of coarse aggregates. The tensile strain and width of cracks in engineered cementitious matrix range from 1 to 8% and 60 to 100 μm, respectively [7]. The high tensile strain capacity with multiple microcracks makes ECC performance superior than regular concrete. The stress–strain curves under tensile loading in Fig. 1 depicts that regular concrete fails suddenly and high-performance fibre-reinforced cementitious concrete (FRC) shows tension softening failure after first cracking, whereas ECC shows pseudo-strain hardening behaviour [8].

2 Design Theory of ECC Mechanism behind micromechanics of ECC is the mechanical interactions between fibre and mortar matrix. Under tensile loading steady state and number of cracks phenomenon promotes pseudo tensile strain hardening in ECC. To achieve pseudo

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Fig. 2 Matrix bridging stress versus crack opening [9]

strain hardening with number of microcracks, two conditions, strength-based and energy-based, need to be satisfied [7, 9–11]. The strength condition that maximum fibre bridging stress (σpeak ) must be more than the first crack strength (σfc ), on each crack plane that is articulated by Eq. 1, must be satisfied. σ peak > σ fc

(1)

As per the energy condition, the propagation of matrix crack should occur in a constant ambient stress (σss ), and flat crack opening (δss ) in a flat crack configuration. This condition leads to an energy balance between externally supplied work and the required energy for fibre bridging to generate the microcracks in matrix. The energy dissipated along the bridging of fibres is articulated by Eq. 2. δss

σss δss = Jtip + ∫ σ (δ)dδ

(2)

0

As per the above-mentioned conditions, upper limit for crack tip toughness of matrix (Jtip ) can be fixed as (Fig. 2), Jtip ≤ Jb

(3) δss

Jb = σpeak δpeak − ∫ σ (δ)dδ 0

where δpeak = maximum crack width at peak stress As per these conditions, the performance index of stress σpeak/ σfc and energy Jb /Jtip can be calculated to observe the pseudo strain hardening [9]. where Jb = Complementary bridging energy

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These indices must need to exceed unity in polymer fibre-reinforced cement matrix to show pseudo strain hardening [9]. Higher the indices margin, higher are the saturated multiple cracks and pseudo strain hardening. Fibre bridging realizes the steady state and number of cracks behaviour. To evaluate the behaviour of crack with bridging effect, various studies with polymeric fibres have been explored [9–11].

3 Role of Waste Materials in ECC Quantity and types of debris are increasing day-by-day. Among these, some of the wastes are such that their fully decomposition may take many years. These nonbiodegradable or trash materials create nuisance in earth environment. Raging of waste accumulation is worldwide, particularly in congested areas. Numbers of investigations have been reported on the performance of ECC, using variety of wastes to replace solid constituents. Mineral admixtures are the powdered ground solid materials, that is fly ash (FA), rice husk ash (RHA), recycled concrete fines (RCF), crumb rubber (CR), BFS (blast furnace slag), iron ore tailings (IOTs) powder, fly ash cenosphere (FAC), palm oil fuel ash (POFA) and silica fume (FA). These are added to the engineered cementitious composite in larger amount than any other materials. Because the use of mineral admixtures has an ability to enhance fresh, mechanical and durability properties of ECC, mineral admixtures can be a good alternative of cement. Cement is dearer than other constitutes in concrete. So, wise use of cement alternative is needed as their use may reduce CO2 emissions. Cost efficiency may also improve using cement alternatives. (a) Fly ash (FA) Thermal power plants produce fly ash (FA) by combustion of coal. Electrostatic precipitators collect fly ash from exhaust gases during burning. Chemical composition of fly ash (FA) is different from various cements, but it resembles in portland cement. The hardening time of FA is lower than cement, due to the chemical reaction between calcium hydroxide and FA. The FA is of two types: (a) Class C and (b) Class F. A huge quantity of FA is used as subrogation of cement in ECC. Most of the researchers used Class F-type FA as cementitious material in ECC [12–22]. In ECC the use of fly ash (FA) as subrogation of cement improves the ductile behaviour. The use of FA in high volume (more than 50%) improves the tensile strain capacity, multiple cracking and fire resistance, whereas decreases the strength properties, that is, compressive, flexural and tensile. Chemical bonding between the fibre and the matrix reduced with the use of FA, which is in favour of achieving pseudo strain hardening. The width of cracks and drying shrinkage decreased with the use of FA, which promotes the durability of ECC [12–22].

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(b) Rice husk ash (RHA) Rice husk is generated from rice mills during processing of rice. Rice husk ash (RHA) can be produced from burning of rice husk. The RHA mainly consists of silica with small amount of carbon. The surface area of RHA depends on the burning temperature [23–27]. Righi et al. [23, 24] investigated the tensile performance of ECC by using RHA as subrogation of cement by 10, 20 and 30%. It was examined that the use of RHA with replacement of 30% cement enhanced the performance of ECC, that is, ductility, resistance to crack generation and decrease in the voids, water absorption and heat of hydration in ECC. The durability properties of ECC by using 30% RHA as replacement of cement were studied by Costa et al. [25]. It was examined that the absorption rate and void content of ECC-RHA is higher than ECC-reference. (c) Recycled concrete fines (RCF) Recycling is the process of changing useful waste material into new products. The usage of generated new products by recycling reduced the pollution of environment and the consumption of fresh materials also. From this process the use of these materials makes the environment eco-friendly. During this process various size of particles are generated, from fine to coarse. The fine aggregates are known as recycled concrete fines (RCF) [28, 29]. In ECC, recycled concrete fines (RCF) with size of 300, 600, 1180 and 2360 μm have been used as replacement of silica sand (SS) by Li et al. [29]. It has been reported that 600 μm size was optimum for flexural strength and tensile strain capacity. It has been also reported that 300 μm size was optimum for compressive strength. And matrix toughness decreased, when size of RCF increased from 300 to 600 μm, and afterwards it increased. (d) Tire rubber Tire rubber is derived by cutting scrap tires or other types of rubber materials in the form of granules or short pieces [30–32]. Crumb rubber has been used as silica sand replacement with 0, 15 and 25% by Zhang et al. [31]. It was examined that compressive strength decreased up to 35% and no change is observed between 15 and 25, whereas deformability increased with the increase of crumb rubber percentages. First cracking strength, toughness, crack width and bonding strength between matrix and rubber powder was much weaker than silica sand. Recycled tire rubber was used as replacement of iron ore tailings (IOTs) powder with 0, 10, 20, 30 and 40% by Huang et al. [32]. It has been observed that compressive strength and elastic modulus decreased up to 63% and 50%, respectively at 10% replacement. Width of cracks, tensile strength and first crack strength decreased, whereas tensile strain capacity, free drying shrinkage increased with the increment of recycled tire rubber as replacement of IOTs.

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(e) Ground granulated blast furnace slag (GGBFS) Ground granulated blast furnace slag (GGBFS) is a by-product of iron and steel industries. Water-quenched molten iron slag turns into a granular product that is grounded to fine powder. It mainly consists of CaO and SiO2 [33–35]. The GGBFS or slag was used in ECC as replacement of cementitious materials. Khan et al. [33] used GGBFS and fly ash (FA) separately as substitute of cement in ECC. It was reported that the use of GGBFS improved the ductility of ECC and lengthens the curing period. At 28 days ECC with 62% GGBFS showed better fresh and hardened properties with strain capacity of 4.2%. Lim et al. [34] used GGBFS as subrogation of cement at different levels. It has been observed that the use of GGBFS enhanced the strength and fibre bridging property, which promoted the ductile nature of ECC. Zhu et al. [35] used the blast furnace slag with combinations of fly ash at different levels as cementitious materials. It has been observed that the combinations of 40% FA and 30% slag (SL) enhanced the tensile strength, tensile strain, compressive strength and flexural strength by 14.37, 5, 30 and 26%, respectively, after 28 days of water curing. And combination of FA and SL also improved the durability properties of ECC. Finally, the combination of these two materials at this level delivered better results than other mixes. (f) Iron ore tailings (IOTs) powder Iron ore tailings powder is produced from beneficiation processes of iron ore as solid waste product. This solid waste product grows faster due to increase in the demand of steel and iron. It mainly consists of SiO2 and Fe2 O3 [36–38]. Iron ore tailings (IOTs) powder was used as silica sand substitution by Huang et al. [37]. It has been observed that strength properties (compressive, first crack and tensile) and width of crack decreased, whereas tensile strain capacity and matrix toughness increased with the use of IOTs [37]. Iron ore tailings powder was used as subrogation of cement by 40 and 80% by Huang et al. [38]. It was reported that compressive strength decreased and tensile strain increased ranging from 46 to 57 MPa and 2.3–3.3%, respectively. Moreover, the use of iron ore tailings powder reduced energy consumption and CO2 emissions from 10 to 32% and 29 to 63%, respectively. (g) Fly ash cenosphere (FAC) Fly ash cenosphere is a light-weight hollow sphere, produced from coal combustion at power plants with fly ash waste. It largely consists of silica and alumina. The density of cenosphere varies from 200 to 800 kg/m3 .

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Fly ash cenosphere (FAC) is used in ECC as substitution of iron ore tailings powder. It was reported that the use of FAC decreased the density, thermal conductivity, matrix fracture toughness and strength properties, whereas improved the tensile strain capacity [39]. (h) POFA (Palm oil fuel ash) In palm oil boilers, fibres, fruit bunches and shells are used as fuel, by which POFA (Palm oil fuel ash) is produced. POFA was used as subrogation of cement with 0.4, 0.8 and 1.2 from the mass of cement by Altwair et al. [40]. It has been examined that compressive strength and number of cracks increased, whereas first crack strength, defection capacity and crack width decreased with the use of POFA. It has been reported that 0.4% of POFA was optimum replacement for flexural strength. (i) Silica fume (SF) Silica fume is produced from silicon metal or ferrosilicon alloys as solid waste product. It is used in concrete as additive, and very reactive with pozzolanic materials. Size of silica fume particle is 0.1μ. It mainly consists of silica. Number of researchers have used silica fume in ECC as a good additive [41–45]. Liu et al. [41] had used 65% fly ash and 5% silica fume as replacement of cement. It has been reported that the use of silica fume improves the mechanical and durability properties of ECC. Zhou et al. had used 0.1 silica fume by mass of cementitious materials in ECC [42]. It has been observed that silica fume improved the fresh and hardened strength properties of ECC.

4 Conclusions The current paper presents a brief summary on used waste materials in ECC as replacement of cementitious materials and fine aggregates. Various types of industrial waste products, such as RHA, tire rubber, silica fume, GGBFS, FA, iron ore tailings powder, palm oil fuel ash and recycled concrete fines and so on, have been used for replacement in ECC at different levels. Appraisal on different properties such as fresh, mechanical and durability has been reported in the literature. The major key findings from the available literature are mentioned in the following: • The work signifies that the use of FA as replacement of cementitious materials improved the strain capacity under tension and resistance against width of cracks in ECC. • The literature reported that the substitution by waste materials in ECC up to some percentages enhanced the ductility and durability of matrix. • The past studies reported that chemical bonding decreased between fibre matrix interactions, which promote the pseudo strain hardening with multiple cracking.

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• The outcome from the past studies showed that the use of industrial by products in ECC reduced the carbon dioxide emissions and energy consumption decreased, which promotes the greenness of environment. Acknowledgements The authors obliged to the University Grants Commission, New Delhi for the financial assistance for research work.

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Studies on Modeling and Control of RCC Frame with MR Damper R. Rakshita , C. Daniel , G. Hemalatha, L. Sarala, D. Tensing, and S. Sundar Manoharan

Abstract Magnetorheological Dampers (MR) have the ability to mitigate seismic hazards caused to a structure by reducing its potential to undergo large displacements. The objective of the paper is to formulate an analytical modeling technique to perform the hybrid simulation. The seismic response of a single-story frame employed with an MR damper is analyzed for hybrid simulation. The paper compares the results of several parameters subjected to specific earthquake ground accelerations using an object-oriented programming software called OpenSees. A program source code developed by OpenSees is run with Active Tcl script and changes are made for specific models to validate the simulations for each model. The time-series data for ground accelerations of the earthquakes considered in the models (El Centro, Kobe, and Northridge earthquakes) is taken as an input to perform a simulation. OpenSees software is present as an executable file that runs this source code of the program, performs the simulation for each of the models, and saves the output. The simulated models give us several outputs like acceleration, displacement, damper force, etc., simultaneously after the program is run. The results of the output are deliberated in the form of graphs. Keywords Magnetorheological damper · Hybrid simulation · Time history analysis · OpenSees

1 Introduction The significance of modeling and control of building for seismic hazards is necessary to eliminate the possibility of failure and associated damage that may be caused due to the occurrence of earthquakes [1, 2]. As earthquake is a natural phenomenon, it is R. Rakshita · C. Daniel (B) · G. Hemalatha · L. Sarala · D. Tensing Karunya Institute of Technology and Sciences, Coimbatore, India e-mail: [email protected] S. Sundar Manoharan Pandit Deendayal Petroleum University, Gujarat, India © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_18

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physically impossible to completely cease its potential. However, its effects can be outlasted by suitable modeling techniques using an analytical approach [3, 4]. Risk reduction of earthquakes is a complex task that involves many crucial decisions, and hence, it is important to understand the probability of its occurrence to formulate rational solutions. An MR damper forms a part of a semi-active control system that helps to reduce the structural vibration [5, 6]. The hybrid simulation frameworks are built using different hardware and software, by using different numerical integration and delay compensation techniques that lead to different system behavior for setups designed to test the same structure. The standardized framework is to help authenticate hybrid simulation and to develop damper models using strategies for semi-active control systems [7]. The control algorithms used in semi-active control affects the performance of the controlled system and the requirements. The Tcl script devised accurate analytical techniques like the implementation of the Blockpulse functions to reach less computational expenses [8]. An accurate model for MR damper, which can constitute the hysteresis and make identification of parameters simple, should be developed. A new simple non-linear model to show the hysteretic behavior of the experimental investigation is incorporated with the analytical studies. The difficulty that is encountered when substantiating the efficacy of the control of semi-active system through numerical analysis [9]. The hybrid simulation technique to verify the validity of the method by performing experimental and analytical studies [10]. The hybrid simulation studies conducted by many researchers are generally performed using a standardized damper of 200-kN capacity [11, 12]. So, there is a necessity to indigenously fabricating a damper at the laboratory to test the response of the structure during ground motion. The main objective of this paper is to formulate a suitable analytical modeling technique using OpenSees and to analytically derive solutions for the displacement of SDOF from the experimental data of MR Damper.

2 Proposed Methodology 2.1 Hybrid Simulation Hybrid simulation integrates the physical testing and analytical modeling using computing software, offering a more coherent and reasonable way to investigate how large structures retaliate to seismic loading. The evaluation of a structure’s response under the ground motion of both components into one simulation. This helps the structural components with a complex response to be modeled experimentally and more renowned components can be represented within this analytical model. The necessity of hybrid simulation is that it helps to analyze the seismic response of large civil structures using a similar methodology adopted for a smaller structure.

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In this research, we are typically going to perform hybrid simulation by formulating an analytical model using OpenSees application software by taking into account the details of experimental investigation. The experimental investigation is conducted in the laboratory using specific testing procedures. The analytical investigation includes the formulation of an analytical model using OpenSees software by writing specific program codes for the simulation of the model.

2.2 MR Damper A magnetorheological damper comprises of magnetorheological fluid, controlled by an external magnetic field, using an electromagnet. In the present study, the fluid composition was mixed in the 60:40 ratio. The smart material Fe3 O4 was fixed as 60% by weight and the carrier oil was 40% by weight currently, magnatec oil in this case. The shear mode of the magnetorheological damper is represented in Fig. 1. The payload of the suggested damper is 2.28 kg. The fabricated MR damper is depicted in Fig. 2. This MR damper is assessed by exciting the damper with the amplitude ±5 mm, current range from 0 to 3 A, and frequency 0.5 Hz using MTS Universal Testing machine, cyclic loading test was done, as shown in Fig. 3. This vibration obtained is similar to that of a cyclic load test. The resulted damping force is measured by a DAS (Data Acquisition System) and the accelerometer helps to measure the motion of the damper. The measured damping force with respect to the displacement is represented in Fig. 4. The damping force value for 0 A is 2 kN and Fig. 1 Schematic shear mode magnetorheological damper

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Fig. 2 Fabricated magnetorheological damper

Fig. 3 MTS universal testing machine

the maximum damping force at 3 A is 3.52 kN. The damping force obtained in the test is appropriate for vibration control.

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Fig. 4 Damping force MRF 60

2.3 Analytical Model In order to develop the program code to run the MR damper model in OpenSees, it is essential to understand the basic working principle of the software. OpenSees is an exclusive software used for the simulation of earthquake engineering structures. The results obtained in the proposed model using OpenSees are damper displacement, damper force, frame displacement, frame force, and acceleration. An idealized schematic model developed based on existing damper models is represented in the Fig. 5. Basic Geometry The single-story frame adopted in the present work shown in Fig. 6 has 1000-mm bay width and 1000-mm story height. The period of the system is 0.7 s. Columns and beams of the frame are modeled with elastic beam–column elements. Damper Links A two-node link element is used to link the two nodes that define the geometry of the MR damper. Constraints The nodes at the base of the frame are fixed. The beam is considered to be rigid.

228 Fig. 5 Model description

Fig. 6 Ground acceleration versus time

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Damper Material To model the MR damper material, the input parameters that are selected for the damper example are as follows: Axial Stiffness K in kN/mm, Damping Coefficient C d in kN (s/mm), and a constant a = 0.35. Loading The single-story frame with MR damper is subjected to three earthquake time history data and the simulation models with each data is developed. In this model, the time history data of the 1940 El Centro Earthquake, 50% JR Takatori record from the Kobe 1995 earthquake, and 1994 Northridge Earthquake are considered.

2.4 Modeling Using OpenSees Initially, we develop a program code depending upon our requirements. The G + 3 RCC frame was analyzed using Staad pro, the critical section details are scaled down from 1:3 scale factor. For example, the prototype size is 230–77 mm using scale factor, the specifications implemented in the current program are as follows. Size of the Frame Thickness of the column and beam Weight of the Frame Reinforcing Steel Stirrups

1 × 1 sq m 0.77 m 10 kN 8 mm dia, 4 rods 3 mm dia, 50 mm spacing.

The fundamental parameters that define the behavior of an MR damper are axial stiffness, damping coefficient, and alpha value (0.35). Three different cases considered in the studies are, • A frame without an MR Damper • A frame with an MR Damper of current 0 Amperes passing through (off state) • A frame with an MR Damper of current 3 Amperes passing through (on state). In each of these cases, the MR Fluid composed of Nano Fe3 O4 particles is responsible for magnetization which indirectly relates to the damping force. The most important factor noticed are the internal damper stiffness K d and the damping coefficient C d . Table 1 depicts the input parameters for the proposed model in the two different states.

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Table 1 MR damper states Off-state

On-state

For a frame with MR damper of current 0 Amperes passing through it, the following values of K d , C d are obtained

For a frame with MR damper of current 3 A passing through it, the following values of K d , C d are obtained

Time = 4 s (Frequency: 0.25 Hz)

Time = 4 s (Frequency: 0.25 Hz)

K d = 0.08

K d = 0.14

C d = 0.32

C d = 0.56

Table 2 Peak ground acceleration

Earthquake

Recorded time

Maximum value of g

El Centro

0.02–31.81

0.31

Kobe

0.01–40.96

0.61

Northridge

0.02–60.00

0.88

3 Results and Discussion 3.1 Ground Acceleration Versus Time The peak ground acceleration and time in seconds of the three earthquakes considered for this study are plotted in a graph, as shown in Fig. 6, by using the software Originpro8. Peak ground acceleration is denoted by g (the acceleration due to earth’s gravity, in m/s2 (1 g = 9.81 m/s2 ) (Table 2).

3.2 Accelerations for Frame Without Damper When the case, where an RCC frame without a damper is considered, upon ground accelerations, the frame fails instantaneously within a time span of few seconds. For El Centro ground accelerations, the RCC frame fails typically at 0.84 s from the start. For Kobe and Northridge ground accelerations, the RCC frame fails at 1.18 s and 2.96 s, respectively. Further, the percentage reduction in frame acceleration between MR Damper 0 A and MR Damper 3 As for the different earthquakes are also calculated. Figure 7 shows frame acceleration versus time without damper (Tables 3 and 4).

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Fig. 7 Frame acceleration versus time without a damper

Table 3 Acceleration of the frame without damper

Earthquake

Max

El Centro

92.08

52.95

Kobe

50.75

180.81

112.03

115.78

Northridge

Table 4 Percentage reduction in acceleration between 0 and 3 A MRD

Min

Earthquake El Centro Kobe Northridge

Percentage reduction 92.08 50.75 112.03

3.3 Frame Displacement Versus Time The frame displacement is obtained from the output. When the force is applied, the frame undergoes a sway and there occurs a displacement from its original configuration. The percentage reduction in the displacement of the frame upon 0 and 3 A MRD is tabulated and it is found to be similar to that of damper displacement. Figure 8 shows frame displacement versus time for different earthquakes (Table 5).

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Fig. 8 Frame displacement versus time for different earthquake

Table 5 Percentage reduction in frame displacement

Earthquake

Percentage reduction (%)

El Centro

37.456

Kobe

24.956

Northridge

25.074

3.4 Damper Force Versus Damper Displacement The damper force versus damper displacement is obtained for the MR Damper with 3 A current and MR Damper with 0 A current. It is observed that the damper with 3 A current has more reduction in the displacement than that of the 0 A current damper. Figure 9 shows damper force versus displacement for different earthquake response (Table 6).

4 Conclusion In this work, the energy created due to earthquake is imparted to the structure and it increases the susceptibility of the collapse was found. The effects of such events are resisted by using external devices such as damper which helps to dissipate this energy that is transferred to the structure. Hybrid simulation has been particularly useful to formulate analytical models and to derive solutions for the displacement of the SDOF system using experimental data of MR damper. It is inferred upon corroborating the three earthquake results that an MR Damper with 3 A current has a maximum percentage reduction of 32.215% in displacement for Kobe Earthquake.

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Fig. 9 Damper force versus displacement for different earthquake response

Table 6 Percentage reduction in damper force versus displacement

Earthquake

Percentage reduction (%)

El Centro

19.692

Kobe

32.215

Northridge

31.897

To conclude, a semi-active control damper at ON state that operates with a minimum current is able to improve the performance of the system by a reduction in the displacement of the structure. Acknowledgements The authors thank Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India, for their constant support. We also extend our acknowledgment to the Department of Science and Technology (Grant No: DST/TSG/STS/2015/30-G).

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Detection of Defects in Concrete Structures by Using Infrared Thermography Madhuraj Naik , Varadmurti Gaonkar, Ganesh Hegde, and Lalat Indu Giri

Abstract This paper presents a report on the use of active infrared thermography in detecting and evaluating the extent of damage in concrete structures. Detection of sub-surface damages in concrete structures by the use of infrared thermography is becoming popular. This is because of advantages like non-contact testing and rapid scanning of any surface for damages. In this study active infrared thermography was conducted on laboratory casted concrete slabs with in-built defects of known sizes. It was found that the defects could be successfully identified by using infrared camera which outputs thermal images of the slab. Further, the images obtained were processed using a program to obtain area of defects. It was found that the defect area estimated had an error of about 32.5% with respect to the actual area. It was concluded that difference between area estimated and the actual area of defects can be minimized by employing adequate amount of thermal excitation. Keywords Infrared thermography · Sub-surface damages · Infrared camera · Thermal images · Thermal excitation

1 Introduction All structures including life line infrastructure works like bridges degrade and develop damage with time due to various reasons like fatigue, environmental factors, M. Naik (B) · V. Gaonkar · G. Hegde Goa College of Engineering, Farmagudi, Ponda, Goa, India e-mail: [email protected] V. Gaonkar e-mail: [email protected] G. Hegde e-mail: [email protected] L. I. Giri National Institute of Technology, Farmagudi, Ponda, Goa, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_19

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unforeseen loads, aftermath of natural calamities, corrosion, and so on. If these damages are not detected in time and repaired it can affect the integrity of the structure and might lead to loss of life and property. Thus, predicting accurately the current health condition of existing structures is a must. This has led to numerous studies and development of new and advanced methods for damage detection in structures. Infrared (IR) thermography has proven to be an effective NDT method to detect defects in objects, both at surface as well as below the surface. Non-destructive testing using IR thermography is known as thermal non-destructive testing (TNDT). TNDT is commonly used in industry to do quality testing of metals, ceramics, machineries, and so on, only until recently it has been used in concrete structures to detect subsurface damages. It generally consists of thermal excitation of the object under examination and monitoring of its surface temperature variation during the transient heating or cooling phase. The existence of defects in the object interrupts heat flow causing localized changes in temperature distribution on the surface. This can be recorded using an infrared camera. The two types of infrared thermography which are broadly used are passive thermography and active thermography. In passive thermography the IR images of the material under test are captured under natural ambient conditions providing information based on radiation of heat absorbed from the environment. In active thermography the object under test is subjected to external excitation/heating so that the hidden defects reveal themselves by causing surface hot spots under thermal nonequilibrium condition. Depending on nature of the heating used, active thermography is divided into stepped thermography, lock-in thermography, pulsed thermography, pulsed phase thermography and frequency modulated thermal wave imaging (FMTWI) [1]. TNDT is a whole field technique compared to the traditional point-by-point ultrasonic inspection. It is also relatively cheaper than X-ray imaging [2]. There has been a steady growth in the use of infrared thermography (IRT) as a health monitoring technique in civil structures, electrical installations, machineries and equipment, material deformation under various loading conditions, corrosion damages and welding processes. IRT has also found its application in nuclear, aerospace, food, paper, wood and plastic industries [3]. In addition to the low hazard associated with IR thermography, a further attraction is that inspections can be performed relatively quickly. Concrete is thermally inert and has low thermal conductivity which means more thermal excitation is required to induce heat flow in concrete structures to detect all defects. This makes proper imaging of concrete structures difficult. Despite these limitations, there has been progress in the development of IRT for concrete structures and more research is still going on. The purpose of this study is to detect all defects present in concrete structures by using active infrared thermography (stepped thermography) and quantify the extent of damage. A MATLAB program incorporating image processing technique has been used to calculate area of defects.

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2 Infrared Thermography for Health Monitoring of Concrete Structures and Challenges Passive thermography is popularly used for testing of large structures like bridges and retaining walls because the size of these structures is large and it takes a large amount of time to heat every part of the surface. Omar et al. [4] developed a stitching algorithm to create a mosaicked thermogram of an entire bridge deck from individual enhanced images for the purpose of identifying objective thresholds using K-means clustering technique. Hiasa et al. [5] explored favorable time windows for concrete bridge deck inspections by IRT through field experiment and finite-element model simulations [6]. In a previous study [7] the same authors worked toward developing an automated IRT system to determine optimal temperature contrast at which all defects are identified in a concrete bridge deck by using FEA simulations. Sultan Ali et al. [8] used receiver operating characteristics (ROC) analysis with image processing methods to characterize the reliability of IRT images from fabricated and in-service bridge decks. They analyzed the obtained thermal images pixel by pixel and compared them with ground truth. Curry [9] identified many problems with infrared thermography when used on concrete and masonry bridges in Europe. Zhao et al. [10] adopted spatial processing of thermal image with various image enhancement techniques to calculate area of defects in concrete retaining wall. Lourenco et al. [11] conducted a study on infrared thermography’s capacity in detection of lack of adhesion in tilling systems. From these works it was found that passive infrared thermography was able to identify defect location accurately. However, when it came to determining extent of damages, infrared thermography was found to give errors. The passive infrared thermography technique suffers from various limitations like edge effects, boundary conditions, time of heating during the day, time of data collection, non-uniform heating and varying emissivity of objects. Also, to obtain additional information like depth and area of defect the thermal images obtained have to be subjected to different post-processing methods (Van Leeuwen et al. [12], Maldague et al. [13]) which have their own limitations. Ró˙za´nski et al. [14] conducted experimental studies on laboratory casted concrete slab with reinforcement and four structure discontinuities imitating damages. Using various thermal excitation sources, the sensitivity of the slab response using infrared cameras was investigated along with numerical simulations. Similar work was done by Milovanovi´c et al. [15] to detect pre-embedded defects in concrete slabs in which the authors did thermal excitation for 60 min using a 1000 W halogen lamp. Surface temperature was monitored during this excitation along with 60 min cooling period at different distances. The authors used pulsed phase thermography (Maldague et al. [16]) to process the images. The authors concluded about favorable conditions for defect detection. Importance of cooling time and quantification of defects was established by Huh et al. [17] through experimental studies with defects at varying depths. Lock-in and stepped thermography were compared by Brown et al. [18] in which they performed trial inspections on two out of service FRP composite strengthened RCC bridge girders. Maierhofer et al. [19] applied impulse thermography successfully to

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locate voids in concrete, location of delaminations of CFRP laminates in concrete and detection of voids inside tendon ducts in laboratory conditions. The authors also demonstrated success of impulse thermography in location of asphalt delaminations in concrete bridge and detection of voids below granite floor on site. Cotiˇc et al. [20] based on a three-dimensional numerical simulation of the thermal transfer occurring in concrete specimens containing a void and the experimental results established relationship between the depth of the defect and t max or f max . To improve defect detection of IRT, it was combined with other methods like elastic wave techniques (Cheng et al. [21]). Maierhofer et al. [22] combined IRT with radar and concluded that both IRT and radar are well suited for detection of voids in concrete. Keo et al. [23] used microwave excitation source to detect the presence and spacing of steel bars in RCC slab using a contrast algorithm. From these works it was found that the ability to detect defects strongly depends on the heating time. A trial and error approach is adopted by all the above-mentioned authors for different heating times and amount of heating. This needs to be optimized. Apart from heating, detection of defect also depends upon the material properties of the object and experimental setup. Also, different methods of active infrared thermography have their own limitations and hence can be combined with other NDT methods for testing on concrete structures. Success of infrared thermography by combining it with other techniques also needs to be demonstrated. The existing methods should be revised to take into effect change in thermal properties of concrete, atmospheric conditions and noise due to emissivity changes and reflection from other sources. Defects of different sizes and at different depths and concrete with varying parameters will require different amounts of excitation energy. Using heat equation or FEM simulation, a mathematical formula can be developed to calculate exact amount of heat required for a concrete structure to identify all defects. This will optimize the process and make it more methodological rather than the current practice of experimenting with different heating times and energy fluxes. A thermogram gives the transient temperature versus time data for each pixel. These images are processed using various techniques to extract important parameters to calculate area of defects and depth. Different researchers have adopted different techniques to calculate extent of damage, and these methods can be improved to determine the extent of damage accurately.

3 Experimental Studies Conducted on Concrete 3.1 Preparation of Concrete Specimen Two concrete slabs were casted to include simulated defects made of thermocol having different sizes at the same depth. The out-to-out dimension of both slabs was 50 cm × 50 cm × 10 cm and they had four bars of 8 mm dia. at same spacing in both the directions. Placement and location of defects and reinforcement is shown

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in Fig. 1. Slab 1 (S1) had one thermocol defect D1 located 12 cm from left corner of slab while Slab 2 (S2) had three defects all named D2. Thermocol has thermal conductivity similar to air and was used to simulate air void in concrete. Figure 2 shows the slabs S1 and S2 before concreting and location of defects. Defect D1 is having size 12.5 × 6.0 × 3.5 cm while Defect D2 is having size 5.0 × 3.7 × 2.0 cm. S1 had clear cover of 20 mm and S2 had clear cover of 25 mm. The grade of both the slabs was M25. Type of cement used is OPC 43 grade (JK cement) and steel rebars of diameter 8 mm (JSW) were provided at equal spacing. Both 20 and 10 mm aggregates were used in the ratio 60:40. Type of sand used was natural sand. Properties of all these materials will be taken into consideration for future experimentation. Both slabs were not tested for their respective compressive strengths. The slabs were demolded 24 h after casting. Curing was done by submerging them in curing tank for 3 days. After curing period got over both slabs were tested using thermal non-destructive testing. Slab S1 was again tested after a period of 3 months from the first experiment.

Fig. 1 Placement of defects in a S1; b S2

Fig. 2 Showing reinforcement and defect location for slabs a S1; b S2

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3.2 Procedure Rough experiments were conducted to evaluate capabilities of infrared camera to detect defects in concrete. The aim of the experiments was to explore possibility of calculating defect area with significant accuracy from the images. The experiments were carried out in concrete laboratory of civil engineering department of Goa College of Engineering, Farmagudi, Ponda-Goa. The ambient temperature and humidity in the beginning of the experiment were not measured. In experiment 1, testing of both slabs commenced after 3 days of curing. Two 500 W halogen lamps were used as photothermal excitation source for the slab. The lamps were placed at a distance of 24 cm above the slabs, as shown in Fig. 3. The slabs were subjected to thermal excitation of 45 min each. Stepped thermography was adopted. Thermal images of the slab were captured randomly at different times and at different distances. The thermal camera used was FLUKE Ti-10 handheld camera. The camera was able to adjust to emissivity of any material and could measure the temperature at any region of interest. It had temperature measurement range of −20 to +250 °C with measurement accuracy ±2 °C or 2% (at 25 °C nominal, whichever is greater). The camera had field of view (FOV) 23° × 17° with 160 × 120 resolution. It had different modes of capturing images like full infrared image, full visual image and infrared image in visual image.

Fig. 3 Experimental setup a S1; b S2

Fig. 4 Series of images taken with FLUKE Ti-10 camera at random times

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Fig. 5 Series of images taken after a 5 min, b 20 min, c 30 min, d 60 min and e 7 min of cooling

The images taken using FLUKE Ti-10 camera are shown in Fig. 4. At different distances camera gave images with different temperatures. Also, the presence of the rod with halogen lamps restricted getting clearer images, as seen in Fig. 4d. In experiment 2, slab S1 was subjected to stepped active thermography using one 500 W Halogen lamp. The horizontal distance between S1 and Halogen lamp was kept constant at 1 m. Height of Halogen lamp above the floor was 45 cm. The slab was subjected to thermal excitation for 60 min. The first image was taken five minutes after the heating started. Next image was taken 20 min after the excitation started; third image after 30 min, fourth image after 60 min and last image 7 min after the lamp was turned off. The sequence of images taken is shown in Fig. 5. The thermal camera used was FLIR E6 hand-held camera. This camera like FLUKE Ti-10 was able to adjust to emissivity of any material and could measure the temperature at any region of interest. It had temperature measurement range − 20 to +250 °C with measurement accuracy ± 2 °C or 2%. The camera had field of view (FOV) 45° × 34° with 160 × 120 resolution. It too had different modes of capturing images, like full infrared image, full visual image and infrared image in visual image.

3.3 Observations The images in Fig. 4 show the temperature at different points of both the slabs for experiment 1. The thermal excitation in experiment 1 was done for 45 min using two 500 W Halogen lamps at 24 cm above the slabs, as shown in Fig. 3. Clearly the heating was non-uniform over the surface as observed from the images. Also,

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the camera displayed different temperatures at different distances from the surface, indicating that distance between surface and camera needs to be standardized. Images in Fig. 5 show the temperature at different times for experiment 2. The red mark indicates the defect D1 which was inserted in S1 at the time of concreting. As seen from sequence of images the defect D1 was visible after just 5 min of heating. As the heating time increased, the temperature over defect area increased non-uniformly. After 7 min of cooling time when image was captured, it was found that temperature over defect had decreased. However, it was found that defect was not formed fully on the image even after 60 min of heating, indicating that excitation done was inadequate. Evaluation of defect area from thermal image was done using a program and compared with the actual area. The images from the camera were exported to the computer using USB cable in RGB format. These images were spatially calibrated with actual dimensions in the program and the area was calculated. Before the program was used for calculating areas, it was necessary to test it to find out its accuracy. Testing of the program is covered in next section.

3.4 Testing of Program The program was tested by first taking a standard A4 size paper and drawing figures of known area on it. A photograph of the A4-sized paper was taken using Moto G4 plus mobile primary camera. The photograph is shown in Fig. 6. The program allows the user to select any one image of choice and display it in the window. The photograph was taken in such a way that the entire paper was in it. The figures drawn on it were a rectangle of area 15 cm2 , one circle of area 28.28 cm2 and one polygon of area 22.47 cm2 . The length of standard A4 size paper is 29.7 cm and width is 21.2 cm making the area of the paper as 629.64 cm2 . The first step in the Fig. 6 Photograph of the A4 size paper with various figures of known area on it

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Table 1 Results of testing of program Figure Rectangular

Obtained area using program (cm2 )

Actual area (cm2 )

Error (%)

15.20

15.00

+1.33*

Circle

27.70

28.28

−2.05*

Polygon

21.90

22.47

−2.54*

A4 paper

627.00

629.64

−0.42*

* ‘+’

in error indicates obtained area from image is higher than actual area. ‘−’ indicates obtained area is lower than actual area

program is calibration in which the user converts any plan dimension of the image in pixels into centimeters. Taking this into consideration both end points of one long edge of the A4-sized paper were selected and distance entered was 29.7 cm. To check if the calibration was done properly, the width of the paper was checked by using measure distance option which turned out to be correct. To be sure another check was performed to measure length of the diagonal of the paper, which also was accurate. Using measure area option in the program, area of the figures was calculated. The accuracy of area obtained from the program depends on how accurately a user selects an area. Similarly, area of other figures was measured and results were tabulated in Table 1. From Table 1 it is observed that the program is fairly accurate in determining dimensions of any figure in the image including the image itself. However, accuracy depends on how close to actual figure a user is selecting the region of interest. Also, this program can be used for spatial calibration of only RGB and it does not eliminate any noise or unwanted objects in the images. Future work can focus on improvement of this program.

3.5 Results of Experiment 2 For Experiment No. 2, areas of defect D1 obtained using MATLAB program for different heating times are presented in Table 2. The obtained area is compared with the actual area of D1.

4 Discussions The general problem addressed in this paper is the application of infrared thermography in civil engineering. The active infrared thermography technique is used for detection of defects in a laboratory casted concrete slab. The aim of the present study is to investigate the application of these techniques to civil engineering structures.

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Table 2 Results of detecting defective area for experiment 2 (S1) Defect

Dimension (cm × cm)

Heating time/cooling time (min)

D1

12.5 × 6.0

5

D1

12.5 × 6.0

20

D1

12.5 × 6.0

30

D1

12.5 × 6.0

60

12.5 × 6.0

7 (Cooling)

D1 * ‘−’

Depth at which D1 is located (cm)

Actual area (cm2 )

Estimated area (cm2 )

Error (%)

2.0

75.00

35.2

−53.1

2.0

75.00

43.7

−41.7

2.0

75.00

44.8

−40.3

2.0

75.00

50.6

−32.5

2.0

75.00

47.7

−36.4

indicates obtained area is lower than actual area

The interest is in calculating area of defects in physical units from the thermograms and comparing this area with the actual area of defects. As seen from the thermal images, defects are visible, that is, the point where red color appears. In experiment 1 it was observed that the images were giving different temperatures of the surface for different distances. Therefore, standardization of distance between camera and surface is very important to get the most accurate temperature representation of the surface. Also, since the heating was focused on very small area and field of view (FOV) of the camera was small, it was observed that temperature at one point was very high. This indicates that heating needs to be uniform. Effect of debris and interference of unwanted objects on the surface also needs to be considered. In experiment 2, defect D1 was visible only after 5 min of heating; however, it was not fully formed on the thermogram even after 60 min of heating, indicating that thermal excitation done was inadequate. The program formulated was tested on a surface of known area and was found to be giving fairly accurate results as seen from Table 1. It was observed that the error (%) between defect actual area and defect area obtained using program reduced with increase in heating time and again increased after cooling (‘−’ indicates that obtained area is lesser than actual area). This method can be used for NDT of concrete structures and can give faster data acquisition rate without having to touch the surface. However, improvements are still needed to be able to adopt it for structural health monitoring of concrete structures. This preliminary experimentation conducted shows the successful application of infrared thermography for NDT of concrete structures.

5 Conclusions The aim of these two experiments was to demonstrate potential of infrared thermography in detecting defects in concrete and to quantify them. The ability of infrared cameras to successfully capture defect areas was also demonstrated. It can be concluded that:

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• Defect detection using infrared thermography depends on the duration and uniformity of thermal excitation used. • Thermal image quality as well as the temperature readings obtained from it is dependent upon the distance from which it is taken and field of view of the camera. • Processing of thermal images is required to obtain results like area and depth of defect as thermal images by themselves give only location of defect.

References 1. Chatterjee K (2011) Development of simulator and image processing tools for multi-technique thermography. Indian Institute of Technology, New Delhi 2. Tuli S (2011) Sub-surface thermal wave imaging 3. Bagavathiappan S, Lahiri BB, Saravanan T, Philip J, Jayakumar T (2013) Infrared thermography for condition monitoring—a review. Infrared Phys Technol 60:35–55. https://doi.org/10.1016/ j.infrared.2013.03.006 4. Omar T, Nehdi ML, Zayed T (2018) Infrared thermography model for automated detection of delamination in RC bridge decks. Constr Build Mater 168:313–327. https://doi.org/10.1016/j. conbuildmat.2018.02.126 5. Hiasa S, Birgul R, Matsumoto M, Necati Catbas F (2018) Experimental and numerical studies for suitable infrared thermography implementation on concrete bridge decks. Meas J Int Meas Confed 121:144–159. https://doi.org/10.1016/j.measurement.2018.02.019 6. Hiasa S, Birgul R, Catbas FN (2017) Investigation of effective utilization of infrared thermography (IRT) through advanced finite element modeling. Constr Build Mater 150:295–309. https://doi.org/10.1016/j.conbuildmat.2017.05.175 7. Hiasa S, Birgul R, Necati Catbas F (2017) A data processing methodology for infrared thermography images of concrete bridges. Comput Struct 190:205–218. https://doi.org/10.1016/j. compstruc.2017.05.011 8. Sultan AA, Washer G (2017) A pixel-by-pixel reliability analysis of infrared thermography (IRT) for the detection of subsurface delamination. NDT E Int 92:177–186. https://doi.org/10. 1016/j.ndteint.2017.08.009 9. Curry TS, Dowdey JE, Murry RE (1990) Application of infrared thermography to the nondestructive testing of concrete and masonry bridges. NDT E Int 36:505 10. Zhao G, Chen JG (2013) Infrared thermo-graphic inspection technique for concrete retaining wall. Electron J Geotech Eng 18 H:1521–1528 11. Lourenço T, Matias L, Faria P (2017) Anomalies detection in adhesive wall tiling systems by infrared thermography. Constr Build Mater 148:419–428. https://doi.org/10.1016/j.conbui ldmat.2017.05.052 12. Van Leeuwen J, Nahant M, Paez S (2011) Study of pulsed phase thermography for the detection of honeycombing defects in concrete structures. Online Work NDT&E Compos Mater 13. Maldague F, Galmiche AZ (2001) Advances in pulsed phase tomography 43:175–181. https:// doi.org/10.1016/s1350-4495(02)00138-x 14. Ró˙za´nski L (2017) Detection of material defects in reinforced concrete slab using active thermography. 63:82–85 15. Milovanovi´c B, Banjad Peˇcur I (2014) Detecting defects in reinforced concrete using the method of infrared thermography. CrSNDT J 16. Maldague X, Marinetti S (1996) Pulse phase infrared thermography. J Appl Phys 79:2694– 2698. https://doi.org/10.1063/1.362662

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17. Huh J, Tran QH, Lee JH, Han D, Ahn JH, Yim S (2016) Experimental study on detection of deterioration in concrete using infrared thermography technique. Adv Mater Sci Eng 2016. https://doi.org/10.1155/2016/1053856 18. Brown JR, Chittineni SH (2015) Comparison of lock-in and pulse-phase thermography for defect characterization in FRP composites applied to concrete. Thermosense Therm Infrared Appl XXXVII 9485:94850B. https://doi.org/10.1117/12.2177260 19. Maierhofer C, Arndt R, Röllig M, Rieck C, Walther A, Scheel H, Hillemeier B (2006) Application of impulse-thermography for non-destructive assessment of concrete structures. Cem Concr Compos 28:393–401. https://doi.org/10.1016/j.cemconcomp.2006.02.011 20. Cotiˇc P, Kolariˇc D, Bosiljkov VB, Bosiljkov V, Jagliˇci´c Z (2015) Determination of the applicability and limits of void and delamination detection in concrete structures using infrared thermography. NDT E Int 74:87–93. https://doi.org/10.1016/j.ndteint.2015.05.003 21. Cheng CC, Cheng TM, Chiang CH (2008) Defect detection of concrete structures using both infrared thermography and elastic waves. Autom Constr 18:87–92. https://doi.org/10.1016/j. autcon.2008.05.004 22. Maierhofer C, Brink A, Röllig M, Wiggenhauser H (2003) Detection of shallow voids in concrete structures with impulse thermography and radar. NDT E Int 36:257–263. https://doi. org/10.1016/s0963-8695(02)00063-4 23. Keo SA, Brachelet F, Breaban F, Defer D (2014) Steel detection in reinforced concrete wall by microwave infrared thermography. NDT E Int 62:172–177. https://doi.org/10.1016/j.ndteint. 2013.12.002

DSP-Based Implementation of MPPT Tracking and Sliding Mode Control for Photo-Voltaic Systems Subramanya Bhat and H. N. Nagaraja

Abstract The conventional energy sources such as thermal and hydro are decreasing and at the same time global demand for energy is increasing almost at an exponential rate. The conversion of renewable or nonconventional energy sources such as solar, wind, and biogas plays an important role. Out of wind, solar, and biogas, the solar energy is easily and more available in nature. In the developed work, solar energy is used as an energy source. Moreover, many rural areas are not electrified even today with the conventional electricity. The efficiency of solar panels is less and their cost is also more. Hence to increase the efficiency, maximum power point tracking (MPPT) techniques are implemented using DSP TMS320F28377s. The load voltage of the converter will be maintained constant using sliding mode control (SMC) algorithm. A single DSP is used for the implementation of MPPT and SMC. The developed work is good in terms of efficiency, regulation, speed, and accuracy and works in real-time scenarios. The developed work can be used as a standalone system in rural areas for their daily electricity needs. Keywords Maximum power point tracking · Converter · Sliding mode control · Renewable energy

1 Introduction Nonconventional energy sources and renewable energy sources are gaining importance as the global demand for energy is rising. Many rural areas are not provided with the conventional electricity even today. These rural areas can be electrified using nonconventional and renewable energy sources easily. Out of nonconventional energy sources, solar energy is abundantly available in nature and can be used as a S. Bhat (B) Department of E & C Engineering, N.M.A.M Institute of Technology, Nitte, India e-mail: [email protected] H. N. Nagaraja Department of E & E Engineering, Graphic Era Deemed to be University, Dehradun, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_20

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primary source of electrical energy in rural areas. The solar cells efficiency is less and hence we need to implement maximum power point tracking (MPPT) for extracting maximum power from our sun. The output voltage from solar cell should be maintained at a constant voltage which we achieved by implementing sliding mode control (SMC). The implementation of SMC requires more computation compared to other control algorithms like voltage mode control, current mode control, proportional integral (PI) control, and so on. In the literature, these control algorithms are implemented using hardware components or microcontroller. However, SMC cannot be implemented using hardware components or microcontrollers. But the advantages of SMC are reduced steady-state error and increased stability. In the developed work, MPPT using perturb and observe method and SMC for converter control are implemented using DSP TMS320F28377s. In the literature, simulation studies on SMC for converters are available but hardware implementation of SMC using DSP is unavailable. The developed work also implements MPPT using light sensors and wiper motor and this type of MPPT is also known as hard tracking. A single DSP is used for the implementation of MPPT for solar panel and SMC for converter control. Block diagram of the proposed work is shown in Fig. 1. The input voltage for the converter is derived from the solar panel. The current and voltages from the solar panel are sensed using current and voltage sensor and it is given to DSP TMS320F28377s to generate PWM waves, and these PWM waves in turn are used to ON the switch in the converter. This type of control is also called feed forward control and the tracking is known as soft tracking. The load voltage or battery voltage should be maintained at a constant value of 12 V. To maintain the same, SMC is employed using the same DSP. This type of control is also called feedback control. The load current and the load voltages are sensed and compared, and the difference signal is taken as input to DSP for generating PWM waves.

Input voltage: Solar panel

Current Sensor

MPPT Control AlgorithmImpleme ntation :DSP: PWM generation : TMS320F28377s

DC Lamp, DC Fan

Buck-Boost Converter

Voltage Sensor

SMC algorithm implementation PWM generation : TMS320F28377s

Current Sensor

Battery

12V Voltage Source Comparator

Fig. 1 Implementation of MPPT and SMC algorithms for PV system

Error Amplifier

DSP-Based Implementation of MPPT Tracking and Sliding Mode …

249

Survey details of various MPPT techniques are discussed in Sect. 2. Implementation of P&O method using DSP is discussed in Sect. 3. The SMC is implemented for buck–boost converter control and the same is discussed in Sect. 4. The developed work is tested and the results are presented in Sect. 5.

2 Implementation of MPPT Techniques The MPPT technique should be applied to PV system to increase the efficiency of conversion for the PV cells and to increase the output power from PV cells. In future, PV system will be used in all residential, commercial, and industrial applications. Different methods are available in the literature for MPPT [1–8]. However, the most popular MPPT is the perturbation and observation (P&O) method. In this method, the operating point is moved toward the maximum power point. The disadvantage of this method is that it cannot track quickly the maximum power points. Also the algorithm does not work well for rapidly changing irradiance level. Another method used for MPPT is the incremental conductance method. In this method maximum power point is tracked by comparing the instantaneous and incremental conductance of solar cells. This method can track the maximum power points quickly but the harmonics of solar cell voltage and current should be measured and considered. Estimate perturb-perturb is developed in [9] to improve the speed of P&O method. In this method, there will be one estimate mode in addition to perturb mode which improves the speed of MPPT. Constant voltage method is mentioned in [10]. Here temperature and solar irradiance effects are neglected. Short current pulse method is mentioned in [10]. In this method maximum power point current is proportional to the short circuit current under specified temperature and irradiance conditions. The short circuit current is measured just before connecting solar panel to the PV system. Microprocessor-based PV system is discussed in [11]. In this work, microcomputer is used for solar cell current feedback, phase locked loop, diagnosis of other parameters, and MPPT. Microcontroller-based PV system is discussed in [12]. In this work, a buck–boost converter is used for charging of batteries. The buck–boost converter makes optimum use of solar energy for any application. To run AC applications, the output of the battery must be converted to AC and this was achieved using an inverter. In this work, cost-effective microcontrollers are used to implement control algorithms. A microcontroller PIC16F873 is used as charge controller and generates rectangular wave to turn ON the MOSFET in the DC–DC converter. But the disadvantage is the presence of harmonics. MPPT is not used in this paper to extract the maximum power. The RBF neural network realized on system on a programmable chip (SOPC) for MPPT is discussed in [13]. In this work, voltage, current, and temperature of solar panel are sensed and taken as input for RBF neural network. The PWM is generated depending on Vref generated from RBF neural network. In this work, the control system consists of RBF neural network, PWM, and PID control algorithm. The PWM

250

S. Bhat and H. N. Nagaraja Begin

Measure V (k),I(k)

P (k) =V(k)*I(k)

ȴP = P(k)-P(k-1)

NO

YES ȴP>0

YES V(K)-V(k1)>0

D=D+ȴD

NO

D=D-ȴD

YES

D=D-ȴD

V(k)-V(k-1)>0

NO

D=D+ȴD

V (k-1) = V(k) P (k-1) = P(k)

Fig. 2 Implementation diagram of P&O algorithm

and PID control algorithm are used to generate PWM signal. The ON period of the PWM wave changes according to input from the solar cell. The advantages of SOPC technology are low cost, stability, and integrity. The implementation diagram of the developed P&O method is shown in Fig. 2.

3 Implementation of Sliding Mode Control In literature, various control algorithms like current mode control, voltage mode control, power control, adaptive control, hysteresis control, PI, and PID control are discussed. The implementation of control algorithm for DC–DC converter using FPGA is discussed in [14]. In this work, the charging and discharging of the converter

DSP-Based Implementation of MPPT Tracking and Sliding Mode …

251

was controlled using FPGA controller by controlling the operation of switches. In this study, FPGAs are used to implement the control algorithm. The voltage mode control was implemented and PWM wave generated from FPGA was used to turn ON the switch in the converter. The converter designed charged the battery when PV power was available, and fed the power from the battery to the DC bus in the absence of sun. The real-time implementation and comparison of PI and modified incremental conductance control algorithms are discussed in [15]. This work mentions that the incremental conduction algorithm is tracking 7.4% more power. The real-time digital simulator is used to verify the results and this can be used to develop the real-time hardware for the developed Simulink models. A very few works have been reported on the implementation of control algorithms for converters using DSP. A digital control algorithm for buck and boost converters can be designed with the use of root-locus theory [16]. In this work, closed-loop poles are placed properly to ensure system stability, good steady-state, and transient-state response. The controller is implemented on a TMS320F2404 DSP and small signal behavior of the converters is analyzed. The drawback of this work is that for the buck converter theoretical values match the practical values, but for the boost converter they do not match. This is due to nonlinearity of boost converter dynamics. Further, a digital control method having the ability to specify the desired voltage and transient behavior of a synchronous buck converter was discussed in [17] and developed for voltage mode. In this work, a control signal is overlapped with a reference voltage. The steady-state error in the load voltage is minimized using an additional dynamics for the control algorithm. The design requirements are obtained by pole placement technique and algorithm was executed using DSP TMS320F240. The implementation of this control algorithm resulted in zero steady-state error. This work discusses the implementation of FPGA-based design using the same controller. The drawback of the system is low switching speed. In this work, analog version of the system was implemented on a chip to make it cost-effective, but the size of the converter was large. A digital control method for DC–DC converter using DSP was discussed in [16, 18], where the control method implemented was PID controller. The drawbacks of these works are that only first few samples of the compensator are considered and the evaluation board of DSP is used. The converters are operated in discontinuous conduction mode. Comparison of PID and fuzzy control methods using DSP is proposed in [19]. In this work, the above control algorithms were evaluated for DC–DC converters such as buck and boost. While comparing the parameters like design methodology, realization problems and performances are considered. Implementation of a linear control method like PID on a DSP is easy, but implementation of nonlinear control method like fuzzy logic is difficult on a DSP. The nonlinear control method requires more memory and computation. The fuzzy controller was superior when compared to PID for the boost converter control. Further, it was found to be more stable and robust for the boost converter control. However, the PID controller was superior compared to fuzzy controller for buck converter control. The DSPs are configured for implementing filters. For the implementation of fuzzy controller, memory required is larger and computational speed required is

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higher when compared to linear controllers. Even for real-time implementation of controllers used in converters, DSP is preferable as compared to microcontrollers. The SMC is obtained from VSCS and is used to control regulators, tracking systems, state observers, and fault detection schemes. The variable structure control system is to analyze and synthesize the system, which intentionally changes its structure with preset control law during transient period to achieve control objectives [20]. VSCS was implemented successfully for the control of electric motors, space systems, and robots. For a double integrator with input x(t), we can write X .. (t) = u(t)

(1)

where u(t) is the control signal. Consider the effect of using feedback control law [21]. u(t) = −K X (t)

(2)

where K is a positive scalar. The resulting closed-loop motion can be analyzed using a phase description. This phase description is a plot of velocity versus position. For the control action from Eq. (1) and multiplying the resulting equation throughout by y yields: X . X .. = −K X X .

(3)

Integrating this equation we get the following expression between velocity and position X .2 + K X 2 = C

(4)

where C denotes a constant of integration which is strictly positive. When K = 1, √ Eq. (4) represents a circle with radius C and center at the origin. A plot of X versus X . is an ellipse and the control law in Eq. (2) is incorrect. The X and X . variables do not travel toward the origin. For any controller, system state should be reached and it should stay on predefined switching surface within the state space. The dynamic behavior of the surface when confined to the surface is called as an ideal sliding motion. The benefits of sliding motion are: order of the system is reduced and insensitivity to parameter variations. The sliding motion control has many merits over the other control methods and they are: simple realization, stability, good transient response, robustness, and less magnetic interference. In SMC, switches are operated as a function of the state variables in such a way that forces the system phase curved paths to remain on the mentioned surface in the state space, known as sliding surface. The main advantage of SMC is robustness achieved by insensitivity to parameter variations [22]. The MPPT technique based on SMC is proposed in [23]. The power output of the PV system is DC and the power output of inverter is AC. This causes oscillations between converter and inverter operations. If these oscillations are not stabilized then

DSP-Based Implementation of MPPT Tracking and Sliding Mode …

253

PV power delivered to the load will be affected. SMC provides a good performance in the control of bulk voltage oscillations and also it gives good performance over the entire range without affecting the system bandwidth. In this work, MPPT is based on SMC for which the reference is given by an external algorithm, and as a result, oscillations are avoided in the bulk voltage. The VSCS law can be modified and it is given in paper [22] as  u(t) =

−1 if S(X, X . ) > 0 1 if S(X, X . ) < 0

(5)

where the switching is defined by S(X, X . ) = K X + X

(6)

u(t) = −sgn(S(t))

(7)

Eq. (5) can be written as

where sgn is the signum function. The dotted line in Fig. 3 denotes the group of points for which S(X, X . ) = 0. This is a straight line of slope—K passing through the origin. But for y values satisfying the K |X . | < 1, then 

lim s 0+ S . < 0 lim s 0− S . < 0

(8)

X'

X

S

Fig. 3 Different curved paths travel toward the sliding line from many starting conditions

254

S. Bhat and H. N. Nagaraja

When K |X . | < 1, system curved path on either sides of the line point, nearer to the line is expressed by S = {(X, X . ) : S(X, X . ) = 0}

(9)

Figure 3 shows the phase description of the system for high X . . The dashed line denotes the sliding line and a curved path travels toward the sliding line. For the infinite switching frequency the sliding motion will be on the line S. When the motion is on the line S then it satisfies the equation, which we get from rearranging S(X, X . ) = 0, namely, X . (t) = −K X (t)

(10)

This indicates first order decrease and the phase curved path will move along the line S to the origin, as depicted in Fig. 3. This dynamic behavior is described as an ideal sliding mode and the line S is known as the sliding surface. The control law assures that the curved path moves toward the sliding surface as shown in Fig. 4. There are two kinds of SMC design and they are [21]: (i) The realization of a switching that satisfies the sliding motion (ii) The selection of control law according to the system state design.

X' X

Trajectory

S Sliding Surface

Fig. 4 Trajectory moving toward the sliding surface

DSP-Based Implementation of MPPT Tracking and Sliding Mode …

255

The scalar control system is given by x . = f (x, t, u)

(11)

where x = the column vector, f = function vector that is discontinuous on the surface S = (x, t) = 0, u = element that can affect the system motion.  f (x, t, u) =

  f + x, t, u +  for S → 0+ f − x, t, u − for S → 0−

(12)

Then the system will be in sliding mode [24]; its corresponding point travels on the surface which is sliding S = (X, t) = 0. The existence and reaching conditions in SMC are explained as follows. The sliding mode will be present when phase curved paths of the two subregions related to the two dissimilar values of the function f should travel toward sliding surface S = (X, t) = 0. When the sliding manifold from the points that satisfy S < 0, the velocity vector f − should travel toward the sliding manifold, and for the same reasons for the points above the sliding surface S > 0, the state velocity vector is f + . These velocity vectors are orthogonal to the sliding surface. Consider the system x = f (x, t, u). The scalar discontinuous input for this system u is expressed by  u=

u + for S(x) > 0 u − for S(x) < 0

(13)

   Let X + X − be the state representative point corresponding to the u + and u − , where x is a column vector. Then a necessary condition for the system to meet the sliding surface is expressed by 

 x + ∈ S(x) < 0



 x − ∈ S(x) < 0

(14)

These equations are implemented in DSP TMS320F28377s. Before implementing these equations ADC of DSP is configured. Code Composer Studio Version 6 is used to implement algorithms on a DSP.

4 Results and Discussions The DSP TMS320F28377s board overview is shown in Fig. 5. This is a low-cost board developed by Texas Instruments. The control algorithms can be easily implemented using this processor compared to conventional DSP. The P&O is implemented using

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Fig. 5 DSP TMS320F28377s board overview

DSP TMS320F28377s and the PWM wave obtained using the same is as shown in Fig. 6. The experimental setup for the implementation of MPPT is shown in Fig. 7. The charging of battery from the solar panel is as shown in Fig. 8. During day time the

Fig. 6 PWM waves obtained from DSP TMS320F28377s

Fig. 7 Experimental setup for the implementation of MPPT

DSP-Based Implementation of MPPT Tracking and Sliding Mode …

257

Fig. 8 Charging of battery from the solar panel

battery is charged using MPPT and SMC and during night the loads are driven from the battery. Electrical characteristics of the solar panel used are tabulated in Table 1. Battery specifications are tabulated in Table 2. For hard tracking wiper motor and light sensors are used and the specifications of the wiper motor are tabulated in Table 3. The developed work is good in terms of efficiency, regulation, speed, and accuracy and works in real-time scenarios. The developed work is tested against 100 different cases during the different timings of different days. The experiment is also carried out during cloudy days. The efficiency of the developed system is 99% and accuracy is 98%. The cost of overall system is Rs. 10,000/-, the speed of operation is 95 µs, and regulation achieved is 2%. The developed system is novel as it is good in terms of efficiency, regulation, speed, and accuracy and works in real-time scenarios. Table 1 Electrical characteristics of solar panel

Table 2 Battery specifications

PASAN tester version module ID code

2.4.4

Pmax

50 W

Voc

21.6 V

Isc

2.99 A

Current at maximum power (Ipm)

2.84 A

Voltage at maximum power (Vpm)

17.82 V

Permissible system voltage

600 V DC

Maximum reverse current

5A

Manufacturer

SELCO

Type

Tubular, lead acid battery, solar

Capacity

15AH

Nominal voltage

12 V

258 Table 3 Specifications of wiper motor

S. Bhat and H. N. Nagaraja Standard

30 W 12 V/24 V

Application

32/ZD2332 Lifting motor

Material

Stainless steel

Wiring

2/4 wires

Gear box

Right hand side

Gear material

Aluminum

HS code

8501310000

Body diameter

55 mm

5 Conclusion In the developed work, soft tracking, hard tracking, and SMC are all implemented to maximize the efficiency of PV system. The developed work can be used as a standalone system for electrical energy in rural areas. As a future work, the battery charging can be regulated using the same DSP processor. The developed work can be used for other nonconventional energy resources such as wind and biogas. The conventional energy sources such as thermal and hydro can also be controlled using SMC. The developed algorithms can be implemented as a system on chip (SOC) which can be easily portable from one place to another place and can be easily used in fields. In the developed work DSPs are configured for implementing control algorithms. This configuration helps for implementing more sophisticated new control algorithms for converters. The control algorithms simulated and implemented for PV system can be used for other electricity generation systems such as wind power plants and biogas power plants.

References 1. Rahmam S, Khallat MA, Chowdhury BH (1988) A discussion on the diversity in the applications of photovoltaic system. IEEE Trans Energy Convers 3:738–746 2. Bose BK, Szczesny PM, Steigerwald RL (1985) Microcomputer control of a residential photovolatic power conditioning system. IEEE Trans Ind Applicat IA-21:1182–1191 3. Huynh P, Cho BH (1992) Design and analysis of microprocessor controlled peak power tracking system. In: Proceedings of 27th IECEC, vol 1, pp 67–72 4. Wasynczuk O (1983) Dynamic behavior of a class of photovoltaic power systems. IEEE Trans Power Appl Syst PAS-102:3031–3037 5. Caldwell DJ et al (1991) Advanced space power system with optimized peak power tracking. In: Proceedings of 26th IECEC, vol 2, pp 145–150 6. Yongji H, Deheng L (1992) A new method for optimal output of a solar cell array. Proc IEEE Int Symp Ind Electron 1:456–459 7. Sullivan CR, Powers MJ (1993) A high-efficiency maximum powerpoint tracker for photovoltaic array in a solar-powered race vehicle. In: Proceedings of IEEE PESC, pp 574–580 8. Hussein KH et al (1995) Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions Proc Inst Elect Eng 142, pt. G(1):59–64

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9. Yafaoui A, Wu B, Cheung R (2007) Implementation of maximum power point tracking algorithm for residential photovoltaic systems. In: 2nd Canadian solar buildings conference, pp 1–6, Calgary 10. Remy G, Bethoux O, Marchand C, Dogan H (2009) Review of MPPT techniques for photovoltaic systems. In: 2nd international conference on energy and environmental protection in sustainable development, Hebron, France 11. Bose BK, Szczesny PM, Steigerward RL (1985) Microcomputer control of a residential photovoltaic-power conditioning system. IEEE Trans Ind Appl IA-21(5):1182–1191 12. Akkaya R, Kulaksiz AA (2004) Microcontroller based stand—alone photovoltaic power system for residential appliances. Appl Energy 78(4):419–431 13. Cao B, Chang L, Li H (2008) Implementation of the RBF neural network on a SOPC for maximum power point tracking. In: IEEE Canadian conference on electrical and computer engineering 2008, Niagara Falls, pp 981–986 14. Raveendhra D, ul Zaman PR, Govind K (2014) FPGA controlled high gain bidirectional DC– DC converter for energy storage of solar power. In: IEEE 2nd international conference on electrical engineering, Chennai, January 2014, pp 300–305 15. Kolluru VR, Mahapatra K, Subudhi B, Ramesh T (2014) Real time implementation and comparison of PI and modified inc Cond control algorithms for sola applications. In: 6th IEEE India international conference on power electronics, December 2014, India, pp 1–6 16. Guo L, Hung JY, Nelms RM (2003) Digital controller design for buck and boost converters using root locus techniques. In: The 29th annual conference of the IEEE industrial electronics society (IECON’03), vol 2, Nov 2003, pp 1864–1869 17. Oliva AR, Ang SS, Bortolotto GE (2006) Digital control of a voltage mode synchronous buck converter. IEEE Trans Power Electron 21(1):157–163 18. Peretz MM, Ben Yaakov S (2012) Time domain design of digital compensators for PWM DC–DC converters. IEEE Trans Power Electron 27(1):284–293 19. Guo L, Hung JY, Nelms RM (2009) Evaluation of DSP based PID and fuzzy controllers for DC–DC converters. IEEE Trans Ind Electron 56(6):2237–2247 20. Ahmed M, Kuisma M (2004) Sliding mode control for switched mode power supplies. A thesis 21. Edwards C, Spurgeon SK (1998) Sliding mode control theory and applications. CRC Press, pp. 1–6 22. Ahmed M, Kuisma M, Silventoinen P, Pyrhonen O (2003) Sliding mode control for buck-boost converter using control desk dSpace. In: Proceedings of 5th international conference on power electronics and drive systems, pp 1491–1494 23. Montoya DG, Paja CAR, Giral R (2013) A new solution of maximum power point tracking based on sliding mode control. In: IECON 39th annual conference of the IEEE 2013, Vienna, Austria, pp 8350–8355 24. Bhandari B, Poudel SR, Lee KT, Ahn SH (2003) Mathematical modeling of hybrid renewable energy system a review on small hydro-solar-wind power generation. Int J Precis Eng Manuf Green Technol 1(2):157–173

Analysis of Resilience Performance of Water Distribution Network A. Ariffa Parakath and T. R. Neelakantan

Abstract Emerging economic focuses on the reliable infrastructure setups for growth. Developed countries also work in more realistic performance indicators for risk assessment of infrastructure. Thus, the reliability of water supply through the water distribution network is improving. Among the risk indicators, resilience is one of the important factors. Resilience of water distribution through pipe network is getting focus in the recent years. Hence, in this paper three important resilience indicators, namely ‘resilience index’, ‘network resilience index’ and ‘total surplus head index’ reported in the literature, are analyzed and the merits and demerits are highlighted. This analysis will be helpful for future research. Keywords Water distribution network · Risk · Resilience · Performance indicators

1 Introduction Water distribution by pipe networks is popular for the past one century. Research on improving the performance of water supply has grown significantly during this period. One of the recent researches in water supply field is using resilience indicators in the design and operation. Though performance indicators like reliability, connectivity, and so on were used for nearly 50 years, the usage of resilience was seen since the year 2000. Resiliency can be defined in so many ways. Two major classifications of resiliency can be (1) based on the recovery time from once the system falls into failure mode; and (2) based on the capacity of the system to absorb a shock and function without much change in performance. The second one is considered in majority of the researches in this field. The objective of this paper is to critically A. Ariffa Parakath (B) · T. R. Neelakantan Department of Civil Engineering, Kalasalingam Academy of Research and Education, Krishnankoil, 626126, Tamil Nadu Srivilliputhur, India e-mail: [email protected] T. R. Neelakantan e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_21

261

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A. Ariffa Parakath and T. R. Neelakantan

analyze three of the resilience indicators so that the outcomes will be useful for future research.

2 Resilience Index One of the important turning points in water distribution network analysis, especially with resilience focus, was due to the introduction of an indicator called Resilience Index by Todini [8] as follows. N 

RI =

j=1 R  i=1

q •j (h j − h •j )

Q i Hi −

N  j=1

= q •j h •j

excess power available excess power supplied

(1)

where N is number of demand junction, q •j is the demand and h j is the actual head at junction j, h •j is the minimum required head for supplying the demand, R is the number of reservoirs or overhead tanks, Q i is the flow rate from reservoir i and Hi is the head from which the water is from the reservoir junction. Attempts to verify the results of Todini [8] revealed that the numerical values reported by Todini [8] are not perfect for the network shown in Fig. 1. For example, in Table 3 of his work, Todini [8] reported that the resilience index of optimum cost case and set A as 0.22 and 0.41, respectively. However, they are worked to be 0.210 and 0.396, respectively. This is reported here as the new researchers can avoid wasting time in the verification. The details of calculations are presented in Tables 1a, 1b, 2a and 2b. Fig. 1 Two-loop network

Analysis of Resilience Performance of Water Distribution Network

263

Table 1a Diameters for two-loop network (Todini, 2004) for optimal cost (0.419 × 106 ) Pipe No. Diameter (in) Diameter (mm)

1

2

3

4

5

6

7

8

18

10

16

4

16

10

10

1

457.2

254.0

406.4

101.6

406.4

254.0

254.0

25.4

Table 1b Recalculation of Todini (2004) results for optimal cost (0.419 × 106 ) Node No.

q•

h•

h

(h-h • )

q • (h-h • )

q •h•

2

100

180

203.25

23.25

2325.0

18000

3

100

190

190.46

0.46

46.0

19000

4

120

185

198.45

13.45

1614.0

22200

5

270

180

183.81

3.81

1028.7

48600

6

330

195

195.44

0.44

145.2

64350

7

200

Total

1120

1 (Reservoir)

Q = 1120

190

190.55

–

–

0.55 –

H = 210

110.0

38000

5268.9

210150

QH = 235200

Table 2a Diameters for two-loop network (Todini, 2004) for Sol A. Cost (0.450 × 106 ) Pipe No. Diameter (in) Diameter (mm)

1

2

3

4

5

6

7

8

18

16

14

6

14

1

14

10

457.2

406.4

355.6

152.4

355.6

25.4

355.6

254

Table 2b Recalculation of Todini [8] resultsâe”Table 3âe”column 3 (Sol A. Cost = 0.450 × 106 ) Node No.

q•

h•

h

(h-h • )

q • (h-h • )

q •h•

2

100

180

203.25

23.25

2325.0

3

100

190

200.19

10.19

1019

19000

4

120

185

198.38

13.38

1605.6

22200

5

270

180

196.19

16.19

4371.3

48600

6

330

195

195.99

0.99

326.7

64350

7

200

190

191.35

1.35

270

38000

9917.6

210150

Total

1120

1 (Reservoir)

Q = 1120

–

– H = 210

–

18000

QH = 235200

The data shown in Table 1b used in Eq. 1 results in a resilience index of 0.21 instead of 0.22 as reported by Todini [8]. From the above data, resilience index works to be 0.396 instead of the reported value of 0.41.

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A. Ariffa Parakath and T. R. Neelakantan

3 Network Resilience Index Prasad and Park [5] proposed Network Resilience Index by introducing an additional factor in the original resilience index as follows. N 

N RI =

j=1 R 

C j q •j (h j − h •j )

Q i Hi −

i=1

N  j=1

(2) q •j h •j

in which npj 

Cj =

Di

i=1

(3)

(npj × max{Di })

and npj is the number of pipes connected to a junction. The logic of using C j is justified by stating that reliable loops can be ensured by uniformity of diameters of the pipes connected to junction. The Network Resilience Index of Prasad and Park [5] lacks physical meaning compared to Todini’s Resilience Index as C j is an arbitrary weight. In this context, Atkinson [1] mentioned that apart from diameter, pipe length, roughness and upstream and downstream pressure heads can also be representative for the network operation. Gheisi et al. [3] also specified this in their review paper. Todini criticized that NRI corrupts the original physical meaning of the resilience index [2]. Extending Atkinson [1], it can also be defined in terms of area of cross-section or length weighted diameter instead of diameter as described below. npj 

Cj =

npj 

Ai

i=1

(npj × max{Ai })

or C j =

L i Di

i=1

(npj × max{L i Di })

(4)

The proposers of Network Resilience Index neither explored nor explained why they have not considered the other forms as above. If a network has a (main source) pipe from reservoir splitting into three branches at a node, the pipes need not be of uniform diameter. Since there is only one inflow pipe and three outflow pipes at the junction node, the main source pipe can be of larger diameter, while the branching pipes may be of smaller size. In the two-loop network at node two, there are three pipes (1, 2 and 3) connected to it. Among these three, pipe1 is from the reservoir and the other two are the branching pipes. During non-failure scenario, pipes 2 and 3 share the flow from pipe1. However, if pipe2 fails, the supply can follow through pipe3 and vice versa. Hence, generally maintaining uniformity of pipe diameters is not essential or required.

Analysis of Resilience Performance of Water Distribution Network

265

4 Total Surplus Head Index Prasad and Park [5] proposed a resilience index called ‘Total Surplus Head Index’ (I t ) which is the summation of surplus head at demand nodes, and is presented below in the mathematical form. It =

N  

Hi − Hil



f or all i = 1, 2, . . . N

(5)

i=1

In the above equation, N is the number of demand junction, Hi is the actual head at junction i and Hil is the minimum required head for supplying the demand. They claimed that maximization of this index improves the ability of the distribution network. However, it has an issue which is discussed here. The surplus head indicates available power or energy for dissipation during a failure event. Water distribution networks, many a times, have different zones like low-pressure zone and high-pressure zone. If we have more number of nodes in a high-pressure zone where the surplus heads are more, then the algebraic sum of all the surplus heads will provide a large total (large I t ). However, if we have more nodes in low-pressure zones, the algebraic sum of all the surplus heads will provide a small total (small I t ). However, during a pipe failure or large demand variation, if the high-pressure zone is going to get affected, the value of I t will fall drastically. Thus, the value of I t depends on the density of demand nodes in different zones and it will not reflect the resilience properly when the nodes are not distributed evenly. Suppose if a demand node is made into two nodes each with 50% of original demand (total demand is same) and the distance between the nodes is very small, the head at these two nodes will be equal to the head obtained with one node with 100% demand. Thus, when a node is split into two nodes the Total Surplus Head Index will also increase. When nodes are increased, the Total Surplus Head Index will also increase. This index is good only to compare a network with different diameter sets. However, a network cannot be compared with another network based on this index. The value for this depends on the density of demand nodes in the network. Nodes placed densely provide higher value for Total Surplus Head Index. To avoid this, weights may be attached to the nodes. For example, if a node is split into two as explained above, each divided node cannot have a weight equal to the original combined node. The natural weight for nodes can be the supply (or demand) from the node. When a node is split into two nodes as explained above, since the demands are also divided into 50%, a weight of 0.5 to each can be considered. For the whole network, this can be expanded such that each demand node can be given a weight value equal to demand or demand ratio to the total demand. When demand is given as weight, it leads to the power concept. Weighted summation provides a function of total power coming out of the network or the weighted summation multiplied with weight density of water provides the total power coming out of the network. The ratio of total power coming out of the network and total power imparted to the network (flow from reservoir or OHT multiplied by the head multiplied by weight density of

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water + pump power if any) provides dimensionless number indicating resilience. A higher ratio indicates higher resilience. Though not explained as above relating to Total Surplus Head Index of Prasad and Park [5], this ratio was used as power efficiency by Suribabu and Neelakantan [6], Suribabu et al. [7] and as Available Power Index by Liu et al. [4]. Though Liu et al. [4] claim that their Available Power Index (API) is a new index developed by them, the same index is reported in the literature earlier [6, 7].

5 Conclusion In this work, three important resilience indicators popularly used in the water distribution network analysis in the last two decades are critically analyzed analytically and issues identified are discussed. From the analyses, it has been identified that resilience index proposed originally by Todini [8] is better and robust than the other two popular indicators developed later. Notation C h h• H N NRI p q• Q RI R

Based on uniformity in diameter of pipes connected to junction Available pressure head at junction Minimum pressure head at junction Sum of elevation and water level of reservoir Number of junctions Network Resilience Index Surplus head Demand at junction Flow from reservoir Resilience Index Number of Reservoirs

Acknowledgments The authors wish to thank the Civil Department, Kalasalingam Academy of Research and Education, India, for providing support for the research work. The authors are also grateful to thank all teaching members of our department for the suggestion during this project work and for their assistances during the research period.

References 1. Atkinson S (2013) A futures approach to water distribution and sewer network (re) design. Ph.D. dissertation, University of Exeter, U.K 2. Creaco E, Franchini M, Todini E (2014) Generalized resilience and failure indices for use with pressure-driven modeling and leakage. J Water Resour Plann Manage 142(8). https://doi.org/ 10.1061/(asce)wr.1943-5452.0000656

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3. Gheisi A, Forsyth M, Naser G (2016) Water distribution systems reliability: a review of research literature. J Water Resour Plan Manag 142:04016047 4. Liu H, Savic DA, Kapelan Z, Creaco E, Yuan Y (2017) Reliability surrogate measures for water distribution system design: comparative analysis. ASCE J Water Resour Plan Manag 143(2). https://doi.org/10.1061/(asce)wr.1943-5452.0000728 5. Prasad TD, Park NS (2004) Multiobjective genetic algorithms for design of water distribution networks. J Water Resour Plann Manage https://doi.org/10.1061/(asce)0733-9496, (2004)130:1(73) 6. Suribabu CR, Neelakantan TR (2012) Sizing of water distribution pipes based on performance measure and break-repair-replacement economics. ISH J Hydraul Eng 18(3):241–251 7. Suribabu CR, Prashanth K, Vignesh Kumar S, Sai Ganesh N (2016) Resilience enhancement methods for water distribution networks. Jordon J Civ Eng 10(2):216–231 8. Todini E (2000) Looped water distribution networks design using a resilience index based heuristic approach. Urban Water 2(2):115–122

Influence of Steel Fibers on Enhancing the Toughness Property on Concrete: A Simplified Approach Meyyappan Palaniappan , Jemimah Carmichael Milton , Sathya Soroopan Ramasubramaniam , Hariharan Palvannan , and Hariharasudan Sundararaj Abstract The limitations of plain conventional concrete on the strength and durability aspects are effectively addressed by incorporating steel fibers into concrete. Many studies proved that there is a drastic improvement in various engineering properties, especially the impact and abrasion resistance. The estimation of impact and toughness is carried out through the areas under stress–strain curves; moreover, it is a time-consuming process. In this investigation, enhancement of toughness property because of the influence of steel fibers in the range of 1–4% is arrived through a simplified approach based on the past researches outcomes and through the experimental study of impact test results. The toughness property drastically improved around 1.81% of the plain concrete in the addition to 2% of volume fraction of steel fibers. Keywords Steel fibers · Impact · Toughness abrasion resistance

M. Palaniappan (B) · S. S. Ramasubramaniam · H. Palvannan · H. Sundararaj Kalasalingam Academy of Research and Education, Krishnankoil 626126, Tamil Nadu, India e-mail: [email protected] S. S. Ramasubramaniam e-mail: [email protected] H. Palvannan e-mail: [email protected] H. Sundararaj e-mail: [email protected] J. C. Milton Vignan’s Lara Institute of Technology and Sciences, Guntur 522213, Andhra Pradesh, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_22

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1 Introduction Earlier research studies indicate that utilization of steel fibers in conventional concrete gained much more advantages [1, 3]. It is well dominated in order to overcome the practical challenges in the strength and durability aspects of the plain concrete. Many studies are conducted on the different aspects of steel fiber-reinforced concrete, especially on compressive strength, flexural strength, split tensile strength, impact strength, permeability, porosity and so on, with different range of addition of steel fibers in various aspect ratios [2, 4–7]. Especially, steel fiber-reinforced concrete is well known for its better energy absorption capacities and it is measured in terms of impact energy and compression toughness energy [1, 5]. This property is estimated by using the area under the stress–strain curves plotted during the testing of mechanical properties, and the way of estimation involved more complexity in time and work engaged [1, 8, 9]. Hence an attempt is made to investigate the effect of steel fibers with the volume of fraction of 1, 2, 3 and 4% on the plain concrete to improve toughness property, such as impact energy and compression toughness energy in a simplified approach based on the graphical representations and findings through the experimental study of impact drop hammer testing.

2 Material Used and Mix Design As per the standards of IS: 8112-2013, ordinary portland cement (OPC) of 43 grade is used and its specific gravity is 3.15. River sand is used as fine aggregate with the specific gravity and fineness modulus found to be 2.68 and 2.77, respectively. It is confirming to zone II as per the standards of IS: 382-2016. Crushed granites are used as coarse aggregate of size 20 mm with a specific gravity of 2.64 and fineness modulus of 4.67. Crimped circular type of steel fibers is used in this study. Its size is 0.6 mm diameter and 36 mm long with an aspect ratio 60. Potable drinking water is used for mixing and curing purpose. In this investigation, IS: 10262-2009 is used for the design of M40 grade concrete. The mix is designed corresponding to the degree of quality control specified as “very good”. The mix proportions are in the ratio of 1 (C):1.60 (FA):2.30 (CA):0.45 (W/c).

3 Experimental Study The experimental study involves evaluating the impact strength of concrete with and without steel fibers. The percentage of volume fraction of steel fibers in the range of 0, 1, 2, 3 and 4% are mixed with the conventional plain concrete of the above arrived mix ratio for curing age of 7, 14 and 28 days. Steel cylindrical molds are used for casting the impact test specimens. The size of the impact specimens is

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150 mm (diameter) × 64 mm (height) as recommended by the ACI committee 544. The casted specimens are kept in the mold for a period of 24 h. After demolding, the specimens are allowed to water curing until the day of testing. The testing is done using ACI drop weight impact testing equipment which consists of a standard manually operated 4.5 kg compaction hammer with a drop height of 45 cm. The hammer is dropped repeatedly and the number of blows required for the first visible crack failure on the top surface of the specimen is recorded based on the visual observation. For the ultimate failure, the hammer is dropped again repeatedly until it opens the cracks in the specimen into multiple pieces and the corresponding number of blows is recorded. Based on the experimental test results, the impact energy and compression toughness energies are calculated based on the references with earlier researches [8, 9].

4 Results and Discussions Table 1 shows the test results of the impact resistance, impact energy and compression toughness energy. Brief discussions on the test results are as follows: Table 1 Test results of impact resistance, impact energy and compression toughness energy Volume of Age of steel fibers curing (%) days

0

1

2

3

4

Impact resistance (No. Impact energy (N/m) of blows)

Minimum compression toughness energy (N/m)

First crack

Minimum

Maximum

Ultimate failure

Minimum

Maximum

7

21

28

106.31

141.75

1200

1200

14

33

48

167.06

243.00

1200

1200

28

43

61

217.69

374.63

1200

1200

7

32

49

162.00

248.06

1771

1936

14

51

82

258.19

415.13

1785

1948

28

70

112

354.38

567.00

1837

1973

7

56

98

283.50

496.13

2487

2877

14

95

175

480.94

885.94

2663

2931

28

132

251

668.25

1270.69

2738

2945

7

84

151

425.25

764.44

3148

3573

14

141

259

713.81

1311.19

3202

3586

28

198

375

1002.38

1898.44

3287

3592

7

113

203

572.06

1027.69

3516

3911

14

201

352

1017.56

1782.00

3642

3938

28

276

519

1397.25

2622.38

3789

3946

Fig. 1 Impact resistance versus volume of steel fibers at 28 days

M. Palaniappan et al. Impact resistance (No. of blows)

272 600 500 400 300 200 100 0

1

2

3

4

5

Volume of steel fibers (%)

First crack

Complete failure

4.1 Impact Resistance In the conventional concrete (without any steel fibers), the first crack and ultimate failure is occurred at the 21st blow and 74th blow, respectively, for the curing age of 7 days. Similarly, for 14 days and 28 days the first crack occurred at 33rd blow and 43rd blow. The ultimate failure occurred in 43rd blow and 74th blow for 14 days and 28 days, respectively. It seems that as age of curing days increased, the impact resistance also increased for concrete with and without steel fibers content. Due to the effective formation of C-S-H gel, the 28 days impact resistance is increased by 2 times and 2.6 times for the first crack failure and ultimate failure in comparison with 7 days resistance. When 1% volume of steel fibers is added on the conventional concrete, the ultimate failure occurred at the 112th blow, in which the impact resistance is 1.6 times higher for the 28 days strength. If the percentage of steel fibers to 2, 3 and 4% of its volume fraction, the ultimate failure occurred at 251st blow, 375th blow and 518th blow, respectively, and its impact resistance significantly increased to 3.39 times, 5.06 times and 7.01 times, respectively. It is observed that as volume of steel fibers increased, the impact resistance also increased, as shown in Fig. 1. Hence, this volume of steel fibers is strongly showing directly proportional character toward impact resistance property. The energy absorption capacity is increased by the influence of steel fibers content. Due to the presence of steel fibers content, the brittle character of the conventional concrete is modified to the ductile character due to high yielding capacity.

4.2 Calculation of Impact Energy In reference with the past researches [8, 9], the minimum and maximum impact energy of the concrete with and without steel fibers content is calculated by using the principles of kinetic energy as mentioned in Eqs. 1 and 2, respectively.

Influence of Steel Fibers on Enhancing the Toughness … 3000

Impact energy (N/m)

Fig. 2 Impact energy versus volume of steel fibers at 28 days

273

2500

Minimum impact energy

2000

Maximum impact energy

1500 1000 500 0

0

1

2

3

4

5

Volume of steel fibers (%)

(EI )min =

1 MV2 Ni 2

(1)

(EI )max =

1 MV2 Nu 2

(2)

where M is the mass of the drop hammer (4.5 kg), V is the drop speed of the hammer during impact (1.5 m/s) which is arrived from the height of drop hammer (45 cm), Ni is the number of blows required for first crack failure and Nu is the number of blows required for ultimate failure of the specimen. Ei min and Ei max are the minimum and maximum impact energy in N/m. For the calculation of impact energy, ‘Ni ’ and ‘Nu ’ values are taken from the experimental impact testing study. The minimum impact energy and maximum impact energy for the conventional concrete at the age of 28 days is calculated as 217.69 and 374.63 N/m, respectively. For 4% of steel fibers, the minimum and maximum impact energy is at the peak of 1397.25 and 2622.38 N/m. For each percentage of volume fractions of steel fibers, the impact energy has much improved; however, the drastic enhancement is apparently seen up to 2% volume fraction of steel fibers. The increment is around 2.3 times. When the volume of steel fibers is increased further to 3 and 4%, the impact energy is increased, but the boosting factor is only around 1.49 times and 1.38 times, respectively. It is clearly distinct that the beyond the increase of 1% steel fibers, the rate of increment is drastic due to the presence of more amounts of steel fibers (as reflected in Fig. 2) and its blending with binding materials; hence energy absorbance undergoes yielding behavior until it completely failed.

4.3 Calculation of Compression Toughness Energy The compression toughness energy is estimated based on the graphical representation as indicated by the past few researches [8, 9]. In reference to that relationship between compression toughness energy and impact energy for different aspect ratio of the steel fibers, the minimum and maximum compression toughness values

Fig. 3 Compression toughness energy versus volume of steel fibers at 28 days

M. Palaniappan et al. Compression toughness energy, (N/m)

274 4500 4000 3500 3000

Minimum Compression Toughness

2500 2000

Maximum compression Toughness

1500 1000

0

1

2

3

4

5

Volume of steel fibers, (%)

are correlated. The correlation was made between the natural logarithmic ratios of corresponding impact energy to the impact energy of the conventional plain concrete with corresponding aspect ratio of the fibers. Constantly the compression toughness energy of the conventional plan concrete is 1200 N/m irrespective of the age of curing days. In addition to 1% of volume fraction of steel fibers, the maximum compression toughness energy is increased by 1.64 times than plain concrete. Similarly for 2% of volume fraction of steel fibers, the incremental factor is raised to 1.81 times. Even though the maximum compression toughness energy increased for 3 and 4% of volume fraction of steel fibers, but the rate of enhancement decreased to 1.21 times and 0.9 times, respectively, as seen in Fig. 3. It indicates that when the volume of fibers added more, the ability of the material initiated undergoes plastic deformation. The result clearly reveals that the conventional plain concrete failed in brittle mode and due to the presence of steel fibers the failure pattern is modified to elasto-plastic mode. Even after the initial crack, the fibers are able to sustain and carry further until complete/collapse failure.

5 Conclusions The impact resistance is increased with the increase in volume fraction of steel fibers. In a maximum of 4% of volume fraction of steel fibers, resistance is increased up to 7.01 times of the conventional concrete. Beyond the increase of 1% steel fibers, the enhancement rate of energy absorbing capacity is drastic and it is around 2.3 times of conventional, since the material undergoes yielding behavior until it completely failed. The optimum compression toughness energy is optimum in the range of 2–3% of volume fraction of steel fibers on the concrete. Based on the simplified approach of the past researches, the toughness property of steel fiber-reinforced concrete is arrived through the experimental study of impact test results.

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References 1. Sharda S, Singh M, Singh S (2016) A review on properties of fiber reinforced cement-based materials. IOSR J Mech Civil Eng 13:104–112 2. Mohammadi Y, Singh SP, Kaushik SK (2008) Properties of steel fibrous concrete containing mixed fibres in fresh and hardened state. Constr Build Mater 22:956–965 3. Atis CD, Karahan O (2009) Properties of steel fiber reinforced fly ash concrete. Constr Build Mater 23:392–399 4. Shende AM, Pande AM, Pathan MG (2012) Experimental study on steel fiber reinforced concrete for M-40 grade. Int Ref J Eng Sci 1, 043–048 5. Balendran RV, Zhou FP, Nadeem A, Leung AYT (2002) Influence of steel fibers on strength and ductility of normal and lightweight high strength concrete. Build Environ 37:1361–1367 6. Katzer J (2006) Steel fibers and steel fiber reinforced concrete in civil engineering. Pac J Sci Tech 7, 53–58 7. Niu D, Jiang L, Bai M, Miao Y (2013) Study of the performance of steel fiber reinforced concrete to water and salt freezing condition. Mater Des 44:267–273 8. Dabbagh H, Amoorezaei K, Akbarpour S, Babamuradi K (2017) Compressive toughness of lightweight aggregate concrete containing different types of steel fiber under monotonic loading. AUT J Civil Eng 1:15–22 9. Marar K, Eren O, Celik T (2001) Relationship between Impact energy and compression toughness energy on high-strength fiber-reinforced concrete. Mater Lett 47:297–304

Behavior of Zero-Cement Mortar: An Experimental Study Jagan Sivamani and Mohammed Sulaiman

Abstract In this study, an attempt is made to study the performance of the mortar by complete eradication of cement with the use of alternative pozzolanic materials, such as ground granulated blast furnace slag (GGBS), bagasse ash (BA), and rice husk ash (RHA). This research focuses mainly on evolving a zero-cement mortar (Z-cem) using supplementary cementitious materials (GGBS, BA, and RHA) with chemical activators like sodium hydroxide in combination with sodium silicate. Five different levels of replacement Z1, Z2, Z3, Z4, and Z5 were proposed to study the optimum level of replacement of pozzolanic materials. Chemical activators having the concentration of 9 M were used in the ratio of 2.5 and 5% by its weight to bind the pozzolanic materials. Various studies such as workability property by slump cone test with mechanical properties like compressive strength, split tensile strength, and durability properties like water absorption and fire resistance tests were performed. Results show that the blending of pozzolanic materials activated by alkaline activators as a complete replacement to cement will perform better, both in terms of strength and durability. Keywords Z-cem · Pozzolanic materials · Strength · Durability · Ground granulated blast furnace slag · Bagasse ash and rice husk ash

1 Introduction Production of cement has increased rapidly due to the urbanization and industrialization [1]. Construction materials such as cement and aggregates play an integral part in concrete production. Among them, cement holds more integrity as it plays J. Sivamani (B) Faculty, School of Environmental and Construction Technology, Kalasalingam Academy of Research and Education, Anand Nagar, Krishnankoil, Srivilliputhur 626126, Tamil Nadu, India e-mail: [email protected] M. Sulaiman Student, School of Environmental and Construction Technology, Kalasalingam Academy of Research and Education, Anand Nagar, Krishnankoil, Srivilliputhur 626126, Tamil Nadu, India © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_23

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a vital role in the hydration process [2]. During such hydration process, C-S-H gel is formed which augments the strength of the concrete. But considering the environmental aspects, the production of cement affects the global environment because of the release of harmful carbon dioxide gas into the atmosphere [3]. Industries on the whole are involved in the production of 25 billion tons of carbon dioxide around the globe. On an average, 1.5 billion tons of cement was produced every year which may rose up to 2.9 billion tons in the near future [4]. This may lead to imbalance in the life cycle of the environment. An alternative method of infrastructural development without the use of cement could be a cognitive solution. This has necessitated the use of pozzolanic materials having cementitious properties as the complete replacement to cement. Utilization of pozzolanic materials as a partial replacement to cement yields positive results to some extent in previous research studies [1, 5, 6, 7]. Research on the complete replacement of cement through the blending of various pozzolanic materials was still a gap which is to be studied. This research on replacement of cement with two/three pozzolanic materials fills the gap and could be an added advantage over geopolymer concrete as it initiates the safe utilization of industrial and agricultural waste. With this as a concern, pozzolanic materials such as ground granulated blast furnace slag (GGBS), bagasse ash (BA), and rice husk ash (RHA) were used as pozzolanic materials for the complete replacement to cement. Pozzolanic materials are finer materials that contain silica and/or alumina. Such pozzolanic materials do not possess any cementing property but in reaction with oxides/hydroxides of calcium, they do so. Ground granulated blast furnace slag (GGBS) is a waste produced by quenching of molten iron [8]. Around 100 million tons of GGBS were produced, out of which 35 million tons were used properly and rest was disposed of [8]. Similarly, 2.5 million tons of fiber residues were being produced during the extraction from sugarcane industries [9]. Such waste fibers are being burnt into ashes and disposed into the land which creates environmental issues. Also, rice husk ash (RHA) is another waste of 110 million tons produced from rice-processing mills. Out of which 22 million tons were being disposed of as waste [10]. Usage of GGBS (40%), FA (30%), and RHA (30%) with activators Ca (OH)2 , NaOH, and KOH in the range of 2.5–5 M will yield better results [1]. To make the pozzolanic materials reactive, alkaline activators should be added at an appropriate amount. Also, the type of alkaline activators has a greater influence on the strength of the concrete. Increase in molarity of alkaline activators will increase the strength of concrete but care should be taken in the percentage of addition of the activators [1]. Activation of pozzolanic materials upon addition of 3–5% of alkaline activators by weight of mix yielded better results. Addition of pozzolanic materials beyond 5% shows the same strength at a level of 5%. This is mainly because the excess of alkaline activators beyond 5% remains unreactive. This, in turn, forms weaker bond which may collapse in a prolonged period of time. Among the various activators, usage of potassium-based activators will retard the reaction process which will nullify the development of strength in concrete [1]. Addition of superplasticizers will also have a greater influence on the role of activators [5]. Some activators do not possess better flowing property even after the addition of superplasticizers. Also subjecting the pozzolanic materials initially to heat treatment will have an influence in

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improving the activity property of the pozzolanic material [6]. Sugarcane bagasse ash collected from industry was also subjected to post-treatment to improve the amount of silica content, as silica is a major constituent of a pozzolanic material [1]. Usage of pozzolanic materials with high porous nature will make the concrete highly permeable forming loosely packed structure when investigated under SEM [1]. Addition of various mineral admixtures like metakolin and silica fume can overcome the effect of porosity and eventually improve the strength of the concrete [8, 11]. Considering all such parameters, our current study examines the performance of zero-cement mortar cubes prepared using GGBS, BA, and RHA with sodium hydroxide in combination with sodium silicate as an activator. In our study, GGBS, BA, and RHA were replaced completely to cement under five different mix combinations. Workability, strength, and durability properties of mortar under such five replacements were studied to analyze the optimum level of replacement of pozzolanic materials.

2 Materials and Methodology Preparation of Materials Ground granulated blast furnace slag (GGBS), rice husk ash (RHA), and bagasse ash (BA) were chosen as pozzolanic materials for this study. GGBS was collected from the iron industry which remains as a residue [8] and preheated to 350 °C to improve its activity [6]. Bagasse ash was collected from the sugarcane industry located at Thoothukudi and post-treated to improve the silica content to make it behave as a pozzolanic material. Rice husk ash was collected from the agricultural land in the nearby village of Melur, Madurai, India. M sand passing through 2.36 mm with fineness modulus 2.76 was used as fine aggregates in this study. Sodium silicate solution in combination with sodium hydroxide prepared at 9 M was used as activators to activate the pozzolanic materials and water confirming to IS 456:2000 was used in this study. Various properties of ingredients of Z-cem mortar used in this study was tested and presented in Table 1 (Fig. 1). Preparation of Alkaline Activators Alkaline activators are prepared by adding sodium hydroxide solution in combination with the sodium silicate solution. Alkaline activator at 9 M was prepared by dissolving Table 1 Properties of ingredients of Z-cem mortar

S. No

Properties

Values

1

Specific gravity of GGBS

2.85

2

Specific gravity of BA

2.68

3

Specific gravity of RHA

2.14

4

Specific gravity of M sand

2.65

5

Fineness modulus of M sand

2.76

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J. Sivamani and M. Sulaiman

GGBS

BagasseAsh

Rice HuskAsh

Fig. 1 Pretreated pozzolanic materials

360 g of sodium hydroxide in 1000 ml of water and adding the same in sodium silicate solution. It is then properly stirred and the solution is prepared one day prior to mixing in concrete. Prepared alkaline activators were used at 2.5 and 5% by weight of the mix in the mortar (Fig. 2). Mix Proportions Mortar mix proportions as presented in Table 2 were prepared to study the properties of mortar. Mortar mix of 1:3 with w/b ratio of 0.45 was adopted for this study. A total of 75 specimens were prepared based on mix combinations from Z1 to Z5 to study its strength and durability properties. Various combinations of mix design used in this study are presented in Table 2. Preparation of Mortar Specimens Mortar cube specimens of size 75 mm × 75 mm × 75 mm and mortar cylindrical specimens of size 100 mm × 200 mm were prepared to study the properties of Z-cem mortar. Pozzolanic materials and fine aggregates were quantified based on the mix

Fig. 2 Preparation of alkaline activators

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281

Table 2 Proportions of raw materials S. no.

Combinations

GGBS

RHA

BA

OPC

1

Z1

60

30

10

0

2

Z2

55

35

10

0

3

Z3

50

30

20

0

4

Z4

40

30

30

0

5

Z5

70

20

10

0

combinations. Quantified materials were then hand mixed thoroughly with alkaline activators for about 3–5 min. After mixing, specimens were filled with the mortar mix compacted under three layers using the tamping rod at each level to ensure proper compaction. The top surface of the specimens is leveled using the trowel to achieve smooth finishing. It is then kept in a hot air oven at 100 °C for about 24 h. Once the specimens set, it is then cured at room temperature for about 7 and 28 days (Fig. 3). Testing of Mortar Specimens Fresh property study such as slump cone test was conducted as per IS 7320 [12]. Various tests conducted on mortar specimens include compressive strength on cubes, split tensile strength on cylinders, water absorption, and fire resistance test. Flow property of concrete was performed as per the IS7320 [12] testing procedure. Strength of mortar specimens was performed to study the hardened property as per IS4031 [13]. Water absorption test to check the permeability property was performed to study the permeable nature of mortar as per IS1124 [14] . Fire attack test to check the resistance of concrete against fire was performed in accordance with IS3809 [15]. Fig. 3 Casting of mortar specimens

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3 Experimental Procedure Workability Workability of the concrete was performed using the slump cone test. Slump cone test was performed using slump cone of 100 mm top diameter, 200 mm bottom diameter, and 300 mm height as per IS standards. Spread of the mix upon lifting of slump cone filled with mix under standard procedures was determined which reveals the cohesive and fresh property state upon addition of pozzolanic materials. Based on the height of the slump retained, the slump can be categorized as a true slump, shear slump, and collapse. Mix with higher slump value will produce higher workability. Compressive Strength Test Compressive strength test was carried out on standard 75 mm × 75 mm × 75 mm cube specimens [13] at the age of 7 days and 28 days under five different levels of replacement having alkaline activators at 2.5 and 5% by weight of the mix. For each mix combination, three cubes were tested at the curing age of 7 and 28 days using a compression testing machine. Average of three specimens was taken as final reading to check if there is an increase in +5% or −5% in the variation of test results as per IS456:2000. The ultimate load divided by the cross-sectional area of the specimen will give the compressive strength. Split Tensile Strength Test Split tensile strength test was carried out on standard 100 mm × 200 mm cylindrical specimens [13] at the curing age of 7 and 28 days under five different levels of replacement having alkaline activators at 2.5 and 5% by weight of the mix. For each mix combination, three cylinders were tested at the curing age of 7 and 28 days under universal testing machine. Average of three specimens was taken as final reading to check if there is an increase in +5% or −5% in the variation of test results as per IS456:2000. Maximum load at which the specimen fails was noted down. Water Absorption Test Water absorption test was conducted on cube specimens of size 75 mm × 75 mm × 75 mm as per IS1124 [14]. Specimens were initially weighed and measured as M1 and immersed in distilled water for 28 days at room temperature without any external disturbances. After curing period, specimens were taken out, dried at room temperature, and weighed again as M2. The difference in weight measured provided the rate of permeability of water through it. Fire Resistance Test Fire resistance test was conducted on cube specimens of size 75 mm × 75 mm × 75 mm to study the resistance of pozzolanic materials against fire attack in accordance with IS3809 [15]. Mortar specimens casted under five different combinations were burnt at a temperature of 300 °C for 2 h. Burnt specimens are then allowed to cool

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down and tested against compression. Percentage of reduction in the strength is the measure of resistance against fire attack.

4 Results and Discussion Workability Workability of concrete under five different levels of replacement of pozzolanic materials was performed using a slump cone test. Slump value for the mix combinations is presented in Fig. 4. From the results, it is evident that the Z5 combination mix exhibits improved workability compared to all other combinations. This is because of the higher percentage of GGBS content in the mix. Among the pozzolanic materials, GGBS is finer having more surface area compared to other pozzolanic materials. As the surface area increases, the rate of absorption increases, making the concrete mix stiffer [16, 17]. Also with respect to other mix combinations, it could also be confirmed that mix with higher GGBS content will provide better workability to the mix. Compressive Strength Test Compressive strength test for five different mix combinations of mortar at the curing age of 7 and 28 days is presented in Fig. 5. In this study, the compressive strength test was conducted on all five different mix combinations by varying the alkaline activators at 2.5 and 5% by weight of the mix. Results indicate that Z5 mix combination shows higher compressive strength of around 39.63 MPa for the mix 5% weight of alkaline activators and 38.17 MPa for the mix 2.5% weight of alkaline activators at the curing age of 28 days. Compressive strength of the mortar at the age of 28 days was found to be 18% more compared to conventional 33 grade mortar specimens. This attribute is due to the presence of finer pozzolanic material like GGBS at higher percentages. Also, it can be found that increase in the percentage of alkaline activators added at 9 M increased the compressive strength of mortar cubes. Fig. 4 Slump cone test

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Fig. 5 Compressive strength at the age of 7 and 28 days

Split Tensile Strength Test Split tensile strength test for five different mix combinations of mortar at the curing age of 7 and 28 days is presented in Fig. 6. In this study, split tensile strength test was conducted on all five different mix combinations by varying the alkaline activators at 2.5 and 5% by weight of the mix. Results indicate that Z5 mix combination shows higher split tensile strength of around 2.70 MPa for the mix 5% weight of alkaline activators and 2.63 MPa for the mix 2.5% weight of alkaline activators at the age of 28 days. This attribute is due to the presence of finer pozzolanic material like GGBS at higher percentages. Also it can be found that increase in the percentage of alkaline activators added at 9 M increased the compressive strength of mortar cubes. Water Absorption Test

Fig. 6 Split tensile strength at the age of 7 and 28 days

Split tensile strength (MPa)

With respect to the test results from the hardened property, it is clear that the Z5 combination exhibits higher strength property compared to other mix combinations. Also, it could be found at unique that as the percentage of alkaline activator increases, strength increases irrespective of percentage of replacement of pozzolanic materials. Among the mix combinations, Z5 shows a reduced rate of water absorption compared to other mix combinations. This is due to the fineness of GGBS added in the mix combination. As a result of it, voids gets filled up which reduces the porosity of 3 2.5 2 1.5 1 0.5 0

Combinations with Activators 7 days

28days

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Fig. 7 Water absorption at the age of 28 days

the mix. As a result of reduced porosity, the rate of water absorption by the Z5 combination mix get reduced. Also, it could be observed that the rate of absorption of water is higher for Z4 combination mix. In Z4 combination, the percentage of rice husk ash and bagasse ash replaced is more. Naturally, these two pozzolanic materials have higher water absorption capacity, as a result of which interconnected pore networks are formed in the mix. This attributes to the higher rate of water absorption of Z4 mix combination. Water absorption of five different mix combinations at the curing age of 28 days is presented in Fig. 7. Fire Resistant Test Fire resistance test was performed in accordance with IS3809: 1979 and resistance of zero-cement mortar against fire at the age of 28 days was presented in Fig. 8. Results reveal that the rate of resistance against fire for Z5 mix combination is more compared to other mix combinations. Reduction in compressive strength is around 9% for Z5 combination mix. This is due to the higher fire resistance capacity of GGBS. As a result of which, the percentage reduction in compressive strength is more in Z5 mix combination.

Fig. 8 Fire resistant at the age of 28 days

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5 Conclusion From the experimental investigations the following conclusions were derived as follows: 1. GGBS and BA contains a moderate amount of silica, whereas RHA has a higher percentage of silica. Silica content in GGBS, BA, and RHA was activated by pretreatment, which enhances the strength property of Z-cem mortar. 2. Workability is achieved more while preparing the mortar mixture comprising higher values of GGBS and RHA compared to other mortar mixes. This is mainly due to the increase in the fineness of GGBS and RHA. Increase in the fineness will preferably increase the workability of mortar specimens. 3. Compressive strength value for the mortar containing 70% of GGBS ranges from 38 to 40 MPa which is around 18% greater than the strength of the mortar prepared from OPC 33 grade cement at 9 M. This clearly shows that the higher percentage of addition of GGBS improves the strength of the mortar [1, 5, 6]. 4. It also could be inferred that pozzolanic materials which are being activated by a higher percentage of chemical activators show higher strength compared to conventional mortar mix of 33 grades. This clearly demonstrates the role of the sodium silicate solution in activating the pozzolanic materials. Strength increase of zero-cement mortar at 70% GGBS by adding sodium silicate of 5% at 9 M is 18% greater than conventional mortar [5]. 5. Also, strength increase of zero-cement mortar at 70% GGBS by adding sodium silicate of 2.5% at 9 M is 13.5% greater than conventional mortar. From these two results, it could be clear that higher strength could be achieved by increasing the alkali activator and GGBS at 9 M level. Addition of alkaline activators beyond 5% did not show further improvement in the strength of the mortar which was confirmed with the previous studies done [1, 6]. 6. Water absorption results show that the percentage of water absorption by mortar ranges from 1.93 to 2.0% by adding higher amount of GGBS. This is mainly due to the less porous structure formed in GGBS mix compared to other mix combinations. This impermeable nature plays a vital role in improving the strength of mortar and enhancing the durability property of the mortar [10]. 7. Fire resistance test results show that there is a reduction in compressive strength from 10% for Z5 mix combinations. The combination with higher GGBS content shows lesser resistance against fire compared to other mix combinations. 8. Research on whole summarizes that GGBS could be an effective pozzolanic material for replacement of cement and also, in addition, rice husk ash and bagasse ash added can improve the strength and durability property of Z-cem mortar. Also reduction in CO2 emission could also be achieved with complete eradication of cement as it is the major contributor toward CO2 emission. This, in turn, improves the sustainability in construction.

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Acknowledgements The authors would like to express their sincere gratitude to the management of Kalasalingam Academy of Research and Education who consistently encouraged the faculty members for the promotion of research.

References 1. Karim MR, Zain MF, Jamil M, Lai FC (2015) Development of a zero-cement binder using slag, fly ash, and rice husk ash with chemical activator. Adv Mater Sci Eng 1 2. Mehta PK (1999) Concrete technology for sustainable development. Concr Int 21 3. Malhotra VM (2006) Reducing CO2 emissions. ACI Concr Int 28 4. Chana P (2011) Low carbon cements: the challenges and opportunities. In: Proceedings of the Future Cement Conference & Exhibition, pp 1–7 5. Muazam Akthar S, Srinivasan R, Yaswanth B (2016) Zero cement concrete with upgraded properties. Int J Civ Eng Technol 7 6. Siddique R, Kaur D (2012) Properties of concrete containing GGBS at elevated temperature. J Adv Res 3 7. Anbarasan S, Sneha V (2015) Eco-friendly zero-portland cement self cured concrete through geopolymerization of fly ash and blast furnace slag powder. In: Proceedings of the International Conference on Engineering Trends and Science & Humanities, pp 45–54 8. Oner A, Akyuz S (2007) An experimental study on optimum usage of GGBS for the compressive strength of concrete. Cem Concr Compos 29 9. Modani PO, Vyawahare MR (2013) Utilization of bagasse ash as a partial replacement of fine aggregate in concrete. Procedia Eng 51 10. Givi AN, Rashid SA, Aziz FNA, Salleh MAM (2010) Assessment of the effects of rice husk ash particle size on strength, water permeability and workability of binary blended concrete. Constr Build Mater 24 11. Rashad AM, Sadek DM (2017) Investigation on Portland cement replaced by high- volume GGBS pastes modified with micro-sized Metakolin subjected to elevated temperatures. Int J Sustain Built Environ 6 12. IS 7320 (1974)—Specification for concrete slump test apparatus 13. IS 4031 (1988)—Evaluation of strength of mortar 14. IS 1124 (1974)—Method for determination of water absorption 15. IS 3809 (1979)—Fire resistance for structures 16. Punmia BC, Jain AK, Arun K, Jain AM (2003) Basic civil engineering, 2nd ed. Firewall Media, India 17. Science of Concrete. http://iti.northwestern.edu/cement/index.html

An Efficient Fire Detection System Using Support Vector Machine and Deep Neural Network Archana Venugopal , Febi Justin , Linju Santhosh , Riya Binny , and NG Resmi

Abstract Fire is a dangerous disaster. Uncontrollable fire can cause massive destruction to life and property. Hence fire detection and alarming is a crucial and everdemanded topic. A fire alarm must be functionally capable and reliable. This paper mainly focuses on a real-time system for fire detection. Videos acquired from CCTVs or webcams are converted to a sequence of images which are then fed to the classifier. Upon detecting fire from the images extracted, an alert is sent to the authorities concerned. Support vector machine (SVM) and deep neural network are used to develop the proposed fire detection system. Both the algorithms are employed to build classification models. Their performances are then compared and the model which gives better accuracy is selected. Keywords Machine learning · Image processing · Support vector machine · Deep neural network · Data mining

1 Introduction Disasters are highly disruptive events that cause suffering, deprivation, hardship, injury and even death. They may also lead to the interruption of commerce and business, the partial or total destruction of critical infrastructure such as homes, hospitals, and other buildings, roads, bridges, power lines, and so on. There are many causes for disasters which are both man-made and natural. One such cause of disaster is fire. Fire can be widespread like a forest fire, or it can be over a small region like a house caught on fire. In either case, it causes great damage and havoc to both people and materials. Late knowledge of the impending danger and delay in making important decisions are major causes of damage during fire disasters. A. Venugopal (B) · F. Justin · L. Santhosh · R. Binny · N. Resmi Muthoot Institute of Technology & Science Varikoli, P.O, Puthencruz, Ernakulam, Kerala, India e-mail: [email protected] URL: http://www.mgmits.com R. Binny e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_24

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Figure 1 depicts the rates of fire alerts in different forest density classes across regions in India. In 2003, the fire detected in very dense forests is below 4000, and in moderately dense forests and open forests, it is in the range of 12000. In 2009, the fire in very dense forests is the same as in 2003, and in moderately dense and open forests, it increases to 16000. In 2016, the fire detected in very dense forests is equal 4000, and in moderately dense forests, it has the range of 16000 and in open forests, it decreased to 12000. Figure 2 depicts the rates of deaths due to fire accidents in India. Fire causes around 24000 death per year and a lot of people lose their houses. In 2003, 22449 people lost their life in fire disasters. In 2016, the human death is reduced to 19513. In recent years, there is slight decrease in the rate of human death.

Fig. 1 Fire alerts in different forest density classes across regions. Source https://www.downtoearth. org.in/news/environment/forest-fires-in-india-increased-by-125-per-cent-in-last-two-years-60349

Fig. 2 Number of deaths due to accidental fire in India till 2014. Source https://www.newslaundry. com/2016/10/19/ndia-has-averaged-59-deaths-per-day-due-to-accidental-fires-in-13-years

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Taking these factors into account, an emergency alert system is being proposed as a source of warning for fire detection. The paper proposes a system that is capable of detecting fire with good classifier accuracy. The rest of the paper is organized as follows: Sect. 2 gives the literature survey, Sect. 3 presents the methodology used by the proposed fire detection system and Sect. 4 provides the results and discussion.

2 Literature Survey Since fire detection is a crucial process, many methods exist for the same. Various papers have been published for detecting fire. This section focuses on the methods and algorithms that already exist for fire detection. It covers discussion on machine learning and deep learning methods. In an earlier fire detection system, heuristic fixed threshold values were used for fire detection. An image processing-based system which employs statistical color model and binary background mask is presented in [1]. An RGB video sequence is taken as input, which is then converted into frames. These frames are passed through the HSI transforms to get the binary background mask for the frame differences. Finally, it finds the fire spot without using any heuristic threshold value. This system claims to figure out the fire spot quickly without any time delay as well as span a wider region as compared to conventional sensor-based systems. Another system which uses computer vision and image processing techniques to detect fire flames based on study of the fire properties besides an alarm notification system is given in [2]. Live sequences of red, green, blue (RGB) images are acquired from web cameras. Background subtraction is applied on each of the adjacent pairs of images to detect movement of fire. Color-based modeling is then used to detect actual fire. Alarm or SMS/emails are sent to the registered authorities contact number. Yet, another method uses hue, saturation, value (HSV) model [3]. The method uses HSV and YCbCr (Luminance; Chroma: Blue; Chroma: Red) color models to separate orange, yellow, and high brightness light from background and ambient light. Fire growth is analyzed and calculated based on frame differences. Difference between the two frames should be positive and large enough to be able to detect fire growth. To ensure that it is actual fire, five-time fire growth between consecutive frames has been checked. The system activates the alarm sound and provides image notification on detecting fire. A more sophisticated method uses artificial neural networks (ANNs). ANNs are statistical learning algorithms that are inspired by properties of the biological neural networks. They are used for a wide variety of tasks, from relatively simple classification problems to speech recognition and computer vision. A fire detector using neural network is presented in [4]. First, the flame color features based on the hue, saturation, intensity (HSI) color model are trained by a back-propagation neural network for flame recognition. Fire regions are separated from the images. Those regions or background images which have orange/red color but are not actual fire are removed

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using image difference method and the invented color masking technique. Finally, users are informed with a warning signal. Machine learning methods are used in [5] for developing a flood protection system. An artificial intelligence (AI) component has been developed for detection of abnormal dike behavior. Dike is a stop bank or flood bank which maintains the water level. The AI module has been integrated into an early warning system (EWS) platform and validated on real-time measurements from the sensors installed in a dike. A more accurate model using support vector machine is discussed in [6]. Support vector machine (SVM) is an image classification algorithm. Data set images are divided into training sets and validation sets. Training sets are given as input for SVM to train the system and build classification model. The trained system is then tested for its accuracy using the validation set images. The basic idea is to adopt a red, green, blue (RGB) color model for extracting fire-pixels, then static and dynamic flame shape characteristics can be calculated, and the decision function is based on SVM algorithm. Image processing step helps to extract the features which are used to calculate the fire indicator. The images are fed into SVM. Based on the fire color and static dynamic shape of the fire, the classifier separates fire and non-fire images. Reference [7] uses a method called convolutional neural networks (CNNs). CNNs are neural networks with more number of layers and a huge amount of input data set images. Human neural system is the main model for this technology. It generates a sophisticated representation of data and classification is more correct and accurate. First, the labels required in the problem are discovered. This can be achieved by analyzing all the images and removing duplicate images. The images are given as input and the system is trained to create a model. A new input image without a label is given to this model and the accuracy is tested. An ideal system would classify the image correctly. Reference [8] focuses on object detection. Object detection is the process of classifying the image and identifying the location where the object is placed. The location is given by outputting the bounding box. Deep CNN is a great technique used for object detection. CNN is a type of artificial neural network with more than three layers. The pooling layers used are max pooling, average pooling, deformation pooling, spatial pyramid pooling and scale-dependent pooling. Different problems such as partial/full occlusion, varying illumination conditions, poses and scale pose a challenge for object detection.

3 Methodology A CCTV or webcam captures live videos of the surroundings. These videos are processed and frames are extracted from the video. Images thus extracted from the video undergo preprocessing steps such as enhancement. The preprocessed images are given as input to the classifier for detecting any occurrence of fire. SVM and

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Fig. 3 Basic architecture of a fire detection system

deep neural network (DNN) are used in this paper for this purpose. Accuracy of the mentioned algorithms is computed to evaluate their performance. An alert in the form of message is sent to the concerned authority in case of a fire. Figure 3 shows the basic architecture of the proposed system.

4 Results and Discussion The first phase is video acquisition where the video can be obtained through either CCTV cameras, web cameras or any other source. The video is then converted uniformly into frames of 360 × 480 pixels. These images are fed as input to SVM and deep neural network for training and testing. The input dataset has a mixture of labeled fire and non-fire images. SVM uses 70% of the input images for training and rest 30% are used for testing. DNN network is also trained using the collection of images obtained from videos. Another set of images, again a mix of fire and non-fire

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Fig. 4 Confusion matrix of SVM classifier

images, is given for testing the system using both the algorithms. Accuracy in testing is measured in either case. The algorithm which gives better accuracy is selected.

4.1 Training and Testing SVM A total of 1033 images are fed to the SVM. Each image is of JPEG format. The images so generated from videos are of height 360 pixels and width 480 pixels. Figure 5 presents the accuracy rate of the classifier when fed with images. 500 images given as input to SVM belong to class Fire and 533 images belong to class No Fire. 70% of these images are used for training the network and the rest 30% images are used for testing. True class of the tested image, predicted class and the accuracy of classification is outputted as the final result. Figure 4 presents the confusion matrix of SVM classifier. From 500 images, 231 fire images were classified correctly and 269 were classified incorrectly as non-fire images. Similarly, from 533 non-fire images, 454 images were classified correctly and 79 were classified incorrectly as fire images. Figure 5 presents the number of images versus accuracy for SVM classifier during testing. First 200 images were used for training. The number of images was increased during each training session. The graph first decreased and then increased.

4.2 Training and Testing Using DNN Images are fed to the DNN, with number of images ranging from 100 to 500. Each image is of size 360 pixels in height and 480 pixels in width. A set of fire and non-fire images are given as training set for DNN. Similarly, another set of images is given as testing set. The test set contains 50 images for fire and 96 images for non-fire cases. Each set of images undergo 3 epochs, each outputting an accuracy value. For instance, for 200 images, epoch 1 outputs a value 0.9887, epoch 2 outputs value 1.00 and epoch 3 outputs value 1.00. Similarly, this repeats for a total of sets with 400, 600, 800 and 1000 images. The accuracy obtained in each case is plotted.

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Fig. 5 Accuracy versus number of images

Figure 6 shows the accuracy obtained (on testing using DNN) against the total number of images in the input dataset for 1, 2 and 3 epochs. Figure 7 shows the confusion matrix for DNN. There are a total of 100 images of which 50 are fire and 50 are non-fire images in the dataset used for prediction. Out of these, 46 images were correctly classified as fire, 4 images were classified as non-fire and 50 images were correctly classified as non-fire.

Fig. 6 Graph showing number of images versus accuracy of deep learning algorithm

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Fig. 7 Confusion matrix of DNN

The fire detection system employing SVM and DNN is capable of detecting fire from videos captured using CCTVs or webcams with good accuracy.

References 1. Cho BH, Bae JW, Jung SH (2009) Image processing-based fire detection system using statistic color model 2. Bayoumi S, AlSobky E, Almohsin M, Altwaim M, Alkaldi M, Alkahtani M (2014) A real-time fire detection and notification system based on computer vision 3. Seebamrungsat J, Praising S, Riyamongkol P (2014) Fire detection in the buildings using image processing 4. Horng WB, Peng JW (2006) Image-based fire detection using neural networks 5. Yang X, Wang J, He S (2012) A SVM approach for vessel fire detection based on image processing 6. Pyayt AL, Mokhov II, Lang B, Krzhizhanovskaya VV, Meijer RJ (2011) Machine learning methods for environmental monitoring and flood protection 7. Pan B, Shi Z, Xu X (2012) MugNet: deep learning for hyperspectral image classification using limited samples 8. Yang W, Liu Q, Wang S, Cui Z, Chen X, Chen L, Zhang N (2018) Down image recognition based on deep convolutional neural network

Engineering Properties of Heavyweight Concrete—A Review B. P. Sharath and Bibhuti Bhusan Das

Abstract Heavyweight concrete which differs from normal weight concrete by having a higher density and special compositions to improve its attenuation properties, the density and cost of the material are really important in order to absorb gamma rays. If the main aim of developing heavyweight concrete is focussed to attenuate neutrons, then the material with less atomic weight should be embodied in the concrete mix which can in turn produce hydrogen. It is used in counterweights of bascule and lift bridges, but its general application includes in radiation shielding structures, offshore, ballasting of pipelines etc. The evolution of nuclear power into peaceful applications has given rise to an expanding use of heavy weight concrete in construction industries nowadays. Heavyweight concrete employs bulky conventional aggregates such as barites or magnetite or artificial aggregates such as Fe ore or Pb shots. This paper states a review on impact on engineering properties of Heavyweight concrete such as compressive, split tensile and flexural strength with different heavyweight aggregates as per the investigations conducted by researchers. Keywords Heavyweight · Compressive strength · Split tensile strength · Flexural strength · Density of concrete

1 Introduction The most common applications of heavy weight concrete are to safeguard the emitting radiations, counterweights and in other such areas wherein a high density is needed. The major factor which differentiates the conventional one from this, is the inclusion of bulk aggregates in the due course of its production. The basic definition of this heavyweight concrete itself says that it should have a specific gravity of more than B. P. Sharath (B) Research Scholar, Department of Civil Engineering, NITK, Surathkal, 575 025 Mangalore, India e-mail: [email protected] B. B. Das Asst. Professor, Department of Civil Engineering, NITK, Surathkal, 575 025 Mangalore, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_25

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2600 kg/m3 and the bulky aggregates, going in it should have more than 3000 kg/m3 . The esteemed fillers which are commonly employed in yielding bulky concrete are conventional ones such as barite, magnetite, limonite and artificial ones such as steel and Fe shots. The other various types of aggregates which can be utilized as heavyweight aggregates in concrete as a partial or fully replaceable to conventional concrete are described in the subsequent section. Nowadays, the most emerging applications of this heavyweight concrete is in radiation shielding structures which has become mandatory depending upon the recent development taking place all around the world and regarding that, the use of such kind of materials have come into picture.

1.1 Heavyweight Aggregates in Heavyweight Concrete The materials which are commonly used in this special type of concrete are as follows which can be bifurcated into two categories depending upon there source of availability, nature and respective properties. Among these, first category comprises minerals which have got significantly higher values of specific gravity and atomic weight as well and also, are synthetic by nature which are referred all in as ‘Heavyweight aggregates. The Second category comprises minerals boron content which is particularly capable of absorbing thermal neutrons without producing highly penetrating gamma rays. [ASTM C638-14]. All these are tabulated below in Table 1. Table 1 Different minerals with their specific gravity’s Sl. No.

Name of the group to which it belongs

Name of the mineral

Specific gravity

1

Iron minerals

Hematite (Fe2O3)

5.26

2

Ilmenite (FeTiO3)

4.72 ± 0.04

3

Lepidocrocite (FeO (OH))

4.09

4

Goethite (HFeO2)

4.28 ± 0.01

5

Limonite

2.7–4.3

6

Magnetite (FeFe2O4)

5.17

Barium minerals

Witherite (BaCO3)

4.29

Barite (BaSO4)

4.50

Boron minerals

Ferrophosphorus

5.72–6.50

10

Paigeite ((Fe ++Mg) Fe +++BO5)

4.7

11

Tourmaline (Na (Mg, Fe, Mn, Li, Al)3Al6[Si6O18]·(BO3)3(OH,F)4)

3.03–3.25

7 8 9

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The main objective of this paper is to review the behaviour of these different heavyweight aggregates in concrete and to understand the impact of the same on engineering properties of concrete reported by various authors during their findings.

2 Engineering Properties of Heavyweight Concrete Heavyweight concretes have been investigated for various aspects in accordance to their necessity and possible application areas in industries in the past, which were mainly focused on the observation of behaviour of the incorporated ingredients on mechanical and armouring properties of it [1]. As mentioned previously, native minerals and ‘mechanical ones’ which can be used as aggregates in high density concrete are hematite, magnetite, limonite, barite and steel punchings and iron shots. It is necessary that these bulky aggregates should be apathetic w.r.t alkalis, oil-free, no adhering of non-native covers which all can be an untoward effect on adherence of paste to the aggregate particles on cement hydration [2]. All the values for the engineering properties of concrete are taken from the table (in appendix) and are plotted in the form of graphs as (Figs. 1 and 2).

Fig. 1 Comparison of compressive strength of different authors at 28 days

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Comparison of Split Tensile Strength of Diff erent Aut hors at 28 Days 10 SO CIO

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Fig. 2 Comparison of split tensile strength of different authors at 28 days

2.1 Discussion of Compressive, Tensile and Flexural Strength at 28 Days From Fig. 3, following interpretations can be drawn for different authors. Reference [3] developed bulk concrete mixtures with varying water/cement ratio’s ranging 0.3–0.6 to find out the ultimate appreciable water/cement ratio of bulky C o m p a ri son of F l e xu ral St r e n gt h of Dif f erent Aut ho rs at 28 Days

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Fig. 3 Comparison of flexural strength of different authors at 28 days

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concrete yielded with barite. Also, there was a utilization of two different types of cement that is PKC 32.5 and PC 42.5 in the experimental analysis. Three cylindrical standard specimens with Ø 15 × 30 cm were used for each water/cement ratio. Experimental results in the case of slump shows that it has increased with an increment in the water/cement ratio and also there was nothing such significant difference in slump for both cement types. In the case of compressive strength, it had dipped with an increment in the same. The peak values for strength for concretes obtained from PC was 42.6 MPa at 0.40 w/c ratios. Another similar study was carried out by [4], wherein he had produced heavyweight concrete by incorporating three normal and 2 heavyweight aggregates, using 3 low water/cement of 0.30, 0.35 and 0.40 to obtain different compressive strengths. A high-performance concrete superplasticiser was employed as chemical admixture in order to the heavyweight concrete workable. In this study, the slump of all concrete mixes ranged between 150 and 200 mm. Added to that, standard specimens with standard dimensions were casted for tensile strength. From experimental results, it can be seen that strength boosts with low water/cement ratio as anticipated. Based on hematite aggregates, another inspection was done out by Sagar et al. [5] on the behaviour of the replacement of conventional coarse aggregates with the same (in 0–50 at 25% intervals) on the as usual basic properties of concrete. Along with this percentage replacement of hematite, three levels of additional cementitious material, that is silica fume was supplemented (in 5, 10 and 15%) by the weight of cement. The properties of concrete were studied for their 28-days strength using the same as usual standard specimens casted for the respective tests to be conducted. By looking at the results obtained for basic properties of concrete, there is not much significant difference in them compared to that of control one, which gives a conclusion that hematite coarse aggregates can be used for making heavyweight concrete without much affecting the above properties. Reference [2], developed concrete mixes using bulky fine aggregates as an alternative for conventional ones at 20, 40, 60, 80, and 100%, by weight. Fresh mixtures were casted into standard specimens for investigating compressive strength. Other mixtures were casted in the respective as usual standard specimens for tensile strength test. Compressive strength at 28 days revealed that there was an increase in it gradually when the substitution levels were (as mentioned above) respectively, in contrast to the reference one. It dropped by 15% when the substitution percentage hiked to 100%. The results showed that the one with 60% of HFA displayed the peak values for compressive strength among all other ones. Tensile strength at 28 days indicates an increase in when conventional fine aggregates were replaced with bulky fine aggregates at ratios (as mentioned above) in contrast to the reference mixture; while it dropped when the substitution percentage escalated from 80 to 100%. The results indicated that the one with 60% bulky fine aggregates had peak values for tensile strength among all the other ones.

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Reference [6], tried to add barite (powdered) as a replacement for sand to investigate the impact of this on basic properties of concrete. Five concrete formulations where performed and were designated accordingly. Experimental Results showed that compressive strength at the end of 28 days was high for the mix M5. This can be justified by saying that concrete density had boosted up with the introduction of a denser compound. In the case of tensile strength, it had dipped with the varying barite incorporation and it comes out to be up to 50% for the total substitution for fines. Reference [7], aimed at investigating the effect of colemanite on properties of concrete as a replacement to aggregates. Five mixes were designed (PC, CC10, CC20, CC30, CC40 and CC50) wherein the aggregates were replaced at 10, 20, 30, 40, 50% by colemanite. Cement content and w/c were fixed in the all mixtures. Standard test specimens were casted for investigating the respective properties. All the properties were tested for 28 days age. From the strength results, it can be known that all the ones with colemanite showed a dip as it’s addition increases. This can be justified by saying that there was a weak adherence between cement paste & colemanite. From the tensile strength results, it can be known that the strength with colemanite was lower than that of PC. The values ranged from 3.7 to 2.2 MPa. The peak one was 3.7 MPa for PC and lowest one was 2.2 MPa for CC50. It also dropped by the increment in colemanite addition ratio. Reference [8], attempted to design heavyweight concrete using two heavyweight aggregates such as hematite and laterite and studied the physical and mechanical properties of concrete. Here, in this experimental work, two concrete mixes were developed wherein the first mix comprises replacement of conventional coarse aggregates with hematite aggregates (in 0, 25, 50, and 100%) and in another mix, it was done with laterite aggregates (varied in the same percentage). W/c of 0.4 was adopted and the specimens for compressive split tensile and flexural strength were prepared according to the respective dimensions for that particular tests which were 150 × 150 × 150 mm, Ø 15 × 30 cm and 10 × 10 × 50 cm respectively. All the three properties of concrete were tested for their 7- and 28-days age. Firstly, in case of workability, slump test results have revealed that there is a dip in its values when there is an increase in percentage of heavy weight aggregates. This may be due to the variation in water absorption values of aggregates. Also, it can be seen that laterite stones have greater values of absorption compared to that of hematite stones which was reason for lower slump for laterite concrete. Split tensile strength was maximum for hematite concrete, 3.70 N/mm2 , for 50% replacement level and for laterite concrete, it was 2.68 N/mm2 , for 25% replacement level. Flexural strength was more for hematite concrete, 7 N/mm2 for 25% replacement level and that for laterite concrete it was 6.16 N/mm2 for 25% replacement level. Reference [9] studied the strength development of concrete at various ages, wherein there was a substitution for conventional cement which was nothing but conventional pozzolan. Split tensile strength results he had come to know that it was maximum with portland cement and minimum with natural pozzolan. From this, it can be concluded from the experimental results obtained by using a part of Portland

Engineering Properties of Heavyweight Concrete—A Review

303

cement, it can be encouraged to re-utilize it even though it poses a negative impact over the environment, but since because it facilitates in bringing down the cost of construction, helps in improving the engineering properties of concrete (mainly in the building construction activities), it can be considered as the most feasible material to look after for such kinds of added advantages especially in construction phases. Reference [10], had tried to develop the heavyweight concrete using the discarded products from industries, which were iron fillings, rebar pieces and barites to study the compressive strength at an age of 7, 28 and 90 days and flexural strength at 28 days age of concrete. Three mixes were set which were designated as OC, BC and AC depending upon the type of aggregates utilized in that particular mix. Each end product was prepared using a unvarying w/c ratio. For compressive strength test, cubic shaped specimens with a dimension of 15 cm and for flexural strength test, prismatic specimens with dimensions (100 × 100 × 500) mm were casted. The flexural strengths for ‘AC’ concrete were higher than those for ordinary concrete (OC) by thirty-five %. Rebars and iron powders have increased the flexural strength. Reference [11], used Hematite and Laterite as heavyweight aggregates to study their performance w.r.t the properties of concrete. Two mixes were developed based upon the type of utilization of aggregates. Standard sized specimens were casted for studying the desired property. From tensile and flexural strength results, it can be observed that the concrete’s with heavyweight aggregates showed more values compared to the control one. Reference [12], aimed at studying the engineering properties of concrete like compressive and split tensile strength at 28 days wherein he had developed two different mixes with the same w/c ratio and cement content by using fine grinded iron dross and a mix of steel punchings with sizes less than 11.2 mm as aggregates. The traditional concrete aggregates were replaced by steel treatment waste in the amount of (in 50% (S50) and 100% (S100)). From the results, it can be seen that strength of bulky concrete declines with incremental steel treatment waste in it. The final compressive strength of concrete specimens with 50% and 100% steel treatment waste aggregate was 40.7 and 36.6 MPa. This can be due to the angular shaped fillers and umiform surface of steel punchings, creating a woozy contact between the cement paste and fillers.

2.2 Discussion of Compressive Strength at the Age of 3, 7, 14, 28 and 90 Days From Fig. 4, the following interpretations can be done which are, for [11], among the two mixes, the maximum strength was obtained for the mix M30 2 at 7, 14 and 28 days which concluded that heavyweight concrete had more strength values compared to normal one. For [9] The compressive strength with 80% C + 20% PU declines substantially at 7 and 28 days compared to the conventional one without pozzolan.

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Compressive Strength (MPa)

Comparison of Compressive Strength of Different Authors at 3, 7, 14, 28 and 90 Days 90

Vidhya et al M30 1

80

Vidhya et al M30 2

70

VLM et al 100% PC

60

VLM et al 80+20 PU

50

Salah et al D

40

Salah et Hc

30

Salah et al Hf

20

Salah et al ILc

10

Salah et al ILf 0

20

40

60

80

100

Salah et al ACSc

Curing Days

Salah et al ACSf

Fig. 4 Comparison of compressive strength of different authors at 3, 7, 14, 28 and 90 days

Reference [13] investigated the impact of Silica Fume on strength characteristics of heavyweight concrete containing IOT aggregates such as hematite, ilmenite and air-cooled slag. By looking at the complied results of split tensile strength, it can be observed that, it tends to increase for all the ones as the curing duration increases. The rate of strength development is dependent on the cementing activity of silica fume as well as the properties of the aggregates incorporated. From the result’s point of view, mixes containing slag have given peak values for strength values than those containing conventional aggregates, hematite and ilmenite by about 10, 52 and 20%, respectively. From Fig. 5, the following interpretations can be done which are, for [14], the concrete mix with magnetite have shown distinctive dominating values than those Comparison of Compressive Strength of Different Authors at 7, 28 and 90 Days Compressive Strength (MPa)

90 80 70 60 50 40 30 20 10 0 0

20

40

60

Curing Days

80

100

ASO M1 ASO M2 ASO M3 ASO M4 ASO B1 ASO B2 ASO B3 ASO B4 ASO G1 ASO G2 ASO G3 ASO G4 ASO S1 ASO S2 ASO S3 AS et al HA25 AS et al LA25 CB B2 CB A3 CB A4

Fig. 5 Comparison of compressive strength of different authors at 7, 14, 28 and 90 days

Engineering Properties of Heavyweight Concrete—A Review

305

containing other substitutes at the age of 7 days. For 28 days strength, the magnetite and barite concretes with 10% Silica Fumes showed ≥600 kg/m3 , than that of same aggregate mixes but with 20% FA and 30% GGBS. On the other hand, the strength of concrete containing Br aggregates was almost near to M60 and it had escalated to 90 days. This increment in strength gives an implication that fumes with its more outer area and content supplies a padding impact and a cementing reaction, thus resulting in a advancement by arresting wimpish Ca(OH)2 binder with the setting up of a sound binder of C-S-H gel, that imparts an added strength compared to FA and GGBS. For [8], it is seen that maximum compressive strength for hematite concrete is 47.26 N/mm2 for 25% replacement of coarse aggregate with hematite stone and that for laterite concrete is 42.03 N/mm2 for 25% replacement of coarse aggregate with laterite stone. Beyond 25% replacement, value shows a decreasing tendency for both the types of concrete. This may be because of higher porosity of both the materials than natural coarse aggregate., which while increasing it, may decrease the strength of concrete. Reference [15], developed 15 different concretes using mixing diversified ratios of basic ingredients along with barite. The objective was to find the ideal water/cement ratio and cement dosage in concrete and to analyse the compressive strength for the different mixes at 7, 28 and 90 days. The 15 mixes were produced into 5 varying series each having 3 varied catgories which was done based on mixing values, that is if the entire volume consists of only normal aggregates, then that concrete was termed as A. If it had barites, it was termed as B, if it had fines as normal and coarse as barites, called as AB, if it was vice versa, called as BA, and the final one, if it had 50% normal and another 50% barite aggregates, called as K. All these 5 sets of concrete in three different series consists of w/c of 0.65, 0.51 and 0.43 respectively. Samples used for determining the strength were of dimensions Ø 15 × 30 cm. Experimental results tell that there was no significant variation in unit weight of concrete for different w/c ratio’s. The maximum value obtained was 3507 kg/m3 , for B type’s concrete for a w/c ratio of 0.5. In case of compressive strength, even though the ratio of 0.43 gave the peak values for strength, the appreciable one was for 0.51. So therefore, it can be abated that binding ratio of 0.5 was favourable for bulky concrete.

2.3 Discussion of Density of Concrete From Fig. 6, the interpretation can be done for various authors with respect to the density of concrete wherein it has behaved in varying nature depending upon the type of material utilized in the concrete. For [2, 4, 7–14, 16, 17], had reported a raise in the mass-by-volume ratio of concrete with the substitution of extra additives, which were nothing but the heavyweight aggregates such as Barites, Hematite, Laterite, Ilmenite, Red Sand, Siderite, Steel Shots, Colemanite and combinations of Iron Dross and Steel shots.

306

B. P. Sharath and B. B. Das Comparison of Density of Concrete w ith respect to different authors and additives 5000

AS O B2 (Barite) AS et al HA100 (Hematite)

4500

AS et al LA100 (Laterite)

Density (kg/cum m)

4000

CB B3 (Barite)

3500

YE et al 50 (Barite)

3000

BC (Barite) VLT et al 80+20 PU

2500

ASO M6 Red Sand 2000

K Vidhya et al M30 2 (Hematite) SAA et al ILf Ilmenite fine

1500

YuE et al S100 (Siderite)

1000

MM et al S0 (Steel Shot) 500 0

OG et al PC (Colemanite) Author

JK et al S100 (Iron Dross+Steel Punchings)

Fig. 6 Comparison of density of concrete with respect to different authors and additives

So, it can be summarized that there will be definitely an increase in the both the densities of concrete (in fresh & hardened states) with the addition of any other new heavyweight aggregates in concrete.

3 Conclusion It can be concluded that there was a drastic change in the engineering properties of concrete irrespective of different heavyweight aggregates admixed with the conventional ones. 1. From compressive, split tensile and tensile strength point of view (at all ages), it can be said that it had increased with the increasing percentages of replacements up to some point, after which, it had decreased. But some have reported it had not much affected them. All the behaviour depends upon the properties of materials being added. 2. From density point of view, it can be seen that it had increased for whatever additive admixed in the concrete with the conventional ones which gives a promising indication of increase in the density in both the states, but it again depends upon the varying nature of additive materials [1].

Engineering Properties of Heavyweight Concrete—A Review

Appendix: Review of Engineering Properties of Concrete with Respect to Various Authors

307

4

3

Athira Suresh et al

Ilker Bekir Topc¸u

1.Hematite 2. Laterite 3.Replaced with conventional aggregates (0, 25, 50 & 50%)

Barite

LA100

LA0 LA25 LA50

HA100

HA0 HA25 HA50

42.5 0.30 0.35 0.40 0.45 0.50 0.55 0.60

Note

32.5 0.30 0.35 0.40 0.45 0.50 0.55 0.60

Note

28 Days 31.8 31.1 31.2 29.2 28.6 27.6 26.0 1. Examined with seven different w/c ratios. 2. Two different cements PKC 32.5 & PC 42.5 ; w/c ratio 0.3-0.6 28 Days 40.1 39.4 42.6 35.9 35.6 33.8 32.5 7 Days 28 Days 29.55 38.01 42.23 47.26 40.35 44.67 25.46 30.59 29.55 38.01 34.23 42.03 31.41 37.48 14.67 26.07

M - Magnetite B - Barite G - Goethite S- Serpentine ‘1’ set – 10% SF ‘2’ Set – 20% FA ‘3’ Set – 30% GGBS ‘4’ Set – Barite Fine aggregate

28 Days 2.14 3.27 3.7 3.3 2.14 2.68 2.32 1.75

28 Days 6.13 7.00 6.16 3.80 6.13 6.16 5.14 3.01

Hardened 2393 2652 2790 3004 2393 2617 2630 2663

1. Water cements ratios of 0.4 were adopted. 2. From col (I), HA25 and LA25 had highest values i.e. 47.26 N/mm2 and 42.03 N/mm2. Beyond 25% strength, it had dipped. 3. From (II), (III) and (IV), max. was for HA50, LA25, HA100 and LA100 respectively.

2. Concretes at w/c ratio of 0.40 give the highest strength and the most favourable one

1.Cement dosage was accepted as constant at 350 kg/m3 because this one was the most common in application for the determination of components.

3.M4 had greater strength than B4 and G4. 4.B1, B2 and B3 exhibited highest density values in both the conditions. M1, M2 & M3 had slightly more values compared to the normal one. 5.G1 & G2 met the requirements of dense concrete; Dipped for all S series mixes.

308 B. P. Sharath and B. B. Das

Basyigit

Yüksel Esen et al

B. Sagar Singh et al

5

6

7

1. Barite CA 2. Series of concrete wherein conventional CA replaced with Barites (0, 10, 20, 30, 40 50%). 1. CA replaced by Hematite with Natural FA

15 different concrete; Mixing in different ratio of cement, aggregates and Barites

M25; H C 25 50

0% 10% 20% 30% 40% 50%

Note

A2 B2 AB2 BA2 K2 A3 B3 AB3 BA3 K3 A4 B4 AB4 BA4 K4

28 Days 3.53 3.46 4.35

32.57 35.57 34.19

28 Days 9.03 9.23 8.56 7.64 7.08 5.85

28 Days for M25 Mixes

7 Days 28 Days 90 Days 17.4 24.7 35.1 18.6 27.4 33.1 18.2 27.0 36.9 17.8 25.0 37.1 18.1 26.2 38.1 30.5 38.6 49.5 23.9 37.3 46.4 28.0 38.4 48.1 27.4 37.8 48.9 27.8 38.0 47.4 43.1 51.9 59.8 36.9 38.8 47.4 38.1 47.1 54.4 35.0 40.0 52.3 37.6 43.3 57.5 Normal aggregate Concrete: A Barite aggregate concrete: B FA Normal + CA Barite: AB CA Barite + FA normal: BA 50% agg normal + 50% barites: K 2,3,4 indices diff. w/c ratio 0.65, 0.51, 0.43 28 Days 56.72 59.58 58.45 55.94 55.22 50.09

4.33 3.54 3.58

28 Days

Hardened 2231 2340 2413 2521 2638 2728

Hardened 2406 3414 3061 2821 2911 2464 3507 3124 2856 2988 2482 3452 3083 2830 2986

Hematite CA can be used for making heavy weight concrete, without affecting much the compressive, split tensile and flexural strength of concrete.

1. W/C ratio was taken as 0.60 to obtain a slump value of 5 cm. Cement dosage: 400 kg/m3 2. From (I), highest was for 10% barites, 59.58 MPa. The same can be seen in the case of (II). 3. From (IV), there was an increasing trend with the increase in the barite ratio.

3.From col. (V), it can be seen that there was an increase in the values w.r.t the increase in the Barite rates. The max. value for B3 (3507 kg/m3)

2.Even though, concrete with w/c 0.43 gives the highest strength, the favourable was obtained at w/c ratio of 0.51.

1.w/c ratio of 0.51 is favourable for heavyweight concrete.

Engineering Properties of Heavyweight Concrete—A Review 309

8

Ş. Kılınçarslan

1. Barite, normal & artificial agg.

2. 3 levels of SF at (5, 10 and 15% were used by wt. of cement. 3. Design was for M25 & M35 grades of concrete H: Hematite CA SF : Silica Fume

OC BC AC

25 5SF 25 10SF 25 15SF 50 5SF 50 10SF 50 15SF M35; H C 25 50 25 5SF 25 10SF 25 15SF 50 5SF 50 10SF 50 15SF 7 Days 37.3 33.5 36.2

3.29 3.27 3.49 3.79 28 Days 3.539 3.468 4.352 3.9 3.97 3.29 3.52 3.66 3.796

35.81 33.71 35.62 36.67 28 Days for M35 Mixes 43.97 44.62 39.55 39.26 44.21 45.63 36.44 41.63 46.44 90 Days 56.7 53.1 55.6

3.97

32.85

28 Days 50.2 45.8 47.3

3.90

31.11

28 Days 4.21 4.34 6.45

4.57

4.185

3.73

3.93

3.86

3.38

3.79 3.58 4.96

28 Days

4.55

4.52

3.69

4.44

3.65

4.12

Fresh 2443 3450 3276

1.From (I), values for AC were higher than that of NC by 10% after 28 and by 7% after 90 days.

310 B. P. Sharath and B. B. Das

1.Replacing 50 % FA partially by Steel shots 2. Designed for M35 grade

1. Design of heavyweight concrete with Heavyweight agg. as a substitute for conventional agg.

Van Lam Tang et al

Dr.V Vasugi

Ahmed S. Ouda et al

9

10

11

Replacement of Portland Cement with Natural Pozzolan in Vietnam

2. Iron Fillings & Rebar Pieces as artificial agg .

M0 M1 M2 M3 M4 M5 M6 M7

1: 1.9 : 3.5

Note

100 PC 80 PC 20 PU

Note

23.5

33.6

7 Days

39.05

32.53

28 Days 48.95 51.30 53.13 54.96 50.21 41.52 56.67 40.22

28 Days

37.8

43.1

28 Days

7 Days

35.2

41.3

14 Days

PC: Portland Cement PU: Natural Pozzolan

17.4

24.3

3 Days

OC: Normal Aggregates BC: Barite Aggregates AC: Artifical Aggregates

28 Days 3.15 3.21 3.41 3.52 3.12 2.50 1.48 1.21

2.93

3.34

28 Days

Hardened 2275 2310 2353 2400 2454 2514 2686 2457

2352

2335

Fresh

1. From (I), the values for mixes increased gradually by about 5, 8.5, 12.15, and 2.55% when replacement levels of HFA were 20, 40, 60, and 80%, respectively, compared to control. It dipped by 15.23% for 100% replacement. Among all, M6 had the highest one

1. Replacement of 50% FA by Steel shots had attained more than 90% strength in 7 days itself.

1.Strengths of PU were less than PC 2.Avg. 28-d strength of concrete for 20% PU was 87.7% w.r.t that of normal one. 3.At 7 & 28-days, strength of PU concrete dipped by 30.1 % at 12.3 % respectively. 4.Spilt tensile results at all ages of concrete with PC were more than PU. 5.But, in the case of Density, its vice versa.

2.From (III), values for AC were found to be higher than those of OC by 35%. 3. From (IV), BC was the highest.

Engineering Properties of Heavyweight Concrete—A Review 311

14

Salah A. Abo-ElEnein et al

13

Yüksel Esen et al

K. Vidhya et al

12

1. Siderite 2. Partially replaced for Normal Agg.

1.Two types of Iron ore (Hematite & Ilmenite), Silica Fume, and Aircooled slag (by-product of Iron & Steel Production Plant)

1.Hematite as HA 2. Design done for M30 grade

2.Additional mix consists of replacing of CA by HFA. 3.HFA was Red Sand.

S20 S40 S60 S80

C

Note

D Hc Hf ILc ILf ACSc ACSf

Note

M30 2

M30 1

Note

14 Days 35.46 36.91

28 Days 39.53 42.29

14 Days

28 Days 34.60 47.03 56.12 64.47 69.24

41.59 68.50 24.66 49.54 35.88 46.48 45.46 60.34 42.61 53.82 53.82 75.84 69.11 80.12 D: Dolomite Hc – C Hematite Hf – F Hematite ILc – C Ilmenite ILf – F Ilmenite ACSc – C Air Cooled Slag ACSf – F Air Cooled Slag

7 Days 71.15 54.02 51.17 62.99 57.69 76.45 82.77

90 Days

‘1’ Mix with CA; ‘2’ Mix with HA

7 Days 27.76 29.80

% replacement (0,20,40,60,80,100) (M1, M2, M3, M4, M5) by wt. respectively. M6 (50:50) and M7 (40:60) HFA: Heavyweight Fine Aggregate

28 Days 4.37 5.00

28 Days 4.38 6.70

Hardened 2230 2420 2560 2680 2780

2.35 2.48 2.83 2.72 3.21 2.6 3.02

Hardened

Hardened 2459 3467

1. S80 had highest strength than compared to others. 2. From (IV), the trend shows an increase with the increase in the siderite ratio.

1. ACSf and ACSf had given highest strength compared to D, Hc, Hf, ILc & ILf by 10, 52 and 90% respectively which was due to enhanced interlocking b/w porous textures of slag & cement paste which leads to the improvement of transition zone in it. 2. From (4), the highest one was for ILf

1.Heavyweight concrete had more compressive, split tensile and flexural strength compared to that of normal one. 2.Density of concrete with hematite was more than that with normal one.

2.From (II), the highest among all was mix M3 3.But, from (IV), the highest density was for M6 among all.

312 B. P. Sharath and B. B. Das

1. Use of Barite in powdered form as replacement to sand

Electric arc furnace slag aggregates and Steel Shots

Colemanite

Iron dross (mainly iron oxides) and Steel Punchings

Khaled Saidani et al

M. Maslehud din et al

Osman Gencel et al

Janis Kazjonos et al

15

16

17

18

(20,40,60,80, 100)

29.61

M100

S100

S50

PC CC10 CC20 CC30 CC40 CC50

Note

36.60

4.15

2265

4640

Hardened 3520

2.77 28 Days 4.10

39.04 28 Days 40.7

Hardened 3682 3480 3454 3369 3146

Hardened 2483 2449 2382 2332 2332

1.69

28 Days 3.09 2.35 2.69 1.80

2890

28 Days 3.71 3.86 3.20 3.16 3.06

14 Days 28 Days 49.73 52.59 52.37 55.13 55.87 58.77 60.98 64.40 53.61 55.82 M0 - Shots 100% M1 - Shots 80% + EAFSA 20% M2 - Shots 65% + EAFSA 35% M3 - Shots 50% + EAFSA 50% M4 - Shots 35% + EAFSA 65% EAFSA – Electric Arc Furnace Slag Agg. 28 Days 60.02 64.04 55.23 52.14 45.47

28 Days 32.35 37.97 32.23 29.01

M0 M5 M40 M70

M0 M1 M2 M3 M4

66.07

S100

1.From (1), it can be seen that, there was a decrease in the values as the percentage replacement raised 2. In the case of (II), the maximum was for CC10, but beyond this, it started dipping. 3.From (IV), it was evident that, the control one had higher value . 1.From (I), it was seen that the values for heavyweight concrete declined with increasing iron dross content but from (IV), it was vice versa.

1. 28-day compressive strength was more than that of 14-day value, but it was not that significant 2. Maximum strength, for both 14and 28-days, was noted in M3. 3. From (IV), maximum was in M0 with 100% steel.

1. From (I), it was maximum for M5 and an increase of 17% compared to the control one. Beyond this, it had dipped by 10% only in comparison with M0.

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References 1. Özen S, Sengül ¸ C, Ereno˘glu T, Çolak Ü, Reyhancan IA, Ta¸sdem˙ir MA (2016) Properties of heavyweight concrete for structural and radiation shielding purposes. Arab J Sci Eng https:// doi.org/10.1007/s13369-015-1868-6 2. Ouda AS, Abdelgader HS Assessing the physical, mechanical properties, and γ-ray attenuation of heavy density concrete for radiation shielding purposes. Geosystem Eng https://doi.org/10. 1080/12269328.2018.1469434 3. Topcu ˙IB (2003) Properties of heavyweight concrete produced with barite. In: Cem Concr Res 33:815–822 4. Esen Y, Yilmazer B (2010) Investigation of some physical and mechanical properties of concrete produced with barite aggregate. Sci Res Essays 5(24):3826–3833 5. Singh BS, Ramana KV Mechanical properties of heavy weight concrete using heavy weight coarse-aggregate as hematite (Fe58 High Grade Iron Ore). IJRET: Int J Res Eng Technol eISSN: 2319-1163 | pISSN: 2321-7308 6. Saidani K, Ajam L, Ouezdou MB (2015) Barite powder as sand substitution in concrete: effect on some mechanical properties. Constr Build Mater 95:287–295 7. Gencel O, Brostow W, Ozel C (2010) An investigation on the concrete properties containing colemanite. Int J Phys Sci 5(3):216–225 8. Suresh A, Abraham R (2015) Experimental study on heavy weight concrete using hematite and laterite as coarse aggregate. Int J Eng Trends Technol (IJETT) 28(4) 9. Van Lam T, Nguyen TC, Hung NX, Van Phi D, Bulgakov B, Bazhenova S (2018) Effect of natural pozzolan on strength and temperature distribution of heavyweight concrete at early ages. In: MATEC web of conferences 193, 03024. https://doi.org/10.1051/matecconf/201819 303024 10. Kılınçarslan S (2015) Investigation of heavy concretes produced with heavy artificial aggregates. In: Special issue of the international conference on computational and experimental science and engineering (ICCESEN 2014), vol 128, No 2-B 11. Vidha K, Dhilipkumar R (2015) An experimental investigation on strength characteristic of high densit concrete incorporating hematite. IJIRST–Int J Innov Res Sci & Technol 2(07), ISSN (online): 2349-6010 12. Kazjonovs J, Bajare D, Korjakins A (2010) Designing of high density concrete by using steel treatment waste 13. Abo-El-Enein SA, El-Sayed HA, Ali AH, Mohammed YT, Khater HM, Ouda AS Physicomechanical properties of high performance concrete using different aggregates in presence of silica fume. Hous Build Natl Res Cent, HBRC J 14. Ouda AS Development of high-performance heavy density concrete using heavy density concrete using different aggregates for gamma-ray shielding. In: Housing and building national research center (HBRC). Dokki, Giza, Egypt 15. Basyigit C (2006) The physical and mechanical properties of heavyweight concrete used in radiation shielding. J Appl Sci 6(4):762–766. ISSN 1812-5664 16. Esen Y, Do˘gan ZM (2017) Evaluation of physical and mechanical characteristics of siderite concrete to be used as heavy-weight concrete. Cem Concr Compos 82:117e127 17. Maslehuddin M, Naqvi AA, Ibrahim M, Kalakada Z (2013) Radiation shielding properties of concrete with electric arc furnace slag aggregates and steel shots. Ann Nucl Energy 53:192–196

Experimental Study on Lightweight Concrete with Copper Slag and Pumice Stone, Leca as a Partial Replacement of Aggregates V. Praveen Jesuraj and V. Sreevidya

Abstract The project presents the usage of copper slag, pumice stone and leca (light expanded clay aggregate) for partial replacement of fine aggregate and coarse aggregate. The experimental procedure is conducted for the replacing percentages of 5, 15 and 25%. For this above-mentioned replacement percentage, M20 grade concrete is used with a water–cement ratio of 0.48. For 5% replacement of pumice, the amount of copper slag replaced is 5% with fine aggregate and the amount of pumice replaced is 5% with coarse aggregate. For 5% replacement of leca, the amount of copper slag replaced is 5% with fine aggregate and the amount of leca replaced is 5% with coarse aggregate. Similarly, 15 and 25% replacement of fine aggregate and coarse aggregate is done, respectively. For this purpose, seven sets were prepared to study the compressive strength, split tensile strength and flexural strength. Each set comprises of three cubes, three cylinders and three prisms. The compressive strength test, split tensile strength test, flexure strength test have been done. A comparison study has been done between leca and pumice to identify the suitable alternate for ordinary concrete. The main objective of this project is to know the strength of partially replaced concrete. Keywords Lightweight concrete · Leca · Pumice · Copper slag

1 Introduction Lightweight concrete (LWC) has been widely used in different structural applications and its consumption grows every year on a global basis. These include a reduction in the dead load of the building, which minimizes the dimensions of structural members the production of lighter in size of the structural members; a reduction in the risk of V. Praveen Jesuraj (B) SSM Institute of Engineering and Technology, Dindigul, Tamil Nadu, India e-mail: [email protected] V. Sreevidya Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_26

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earthquake damage; and increased thermal insulation and fire resistance. LWC can be produced in a practical range of densities between about 300 and 2000 kg/m3 and smaller pre-cast elements with inexpensive casting, handling and transportation operations; the provision of more space is due to the reduction. The popular method is carried out by using lightweight aggregate. This may come from either a natural or an artificial source. The main objective of this dissertation is to study the properties of LWC blocks. LWC blocks are cast with 5, 15 and 25% of copper slag replacement of fine aggregate and 5, 15 and 25% replacement of coarse aggregate. The copper slag is a common replacement for fine aggregate. Pumice and leca act as a replacement of coarse aggregate for both concrete blocks.

2 Review of Literature A brief review of the available studies related to the present strength properties of cementitious materials is presented. LWC is not a new technology; its first use was recorded in the early 1920s. Its applications are limited due to the lack of knowledge about its properties and stability [1]. Concrete is a composite material composed of water, coarse granular material (the fine and coarse aggregates or filler) embedded in a hard matrix of material (the cement or binder) that fills the space among the aggregate particles and glues them together [2]. For the replacement of coarse aggregate by pumice aggregate with varying percentages, the density decreases with an increase in the percentage of pumice aggregate. By using 20% of lightweight aggregate as partial replacements to natural coarse aggregate, the compressive strength is promising [3]. The density of LWC typically ranges from 1400 to 2000 kg/m3 compared with that of 2400 kg/m3 for normal weight concrete (NWC). The use of high-strength LWC can reduce the self-weight of structures and cross-sectional areas of structural elements [4]. Tensile strength of concrete is important when considering cracking. Lightweight aggregate concrete presents a flexural and tensile splitting strength slightly inferior to that of NWC of the same compressive strength [5]. Natural lightweight aggregates may be defined as inherently low-density natural mineral materials. The primary user is the construction industry where weight reduction equates to cost savings. Principal products in which natural lightweight aggregate is utilized because of its lower density include lightweight Portland cement concrete and LWC masonry units. In addition, due to location, some natural lightweight aggregates compete with normal weight constructions aggregates [6]. Lightweight aggregate concrete was used for structural purposes since the twentieth century. As per this study, the lightweight aggregate concrete is a material with low unit weight and often made with spherical aggregates [7]. LWC application for construction works has been widely used in these recent years, both for structural and non-structural purposes, due to its advantages over ordinary concrete [8]. The use of LWC has been widely spread across countries such as the USA, the United Kingdom and Sweden [9]. The most popular among them are slag pumice, ash gravel, expanded perlite, volcanic slag, pumice, vermiculite, etc.

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All the porous aggregates have their own characteristic properties, which markedly affect the properties of LWCs. Among the LWCs, pumice concrete was generally considered as being unsuitable for load-bearing uses. For this reason, it has been mainly used for the production of partitions and panel walls [10].

3 Materials 3.1 Cement In this project, for the production of LWC, Ordinary Portland Cement 53 grade is used.

3.2 Copper Slag In this project, for the production of LWC, copper slag is used which is collected from Madurai copper manufacturing factory with a specific gravity of 3.5.

3.3 Leca In this project, for the production of LWC, leca is used which is collected from R-Tech consultancy with a density of 800 kg/m3 .

3.4 Pumice Pumice is used which collected from NM Enterprises, density 1200 kg/m3 with a specific gravity of 1.3.

3.5 Water Water should be avoided if it contains large quantities of suspended solids, excessive amounts of dissolved solids or appreciable amounts of organic materials. Water which is used in this project is conforming to the specification of IS 456:2000.

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4 Mix Proportion Concrete mix design is the manner of selecting suitable constituents of concrete and determining the relative amount of the materials to produce the most economical concrete while holding the specified minimum properties such as strength, consistency, etc. There is no standard method of proportioning the LWC, like conventional concrete. From the literatures reviewed, it is quite significant that the density is the prime factor to be considered for manufacturing the LWC. The properties of LWC are directly or indirectly related to its density, such as the strength of the LWC decreases exponentially with the reduction in its density. Thermal and sound insulation is increased with the reduction in density. So, density is a prime concern for the production of LWC rather than target mean strength in conventional concrete. Six trail mix is cast with a target density of approximately 1500 kg/m3 . The specimens cast for the proportions are shown in the following Tables 1 and 2.

4.1 Mix Procedure The manufacturing procedure is thoroughly different from conventional concrete because mix design is not fit for LWC. It is done by trial and error process. The manufacturing of LWC finishes in two stages. • The copper slag and sand are dry mixed partially and mixed with cement. • The lightweight aggregate is soaked in water for 24 hours. • Then the concrete is prepared by the conventional method using the lightweight aggregate. • SP430-conplast is used to reduce the initial setting time of concrete. Table 1 Mix proportion of lightweight concrete

Table 2 Mix proportion of lightweight concrete

Mix name

Copper slag (fine aggregate) (%)

Pumice (coarse aggregate) (%)

M1

5

5

M2

15

15

M3

25

25

Mix name

Copper slag (fine aggregate) (%)

Leca (coarse aggregate) (%)

M4

5

5

M5

15

15

M6

25

25

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Starting with the first stage, cement and sand are mixed thoroughly for few minutes. Coarse aggregate is added and mixed well again for few minutes until the mix attained a homogenous state. The second stage is started with SP430-conplast. The admixture is diluted with water and made to a solution. Then water was added step by step and mixed well for few minutes until it attained its workability.

4.2 Casting of Moulds After mixing concrete, the material should be placed in moulds as soon as possible to maximize the time availability for mortar to set around the voids before the foam that results in the breaking down of voids. Concrete is used where a reduction in density is required. The formation of large voids as a result of entrapped air rather than entrained air can be prevented by softly tapping the outside of the mould with a rubber hammer during the filling operation. Moulds are generally filled to compensate for some subsidence due to overflowing of water through the bottom of the moulds. For smooth surfaces, moulds are cleaned completely before casting, form oil was applied to the moulds to make sure concrete will not stick to it. The specimens were then left to set for 24 hours. The specimens were demoulded after 24 hours with necessary tools and were transferred for curing to the curing room.

4.3 Curing The curing of the LWC is usually done by two methods: one is moist curing and other is steam curing at atmospheric pressure. In the moist curing, the concretes are usually given a short period of moist curing, generally about 1–7 days and then allowed to air-dry, prior to the application of a moisture-proofing material. The time required for satisfactory air-drying is the smallest in the material with the lowest density. Steam curing at atmospheric pressures at 50–80 °C accelerates the hardening of concretes. Drying shrinkage and moisture movement of concretes after atmospheric pressure steam curing of various durations, up to 24 hours, differ little from those properties of similar concretes after moist curing for 28 days at 21 °C. Steam curing at atmospheric pressure produces strengths generally near those attained after 3 days of the moist curing at 21 °C. In this project, moist curing is done for 28 days.

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5 Result and Discussion 5.1 Compressive Strength Result of the compressive strength test of LWC is given in Figs. 1, 2, 3 and 4. The introduction of copper slag in LWC proportion increases the compressive strength of LWC. Compressive strength increases as copper slag content in proportion increases. The compressive strength of pumice- and leca-replaced specimens after 28 days of curing is given in Tables 3 and 4. 35 30 25 20 15 10 5 0

28Days

M3

M2

M1

CC

7Days

Fig. 1 Compressive strength of lightweight concrete with pumice replacement 35 30 25 20 15 10 5 0

7Days

CC

M4

M5

28 Days

M6

Fig. 2 Compressive strength of lightweight concrete with leca replacement

35

7Days

30

28Days

25 20 15 M3

M2

M1

CC

10

Fig. 3 Compressive strength of lightweight concrete with pumice replacement (line chart)

Experimental Study on Lightweight Concrete with Copper … Table 3 Compressive strength of lightweight concrete with pumice replacement

Table 4 Compressive strength of lightweight concrete with leca replacement

321

Mix

Compressive strength (N/mm2 ) 7 days

Compressive strength (N/mm2 ) 28 days

CC

13.70

30.20

M1

13.20

28.82

M2

12.75

27.64

M3

12.10

26.21

Mix

Compressive strength (N/mm2 ) 7 days

Compressive strength (N/mm2 ) 28 days

CC

13.70

30.20

M4

13.25

27.5

M5

13.18

26.8

M6

12.9

26.1

40 7Days

28Days

30 20 10 0 CC

M4

M5

M6

Fig. 4 Compressive strength of lightweight concrete with leca replacement (line chart)

5.2 Split Tensile Strength Result of split tensile strength test of LWC is given in Figs. 5, 6, 7 and 8. The introduction of copper slag in LWC proportion increases the split tensile strength of LWC. Split tensile strength increases as copper slag content in proportion increases. The split tensile strength of pumice- and leca-replaced specimens after 28 days of curing is given in Tables 5 and 6. 6 7Days

28Days

4 2 0 CC

M1

M2

M3

Fig. 5 Split tensile strength of lightweight concrete with pumice replacement (bar chart)

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7Days

CC

M4

M5

28Days

M6

Fig. 6 Split tensile strength of lightweight concrete with leca replacement (bar chart) 6

28Days

7Days

4 2 0 CC

M1

M2

M3

Fig. 7 Split tensile strength of lightweight concrete with pumice replacement (line chart) 6 4 2 0 CC

M4

M5 7Days

M5

28Days

Fig. 8 Split tensile strength of lightweight concrete with leca replacement (line chart) Table 5 Split tensile strength of lightweight concrete with pumice replacement

Table 6 Split tensile strength of lightweight concrete with leca replacement

Mix

Split tensile strength (N/mm2 ) 7 days

Split tensile strength (N/mm2 ) 28 days

CC

2.5

4.9

M1

2.33

4.57

M2

2.24

4.23

M3

1.98

3.84

Mix

Split tensile strength (N/mm2 ) 7 days

Split tensile strength (N/mm2 ) 28 days

CC

2.5

4.9

M4

2.32

4.42

M5

2.20

4.01

M6

1.82

3.78

Experimental Study on Lightweight Concrete with Copper … 6

323 7Days

4

28Days

2 0 CC

M1

M2

M3

Fig. 9 Flexural strength of lightweight concrete with pumice replacement (bar chart)

5.3 Flexural Strength Test Result of flexural strength test of LWC is given in Figs. 9, 10, 11 and 12. The introduction of copper slag in LWC proportion increases the flexural strength of LWC. Flexural strength increases as copper slag content in proportion increases. The flexural strength of pumice- and leca-replaced specimens after 28 days of curing is given in Tables 7 and 8.

6 7Days

28Days

4 2 0 CC

M4

M5

M6

Fig. 10 Flexural strength of lightweight concrete with leca replacement (bar chart)

6 4 2 7Days

0 CC

M1

M2

28Days M3

Fig. 11 Flexural strength of lightweight concrete with pumice replacement (line chart)

5

28Days

7Days

0 CC

M4

M5

M6

Fig. 12 Flexural strength of lightweight concrete with leca replacement (line chart)

324 Table 7 Flexural strength of lightweight concrete with pumice replacement

Table 8 Flexural strength of lightweight concrete with leca replacement

V. Praveen Jesuraj and V. Sreevidya Mix

Flexural strength (N/mm2 ) 7 days

Flexural strength (N/mm2 ) 28 days

CC

3.32

4.73

M1

3.23

4.62

M2

2.88

4.12

M3

2.73

3.92

Mix

Flexural strength (N/mm2 ) 7 days

Flexural strength (N/mm2 ) 28 days

CC

3.32

4.73

M4

3.18

4.51

M5

2.91

4.023

M6

2.64

3.76

6 Conclusion The present study contains the study of properties of LWC and also the utilization of copper slag in the proportion of LWC. Conclusions drawn from the present study are given below. Compressive strength of the LWC is increased when copper slag is partially replaced by fine aggregate content. It is also observed that increasing content of copper slag in the composition increases the compressive strength of LWC and results in the replacement of fine aggregate by copper slag up to 25%. But, the presence of lightweight aggregate reduces the compressive strength. Comparing leca and pumice concretes, 5% replacement is advisable. It gives a nearer compressive strength like conventional concrete.

References 1. Hindoriya AK, Jain D, Agarwal SC (2016) Study of light weight cellular block. IJSRD 4(03):1383–1384. ISSN (online):2321-0613 2. Tamil Selvi P, Lakshmi Narayani P, Ramya G (2014) Experimental study on concrete using copper slag as replacement material of fine aggregate. J Civil Environ Eng 3. Minapu LK, Ratnam M, Rangaraju U (2014) Experimental study on light weight aggregate concrete with pumice stone, silica fume and fly ash as a partial replacement of coarse aggregate. Int J Innov Res Sci Eng Technol 3(12) 4. Mahdy M (2016) Structural lightweight concrete using cured LECA. Int J Eng Innov Technol (IJEIT) 5(9) 5. Clarke JL (1993) Design requirements. Structural light weight aggregate concrete. Chapman & Hall, London, pp 45–74 6. Bryan DP (1989) Occurrence and uses of natural lightweight aggregate in the Western United States. Lightweight aggregate in Western United States, pp 89–193

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7. Owens PL (1993) Light weight aggregates for structural concrete. Structural light weight aggregate concrete. Chapman & Hall, London, pp 1–18 8. Widodo S (2014) Experimental study on the potential use of pumice breccia as coarse aggregate in structural lightweight concrete. Int J Sustain Construct Eng Technol 5(1) 9. Ismail KM et al (2004) Study of light weight concrete behaviour 10. U˘gur I (2003) Improving the strength characteristics of the pumice aggregate lightweight concretes

Influence of Magnetic Water on Properties of Concrete Paver Blocks R. Malathy, N. Karuppasamy, V. Adithya, and P. Gokulapriya

Abstract Existing paver blocks are brick-like piece made of concrete (cement, sand and aggregates). They are commonly used for exterior flooring. Concrete is the most widely used man-made building material on the planet. Demand of natural sand is one of the setback to the concrete industry. Serious environmental problems formally originated from unrestrained sand and gravel taken from rivers. Owing to high cost of natural sand, there is a need for the construction industry to search for alternate materials. Industrial waste products such steel slag and M-sand were found to be replacement for natural sand. Water is a critical and finite resource that plays a key role in the construction environment. In particular, drinking water quality is depleting due to increasing population and usage at its peak. Magnetic water seems to have some potential impact on quality of water used for construction. In this study, natural sand is completely replaced with M-sand and steel slag and cement content is reduced to about 5–30% optimizing the strength, and an attempt is made to investigate the performance of mechanical properties of paver blocks, when mixed with magnetic water with M30 grade concrete mix. The casted paver blocks are tested for compression and flexural strength. The manufacturing cost of paver block is also less compared to natural sand. It is eco-friendly and cost-efficient in real-time construction industry. Keywords Magnetic water · Steel slag · M-sand · Compressive strength

R. Malathy (B) Professor & Dean (R&D), Department of Civil Engineering, Sona College of Technology, Salem, India e-mail: [email protected] N. Karuppasamy Research Scholar (PhD full time), Department of Civil Engineering, Sona College of Technology, Salem, India V. Adithya · P. Gokulapriya B.E Student, Department of Civil Engineering, Sona College of Technology, Salem, India © Springer Nature Singapore Pte Ltd. 2021 S. K. Shukla et al. (eds.), Smart Technologies for Sustainable Development, Lecture Notes in Civil Engineering 78, https://doi.org/10.1007/978-981-15-5001-0_27

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1 Introduction The history of concrete paver block dates back to nineteenth century when paving stones were used by Europeans for construction of roads serving as footpaths. Existing paver blocks are brick-like piece made of concrete. A huge amount of industrial wastes are produced and are dumped in yards in large scales, which create environmental problems to the society. Calcium carbonate (CaCO3 ) scale deposition on natural waters often leads to numerous technical and economical problems [1]. Water in concrete plays a vital role in strength parameter. Russia started research on using magnetic field treated water (MFTW) to mix concrete in 1962 [2]. The passage of water through the magnetic field of certain strength is called MFTW. MFTW will improve the concrete characteristics explained by the water molecular structure [3]. Magnetic effect on water breaks the cluster into single molecule or smaller ones, which improve the activity of water [4]. Cement particles under hydration process through the MFTW easily penetrate. During hydration of cement particles is in progress the, magnetic field treated water (MFTW) can penerate into the core region of the cement particles and enhances the hydration rate. Into the core region more easily, which implies hydration of cement can be done more efficiently, which in turn improves the concrete strength. A patent claimed in Japan that when concrete is cured using magnetic field, its molecular arrangement orients along uniform direction, which results in increase of strength parameters [5]. Some researchers report that water usually does not take magnetism easily, and it is only a temporary process [6, 7]. The rate of increase in strength after 24 h is very less. After magnetization within certain duration water reclaims its original art of state [8]. The mechanism still remains to be solved since many phenomena in liquid state have not been satisfactorily explained yet. Furthermore, studies on the effect of MFTW on concrete containing granite powder have also been rare. Concrete paver blocks with granite powder will decrease the waste pollution and enhance the engineering properties. The objective of this study is to investigate the mechanical properties of concrete paver blocks mixed with magnetic water at early age, which provides a new way to improve strength properties of concrete paver blocks. The cost and environmental pollution are reduced in this way. Moreover, the effect of magnetic water on the microstructure of paver block is also examined and the mechanism about the effect of magnetic water on the paver block is discussed.

1.1 Magnetic Water In a substance like water, constituent molecules of structural element can be aligned in a definite direction by the influence of an external magnetic field. The molecular group of magnetic water is different from the molecular group of tap water in terms of degree of consolidation, and volume of molecules is more uniformly narrated in Australian fluid energy [9]. Figure 1 shows the arrangement of water molecules in

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Fig. 1 Directional arrangement of water molecules under effect of magnetic field

one direction due to the effect of magnetic field. The cluster contains about 100 water molecules at room temperature. In a magnetic field, magnetic force can break apart water clusters into single molecule or smaller ones [10], and the activity of water gets improved. In a liquid or in a gas, this can only happen to molecules that possess an odd number of electrons. Water (H2 O) contains 10 electrons, so it is not attracted to or oriented by a magnet [11]. In fact water, like most molecules is diamagnetic, and it is actually repelled by a magnetic, although so weakly, these sensitive instruments are needed to observe the effect. The mode of structural arrangements due to uniformity will decrease the bond angle from 105° to 103.5°, which enlarge the fluidity of water. This change in the water molecule composite causes a change in permeability pressure, surface tension, pH and electric conduction, which improves some of the properties of concrete [12].

2 Experimental Design 2.1 Materials A normal PPC grade was used throughout this study. The coarse aggregate used was continuous graded crushed stone with a maximum size of 10 mm [16]. The fine aggregate used was river sand with fineness modulus of 2.74 [17]. The physical properties of coarse aggregate and river sand are given in Table 1 [18]. The tap water used in the experiment is taken from Salem, and the quality of it is shown in Table 2 [15]. Granite powder is obtained from an industry in Salem. Its physical and chemical properties are listed in Table 3. In this study, granite powder is used as a substitute for cement of equal weight in the mixing process.

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Table 1 Physical properties of coarse aggregate, fine aggregate and granite powder

Properties

Coarse aggregate

Fine aggregate

Granite powder

Bulk density (kg/m3 )

1766

1693

2562

Fineness modulus

7.17

2.78

2.43

Shape

Angular

Round

Round

Surface texture

Rough

Smooth

Smooth

Table 2 Quality tests of tap water Properties

Before magnetization

After magnetization

Regulatory standard for tap water IS 3025

Total dissolved solids (TDS) (mg/L)

2050

1350