Sustainable Practices and Innovations in Civil Engineering: Select Proceedings of SPICE 2019 [1st ed.] 9789811551000, 9789811551017

Table of contents :
Front Matter ....Pages i-xii
Studies on the Impact of Ternary Blend for Early Prediction of Compressive Strength Using Accelerated Curing (P. Murthi, K. Poongodi, R. Gobinath)....Pages 1-11
Review Study on Glass Fibre Reinforced Gypsum (GFRG) Panels (S. Ragav)....Pages 13-23
Modelling of Organic Acid Transport in Unsaturated Subsurface System (Berlin Mohanadhas, G. Suresh Kumar)....Pages 25-35
State-of-the-Art Review—Methods of Chromium Removal from Water and Wastewater (D. Rama Devi, G. Srinivasan, S. Kothandaraman, S. Ashok Kumar)....Pages 37-51
Study of Behaviour of Web-Stiffened Built-up Beam (C. Divya Megala, M. Anbarasu)....Pages 53-61
Geotechnical Properties of β-Glucan-Treated Clayey Sand (M. Vishweshwaran, Evangelin Ramani Sujatha, Nadendla Harshith, Cheni Umesh)....Pages 63-73
Composite Leaching of Thermal Power Plant Bottom Ash to Ensure Its Performance on Cement Mortar (Sivakumar Naganathan, Salmia Beddu, Muhammad Zulfiqar Ajmulkhan, Jegatheish Kanadasan, Zakaria Che Muda, Siti Nabihah Sa’don et al.)....Pages 75-79
Enhancing the Performance of Bottom Ash Using Acid Leaching Method (Sivakumar Naganathan, Salmia Beddu, Muhammad Zulfiqar Ajmulkhan, Jegatheish Kanadasan, Zakaria Che Muda, Siti Nabihah Sa’don et al.)....Pages 81-86
An Experimental Investigation of Flexural Behaviour of Ferrocement Box Beams Using Micro Fillers (K. Ramakrishnan, D. Muthu, S. Viveka)....Pages 87-96
An Analytical Framework of Climate Change Impacts on Water Resources: Vulnerability and Integrated Adaptation Strategies (K. Shimola, M. Krishnaveni)....Pages 97-106
Compaction and Permeability Characteristics of Biopolymer-Treated Soil (S. Anandha Kumar, Evangelin Ramani Sujatha)....Pages 107-117
Inflow Forecasting of Bhavanisagar Reservoir Using Artificial Neural Network (ANN): A Case Study (S. Suriya, K. Saran, L. Chris Anto, C. Anbalagan, K. R. Vinodh)....Pages 119-131
Mitigation of Energy Consumption Impact by Planning and Formulation of Environmental Management System for Indian Infrastructure Projects (C. Akin, V. Vandhana Devi, R. Samuel Devadoss)....Pages 133-139
Nitrate Sequestration and Sorption Capacity in Soil Under Varying Organic Loading Conditions (P. Balaganesh, E. Annapoorani, S. Sridevi, M. Vasudevan, S. M. Suneeth Kumar, N. Natarajan)....Pages 141-150
Behaviour of Lignosulphonate Amended Expansive Soil (G. Landlin, M. K. Soundarya, S. Bhuvaneshwari)....Pages 151-162
Push-Out Tests for Determining the Strength and Stiffness of the Channel Connectors—Experimental Study (P. Sangeetha, R. Vijayalakshmi, Aaditya Jagadeesh, S. Ahalya, K. Deveshwar, D. Swarna Varshini)....Pages 163-171
Experimental Study of the Headed Stud Connectors in Composite Structure (P. Sangeetha, S. Ramanagopal, U. Amrutha, A. Balasubramaniam, V. Madhumitha, G. Arun)....Pages 173-181
Compaction Characteristics of Modified Clay Soils with Various Proportions of Crumb Rubber (S. V. Sivapriya)....Pages 183-190
Design and Development of Low-Cost Medium Size Shake Table for Vibration Analysis (R. B. Malathy, Govardhan Bhat, U. K. Dewangan)....Pages 191-203
Experimental Investigation on Suitability of Sea Water for Concrete Mix (K. Srinivasan, E. Arunachalam)....Pages 205-214
Assessment of Emerging Contaminants in a Drinking Water Reservoir (Riya Ann Mathew, S. Kanmani)....Pages 215-225
Estimating the Loss of Water Spread Area in Tanks Using Remote Sensing and GIS Techniques in Ambuliyar Sub-basin, Tamilnadu (N. Nasir, R. Selvakumar)....Pages 227-237
Influence of Zinc on Engineering Properties of Soil (N. Gopinath, M. Muttharam)....Pages 239-248
Sustainability Approaches in Ground Improvement Measures (Gowtham Padmanabhan, Ganesh Kumar Shanmugam, Sathyapriya Subramaniam)....Pages 249-255
Shear Behaviour of Concrete Wall Panels Reinforced with FRP Bars (Y. K. Sabapathy, V. Nithish, S. Vishnu Varadan, K. Udhaya Prabhu)....Pages 257-273
Behaviour of Concrete Filled FRP Tubular Columns Under Axial Compression (S. Ramanagopal)....Pages 275-282
A Study on Flexural Strength of Concrete Beams Reinforced with Manually Pultruded GFRP Bars (Y. K. Sabapathy, C. N. A. Nithish, Sajid Ali, K. P. Priyadarshini)....Pages 283-294
A Novel Technique on Improving the Strength of Concrete Using Microorganisms (S. Lokesh, Ahaned Noorani, S. Sanjay, G. Dhanalakshmi, S. Swaminathan)....Pages 295-308
Glass Fibre Reinforced Gypsum (GFRG) as an Emerging Technology (J. Gokul Krishna, R. Roshan, S. N. Vinothni, S. V. Sivapriya)....Pages 309-324
Immediate Load-Penetration Behaviour of Sand Piles with Sustainable Material (A. Mugesh, J. Niranjan, S. Gunalan, S. V. Sivapriya)....Pages 325-331
Expediency of Sand Compaction Piles and It’s Earlier Studies (R. Manjula, S. V. Sivapriya)....Pages 333-348
Numerical and Experimental Evaluation on the Behaviour of Cold-Formed Steel Box Struts and Prediction of Experimental Results Using Artificial Neural Networks (P. Sangeetha, M. Shanmugapriya, Aaditya Jagadeesh, K. Deveshwar)....Pages 349-357

Citation preview

Lecture Notes in Civil Engineering

S. Ramanagopal Madhavi Latha Gali Kartik Venkataraman Editors

Sustainable Practices and Innovations in Civil Engineering Select Proceedings of SPICE 2019

Lecture Notes in Civil Engineering Volume 79

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

Lecture Notes in Civil Engineering (LNCE) publishes the latest developments in Civil Engineering - quickly, informally and in top quality. Though original research reported in proceedings and post-proceedings represents the core of LNCE, edited volumes of exceptionally high quality and interest may also be considered for publication. Volumes published in LNCE embrace all aspects and subfields of, as well as new challenges in, Civil Engineering. Topics in the series include: • • • • • • • • • • • • • • •

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More information about this series at http://www.springer.com/series/15087

S. Ramanagopal Madhavi Latha Gali Kartik Venkataraman •

•

Editors

Sustainable Practices and Innovations in Civil Engineering Select Proceedings of SPICE 2019

123

Editors S. Ramanagopal SSN College of Engineering Chennai, Tamil Nadu, India

Madhavi Latha Gali Indian Institute of Science Bangalore Bangalore, Karnataka, India

Kartik Venkataraman Tarleton State University Stephenville, TX, USA

ISSN 2366-2557 ISSN 2366-2565 (electronic) Lecture Notes in Civil Engineering ISBN 978-981-15-5100-0 ISBN 978-981-15-5101-7 (eBook) https://doi.org/10.1007/978-981-15-5101-7 © 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

Sustainable development is an urgent demand of the society. Over the years, the Civil Engineering profession involved in the development of the society has been reported to consume the natural and energy resources indiscriminately, thereby requiring an urgent introspection aiming towards achieving sustainable development. Though, the concept being age old, it has gained prominence in recent times, especially in the field of Civil Engineering. Today sustainable solutions in Civil Engineering do not stop with alternative materials but go beyond in terms of energy efficiency in buildings, efficient and eco-friendly transportation systems, efficient water resource management, cleaner environmental processes, sustainable geosystems to name a few. In light of such progress in achieving sustainable development, a platform is needed for all stakeholders concerned to present, discuss, cooperate, redefine and innovate sustainable solutions for the continuance of the human civilizations to higher levels of sophistication and technological advancement. With this intention of providing a sound platform for sustainability research, this conference, the First International Conference on Sustainable Practices and Innovations in Civil Engineering (SPICE) 2019, was conceived and organized by the Department of Civil Engineering, SSN College of Engineering, Chennai, Tamil Nadu, India, on 26 and 27 March 2019. SPICE 2019 focussed on achieving sustainability in Civil Engineering through materials, technology, processes and practices adopted in the domain. The conference witnessed participation from both India and abroad with authors presenting their research in the technical sessions of the conference over the 2 days. This book titled Sustainable Practices and Innovations in Civil Engineering documents the 32 research articles selected for publication covering different sub-streams of Civil Engineering, including Structural Engineering, Construction Materials, Environmental Engineering, Water Resources and Geotechnical Engineering. Sustainability and sustainable development have started to receive attention in developing economies as well as in recent times. However, the related efforts to achieve the same have not attained expected levels. Thus, it became imperative to compile the various sustainability issues and solution prospects in different sub-streams of Civil Engineering. This book will be useful to students, researchers v

vi

Preface

and academicians, who are involved in sustainability research in the stream of Civil Engineering. We would like to thank Ms. Swati Mehershi, Dr. Akash Chakraborty and the whole Springer team for their full support and cooperation at various stages of the preparation and production of this book. Chennai, India Bangalore, India Stephenville, USA

S. Ramanagopal Madhavi Latha Gali Kartik Venkataraman

Contents

Studies on the Impact of Ternary Blend for Early Prediction of Compressive Strength Using Accelerated Curing . . . . . . . . . . . . . . . . P. Murthi, K. Poongodi, and R. Gobinath Review Study on Glass Fibre Reinforced Gypsum (GFRG) Panels . . . . S. Ragav

1 13

Modelling of Organic Acid Transport in Unsaturated Subsurface System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Berlin Mohanadhas and G. Suresh Kumar

25

State-of-the-Art Review—Methods of Chromium Removal from Water and Wastewater . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Rama Devi, G. Srinivasan, S. Kothandaraman, and S. Ashok Kumar

37

Study of Behaviour of Web-Stiffened Built-up Beam . . . . . . . . . . . . . . . C. Divya Megala and M. Anbarasu

53

Geotechnical Properties of b-Glucan-Treated Clayey Sand . . . . . . . . . . M. Vishweshwaran, Evangelin Ramani Sujatha, Nadendla Harshith, and Cheni Umesh

63

Composite Leaching of Thermal Power Plant Bottom Ash to Ensure Its Performance on Cement Mortar . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sivakumar Naganathan, Salmia Beddu, Muhammad Zulfiqar Ajmulkhan, Jegatheish Kanadasan, Zakaria Che Muda, Siti Nabihah Sa’don, and B. Mahalingam Enhancing the Performance of Bottom Ash Using Acid Leaching Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sivakumar Naganathan, Salmia Beddu, Muhammad Zulfiqar Ajmulkhan, Jegatheish Kanadasan, Zakaria Che Muda, Siti Nabihah Sa’don, and B. Mahalingam

75

81

vii

viii

Contents

An Experimental Investigation of Flexural Behaviour of Ferrocement Box Beams Using Micro Fillers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ramakrishnan, D. Muthu, and S. Viveka

87

An Analytical Framework of Climate Change Impacts on Water Resources: Vulnerability and Integrated Adaptation Strategies . . . . . . . K. Shimola and M. Krishnaveni

97

Compaction and Permeability Characteristics of Biopolymer-Treated Soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 S. Anandha Kumar and Evangelin Ramani Sujatha Inflow Forecasting of Bhavanisagar Reservoir Using Artificial Neural Network (ANN): A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 S. Suriya, K. Saran, L. Chris Anto, C. Anbalagan, and K. R. Vinodh Mitigation of Energy Consumption Impact by Planning and Formulation of Environmental Management System for Indian Infrastructure Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 C. Akin, V. Vandhana Devi, and R. Samuel Devadoss Nitrate Sequestration and Sorption Capacity in Soil Under Varying Organic Loading Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 P. Balaganesh, E. Annapoorani, S. Sridevi, M. Vasudevan, S. M. Suneeth Kumar, and N. Natarajan Behaviour of Lignosulphonate Amended Expansive Soil . . . . . . . . . . . . 151 G. Landlin, M. K. Soundarya, and S. Bhuvaneshwari Push-Out Tests for Determining the Strength and Stiffness of the Channel Connectors—Experimental Study . . . . . . . . . . . . . . . . . 163 P. Sangeetha, R. Vijayalakshmi, Aaditya Jagadeesh, S. Ahalya, K. Deveshwar, and D. Swarna Varshini Experimental Study of the Headed Stud Connectors in Composite Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 P. Sangeetha, S. Ramanagopal, U. Amrutha, A. Balasubramaniam, V. Madhumitha, and G. Arun Compaction Characteristics of Modified Clay Soils with Various Proportions of Crumb Rubber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 S. V. Sivapriya Design and Development of Low-Cost Medium Size Shake Table for Vibration Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 R. B. Malathy, Govardhan Bhat, and U. K. Dewangan Experimental Investigation on Suitability of Sea Water for Concrete Mix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 K. Srinivasan and E. Arunachalam

Contents

ix

Assessment of Emerging Contaminants in a Drinking Water Reservoir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 Riya Ann Mathew and S. Kanmani Estimating the Loss of Water Spread Area in Tanks Using Remote Sensing and GIS Techniques in Ambuliyar Sub-basin, Tamilnadu . . . . 227 N. Nasir and R. Selvakumar Influence of Zinc on Engineering Properties of Soil . . . . . . . . . . . . . . . . 239 N. Gopinath and M. Muttharam Sustainability Approaches in Ground Improvement Measures . . . . . . . . 249 Gowtham Padmanabhan, Ganesh Kumar Shanmugam, and Sathyapriya Subramaniam Shear Behaviour of Concrete Wall Panels Reinforced with FRP Bars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257 Y. K. Sabapathy, V. Nithish, S. Vishnu Varadan, and K. Udhaya Prabhu Behaviour of Concrete Filled FRP Tubular Columns Under Axial Compression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 S. Ramanagopal A Study on Flexural Strength of Concrete Beams Reinforced with Manually Pultruded GFRP Bars . . . . . . . . . . . . . . . . . . . . . . . . . . 283 Y. K. Sabapathy, C. N. A. Nithish, Sajid Ali, and K. P. Priyadarshini A Novel Technique on Improving the Strength of Concrete Using Microorganisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295 S. Lokesh, Ahaned Noorani, S. Sanjay, G. Dhanalakshmi, and S. Swaminathan Glass Fibre Reinforced Gypsum (GFRG) as an Emerging Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309 J. Gokul Krishna, R. Roshan, S. N. Vinothni, and S. V. Sivapriya Immediate Load-Penetration Behaviour of Sand Piles with Sustainable Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325 A. Mugesh, J. Niranjan, S. Gunalan, and S. V. Sivapriya Expediency of Sand Compaction Piles and It’s Earlier Studies . . . . . . . 333 R. Manjula and S. V. Sivapriya Numerical and Experimental Evaluation on the Behaviour of Cold-Formed Steel Box Struts and Prediction of Experimental Results Using Artificial Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . 349 P. Sangeetha, M. Shanmugapriya, Aaditya Jagadeesh, and K. Deveshwar

About the Editors

Dr. S. Ramanagopal is a Professor of Civil Engineering at S.S.N. College of Engineering (Autonomous), Chennai. He obtained his Bachelor’s degree in Civil Engineering from College of Engineering, Chennai, Master’s degree in Structural Engineering from Annamalai University, Chidambaram and his Ph.D. from Anna University, Chennai. He has nearly thirty years of wide and varied experience of teaching and research in various capacities. His research interests include Composite Structural system and use of supplementary cementing materials in concrete. He has published more than twenty papers in refereed journals and conferences besides two presentations in the International conference held at U.K. and Australia. He has conducted workshops and seminars in the field of structural engineering and Sustainable building construction. Dr. Madhavi Latha Gali is a Professor of Civil Engineering at Indian Institute of Science. She holds a PhD in Civil Engineering from IIT Madras, MTech degree from NIT Warangal and a bachelor's degree in Civil Engineering from JNT University, Kakinada. She worked as a postdoctoral researcher at IISc from 2002-2003. Madhavi's research interests center around fundamental aspects of soil and ground reinforcement. Several topics explored in the area of soil reinforcement include strength and stiffness of geocell reinforced soils; model tests on geosynthetic reinforced foundation beds, retaining walls and slopes; seismic response of rigid, wrap-faced, modular block faced and geocell retaining walls through shaking table studies. She also maintains an active interest in many topics in rock engineering, including numerical modelling of jointed rock masses, stability analysis of rock slopes, and rock slope reinforcement. Dr. Kartik Venkataraman is an Associate Professor of Environmental Engineering at Tarleton State University (part of the Texas A&M University system), United States. His research interests include groundwater contamination investigation, evaluation of hydrologic trends and the broad application of geospatial techniques in water resource management. He has received state and federal funding from agencies such as the United States Environmental Protection xi

xii

About the Editors

Agency and regularly publishes in high-impact journals such as the Journal of Hydrology. In 2016, he received the Outstanding Junior Faculty award at Tarleton State University. Dr. Venkataraman is also a registered Professional Engineer in the State of Texas and actively mentors the student chapter of the Texas Society of Professional Engineers [TSPE] at his university as well as serves on the TSPE Education Committee.

Studies on the Impact of Ternary Blend for Early Prediction of Compressive Strength Using Accelerated Curing P. Murthi, K. Poongodi, and R. Gobinath

Abstract This experimental study is intended to investigate the applicability of existing relationships as prescribed in IS: 9013-1978 between the accelerated curing compressive strength and actual compressive strength of ternary-blended concrete. Class F type Fly ash (FA) was used to develop binary-blended concrete by replacing 20% of cement in the mixture and Rice Husk Ash (RHA) was also used to prepare another binary-blended concrete by replacing 18% of cement. Further Silica Fume (SF) was used for preparing ternary-blended concrete at 4, 8 and 12% by replacing the weight of cementitious content. Analysis of the test results shows that the relationship between accelerated curing compressive strength and the actual compressive strength is interrelated and the constant in the correlated equations specified in the code were found to be inaccurate in all the blended combinations. Thus, the alternative relations were proposed for the ternary-blended system with the supports of results and figures. Keywords Binary and Ternary-blended concrete · Compressive strength · Accelerated curing

1 Introduction The compressive strength is one of its most important engineering properties of structural concrete and reflects its mechanical quality. The compressive strength provides insinuation of its many other properties. In order to meet the challenges in the improvement of infrastructural development, the demand in the production of cement is an inevitable one. However, the cement production emits an equal amount P. Murthi (B) · K. Poongodi · R. Gobinath Civil Engineering Department, SR Engineering College, Warangal, India e-mail: [email protected] K. Poongodi e-mail: [email protected] R. Gobinath e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_1

1

2

P. Murthi et al.

of CO2 into the atmosphere [1]. Thus, increasing production of Ordinary Portland Cement (OPC) worldwide is aggravating the problems associated with its production and consumption. The usage of lime in the construction industry is an age-old practice that proves the durability of structures. The fly ash, one of the factories made by-product, was utilized as pozzolanic material in cement worldwide. The replacement of cement by fly ash improves from a minimum level to a maximum of 60% for mass concrete construction. The substitution of FA in cement proves the durability of cement concrete but the strength development of blended concrete during the initial curing period is relatively lesser than the conventional concrete. The substitution of SF in the binary-blended concrete as a third cementitious material surprised to overcome the early age problem [2]. The studies on the ternary-blended concrete have been acknowledged with the improvement in early age strength of concrete for the past few years [3, 4]. Some of the developed countries are currently being produced the ternary-blended cement including a combination of Fly Ash, Slag and Silica Fume [5]. It is very much essential to allow curing the concrete specimens up to 28 days for identifying its actual strength. Since it is a long time to ascertain the strength of the concrete it will affect the actual execution of project and finally prolongs the project construction duration. To overcome the difficulty, it is necessary to find the strength within a day with the help of accelerated curing technique. The BIS code IS: 90131978 describes the procedure for the acceleration curing by boiling water method for normal concrete [6]. The maturity of concrete for attaining the full strength is a product of temperature and its corresponding time of curing [7, 8]. Maturity of concrete =



(time × temperature).

Based on the maturity concept, the code provides an equation for correlating the accelerated curing and normal curing such as f ck = 8.09 + 1.64 Ra where f ck is the actual compressive strength of concrete at 28 days and Ra is the accelerated curing strength of concrete. Similarly, the research findings have been predicted for the 28 days compressive strength of concrete with various mix proportioning and blended combinations during the early periods [8–15].

2 Research Significance The correlated equation mentioned in the BIS code was applicable to the normal concrete prepared by ordinary Portland cement. Once the fineness of the cementitious material changes, the microstructural properties of concrete may change and lead to varying the compressive strength of the concrete. Based on these concepts in mind, the objective of the research work was nurtured to verify the applicability of existing relationship as per IS: 9013-1978 between the accelerated curing and actual

Studies on the Impact of Ternary Blend for Early Prediction …

3

compressive strength of ternary-blended concrete and predict a new correlation to find out the actual compressive strength.

3 Experimental Study Two series of binary-blended concrete mixtures were considered for developing the ternary-blended concrete in this study. Based on the preliminary investigation conducted by the authors, the replacement level (that is, replacement by mass of the Portland cement) in binary-blended concrete with FA and RHA was considered as 20% and 18%, respectively, and the ternary-blended concretes were developed by adding silica fume with 4, 8 and 12% replacement levels. The following combinations were considered in this study. 1. Binary-blended concrete, • Cement + FA, • Cement + RHA. 2. Ternary-blended concrete, • Cement + FA + SF, • Cement + RHA + SF. Meantime, the other parameters like total cementitious material content, water binder ratio, fine and coarse aggregate content were maintained as constant. In this study, the widely consumed normal strength M20 grade concrete was considered. The mix design for the above grade of concrete was followed by the BIS code procedure as per IS: 10262-1982. Water binder ratio of the mix was maintained as 0.55. Table 1 shows the summary of concrete mix proportion for control concrete used in this investigation. The various mix combinations of binary and ternary-blended concrete are shown in Table 2. The mix designations are entitled according to the blended combinations. The mix BFC 20 mentioned binary-blended concrete with 20% FA and mix BRC 18 denotes binary-blended concrete with 18% RHA. The mix TFS and TRS are indicating the ternary-blended concrete with FA & SF and RHA & SF combinations, respectively, and the numerical values are mentioning SF contribution in the ternary mixes. However, PCC is the mix for control concrete called plain cement concrete. Table 1 Mix proportion for one cubic metre of control concrete (PCC)

Cement (kg)

Fine aggregate (kg)

Coarse aggregate (kg)

Water (L)

326

675

1109

179

4

P. Murthi et al.

Table 2 Mixture proportioning of blended concrete S.No

Mix designation

Cement content (%) %

kg/m3

Mineral admixture content (%) Fly Ash %

Rice Husk Ash Silica Fume

kg/m3

%

kg/m3

%

kg/m3

1.

PCC

100

326.00

–

–

–

–

–

–

2.

BFC-20

80

260.80

20

65.20

–

–

–

–

3.

BRC-18

82

267.30

–

–

18

58.70

–

–

4.

TFS-4

76

247.76

20

65.20

–

–

4

13.04

5.

TFS-8

72

234.72

20

65.20

–

–

8

26.08

6.

TFS-12

68

221.68

20

65.20

–

–

12

39.12

7.

TRS-4

78

254.26

–

–

18

58.70

4

13.04

8.

TRS-8

74

241.22

–

–

18

58.70

8

26.08

9.

TRS-12

70

228.18

–

–

18

58.70

12

39.12

3.1 Materials The cementitious materials like FA, RHA and SF were considered along with ordinary Portland cement confirmed to IS: 8114-1978 to carry out this investigation. The specific gravity of the cement and FA was 3.15 and 2.92, respectively. The specific gravity of RHA was determined as 2.67 and the specific gravity of SF was determined as 2.28. The fineness of cement was determined as 2950 cm2 /g. The fineness of FA and RHA was 2550 cm2 /g and 2170 cm2 /g, respectively. The fineness of the Silica Fume was 20750 cm2 /g. The combinations of SiO2 + Al2 O3 + Fe2 O3 all the cementitious materials were mentioned in Table 3. Grade zone-II sand was used as fine aggregate and its fineness modulus was determined as 2.67. The specific gravity of the sand was 2.71. Blue granite metal of 20 mm size (maximum) was used as a coarse aggregate. The fineness modulus and the specific gravity of the coarse aggregate were 2.78 and 7.19, respectively. Both the aggregate complied with the requirements of IS: 383-1970. Table 3 Chemical composition of cementitious materials S.no

Chemical composition (%)

Cement

FA

RHA

SF

1

SiO2 + Al2 O3 + Fe2 O3

26.18

85.90

91.89

87.10

2

CaO

61.60

0.62

0.78

0.9

3

LoI

1.70

2.50

3.49

1.09

Studies on the Impact of Ternary Blend for Early Prediction …

5

Fig. 1 Failure of concrete cube under compression

3.2 Testing the Concrete Specimens 3.2.1

Compressive Strength of Concrete Specimens

The concrete cubes were cast using 150 mm size steel moulds and compacted with the help of table vibrator. The concrete was prepared using a laboratory concrete mixer machine and more precautions were taken to ensure uniform mixing of ingredients. Demoulding was carried out after 24 h after preparing the specimens. The compressive strength of concrete was determined with the help of 200 kN electrically operated compression testing machine as shown in Fig. 1.

3.2.2

Boiling Water Method of Curing

The specimens were allowed to cure for 23 h ± 15 min in room temperature before immersed into the accelerated curing tank as shown in Fig. 2. Then the specimens were allowed to cure in boiling water for a period of 3 h 30 ± 15 min. Further, the demoulded specimens were cured in normal water for 2 h before conducting the compressive strength test. This procedure is completed within 28 h ± 20 min to determine the compressive strength of concrete.

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Fig. 2 Concrete cubes in accelerated curing tank

4 Result and Discussion 4.1 Compressive Strength of Ternary-Blended Concrete The compressive strength development pattern for FA- and SF-based ternary-blended concrete is shown in Fig. 3. The compressive strength development of the ternaryblended designated concrete is shown in Fig. 4. From Fig. 3, it can be seen that both 7 and 28 days compressive strength of FA-based binary-blended concrete were lesser than the ternary-blended concrete. The addition of 4% SF in FA-based binaryblended concrete shows the same results compared to the plain cement concrete.

40

Compressive strength (MPa)

Fig. 3 Compressive strength of FA- and SF-based ternary-blended concrete

35 30 25 20 15 10

PCC TFS 4 TFS 12

5

BFC 20 TFS 8

0 0

30

60

90

120

Curing period (Days)

150

180

Studies on the Impact of Ternary Blend for Early Prediction …

40 Compressive strength (MPa)

Fig. 4 Compressive strength of RHA- and SF-based ternary-blended concrete

7

35 30 25 20 15 10

PCC TRS 4 TRS 12

5

BRC 18 TRS 8

0 0

30

60

90

120

150

180

Curing period (Days)

During the latter age, the ternary-blended concrete with 4% SF shows higher strength than that of control concrete and also the 90 days compressive strength of 8% SFbased ternary concrete shows the same strength of control concrete. This is due to the micro-filler effect of the extremely fine particle of SF and hence dense homogeneous concrete has been developed. A similar kind of trend was observed in the RHA-based ternary-blended concrete system from Fig. 4, but the rate of strength development was lesser than the FA-based ternary-blended system. Replacing 12% SF in both blended combinations resulted in a reduction of compressive strength and it is due to that the reduction of calcium hydroxide content due to the secondary reaction. The excess mineral admixtures present in concrete were lying in the mix just as an inert material contributing nothing to the strength of concrete.

4.2 Effect of Accelerated Curing on the Addition of Silica Fume The compressive strength variation of concrete under accelerated curing for the ternary-blended concrete by varying the replacement level of SF is shown in Fig. 5. The FA- and SF-based ternary system shows better performance when compared to the RHA- and SF-based ternary system. The accelerated compressive concrete with FA- and RHA-based binary system shows the value of 8.32 and 7.63 MPa, respectively. The addition of 4% SF in the concrete improves the accelerated curing compressive strength by 49.76% in FA and 49.54% in RHA-based ternary-blended system. The strength increasing rate was reduced when the addition of SF at the rate of 8 and 12% in both the ternary system. Meantime of the accelerated curing strength

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Fig. 5 Compressive strength variation of concrete after accelerated curing

at 8 and 12% SF replacement level shows the higher values than the binary system in both the ternary-blended concrete.

4.3 Development of Correlated Equation The relationship between the accelerated curing and normal curing of ternary-blended concrete at 7, 28 and 90 days was mentioned in Figs. 6, 7 and 8. The trend line between accelerated curing and normal curing compressive strength of ternaryblended concrete shows the linear relationship. The new regression equations and Fig. 6 Relationship between the accelerated curing and normal curing of ternary-blended concrete at 7 days

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Fig. 7 Relationship between the accelerated curing and normal curing of ternary-blended concrete at 28 days

Fig. 8 Relationship between the accelerated curing and normal curing of ternary-blended concrete at 90 days

its coefficient are also mentioned in Table 4. Meantime of the BIS code IS: 90131978 mentions the relationship of accelerated curing and normal curing compressive strength at 28 days as f c = 8.09 + 1.64 f a for normal concrete [6]. Chowdhury and Chowdhury [14] has been developed a similar strength prediction models of fly ash concrete by accelerated curing method as R28 = 1.383 × Rac + 8.604. The deviations of compressive strength at 28 days with the code recommendation and the new predicted equation was mentioned in Table 5. The deviations very clearly indicate that the exiting code recommended equation was found to be invalid for

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Table 4 New regression equations for ternary-blended concrete at various curing periods S.No

Curing period (days)

Regression equationa

Regression coefficient

1.

7

f c = 2.00 + 1.44 f a

0.83

2.

28

f c = 10.70 + 1.55 f a

0.93

3.

90

f c = 14.80 + 1.52 f a

0.80

c = Compressive strength of ternary-blended concrete in MPa f a = Accelerated compressive strength of ternary-blended concrete in MPa af

Table 5 Comparison between the code recommendation and the new predicted equation at 28 days curing S.no

Silica Fume replacement level (%)

Compressive strength (MPa) Actual

Predicted as per IS code

Deviationa (%)

Predicted as per new correlation

Deviationa (%)

1.

0

23.67

21.73

−8.20

23.59

−0.34

2.

4

30.97

28.52

−7.91

36.01

−1.16

3.

8

27.17

25.39

−6.55

27.05

−0.44

4.

12

24.90

23.01

−7.59

24.81

−0.36

a The

negative sign indicates lesser value than the actual compressive strength

blended concrete, since the strength development pattern for the blended concrete was not similar to that of normal Portland cement concrete.

5 Conclusions The following conclusions have been drawn from this investigation: • The reduced rate of strength development of both the binary-blended concrete was revealed compared to the control concrete during the early age. • The addition of 4% SF in FA-based blended concrete shows better results than the control concrete in all the curing days. • The addition of 8% SF in FA-based blended concrete shows the same result when compared to the control concrete at 90 days curing. • The ternary-blended concrete with 4% F and 18% RHA has improved the early age compressive strength and shows the equal strength at the age of 90 days curing. • The addition of 8% SF in RHA-based blended concrete also improves the early age strength than that of binary-blended concrete. • The SF-based ternary-blended concrete improves the early age strength development of concrete.

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• The addition of 4% SF in FA- and RHA-based binary concrete improves the accelerated curing compressive strength by 49.76% in and 49.54%, respectively. • The existing BIS code relationship between the accelerated curing and normal curing compressive strength (f c = 8.09 + 1.64 fa ) was not valid for blended concrete. • The new regression equation for the relationship between the accelerated curing and normal curing compressive strength of ternary-blended concrete system was found for 7, 28 and 90 days curing and mentioned in Table 4.

References 1. Murty DSR et al (2006) Conservation of concrete making materials. J Struct Eng 33(3):237–241 2. Bouzoubaa N et al (2004) Development of ternary blends for high performance concrete. ACI Mater J 101(1):19–29 3. Mullick AK (2007) Performance of concrete with binary and ternary cement blends. Indian Concrete J 15 4. Berry EE (1980) Strength development of some blended cement mortars. Cem Concrete Res 10(1):1–11 5. Nehdi M (2004) Ternary and quaternary cements for sustainable development. Concrete Int 23(4):34–42 6. BIS code IS: 9013-1978, Method of making curing and determining compressive strength of accelerated cured concrete specimens 7. Shetty MS (2005) Concrete technology. S.Chand & Company Ltd., 8. Tokyay M (1999) Strength prediction of fly ash concretes by accelerated testing. Cem Concrete Res 29:1737–1741 9. Jayadevan V, Valsalakumary VR, Sufeera OB (2014) Reliability of accelerated curing techniques for speedy design of concrete mixes—An appraisal of IS 9013:1978 code. Indian Concrete J 10. Neelakantan TR, Ramasundaram S, Shanmugavel R, Vinoth R (2013) Prediction of 28-days compressive strength of concrete from early strength and accelerated curing parameters. Int J Eng Technol 5(2):1197–1201 11. Shelke NL, Gadve S (2013) Prediction of compressive strength of concrete using accelerated curing. Int J Pure Appl Res Eng Technol 1(8):90–99 12. El-kholy SA, Metwally KA (2017) Different accelerated curing methods of concrete. Int J Sci Eng Res 8(5):695–697 13. Resheidat MR, Ghanmat MS (1997) Accelerated strength and testing of concrete using blended cement. Adv Cem Based Mater 5:49–556 14. Chowdhury JN, Chowdhur J (2016) Development of strength prediction models of 28 days fly ash concrete strength by accelerated curing method. Int J Sci Eng Res 7(4) 15. Kheder GF, Al Gabban AM, Abid SM (2003) Mathematical model for the prediction of cement compressive strength at the ages of 7 and 28 days within 24 h. Mater Struct 36:693–701

Review Study on Glass Fibre Reinforced Gypsum (GFRG) Panels S. Ragav

Abstract The tremendous increase in Urbanization leads to the various innovation techniques in Building Technology to improve their efficiency. As a part of this, Glass Fibre Reinforced Gypsum (GFRG) Panels are the new technique that is widely used in Australia, India, China, etc. These are panel-based building systems, which can be used as a replacement of nominal walls and slabs. This can be used as LoadBearing structures as well as shear wall by adding reinforced cement concrete in panel cavities. In the mass housing system, GFRG Panels play a vital role in easy transportation, erection and construction of large units in the desired time period with less manpower. It is also eco-friendly, cost-effective, high resistance to heat and fire compared with traditional construction. The methodology involved mainly to analyse, discuss and recommends the GFRG panels as per the site conditions. To conclude this, conventional building construction indirectly impacts the increase of pollution in the world, as an alternative for this, we can use GFRG panels made up of industrial waste and also with the minimum usage of virgin materials during execution. Hence, it is one of the green building technologies to sustain our environment. In this review paper, general structural requirements, design and erection process of Glass Fibre Reinforced Gypsum Panels are discussed. Keywords Glass fibre reinforced gypsum (GFRG) panels · Shear wall · Mass housing system · Load-bearing structures · Green building

1 Introduction Glass Fibre Reinforced Gypsum (GFRG) Panel is one of the new building techniques for mass-scale housing as well as cost-effective and eco-friendly to the environment. It was first developed in Australia in the early 90 s and now followed in China, India, Japan, Saudi Arabia, etc. These panels have a nominal size of 12 m length, 3 m height S. Ragav (B) PG Scholar, Department of Civil Engineering, Sona College of Technology, Salem, Tamil Nadu, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_2

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and 124 mm thickness inside with cellular cavities of 230 mm width (Figs. 1 and 2). It can be cut to the required size in a special cutting machine based on the site requirements [1–6]. The major raw materials used for manufacturing are calcined gypsum (a by-product from chemical industries) and glass fibres (slender filament). For the normal partition wall, it is directly used while for carrying loads reinforcing steel bars with cement concrete is added in the cavities of the panel. It is also used as a roof and floor slabs [6–9]. By placing more longitudinal reinforcing steel bars in cavities, it also used as a shear wall to resist lateral loads such as wind load and seismic load. For foundations, strip footing is adopted since it is a load-bearing structure and reinforced concrete plinth beams on the top are constructed in the footing, above that panels can be placed. The main objective of this review work is to understand the

Fig. 1 Plan and elevation of GFRG panel

Fig. 2 Cross section of GFRG panel

Review Study on Glass Fibre Reinforced Gypsum (GFRG) Panels

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uses and benefits of using GFRG panel technology over the conventional building for effective and efficient construction. GFRG panel was approved as a building material suitable for construction by BMTPC (Building Materials & Technology Promotion Council, Ministry of Housing & Urban Poverty Alleviation, Government of India) and the joint effort by BMTPC & IIT Madras has resulted in the development of a ‘GFRG Design Manual’ for the structural design of buildings [1]. Construction manual prepared by FACT-RCF Building products Ltd (FRBL) gives a brief knowledge of GFRG panel construction at the site [2]. Devdas Menon (Professor at IITM) and his Ph.D. Scholar has published many research papers on GFRG panels [3, 4]. Also, many researchers have done a research study on this technology and some of them are given in references.

2 Manufacturing Process Gypsum is the by-product obtained from chemical industries mainly in fertilizer industries. There are around totally 7 million tons of gypsum obtained from industries with a new production of 2 thousand tons every day. The raw gypsum is converted into calcined gypsum by calcination process, which includes heating the gypsum up to 1500 °C to evaporate the crystalline water and then it made into a fine powder. The calcined gypsum is added with some additives such as water, retarders, waterresisting resins and formed as a slurry flowable paste. In the casting unit, first the gypsum slurry is poured in a casting table followed by glass fibres spread over it and then damped with the roller. The aluminium planks are placed over this with a spacing of 20 mm for the hollow sections. Then the gypsum slurry is poured over it followed by glass fibres and continued by damping to form a rib between the aluminium planks [1–5]. The top layer is smoothed to get an even surface with a total thickness of 124 mm. After a setting time of 30 min, the aluminium planks are taken out slowly. Next, the casting table is rotated vertically to remove the panels (Fig. 3) and it is taken for drying. In the drying chamber, hot air is blown for 90 min to completely dry. After this process, GFRG Panels are ready to use and it is cut into desired dimensions with the special cutting machines based on the site requirements. In India, FACT-RCF Building products Ltd (FRBL) Mumbai and Kochi branches are manufacturing GFRG Panels in a large scale.

3 Mechanical Properties A detailed research done by IIT Madras for several years led to the preparation of the design manual and it was published by BMTPC in the year 2013 [1]. This design manual is mandatory and required to be followed for GFRG Panel based constructions in India. It comprises of many test results and guidelines for GFRG

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Fig. 3 GFRG panel manufacturing in casting unit

panels. Based on this, the mechanical properties of GFRG Panels are shown in the Table 1.

4 Design and Construction The Panel design shall be as per the design manual prepared by IIT Madras & BMTPC and other nominal design as per Codal Provisions (IS 456:2000, IS 1893(part I):2002, etc.). Constructions manual prepared by FACT-RCF Building products Ltd (FRBL) gives the complete detailing drawings for GFRG Building construction. GFRG Panels can be designed as load-bearing structures and it can be built up to 10 storey buildings in moderate seismic areas. Since it is a load-bearing structure, there is no need for columns and beams. Figure 4 shows the typical construction of GFRG panel house.

4.1 Load-Bearing Walls By introducing steel bars and concrete (preferably self-compacting concrete, as it has more workability) in hollow cavities it can be used as a load-bearing panel. The connection between the wall panels and foundation is achieved by providing starter bars embedded in the plinth beam over the footing at the hollow cavity locations. Then the vertical bars and starter bars can be connected. For cost reduction, one in a

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Table 1 Mechanical properties of GFRG panels Mechanical property

Nominal value

1

Unit Weight

0.433 kN/m2*

2

Modulus of elasticity, E G

7500 N/mm2

3

Uni-axial compressive strength, Puc

160 kN/m

4

Uni-axial tensile strength, T uc

34–37 kN/m

5

Ultimate shear strength, V uc

21.6 kN/m

6

Out-of-plane moment capacity, 2.1 kNm/m Rib parallel to span, M uc

7

Out-of-plane moment capacity, 0.88 kNm/m Rib perpendicular to span, M uc-perp

8

Mohr hardness

1.6

9

Out-of-plane flexural rigidity, EI, Rib parallel to span

3.5 × 1011 Nmm2 /m

10

Out-of-plane flexural rigidity, EI, Rib perpendicular to span

1.7 × 1011 Nmm2 /m

Remarks

Strength obtained from longitudinal compression/tension tests with ribs extending in the longitudinal direction

(continued)

Table 1 (continued) Mechanical property

Nominal value

11

Coefficient of thermal expansion

12 × 10−6 mm/mm/°C

12

Water absorption

1.0%: 1 h 3.85%: 24 h

Average water absorption by weight % after certain hours of immersion

13

Fire resistance: structural adequacy/Integrity/Insulation

140/140/140 min

CSIRO, Australia

14

Sound transmission class (STC)

40 dB

ISO 140-3-1996

* Panel

Remarks

has a constant thickness of 124 mm and hence it is mentioned as kN/m2

three hollow cavity is filled with concrete and the other two hollow cavities are filled with fly ash mixed with 5% cement [4–6].

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Fig. 4 Construction of GFRG panel house

4.2 Partition Walls Generally, the GFRG panels can be used a partition wall without providing any steel bars and concrete in hollow cavities continuously rather providing cement concrete in every one in four hollow cavities with minimum 3 starter bars of every 1 m for connecting each storey and in all four corners tie rods should be given throughout the entire height for stability. It can also be used as compound walls/security walls, industrial building walls, etc [1, 2].

4.3 Roof Slab and Floor For GFRG Panels as a roof slab, every third or alternate cavity is removed and in that place three steel bars connected with stirrups (Micro-beams) are placed (Fig. 5). Next to that, welded steel mesh of Fe250 Grade with a spacing of 100 mm × 100 mm are placed over it. Then the suitable cover block of 25 mm thickness placed at 750 mm on both directions are placed to hold the mesh and to level the concrete. The concrete is poured over it and screed (Fig. 6). Now the slab will act as a tee-beam and a oneway slab system is considered for deflection and strength. The minimum grade of concrete to be used is M20 and the maximum size of aggregate is 12 mm [1, 2].

Review Study on Glass Fibre Reinforced Gypsum (GFRG) Panels

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Fig. 5 GFRG panel slab

Fig. 6 Cross section of GFRG panel slab

4.3.1

Connection Between Roof/Floor Slab and Wall

The connection between the roof/floor slab and the vertical wall should be strong enough to transmit the loads. An embedded horizontal RC tie beam has to be provided on top of all the walls with a size of 200 mm depth and 94 mm width by cutting and removing the top portion of the web of GFRG Panels [1, 2, 5]. Then the roof/floor slab and the vertical wall panel are connected with 1 m long ‘C’ anchorage at 0.75 m spacing with a 40 mm bearing of the slab into the wall (Fig. 7).

4.4 Staircase GFRG Panels can be used as a waist slab in the staircase as all the hollow cavities can be removed and steel bars can be placed in that and concrete can be poured with the cover thickness of 25 mm. Over that rise and tread can be built-up with brickwork.

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Fig. 7 Connection between roof slab and wall panel

5 Discussion GFRG Panels play a vital role in the new building technology, as it has more benefits compared with the conventional building method. They can be used as walls, roof slabs, floorings, staircases, etc. The advantages of GFRG panels are as follows i. ii. iii. iv.

v. vi.

GFRG Panel is an eco-friendly material as it reduces the usage of construction materials such as cement, sand, gravels, etc. The thickness of the panel is 124 mm (5 inch) but the nominal thickness of the wall is 230 mm (9 inch), hence it gives more carpet area of the building. GFRG panel is 5 times stronger than conventional building as their lifetime is considered as 80 years whereas 50 years for a conventional building. GFRG Panel can resist earthquakes effectively since joints in the structures are very less but in conventional building, joints are more. For earthquake design in high seismic areas, it should follow the codal provisions such as IS 1893(part I):2002 and IS 13920: 1993. An example of earthquake design in the GFRG panel is given in Design Manual [1]. It is a lightweight structure (0.433 kN/m2 ), so a heavy foundation is not required in the multi-storey building also. It is a very good fire-resistant structure as it can withstand 1000° of heat for 4 h. So, in heavy fire accidents also the structure won’t collapse till 4 h.

Review Study on Glass Fibre Reinforced Gypsum (GFRG) Panels

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vii. It is water resistant because there are no minute pores in the surface of panel and also suitable waterproofing solution is applied while constructing, hence water seepage into the structure is restricted. viii. Plastering is not required since the panels have even surface. ix. Since there are no beams, RC slabs and columns, there is no curing time is required. x. Less manpower is required at the site compared with conventional building. xi. As overall usage of GFRG Panels saves up to 30% of the total construction cost of a conventional building [6, 7]. Though it has more advantages some small disadvantages are also there as follows i. Skilled workers are required both in on-site and off-site construction. ii. For fixing the panels in building construction requires cranes and a minimum 3–4 m open space should be available in all directions around the site for crane movements. iii. Cutting of GFRG panels into desired dimensions is to be carried out in factories with a special type of cutting machines. iv. Storage of GFRG panels at the site is hard as it requires even surface and covers more space and it should free from moisture and dirt.

6 GFRG Buildings in India As a part of the research, IIT Madras constructed a two-storey GFRG building to demonstrate and observe the GFRG technology. This model building has a total area of 1981 sq. ft with 2 houses on the ground floor and 2 houses on the first floor (Fig. 8). It is interesting that the entire building was constructed within 30 days [3, 4]. Till now, around 300 GFRG buildings were constructed in India.

7 Conclusions and Recommendations Further research studies on GFRG panel technology can give a way to new building technology at an affordable cost. With more analysis and observations, the disadvantages can be controlled effectively for the efficient usage of this technology. Day-by-day, all the natural raw materials are depleting and their market price goes on increasing, as an alternative GFRG Panels can be used for rapid affordable mass housing. To reduce global warming and pollution, nowadays all fields are giving more preference to recycled and reused products. As a part of this, industrial waste gypsum is used as the main raw material and cement usage is very much minimized which indirectly prevents the emission of carbon dioxide into the air from cement manufacturing industries. Hence, it is recommended to use this type of green building

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Fig. 8 GFRG panel building in IIT madras

technology to safeguard our surrounding environment and to mitigate greenhouse gas emissions. GFRG Panel based building construction is more economical than conventional building and also requires less time to complete. People who are all having low budget can go for this technology. The government can also adopt this technology to build houses for the needy peoples. From all this consideration, we conclude that the house for living is the basic need for a human and that house can be built as affordable, reliable, eco-friendly, more lifetime, more strength by using GFRG Panels based building.

References 1. GFRG/Rapidwall building structural design manual, prepared by structural engineering division, department of civil engineering, IIT Madras & BMTPC, 2013 2. Glass Fiber Reinforced Gypsum (GFRG) Wall Panels- (FRBL) Construction Manual, prepared by FACT RCF Building Products limited, Kochi 3. Paul S, Menon D (2017) Sustainable, rapid and affordable mass housing using GFRG panels. IJAMC 4(3). ISSN: 2394-2827 4. Menon D (2014) Rapid affordable mass housing glass fiber reinforced gypsum (GFRG) panels. IJSER 5(7). ISSN 2229-5518 5. Shukla A, Khan MAF (2016) A review of research on building system using glass fiber reinforced gypsum wall panels. IRJET 03(02). e-ISSN: 2395-0056, p-ISSN: 2395-0072 6. Francis S (2017) Green, affordable & rapid housing using Gypwall. IJCRT. ISSN: 2320-2882 7. Mujeeb VM, Udhayasakthi R (2017) Case study on glass fiber reinforced gypsum panel in mass house economics. TARCE 6(2). ISSN: 2249-6203

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8. NithyaNandan A, Renjith R (2016) Experimental study on glass fiber reinforced gypsum (GFRG) panels filled with alternate concrete mix using shredded thermocol and phosphogypsum. IJSER 7(10). 225 ISSN 2229-5518 9. Wu YF (2009) The structural behavior and design methodology for a new building system consisting of glass fibre reinforced gypsum panels. Constr Build Mater 23:2905–2913

Modelling of Organic Acid Transport in Unsaturated Subsurface System Berlin Mohanadhas and G. Suresh Kumar

Abstract Leachate from municipal solid waste landfill contains a variety of contaminants including organic acids. The subsequent vertical movement of organic acids from the landfill may reach and pollute the groundwater. Hence, the prediction of vertical movement in the unsaturated sub-surface system is essential to monitor the groundwater contamination. To achieve this, a one-dimensional numerical model has been developed to understand and forecast the transport of organic acids in unsaturated soil using a finite difference technique. This study considers acetic acid as a representative organic compound in the landfill leachate. The Richards equation is used to simulate the water content in the unsaturated soil and advection–dispersion equation is used to predict the transport of organic acid. Moreover, first-order decay coefficient is also considered during the migration of organic acid. The numerical results suggest that the transport of organic acid is strongly influenced by water content variation in the unsaturated subsurface. Further, it is also observed that the soil distribution coefficient was found to be one of the most influencing parameters, which is significantly affecting the organic acid concentration profile in the unsaturated soil. Moreover, the decay coefficient is also affecting the distribution of organic acid in the vadose zone. Overall, the numerical results show that the higher simulation time allows the concentration of organic acid to reach larger depth. Hence, there is a high probability of groundwater contamination by organic acid concentration. Keywords Numerical modelling · Organic acid · Landfill leachate · Groundwater contamination · Finite difference

B. Mohanadhas (B) Department of Civil Engineering, National Institute of Technology Arunachal Pradesh, Yupia, India e-mail: [email protected] G. Suresh Kumar Department of Ocean Engineering, Indian Institute of Technology Madras, Chennai, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_3

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1 Introduction Soil and groundwater contamination by various pollutants has been a key problem in most of the countries during the past few decades. The most common cause of contamination is from wastewater used in agricultural sites, septic tanks, leakage from subsurface loading chambers, pipelines, overflows during overloading or accidents while transport of petroleum hydrocarbons and waste disposal sites. During the above activities, a large number of dangerous substance travels over the unsaturated zone and further arrives into the groundwater resources. The common exercise for municipal solid waste (MSW) dumping throughout the world are landfills and/or open dumpsites [1]. Currently, sanitary landfill represents a sustainable and the most frequently used method for solid waste disposal because it may attain the reclamation of neglected area [2]. Suitably planned and functioned sanitary landfills excluded some aggressive environmental problems that effect from other solid waste final clearance replacements such as burning in open-air burning sites and open-pit dumping. But, uncontrolled dumping may influence to arise gas and leachate formation [3]. Landfill leachate contains a variety of heavy metals, organic and inorganic contaminants [4]. Generally, mathematical models on leachate transport include either geochemical processes or biological transformation in soils and rarely few models accomplish both processes. The modelling of flow and transport through the unsaturated zone of porous media is a complex phenomenon due to the non-linearity of flow model as well as the various physical–chemical–biological processes of contaminants. Such modelling can be useful for predicting and analysing the effect of contamination in groundwater. Numerous studies have been performed on contaminant transport through the saturated and unsaturated porous media using the classical advection– dispersion equation. Many literature have addressed the transport and transformation models of various contaminants from the leachate of landfill into subsoil and groundwater. Top et al. [5] addressed the transport of phenolic compounds prevailing in leachate through landfill liner systems by evaluating the groundwater quality. The one-dimensional reactive transport model PHREEQC-2 has been used to model and quantify the biogeochemical processes governing leachate diminution inside a landfill leachate plume (Banisveld, the Netherlands) [6]. A groundwater and leachate mass transport model has been developed to categorize the contamination threat due to leachate migration below the municipal dumpsite [7]. A coupled one-dimensional reactive multicomponent landfill leachate transport model was proposed to simulate the movement of contaminants in soil from landfill [8]. This model integrates the geochemical equilibrium, kinetic biodegradation, and kinetic precipitation–dissolution processes in the subsurface system. Further, a model has been developed to measure the chemical oxygen demand in the groundwater below the sanitary landfill and also predict the concentration of organic in the landfill leachate [9]. The environmental consequences of landfill leachate were studied by LandSim (Landfill Performance Simulation) modelling software [10].

Modelling of Organic Acid Transport in Unsaturated Subsurface …

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Carboxylic acids are found to be a very common organic pollutant in the landfill leachate [4]. The transport of organic acids through the porous system is a complex phenomenon due to the various chemical and transformation processes. The vertical transport by soil water, of any organic acids coming from landfill leachate, is of key concern in evaluating the susceptibility of groundwater pollution. Generally, the prediction models on fate and transport of any organic pollutant in under-saturated and saturated zone consider the basic physicochemical processes such as advection, dispersion, volatilization and degradation. A recent study investigates the transportation of organic acid over a partially saturated liner system underneath the landfill [11]. Although, Liu and Hu [11] have incorporated the variation of volumetric water in the space (depth), the temporal variation of water content also needs to be incorporated to study the real unsaturated porous system. Hence, the importance of the current study is to comprehend the effect of spatial and temporal variation of water content and the associated unsaturated soil hydraulic parameters such as hydraulic conductivity and pressure head on the fate and transport of organic acids (acetic acid) in an unsaturated zone. Acetic acid is found to be one of the most poisonous components of landfill leachate. To this extent, a one-dimensional numerical model is established to mimic the transport of organic acid in homogeneous, isothermal and unsaturated porous systems. The advection, dispersion, degradation and decay are the few of the foremost processes considered in this study.

2 Model Formulation In this section, the mathematical model for water flow and transport of organic acid in the unsaturated subsurface system is discussed.

2.1 Water Flow Modelling The water flow in unsaturated porous media [12–14] is given in Eq. 1: C(h)

  ∂ ∂h ∂K ∂h = K − ∂t ∂z ∂z ∂z

(1)

where C(h) = ∂θ/∂h—specific moisture capacity (1/L), h—pressure head (L), K— unsaturated hydraulic conductivity (L/T ), t—time (T ), z—vertical depth (L) which is positive in downward direction. In order to solve the equation, the constitutive relationships [15, 16] are shown in Eqs. 2–4: Se =

θm − θr θs − θr

(2)

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θs − θr θm = θr +  η 1 + |αh|β   η 2 K (h) = K s Se1/2 1 − 1 − Se1/η

(3) (4)

where θ—water content (L 3 /L 3 ), S e —effective water saturation, θs —saturated water content, θr —residual water content, K s —saturated hydraulic conductivity (L/T ), α, β and η—fitting parameters.

2.2 Transport Modelling The modified one-dimensional contaminant transport of organic acid [17] in unsaturated soil is shown in Eq. 5.   ∂C ∂qC ∂θC ∂ρ S ∂ θD − + = + ∅1 ∂t ∂t ∂z ∂z ∂z

(5)

where C—concentration of organic acid in aqueous phase, D = q*λL , D—dispersion coefficient, q—Darcy velocity, λL —longitudinal dispersivity, ρ—bulk density of soil; S—amount of organic acid in the adsorbed phase per unit mass of soil; ∅1 — first-order decay of organic acid can be written [18] as shown in Eq. 6: ∅1 = −μθC

(6)

where μ—first-order decay rate coefficient (T −1 ).

2.3 Initial and Boundary Conditions The initial and boundary conditions for water flow equation from Mitchell and Mayer [17], are h (z, t = 0) = −1000 cm, h (z = 0, t) = −75 cm and h (z = L, t) = −1000 cm. Similarly, the organic acid transport equation consists of the following initial and boundary condition: C (z, t = 0) = 0 mg/l, C (z = 0, t) = 4000 mg/l [11], ∂C/∂z (z = L, t) = 0, where L is the total length of domain.

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Fig. 1 Comparison of the present water flow model result with the existing study [18]

2.4 Numerical Solution The fully implicit finite difference method is used to solve the system of partial differential equations relating water flow and transport of contaminants. Thomas algorithm is used to solve the subsequent tri-diagonal systems of linear algebraic equations. Firstly, the unsaturated water flow model is resolved to obtain the pressure head values in the unsaturated soil and the Darcy velocity and dispersion coefficients are found from the gained pressure head and water content. Secondly, the concentration of organic acid in the unsaturated zone is arrived by solving the contaminant transport equation using the given initial and boundary conditions. In order to make sure the accuracy of solved results the water flow and contaminant transport models in unsaturated zones are validated by matching with the established analytical/numerical results. The assessment of the results found from the present model and the existing results [18] show that the model predictions (Fig. 1) are in good agreement with the reported predictions. Likewise, the results projected by Ojha et al. [19] are also matching with the present contaminant transport model which is shown in Fig. 2.

3 Result and Discussions The concentration of organic acid in the unsaturated zone is analysed using an implicit finite difference numerical method after considering various physical and chemical processes. This study comprises advection, dispersion, first-order degradation, and sorption processes to forecast the organic acid concentration. The soil and transport parameters are given in Table 1.

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Fig. 2 Comparison of present contaminant model result with the existing study [19]

Table 1 Soil and transport parameters Parameter

Value

Reference

Van Genuchten parameter (α)

0.0335

Van Genuchten parameter (β)

2

Van Genuchten parameter (η)

0.5

(cm−1 )

Mitchell and Mayer [17] Mitchell and Mayer [17] 1 − (1/β)

m3 /m3

Saturated water content (θs )

0.381

Residual water content (θr )

0.102 m3 /m3

Mitchell and Mayer [17] Mitchell and Mayer [17]

Saturated hydraulic conductivity (Ks )

0.00922 cm/s

Mitchell and Mayer [17]

Soil bulk density (ρ)

1.6 × 106 g/m3

Sulaymon and Gzar [20]

Soil partitioning coefficient (Kd )

9 × 10−8 L/mg

Ogram et al. [21]

Longitudinal dispersivity (λL )

0.0299 cm

Sulaymon and Gzar [20]

Decay rate (μ)

0.11 × 10−9 /s

Liu and Hu [11]

Figure 3 shows the vertical distribution of water content at various time intervals in the unsaturated porous media. Figure 3 shows the variation of water content nearly from 0.102 to 0.38 m3 /m3 . This variation is due to the hydraulic properties of unsaturated porous media such as pressure head, water content and hydraulic conductivity. These hydraulic properties are varying in nature with respect to time and space in the unsaturated zone. The observed variation in water content is lying between the residual and saturated water content of the soil. Further, it is also observed that the water content is maximum (approximately 0.205 m3 /m3 ) at the soil surface and moving to downward direction and abruptly reduced to nearly 0.11 m3 /m3 at the

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Fig. 3 Distribution of water content in the unsaturated porous media at various time intervals

depth of 300 cm from the surface after 10 days. A similar trend is also observed at 25 and 50 days with larger migration in the vertical direction. It is observed that the water content is reduced to its minimum value at the depth of approximately 700 cm and 1350 cm at the end of 25 days and 50 days, respectively. Figure 4 provides the concentration distribution of organic acid in the unsaturated porous media during various time intervals. The developed model includes the adsorption process of organic acids with soil particles and decay process. The numerical experiments show that the organic acid concentration diminishing from its peak value (approximately 4000 mg/l) at the soil surface and vanishes at the depth of nearly 150 cm at the end of 10 days. This reduction in concentration is due to various physical, chemical and biological processes. In this study, sorption and decay are the predominant processes considered and which are affecting the movement of organic acid along with advection and dispersion processes. Further, the similar trend is observed at 25 and 50 days with larger migration depth. The maximum concentration exists up to the depth of 100 cm and 200 cm at 25 days and 50 days, respectively. Moreover, the concentration becomes zero at a depth of 300 cm and 550 cm for 25 days and 50 days, respectively. The results show that the concentration is travelling towards the downward direction when the time increases which is directly influenced by water content profile as shown in Fig. 3. The dissolved concentration of organic acid is migrating towards the downward direction along with the water content movement. The varying hydraulic properties such as pressure head, volumetric water content and hydraulic conductivity of unsaturated soil are intensely influencing the transport of organic acid.

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Fig. 4 Distribution of concentration of organic acids in the unsaturated porous media at various time intervals

Figure 5 describes the concentration variation of organic acids for varying distribution coefficient between solid and liquid concentration after 25 days without changing other parameters. The results show that the concentration of organic acid reaches the depth of 100 cm during the distribution coefficient (k d ) 9 × 10−7 l/mg, whereas the migration of organic acid reaches 300 cm for the distribution coefficient 9 × 10−8 l/mg. It is also perceived that the further reduction in the distribution coefficient increases the depth of penetration of organic acid. For example, the distribution coefficient 9 × 10−9 l/mg allows the organic acid to migrate up to 450 cm depth. It is also observed from Fig. 5 that the larger values of distribution coefficient significantly retard the movement of organic acid than the lower values. One order of reduction in distribution coefficient from 9 × 10−8 l/mg reduces the migration depth from 450 to 300 cm. On the other hand, one order of magnitude increase from 9 × 10−8 l/mg reduces the depth from 300 to 100 cm. This shows that the higher order of distribution coefficient significantly affects the movement of organic acid in unsaturated porous media. Further, a set of numerical experiments are performed to examine the effect of decay on the transport of organic acid in the vadose zone which is shown in Fig. 6. The results show that the overall depth (approximately 300 cm) of penetration of organic acid is independent on the variation in decay coefficient. However, the reduction in concentration is observed for different decay coefficient. This reduction in aqueous phase organic acid concentration is due to the loss by the decay of organic acid. Further, it is also observed from Fig. 6 that the decay coefficient variation higher than 0.11 × 10−6 /s claim the significant effect in the concentration variation, whereas

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Fig. 5 Sensitivity analysis of distribution coefficient on the concentration of organic acids after 25 days

Fig. 6 Sensitivity analysis of decay coefficient on the concentration of organic acids after 25 days

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the lower rates bring minor influence in the organic acid distribution in unsaturated porous media. It can be concluded from Fig. 6 that the decay process is a critical phenomenon on the transport of organic acid in vadose zone especially the rate of decay coefficient higher than 0.11 × 10−6 /s.

4 Conclusion The current study investigates the transport of organic acid in an unsaturated porous medium using an implicit finite difference scheme in a one-dimensional domain. The adsorption and decay effects were effectively compiled with the water flow and transport model. The published results are used to verify the developed water flow and single species contaminant transport model results. The numerical results suggest that the transport of organic acid is strongly influenced by water content variation in the unsaturated subsurface. Further, it is also observed that the soil distribution coefficient found to be one of the most influencing parameters, which is extensively affecting the organic acid concentration profile in unsaturated soil. Moreover, the decay coefficient is also affecting the spread of organic acid in the vadose zone. Overall, the numerical results show that the higher simulation time permits the concentration of organic acid to reach larger depth, which directs the high likelihood of organic acid concentration touching the groundwater and eventually it is a threat for groundwater contamination.

References 1. Nagendran R, Selvam A, Joseph K, Chiemchaisri C (2006) Phytoremediation and rehabilitation of municipal solid waste landfills and dumpsites: a brief review. Waste Manag 26:1357–1369 2. Erses AS, Fazal MA, Onaya TT, Craig WH (2005) Determination of solid waste sorption capacity for selected heavy metals in landfills. J Hazard Mater B121:223–232 3. El-Salam MM, Abu-Zuid GI (2015) Impact of landfill leachate on the groundwater quality: a case study in Egypt. J Adv Res 6:579–586 4. Kjeldsen P, Barlaz MA, Rooker AP, Baun A, Ledin A, Christensen TH (2002) Present and long-term composition of MSW landfill leachate: a review. Crit Rev Environ Sci Technol 32:297–336 5. Top S, Varank G, Demir A, Sekman E, Bilgili MS (2011) Modelling of groundwater contamination by landfill leachate. WIT Trans Ecol Environ 145:459–470 6. Breukelen BM, Griffioen J, Roling WFM, Verseveld HW (2004) Reactive transport modelling of biogeochemical processes and carbon isotope geochemistry inside a landfill leachate plume. J Contam Hydrol 70(3–4):249–269 7. Papadopoulou MP, Karatzas GP, Bougioukou GG (2007) Numerical modelling of the environmental impact of landfill leachate leakage on groundwater quality—A field application. Environ Model Assess 12(1):43–54 8. Islam J, Singhal N (2002) A one-dimensional reactive multi-component landfill leachate transport model. Environ Model Softw 17(6):531–543 9. Sykes JF, Soyupak S, Farquhar GJ (1982) Modeling of leachate organic migration and attenuation in groundwaters below sanitary landfills. Water Resour Res 18(1):135–145

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10. Slack RJ, Gronow JR, Hall DH, Voulvoulis H (2007) Household hazardous waste disposal to landfill: using LandSim to model leachate migration. Environ Pollut 146(2):501–509 11. Liu T, Hu L (2014) Organic acid transport through a partially saturated liner system beneath a landfill. Geotext Geomembr 42:428–436 12. Antonopoulos VZ (2006) Water movement and heat transfer simulations in a soil under ryegrass. Biosys Eng 95(1):127–138 13. Berlin M, Suresh Kumar G, Nambi IM (2014a) Numerical modeling on the effect of dissolved oxygen on nitrogen transformation and transport in an unsaturated porous system. Environ Model Assess 19:283–299 14. Berlin M, Suresh Kumar G, Nambi IM (2014b) Numerical modeling on transport of nitrogen from wastewater and fertilizer applied on paddy fields. Ecolo Model 278:85–99 15. Berlin M, Suresh Kumar G, Nambi IM (2014c) Numerical modeling of biological clogging on transport of nitrate in an unsaturated porous media. Environ Earth Sci 73(7):3285–3298 16. Berlin M, Suresh Kumar G (2018) Numerical modelling on sorption kinetics of nitrogen species in wastewater-applied agricultural field. Appl Water Sci 8:216 17. Mitchell RJ, Mayer AS (1998) A numerical model for transient-hysteretic flow and solution transport in unsaturated porous media. J Contam Hydrol 50:243–264 18. Phoon KK, Tan TS, Chong PC (2007) Numerical simulation of Richard’s equation in partially saturated porous media: under-relaxation and mass balance. Geotech Geol Eng 25:525–541 19. Ojha CSP, Hari Prasad KS, Ratha DN, Surampalli Y (2012) Virus transport through unsaturated zone: analysis and parameter identification. J Hazard Toxic Radioact Waste 15(2):96–105 20. Sulaymon AH, Gzar HA (2011) Experimental investigation and numerical modeling of light nonaqueous phase liquid dissolution and transport in a saturated zone of the soil. J Hazard Mater 186:1601–1614 21. Ogram AV, Jessup RE, Ou T, Rao PSC (1985) Effects of sorption on biological degradation rates of (2, 4-dichlorophenoxy)acetic acid in soils. Appl Environ Microbiol 49(3):582–587

State-of-the-Art Review—Methods of Chromium Removal from Water and Wastewater D. Rama Devi, G. Srinivasan, S. Kothandaraman, and S. Ashok Kumar

Abstract Many countries throughout the world have found drinking water sources to be contaminated with chromium. The presence of chromium occurring naturally or anthropogenic in water at higher concentrations has proven to be carcinogenic to different internal and external organs of living organisms. Chromium is a well-known highly toxic metal, considered a priority pollutant. The dissolution of chromium in water is due to its physical, chemical and biological properties. Industrial sources of chromium include effluents from leather tanning, cooling tower blowdown, plating, electroplating, anodizing baths, rinse waters, etc. This article provides an overview of chromium and its toxicity, WHO standards of chromium in drinking water, removal techniques for chromium-contaminated aqueous solutions and comparison of methods for chromium reduction. A particular focus is given to adsorption, membrane filtration, ion exchange, electrochemical treatment methods and biological techniques. Suitability of these treatment methods to meet the required disposal standard is very difficult as these methods have some limitations, which have been reviewed in this paper. Keywords Chromium removal · Coagulation · Filtration · Reduction · Water pollution

D. Rama Devi (B) Civil Department, Meenakshi College of Engineering, Chennai, India e-mail: [email protected] G. Srinivasan · S. Ashok Kumar Department of Chemical Engineering, PEC, Pondicherry, India e-mail: [email protected] S. Ashok Kumar e-mail: [email protected] S. Kothandaraman Department of Civil Engineering, PEC, Pondicherry, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_4

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1 Introduction Chromium is an important steel grey metallic element that is found in the earth’s crust. It is a metal that is used in industries for manufacturing various products and processes. Out of the chromium metal produced 60% goes into the production of chromium-based alloys and 20% of it is used in the electroplating chemical industry, the rest goes into the manufacturing of furnace bricks and other refractory products. When Cr(III) found in ultramafic-derived soils and ophiolitic rocks [1] is oxidized, Cr(VI) is formed. Industries like mining, smelting of metallic ferrous materials, surface finishing, metal surface treatment, metallurgy, iron and steel, electroplating, electrolysis electro-osmosis, leatherworking, photography, electric appliance manufacturing, fertilizers and pesticides, energy and fuel production, aerospace and atomic energy installations generate process waters with heavy metals [2]. Wastes are discharged from metal plating, steel fabrication, paint and pigment production, wood treatment, leather tanning and chromium mining and milling industries. Effluents from coal-burning power plants contain chromate. Industrial processes produce wastewater with 500 ppm of Cr(VI) [3]. In steel finishing units, steel is passivated with chromium plating bath for the anticorrosive property. Rinsing is done using demineralized water. The water generated may contain chromium with a slightly acidic or neutral pH. Annually 17000 tons of wastewater-containing chromium is discharged into the environment [4]. Improper disposal practices, improper storage and leakages have exposed our environment to chromium. Chromium at higher concentrations is present in natural groundwater source used for public water supply. Chromium exists in different oxidation states from Cr(II) to Cr(VI). Of these, Cr(III) and Cr(VI) are the most stable oxidation states present in aqueous systems [5]. Chromium is an undesirable element present in drinking water and is a serious health hazard. Depending on the pH and concentration of Cr(VI), Cr(VI) occurs in water either in the chromate or dichromate form. In acidic aqueous environments, Cr2 O7 2− dominates and in basic condition CrO4 2− prevails. In acidic aqueous conditions Cr2 O7 2− transforms to HCrO4 − [6]. Cr(VI) is soluble in water and it occurs as an anion in water. Smaller levels of Cr(VI), even at ppb levels are toxic to humans and the environment as it is a strong oxidizing agent with cytotoxic, mutagenic and carcinogenic effects. In aquatic solutions, Cr(III) occurs as insoluble cation which is precipitated as Cr(OH3 ) at neutral pH. Treatments of water-containing toxic metals are on the priority list as they are a high risk even if they are present in trace amounts. These heavy metals present in feed water and effluents are non-biodegradable in nature, posing a threat to both humans and environment because of their bioaccumulation. Cr(III) at low concentrations is not toxic but is a nutrient and a component of glucose tolerance factor [7]. It is 1000-fold less mutagenic and cytotoxic than Cr(VI) compounds [8]. EPA has applied stringent regulations on the permissible level of total chromium including Cr(III) and Cr(VI) as 100 ppb in water and wastewater. The maximum allowable concentration of chromium in potable water is 50 ppb. The permissible limit of Chromium(VI) discharge in the state of California has been set as 1 ppb and the European Chemical Agency (ECHA) has set it to 0.1 ppm. In Greece, in the

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region of Asopos river, extensive industrial activity has lead to high concentrations of Cr(VI) discharge which has been reduced below 30 ppm. Treatment with coagulation, precipitation and flocculation of these process waters will produce waters with low amounts of metals which can be discharged into streams. Chemical precipitation, ion exchange, adsorption and membrane filtration are techniques used to remove heavy metals from process waters [9]. Cr(VI) removal from wastewater is aimed at reducing its toxicity or making it to Cr(III) form, which has less solubility in aqueous media. Methods available for treatment especially conventional methods are restricted because of technical or economic constraints [9, 10]. Using bacteria, algae, yeasts and fungi [10] and biosorption process are the biological methods available for removal [11]. The most common and promising methods are biological treatments which reduce Cr(VI) into Cr(III) through microorganisms using either pure or mixed cultures [12, 13]. When a high concentration of Cr(VI) is present in wastewater, reduction of Cr(VI) by microorganisms causes a lower reduction rate [14]. Membrane technology so far to a large extent has been used for drinking purposes. Usage of this separation technique for removal of metals will gain momentum as the water consumption will be reduced as treated water can be recycled and recovery of metal will add value to the metal finishing industry. In this study, sources of chromium, the health hazards its causes and the various treatment methods to remove it is discussed in detail [15].

2 Occurrence of Chromium in Water To a larger extent chromium occurs naturally in the earth’s crust as Chromite (FeOCr2 O3 ) and to a lesser extent as Crocoite (PbOCrO3 ) or Chromic oxide (Cr2 O3 ) to a lesser extent. Chromium is produced from chromite with Cr2 O3 content varying between 40 and 55% [16]. In many places around the globe natural groundwater has been found to contain chromium. In California, Washington, Indiana, South Carolina, North Carolina and New Jersey in the USA groundwater is found to be contaminated by hexavalent chromium [17]. Hexavalent chromium contamination in water sources has also occurred in cities in India, namely Ludhiyana, Kanpur and Lucknow and in Mexico in the city of Leon and in Ontario in Canada [18]. Concentrations of chromium as high as 120 µg/l have been reported but generally the chromium concentration occurring naturally in groundwater is as low as 2 µg/l [19]. Chromium present in groundwater was up to 50 µg/l and 2–10 µg/l in shallow groundwater in the USA [20]. A maximum of 5 µg/l and a mean concentration of 0.7 µg/l have been reported in the Netherlands [21]. Drinking water in Canada reported the presence of 14 µg/l of chromium in raw water and 9 µg/l present in treated water [22]. A wide range of hexavalent chromium has been reported in the natural source of groundwater with concentrations of 5–73 µg/l in Italy [23]. Wide range of industries using chromium and its salt in their manufacturing process discharge toxic forms of chromium which have a possibility of contaminating freshwater sources.

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3 Chromium and Its Toxicity Chromium Cr(III) is a dietary supplement that is required for the metabolism of glucose, liquid and amino acids and the daily dietary range for an adult is 20–35 µg of chromium [24]. Chromium is found in different parts of human body, i.e. even in the tissues of human foetuses and infants. As we grow the amount of chromium present in the body reduces except in the lungs. Deposits of chromium in the lungs are due to inhalation of chromium which is detectable in the lungs only in the 10th year. Nail has the highest accumulation of chromium (0.52–172.92 mg/kg). Cellular structures get affected when Cr(III) is present at higher concentrations. Metabolism of dietary supplements causes partial oxidation of Cr(III) present in the supplement in vivo by intracellular oxidation producing carcinogenic Cr(VI), Cr(V) and Cr(IV) [25]. When the pH of an aqueous solution containing Cr(VI) is within pH6.0, anionic species CrO4 2− is formed from Cr(VI) which has a similar structure as that of sulphate ion SO4 2− [26]. When Cr(VI) combines with a different reducing agent inside the cells, Cr(VI) being a strong oxidizer forms Cr(V) and Cr(IV) and finally gets converted to Cr(III). The intermediates that are catalyzed inside the cells when Cr(VI) is reduced to Cr(III) are nascent oxygen(O), super oxide ions (O2 − ), hydroxyl ions (OH− ), peroxo ions (O2 H− ) and free radicals [27]. When exposure to chromium increases, generation of reactive species and free radicals also increases [28]. Oxidative and non-oxidative forms of DNA damage occur when Cr(VI) is metabolized inside the cell causing Cr-DNA binding. Mutations and chromosomal breaks are caused by Cr-DNA binding in vitro and in various cultured cells because of reduction reactions. Oxidative DNA damage is produced when the reactive species from the intercellular reduction of Cr(VI) combines with DNA proteins. Mutagenic and toxic Cr(III) DNA complexes are formed when Cr(III) species interacts electrostatically with negatively charged phosphate groups of DNA. Mutagenesis could be the result as natural DNA replication and transcription are affected by these complexes. Metabolism of Cr(VI) also produces single-strand DNA breaks, which can lead to cancers in the liver, kidney and lungs by altering the cell function. Dermatitis, dermal necrosis and dermal corrosion are caused when skin comes into direct contact with Cr(VI) due to passivation. The risk of cancer in the respiratory system is more when Cr(VI) is inhaled due to occupational exposures [29]. Chromates were found to be carcinogenic whether they had high or poor solubility [30]. Carcinomas of the bronchial systems are caused if exposed for a long time to Cr(VI) from different chromate industries and chromate mines. Drinking water contaminated by Cr(VI) released from ore smelting in the Liaoning province of China resulted in increased mortality from stomach cancers among rural residents [31]. The number of neuronal cells is reduced showing neurotoxicity [32]. Sperm and reproductive system of animals are damaged due to physiological stress caused by Cr(VI) [33].

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4 Who Standards for Chromium in Drinking Water The toxicity of chromium and its health effects depends on the exposure to the type of chemical species of chromium [34]. When plants, microorganisms, animals and humans are exposed to Cr(VI) and Cr(III) compounds, the toxicity and solubility level of Cr(VI) compounds is much higher than Cr(III) compounds [35]. But when Cr(III) is exposed to moderate alkaline to slightly acidic conditions, it is immobile and the toxicity is much lower [36]. Cr(III) is an essential trace element whose deficiency results in glucose tolerance, inability to use glucose and other metabolic disorders. It is an element that is nontoxic, poorly absorbed and with nutritional value. Absorbable Cr(III)’s daily requirement ranges from 0.5 to 2 µg, but above this level, chromium becomes toxic to human health. Severe acute effects and death may result followed with a cardiovascular shock when 1–5 g of chromate is digested [37, 38]. Liver and kidney damage, internal hemorrhage and respiratory disorders occur when exposed to Cr(VI) as it is very toxic. Soluble hexavalent chromium compound could be fatal to human beings if oral doses of 2–5 g are taken. Kidney and liver damage results after 1–4 days of exposure when less than 2 g of hexavalent chromium compound is ingested [38]. Dermatitis and skin ulceration are the subchronic and chronic effects of Cr(VI) exposure. Though inhalation of Cr(VI) has proved to cause cancer in humans and animals, so far ingestion of Cr(VI) has not proven to cause cancer. In factory workers, Cr(VI) compounds have been the cause of lung cancer.

4.1 Cr(VI) Drinking Water Standards The recommended guideline value for total chromium by World Health Organization (WHO) is 50 µg/lt due to its highly toxic nature [19]. Total chromium value of 100 µg/lt has been recommended as the maximum contaminant level (MCL) by USEPA and has classified chromium as a human carcinogen (group A) [39]. Canadian and Australian drinking water quality guidelines and the EC water directive for the Maximum allowable concentration of total chromium in water is 50 µg/lt [40–42]. Regarding the health effects and guideline value for chromium in drinking water, WHO has made the following decision “In principle, because the health effects are determined largely by the oxidation state, different guideline values for chromium(III) and chromium(VI) should be derived. However, current analytical methods and the variable speciation of chromium in water favour a guideline value for total chromium. Because of the carcinogenicity of chromium(VI) by the inhalation route and its genotoxicity, the current guideline value of 0.05 mg/L has been questioned, but the available toxicological data do not support the derivation of a new value. As a practical measure, 0.05 mg/L, which is considered to be unlikely to give rise to significant risks to health, has been retained as a provisional guideline value until additional information becomes available and chromium can be re-evaluated” [37].

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5 Comparison of Methods for Chromium Reduction Reduction of hexavalent chromium by physicochemical processes is of great importance because of the toxic effects they have on the human body. Conventional processes use a large amount of chemicals generating toxic sludge. Conventional processes have undergone developments and the emergence of various techniques such as thermal treatment [42] desalination [43] direct reduction [44, 45], resin adsorption [45–48], electrolysis [49, 50], electrocoagulation [50, 51], activated carbon adsorption [52, 53], composite ceramic adsorption [54–56], carbon nanofibers adsorption [57, 58], nanomaterials catalyzed reduction [59, 60] and catalytic reduction [61, 62]. These processes are complex processes as they have different intensive sub-processes [63–65]. Cr(VI)-contaminated soil sample with 15% carbon at a temperature range from 1000 to 1400 °C is placed in a TGA apparatus for carbon thermal reduction of Cr(VI), CO2 gas emitted during the process was ignored [42]. Reduction of Cr(VI) by electrochemical desalination method to separate the desalination chamber from anode and cathode involves the usage of two costly membranes [43]. The conventional methods of Cr(VI) reduction by the synthesis of nanomaterials carbon fibres, composites, required costly resins which were not very costeffective and ecofriendly [43–65]. To treat chromium-borne effluent at the site itself by conventional methods involves setting up the pilot-scale operations which has multiple steps at the place of discharge. The complications involved in the treatment by conventional methods have led to developing alternate methods.

5.1 Chromium Removal from Water The Treatment Methods Can Be Classified as Follows (i) (ii) (iii) (iv) (v)

Coagulation–precipitation–filtration (including redox-assisted coagulation). Adsorption onto different media. Ion exchange. Membrane technology and electrodialysis. Biological removal.

When high concentrations of chromium are present, the above methods are the most suitable. Chromium recovery and reuse of chromium are the traditional methods of chromium removal from wastewater. The amount of chromium is much lower and the aim is to reduce their concentrations below the level specified by the drinking water quality standards and guidelines. The advantages, disadvantages and the treatment methods suitable for chromium removal from water sources have been discussed below.

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5.2 Coagulation–Precipitation–Filtration Coagulation using alum and Fe(III) as coagulants have been used for Cr(III) removal in the conventional treatment process. Cr(OH)3 precipitates and Al(OH)3 or Fe(OH)3 co-precipitates removing Cr(III) from water. The removal efficiency was 85.4% and 89.6%, respectively, when alum (pH = 7.7, dosage = 10 mg/l) and Fe(III) sulphate (pH = 7.4, dosage = 13 mg/l) was used to remove chromium from wastewater containing 0.46 mg/l initial concentration as was investigated by Fatoki and Ogunfowokan [66]. But for Cr(VI) removal, these coagulants are ineffective and therefore Cr(VI) is reduced to Cr(III) using Fe(II) sulfate, zero-valent iron, sulphur dioxide or sodium bisulfite which precipitates Cr(OH)3 . Using Fe(II) sulphate as a coagulant for removal of Cr(VI) is 100% effective as Cr(OH)3 is precipitated when Cr(VI) is reduced [67–69]. The most effective pH range is 5.0–9.0 for fast reduction of Cr(VI) to Cr(III) which will take minutes to hours. Depending on the concentration of Cr(VI), the Fe(II) dosage requirement will be 3–5 times of Cr(VI) [68, 70]. To meet the environmental standards for discharge of Cr(VI), the reducing agent requirement is 50% excess than the stoichiometric requirement after precipitation of Cr(III) as was reported by Barrera-Diaz et al. [70]. Reduction of Cr(VI) can be done electrochemically by Fe(II) in water in the form of pure ion electrode. This electrode would release Fe2+ ions into the solution, thereby reducing Cr(VI) to Cr(III) [71]. When Fe(II) salts are used as a reduction agent in the removal of Cr(VI), Fe(II) ions get converted to Fe(III) compounds which is an excellent coagulating agent produced at site. During simultaneous oxidation–reduction process, Fe(III) hydroxides formed coagulate the poorly water-soluble Cr(III) compounds formed. The Fe(III)-hydroxide–Cr(III)-hydroxide aggregations ease the separation in conventional solid–liquid phase treatment [72]. Separation of Cr(VI) by coagulating and precipitating it depends on the pH of the solution. Acidic conditions prevail when Cr(VI) is reduced to Cr(III) with the formation of chromium oxide. By adding NaOH or lime, pH is raised precipitating the hydrated chromium oxide. When chromium is present as Cr(III), it is removed by adding NaOH and raising its pH. Cr(III) can be effectively removed by precipitation with the addition of NaOH or lime [73, 74]. Removal of chromium can also be simply achieved by direct filtration than the conventional coagulation–precipitation– filtration method. Practical limitations in the coagulation–precipitation process for removal of heavy metal are the following: (i)

If metals are in complex form or if they are present as anions precipitation is not very effective. (ii) Solubility of the product governs the lowest metal concentration. (iii) Small particles formed when metals precipitate may not settle quickly, and therefore to collect this large settling basin is required followed by a filtration unit causing difficulty in the solid–liquid separation [74]. Disposal of a large amount of chromium-rich sludge produced by this method becomes a problem.

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5.3 Adsorption onto Different Media Adsorption process is used to remove inorganically and organically complexed metals as well as oxyanionic metals such as CrO4 2− and SeO3 2− when it is not possible to remove by conventional treatment methods [74]. Efficiency achieved by using precipitation processes to reduce the concentrations of many metals in solution is less compared to adsorption onto iron oxide. A common adsorbent used in metal removal processes has been ferrihydrite. An effective way to remove chromium from wastewater effluent is by using iron-oxide-coated sand (IOCS) as an adsorbent, which is produced by coating quartz sand with ferric nitrate [75, 76] Adsorption of heavy metals from drinking water can be achieved by using IOCS, which is a promising method as shown by previous studies done by researchers [76]. For removal of different contaminants including heavy metals activated carbon has been widely used. Effectiveness on Cr(III) and Cr(VI) removal using activated carbon has been studied at several laboratory scale as activated carbon has an affinity for heavy metals [77–80]. Removal of chromium from drinking water sources containing low chromium content using activated carbon so far has no proof of application and efficiency. From wastewater Cr(VI) removal using batch, fixed bed and fluidized bed processes with various adsorbents like pyrite fines, calcined Mg–AlCO3 hydrotalcite [36, 81], coal [82], bone charcoal [83] and manganese-oxide coated sand (MnOCS) [84] have been studied for their effectiveness by different researchers but these studies were conducted only at the laboratory scale.

5.4 Ion Exchange USEPA recommends ion exchange as the best available technology to remove chromium [85]. When a low concentration of chromium is present in small systems, it is the best-proven technology that has been studied [86–90]. Cr(VI) can be appropriately removed by anion exchangers and cation exchangers remove Cr(III). A strongbasic anion exchangers with an exchangeable counterion of Cl− are commonly used for removal of Cr(VI). As chromate prefers anion in water, synthetic resins are considered as an ideal anion exchanger for chromium removal [90]. For removal of chromium in water several ion-exchange resins, namely, strong anionic resins (e.g. Amberlite IR and IRA-900, DOWEX 1), weak anionic resins (e.g. Amberlite IR 67RF and IRA-94, DOWEX MA43 and MAC3) and cationexchange resins (e.g. Amberlite IR-120, IRN77 and SKN1) have been used [88, 90, 91]. When both species Cr(III) and Cr(VI) are present in water than a two-step ion exchange process would be effective which uses a cation resin for removal of Cr(III) and an anion resin for removal of Cr(VI). An Illinois firm in its chrome plating line has a two-step ion-exchange treatment system for removal of chromium from its wastewater. It is done by passing it through a cation exchange resin Amberlite

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IRA-120 were iron, nickel, trivalent chromium and then various other cations are removed and then for the removal of hexavalent chromium, fluoride, and other anions, passing it through a second column packed with Amberlite IRA-402 anion exchange resin [77]. Generally, weak base anion exchange resins are used under acidic pH values to remove chromates from water. A stoichiometric ratio of NaOH is used for regeneration of the resin. At neutral pH, strong-base anion exchange resins can be used for the removal of traces of chromate from tap water. For regeneration of resin 5–8%, sodium chloride solution is used. By adding sodium hydroxide to the regeneration solution, the resin in HCrO4 − form transforms into CrO4 − form thereby improving the regeneration efficiency. Though the ion-exchange method has so far proved as the best method for chromium removal the deficiency in using resins are (i) (ii) (iii) (iv)

regular regeneration requirement, concentrate disposal, potential fouling of the resins, effect of other ions present in the water on removal efficiency.

5.5 Membrane Technology and Electrodialysis Reverse osmosis is considered as one of the best membrane technologies to improve chromium [86, 92, 93]. All forms of chromium can be removed by reverse osmosis that is considered good (60–90% removal to excellent (90–100%) removal) for Cr(VI), and excellent(90–100% removal) for Cr(III). Different wastewater effluents have been treated with a reverse osmosis process for the removal of chromium and other heavy metals. Very few literature on the use of nanofiltration for effective removal of Cr(VI) have been published [93]. Modification of membrane technology to improve the effectiveness of chromium removal have been examined. They are (i) micellar-enhanced ultrafiltration using cationic surfactant [94]. (ii) Use of polymer inclusion membranes [95]. (iii) ion-exchange membranes [96]. Report on the effectiveness of Cr(III) removal by electrodialysis from water and wastewater has been investigated [97–99]. Removal of both Cr(III) and Cr(VI) by reverse osmosis technique for producing drinking water is one of the best available technologies. Investments have to be done as membranes are subjected to fouling incurring operational costs. Membrane fouling can be avoided by preventing corrosion of well casings and entrapment of air that oxidize iron and sulphur compounds. Using non-corrosive piping materials, namely stainless steel, polyvinyl chloride and fiberglass and ensuring airtight system by using vertical turbine pumps with mechanical seals or submersible pumps will prevent corrosion [100].

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5.6 Biological Removal Researchers have used different types of bacteria and biomass to remove chromium successfully from wastewater in the laboratory-scale studies. But using them in water sources for producing drinking water has seen limited work done. For drinking water treatment applications, this method is not suitable as biological methods are more effective with pH < 6 and which is not possible for drinking water. Increasing attention has been given to microbial Cr(VI) removal methods [101, 102]. Bacterias, namely Pseudomonas fluorescens LB300 [103], Enterobacter cloacae HO1 [104] and Bacillus sp have been used for Cr(VI) reduction under aerobic or anaerobic conditions [105]. Both species of chromium can be removed by alfalfa biomass, which has shown high potential as was reported by Dokken et al. [105]. Good chromium biosorption has been demonstrated in treating effluents by Kratochvil et al. [106], using biomass of marine alga Sargassum sp. Effective removal of chromium in water by using fungal biomass has been reported by Bai and Abraham [107] and Srivastava and Thakur [108]. Compared to treatment by chemical processes, treating wastewaters and soils contaminated by Cr(VI) by biological detoxification to Cr(III) makes it less toxic and less mobile [109, 110]. Biosorption, phytoremediation, indirect reduction by application of different electron shuttles, bioremediation, bioaccumulation, inner and outer cellular reactions such as direct reduction by chromium reducing bacteria are the different detoxification processes of Cr(VI) [63, 109]. 95% of Cr(VI) reduction is due to the production of ascorbate with glutathione and cysteine during the metabolism of cells [110, 111]. This cellular metabolism is a simple natural biological metabolism process requiring the ambient atmospheric conditions for the biological species to grow. Requirement of extra nutrients is not required for the biological species when used in the upscale applications of the bio-reduction of Cr(VI) as the species grown are indigenous species [65].

6 Conclusion Water systems are enriched by different anthropogenic activities such as chromite or ferrous-chromite mining, leather tanning, pigment synthesis, electroplating and metal finishing. Water source contaminations by chromium have been reported in many countries either naturally or anthropogenically. Regulatory agencies worldwide have set standards for chromium in drinking water, with emphasis on Toxicity and carcinogenicity of chromium when present in the drinking water source. This study was done to have complete knowledge about the environment and the source of chromium in it, the effect of it on biotic components, the process of addition

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of Cr(VI) to the water bodies, microorganisms’ behaviour and their resistance to toxicity. Factors that contribute to the effective removal of chromium from water are species of the chromium present and their concentrations, pH and the concentrations of other cations and anions in the water. Removal of Cr(VI) is difficult than Cr(III) removal, as Cr(III) is insoluble at neutral and higher pH. Removal of chromium has been done by coagulation followed by filtration, adsorption, ion exchange and membrane filtration. The most effective method of chromium removal is the coagulation–precipitation followed by the adsorption process. These processes generate chromium-rich sludge, adsorbent and regenerant whose disposal is the main problem. In a small system, ion exchange is a good method for the removal of low concentration chromium. Ion exchange can also be used for large systems but for removal of Cr(III) and Cr(VI) different types of exchange resins are required. Both species of chromium can be removed by reverse osmosis and nanofiltration, but it comes with certain limitations, namely membrane fouling, large volumes of concentrated liquid toxic waste generated and with high processing costs. Cr(VI) is reduced to Cr(III) as Cr(VI) causes toxicity in the living organisms. Carcinogenicity could be caused by the generation of reactive species inside cells followed by Cr(III) protein coordination complex formation and finally DNA damage. In humans, adsorption of Cr(VI) leads to adsorption on the stomach wall, effects sperm productivity and causes cancer of the bronchial systems and neurotoxicity. Reduction of Cr(VI) to less soluble Cr(III) and then hydrating it to solidify the reduced species than direct precipitation of Cr(VI) is an easier way to remove Cr(VI) from water. Bio-reduction by chromium reducing bacteria is very effective at a variety of conditions including pH, temperature, contact time, agitation, nutrient medium, redox stimulating reagents, carbon and nitrogen sources, immobilizers, free cell reductase and many more. Removal of chromium from drinking water source by a process that is efficient and cost-efficient still remains a requirement. More focus should be given to Cr(VI) removal on pilot scale and industrial scale.

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Study of Behaviour of Web-Stiffened Built-up Beam C. Divya Megala and M. Anbarasu

Abstract Behaviour of cold-formed steel built-up beams with web stiffeners and the results of flexural buckling strength are presented in this paper. Cold-formed steel sections are used to minimize heat loss, providing thermal insulation to the structure hence making the structure more sustainable. Investigation of simply supported built-up section beam configuration has been conducted under uniform bending with forked edge condition. The built-up section is formed by placing web-stiffened channels to form closed section by using the self-tapping screws. Intermediate stiffeners were employed to the webs of built-up sections to improve the buckling strength. The numerical models of selected sections were developed and validated against the results reported by Wang (2017) and kankanamge (2010). The parametric study is carried out to study the influence of different cross sections by varying thickness, height to width ratio and length of the beams. Buckling analysis was performed on selected parametric models by the finite element software ABAQUS and by the suitability of design methods established in EN1993-1.1. The moment carrying capacity and buckling design resistance was also investigated using the developed finite element model. Critical buckling moments obtained from the analysis were compared with the results predicted by using EUROCODE specifications and discussed. Keywords Buckling strength · Built-up beam · Cross sections · Design resistance · Thermal insulation

C. D. Megala (B) · M. Anbarasu Department of Civil Engineering, Government College of Engineering, Salem 636 011, India e-mail: [email protected] M. Anbarasu e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_5

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C. D. Megala and M. Anbarasu

1 Introduction Steel sheets of less thickness are folded to form cold-formed steel (CFS). Coldformed steel sections are used to minimize heat loss, by proper design providing thermal insulation to the structure hence making the structure more sustainable. In thin-walled structure of the cold-formed, longitudinal stiffeners are provided to improve the buckling strength of the section. The structural behaviour of the CFS built-up beams are studied and ultimate moment capacities were found out to develop more accurate design methods to assess the stability of built-up members. Most of the research studies are related to the behaviour of CFS by means of analytical and numerical valuations. Different profiled sections were chosen and it was found that open sections are susceptible to lateral torsion buckling and closed sections were susceptible to distortional buckling [1]. A similar study was done varying the profiles and providing stiffeners to find the behaviour of the section [2, 3]. Work was undertaken for lipped channel section to study the behaviour at both normal and elevated temperatures with EUROCODE provisions and new buckling curve ‘a’ was provided for elevated temperatures [4]. Based on the studies built-up beam with different profile was selected and its structural behaviour was examined by analytical and numerical analysis [5–9].

2 Specimen Selection The section dimensions were selected based on the guidelines provided in EN 19931-3 [4] for CFS sections. Figure 1 shows the typical specimen selected for this work. The built-up section is made by placing two web-stiffened channel section one above the other to form the closed section, where the shear centre and centroid coincides for the section as shown in Fig. 1. The flanges of the channel sections were fastened by using self-driving screws. Fig. 1 Typical section details

Study of Behaviour of Web-Stiffened Built-up Beam

55

where h—Depth of the section, bf —Breadth of the section, t—Thickness of section. The labelling is illustrated below by taking an example of 100 × 50 × 1 built-up beam.

3 Finite Element Modelling The finite element program ABAQUS 6.13 [10] is a computational tool for modelling structures. The finite element modelling has been done using ABAQUS software. GBTUL software is used to calculate the section properties of the specimen and using this software buckling failure modes can also be predicted. All profiles were modelled by using shell elements (S4R). Material modelling was done by assuming the density of 7.89e-9 MPa, the elastic modulus was equal to 2.1e5 MPa and the Poisson’s ratio to be 0.3. With reference to Wang thesis to save computational time 10–10 mm meshes were generated [10, 11]. Interaction: In modelling the contact behaviour, two assumptions were introduced, i.e. tangential friction and hard contact for analyses. The fasteners are assigned to the attachment with 5 mm c/c spacing for 1.5*web depth length as end fasteners and intermediate fasteners are provided at 150 m c/c spacing for remaining length as per Schafer and Pekoz paper specifications [12]. Figure 2 shows a section with fasteners at the appropriate spacing. Boundary and Loading Conditions: With regard to the loading on the beams, forces were applied as uniform bending moment using shell edge load. The uniform load applied in the section is shown in Fig. 3

Fig. 2 Section with fasteners

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C. D. Megala and M. Anbarasu

Fig. 3 Loading condition

3.1 Validation The FE modelling approach has been validated with 4 experimental cold-formed built-up steel beam sections by Wang et al. [11] and Kankanmge [13]. From Behaviour of CFS Built-Up Sections with Intermediate Stiffeners under Bending Tests and Numerical Validation of Wang et al. [10], sections were chosen and the procedure for performing the analysis was found out by validating the ultimate moments [11]. Local buckling failure was found. Therefore Kankanmge thesis [13] is chosen and channel section is validated for lateral torsional buckling (LTB) behaviour. The comparison between the ultimate moment (Mu) of the tested specimens, and those computed by the finite element analysis are presented in Tables 1 and 2, which shows a reasonable agreement between the finite element results and test results. Therefore, this procedure is adopted to perform parametric analysis for the selected specimen with few modifications. Table 1 Comparison of experimental and FEA ultimate moment capacities Section

Mu from validated paper kNm

Mu from FEA kNm

Failure mode

Accuracy (%)

CV-1.0-B4

4088

4019

Local + flexure

98.32

CV-1.0-B3

4218

4992

Local + flexure

84.5

Table 2 Comparison of Experimental and FEA Ultimate Moment Capacities S. No

Specimen ID

Ultimate load MU (kNm) FEA

Test m o FEM m o

Test m u FEM m u

Failure mode

TEST

Mo

Mu

Mo

Mu

1

G450-110-35-15-1.9 (l = 2 m)

2.21

1.58

2.16

1.82

0.98

1.15

LTB

2

G450-110-35-15-1.9 (l = 3 m)

1.12

0.91

1.16

1.17

1.03

1.008

LTB

*LTB––lateral–torsional buckling

Study of Behaviour of Web-Stiffened Built-up Beam

57

4 Parametric Study Parametric analysis was performed with about 72 numerical simulations, in order to investigate the influence of the thickness, the height and the length on the flexural behaviour of the beams. The aim of the parametric study is to understand the different buckling behaviour of the CFS built-up C beams and also to generate data for the development of design rules. Finally, the numerical analysis was performed for those selected sections and the obtained results were compared with the results calculated by the design methods for CFS members established in EN1993-1-3 [4]. A total of 72 FE models with beam lengths varying from 3000 mm to 15000 mm with 2.5 mm and 4 mm thickness, three different cross sections of 100 × 50, 112.5 × 50 and 125 × 50 (all in mm) were analysed in the FE parametric studies of coldformed built-up steel beam sections. The cross-sectional properties and their calculations were verified by checking with earlier works. Linear analysis was performed to obtain the critical elastic buckling moment. Figure 4 shows the deformed shape after linear analysis, along with the cut section view. Critical elastic moment (M cr Pred) of the section can be calculated from EN19931-3 guidelines by using the following equation  Mcr = Cb

  π 2 EI y π 2 EIW  2 GJ + (LKW )2 LK y

(1)

where EIy , EIw and GJ are the major axis flexural rigidity, warping rigidity and torsional rigidity, respectively. The value of the factors k y and k w are equal to 1. Constant C b was equal to 1.

Fig. 4 Deformed shape and cut section after analysis

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C. D. Megala and M. Anbarasu

5 Results A total of 72 FE models with beam lengths varying from 3000 mm to 15000 mm with 2.5 mm and 4 mm thickness, three different cross sections of 100 × 50, 112.5 × 50 and 125 × 50 (all in mm) were analysed in the FE parametric studies of coldformed built-up Steel beam sections. The results obtained from the FE analysis were compared with EUROCODE calculations and shown in Table 3.

6 Discussion As per EUROCODE standards, the behaviour of lateral–torsional buckling (LTB) was studied for the non-dimensional slenderness ratio ranges 0.3–1 and thickness varying from 2.5 mm to 4 mm. Three cross-sectional specimens of varying length were investigated. The failure mode observed was LTB for all the sections. The existing elastic buckling moment equation in EC3 code conservatively predicts the LTB strength for sections with greater thickness as inferred from Graphs 1 to 2. From Table 3, conservatism is found for reduced thickness sections with a slenderness ratio ranging from 0.4 to 0.55 and it is becoming non-conservative as slenderness ratio exceeds 0.55. It is observed that the increase in slenderness ratio, will give more accurate results predicted by using EUROCODE in comparison with the FEA analysis results. Thus, for the increase in length, EUROCODE provisions are conservative. The variation in EUROCODE predictions was mainly due to not considering the effect of screw spacing along the length of the built-up sections.

7 Summary and Conclusions This project describes the LTB strength and behaviour of CFS built-up beams with web stiffeners. The numerical model was validated by means of comparison with the experimental results reported by Wang [11] and Kankanamge [13]. A total of 72 numerical simulations performed with the finite element program ABAQUS were made. Lastly, the suitability of design methods established by EN1993-1.1 for the moment carrying capacity. Based on this study, the following conclusions are drawn: • The failure mode observed was lateral–torsional buckling for all the sections. • The finite element results showed that the elastic critical buckling moment decreases as the length of the beam increases. • It is also shown that EN1993-1.3 predictions may be conservative for beams of greater thickness and slenderness ratio varying from 0.4 to 0.55. However, these design guidelines may give unsafe results for these beams with a slenderness ratio greater than 0.55 and reduced thickness less than 4 mm.

Study of Behaviour of Web-Stiffened Built-up Beam

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Table 3 Comparison of moment capacities from FEA with codal prediction Specimen

Span (mm)

λLT

FEA (kNm) M cr M CR pred (kNm)

M cr /M CR pred

Thickness in mm CV-100-50

CV-112.5-50

CV-125-50

2.5

4

2.5

3000

0.33

0.33

24.63

4000

0.38

0.39

5000

0.43

0.44

6000

0.47

7000 8000

4

2.5

4

2.5

4

54.97

66.31

59.73

0.37

0.92

18.6

38.31

49.72

44.79

0.37

0.86

13.63

28.09

39.77

35.82

0.34

0.78

0.48

10.38

21.39

33.14

29.85

0.31

0.72

0.51

0.52

8.15

16.77

28.4

25.59

0.28

0.66

0.54

0.55

6.56

13.46

24.85

22.39

0.26

0.6

9000

0.58

0.58

5.38

11.01

22.09

19.9

0.24

0.55

10000

0.56

0.61

4.48

9.16

19.88

17.91

0.22

0.51

11000

0.64

0.64

3.79

7.73

18.07

16.28

0.21

0.48

12000

0.66

0.67

3.25

6.6

16.56

14.92

0.19

0.44

13000

0.69

0.7

2.81

5.7

15.29

13.78

0.18

0.41

14000

0.72

0.73

2.45

4.97

14.2

12.79

0.17

0.39

15000

0.75

0.75

2.16

4.37

13.25

11.94

0.16

0.37

3000

0.33

0.34

58.28

75.88

68.68

0.77

1.53

4000

0.39

0.39

47.86

94.13

56.88

51.49

0.84

1.83

5000

0.43

0.44

39.98

77.73

45.49

41.19

0.88

1.89

6000

0.48

0.48

33.77

59.01

37.91

34.32

0.89

1.72

7000

0.51

0.52

28.78

45.71

32.49

29.42

0.89

1.55

8000

0.55

0.56

24.82

36.08

28.43

25.74

0.87

1.4

9000

0.58

0.59

21.51

29.01

25.27

22.88

0.85

1.27

10000

0.62

0.62

18.88

19.7

22.74

20.59

0.83

0.96

11000

0.65

0.65

16.58

16.51

20.67

18.72

0.8

0.88

12000

0.67

0.68

14.68

14.13

18.95

17.16

0.78

0.82

13000

0.7

0.71

13.05

12.17

17.49

15.84

0.75

0.77

14000

0.73

0.74

11.66

10.59

16.24

14.71

0.72

0.72

15000

0.75

0.76

10.47

9.29

15.16

13.73

0.69

0.68

3000

0.32

0.35

64.14

142.7

85.46

77.66

0.75

1.84

4000

0.37

0.39

48.32

111.8

64.06

58.22

0.75

1.92

5000

0.42

0.44

33.89

87.87

51.23

46.56

0.66

1.89

6000

0.45

0.49

24.14

69.62

42.69

38.8

0.56

1.79

7000

0.49

0.52

16.96

55.74

36.58

33.25

0.46

1.68

8000

0.52

0.56

13.30

45.24

32.01

29.09

0.41

1.56

9000

0.55

0.59

10.77

37.19

28.45

25.86

0.38

1.44

104.8

(continued)

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C. D. Megala and M. Anbarasu

Table 3 (continued) Specimen

Span (mm)

λLT

FEA (kNm) M cr M CR pred (kNm)

M cr /M CR pred

Thickness in mm 2.5

4

2.5

4

2.5

4

10000

0.58

0.63

2.5 8.66

4 30.98

25.60

23.27

0.39

1.33

11000

0.61

0.66

6.41

26.12

23.28

21.16

0.28

1.24

12000

0.64

0.69

5.52

22.27

21.33

19.39

0.26

1.15

13000

0.67

0.72

4.92

19.19

19.69

17.9

0.25

1.07

14000

0.69

0.75

4.43

16.69

18.29

16.62

0.24

1

15000

0.71

0.77

4.12

14.61

17.07

15.51

0.24

0.94

0.54

1.18

Average Graph 1 Comparison graph for FEA and predicted M cr (2.5 mm thickness)

Mcr comparison graph for 2.5mm thickness 100 cv-1-1

Buckling moment in kNm

80

cv-1-2

60

cv-2-1

40

cv-2-2

20

cv-3-1

0

cv-3-2 0

2

4

6

8 10 12 14 16

Length in m

Buckling moment in kNm

Graph 2 Comparison graph for FEA and predicted M cr (4 mm thickness)

160 140 120 100 80 60 40 20 0

Mcr comparison graph for 4mm thickness cv-4-1 cv-4-2 cv-5-1 cv-5-2 cv-6-1 cv-6-2 0

2

4

6

8

10

Length in m

12

14

16

Study of Behaviour of Web-Stiffened Built-up Beam

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Further study can be extended to more number of sections aided with experimental results to develop the new design guidelines for the built-up beam with web stiffeners.

References 1. Laim L, Rodrigues JPC, da Silva LS (2013) Experimental and numerical analysis on the structural behaviour of cold-formed steel beams. Thin-Walled Struct 72:1–13 2. Wang L, Young B (2014) Design of cold-formed steel channels with stiffened webs subjected to bending. Thin-Walled Struct 85:81–92 3. Wang L, Young B (2015) Behaviour of cold-formed steel built-up sections with intermediate stiffeners under bending. I: Tests and numericalvalidation. J Struct Eng. https://doi.org/10. 1061/(asce)st.1943541x.0001428,04015150 4. European Committee for Standardization (CEN) (2006) Design of steel structures, part 1.3: General rules—Supplementary rules for cold-formed members and sheeting. EN 1993-13:2006, Eurocode 3, Brussels, Belgium 5. Anbarasu M (2016) Local-distortional buckling interaction on cold-formed steel lipped channel beams. Thin-Walled Struct 98:351–359 6. Adil Dar M, Subramanian N, Dar AR, Anbarasu M, Lim JBP, Atif M (2019) Behaviour of partly stiffened cold-formed steel built-up beams: experimental investigation and numerical validation. Adv Struct Eng 22(1):172–186 7. Hancock GJ, Kwon YB, Bernard S (1994) Strength design curves for thin-walled sections undergoing distortional buckling. J Constr Steel Res 31(2–3):169–186 8. Yu C, Schafer BW (2006) Distortional buckling tests on cold-formed steel beams. J Struct Eng, ASCE 132(4):515–528 9. Wang L, Young B (2014) Cold-formed steel channel sections with web stiffeners subjected to local and distortional buckling—Part II: parametric study and design rule. In: International specialty conference on cold-formed steel structures 10. ABAQUS (2013) Dassault Systems Simulia Corp, ABAQUS Standard User’s Manual Version 6.13. USA 11. Wang L, Young B (2017) Behaviour of cold-formed steel built-up sections with intermediate stiffeners under bending. I: parametric study and design. J Struct Eng. https://doi.org/10.1061/ (asce)st.1943-541x.0001427 12. Schafer B, Pekoz T (1998) Computational modelling of cold-formed steel: characterizing geometrical imperfections and residual stresses. J Constr Steel Res 47:193–210 13. Kankanamge ND, Mahendran M (2010) Structural behaviour and design of cold- formed steel beams. Thin walled Struct 51:25–38

Geotechnical Properties of β-Glucan-Treated Clayey Sand M. Vishweshwaran, Evangelin Ramani Sujatha, Nadendla Harshith, and Cheni Umesh

Abstract Various techniques are used to improve and stabilize soil, most common are the mechanical and chemical methods. The materials used for soil stabilization pose challenges such as possible contamination of soil and groundwater, and emission of carbon dioxide during manufacturing. β-glucan, a biopolymer offers an attractive alternative and has greater potential for application in soil stabilization, yet only limited research is available. Monomers of D-glucose (C6 H12 O6 ) connected by β-glycosidic bonds lead to the formation of β-glucan. The structure of β-glucan can be varying. β-1,3/1,6-glucan possesses ramiform and helical shapes. They exhibit hydrogen bonding with external ions. β-glucans which possess good tensile strength have potential applications in controlling the cracking and tensile failure of many earth structures. They also exhibit better adsorption features. In this work, it was added in quantities of 0.5, 1, 1.5, 2, 2.5 and 3% to clayey sand. Select geotechnical properties such as liquid and plastic limits, optimum moisture content (OMC), maximum dry density, shear strength and permeability were determined. Durability tests, tests on biopolymers such as gel matrix formation and its degradation were conducted. Keywords Soil stabilization · Biopolymer · Angle of internal friction · β-glucan · Durability

M. Vishweshwaran (B) · E. R. Sujatha · N. Harshith · C. Umesh School of Civil Engineering, SASTRA Deemed University, Thanjavur, India e-mail: [email protected] E. R. Sujatha e-mail: [email protected] N. Harshith e-mail: [email protected] C. Umesh e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_6

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1 Introduction Biopolymers are broadly classified into protein and polysaccharides. β-glucan falls under polysaccharides type. Choosing a biopolymer for soil stabilization depends on various factors such as cost, availability, viscoelastic properties and affinity to water. Biopolymers are widely used in different industries such as food processing, paper production, cosmetics and pharmaceuticals. Chemical stabilization poses a threat to groundwater contamination and soil pollution. Traditional stabilization methods also pose a threat of pollution during the manufacturing process whereas biopolymers are naturally occurring polymers and are biodegradable. Biopolymers have been a topic of research for the past few decades but geotechnical properties of various biopolymer-treated soils have not yet been studied in detail. In geotechnical engineering, they have potential applications for surficial erosion control, shear strength improvement, liner material, pavement stabilization, etc. In 1997, guar gum slurry prevented the collapse of side walls when used during the excavation of trenches [1]. Xanthan gum has been effective in improving the properties of soils [2, 3]. β-glucans are food-grade biopolymers and detailed information on β-glucans related to geotechnical engineering are constrained. β-glucan solutions exhibit typical viscoelastic flow behavior, and do not form a gel within a reasonable time period [4]. Under lower temperatures, a thermo-reversible gel could be formed if the β-glucan solutions are allowed to stand for a time interval [5]. In civil engineering, beta-glucan is sometimes used as a superplasticizer material. It can also be used as a water-reducing agent [6]. Biopolymers are generally known to increase the plasticity of soil [7]. Even a small quantity such as 1% of xanthan gum is enough to increase the unconfined compressive strength of clays [3]. The addition of biopolymers resulted in cohesive strength for cohesionless sands [8]. pH influences the effect of negative charge on the biopolymer because it regulates the disassociation of carboxyl groups. Xanthan gum did not decompose even after 750 days [9].

2 Materials and Methodology 2.1 Soil Properties The soil is classified as Clayey Sand (SC). Free swell index was found to be 11.11%, indicating it’s a low swelling soil. Properties of the soil are indicated in Table 1.

2.2 Sample Preparation Wet mixing method was adopted to prepare the treated soil specimens. Water was added to β-glucan powder at its OMC with a reduction of 1% of OMC reserved for

Geotechnical Properties of β-Glucan-Treated Clayey Sand Table 1 Soil properties

65

Properties

Value

Liquid limit, wL

34%

Plastic limit, wp

17.83%

Plasticity Index, Ip

15.17%

Flow Index, If

6

Toughness Index, It

1.517

Free Swell Index

11.11

Classification

SC

mixing with soil. Thus β-glucan solution was obtained by adding the required amount of water to β-glucan powder and the solution was kept sealed for 2 h. The β-glucan solution was then mixed with the soil by initially mixing the soil with 1% water and immediately followed by mixing of β-glucan solution. The treated soil mixture was covered on top with a container to prevent loss of moisture. After 2 h, it is presumed that the treated soil has reached Equilibrium moisture content. The soil was then moulded for the respective tests. Wet mixing was adopted based on the results of the previous studies conducted for various other biopolymers [9]. For sandy soils, significant changes in strength were not observed in adopting a dry mixing method [10].

2.3 Grain Size Analysis The test was performed as per IS: 2720 (Part 4):1985 for the oven-dried soil [11]. The composition of coarse, medium and fine sand was 25%, 12% and 18.8%, respectively. Hydrometer analysis was conducted as per IS: 2720 (Part 4):1985. Percentages of clay and silt were 29% and 15.2%, respectively.

2.4 Liquid and Plastic Limits Properties and behaviour of clays are governed by the quantity of moisture present in them. At the liquid limit, a soil exhibits the lowest shear strength since the soil is practically similar to a liquid. Liquid limit was determined with the standard liquid limit apparatus as per IS: 2720 (Part 5):1980 [12]. Flow index was determined from the slope of the flow curve. Plastic limit indicates the water content below which the soil stops behaving as a plastic material. The liquid and plastic limits of the soil were found to be 34% and 17.83%, respectively. Flow index and toughness index were 6% and 1.517%, respectively.

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Fig. 1 Direct shear specimens

2.5 Standard Proctor Test Identification of OMC is crucial in adding the correct amount of water for the subsequent engineering properties’ tests. The OMC and MDD were determined using the standard proctor test in accordance with IS: 2720 (Part 7):1980 [13]. After four hours of mixing, the test was done.

2.6 Direct Shear Test Shear strength is a very important engineering property for soils since the stability of the soil depends on its shear strength. Direct shear test was carried out in accordance with the specifications outlined in IS: 2720 (Part 13):1986 for both untreated and treated samples [14]. Samples of 6 cm × 6 cm size were moulded at the required biopolymer content and OMC. It was air-cured for the required period and tested in the direct shear testing machine. The test was carried out at 0, 7, 14 and 28 days. Figure 1 shows the specimens after failure at 0.5% and 1%.

2.7 Free Swell Index Test The test was conducted as per IS: 2720 (Part 40):1977 [15]. Free swell index indicates the surge in the volume of a soil, in the absence of external agents, on submergence in water.

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2.8 Durability Test Durability test was performed to study the performance of the clayey sand and its stabilized mixture for 12 cycles of wetting and drying. The test was conducted as per IS: 4332 (Part 4):1968 [16]. The test was done to identify the ability of the soil to resist weathering forces by retaining the integrity and stability of the stabilized soil. Both untreated and treated soils were mixed with OMCs and the specimens were prepared in a mould of 4 cm diameter and 8 cm length. The specimens were wrapped in a cling firm while the top and bottom surfaces were exposed. Initial weights of the soil specimens were noted. All the specimens were placed on suitable carriers in the moist chamber and protected from free water for a period of 7 days. At the end of the storage in the moist room, the specimens were submerged in potable water at room temperature for a period of 5 h and removed. Weight and dimensions of the specimens were recorded. The specimens were then placed in an oven at 70 °C for 42 h and removed. Weight and dimensions of the specimens were recorded again. This procedure is repeated for 12 cycles and observations were recorded for changes in volume and strength.

2.9 Gel Matrix and Dehydration Tests About 1.5 grams of β-glucan was added to a measuring jar and water was sprinkled inside the measuring jar up to a height of 50 ml. This test was conducted to analyse the effect of water on β-glucan. Dehydration test was done to analyse the gel stability of β-glucan by wrapping the top portion of the measuring jar and was exposed to sunlight for 6 months.

3 Results and Discussions 3.1 Specific Gravity Specific gravity of the β-glucan was 1.44. Thus, the addition of β-glucan decreased the specific gravity of the treated soil.

3.2 Atterberg’s Limits Atterberg’s limits of a soil are dependent on the specific surface conditions of soil particles. The hydrogen bonds, ion exchange and Van der Waals force between organic matter and soil particles affect the double layer, rendering different responses

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Table 2 Liquid and plastic limits for different percentages Atterberg’s limits

0%

0.5%

1%

1.5%

2%

Liquid limit

34

35.2

36

36.6

37.4

Plastic limit

17.83

18.1

18.47

18.96

19.53

on the liquid limit behaviour. Liquid limit and plastic limit of the soil increased on the addition of β-glucan to the soil. But the increase was very minimum. Unlike other gum-based biopolymers which immediately become viscous on the addition of water, β-glucan only had a negligible effect on viscosity. The marginal increase in liquid limit is due to the imbibing of water for hydration of the biopolymer. The results of Atterberg’s limits have been indicated in Table 2.

3.3 Maximum Dry Density and Optimum Moisture Content An increase in biopolymer content led to an increase in the OMC. The OMC of the soil was found to be 12%. On addition of β-glucan for 2.5%, the OMC increased to 15%. MDD of soil was 18.1 kN/m3 . MDD increased with increasing percentages of β-glucan, the highest being 19.2 kN/m3 . The maximum value of dry density was observed at 1% followed by decreasing densities. Figure 2 indicates the variation of OMC and MDD. However,

Fig. 2 OMC and MDD for different percentages

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Fig. 3 Permeability for different percentages

the MDD values of treated soil were higher than the MDD of untreated soil at all biopolymer contents investigated. The increase of optimum water content is a result of the hydrophilic property of the biopolymer used in the study. Inter-particle cohesion enhancement depends on the strength of the biopolymer–clayey sand matrices, which is higher with lower water content. The friction angles of the soil increase with biopolymer treatment due to improved particle contact [17]. Biopolymers have high specific surfaces with electrical charges, which enable direct interactions between the biopolymers and fine soil particles, thereby providing firm biopolymer–soil matrices with high strength [17].

3.4 Permeability On addition of β-glucan, the coefficient of permeability decreases. Addition of a biopolymer plugs the pores and thereby reduces the path available for pore fluid to travel. This leads to a decrease in the permeability of biopolymer-treated soil. This property makes it suitable to be used as liners in canal beds and in farmlands to avoid erosion. The rate of decrease in permeability increases with the increase in the quantity of biopolymers as shown in Fig. 3.

3.5 Shear Strength Parameters Cohesion and angle of internal friction for untreated soil at 0 days were 29.75 kPa and 34.45°. Treated soil samples after 28 days of curing at 1% addition of β-glucan

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Fig. 4 Cohesion for different percentages

showed an increase in cohesion by 6 times and in the angle of internal friction by 13°. 1% addition of β-glucan resulted in maximum cohesion. On the other hand, a 0.5% addition of the same led to the highest value of angle of internal friction. On addition of β-glucan, hydrogen bonds that were formed stiffened the soil matrix. This results in higher strength of the biopolymer-treated soil. The addition of β-glucan fills the voids, coats the particles and forms hydration bonds that add strength to the treated soil [18]. After 0.5%, the bonding of biopolymer with soil contributes to an increase in cohesion but causes a decrease in friction angle. For stabilization of slopes, a better angle of internal friction is preferred. 0.5% shall be the optimum percentage for treatment in slopes. Cohesion improves the overall shear strength of the soil. 1% cohesion shall be best for improving the strength of the soil which has applications in improving pavement subgrade, stability of slopes, etc. Results of cohesion and angle of shearing resistance are shown in Figs. 4 and 5, respectively.

3.6 Durability Test After 12 cycles of wetting and drying, it was observed that the β-glucan-treated specimens did not undergo a high variation in weight and volume. The change in the weight was found to be slightly increased by not more than 4%. This result was in accordance with the gel matrix and dehydration test, which indicate the gel stability in an adverse environment. The maximum increase in weight was observed at 0.5% addition of biopolymers. The increase in weight with time is ascribed to the development of hydration products with age. The inter-linking of a biopolymer in the soil matrix may retard the degradation of the biopolymer. Even without thermal treatment, up to 96 days, the soil–biopolymer mixture did not undergo degradation. Soil specimens tested for durability are shown in Fig. 6.

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Fig. 5 Angle of internal friction for different percentages

Fig. 6 Durability test specimens

3.7 Gel Matrix and Dehydration Tests Gel matrix was not formed immediately. After 14 days, the solution became slightly viscous and translucent. Despite the β-glucan kept in a measuring jar without any enclosure, the viscous β-glucan showed no signs of decomposition. After 30 days, it became a highly viscous solution and almost became a solid matrix. The height of this solid matrix increased as the number of days increased. Even until 150 days, βglucan did not decompose. The powder form of β-glucan was not present throughout the measuring jar. Dehydration test indicated that the gel remained stable for a long period of time under the exposure of sunlight.

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4 Conclusions The results of the study point to the following conclusions. Compaction test indicates the hydrophilic nature of β-glucan and the increase in density of the soil. Permeability reduces on the addition of β-glucan because the biopolymer causes plugging effect and pores get filled to the maximum extent. β-glucan improves the shear strength of the clayey sand. 1% and 0.5% addition of β-glucan led to maximum cohesion and maximum angle of internal friction. Durability test indicated that, even without thermal treatment, up to 96 days, the soil–biopolymer mixture did not undergo degradation. Gel matrix test and dehydration test indicated that the gel remained stable for 150 days. These findings suggest that β-glucan helps in improving the engineering properties of the clayey sand.

References 1. Aminpour M, O’Kelly BC (2015) Applications of biopolymers in dam construction and operation activities. In: Proceedings of the 2nd International Dam World Conference, Lisbon, Portugal, vol. 1, pp 937–946 2. Rashid ASA, Latifi N, Meehan CL (2017) Sustainable improvement of tropical residual soil using an environmentally friendly additive. Geotech Geol Eng 35(6):2613–2623 3. Latifi N, Horpibulsuk S, Meehan CL (2016) Improvement of problematic soils with biopolymer—an environmentally friendly soil stabilizer. J Mater Civil Eng 29(2):04016204 4. Kasapis S, Norton IT, Johan B (2009) Modern biopolymer science: bridging the divide between fundamental treatise and industrial application. Academic Press 5. Cui X, Shin H, Song C, Laosinchai W, Amano Y (2001) A putative plant homolog of the yeast β-1, 3-glucan synthase subunit FKS1 from cotton (Gossypiumhirsutum L.) fibers. Planta 213(2):223–230 6. Kiho T, Sakushima M, Wang S (1991) Polysaccharides in Fungi. XXVI. Two branched (1 → 3)-β-D-Glucans from hot water extract of Yu e˘ r. Chem Pharm Bull 39(3):798–800 7. Nugent RA, Zhang G, Gambrell RP (2010) The effects of exopolymers on the erosional resistance of cohesive sediments. Scour and Erosion:162–171 8. Qureshi MU, Chang I, Al-Sadarani K (2017) Strength and durability characteristics of biopolymer-treated desert sand. Geomech Eng 12(5):785–801 9. Chang I, Im J, Prasidhi AK, Cho GC (2015) Effects of Xanthan gum biopolymer on soil strengthening. Constr Build Mater 74:65–72 10. Rezaeimalek S, Nasouri A, Huang J (2017) Comparison of short-term and long-term performances for polymer-stabilized sand and clay. J Traffic Transp Engineering (English ed.) 4(2):145–155 11. BIS, I. 2720, Methods of test for soils: Part 4 grain size analysis, 1985 12. BIS, I. 2720, Methods of test for soils: Part 5: Determination of liquid and plastic limit, 1985 13. BIS, I. 2720, Methods of Test for Soils: Part 7: Determination of water content-dry density relation using light compaction, 1980 14. BIS, I. 2720, Method of test for soils: Part 13 Direct shear test, 1986 15. BIS, I. 2720, Methods of test for soils, Part 40: Determination of free swell index of soils, 1977

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16. BIS, I. 4332.Methods of test for stabilized soils, Part 4: Wetting and drying, and freezing and thawing tests for compacted soil-cement mixtures, 1968 17. Chang I, Im J, Cho GC (2016) Introduction of microbial biopolymers in soil treatment for future environmentally-friendly and sustainable geotechnical engineering. Sustainability 8(3):251 18. Chang I, Cho GC (2012) Strengthening of Korean residual soil with β-1, 3/1, 6-glucan biopolymer. Constr Build Mater 30:30–35

Composite Leaching of Thermal Power Plant Bottom Ash to Ensure Its Performance on Cement Mortar Sivakumar Naganathan, Salmia Beddu, Muhammad Zulfiqar Ajmulkhan, Jegatheish Kanadasan, Zakaria Che Muda, Siti Nabihah Sa’don, and B. Mahalingam

Abstract Power plant bottom ash is classified as hazardous waste in Malaysia and hence its reuse needs to be carefully decided. The chemical content in the bottom ash may interfere with the performance of bottom ash in construction applications. This paper discusses the effect of chemical leaching of bottom ash using a mixture of Hydrochloric acid with Hydrofluoric acid, Hydrochloric acid with Nitric acid and water washing method on the performance of bottom ash in cement mortar. Tests such as sieve analysis, specific gravity, water absorption, fineness modulus, bulk density and compacted density have been carried out for physical characteristics for the leached and washed bottom ash. Mortar mixtures were prepared using bottom ash and cement at a ratio of 1:3 for the strength test. The results reveal that the difference in the particle characteristics did not differ much with the process of leaching. The strength of the mortar is reduced with the leaching and washing method compared to unwashed bottom ash in mortar up to 38%. Despite that, the strength of the mortar containing leached bottom ash still complies with the standards. Keywords Bottom ash · Particle size · Leaching · Cement · Compressive strength

1 Introduction Bottom ash from a power plant is a waste product which has been landfilled all this while. This bottom ash has been characterized as hazardous waste which has to be used under certain conditions in Malaysia. Most of the hazardous waste has to be S. Naganathan (B) · B. Mahalingam Department of Civil Engineering, S.S.N. College of Engineering, Old Mahabalipuram Road, Kalavakkam, Chennai 603 110, India e-mail: [email protected] S. Beddu · M. Z. Ajmulkhan · Z. C. Muda · S. N. Sa’don Department of Civil Engineering, Universiti Tenaga Nasional, 43000 Kajang, Malaysia e-mail: [email protected] J. Kanadasan Buildcon Concrete Sdn Bhd (YTL Cement), Kuala Lumpur, Malaysia © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_7

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cleaned before we can use this bottom ash in construction material specifically in cement mortar. Methods have been proposed by researchers around the world to ensure the capability of the bottom ash to be safely used in construction material. This paper focused mainly on composite leaching of thermal power plant bottom ash to ensure its performance on cement mortar. In the future, this could reduce the hazardous waste to be landfilled and indirectly reduce pollution toward the environment.

2 Literature Review Thermal power plant bottom ash is basically one of the waste products which researchers around the world are focusing on. This TPPBA can reduce the usage of natural river sand where there is a certain country like India facing illegal sand mining problems [1]. Hence in Malaysia, we can avoid this problem in the future by taking early steps to reduce the usage of natural river sand meanwhile reducing the hazardous waste to be landfilled [2]. Cement mortar is one the main materials used in construction work as one of the main roles, i.e., plastering and holding brickwork, containing only sand, cement and water. For cement mortar, the strength needed will be much lesser compared to concrete which works as a load transfer mechanism. According to ASTM C1329, there are 3 types of cement mortar which basically differentiate by the compressive strength which is N, S and M type. Overall, the minimum needed strength will be 3.5 MPa. Bottom ash leaching process was done by a few researchers and this where we use HCI, HF and HNO3 will be focused on a few papers. According to [3, 4], the leaching process using HCI, HNO3 and HF has been extremely effective to react and remove some of the elements such as Ca, Mg, sulfates and phosphates. This paper focused mainly on the composite leaching of power plant bottom ash using hydrochloric, hydrofluoric and nitric acid, and the effect on cement mortar compressive strength.

3 Methodology TPPBA leached using a composite leaching method where each acid will consume 50% of the total solution, i.e., Hydrochloric (HCI) + Hydrofluoric (HF) acid, HCI + Nitric(HNO3). The washing process will be in terms of 1:3 proportion which is 1 kg of TPPBA leached with 3L of solution containing 15% acids and 85% of water. After the leaching process for 24 h, the TPPBA will be washed with water for 3 days and let to dry in an oven for 24 h. The cement mortar will be prepared according to 1:3 (1 cement: 3 TPPBA) proportions and cast in 70.7 mm mold. After 24 h, the mold was opened and cured in a curing tank until the testing day.

Composite Leaching of Thermal Power Plant Bottom Ash … Table 1 Physical Characteristic of sand, washed and unwashed bottom ash

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Characteristic

Sand

Washed with acids and water

Unwashed bottom ash

Specific gravity

2.48

1.7–1.8

1.75

Bulk density (kg/m3 )

1.49

0.65–0.67

0.65

Compacted density (kg/m3 )

1.61

0.74

0.72

Water absorption (%)

2.6

4.9–5.1

5.0

3.2–3.5

3.5

Fineness modulus 3.17

3.1 Material In this research, bottom ash from a thermal power plant, Kapar (Selangor), has been used. The cement used was a normal pozzolanic cement (MS EN 1971:2007). Natural river sand was used for control cement mortar which has physical characteristics as mention in Table 1.

3.2 Aggregates Thermal power plant bottom ash (TPPBA) leached and washed with different acids has been used as a fine aggregate for this research. The physical properties of the TPPBA are tabulated in Table 1. TPPBA washed with different types of acid combinations gives almost the same readings. This TPPBA is washed using a combination of acids for 1 day and then washed with water for 3 days.

3.3 Mix Design Three mixture proportions were made which using TPPBA washed with two different of composite leaching, unwashed TPPBA and one control cement mortar containing natural river sand. TPPBA is washed by mixing 2 different acids for 24 h and washed with normal water for 3 days to remove the acidic element on top of TPPBA. The water bind ratio was kept in between 0.6 and 0.7 as the TPPBA water absorption level is much higher than the natural river sand. The flow table value was controlled up to 110 ± 5 cm. The mix proportions for cement mortar containing sand and bottom ash are given in Table 2.

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Table 2 Mix proportions of concrete mortar Mixture no.

M1

M2

M3

M4

Cement

1

1

1

1

Bottom ash

0

3 HCI + HF

3 HCI + HNO3

3 unwashed

Water

0.6

0.7

0.7

0.7

Sand

3

0

0

0

4 Result and Discussion In this study, the result and discussion were conducted according to BS EN 101511:1999 in Universiti Tenaga Nasional Civil Laboratory. Universal testing machine (UTM) was used for the compressive strength test. The test involved centering the sample in the testing machine. The force applied was at the constant rate to ensure the compression force on the sample applied exactly follows the standards BS EN 1015-11. The compressive test of the cement mortar with 4 types was tested and then was compared. Figure 1 shows the result of the compression strength test on M1, M2, M3 and M4 at the age of 14 days. The compression strength of bottom ash washed with acids is lower than the control mortar up to 78% at the age of 14 days. At the same time, the unwashed bottom ash shows a higher compression strength compared to that of the washed one. But still, mortar which contains bottom ash washed using HCI + HF shows

Fig. 1 Compression result at the age of 14 days

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higher compression test values compared to the other mortar which contains bottom ash washed with HCI + HNO3. This will be supported by [5] where the author finds the massive change in the structure of the bottom ash where it also reduces the carbon contained in it. All the cement mortar cubes are still under a sufficient amount of strength when compared to the standards which is ASTM C1329. This washed and unwashed bottom ash gives a reading where it should go through further research to make sure it is safe to be used as a construction material.

5 Conclusion Basically, the compression test shows the mortar containing natural river sand is much higher compared to the cement mortar containing washed and unwashed bottom ash. Anyhow, the unwashed bottom ash shows an increase in strength compared to washed bottom ash with acid, whereas the washed bottom ash using HCI + HF shows higher compression strength compared to bottom ash washed using HCI + HNO3. It’s too early to make the conclusion as the data and the effectiveness of the washing process could change with further research as for this research, only day 14 is considered. It is important to consider the data of tensile strength, compressive strength, durability and water absorption rate at the later ages so, a better picture of the influence of washing and leaching can be observed and is applicable in construction. Acknowledgments Authors wish to acknowledge the Civil Engineering Department of Universiti Tenaga Nasional, Malaysia, for facilitating the research. Also, acknowledgements are due to Universiti Tenaga Nasional, Malaysia, for funding this work vide UNITEN BOLD research grant No. 10289176/B/9/2017/6.

References 1. Saviour MN (2012) Environmental impact of soil and sand mining: a review. Int J Sci Environ Technol 1:125–134 2. Naganathan S, Razak HA, Hamid SNA (2012) Properties of controlled low-strength material made using industrial waste incineration bottom ash and quarry dust. Mater Des 33:56–63 3. Steel KM, Patrick JW (2003) The production of ultra-clean coal by sequential leaching with HF followed by HNO3 . Fuel 82:1917–1920 4. Steel KM, Besida J, O‫׳‬Donnell TA, Wood DG (2001) Production of ultra-clean coal. Part-I— dissolution behavior of mineral matter in black coal toward hydrochloric and hydrofluoric acid. Fuel Process Technol 70:171–192 5. Behera SK, Meena H, Chakraborty S, Meikap BC (2018) Application of response surface methodology (RSM) for optimization of leaching parameters for ash reduction from low-grade coal. Int J Mining Sci Technol

Enhancing the Performance of Bottom Ash Using Acid Leaching Method Sivakumar Naganathan, Salmia Beddu, Muhammad Zulfiqar Ajmulkhan, Jegatheish Kanadasan, Zakaria Che Muda, Siti Nabihah Sa’don, and B. Mahalingam

Abstract The thermal power plant bottom ash is normally landfilled which causes pollution and is not sustainable. Hence, bottom ash needs to be recycled. However, the presence of carbon on the bottom ash poses a challenge to the its recycling. This paper reports a research on the leaching process of bottom ash and the effect on the physical characteristics and compressive strength of the mortar containing bottom ash as sand replacement. The bottom ash was subjected to leaching with Hydrochloric, Citric, Nitric, Sulfuric and Hydrofluoric acids. Physical characteristics such as sieve analysis, bulk density, specific gravity and water absorption were considered. Bottom ash, thus prepared, has been used to cast mortar cubes. The strength test was conducted on hardened cubes. Results show that the physical properties such as water absorption, specific gravity and bulk density for different leaching methods did not show any noticeable variation. Sieve analysis shows a reduction in particle size upon leaching. The compressive strength range from 6.43 to 10.04 MPa at 14 days. It is concluded that the use of bottom ash in mortar could reduce its weight while exhibiting the required strength. Keywords Bottom ash · Citric acid · Leaching · Mortar · Characteristic

S. Naganathan (B) · B. Mahalingam Department of Civil Engineering, S.S.N. College of Engineering, Old Mahabalipuram Road, Kalavakkam, Chennai 603 110, India e-mail: [email protected] S. Beddu · M. Z. Ajmulkhan · Z. C. Muda · S. N. Sa’don Department of Civil Engineering, Universiti Tenaga Nasional, 43000 Kajang, Malaysia e-mail: [email protected] J. Kanadasan Buildcon Concrete Sdn Bhd (YTL Cement), Kuala Lumpur, Malaysia © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_8

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1 Introduction Power plant bottom ash which is used as a waste product contains impurities and compounds known as hazardous waste. This hazardous waste was a landfill and could cause pollution in the future. Research on this hazardous waste has been carried out for years to be used in construction material. A lot of methods have been proposed to ensure that BA can be used in construction material. This paper mainly focused on leaching method to ensure the compounds in the BA could be washed away and used in construction material such as mortar. This could reduce the waste product becoming landfill and causing pollution in the future, also reduce the cost in construction.

2 Literature Review Mortar is one of the main materials to be used in construction work for holding brickworks, plastering, etc. containing only cement, sand and water. The strength needed is much lower compared to concrete as it won’t work as a load transfer mechanism. Thermal power plant bottom ash is now widely produced as waste and hazardous material all around the world. This is gaining a lot of attention from the researcher all around the world to utilize this waste material in construction material. This particle bottom ash (BA) is angular, irregular and porous and has a rough surface texture [1]. The chemical compound in BA becomes one of the factors which affects the strength and workability in mortar. The main compound is stated in Table 1 [2] below which shows the high contamination of aluminate oxide. Leaching or washing method proposed by a few researchers gives a lot of different results on the Table 1 Chemical components of bottom ash from Kapar power plant [2]

Chemical components

Materials Cement

Fly ash

Bottom ash

SiO2

21.54

56.58

56.0

Al2 O3

5.32

27.83

26.7 5.80

Fe2 O3

3.6

4.0

K2 O

63.6

–

2.60

CaO

–

4.3

0.80

TiO2

–

–

1.30

SO3

2.1

–

0.10

Na2 O

–

–

0.20

MgO

1.0

1.40

0.60

Loss in ignition

2.48

2.53

4.60

Espacific gravity

3.15

2.323

2.1–2.7

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application of construction material. Leaching or washing using acid is a process used by most of the researchers around the world to reduce heavy metal compound. A few researchers have been using sulfuric acid, hydrochloric acid, citric acid, nitric acid and hydrofluoric acid to remove the hazardous compound and extract certain compound which is beneficial to be used in construction material [3–5].

3 Methodology Bottom ash which is leached using acids, i.e. HCI, Citric, nitric, sulfuric and hydrofluoric acid for 3 days will replace 100% fine aggregate by weight. It is expected that the strength of the mortar will increase and is higher compared to the control mortar which uses 100% natural river sand. The bottom ash was leached using 1:3 (bottom ash: solution) where the solution contained 15% of acid and 85% of water. After the leaching process for 24 h, the bottom ash was then washed using normal water for 3 days to remove the acidic solution. The cube mould measuring 70.7 mm was prepared for the compression test. The specimen was cast, demoulded after 24 h and cured in a curing tank until the testing day.

3.1 Material The bottom ash used for this research, initially, is a waste product from Kapar thermal power plant, Selangor. This bottom ash has low specific gravity and high water absorption level which is 1.75 and 5.0%. The control sample using natural river sand has high specific gravity and low water absorption level which is 2.48 and 2.46%. The cement used was a normal pozzolanic cement (MS EN 197-1:2007).

3.2 Aggregates Bottom ash leached with different acids was used as a fine aggregate for this research. The physical properties of the bottom ash are tabulated in Table 2; bottom ash washed with different types of acids gives almost the same physical result as all the bottom ash are washed in the same method. All the tests have been taken on average so as to reduce the errors.

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Table 2 Physical characteristic of sand, washed and unwashed bottom ash Characteristic

Sand

Washed with acids and water

Unwashed bottom ash

Specific gravity

2.48

1.7–1.8

1.75 0.65

Bulk density

(kg/m3 )

1.49

0.65–0.67

Compacted density (kg/m3 )

1.61

0.74

0.72

Water absorption (%)

2.6

4.9–5.1

5.0

Fineness modulus

3.17

3.2–3.5

3.5

Table 3 Mix proportion of concrete mortar Mixture no.

M1

M2

M3

M4

M5

M6

Cement

1

1

1

1

1

1

Bottom ash

0

3 HCI

3 Sulfuric

3 Nitric

3 Citric

3 Hydrofluoric

Water

0.6

0.7

0.7

0.7

0.7

0.7

Sand

3

0

0

0

0

0

3.3 Mix Design Four mixture proportions were made which by using bottom ash were washed with different acids and methods. Normal mortar was used as a control mix which contains natural river sand. The water bind ratio was kept at 0.6. The flow table value was controlled up to 110 cm plus minus 5 cm. The mix proportion for mortar containing sand and bottom ash are given in Table 3.

4 Result and Discussion The compression test on mortar was conducted in accordance with BS EN 101511:1999 in Universiti Tenaga Nasional Civil Laboratory. The compression test of control mortar which contains sand was compared to 5 other types of mortar which contain bottom ash washed with different types of acids. Universal testing machine (UTM) was used for the compressive strength test with a loading rate of 0.02 N/mm2 . The test involved centering the sample in the testing machine. The force applied was at the constant rate to ensure the compression force on the sample applied exactly follows the standards BS EN 1015-11. Figure 1 shows the result of compression strength test of control mortar and mortar containing bottom ash washed with different types of acids at the age of 14 days. Figure 1 shows the compression strength of bottom ash washed with acids lower than the control mortar up to 74% at the age of 14 days. But still, mortar which contains bottom ash washed using hydrofluoric and sulfuric acid shows higher

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Fig. 1 Compression result at the age of 14 days

compression test values compared to the other mortar which contains bottom ash washed with HCI, citric and nitric acid. This is supported by [6] where the bottom ash washed with hydrofluoric acid could give the same strength as the control mortar when the percentage of mortar substituted by the natural river sand was 40%. Although the samples show an increasing number of compression strength, the control mortar still gives a higher value. This bottom ash washed with acids gives different readings which should go through further research and could increase the compressive strength using different skills of washing and amount of acid for washing process.

5 Conclusion In general, the compression test of mortar containing bottom ash is much lower compared to the control mortar containing natural river sand. Still, there is an increase in strength of mortar containing bottom ash washed with hydrofluoric and sulfuric acids. It’s too early to make the conclusion about the influence of washed bottom ash in a mortar with data on day 14. It is important to provide the data of compressive and tensile strength at the later ages, soa better picture of the influence of the acids on bottom ash indirectly towards the mortar can be observed. Acknowledgments Authors wish to acknowledge the Civil Engineering Department of Universiti Tenaga Nasional, Malaysia, for facilitating the research. Also, acknowledgements are due to

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Universiti Tenaga Nasional, Malaysia, for funding this work vide UNITEN BOLD research grant No. 10289176/B/9/2017/6.

References 1. Singh M, Siddique R (2013) Effect of coal bottom ash as partial replacement of sand on properties of concrete. Resour Conserv Recycl 72:20–32 2. Naganathan Sivakumar, Mohamed Almamon Yousef Omer (2015) Kamal Nasharuddin Mustapha performance of bricks made using fly ash and bottom ash. Constr Build Mater 96:576–580 3. Faizul CP, Abdullah C, Fazlul B (2014) Extraction of silica from palm ash using organic acid leaching treatment. Key Eng Mater 594:329–333 4. Tang J, Steenari BM (2016) Leaching optimization of municipal solid waste incineration ash for resource recovery: a case study of Cu, Zn, Pb and Cd. Waste Manag 48:315–322 5. Yahya AA, Ali N, Mohd Kamal NL, Shahidan S, Beddu S, Nuruddin MF, Shafiq N (2017) MATEC Web of Conf. 103 (Paris: EDP Sciences) reducing heavy metal element from coal bottom ash by using citric acid leaching treatment 01004 6. Hashemi SSG, Mshmud HB, Djobo JNY, Tan CG, Ang BC, Ranjbar N (2018) Microstructural characterization and mechanical properties of bottom ash mortar. J Clean 170:797–804

An Experimental Investigation of Flexural Behaviour of Ferrocement Box Beams Using Micro Fillers K. Ramakrishnan, D. Muthu, and S. Viveka

Abstract The experimental work consists of strength and flexural behaviour of ferrocement box beams for precast purposes. By partially replacing the cement (binder) with various percentages of Silica Fume (SF) (0–25% in steps of 5%), ferrocement box beam is cast to ascertain whether there is an increase or decrease in compressive and tensile strength due to the addition of SF. From the results of compressive and split tensile strengths, it is found that 10% of SF replacement produced higher strength. After obtaining the optimum percentage of micro filler, two ferrocement box beams with SF (10% SF with 90% cement) and two without SF and two ferrocement solid beams are cast and tested for bending, under two-point loading with two layers of wire mesh. The flexural strength of ferrocement box beam without micro filler is compared with ferrocement solid beam. The test results indicated that the flexural strength drop for the beam with voids is less in comparison with a solid beam due to the reduction in self-weight of the hollow box beam. Keywords Ferrocement box beam · Micro filler · Silica fume · Flexural behaviour · Flexural strength

1 Introduction Ferrocement is a mixture of binder (Portland cement) and fine aggregate laid over the layers of mesh. The mesh is of woven or expanded steel mesh with closely spaced small diameter rebar rods. It can be used to construct the box beams, I beams, K. Ramakrishnan (B) · D. Muthu School of Civil Engineering, SASTRA Deemed to be University, Thanjavur, Tamil Nadu, India e-mail: [email protected] D. Muthu e-mail: [email protected] S. Viveka M.Tech. in Structural Engineering, SASTRA Deemed to be University, Thanjavur, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_9

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channel units, wall panels, etc. Al Sulaimani et al. spell out that relatively good strength, resistance to impact, fire, earthquake and corrosion can be achieved using ferrocement in comparison with wood, adobe and stone masonry [1]. Eskandari et al. found that the strength of ferrocement elements, which are lighter in weight, good hardness and longevity in life (durability) are superior among the thin construction elements [2]. Alhajri et al. experimented on the utilization of different materials in the ferrocement slab panel construction to improve the desired characteristics [3]. Arash Behnia et al. investigated the fracture behaviour of multilayer ferrocement composite slabs with normal compact cement mortar, self-compact cement mortar, fly ash and tyre rubber powder with varying steel mesh reinforcement layers. The failure mode of the slab from brittle to ductile was characterized by acoustic emission techniques [4]. Areej et al. evaluated the tensile, compressive and flexural strength of aerated slurry-infiltrated chicken mesh, and the theoretical model was also developed for ascertaining the mechanical behaviour [5]. The experimental work related to determining the flexural strength of ferrocement box beam with binder replacement (with micro filler) was very limited in the literature arena. Hence this experimental work was carried out on a ferrocement box beam with Silica Fume (SF) as binder replacement and the flexural strength of the beam was determined.

1.1 Construction Method The various methods of ferrocementing are (i) Armature system, (ii) Closed mould system, (iii) Integral system and (iv) Open mould system. Al Nuiami et al. cast the box beams with the Integral mould system, using minimum reinforcement as an integral mould is first considered to act as a framework [6]. Mesh layers are fixed on either sides of the mould and plastering is done on both sides. The mould remains permanently in the finished structure as an integral part. Firm connection is achieved between the mould and layers filled with ferrocement. Adequate care should be taken to ensure that the finished product will behave as a whole structural unit. Micro Fillers: Micro fillers are small spherical particles, with diameters in the micrometre range (typically 1–100 μm). Micro fillers are sometimes referred to as microparticles. Silica fume (SF) is also known as micro silica. The by-product obtained during the production of silicon and ferrosilicon is the SF which is an ultrafine powder with spherical particles with an average particle diameter of 150 μm. Katdhuda et al. found that the mechanical properties viz. compressive strength, tensile and flexural strength was found to increase when they experimented light weight concrete with SF as a partial replacement of binder. They experimented binder replacement with different percentage of SF at different water-binder ratios [7]. Kumar stated that the main field of application of micro filler is to act as pozzolanic material for high-performance concrete [8]. Naveen et al. used SF as an additional material with the binder (cement) to improve the mechanical properties, viz., compressive strength, bond strength and

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abrasion resistance [9]. These improvements are attributed to the addition of very fine powder to the cement matrix and in turn pozzolanic reactions induced by the SF with the free calcium hydroxide in the cement paste. The permeability of concrete to chloride ions, to prevent corrosion of reinforcement, is reduced due to the addition of SF.

2 Experimental Investigations Mahmoud et al. conducted an experiment on high-strength mortar to minimize the percentage of cement content in the mortar by adding SF [10]. It comprises the casting of cubes for compressive strength, casting of the cylinder for split tensile strength, and casting and testing of the element under flexural two-point loading test [11]. The materials used, mix proportions and the test methods are described below.

2.1 Materials Used and Its Properties Cement: Sr. No.

Type/Properties

Description of the types/Value of the property

1

Ordinary Portland Cement (OPC)

53 Grade conforming to IS: 12269

2

Specific gravity

3.03

3

Initial setting time in minutes

35

4

Final setting time in minutes

380

Silica Fume (SF) (Micro filler): Mineral admixture, viz., silica fume (SF) was purchased from a Ferro Alloys Industry available locally, conforming to ASTM C1240 [12]. The value of the specific gravity of SF was found to be 2.21. Fine aggregate: Locally available, passing through 4.75 mm river sand was used. The specific gravity of the fine aggregate was found to be 2.63. Galvanized woven square mesh: Galvanized woven square mesh was used as reinforcement in the ferrocement beams. The diameter of the wire is found to be 0.55 mm. The openings in the mesh are 4 mm × 4 mm. The mesh wire is shown in Fig. 1. Water: Normal potable water available locally was used for mixing and curing purposes.

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Fig. 1 View of wire mesh

Superplasticizer: To improve the workability in the mortar, sulphonated naphthalene formaldehyde conforming to ASTM C494 [13] was added.

2.2 Casting The mortar consisted of cement and fine sand mixed in the proportion of 1:2, while the water binder ratio is 0.35 by weight. Twenty four hours after casting, the cubes and cylinders were de-moulded and cured in water for 7, 14 and 28 days, respectively. Kazimturk et al. used SF as a partial replacement of binder with a replacement percentage as 5, 10, 15, 20, 25 [14]. The optimum dosage of superplasticizer to be added in SF mortar conforms to BIS code [15]. The flexural elements are cast after determining the optimum dosage of SF. The six beams are divided into three series, A, B and C. The A indicates the solid beams, B represents the box beams and C represents the box beams with micro fillers.

2.3 Testing 2.3.1

Compressive Strength Test

The compressive strength test determines the behaviour of the material under crushing loads. The mortar cube specimen of size 70.7 mm × 70.7 mm × 70.7 mm is tested in the compression testing machine to determine its compressive strength. All the cube specimens are compressed and their ultimate compressive failure loads are recorded.

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Split Tensile Strength

The determination of tensile strength of concrete is necessary to determine the load at which the concrete members may crack. The split tensile strength on a cylinder was conducted on a computerized compressive testing machine of capacity 300 tonnes. The tensile strength was conducted on 100 mm × 200 mm cylinders.

2.3.3

Two-Point Loading Test

All the beams are tested on Universal Testing Machine. The load is transferred as twopoint symmetrical load through a rigid steel girder. The span of the beam between the supports is 1000 mm, thus the flexural span is 333.33 mm. The crack patterns are drawn directly on the beam and the test is continued until the ultimate load is reached. The size of the beam is 100 mm × 150 × 200 mm.

3 Results and Discussion 3.1 Compressive Strength The isolated effect of Shear Force increases the compressive strength as presented in Table 1. At the age of 28 days, the optimum percentage of binder replacement with SF is 10% by weight of cement, which has a higher compressive strength (56 N/mm2 ).

3.2 Split Tensile Strength The tensile strength of the mortar is presented in Table 2. The strength gain is the same as that of compressive strength. At the age of 28 days, the optimum percentage Table 1 Compressive strength of mortar specimens Sr. No.

Specimen

Compressive strength in N/mm2 7 days

14 days

28 days

1.

CS

31

34

40.3

2.

SF 5%

32

36

46

3.

SF 10%

34.5

41.3

56.6

4.

SF 15%

30.3

35.3

39.9

5.

SF 20%

18

23

36.2

6.

SF 25%

14.6

19.5

20

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Table 2 Tensile strength of mortar specimens Sr. No.

Specimen

Tensile Strength (MPa) 7 days

14 days

28 days

1.

CS

3.2

3.5

3.9

2.

SF 5%

3.7

4.2

4.8

3.

SF 10%

3.9

5

5.7

4.

SF 15%

3.16

3.3

3.8

5.

SF 20%

2.7

2.9

3.2

6.

SF 25%

2.2

2.4

2.7

of binder replacement with SF is 10% by weight of cement, which has a higher split tensile strength (5.7 MPa) than other replacement proportions.

3.3 Flexural Strength The flexural strength of the box beams and solid beams is calculated by using the bending theory method. Theoretical calculations of three types of beams are given below.

3.3.1

Specific Surface Area and Volume Fraction

Volume fraction (V f ) Vf =

N π db2 ∗ 4h



1 1 + Dt Dl

 = 0.038%

V f —Volume fraction = 0.038% N—Wire mesh layer in numbers d b —Bar diameter h—Thickness of Ferrocement composite Dt —Transverse direction (c/c) centre-to-centre distance of wire mesh Dl —Longitudinal direction c/c distance of wire mesh. Specific surface area (S r )  Sr =

0 = 0.276 mm2 bh

S r —Specific surface area  0 —Total surface area of bonded reinforcement per unit length.

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Cracking Load Pcr =

Mcr× 6 l

  Mcr = σcr×{ Ig |y } = σcr∗ Ig /y M cr —Crack moment in kN-m σcr —Cracking stress in MPa I g —Gross moment of inertia of the un-cracked section y—Half of the overall depth of the beam. σcr = 24.52SL + σt σt —Split tensile strength S L —Specific surface of the longitudinal reinforcement.

3.3.3

Crack Width wav = Sβεs

wav —Average crack width S—Mesh opening β—Ratio between the distance of extreme tensile fibre of the outermost steel and the neutral axis εs —Mesh layer extreme tensile layer strain.

3.3.4

Crack Spacing

The average crack spacing in the beam can be estimated using the following expression Alav = (θ/n)(1/SL ) Alav – Average crack spacing θ/n – 1 (for square mesh) S L − Specific surface area in a longitudinal direction 1.

3.3.5

Load Deflection Response

The load-deflection response of ferrocement box beams and ferrocement solid beams are presented in Fig. 2. From Fig. 2, it is clear that, under the same amount of deflection, the B2L (beam B) (hollow box beam without micro filler) has more

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Fig. 2 Load deflection curve

14

Load in kN

12

10

A 2L

8

B 2L

6

C 2L

4 2 0

0.5

1

1.5

2

2.5

3

Deflection in mm amount of load-carrying capacity than other beams. The remaining two beams the beam C2L (beam C) (hollow box beam with micro filler as SF at 10% by weight of cement) and A2L (beam A) (solid beam) have lesser load carrying capacity with lesser deflection. The crack patterns at the ultimate load level are shown in Fig. 3.

Ferrocement solid beam (A2L)

Ferrocement box beam without micro filler (B2L)

Ferrocement box beam with micro fillers (C2L)

Fig. 3 Crack pattern for various beams

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4 Conclusion • The following conclusions could be drawn based on the results of the compressive strength and tensile strength of the mortar and flexural behaviour of beams. • The replacement of cement by silica fume increased the compressive strength and split tensile strength of the mortar at all ages compared to the control mix. There is also a significant gain in strength with the age of concrete as 28 days. These improvements are attributed to the addition of very fine powder to the cement matrix and in turn pozzolanic reactions induced by the SF with the free calcium hydroxide in the cement paste. • The highest value of 28 days compressive strength as 56.6 MPa and tensile strength as 5.7 MPa was obtained at 10% of SF replacement of cement. • Central hollow portion reduced the weight of the beam compared to the solid box beams with two layers of wire mesh. The use of a ferrocement box beam will be economical and the structure has lower self-weight. It is suitable for seismic resistant structures. • The deflection under the same load produced higher value for ferrocement box beams without micro filler and lesser value for ferrocement solid beam. The deflections of solid beams and the ferrocement box beam with micro filler showed lesser deflection compared to the box beam without micro filler. The reason for the lesser deflection of ferrocement box beam with micro filler was due to the densification and compactness achieved by the presence of micro filler (SF) in the cement matrix. This densification enhanced the stiffness of the beam.

5 Limitations The durability aspects are not considered in the present work. Discussion is limited only to the flexural strength of the ferrocement box beam with micro filler. Cost analysis and comparison are not considered in this work. It is a known fact the cost of SF is more. But the use of SF up to 10% replacement of binder for casting hollow box beam, and 25% replacement for mortar cube is not that much expensive as far as this experimental work was concerned.

References 1. A1-Sulaimani GJ, Basunbul IA, Mousselhy EA (1991) Shear behavior of ferrocement box beams. Cement Concrete Comp 31:29–36 2. Eskandari HA, Madadi (2015) Investigation of ferrocement channels using experimental and finite element analysis. Int J Eng Sci Technol 18(4):769–775 3. Alhajri TM, Tahir M, Azimi M, Mirza J, Lawan M, Alenezi K, Ragaee M (2016) Behaviour of pre-cast U-Shaped composite beam integrating cold-formed steel with ferro-cement slab. Thin-Walled sStruct 102:18–29

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4. Behnia Aradh, Ranjbar N, Chai HK, Abdullah AI, Masaeli M (2017) Fracture characterization of multi-layer wire mesh rubberized ferrocement composite slabs by means of acoustic emission. J Clean Prod 157:134–147 5. Almalkawi Areej T, Hong W, Hamadna S, Soroushian P, Darsanasiri AGND, Balchandra A, Al-Charr G (2018) Mechanical properties of aerated cement slurry infiltrated chicken mesh. Constr Build Mater 166:966–973 6. Al-Nuaimi AS, Bhatt (2005) 2D Idealization of hollow reinforced concrete beams subjected to combined torsion, bending and shear. J Eng Res 2(1):53–68 7. Katkhuda H, Hanayneh B, Shatarat N (2009) Influence of silica fume on high strength lightweight concrete. World Acad Sci Eng Technol 34:781–788 8. Kumar A (2005) Ferrocement box sections-viable option for floors and roof of multi-storeyed buildings. Asian J Civil Eng 6(6):569–582 9. Naveen GM, Suresh GS (2012) Experimental study on light weight ferrocement beam under monotonic and repeated flexural loading. Int J Civil Struct Eng 3(2):294–301 10. Abo Mahmoud, El-Wafa KF (2010) Flexural behavior of lightweight ferrocement sandwich composite beam. J Sci Technol 15(1):1–46 11. Desayi P, Reddy V (1991) Strength of lightweight ferrocement in flexure. Cement Concrete Comp 13:13–20 12. ASTM C 1240 Silica fume in cementitious mixer 13. ASTM C 494 Standard specification for chemical admixtures in concrete 14. Turk Kazim, Karatas Mehmet, Gonen Tahir (2013) Effect of fly ash and silica fume on compressive strength, sorptivity and carbonation of SCC. KSCE J Civil Eng 17(1):202–209 15. BIS 5512-1983. Specification for flow table for use in tests of hydraulic cements and pozzolanic materials

An Analytical Framework of Climate Change Impacts on Water Resources: Vulnerability and Integrated Adaptation Strategies K. Shimola and M. Krishnaveni

Abstract Climate change has already started altering water resources and also transforming life on the earth. Water resources are one of the major sectors vulnerable to climate change in a developing country like India. Climate change impact assessment is the main concern for water resource availability and sustainable water use activities like agricultural production. Water resources and agricultural sectors are put into the top priority list for adaptation plans as these sectors are vulnerable to climate change. A detailed framework is necessary to assess the responses of spatial and temporal water availability to a range of baseline and climate change scenarios. Climate change impact assessment can be performed using modelling approaches such as climate change analysis (existing climate trends and jumps), analysis of hydrological extremes, downscaling and hydrological models. The results of vulnerability assessment on water resources can be transferred as information to farmers and government agencies in order to support them in the planning of appropriate sustainable adaptation measures. Farmers’ perception of climatic conditions, environmental conditions and biological systems, and major coping strategies undertaken can be identified by questionnaire surveys. Thus, an analytical framework for integrated adaptation strategies based on the modelling approaches (climate downscaling and hydrological modelling), water resources’ vulnerability assessment, farmers’ perception and coping strategies is attempted in this paper. Keywords Climate change · Downscaling · Hydrological model · Vulnerability · Farmers’ perception · Coping strategies

K. Shimola (B) Malla Reddy Engineering College, Secunderabad, India e-mail: [email protected] M. Krishnaveni Centre for Water Resources, Anna University, Chennai, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_10

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1 Introduction Climate change refers to variations in the mean state of climate or variability of its properties in its rate, range and magnitude that extends for a long period, usually a decade or longer [9]. The remarkable signs of climate change are temperature and sea level rise, change in rainfall pattern which alters water accessibility and transformations in floods and drought events. Attributes of climate change comprise changes in the frequency and intensity of extreme events, spatial, temporal, and duration of climate events. These changes include changes in mean, variance and shape in the probability distributions of climate variables. Climate change can be known by analysing the long-term climate trends, Intra and Inter-annual variability and sporadic fluctuations in climate series. The extent of climate change in a region has more direct consequences on water resources and it can be identified by climate trends or jump. Analysing the rainfall characteristics are considered to be important in dealing with climate variability. As rainfall is one of the major governing factors in crop production, the knowledge of rainfall patterns and its distribution is important for agricultural planning. El-Nino/Southern Oscillation index events bring scarce rainfall to the Indian subcontinent, therefore, there is a need to understand the interrelationship between rainfall and ENSO events. In India, more than 75% of the agricultural area falls under semi-arid regions. The arid and semi-arid regions face serious challenges due to the unavailability of water resources and lack of crop production. Erratic change in rainfall events, inappropriate utilization of groundwater and less replenishment by rainwater harvesting structures are related to climate variability. In the last decade, there was considerable progress in industries, urban construction, migration of farmers from agriculture to industrial works and decrease in cropping area. Better management of water resources and agricultural planning can be made by studies related to climate. Analysing the climate variability and impact of climate change on the river basin hydrology helps to cope with the climate change effects. Understanding farmers’ perception of climatic change is also crucial in developing adaptation strategies. Therefore, a critical study that evaluates the existing climate trends and rainfall anomalies, responses of spatial and temporal water availability to a range of climate change scenarios based on downscaling technique and hydrological modelling is important for each river basin. Water resources’ vulnerability for a river basin can be assessed by a 4-step approach. This paper provides a framework for integrated adaptation strategies based on modelling techniques like detection of trends and jumps, hydrological extreme analysis, climate downscaling, hydrological modelling, water resources’ vulnerability assessment, farmers’ perception and the coping strategies in practice. This paves a way for structuring a framework to implement and promote applicable farm-level adaptation measures to deal with climate change issues.

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2 Climate Change Scenario in India Climatic change over the Asian monsoon region, of which India is a major component, is of global concern particularly with respect to human population explosion [16]. India is already facing climate change effects which embrace water unavailability, temperature rise, droughts, severe storms and flooding, which are associated with ill effects on health and source of revenues also [14]. The results of a study in major cities in India showed an increasing tendency in temperature for both annual and seasonal scales during the last century [7]. All over India, rainfall is trendless, highly erratic in nature and the mean annual temperature follows an increasing trend of 0.4 °C/100 years. The Indian monsoon rainfall shows an interannual variability [11]. Climate change is expected to increase the droughts in semi-arid regions with prime impacts such as reduced water availability, declined agricultural production and reduced hydropower generation. Guhathakurta and Saji [8] studied the changing pattern of rainfall using seasonality indices in district scale over Maharashtra. Climate change brings serious discrepancy of socio-economic social impacts in India. Hence, identification of technologies, processes and implementation of policies to develop sustainability in these sectors to climate change and current climate variability is vital. Kripalani et al. [12] calculated climate change impact on Indian crops, farm-level total net revenue would decrease by 9% reduce with a increase of 2 °C and increase of +7% rainfall whereas, with a increase of +3.5 °C and 15% rainfall, crop revenue will increase up to 25%. Baca et al. [2] have developed a framework for identifying adaptation strategies. They also analysed and captured the vulnerability of the livelihoods of coffee growers in Meso-America at local levels.

3 Climate Change Impacts on Water Resources A small change in climate variables such as temperature and precipitation will bring a large percentage of changes in the runoff as well as an increase in the severity of floods or droughts. Climate change has vital implications for the current water balance and conjointly for future water resources project design and management [19]. Projected future climate will have a considerable effect on hydrological systems which eventually water availability, runoff and river flows [13]. Climate change brings changes in precipitation trends and the regional distribution of water resources. Due to low replenishment, water quality will be deteriorated. It can modify the runoff events, evaporation rates with the change in incoming solar radiation. The reduction in the runoff volume will lead to a decrease in the water resources potential and crop yields consequently. GCM for different emission scenarios in conjunction with the hydrological models is a widely implemented technique for assessing the regional hydrological impacts. Anandhi and Kannan [1] developed a novel tool which can translate a theoretical concept to an operational framework mainly under changes in climate variables and population.

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3.1 Analysis of Trends, Jumps and Hydrological Extremes for Present Scenario A trend or jump in a series can imply changes in either climatic factors or catchment characteristics [17]. The parametric and non-parametric tests can be used for the detection of significant trends in hydro-climatological time series. Parametric tests include t-test and linear regression while non-parametric tests are Mann–Kendall, Spearman’s rho and Mann–Whitney. The Cumulative Sums (CUSUM) techniques can be used to determine the inconsistencies in rainfall records, which might have resulted from climate changes and also to detect the climate jumps. Extreme climate events often result in floods and droughts at global to regional scale. The implications of climate change can be detected using hydrological extreme analysis. Frequency analysis is an extensively used method to estimate the design event.

3.2 Downscaling Climate Variables for Future Scenario General Circulation Models are the most advanced tools available for simulation of the current global climate and future climate scenario projections. GCMs for specified emission scenarios are suitable for global-scale impact assessment studies but it is incapable to do river basin level analysis due to inherent biases and low spatial resolution. There is an expanding requirement for basin-scale high-resolution local information for future climate scenarios. Therefore, downscaling global climate projections and producing fine-scale regional climate information are important in climate modelling. Various researchers have applied different bias corrections and downscaling approaches to link GCM outputs and the hydrological model. Nesting of a high-resolution regional climate model (RCM) within a GCM uses complex algorithms to describe atmospheric processes [3]. Statistical downscaling deals with the identification of empirical relationships between large-scale observations (predictors) and regional-scale climatic systems (predictands). Statistical downscaling is broadly classified into three categories such as weather typing, weather generators and regression methods. Weather typing involves methods such as analog method, Monte Carlo method, fuzzy classification and hybrid approaches, which apply cluster analysis to atmospheric fields. Weather generators involve methods such as Markov chain, spell length methods and storm arrival times. Regression methods involve linear multiple regression, artificial neural networks and canonical correlation analysis.

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3.3 Hydrological Modelling of Climate Change Impacts A hydrological model is necessary to understand the processes of the hydrological cycle and is often used to estimate climate change impacts on the horology of a river basin. Deterministic hydrological models can be classified into three main types: (i) lumped models (no spatial variation), (ii) semi-distributed models (divides the basin into smaller subbasins) and (iii) distributed models (fully spatial variation) [10]. Understanding the processes concerned in the hydrological cycle would ultimately result in addressing the effects of climate change on water resources in addition to developing adaptation measures. The hydrology of the basin can be determined using hydrological models under the projected climate change scenarios (Fig. 1). The baseline conditions of climate and streamflow are established and then they are used to compare the effect on water balance components due to changes in precipitation,

Climate change impact assessment of a river basin

BASELINE SCENARIO 1. 2.

Trend and change point detection Hydrological extreme analysis

FUTURE SCENARIO 1. Statistical Downscaling 2. Dynamic Downscaling (Using Global Circulation Model outputs)

HYDROLOGICAL MODELLING SWAT, HEC-HMS etc;

Calibration/Validation (for baseline period)

Simulation of baseline and climate change scenario

Future climate datasets

Water balance components

HYDROLOGICAL IMPACT ASSESMENT 1.

Comparison between climate change scenario and baseline scenario 2. Spatial mapping using GIS (streamflow, ET, water yield, ground water recharge etc.,)

Fig. 1 Framework for climate change impact assessment of a river basin hydrology

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temperature and some more climate factors. Some hydrological models used for the basin-scale climate change impact assessment are BASINS-CAT, WEPPCAT, VIC MODEL, HEC-HMS, WATBAL, WEAP and SWAT.

3.4 Water Resources’ Vulnerability Assessment Vulnerability is often outlined as the degree at which a system or unit is probably going to expertise damage because of exposure to perturbations or stress [17]. IPCC [9] defines vulnerability assessment as a process of evaluating, quantifying and characterizing the exposure, sensitivity and adaptive capacity of watersheds due to climate change effect. Exposure is sketched out as the measure of climate stress upon a particular unit. It is going to be described either by continuing changes in climate conditions. For example, changes in climate variables like rainfall and temperature. Sensitivity is the biophysical effect of climate change,. for example, changes in crop ET and water yield. Adaptive capacity is the capability of a system to adapt to climate change effects by minimizing the possible damages, for example, water resources system. The IPCC framework is the most commonly used framework for vulnerability mapping [18]. The vulnerability can be quantified by a 4-step approach [15]. In this approach, spatial data layers for vulnerability indicators are used to develop vulnerability indices. Thus, the vulnerability maps can be produced by overlaying the spatial data layers in a GIS environment. Identifying the extent and level of vulnerabilities plays an important role in developing the coping capacities for climate change. Assessment of vulnerability to climate change also helps to facilitate the decision-making process and to select appropriate adaptation strategies.

4 Farmers’ Perception and Coping Strategies Water resources and agriculture are the two major sectors affected by climate change in the context of food security for South Asian countries like India. Adaptation plans mainly focus on increasing the adaptive capacity of the different systems, by changes in processes, practices or structures to reduce climate risks [9]. To understand the impacts of climate change, it is important to assess the farmers’ perception [5]. Farmers are a vulnerable group to climate change [6]. Understanding farmers’ perception of climate change is therefore crucial in developing appropriate adaptation strategies. They have the least ability to adjust to changes in climatic conditions. Climate change also negatively impacts their domestic farms. It is one of the forcing factors for most of the landless, small and marginal farmers to migrate to other work in cities. In the developing countries, researchers are adopting methods like Questionnaire survey and group discussion to understand farmers’ perception with data records from meteorological stations [4]. A better understanding of farmers’ perceptions regarding climate change, coping strategies and their responses to climate

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change will be important to inform policy for future successful adaptation of the agricultural sector.

5 Integrated Adaptation Strategies for Water Resources’ Vulnerability in Agriculture Formulation of integrated adaptation strategies is based on combining the modelling techniques with farmers’ perception. The climate change impact assessment framework mainly consists of statistical analysis of climate, climate downscaling, hydrological modelling and water resources’ vulnerability assessment. Farmers’ perception of climate change, coping strategies by farmers are understood through questionnaire survey. Modelling techniques in climate change analysis includes the detection of climate trends and change points, rainfall variability and downscaling. Hydrological modelling of climate change impact incorporates the simulation of water-balance components under baseline and climate change scenarios. The spatial changes in climate change indicators can be integrated into GIS platform to perform water resources’ vulnerability assessment. Formulation of adaptation strategies also considers the farmers’ perception of climate change and the coping strategies practised by the farmers. By considering the above methods subbasin-wise adaptation strategies can be formulated based on the degree of vulnerability of each subbasin. Overall, these integrated adaptation strategies for water resources’ vulnerability is mainly formulated through this study will enhance the adaptive capacity of agricultural systems (Fig. 2).

6 Conclusions Most of the river basins in India are vulnerable to climate variability and change due to the sensitivity of the water resources and its limited adaptive capacity in agricultural sectors. The magnitude and frequency of extreme events such as droughts are increased with climate change. The framework of climate change impact assessment of a river basin is mainly used to predict the impacts of climatic change on the availability of present and future water resources. An indicator-based water resources’ vulnerability mapping identified the vulnerable subbasins to climate change using GIS. Climate change impact assessment is mainly important for government agencies, meteorological departments and agricultural departments to raise awareness of the changes in climatic conditions by appropriate communication to the farmers through radio and television, extension services and non-governmental organizations. Therefore, the farmers should take necessary actions and implement appropriate sustainable adaptation practices for the projected climate conditions. This analytical framework on climate change impact assessment gives a baseline for

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Exposure Assessment eg: Rainfall Coefficient of Variation (CV) Monsoon onset Monsoon end days Rainy days Seasonality indices Temperature

Sensitivity Assessment eg: Water yield Ground water recharge Evapo Transpiration ranspiration Adaptive capacity Assessment eg: Type of Irrigation Storage structures

Climatic Conditions Modelling Approach (climate downscaling, hydrological modelling)

Water resources vulnerability mapping (Overlay Analysis)

FORMULATION OF INTEGRATED ADAPTATION STRATEGIES

Changes in rainfall Changes in temperature No of rainy days are decreasing Long dry spell Rainfall pattern unpredictable Late onset of monsoon

Farmers’ perception about climate change

Environmental Interactions Water source & availability is decreasing Changes in land use and land cover pattern Changes in cropping pattern & season

Coping strategies in practice

Biological Systems

Changes in flowering & fruiting time New plant species seen Changes in fish species in ponds

Fig. 2 Framework for formulation of integrated adaptation strategies

the development of appropriate technologies to help farmers adapt to changes in climatic conditions. Government should implement proper guidelines and strategies to reinforce the adaptation capability of irrigational systems, for example, growing drought-resistant crops, climate information forecasting and on-hand information to the farmers through the latest technologies. Integrated adaptation strategies to climate change are essential for better managing the impacts of climate change and improving agricultural sector in a river basin. Thus, subbasin-wise integrated adaptation strategies for combating water resources’ vulnerability can be formulated based on modelling techniques, vulnerability assessment, farmers’ perceptions and adaptation strategies. The overall framework of this paper should be incorporated into water resources’ management plans in order to promote sustainable agriculture in this basin. Hence, practices and management techniques to reduce the water resource vulnerability to climate change can be arrived based on the framework are important for coping climate change.

Annexures • ENSO—El-Nino/Southern Oscillation • GCM—General Circulation Models • RCM—Regional climate model

An Analytical Framework of Climate Change Impacts …

• • • • • • • • •

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CUSUM—Cumulative Sums BASINS-CAT—BASINS Climate Assessment Tool WEPPCAT—Water Erosion Prediction Project (WEPP) Model VIC MODEL—Variable Infiltration Capacity (VIC) Model HEC-HMS—Hydrologic Engineering Center Hydrologic Modelling System WATBAL—Water balance model WEAP—Water Evaluation And Planning System SWAT—Soil & Water Assessment Tool IPCC—Intergovernmental Panel on Climate Change

References 1. Anandhi A, Kannan N (2018) Vulnerability assessment of water resources—translating a theoretical concept to an operational framework using systems thinking approach in a changing climate: case study in Ogallala Aquifer. J Hydrol 557:460–474 2. Baca M, Läderach P, Haggar J, Götz S, Oriana O (2014) An integrated framework for assessing vulnerability to climate change and developing adaptation strategies for coffee growing families in Mesoamerica. PLoS ONE 9:e88463 3. Christensen JH, Machenhauer B, Jones RG, Schär C, Ruti PM, Castro M, Visconti G (1997) Validation of present-day regional climate simulations over Europe: LAM simulation with observed boundary conditions. Clim Dyn 13:489–506 4. David S, Thomas G, Thyme C, Osbahr H, Hewitson B (2007) Adaptation to climate change and variability: farmers’ responses to intra-seasonal precipitation trends in South Africa. Clim Change 83:301–322 5. Deresa TT, Hassan RM, Ringler C (2011) Analysis of perception and adaptation to climate change in the Nile basin of Ethiopia. J Agric Sci 149:23–31 6. Dhaka BL, Chayal K, Poonia MK (2010) Analysis of farmers’ perception and adaptation strategies to climate change. Libyan Agric Res Centre J Int 1(6):388–390 7. Dhorde A, Dhorde A, Gadgil AS (2009) Long-term temperature trends at four largest cities of India during the Twentieth Century. J Geophys Union 13(2):85–97 8. Guhathakurta P, Saji E (2013) Detecting changes in rainfall pattern and seasonality index vis-‘a-vis increasing water scarcity in Maharashtra. J Earth Syst Sci 122(3):639–649 9. IPCC (2001) Impacts, Adaptation, and Vulnerability Climate change. Third Assessment Report of the IPCC. Cambridge University Press, UK 10. IPCC (2007) Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA 11. Juraj M (2003) Hydrological model selection for CFCAS project, Assessment of water resource risk and vulnerability to change in climate condition. University of Western Ontario 12. Kripalani R, Kulkarni A, Sabade S, Khandekar M (2003) Indian monsoon variability in a global 360 warming scenario. Nat Hazards 29:189–206 13. Kumar KSK, Parikh J (2001) Indian agriculture and climate change sensitivity. Glob Environ Change 11(2):147–154 14. Meenu R, Rehana S, Mujumdar PP (2013) ‘Assessment of hydrologic impacts of climate change in Tuna-Bhadra river basin India with HEC-HMS and SDSM. Hydrol Process 27:1572–1589 15. NIC, National Intelligence Council (2009) India: the impact of climate change to 2030 geopolitical implications, Conference report

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16. O’Brien K, Leichenko R, Kelkar U, Venema H, Aandahl G, Tompkins H, Javed A, Bhadwal S, Barg S, Nygaard L, West J (2004) Mapping vulnerability to multiple stressors: climate change and globalization in India. Global Environ Change 14:303–313 17. Rupa Kumar K, Krishna Kumar K, Pant GB (1994) Diurnal asymmetry of surface temperature trends over India. Geophys Res Lett 21:677–680 18. Tu M, Hall MJ, Laat PJMD, Wit MJMD (2004) Detection of long-term changes in precipitation and discharge in the Meuse basin. In: Proceedings of ICGRHWE, GIS and remote sensing in hydrology, water resources and environment, IAHS Publications, vol 289, pp 169–177 19. Turner BL, Kasperson RE, Matsone PA, McCarthy JJ, Corellg RW, Christensene L, Eckley N, Kasperson JX, Luers A, Martello ML, Polsky C, Pulsipher A, Schiller A (2003) A framework for vulnerability analysis in sustainability science. Proc Natl Acad Sci 100(14):8074–8079 20. UNDP (2010) Mapping climate change vulnerability and impact scenarios: a guidebook for sub-national planners. UNDP, New York 21. Waggoner PE (1990) Climate change and US water resources. Wiley

Compaction and Permeability Characteristics of Biopolymer-Treated Soil S. Anandha Kumar and Evangelin Ramani Sujatha

Abstract Choice of biodegradable, environment-friendly materials like biopolymers for soil stabilization is a step forward in sustainable development. An attempt was made to study the effect of two different biopolymers namely Xanthan gum and Guar gum on the compaction and permeability characteristics of soil for 0, 3, 7 and 28 days. The tests were conducted in accordance with the IS: 2720 and IS: 4332 specifications. The results of the study showed that the dry density of the treated soil decreased for guar gum, but in the case of xanthan gum increased at 0.25% and then on further addition decreased. The optimum moisture content increased for both guar gum and xanthan gum. The permeability of the treated soil for both biopolymers and at all biopolymer contents showed a marked decrease. On the 28th day, the permeability of the in situ soil decreased from 1.03 × 10−2 cm/s to 7.23 × 10−9 cm/s and 6.41 × 10−8 cm/s at 1.5% addition of xanthan gum and guar gum, respectively. The results show that xanthan gum is more effective than guar gum. This study is limited to a period of 28 days. Keywords Biopolymer · Xanthan gum · Guar gum · Compaction · Permeability

1 Introduction Geotechnical properties of the soil can be improved by several techniques broadly classified as mechanical, chemical and biological methods. Mechanical and chemical stabilization techniques are widely adopted [1–4]. The most common admixtures used in chemical stabilization are lime, cement, chemicals, and flyash [5–7]. Soil stabilization using chemical admixtures has proven to be effective over the years. The addition of these admixtures though have several drawbacks and chief of them are S. Anandha Kumar · E. R. Sujatha (B) School of Civil Engineering, SASTRA Deemed University, Thanjavur, Tamil Nadu, India e-mail: [email protected] S. Anandha Kumar e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_11

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the permanent modification of the soil environment, soil properties, causes soil and ground pollution and results in the increase of carbon emissions at their production stage leading to global warming [1, 8, 9]. The need for environment-friendly and sustainable alternatives has increased of late [1, 5]. Utilization of biopolymers for soil improvement is increasingly investigated as these are natural materials, plant or animal derivatives which do not pollute the soil or alter its environment permanently. Biopolymers are natural polymers and are derived from agricultural by-products or microbial action. They react with water to form hydrogels [3] and on drying attain a rubbery or glassy state which will lead to plugging of pore spaces in the soil medium [3, 10]. This nature of the biopolymer helps in improving the soil properties like compaction characteristics, shear strength, hydraulic conductivity, stress-strain behaviours, etc. [3, 11]. They have the ability to bio-clog the pore spaces in the soil matrix and bio-cement the soil particles [12, 13]. Bio-clogging property is useful in decreasing the hydraulic conductivity of the soils and the bio-cementation in increasing the strength and stability of the weak soil [12, 14–16]. The choice of biopolymers for use as hydraulic and contaminant barriers, clay liners and for stabilization of cuts and deep excavations is very attractive but has been investigated by only very few authors [5, 8, 10, 11, 14, 17]. The literature shows that the hydraulic conductivity of the Korean residual soil decreased on adding biopolymers like β-1,3/1,6-glucan as an engineered additive [14]. It also influences the various index properties of the soil [14, 17]. The engineering properties of montmorillonite and kaolinite clays were improved significantly by adding the xanthan gum during the first 28 days of curing [5, 8, 10, 11, 18]. This study investigates the effect of two polysaccharides—guar gum and xanthan gum—on the permeability of the soil for a period of 28 days.

2 Materials 2.1 Soil The soil collected from the local site in Tiruchirappalli District, Tamil Nadu, was used for the study. It was extracted from a trench cut at a depth of 1.5 m from the ground level. The soil was brown in colour with no characteristic odour. Atterberg’s limits and compaction characteristics of the soil are given below in Table 1. The soil is classified as clayey sand according to Indian Standard Soil Classification System.

Compaction and Permeability Characteristics … Table 1 Properties of the soil

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S. no.

Properties

Value

1

Specific gravity

2.28

2

Liquid limit (%)

38

3

Plasticity index (%)

18.9

4

Flow index (%)

22.9

5

Toughness index

0.83

6

Optimum moisture content (%)

10

7

Maximum dry density (kN/m3 )

19.33

2.2 Biopolymers Xanthan gum (C107 H158 O90 K5 )n is a natural biopolymer [16] and polysaccharide commonly used for various purposes in the food industry [16, 19–21]. It is naturally derived from a bacteria called Xanthomonas campestris through the fermentation process [22–26]. The gum generally consists of D-Glucose, D-Mannose, DGlucuronic acid, Acetal linked pyruvic acid and O-acetyl [23]. Xanthan gum used for this study was purchased from Opera Chemisol India Private Limited, Chennai, India. It is creamy white in colour and in the form of dry powder. Guar gum is a polysaccharide and is extracted from the Cyamopsis tetragonoloba [13, 16, 27–29]. It is also termed as guar and is commonly available in the market. It was also purchased from the Opera Chemisol India Private Limited, Chennai, India. Both the biopolymers are hydrophyllic and form highly viscous solutions on adding water. In this study, both biopolymers were mixed with the soil in percentages of 0.25, 0.5, 0.75, 1, 1.25 and 1.5% by its weight in the dry powder form. The choice of xanthan and guar gum is based on a literature review where authors have successfully used these biopolymers to form hydraulic barriers and modified the nature of collapsible deposits [9, 15, 16, 22] though their effect with ageing is not studied.

3 Methods 3.1 Sample Preparation The soil is oven-dried to remove the field moisture content and then pulverized. Biopolymers were mixed with the soil as a dry powder in the required percentages at a low moisture content of about 2–3% by weight and mixed thoroughly before further addition of water to attain an equilibrium mixture [8, 9, 16]. The soil samples were then packed in air-tight containers for 12 h for saturation at the optimum moisture content before testing. Samples for testing permeability were moulded at their optimum moisture content.

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3.2 Light Compaction Test The light compaction test was conducted in accordance with the procedure stipulated in IS: 2720 and IS: 4332.

3.3 Hydraulic Conductivity Test Hydraulic conductivity was carried out according to the procedure outlined in IS: 2720. It was conducted on samples immediately after 12 h of curing and this is termed as 0 days, and samples cured for 3, 7 and 28 days. All the specimens were saturated using the bottom-up method [9, 16]. The hydraulic conductivity of the natural soil and soil–biopolymer mixtures were determined using the falling head test method [9, 10, 20, 30].

3.4 pH The various percentages of the biopolymer were mixed in 100 ml of distilled water by its weight and were stirred thoroughly using a magnetic stirrer. The solution was tested using the automatic pH meter. Initially, the pH meter was calibrated with two standard stock solutions of acid and base, respectively (i.e., 7 pH value). Then the probe is inserted into the target solution and the pH value was recorded from the digital pH meter.

3.5 Viscosity The viscosity of the solution was determined using Brookfield DV II plus pro extra viscometer. Viscosity for various percentages of xanthan and guar gum were recorded at 100 rpm at room temperature.

3.6 Microstructure Characteristics Scanning electron microscope (SEM) was used for capturing the microstructural characteristics of the soil, xanthan gum, guar gum and the soil–biopolymer mixtures.

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4 Results and Discussion Biopolymers show tremendous promise to be used as hydraulic barriers, clay liners and contaminant barriers. This study attempts to investigate the choice of the two commonly available biopolymers—guar gum and xanthan gum—for their effectiveness in controlling the permeability of the soil. The results of the study are discussed below.

4.1 pH and Viscosity pH and viscosity of the soil describe its rheological behaviour and suitability for use as a soil stabilizer. The pH of both xanthan and guar gum varies marginally for all contents of the biopolymer investigated. This shows that the addition of a biopolymer does not adversely affect the soil environment. Figure 1 shows the variation of pH with biopolymer content. Viscosity increases significantly with the increase in biopolymer content. The increase in viscosity is observed to be gradual for xanthan gum but guar gum shows a higher rate of increase at higher biopolymer contents (Fig. 1). Their more viscous nature advocates the choice of these biopolymers for controlling permeability in soils. The viscous gel is very effective in pore plugging.

Fig. 1 Effect of biopolymer content on pH and viscosity

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Fig. 2 Compaction characteristics of the soil treated with a Xanthan gum b Guar gum

4.2 Compaction Characteristics Unit weight of a soil reflects the packing of the soil mass in a given volume and is a vital parameter for the design of liner systems. The moulding water content and the corresponding dry unit weight are deciding factors in deciding the choice of the compaction equipment. Compaction characteristics of the soil treated with biopolymers are presented in Fig. 2. Biopolymers, both xanthan and guar gum, are hydrophyllic in nature and hence optimum water content increases with the biopolymer content. The monomers absorb water to form hydration bonds [9, 31]. At higher biopolymer contents, they tend to absorb more water for the formation of the hydration bonds and also the suspension is highly viscous. They occupy the pore space and resist the compactive effort leading to a marginal decrease in the dry unit weight at higher biopolymer content both in the case of xanthan and guar gum. Also, the presence of these viscous suspensions inhibits particle-to-particle interaction in the soil matrix, increasing void space, thus resulting in lower unit weight with the increase in the biopolymer content. This can also be evidenced in the change in void ratio pattern at the maximum dry unit weight (Fig. 2a and b). Figure 2a and b also shows that both in the case of xanthan gum and guar gum the rate of change in dry density is marginal indicating that the biopolymer-treated soil is less sensitive to moisture changes and can be compacted over a wide range of water contents, respectively.

4.3 Permeability The soil selected for the study is clayey sand and has a permeability of 1.023 × 10−3 cm/s which restricts its choice as a barrier material. This soil is selected to understand the impact of biopolymer treatment on pervious soils. The viscous nature of the biopolymer and its tendency to form gel plugs make biopolymer an ideal choice for any geotechnical application that involves control of permeability, like in

Compaction and Permeability Characteristics …

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Biopolymer Content in % 0

0.5

1

0

1.5

1.E-02

XG

1.E-03

GG

1.E-04

Permeability in cm/s

Permeability in cm/s

1.E-03

1.E-05 1.E-06 1.E-07

1.5

XG

GG

1.E-04 1.E-05 1.E-06 1.E-07 1.E-08

1.E-08

1.E-09

1.E-09

a) 0 days

b) 3 days Biopolymer Content in %

Biopolymer Content in % 0

0.5

1

0

1.5

XG

1.E-03

GG

Permeability in cm/s

1.E-03 1.E-04 1.E-05 1.E-06 1.E-07

1.E-08

0.5

1

1.5

1.E-02

1.E-02

Permeability in cm/s

Biopolymer Content in % 0.5 1

1.E-02

XG

GG

1.E-04 1.E-05 1.E-06

1.E-07 1.E-08

1.E-09

1.E-09

c) 7 days

d) 28 days

Fig. 3 Effect of type of biopolymer, content and ageing on permeability

the case of liners, hydraulic and contaminant barriers, stabilizing excavations, etc. Effect of type of biopolymer, biopolymer content and ageing affect the reduction in the permeability which is shown in Fig. 3.

4.4 Effect of Type of Biopolymer on Permeability Both xanthan and guar gum effectively reduce the permeability of the soil. Results of the study show that xanthan gum shows better reduction capacity than guar gum (Fig. 3). For example, at 0.5% xanthan gum-treated soils are 85.25% less permeable than guar gum-treated soil, and for 1.5% a decrease of 76.38% is observed after 7 days of curing, respectively. Xanthan gum is anionic in nature and this causes higher surface adsorption resulting in the interaction between the soil particles and the xanthan particles. This enhanced interaction within the soil matrix leads to a greater number of hydration bonds/cross-link elements to be formed, clogging the pore spaces and leading to a significant decrease in permeability. But guar gum is non-ionic in nature and hence performs slightly poorer than xanthan gum with the same biopolymer contents. Similar results are reported by various authors like [5, 9, 32].

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Fig. 4 Formation of gel plug and hydration bonds after 7 days of curing

4.5 Effect of Biopolymer Content on Permeability Permeability shows a significant decrease with the addition of biopolymers (Fig. 3). It holds true in the case of both xanthan and guar gum. A reduction of 67.23% and 79.53% is observed between 0.5% and 1.5% addition of xanthan and guar gum addition, respectively, after 7 days of curing. At higher biopolymer contents, rate of cross-linkage elements formed in the soil matrix that fills the voids in the soil matrix is higher. This effectively obstructs the movement of water through the treated soil medium which results in the reduction of permeability. Figure 4 shows the micrographs of the biopolymer-treated soil matrix. It can be observed that at higher biopolymer contents, thicker hydration threads and gel plugs are formed. The microscopic images of the cross-links and gel plug formed after 7 days of curing presented in Fig. 4 supplements the better performance of xanthan gum. Thicker hydration bonds, better coating of biopolymer over the soil particles and thicker gel plugs are seen for xanthan gum (Fig. 4a) than for guar gum (Fig. 4b).

4.6 Effect of Ageing on Permeability Degradation is a concern with any natural material. Though xanthan and guar gum are thermostable in nature [33], it is prone to degradation by bacterial or aerobic microorganism action. Also, the study on the ageing of biopolymers will help in understanding the time taken for void plugging and the formation of hydration bonds.

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Results show that in the early days of curing, a definite pattern of decrease in permeability with an increase in biopolymer is not clearly evident, particularly in the case of guar gum (Fig. 3a, b, c and d). Xanthan gum though exhibits a reduction in permeability with an increase in biopolymer content at all days of curing investigated (Fig. 3a, b, c and d). This slightly indefinite trend in the early days of curing can be attributed to the rate of formation of hydrogen bonds and cross-link elements and the non-ionic nature of the guar gum. But after 7 days of curing, a definite trend of decrease is seen for both the biopolymers used. It can be observed that with the increase in the days of curing, permeability decreases for all biopolymer contents in case of xanthan gum while guar gum-treated soils at 1.5% addition show a slight increase till 7 days of curing (Fig. 3c), and beyond that permeability decreases with increase in biopolymer content (Fig. 3d). Nearly 84.23% reduction is observed between 0 and 7 days in the case of xanthan gum and 87.29% in the case of guar gum at 1.5% biopolymer addition. Figure 3c shows that with the increase in the number of days of curing the rate of change of permeability for all biopolymer contents investigated is marginal indicating that the bio-clogging process requires a minimum of 3 days to be entirely mobilized though a significant reduction is achieved immediately after treatment with biopolymer. The results show consistency with similar results published [1, 9, 10, 16].

5 Conclusion The study strongly advocates the choice of biopolymers for use as seepage and hydraulic barriers, liners and contaminant barriers. The selected biopolymers xanthan gum and guar gum are stable over a wide range of pH and viscosity. The study on the compaction characteristics shows that the treated soil can be compacted over a wide range of water contents. Type of biopolymer, biopolymer content and days of curing influence the permeability of the treated soil. The study shows that xanthan gum is more effective than guar gum in reducing the permeability. The study is limited to a short duration of 28 days and further investigation on the effect of curing and durability of biopolymer-treated soil can be a useful addition. Acknowledgments This study is supported by the T.R.R. [18] scheme of the SASTRA Deemed University. The authors sincerely acknowledge the financial support from the University. The authors would also like to thank Aatchaya S, Sivasaran S and Keerthi P for their assistance in the experimental investigation.

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25. Chang I, Im J, Cho G (2016) Introduction of microbial biopolymers in soil treatment for future environmentally-friendly and sustainable geotechnical engineering 26. Chang I, Cho G (2014) Biopolymer-treated residual soil. Geomech Eng 7(6):633–647 27. Gresta F et al (2014) Economic and environmental sustainability analysis of guar (Cyamopsis tetragonoloba L.) farming process in a Mediterranean area: two case studies. Ital J Agron 9(565):20–24 28. Chudzikowski RJ (1971) Guar gum and its applications. J Soc Cosmet Chem 22:42–60 29. Khachatoorian R, Petrisor IG, Kwan CC, Yen TF (2003) Biopolymer plugging effect: laboratory-pressurized pumping flow studies. J Pet Sci Eng 38:13–21 30. Shirazi SM, Kazama H, Salman FA, Othman F, Akib S (2010) Permeability and swelling characteristics of bentonite. 5(11):1647–1659 31. Chen R, Lee I, Zhang L, Asce M Biopolymer stabilization of mine tailings for dust control. 141(2):1–10 32. Im J, Tran ATP, Chang I, Cho G (2017) Dynamic properties of gel-type biopolymer-treated sands evaluated by Resonant-Column (RC) Tests. Geomech Eng 12(5):815–830 33. Chang I, Im J, Kharis A, Cho G (2015) Effects of Xanthan gum biopolymer on soil strengthening Effects of Xanthan gum biopolymer on soil strengthening. Constr Build Mater 74(1):65–72

Inflow Forecasting of Bhavanisagar Reservoir Using Artificial Neural Network (ANN): A Case Study S. Suriya, K. Saran, L. Chris Anto, C. Anbalagan, and K. R. Vinodh

Abstract Hydrologic forecasting of inflows into a reservoir plays an important role in efficient reservoir management and control. Efficient reservoir operation and management rely on the proper forecast of the inflow into the reservoir and it leads to enhanced reservoir yields and better flood protection. But, most of the hydrological parameters are subjected to uncertainty. Hence, an appropriate forecasting method, a feedforward Artificial Neural Network (ANN) was used in this study to obtain reliable information of inflow into a reservoir. The ANN models were trained and simulated using MATLAB with raw and transformed data. Synthetic data and stochastic models are generated to obviate a lack of data and they are utilized to forecast inflow. A total of 24 years (1989–2013) of historical data in the form of average monthly inflow to Bhavanisagar reservoir was used to train, test and validate the model. Then, the results are compared with the observed values of the reservoir. Further, it was found that the Mean Square Error (MSE) obtained is within the range. Hence, this model is used to simulate the inflow for the period 2049–2064 (as per IPCC AR4 report). From the predicted values, appropriate storage and discharge from the reservoir can be decided to prevent the extreme crisis in the near future. Keywords Inflow forecasting · Bhavanisagar reservoir · ANN · Feedforward algorithm · MATLAB S. Suriya (B) · K. Saran · L. Chris Anto · C. Anbalagan · K. R. Vinodh Jerusalem College of Engineering, Chennai, India e-mail: [email protected] K. Saran e-mail: [email protected] L. Chris Anto e-mail: [email protected] C. Anbalagan e-mail: [email protected] K. R. Vinodh e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_12

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1 Introduction The relationship between available water resources and their needs varies for countries exposed to diverse climatic conditions. This irregularity can be conquered by constructing water reservoirs and practising effective operation. Effective reservoir operation has become a major focus for water resource management in recent decades. In reservoir operation, an optimal solution must be obtained to release water by maintaining maximum storage within the reservoir with no or minimal flood damage. This problem can be addressed by getting appropriate inflow data of a reservoir. Historical records of inflow to the reservoir are not available in many cases and even if data persists, existing records are too short to give any statistically significant meaning. In such situations, the lack of data is obviated by generating synthetic data, and stochastic models can be utilized in forecasting to protect the hydrological safety of the structure as well as life and property of the downstream population. The World Meteorological Organization (WMO) defines inflow forecasting as “the prediction of stage, discharge, time of occurrence and duration of inflow— especially at peak discharge at a specified point on a stream—resulting from precipitation and for snow melt” [18]. Inflow forecasting of a reservoir is a complex process due to spatial and temporal variability of topographical, meteorological, hydrological and geographical factors that prevails in the reservoir catchment. Therefore, Artificial Neural Networks (ANN), Genetic Algorithms (GA) and fuzzy theory are adopted to solve complex issues related to hydrological and water resources systems. Artificial Neural Networks (ANNs) are adaptive in nature and having non-linear modelling capabilities, and are used in various inflow forecasting models. It establishes a connection between input–output pairs for the system to be modelled. ANN architecture to solve an issue can be broadly classified into three steps: designing the architecture, training and testing the network [8]. Many researchers have applied Artificial Neural Networks (ANNs) to model different hydrological processes. They have applied ANN technique as an alternative modelling tool for various hydrologic problems such as streamflow forecasting, groundwater modelling, precipitation forecasting, rainfall–runoff modelling, flood forecasting and reservoir operations [2, 5, 6, 12–17]. Thus, ANN methods can be employed in simulating the non-linear dynamics of hydrological processes rather than traditional physical-based models or classical regression techniques. ANNbased approach does not require any precise details of the physical parameters, it rather determines the system patterns based on the relationships between inputs and outputs mapped in the training process [13]. In ANN, it is difficult to decide the optimal number of nodes in the hidden layer. For this reason, the final structure is determined by starting the process with a minimal number of nodes, and the network is trained until a minimum mean square error is attained. Then the nodes are gradually increased in the hidden layer until an optimal number is obtained. The entire procedure of optimizing the connection weights is known as ‘training’ or ‘learning’ [7].

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Supervised or Unsupervised training mechanism can be used to determine the weight matrix of the ANN model. A supervised training mechanism is also called as backpropagation training algorithm which requires an external instructor to guide the entire training process. This backpropagation training algorithm aims in minimizing the error at the output layer and hence it is adopted in many engineering applications. Unsupervised training method is otherwise called as self-organizing neural network. It divides the input–output space into the required number of classes and with the help of supervised training methods, a separate feedforward Multi-Layer Perceptron (MLP) models are developed. ANNs are treated as a black box model since the dynamics of the problem are not considered [10]. The neural networks are categorized based on the number of layers, direction of information flow and non-linear equations. These equations are utilized to fetch outputs from the nodes and also to find the weights between nodes of different layers. The neurons can be linked in two ways: (i) Feedforward networks (neurons are arranged in multiple layers and information flows from input to output layer); (ii) Recurrent networks (neurons are arranged in one or more layers and the feedback is initiated between neurons in the same layer or to neurons in preceding layers). The most commonly used neural network is the three-layered feedforward network capable of handling different problems [9]. Artificial Neural Networks (ANN) modelling is a flexible tool which has the capability to mathematically map the input and output variables of non-linear systems. It can also be used to control, classify and predict the variables. They are capable of solving complicated problems which do not have a tractable solution by adopting a neuron-computing approach [1]. The present study attempts to arrive at an explicit inflow forecast of the Bhavanisagar reservoir using Artificial Neural Networks (ANN).

2 Study Area Description The Bhavani River that flows along Coimbatore and Erode districts is a source for drinking, agriculture and industry. Due to population explosion, urbanization in the command area increases domestic and industrial water demand, hence, the basin is stressed. As a consequence, there exists a huge demand–supply gap in agriculture and domestic sectors. Hence, it is necessary to find the best solution to pile up these fissures. Lower Bhavani basin irrigation system is selected for the present study. The Bhavani basin is located between 10°55 N and 11°45 N latitude and 75°30 E and 77°40 E longitude. The area comprises hilly regions and plain terrain with an altitude range between 215 and 1487 m above Mean Sea Level (MSL). The entire study area is situated in Tamil Nadu state which spreads over the Erode District. The catchment area of the study area is found to be 4200 km2 . The average annual rainfall of the basin is found to be 618 mm. The index map of the study area is depicted in Fig. 1.

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Fig. 1 Index map of study area [11]

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3 Materials and Methods 3.1 ANN Architecture ANN architecture is multilayered wherein a layer is a collection of parallel processing units (or nodes). A three-layered network (input layer (I), a hidden layer (H) and an output layer (O)) shown in Fig. 2 is implemented in this study. Many experimental results confirmed that one hidden layer is enough for inflow forecasting problems [19]. The hidden-layer node allows the network to find and capture the relevant pattern(s). It performs complex non-linear mapping between input and output variables. The input layer of nodes relays external inputs to the

Fig. 2 Structure of ANN network

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neurons in the hidden layer. The input nodes correlate with the input variables. The final output of the network is provided by the hidden layer outputs. A small network (i.e., with very few hidden nodes) will face difficulty in learning the data, whereas a complex network will overfit the training samples and it leads to poor generalization capability [3]. Finding a parsimonious model for accurate prediction is particularly critical since there are no formal methods for determining the appropriate number of hidden nodes prior to training. Therefore, the trial-and-error method is adopted for network design. Figure 3 illustrates the methodology flow chart.

Fig. 3 Methodology flow chart

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3.2 Data Used According to the Intergovernmental Panel on Climate Change (IPCC), increasing average global temperatures lead to drastic precipitation changes. Variation in precipitation leads to changes in runoff, impacting water supply management regimes. Water resource managers who experience an increase in precipitation may need to make infrastructure investments to mitigate increased risk of flooding and higher reservoir levels. Apart from temperature and precipitation, wind speed, relative humidity and solar radiation also play a major role in climate change. Therefore, the climatic data such as temperature, precipitation, wind speed, relative humidity and solar radiation of Bhavani basin and monthly inflow of the reservoir are utilized for inflow forecasting. The available data are split into three parts: • Training sets (to determine network weights). • Validation sets (to estimate network performance). • Prediction set (to estimate future expected performance). Time-series data of reservoir’s average monthly inflow is used to train and validate the ANN model. Processed inflow time series from 1989 to 2013 is divided into two sets: training and validation sets. Each training dataset is subdivided into two parts: training dataset (to compute the gradient and to update the network weights and biases) and checking dataset (to compute the model performance).

3.3 Features of ANN Some of the salient features considered for development of the ANN-based model for reservoir operation are as follows: • type of ANN like feedforward, neuro-fuzzy, etc., • input information like inflow, storage, demand, precipitation, etc., • output information like multiple output networks, storage variation, water releases and • inflow condition like previous, average, expected and forecasted values.

3.4 ANN Using MATLAB Software Neural Network Toolbox in MATLAB provides functions to model complex nonlinear systems that cannot be modelled with a closed-form equation. This toolbox supports both supervised learning with feedforward and backpropagation algorithm, radial basis and dynamic networks, and unsupervised learning with self-organizing maps and competitive layers. It allows user to design, train, visualize and simulate

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neural networks. It is also used for various applications such as data fitting, pattern recognition, clustering, time-series prediction, and dynamic system modelling and control. A feedforward network is a one-way flow from input to output layers and is used for prediction, pattern recognition and non-linear function fitting. MATLAB toolbox also supports a variety of training algorithms (gradient descent methods, conjugate gradient methods, the Levenberg–Marquardt algorithm (LM) and the resilient backpropagation algorithm (Rprop)). The toolbox’s modular framework helps the user to develop custom training algorithms which in turn can be integrated with built-in algorithms. These training algorithms can be accessed from the command line or via apps which show the diagram of the network to be trained and it provides network performance plots and status information to help the user to monitor the training process [4]. Custom network architectures using feedforward backpropagation algorithm are developed using Neural Network Toolbox in MATLAB in order to predict the inflow of a reservoir in the lower Bhavani basin. Input data such as rainfall, relative humidity, solar radiation, wind speed, maximum temperature and minimum temperature for 24 years (1989–2013) are stored in excel format and are imported into the workspace in MATLAB. Then a new network is created using the given input target. Then, the network properties like network type (feedforward neural network with backpropagation algorithm), training function and adaption learning function, and the number of layers and nodes are chosen. The function fitting neural network can be viewed with six input nodes, 10 hidden neurons and an output layer as shown in Fig. 4. The Levenberg–Marquardt backpropagation training (LMBP) is used to train a feedforward neural network. The Mean Squared Error (MSE) function is reduced during training. The backpropagation algorithm used in layered feedforward ANNs arranges artificial neurons in multiple layers, sends forward signals and propagates the errors backwards. The network receives inputs within the input layer neurons. The output of the network is given by the output layer neurons. There could be one or many intermediate hidden layers. For each of the input nodes, a random weightage is assumed based on the corresponding output. Then the weight ages are modified during calibration for a more accurate prediction of inflow. Since there are 10 hidden

Fig. 4 Function fitting neural network diagram for inflow forecasting of Bhavanisagar reservoir

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Fig. 5 Monthly reservoir inflow data

neurons, 10 sets of weightages are assumed. Monthly reservoir inflow data during the period 1989–2013 used for training and validation is shown in Fig. 5. In training networks, the data is divided into three subsets. The first subset is the training set which is used to compute gradient and update network weights and biases. The second subset, the validation subset, is monitored during the training process, and the validation error decreases during the initial phase of training, as does the training set error. The third subset is the testing set. The performance of the network is measured in terms of three parameters such as regression coefficient, error histogram and mean square error. On the whole, model calibration, testing and validation are performed using the observed three-hour concurrent rainfall and runoff for three peak storm events that happened during the monsoon period in the study area.

4 Results and Discussions With the help of hydrological parameters and the future inflow obtained using the AR4 report of IPCC are utilized to predict the future inflow of the Bhavanisagar dam. Model training and prediction was done through neural network toolbox in MATLAB because of its flexibility in operation and its user-friendly nature. The connection between the network outputs and the targets can be depicted using regression plots. The solid line in Fig. 6 represents the best fit linear regression line between outputs and targets. The R-value indicates the relationship between the outputs and targets. If R = 1, then there exists a linear relationship between outputs and targets. If R-value is close to zero, then no linear relationship exists between outputs and targets. The training data shows a good fit as depicted in the regression plot. The validation and

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Fig. 6 Regression analysis between output and target

test result also indicates that R = 0.9. Hence the network can be employed to predict future inflow. Error histogram shows error distribution in the network. Figure 7 illustrates the number of instances of the particular value of error occurred during training, validation and testing. After training several times and changing the hidden neurons, the mean square error is obtained as follows: Training = 7.2463 Validation = 20.6529 Testing = 124.6957 Therefore, it is found from the histogram and MSE values and the error values are minimum in training and maximum in testing.

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Fig. 7 Neural network training of error histogram with 20 bins

The simulated input values are imported into the data manager. Then using the simulate option, the future inflow can be obtained and saved in the workspace. AR4 report of IPCC is considered and the model run is done. According to A1B scenario of the AR4 report, the data of the study area for the period 2049–2064 is taken and analysed. The process is similar to the present scenario simulation process. The generated data of the basin based on the AR4 report is incorporated and the inflow of the reservoir is generated. Thus, the future inflow data for the period 2049–2064 are obtained. The values of the inflow of the Bhavanisagar reservoir are trained by the ANN model and the observed value of the reservoir for the same period (1989–2013) is compared with the predicted data to check whether the data simulated fits with the observed value as shown in Fig. 8. Once the training and validation process is complete, the network object can be used to simulate a response to any input.

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Fig. 8 Observed and predicted inflow in ANN

5 Summary and Conclusion The Bhavanisagar reservoir is a major agricultural source in the lower Bhavani basin. Increase in temperature, intensity of rainfall, wind speed, humidity and solar radiation will influence the reservoir’s inflow pattern and hence lead to an imbalance in reservoir storage and release. The reservoir inflow is simulated using ANN and the present scenario is trained for the period 1989–2013. The results are then compared with the observed values of the reservoir. The mean square error value obtained is within a reasonable range. Further, the inflow is simulated for the period 2049–2064 by using the IPCC Assessment report. The inflow values are then compared with the present scenario. The Mean Square Error values obtained during training, validation and testing are 7.246, 20.653 and 124.69. The basin values are generated according to the AR4 report and are incorporated, and the reservoir inflow is simulated. The prediction of reservoir inflow for the future is done using the ANN model and it shows there is a meagre reduction in the average inflow of reservoir for a year. The intensity of the inflow during monsoon periods gets severe as expected. By adopting the simulated values, appropriate measures on reservoir storage and release can be done to prevent extreme crisis in the future.

References 1. Chaves P, Chang FJ (2008) Intelligent reservoir operation system based on evolving artificial neural networks. Adv Water Resour 31:926–936

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2. Choobbasti AJ, Shooshpasha E, Farrokhzad F (2013) 3-D modelling of groundwater table using artificial neural network—case study of Babol. Indian J Geo-Marine Sci 42(7):903–906 3. Dan ED, Aqueen EC, Onukogy IB (2013) An experimental design method for solving constrained optimization problem. Int J Eng Sci 2(6):28–39 4. Demuth H, Beale M (2004) Neural network toolbox: for use with MATLAB. User’s guide, The Mathworks, Version 4, pp 1–846. www.mathworks.com 5. Dounia M, Sabri D, Yassine D (2014) Rainfall–Runoff modeling using artificial neural network. Proc APCBEE 10:251–256 6. Elsafi SS (2014) Artificial Neural Networks (ANNs) for flood forecasting at Dongola station in the River Nile. Alex Eng J 53:665–662 7. Googhari SK, Feng HY, Ghazali AHB, Shui LT (2010) Neural networks for forcasting daily reservoir inflows. Pertanika J Sci Technol 18(1):33–41 8. Govindaraju RS (2000) Artificial neural networks in hydrology I: preliminary concepts by the ASCE task committee on application of artificial neural networks. J Hydrol Eng 115–123 9. Lohani AK, Kumar R, Singh RD (2012) Hydrological time series modelling, A comparison between adaptive neuron-fuzzy, neural network and autoregressive techniques. J Hydrol 442– 443:23–35 10. Maier H, Dandy GC (2000) Neural networks for the prediction and forecasting of water resource variables: a review of modelling issues and applications. Environ Modell Softw 15:101–124 11. Mirudhula K (2014) Impact of lined/unlined canal on groundwater recharge in the lower Bhavani basin. Int J Eng Res Technol 3(9):1327–3129 12. Amnatsan S, Yoshikawa S, Kanae S (2018) Improved forecasting of extreme monthly reservoir inflow using and Analogue—based forecasting method: a case study of the Sirikit Dam in Thailand. Water 10(1614):1–22 13. Sun Y, Wendi D, Kim DE (2016) Technical note: application of artificial neural networks in groundwater table forecasting—a case study in a Singapore swamp forest. Hydrol Earth Syst Sci 20:1405–1412 14. Suryawanshi RK, Gedam SS, Sankhua RN (2012) Inflow forecasting of lakes using Artificial Neural Networks. WIT Trans Ecol Environ 159:143–151 15. Sattari MT, Yurekli K, Pal M (2012) Performance evaluation of artificial neural network approaches in forecasting reservoir inflow. Appl Math Model 36:2649–2657 16. Tiwari MK, Kumar S (2018) Reservoir inflow forecasting using extreme learning machines. In: Singh V, Yadav S, Yadava R (eds) Hydrologic modeling, Water Science and Technology Library, vol 81. Springer, Singapore 17. Valipour M, Banihabib ME, Behbahani SMR (2012) Monthly inflow forecasting using autoregressive artificial neural network. J Appl Sci 12(20):2139–2147 18. WMO-UNESCO-XXIV International Glossary of Terms in Hydrology-WMO (1974)/(385-II edition-+413PP) 19. Zhang G, Patuwo BE, Hu MY (1998) Forecasting with artificial neural networks: the state of the art. Int J Forecast 14:35–62

Mitigation of Energy Consumption Impact by Planning and Formulation of Environmental Management System for Indian Infrastructure Projects C. Akin, V. Vandhana Devi, and R. Samuel Devadoss

Abstract India is a country where enormous natural resources are utilized for large infrastructure and construction projects which leads to environmental impacts. Every year, due to the consumption of enormous natural resources for large infrastructure and construction projects, more energy is consumed which has a negative impact on the environment. Though modern construction techniques and low-cost effective materials were utilized to mitigate Energy usage, the volume of impact reduction is not efficient. The present paper focuses on the planning and formulation of Environmental Management System (EMS) to reduce the impact of energy consumption patterns in large infrastructure and construction projects. The planning of EMS is done based on the Energy usage in mega level construction projects under the environmental impact checklist provided by the Ministry of Environment, and Forest and Climate Change (MoEF&CC), Government of India, and the Formulation is done through Material Flow Cost Accounting (MFCA) techniques that implement EMS to reduce the impact due to energy conservation in large infrastructure and construction projects. Using these techniques, the implementation of EMS is needed in order to reduce the impact due to enormous energy consumption in large infrastructure and construction projects. It was concluded that the material loss was reduced from 4 to 1.2% before and after the implementation of MFCA which simultaneously mitigates the energy consumption pattern in large infrastructure projects. Finally, the Planning and Formulation of EMS gives a solution to reduce the impacts caused due to energy consumption in large infrastructure and construction projects. Keywords Energy conservation · Environmental impact · Environmental management system · Infrastructure projects · Mitigation C. Akin (B) · V. Vandhana Devi Department of Civil Engineering, KCG College of Technology, Chennai, India e-mail: [email protected] V. Vandhana Devi e-mail: [email protected] R. Samuel Devadoss Department of Civil Engineering, Hindustan Institute of Technology and Science, Chennai, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_13

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1 Introduction For infrastructure projects, the consumption of natural resources is a common application behind construction activities. The need for energy is mandatory to manufacture construction materials such as cement, steel, bricks, and woodworks. To manufacture 1 kg of cement, it indeed consumes 200 kg of coal [1–3]. 1 kg of coal produces 7 kwhr of electricity, and 1 kwhr electricity charges Rs. 8 [4, 5]. Therefore, the consumption of energy in the manufacturing of construction materials causes a major impact on natural resources. Ministry of Environment, Forest and Climate Change (MoEF&CC) under the Government of India has given guidelines to mitigate the environmental impact due to energy consumption for large infrastructure projects [6, 7]. This present paper focuses on mitigating the impact on energy conservation of infrastructure project by Environment Management System (EMS) technique following the guidelines of MoEF&CC through planning and formulation. Environmental Management System is an ISO 14051 concept of reducing the environmental impact, and it saves energy and cost of a project and increases profit to a company [8–10]. The concept of EMS is Plan, Do, Check, and Act format which is otherwise known as PDCA cycle. And finally, EMS concept leads to reduce, reuse, recycle, and dispose of waste materials as an effluent of product. Here in the infrastructure project and construction industry, the final product will be a residential or commercial building, dam, Bridges, etc., and the wastes are due spillage waste, carriage waste, accidental waste, etc. [6, 7]. The Formulation is done through Material Flow Cost Accounting (MFCA) techniques that implement EMS to reduce the impact due to energy conservation in large infrastructure and construction projects [11, 12].

2 Methodology The method used in the present paper is the planning and formulation of Environmental management system for a construction project as a case study. The planning of EMS is done based on the Energy Conservation provided by the environmental impact checklist of Ministry of Environment, Forest and Climate Change (MoEF&CC) under Government of India, and the Formulation is done through Material Flow Cost Accounting (MFCA) techniques that implement EMS to reduce the impact due to energy conservation in large infrastructure and construction projects.

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3 Case Study 3.1 Step 1—Plan The Building Construction project involves numerous materials for each and every item of work starting from earthwork excavation to finishing of the building. In this chapter, the data of each and every item of work is analyzed and the material requirement, labor component, and conveyance of material are worked out based on the standard data available in Government of Tamil Nadu [12, 13]. For this study, the Tsunami reconstruction project of 100 Nos. of Vulnerable houses at Thandavamoorthykadu Habitation in Thirupoondi East Panchayat of Keelaiyur block in Nagapattinam district implemented by the Rural Development Department, Government of Tamil Nadu is considered, and it was funded by World Bank [13]. This building estimate is taken up for the analysis. The detail of the quantities of each item of work in combination with the data is discussed. The MFCA is done for the Tsunami reconstruction project of one house as a case study. The house has the plinth area of 325 sq ft; it was taken up for the analysis, and the cost of estimate is 3.35 lakhs.

3.2 Step 2—Do The list of quantity centers for the tsunami reconstruction project for a single house is given as follows: • • • • • • • • • • • •

Cement Concrete mix 1:4:8 and 1:5:10 using 40 mm metal. Sand Filling Brickwork in CM 1:6 mix using Country Bricks RCC M20 using 20 mm metal Cement Concrete mix 1:2:4 using 20 mm metal Weathering Course using brick jelly concrete Plastering 1:4 mix to 12 mm thick Granolithic flooring Supply and fabrication of steel Cement Paint and Electrification Pressed tiles Plastering 1:3 10 mm thick and Country wood.

These are the quantity centers in which the cost accounting was done for total input and output of the materials such as cement, sand, steel, tiles, planks, paints, and metals, and material loss is found for each and every quantity center.

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Fig. 1 Total input and output of materials, energy and systems

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3.3 Step 3—Check Figure 1 shows the total input and output of materials, energy, and the systems in which the amount of final product and material loss was founded through a spreadsheet.

3.4 Step 4—Act The waste management process is done by reducing, reusing, recovering, and disposing the materials. In the tsunami reconstruction project, the material loss was treated for reduce 10%, reuse 40%, recover 20%, and dispose for landfills 20%, and the remaining 10% is the material loss.

4 Result and Discussion The total input and output of material, energy, and system gained before implementation and after implementation of MFCA were found through spreadsheet by cost accounting; the amount of material loss was found for each and every quantity center, and the material loss was treated for waste management. The waste management for the material loss was treated based on four concepts. They are reduce, reuse, recover, and finally, dispose for landfills. Therefore, these four concepts of waste management are applied for the material loss obtained in the construction project, and cost accounting was done for waste management. Hence before implementing MFCA, the material loss was 4% due to spillage waste, reworks, and damaged materials during construction without waste management, and after implementing MFCA, the material loss was reduced to 1.2% with waste management. Table 1 shows the difference between before and after the implementation of MFCA in the Tsunami reconstruction project for a single house. From Fig. 1, before implementation data was taken for reference in Table 1 and after implementation data was taken from the waste management process in the tsunami reconstruction project in which the material loss was treated for reuse 40%, recover 20%, reduce 10%, and dispose for landfills 20%, and remaining 10% is the material loss. Figure 2 shows the waste management chart in which the remaining 10% was the material loss after the implementation of MFCA in construction. Finally, the reduction in material loss after the implementation of MFCA leads to a reduction in the energy and system loss which boosts to 2.8% profit in cost and materials from the overall cost of the Tsunami reconstruction project. Therefore, the application of MFCA is used to reduce the environmental impact which leads to a reduction in CO2 emission, and it also increases productivity.

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Table 1 Adoption of MFCA COST

Unit

Material

Energy

System

Total

Rs.

200914

23298

107752

331964

%

96

96

96

96

Material loss

Rs.

9314

489.3

2263

12067

%

4

4

4

4

Total

Rs.

210224

23787

110016

344027

%

100

100

100

100

Rs.

207021

24311

107916

339248

%

98.8

98.8

98.8

98.8

Rs.

4204

475.7

2200

6881

%

1.2

1.2

1.2

1.2

Rs.

211225

24787

110116

346128

%

100

100

100

100

Before MFCA implementation Product

After MFCA implementation Product Material loss Total

Fig. 2 MFCA in construction

100% 80% 60% 40%

Material Loss

20%

Product

0% Before MFCA

Aer MFCA

Table 1 shows the adoption of MFCA before implementation and after implementation in construction. Figure 2 shows the difference between before implementation and after implementation of MFCA in construction. Before the implementation of MFCA in the building construction, the material loss is more, and after the implementation of MFCA, the material loss is less due to waste management.

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5 Conclusion The present paper helps to reduce the environmental impact by mitigating energy conservation for infrastructure projects with a similar case study through the planning and formulation of EMS technique of MFCA. The MFCA is applied in construction, and the cost accounting was done for the building product. The material loss was identified, and it helps in reducing the environmental impact by construction waste management concept through reduce, reuse, recover, and dispose, and also it reduces the footprint of CO2 emission. And simultaneously, it improves the efficiency of productivity of the construction project. Planning and Formulation of EMS helps to reduce the overall cost of the project and increase the profitability. Hence, the Planning and Formulation of EMS gives a solution to reduce more volume of energy conservation impacts due to large infrastructure and construction projects.

References 1. Kytzia S, Faist M, Baccini P (2004) Economically—extended MFA: a material flow approach for a better understanding of food production chain, Applications of Industrial ecology. J Clean Product 2. Schmidt M, Nakajima M (2013) Material flow cost accounting as an approach to improve resource efficiency in Manufacturing companies. MDPI J Open Access Resour 2:358–369 3. Hyrslová J, Vágner M, Palásek J (2011) MFCA-tool for optimization for corporate production processes. Busi Manag Educ 9(1):5–18 4. Viere T, Möllerand A, Prox M (2011) A Material flow cost accounting approach to improve assessment in LCA. Int J Sustain Innov 1(1) 5. Bierer A, Götze U (2012) Energy cost accounting: conventional and flow oriented approaches. J Compet 4(2):128–144 6. ISO/DIS 14051 (2011) Environmental management. Material flow cost accounting, General framework 7. Kokubu K, Campos M, Furukawa Y, Tachikawa H (2008) Material flow cost accounting with ISO 14051. ISO Manag Syst 1:15–18 8. (2006) Manual on norms and standards for environment clearance of large construction projects, New Delhi, India 9. Sundaresan V, Ganapathy Subramanian KS, Ganesan K (2000) Resource management techniques. A.R. Publications, Tamil Nadu, India 10. Christini Gwen, Fetsko Michael, Hendrickson Chris (2000) Environmental management systems and ISO 14001 Certification for construction firms. J Construct Eng Manag 130(3):330–336. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:3(330) 11. Amiri MM, Noubbigh H, Naoui K, Choura N (2000) Environmental management system: environmental impacts and productivity. Int J Bus Manag. https://doi.org/10.5539/ijbm.v10 n11p107 12. Akyurek A, Agdag ON (2017) Evaluation of environmental management system implementation in construction projects. Eur Sci J SPECIAL/edition 13. Tender Document, Reconstruction of 100 nos of vulnerable houses at various habitations of Thirupoondi East Panchayat and Viluthamavadi Panchayat in Nagapattinam District. Package No: TNRD/VH/05/ETRP/12

Nitrate Sequestration and Sorption Capacity in Soil Under Varying Organic Loading Conditions P. Balaganesh, E. Annapoorani, S. Sridevi, M. Vasudevan, S. M. Suneeth Kumar, and N. Natarajan

Abstract Organic nitrogen occurs generally as a part of soil organic matter and has multiple sources and pathways in soil based on the prevailing bio-geo-ecosystems. Since their mobility defines sequestration capacity and adsorption kinetics, it is necessary to understand the fate and transport of nitrogen species in organic amended agricultural soils. The present study investigates the distribution of nitrogen species in a monocultured field in Alathukombai, Erode District, Tamil Nadu. Adsorption and mass transfer parameters were estimated by batch and column experiments by varying the proportions of organic amendments to assess source zone influence. Statistical analysis showed that labile fraction of organic matter has the least influence on nitrogen species sequestration in soil compared to the inert fraction derived from compost amendments. The batch experiments resulted in maximum adsorption capacity of 34% for nitrate-nitrogen onto the sugarcane-monoculture soil. When the soil is mixed with compost, the maximum available total nitrogen (TN) was found to be 86.71 ppm. The leaching trends in the sugarcane field were simulated by a continuous column experiment where the redistribution of organic nitrogen was found to be dependent on the prevailing soil conditions. The results might be quite helpful in identifying the suitable fertigation strategy for monocultured soils. P. Balaganesh (B) · E. Annapoorani · S. Sridevi · M. Vasudevan · S. M. Suneeth Kumar Bannari Amman Institute of Technology, Sathyamangalam 638401, Tamilnadu, India e-mail: [email protected] E. Annapoorani e-mail: [email protected] S. Sridevi e-mail: [email protected] M. Vasudevan e-mail: [email protected] S. M. Suneeth Kumar e-mail: [email protected] N. Natarajan Dr. Mahalingam College of Engineering and Technology, Pollachi 642003, Tamilnadu, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_14

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Keywords Nitrogen sequestration 1 · Sorption capacity 2 · Sewage sludge 3 · Soil organic matter 4 · Compost 5

1 Introduction The physicochemical and biological characteristics of soil play a major role in maintaining the soil organic carbon (SOC) content in the agricultural field. Hence, SOC is considered to be a critical parameter for evaluating soil fertility in terms of soil organic matter (SOM) [1]. The activity of SOM depends on the available nutrients, soil nitrogen, and porosity [2]. In agricultural soils, the crop yield reduces significantly due to the loss of nitrogen and volatile elements through leaching. This nutrient washout process leads to eutrophication, thus increasing the level of nitrates in groundwater as well as the emission of nitrous oxide [3]. So, it is imperial to know the dynamics of nitrogen species within the entire soil strata from the surface to the crop root zone as well as to the groundwater table [4, 5]. Leaching behavior is generally well synchronized by water movement and hence, it depends on the structure and texture of the soil. Due to preferential flow and deep percolation, the soil nutrients can get lost with the water lost from the root zone of the crop easily. The porosity and pore-size distribution of the soil can be modified by tillage operations. In other words, water movement and associated nutrient transport depend upon the degree of tillage [6, 7]. Adsorption studies are preferred for evaluating the mass transfer potential of SOC under various field conditions. Based on the adsorption results, scaling-up and practical implementation can be achieved with a simple design and less maintenance cost [8]. Batch and column experiments are the best techniques to predict the adsorption potential and infiltration rate. The primary motivation behind batch and column tests is to explore the transport and attenuation of a specific compound inside a particular sediment or substrate. Column tests are quick, adaptable, and simple to oversee; their boundary conditions can be controlled easily and they are economical with broad field tests. They can give better evaluations of relevant transport parameters by tracking the contaminant/nutrient movement. On the other hand, the acquired outcomes may quite often be restricted to the size of the test and are not specifically transferrable to handle scales as such since a large number of parameters are elite to the column setup [9]. The present study aims to characterize the transport of nitrate through soil columns uniformly packed with sugarcane monocultured (SMC) field soil and to investigate the rate of attenuation under varying conditions of SOM.

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2 Materials and Methods 2.1 Compost Preparation Biologically active sludge was collected from sewage treatment plant (STP) of Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India. After primary dewatering, STP sludge was mixed with various organic wastes in different ratios. These combined wastes were fed into three different aerobic bins that were placed near the STP. To get a good decomposition rate, the contents were turned frequently, and the vital parameters such as moisture and temperature were maintained in optimum conditions. By monitoring the physicochemical and biological parameters, the maturity of the compost was assessed over a period of 40 days.

2.2 Batch Experiment The batch experiment was performed using 250 ml Erlenmeyer flask in which five grams of composite soil samples gathered from a close-by SMC field along with 50 ml nitrate solution were taken. Initial concentrations of 25, 50, 75, and 100 ppm of nitrate solution were prepared using potassium nitrate salt. The 250 ml Erlenmeyer flask was kept in an orbital shaker at 80 rpm for thorough mixing. The time of contact varied from 5 to 20 min. Then, the adsorbed samples were filtered using the Whatman filter paper, and the supernatant was tested for nitrate-nitrogen. Further similar batch experiments were carried out with (i) SMC soil, (ii) compost, and (iii) SMC soil + compost mixture each of 5 g taken in respective labeled 250 ml Erlenmeyer flask and mixed with 50 ml nitrate solution of 50 ppm concentration. After extraction and filtration, the supernatant is analyzed for pH, electrical conductivity (EC), total nitrogen (TN), and total organic carbon (TOC).

2.3 Column Experiment The laboratory column setup comprises of a 30 cm long acrylic segment (5 cm dia.) with permeable lumps and lid covered at the ends. The artificial nutrient solution (nitrate solution) from the canister was passed to the highest point of the section through silicon tubes (6 mm dia.) connected through a peristaltic pump (Fig. 1). The section was initially filled up gradually with local SMC soil gathered from a close-by sugarcane field at Alathukombai, Tamil Nadu. The soil was insignificantly exasperated while gathering and washed with de-ionized water for a few runs to balance out the dispersive conduct of dissolved solids. The flow rate of the siphon was balanced at 12 ml/h in order to resemble a predominant infiltration rate in SMC soil [10]. The

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Fig. 1 Sampling from laboratory column setup

vertically aligned soil segment speaks the underlying invasion and leaching characteristics of supplements in the particular stream course. After the initial stabilization of the column, the stock nitrate solution (50 pmm) was pumped to the top of the column. Samples were collected every 5 min and taken for physicochemical analysis. In another trial, extensive soil washing was performed in order to simulate the rainfall and runoff effects in the field. This resembles the leaching of nutrients during infiltration and serves as a measure of moisture withholding capacity of field SMC soil.

2.4 Chemical Analysis Soil samples were extracted with 50 ml of 2 M potassium chloride [9, 10] solution for 2 h using an orbital shaker (LabTech, LTRS 750 W, Chennai, India). After settling, the

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supernatant was filtered using syringe filters (20 µm) and directly used for measuring pH (Elico LI120, Chennai, India) and EC (ElicoCM 180, Chennai, India). The presence of TOC and TN was analyzed using TOC Analyzer (Shimadzu, TOC-L, TNM-L, Malaysia) with 680 °C combustion (catalytic oxidation) and non-dispersive infrared detection (NDIR) method. It is a preferred method for estimating organic carbon in environmental samples over the conventional Walkley–Black method and losson-ignition (LOI) method for its comprehensive and accurate detection mechanism [11]. The samples were acidified with 25% phosphoric acid and 1 M HCl in order to separate the inorganic components, and TOC and TN values were measured. The aqueous concentration of nitrate-nitrogen (NO3-N) was estimated using UV-Visible spectrophotometer (Systronics PC based 2202, Chennai, India) [12, 13].

3 Results and Discussion 3.1 Adsorption Capacity Four different Initial nitrate concentrations were prepared using potassium nitrate as mentioned in Sect. 2.2 and examined the adsorption capacity of SMC soil. The adsorption efficiency as well as maximum adsorption capacity was evaluated as [14–16] Adsorption efficiency (%) = 100 ∗ (Ci − Ce )/Ci

(1)

qe = (Ci − Ce )V / X

(2)

where C i is initial nitrate concentration (mg/L), C e is equilibrium nitrate concentration (mg/L), qe is solute amount adsorbed per unit mass adsorbent (mg/g), V is the volume of solution (L), and X is the adsorbent weight (g) (Fig. 2). The SMC soil adsorption efficiency percentage varied from 16% to 28% with respect to the initial concentrations of 25–100 ppm of nitrate during the first 5 min of contact time. This reveals that when the concentration of nitrate solution increased, the adsorption efficiency of SMC soil also increased subsequently. The SMC soil could adsorb to a maximum of 31% when the adsorption time increased to 10 min. Further, an increase in contact time to 15 min yielded soil adsorption from 19 to 33%. Overall maximum SMC soil adsorption percentage of 34 was obtained for 20 min of contact time in the orbital shaker. There is not much variation in adsorption% observed for the contact time of 15 and 20 min. So the maximum adsorption efficiency of SMC soil was 34% after a contact time of 20 min.

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Fig. 2 Adsorption percentage with respect to initial concentration for different times of contact

Table 1 Batch experiment conditions S. No. Sample

EC (mS/cm) pH

TN (ppm) TOC (ppm)

1

SMC soil + 50 ppm KNO3

0.07

7.58

49.91

6.63

2

Compost + 50 ppm KNO3

0.17

6.27 149.77

73.55

3

SMC soil + Compost + 50 ppm KNO3 0.11

6.69

30.46

86.71

3.2 Impact of Nitrate Solution on Chemical Parameters The nitrate solution of 50 ppm concentration with SMC soil yielded lesser values of various physicochemical parameters. This reveals that most of the nutrients in the SMC soil were consumed by the crops at earlier stages; hence, the SMC soil remains with inappreciable nutrient quantity. The compost when combined with slight alkaline SMC soil resulted in a pH of 7.58, whereas the mixture compost– nitrate solution and SMC soil–compost–nitrate solution showed acidic pH 6.27 and 6.69, respectively. Since the compost consists of high EC, TN, and TOC, it can act as an efficient soil conditioner to supplement the necessary nutrients to the soil. The SMC soil which is less fertile has thus received optimum nutrient values when mixed with compost (Table 1).

3.3 Variations of EC with Respect to Time in Column The samples collected from the column experiments as mentioned in Sect. 2.3 were further examined for EC, pH, and TN. The EC values range between 0.088 and

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Fig. 3 Variations of EC with respect to time in column

0.576 mS/cm for the entire duration of column leaching. The EC range lies between 0.5 and 0.8 mS/cm for sampling time 35th to 65th min whereas, for batch experiment, it ranges from 0.05 to 0.1 ms/cm. Hence, it can be proclaimed that outlet water from column experiments resembles the quality of treated water for irrigation. The maximum EC value of 0.576 mS/cm was obtained at 65th min. The nutrients initially percolate through the SMC soil with low dispersion effect thus yielding initially low salt contents and thereby, low EC values. However, the percolation gradually increased with respect to time, and hence, the observed EC values gradually increased. In contrast, while washing with distilled water, a significant reduction in the salt contents was observed due to increased solubilization experienced during leaching. After obtaining the peak concentration, the time–concentration curve showed a clear breakthrough where the concentration values started dropping significantly. The breakthrough curve denotes that initially, the infiltration rate is low, but it gradually increases with time and then falls down while washing (Fig. 3).

3.4 Variations of pH During Leaching The pH ranges varied from 6.59 to 7.08 for the sampling time 35th and 75th min, respectively (Fig. 4). In general, there is not much variation in pH with respect to time. The observed result for the samples discloses that the vertical leaching of nitrate solution through SMC soil depends upon the ion exchange capacity and pH of the soil which varied slightly from acidic to neutral. This result, however, contrasted to some extent with batch studies due to the bulk mixing of soil and nitrate solution. It also reveals that hydrogen ions (or other cations) present in the leaching water have less significance over the time of flow in the adsorption capacity of SMC soil.

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Fig. 4 Variations of pH with respect to time in column

3.5 Variations of TN During Leaching The TN values for the first few samples were observed to be very low due to less diffusion. As contact time increases, the percolation of nitrate through SMC soil resulted in improved TN values. The maximum TN observed by SMC soil 55.38 ppm matches well with 90% similarity during the batch study which is 49.91 ppm. This breakthrough curve also follows the trend similar to EC in such a way that the penetration of nitrate solution into the SMC soil results in low TN initially, increases gradually, and falls down while washing with distilled water. TN starts to decrease rapidly after 65th min (Fig. 5).

4 Conclusions Soil organic matter is expected to be a good sink for nutrients during extreme fertigation conditions. The fate and transport of dissolved nutrients depend largely on the mass transfer limiting properties of soil. Results from batch and column experiments with a typical field soil (SMC soil) showed the significance of improving the adsorptive removal of nitrates in SOM as a suitable fertigation strategy in SMC soil. The SMC soil with nitrate solution in the batch experiment showed the maximum nitrate adsorption of 34% under various initial concentrations as well as various contact times. The leaching experiments depicted that nitrate sequestration and adsorptive

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Fig. 5 Variations of TN with respect to time in column

removal were found to be enhanced in SMC soil amended with sewage sludge cocompost. Hence, it is imperative to evaluate an optimum proportion of SMC soil and compost in order to effectively design suitable soil conservation measures. Acknowledgments This research was funded by the Science and Engineering Research Board, Department of Science and Technology, Government of India under Swacch Bharat Mission (ECR/2016/001114/ES). The authors would like to acknowledge the support rendered by the management, staff, and students of Bannari Amman Institute of Technology, Sathyamangalam.

References 1. Martyniuk S, Pikuła D, Kozieł M (2019) Soil properties and productivity in two long-term crop rotations differing with respect to organic matter management on an Albic Luvisol. Sci Rep 9(1):1878 2. Middha R, Jain S, Juneja SK (2015) A comparative study of physico-chemical parameters of restored and unrestored soils of two villages of Chaksu block, Jaipur, Rajasthan. Methodology 3. Nguyen TTN, Xu CY, Tahmasbian I, Che R, Xu Z, Zhou X, Bai SH (2017) Effects of biochar on soil available inorganic nitrogen: a review and meta-analysis. Geoderma 288:79–96 4. Costa JL, Prunty L (2006) Solute transport in fine sandy loam soil under different flow rates. Agric Water Manag 83(1–2):111–118 5. Biggar JW, Nielsen DR (1976) Spatial variability of the leaching characteristics of a field soil. Water Resour Res 12(1):78–84 6. Dinesh Kumar C, Kumaresh V, Abhimanyu J, Vasudevan M (2018) An experimental study on soil erosion and evaluation of soil conservative systems. Nat Environ Pollut Technol 17(1):249– 254

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7. Zhen Q, Zheng J, Zhang X, Shao MA (2019) Changes of solute transport characteristics in soil profile after mining at an opencast coal mine site on the Loess Plateau. China, Science of The Total Environment 8. Meghdadi A (2018) Characterizing the capacity of hyporheic sediments to attenuate groundwater nitrate loads by adsorption. Water Res 140:364–376 9. Banzhaf S, Hebig KH (2016) Use of column experiments to investigate the fate of organic micro pollutants–a review. Hydrol Earth Syst Sci 20(9):3719–3737 10. Shahandeh H, Wright AL, Hons FM (2011) Use of soil nitrogen parameters and texture for spatially-variable nitrogen fertilization. Precis Agric 12:146–163 11. Amponsah D, Godfred E, Sebiawu DO (2014) Determination of the amount of the exchangeable ammonium-nitrogen in soil samples from the University of Cape Coast School Farm. Int J Sci Eng Res 5(6):731–736 12. Bautista F, García E, Gallegos A (2016) The App SOC plus a tool to estimate and calculate organic carbon in the soil profile. J Appl Res Technol 14:135–139 13. Nartey EG, Amoah P, Ofosu-Budu GK, Muspratt A, Pradhan S (2017) Effects of co-composting of faecal sludge and agricultural wastes on tomato transplant and growth. Int J Recycl Org Waste Agric 6:23–36 14. Marín-Benito, JM, Barba V, Ordax JM, Soledad Andrades M, Sánchez-Martín MJ, RodríguezCruz MS (2018) Application of green compost as amendment in an agricultural soil: effect on the behaviour of triasulfuron and prosulfocarb under field conditions. J Environ Manag 207:180–191 15. Mohsenipour M, Shahid S, Ebrahimi K (2015) Nitrate adsorption on clay kaolin: batch tests. J Chem 16. Schwantes D, Gonçalves AC, Schons DC, Veiga TG, Diel RC, Schwantes V (2015) Nitrate adsorption using sugar cane bagasse physicochemically changed. J Agric Environ Sci 4(1):51– 59

Behaviour of Lignosulphonate Amended Expansive Soil G. Landlin, M. K. Soundarya, and S. Bhuvaneshwari

Abstract Expansive soils are problematic soils which exhibit large volume change behaviour on exposure to moisture changes. These soils are often chemically treated to mitigate the volume change behaviour. The chemical treatment involves the addition of chemical additives and various other waste materials which can curtail the volume change behaviour. However, the usage of chemical additives leads to large environmental issues and affects the biodiversity of the surrounding environment. In an attempt to cater to these issues, a non-conventional additive, with a biopolymer base namely Lignosulphonate is used for treating the expansive soil. The soil selected is of highly expansive in nature, and the additive is added in small percentages of 1, 1.5 and 3%, and its effects on various soil properties are evaluated. The bio-polymer based additive basically curtails swelling and has a good influence on strength and improvement of compaction characteristics. The microstructural aspects are also evaluated through XRD (X-Ray Diffraction) and SEM (Scanning Electron Microscope) techniques, in order to understand the changes at the microstructure level, particle orientation and probable formation of cementitious compounds, and the comprehensive behaviour of the additive amended expansive soil. The lignosulphonate-treated samples depicted a 5-fold increase in strength, due to the particle aggregation and floc formation. Keywords Expansive soil · Stabilization · Swelling · Lignosulphonate · Microstructure

G. Landlin (B) · S. Bhuvaneshwari Department of Civil Engineering, SRM Institute of Science and Technology, Chennai, India e-mail: [email protected] S. Bhuvaneshwari e-mail: [email protected] M. K. Soundarya Department of Civil Engineering, Vels Institute of Science, Technology and Advanced Studies, Chennai, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_15

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1 Introduction The expansive clay is a type of clay which exhibits the property of swelling with the addition of water and shrinkage with the reduction of water. This property of the clays to swell and shrink comes into action due to the seasonal moisture changes throughout the year. The drying of soil takes place during the summer which causes the clay to shrink and form cracks. During rains, the soil absorbs water and expands. The construction industry faces major problems on account of this drastic volume change behaviour of these soils. Hence, the soil needs to be stabilized against this volume change behaviour. This can be done by many methods like adding additives, reinforcing columns, replacement, geotextiles, etc. Soil stabilization is one of the ground improvement methods of treating the weak soils, unfit for engineering purposes and making them suitable for construction purposes. Some of the research works were conducted by earlier researchers for treatment of expansive soil using various additives such as lime, fly ash, foundry sand, iron turning, lime powder, blast furnace slag, cement kiln dust, and lime dust. Extensive research has been carried out in the field of soil stabilization, and few of the studies with conventional stabilizers and industrial wastes are described here. Zhang Ji-ru and COA Xing studied the influence of lime and fly ash on expansive clays. The lime ionizes the clay particles and changes the particle structural arrangement from dispersed to flocculated by the chemical reaction which takes place with the soil. The fly ash contributes to the stabilization of the soil by increasing the percentage of silt particles. Various percentages of lime (4, 5 and 6%) and fly ash (40, 50%) were added to the expansive clays and their behaviours were analysed. Also, the lime (4%) and fly ash (40%) were added together to the soil. The swell capacity under 50 kPa pressure was minimum for the stabilized clay with the addition of lime and fly ash [1]. A study was done in the improvement of expansive clays using a petrochemical waste and lime in varying percentages (4, 6, 8, 10 and 12%). The effect of the waste and lime on unconfined compression test, pH, Atterberg’s limits and shear strength has been studied. Though the swelling capacity of the improved soil did not show much decrease with the addition of waste than the lime, the strength characteristics of the soil have been observed to be increased drastically [2]. The foundry sand, fly ash and lime powder are used as admixtures for treating the expansive soil. The maximum strength was achieved for soil, foundry sand, fly ash, lime powder mix 54:36:10:2.25 as the desired proportion. The strength of the soil was improved, and void in the mix is occupied by the bonding agent (lime powder) [3]. By the addition of lime powder in varying proportions (10, 20, 30%), the CBR value was increased up to 105% from untreated soil by the 20% addition of lime powder. The swelling pressure was decreased to 48% by 20% addition of lime powder. This finds its application in pavement technology, and this could be utilized in the flexible pavement for strengthening the problematic soil and can be more economical in construction [4]. A research concluded that the optimum moisture content of Black cotton soil was 60% and copper slag was 40% and it showed the increase in the value

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of CBR and concluded that such soil can be effectively used in road embankment subbase and subgrade [5]. Muthu Kumar et al. studied lime dust, a by-product of the lime industry, which could be used for soil stabilization to control the disposal problems and preserve the ecological system by utilization of lime powder. It is used to improve the geotechnical properties of expansive soil and make them more stable and also to stabilize the soil with low-cost material. The lime powder was added in different proportions such as (5, 10, 15, 20 and 25%) and studied the compaction characteristics of the soil. The max strength of 215 kN/m2 was attained at 15% of lime powder [6]. Most of the studies were based on the treatment of expansive soil using conventional additives such as the lime and fly ash. However, the use of non-conventional additive such as lignosulphonate (LS) was limited. The present study focuses on the stabilization of expansive soil using a non-conventional additive—Lignosulphonate. Lignosulphonate (LS) derived from the paper industry is basically a bio-polymer which makes it more environment friendly [7]. It has both water attracting and repelling groups of compounds which makes the application rather limited. The usage of lignosulphonate is highly safe for the soil and other construction materials. Few of the research studies are presented here. Indraratna et al. carried out laboratory strength tests on LS-treated clay soils. The Unconfined Compressive strength test results indicated an increase in the ultimate strength and stiffness of LS-treated soils. They also observed that the LS stabilization completely depends on the clay mineralogy. The reactive clay soil which has the presence of Montmorillonite reacts better with LS than kaolinite. The results revealed a reduction in the double layer thickness, due to an increase in the ionic concentration [8]. One-dimensional swell tests were carried out on LS-treated Australian expansive soil. The LS-treated samples exhibited a considerable reduction in swelling, and were stable over freeze–thaw cycles. The microstructural analysis also revealed a reduced specific surface area which has further reduced the swell potential of the otherwise expansive soil [9]. The improvement in the behaviour of silty foundation soil was studied by Zhang et al., and the silty soil was treated with the lignin-based industrial by-product. The engineering property tests revealed a ductile behaviour for around 12% of LS-treated silty soil [10]. Though few research works had been carried out in the utilization of lignosulfonates for stabilizing process, there does not exist a protocol or codal provisions for the usage of the LS. This study primarily focusses on bringing out the basic understanding of the behaviour of expansive soil treated with 1–3% of LS. The change in index and engineering properties is observed and reported.

154 Table 1 Properties of natural soil

G. Landlin et al. Properties

Values

Specific gravity

2.71

Clay content

70%

Silt content

30%

Sand content

0%

Soil classification

CH

Liquid Limit

76%

Plastic Limit

23%

Plasticity index

53

Shrinkage Limit

9%

Free swell index

105%

Optimum moisture content

28%

Maximum dry density

14.1 kN/m3

2 Materials and Methodology 2.1 Soil The expansive soil used in the project was taken from the soil site Siruseri, Chennai, Tamil Nadu (12.8350N, 80.200E). The soil was air-dried, pulverized and crushed, then sieved through 1.0 mm IS sieve. The index properties of the soil such as the particle size distribution, Atterberg’s limits, mini compaction and the Unconfined Compression strength were tested and represented in Table 1.

2.2 Lignosulphonate (LS) The non-conventional stabilizer, lignosulphonate, used is a commercially available calcium lignosulphonate. The properties and the composition of lignosulphonate are shown in Table 2.

2.3 Experimental Methodology The pulverized soil was mixed with 1, 1.5 and 3% of lignosulphonate by weight. The quantity of additives to be added was decided based on the literature review. In order to understand the influence of LS on the expansive soil, both the untreated soil and the soil treated with the various percentages of LS were tested for Atterberg’s limit and compaction characteristics. In order to access the strength characteristics,

Behaviour of Lignosulphonate Amended Expansive Soil Table 2 Properties of lignosulphonate

155

Properties

Values

Appearance

Yellow brown powder

PH value

5–7

Dry matters

95% min

Water insoluble

2.50%

Sulphate

2% min

Total Calcium magnesium (sulphate)

5–6%

Lignosulphonate

50% min

Sugar

10–12%

Reducing sugar

7% around

Ash

18–21%

Bulk density (kg/m3)

205

Moisture

7%

Unconfined Compression tests were carried out on the soil blended with 1.5% of LS. The compacted samples were further cured for 3 and 28 days and tested for Unconfined Compressive strength. Further, in order to understand the microstructural aspects of the soil and treated soil, SEM and X-ray diffraction analysis were carried out on the treated and untreated soil samples. The grain size analysis was done using Hydrometer as per the IS 2720: Part 41985 [11]. The specific gravity of the soil was found to be 2.71 as per IS 2720: Part 3 Section 1-1980 [12]. The liquid limit, plastic limit and the shrinkage limit (Atterberg’s limits) were determined by conducting their respective tests conforming to IS 2720: Part 5-1985 and IS 2720: Part 6-1972 [13, 14]. The soil was classified as CH conforming to Indian Standard system of classification as per IS 1498-1970 [15]. The optimum moisture content and the maximum dry density of the soil were determined using the mini compaction apparatus suggested by Sridharan and Sivapulliah [16]. The free swell index of the expansive clay was determined according to IS 2720: Part 40-1977 [17]. The Unconfined compression test was carried out on soil samples as per IS: 2720: Part 10-1991 for both untreated and treated soil samples [18]. The computer-controlled X-ray diffractometer gives the X-ray patterns of the minerals. The analysis of the d-spacing and intensities was done using the JCPDS software (ICDD 2002-PCPDFWIN V 2.3). The samples were prepared as suggested by the procedure given by Brown and Brindley [19]. The virgin soil and the treated soil are studied for the variation of the X-ray diffraction pattern. The micro-level graph lets us analyse the arrangement of soil fabric. SEM (Scanning Electron Microscope) is an analytical tool usually used to capture the image or the fabric arrangement of the sample at the micro level. The virgin soil and treated soil samples were analysed to study the alteration at the microstructural level caused by LS treatment.

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3 Results and Discussions The soil sample treated with various % of LS were tested for Atterberg’s limits, free swell index, compaction, strength characteristics, mineral quantification and microstructural arrangements. The following section discusses the tests and results carried out.

3.1 Atterberg’s Limits and Free Swell Table 3 gives the variation of liquid limit, plastic limit, shrinkage limit and free swell index of the soil samples treated with 1, 1.5 and 3% of LS. The liquid limit values reduce from 76 to 59% for LS-treated soil. Not much variation was noticed in the plastic limit. However, there is nearly 20% decrease in plasticity index values. There was only a minor increase in shrinkage limit values from 9.5 to 13%. Some reduction was noticed in FSI from 105 to 85% for 3% LS.

3.2 Compaction Characteristics Figure 1 depicts the compaction characteristics of soil and LS-treated soil. The LStreated soil shows a decrease in dry density and also increase in optimum moisture content. For 3% LS, the optimum moisture content is 24 and 21% compared to untreated soil.

3.3 Strength Characteristics The virgin soil and 1.5% LS-treated soil were compacted to the respective densities and cured for 3 days and 28 days. The stress–strain behaviour of the treated samples was determined by Unconfined Compression test and Fig. 2 shows the stress–strain relationship. The UCC strength of LS treated soil shows a considerable increase in strength after 28 days of curing compared to the strength of untreated soil. The strength of LS-treated soil depicted an increase of 786 kPa for 28 days curing compared to that of the untreated soil which was 158 kPa. The samples tested immediately and after 3 days curing depicted only a smaller increase in the strength compared to 28 days curing.

76.16

59.14

57.65

59.22

soil

soil + 1.0% (LS)

soil + 1.5% (LS)

soil + 3.0% (LS)

Liquid limit (%)

Sample

Table 3 Atterberg’s limits and free swell index

23.76

21.6

25.87

23.04

Plastic limit (%)

35.46

36.05

33.34

53.12

Plasticity index (%)

13

12

11.5

9.5

Shrinkage limit (%)

85

90

90

105

Free swell index (%)

Behaviour of Lignosulphonate Amended Expansive Soil 157

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Fig. 1 Compaction characteristics of treated (LS) and untreated soil

Fig. 2 Unconfined compression test result for soil with 1.5% LS

3.4 X-Ray Diffraction Analysis Peaks of Quartz at 2θ = 27° were suppressed in LS-treated samples. This corresponds to the decrease in ‘d’ spacing, that is the distance of separation of atomic planes. The peaks of Illite and Montmorillonite also depict boarding and suppression. This is due to the peripheral adsorption of LS on the surfaces of the minerals. This coating on the soil leads to the formation of flocs and aggregates which has subsequently led to the decrease in swell (free swell index = 90%) and a gradual increase in strength [9]. Table 4 shows the broadening and suppression of minerals for untreated and 1.5% LS-treated samples. The result of the X-Ray diffraction analysis of the untreated soil

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Table 4 Peak 2θ values of minerals Mineral

2θ Standard

Quartz

Untreated sample

21° 27°

20.933° 26.853°

37° 50° Montmorillonite

LS-treated sample 26.655° 36.576°

50.303°

50.170°

5.6° 18°

19.807°

28°

28.230°

27.496°

35.5°

35.190°

36.576°

54°

55.077°

54.810°

Fig. 3 X-ray diffraction analysis result for untreated soil and soil treated with 1.5% LS

and the soil treated with 1.5% LS is given in Fig. 3 which shows the peak for the various minerals.

3.5 Scanning Electron Microscopy SEM was adopted to the quantify the microstructural development in the untreated and LS-treated soil as well. In Fig. 4, the untreated soil does not show much of

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Fig. 4 Untreated soil, under 5000x and 20000x magnification

aggregation at 5000x magnification and 20000x magnification. However, LS-treated samples show an aggregated structural arrangement with a few larger pores as shown in Fig. 5. Thus, the change at the micro level attributed to the increase in the strength of the treated samples.

Fig. 5 1.5% LS-treated Soil, under 5000x and 20000x magnification

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4 Conclusions A potential expansive soil sample was treated with the bio-polymer Lignosulphonate. The samples were tested for the basic index properties as well as for the strength and compaction characteristics. The following inferences were drawn from the test results. The LS-treated samples showed a 20% decrease in the plasticity characteristics compared to the virgin soil. A marginal increase in shrinkage limit and reduction in free swell were observed. However, there was a nearly 5-fold increase in UCC strength for 1.5% LS-treated soil samples. Based on the X-ray diffractograms and Micrographs, the increase in strength was attributed to the formation of flocs and aggregation of the soil due to the peripheral coating of Lignosulphonate on soil minerals. However, the understanding of the exact phenomenon of the soil–lignosulphonate interaction warrants more extensive tests with LS with different percentages and curing periods.

References 1. Ji-ru Z, Xing COA (2002) Stabilization of expansive soil using lime and fly ash. J Wuhan Univ Technol 17(4):73–77 2. Khazaei J, Moayedi H (2015) Soft expansive soil improvement by eco-friendly waste and quick lime. Arab J Sci Eng. https://doi.org/10.1007/s13369-017-2590-3 3. Kumar A, Sharma RK, Babita S (2015) Compaction and sub-grade characteristics of clayey soil mixed with foundry sand and fly ash and tile waste. IOSR J Mech Civil Eng 01–05 4. Rani G, Shivanarayana C, Prasad M, Raju GVRP (2014) Strength behaviour of expansive soil treated with tile waste. Int J Eng Res Dev 10(12):52–57 5. Qureshi MA, Mistry HM, Patel VD (2015) Improvement in soil properties of expansive soil by using copper slag. Int J Adv Res Eng Sci Technol 2(07) 6. Kumar M, Tamilarasan VS Experimental study on expansive soil with marble powder. Int J Eng Trends Technol (IJSR) 22:504–507 7. Zinping O, Xueqin Q, Chen P (2006) Physiochemical characterization of calcium lignosulphonate – a potentially useful water reducer. Colloids Surf A: Physiochem Eng Asp 282–283:489–497 8. Indraratna B, Athukorala R, Vinod J (2012) Estimating the rate of erosion of a silty sand treated with lignosulfonate. Eng Geol 196:1–11. https://doi.org/10.1016/j.enggeo.2015.07.003 9. Alazigha D, Indraratna B, Vinod JS, Ezeajugh L, Emeka L (2016) The swelling behaviour of lignosulfonate-treated expansive soil. Proc Inst Civil Eng – Gr Improv 169(3):182–193 10. Zhang T, Ca G, Liu S, Puppala AJ (2016) Engineering properties and microstructural characteristics of foundation silt stabilized by lignin-based industrial byproduct. KSCE J Civil Eng Korean Soc Civil Eng 1–12. https://doi.org/10.1007/s12205016-1325-4 11. IS: 2720 (1975) Methods of tests for soil, part IV, grain size analysis 12. IS: 2720 (1980) Methods of tests for soil, part III/sec1, specific gravity 13. IS: 2720 (1975) Methods of tests for soil, part V, liquid limit and plastic limit 14. IS: 2720 (1972) Methods of tests for soil, part VI, determination of shrinkage factors 15. IS: 1498 (1970) Classification and identification of soils for general engineering purpose 16. Sridharan A, Sivapullaiah PV (2005) Mini compaction test apparatus for fine grained soils. J Test Eval ASTM 28:240–246 17. IS: 2720 (1977) Methods of tests for soil, part XL, determination of free swell index of soils

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18. IS: 2720 (1991) Methods of tests for soil, part X, determination of unconfined compression strength 19. Brown G, Brindley GW (1980) X-ray diffraction procedures for clay minerals identification in crystal structure of clay minerals and their X-ray identification. Minerol Soc, London, pp 305–359

Push-Out Tests for Determining the Strength and Stiffness of the Channel Connectors—Experimental Study P. Sangeetha, R. Vijayalakshmi, Aaditya Jagadeesh, S. Ahalya, K. Deveshwar, and D. Swarna Varshini

Abstract Steel–concrete composite structures have been used for a long time in the construction of bridges and buildings. The composite action between steel and concrete is achieved by means of shear connectors. In this paper, push-out test was carried out using the channel connectors in the composite specimens. The parameters considered in the test were the number of channel connectors and specimens with or without ribbed deck sheet. Four specimens were tested to failure and observed that the failure of the specimens is mainly due to channel connectors and concrete slab. The specimens with ribbed decking sheets carried a higher load when compared to the specimen without decking sheets. The strength of the channel connectors was calculated and compared with the codal provision and proposed equations of the researchers. The values calculated using equations were in good agreement with the experimental test results. From the load–slip and load–strain behaviour, it is also observed that the specimens with decking sheet are stiffer than the specimens without decking sheet. Keywords Composition action · Channel connector · Ribbed decking sheet · Strength · Stiffness P. Sangeetha (B) · R. Vijayalakshmi · A. Jagadeesh · S. Ahalya · K. Deveshwar · D. Swarna Varshini Department of Civil Engineering, SSN College of Engineering, Chennai, India e-mail: [email protected] R. Vijayalakshmi e-mail: [email protected] A. Jagadeesh e-mail: [email protected] S. Ahalya e-mail: [email protected] K. Deveshwar e-mail: [email protected] D. Swarna Varshini e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_16

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1 Introduction Shear connectors are used to transfer the shear between concrete and steel. The composite action between the steel and concrete is influenced by the suitable choice of shear connectors. The channel connector is one of the shear connectors used in composite structures. The strength and stiffness of the shear connectors are studied by conducting push-out test. The push-out specimens were made with varying parameters like with or without profile decking sheet and a number of the channel connectors (one or two connectors). Balasubramanian and Rajaram [1] have studied the behaviour of connection between the steel beam and concrete slabs using deck sheet welded shear connectors and compared the results with the published experimental work. Kim et al. [2] have tested six push-out specimens with two different lengths of angle shear connectors embedded in normal concrete and compared the results with design code formula. Paknahad et al. [3], have studied the effect of high-strength concrete on the shear capacity of the channel shear connectors in the steel–concrete composite floor system by both experimental and analytical studies. Pashan and Hosain [4] have carried out push-out test on the specimens along with channel connectors with or without wide-ribbed metal deck. A concrete shear failure occurred in the specimens with ribbed metal decks. Many researchers [5–9] have studied the behaviour of composite action and its performance in the composite structures. In this study, the behaviour and effects of the channel shear connectors under compression are examined, and the results are compared with the codal formula and equations proposed by researchers.

2 Experimental Study 2.1 Specimen Description All the specimens are fabricated and channel connectors are welded in position. The concrete of M25 grade is used for casting the specimens. All the specimens are subjected to three strain gauges and one dial gauge in order to measure the strain in channel connector in the concrete slab and in central steel I-beam and also to measure the slip between steel and concrete. Table 1 gives the specification of the specimen and material properties. In the table, the specimen is number as CC represents Channel Connector, 1 & 2 represents the number of connectors and DC represents the Decking sheet. The detailed dimensions of the specimens are given in Fig. 1. Figure 2 shows specimens with channel connectors along with or without a profile decking sheet after welding. Slabs are cast in the horizontal position without reinforcement on to the levelled surface using proper formwork. The slabs are cured under normal condition, and after curing, the other side of the slab is prepared.

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Table 1 Specification and mechanical properties of the specimen Sl.No

Specimen ID

No of the channel connectors

Elastic modulus of steel and decking sheet (N/mm2 )

Characteristic compressive strength of concrete (N/mm2 )

Elastic modulus of concrete (N/mm2 )

1

CC-1

1

2 × 105

26.25

25,620

2

CC-2

2

3

CC-1-DC

1

4

CC-2-DC

2

Figure 3 shows the construction of formwork for the specimens. Figure 4 shows all four push-out specimens after placing the concrete. The push-out specimens were tested in the universal testing machine. All the specimens are fixed with three strain gauges of 20 mm to measure the strain, one on to the channel connectors, second on to the structural steel and another one on to the concrete slab. The position of the strain gauges and dial gauges is shown in Fig. 5. The specimens were loaded using a universal testing machine of capacity 600kN. The load was applied until the specimen fails. The strains from all the three strain gauges were recorded using strain indicator. The axial deflection measured using dial gauge represents the slip between steel and concrete.

3 Result and Discussion 3.1 Failure Type Normally, two types of failure are defined in the push-out specimen. The type I is the fracture of the channel shear connectors and the type II is the crushing and splitting of the concrete slab. The load–slip behaviour shown in Fig. 6 shows the sudden failure of the specimens that are made without profile decking sheet whereas the specimens with profile decking sheet able to resist more load and also increase the stiffness of the channel connectors were increased. The percentage increase in the load-carrying of the specimen with profile decking sheet is 62% when compared to specimens without profile decking sheet, irrespective of change in the number of channel connectors in the push-out specimen. The strength of the composite specimen with one-channel connectors is nearly half that of the specimens with two number of channel connectors. In the case of the specimens with profile decking sheet, the strength of specimens with one connector is around one-third of the strength achieved by the specimens with two connectors. From the load–slip behaviour, the stiffness of the connectors was found, and it was 90 and 122 kN/mm for the specimens with or without profile decking sheet, respectively.

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Fig. 1 Detailed specification of the specimen

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Fig. 2 Push-out specimens after fabrication

Fig. 3 Push-out specimens with formwork

Fig. 4 Push-out specimens after placing concrete on one side

The plot between the load and strain in central I-beam was shown in Fig. 7. The specimen with two-channel connectors along with decking sheet (CC-1-DS) shows better performance up to 100 microstrain and is also able to resist the deformation due to the increase in the load. The first crack is observed at 70% of the maximum load applied on the specimen. Table 2 gives the failure load of the specimens and the percentage of strength degradation.

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Fig. 5 Position of strain gauges and specimens under testing

Fig. 6 Load versus slip behaviour of the push-out specimen with channel connectors

3.2 Theoretical Comparison The shear resistance obtained using experimental study was compared with the design code formula and design equation proposed by researchers. The shear resistance of the channel connectors which is embedded in the concrete slab using Canadian code (CAN/CSA-S16-2001) was calculated using Eq. 1

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Fig. 7 Load versus strain behaviour of the push-out specimen with channel connectors

Table 2 Push-out test results and comparison Specimen

Slab details

No of channels

Failure type

Failure load (kN)

Strength degradation (%)

Maximum slip (mm)

CC-1

Solid slab

1

Channel failure

225

51

2.40

CC-2

Solid slab

2

Channel failure

460

CC-1-DC

Slab with ribbed metal deck

1

Slab failure

575

CC-2-DC

Slab with ribbed metal deck

2

Slab failure

767

qr s = 36.5ϕsc(t + 0.5w)Lc

5.20 33

4.75

6.20

√

fc

where ϕsc = Resistance factor for shear connectors t = Flange thickness of channel (mm) w = Web thickness of channel (mm) Lc = Length of channel shear connector (mm) f c = Compressive cylinder strength of concrete (MPa).

(1)

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Pashan and Hosin [4] have proposed a design equation (Eq. 2) to calculate the ultimate shear strength per channel connector in N of the channel connectors in solid concrete slab and slabs with wide-ribbed metal deck, respectively. Channel connectors in solid slab; qu = (336 w2 + 5.24 L H ) Channel connectors in ribbed slab; qu = (1.7L H + 275.4 w ) 2

√ √

fc fc

(2)

w = Thickness of the web (mm) L = Length of the channel connector (mm) H = Height of the channel connector (mm) f c = Compressive cylinder strength of concrete (N/mm2 ) wd = Width to depth ratio of the rib of the metal deck. hd The design equation (Eq. 3) proposed by Paknahad et al. [3] was used to calculate the shear strength of the channel connectors in the solid slab in N. Qn = 39.45 × (t f + 0.5tw ) × Lc ×

√

fc

(3)

Using Eqs. 1–3, shear strength of the channel connectors were calculated and compared with experimental shear strength. Figure 8 shows the comparison between the calculated shear strength of the channel connectors with experimental shear strength for the solid and metal ribbed slab. From the bar chart, it is observed that the performance of channel connectors with ribbed deck sheet improved 50% when compared with the specimen with a solid concrete slab.

Shear resistance [kN]

700 Solid Slab Ribbed Slab

600 500 400 300 200 100 0

Experimental

Canadian Code

Design Equation[1]

Design Equation[2]

Fig. 8 Comparison between the shear resistances of the channel connectors on the solid and ribbed slab

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4 Conclusion The push-out specimens with solid and ribbed slab using channel connectors were tested to failure. The shear resistance of the connectors and its behaviour in terms of load–slip and load–strain were also studied. The values of shear strength obtained from the experimental study were compared with the recommendation given in the Canadian Code and also the with proposed equations in the literature. • From the experimental study on the push-out specimen, it was concluded that the composite action between steel and concrete was enhanced by placing channel connectors along with ribbed decking sheet than the channel connectors without deck sheet. The percentage increase in the shear resistance of the push-out specimen with ribbed deck sheet is 60%. • The average stiffness of the channel connectors with or without ribbed deck sheet is 90 kN/mm and 122 kN/mm, respectively, and which is nearly close to the average value present in the literature. • It was observed that the failure of the specimens with ribbed sheet is mainly by cracking of the concrete and it can be reduced by placing high-strength concrete. • It was found that load-carrying capacity of the push-out specimens with twochannel connectors was two times more than specimens with one connector.

References 1. Balasubramanian R, Rajaram B (2016) Study on behaviour of angle shear connector in steelconcrete composite structures. Int J Steel Struct 16(3):807–811 2. Kim B, Wright HD, Cairns R (2001) The behaviour of through-deck welded shear connectors: an experimental and numerical study. J Constr Steel Res 57:1359–1380 3. Paknahad M, Shariati M, Bazzar M, Khorami M (2018) Shear capacity equation for channel shear connectors in steel-concrete composite beams. Steel Compos Struct 28(4):483–494 4. Pashan A, Hosain MU (2009) New design equations for channel shearconnectors in composite beams. Can J Civil Eng 36:1435–1443 5. Prakesh A, Anandavalli CK, Madheswaran N, Lakshmanan N (2012) Modified pusk-out tests for determining shear and stiffness of HSS stud connector-experimental study. Int J Compos Mater 2(3):22–31 6. Sangeetha P, Ashwin Muthuraman R (2018) Performance of steel concrete sandwich beam with varying shear connectors. Indian J Sci Technol 11(34):1–7 7. Sangeetha P, Senthil R (2017) A study on ultimate behaviour of composite space trusses. KSCE J Civil Eng 21(3):950–954 8. Eurocode 2 (2005) EN 1992-1-1; design of concrete structures part 1.1 general rules and rules for buildings. CEN-European Committee for Standardisation, Brussels, Belgium 9. CSA (2001) CAN/CSA-S16-01, limit states design of steel structures. Canadian Standard Association, Rexdale, Ontario

Experimental Study of the Headed Stud Connectors in Composite Structure P. Sangeetha, S. Ramanagopal, U. Amrutha, A. Balasubramaniam, V. Madhumitha, and G. Arun

Abstract Steel–concrete composite members have been widely used in the construction of high-rise building. The parameters which affect the composite action between steel and concrete are the strength of the connectors and concrete strength. In this study, the push-out test was conducted to find the strength and stiffness of the stud connectors embedded in the solid concrete slab and concrete slab with decking sheet. Four numbers of push-out specimens were made with one or two stud connectors. The failure was observed on the surface of the concrete slab. The load–slip behaviour and shear capacity of the stud connectors on the solid slab with or without decking sheet were calculated and compared with current codes of practice. There was a good agreement between the shear strength obtained using experimental study and codal equations. Keywords Stud connector · Push-out test · Load–slip · Load–strain · Codal comparison

1 Introduction Composite structures are the most trending type of material composition used to build high-rise structures, bridges, etc. The composite beam consists of steel, connectors, deck sheet and concrete, in which steel takes up the tensile loading and concrete takes up the compressive loading of the structure. In composite construction, the effective utilisation of the steel and concrete material leads to cost effective construction. They have proved to be stronger than the usual structures, taking a longer time to fail, encountering much less deflection and floor vibrations. Stud connectors play an important role in transferring the horizontal shear force from steel to concrete and vice versa. The stud connectors are fitted in between steel and concrete by welding it with the I-beam on the flange side of the beam, and then, the formwork is made P. Sangeetha (B) · S. Ramanagopal · U. Amrutha · A. Balasubramaniam · V. Madhumitha · G. Arun Department of Civil Engineering, SSN College of Engineering, Chennai, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_17

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to pour concrete on the setup. The structure is held intact with the help of these connectors resisting the uplift force encountered by the steel or concrete and also making the structure act in unison. Using decking sheets in the composite beams makes it cost-effective in reducing the amount of concrete, and formwork is not required to place the concrete. Decking sheets also provide tensile reinforcement when the composite beams are used for flooring. Dennis Lam and El-Lobody [1] have carried out experimental and analytical studies on the steel–concrete interface with headed stud connector to know the load–slip and to find the shear capacity of the stud connector. Rocha et al. [2] have predicted the shear capacity of stud connectors along with decking sheet in composite beams and also compared with current codal provisions. Prakash et al. [3] have carried out modified push-out test on the composite specimen with high-strength headed stud connectors and studied the strength and stiffness of the connectors. Many researchers [4–7] have studied the behaviour of composite action in the composite structures for varying the types of connectors and spacing of the connectors. Push-out tests are performed on these composite beams by varying the parameters such as the number of connectors and with or without using decking sheets. The load–slip behaviour and shear capacity were studied and compared with the codal equations.

2 Materials and Methods 2.1 Push-Out Specimen Push-out tests were conducted for the four specimens to study the behaviour of the connectors. The specimens were named as SC-1, SC-2, SC-1-DC and SC-2-DC; in this, SC stands for Stud Connectors, DC stands for Decking Sheet and 1 and 2 are the number of the stud connectors. The dimensions of the stud connectors and the spacing between the connectors are given in Table 1. The ISMB 200 made from Fe 415 was used as a central vertical member, and stud connectors are welded on the flanges at the centre and on the spacing of 133.33 mm for one connector and Table 1 Details of specimen and dimensions of the stud connector Specimen

Number of connectors

Stud dimensions (mm)

Stud Spacing (mm)

Shank diameter

Shank length

Head diameter

Head thickness

SC-1

1

18

88

30

8

–

SC-2

2

18

88

30

8

134

SC-1-DC

1

18

88

30

8

–

SC-2-DC

2

18

88

30

8

134

Experimental Study of the Headed Stud …

175

Fig. 1 Push-out specimen after fabrication with or without decking sheet

Fig. 2 Specimens before testing

two connectors, respectively. The decking sheet of size 500 × 450 × 3 mm was welded on the flange of the I-Beam along with the connectors. The solid slabs of size of 500 × 450 × 150 mm were cast using M25 grade of concrete. Figure 1 shows the specimens with or without decking sheet welded with stud connectors. Figure 2 shows all the push-out specimens before testing.

2.2 Experimental Setup All the specimens were subjected to three strain gauges in three locations in order to measure the strain from the central I-Beam, shear connectors and concrete slab. The dial gauge was used to measure the slip between steel and concrete. The position of the dial gauge and strain gauges is shown in Fig. 3. All the specimens were tested using UTM of 600 kN capacity, and the loads were applied at a rate of 12.5 kN. The strain was recorded using five-channel strain indicator. The ultimate load-carrying capacity of the specimens was noted, and failure in the concrete slab in the form of cracks and failure of the shear connectors were observed. The testing of the specimen SC-2-DC under UTM was shown in Fig. 4.

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Fig. 3 Dimension of the specimens with two connectors and position of the strain gauge and dial gauge

3 Result and Discussion 3.1 Load–Slip and Load–Strain Behaviour The load was applied at the rate of 12.5 kN to all the specimens. The loading was stopped after the specimen fails. The mode of failure observed was the splitting of concrete due to the excess shear force between the connectors and the concrete surface, and as a result, the bonding between the concrete surface and the connectors was lost. This leads to the development of cracks on the surface of the concrete. The specimen with deck sheet took more load and fails due to the failure of the stud connectors. These failures can be overcome by providing high-strength stud connectors and high-strength concrete. The plot between the load and slip was made to know the strength and stiffness of the headed stud connectors. Figure 5 shows the load–slip behaviour of the specimens. From Fig. 5, it is found that SC-2-DS was stiffer than all the specimens, and its stiffness is two times more than SC-2. The push-out specimen with deck sheet acts as the formwork for concrete slab as well as improves the shear resistance of the headed stud connectors.

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Fig. 4 Specimens under testing

Fig. 5 Load–slip behaviour of the steel–concrete composite specimen

300 SC - 1

SC - 2 - DS

SC - 1 - DS

SC - 2

Load ( kN)

250 200 150 100 50 0 0

50

100

150 200 Slip (mm) x 10-2

250

300

From the load–strain behaviour shown in Fig. 6, it is observed that all the specimens behave uniformly. The failure of the headed stud connectors in the specimen was due to the reversal strain which triggers the failure of the specimen. The resistance against slip was more for the specimens with the profile deck sheet. The maximum strain recorded in the strain indicator for all the test specimens was tabulated in Table 2. The percentage increase in the resistance to slip is 35% for the specimens with solid concrete slab and 64% for the specimen with profile deck sheet for change

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Fig. 6 Load–strain behaviour of the shank of stud connectors

SC - 1 SC - 2 - DS SC - 1 - DS SC - 2

Load ( kN)

300

250

200

150

100

50

0 -300

-200

-100

0

100

200

300

Microstrain

Table 2 Codal comparison between the shear resistances of the stud connectors Specimen

Number of connectors

Shear resistance of the stud connectors (kN) Exp.

EC 4 [8]

SC-1

1

123

74.28

AISC [9]

Maximum experimental strain

JSCE [10]

100.59

81.23

0.0011

SC-2

2

155

148.56

201.18

162.46

0.0018

SC-1-DC

1

235

173.19

227.11

201.53

0.0026

SC-2-DC

2

258

196.19

290.07

272.50

0.0035

in the number of stud connector from 1 to 2. Figure 7 shows the plot between the load and the strain from the central I-beam.

3.2 Comparison Between the Codal Provisions The following formula from the EC 4 (Eqs. 1 and 2), AISC 360-05 (Eqs. 3 and 4) and JSCE (Eqs. 5 and 6) was used to calculate the shear resistance of the headed stud connectors in the concrete solid slab and concrete slab with decking sheet. Table 2 gives a comparison between the experimental shear strength of the stud connectors and the calculated shear strength using codal equations. Solid slab PRd = 0.29 · α · d 2 ·

√

f ck E cm

With decking sheet PRd = Rc · Rn · Rd · As · f u

(1) (2)

Experimental Study of the Headed Stud … Fig. 7 Load–strain behaviour of the Central Steel I-Beam

179 SC - 1 SC - 1 - DS

300

SC - 2 - DS SC - 2

Load (kN)

250 200 150

100 50 0 0

200

400

600

800

1000

Microstrain

Solid slab Q n = 0.5As

√

With decking sheetQ n = 0.5As

f ck E c ≤ As f u

√

(3)

f ck E c ≤ Rg R p As f u

(4)

Solid slab Vsud = Ass f sud /γb

(5)

With decking sheetVsud = Ass f sud /γb ≤ Rg R p Ass f sud

(6)

From Table 2, it is observed that for the increase in the number of connectors from 1 to 2, there is an increase in the shear strength by 50 and 40% for specimens with or without profile decking sheet, respectively. Figure 8 shows the comparison of shear resistance of the connector with the codal equations and experimental results. The shear resistance of the experiment was close to calculated values using AISC and Japan society of civil Engineering (JSCE). From the graph, the uniform trend between 300

Shear resistance of the stud connectors[kN]

Fig. 8 Codes comparison of the shear resistance of the stud connectors for the specimens

EC 4 AISC

Experimental JSCE

250 200 150 100 50 0 SC - 1

SC - 2

SC - 1 - DC

SC - 2 - DC

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the calculated shear resistances using different codal equations is also observed. From the study, it is observed that strength obtained from the experimental work is more when compared to the required strength as per the code and it also gives confidence to use recycled aggregates in the concrete mix to achieve the required strength.

4 Conclusions A standard push-out test was conducted to study the behaviour of the headed stud connectors in the composite structure along with or without decking sheet. The ultimate shear resistance, maximum slip and stiffness of the head stud connectors were studied and the following conclusions were drawn: • The push-out specimen with profile decking sheet increases the strength of the headed stud connectors twice than that of the specimens without decking sheet. • The percentage increase in the shear resistance of the headed stud connector is 60% if the number of shear connectors increases from one to two. • Test results show that the specimen with solid concrete slab were failed by the shank failure and the specimens with decking sheet were failed by cracking of concrete. These failures have been effectively reduced by providing high-strength stud connectors along with high-strength concrete. • It has been proved that the experimental shear strengths of the connector are relatively close to the recommended design strength calculated using AISC and JSCE codes.

References 1. Dennis Lam M, El-Lobody E (2005) Behaviour of headed stud shear connectors in composite beam. J Struct Eng 131(1):96–107 2. Rocha JDB, Bezerra LM, Quevedo RL (2015) Study of stud connectors behaviour in composite beams with profiled steel sheeting. Revista de la Constr 14(3):47–54 3. Prakash A, Anandavalli N, Madheswaran CK, Lakshmanan N (2012) Modified push-out tests for determining shear strength and stiffness of HSS stud connector-experimental study. Int J Compos Mater 2(3):22–31 4. Bouchair A, Bujnak J, Duratna P, Lachal A (2012) Modeling of the steel- concrete push-out test. Proc Eng-Steel Struct Bridg 40:102–107 5. Han Q-H, Xu J, Xing Y, Li Z-Y (2015) Static push-out test on steel and recycled tire rubber-filled concrete composite beams. Steel Compos Struct 19(4):843–860 6. Sangeetha P, Ashwin Muthuraman R (2018) Performance of steel concrete sandwich beam with varying shear connectors. Indian J Sci Technol 11(34):1–7 7. Sangeetha P, Senthil R (2017) A study on ultimate behaviour of composite space trusses. KSCE J Civil Eng 21(3):950–954 8. EN 1994-1-1 (2004) Design of composite steel and concrete structures part 1.1. European Committee for Standardization, Brussels

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9. AISC-LRFD (2010) Load and resistance factor design (LRFD) specification for structural steel building. American Institute of Steel Construction (AISC), Inc., Chicago, IL 10. JSCE (2009) Standard specification for design of steel and composite structures: I general provision, II structural planning, III design. Japan Society of Civil Engineers

Compaction Characteristics of Modified Clay Soils with Various Proportions of Crumb Rubber S. V. Sivapriya

Abstract The reuse of waste material is becoming an emerging thrust area in Civil Engineering. Crumb rubber produced in abundant worldwide is reused in concrete, pavements, sports field, etc. The influence of crumb rubber, when mixed with highly compressible and inorganic clay, shows significant influence in its compaction characteristics under light compaction. Various proportions of crumb rubber were added namely 10,15,20,30,40 and 50% by weight and tested to understand its compaction characteristics. The behaviour of wet and dry of optimum side of modified soil with various percentages of crumb rubber was discussed. A model is generated to calculate the maximum dry density of the modified clay. Keywords Crumb rubber · Clay · Dry unit weight · Optimum moisture content · Model

1 Introduction Crumb rubber/ shredded tyre is a recycled product from various automobiles. As it has major proportions of synthetic material, it becomes non-decomposable in due course of time: they are simply dumped in an open area as fill material or as stockpiles. In turn, it is causing a threat to the environment and human health in terms of leaching and producing large heat energy. To overcome the above-said scenario, the reuse of crumb rubber (CR) comes into practical application. In the Civil engineering field, it is widely used as a partial replacement material in the construction industry and also used as backfill material in retaining wall ([1–3], etc). The size of the rubber plays a vital role in determining the strength characteristics of the cementitious composite. When comparing the fine particle size with a large size of crumb rubber, the former produces better workability [4]. The concrete where crumb rubber replaces cement has lesser tensile strength than the concrete which has crumb rubber as a partial replacement for fine aggregate [5]. S. V. Sivapriya (B) Department of Civil Engineering, SSN College of Engineering, Chennai, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_18

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The use of recycled tyres in road embankment serves as a better reinforcing element in the construction field and reduces the cost of raw material [3]. The increase in the angle of internal friction was observed when 10% of CR was added to the soil, and it increases the bearing capacity and stability of the embankment and reduces the settlement [6]. The exothermic reaction was not generated in highway embankment when using shredded tyres, and the magnitude of the settlement was reduced by 50% [7]. If CR is added beyond 20%, there will be a reduction in shear and density properties of various clayey soils [8]. The compressive strength of the cement-treated soil with crumb rubber reduces beyond that percentage. With a maximum replacement percentage of 20% of CR, the compressive strength reduces by 17% for 28 days and 31% for 90 days curing [9]. Similar observations were done by Yadav and Tiwari [10], and they also found that the rate of occurrence of post-peak strength was reduced with the inclusion of CR in cement stabilized soil. The axial strain at failure was increased with an increase in the percentage of CR. To increase the strength of the soil to 250 kPa, a minimum of 4% cement should be added with a minimum of 5% CR to the cement–rubber chip mixture [11]. The angle of internal friction of dense soil increases from 37 to 37.6 deg and for loose soil, it increases from 31.2 to 35.3 degrees upon the inclusion of 15% of CR to the sandy soil mix [12]. A correlation as mentioned in Eq. 1 was obtained to calculate the maximum dry density and optimum moisture content with respect to the plastic limit of the soil [13] wopt = 0.941wP and γdmax = 0.932γdP

(1)

where wopt is the optimum water content, wP is the plastic limit, γdmax is the maximum dry unit weight and γdP is the dry unit weight at the plastic limit. A proportion of 30: 70 (CR: sand) provides less effect of horizontal displacement when used as backfill material in the wall [14]. With less specific gravity and reduced bulk unit weight, it can also reduce the settlement of the footing [15]. The swell pressure and compression index got reduced with the addition of CR in backfill soil, and the incorporation of CR reduces the reinforcement cost of cemented and uncemented soil [16]. From various literature studies, it is confirmed that usage of CR as a partial replacement is an effective method to reuse the CR. However, the compaction characteristics were not studied extensively by the researchers. Hence, an attempt is made to understand the compaction characteristics of different clayey soils.

Compaction Characteristics of Modified Clay Soils … Table 1 Properties of the soil [17]

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Parameter

Soil (S1)

Soil(S2)

Specific gravity

2.71

2.63

Gravel

–

2

Sand

7

22

Silt + clay

93

76

Liquid limit

63

39

Plastic limit

31

16

Shrinkage limit

12

8

Soil classification

High Compressible Clay (CH)

Medium Compressible Clay (CI)

2 Experiment Methodology 2.1 Materials Used 2.1.1

Soil

To understand the compaction characteristics, two different soils were used namely highly compressible and intermediate compressible clay, taken from two different locations from Chennai, India. The properties of the soil are (Table 1) found using relevant Indian standard codes.

2.1.2

Crumb Rubber

Crumb rubber was obtained from a local commercial supplier of 35 mesh size. To have uniformity, the CR was readily passed through 425 microns and added at 10, 15, 20, 30, 40 and 50% to the soil by weight with a specific gravity of 0.4.

2.2 Experimental Procedure A standard compaction test was carried to find the compaction characteristics of the soil as per IS 2720 part VII [18]. A total quantity of 3 kg air-dried soil with a particle size of 4.75 mm sieve passed was taken. The soil is mixed for suitable water content and compacted with an energy of 25 blows, 3 layers with a hammer weight of 2.6 kg and a free fall of 310 mm. The dry density and void ratio (e) were calculated using the following Eqs. 2 and 3

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γbulk 1+w

(2)

Gγw −1 γd

(3)

γd = e=

where γbulk (kN/m3 ) is the bulk unit weight of soil with specific gravity, G and water content, w (%) and unit weight of water as γw (=9.81 kN/m3 ).

3 Results Compactions tests were carried out for two different soils namely CH and CI initially without any admixtures. The maximum dry unit weight of CH and CI soils was 17.90 and 19.26 kN/m3 with optimum moisture content(OMC) as 16.03 and 15.16%, respectively (Fig. 1). The void ratio calculated using Eq. 3 for CH and CI soils was 0.38 and 0.34, respectively, for maximum dry unit weight.

3.1 Compaction Behaviour of CH and CI Soils CR is mixed with the soil in various proportions say 10, 15, 20, 30, 40 and 50% by weight, and compaction tests were carried out. From the graph (Fig. 2), it is clearly visible that the curve is shifting to the left upper side, which indicates the reduction in OMC and an increase in maximum dry density [19]. Due to the lower absorption nature of the CR, the OMC reduces. The range for high swell and shrink potential for both soil types changes with an increase in the percentage of CR. The reduction in void ratio explains us the change in the range of wet and dry of the optimum side. Fig. 1 Compaction characteristics of soil alone

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Fig. 2 Compaction characteristics of modified clay

Fig. 3 Relation between void ratio and % CR

As the soil particles interlock with each other with the intrusion of CR, the void ratio reduces. Figure 3 shows the relationship between the various percentages of CR and the void ratio at maximum dry density. The void ratio values for homogenous/unmodified CH and CI soils are 0.66 and 0.34, respectively. Upon adding 10% of CR to the soil, it increased to 1.01 and 0.51 for CH and CI soils. On further addition of CR percentage beyond 10%, the void ratio decreases and reaches a value almost equal to the unmodified soil; the obtained results were similar to the results of Yadav and Tiwari [20].

3.2 Developed Equation A comparative graph was plotted for maximum dry unit weight and optimum moisture content for various proportions of CR. An equation was generated for highly

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Fig. 4 Max dry density and OMC for different percentages of CR

compressible clay and intermediate clay to determine the maximum dry density for any percentage of CR (Eqs. 4 and 5) obtained from Fig. 4. γd = 0.055C R + 13

(4)

γd = 0.033C R + 17

(5)

From the obtained equation, a comparison was made between the measured and predicted values (Fig. 5). For CH soil, R2 value is 0.95 which indicates a good correlation. However, for CI type of soil, the R2 value is 0.88, and it is also equal to 1. The main cause is due to the influence of water content and the mineralogical property of the soil and CR.

4 Conclusion A detailed experimental study was conducted to understand the compaction characteristics of CR in CH and CI. It is observed that with an increase in the percentage of CR, the maximum dry density increases and the optimum water content reduces; the same observation was observed by Yadav J. S and Tiwari S. K [10] and Al-Tabba et al., [8]. With a maximum of 10% CR, the soil shows better behaviour. An equation

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Fig. 5 Model generated

was developed to calculate the maximum dry density with various percentages of crumb rubber.

References 1. Lee JH, Salgado R, Bernal A, Lovell CW (1999) Shredded tires and rubber-sand as lightweight backfill. J Geotech Geoenvironmental Eng 125(2):132–141 2. Reddy SB, Krishna AM, Reddy KR (2018) Sustainable utilization of scrap tire derived geomaterials for geotechnical applications. Indian Geotech J 48(2):251–266 3. Seyed Moghaddas Tafreshi and Amirhossein Norouzi (2015) Application of waste rubber to reduce the settlement of road embankment. Geomech Eng 9(2):219–241 4. Khed VC, Mohammed BS, Nuruddin MF (2018) Effects of different crumb rubber sizes on the flowability and compressive strength of hybrid fibre reinforced ECC. IOP Conf Ser Earth Environ Sci 140(1) 5. Sofi A (2017) Effect of waste tyre rubber on mechanical and durability properties of concrete - a review. Ain Shams Eng. J. 1(1):1–10 6. Magdalena K, Maciej C (2017) Mechanical parameters of rubber-sand mixtures for numerical analysis of a road embankment. IOP Conf Ser Mater Sci Eng 245(5) 7. Hoppe EJ, Mullen WG (2004) Field study of a shredded-tire embankment in virginia. Virginia 8. Al-Tabbaa A, Blackwell O, Porter SA (1997) An investigation into the geotechnical properties of soil-tyre mixtures. Environ Technol (UK) 18(8):855–860 9. Wang FC, Song W (2015) Effects of crumb rubber on compressive strength of cement-treated Soil. Arch Civ Eng 61(4):59–78 10. Yadav JS, Tiwari SK (2016) Effect of inclusion of crumb rubber on the unconfined compressive strength and wet-dry durability of cement stabilized clayey soil. J Build Mater Struct 3:68–84 11. Ho M-H, Chan C-M (2010) The potential of using rubberchips as a soft clay stabilizer enhancing agent. Mod Appl Sci 4(10):122–131 12. Mahmoud G (2004) Shear strength characteristics of sand-mixed with granular rubber. Geotech Geol Eng 22(3):401–416 13. Amin S, An D, Abbas T, Asuri S (2018) Consistency limits and compaction characteristics of clays soils containing rubber waste. Proc Inst Civ Eng - Geotech Eng 1–34 14. Tajabadipour M, Marandi M (2017) Effect of rubber tire chips-sand mixtures on performance of geosynthetic reinforced earth walls. Period Polytech Civ Eng 61(2):322–334

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15. Ahirwar SK, Mandal JN ( 2017) Finite element analysis of embankment using tire crumb rubber. In: Indian Geotechnical Conference, 2017, vol 1, December, pp 14–16 16. Yadav JS, Tiwari SK (2017) A study on the potential utilization of crumb rubber in cement treated soft clay. J Build Eng 9(November):177–191 17. Sivapriya SV (2018) Stress-strain and penetration characteristics of clay modified with crumb rubber. Rev Fac Ing 28(49):65–75 18. Bureau of Indian Standards, IS: 2720 (Part VII-1980), Methods of test for soils, determination of water content dry density relation using light compaction. 2011, pp 1–16 19. Sivapriya SV, Charumathy N (2019) Effect of crumb rubber on inorganic and hifh compressible clay. Adv Mater Metall 1(1):159–169 20. Yadav JS, Tiwari SK (2017) Influence of crumb rubber on the geotechnical properties of clayey soil. Environ Dev Sustain 1–22

Design and Development of Low-Cost Medium Size Shake Table for Vibration Analysis R. B. Malathy, Govardhan Bhat, and U. K. Dewangan

Abstract The structural system’s vibration analysis plays a prime role in dynamic experiments as researchers attempt to study the effects of the variables that are responsive to the damage occurring in the structure. However, they require data acquisition of nearly a comprehensive-state of the structure and high manipulations. To analytically evaluate the structural behavior, vibration analysis can be worked out by statically establishing some horizontal inertia forces, on the basis of scaled ground accelerations. The structural parameters such as stiffness, mass, vibration signatures illustrated through frequencies, mode shapes, and stress–strain energies are thus identified. In setting this context, this paper discusses the development of a low-cost uniaxial shake table which can analyze any type of 3-D model that helps in detecting the inelastic behavior of the frames at a reasonable cost. The description of the test specimen, instruments, setup procedures, and results is also presented. Keywords Earthquake simulation · Low-cost shake table · LabVIEW · 3-D model · Structural response

1 Introduction It is an important approach to assess structures’ seismic performance using a shaking table test and also to study structural failure mechanisms of earthquake action. For marking various unlatched affairs related to the seismic behavior of the structures of mixed type, the shake table test was designed. These issues were drift and acceleration profiles along the height of the building, damage monitoring, and variation in drift R. B. Malathy · G. Bhat (B) · U. K. Dewangan (B) Civil Engineering Department, NIT Raipur, Raipur, India e-mail: [email protected] U. K. Dewangan e-mail: [email protected] R. B. Malathy e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_19

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limits for different performance levels and also story accelerations with high shaking intensity [1]. The equipment system as well as the controlling technologies of the shaking table is significantly enhanced with the passing years. The shake table of electromagnetic type is distinguished using the frequency’s broadband, wave shape of high-quality, and ease of controlling. Moreover, an electro-mechanical shaking table has a much larger load capacity than what it has. An analog to digital converter converts analog signals obtained from the motion of the specimen to the digital signal which is then fed to the computer for further analysis. The random vibration method reproducing power spectrum tests allows the software program to monitor and control the vibrations of the equipment precisely. Regress study is required for controlling the stability in algorithm and its convergence. The precision in the development of several apparatuses like acceleration, velocity, and displacement sensors and high-resolution cameras that allow easy collection and recording of the parameters is also mandatory. The vibration responses of the test specimens are also achieved through this study. Additionally, through the processing of the collected data, the relative primary dynamic structural behavior is achieved by specialized software. There are some substantial limitation in the test results due to influential factors such as the number of specimens chosen, testing time and the expenditure. The high inflating cost in the laboratory equipment and infrastructures in the field of earthquake geotechnical engineering in India undergoes greater challenges [2]. Hence, in order to determine the relevance between various influential factors and identifying an accurate method for conducting vibration tests, additional exploration is required. This study describes the process of configuring the software to the hardware parts of a shaking table for analyzing reduced-scaled structures, the design, and development of the same, and also tries to provide references for shaking table seismic test.

1.1 Literature Review A review of some of the recent developments of the shake table for earthquake simulation and damage detection in published articles is presented here. Many largescale shaking tables have been successfully established in various parts of the world since the 1940 s for simulating earthquakes. Most of them have been equipped with high speed and high torque motor. Che et al. [3] performed the scaled model shaking tests as well as its simulation analysis on subway structures of 1995 Hyogoken-nanbu earthquake for clarifying the dynamic response along with the dynamic forces which are shear earth pressure and lateral earth pressure acting on the structure. The strain due to bending produced in the center columns because of the horizontal and vertical input motions is also discussed based on the experimental analysis on the shake table. Arash Rezavani et al. [4] performed shaking table experiments on two small-scale moment resisting frames to study the pounding of adjacent buildings. The frames were subjected to both harmonic and seismic load excitations which thus helped in understanding the major reasons for damages in buildings during an earthquake. S. K.

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Prasad et al. [5] stated within their paper that a very economically developed manual shaking table can be made use of instead of a more sophisticated shaking table in order to perform model testing as it is the essential requirement of earthquake geotechnical engineering. The behavior of geotechnical facilities and their performance while an earthquake is taking place can be further understood with its help. Ye Xianguo et al. [6] conducted an analysis of a sophisticated 3-D frame model to study the earthquake responses of the chosen prototype building. The output obtained from the shaking table test with similarity transformation was used as input motion for the dynamic analysis. At the time of severe earthquakes, the bridges may suffer very high pounding damage due to the relative displacement between adjacent bridge structures. Bo Li [7] in his research has said that this relative displacement results in girder unseating. The main reason for the causes of relative displacement was found in the Spatial variation that is formed due to ground motions. The study was done with APS Model 400 Electro-Seismic unidirectional shake tables. Two shake tables each with a frequency range of 0–200 Hz are used. Bidur Kafle et al. [8] reported that shaking table experiments done provide the phenomena of the response of (“non-ductile”) the structures during earthquakes. Xilin Lu et al. [9] performed a shake table test on a tall building that had two towers located at two different heights. They were connected to each other by trusses, and it was realized that the connecting trusses had more stiffness to withstand the towers. Thus, the connected trusses resist the lateral forces to withstand the earthquakes. Kheng Teh [10], G. MadhaviLatha et al. [11] have said that shaking table research provides important insight into the process liquefaction, foundation response, postearthquake settlement soil–structure interaction, and lateral earth pressure problems. Xu Weixiao et al. [12] introduced a new structural system known as a stepped wallframe structure in their study, to solve the bottom yielding in RC frames, which had been occurring widely during earthquakes as that of Wenchuan and Yushuin China. An ordinary RC frame model of 1/5 scale and also a stepped wall-frame model is subjected to a shake table experiment in order to undergo a study on the seismic behavior. According to the test results, it is concluded that the seismic performance of stepped wall-frame structures is superior to ordinary RC frames. Andrew Boon Kheng Teh et al. [13] designed and developed a seismic shaking table to analyze the performance of elastomeric bearings against earthquake. The method used was to generate the same ratio of analog voltage signals to that of the original earthquake displacement data. In order to drive the shake table in accordance with real-time recorded earthquake displacement data, a pneumatic cylinder uses Arduino microcontroller. Seismic signals with greater accuracy were reproduced through the proposed system. P. Kulkarni et al. [14] in their paper used horizontal shake table analysis of deflection to find the stability of a three-story building in various conditions. Designing of shake table is done considering the factors and specifications of the earthquake produced. A.N Swaminathan et al. [15] proposed the concept of shake table provides stability on the application of it in the structure against earthy movements. Tiwari Darshita et al. [16] stated that for more appropriate study of the earthquake, well-equipped laboratory facilities are required. To study the behavior of

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structures, single translation (horizontal) degree of freedom, shaking tables are good for laboratory testing. Based on these points, an effort is to fabricate a low-cost shake table having specific classification for testing models in Earthquake Engineering Laboratory along with an instrumentation setup having LVDT.

2 Specification, Mechanism, and Kinematic Arrangement The schematic diagram of the mechanical arrangement of the shake table is shown in Fig. 1.

2.1 Main Components of Shake Table 2.1.1

Motor

It usually has two basic parts, an outer stationary stator having multiphase coils supply which uses alternating current to produce a rotatory magnetic field, and to the relative mechanical rotation of the output shaft, an insider rotor attached to the output shaft for producing a rotating magnetic field [17]. Pulling or pushing the poles of the two magnetic fields along, the stator as well as the rotor rotating magnetic fields must be maintaining synchronization for the production of average torque. Pulsating or non-average torque will be produced by unmatched rotating magnetic fields. Using DC or AC electrical windings, by using permanent magnets, the magnetic poles of the rotor magnetic field are being produced.

2.1.2

Pulley

Two pulleys common to a belt are identified by a belt and pulley system. This lets the torque, mechanical power, and speed to get transmitted across axles. If the pulleys have different diameters, a mechanical advantage is found. A belt drive system is used to reduce the jerk produced during operation on the motor as compared to other torque transmission systems. However, a belt drive may slip during the performance

Fig. 1 Schematic diagram of mechanical arrangement

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resulting in the reduction of speed up to 3:1. Hence two driven pulley each of 12inch diameter and 4-inch diameter is provided to enhance the torque resulting in the reduction in power loss.

2.1.3

Shaft

The shaft is a mechanical device used to transmit power from one part of the system to others. It is circular in diameter with uniform or stepped cross-section. A shaft of 35 mm stepped from both the ends and simply supported from UC bearings is provided. It is made of EN19 grade steel with high tensile to resist high shocks at the time of operation. Thus, at one end of the system, a pulley of 12-inch diameter is connected followed by a crank at the other end.

2.1.4

Crank

A crank is a mechanical part which is able to transform rotary motion into reciprocating motion or vice versa. Basically, it is having one offset axis from its center axis, and when we applying reciprocating motion to its offset axis, then it transforms the motion into circular or rotational motion, or vie versa. Here, I made this part from the Mild Steel disk plate of Dimension 320 mm Diameter and 25 mm thick. And at one of the end, I welded a bush which is made from mild steel and has a bore of 35 mm and a key way of 12 mm so that whole crank can be attached to convert rotary motion into reciprocatory motion without any slip while transmitting motion from Pulley to Shaft and from Shaft to Crank.

2.1.5

Connecting Rod

A rigid rod is termed as a connecting rod when its both ends are connected to a mechanism of a crankpin (or crankshaft) and piston to form a mechanism that converts reciprocating motion to rotary motion or vice versa. In my project, I use two bushes in the ends of connecting rod, and each bush is fitted under the cavity made from machining in mild steel roll of Dimension (Outer Dia. 100 mm and thickness 70 mm) with two bearings of (Inner Dia. (ID) 20 mm and Outer Dia. (OD) 54 mm) for smoothing the motion. And this rod is of Dimension (OD 30 mm X 1200 mm length).

2.1.6

Shake Table

Shake table frames are made from Structural Steel grades of ISI standards which consists of the following three frames:

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• Main Frame: This frame is at the top and consist of 6 wheels in its bottom, each wheel consist of 2 bearings which is fitted in the cavity of the wheel, Nylon is the material used to create the wheel and in between the wheel, we did V Groove cutting so that wheel can slide in between the guide frame, and due to nylon and bearings, the friction between the wheel and frame is very less. For making frame, we use a square tubular section of dimension 50X50X3mm. The total area of the bed is 3-3000 × 2500 mm. • Guide Frame: This frame is in the middle of Main Frame and Base frame, and it is made with a square tubular section of dimension 60 × 60 × 4 mm, which is diagonally inclined from base frame and welded from the corner with an angular section of dimension 60 × 60 × 6 mm • Base Frame: This frame is constructed to support the whole structure and give proper strength and stability while putting loads for testing. Due to its eight columns, the load is equally balanced and working under the line of action which gives this frame extra stability under high frequency of testing. This frame is built from 60X60X6mm angles which is also ISI grade structural steel. 2.1.7 1. 2. 3. 4.

Other Component Used

Nuts and Bolts: M20 × 2.5 × 120 (High Tensile) Nuts and Bolt: M12 × 1.75 × 80 (High Tensile) Plywood: 8 × 4 × 18 mm thick (High density) Welding Rods

3 Components of the Hardware of a Motorized Shaking Table—Setup 3.1 Shaking Table and Driving Devices Figure 2 shows the various components of the proposed shaking table system. The moving parts act like the actuators of the control unit. For simulating the vibration environment, they are like the physical basis and carrier. A low-cost shaking table comprises of table body, supporting device, the driving motor, accelerometer sensor, Arduino, LabVIEW, etc. Thus, the precisely designed shaking table is applicable to simulate earthquake vibration accurately on a reduced-scale. It could also fulfill the relevant technical indicator specifications required by the test. As it is known, the natural vibration of the reduced-scale structure at each step is more than the prototype structure; the upper limit of the working frequency of the designed shaking table is kept less than 5 Hz, and the lower limit more than 1 Hz. The accuracy in frequency is maintained upto 0.01 Hz. Hence, meeting the requirements for the low-cost shaking table is thus

Design and Development of Low-Cost Medium Size Shake Table … Variable Frequency Drive

Inducon Motor

LABVIEW(Monitorin g and controlling)

Aurdino

197 Shaking Table(Test Specimen)

Gyro Sensor

Fig. 2 Elements used in shaking table

feasible. The motor can achieve the existing academic achievement of the event. The seismic simulation can be achieved by keeping the amplitude–frequency fluctuation range of the shaking table within ±3 dB. The motor, table body, and the supporting device are the key elements of the shaking body. The shake table should provide enough strength and stiffness to install the test specimen, for the seismic test. The table is calibrated to withstand intrinsic vibration and hence, the working frequency range is kept less than 20 Hz. The size of the table limits the maximum dimension of the structural test specimen. The working platform, the weight of the test specimen, and the working frequency range determine the dead weight of the table body. It is recommended that the ratio between the weight of the test specimen and the weight of the table body is kept less than 2 times. The total load-bearing capacity of the shaking table foundation should be 10–20 times more than the moving parts or the exciting force. Thus, the high-frequency requirement in the system can be improved, and impacts from surrounding buildings or other equipment can be reduced by this arrangement. The shaking table setup vibrates uniaxially so as to read the vibration of the seismic test. The test specimen should weigh within 100 kg, so that it is more feasible and economical. In order to achieve accuracy in the seismic test experiment on a reducedscale, the maximum acceleration should not be less than 2 g under full load, where the maximum displacement can be controlled in ±150 mm.

3.2 Data Acquisition Unit 3.2.1

Sensor

The MPU motion sensor is calibrated before applying to the seismic test and marked with indicators such as sensitivity, frequency response curve, linear dynamic features, and transverse susceptibility. The necessities are as follows: sensitivity error is ±0.5%; sensitivity stability is ±0.5%/year; frequency response and relative motion sensitivity change are −2%; sensitivity change is ±4%; and strain sensitivity is

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0.001 g/με. By using a sine wave as the calibration excitation signal, precision could be achieved in order to calibrate a sensor, and frequency bandwidth can be obtained with random waves.

3.2.2

LabVIEW

A medium for the control of the equipment was needed in order to read the data into a suitable environment for distance learning. For a high level of control and flexibility, LabVIEW is chosen. LabVIEW is a programming language like C, C++, and Java. Graphics and logic diagrams are used instead of lines of code with programming objects such as loops to produce the desired results. LabVIEW is referred to as a graphical programming language or “g” programming. In LabVIEW commands are replaced with modules which makes this work bench much easier than other programming softwares. Due to the ability to drop dials, switches, buttons, etc., directly onto the LabVIEW front panel, the LabVIEW provides a more intuitive environment for creating controls. This property allows us to construct an easy-to-use, professional-looking interface, to plot the output, and to easily manage the monitoring and controlling process. The programs made are called virtual instruments or vi’s.

3.2.3

Arduino

Arduino is an open-source platform single-board microcontroller. It is used for developing digital devices and interactive objects. The boards comprise of digital and analog input/output (I/O) pins. These pins can be interfaced with various breadboards as well as with other circuits. Serial communications interfacing is allowed by it which also includes Universal Serial Bus (USB) cable. In this project, the Arduino Nano is used for measuring the vibration of the specimen.

3.2.4

Specification of System Design

Shaking Direction—Uniaxial horizontal motion Base frame—10 × 7 feet Driving unit—4 × 1.5 feet Pulley—12 inch Ac motor—1440 rpm 2hp Small pulley—4 inch

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4 Procedure Variable Frequency Drive shown in Fig. 3 is used for giving input to the system. The electric motor is driven by ramping down the frequency to run at full speed; thus, the shake table does not require an electric motor. The input to the VFD is a single phase, but a three-phase output is obtained. The VFD takes the AC input source and converts it into the DC. It has an inverter inside which gives the output of 440 V. The above Fig. 3 show the VFD used in our project. The specifications of the VFD are as follows: • Input: Uin 1~AC, 208–240 mV, 50/60 Hz, 8.3 A • Output: 3~AC, 0 – Uin , 0–320 Hz, 3.7 A • Power: 0.75 kw, 230 V/1HP, 230 V The frequency from the VFD is given to the three-phase induction motor. This motor can be driven in both clockwise and anticlockwise directions. The motor moves in the clockwise direction when the positive frequency is applied specifically. Transistors or insulated-gate bipolar transistors (IGBTs) are driven by the alternative current drives. This is achieved using the PWM techniques in order to generate the proper root-mean-square (RMS) voltage levels. Thus, the output frequency and voltage are obtained by controlling and varying the width of the pulses. Figure 4 shown below is the three-phase induction motor attached to Variable Frequency Drive to give input. The following are the specifications of the induction motor used [17]. • Input: 230 V • RPM: 1440, 2HP • Output: 440 V This motor is connected to the shaking table. As the motor rotates, it causes the forward and backward motion of the table [17]. This causes the displacement of 25 cm in both the back and forth movement directions. Fig. 3 Variable frequency drive

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Fig. 4 Three-phase induction motor with VFD

The motor starts moving and causes the shaking table to move. Tables have the acceleration equivalent to the 1/3rd RPM of the three-phase induction motor. This is due to the pulley attached to the table. The object will be placed above the specimen. As the shaking table starts moving in the back and forth direction, the object also moves along with it. The vibration and acceleration induced in the specimen are recorded and analyzed. The MPU sensor is attached to the specimen which provides the feedback of the motion. As the feedback is received, the graphical data is displayed in the LabVIEW using Arduino. The Fig. 5a, b below shows the front panel and the block diagram of the LabVIEW program done [18] (Fig. 6).

5 Result Figure 6 is the responding graph of the shake table depicting the acceleration created in the table taken in LabVIEW. The graph obtained depends on the input frequency given by the variable frequency drive (VFD). The testing of the shaking table is done from 1 Hz to 5 Hz frequency. These data are sent to the cloud using ESP8266 and UBIDOTS as the server where all the data are received in the UBIDOT page.

6 Conclusion A shaking table is developed to check the response of the earthquake on the specimen. The vibration to the table is provided using the three-phase induction motor. The frequency is governed by using the variable frequency drive (VFD). The table shakes and accelerates according to the frequency. The acceleration responses and displacement responses are gained and analyzed in the LabVIEW and updated in the

Design and Development of Low-Cost Medium Size Shake Table …

(a)

(b) Fig. 5 Block diagram and front panel on LabVIEW program Fig. 6 Responding graph of the shake table

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UBIDOT page. The study of the shaking table gives the knowledge of the behavior of the specimen during the earthquake. Shake tables can be used to check the stability of the structure by producing ground motions similar to that during earthquake.

References 1. Beyer K, Tondelli M, Petry S, Peloso S (2015) Dynamic testing of a four-storey building with reinforced concrete and unreinforced masonry walls: prediction, test results, and data set. Springer Science, Business Media Dordrecht 2. Unni KG, Beena KS, Mahesh C (2018) Development of 1-D shake table testing facility for liquefaction studies. Journal 99:423–432 3. Che A, Iwatate T (2002) Shaking table test and numerical simulation of seismic response of subway structures. Structures Under Shock and Impact VII, ISBN 1-85312-911-9 (2002) 4. Rezavandi A, Moghadam A (2004) Using shaking table to study different method of reducing effects of buildings pounding during earthquake. In: 13th World Conference on Earthquake Engineering, Vancover, Canada 5. Prasad SK, Towhata I, Chandradhara GP, Nanjundaswamy P (2004) Shaking table tests in earthquake geotechnical engineering. Curr Sci 87(10) 6. Xianguo Y, Jiaru Q, Kangning L (2004) Shaking table test and dynamic response prediction on an earthquake-damaged RC building. Earthq Eng Eng Vibr 3:205–214 7. Li B, Nawawi C (2014) Experimental investigation of inelastic bridge response under spatially varying excitations with pounding. Eng Struct https://doi.org/10.1016/j.engstruct.2014.08.012 8. Lam N, Kafle B, Wilson J, Gad EF, Patole-cole V (2009) Shaking table tests on strength degradation behavior. Annual Technical Conference of the Australian Earthquake Engineering Society, New Castle, New South Wales 9. Lu X, Chen L, Zhou Y, Huang Z (2009) Shaking table model tests on a complex high-rise building with two towers of Di. Event height connected by trusses. Struct Des Tall Spec Build 18(7):765–788 10. Andrew BKT, Chitturi V (2015) Design and development of a seismic shaking table for evaluation and analysis of the performance of elastomeric bearing. In: 2015 IEEE Student Conference on Research and Development (pp 111–116). https://doi.org/10.1109/scored.2015.7449306 11. Latha GM, Karpurapu R, Krishnaswamy NR (2006) Experimental and theoretical investigations on geocell-supported embankments. Int J Geomech 6:1(30). https://doi.org/10.1061/(asc e)1532-3641(2006)6:1(30) 12. Weixiao X, Jingjiang S, Weisong Y, Ke D (2014) Shaking table comparative test and associated study of a stepped wall-frame structure. Earthq Eng Eng Vibr 13(3) 13. Kheng Teh AB, Venkatratnam C (2015) Design and development of a seismic shaking table for evaluation and analysis of the performance of elastomeric bearing. In: IEEE student conference on research and development (scored), 978-1-4673-9572-4/15 ©2015 Ieee 14. Kulkarni AP, Sawant MK, Shinde-Patil MS (2107) Experimental study using earthquake shake table. Int Res J Eng Technol (IRJET) e-ISSN: 2395 -0056 04(04) 15. Swaminathan AN, Sankari P (2017) Experimental Analysis of earthquake shake table. Am J Eng Res (AJER) 6(1)148–151 16. Darshita T, Patel A (2014) Development and instrumentation of low cost shake table. Int J Sci Res 3(6)

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17. Hiren G, Patel HG, Raval M (2018) Closed-loop control of flow under the influence of varying temperature in air blower system using and VFD. Proceedings of the International Conference On Intelligent Systems and Signal Processing 18. Hu C, Gao M, Chen Z, Zhang H, Liu S (2010) Magnetic analysis and simulations of a selfpropelled capsule endoscope. In: 11th International Thermal, Mechanical & Multi-Physics Simulation, and Experiments in Microelectronics and Microsystems

Experimental Investigation on Suitability of Sea Water for Concrete Mix K. Srinivasan and E. Arunachalam

Abstract This paper explored the results of experimental investigations on the effect of sea water on mechanical properties of concrete. It is well-known that the make use of sea water in concrete mix does not substantially diminish the concrete strength properties but may lead to corrosion of reinforcement in some certain cases. In this study, concrete compressive strength of 24.22 MPa was used. The concrete mix was cast using fresh water and sea water and tested after 7 and 28 days of curing for determining the mechanical properties of concrete. Findings of the test results show enhanced mechanical properties of concrete using sea water when compared to that of concrete using fresh water. Keywords Compressive strength · Flexural strength · Fresh water · Mechanical properties · Sea water · Water–cement ratio

1 Introduction The most common man made construction material is concrete. Concrete is made up of cement, aggregates and water. Cement plays a vital role as binding agent. The concrete strength mainly depends on the mix ratio, method of curing, W/C ratio, aggregates and cement types. Water plays an imperative role on concretes participation in chemical reaction with cement. Presently the Potable water is flattering a scarce commodity on Earth with moment in time. Utilization of seawater in concrete for mixing would affect the setting time of concrete, for which suitable chemical admixtures should be incorporated in concrete suggested by Kaushik and Islam [1]. The outcome of using seawater for mixing and curing the concrete showed signs of loss in compressive strength of about 10% when compared with plain water was K. Srinivasan (B) · E. Arunachalam Department of Civil Engineering, Annamalai University, Chidambaram, India e-mail: [email protected] E. Arunachalam e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_21

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206 Table 1 Concrete mix proportions

K. Srinivasan and E. Arunachalam Quantity in kg/m3

S. No.

Concrete materials

1

53 Grade cement

292

2

Fine aggregate

612

3

Coarse aggregate

4

Water

1348 145

Fig. 1 Concrete mix

examined by Islam, Md Islam, Md Al-Amin and Md Islam [2]. The compressive strength of concrete batches cast using sea water and cured using fresh exhibit an increase in strength even after 90 days of curing was reported by Olutoge and Amusan [3]. Hence, sea water can be used as an alternative for potable water in construction activities. The comparison study on concrete cast and cured with salt water and fresh water concluded that there was no lessening in compressive strength while using salt water in concrete mixing and curing. The concept of using salt water in region having salty bore water was suggested by Gawande, Deshmukh, Bhagwat, More, Nirwal and Phadatare [4]. Physical worsening initiated by crystallization of soluble salts in pores of the concrete promotes further breakdown in concrete Shetty [5]. The practice of using sea water in concrete was done by Swati Maniyal and Ashutosh Patil [6]. The effects of using sea water in mixing and curing of concrete on mechanical properties were investigated by Falah M. Wegian [7]. In this study the authors compared the author reported that concretes mixed and cured in sea water have higher compressive, tensile, flexural strengths of concrete mixed and cured in seawater and then concretes mixed and cured in fresh water in the early ages at 7, 14 and 28 days. The mix proportions of concrete used in this study is as shown in Table 1. The mix ratio of 1:2.09:4.61:0.5 with a strength of 24.22 MPA was adopted for the investigation. A total of 20 cube specimens, 20 cylinder specimens and 20 prism specimens were cast and tested to determine the mechanical properties.

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2 Preparation of Test Specimens The concrete mix was prepared shown in (Figs. 1, 2, 3) using tilting type concrete mixer machine in terms of batches, first batch of concrete using fresh water and second batch of concrete using sea water. Placing of concrete was also done in batches. Each batch consists of 10 cubes, 10 cylinders and 10 prisms. Steel moulds were used to cast the specimens and vibrating table was used for uniform compaction. All the test specimens were remoulded after a day and the test specimens were cured in water for 7 days and 28 days before the specimens being tested.

2.1 Test Procedure The cubes and cylinders were tested in compression testing machine of capacity 2000 kN. The cubes and cylinders were loaded in the compression testing machine until failure in order to find the ultimate compressive strength of cubes and cylinders. The prisms were tested under two-point loading in a loading frame. The mid span deflection was measured using a dial gauge and the deflection corresponding to the maximum load was noted and the modulus of rupture (Flexural strength) was calculated. Fig. 2 Placing of concrete

Fig. 3 Curing of test specimens

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3 Results and Discussion A total of 20 cubes, cylinders and prisms were cast and tested after 7 and 28 days is presented in Tables 2, 3, 4, 5, 6, 7. The comparison of mechanical properties of concrete test specimens such as compressive strength and flexural strength for concrete using fresh water and sea water are also presented and discussed. Table 2 Comparison of cube compressive strength of concrete after 7 days Specimen No

Compressive strength after 7 days using fresh water in Mpa

Compressive strength after 7 days using sea water in Mpa

Percentage increase in strength in %

1

19.36

21.66

10.62

2

20.22

21.09

4.13

3

20.04

21.35

6.14

4

18.06

20.46

11.73

5

20.88

21.78

4.13

Average

19.71

21.27

7.35

Table 3 Comparison of cube compressive strength of concrete after 28 days Specimen No

Compressive strength after 28 days using fresh water in Mpa

Compressive strength after 28 days using sea water in Mpa

Percentage increase in strength in %

1

24.22

27.47

11.83

2

24.03

26.33

8.74

3

23.88

27.31

12.56

4

24.12

27.35

11.81

5

24.08

26.98

10.75

Average

24.07

27.09

11.14

Table 4 Comparison of cylinder compressive strength of concrete after 7 days Specimen No

Compressive strength after 7 days using fresh water in Ma

Compressive strength after 7 days using sea water in Mpa

Percentage increase in strength in %

1

15.49

17.33

10.62

2

16.18

16.87

4.13

3

16.03

17.08

6.14

4

14.45

16.37

11.73

5

16.70

17.42

4.13

Average

15.77

17.01

7.35

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Table 5 Comparison of cylinder compressive strength of concrete after 28 days Specimen No

Compressive strength after 28 days using fresh water in Mpa

Compressive strength after 28 days using sea water in Mpa

Percentage increase in strength in %

1

18.47

19.88

7.09

2

17.80

19.06

6.61

3

18.03

20.90

13.73

4

18.36

19.68

6.71

5

16.98

19.80

14.24

Average

17.93

19.86

9.68

Table 6 Comparison of flexural strength of concrete after 7 days Specimen No

Compressive strength after 7 days using fresh water in Mpa

Compressive strength after 7 days using sea water in Mpa

Percentage increase in strength in %

1

3.22

3.31

2.72

2

2.79

3.09

9.71

3

3.08

3.33

7.51

4

3.15

3.35

5.97

5

2.88

3.06

5.88

Average

3.02

3.23

6.36

Table 7 Comparison of flexural strength of concrete after 28 days Specimen No

Compressive strength after 28 days using fresh water in Mpa

Compressive strength after 28 days using sea water in Mpa

Percentage increase in strength in %

1

5.01

5.67

11.64

2

4.61

5.71

19.26

3

4.39

5.32

17.48

4

4.66

5.19

10.21

5

4.51

5.29

14.74

Average

4.64

5.44

14.67

3.1 Effect of Sea Water on Compressive Strength of Cubes It is observed from the Tables 2 and 3 and Figs. 4 and 5 that the average compressive strength of concrete cubes casted in fresh water and sea water at 7 days was found to be 19.71 N/mm2 and 21.27 N/mm2 , respectively. The average compressive strength of concrete cubes casted in fresh water and sea water at 28 days was found to be 24.07 N/mm2 and 27.09 N/mm2 , respectively.

K. Srinivasan and E. Arunachalam

Compressive Strength in Mpa

210

25 20

21.66 19.36

20.22

21.09

20.04

21.35

20.46 18.06

20.88

21.78

15 10 5 0

1

2

3

4

5

Cube Compressive Strength after 7days using Fresh Water in MPa Compressive Strength after 7days using Sea Water in MPa

Compressive Strength in Mpa

Fig. 4 Comparison of cube compressive strength of concrete after 7 days

28

27.47

27

27.31

27.35

26.98

26.33

26 25 24

24.22

24.03

23.88

24.12

24.08

23 22

1 2 3 4 5 Cube Compressive Strength after 28days using Fresh Water in MPa Compressive Strength after 28days using Sea Water in MPa

Fig. 5 Comparison of cube compressive strength of concrete after 28 days

The percentage increase in cube compressive strength of cubes using sea water was found to be 11.14% when compared to that of concrete cubes made using fresh water.

3.2 Effect of Sea Water on Compressive Strength of Cylinders It is observed from the Tables 4 and 5 and Figs. 6 and 7 that the average compressive strength of concrete cylinders casted in fresh water and sea water at 7 days was found to be 15.77 N/mm2 and 17.01 N/mm2 , respectively. The average compressive

Compressive Strength in Mpa

Experimental Investigation on Suitability …

20.00

17.33 15.49

16.1816.87

211

17.08 16.03

15.00

16.37 14.45

17.42 16.70

10.00 5.00 0.00

1

2

3

4

5

Cylinder Compressive Strength after 7days using Fresh Water in MPa Compressive Strength after 7days using Sea Water in MPa

Compressive Strength in Mpa

Fig. 6 Comparison of cylinder compressive strength of concrete after 7 days

25.00

20.00

19.88 18.47

19.06 17.80

20.90 18.03

19.68 18.36

19.80 16.98

15.00 10.00 5.00 0.00

1 2 3 4 5 Cylinder Compressive Strength after 28days using Fresh Water in MPa Compressive Strength after 28days using Sea Water in MPa

Fig. 7 Comparison of cylinder compressive strength of concrete after 28 days

strength of concrete cylinders casted in fresh water and sea water at 28 days was found to be 17.93 N/mm2 and 19.86 N/mm2 , respectively. The percentage increase in cylinder compressive strength of cylinders using sea water was found to be 9.68% when compared to that of concrete cylinder made using fresh water.

3.3 Effect of Sea Water on Flexural Strength of Prisms It can be inferred from the Tables 6 and 7 and Figs. 8 and 9 that the average flexural strength of concrete prisms casted in fresh water and sea water at 7 days was found

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Flexural Strength in MPa

3.5

3.22 3.31

3.09

3.08

3.33

3.15

3.35

2.79

3

2.88

3.06

2.5

2 1.5 1 0.5 0

1

2

3

4

5

Flexural Strength after 7days using Fresh Water in MPa Flexural Strength after 7days using Sea Water in MPa Fig. 8 Comparison of flexural strength of concrete after 7 days

Flexural Strength in MPa

6

5.71

5.67 5.01

5

4.61

5.32 4.39

5.29

5.19 4.66

4.51

4

5

4 3 2

1 0

1

2

3

Flexural Strength after 28days using Fresh Water in MPa Flexural Strength after 28days using Sea Water in MPa Fig. 9 Comparison of flexural strength of concrete after 28 days

to be 3.02 N/mm2 and 3.23 N/mm2 respectively. The average flexural strength of concrete prisms casted in fresh water and sea water at 28 days was found to be 4.64 N/mm2 and 5.44 N/mm2 , respectively. The percentage increase in flexural strength of prisms using sea water was found to be 14.67% when compared to that of concrete prisms made using fresh water.

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4 Conclusions Experimental investigation to enumerate the effectiveness of using sea water in M-20 grade concrete of mix ratio 1:2.09:4.61:0.5 the cubes, cylinders and prisms were cast in fresh water and sea water and tested at different curing periods of 7 and 28 days as per the relevant IS code of practice. From the strength test results the succeeding conclusions were made: 1. The average compressive strength of concrete cubes casted in fresh water and sea water at 7 days was found to be 19.71 N/mm2 and 21.27 N/mm2 , respectively. 2. The average compressive strength of concrete cubes casted in fresh water and sea water at 28 days was found to be 24.07 N/mm2 and 27.09 N/mm2 , respectively. 3. The average compressive strength of concrete cylinders casted in fresh water and sea water at 7 days was found to be 15.77 N/mm2 and 17.01 N/mm2 , respectively. 4. The average compressive strength of concrete cylinders casted in fresh water and sea water at 28 days was found to be 17.93 N/mm2 and 19.86 N/mm2 , respectively. 5. The average flexural strength of concrete prisms casted in fresh water and sea water at 7 days was found to be 3.02 N/mm2 and 3.23 N/mm2 , respectively. 6. The average flexural strength of concrete prisms casted in fresh water and sea water at 28 days was found to be 4.64 N/mm2 and 5.44 N/mm2 , respectively. 7. The percentage increase in cube compressive strength of cubes using sea water was found to be 11.14% when compared to that of concrete cubes made using fresh water. 8. The percentage increase in cylinder compressive strength of cylinders using sea water was found to be 9.68% when compared to that of concrete cylinder made using fresh water. 9. The percentage increase in flexural strength of prisms using sea water was found to be 14.67% when compared to that of concrete prisms made using fresh water.

References 1. Kaushik SK, Islam S (1995) Suitability of sea water for mixing structural concrete exposed to a marine environment. Cement Concr Compos 17(3):177–185 2. Islam M, Md Islam S, Md Al-Amin, Md Islam M (2012) Suitability of sea water on curing and compressive strength of structural concrete. J Civ Eng (IEB) 40(1):37–45 3. Olutoge FA, Amusan DM (2014) The effect of sea water on compressive strength of concrete. Int J Eng Sci Invention 3(7):23–31 4. Gawande1 S, Deshmukh Y, Bhagwat M, More S, Nirwal N, Phadatare A (2017) Comparative study of effect of salt water and fresh water on concrete. Int Res J Eng Technol (IRJET) 4(4):2642–2646 5. Shetty MS (2014) Concrete technology- theory and practice textbook

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6. Maniyal S, Patil A (2015) An experimental review of effect of sea water on compressive strength of concrete. IJETAE 5(3):199–203 7. Wegian FM (2010) Effect of seawater for mixing and curing on structural concrete. IES J Part A: Civ Struct Eng 3(4):235–243

Assessment of Emerging Contaminants in a Drinking Water Reservoir Riya Ann Mathew and S. Kanmani

Abstract Urbanisation and changes in lifestyle have resulted in the release of emerging contaminants (ECs) into the environment. The present study has assessed the ECs in a drinking water reservoir in Chennai, India using LC-MS/MS. Of the 138 ECs screened, it was observed that 2,4-dichlorophenoxyacetic acid (2,4-D), a herbicide, had the highest concentration of 0.13 mg/L followed by 1,2 Dibromo 3 chloro propane (DBCP), a pesticide, with a concentration of 0.12 mg/L, which is 600 times higher than the USEPA regulatory standard. Two pharmaceuticals carbamazepine, an antiepileptic, and N-methylphenmacetin, an anti-inflammatory drug, were found at concentrations of 0.003 mg/L and 0.005 mg/L, respectively. The risk quotient for predominant ECs was computed. Endrin had the highest risk quotient followed by chlorpyrifos. The landuse map of the study area prepared using GIS showed 91.901 km2 of vegetation area. The presence of pesticides, herbicide and insecticide can be attributed to agricultural activities in the catchment area of the reservoir while the polychlorinated biphenyl and benzo(a)pyrene in water could be due to industrial activities in the vicinity. The pharmaceuticals in water might be due to leakage in sewers or discharge of wastewater from residential communities. Keywords Emerging contaminants · PPCPs · LC- MS/MS · Risk quotient · Landuse map

1 Introduction Water quality is declining due to the presence of micropollutants in water. These pollutants may undergo transformation to by-products which may have toxicity R. A. Mathew (B) Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77204, USA e-mail: [email protected] S. Kanmani Centre for Environmental Studies, Anna University, Chennai 600025, Tamil Nadu, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_22

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different from the parent compound. But the fate and occurrence of many of these transformation products still remain elusive. Recent studies have identified several classes of emerging contaminants in the water bodies worldwide using advanced analytical techniques. The United States Geological Survey (USGS) defines an emerging contaminant (EC) as any synthetic or naturally occurring chemical or microorganism that is not commonly monitored in the environment but has the potential to enter the environment and cause unknown or suspected adverse ecological and (or) human health effects. Changes in lifestyle and urbanisation have resulted in the release of ECs into the environment, which ends up polluting the water bodies. Sources of ECs are compounds such as pharmaceuticals and personal care products (PPCPs), contrast media, plasticizers, food additives, wood preservatives, laundry detergents, surfactants, flame retardants, pesticides, natural and synthetic hormones, and a few disinfection by-products (DBPs) [1]. The ECs make their way into the environment through several pathways. PPCPs, DBPs and other chemicals discharged from residential communities, industries, hospitals and health care centres may enter the surface water bodies through surface runoff and leaks in sewer. The effluent runoff from livestock and poultry farms may contain pesticides, antibiotics and hormones [2]. Analytical technique for the determination of PPCPs includes high resolution mass spectrometers such as liquid chromatography–tandem mass spectrometry (LCMS/MS), Gas Chromatography Mass Spectrometry (GC-MS), quadrapole Time of Flight (ToF) and Orbitrap technology are popular instruments due to their high sensitivity, accuracy and throughput. The disadvantage of GC analysis is that it requires prior derivatisation step, usually using highly toxic compounds and may result in thermal degradation of product. On the other hand, LC does not require prior derivatisation. Due to the high boiling points of most ECs, LC-MS/MS is more widely used [3, 4]. The active pharmaceutical ingredient in water consists of antibiotics, analgesic, antiepileptic, non-steroidal anti-inflammatory drugs which could impart antimicrobial resistance to microorganism present in water resulting in microbes with antibiotic resistant genes which can also be genetically transferred to the progeny. A study in Bangladesh on antimicrobial resistance of bacteria causing urinary tract infection found uropathogens resistant to 13 antibiotics [5]. Several studies established the presence of pharmaceuticals in water bodies worldwide [6–11]. Several other studies have reported the presence of organochlorine pesticides in surface water [12, 13]. Perchlorate, used as an oxidizer in rocket propellent and fireworks, was found in groundwater and surface water samples with highest concentrations of 7.27–7.69 mg/L and drinking water had a concentration of 0–0.00039 mg/L [14, 15]. Some ECs are carcinogenic, teratogenic and genotoxic. It can affect the endocrine system of humans and aquatic animals. They can be persistent, bio-accumulative and toxic at even low concentrations. Extensive ecotoxicological studies are required to understand the toxic effect of contaminants on the environment. Ecotoxicological risk characterisation based on risk quotient (RQ) is calculated as the ratio of Maximum Environmental Concentration (MEC) to the Predicted No Effect Level (PNEC). The

Assessment of Emerging Contaminants in a Drinking Water Reservoir

217

PNEC is calculated by applying assessment factors to the acute or chronic toxicity [6, 16–19]. Hence the present study has attempted to provide an evidence for the presence of ECs in a drinking water reservoir and calculate the RQ of ECs for aquatic organisms.

2 Methodology The methodology of the study for the analysis of ECs in a drinking water reservoir of Chennai and computation of risk quotient for aquatic organisms is given below.

2.1 Study Area The study area is a drinking water reservoir in Chennai, Tamil Nadu, India as shown in Fig. 1. The reservoir supplies water to two water treatment plants (WTP) in Chennai and supports aquatic life. The treated water from WTP is distributed to the city for water supply. Sampling locations in the reservoir is located near the intake tower.

Fig. 1 Map of study area

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2.2 Sampling and Analysis The sample was collected in early October 2018, before North-East monsoon, by composite grab sampling using 5 glass bottles, each of 1 litre capacity. The glass bottles were pre-washed in the order with tap water, HPLC water, acetone and sterilised in hot air oven at 105 °C for 3 hours. The pH of reservoir water sample was 8.85. The analysis of 138 ECs belonging to the class of pharmaceuticals, personal care products, pesticides and disinfection by-products was carried out using Liquid Chromatography–Tandem Mass Spectrometry (LC–MS/MS) as per USEPA methods [20, 21]. The sample was filtered using a 0.45 µm membrane filter and the pH was adjusted to 3 using sulphuric acid. 5 mL methanol and deionised water were used to precondition the Solid Phase Extraction (SPE) columns. 100 mL water sample was applied to SPE columns at flow rate of 5 mL/min. The sample was eluded with 5 mL methanol. Eluates were evaporated using air stream up to a volume of 20 µL and further made up to 1 mL (95% water, 5% acetonitrile and 0.1% formic acid). 10 µL of calibration solution and sample extracts were injected to C18 column. Water and acetonitrile, both comprising of 0.1% formic acid, were used as mobile phase. Analytes were chromatographically separated from 95% water and 5% acetonitrile to 40% water and 60% acetonitrile for 10 min and brought to initial condition. Analysis was done at a flow rate of 0.8 ml/min. The analytes were quantified by selected reaction monitoring with the most abundant daughter ion recorded in each case. The standard calibration method was used and analyte to surrogate standard peak area ratios was calculated. Calibration curves generated from standards prepared in water to acetonitrile (95:5) and 0.1% formic acid, with varying concentrations of the model pollutant were used for quantification.

2.3 Ecotoxicological Risk Characterisation For risk assessment, USEPA and European Medical Agency uses a deterministic approach to compare toxicity to environmental exposure. The toxicity of a particular EC to the environment is expressed in terms of RQ which is the ratio of highest measured environmental concentration (MEC) of a particular EC to the predicted no effect concentrations (PNEC) as given in Eq. (1). This ratio is a simple, screeninglevel estimate that identifies high or low risk situations. The PNEC values were obtained by dividing acute and chronic toxicity end points EC50 or LC50 and No Observed Effect Concentration (NOEC) values, respectively by assessment factors. Assessment factor of 100 and 10 was used for acute and chronic toxicity endpoints. The toxicity end points are obtained from PBT Profiler, literatures and Pesticide Property Database (PPDB). The lowest acute or chronic toxicity end points of Daphnia magna and fish was used to obtain the maximum risk.

Assessment of Emerging Contaminants in a Drinking Water Reservoir

Risk Quotient (RQ) =

Max. Environmental Concentration (MEC) Predicted no effect level (PNEC)

219

(1)

RQ value greater than 1 indicates that the EC is likely to cause risk on the aquatic life.

3 Results and Discussion The test results showed presence of ECs in the water belonging to the class of soil fumigants, insecticides, herbicides, termiticide, pesticides, pharmaceutical drugs, solvent, cleaning agent and disinfection by-products. Agriculture is practised in the catchment area; the reservoir is the source of water for drinking water treatment plants and supports aquatic life.

3.1 Analysis of Emerging Contaminants The reservoir water sample was analysed using LC-MS/MS for 138 ECs. It was observed that 21 ECs were above the detection limit. Table 1 shows the predominant ECs with the concentration, regulatory standards as per USEPA and Indian standards IS 10500, common usage and potential health effects [22]. The ECs that are not regulated are left blank in Table 1. The fold of increase of the ECs that exceeded the USEPA MCL standard was calculated and represented graphically in Fig. 2. 1,2Dibromo-3-Chloropropane (DBCP) showed a sky rocketing increase of 600 folds compared to the USEPA MCL standard. It was followed by Benzo(a)pyrene (PAHs) and chlordane which was 30 and 25 times higher than the MCL standard, respectively.

3.2 Sources of Emerging Contaminants To identify the potential sources of contamination of the reservoir, landuse map of the study area was prepared in Geographical Information System (GIS) platform using ArcGIS software as shown in Fig. 3. Landuse details with spatial extent are given in Table 2. Based on the landuse details, the most likely pathway of contamination can be inferred. Of the total ECs that exceeded the regulatory standards, six of them belonged to the class of pesticides such as insecticide, herbicide and fungicide. It can be attributed to agricultural runoff from the catchment area. The landuse map of the reservoir watershed showed large agricultural lands with a spatial extent of 91.901 km2 . The contamination may also be due to discharge from industries manufacturing fertilizers, insecticides and pesticides located in close vicinity of the reservoir. In addition, runoff

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R. A. Mathew and S. Kanmani

Table 1 Predominant ECs observed in the reservoir Sl ECs No

Result MCLG MCL IS mg/L (USEPA) (USEPA) 10500 mg/L mg/L mg/L

Use

Health effects

1

1,2-Dibromo3-Chloropropane (DBCP)

0.12

2

0

0.0002

Insecticide Fungicide Pesticide

Reproductive difficulties, increased risk of cancer

1,2,4-Trichlorobenze 0.03 ne

0.07

0.07

Textile finishing product

Reproductive, developmental, carcinogenic effects, local irritation

3

2,4 - D (2,4-dichloropheno xyacetic acid)

0.13

0.07

0.07

Herbicide

Kidney, liver or adrenal gland problems

4

Benzo(a)pyren e (PAHs)

0.006

0

0.0002

Coal tar, Bitumen

Reproductive difficulties, increased risk of cancer

5

Carbamazepine

0.003

Antiepileptic

Drowsiness, vomiting

6

Chlordane

0.05

0

0.002

Pesticide

Liver or nervous system, increased risk of cancer

7

Chlorpyrifos

0.003

0.002

0.002

Pesticide

Damages nervous system

8

Dichloroacetate

0.006

0.02

0.02

Disinfection Numbness, by-product memory loss

9

Dichloromethane

0.06

0

0.005

Solvent, Cleaning agent

10

Endrin

0.005

0.002

0.002

Insecticide

Liver problem

11

Fonofos

0.003

0.01

0.01

Insecticide

Muscle twitches, decreased blood pressure

12

Heptachlor

0.002

0

0.0004

Termiticide

Liver damage, increased risk of cancer

13

Lindane

0.003

0.0002

0.0002

Insecticide

Liver or kidney problem

0.03

0.03

0.002

Liver problem, increased risk of cancer

(continued)

Assessment of Emerging Contaminants in a Drinking Water Reservoir

221

Table 1 (continued) Sl ECs No

Result MCLG MCL IS mg/L (USEPA) (USEPA) 10500 mg/L mg/L mg/L

Use

Health effects

14

Metolachlor

0.005

0.7

0.7

Herbicide

cytotoxicand genotoxic effects

15

Monochloroacetate (MCA)

0.003

0.06

0.07

Cosmetic, Pesticide

Skin problems

16

N-methylphenma cetin

0.005

Antiinflammato ry (Vicks, paracetam ol)

Methemoglobi nemia, hemolytic anaemia, cardiac arrest

17

p -Dichlorobenzene

0.004

0.075

0.075

Insecticide

Anaemia, liver, kidney or spleen damage, changes in blood

18

Pentachlorophenol

0.004

0

0.001

Fungicide

Liver or kidney problem, increased risk of cancer

19

Polychlorinated Biphenyl (PCB)

0.005

0

0.0005

20

Terbulylazine

0.004

21

Toluene

0.005

1

1

0.0005 Plasticizer

Reproductive, nervous and thymus gland problem, increased risk of cancer

Herbicide Solvent

Nervous kidney and liver problem

MCLG—Maximum Contaminant Level Goal MCL—Maximum Contaminant Level

from tar coated roads and discharge from industries manufacturing iron and steel, range of magnetic vibrating equipment and carrier vibrating equipment, fiberglass reinforced plastic tanks, pipes, surface protection adhesive tapes located in the catchment area may be the cause of Polychlorinated Biphenyl (PCB) and Benzo(a)pyrene (PAHs) in water. As the emerging contaminants have high risk, identifying its presence and concentration in drinking water source is of paramount importance for the human health and environment.

Fold of increase above MCL

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R. A. Mathew and S. Kanmani

600

600

500 400 300 200 100 0

1.857 30

25

1.5

12

2.5

5

15

4

10

Emerging Contaminants

Fig. 2 Fold of increase of ECs against USEPA MCL standard

Fig. 3 Landuse map of the study area

3.3 Ecotoxicological Risk Characterisation The Risk Quotient (RQ) of an EC is calculated as the ratio of maximum environment concentration to the predicted no effect concentration. PNEC used is the lowest acute or chronic toxicity endpoints after applying the assessment factors. The RQ value of the ECs that exceeded the regulatory standards have been tabulated in Table 3.

Assessment of Emerging Contaminants in a Drinking Water Reservoir Table 2 Landuse details with spatial extent

223

Area (km2 )

Landuse Water Bodies

22.559

Wasteland

0.689

Vegetation

92.901

Sandy area

5.752

Road

3.158

Build-up Land

19.306

Barren Land

8.416

Total

152.781

Table 3 Calculated risk quotient of ECs Sl. No

ECs

Toxicity endpoint (mg/L)

RQ

1

2,4-D

NOEC—27.2

0.047 LR

2

Endrin

LC 50—0.00073

685 HR

3

Chlordane

LC 50—0.09 mg/

56 HR

4

Chlorpyrifos

NOEC—0.00014

214 HR

5

1, 2 Dibromo 3 chloro propane (DBCP)

LC 50—152.5

0.079 LR

6

Heptachlor

LC 50—0.007

28.57 HR

7

Lindane

NOEC—2.9

0.01 LR

8

Pentachlorophenol

LC 50—0.17

2.35 HR

9

Poly Chlorinated Biphenyls (PCB)

LC 50—0.015

33.34 h

10

Poly Aromatic Hydrocarbon (BaP)

NOEC—0.0063

9.52 h

11

Dichloromethane

LC 50—193

0.03 LR

12

Carbamazepine

LC 50—15

0.02 LR

LR—Low Risk HR—High Risk

It was observed that endrin had the highest risk quotient followed by chlorpyrifos and chlordane. Besides affecting the aquatic organisms, it can also affect humans. Studies have shown that these pesticides are hepatotoxic, i.e., it affects the liver. It can also affect neurotransmitters in brain causing damage to the nervous system and are suspected carcinogens. PCBs affect reproductive and nervous system. It can also cause thymus gland disorders and lead to increased risk of cancer.

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4 Conclusions Emerging contaminants are a growing concern in water treatment as conventional treatment processes are unable to remove it completely. ECs are persistent micropollutants which have adverse effect on human health and ecosystem. To effectively design a treatment facility, it is necessary to assess the concentration of ECs, study the ecotoxicological effects and its fate and transport to the water body. This study provided evidence for the presence of ECs in the drinking water reservoir. The analysis confirmed pharmaceuticals, pesticides, benzo(a)pyrene, polychlorinated biphenyl in concentrations which does not comply with the USEPA (MCL) regulatory standards. High concentrations of pesticides—2,4 D and DBCP at 0.13 mg/L and 0.12 mg/L, respectively were detected. Pharmaceuticals such as Nmethylphenmacetin and carbamazepine were detected at 0.005 mg/L and 0.003 mg/L, respectively. High risk quotient was obtained for pesticides such as endrin, chlorpyrifos, chlordane and heptachlor. Further the study can be extended to investigate human health risk and antimicrobial resistance in bacteria. It is the need of the hour to detect the presence of ECs in water matrix, understand the fate and transport, design removal and mitigation strategies thereby ensuring sustainability of our ecosystem and human health.

References 1. Farré ML, Pérez S, Kantiani L, Barceló D (2008) Fate and toxicity of emerging pollutants, their metabolites and transformation products in the aquatic environment. TrAC Trends Anal Chem 27(11):991–1007 2. Sophia AC, Lima EC (2018) Removal of emerging contaminants from the environment by adsorption. Ecotoxicol Environ Saf 150:1–17 3. Alder L, Greulich K, Kempe G, Vieth B (2006) Residue analysis of 500 high priority pesticides: Better by GC–MS or LC–MS/MS? Mass Spectrom Rev 25(6):838–865 4. Liu Y (2013) Fate of contaminants of emerging environmental concern (ceecs) during drinking water treatment processes. A thesis submitted to the faculty of the University of North Carolina at Chapel Hill 5. Hossain A, Rahman F, Chowdhury S, Rahman MM, Ahmed D (2010) Antimicrobial resistance pattern of gram-negative bacteria causing urinary tract infection. Stamford J Pharm Sci 2(1) 6. Ramaswamy BR, Shanmugam G, Velu G, Rengarajan B, Larsson DJ (2011) GC–MS analysis and ecotoxicological risk assessment of triclosan, carbamazepine and parabens in Indian rivers. J Hazard Mater 186(2–3):1586–1593 7. Tran NH, Li J, Hu J, Ong SL (2013) Occurrence and suitability of pharmaceuticals and personal care products as molecular markers for raw wastewater contamination in surface water and groundwater. Environ Sci Pollut Res 21(6):4727–4740 8. Xu W, Yan W, Huang W, Miao L, Zhong L (2014) Endocrine- disrupting chemicals in the Pearl River Delta and coastal environment: sources, transfer, and implications. Environ Geochem Health 36(6):1095–1104 9. Agunbiade FO, Moodley B (2014) Pharmaceuticals as emerging organic contaminants in Umgeni River water system, KwaZulu- Natal, South Africa. Environ Monit Assess 186(11):7273–7291

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10. Fick J, Söderström H, Lindberg RH, Phan C, Tysklind M, Larsson DJ (2009) Contamination of surface, ground, and drinking water from pharmaceutical production. Environ Toxicol Chem 28(12):2522–2527 11. Mutiyar PK, Mittal AK (2013) Occurrences and fate of selected human antibiotics in influents and effluents of sewage treatment plant and effluent-receiving river Yamuna in Delhi (India). Environ Monit Assess 186(1):541–557 12. Singh KP, Malik A, Sinha S (2006) Persistent organochlorine pesticide residues in soil and surface water of northern indo- gangetic alluvial plains. Environ Monit Assess 125(1–3):147– 155 13. Mishra K, Sharma RC (2011) Contamination of aquatic system by chlorinated pesticides and their spatial distribution over North-East India. Toxicol Environ Health Sci 3(3):144–155 14. Nadaraja AV, Puthiyaveettil PG, Bhaskaran K (2015) Surveillance of perchlorate in ground water, surface water and bottled water in Kerala, India. J Environ Health Sci Eng 13(1) 15. Isobe T, Ogawa SP, Sugimoto R, Ramu K, Sudaryanto A, Malarvannan G, Devanathan G, Ramaswamy BR, Munuswamy N, Ganesh DS, Sivakumar J, Sethuraman A, Parthasarathy V, Subramanian A, Field J, Tanabe S (2012) Perchlorate contamination of groundwater from fireworks manufacturing area in South India. Environ Monit Assess 185(7):5627–5637 16. Carlsson C, Johansson A-K, Alvan G, Bergman K, Kühler T (2006) Are pharmaceuticals potent environmental pollutants? Part II: Environmental risk assessments of selected pharmaceutical excipients. Sci Total Environ 364(1–3):88–95 17. Santos LH, Araújo A, Fachini A, Pena A, Delerue-Matos C, Montenegro M (2010) Ecotoxicological aspects related to the presence of pharmaceuticals in the aquatic environment. J Hazard Mater 175(1–3):45–95 18. Wu B, Zhang R, Cheng S-P, Ford T, Li A-M, Zhang X-X (2011) Risk assessment of polycyclic aromatic hydrocarbons in aquatic ecosystems. Ecotoxicology 20(5):1124–1130 19. Fowle JR, Dearfield KL (2000) Risk characterization handbook. Science Policy Council, U.S. Environmental Protection Agency, Washington, DC 20. Method 542: Determination of Pharmaceuticals and Personal Care Products in Drinking Water by Solid Phase Extraction and Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry (LC/ESI-MS/MS). Washington DC: United States Environmental Protection Agency, 2016 21. Eichelberger JW, Behymer TD, Budde WL, Munch JW (1995) Method 525.2: Determination of organic compounds in drinking water by liquid-solid extraction and capillary column gas chromatography/mass spectrometry. rev. 2.0. Cincinnati, OH: U.S. Environmental Protection Agency 22. Contaminants Regulated by the U.S. Environmental Protection Agency and their Health Effects’ Safe Drinking Water Foundation www.safewater.org/fact-sheets-1/2017/1/23/contam inantsregulatedbyepa

Estimating the Loss of Water Spread Area in Tanks Using Remote Sensing and GIS Techniques in Ambuliyar Sub-basin, Tamilnadu N. Nasir and R. Selvakumar

Abstract The tanks of South India have a higher demand in agricultural, industrial and domestic sectors. Notably, in the state of Tamil Nadu, there are around 39,000 tanks with varying size and capacity, meant for storing and supplying water towards multifunctional needs of the people. But, the recent statistics show a decreasing trend in their effective utilization. Amongst various reasons for declination, the loss in their storage capacity seems to be the prime cause. But for estimating the storage capacity, extensive field measurements are mandate. However, studies shows that a broad correlation can be established between the capacity and the water spread area of tanks. The water spread area can be precisely mapped using remotely sensed images. By periodically analyzing the changes, the loss in their water spread area can be qualitatively assessed and also the deteriorated tanks can be identified. Accordingly, the Ambuliyar watershed falling in parts of Tamil Nadu is studied. Despite having 809 tanks, the area is now designated under the semi-critical category. The actual extent of the tanks during the year 1972 was mapped using the Survey of India topographic sheets. Subsequently, their water spread area during 1988, 1995 and 2015 was mapped using remote sensing data. The perusal of the overall data shows that almost all the tanks have significantly reduced in their extent, and the reduction varies from 3.13% to 91.36%. Based on their percentage of shrinkage, they were categorized into high, moderate and low deteriorated tanks and accordingly the tanks can be prioritized for reclamation. Keywords Tanks · Remote sensing · Normalized difference water index · Water spread area

N. Nasir · R. Selvakumar (B) School of Civil Engineering, SASTRA Deemed University, Thanjavur, Tamil Nadu, India e-mail: [email protected] N. Nasir e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. Ramanagopal et al. (eds.), Sustainable Practices and Innovations in Civil Engineering, Lecture Notes in Civil Engineering 79, https://doi.org/10.1007/978-981-15-5101-7_23

227

228

N. Nasir and R. Selvakumar

1 Introduction Tank irrigation is one of the oldest and significant sources of irrigation, particularly in south India. Especially in Tamil Nadu, Karnataka and Andhra Pradesh they account for more than one-third of the total irrigated area [1]. Added, support multiple needs like drinking water livestock maintenance, fish culture, recharge of groundwater, control of floods and so on [2]. But, their functionality has declined gradually in recent decades. Besides many reasons, the green revolution and its increased productivity have pressurized not only the government institutions but also the farmers towards more reliable water resources like a canal and deep bore irrigation [3]. In turn, mismanagement and other anthropogenic and natural phenomena like encroachment, deforestation and its induced catchment erosion, siltation, defective tank structures and so on lead to the reduction in their storage capacity [4–8]. In general, the storage capacity of a tank is the function of size, shape, tank bed slope, water supply and so on. But, identification and estimation changes in the above parameters through field-based measurement will be cumbersome. However, studies have proven that the reduction in water spread area of a tank indirectly depicts the reduction in their storage capacity [9, 10]. Remotely sensed images, owing to their multispectral capability can be effectively used for mapping the extent of water spread in tanks [11, 12]. Thus by mapping the water spread area periodically, a time series analysis can be done and there from the changes in water spread extent can be analysed [13–16]. In the state of Tamil Nadu, there are around 39,000 tanks, supporting multifunctional needs of the people. But, the recent statistics show a decreasing trend in their effective utilization [17]. The Ambuliyar watershed falling in parts of Pudukottai and Thanjavur districts of Tamil Nadu covering an area of 930 km2 is also showing a similar trend (Fig. 1). The area comprises 809 system and non-system tanks. Mostly in situ act as their prime input source of water, while few tanks in the middle receive water from Ambular river and few in the eastern part from Grant Anicut canal. The irrigation in the area chiefly depends on the tanks but now in a critical status due to the degraded system. The Thiruvarankulam block comprising a significant part of the watershed is designated under the semi-critical category [6]. Though the watershed is receiving ample mean annual rainfall of 910 mm, due to the deteriorated surface water storage system, most of the storm water is draining into the Bay of Bengal as sheet flow. Hence it is time deserving of harvesting the water by reviving the already existing tank system. Thereby the surface, as well as the groundwater quantity and quality in the area, can be enhanced.

2 Materials and Methods Since the Survey of India topographic sheets is the reliable and the oldest data source available for the study area, the same is used for mapping the original extent of tanks. The perusal of the map shows that in the study area, there are around

Estimating the Loss of Water Spread Area in Tanks …

229

Fig. 1 GIS map showing the study area

809 tanks with different shape and size and the extent ranges from 0.00032 km2 to 2.54 km2 . Amongst, the tank having a surface area of more than 0.1 km2 (10 ha) seems to be effectively contributing towards the agricultural needs. Thus, out of 809 tanks, 181 were considered for further analysis. A time series analysis has been carried out using the post-monsoon Landsat satellite images of the years 1988, 1995 and 2015 to assess the periodic change. Further, for precise demarcation of the boundary between land and water within the tanks, Normalized Differential Water Index (NDWI) images were generated from the satellite data using Environment for Visualizing Images 5.2 (ENVI 5.2) software. Later, by superposing the actual water spread map prepared earlier over the derived NDWI images, the water spread in each tank during the above periods were mapped. Subsequently, the area was calculated using the calculate geometry tool in the ArcGIS software. By comparing the derived results, a reduction in the water spread area of each tank was calculated. Subsequently, based on the percentage of reduction in their water spread area, they were categorized in high, moderate and low degraded tanks.

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3 Mapping the Water Spread Area Besides many parameters, the storage capacity primarily dictates the functionality of a tank. Due to its number and negligence, the data on physical and hydrological parameters of tanks are generally lacking. Hence, an extensive field measurement is essential to collect the data, especially on their storage capacity. But it will be difficult and time-consuming. Further, such measures can provide data only on their present status and not on the original condition, especially before deterioration. However, earlier studies show that a broad relationship can be established between the storage capacity and surface water spread area of tanks [18–20]. Thus, using SOI toposheets, the actual water spread area of tanks was mapped then, using the satellite images, periodical changes in their extent were mapped.

3.1 Actual Water Spread Area (1972) As discussed earlier, the changes in water spread area imply a reduction in their storage capacity, which in turn depicts their functionality. However, most of the tanks in the study area were incepted during the period of King’s rule [1]. Hence, data on their hydrological parameters of most the tanks are not available either with the government or other agencies. Since the Survey of India, topographic sheets are the oldest reliable data source and further up to mid-nineteenth century; the tanks were maintained properly [10], the same can be considered as the original extent of tanks before deterioration. Accordingly, using the Survey of India (OSM) toposheet no. 58J15, 58J16, 58N3, 58N7, 58N4 and 58N8, the original extent otherwise the water spread area of tanks were mapped on 1:50,000 scale and converted into the digital database using GIS software. As discussed earlier, amongst 809 tanks in the study area, 181 tanks were considered for further analysis.

3.2 Changes in Water Spread Area The remotely sensed image not only provides a multi-temporal data but also affords an unbiased data with distinct spectral characteristics between water and land. Thus using satellite images, a time series analysis was done. For the same, Landsat satellite images were procured from the web archives [21], and the water spread area (WSA) in the above 181 tanks were mapped periodically. Since the entire analysis is based on WSA, it is essential to ensure that the tanks are with their maximum water spread in their respective periods. To deduce the same, the daily rainfall data was collected from twelve rain gauge stations located in and around the study area from the Indian Meteorological Department (IMD) and their monthly mean rainfall was worked out for 41 years (1970–2011) (Table 1).

Estimating the Loss of Water Spread Area in Tanks …

231

Table 1 Mean monthly rainfall of the study area Month

Jan

Feb

Mar

Apr

May

Jun

Rainfall (mm)

21.1

14.4

15.4

49.4

52.7

36.0

Month

Jul

Aug

Sep

Oct

Nov

Dec

Rainfall (mm)

71.0

81.2

97.80

186.8

180.7

108.01

(Source IMD)

Table 2 Details on satellite images Data

Acquired date

Rainfall (mm)

Landsat MSS

12th December 1988

190.83

Landsat TM

12th January 1995

225.97

Landsat 8

15th December 2015

367.30

The perusal of the table shows that during October and November (northeast monsoon) months, the watershed is receiving maximum rainfall. Thus it is perceived that during the above months, the tanks will be at their full tank level otherwise with their maximum water spread area. By dully considering the above and other parameters like the availability of data and percentage of cloud cover in the image, the following post-monsoon satellite images, namely Landsat MSS (acquisition date:12/12/1988), Landsat TM (12/01/1995), Landsat 8 (15/12/2015) were collected and used for the analysis (Table 2). As stated earlier, the functionality of the tanks can be assessed indirectly based on their WSA. Since the above satellite data are with low to medium spatial resolution; it is difficult to demarcate the boundary between various land cover features precisely [16, 22]. The NDWI (Normalized Difference Water Index) images precisely discriminates the boundary between land and water bodies. Accordingly, various NDWI thresholds were build using the near and shortwave infrared wavelength bands using ENVI 5.2 software Two band combination: Landsat MSS, TM, ETM+ : (B7–B5)/(B7 + B5); (B4–B7)/(B4 + B7); (B4–7)/(B4 + B7) and Landsat 8: (B5–B6)/ (B5 + B6). (ii) Three band combination: LandsatMSS, TM, ETM+ :(B7–B6–B5)/(B7 + B6 + B5); (B4–B5–7)/(B4 + B5 + B7); (B4–B5–B7)/(B4 + B5 + B7) and Landsat 8: (B5–B6–B4)/(B5 + B6 + B4). (iii) Four band combination: LandsatMSS, TM, ETM+ :(B7)–(B4 + B6 + B5)/(B7) + (B4 + B6 + B5);(B7)–4 + B5 + B2)/(B7) + (B4 + B5 + B2); (B7)–(B4 + B5 + B2)/(B7) + (B4 + B5 + B2) and Landsat 8: (B7)–(B5 + B6 + B4)/(B7) + (B5 + B6 + B4). (i)

Amongst the derived NDWI outputs, for the year 1988 the two band combination (B4–B7)/(B4 + B7), for the year 1995 the three-band combination (B4–B5–B7)/(B4 + B5 + B7) and for the year 2015 the four band combination (B7)(B5 + B6 +

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N. Nasir and R. Selvakumar

B4)/(B7) + (B5 + B6 + B4) images has yielded better results and thus used for mapping the water spread area of the tanks (Fig. 2).

Fig. 2 Map showing Landsat and NDWI images

Estimating the Loss of Water Spread Area in Tanks …

233

4 Results and Discussion Later, over the above derived NDWI images (Fig. 3), the digital data on tanks prepared earlier using SOI topographic sheets (Fig. 1) were overlaid, and their present water spread extent was digitized. Since both the images are co-registered, they precisely superpose one over the other. For instance, the water spread area map prepared using 1972 topographic sheet was overlaid over the NDWI image of 1988 and using cut polygon tool in ArcGIS software, the new contact boundary was precisely digitized and later using the calculate geometry tool in ArcGIS software, the present water spread area was computed. Then by comparing it with its actual area (1972), the loss was calculated. Similarly, the database was generated on the WSA of tanks during 1988, 1995 and 2015 and tabulated (Table 3).

Fig. 3 Time series analysis showing a reduction in the extent of water spread area

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N. Nasir and R. Selvakumar

Table 3 Databases on water spread area of tanks during 1988, 1995 and 2015 Tank Id

Water Spread Area (km2 )

Water spread area concerning 1972 (in %)

1972

1988

1995

2015

1988

1995

2015

1

0.1530

0.0124

0.0133

0.0746

91.92

91.33

51.25

2

0.1100

0.0068

0.0149

0.0268

93.82

86.47

75.66

3

0.1541

0.0174

0.0261

0.0242

88.69

83.06

84.33

4

0.2604

0.0487

0.1688

0.1593

81.30

35.18

38.85

5 .. .

0.1607

0.0108

0.0668

0.0819

93.30

58.46

49.04

101

0.1551

0.0655

0.0505

0.0613

57.79

67.43

60.48

102

0.1063

0.0099

0.0083

0.0409

90.66

92.15

61.53

103

0.3317

0.0161

0.1444

0.0567

95.15

56.47

82.90

104

0.7088

0.1834

0.1411

0.3024

74.13

80.10

57.34

105 .. .

0.1509

0.0599

0.0559

0.0745

60.34

62.98

50.65

177

0.1254

0.0840

0.0652

0.0824

32.99

48.04

34.31

178

0.2020

0.0564

0.0465

0.0519

72.08

76.99

74.31

179

0.2243

0.1763

0.1597

0.1259

21.38

28.80

43.85

180

0.5665

0.2058

0.2631

0.2765

63.67

53.55

51.18

181

0.2601

0.1416

0.1352

0.1261

45.56

48.04

51.52

The perusal of the Table 3 indicates that almost all the tanks have substantially shrunk during 2015 when compared to their original extent during 1972. The percentage of reduction varies from 3.13% (Periyalur Kanmoi, Tank Id—109) to 91.36% (Korattur tank, Tank Id—97) with an average decrease of about 50.13%. Then based on the percentage loss, the tanks were classified into three categories as high, moderate and low (Table 4) degraded tanks. Amongst 181 tanks, 90 tanks (about 50%) fall under the high category and 68 tanks (about 38%) under the moderate category, thus indicating that the entire system is highly deteriorated. Subsequently, all the 181 tanks were categorized, and the GIS map was generated (Fig. 4). The perusal of the above map shows that both the system and non-system Table 4 Categorization of tanks based on the loss in their WSA Sl. no.

Category

Percentage of reduction (%)

Number of tanks

1

High

>50

90 tanks

2

Moderate

>25–< 50

68 tanks

3

Low