Recent Advances in Mechanical Infrastructure: Proceedings of ICRAM 2020 (Lecture Notes in Intelligent Transportation and Infrastructure) 9813341750, 9789813341753

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Lecture Notes in Intelligent Transportation and Infrastructure Series Editor: Janusz Kacprzyk

Ajit Kumar Parwani PL. Ramkumar Kumar Abhishek Saurabh Kumar Yadav   Editors

Recent Advances in Mechanical Infrastructure Proceedings of ICRAM 2020

Lecture Notes in Intelligent Transportation and Infrastructure Series Editor Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

The series “Lecture Notes in Intelligent Transportation and Infrastructure” (LNITI) publishes new developments and advances in the various areas of intelligent transportation and infrastructure. The intent is to cover the theory, applications, and perspectives on the state-of-the-art and future developments relevant to topics such as intelligent transportation systems, smart mobility, urban logistics, smart grids, critical infrastructure, smart architecture, smart citizens, intelligent governance, smart architecture and construction design, as well as green and sustainable urban structures. The series contains monographs, conference proceedings, edited volumes, lecture notes and textbooks. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable wide and rapid dissemination of high-quality research output.

More information about this series at http://www.springer.com/series/15991

Ajit Kumar Parwani PL. Ramkumar Kumar Abhishek Saurabh Kumar Yadav •

•

•

Editors

Recent Advances in Mechanical Infrastructure Proceedings of ICRAM 2020

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Editors Ajit Kumar Parwani Department of Mechanical and Aero-space Engineering Institute of Infrastructure Technology Research and Management Ahmedabad, Gujarat, India

PL. Ramkumar Department of Mechanical and Aero-space Engineering Institute of Infrastructure Technology Research and Management Ahmedabad, Gujarat, India

Kumar Abhishek Department of Mechanical and Aero-space Engineering Institute of Infrastructure Technology Research and Management Ahmedabad, Gujarat, India

Saurabh Kumar Yadav Department of Mechanical and Aero-space Engineering Institute of Infrastructure Technology Research and Management Ahmedabad, Gujarat, India

ISSN 2523-3440 ISSN 2523-3459 (electronic) Lecture Notes in Intelligent Transportation and Infrastructure ISBN 978-981-33-4175-3 ISBN 978-981-33-4176-0 (eBook) https://doi.org/10.1007/978-981-33-4176-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021, corredted publication 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

This book is brought out to mark the occasion of 2nd International Conference on Recent Advances in Mechanical Infrastructure (ICRAM-2020) during 21–23 August 2020 organised by Department of Mechanical Engineering, IITRAM, Ahmedabad. The purpose of this conference is to provide platform for academicians, researchers and industrial professionals to exchange their views, ideas and experiences and collaborate for expediting progress in the fields of thermal, manufacturing, planning and design infrastructure. The submitted manuscripts went through a peer review process. Each manuscript received at least two reviews. Finally, 42 manuscripts were selected for presentation in three different tracks like thermal, manufacturing and design infrastructure. The conference conveners would like to thank the delegates who have contributed for the conference proceedings as chapters. We would also like to thank our outstanding keynote speakers: Dr. Fillipo de Monte, Associate Professor, University of L’Aquila, Italy; Dr. Lailesh Kumar, Senior Research Scientist, Pintree PosMagnesium Co. Ltd., South Korea; Dr. Udayraj, Assistant Professor, IIT Bhilai; Selvaraji Muthu, Senior General Manager, Design and Development, Mahle Engine Components India Pvt. Ltd., Chennai; and Dr. Manoj Kumar Gaur, Professor, MITS Gwalior, for sharing their deep insights on future challenges and trends. We would like to thank all the reviewers for their great effort on reviewing the papers submitted to ICRAM-2020. We are grateful to the management of IITRAM for their help and support in organising this mega event. We hope that this book will motivate many academicians and industrial professionals to specialise in the fields of thermal, manufacturing, planning and design infrastructure. Ahmedabad, India

Ajit Kumar Parwani PL. Ramkumar Kumar Abhishek Saurabh Kumar Yadav

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Contents

Recent Advances in Manufacturing Infrastructure Prediction of Mechanical Properties in Rotational Moulding of LLDPE Using Machine Learning Model for the Given Oven Residence Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Akshay Kumar, PL. Ramkumar, Aman Shukla, and Nikita Gupta Friction Stir Additive Manufacturing—A Review . . . . . . . . . . . . . . . . . Dhruv Shah and Vishvesh J. Badheka

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Processibility Analysis of Rotationally Moldable Linear Low-Density Polyethylene/Glass Fiber Blend . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nikita Gupta and PL. Ramkumar

37

Feasibility of Joining Aluminum to Nylon Using Friction Stir Welding (FSW) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nitesh Kumar Jha, Darshit K. Desai, and Vishvesh J. Badheka

45

Rejection Rate Minimization of Cast Iron Components Through Metallurgical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Santhy and D. R. Rajkumar

55

A Study on the Comparison Between Activated TIG Variants on Weld Bead Profile of P91 Steel. Part: 1 . . . . . . . . . . . . . . . . . . . . . . . Purvesh K. Nanavati, Vishvesh J. Badheka, Solanki Darshan, Idhariya Jaynish, Chintan Patel, and Maharshi Pandya Role of Surface Cracking and Recast Layer Deposition on Formation of Hardened Layer During EDM of Inconel 825 with Varied Electrode Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Soni Kumari, Thrinadh Jadam, Gobinda Chandra Behera, Santosh Kumar Sahu, Saurav Datta, Goutam Nandi, and Pradip Kumar

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83

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On Abrasive Flow Finishing of Straight Bevel Gear . . . . . . . . . . . . . . . Anand Petare, Neelesh Kumar Jain, and I. A. Palani

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An Effect of Process Parameter on Physical Appearance of Deposited Friction Surfaced Layer: A Feasibility Approach . . . . . . . . . . . . . . . . . . 105 Kedar Badheka and Vishvesh J. Badheka A Review on Applications of Nitinol Shape Memory Alloy . . . . . . . . . . 123 Rakesh Chaudhari, Jay J. Vora, and D. M. Parikh Surface Composite AA6061/SiC Manufactured by Hole and Groove Method Friction Stir Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Daulat Kumar Sharma, Harshadkumar H. Jadav, Naishadh P. Patel, Devang Mahant, and Gautam Upadhyay Reliability Analysis of Car Subsystem by Weibull Two Parameter Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Pushpdant Jain and Lijo Varghese A Review of Challenges to Hastelloy – C Series Weld Overlay . . . . . . . 157 Manish V. Mehta, Jay J. Vora, and Mrunalkumar D. Chaudhari Analysis of Dimensional Accuracy of ABS M30 Built Parts Using FDM Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Mahajan Vaibhav Mansaram, Suman Chatterjee, Dinbandhu, Anshuman Kumar Sahu, Kumar Abhishek, and Siba Sankar Mahapatra Reduction of Scrap and Rework Cost by Implementing 5S Methodology: A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Gnanesh Vora, Hemendrasinh Umat, Soni Kumari, Dinbandhu, Chetansingh Rajput, and Kumar Abhishek Grain Refinement and Improvement in Microhardness of AZ91 Mg Alloy Via Friction Stir Processing . . . . . . . . . . . . . . . . . . . 197 Minal S. Dani and I. B. Dave Effect of Number of Passes and Pass Directions in Friction Stir Processing of Copper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Nisarg Patel, Farhan Khimani, and Vishvesh J. Badheka Applicability of Bobbin Tool Friction Stir Welding for Dissimilar Al-Mg Joint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Harshadkumar H. Jadav, Vishvesh J. Badheka, Kishan Fuse, Kush Mehta, and Gautam Upadhyay Recent Advances in Thermal Infrastructure Estimation of Thermodynamic and Transport Properties of Metallic Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 Filippo de Monte and Giampaolo D’Alessandro

Contents

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Design Improvement of a Vertically Oriented Thermal Energy Storage System Considering Melting Front Propagation . . . . . . . . . . . . 245 Kedumese u Mekrisuh, Udayraj, and Dushyant Singh Numerical Study of Slot Jet Impingement on a Cylinder by Using Two-Equation Turbulence Models . . . . . . . . . . . . . . . . . . . . . 257 Dushyant Singh and Saurabh Kango Thermal Simulation of Li-Ion Battery Pack Using ANSYS Fluent . . . . . 265 Mann P. Parmar, Deep R. Patel, Vivek K. Patel, and Rajesh S. Patel Experimental Investigation of Heat Sinks with and Without Perforation—Addressing Toward Higher Cooling Rates and Optimum Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 Rajshekhar V. Unni and M. Sreedhar Babu Selection of Optimum Castor–Rapeseed Emulsified Fuel Based on Engine Performance, Combustion and Emission Analysis . . . . . . . . . 285 Sajan Chourasia, Rajesh Patel, and Absar Lakdawala Experimental Measurement of Laminar Flame Velocities of LPG–Air Mixtures with Cylindrical Flame Tube Method . . . . . . . . . . . . . . . . . . . 297 Akshay A. Kadam, Abhinandan D. Kadam, Nikhil P. Daphale, and M. Sreedhar Babu Performance Analysis of Double Pipe by Using Different Nanofluids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 Bharat Naik, Merwyn Thomas, M. Sreedhar Babu, Anand K. Hosmani, Omkar Alloli, Kshitij Dasurkar, and Mahalaxmi Alloli Estimation of Contact Conductance Between Two Dissimilar Metal Rods by Jaya Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313 Meet Parikh, Harsh Vaghela, Sanil Shah, and Ajit Kumar Parwani Emission and Performance Analysis of Four-Stroke Dual-Cylinder Engine Using Waste Plastic Pyrolysis Oil as Biodiesel . . . . . . . . . . . . . . 321 Milind Dalal, Romin Virani, Pulkit Choudhary, and Ajit Kumar Parwani Estimation of Transient Boundary Heat Flux Using Modified JAYA Algorithm in Laminar Duct Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331 Ravi Prajapati, Viral Thakkar, Sanil Shah, and Ajit Kumar Parwani Estimation of Boundary Heat Flux with Conjugate Gradient Method by Experimental Transient Temperature Data . . . . . . . . . . . . . . . . . . . . 343 Parth Sathavara, Ajit Kumar Parwani, Maulik Panchal, and Paritosh Chaudhuri A Study of Linear Fresnel Solar Collector Reflector Field for Performance Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353 Gunjan Kumar and Hemant Gupta

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Recent Advances in Design Infrastructure Kinematic Analysis of Planar Mechanisms by Means of Computer-Aided Design Software . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Amit Talli and Arunkumar C. Giriyapur Superplasticity: Recent Approaches and Trends . . . . . . . . . . . . . . . . . . 387 Deepika M. Harwani, Vishvesh J. Badheka, and Vivek Patel Design for Retractable Staircase for Buses . . . . . . . . . . . . . . . . . . . . . . . 399 Kunal Gawhade, Pranav Raj, and PL. Ramkumar Industry 4.0 Technology: Design and Manufacturing of Modular Fixture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 411 Pooja Raval, Nirav P. Maniar, Sudhir Thaker, and Pradeep Thanki Design and Development of Spoon Bundling Machine . . . . . . . . . . . . . . 419 Kartik Konkatti and G. D. Bassan Effect of Optimized Slip and Texture Zone on the Performance of Hydrodynamic Journal Bearing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433 Mohammad Arif, Saurabh Kango, Dinesh Kumar Shukla, and Nitin Sharma Structural Analysis, Design, and Implementation of Safety Access to High Pressure Helium Gas Storage Vessels at IPR . . . . . . . . . . . . . . 443 Rajiv Sharma and Vipul Tanna Design and Analysis of Circular and Square Arm for an Articulated Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457 Keval Bhavsar, Dharmik Gohel, and Jaimin Panchal Kinematic Analysis and Simulation of Industrial Robot Based on RoboAnalyzer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473 Amit Talli and Arunkumar C. Giriyapur A Simplified Method for Conversion of Lumbar Spine CT Images into Three-Dimensional Solid Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 485 Pushpdant Jain and J. Francis Xavier Design of Automatic Multipurpose Indian Flatbread Maker . . . . . . . . . 495 Shivam Kishore Sinha, Vaibhav Chopde, Kumar Abhishek, and Amit Devani Correction to: Superplasticity: Recent Approaches and Trends . . . . . . . Deepika M. Harwani, Vishvesh J. Badheka, and Vivek Patel

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Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511

About the Editors

Dr. Ajit Kumar Parwani is working as an Assistant Professor in the Department of Mechanical Engineering at the Institute of Infrastructure Technology Research and Management (IITRAM), Ahmedabad, India. He has completed his Ph.D. from Indian Institute of Technology (IIT), Delhi, India, in 2013. He has over 15 years of teaching and research experience. His research interests include heat transfer, inverse heat transfer, computational heat transfer, renewable energy and IC engines. He has published several papers in international journals. He has filed an Indian patent title “Simultaneous reduction of NOx and CO2 using exhaust gas recirculation and carbon capture.” He has conducted several workshops, short-term training programs and seminars. He is Editor of a book titled “Recent Advances in Mechanical Infrastructure” in the Lecture Notes in Intelligent Transportation and Infrastructure published by Springer Singapore. He has two ongoing research projects funded by SERB-DST, Government of India, and Institute of Plasma Research, Government of India. Dr. PL. Ramkumar is an Assistant Professor in Mechanical Engineering department at IITRAM, Ahmedabad. He served as a Lecturer in the Mechanical Engineering department at the Birla Institute of Technology and Science, Pilani, KK Birla Goa Campus, Goa, India, for 8 years. He has over 12 years of teaching and research experience. He completed his graduation in Mechanical Engineering from Madurai Kamaraj University in 2003. He obtained M.E. degree in Computer Aided Design from Anna University, Tamil Nadu, India, in 2008 securing University rank with Gold medal. He received his Ph.D. from BITS PILANI in the year 2016. His area of research includes experimental analysis of manufacturing processes, process modeling, computer-aided analysis and optimization. He has organized various workshops and conferences. He has published good number of research papers in the international journal/conferences of repute. He has written/ edited a book titled “Recent Advances in Mechanical Infrastructure” in the Lecture Notes in Intelligent Transportation and Infrastructure published by Springer

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About the Editors

Singapore. He is a life member of various prestigious societies which includes Institute of Engineers (MIE), Indian Institute of Metals (IIM) and Hong Kong Society of Mechanical Engineers (HKMSE). Dr. Kumar Abhishek is an Assistant professor in Mechanical Engineering department at IITRAM, Ahmedabad. He has over 4 years of teaching experience. He received his Ph.D. from NIT Rourkela in the year 2016. His area research includes experimental analysis of manufacturing processes, manufacturing and industrial engineering and decision and information science. He has organized various workshops and conferences. He has published good number of research papers at the international journal/conferences of repute. Dr. Saurabh Kumar Yadav is an Assistant Professor in the Department of Mechanical Engineering at the IITRAM, Ahmedabad. Dr. Saurabh Kumar Yadav feels that teaching is an art that requires a constant effort for improvement. He consistently conducts research experiments and searches for interactive means of classroom instruction. Dr. Saurabh teaches finite element method at the undergraduate level and dynamic and vibration at both undergraduate and graduate levels.

Recent Advances in Manufacturing Infrastructure

Prediction of Mechanical Properties in Rotational Moulding of LLDPE Using Machine Learning Model for the Given Oven Residence Time Akshay Kumar, PL. Ramkumar, Aman Shukla, and Nikita Gupta

Abstract Enhancing the mechanical property of rotationally mouldable product, while sustaining the mouldability, becomes a strenuous task. Examining these properties on practically built product has always been laborious and economically challenging. Machine learning can consequently provide an ample assistance for such exposition. Thus, a new approach has been developed based on machine learning in the present study in order to predict mechanical properties of roto moulded product on the basis of oven residence time using linear low density polyethylene (LLDPE). The two machine learning models utilized for the investigation include linear regression model and polynomial regression model. Variation of mechanical properties of linear low density polyethylene (LLDPE) roto moulded product with oven residence time based on the existing statistics has been used as training data for these models. Preliminary results show that polynomial regression model has given more precise data than linear regression model. From economic prospective, machine learning methods were able to achieve acceptable quality results, which are beneficial, since obtaining the similar amount of data by developing a product practically can prove to be expensive.* Keywords Rotational moulding · Oven residence time · LLDPE · Machine learning · Training data · Polynomial regression model

1 Introduction 1.1 Rotational Moulding Rotational moulding (also known as rotational casting or roto moulding) is a polymer processing technique mainly used to manufacture hollow parts, with simple and complex structures. It is relatively a stress-free process compared with the other A. Kumar (B) · PL. Ramkumar · A. Shukla · N. Gupta Department of Mechanical and Aero-Space Engineering, IITRAM, Ahmedabad, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_1

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moulding processes as the molten plastic is not forced to take any shape. And due to this, products with good mechanical properties can be manufactured. Products manufactured from this technique have wide range of applications in various fields like in agriculture, automobiles, medical equipment’s, furniture tanks, etc. [1–3]. This whole process is completed mainly in four stages as which starts with charging the mould with a thermoplastic material (usually linear low density polyethene) which is in the powdered form with an average of 500-micron particle size. Secondly, heating and melting of the powder in the mould which is rotated biaxially, so that the melted powder sticks to the surface of mould followed by cooling of the mould and lastly de-moulding of the part at a temperature which is slightly higher than the room temperature. There is no doubt that there have been great technological advancements in rotational moulding process in the recent decade. It has been evolved from a manufacturing process overlooked for many as ‘black art’ to a refined moulding process for making high quality products, which cannot be made by any other moulding processes [4, 5]. Rotational moulding process is capable of producing products that have different mechanical properties like tensile strength, impact strength and flexure strength. And this can be done only by changing oven residence time. In present scenario of industries, there has been a need of products of different mechanical properties, and for this, we need to know the appropriate oven residence time for manufacturing such products [6, 7]. The term ‘oven residence time’ is generally understood to mean the total time a polymer resides in the oven from room temperature till the oven in turned off. At present, these mechanical properties for different oven residence timings are obtained by manually done experiments. And due to this, the whole process becomes costly and time consuming. A less costly and time-consuming approach can be using machine learning models to predict the mechanical properties of the roto moulded product for different oven residence timings.

1.2 Machine Learning Machine learning is a subdivision of artificial intelligence (AI) that gives a model which can learn and improve with time without being explicitly instructed or programmed, so instead of writing codes, some input data is provided in the generic algorithm, and the algorithm itself generates a logic from the given data. These algorithms are created in such a way that they learn and improve themselves over time when are provided with more data [8, 9]. In the past recent years, it can be observed that machine can be used as to automatize different tasks that were thought of as only humans can do like playing games, face recognition, text generation, etc. [10–12] Applying machine learning in various industries like in medicine, transportation, banking can be very useful as it can be used as to perform tasks like video surveillance, spam and malware, fraud detection, prediction and many more [13–15]. Machine learning has mainly divided into four parts as follows [16–18]:

Prediction of Mechanical Properties in Rotational Moulding …

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Supervised Learning. In this type, the model learns from the given data set known as training set, containing both input and output parameters. It contains mainly two types, known as classification and regression. Classification is used to identify an observation to which category it belongs, on the basis of the provided training set to the model. Whereas regression is used when the output is continuous, i.e. there exists an output variable for an input parameter, and to predict an output for a given new input parameter from the model which has the training set. It can be a linear or a polynomial regression on the basis of the variation of outputs with the inputs. In linear regression model, hypothesis is done from one-degree polynomial, whereas in polynomial regression model, hypothesis is done from a polynomial having more than one degree depending upon the inputs and their corresponding outputs. Unsupervised Learning. In this type, the model learns from the data sets that contains only inputs, and from this training data set, the model analyses the structures in the data set, like grouping and categorizing. Semi-supervised Learning. This type is the combination of supervised and unsupervised learning in which model learns from the training set which has both labelled (containing both input and output parameters) and unlabelled (containing only inputs) data sets. Reinforcement Learning. It has three major components: the agent, environment and action. In this type, agent has the ability to interact with the environment and analyses what would be the best outcome with the hit and trial method.

1.3 Application of Machine Learning in Different Fields It has been evident that in the recent years, machine learning has shown greater impact on our lives and onto various fields. Some of the major fields and works done by researchers are as follows: Scikit-learn: Machine Learning in Python. Scikit-learn is a Python module that as the best machine learning algorithms for medium level of supervise and unsupervised problems. This module mainly concentrates on the usage of machine learning by non-specialists in this field [19]. Machine Learning in Medical Sector. It is important to note that large medical data sets are present for us including patient reports, diagnostics, disease characteristics, etc., for the training data sets for the machine learning models. And with the help of these models, various problems have been solved. Like in the case of cancer, it has predicted the survival outcome and also by the attracter metagene algorithm it had found out a cluster of genes in the tumour cells which was similar in the cancer patients [20]. Machine Learning in Financial Sector. Machine learning has also contributed to the financial sector. It was found that machine learning model can learn to price the

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options in the stock market very precisely, this reduces the chances of human error involved. Nowadays, it is also used to calculate the stock prices with the help of the history of the stock prices and various company data as the training data sets [21]. Machine Learning in Manufacturing. In the present years, smart manufacturing ideas are taking a step ahead, and according to the research carried by Wang [22], various machine learning models are made to improve the system performance in the manufacturing systems [22]. Machine Learning in Plastic Moulding. It is evident from the research done by Tellaeche and Arana [23] that machine learning algorithms are very useful in the quality control in the plastic moulding industry as they can perform fault detection in fabrication of plastic products better that the traditional quality control methods [23].

1.4 Research Gap Application of machine learning in the field of rotational moulding has not yet been fully explored. Like in the other fields, machine learning can also be applied in rotational moulding for the prediction of mechanical properties of roto moulded product for the given oven residence time by using machine learning models.

2 Methodology For the prediction of mechanical properties for the given oven residence time, a training data was taken which had the value of tensile strength, impact strength and flexure strength for different oven residence timings which were obtained by doing experiments manually by Ramkumar [24]. From these training data set, machine learning models were created (here polynomial regression model and linear regression model supervised learning models, as there were both input parameters and output variables in the training data sets), in Python. For building the required machine learning model, Python programming was used. From these models, various prediction curves (mechanical property vs. oven residence time) were obtained. Further, curves from the two models (linear regression model and polynomial regression model) were compared on the basis of precision of the obtained value of mechanical property, and then, best suited model for the prediction was selected.

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Table 1 Oven residence time and corresponding mechanical properties [24] S. No.

Oven residence time (min)

Tensile strength (MPa)

Impact strength (J)

Flexure strength (MPa)

1

32

16

0.52

18.2

2

34

16.2

0.69

18

3

36

17.2

0.92

17.6

4

38

17.4

0.97

17

5

40

17.4

1

17.2

6

42

16

0.8

16.7

7

44

15.3

0.6

16

2.1 Training Data The above data was taken from the experimental work done by Ramkumar [24]. Then from the selected model, hypothesis polynomial of the curve is obtained. And further, from the hypothesis, polynomial values of mechanical properties were obtained for different oven residence timings. Degree of hypothesis polynomial changes according to the inputs and their corresponding outputs (Table 1).

3 Result and Discussion From the two machine learning models, following prediction curves were obtained: Figure 1 depicts the prediction curve obtained from linear regression model for various mechanical properties for different oven residence timings. It can be observed from the prediction curves that the input points deviate from the prediction curve in a great manner which is not suited for the required machine learning prediction model. Figure 2 depicts the prediction curve obtained from polynomial regression model for various mechanical properties for different oven residence timings. It can be observed from the prediction curves that the deviation of input points from the prediction curve is relatively smaller that the linear regression model (Fig. 3). From the above observation, it can be inferred that polynomial regression model gives more precise prediction of mechanical properties of roto moulded product. This finding confirms that polynomial regression model is best suited for the purpose of predicting the mechanical properties of the roto moulded product when the oven residence time is varied. Further from the polynomial regression prediction curve that was obtained from polynomial regression machine learning prediction model, different polynomial functions of the best suited degree were obtained that shows the variation of mechanical properties with the change in oven residence timings.

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Fig. 1 Process involved in the methodology

Training Data was obtained.

Machine Learning models (Linear and Polynomial Regression) were created.

Prediction Curves were obtained from the models.

Models were compared and suitable model was selected.

Hypothesis polynomial of the curve was obtained from the suitable model.

Values of mechanical properties were obtained from the hypothesis polynomial.

Fig. 2 Linear regression prediction curve for a tensile strength versus oven residence time, b impact strength versus oven residence time, c flexure strength versus oven residence time

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Fig. 3 Polynomial regression prediction curve for a tensile strength versus oven residence time, b impact strength versus oven residence time, c flexure strength versus oven residence time

For tensile strength versus oven residence time, degree five polynomial was obtained, T (t) = 0.0001t 5 − 0.0254t 4 + 1.7892t 3 − 62.288t 2 + 1073.1t − 7302.7 For impact strength versus oven residence time, degree five polynomial was obtained, I (t) = 0.000005t 5 − 0.0008t 4 + 0.0505t 3 − 1.4305t 2 + 18.176t − 73.628 For flexure versus oven residence time, degree four polynomial was obtained, F(t) = −0.0008t 4 + 0.1242t 3 − 6.9535t 2 + 172.13t − 1570.8 From these hypothesis polynomials, values of various mechanical properties were obtained for different oven residence timings (every interval of 30 s) (Table 2). This technique shows clear advantage over manually obtaining mechanical properties of roto moulded product for different oven residence timings. And by acquiring the data that has larger range of input values that is oven residence time to the corresponding output values that are mechanical properties, a larger range of predictions can be obtained.

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Table 2 Oven residence time and obtained corresponding mechanical property Oven residence time (min)

Tensile strength (MPa)

Impact strength (J)

Flexure strength (MPa)

32

15.99015152

0.518290043

18.20324675

32.5

15.97653309

0.556402096

18.21287604

33

16.02068537

0.600685877

18.17530777

33.5

16.1174825

0.649253511

18.10229027

34

16.25909091

0.70025974

18.004329

34.5

16.43550637

0.75192145

17.89068651

35

16.63509115

0.802537202

17.76938244

35.5

16.84511108

0.850506766

17.64719355

36

17.05227273

0.894350649

17.52965368

36.5

17.24326042

0.93272963

17.4210538

37

17.40527344

0.964464286

17.32444196

37.5

17.52656305

0.988554529

17.24162333

38

17.5969697

1.004199134

17.17316017

38.5

17.60846003

1.010815271

17.11837185

39

17.55566406

1.008058036

17.07533482

39.5

17.43641228

0.995839981

17.04088267

40

17.25227273

0.974350649

17.01060606

40.5

17.00908813

0.944076102

16.97885277

41

16.71751302

0.905818452

16.93872768

41.5

16.3935508

0.860715395

16.88209276

42

16.05909091

0.81025974

16.7995671

42.5

15.74244588

0.756318941

16.68052688

43

15.47888849

0.701154627

16.51310538

43.5

15.31118885

0.647442136

16.284193

44

15.29015152

0.598290043

15.97943723

Also, obtained hypothesis polynomial needs to be interpreted with caution due to the fact that the coefficients were approximated by the model to a lower decimal number.

4 Conclusion In this work, mechanical properties of roto moulded product were obtained using machine learning model. Machine learning models were created in Python programming language. Here, linear regression and polynomial regression model were created. Further, a suitable model was selected that has least variation from the

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training data set. Using this model, value of mechanical properties at the given oven residence time is obtained, and provided value of oven residence time is in the range of the training data set. It is suggested that, a similar procedure of creating a machine learning model can be used for the other materials for a range of oven residence timings. Also, from a reverse approach, from the given mechanical properties, we can obtain the corresponding oven residence time required for that particular roto moulded product. And this approach can also be used in various fields and contribute significantly reducing human errors, reducing work time, making things more economical.

References 1. Crawford RJ (ed) (1996) Rotational moulding of plastics. Research Studies Press, London, UK 2. Unkles PJ (2001) Rotational moulding process. U.S. Patent No. 6,180,203, 30 Jan 2001 3. Ramkumar PL et al (2015) Prediction of heating cycle time in rotational moulding. Mater Today Proc 2(4–5):3212–3219 4. Shaker R, Rodrigue D (2019) Rotomolding of thermoplastic elastomers based on low-density polyethylene and recycled natural rubber. Appl Sci 9(24):5430 5. Garg A et al (2019) Handling constraints and raw material variability in rotomolding through data-driven model predictive control. Processes 7(9):610 6. Ramkumar PL et al (2014) Investigation of melt flow index and impact strength of foamed LLDPE for rotational moulding process. Procedia Mater Sci 6:361–367 7. Torres FG, Aragon CL (2006) Final product testing of rotational moulded natural fibrereinforced polyethylene. Polym Test 25(4):568–577 8. Rasmussen CE (2003) Gaussian processes in machine learning. In: Summer school on machine learning. Springer, Berlin 9. Harrington P (2012) Machine learning in action. Manning Publications Co., New York 10. Cevikalp H, Triggs B (2010) Face recognition based on image sets. In: 2010 IEEE computer society conference on computer vision and pattern recognition. IEEE 11. Biran O, McKeown KR (2017) Human-centric justification of machine learning predictions. IJCAI 2017:1461–1467 12. Bowling M et al (2006) Machine learning and games. Mach Learn 63(3):211–215 13. Kononenko I (2001) Machine learning for medical diagnosis: history, state of the art and perspective. Artif Intell Med 23(1):89–109 14. Jahangiri A, Rakha HA (2015) Applying machine learning techniques to transportation mode recognition using mobile phone sensor data. IEEE Trans Intell Transp Syst 16(5):2406–2417 15. Jain AK, Gupta BB (2016) Comparative analysis of features based machine learning approaches for phishing detection. In: 2016 3rd international conference on computing for sustainable global development (INDIACom). IEEE 16. Ayodele TO (2010) Types of machine learning algorithms. In: New advances in machine learning. IntechOpen, London 17. Alpaydin E (2009) Introduction to machine learning. MIT Press, Cambridge 18. Lison P (2015) An introduction to machine learning. Language Technology Group (LTG), pp 1–35 19. Pedregosa F et al (2011) Scikit-learn: machine learning in python. J Mach Learn Res 2825–2830 20. Deo RC (2015) Machine learning in medicine. Circulation 132(20):1920–1930 21. Culkin R, Das SR (2017) Machine learning in finance: the case of deep learning for option pricing. J Investment Manage 15(4):92–100 22. Wang J et al (2018) Deep learning for smart manufacturing: methods and applications. J Manuf Syst 48:144–156

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23. Tellaeche A, Arana R (2013) Machine learning algorithms for quality control in plastic molding industry. In: 2013 IEEE 18th conference on emerging technologies & factory automation (ETFA). IEEE 24. Ramkumar PL, Waigaonkar SD, Kulkarni DM (2016) Effect of oven residence time on mechanical properties in rotomoulding of LLDPE. S¯adhan¯a 41(5):571–582

Friction Stir Additive Manufacturing—A Review Dhruv Shah and Vishvesh J. Badheka

Abstract Aerospace and automobiles provide a great potential to the development of metal additive manufacturing. Most of these techniques are fusion based and face the drawback of solidification issues and are not applicable for every alloy. Friction stir additive manufacturing (FSAM) is a family of novel techniques that utilizes friction stir welding principle for layer-by-layer additive manufacturing of materials. This technology is revered to be a breakthrough in the field of metal additive manufacturing (MAM) due to the advantages of solid-state welding which are intrinsic to these processes. The paper highlights the recent developments in the much uncharted field of friction stir additive manufacturing, introduces the major technologies of the FSAM and underscores the advantages of FSAM over its fusionbased counterparts. The paper also throws a light on the outlook and the potential of FSAM technologies in the domain of industrial manufacturing. The paper sums up by presenting some of the noteworthy research works done in this field. Keywords Metal additive manufacturing · Solid-state additive manufacturing · Friction stir additive manufacturing

1 Introduction Additive manufacturing (AM) is a technique of production based on an incremental layer-by-layer production [1]. Additive manufacturing differs from conventional machining which is subtractive in nature [2]. American Society for Testing and Materials (ASTM) F2792 defines additive manufacturing as follows: “process of joining materials to make objects from three-dimensional (3D) model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies” [3] AM is D. Shah (B) · V. J. Badheka Department of Mechanical Engineering, SOT, Pandit Deendayal Petroleum University (PDPU), Raisan, Gandhinagar, Gujarat 382007, India e-mail: [email protected] V. J. Badheka e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_2

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considered to be the most substantial manufacturing approach to have emerged over the past few decades. Its attributes like unparallel freedom in terms of design and short lead times have enticed a lot of attention in the past 15 years [4]. Moreover, AM results in products manufactured with increased accuracy, efficiency and moderates the wastage which classifies it as a sustainable manufacturing method [5]. The main advantage of AM is its ability to create almost any possible shape, and this capacity is run by the layer-by-layer manufacturing. Intricate geometries and variety of products can be handled with ease through this method. Tremendous economic growth in the market is attributed to the advent of additive manufacturing technologies. It was predicted that an asset of $3 bn would be achieved by 2016 for additive manufacturing in the industrial market [6]. The momentum in this field is still ongoing with the addition of several new techniques which are comprehensively documented in a few review papers [7, 8].

1.1 History of Metal Additive Manufacturing (MAM) In contrast to conventional, subtractive manufacturing methods, additive manufacturing (AM) is based on incremental layer-by-layer manufacturing [1]. MAM technologies are 25 years old [9], and they were used initially for rapid prototyping only. But with increase in operable thickness and builds yielding higher quality, they are being used widely. In the initial stages, these technologies were constricted to only industrial applications, e.g. developing tool inserts [10], but today they are being applied for varied applications, e.g. development of dental prostheses [11] in the field of medical surgery. Developing thick and reliable metallic parts from a number of materials like steel, aluminium, titanium, etc., is conceivable with certain MAM processes [12]. Thus, additive manufacturing has a varied spectrum ranging from rapid prototyping to rapid manufacturing applications [13]. The properties of the manufactured part are affected by the: • Type of process • Microstructure which is influenced by the process parameters.

1.2 Types of MAM Different types of processes have been developed and optimized for producing a variety of products for numerous applications. There are various classifications of AM processes in the literature. The classifications include: (a) according to the base material, such as polymers, ceramics and metals; (b) indirect and direct processes depending on the bonding method; and (c) according to the state of the raw material input, such as liquid, molten, powder and solid layer processes [14–16]. Figure 1 shows the different families of additive manufacturing. Among these seven types of technologies as classified by the American Society for Testing and

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Fig. 1 Graphic representation of the seven families of additive manufacturing that encompasses all the process for metal additive manufacturing according to ASTM F2792 Standards [29]

Materials (ASTM) [3], only a handful of technologies are actually viable for industrial application. Powder bed fusion and direct energy deposition are the two major fields that are opted for commercial applications. These are high-energy and hightemperature methods which employ the use of laser and electron beams to fabricate components. At present, the majority of multi-layered metal fabrication methods are high-energy and high-temperature methods [17–24] limited to laser-based techniques, electron beam melting and shaped metal deposition [25–28]. Laser beam melting (LBM), electron beam melting (EBM) and laser metal deposition (LMD) have the highest industrial relevance currently [2]. Though these technologies have come to the forefront by virtue of several innovations, numerous key challenges persist.

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1.3 Drawbacks of Conventional Metal Additive Manufacturing (MAM) Techniques These conventional techniques have various drawbacks. Many of the feasible methods embroil following problems: 1. The parts produced exhibit cast microstructures and inhomogeneous composition due to segregation which is a consequence of melting and solidification [30]. 2. Alloys that are susceptible to solidification cracking like aluminium, magnesium, etc., cannot be produced with sound properties with these methods. 3. Mechanical properties can be affected due to thermal residual stresses. 4. Fabrication of multi-alloy structure is constrained by metallurgical compatibility. 5. These methods are expensive, and the production is also limited due to low deposition rates (less than 1 g/min) [31]. Taking into account the discussion up till now, the objective of the paper is to explore the relatively uncharted field of FSAM technologies. This review aims at presenting an overview of the emerging field of friction stir-based additive manufacturing techniques and presents the effect and opportunities that it holds in the context of the future of the manufacturing industry. The paper has been categorized into four parts: (1) introduction of friction-based technologies in MAM, (2) basics of FSAM technologies, (3) advantages and the potential of FSAM technologies and (4) recent advancements and literature regarding FSAM.

2 Friction-Based Manufacturing 2.1 Introduction of Solid-State Welding Solid-state welding (SSW) process family consists of technologies that are used to fabricate components at temperatures that are essentially below the melting point of the workpiece in the process. Strong bonding is achieved through deformation and diffusion of material from one place to another with the help of mechanical, electrical or thermal energy. There is no melting involved in these processes, and all the hindrances involved with conventional techniques as stated in Sect. 1.3 can be surpassed by employing solid-state techniques. Thus, they hold a prominent place in the field of manufacturing technologies. Solid-state welding family consists of cold welding, ultrasonic welding, friction and friction stir welding, diffusion bonding, resistance welding and explosion welding [32]. In principle, many SSW welding processes can be utilized for additive manufacturing while ultrasonic welding and friction-based welding are the most widely utilized techniques currently. The use of SSW additive technology is being explored for the replacement of the conventional techniques especially in the aerospace and automotive industry.

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Ultrasonic seam welding was the first process to be deliberated for additive manufacturing which piloted the development of a direct metal manufacturing process, “ultrasonic consolidation” in 2001 [33]. Researchers at Boeing have manufactured large complex structures from simple building blocks through linear friction welding at Boeing [34]. Airbus [35] and Boeing [36] claimed that the technology is capable of addressing two of the specified challenges, (a) achieving high throughput leading to faster production rates and (b) less material wastage [37]. The friction stir-based techniques show great potential in the field of additive manufacturing among other solid-state techniques. As they use mechanical energy to bond the material together, they tend to be more energy efficient. Further, they are not limited by the size of material and have a vast number of different processes which can be customized according to the need of the operation and the type of material. Moreover, they show the highest synergy with conventional techniques and are very suitable for the development of hybrid processes.

2.2 Friction Stir-Based Welding Joining Techniques All friction stir-based technologies can be classified into two major categories on the basis of their application, welding and processing. The various techniques are classified according to their applications under welding and processing categories and are shown in Fig. 2. The welding techniques are fundamentally employed for material fusing and joining, while processing techniques are undertaken for applications that are intended at improving the quality of the material in terms of its mechanical, chemical and physical properties [38–40]. The friction stir equipment constitutes of a rotating tool also called the shoulder and has a protruding pin in most of the technologies listed in Fig. 2. The tool is used to generate frictional heat required for the plastic deformation of the material. The tool rotates and translates relative to the substrate with a substantial axial pressure that generates significant heat due to friction at the interface. As the heat is generated through friction produced by stirring of the tool, this family of operations is widely known as friction stir technology. The frictional heat ensures the development of a regional zone that is distinct from the tool as well as the workpiece which is known as the ‘third body region’ [42]. This plastically deformed region is characterized by solid state displaying (1) three-dimensional fluidity, (2) relatively high viscosity and (3) low flow stress [41]. These characteristics are specific only to the local third body region and allow the material to flow and mix with other material in this region. These local regions develop at temperatures ranging from the recrystallization temperature and melting point of the material that is deformed. Figure 3a, b show the welding positions and location of the third body regions in the friction stir operations using non-consumable and consumable tools, respectively. The third body region is produced either on the workpiece when the tool is nonconsumable or on the tool when the tool is consumable during the operation. The tool is the chief part of the process because it generates the required frictional heat. Further,

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Fig. 2 Classification of all the friction-based technologies based on the type of operation employed [41]

Fig. 3 Position of third body region in friction stir operations. a Non-consumable tool and b consumable tool [41]

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the concave or flat shoulder of the tool which is pushed down on the workpiece through axial force helps in containing the third body region. The sustainability of a given friction stir technology is determined by the design, material section, performance and durability of the tool [43–50].

3 Friction Stir Additive Manufacturing (FSAM) Friction-based joining for additive manufacturing was patented by White in 2004 [51], and Airbus published the first report [35] that reported the use of friction stir technology for additive manufacturing of metals in 2006, but only recently the possibility to build 3-D layers through FSAM has been explored extensively. Friction stir additive manufacturing is a welding technique of friction stir-based family as mentioned in Fig. 2. It is a novel additive manufacturing technique that employs part-by-part formation of the desired product. Although this technique has been introduced in 2004, its ability to realize higher productivity and lower loss of material had been envisaged closely afterwards [52], its actual performance in lighter constructions for essential functions has been critically evaluated and explored only recently. FSAM, being a solid-state technology, obviously has several advantages over its fusion counterparts as mentioned earlier in the paper. The friction stir-based additive manufacturing (FSAM) processes are further classified based on the joining process as Type 1 and Type 2 [41]. Type 1 is a combination of additive manufacturing and friction deposition, while Type 2 is a combination of additive manufacturing and friction stir welding.

3.1 Type 1 Friction Stir Additive Manufacturing In the type 1 FSAM, rotary friction welding is combined with friction deposition process. This family of operations employs a rotating tool that is rubbed on the workpiece to generate the frictional heat for joining. The distinguishing characteristic of these processes that a consumable tool is employed and the third body region is developed in the tool itself. The tool deposits a layer on the surface of the workpiece through which it rotates and translates. The two major processes included here are friction surfacing and friction deposition, and both work basically on the same principle, solid-state material transfer from a consumable rod onto the substrate by rubbing. Friction surfacing is a solid-state cladding technology [53]. Friction surfacing was first patented in 1941 by Klopstock and Neelands [54], but only recently the possibility for additive manufacturing through this technique has been explored [55]. It is a promising technology which is used for depositing bonded coatings on the substrate [56]. The rotating consumable tool is forced down on a flat substrate, and heat is

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Fig. 4 a Schematic of a single pass of a typical friction surfacing operation [58], b multi-layer multi-track deposit of mild steel deposited on a plate of mild steel. The first layer consists of five tracks, the second layer consists of four tracks, and the third layer consists of three tracks [30]

generated due to the friction between the mechtrode (rotating tool) and the substrate. After softening due to the heat, the part of the mechtrode at the interface undergoes plastic deformation and forms a third body region. This mechtrode is moved along the surface of the substrate where the material has to be deposited. The schematic of the process is shown in Fig. 4. The amount of heat involved is about 60–90% of the melting point of the mechtrode material [57]. After letting the first layer cool down, the process is repeated on top of the preceding layers. The process involves multiple repetitions of material deposition on an already deposited layer. Essentially, the width and thickness of the deposited track depend on the speed and diameter of the mechtrode, respectively. The friction surfacing parameters also have an effect on the deposited layer. Friction surfacing has a variety of applications. This technique has been used majorly for deposition of corrosion and wear-resistant coatings for various alloys and metals [59–64]. This process can also be utilized for repairing broken parts [65]. Friction surfacing cannot be used as a standalone process for additive manufacturing and is generally used in hybrid welding [30]. Moreover, the deposition rate is very less, and uniformity of substrate deposited is hard to control. Friction Deposition. Additive friction stir deposition is another process of Type 1 FSAM which is a modified FSW process. The rotating tool is a hollow cylinder attached to a shoulder through which feed material either as a solid rod or in powder form is delivered to the substrate surface [66]. The filler material is softened by the heat produced by the frictional resistance at the interface. The tool is then traversed along the substrate surface where the material is deposited. Subsequently, the layers are deposited on top of each other, and a 3-D structure can be prepared in such a fashion. This kind of process, where the feedstock is added through a rotating stirring

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Fig. 5 Friction deposition technique employed by aeroprobe corporation. a The schematic of the process of friction deposition [69], b the aeroprobe nozzle that employs a continuous feeding system with a self-reacting tool [69, 71, 72]

tool, was developed by Aeroprobe corporation, a company specializing in frictionbased deposition [67] which was also the first one to develop the commercialized technology based on this process [68, 69]. Their patented technology of friction stir fabrication (FSF), which was rebranded under the name of MELD technology [70], can be used for additive manufacturing, coating and repairing of varied industrial applications. As shown in Fig. 5a, the stirring tool rotates and translates relative to the substrate. The stirring tool, as shown in Fig. 5b, is a hollow cylinder with a throat that feeds the coating material to the surface of the substrate through an auger-shaped plunging tool which moves relative to the sleeve of the stirring tool. The process of depositing the material is completed by plastically deforming material from the tool and spreading it on the surface of the substrate through the translative motion. The stirring tool comprises a shoulder [72] that moves relative to the surface of the substrate. The shoulder is used for trapping and shearing the material below. The material is subjected to the frictional heat and compressive load against the substrate. As the load increases, more material is deformed. This material is trapped below the shoulder and is sheared across the substrate surface where it has to be deposited. The feed material is in the form of powder or pellet for continuous feed applications through this technology. Notably, this technology is the answer to the lower deposition rates of friction surfacing process. The deposition rate on the substrate can be controlled by the varying the parameters of the auger screw like the threads or the relative velocity between the auger and the screw [69]. This technology can produce high-strength welds and coatings. The mechanical properties of the fabricated structures match with that of the base metal and they also retain a wrought microstructure with negligible porosity.

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3.2 Type 2 Friction Stir Additive Manufacturing Another novel technique of solid-state welding is friction stir additive manufacturing using a non-consumable tool. The fundamentals of the process are analogous to friction stir lap welding (FSLW) and only differ in their functions. The type 2 FSAM, involves producing a lap joint of two sheets by FSW and then welding more sheets in a similar fashion to the existing structure in lap configuration using successive FSW operations [37]. A custom non-consumable rotating tool with the specific designed pin and shoulder parameters is inserted into the top plate. The depth of the pin is designed to enter 20–30% of the lower plate generally for efficient joining, and other parameters are varied according to the requirement. In the first step of the process, a non-consumable rotating tool produces a lap joint of the two overlapping plates in the traversing direction. This process is repeated again by placing another sheet of metal on top of the structure. The friction stir lap welding is repeated by sequentially stacking the plates on top of the welded structure, and a multi-layered build is prepared additively as shown in Fig. 6. The thickness of the final structure to be produced by Type 2 FSAM is controlled by the number of steps.

Fig. 6 Schematic of a type 2 FSAM process where a structure is built by welding four plates in lap configuration; the distinct stirred zones (third body regions) formed are highlighted by zone 1, zone 2 and zone 3 and have distinct microstructure [73]

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The heat required for the development of the third body region is generated by the frictional resistance between the shoulder and the workpiece in addition to the heat generated by the pin; severe plastic deformation is caused by the rotating and translating motion of the pin. The geometry of the pin affects the macroshape of the weld which is generated by the movement of the material from the front end to the rear of the pin. This is a solid-state welding process, and by the virtue of it, there is no melting involved [74]. The microstructural characterization is of specific interest for type 2 FSAM because of intricacies associated in terms of heat exposures, deformation and material flow from the bottommost to the topmost layer. During FSAM, the material is vigorously stirred, plastically deformed, and then, it undergoes dynamic recrystallization (DRX). Further, considering the pin length not to be greater than twice the thickness of the plates that are subsequently being welded on top each other, all the plates undergo the phenomenon of dynamic recrystallization twice except the topmost and bottommost plate. This understanding of this phenomenon is vital to understand and interpret the macro- and microstructure of the new weld. Due to multiple recrystallizations, the weld nugget has a finer grain structure and imposes a higher resistance to deformation because of Hall–Petch strengthening [75, 76]. This signifies the capability of the FSAM process to manipulate microstructures. In their study of FSAM of AA 5083, Palanivel et al. [77] reported an increase in the mechanical properties of the weld as compared to the base metal. The hardness increased by 18 percent and yield strength (YS) of 267 MPa and ultimate tensile strength (UTS) of 362 are reported after FSAM compared to the YS of 190 MPa and UTS of 336 MPa of the base metal. The process of FSAM is not immune to the defects of FSW welding. The complex process influences the material flow in the additively manufactured structure that involves a series of lap welds on top of each other and results in various kinds of defects. Most of the defects are analogous to the defects observed in a normal FSW lap and butt welds and have characterized in FSW process parameters [78–83]. Furthermore, the complexity increases due to (a) difference of grain structure in the bottom and top layers during every succeeding weld, (b) defects already present from the previous welds and (c) overlapping of the new weld nuggets on top of the old weld nuggets.

4 Scope of Friction Based Additive Technologies 4.1 Advantages of Friction-Based Additive Technologies Over Fusion AM The potential utility and capability of FSAM to penetrate the commercial market stem out from the shortcomings of the conventional techniques. Unique properties

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of this technology have a competitive edge over the conventional additive manufacturing (AM) techniques. This technology provides major advantages at two fronts: (a) increases production efficiency and (b) increases part efficiency. FSAM processes can answer the problem of energy reduction and thus decrease the production cost and more importantly have a positive impact on the environment [84]. A method is designed to calculate the mean energy consumption of fusion additive processes. The mean power required was 2–3 kW for fabricating a building according to this methodology. For the EOSINST laser-based process, the specific energy efficiency was reported between 100 and 400 MJ/kg [84]. The energy required for a friction-based process for an analogous operation was approximately 2.5% of that of the fusion-based counterpart operation [74]. This drastic difference has given much impetus to the development of FSAMs. Further, Boeing published a report in 2012 [36] that estimated an emission reduction of 60 billion pounds of CO2 and volume reduction of nearly 5 billion pounds of Al over the next 25 years using friction-based technologies. This report concluded that a shift towards friction-based technologies from conventional techniques will be a metamorphosis in the field of sustainable manufacturing space [85]. The increased part efficiency of FSAM products as compared to the fusion alternatives is due to the solid-state nature of the process. A typical laser and electron beam AM involve a much larger heat flux of ~107 W/m2 as compared to ~103 W/m2 heat flux involved in FSAM techniques [86]. Intense thermal gradients develop in the fusion-based methods because of the high heat flux which makes the welds susceptible to cast structure defects, residual stress, rapid solidification defects like cavities, porosities, thermal cracking and result in lower mechanical strength and lower weld quality. Moreover, post-weld treatments are necessary to increase the strengths of the welds. All these shortcomings are eliminated due to the intrinsic property of solidstate welding, and a part with higher structural integrity and wrought microstructure can be obtained with FSAM.

4.2 Material Feasibility of Friction Stir Additive Manufacturing The void spaces of metal additive manufacturing that are inaccessible with fusionbased technologies can be filled with friction-based additive manufacturing technologies. These technologies can be employed for welding of similar as well as dissimilar alloys. Structures of ferrous and non-ferrous alloys, pure metals and composites can be fabricated with this technique. Areas of additive manufacturing that are hard to access due to the fusion-based hindrances can be tackled with these technologies. One such area is where FSAM can contribute to additive manufacturing of metals is the manufacturing of high-strength Al alloys which are not viable using fusionbased techniques due to hot cracking [85]. Al alloys 2XXX and 7XXX which have high strength (>400 MPa) bolster the potential of FSAM because of their requirement

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in the aerospace industry. Furthermore, as mentioned earlier, the Hall–Petch strengthening ability [75, 76] in addition to the welding defects occurring due to fusion processes makes this technology ideal for additive manufacturing of lightweight Mg alloys, titanium alloys and steels. FSAM also creates the possibility of fabricating graded structures of multiple materials/alloys along with welding single alloy structures. Traditional additive manufacturing (AM) techniques face challenges in the context of manufacturing graded components due to difference in thermomechanical properties, thermal expansion coefficients and melting points. Also, the formation of undesirable inter-metallic compounds (IMCs) erodes the strength of the welds [87]. These problems can be circumvented through FSAM. The thermal expansion problem is avoided since there is no melting and only localized heat transfer owing to solid-state nature of FSAM, while the intense plastic motion and shearing action help distribute and control the size and uniformity of IMCs at the interface. Tantalizingly FSAM processes can also create custom materials and alloys in a single process. These processes can also manipulate the composition of the alloys and microstructure by dictating the mixing of materials. Friction deposition is a promising technique for creating alloys and new materials in the weld pool itself. Thus, FSAM can be considered one of the most feasible techniques for the production of functionally graded components if not the best.

4.3 Industrial Impact FSAM is a relatively new process at the industrial scale. The applications for it are in aerospace and defence. This technique can pave the way for efficient manufacturing of high-strength structural parts for aircraft and other technical parts. Also, large parts can be manufactured with these processes, and they can also be used for fabrication of entire structures of satellites and spacecraft. Production of stiffeners/stringers for the aviation industry is one of the pertinent applications of FSAM in aerospace. Potential of FSAM in the aerospace industry has been supported by the reports of Boeing [36] and Airbus 2006 [52]. They have concluded that FSAM can be used to achieve higher efficiency in terms of productivity and material loss. The developments in the friction stir welding are directly translated to the developments in this technology because their fundamental process is analogous. The FSW technique was invented by TWI in 1991, and there are 3294 patents (from 1993 to 2014) [88] registered considering this technology by various industries. Hitachi has 214 related patents, and Boeing has 67 and there are around 172 license holders for the TWI patents [89]. The industrial groups that already have access to FSW technology are the forerunners in commercializing 3D printing FSAM technologies. Groups such as UTC have patents on FSAM systems [89].

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5 Research in the Field of FSAM Although this technique has been invented in 2004 by Dawn White, only recently substantial research work has been published in this domain especially in the field of FSAM Type 2. Unlike the other fields of solid-state techniques and additive manufacturing techniques, this field has very less amount of experimental work published. The works of S. Palanivel and Rajiv Mishra are pioneers in the field of additive manufacturing through friction technologies. Table 1 categorizes notable research work in this field according to the technologies used with a brief description for reference.

6 Conclusion Friction stir-based technologies are the newest addition to the additive manufacturing technologies, and there is a lot of unrealized potential. FSAM technology is still in the developing phase and still is the potential solutions to various metal additive manufacturing challenges. A few key takeaways: 1. The structures fabricated through FSAM show greater mechanical properties as compared to that of conventional techniques due to their ability to impart finer microstructure and immunity to fusion-based defects. These properties can even exceed the wrought properties of the alloy, and thus, FSAM can pave the way for improvement in structural properties. 2. The additive nature of FSAM makes it much more vulnerable to welding defects than other friction-based operations. If the defects are formed in the initial layers of the process, they also affect the subsequent welds and can multiply. The defects grow with compounding of layers on top of each other. Current research work in the field of optimization of process parameters for FSAM is very limited, and this data can vary for different materials and a different number of layers of deposition as well. 3. FSAM has the capability to become the key technique for fabrication of highstrength multi-material structures efficiently. As discussed in the article, it overcomes the major obstacles in the production of multi-layer alloys and also creates a way to numerous other avenues in the field of functionally graded composites. 4. Though this domain has experienced a myriad of innovative trends, numerous research and development opportunities still lie unexplored. On a commercial scale, it is advisable to exploit FSAM techniques like friction deposition which are much more mature than its other counterparts. FSAM technologies are relatively complex, have a compounded mechanism and vary vastly from process to process as well as material to material. Without comprehensive research about each and every aspect of the particular FSAM process, it should not be applied on an industrial scale.

Type

FSAM Type 1

FSAM Type 1

S. No.

1

2

Experimental paper on additive friction stir of inconel 625

Experimental paper on similar and dissimilar friction surfacing of mild steel and stainless steel

Process

(continued)

This article aims at introducing additive friction stir (AFS) to develop completely dense exact shape components. In this study, the microstructure and mechanical properties of Inconel 625 (IN625) produced through AFS have been analysed. High heat applications of inconel are very useful piques the interest of the aerospace sector. Aeroprobe corporation provided the AFS fabricated specimens of IN625. A meticulous study of the samples has been reported in the article which found out a significantly refined, equiaxed grain structure produced through continuous dynamic recrystallization. The report concludes that the mechanical properties displayed significantly higher values than that of cast, wrought or materials produced by fusion-based AM for IN625 [57]

In this work, sound multi-layer deposits were realized through friction surfacing technique in both single- and multi-layer approaches. A three-layer multi-structure in the brick architecture of mild steel on a plate of mild steel with a thickness of 1 mm per layer after surface machining and total 3 mm was fabricated. Also, a single track with five layers each of 1.5 mm of AISI stainless steel; total amounting to 7.5 mm was also produced. Likewise, a multi-material structure of total thickness of 6 mm with two different alloys of stainless steel AISI 316 and AISI 410 was also built. Here, three strips (each of 1 mm) of each alloy were welded on top of the other alloy in an alternating fashion. The microstructure examination revealed an excellent inter-layer bonding, and one interesting property was the potential of this technique to make parts with completely enclosed internal features with negligible cavities. The mechanical properties were found to be at par with standard wrought counterparts [30]

Description

Table 1 Experimental and theoretical literature in the field of FSAM technologies categorized according to the type of process carried out with a brief description

Friction Stir Additive Manufacturing—A Review 27

Type

FSAM Type 1

FSAM Type 1

S. No.

3

4

Table 1 (continued)

Process

Theoretical review on friction deposition

Experimental paper on friction surfacing of Al 6351

Description

(continued)

This article is a comprehensive study on friction stir deposition technique. The interrelationship between friction deposition and friction stir welding and the complete thermomechanical process of welding at the microscopic level has been described here. Furthermore, the advantages, limitations and potential of friction deposition technique have also been reported here. A qualitative analysis between the friction deposition and other solid-state process: ultrasonic additive manufacturing and Type 2 FSAM is the highlight of the article [90]

This paper investigates the possibility of friction surfacing for Al 6351 on steel. Four types of filler rods of Al 6351 with different diameters: 8 mm, 12 mm, 16 mm and 22 mm were used for friction surfacing on a 6 mm-thick steel plate. The experiment reported varied results for different diameters of the rotating tool. For 8 mm dia., the surfacing was not possible due to bending of the tool. The 16 mm rod gave a better output than the 12 mm, but both of them gave patchy depositions nonetheless. The 22 mm rod gave the ideal output with a uniform width and thickness of the deposition. The highest temperature achieved recorded was 451 °C, and the essential finding from this experiment was that a threshold condition has to be followed in context of the diameter of the friction surfacing consumable mechtrode. Only above a certain value of the dia., friction surfacing produces sound welds, in this case, that being around 22 mm dia. of the mechtrode [55]

28 D. Shah and V. J. Badheka

Type

FSAM Type 2

FSAM Type 2

S. No.

5

6

Table 1 (continued)

Process

Experimental paper on similar FSAM of Al 7055

Experimental paper on FSAM of Mg-based WE43

Description

(continued)

This report investigates the feasibility of FSAM for aluminium 7055 alloy. A 101.6 mm structure is built by joining 15 plates of Al 7055 of equal thickness (6.7 mm each). Mechanical testing reported a yield strength of 300 MPa, ultimate strength of 382 MPa and elongation of 1.94%. This is almost a 60% reduction as compared to the base metal (YS: 552 MPa, UTS: 644 MPa, elongation: 9.55%). Heat treatment of the specimens was not effective and reported a very small increase in the properties. The probable reason for the low strength was attributed to welding defects especially cold lapping and wormholes which were revealed by the macrographic study. The report suggested that welding defects have a major influence in FSAM as compared to FSW processes due to the recurring nature of the process. Thus, welding parameter optimization is an important aspect to realize the complete potential of FSAM [91]

In this study, two multi-layered builds of a total thickness of 5.6 mm each have been fabricated from lap welding of four plates of Mg-based WE43 alloy under different welding parameters. The mechanical properties have been analysed in detail, the microstructure for various different levels of the weld has been studied individually and the defects and problems faced in welding through FSAM technique have been discussed. The study reports a higher strength (400 MPa) with considerable ductility (17%) of the welded specimen [37]

Friction Stir Additive Manufacturing—A Review 29

Type

FSAM Type 2

FSAM Type 1 and 2

S. No.

7

8

Table 1 (continued)

Process

Experimental paper on repairing of Al 7075 through FSAM

Theoretical review

Description

(continued)

This article explores the possibility of FSAM for repairing of materials. Repairing of damaged structures is of great interest to the aerospace and defence sectors. Holes and grooves were made in 7075 Al alloy. The holes were filled through Type 2 FSAM, and the grooves were filled with Type 1 FSAM with a similar filler material. There was sufficient mixing between the deposited material and the sidewalls, but the repair quality at the lower portions was not at par in both the cases. Although this technique shows promising results, much work has to be done such as finding optimized parameters to avoid defects and lack of mixing at the lower portions. A more mature technique like Refill Friction Stir Spot Welding, friction taper plug welding and filling friction stir welding should be used as they produce a much higher weld quality [92–94]. This article also bolsters the possibility of Friction deposition techniques having a vast effect on repair applications on a large scale due to its good scalability [95]

In this article, the potential for FSAM in fabricating high-performance lightweight alloys. The microstructure and strength analysis of Mg-4Y-3Nd and AA5083 are illustrated here. The hardness of the structure built through FSAM of Mg-based alloy was 120 HV, significantly higher than 97 HV of the base metal, and the same for Al-based alloy having base hardness of 88 HV was found out to be 104 HV. This review bolsters the fact that structurally stronger components can be fabricated through FSAM. The possible future trends in this technique are also predicted in this paper [77]

30 D. Shah and V. J. Badheka

Type

FSAM Type 1 and 2

FSAM Type 1 and 2

S. No.

9

10

Table 1 (continued)

Process

Theoretical review

Theoretical review

Description

This comprehensive review article is aimed at listing the recent developments in FSAM technology. This article encompasses all the frictions-based additive processes along with a critical review of the timeline of developments in this field [96]

This article comprises the complete family of all the friction-based additive technologies namely rotary friction welding (RFW), friction deposition, friction surfacing, linear friction welding (LFW), FSAM, and additive friction stir (AFS). This extensive review summarizes the innovations in this field, identifies the limitations and advantages of and also provides current and potential applications of each technology individually [85]

Friction Stir Additive Manufacturing—A Review 31

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FSAM technologies, especially Type 1 FSAM, show a high synergy with the existing additive manufacturing techniques and high-grade hybrid technologies can be developed. Distinctive advantages of FSAM coupled with other traditional methods will be an ideal tool to achieve higher process and structure efficiency. These technologies still have a lot of room to grow, and they fill the voids in the current AM market. They are a valuable addition and an integral part of the metal AM family and show promise to evolve into mainstream manufacturing.

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Processibility Analysis of Rotationally Moldable Linear Low-Density Polyethylene/Glass Fiber Blend Nikita Gupta

and PL. Ramkumar

Abstract Rotational molding is the easiest way to manufacture hollow plastic products. In this method, linear low-density polyethylene (LLDPE) is mainly used as a base resin, but pure LLDPE is unable to offer the required mechanical property in some critical applications where strength is on a considerable level. Additives proved valuable in filling out this void. In this paper, an attempt is made to evaluate the optimum range of LLDPE/glass fiber from the distinguished blends of glass fiber blended with LLDPE (15%, 20%, 25%, and 30%) resulting in better processing for rotational molding. The Fourier transform infrared spectroscopy test is considered the main investigation for evaluating the optimum percentage of the blend in order to ensure the presence of both the resins in the blend. It was found from the experiment that the concentration of glass fiber above 20% confirms negligible significance of LLDPE and 15% or below marks unsuitability as glass fiber peaks hardly prevails. Thus, it can be inferred from the experiment that approximately 20% of glass fiber combined with LLDPE can be considered as a suitable blend range, making it appropriate for rotomolding processability, ensuring that properties of both LLDPE and glass fiber are incorporated into the rotomolded product. Keywords Rotational molding · FTIR · Additives · LLDPE · Glass fiber

1 Introduction Plastics are considered over wide range of materials nowadays. The reason is obvious as it provides some salient features like light in weight, better corrosion resistivity, easily processable, etc. [1–4]. Although distinct plastic-processing techniques are available till date to the users such as thermoforming, rotational molding, injection molding, blow molding, etc., engineers need to be aware of the constraints and N. Gupta (B) · PL. Ramkumar Department of Mechanical and Aero-Space Engineering, Institute of Infrastructure Technology Research and Management, Ahmedabad, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_3

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development associated with each process [5–7]. For example, undercut is a limitation when subjected to injection molding, whereas an appropriate melting of plastic material becomes mandate when users switch to thermoforming process. Various other such drawbacks are associated with distinguished techniques [8–10]. Rotational molding process has proved its capability in overcoming all such limitations. Therefore, it has been augmented among researchers in the last few decades. Rotational molding is a method that typically fabricates thermoplastics and is majorly utilized in preparing large overhead tanks. A rotomolded product may have undercuts, inserts, and flat surfaces that become strenuous to achieve in other forms of plastic manufacturing process [11]. Even the steps involved while dealing rotational molding process is equitably easy. Disparate materials can be employed for this purpose, still a classic material variation is needed in this technique in order to increase the strength of the end product [12–15]. Consequent to this, an appropriate selection of material becomes essential when one deals with rotational molding process. Thermoplastics, from the different range of plastics are typically preferred for rotational molding process, and most of them are polyethylene. Linear low-density polyethylene (LLDPE) is largely utilized for this technique as it provides different favorable properties like low shear sensitivity and required fluidity [16–18]. But the mechanical properties of these polymers are fairly low, and rotomolded goods, on the other hand, find large-scale applications in the areas where strength is given full consideration like battle tanks, kayaks, etc. [19–21]. In the past decades, an ample amount of noteworthy work has been reported in the field of rotational molding, in order to address the limitations associated with it. Various experiments have been outlined based on adding fillers or additives with the base resin aiming the enhancement of mechanical properties in the rotomolded product. The numerous methods that researchers have developed in recent years till date include the blend or composite preparation utilizing particle reinforcement, nano fillers or short fibers [22–27]. For every research linked with utilizing fiber addition to prepare composites, there are various constraints that make the blend unsuitable to some extent for rotomoldability. These restraints can be either in terms of material processibility or mechanical characterization of the end product. For instance, particle reinforcing with the base resin increases brittleness in the fabricated part. Moreover, the concentration of additives beyond a particular percentage even increases the viscosity of the blend, making it unsuitable in terms of fluidity [21]. Further, the resin and additives usually have differences in the density, which agglomerates the heavier particle on the outer surface of the product deteriorating its mechanical property. Work related to the incorporation of fillers has therefore been largely on the research mode since ages to satisfy the required strength requirement in the end product. For the particular study, an endeavor has been made to investigate an appropriate mixing of glass fiber being concentrated with linear low-density polyethylene (LLDPE) so as to achieve necessary strength of rotomolded product for further analysis. For proper mixing and to get an optimum blend, characterization of glass fiber (GF) mixed with LLDPE is carried out using Fourier transform infrared technique (FTIR). From the analysis, perfect mixing between both the materials is acquired.

Processibility Analysis of Rotationally Moldable Linear …

39

In addition to examining the mechanical properties of the end product in order to analyze the compatibility of the additive with the base resin, the assessment of material processability becomes important. The processability study helps to achieve an optimal blend range from the specific prepared mixture of fiber combined with base resin to verify the potential of material sustaining rotomoldability. Research regarding the processability of LLDPE/glass fiber blend for rotational molding process is seldom available until date to the author’s knowledge. For this reason, FTIR has been considered as the initial preliminary analysis to be followed by distinguished processability investigation methods such as melt flow index test, shear stress-based fluidity analysis, thermal behavior of material, weatherability, and so on. The paper outline begins with the experimental details which include the procurement of material. The experiments were conducted after material availability that included FTIR technique in order to justify the significance of the peaks of both LLDPE and glass fiber. Through the test, the optimal percentage of glass fiber that needs to be combined with LLDPE has been suggested that will produce preferable processibility assuring the presence of both the resin and additive.

2 Experimental Procedure 2.1 Materials The materials used for the present investigation are linear low-density polyethylene (LLDPE) and glass fiber. Greenage Industries Ltd., Ahmedabad, India, provided with pure LLDPE of rotomolded grade Ge3645 having MFI 4.5 g/10 min and 0.936 g/cm3 density. For glass fiber, a 2.55 g/cm3 density E-glass fiber was purchased from HS Enterprise, Ahmedabad, India, which was used as an additive. The sample being prepared in the laboratory by mixing 15%, 20%, 25%, and 30% of glass fiber with LLDPE are as shown in Fig. 1. The sample is dry blended using Electromix industrial mixer with the percentage by weight fraction of glass fiber with LLDPE. In order to characterize the blend of LLDPE and glass fiber, Fourier transform infrared technique has been considered for experimentation.

2.2 Equipment Used Fourier transform infrared technique (FTIR) Basically, a Perkin Elmer FTIR Spectrum Two Universal ATR has been utilized to obtain the peaks by transmitting the infrared light on the atomic level of the material. Transmission data were collected within the range of 450–4000 cm−1 . The interval of data was maintained as 1 cm−1 . A prior resolution set beforehand was 4 cm−1

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Fig. 1 Sample preparation with various blends of glass fiber mixed into LLDPE

for the particular experiment. The transmission and absorption bands are obtained from this spectrometer which is analyzed in Perkin Elmer software. Such bands are then correlated with the compound’s bands of absorption or transmission existing in the given sample from the available literature. Ethanol was used in order to ensure proper cleaning of ATR crystal after every the testing of every sample.

3 Result and Discussion The characterization is achieved using FTIR by transmitting light through the substance atoms. Several characteristic peaks are obtained with this phenomenon which gives information about the existing bond in the substance. For example, the Perkin Elmer library recognizes significant peaks at 2915, 2845, 1467, 1462, 1377, 730, 717 cm−1 for pure LLDPE. These peaks signifies some peculiar bonds like H=O, C=O, CH2 , and other similar bonds present in pure LLDPE. So, one can define the characteristic peak curves for pure LLDPE. Similarly, glass fiber has distinctive peaks that range from 3200 to 3600 cm−1 . N–H/O–H compound when bonded to C and Si shows relevance at peaks 3200–3600 cm−1 . Similarly, a group of aliphatic and aromatic compound gets their dominant peaks at the value of 2965–2873 cm−1 which depicts the extending bond of carbon and hydrogen bond like CH3 , CH2 , CH, etc. Band at 1735 cm−1 compares to extending of C=O in esters/carbonyl and 1100 cm−1 gives C–O and Si–O bond [28]. From the data available from literature, characterization peaks of both the materials (LLDPE and glass fiber) are identified. Now, the blend made with 15% to 30% by weight of glass fiber blended with LLDPE is characterized using FTIR. The particular concentration of glass fiber is considered to be optimum in LLDPE where the

Processibility Analysis of Rotationally Moldable Linear … Fig. 2 Spectra of 15% GF with LLDPE

41 Transmittance

98

Transmittance (%)

96 94 92 90 88 86 4000

3500

3000

2500

2000

1500

1000

500

Wavenumber (cm-1)

evidence of peaks both LLDPE and glass fiber are significantly observed. Then, it can be said that the particular range selected is on the basis of considering the spectra where dominance of peaks of both the materials is maintained. With all the samples being characterized, at 15% glass fiber with LLDPE, as shown in Fig. 2, shows the peak value of only LLDPE, as C–O and Si–O bond of glass fiber is inevident, so 15% or below it is not viable. Similarly, for 30% glass fiber and LLDPE blend, LLDPE makes lesser significance as the spectra obtained from FTIR do not show peaks of it, which is depicted in Fig. 3, where the dominance of glass fiber peak prevails. Hence, 30% LLDPE/GF blend is less feasible. Now, with the experiments performed for 20% and 25%, as shown in Figs. 4 and 5, respectively, from the said range, the noteworthiness of peak of both the materials 100

Fig. 3 Spectra of 30% GF with LLDPE

Transmittance

Transmittance (%)

98 96 94 92 90 88 86 4000

3500

3000

2500

2000

1500

Wavenumber (cm-1)

1000

500

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Fig. 4 Spectra of 20% GF with LLDPE

Transmittance

98

Transmittance (%)

96 94 92 90 88 86 4000

3500

3000

2500

2000

1500

1000

500

Wavenumber (cm-1)

100

Fig. 5 Spectra of 25% GF with LLDPE

Transmittance

Transmittance (%)

98 96 94 92 90 88 86 4000

3500

3000

2500

2000

1500

1000

500

Wavenumber (cm-1)

can be seen at 20% of glass fiber dry mix with the base material LLDPE. This type is similar work that is found to be in agreement with past literature where Meireles et al. checked the compatibility of waste materials with polystyrene (PS). They observed the inexistency of CH2 vibrating bond beyond 30% PS which suggested to utilize the blend below 30% PS miscible with the waste materials [29]. Hence, the optimal blend can be recognized where both the peaks of LLDPE and glass fiber is dominant, so that it can reflect the properties and characteristic of both the material. Experiments showed the graphs of spectra which clearly revealed that the dominance of peaks of both the powders is highly reflected at a mixture of 20% of glass fiber blended with LLDPE.

Processibility Analysis of Rotationally Moldable Linear …

43

4 Conclusion The strength of the product with other adequate mechanical properties is of paramount importance for any rotomolded product. Much work is underway to improve the strength of rotomolded product. For this process, LLDPE is largely used as a charge material, since it deliberately provides unique flow characteristics. However, in providing the requisite strength it finds its deficiency. Hence, an attempt is made to blend LLDPE with Glass Fiber. An optimum mixture is an adequate requirement for any prepared composite. So the experiments were performed to identify an appropriate blend of glass fiber with LLDPE. To achieve this, a dry mixture in powder form was prepared with 15%, 20%, 25%, and 30% by weight fraction of glass fiber mixed with LLDPE. The sample was then characterized, and the experiments were performed using FTIR. The results obtained were in the form of the spectrum graphs acquired by FTIR. The peaks obtained resemble the distinctive characteristics present in the specific sample being examined for the various compounds. LLDPE and glass fiber are maintained when 20% of glass fiber weight is combined with LLDPE. As a result, the optimum blend can be suggested as 20% of glass fiber concentrated with LLDPE ensuring adequate blend miscibility.

References 1. Ramkumar PL, Kulkarni DM (2016) Impact strength investigation of foamed linear low density polyethylene in rotational moulding process. Int J Mater Eng Innov 7:159. https://doi.org/10. 1504/IJMATEI.2016.084617 2. Hou L-D, Li Z, Pan Y, Sabir M, Zheng Y-F, Li L (2016) A review on biodegradable materials for cardiovascular stent application. Front Mater Sci 10:238–259. https://doi.org/10.1007/s11 706-016-0344-x 3. Bart JCJ (2005) Additives in polymers: industrial analysis and applications. Wiley, Hoboken 4. Abdullah AHD, Putri OD, Fikriyyah AK, Nissa RC, Intadiana S (2020) Effect of microcrystalline cellulose on characteristics of cassava starch-based bioplastic. Polym Technol Mater 59:1250–1258. https://doi.org/10.1080/25740881.2020.1738465 5. Ramkumar PL, Kulkarni DM, Abhijit VVR, Cherukumudi A (2014) Investigation of melt flow index and impact strength of foamed LLDPE for rotational moulding process. Procedia Mater Sci 6:361–367. https://doi.org/10.1016/j.mspro.2014.07.046 6. Ramkumar PL, Kulkarni DM, Chaudhari VV (2014) Parametric and mechanical characterization of linear low density polyethylene (LLDPE) using rotational moulding technology. Sadhana 39:625–635. https://doi.org/10.1007/s12046-013-0223-4 7. Toom K, Miller PF (2018) Ethics and integrity. Elsevier Inc., Amsterdam 8. Crawford RJ (1996) Recent advances in the manufacture of plastic products by rotomoulding. J Mater Process Technol 56:263–271. https://doi.org/10.1016/0924-0136(95)01840-9 9. Crawford RJ, Nugent P, Xin W (1991) Prediction of optimum process conditions for rotomolded products. Int Polym Process 6:56–60. https://doi.org/10.3139/217.910056 10. Gupta N, Ramkumar P, Sangani V (2020) An approach toward augmenting materials, additives, processability and parameterization in rotational molding: a review. Mater Manuf Process 1–18. https://doi.org/10.1080/10426914.2020.1779934

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11. Crawford RJ, Throne JL (2002) Rotational molding polymers. In: Rotational molding technology. Elsevier, Amsterdam, pp 19–68 12. Ramkumar PL, Kulkarni DM, Chaudhari VV (2019) Fracture toughness of LLDPE parts using rotational moulding technology. Int J Mater Prod Technol 58:305. https://doi.org/10.1504/ IJMPT.2019.100003 13. Jamshidi S, Sundararaj U (2015) Improvement of barrier properties of rotomolded PE containers with nanoclay. In: AIP conference proceedings, p 070014 14. González-López ME, Pérez-Fonseca AA, Cisneros-López EO, Manríquez-González R, Ramírez-Arreola DE, Rodrigue D, Robledo-Ortíz JR (2019) Effect of maleated PLA on the properties of rotomolded PLA-agave fiber biocomposites. J Polym Environ 27:61–73. https:// doi.org/10.1007/s10924-018-1308-2 15. Madhu P, Sanjay MR, Jawaid M, Siengchin S, Khan A, Pruncu CI (2020) A new study on effect of various chemical treatments on Agave Americana fiber for composite reinforcement: physico-chemical, thermal, mechanical and morphological properties. Polym Test 106437. https://doi.org/10.1016/j.polymertesting.2020.106437 16. Sitticharoen W, Chainawakul A, Sangkas T, Kuntham Y (2016) Rheological and mechanical properties of silica-based bagasse-fiber-ash-reinforced recycled HDPE composites 52:421– 432. https://doi.org/10.1007/s11029-016-9594-z 17. Waigaonkar S, Babu BJC, Durai Prabhakaran RT (2008) A new approach for resin selection in rotational molding. J Reinf Plast Compos 27:1021–1037. https://doi.org/10.1177/073168440 7086629 18. Ramkumar PL, Waigaonkar SD, Kulkarni DM (2016) Effect of oven residence time on mechanical properties in rotomoulding of LLDPE. Sadhana Acad Proc Eng Sci 41:571–582. https:// doi.org/10.1007/s12046-016-0489-4 19. Boujelben M, Abid M, Kharrat M, Dammak M (2020) Production and mechanical characterization of LLDPE biocomposite filled with almond shell powder. Polym Polym Compos 096739112091086. https://doi.org/10.1177/0967391120910869 20. Ogah OA (2017) Rheological properties of natural fiber polymer composites. MOJ Polym Sci 1:147–148. https://doi.org/10.15406/mojps.2017.01.00022 21. Ramkumar P, Panchal Y, Panchal D, Gupta N (2020) Characterization of LLDPE/coir blend using FTIR technique. Mater Today Proc. https://doi.org/10.1016/j.matpr.2020.04.819 22. Planes E, Duchet J, Maazouz A, Gerard J-F (2008) Characterization of new formulations for the rotational molding based on ethylene–propylene copolymer/graphite nanocomposites. Polym Eng Sci 48:723–731. https://doi.org/10.1002/pen.21012 23. Calò E, Massaro C, Terzi R, Cancellara A, Pesce E, Re M, Greco A, Maffezzoli A, GonzalezChi PI, Salomi A (2012) Rotational molding of polyamide-6 nanocomposites with improved flame retardancy. Int Polym Process 27:370–377. https://doi.org/10.3139/217.2552 24. Yan W, Lin R, Bhattacharyya D, Bickerton S (2003) Rotational moulding of particulate reinforced polymeric shell structures. Mater Sci Forum 437–438:235–238. https://doi.org/10.4028/ www.scientific.net/MSF.437-438.235 25. Tasdemir M (2017) Effects of olive pit and almond shell powder on polypropylene. Key Eng Mater 733:65–68. https://doi.org/10.4028/www.scientific.net/KEM.733.65 26. Ferrero B, Fombuena V, Fenollar O, Boronat T, Balart R (2015) Development of natural fiberreinforced plastics (NFRP) based on biobased polyethylene and waste fibers from Posidonia oceanica seaweed. Polym Compos 36:1378–1385. https://doi.org/10.1002/pc.23042 27. Gholampour A, Ozbakkaloglu T (2020) A review of natural fiber composites: properties, modification and processing techniques, characterization, applications. J Mater Sci 55:829–892. https://doi.org/10.1007/s10853-019-03990-y 28. Jung MR, Horgen FD, Orski SV, Rodriguez CV, Beers KL, Balazs GH, Jones TT, Work TM, Brignac KC, Royer S-J, Hyrenbach KD, Jensen BA, Lynch JM (2018) Validation of ATR FT-IR to identify polymers of plastic marine debris, including those ingested by marine organisms. Mar Pollut Bull 127:704–716. https://doi.org/10.1016/j.marpolbul.2017.12.061 29. Meireles S, Filho GR, De Assunc RMN, Zeni M (2007) Blend compatibility of waste materials—cellulose acetate (from sugarcane bagasse) with polystyrene (from plastic cups): diffusion of water, FTIR, DSC, TGA, and SEM study. https://doi.org/10.1002/app

Feasibility of Joining Aluminum to Nylon Using Friction Stir Welding (FSW) Nitesh Kumar Jha, Darshit K. Desai, and Vishvesh J. Badheka

Abstract Friction stir welding has been showing the promising result for joining the thermoplastic and aluminum over conventional joining because of heat produced by friction rather than direct flame. In the coming future, the joining of aluminum and thermoplastic will make innovative manufacturing due to its lightweight and high strength-to-weight ratio. This experimental work comes up with the feasibility of joining dissimilar material through numerous process parameters such as changing position, offset, and tool rotation. The dissimilar joining (butt joint) of aluminum and nylon with the thickness of 6-mm plate was executed by friction stir welding (FSW). We started our work by varying the tool rotational speed from 270 to 540 rpm by fixing the traverse speed. The further experiment was carried by varying the position of material taking the constant tool speed and under various offsets. It was perceived that to gain an effective joint process parameter plays a significant role. Keywords Friction stir welding · Aluminum · Nylon · Dissimilar joining

1 Introduction In recent days, the use of aluminum and its alloys, and thermoplastic is more due to their dominant mechanical properties such as high strength-to-weight ratio, relatively low cost, non-magnetic and corrosion resistance properties. They are used in the fledgling aeronautical industry, missile, and automobile (supercars) industry [1]. In the case of aerospace and automobile industry, it reduces the weight [2]. Aluminum and plastic give a high degree of freedom for design as well as manufacturing of products, so fabrication or joining is very important [3, 4]. There are N. K. Jha (B) · D. K. Desai · V. J. Badheka Department of Mechanical Engineering, Pandit Deendayal Petroleum University, Gandhinagar 382007, India e-mail: [email protected] V. J. Badheka e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_4

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three techniques used for the fabrication of metal and thermoplastic parts (dissimilar material). 1. Mechanical fastening 2. Adhesive bonding 3. Solid-state welding [5]. But each welding process has some limitation, Mechanical Fastening (Riveting) such as increment in weight of component and stress rivets holes lead to stress concentration, which debases the strength as well as generates corrosion, an additional limitation of Adhesively bonded joints often fail instantaneously instead of progressively that is why forecasting can be burdensome (life Span). This limitation restricts the use of mechanical fastening and adhesive bonding joining techniques that is why the new technique used is welding [6]. In welding, conventional processes (SMAW, GTAW, and GMAW) cannot be used due to the high heat input fusion process which results in metallurgical distortion and also melting temperature of metals is extremely high compared to the melting temperature of thermoplastic. Hence, polymers tend to degrade before metals melt so new promising techniques can be used for joining of dissimilar materials like ultrasonic welding, laser welding, and friction stir welding and each process amounts to advantages and limitation [7]. Ultrasonic welding is widely used for overlap joining with a small amount of plate thickness (1–2 mm) [5]. During laser welding, heat generated is maximum so polymers tend to degrade before metal; due to this, we acquire to use the joining technique known as friction stir welding in our research [7]. It is a solid-state joining technique in which non-consumable tools in the absence of filler wire and pressure may or may not be used to join the components [8, 9]. The tool used in friction stir welding is having two parts that are pin and shoulder which is pushed inside the adjoining edges of two different or the same material where the material is in the form of plates. When shoulders come in contact with the material to be joined, friction takes place between them and results in heat generation and pin shows its importance in the movement of material in such a way that material flows from the front to the back of the pin. This process results in solid-state welding [9]. The schematic of friction stir welding is shown in Fig. 1. The intension of this experimental work is to assess the feasibility of the FSW joint between the aluminum alloy and nylon plates in butt joint configuration and also exhibit the effects of process parameters such as material position, tilt angle, offset, and tool rotation.

2 Experiment Procedures The joining experiments were steered on a vertical milling machine (VMC) as shown in Fig. 2. The fixture used during the welding process is shown in Fig. 3 made of stainless steel. Commercial aluminum (Al) plates and nylon sheets having a thickness of 6 mm were joined by friction stir welding. Initially, the specimen was cut into

Feasibility of Joining Aluminum to Nylon Using Friction …

Fig. 1 Friction stir welding

Fig. 2 Friction stir welding, an FSW setup at Pandit Deendayal Petroleum University

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Fig. 3 FSW fixture

100 mm × 50 mm × 6 mm. A tapered steel tool having shoulder diameter 20 mm, pin length 5 mm, and pin diameter 6 mm at root and 4 mm at the tip has opted as shown in Fig. 4. The initial trial was conducted on nylon to nylon to read the parametric range. The heat is generated by friction between the tool and the workpiece which leads to softening the material around the pool area, and the rotation of the tool along with translation motion helps to distribute the material. The chemical composition of nylon 6 can be indicated by chemical formula (C12 H22 N2 O2 )n , and in the same way, aluminum 6061-T6 is composed of different other chemicals as demonstrated in Table 1. Experiments were carried out in three different ways initially rpm to 31.5 mm/min, tilt angle—1°, offset—7 mm toward the aluminum, AS—aluminum RS—nylon, and these parameters are constant throughout the process. Having the above parameter fixed, the variable spindle speed experiments were performed. Observation is presented in Table 2. Fig. 4 Tool used in the joining process during the experiment carried

a. Actual design

b. Schematic of tool design

Aluminum

95.80–98.60

Constituents

Wt%

0.040–0.37

Chromium 0.15–0.41

Cupper

Table 1 Chemical composition of Aluminum 6061-T6 Max. 0.75

Iron 0.8–1.21

Magnesium Max. 0.14

Manganese

0.40–0.80

Silicon

Max. 0.150

Titanium

Max. 0.250

Zinc

Feasibility of Joining Aluminum to Nylon Using Friction … 49

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Table 2 Experiments carried out by changing the spindle speed S. No.

Spindle speed (rpm)

Feeds (mm/min)

Tilt angle (°)

Offset (toward AL) (mm)

Advancing side (AS)

Retracting side (RS)

1

270

31.5

1

7

Al

Nylon

2

380

31.5

1

7

Al

Nylon

3

545

31.5

1

7

Al

Nylon

Table 3 Experiments carried out by changing the position of a specimen S. No.

Spindle speed (rpm)

Feeds (mm/min)

Tilt angle (°)

Offset (toward AL) (mm)

Advancing side (AS)

Retracting side (RS)

1

380

31.5

1

7

Al

Nylon

2

380

31. 5

1

7

Nylon

Al

Table 4 Experiments carried out by changing the offset toward aluminum S. No.

Spindle speed (rpm)

Feeds (mm/min)

Tilt angle (°)

Offset (toward AL) (mm)

Advancing side (AS)

Retracting side (RS)

1

380

31.5

1

7

Al

Nylon

2

380

31.5

1

3

Al

Nylon

The second investigation was carried out where the spindle speed was maintained constant along with other parameters just by changing the advancing and retracting side. In one case, we maintained the aluminum in advancing side, and in another case the aluminum was maintained in the retracting side. The different variables are shown in Table 3. In the third experiment set by changing the offset at starting, the offset was kept 7 mm toward aluminum and then it changed the offset to 3 mm toward the aluminum. All the variables are shown in Table 4.

3 Result and Discussion The aluminum and nylon plates of 100 × 50 × 6 mm (length × breadth × height) as shown Fig. 5 are joined using a friction stir welding where at the abutting edges of plates the tool rotates. In Fig. 5a, the image shows the welding at 270 rpm where the heat generated is not enough to melt the nylon and it results in poor welding. The surface cavity is seen throughout the weld because of low heat generated, and nylon

Feasibility of Joining Aluminum to Nylon Using Friction …

a

c

e

51

b

d

f

Fig. 5 Welded joint; a spindle speed 270 rpm front side; b spindle speed 270 backsides; c spindle speed 380 front sides and spindle speed 380 backside; e spindle speed 545 front sides; f spindle speed 545 backside

does not melt properly as seen in the weld surface. Figure 5b shows the backside view of the joint indicating that some part of nylon is exchanged with Al.

3.1 Effect of FSW Parameter (Spindle Speed) The joint obtained from 380 rpm does not show any gap between two specimens as shown in Fig. 5c, and the proper distribution of material is seen due to the required heat generated. It is observed that no cavity is formed and the burning of nylon does not take place; even the flash produced on both sides is negligible; these indicate the fissile joint. The back view is shown in Fig. 5d; it clarifies the interlock between nylon and Al. The joint obtained from 545 rpm seems to have an overmelting of nylon which lacks a proper joint. An excessive flash of nylon can be observed as well as the slag formed in the weld surface and burning of plastic took place clarifying excessive heat. The backside view is shown in Fig. 5f where it is observed maximum amount of nylon is in Al side making good interlock between them.

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Fig. 6 Welded joint by changing the aluminum to retracting side front side coupon

Fig. 7 Welded joint by changing the aluminum to retracting side and backside coupon

3.2 Effect of Material Position It was observed that the joint seems to be better at 380 rpm having free from welding defect, so it was decided to initiate the joining process by varying the offsets and position of material specimens. When with the same parameter used in 380 rpm, we just change the Al to the retracting side, we observed that there was much difference in terms of surface finish of the joint along with flash seen on both Al and nylon parts as shown in Fig. 6. When we observe the backside of the joint, an amount of nylon was found to be on Al sides which gives us clarity about the possibility of joining the nylon to aluminum shown in Fig. 7.

3.3 Effect of Offset Further, experiments were performed under changing the offset. Figure 8a shows the welding done by taking offset 7 mm toward aluminum, and the weld finish was stable and seems fully distribution of two materials. When we observed backside of welded component, it shows that some part of aluminum is placed over nylon which gives the idea of the good joint. In the second experiment, the offset to 3 mm toward aluminum and joint formed is shown in Fig. 8c. It can see the surface where the slag is formed making the gap between the weld and the flash formed clearly visible. Under the root side, some part of molten nylon was spread all over the aluminum in an irrespective manner which looks like the poor quality of the weld as shown in Fig. 8d because when at less offset that means nylon has developed excessive heat.

Feasibility of Joining Aluminum to Nylon Using Friction …

53

a

b

c

d

Fig. 8 Welding changing offset; a offset 7 mm toward the aluminum front side; b offset 7 mm toward the aluminum backside; c offset 3 mm toward the aluminum front side and offset 3 mm toward the aluminum backside

4 Future Scope In the future, welded joints will be subjected to mechanical and metallurgy characterization of the welded joints and implementation in different manufacturing areas.

5 Conclusion Through the different experiments conducted, it can be concluded that solid-state welding is feasible for two materials that are nylon and aluminum. When the heat generated is more, then it is very critical to obtain the sound joint. At 380 rpm, sound joint was reported. By changing the advancing and retracting side, there is a vast difference in weld surface quality. Generally, the maximum offset is half of the pin diameter but in this case, it was 7 mm toward the aluminum for the sound joint. Offset at 3 mm, the weld quality does not sound well and excessive heat was produced as well. Acknowledgements The authors would like to thank the Student Research Program of Office of Research and Sponsored Program, Pandit Deendayal Petroleum University (PDPU), Gandhinagar, India, for providing necessary support and infrastructure to carry out this work under project No.: ORSP/R&D/SRP/2019-20/1454/61. The whole experimentation was carried out on a Vertical Machining Centre available at Pandit Deendayal Petroleum University gained under funding from the Department of Space, Indian Space Research Organisation, Government of India, Bangalore (collaboration with Space Applicant Center, Ahmedabad) under the RESPOND program (Project number-ISRO/RES/4/567/09-10).

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References 1. Thompson FC (1956) Welding of aluminum and its alloys, vol 177, no 4508 2. Prasad Rambabu VVK, Eswara Prasad N, Wanhill RJH (2017) Aerospace materials and material technologies. Aerospace material technologies, vol 1, p 586. https://doi.org/10.1007/978-98110-2134-3 3. Patel AR, Kotadiya DJ, Kapopara JM, Dalwadi CG, Patel NP, Rana HG (2018) Investigation of mechanical properties for hybrid joint of aluminium to polymer using friction stir welding (FSW). Mater Today Proc 5(2):4242–4249. https://doi.org/10.1016/j.matpr.2017.11.688 4. Dalwadi CG, Patel AR, Kapopara JM, Kotadiya DJ, Patel ND, Rana HG (2018) Examination of mechanical properties for dissimilar friction stir welded joint of Al alloy (AA-6061) to PMMA (Acrylic). Mater Today Proc 5(2):4761–4765. https://doi.org/10.1016/j.matpr.2017.12.049 5. Temesi T, Czigany T (2020) Integrated structures from dissimilar materials: the future belongs to aluminum–polymer joints. Adv Eng Mater 2000007. https://doi.org/10.1002/adem.202000007 6. Meyer SP, Jaeger B, Wunderling C, Zaeh MF (2019) Friction stir welding of glass fiber-reinforced polyamide 6: analysis of the tensile strength and fiber length distribution of friction stir welded PA6-GF30. IOP Conf Ser Mater Sci Eng 480(1). https://doi.org/10.1088/1757-899X/480/1/ 012013 7. Hajili S (2018) Welding processes for joining dissimilar metals and plastics, pp 12–14 8. Mehta KP, Badheka VJ (2016) A review on dissimilar friction stir welding of copper to aluminum: process, properties, and variants. Mater Manuf Process 31(3):233–254. https://doi.org/10.1080/ 10426914.2015.1025971 9. Mishra RS, Ma ZY (2005) Friction stir welding and processing. Mater Sci Eng R Rep 50(1– 2):1–78. https://doi.org/10.1016/j.mser.2005.07.001

Rejection Rate Minimization of Cast Iron Components Through Metallurgical Analysis K. Santhy and D. R. Rajkumar

Abstract Many small-scale industries are producing various components by sand casting method. The rejection rate of these components is reasonably high which can reduce by proper failure analysis. The current work involved detailed investigation on rejections, and its causes of ductile and grey cast iron components such as harvest cup, chain link, and non-return valve in an industry. Initially, the major defects which cause the significant rejection of the products are identified by visual inspection. First analyses were carried out to understand the causes for the defects by permeability test, moisture determination test, grain fineness test, swelling index of bentonite test, green compression strength test, loss of ignition test, mould hardness test and refractoriness test for sand and mould; secondly, chemical composition was analysed before and after inoculation addition by spectroscopy test. It helps to identify if the carbon equivalent falls in the required range or not. Thirdly, microstructure of the material was studied before and after etching by employing optical microscopy test and phase analysis by XRD. In addition, the mechanical properties of the cast materials were studied using UTM and fractography study with the help of SEM. Based on the consideration of test results, procedures adapted in the casting process and environment condition, suitable corrective actions are recommended to reduce the rejection rate of the components. Keywords Defect analysis · Ductile and grey cast iron · Sand and mould test · Microstructure · Materials characterization · Mechanical testing

K. Santhy (B) Department of Materials and Metallurgical Engineering, Indus Institute of Technology and Engineering, Indus University, Ahmedabad 382115, India e-mail: [email protected] D. R. Rajkumar Department of Mechanical Engineering, CARE Group of Institutions, Tiruchirappalli 620009, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_5

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1 Introduction Casting is widely used in an industry to make large and or complicated components which cannot be obtained by metal forming techniques. The advantage of casting is inexpensive and relatively simple. Particularly sand casting has its own traditional history. But, cast product always carries risk of failure during the manufacturing process. The good sand casting component depends on many parameters such as designing of component, proper preparation of mould, pouring temperature of metal, and property of sand. The knowledge of process parameter and its consequence in defects help out to minimize the rejection rate of the products. Present work concentrates on the defect analysis of harvester cup, chain link and non-return valves using process parameter in an industry. A harvester cup is used as a guide way in harvester vehicle. The chain link is used over the conveyer belt for transferring like coal in a thermal plant. Both the components are made up of ductile cast iron and casted in single process. Using solidworks software [1], harvester cup and chain link are shown in Fig. 1a, b, respectively. Check valve is used in the compressor to maintain the diverse pressure in various parts. The check valves are obtained by non-return valves. Figure 1c shows the non-return valves outline using solidworks [1]. The non-return valves are made up of grey cast iron. The process flows followed by the foundry for production of grey and ductile cast iron are shown in Fig. 2. Both the ductile and grey cast iron have significant metallurgical properties at low cost [2, 3]. Magnesium (Mg) has high affinity towards sulphur and oxygen. However, Mg is added purposely in induction furnace to remove the impurities such as sulphur and oxygen which is called as magnesium treatment. The shape, size and quantity of graphite and or cementite play a vital role in the properties of cast iron. In addition, the length of graphite flake plays important role in damping nature of the component [4]. Normally, inoculants added for graphite nucleation. In grey cast iron, inoculation agent such ferrosilicon is added in ladle to avoid fading effect. Ductile cast iron requires both spheroidizing and inoculation to get required microstructure and properties. To remove impurities like sulphur and oxygen and spheroidizing, magnesium treatment is required for ductile cast iron. The choice of magnesium treatment

Fig. 1 Cast components. a Harvester cup, b chain link and c non-return valves using solidworks software (Solidworks 2015)

Rejection Rate Minimization of Cast Iron Components …

Raw materials

57

Ductile Cast iron

Mg Treatment & Inoculants

Induction furnace (1550˚C) Sand Binder Additives Water

Ladle (1450˚C)

Sand mixer

Mould

Sand reclamation

Casting

Scraps

Grey Cast iron

Inoculants

Fettling

Cleaning Fig. 2 Casting process of grey and ductile cast iron

will vary based on the furnace and individual foundry circumstances [5]. In ductile cast iron, inoculation agent such cerium (Ce) is added in induction furnace itself which produces nodular form of graphite followed by cementite phase. The inoculate Ce and slow solidification normally promotes formation of chunky graphite [6]. In industry, to minimize the slag inclusion and smooth metal flow, ceramic filter is used in the gating system. The nodularity of graphite varies with respect to thickness of the component [7]. This work concentrates on the major defects on the selected components which nurtures the rejection rate and its cause. The defect formation is due to material, machine, method and man (4M’s). Hence, various experimental tests have been extensively conducted starting from raw material to manufacturing process. For better understanding and supporting the decisions on the selected components, metallurgical and mechanical testing is also done.

2 Experimental Procedure Due to the presence of various defects in cast products, during inspection 30–45% of harvester cup, chain link and non-return valves are rejected. Some of the defects in the components are shown in Fig. 3, and the corresponding percentage of rejection

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Fig. 3 Some of defects present in cast products

due to defects in the components is listed in Table 1. The raw materials such as cast iron and sand play a vital role. Hence, the qualities of foundry sand studied by various test as per Indian standard [8]. The sand which is used for casting should have specific properties at low and high temperatures. It is extremely critical and affects the casting quality. Including refractoriness of sand measured in terms of pyrometric cone equivalence. At design point of view sprue, runner, and gate ratio are compared with Indian and ASM standards. The chemical composition of cast iron before and after inoculants addition is studied using spectroscopy. In addition, microstructure Table 1 Rejection rate (in %) of products based on various defects

Defects

% of rejection

Sand pour

15

Sand crush

15

Harvester cup Chain link Non-return valves 15 15

Veining defect 5

5

Porosity

10

10

Sand burn

13

Mismatch

9

Blow holes

5

Run out

3

Rejection Rate Minimization of Cast Iron Components …

59

and mechanical properties of cast iron such as yield strength (YS), tensile strength (TS) and percentage of elongation are studied with help of ultimate tensile machine and fractography using scanning electron microscopy (Tescon Vega 3 SBH model). Phases present in grey and ductile cast iron are confirmed by employing XRD (Rigaku Miniflux 600 model).

3 Results and Discussion Table 2 shows the various test result of casting sand for ductile and grey cast iron [9]. The optimum moisture content is necessary for quality moulds and good casting [10]. Moisture content for all the three components lies within expected range such as 2.8–4.6% for effective moulding practice. Compatibility of green sand for casting grey cast iron lies below the expected range. This shows that the binder efficiency is less than the required limit. On the other hand, though ductile cast iron lies within the expected range, the compatibility valve is marginal. The optimum permeability of mould is 120–150 which is necessary to maintain within the range to avoid blowholes, pinholes expansion defects and rough surface finish. Present results show that permeability is slightly higher than the optimum valves such as 161 and 159. It shows that one of the causes for blow holes in grey cast iron (non-return value) and porosity issues in ductile cast iron (harvester cup) which is due to high permeability valves of the mould. In casting processes, pressurized gating system ensures a short filling time and full sprue during casting. For sand casting, Sprue:Runner:Ingate ratio should be 4:8:3 and 1:1.5:0.75 as per ASM and Indian standard, respectively. In non-return value design, Sprue:Runner:Ingate ratio is 1:1.75:0.75 which deviates from ASM and also Indian standard. Table 2 Testing result of casting sand quality Name of sand test

Expected range

Ductile cast iron

Grey cast iron

Moisture test

2.8–4.6%

3.23%

3.21%

Compatibility test

40–50%

41%

37%

LOI test

0 2 ∂ x˜ ∂ t˜

       ∂θ f ∂θ t˜ > 0 + CR − = H t˜ − H t˜ − t˜h ˜ ∂ x˜ x=0 ∂ t   ˜ q˜ f (t˜)       ∂θ 1  − θ f t˜ − θ 0, t˜ t˜ > 0 = ˜ ∂ x˜ x=0 Rc ˜  

     ∂θ − t˜ > 0 = Bi L θ 1, t˜ − θ∞ ∂ x˜ x=1 ˜ θ (x, ˜ 0) = 0 (0 < x˜ < 1)

(1a) (1b)

(1c) (1d) (1e)

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θ f (0) = 0

(1f)

where the Biot number Bi L simulates the insulating material on the sample backside in contact with a fluid at T∞ temperature, while the dimensionless variables are defined as: θ= θf =

αt T − Tin  q  x αth T∞ − Tin , q ˜ , t˜ = 2 , t˜h = 2 , θ∞ =  =   , x˜ = q f,0 L/k q f,0 L L L q f,0 L/k q f T f − Tin  Cf Lf ˜ Rc hL , q ˜ , Rc = , Bi L = = , CR = f q f,0 L/k q f,0 CL L/k k/L

(2)

Equations (1b) and (1c) represent the BC of the 6th kind, where the former is derived by applying the first law of thermodynamics to the heater; while the latter takes into account the contact resistance at the interface thin heater/specimen. When the sample is characterized by a very high thermal conductivity, for example, is a metallic material, it results in k/L  hL . In such a case, the Biot number tends to zero and the 3rd kind BC defined by Eq. (1d) reduces to a perfect insulated condition     ∂θ = 0 t˜ > 0 − ∂ x˜ x=1 ˜

(2a)

Then, using the numbering system proposed in [11, Chap. 2, 12], the above problem may be indicated as X62B50T00. In detail, this number denotes a transient heat diffusion problem regarding a 1D rectangular finite body (by the “X”), subject to a BC of the 6th kind at x = 0 (by the “6” in X62) with a time step change in the applied surface heat flux (by the “5” in B50), and having a thermally insulated boundary at x = L (type 2 BC by the “2” in X62, and zero heat flux by the “0” in B50); also, T00 indicates a zero initial temperature for the two layers.

3.1 Temperature Solution To obtain the solution to the above X62B50T00 problem, the temperature distribution to the companion X62B10T00 problem where the surface heat flux is applied for an unlimited period of time (by the “1” in B10) has to be derived. In dimensionless form, it results in [13]. x˜ 2 x˜ 1 − 3C R R˜ c t˜ + − + C R + 1 2(C R + 1) C R + 1 3(C R + 1)2



 ∞ C R R˜ c βm2 − 1 cos βm (1 − x) ˜   2 e−βm t˜ 0 ≤ x˜ ≤ 1, t˜ > 0 +2 2 ˜ Nm βm cos(βm ) m=1 (3a)

  θ x, ˜ t˜ =

Estimation of Thermodynamic and Transport Properties …

 θ f t˜ =

2 ∞  e−βm t˜  t˜ R˜ c + 1/3 − 2 t˜ > 0 + 2 ˜ 2 C R + 1 (C R + 1) m=1 Nm βm

239

(3b)

where the dimensionless norm N˜ m is 2 

N˜ m = C R R˜ c βm4 + C R + C R R˜ c − 2 R˜ c C R βm2 + C R + 1,

(3c)

and the βm eigenvalues satisfy the following eigen condition

 C R βm cos(βm ) − C R R˜ c βm2 − 1 sin(βm ) = 0

(3d)

Then, the temperature solution to the X62B50T00 problem is obtained by means of the superposition principle for linear cases as shown below.      ˜ ˜ θ x, ˜ t˜  0 ≤ t ≤ th  θ x, ˜ t˜ − θ x, ˜ t˜ − t˜h t˜ > t˜h     ˜ ≤ t˜h 0 ≤ t θ f t˜    θf = θ f t˜ − θ f t˜ − t˜h t˜ > t˜h

θ=

(4a)

(4b)

Also, when R˜ c → 0 (perfect contact), the X62B10T00 problem tends to the X42B10T00 case. Equations (3a)–(3d) reduce to [10]   x˜ 2 x˜ 1 t˜ + − + θ x, ˜ t˜ = ˜ ˜ ˜ 2 N0 3 N˜ 02 N0 N0 ∞ cos(βm x) ˜ − C R βm sin(βm x) ˜ −βm2 t˜ − e 2 ˜ Nm βm m=1      θ f t˜ = θ 0, t˜ t˜ > 0

(5a) (5b)

where the non-dimensional norm N˜ m and the eigenvalues βm are, respectively,  N˜ m =

CR + 1 (C R βm )2 +C R +1 2

m=0 m = 1, 2, . . .

βm cot(βm ) = −C R−1 m = 0, 1, 2, . . . Note that the X42B50T00 solution can be obtained by using Eqs. (4a), (4b).

(5c) (5d)

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4 Estimation Procedure and Optimal Experiment Design The parameter estimation (PE) technique is based on the minimization of the ordinary least square (OLS) norm. This leads to the following recursive expression [14]

 p (k+1) = p (k) + A(k) X T(k) Y − T (k)

(6a)

where k is the iteration index, p denotes the estimated parameter vector (in the current case p T = [ k C ]), Y is the measured temperature vector, T is the calculated temperature vector and X is the sensitivity coefficient matrix. Also, −1

A(k) = X T(k) X (k)

(6b)

The most common criterion to design the optimal experiment is based on the maximization of the determinant of the X T X matrix (denoted by + afterwards), and it is known as D-optimum criterion. It permits the hypervolume of the confidence region of the estimates to be minimized if certain statistical assumptions are verified [1, Chap. 8]. If the properties of concern are k and C and two T-sensors are utilized at different positions, the sensitivity matrix product X T X results in 

Ckk CkC X X= CkC CCC



T

(7a)

where the elements Ckk , CCC and CkC = CCk may be taken as Ckk =

2 N s=1 n=1



 ∂ Ts 2 ∂k  

, CCC =

s=1 n=1

X s,k , sensitivity to k

CkC = CCk =

2 N  s=1 n=1

∂ Ts ∂k

2 N



∂ Ts ∂C





 ∂ Ts 2 ∂C   X s,C , sensitivity to C

(7b)

where N denotes the number of measurements performed. When practical experimental conditions of: (1) a fixed large number of measurements uniformly spaced in time (between the initial time t = 0 and the experiment time t N ); and (2) a specified maximum temperature rise (Tmax − Tin ) to normalize the various variables are considered, the + determinant can be computed in dimensionless form as [7]  + +  2

 C˜ C˜  + ˜+ + kk kC  = C ˜ kk ˜ kC − C C + =  ˜ + + CC  CkC C˜ CC where

(8a)

Estimation of Thermodynamic and Transport Properties …

241 ˜

2 t N 2 k 2 Ckk /N 1 + X˜ s,k = ≈ 2 dt˜ 2 2θmax t˜N s=1 2(Tmax − Tin )

+ C˜ kk

(8b)

0

˜

+ C˜ CC

2 t N 2 C 2 CCC /N 1 + ˜ s,C X = ≈ dt˜ 2 t˜ 2θmax 2(Tmax − Tin )2 N s=1

(8c)

0

t˜N

+ C˜ kC =

2  kCCkC /N 1 + ˜+ ≈ 2 X˜ s,k X s,C dt˜ 2θmax t˜N s=1 2(Tmax − Tin )2

(8d)

0

The factor of 2 appearing on the denominator of the equations listed before accounts for the number of sensors utilized when performing the experiment, that + + = X s,k /(q f,0 L/k) and is another practical experimental condition. Also, X˜ s,k +  X˜ s,C = X s,C /(q f,0 L/k) denote the non-dimensional scaled sensitivity coefficients of temperature with respect to k and C, respectively, at the s-th sensor position (s = + + = k X s,k and X s,C = C X s,C , and θmax is computed as follows 1 or 2), with X s,k θmax =

Tmax − Tin = q f,0 L/k



  T˜ f t˜N for t˜N < t˜h T˜ f t˜h for t˜N ≥ t˜h

(9)

The optimal experiment aimed at estimating k and C under X62B50T00 (imperfect contact) and X42B50T00 (perfect contact) models is defined by Figs. 3 and 4, respectively, when C R = 0.05.

Fig. 3 + criterion for simultaneous estimation of k and C under X62B50T00 model ( R˜ c = 0.5)

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Fig. 4 + criterion for simultaneous estimation of k and C under X42B50T00 model

When a contact resistance at the heater/sample interface is considered, the optimal experiment and heating durations (t˜N and t˜h , respectively) are about 10% longer than those obtained when the contact is perfect.

5 Standard Deviations of the Estimates The dimensionless standard deviations of k and C under uncorrelated measurements errors can be computed as a function of the experiment duration through the following relations:  √ + σk (Tmax − Tin ) N ∼ C˜ CC (10a) σ˜ k+ = = k σ +  √ + σC (Tmax − Tin ) N ∼ C˜ kk σ˜ C+ = (10b) = C σ + Results for imperfect and perfect contact are given in Figs. 5 and 6, respectively. In these figures, the + determinant is also plotted. In both cases, σ˜ k+ reaches a minimum for a certain t˜N shorter than the optimal one (maximum + ), while σ˜ C+ continues to decrease for longer and longer experiment durations.

Estimation of Thermodynamic and Transport Properties …

243

Fig. 5 Standard deviations of k and C under X62B50T00 model (for t˜h = 0.55)

Fig. 6 Standard deviations of k and C under X42B50T00 model (for t˜h = 0.5)

6 Conclusions The plane source experimental apparatus used for thermal properties estimation has been modelled accounting for the heater heat capacity and a finite heating period but only for metallic materials. Also, the thermal contact at the heater–sample interface has been considered both perfect (X42B50T00 case) or imperfect (X62B50T00 case). The optimal experiment for estimation of conductivity and heat capacity has been designed using a D-optimum criterion. Then, the dimensionless standard deviations of k and C have been computed. When an imperfect contact at the heater–specimen interface is considered, the optimal experiment and heating durations are about 10% longer than those obtained when the contact is perfect.

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References 1. Beck JV, Arnold KJ (1977) Parameter estimation in engineering and science. Wiley, New York 2. Dowding KJ, Blackwell BF, Cochran RJ (1999) Application of sensitivity coefficients for heat conduction problems. Numer Heat Transf Part B 36:33–55 3. Molavi H, Hakkaki-Fard A, Rahmani RK, Ayasoufi A, Molavi M (2010) A novel methodology for combined parameter and function estimation problems. J Heat Transf ASME 132:1–11 4. Ahadi M, Andisheh-Tadbir M, Tam M, Bahrami M (2016) An improved transient plane source method for measuring thermal conductivity of thin films: deconvoluting thermal contact resistance. Int J Heat Mass Transf 96:371–380 5. Dowding K, Beck JV, Ulbrich A (1995) Estimation of thermal properties and surface heat flux in carbon-carbon composite. J Thermophys Heat Transf 9:345–351 6. Monde M, Kosaka M, Mitsutake Y (2010) Simple measurement of thermal diffusivity and thermal conductivity using inverse solution for one-dimensional heat conduction. Int J Heat Mass Transf 53:5343–5349 7. D’Alessandro G, de Monte F (2019) Optimal experiment design for thermal property estimation using a boundary condition of the fourth kind with a time limited heating period. Int J Heat Mass Transf 134:1268–1282 8. Carslaw HS, Jaeger JC (1959) Conduction of heat in solids, 2nd edn. Oxford University Press, New York 9. Al-Nimr MA, Alkam MK (1997) A generalized thermal boundary condition. Heat Mass Transf 33:157–161 10. D’Alessandro G, de Monte F (2017) Sensitivity coefficients for thermal property measurements using a boundary condition of the 4th kind. In: Proceeding of the 34th UIT heat transfer conference 2016, vol 796, Ferrara, Italy. Journal of physics: conference series 11. Cole KD, Beck JV, Haji-Sheikh A, Litkouhi B (2011) Heat conduction using Green’s function, 2nd edn. CRC Press Taylor & Francis, Boca Raton FL 12. Cole KD, Beck JV, Woodbury A, de Monte F (2014) Intrinsic verification and a heat conduction database. Int J Therm Sci 78:36–47 13. D’Alessandro G, de Monte F, Amos DE (2019) Effect of heat source and imperfect contact on simultaneous estimation of thermal properties of high-conductivity materials. Math Probl Eng 2019: 1–15. Article ID 5945413 14. McMasters RL, de Monte F, Beck JV (2018) Estimating two heat-conduction parameters from two complementary transient experiments. J Heat Transf ASME 140(7):071301-1–071301-8

Design Improvement of a Vertically Oriented Thermal Energy Storage System Considering Melting Front Propagation Kedumese u Mekrisuh, Udayraj, and Dushyant Singh

Abstract Total melting time of phase change material (PCM) is an important parameter of a latent heat-based thermal energy storage (TES) system. A numerical study of a vertically orientated shell- and tube-type TES system has been performed in the present study. It is identified that one of the major factors causing lower performance of the TES systems is the late melting of PCM situated in the bottom region of the system. It is proposed to introduce partition in the PCM region to address the issue. To assess the improvement in performance of the TES system based on the melting front propagation and zonal melting time, different designs and locations of partition in PCM regions are analyzed. With a radial partition introduced into the TES system such that 85% of the total PCM mass is situated in the upper zone and remaining in the lower zone, the total melting time of PCM can be decreased by 29.69% when compared with the normal TES system. Keywords Total melting time · Phase change material · Melting front propagation · Partition · Extended surface · Thermal energy storage system

1 Introduction Vertically oriented shell- and tube-type latent heat-based thermal energy storage (TES) system contains phase change material (PCM) in the shell and a heat transfer fluid (HTF) flows through the tube to charge the PCM. For particular geometric configurations and flow behavior of HTF of TES system as reported in [1], it is observed that the melting front propagation of PCM in the bottom region takes longer time than the top region due to buoyancy effect in the PCM domain, making K. Mekrisuh · D. Singh Department of Mechanical Engineering, National Institute of Technology Manipur, Imphal, Manipur 795004, India Udayraj (B) Department of Mechanical Engineering, Indian Institute of Technology Bhilai, Bhilai, Chhattisgarh 492015, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_20

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the entire system to acquire high total melting time of PCM. This issue is addressed differently by various researchers. Akgün et al. [2] studied this effect through the modification of storage geometry by making the outermost surface of the PCM domain tilt 5° angle to achieve greater area at the top region than the lower region. They concluded that the 5° inclination leads to a 20% decrease in total melting time of PCM when compared with 0° inclination. Mahdi et al. [3] addressed this issue while studying horizontal triplex tube TES system by incorporating longer longitudinal fins toward the bottom region where the melting rate is slower. Further, the same author has reported that introducing more number of fins in the bottom region has better enhancement compared to fins placed in the upper region [4]. Singh et al. [5] reported a novel fin design of vertical shell and tube TES. The novel fin design introduced in the PCM domain is of decreasing fin height along the length of the TES system (longer at the bottom, shorter at the top). It resulted in 16% reduction in total melting time of PCM. As the HTF leaves the TES system with a decreased temperature during the charging of PCM, PCMs of different melting temperatures are employed and contained in the order of their decreasing melting temperature along the flow direction (Cascade system). One of the early studies on such systems has been reported by Farid and Kanzawa [6]. They have investigated the performance of a TES system filled with PCM. Multiple PCMs of different melting temperatures have shown significant difference in charging/discharging rates of the TES system. Extensive investigations on this method were performed. Fang and Chen [7] numerically investigated such system on melt fraction, thermal energy stored and HTF outlet temperature. They concluded that there exists an optimum proportion of multiple PCMs besides their melting temperature difference which plays an important role in obtaining the best charging rate of a thermal storage system. Adine and Qarnia [8] numerically analyzed the thermal behavior of the storage system filled with two different PCMs of melting temperatures 50 and 27.7 °C at various HTF inlet temperatures (55–65 °C), HTF mass flow rate (10–4 to 10–2 kg/s) and proportion of PCM mass. They concluded that with the HTF mass flow rate of 10–3 kg/s, TES is more efficient at a low HTF inlet temperature of 55 °C. Li et al. [9] investigated the horizontal shell- and tube-type TES system using three different PCMs of high melting temperatures. The domain size for this different PCM within the storage system was suggested based on total melting time of the PCM. To address the issue of late melting of PCM situated at the lower portion of a vertically oriented shell- and tube-type PCM-based TES system, a partition is introduced in the PCM domain which divides the PCM domain into the upper and lower (or inner and outer) zones. As natural convection plays a major role during the melting of PCM, providing partition will achieve two circulation zones and may result in more uniform melting in the entire PCM domain. The optimum proportion of PCM mass in each zone is to be analyzed for the same storage capacity and operating conditions. This is said to achieve when the complete melting of PCM of each zone takes place at the same time. Considering this, effect of the location of the partition in the PCM domain is investigated in the present work. This study is important as it aims to control overcharging of PCM located at the top region due to early melting than at the bottom region of the TES system as identified from the previous study

Design Improvement of a Vertically Oriented Thermal …

247

[1]. Due to early melting of PCM at the top region of the TES system, this zone continues to store sensible energy instead of effectively contributing to the latent heat storage by not allowing melting of PCM in the bottom zone of the TES system. This is one of the reasons for the prolonged total melting time of PCM and limits the fast storage rate of the TES system as a whole. It is thus aimed in the present work to obtain an optimized geometric configuration (location and orientation of partition) of TES system which can minimize the delay in storing energy as per the capacity and avoid non-uniform melting of PCM. The objective is to maintain almost comparable total melting time of both the zones (top and bottom regions) separated by partition. Enhancement in the rate of energy storage with this method and physics of it is discussed in terms of phase front propagation, total melting time and melt fraction of the PCM.

2 Problem Statement Vertically oriented shell- and tube-type latent heat-based TES system where PCM is placed in the shell and HTF (water) flows in a tube is studied in the present work. TES system (base case) as shown in Fig. 1a has a radius of inner tube (r i ) of 0.011 m with a tube thickness of 1 mm, a radius of the outer tube (r o ) of 0.0365 m and height (Z) of 1.4 m. To study the effect of partitions of the PCM domain and incorporation

Partition

PCM

HTF in

Z

z r ri

ro (a)

(b)

(c)

(d)

(e)

Fig. 1 Computational domain of the studied TES system: a base case, b case 1 with annular partition at the mid-section, c case 2 with radial partition at the mid-section, d case 3 and e case-4

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Table 1 Thermophysical properties PCM [1] and HTF [10] Material

Density (kg/m3 )

Specific heat (J/kg K)

PCM

780

2000

0.2

0.0289

HTF

961.9

4210

0.6634

0.000297

Thermal conductivity (W/m K)

Dynamic viscosity (kg/ms)

of thermally conductive (copper) partitions in the PCM region on melting front propagation and performance of TES system, the base case is modified as follows: • Case 1: PCM domain of the base case is divided with the help of annular partition layer of thickness 1 mm into two zones of equal PCM mass/volume. The partition layer is located in the mid of the PCM region. The zone of the PCM domain nearer to the HTF tube is considered as inner zone, and the zone further away from the HTF tube is considered as outer zone. This arrangement is shown in Fig. 1b. • Case 2: In this configuration, PCM domain of the base case is divided from the center using radial partition of 1 mm thickness into two zones of equal PCM mass/volume as shown in Fig. 1c. The upper half of the PCM domain above the radial partition is referred here as the upper zone, and lower half is referred as lower zone. • Case 3: In this case, TES geometry of the case 1 is modified by introducing the annular partition at a distance such that the PCM mass of the inner zone has 85% of the total mass of PCM present in the TES system as shown in Fig. 1d. • Case 4: In this case, TES geometry of the case 2 is modified by introducing the radial partition at a distance such that the PCM mass of the upper zone has 85% of the total mass of PCM present in the TES system as shown in Fig. 1e. It is to be noted here that the storage capacity is the same for all the cases mentioned above and studied in the present work. PCM material, HTF and the operating conditions are also same for all the cases. The Reynolds number associated with the HTF is 1557.6 for all the cases which correspond to a laminar flow. The thermophysical properties of PCM and HTF used in the present study are shown in Table 1. TES system configurations studied in case 3 and case 4 are the results of the attempts to achieve the same total melting time of PCM at each zone.

3 Numerical Modeling To study the thermal performance of PCM-based TES system, a numerical model is developed. Enthalpy–porosity method [11] is used in which the PCM domain is considered as a porous medium, where porosity is equal to 1 and 0 for liquid and solid phases, respectively. The detailed methodology can be found in [11, 12]. Governing equations for the unsteady incompressible and laminar flow are as follows:

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Continuity equation: ∂(ρu i ) ∂ρ + =0 ∂t ∂ xi

(1)

  ∂τi j ∂(ρu i ) ∂ ρu i u j = + ρβgi (Ti − Tref ) + Si + ∂t ∂x j ∂x j

(2)

Momentum equation:

where ρ is the density, u is the fluid velocity, τ is the shear stress, p is the pressure, g is the gravitational acceleration and T ref is the reference temperature. The Boussinesq approximation is considered to deal with the natural convection in the melted PCM region. The source term S i derived from the Darcy’s law is expressed as, Si = Amush (1 − f )2

ui f3 +e

(3)

where f is the liquid volume fraction and Amush is mushy zone constant ranges from 104 to 107 . The term e is a small value (taken as 0.001) considered to avoid division by zero. Energy equation:   ∂T ∂ ∂(ρ H ) ∂(ρu i H ) k + = ∂t ∂ xi ∂ xi ∂ xi

(4)

where k is the thermal conductivity and T is temperature. H and h are the total and sensible enthalpy, respectively, and are related as follows: H =h+ fL

(5)

The liquid volume fraction (f ) can be obtained with the help of the lever rule as follows: ⎧ ⎪ if T < Tsol ⎨0 sol if Tsol < T < Tliq (6) f = TTliq−T −Tsol ⎪ ⎩1 if T > Tliq

3.1 Initial and Boundary Conditions The HTF enters into the tube from top at a constant mass flow rate of 0.008 kg/s and leaves the other end at the atmospheric pressure. The inlet temperature of the HTF is

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considered constant at 368 K. All the outer walls of the storage system are considered adiabatic. PCM is considered to be in the solid state initially with its temperature well below its solidus temperature (i.e. 298 K). Initial and boundary conditions are expressed mathematically as below: T (r, z, 0) = Ti

(7)

T (r, Z , t) = Tin (0 ≤ r ≤ ri )

(8)

dT (0, z, t) = 0 (0 ≤ z ≤ Z ) dr

(9)

3.2 Solution Procedure In the present work, two-dimensional axisymmetric geometry of the TES system as shown in Fig. 1 is considered. Commercial software, Ansys ICEM, is used for geometry modeling and meshing of the computational domain. The governing equations, Eqs. (1)–(6), are solved considering the following schemes: SIMPLE algorithm is utilized for the pressure–velocity coupling, energy and momentum equations are discretized using the QUICK differencing scheme and PRESTO scheme is used for the pressure correction. The under-relaxation factors for pressure, momentum, energy and liquid fraction are taken as 0.3, 0.7, 1.0 and 0.9, respectively. The convergence criteria for the continuity and momentum equations are taken as 10–6 , and for energy equation as 10–8 .

4 Model Validation and Independence Study Numerical model used in the study has been validated with the experimental study of Agyenim et al. [13]. The experiments [13] were performed on the TES system with Erythritol (PCM) filled in the annular space and silicon oil at 140 °C flowing in a tube of 0.051 m diameter at a mass flow rate of 30 kg/min. HTF flow was in the laminar regime. Numerically obtained average temperature of PCM in the present study was found to be in good agreement with the reported experimental data [13] with just 1.76% deviation. The reliability of the numerical result with least possible computational time is ensured by conducting detailed grid and time step size independence studies. The results of the base case considered in the present study are discussed as far as independence study is concerned. For brevity, the results corresponding to other cases are not discussed here. Grid independence study is performed with the time

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step size of 0.5 s. Different grid sizes with 16,000, 32,000 and 64,000 nodes are considered. There is an increase in the total melting time of PCM by 1.59% as the number of nodes is increased from 16,000 to 32,000, whereas there is no change in the total melting time of PCM when the number of nodes is increased from 32,000 to 64,000. Therefore, the grid size with 32,000 nodes is considered further for the time step independence study. No effect of time step size is found on the total melting time of PCM. Consequently, 32,000 nodes with 0.5 s time step size were considered suitable for the present study.

5 Results and Discussion For the geometric configurations and flow behavior of the TES system considered in the present study, the melting front propagates downward as observed from the previously reported work [1]. This causes the late melting of PCM situated in the bottom region of the TES system and affects the total melting time of PCM. At the initial stage of melting, PCM near the HTF wall will be melted completely and create a zone connecting the top and bottom regions. The instability results in the establishment of a natural convection current which assists the melting of PCM. Since natural convection is one the driving mechanism during melting, to take advantage of it, it is proposed to provide a partition in the PCM domain which can create two zones of circulation for more uniform melting of the PCM throughout the domain. The effect of introducing the partition and its configuration on melting behavior and thermal performance of the TES system is studied in the present work. Further, the study is performed to determine the optimum PCM mass proportion in each zone created by dividing the overall PCM domain. This is done because the total melting time of PCM is not only affected by the type of partition but also by the PCM mass in each zone. The results are presented and discussed in the following subsections.

5.1 Effect of Type of Partition This section discusses the study on the effect of introducing the two types of partitions (annular—case 1 and radial—case 2) in the simple TES system (base case). Effect of introducing partitions is also analyzed on the performance of the TES system by considering cases with partition (case 1 and case 2) and without partition (base case). The temporal variation of a liquid fraction in the PCM domain is presented in Fig. 2 for all the three cases studied. The total melting time of PCM for the base case is found to be 256 min. It is noticed that as partition is introduced in the PCM domain of the TES system, the total melting time of PCM is reduced. For case 1, the total melting time of the PCM in inner and outer zones is found to be 108 min and 208 min, respectively. The total melting time of PCM for case 1 is 18.75% lower than the total melting time for the base case. For case 2, the total melting time of the

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Liquid fraction

0.8 0.7 0.6 0.5 0.4

Base case Case-1 inner zone Case-1 outer zone Case-2 lower zone Case-2 upper zone

0.3 0.2 0.1 0.0 0

30

60

90

120

150

180

210

240

270

Time (min)

Fig. 2 Variation of the liquid fraction on the effect of with (case-1 and case-2) and without partition (base case)

PCM in upper and lower zones is found to be 152 min and 228 min, respectively. The total melting time of PCM for case 2 is 10.94% lower than the base case. This shows that the introduction of partition in the TES system reduces total melting time of PCM and thus improves its performance. Further, it is observed that the annular partition (case 1) leads to better performance compared to radial partition (case 2) in case of equal distribution of storage material in each zone. Liquid fraction contour showing melting front at 60 min of melting for all the 5 cases analyzed in the study is presented in Fig. 3. The area-weighted average value

Fig. 3 Liquid fraction contours at 60 min. Area-weighted average liquid fraction value of a base case is 0.76, b case 1: inner zone is 0.91 and outer zone is 0.45, c case 2: upper zone is 0.75 and lower zone is 0.83, d case 3: inner zone is 0.44 and outer zone is 0.12, e case 4: upper zone is 0.76 and lower zone is 0.80

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of the liquid fraction of each case has been mentioned. At 60 min of melting, the base case obtains a liquid fraction value of 0.76. For case 1, area-weighted liquid fraction is found to be 0.68 (with the inner zone liquid fraction value of 0.91 and the outer zone liquid fraction value 0.45), whereas for case 2, area-weighted liquid fraction is found to be 0.79 (with the upper zone liquid fraction value of 0.83 and the lower zone liquid fraction value 0.75). It is observed that in the case 1, inner zone has a relatively higher liquid fraction value than the outer zone. Similarly, in case 2, the upper zone has a higher liquid fraction value than the lower zone. Therefore, if the same value of liquid fraction value is attained in each zone (same melting time of the PCM kept in the zone), performance of the TES system can be improved further. The factor that results in the improvement of the TES system due to the introduction of partition is the establishment of separate melting front and circulation in each zone. Domination of natural convection during melting and occurrence of more than one melting front results in melting rate enhancement. Further, case 1 showed lower melting time than case 2 because of the greater height of each zone. It can be noted that for all the cases shown in Fig. 3, the melting front propagates downward (irrespective of the partition). For case 1, the top region of the inner zone is melted initially (almost complete melting is achieved at 60 min). This helps to start melting the outer zone. In fact, with this arrangement melting in the outer zone cannot start until the inner zone is melted. Therefore, achieving the same total melting time at each zone that can reduce the melting time substantially due to the modification of the system is limited in this case although case 1 showed better improvement than case 2. While in case 2, the PCM in both zones begins to melt since the start. Due to the presence of the partition that is attached between the inner tube of HTF and outer tube of PCM, it acts as an extended surface. Therefore, the bottom region of the upper zone also melts. This is not present in the base case or the lower zone of case 2. Consequently, upper zone in case 2 has lower total melting time of PCM. Another factor that assists faster melting of PCM situated at the top region is the presence of higher energy content of HTF near the entry. Thus, case 2 can be modified to have the partition introduced closer to the bottom region to achieve approximately same melting time in each zone and overall faster melting of PCM in the TES system. It is observed that the introduction of partition in the PCM domain can significantly enhance the melting rate of PCM and improves the thermal performance of the TES system. It is also noticed that there can be an optimum proportion of PCM mass in each zone. Melting should be completed at the same time in each zone to further improve the performance of TES system.

5.2 Effect of PCM Mass Proportion in Each Zone The provision of partition in the PCM domain improves the performance of the TES system due to improved natural convection current and the partition that itself acts as an extended surface. However, PCM mass proportion in each zone also affects the total melting time of PCM. The total melting time of PCM is an important factor for

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a TES system to avoid incomplete utility of the storage material or the system. To further improve the performance of TES system by achieving the same total melting time of PCM in each zone, case 3 and case 4 are studied. As observed from the previous section that the inner zone of case 1 and upper zone of case 2 melt faster. Therefore, the outer zone of case 3 and lower zone of case 4 are filled with only 15% of the total mass of PCM by suitable placing of the partitions. This is done considering that the total melting time of PCM is dependent on the PCM mass proportion in each zone and to achieve same melting time for each zone of the TES system. The temporal variation of liquid fraction for case 3 and case 4 is compared with base case in Fig. 4. It can be also noticed from Fig. 4 that with these arrangements, the total melting time of PCM is further reduced as compared to case 1 and case 2. Figure 3d, e shows the liquid fraction contour at 60 min of melting for case 3 and case 4, respectively. For case 3, total melting time of PCM in the inner and outer zones is obtained as 204 min and 188 min, respectively. The total melting time of PCM for case 3 is 20.31% lower than the base case. For case 4, total melting time of PCM in the upper and lower zones is obtained as 180 min and 172 min, respectively. The total melting time of PCM for case 4 is 29.69% lower than the base case. Case 4 showed a good improvement in the performance of TES system compared to all the cases studied in the present work. Since both the zones in case 3 and case 4 achieved similar total melting time of PCM, these cases can be considered as the optimum geometric configurations for their respective type of partitions. The lower melting rate of PCM at the bottom region when modified as in case 4 can enhance the performance of TES system drastically. It is intriguing to note that such a simple modification based on melting front propagation and zonal melting time can improve the thermal performance of the TES system drastically. The optimized PCM mass proportion at each zone further improves the thermal performance of the TES system effectively. It is believed that 1.0 0.9

Liquid fraction

0.8 0.7 0.6 0.5 0.4

Base case Case-3 inner zone Case-3 outer zone Case-4 lower zone Case-4 upper zone

0.3 0.2 0.1 0.0

0

30

60

90

120

150

180

210

240

270

Time (min)

Fig. 4 Variation of the liquid fraction in the upper and lower zones of case 2 and case 3 in comparison with simple TES system (base case)

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providing two/more partitions instead of one can further improve the thermal performance of the TES system. Therefore, such optimization study can be extended further for the cases involving more number of partitions to further improve the performance of TES systems.

6 Conclusions In the present numerical study, a method to improve the performance of the TES system is identified and the effects of such methods are investigated. The effects of the introduction of the partition, types of partition and PCM mass proportion of each zone are analyzed on the performance of the TES system. Following are the major conclusions that are drawn from this study: • Increase in surface area and natural convection during melting due to the introduction of partition improves the performance of the TES system. • On the effect of partition and its arrangement: Case 1 of the studied system decreases the PCM total melting time by 18.75%, whereas case 2 decreases it by 10.94% when compared with a simple TES system (base case). • On the different proportions of PCM mass in each zone: Case 3 and case 4 decrease the total melting time of PCM by 20.31% and 29.69%, respectively, when compared with a simple TES system (base case).

References 1. Mekrisuh K, Singh D, Udayraj (2020) Performance analysis of a vertically oriented concentrictube PCM based thermal energy storage system: parametric study and correlation development. Renew Energy 149:902–916. https://doi.org/10.1016/j.renene.2019.10.074 2. Akgün M, Aydın O, Kaygusuz K (2008) Thermal energy storage performance of paraffin in a novel tube-in-shell system. Appl Therm Eng 28:405–413. https://doi.org/10.1016/j.appltherm aleng.2007.05.013 3. Mahdi JM, Lohrasbi S, Ganji DD, Nsofor EC (2018) Accelerated melting of PCM in energy storage systems via novel configuration of fins in the triplex-tube heat exchanger. Int J Heat Mass Transf 124:663–676. https://doi.org/10.1016/j.ijheatmasstransfer.2018.03.095 4. Mahdi JM, Lohrasbi S, Ganji DD, Nsofor EC (2019) Simultaneous energy storage and recovery in the triplex-tube heat exchanger with PCM, copper fins and Al2 O3 nanoparticles. Energy Convers Manage 180:949–961. https://doi.org/10.1016/j.enconman.2018.11.038 5. Singh RP, Xu H, Kaushik SC, Rakshit D, Romagnoli A (2019) Effective utilization of natural convection via novel fin design & influence of enhanced viscosity due to carbon nano-particles in a solar cooling thermal storage system. Sol Energy 183:105–119. https://doi.org/10.1016/j. solener.2019.03.005 6. Farid MM, Kanzawa A (1989) Thermal performance of a heat storage module using PCM’s with different melting temperatures: mathematical modeling. J Sol Energy Eng 111:152–157. https://doi.org/10.1115/1.3268301

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7. Fang M, Chen G (2007) Effects of different multiple PCMs on the performance of a latent thermal energy storage system. Appl Thermal Eng 27:994–1000. https://doi.org/10.1016/j.app lthermaleng.2006.08.001 8. Adine HA, Qarnia HE (2009) Numerical analysis of the thermal behaviour of a shell-and-tube heat storage unit using phase change materials. Appl Math Model 33:2132–2144. https://doi. org/10.1016/j.apm.2008.05.016 9. Li YQ, He YL, Song HJ, Xu C, Wang WW (2013) Numerical analysis and parameters optimization of shell-and-tube heat storage unit using three phase change materials. Renew Energy 59:92–99. https://doi.org/10.1016/j.renene.2013.03.022 10. Dinçer I, Zamfirescu C (2016) Drying phenomena: theory and applications, 1st edn. Wiley, Hoboken, pp 457–459. https://doi.org/10.1002/9781118534892.app2 11. Voller VR, Prakash C (1987) A fixed grid numerical modelling methodology for convectiondiffusion mushy region phase-change problems. Int J Heat Mass Transf 30:1708–1719. https:// doi.org/10.1016/0017-9310(87)90317-6 12. Brent AD, Voller VR, Reid KJ (1988) Enthalpy-porosity technique for modeling convectiondiffusion phase change: application to the melting of a pure metal. Numer Heat Transf 13:297– 318. https://doi.org/10.1080/10407788808913615 13. Agyenim F, Eames P, Smyth M (2009) A comparison of heat transfer enhancement in a medium temperature thermal energy storage heat exchanger using fins. Sol Energy 83:1509–1520. https://doi.org/10.1016/j.solener.2009.04.007

Numerical Study of Slot Jet Impingement on a Cylinder by Using Two-Equation Turbulence Models Dushyant Singh and Saurabh Kango

Abstract In this paper, the numerical results of turbulence slot jet on a heated cylinder are presented. The main objective of this study is to recognize suitable RANs turbulence model, which predicts the accurate results as compared to the previous published experimental results. To model turbulent flow, widely used k–ε Std., k–ε realizable, k–ε RNG, k–ω Std. and k–ω SST turbulence models were used. It was found that Std. k–ω turbulence models better predict as compared to other turbulence model in the pressure distribution on the cylinder. However, the k–ε Std. and k–ε RNG models better predict the heat transfer as compared to other turbulence models. Keywords Turbulence model · Jet impingement · Heat transfer

Nomenclature Cp D h S kf Nuθ Pw Pα q  Res

Pressure coefficient. Cylinder diameter, m. Nozzle to target distance, m. Slot width, m. Fluid thermal conductivity, W/m K. Local Nusselt number, Nuθ = (Twq−TDjet )kf . Wall static pressure, Pa. Wall static pressure, Pa. Heat flux, W/m2 . Reynolds number defined based on the slot width, ReS =

ρUjet S . μ

D. Singh (B) Department of Mechanical Engineering, NIT Manipur, Imphal, Manipur, India e-mail: [email protected] S. Kango Department of Mechanical Engineering, Dr B R Ambedkar NIT Jalandhar, Jalandhar, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_21

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ReD S T jet Tw U jet

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Reynolds number defined based on the heated cylinder, ReD = Width of slot jet, m. Jet exit temperature, K. Impingement wall temperature, K. Jet exit velocity, m/s.

ρUjet D . μ

Greek Symbol θ μ ρ

Angle. Density, kg/m3 . Dynamic viscosity, kg/m s.

1 Introduction Turbulent jet impingement cooling is commonly used in real engineering applications, i.e., industrial cooling, heating and drying of a system. Extensively, studies have been carried out by various researchers using cooling of flat surfaces by using this technique [1–4]. However, the literature on jet impingement on cylinder is limited. Gori and Bossi [5] experimentally investigated slot jet impingement heat transfers on cylinder for different Reynolds numbers and h/S = 2–10. They also provided the heat transfer correlations for the average Nu for h/S from the two to ten. Authors observed that h/S = 6 provides maximum heat transfer rate. Similar study was also carried out by the same authors for different parameters for ReD = 4000–22,000 [6]. It was observed that at h/S = 8 pprovided maximum Nu value for the range of Reynolds number (4000–22000). Based on their earlier work, they also observe that the maximum Nu value is obtained at D/S = 4. On the other hand, D/S = 2 provides maximum heat transfer rate. McDaniel and Webb [7] studied the heat transfer characteristics cylinder by turbulent slot jet impinging. In their study, ReD , varied from 600–8000. They used both sharp edge and contour nozzles to order to understand the effect of nozzle shape. In this study, cylinder diameter to jet width was varied from 0.66 to 2. They also reported correlations for the average Nu for the range of parameters considered. Olsson et al. [8] numerically investigate the turbulent slot jet impingement heat transfer on cylinder placed on a flat plate; considering food processing is a potential application. As the flat surface confines the fluid flow, the flow and heat transfer characteristics of this study differ from the geometries considered by [5–7]. In this study, the ReS from 23,000 to 100,000, h/D varied from 2 to 8. In order to investigate the curvature effect, they considered S/D in the range 0.29–1.14. Dirita et al. [9] also carried out numerical investigation similar to the geometry considered by Olsson et al. [8].

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Imraan and Sharma [10] carried out experimental as well as numerical studies on a turbulent slot jet impingement on heated cylinder placed in a confined passage. They considered this geometry for the design configuration of frost-free refrigerator. They varied the non-dimensional width of confined passage, H/D from 2 to 22 while maintaining the non-dimensional parameters at D/S = 1 for h/S = 5 and ReD varying from 10,000 to 12,000. However, their comparison with the free stream case shows that jet impingement with flow confinement gives higher rate of the heat transfer. The objective of the present work is to demonstrate that accurate flow feature as well as heat transfer characteristics can be obtained from turbulence slot jet impingement on a heated cylinder obtained appropriate two-equation turbulence models.

2 Problem Statement and Computational Model In the present work, cooling of a heated cylinder by turbulent slot air jet impinging has been investigated numerically with RANs turbulence model. The computational domain considered in the present study is shown in Fig. 1. For a turbulent slot jet, a long channel of slot width, S, is considered as a nozzle jet exit. A heated cylinder of diameter, D, with a uniform heat flux is considered as a target. The distance between the slot jet exit and the impingement target surface is h. Structured and non-uniform meshes were used to discretize the computational domain as shown in Fig. 2. The very fine meshes were used near wall boundaries for maintaining y+ less than unity. The

Fig. 1 Two-dimensional computational domain

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Fig. 2 Computational mesh

Fig. 3 Grid-sensitive studies

1.5 X 103 7.7 X 103 1.7 X 104 2.8 X 104

180

Nuθ

150 120 90

h/S = 2, S/D = 0.5 Re D = 20,000

60 0

45

90

θ

135

180

finite volume method-based open-source flow solver, Fluent, was used for solving the governing equations. The SIMPLE algorithm was used for pressure and velocity coupling. For modeling Reynolds stresses, two-equation models are used. The main objective of this study is to recognize suitable RANs turbulence model based on fluid flow and heat transfer for slot jet impingement on a heated cylinder. Figure 3 shows the results of grid-sensitive study for the present study.

3 Results and Discussion Brahma et al. [11] presented the experimental investigation of flow characteristics on slot jet impingement on a cylinder. They presented pressure distribution on cylinder

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Fig. 4 Comparison between the variations of pressure distribution on the cylinder

surface for h/S = 8, S/D = 0.1 and ReS = 19,300. The pressure distributions obtained from the numerical simulations were compared with experimental results of Brahma et al. [11]. It was observed that Standard k–ω model predicts the pressure distribution on the cylinder accurately compared to other two-equation model as shown in Fig. 4. Similar study was carried out to recognize suitable RANs turbulence model for turbulence slot jet on a heated cylinder. The numerical results are calculated from RANs turbulence model validated with experimental data [5]. Figure 5 shows the comparison of calculated numerical results with the experimental results of [5]. Figure 5 shows the local Nu distribution from the stagnation point to along the circumferential position θ = 0° to 180° by using two-equation different turbulence models and the experimental data for ReD = 6000 and 20,000. All turbulence models overpredict the local Nusselt number distribution in the region θ = 50°. However, the predictions of the Standard k–ε and Realizable k–ε models are closure to the experimental results at stagnation point. Compared to the experimental value, the stagnation point Nusselt number overpredicted by Standard k–ε and Realizable k–ε models is 30% as shown in Fig. 5a, b.

4 Summary The present work was carried out to recognize suitable RANs turbulence model for simulating turbulence slot jet on a heated cylinder. Based on the present study, the following conclusions were drawn: 1. Standard k–ω turbulence model predicts better results for pressure distribution on the cylinder. 2. Standard k–ε and Realizable k–ε models predict the accurate stagnation Nusselt number distribution.

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Fig. 5 Comparison of the numerical results with experimental results of Gori and Bossi [5] for a ReD = 6000 and b ReD = 20,000

References 1. Martin H (1977) Heat and mass transfer between impinging gas jet and solid surfaces. Adv Heat Transf 3:1–60 2. Livingood JNB, Hrycak P (1973) Impingement heat transfer from turbulent air jets to flat plates—a literature survey. NASA Technical Memorandum, NASA TM X-2778, Lewis Research Center, Cleveland 3. Jambunathan K, Lai E, Moss MA, Button BL (1992) A review of het transfer data for single circular jet impingement. Int J Heat Fluid Flow 13:106–115 4. Zuckerman N, Lior N (2006) Jet impingement heat transfer physics, correlations and numerical modeling. Adv Heat Transf 39:565–632 5. Gori F, Bossi L (2000) On the cooling effect of an air jet along the surface of a cylinder. Int Commun Heat Mass Transf 27:667–676 6. Gori F, Bossi L (2003) Optimal slot height in jet cooling of a circular cylinder. Appl Thermal Eng 23:859–870 7. McDaniel CS, Webb BW (2000) Slot jet impingement heat transfer from circular cylinders. Int J Heat Mass Transf 43:1975–1985

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8. Olsson EEM, Ahrne LM, Tragardh AC (2004) Heat transfer from a slot air jet impinging on a circular cylinder. J Food Eng 63:393–401 9. Dirita C, Bonis MVD, Ruocco G (2006) Analysis of food cooling by jet impingement, including inherent conduction. J Food Eng 81:12–20 10. Imraan M, Sharma RN (2009) Jet impingement heat transfer in a frost—free refrigerator: the influence of confinement. Int J Refrig 32:515–523 11. Brahma RK, Faruque O, Arora RC (1991) Experimental investigation of mean flow characteristics of slot jet impingement on a cylinder. Heat Mass Transf 26(5):257–263

Thermal Simulation of Li-Ion Battery Pack Using ANSYS Fluent Mann P. Parmar, Deep R. Patel, Vivek K. Patel, and Rajesh S. Patel

Abstract World is facing many problems with the current sources of energy such as petroleum and coal. Li-ion battery is the most suitable clean and green alternative to fossil fuels. However, major issues with Li-ion batteries are temperature non-uniformity and a higher rate of heat generation. Efficient and optimized cooling system can be only designed after having the knowledge of temperature and heat generation throughout the battery. In this paper, we have presented the simulation results of three different types of Li-ion battery packs using Ansys Fluent which indicates the profile of total heat generation, ohmic heat generation, and static temperature of the battery pack. Keywords Li-ion battery · Ohmic heat generation · Total heat generation · Static temperature

1 Introduction Energy is the world’s primary need in the machine era. One could not think of life without energy. As per studies done by world-leading companies, the world will face shorthand in current sources of energy such as petroleum and coal in a few years. Global warming is another issue that the world is currently facing due to the constant burning of fossil fuels. Batteries are the good alternative as; it has applications in M. P. Parmar · D. R. Patel · V. K. Patel (B) · R. S. Patel Department of Mechanical Engineering, School of Technology, Pandit Deendayal Petroleum University, Gandhinagar, India e-mail: [email protected] M. P. Parmar e-mail: [email protected] D. R. Patel e-mail: [email protected] R. S. Patel e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_22

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Fig. 1 Schematic arrangement of Li-ion battery [2]

small wrist watch to bigger fighter plane. Li-ion battery gives clean energy and is also a sustainable alternative of fossil fuel in terms of cost and energy. A major component of Li-ion battery includes anode and cathode (which primarily stores lithium), electrolyte (which act as a carrier for positively charged electrons to move from anode to cathode), and current collector (The charge will be created at the positive current collector when free electrons are generated at the anode due to the movement of lithium ions). Then the current collector will carry the current to the electrical device. This is the phenomena for discharging of the battery and is vice versa while charging. The need for separator is to ensure complete insulation of current inside the battery, the current cannot flow inside the battery, and it needs to get away by current collectors [1]. All the parts and working are shown in the schematic (Fig. 1).

2 Efficiency and Heat Generation In Li-ion battery, there are two prominent ways by which heat is generating, the first is ohmic heat which also called Joule heating, and the second is related to the electrochemical reaction in battery. As per the study by Zhang [3], around 54% of the total heat generation is because of ohmic heat generation, and on an average 30% is generated by the electrochemical reaction in battery, which is an exothermic reaction came by a chemical reaction in the battery. The heat generated from these both contributors is enough to reach the temperature of the battery as high as 70 °C, which is not feasible and has a drastic effect on a performance of a battery for a long period. For good performance, the battery should work between 20 and 60 °C; otherwise, this could cause some serious damage to the battery, and the efficiency of the battery will

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keep on decreasing with time [4]. Pesaran et al. [5] showed that the optimal temperature range for Li-ion batteries is 15–35 °C. The effect of temperature on efficiency is studied by Ma et al. [6], and according to his work, the efficiency of the battery is decreased by 60–70% in some timeline of 10 days and of including various charge– discharge cycles. For prolonged battery performance, a proper cooling system is required to reduce the effects of higher temperatures.

3 Different Type of Cooling Method for Li-Ion Battery Two types of cooling methods are there; the first one is related to modifying internal parts of the battery and the second is through providing external cooling. In these two categories, there are several methods available which are mentioned here: 1. By modifying electrode thickness—The thick electrode was found to be highly resistive while current is flowing through it. A high resistance leads to an increase in ohmic heat generation, severe capacity loss can be found at higher discharge rates, and unbalanced heat generation was also increased in a cell. Zhao et al. [7] suggested that to optimize the thermal and electrochemical performance of Li-ion battery cells, one way is to reduce the particle size of active material and thickness of electrode which in turn shorten the distance traveled by ions in electrodes and active particles. 2. By modifying material of the battery—Various techniques such as doping, coating, deposition, and additives have been adopted for modification of electrode material. The main purpose behind these modifications is to decrease the transport distance of electrons so that the overall conductivity and thermal performance can be improved. Reduction in the diffusion distances of lithium ions can result in better conductivity of Li-ion battery cells, and it is possible by reducing the particle size of the electrode. Better conductivity will result in improved thermal performance of the Li-ion battery. 3. Air cooling—Air cooling is cooling just by air. It is only suitable for small battery packs. According to one research [8], air cooling can cool down the battery around 72 °C, which requires additional cooling methods such as liquid cooling or PCM cooling. 4. Liquid cooling—It is suitable for large battery packs [9]. The advantages of liquid cooling are rapid cooling and higher temperature uniformity, but the drawback is that it is bulkier compared to air cooling and PCM cooling [10]. 5. PCM cooling—In this cooling method, a particular material will change its phase throughout the cooling cycle. So the latent heat of the material can be fully utilized to reduce the temperature of the battery pack. Paraffin wax is the most popular for research purposes among researchers, due to its range of phase change temperature. PCMs are mixed with graphene, carbon fiber in order to increase its thermal conductivity. Based on one research, this mixture’s thermal conductivity could reach values near to 40 W/m K [11] which is considered to be very high.

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4 Simulation Setup, Data, and Mathematical Equation 4.1 Simulation Setup The geometrical shape of the lithium-ion battery is cylindrical. The software that we have used for this simulation is Ansys Fluent (Available in Ansys Workbench 2020 R1 Student Version) [12]. In Ansys Fluent, there are two types of battery models available: (1) single-potential empirical battery model and (2) dual-potential MSMD battery model. From these battery models, we have chosen the dual-potential MSMD battery model, because after going through several references [13] we found that single-potential empirical battery model is suitable for only a single lithium-ion battery cell (Fig. 2), whereas the dual-potential MSMD battery model suitable for a whole battery pack (Fig. 2) consisting of more than one lithium-ion battery pack is connected in series or parallel connection. Further in the dual-potential MSMD battery model, there are three types of sub-models available: (1) Newman, Tiedemann, Gu, and Kim (NTGK) empirical model, (2) electric circuit model (ECM), and (3) Newman pseudo-2D (P2D) model. According to the availability of input data, we have chosen the NTGK empirical model from these three sub-models. Now, to connect two Li-ion battery cells, there are two types of battery cell connection methods available: (1) using busbar and (2) using virtual connection. In the busbar method, we need to create a physical (and very thin) component named busbar as shown in Fig. 3, whereas in the virtual connection method there is no need to create a busbar, and we can virtually connect two lithium-ion battery cells. We have done a couple of simulations using both of these methods and found that the virtual connection method is more stable (Fig. 4) compared to the busbar connection method. In the figure, you can see that there is large non-uniformity in the simulation result of the busbar connection method, and in the case of virtual connection simulation result is very uniform (Fig. 4). The second advantage of the virtual connection method is that meshing time is reduced because there is no busbar

Fig. 2 Li-ion battery cell and Li-ion battery pack

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Fig. 3 Busbar connection and virtual connection

Fig. 4 Results of busbar connection and virtual connection method

in this method and meshing of the busbar is a very challenging task since it is very thin.

4.2 Mathematical Equations These equations are used to solve the electrical and thermal fields in the computation fluid dynamics domain at the battery cell’s scale. σ+ and σ− denote the effective electric conductivities for the positive and negative electrode, ϕ+ and ϕ− are phase potentials for the positive and negative electrodes, j represents volumetric transfer current density, and q stands for heat generation rate. These equations are directly taken from the software’s manual. ∂ρC pT − ∇.(k∇T ) = q˙ ∂t

(1)

∇.(σ+ ∇ϕ+ ) = − j

(2)

∇.(σ− ∇ϕ− ) = j

(3)

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4.3 Data Taken for Simulation • • • • • • •

Cell diameter = 26.1 mm Cell length = 65 mm The gap between the two cells in a battery pack is approximately 2 mm C rate = 5C Number of nodes per cell = 1459 Free stream air temperature = 300 K U and Y coefficients—The condition of these coefficients totally depends upon the polarization test of the battery. We have taken the values of these coefficients from Kim’s paper [14] • Min. stop voltage = 3 V • Max. stop voltage = 4.3 V. The C rate is the hourly rate at which the battery discharges. A higher C rate means high heat generation, and a lower C rate indicates low values of heat generation. The simulation will automatically stop once the battery cell voltage reaches the minimum or maximum value. For a battery pack, the battery average cell voltage is used.

5 Results In this work, we have done the simulation of three (1p2s, 1p5s, 5p5s) different types of Li-ion battery pack arrangement. Here p stands for parallel and s stands for series so 1p2s means one parallel two series connection so the number of a lithium-ion battery cell, in this case, will be two. 1p5s means one parallel five series connection so the number of lithium-ion battery cell will be five. 5p5s arrangement means five parallel five series connection so in this case number of lithium-ion battery cell will be 25. Currently, this 5p5s battery pack is used in an electric scooter [15]. Simulation is showing data about total heat generation, ohmic heat generation, and static temperature for each arrangement of the Li-ion battery pack.

5.1 Total Heat Generation It has been found (Figs. 5 and 6) that total heat generation value is higher at the cell zone (middle part of the lithium-ion battery cell) compare to the tab zone (extremely right and left part of lithium-ion battery cell).

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Fig. 5 Total heat generation profile for 1p2s and 1p5s arrangements

Fig. 6 Total heat generation profile for 5p5s arrangement

5.2 Ohmic Heat Generation Ohmic heat generation is due to the battery’s internal resistance to the flow of electricity that is why it will be higher at a contact point. This can be observed (Figs. 7, and 8) that at the contact where the cell and tab zone met the value of ohmic heat generation value is much higher.

Fig. 7 Ohmic heat generation profile for 1p2s and 1p5s arrangements

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Fig. 8 Ohmic heat generation profile for 5p5s arrangement

5.3 Static Temperature Higher values of temperature can be observed at positive and negative tab zone compared to the cell zone (Figs. 9, and 10) from the results of the simulation. The

Fig. 9 Static temperature profile for 1p2s and 1p5s arrangements

Fig. 10 Static temperature profile for 5p5s arrangement

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second observation is that which are at the bottom has a higher value of temperature compared to the cells which are at the top.

6 Conclusion Prolonged battery life can be only achieved by an efficient cooling system, which needs the knowledge of temperature distribution and heat generation of the battery. In this paper, we have presented the simulation results of the Li-ion battery pack, which shows the contours of heat generation and temperature distribution. So, the major cause of heat generation we found using Ansys simulation is the ohmic heat generation, which was caused by the internal resistance of the battery, and it was observed that the temperature of the battery pack was almost identical at all areas but there was a slight increment at the contact zone of two Li-ion battery cell. The heat was distributed almost uniformly throughout the battery pack. The second important outcome was we can be able to get the value of temperature at different points of the battery pack without doing extensive and time-consuming experiments. Another important result is that the virtual connection method is more stable compared to the busbar connection method. The benefit of the virtual connection method compared to the busbar connection method is that calculation time is drastically reduced. Busbar is a tiny component that connects two battery cells and meshing of it is a very challenging task. After knowing the thermal behavior of Li-ion battery, a customizable cooling system can be designed easily. In future aspects of research, we would like to change the dimension of the battery cell and battery pack arrangements and compare the results with experiments. Acknowledgements Without the guidance and motivation provided by our mentor Dr. Vivek K. Patel, this work would not be possible. We would also like to acknowledge all the support provided by our institute Pandit Deendayal Petroleum University.

References 1. https://www.energy.gov/eere/articles/how-does-lithium-ion-battery-work 2. https://hone.mentra.mohammedshrine.org/diagram-basic-lithium-ion-battery-charger-circuitlithium-ion-battery.html 3. Zhang X (2011) Thermal analysis of a cylindrical lithium-ion battery. Electrochim Acta 56(3):1246–1255. https://doi.org/10.1016/j.electacta.2010.10.054 4. Kizilel R, Sabbah R, Selman JR, Al-Hallaj S (2009) An alternative cooling system to enhance the safety of Li-ion battery packs. J Power Sources 194(2):1105–1112. https://doi.org/10.1016/ j.jpowsour.2009.06.074 5. Pesaran A, Santhanagopalan S, Kim GH (2013) Addressing the impact of temperature extremes on large format Li-ion batteries for vehicle applications. Presented at: Proceedings of the 30th international battery seminar, Ft. Lauderdale, Florida

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6. Ma S, Jiang M, Tao P, Song C, Wu J, Wang J et al (2018) Temperature effect and thermal impact in lithium-ion batteries: a review. Prog Nat Sci Mater Int. https://doi.org/10.1016/j.pnsc.2018. 11.002 7. Zhao R, Liu J, Gu J (2015) The effects of electrode thickness on the electrochemical and thermal characteristics of lithium-ion battery. Appl Energy 139:220–229. https://doi.org/10.1016/j.ape nergy.2014.11.051 8. Fan L, Khodadadi JM, Pesaran AA (2013) A parametric study on thermal management of an air-cooled lithium-ion battery module for plug-in hybrid electric vehicles. J Power Sources 238:301–312. https://doi.org/10.1016/j.jpowsour.2013.03.050 9. Mahamud R, Park C (2011) Reciprocating airflow for Li-ion battery thermal management to improve temperature uniformity. J Power Sources 196(13):5685–5696. https://doi.org/10. 1016/j.jpowsour.2011.02.076 10. Karimi G, Dehghan AR (2012) Thermal management analysis of a lithium-ion battery pack using flow network approach. Int J Mech Eng Mechatron 1:88–94. https://doi.org/10.11159/ ijmem.2012.011 11. Goli P, Legedza S, Dhar A, Salgado R, Renteria J, Balandin AA (2014) Graphene-enhanced hybrid phase change materials for thermal management of Li-ion batteries. J Power Sources 248:37–43. https://doi.org/10.1016/j.jpowsour.2013.08.135 12. https://www.ansys.com/en-in/academic/free-student-products 13. ANSYS fluent battery module manual 14. Kim US et al (2011) Modeling the dependence of the discharge behavior of a lithium-ion battery on the environmental temperature. J Electrochem Soc 158(5):A611–A618 15. Jiang G, Huang J, Liu M, Cao M (2017) Experiment and simulation of thermal management for a tube-shell Li-ion battery pack with composite phase change material. Appl Therm Eng. https://doi.org/10.1016/j.applthermaleng.2017.03.107

Experimental Investigation of Heat Sinks with and Without Perforation—Addressing Toward Higher Cooling Rates and Optimum Material Rajshekhar V. Unni and M. Sreedhar Babu

Abstract This paper reports an attempt made to investigate the effect of fins with and without perforation on the convection coefficient (h) for cooling purpose. Experiments were conducted considering two specimens with six fins, one with solid fins and the other with perforations (of 8 and 10 mm diameters) on fins. The convection coefficient in terms of Nusselt number and Rayleigh number was also studied and compared with available literature work. It was found that experiments with perforated fins increased the convection coefficient up to 36%. Keywords Convection coefficient (heat-transfer coefficient) · Heat sink · Cooling · Nusselt number · Rayleigh number

1 Introduction The components (especially electronic) are continuously exposed to thermal environment need cooling. Their prolonged usage causes malfunctioning due to overheating of the components and eventually leading to technical failure. To address such needs, methods such as natural and forced convection are generally employed. The cooling process via forced convection is a costly affair and sensitive, as the operations are completely dependent on rotating element (or fan). In applications, such as nuclear and steam power plants, natural convection method is preferred for specific components. In case of natural convection, heat sinks (HS) with extended surfaces or fins are most effective to facilitate heat transfer. HS of various types are adopted for cooling of transformers, computers, LED bulbs, printed circuit boards and transistors. Use of HS is economical and also space saving. When HS or fin arrays are used for cooling R. V. Unni (B) · M. Sreedhar Babu Department of Mechanical Engineering, Jain College of Engineering, Belagavi, Karnataka 590014, India e-mail: [email protected] M. Sreedhar Babu e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_23

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under natural convection, the use of geometry which results in optimum cooling rate becomes significant. Therefore, the geometry of HS promoting optimum cooling with least material is an area to explore. Thus, the design of HS is considered as an important subject to pursue and contribute. Besides this, materials used for fins should possess good thermal conductivity to facilitate better heat transfer. Materials, such as aluminum, copper, silver, are known for their higher thermal conductivity. However, among these aluminum is cost-effective. In the following sections, discussions related to experimental method and the outcome of experiments are presented.

2 Literature Review Starner et al. [1] performed experimental studies on rectangular fin arrays and compared the results with Elenbass [2]. Retaining the fin length (10 in.), fin width (5 in.) and fin height (0.04 in.) constant, he varied fin spacing (0.25–0.313 in.) and number of fins (15 and 17). For different inclinations, flow patterns were studied and observed that the use of optimum number of fins increases the rate of heat dissipation. It was also observed that, for small spacing, due to interference in the boundary layer, i.e., airflow obstruction, convection coefficient values were less as compared to wider values of spacing. Average heat-transfer coefficient values [3] for shorter fin (5 in.) length were higher as compared to longer (10 in.) fin length. Leung et al. [4] carried out experimental work considering three cases, namely vertical fins with horizontal base, vertical fins with vertical base and horizontal fins with vertical base. For constant temperature difference (T wall − T amb ) and same geometry under free convection, heat dissipation from vertical fin with horizontal base was highest, horizontal fins with vertical base were lowest and the other setup was intermediate. Optimum fin spacing was 10.5 ± 1 mm with duralumin fin material. Leung and Probert [5] studied the influence of fin height (10 mm, 17 mm), and the authors concluded that the variation in fin height and temperature difference (T wall − T amb ) did not affect the optimum spacing of fin values. Leung and Probert [6] experimentally studied the effect of spacing between consecutive vertical rectangular fin arrays under natural convection heat transfer at steady state. 3% increase in the dissipation rate was seen with material saving of fin for a gap width of 18 ± 2 mm. Yuncu and Guvenc [7] studied vertical base rectangular fin array arrangement under natural convection mode. It was found that experiments with vertical base were efficient than that of horizontal base. The influence of height and spacing of fins and temperature difference (T base − T amb ) on the heat dissipation rate was observed for different power inputs. From the results, it was concluded that the thermal performance of fin arrays is majorly influenced by fin spacing. Awasarmol and Pise [8] investigated rectangular fin arrays under natural convection, and the results were compared with and without perforation. Experiments were conducted for 0–90° inclinations by changing perforation diameter (4–12 mm). For the HS with 45° inclination and 12 mm perforation diameter, 32% increase in convection coefficient was noted along with the material saving of 30%.

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Table 1 Properties of Aluminum alloy 6082 Material property

Property value

Density

2680 kg/m3

Melting point

660 °C

Modulus of elasticity

70 GPa

Electrical resistivity

0.031 × 10−6 

Thermal conductivity

200 W/m K

Thermal expansion

23.5 × 10−6 /°K

It is inferred from the above literature that the optimum fin spacing is ranging from 6.1 to 11.9 mm which gives maximum heat dissipation, when the fin length is ranging from 150 to 375 mm, fin width from 190 to 250 mm, fin height from 25 to 90 mm and the base-to-ambient temperature difference from 20 to 150 °C. With most of the above experimental work, cost-effective higher thermal conductivity material was chosen. Also, fin thickness was varied between 3 and 19 mm.

3 Materials and Methodology Aluminum alloy (6082) as a HS material was considered in the present work. It is basically a medium strength alloy material with excellent corrosion resistance. Table 1 shows the physical properties of the material. The convection coefficient was determined by supplying a known quantity of heat input to the heating coil. All the required temperatures were noted after HS attained a steady-state condition. Four thermocouples T 1 , T 2 , T 3 and T 4 were used to measure the surface temperature; these thermocouples were fixed tightly at the drilled hole locations as shown in Fig. 2. Another thermocouple (T amb ) was used to measure the prevailing (ambient) temperature. Furthermore, Nusselt number as a representative parameter was studied to validate the present experimental results. The list of assumptions followed in the present work for HS analysis is presented below. 1. 2. 3. 4. 5. 6.

Material is isotropic. Thermal conductivity is assumed to be constant. Shape factor is assumed to be 0.05. At steady-state heat supplied is equal to heat conducted through the fin base. Fin temperature is same as the temperature of base. The heat input gets divided equally in two halves of the HS.

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3.1 The Heat Sink and the Heating Coil The specimen was made up of two halves, having a geometric similarity with a heating coil at the center as shown in Fig. 1. This arrangement helps in equal distribution of heat to both the halves of HS. The base of HS was thermally insulated as largely followed in the literature [7]. Figure 1 represents the assembly of HS and the heating coil. Schematic view of one half of the HS depicting the notation followed in the present work for various dimensions is as shown in Fig. 2 where, L—length of the HS, W —base width of HS, S—spacing between the adjacent fins, H—height of the fin, t f —thickness of fin, t b —thickness of the HS base. Heater is rectangular in shape (180 mm × 66 mm), made through winding nichrome wire on mica sheet. The electrical resistance of a heating coil is about 50–60 . The heating coil was sandwiched between the two halves of HS and firmly fixed using screws and nuts at all corners.

Fig. 1 Symmetric heat sink assembly

Fig. 2 Various notations of a heat sink

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Fig. 3 Schematic view of experimental test-rig

Table 2 Instruments and the least count

Instrument

Least count

Ammeter (I)

0.01 A

Voltmeter (V )

0.0001 V

Temperature indicator (T )

0.1 °C

Alternating current from mains is supplied to the heating coil attached to the HS through an auto-transformer (dimmer stat). Voltage and current are measured using digital meters as shown in Fig. 3.

3.2 Uncertainty Analysis Based on the method proposed by Kline and McClintock [9], the uncertainty involved in the present experimental work was 3%. The list of instruments used for the uncertainty calculation is set out in Table 2.

4 Results and Discussion 4.1 Temperature History for Steady-State Analysis Temperatures from T 1 , T 2 , T 3, T 4 , and T amb were noted at regular time intervals to ensure a steady-state condition. The test-rig achieved steady-state condition almost

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Fig. 4 Time history of temperature difference for steady-state analysis

after 2–3 h as shown in Fig. 4. At steady state, for the supplied heat input, the convection coefficient was calculated [7] accordingly.

4.2 Experiments with Solid 6 Fin Based Heat Sink From Fig. 5a, b, it has been observed that the magnitude of convection coefficient and the base-to-ambient temperature difference increases with increase in total heat supply for solid fin-based HS.

Fig. 5 Variation of convection coefficient and base temperature difference

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4.3 Experiment with Six Fin-Based Perforated (8 and 10 mm) Heat Sink Figure 6a, b, shows the geometrical details of 6 fin-based HS with 8 and 10 mm perforations. The convection coefficient values were found to increase with increase in heat

Fig. 6 a Fin configuration with 8-mm-based perforated heat sink. b Fin configuration with 10mm-based perforated heat sink

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Fig. 7 Comparison of convection coefficient for different heat inputs

supply. HS with 10 mm perforation resulted in highest yield of heat-transfer coefficient, followed by an 8 mm-based perforated HS and the solid HS being the least. In summary, with 26.2% of material saving, an appreciable increase in convection coefficient of approximately 36% was noted (Fig. 7). Experimental results obtained in the present work were verified by analyzing non-dimensional parameters, namely Nusselt (Nu) and Rayleigh (Ra) number as followed in the literature. The Rayleigh number was calculated using standard heattransfer relation, and the Nusselt number was calculated experimentally through convection coefficient [7, 10]. Furthermore, the experimentally calculated Nu number was compared against the Nu number calculated using standard Churchill and Chu’s correlation [7, 8, 10] as depicted in Fig. 8. On comparison, present work was found in agreement with Churchill and Chu’s work with an error of 4%. The cause of error was attributed to consideration of HS with vertical fins in present work as compared to HS surface without fins of Churchill and Chu’s work.

5 Conclusion In the present work, experiments were conducted on heat sink to assess the scope of heat-transfer rate for promoting the cooling process. It has been inferred that heat sink with perforated fins yielded the higher magnitude of convection coefficient as compared to non-perforated plane fins. Estimates indicated an overall increase of 36% in heat-transfer coefficients with 26.2% of material saving. As a way forward, experiments with variation in perforation diameters and shapes can be examined.

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Fig. 8 Validation of present work with literature

Acknowledgements Authors would like to thank the Director and Principal of Jain College of Engineering, Belagavi, for financial assistance. Sincere thanks to Head of Mechanical Engineering Department for the infrastructure support and motivation through the work.

References 1. Starner KE, McManus HN (1963) An experimental investigation of free convection heat transfer from rectangular fin arrays. J Heat Transf 85:273–278 2. Elenbaas W (1942) Heat dissipation of parallel plates by free convection. Physica 9(1) 3. Harahap F, McManus HN (1967) Natural convection heat transfer from horizontal rectangular fin arrays. Trans ASME Ser C J Heat Transf 89:32–38 4. Leung CW, Probert SD, Shilston MJ (1985) Heat exchanger design: thermal performances of rectangular fins protruding from vertical or horizontal rectangular bases. Appl Energy 19:287– 300 5. Leung CW, Probert SD (1989) Thermal effectiveness of short-protrusion rectangular, heatexchanger fins. Appl Energy 34:1–8 6. Leung CW, Probert SD (1997) Heat-exchanger performance: influence of gap width between consecutive vertical rectangular fin-arrays. Appl Energy 56(1):1–8 7. Yuncu H, Guvenc A (2001) An experimental investigation on the performance of rectangular fins on a vertical base in free convection heat transfer. Heat Mass Transf 37:409–416 8. Awasarmol UV, Pise AT (2015) An experimental investigation of natural convection heat transfer enhancement from perforated rectangular fins array at different inclinations. Exp Therm Fluid Sci 68:145–154 9. Kline SJ, McClintock FA (1953) Describing uncertainties in single sample experiments. Mech Eng 3–8 10. Yazicioglu B (2005) Performance of rectangular fins on a vertical base in free convection heat transfer. Thesis of M.S. in Mechanical Engineering

Selection of Optimum Castor–Rapeseed Emulsified Fuel Based on Engine Performance, Combustion and Emission Analysis Sajan Chourasia , Rajesh Patel , and Absar Lakdawala

Abstract The existence of water with inside biodiesel–diesel blended fuel in the form of W/O emulsion drops the percentage of NOx and SD due to micro-explosion phenomena. Considering this in mind in the current work, optimum blend of dual biodiesel with diesel blend (C15R15) has been selected directly based upon previous work carried out on engine performance, combustion and emission of duel fuel optimum percentage using MCDM technique. This optimum blend has been used for the preparation of W/O emulsified fuel. In emulsified fuel, water percentages were varying from 1 to 5%, and different emulsified sets of fuel blend are prepared based on HLB ratio ranging from 4.3 to 6. The current experiments were carried out on VCR single-cylinder, four-stroke, water-cooled diesel engine operated under varying load conditions 0–110% at constant operating speed (1500 rpm) with injection time 20° BTDC. Based upon the engine performance, combustion, and emission analysis and then multiplying them with load factor, the best optimum emulsified fuel has been selected. From the results emulsified fuel having 5% water concentration, HLB: 6 and 2% surfactant were found to be the best optimum emulsified blend. Keywords C.I engine · Alternate fuel · Engine performance · Emission analysis · Emulsification · Dual bio-diesel

1 Introduction In India, agriculture is one of the major sectors the farming incorporates mostly in the GDP of India. One of the alternatives to diesel can be biofuel obtained from plants. Biofuels can be used as an alternative in the existing CI engines fully or partially in a blended form with diesel without modification resulting in less dependency on foreign crude oil import, which increased the economic growth of the country. Among all work done with biodiesel, it has been observed that it reduces exhaust emissions S. Chourasia (B) · R. Patel · A. Lakdawala Mechanical Engineering Department, Institute of Technology, Nirma University, Ahmedabad, Gujarat 380015, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_24

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such as PM, CO2 , NOx , HC and CO [1–4]. NOx is mainly produced due to high peak temperatures during the combustion. To reduce the effect of this on environment, various researchers are trying to reduce the peak temperature at which N2 and O2 react to form the NOx . Exhaust gas recirculation can reduce NOx emission, but it increases PM emission, and oxygen enrichment reduces PM emissions but increases NOx emission. For the fulfillment of the latest European emission norms and to keep the environment safe, further reduction in NOx is needed which is being obtained by the use of biodiesel–diesel blend, and this can be reduced by the addition of water in fuel as an additive. Emulsification is the method in which two or more immiscible fluids (polar and non-polar) are mixed to form a homogeneous mixture in the presence of active surface agents known as surfactants or emulsifiers using externally applied force. This force is applied using mechanical work, humanizer, ultrasonic and supersonic vibrations, etc. These fluids are thermodynamically stable. Prof. B. Hopkins proposes the introduction of water inside the engine for the enhancement of BTE and the reduction of toxic emissions. There are three methods by which water can be introduced in the system: Preparing water–oil emulsion, fumigating water into intake of air and direct injection into the combustion chamber with the help of injector [5]. Water can be added to the engine without any modification. The addition of water into the fuel is one of the methods of reducing the NOx emission and PM without affecting the performance of the engine [6, 7]. With the emulsified fueled engine, during combustion, the water has a lower boiling point compared to that of diesel. In combustion, during primary fuel atomization in the combustion chamber, compressed heated air transfers heat to water droplet before that of diesel and results in conversion into water vapor with into fraction of second. This will cause a micro-blast into water droplet, which is inside the oil droplet and hence due to this, diesel droplets spread into surrounding, which is now divided into very smaller (fine) particles (secondary atomization). The surface area of the fuel to air increases during the combustion process, and this phenomenon is known as “micro-explosion.” The combustion efficiency improves by the addition of water in emulsified form. Break power, break thermal efficiency and engine torque are also improved. Figure 1 shows a schematic diagram of the “micro-explosion” phenomenon. The micro-explosion phenomenon of the water enhances the atomization and vaporization [8]. Due to addition of water in fuel, a marginal improvement in the BP, torque, BTE, BSFC, etc., can also be obtained, not only this during combustion the peak

Fig. 1 Schematic diagram of water in oil emulsion fuel during the micro-explosion phenomenon

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temperature of combustion chamber also reduces because the water droplets absorb the heat (acts as an intercooler of gas). It also provides better burning efficiency resulting in the NOx emission which reduces due to the reduction of peak temperature at which N2 and O2 react to form the NOx .

2 Experimental Setup and Methodology 2.1 Experimental Setup All the experiments were carried on an automatic computerized CI engine test rig fitted with mono cylinder, four-stoke, multi-fuel, direct injection, water cooling CI engine having 110 mm stroke and 87.5 mm bore made by Kirloskar India. The computerized test rig is equipped with crank angle encoder that can measure up to 5500 rpm (TDC pulse), water-cooled eddy current dynamometer for load measurement, K type load cell for load measurement (0–50 kg), piezo sensor having max capacity of 5000 PSI equipped with optical low noise cable for pressure measurement, RTD-type thermocouple temperature measurement sensor, rotameter for water flow measurement, 16 lit fuel tank capacity, etc. The test rig can record BP, BSFC, BTE, ME, NHR, etc., using NI USB-6210 data acquisition system. The engine compression ratio can be adjusted between 12 and 18. Fuel injection can also vary from 0–25° BTDC. For the measurement of engine emission, gas analyzer and smoke density analyzer are used, which can measure NOx , CO, CO2 , HC, etc (Fig. 2).

Fig. 2 Schematic line diagram of the CI engine experimental setup

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2.2 Experiment Methodology A B30 blend of 15% castor and rapeseed each biodiesel and 70% diesel (C15R15) has been directly selected from the previous research work using the MCDM technique for the identification of optimum percentage of duel biodiesel based on their performance, combustion and emission characteristics. In the current experiment, water has been added as an additive in the range of 0–5% with an interval of 1% for the preparation of W/O (water in oil)-type emulsified biodiesel–diesel blend. A mixture of lipophilic and hydrophilic has been chosen as a surfactant in a range of 0–3% with an interval of 1%, and the hydrophilic–lipophilic balance (HLB) ratio has been selected as 4.3, 5 and 6. SPAN 80 (Sorbitan monooleate) (HLB 4.3) and TWEEN 80 (Polysorbate 80) (HLB 15.0) are chosen as a surfactant. A combination of all the abovementioned ranges of water, surfactant and HLB ratio has been considered for the selection of best stable blend, which is blended for 4 h at 3000 RPM using mechanical stirrer at room temperature. All the experiments were carried out with a constant 20° BTDC of injection timing, 220 bar of injection pressure, and 18-compression ratio has been directly selected from the previous research work [9]. The engine has been operated at various loading conditions such as 0–100% load with an interval of 25% and with 10% overloading at 110% having 0–12 kg load with an interval of 3 kg and an overload of 13.2 kg for all the emulsified stable blends. 95% of confidence level has been maintained by taking readings six times as per the student-t chart.

3 Result and Discussion 3.1 Stability Analysis The stability of emulsified fuel can be defined as the property of fuel in which the mixture of additives and fuel keeps themselves in a homogenous state with respect to time and surrounding temperature. The stability of two-phase W/O emulsion has been calculated based upon the separation percentage and volumetric sedimentation of the water and biodiesel–diesel blend as per ASTM D3707-89 and D3709-89. The stability of the emulsified fuel depends on the emulsification technique, process time, water concentration, quantity of surfactant and stirring intensity. At every interval of every 1 h, the separation percentage of the emulsion is observed and recorded. The separated percentage of water in emulsified fuel gets settled at the bottom of the measuring cylinder, which is prepared from various blends with a variation in HLB ratio and surfactant percentage. The most stable blend among the abovementioned range of HLB and surfactant percentage is found to be HLB 6 and 2% surfactant. The droplet diameter of the micro-emulsions is found to be 1.68 µm, and it should not vary away from 0.1 to 20 µm. Figure 3 shows only water percentage variation from 1 to 5% with HLB 6

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Fig. 3 Stability study of an emulsified water–biodiesel–diesel blend containing water varying from 1 to 5%, respectively. Figure a (1% water) to e (5% water), HLB: 6 and surfactant: 2%

and 2% surfactant after 24 h of the time interval. It can be observed that with 5% water, the most stable blend has been found, and as the water percentage increases beyond 5%, the stability of emulsified fuel reduces. The reason behind this is for higher water concentration, the higher cohesion force attracts extra water droplets to come closer to each other. Resulting formation of bigger droplets and because of its higher weight, it gets settled down. Coalescence and Ostwald ripening are accounted as two major probable reasons of separation or break down process in the emulsion system. The polydispersity index of fuel is found to be 0.275, and for an effective micro-explosion, the dispersity index should fall between these two extreme values of PDI (i.e., 0.05–0.7). The calculations used for the determination of size and PDI parameters are defined in the ISO standard documents 13321:1996 E and ISO 22412:2008 [10] (Tables 1 and 2).

3.2 Performance Analysis The variation of different engine performance parameters (BP, BTE, ME, BSFC) with engine loading by using emulsified fuel in the engine is shown in figure. Figure 4a shows a variation of BP with engine load. There is no difference brake power at 100% loading condition for C15R15 and W4 S2 HLB6 blend in comparison with neat diesel fuel. For 10% overloading with 110% loading brake power, 3.60 kW

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Table 1 Properties of fuels measured as per ASTM D 6751 KV cSt@40 °C

D (kg/m3 )

CV (kJ/kg)

FP (°C)

CN

830

42,550

63

48

S. No.

Fuel/Blends

1

Diesel

2

C15R15

857.45

40,945

91.35

48.105

3

W1S2HLB6

16.9971

862.1865

40,366.45

91.8595

46.66185

4

W2S2HLB6

16.97286

863.612

39,957

90.946

46.1808

5

W3S2HLB6

16.94862

865.0375

39,547.55

90.0325

45.69975

6

W4S2HLB6

16.92438

866.463

39,138.1

89.119

45.2187

7

W5S2HLB6

16.90014

867.8885

38,728.65

88.2055

44.73765

2.51 3.083

KV Kinematic viscosity, D Density, CV Calorific value, FP Flashpoint, CN Cetane number

Table 2 Composition of fuels S. No.

Fuel/Blends

Composition

1

Diesel

100% Diesel

2

C15R15

70% Diesel + 15% Castor + 15% Rapeseed

3

W1S2HLB6

97% C15R15 + 2% Surfactant + 1% Water

4

W2S2HLB6

96% C15R15 + 2% Surfactant + 2% Water

5

W3S2HLB6

95% C15R15 + 2% Surfactant + 3% Water

6

W4S2HLB6

94% C15R15 + 2% Surfactant + 4% Water

7

W5S2HLB6

93% C15R15 + 2% Surfactant + 5% Water

is obtained with W3 S2 HLB6 and W4 S2 HLB6 blend. This is mainly due to the micro-explosion phenomenon, which exerts an additional force on the piston top. Figure 4b shows the variation of thermal efficiency with engine load. We can see that BTE is increased with an increase in water content. Due to higher density, oxygen contains and caloric value of castor and rapeseed biodiesel and emulsification of fuel improve the combustion efficiency and hence BTE increases. Figure 4c shows the variation of mechanical efficiency with the load. It can be seen that maximum mechanical efficiency (ME) is obtained with a W4 S2 HLB6 emulsified blend. ME is 58% higher compared to neat diesel fuel. The reason for increasing the ME is the increase of BP of the engine due to emulsification. Figure 4d shows a variation of BSFC with engine load. BSFC reduces with an increase in load. There is no difference in BSFC for C15R15 and neat diesel blend. However, emulsified fuel has a higher BSFC compared to neat diesel and C15R15. With the increase of water percentage in emulsified diesel–biodiesel fuel blend, the BSFC and density increase and calorific value reduces.

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Fig. 4 Engine performance analysis. a Load versus BP, b load versus BTE, c load versus ME, d load versus BSFC

3.3 Combustion Analysis Figure 5 shows the effects of emulsified fuel on combustion analysis (Pmax , NHR and DP). Figure 5a shows the variation of Pmax with the load. Cylinder pressure is maximum for the C15R15 blend. The lowest pressure is obtained with the emulsified blend having 5% water. With the addition of water, Pmax reduces and this may be because lower CV of fuel, water droplet absorbs high heat energy surrounding during combustion and reduces the high temperature and pressure. Figure 5b shows the ignition delay or delay period (DP) of different blends. Lower ignition delay reduces the accumulation of fuel during the pre-flame combustion and reduces the knocking tendency. The higher delay period is reported for diesel, whereas lower is reported with emulsified fuel. Figure 5c shows the variation of net heat release (NHR) per degree crank angle at 100% loading condition. With increasing water content, NHR reduces. This may be because peak pressure inside the cylinder is reduced due to the emulsification process. The NHR of fuel combustion is negative during the initial

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Fig. 5 Combustion analysis. a Load versus Pmax , b load versus DP, c CA versus NHR, d CA versus Pmax

stages of fuel injection. During the initial stages, the atomized fuel injected into the engine absorbs the heat from high-temperature air and starts vaporizing. The reaction between the molecules of the fuel starts in the absence of flame that is known as pre-flame combustion. Due to pre-flame combustion, the pressure of the cylinder decreases and reaches the minimum value, at which the rate of net heat absorption is equal to the rate of net heat release. After this, the cylinder pressure increases due to an increase in the rate of NHR as the combustion of fuel starts. Figure 5d shows the variation of Pmax with a crank angle at 100% loading condition. Maximum pressure is obtained with the C15R15 blend, and the minimum is obtained with a W5 S2 HLB6 emulsified blend due to low calorific value.

3.4 Emission Analysis Figure 6 shows the effects of emulsified fuel on emission analysis (NOx , HC, CC

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Fig. 6 Emission analysis. a Load versus NOx , b load versus HC, c load versus smoke density

and SD). Figure 6a shows the variation of NOx emission with engine loading. The maximum value is obtained with neat diesel fuel, and the lowest is with emulsified fuel having 5% water. 64% reduction in NOx emission is reported with 5% water in comparison with diesel fuel. By adding water into a blend of biodiesel, the latent heat of vaporization increasing due to that maximum temperature at which N2 and O2 react to form NOx reduces and hence reduction in NOx emission. One more reason is due to the lower viscosity and calorific value of the biodiesel, emulsified blends of biodiesels due to the addition of water may be the reason for the falling trend of NOx formations [11]. Figure 6b shows the variation of HC with respect to engine load. Maximum HC is obtained with emulsified fuel having 1% water, and the minimum is reported for emulsified fuel having 5% water. During the combustion of fuel in the CI engine, some fuel molecules remain unburned due to a lower rate of reaction. This reduction is because of the addition of water to the blended biodiesels and the water, which is produced at a significant rate due to the breakdown of fuel particles during the combustion process. Also due to proper turbulent mixing of fuel and air, the combustion characteristics improve significantly, which is evident from the graphs,

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as shown in the combustion analysis. This improves the burning of the fuel and hence causes uniform and complete burning of fuel particles, which in turn reduces the amount of soot formation. The higher temperatures at higher loads significantly improve the combustion and the micro-explosion processes, which enhances the burning quality of fuel and thereby reducing the HC emissions [12]. The emission (NOx + HC) of the existing engine is found to be 2.95 g/kWh, which is more than two times lower than maximum allowable limit BS-4 norms (NOx + HC) 7.5 g/kWh. Figure 6c shows the variation of smoke density with engine load. Lower smoke density is reported at higher water percentage due to better combustion efficiency. The possible reason might be due to the richness of fuel, high viscosity due to the addition of water and due to lower fuel volatility, which eventually leads to slower combustion of emulsified fuel in contrast to diesel [13].

3.5 Selection Parameters The result includes different parameters and having different measuring units, so a direct comparison of these parameters is not possible. Therefore, percentage weightage has been given to different parameters as per the current objective of the paper. The parameters are NOx , HC, SD, BSFC, BTE, DP and Pmax . These seven parameters are sorted into three major groups, such as engine performance, combustion and emission. Based on the importance, the weightage of these groups has been decided. The objective of this paper is to reduce emissions, so 50% weightage has been allocated to engine emission and 25% to engine performance and combustion each. As in real world during the entire life of CI engine, it is not continuously operated at its full rated load (100%) so to get results near to real-life scenario, all the results are multiplied with the load factor at which the engine runs maximum time that is 50% or 6 kg load as shown in Table 3. The load factor value is considered as 0.6 based on 60% weightage provided to 50% engine load. For validating the load factor, reference has been taken, which is provided by the US environmental protection agency, which is “median life, annual activity and load factor values for non-road engine emissions modeling NR-005b”. As per this document, the off-road SI and CI engines are bifurcated, and a load factor has been provided. The CI engine, which is being used for the current experiment investigation, comes under diesel other agricultural equipment (SCC-2270005055), and the loading factor is provided as “0.59” [14]. After applying load factors on engine performance, combustion and emission data, the final result is obtained and is shown in Table 4. On the basis of that, it can be justified that using emulsified fuel containing 5% water fulfills the current Table 3 Selection parameters for load factor distribution Load (%)

0

25

50

75

100

Load factor

0.05

0.15

0.6

0.15

0.05

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Table 4 Final result after applying the load factor S. No.

Fuel/Blends

NOx

HC

SD

BSFC

BTE

DP

Pmax

1

Diesel

238.98

4.87

0.57

0.39

25.40

6.52

50.79

2

C15R15

152.98

3.60

0.26

0.39

25.10

3.26

53.68

3

W1S2HLB6

193.57

7.91

0.73

0.41

21.73

5.25

52.32

4

W2S2HLB6

142.73

6.35

0.97

0.44

22.57

5.93

50.52

5

W3S2HLB6

141.23

5.55

0.93

0.46

23.18

5.56

49.95

6

W4S2HLB6

129.69

4.30

0.71

0.46

23.75

3.45

48.91

7

W5S2HLB6

107.60

2.01

0.36

0.48

24.12

3.00

48.51

NOx Nitrogen oxide, HC Hydrocarbon, SD Smoke density, BSFC Break specific fuel consumption, BTE Break thermal efficiency, DP Delay period, Pmax Maximum pressure

objective of the research, which is a reduction in engine emission and improvement in engine performance.

4 Conclusion The conclusions of the present work are mentioned below: • With the increase of water percentage, NOx and smoke density (SD) are found to be reduced with a marginal increase of HC due to micro-explosion phenomena. • Marginal improvement in the performance of the engine including BP, ME, BTE due to micro-explosion phenomena. • 5% water with 2% surfactant having a 6 HLB with optimum blend C15R15 is found to be the best emulsified optimum fuel blend.

References 1. Agarwal AK, Bijwe JJ, Das LM (2003) Effect of biodiesel utilization of wear of vital parts in compression ignition engine. ASME J Eng Gas Turbines Power 125(2):604–611 2. Agarwal AK, Dhar A (2010) Experimental investigation of preheated Jatropha oil fueled direct injection compression ignition engine-part 2: engine durability and effect on lubricating oil. J ASTM Int 1477:355–375 3. Agrawal AK (2007) Bio fuels (alcohols and biodiesel) applications as fuels for internal combustion engines. Prog Energy Combust Sci 33:233–271 4. Syed AB, Rajagopal K (2012) A review of the effects of catalyst and additive on bio-diesel production, performance, combustion and emission characteristics. Renew Sustain Energy Rev 16:711–717 5. Vellaiyan S, Amirthagadeswaran KS (2016) The role of water-in-diesel emulsion and its additives on diesel engine performance and emission levels: a retrospective review. Alexandria Eng J 55(3):2463–2472

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6. Selim MYE, Ghannam MT (2007) Performance and engine roughness of a diesel engine running on stabilized water diesel emulsion. SAE papers 2007-24-01 7. Bertola A, Li R, Boulouchos K (2003) Influence of water-diesel fuel emulsions and EGR on combustion and exhaust emissions of heavy duty DI-diesel engines equipped with common-rail injection system. SAE papers 2003-01-31 8. Daly DT, Langer DA (2000) Future fuels and fuel additives for vehicle emissions control. In: International proceedings of the 219th american chemical society national meeting, American Chemical Society, San Francisco, pp 26–31 9. Patel PD, Lakdawala A, Patel RN (2016) Box-Behnken response surface methodology for optimization of operational parameters of compression ignition engine fuelled with a blend of diesel, biodiesel and diethyl ether. Biofuels 7(2):87–95 10. Worldwide MI (2011) Dynamic light scattering, common terms defined. Inform white paper. Malvern Instruments Limited, Malvern, UK, pp 1–6 11. Chuah LF, Abd AR, Yusup S, Bokhari A, Klemes JJ, Abdullah MZ (2015) Performance and emission of diesel engine fuelled by waste cooking oil methyl ester derived from palm olein using hydrodynamic cavitation. Clean Technol Environ Policy 17(8):2229–2241 12. Parlak A (2005) The effect of heat transfer on performance of the diesel cycle and energy of the exhaust gas stream in a LHR diesel engine at the optimum injection timing. Energy Convers Manage 46(2):167–179 13. Melo E, Piloto R, Tobio I, Goyos L, Verhelst S (2014) Performance of a single cylinder diesel engine fuelled with emulsified residual oleins and standard diesel fuel. Renew Energies Power Qual J 12:183–188 14. Assessment and Standards Division EPA, Office of Transportation and Air Quality (2002) Median life, annual activity, and load factor values for non-road engine emissions modeling

Experimental Measurement of Laminar Flame Velocities of LPG–Air Mixtures with Cylindrical Flame Tube Method Akshay A. Kadam, Abhinandan D. Kadam, Nikhil P. Daphale, and M. Sreedhar Babu

Abstract This paper reports an experimental work related to measurement of laminar flame speeds of liquefied petroleum gas (LPG) (Indian domestic grade) against calibrated LPG fuel (70% propane + 30% n-butane). The measurements were carried out on in-house developed cylindrical flame tube apparatus. The flame speed was calculated by measuring the distance propagated by flame front of a known test length on flame tube. The reported work also brings out the partial automation feature that was added to the existing flame tube apparatus, which lead to determination of flame speed electronically. The average flame speed of respective gaseous fuels was measured on manual basis (using stop watch) and also through photocells (LDR sensors). The error in measurements was found to be well within 2% and quite satisfactory. The experimentally obtained values were compared against literature to address the gap. Keywords Laminar flame speed · Flame tube · LPG · LDR sensors

1 Introduction In the recent times, combustion has played a vital role in driving the humanity toward the pathway of prosperity and progress, but at the cost of environmental degradation. About, 80% of the worldwide energy demand is alleviated by combustion of fuels. A. A. Kadam (B) · A. D. Kadam · N. P. Daphale · M. S. Babu Department of Mechanical Engineering, Jain College of Engineering, Belagavi, Karnataka 590014, India e-mail: [email protected] A. D. Kadam e-mail: [email protected] N. P. Daphale e-mail: [email protected] M. S. Babu e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_25

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Hence, studies related to combustion phenomena still attract the interest of many combustion engineers for meeting the twenty-first-century society needs. The challenge posed by modern society in terms of curtailing the effect of global warming is critical and is of paramount interest. Therefore, better quality of life is at a crux of combustion. In reality, combustion is an everyday business with wide variety of applications ranging from usage of firewood to powering the space ships. Combustion as a process proceeds with a small kernel formation and grows up to a matured flame front through unburnt charge. Furthermore, nature of flame front may initially begin as laminar and then progress to turbulent phase depending on the prevailing conditions, as generally witnessed in fire hazard cases. Therefore, studies related to effects of combustion process (flame stabilization, lift-off, blow-off, auto-ignition, etc.) are significant. The combustion properties such as flame speed, ignition delay, minimum ignition energy, and the flammability limits [1–3] are greatly influenced by mixture strength, pressure, and temperature. Among these, laminar flame speed is significant, which strongly affects the burn rate and thus a critical property in the design of combustors [3]. Furthermore, laminar flame speed possesses inherent details such as diffusivity and reactivity of mixture involved [4], and the laminar flame speed data is also used in validation of chemical reaction mechanisms [5]. Various methods of measuring flame velocity are flat flame burner, slot burner, constant volume bomb method, constant pressure bomb method, tube methods, and so on [6]. For the present work, tube method was considered because of its simplicity for the purpose of burn rate model studies at the Combustion Research Laboratory of Jain College of Engineering, Belagavi. Major advantage of the tube method is that the effect of the surrounding atmosphere due to diffusion is not present as in case of burner method. Also, the quantity of fuel required is small as compared to the burner system. To minimize the effect of convection, a horizontal tube is used instead of a vertical one. On the other hand, the cylindrical tube method possesses few problems such as parallax error of human eye, quenching effect along the walls of tube, a hook shaped flame front along the axis, and distorted flame front due to reflected pressure waves which are well known issues. In the following section, the details of automation on in-house developed flame tube along with measurement of flame speed considering LPG–air mixtures are discussed.

2 Experimental Setup Flame propagation as a subject needs sophisticated modern measurement system due to the sensitivity in handling time intervals and flame front studies; this constitutes a major challenge while studying this subject. Transparent glass tube made up of borosilicate glass of 3 m length and 0.025 m of internal diameter was considered. The entire test-rig was designed based on the dimensions of the flame tube. The

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Fig. 1 Schematic of experimental setup

test-rig comprises of mixing chamber, buffer tank, flame arrestor, ignition unit, and finally, the flame speed measuring chain unit as shown in Fig. 1. The mixing chamber was fabricated using a simple Y-joint concept for achieving theoretically right amount of fuel and air mixture ratio. The mixing chamber was designed based on stoichiometry condition for the given fuel. Buffer tank was used to enable constant flow of required air and there by overcome variation in area ratios across the flow meters. An electronic gas igniter was used to generate the spark. The tube was open to the atmosphere at the ignition end while the other end of the tube was fitted with flame arrestor in order to confine the flame within the tube itself. Two cadmium sulfide light-dependent resistor (LDR) sensors at a known test distance were fitted on the flame tube. These LDR sensors were connected to Arduino board at the other end. The Arduino platform consists of a programmable circuit along with inbuilt software to accomplish an electronic intended task. A computer code was written to compute the flame speed as per Eq. 1. Furthermore, Miller’s law was invoked in the code to measure the time interval of flame propagation. The entire measuring chain system is represented as shown in Fig. 2. For comparison purpose, manual measurement of flame propagation using stop watch was also followed to estimate the error.

Fig. 2 Measurement chain system

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2.1 Experimental Procedure Bottled LPG fuel and zero-air grade (oxidizer) was procured and supplied to the mixing chamber at ambient conditions. The pressure factor arising from domestic LPG cylinder and the calibrated bottled LPG cylinder plays an important role from operational point of view. The oxidizer (zero-air grade) had a built-in pressure of 100 bar, domestic LPG > 2 bar (for ≈ 26 m3 capacity) and calibrated bottled LPG > 2 bar (for ≈ 2 m3 capacity). Higher pressure levels of fuel and oxidizer cylinders was reduced and regulated to near-ambient conditions by using a two-stage commercial regulator. The fuel and air flow rates were set close to stoichiometric values obtained from theoretical calculations. Rotameters (fuel and air) calibrated on water equivalent having accuracy within ±2% of full scale division were used to measure the flow rates as shown in Fig. 3. The fuel and oxidizer were allowed to mix prior to ignition, and as the spark was triggered the flame front developed travelled along the length of the tube consuming the unburnt charge as shown in Figs. 2 and 4. Flame speed =

distance travelled by flame front time taken to propogate test length

Fig. 3 Calibrated rotameters for flow measurements

(1)

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Fig. 4 Flame front propagation in a horizontal tube open at the ignition end [7]

3 Results and Discussion Experiments at ambient conditions (303 K and 101.325 kPa) were conducted to measure flame speeds on in-house developed flame tube apparatus. The outcome of experiments with domestic and calibrated LPG–air mixtures is set out in Table 1. The average time interval of flame propagation and the average laminar flame velocity with domestic LPG–air mixture on manual mode was 3.44 s and 0.58 m/s, respectively. However, the sensor-based obtained values stood at 3.39 s and 0.59 m/s, respectively. The error noted in flame velocity measurement was well within 2% and acceptable. The customized calibrated LPG (69.87% propane and 30.13% n-butane)–air mixtures under manual mode measurement resulted in 3.83 s and 0.52 m/s, respectively. However, the electronic-based measurement recorded 3.80 s and 0.53 m/s, respectively. A similar type of work by Tripathi et al. [8] with customized LPG Table 1 Laminar flame speed for LPG–air mixture Fuel

Oxidizer

Indian domestic LPG fuel

Air

Calibrated LPG fuel

Air

Manually recorded

Sensor recorded

Time (s)

Flame speed (m/s)

Time (s)

Flame speed (m/s)

% error in flame speed

3.48

0.575

3.43

0.583

1.37

3.44

0.581

3.38

0.591

1.69

3.40

0.588

3.36

0.595

1.17

4.14

0.483

4.10

0.487

0.82

3.61

0.554

3.59

0.557

0.54

3.76

0.531

3.71

0.539

1.48

The fuel and air were operated at an output pressure of 1 bar; Flame propagation test length: 2 m

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(a)

(b)

Fig. 5 a Domestic LPG flame front, b calibrated LPG flame front

fuel (n-butane: 44.98%, propane: 39.9%, methane: 1.9%, ethane: 4.1% and pentane: 9.12%) reported a flame velocity of 0.55 m/s at equivalence ratio (∅) = 1 and 0.57 m/s at ∅ = 1.2 with burner method. On comparison, flame velocities based on present work at lean mixtures are close, and the deviation is attributed to variation in LPG fuel content and method followed. However, at stoichiometry condition in the present work, an issue of triggering was encountered may be because of insufficient voltage at the electrode terminals [9]. Furthermore, distorted flame shapes at extreme flammable limits (lean or fuel rich conditions) were observed. The possible cause may be because of viscous and wall-quenching effects, and more details on the same can be found in any standard combustion literature [10]. One such elongated flame front curvature with higher amplitude in suspended form at fuel rich condition is shown in Fig. 5a. The corresponding flame front colors with domestic and standard calibrated LPG fuels were also quite different as shown in Fig. 5.

4 Conclusion In this paper, experimental measurement of flame speeds considering domestic LPG and calibrated LPG fuel–air mixtures on in-house developed flame tube is presented. To overcome manual errors in measurement of flame propagation time interval (and therefore flame speeds), a multidisciplinary approach (with a mix of combustion science, electronics, and coding interface) was followed. Under premixed and ambient conditions, the average laminar flame velocity of domestic LPG and calibrated LPG was found to be 0.59 m/s and 0.53 m/s, respectively, at lean condition. The error in manual measurement of flame velocities were well within 2%. The measurement of flame velocity finds its place in burn rate modeling studies, and it is a part of future work. Acknowledgements This paper and the research behind it would not have been possible without the exceptional encouragement and support of Dr. K. G. Vishwanath (Principal and Director, Jain college of Engineering, Belagavi) and Prof. D. B. Patil (HOD, Mechanical department). Authors would also like to extend gratitude to Col. Melville D’souza (Administration, Jain college of Engineering) for

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the basic infrastructure provided. Finally, it is with true pleasure that I acknowledge the contribution of Mr. Fernandes Yashlie Felestio, Mr. Gawas Sahil Vishwanath, Mr. Walke Pratik Mahesh, Mr. Asnotikar Sajan Vivekanandand, and Mr. Anup J. Gourgonda who have helped us in conducting the experiments.

References 1. Noor M, Wandel AP, Yusaf T (2014) Effect of air-fuel ratio on temperature distribution and pollutants for biogas MILD combustion. Int J Automot Mech Eng 10:1980–1992 2. Bosschaart KJ, De Goey L (2004) The laminar burning velocity of flames propagating in mixtures of hydrocarbons and air measured with the heat flux method. Combust Flame 136:261– 269 3. Hu E, Huang Z, He J, Jin C, Zheng J (2009) Experimental and numerical study on laminar burning characteristics of premixed methane–hydrogen–air flames. Int J Hydrogen Energy 34:4876–4888 4. KocharYTL, Seitzman J (2009) Laminar flame speeds of C1-C3 alkanes at elevated pressure and temperature with dilution. Presented at the Proceedings of the 6th US National Combustion Meeting 5. Yu Cheng CT, Huang Z (2015) Kinetic analysis of H2 addition effect on the laminar flame parameters of the C1-C4 n-alkane-air mixtures: from one step overall assumption to detailed reaction mechanism. Int J Hydrogen Energy 40:703–718 6. Mishra DP (2008) Fundamentals of combustion. Prentice-Hall of India Publications, New Delhi 7. Mulla TA, Kesarapenti MS, Shetye TK, Lad HJ et al (2020) Design and development of laboratory scale flame tube apparatus. AIP Publishing 8. Tripathi A, Chandra H, Agarwal M (2010) Effect of mixture constituents on the laminar burning velocity of LPG-CO2 -Air mixtures. ARPN J EngApplSci 2(3) 9. Yousif AA, Sulaiman SA, Nasif MS (2015) Experimental study on laminar flame speed and Markstein length of propane air mixtures at atmospheric conditions. Int J Automot Mech Eng (IJAME) 11:2188–2198 10. Glassman I (2008) Combustion, 4th edn. Academic Press, USA

Performance Analysis of Double Pipe by Using Different Nanofluids Bharat Naik, Merwyn Thomas, M. Sreedhar Babu, Anand K. Hosmani, Omkar Alloli, Kshitij Dasurkar, and Mahalaxmi Alloli

Abstract The study represents an enhancement of heat transfer using different nanofluids containing nanoparticles (Al2 O3 , SiO2 , Fe3 O4 ) volume fraction (0.02 ≤ φ ≤ 0.05). Numerical simulations are conducted using computational fluid dynamics (CFD) and the model is generated using SOLIDWORKS. The governing equations are solved iteratively using a SIMPLE technique and discretized using a finite volume approach. The results show that the heat transfer rate increases with the increase of the flow rates, also it has been observed that the heat transfer rate increases with increase of operating temperature and also by the concentration of nanoparticles. Keywords Computational fluid dynamics · Heat transfer · Nanofluids · Double pipe heat exchanger · ANSYS FLUENT · SOLIDWORKS

B. Naik (B) · M. Thomas · M. S. Babu · A. K. Hosmani · O. Alloli · K. Dasurkar · M. Alloli Department of Mechanical Engineering, Jain College of Engineering, Belagavi, Karnataka 590014, India e-mail: [email protected] M. Thomas e-mail: [email protected] M. S. Babu e-mail: [email protected] A. K. Hosmani e-mail: [email protected] O. Alloli e-mail: [email protected] K. Dasurkar e-mail: [email protected] M. Alloli e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_26

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1 Introduction Heat exchanger is a device which is designed to perform the heat transfer action by obeying the fundamentals of thermodynamics. The applications of heat exchangers are in various sectors such as power plants, heating and air conditioning in buildings, household refrigerators, and radiators. The heat exchangers are classified according to heat transferring method, design and construction, flow configuration, and the number of fluids used. The examples of heat exchangers are boilers, superheaters, condensers, automobile radiators, etc. The most commonly used fluids in the heat exchangers which are being used in the current industries are less efficient. There is a demand needed in industries for fluids which are having higher heat transfer co-efficient. There are various methods for enhancing the thermal properties and its performances and one of the best methods to do so is by using nanofluids [1–5]. Nanofluids are colloidal suspensions of nanosized (smaller than 100 nm) particles. Nanofluids are used for various applications and have many advantages such as better stability and rheological properties, no extra pressure drop, and high thermal conductivity. Masuda et al. [6] experimented thermal conduction of nanofluids using water as the base fluid which contains the particles of SiO2 , TiO2 , and Al2 O3 . Thermal Conductivity is determined from Maxwell model [7]. Li [8] studied the effects of temperature on thermal conduction of Al2 O3 and CuO using water (base fluid), keeping volume fraction as constant, the nanofluids clearly indicate thermal conductivity ratio increases with temperature. The viscosity of the base fluid affects the thermal conductivity and Brownian motion of the nanofluid [9]. Mateescu et al. [10] detailed an exploratory examination on constrained convective warmth move on nanofluids with 0–0.2 vol% of Al2 O3 nanoparticles streaming in a twofold funnel heat exchanger. According to Palm et al. [11] and Liu et al. [12], introducing nanoparticles at low concentrations (i.e., 1–5%) can enhance the heat transfer co-efficient.

2 Numerical Analysis The geometric model of the double pipe is prepared by the specification according to Table 1. Assuming there is no heat loss in the system. The heat removed Q h is Table 1 Geometry parameters

Geometry

Value

Outer tube (inlet dia)

0.062 m

Inner tube (inlet dia)

0.037 m

Inner tube (outer dia)

0.04 m

Length

1.575 m

Area

0.208 m2

Bend radius

0.035 m

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hot fluid (nanofluid) which is calculated by Eq. (1). The heat absorbed Q c (water) calculated by Eq. (2),   ˙ p h Th Q = Q h = mC

(1)

  Q = Q c = mC ˙ p c Tc

(2)

The effectiveness is calculated using Eqs. (3), (4), and (5), Q Q max

(3)

ε=

(Thi − Tho ) m h Ch < m c Cc (Thi − Tci )

(4)

ε=

(Tco − Tci ) m c Cc < m h Ch (Thi − Tci )

(5)

ε=

CFD method comprises of numerical arrangements of force, mass, and vitality protection with different conditions. The CFD method has been used to explore the heat exchanging process in the double pipe exchanger. Consistent state, incompressible liquid stream without mass exchange, and substance response were expected. Consequently, just the congruity, force, and vitality conditions are thought of. The overseeing conditions for laminar flow, consistent, and incompressible liquid stream are as follow. Continuity,  − → div ρ V = 0

(6)

 −  − →− → → div ρ V V = −gradp + ∇. μ∇ V + Sm

(7)

  − → div ρ V C P T = div(kgradT ) + Se

(8)

Momentum,

Energy,

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The Drew and Passman [13] relation is used for calculating the viscosity of nanofluid. μn f = μ f (1 + 2.5φ)

(9)

By using Choi relation [14], the density of nanofluid is calculated. ρn f = (1 − φ)ρ f + φρs

(10)

Xuan and Roetzel co-relation [15, 16] is used for the calculation of the heat capacity.     C p n f = (1 − φ)(ρC p ) f + φ(ρC p )s ρn f

(11)

Maxwell-Garnett’s approximation equation for thermal conductivity [7]   ks + 2k f − 2φ k f − ks kstationary   = kf ks + 2k f + φ k f − ks

(12)

The ANSYS FLUENT 17.1 was utilized in the current investigation. The program utilizes a method dependent on the control volume hypothesis to change over exemplary singular stage conservation conditions to mathematical conditions. The SIMPLE semi-certain strategy for pressure connected conditions was utilized to combine the weight and speed. The conditions were characterized at the inlet boundary as mass flow inlet and pressure outlet for outlet boundary. The magnitude of inlet velocity was specifically determined and velocity direction was considered as normal to the boundary. The velocity values and the temperature values are indicated.

3 Results and Discussion The geometry of the domains and meshing was done by ANSYS 17.1. The cut cell method was used for meshing. The geometrical config of double pipe for CFD simulation is shown in Fig. 1a. The model was meshed by 80,340 unstructured quadrilateral cells. The flow rates applied for the hot fluid (nanofluid) are 100, 150, 200, 250, and 300(l/h) and the cold fluid was kept constant at 90(l/h). The temperatures distributed in the double pipe are ranged from 296 to 323 K which indicates the temperature contour of the nanofluid is shown in Fig. 1b. Figure 2a–c illustrates the effects of Al2 O, SiO2 , Fe3 O4 nanofluid on the heat transfer rate Q(W ) versus flow rate (l/h) are seen. The 5% of Al2 O3 nanofluid is 19% higher than that of 2% Al2 O3 . The 5% of SiO2 (nanofluid) is 12% is higher than that of 2% SiO2 (nanofluid). The 5% of Fe3 O4 (nanofluid) is 3.27% is higher than that of 2% Fe3 O4 (nanofluid).

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Fig. 1 a Mesh double pipe heat exchange, b temperature contour, c indicates the relationship between the error in average heat transfer vs number of cells in the double pipe

Figure 3a–c illustrates the influence of Al2 O3 , SiO2 , and Fe3 O4 nanofluid on effectiveness and flow rate (l/h). The effectiveness of 5% Al2 O3 nanofluid is about 20.4% higher than that of 2% Al2 O3 nanofluid. The effectiveness of 5% SiO2 nanofluid is about 16.7% higher than that of 2% SiO2 nanofluid. The effectiveness of 5% Fe3 O4 nanofluid is about 7.85% higher than that of 2% Fe3 O4 nanofluid. Figure 4 shows the result of the present study being compared with Akhtari [15] of Al2 O3 nanofluid. After comparing the results with Akhtari [15], the heat transfer rate has increased by 6.3% in the present study.

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Fig. 2 Effects of nanofluids on heat transfer: a Al2 O3 , b SiO2 , c Fe3 O4

4 Conclusion The heat transfer performances of the nanofluids streaming within the double pipe were examined. Impacts of nanofluid on temperature, concentrations of nanoparticles, flow rates, and also on the heat transfer co-efficients were explored. The following conclusion is obtained, and the nanoparticles enhanced the rate of heat transfer and the effectiveness of base fluid. Nanofluid temperature and flow rates of nanofluid increase the heat transfer rate.

Performance Analysis of Double Pipe by Using Different Nanofluids

Fig. 3 Effects of flow rate on the effectiveness: a Al2 O3 , b SiO2 , c Fe3 O4

Fig. 4 Comparison between present result and Akhtari [15] of (Al2 O3 ) nanofluid

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References 1. Hwang KS, Jang SP, Choi SUS (2009) Flow and convective heat transfer characteristics of water-based Al2 O3 nanofluids in absolutely developed streamline flow regime. Int J Heat Mass Transfer 52:193–199 2. Demir H, Dalkilic AS, Kürekci NA, Duangthongsuk W, Wongwises S (2011) Numerical investigation on the single phase forced convection heat transfer characteristics of TiO2 nanofluids in a double-tube counter flow heat exchanger. Int Commun Heat Mass Transfer 38:218–222 3. He Y, Jin Y, Chen H, Ding Y, Cang D, Lu H (2007) Heat transfer and flow behaviour of liquid suspensions of TiO2 nanoparticles (nanofluids) flowing upward through a vertical pipe. Int J Heat Mass Transfer 50:2272–2281 4. Bianco V, Manca O, Nardini S (2011) Numerical investigation on nanofluids turbulent convection heat transfer within a circular tube. Int J Therm Sci 50:341–349 5. Namburu PK, Das DK, Tanguturi KM, Vajjha RS (2009) Numerical study of turbulent flow and heat transfer characteristics of nanofluids considering variable properties. Int J Therm Sci 48:290–302 6. Masuda H, Ebata A, Teramae K, Hishinuma N (1993) Alteration of thermal conductivity and viscosity of liquid by dispersing ultra-fine particles (dispersion of γ-Al2 O3 , SiO2 , and TiO2 ultra-fine particles). Netsu Bussei 4(4):227–233 7. Maxwell JC (1873) A treatise on electricity and magnetism. Clarendon Press, Oxford 8. Li CH, Peterson GP (2006) Experimental investigation of temperature and volume fraction variations on the effective thermal conductivity of nanoparticle suspensions (nanofluids). J Appl Phys 99(8):084314 9. Daungthongsuk W, Wongwises S (2010) Comparison of the results of measured and computed thermophysical properties of nanofluids on heat transfer performance. Exper Therm Fluid Sci 34:616–624 10. Luciu RS, Mateescu T, Cotorobai V, Mare T (2009) Nusselt number and convection heat transfer coefficient for a coaxial heat exchanger using Al2 O3 –Water ph=5 nanofluid. Bull Polytech Inst Jassy 2:71–80 11. Palm SJ, Roy G, NguyenCT (2006) Heat transfer enhancement with the use of nano-fluids in radial flow cooling systems considering temperature-dependent properties. Appl Therm Eng 26:2209–2218 12. Liu MS, Lin MCC, Huang IT, Wang CC (2006) Enhancement of thermal conductivity with CuO for nano-fluids. Chem Eng Technol 29:72–77 13. Drew DA, Passman SL (1999) Theory of multicomponent fluids. Springer, Berlin 14. Kumar D, Choi SUS, Patel HE (2006) Heat transfer in nanofluids—a review. J Heat Transfer Eng 21(10):3–19 15. Akhtari M, Haghshenasfard M, Talaie MR (2013) Numerical and experimental investigation of warmth transfer of α-Al2 O3 / water nanofluid in double pipe and shell and tube heat exchangers. Appl Int J Comput Methodol 16. Xuan Y, Roetzel W (2000) Conceptions for heat transfer correlation of nanofluids. Int J Heat Mass Transf 43(19):3701–3707 17. Bianco V, Chiacchio F, Manca O, Nardini S (2009) Numerical investigation of nanofluids forced convection in circular tubes. Appl Therm Eng 29:3632–3642

Estimation of Contact Conductance Between Two Dissimilar Metal Rods by Jaya Algorithm Meet Parikh, Harsh Vaghela, Sanil Shah, and Ajit Kumar Parwani

Abstract Estimation of thermal contact conductance between two dissimilar metal rods for 1D transient heat conduction problem is carried out by inverse heat transfer using Jaya algorithm. Aluminum and brass are chosen as rod materials. Jaya is a simple and efficient algorithm in which the results achieved for a particular problem should move toward the best solution. Various cases like different population size, different profiles of contact conductance, and different errors in temperature measurements are considered. Jaya excellently estimates all profiles and is found to be a promising algorithm for other inverse heat transfer problems. Keywords Thermal contact conductance · Inverse heat transfer · Jaya algorithm

1 Introduction Generally, when two cylindrical rods are pressed against each other, a perfect contact is assumed at the interface. However, no surface is perfectly smooth, and the contact is between the peaks and valleys of the two mating surfaces of rods. The heat transfers through peaks take place due to conduction, and the valleys form air pockets offering some resistance as air acts as an insulation. This leads to temperature drop at the interface of two layers [1]. The interface conductance plays a vital role in the design of various engineering systems that are concerned with flow of heat, like valve and seal of IC engine, heat exchangers, and many other applications. The use of inverse methodology in this field is conducted to avoid the various problems faced in estimating the interface conductance using experimentation. There has been lot of work available in estimation of contact conductance by experimental approach M. Parikh (B) · H. Vaghela · S. Shah · A. K. Parwani Department of Mechanical and Aero-Space Engineering, Institute of Infrastructure Technology Research and Management, Ahmedabad, Gujarat 380026, India e-mail: [email protected] A. K. Parwani e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_27

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[2, 3]. The main limitation of experiment analysis is that it is very difficult to put probe at interface, and hence, interface conductance is estimated by extrapolation of temperature field. Inverse heat transfer (IHT) techniques are used when the unknown quantity is practically not accessible, the quantity is estimated by using temperature data through some accessible distance, and the data is converged by minimizing the least squarebased objective function. These techniques are most widely used in the estimation of boundary heat flux, heat transfer coefficient, thermo-physical properties of materials, contact conductance between two contacting surfaces, etc. [4]. The IHT techniques are classified in two categories: deterministic methods and stochastic methods. Deterministic methods use gradient of objective function for convergence while stochastic methods are search based methods which pick the best fitting solutions from randomly generated solution set. Conjugate gradient method (CGM) with an adjoin problem is the most widely used deterministic method [5]. CGM method is fast, but its main limitation is that it may converge up to local minima, and it is very sensitive to measurement of errors. Jaya is a stochastic algorithm developed by Rao [6]. It is simple in structure and does not require any other tuning parameters. The experimental solutions achieved by using Jaya algorithm proved to be superior over results obtained by using the MOGA, NPGA, GEM, TLBO, LFOPC, and RSM algorithms in terms of the results, computational effort, and function evaluations [7]. The current work includes estimation of contact conductance between two metal rods for one-dimensional transient heat conduction problem using Jaya as an inverse algorithm. Aluminum (K a = 205 W/mK) and brass (K b = 109 W/mK) are chosen as rod materials, and several cases like different population size, different profiles of contact conductance, and altered errors in temperature measurements are considered.

2 Methodology The methodology includes: (1) Obtaining the temperature field profile by solving direct problem using known value of contact conductance. (2) Formulation of inverse heat transfer problem by using Jaya algorithm to estimate the contact conductance using the temperature field obtained from direct problem.

2.1 Direct Problem Figure 1 shows computational domain for one-dimensional transient heat conduction between two contacting surface. Aluminum is used in region-1, while brass is used in region-2. The left boundary (x = 0) is subjected to transient heat flux q(t), and constant temperature is applied on right boundary (x = L 2 ). The interface is located at x = L 1 where contact conductance h(t) is present [5, 8].

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Fig. 1 Computational domain

The governing equation for region-1 are:   ∂ Tai ∂ Tai ∂ Ka = ρa C pa ∂x ∂x ∂τ

(1)

with boundary conditions: −K a Ka

∂ T1 = q(t) at x = 0; τ > 0 ∂x

  ∂ Ti = h Ti − T j at x = L 1 ; τ > 0 ∂x

(1a) (1b)

The governing equation for region 2:   ∂ Tbj ∂ Tbj ∂ Kb = ρb C pb ∂x ∂x ∂τ

(2)

With boundary conditions: −K b

  ∂ Tj = h T j − Ti at x = L 1 ; τ > 0 ∂x

(2a)

T2 = constant at x = L 2 ; τ > 0

(2b)

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Fig. 2 Validation of direct problem with ANSYS software

where For region 1 (Aluminum rod):

For region 2 (Brass rod):

Tai = Temperature of aluminum rod

Tbj = Temperature of brass rod

T1 = Temperature of aluminum rod at x = 0

T2 = Temperature of brass rod at x = L2

Ti = Temperature of aluminum rod at x = L1

T j = Temperature of brass rod at x = L1

ρa = 2710 kg/m3 , Cpa = 921.096 J/kg-K

ρb = 8587 kg/m3 , C pb = 401.93 J/kg K

K a = 205 W/mK

K b = 109 W/m

System is discretized using above-shown governing equations for individual regions with the help of finite volume method (FVM). The direct problem is solved by MATLAB 2016b environment, and it is validated using ANSYS 17.2 academic software as shown in Fig. 2.

2.2 Inverse Problem Solutions of direct problem are taken as input parameters for the inverse heat transfer methodology. Jaya algorithm which is selected as the evaluation algorithm approximate temperatures which are evaluated from direct problem for the given heat flux and constant temperature boundary condition. Evaluation was carried out considering four measurement locations (two locations on each rods). The algorithm converges by minimizing the following objective function: tn  n J (h(t)) = [Ta (t) − Te (t)]2 dt 1

1

(3)

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where n = number of measurement locations; tn = total time interval under consideration. T a (t) = Temperatures obtained from the direct problem (chosen measured temperature on rods). T e (t) = Estimated temperatures. The Jaya algorithm starts with random selection of ‘P’ number of candidate solutions (i.e., population size, p = 1, 2, …, P) with ‘n’ measurement locations (j = 1, 2, …, n). Let best candidate obtains the best value of objective function J(h(t)) (i.e., J(h(t)) best), and worst candidate obtains the worst value of objective function J(h(t)) (i.e., J(h(t)) worst) in the whole set of solutions. If hj,p,G is the value of jth variable for pth candidate during Gth iteration, then this value is modified according to following equation:   h(t)j, p,G = h(t) j, p,G + r1 j , G h(t) j,best,G − |h(t) j, p,G |   − r2 j , G h(t) j,worst,G − |h(t) j, p,G |

(4)

where h(t)j, p,G is updated value of variable h(t)j,p,G , and h(t)j,best,G and h(t)j,worst,G are best and worse solutions of jth candidate. The r 1j,G and r 2j,G are random numbers for jth variable during Gth iteration, and their range is [0, 1]. With Eq. (4), the inverse solution will approach toward best and move far from the worst solutions. At the end of current iteration, if h(t)j, p,G gives better result than the previous, it is stored and will go for the next iteration; otherwise, it is discarded, and old solution (h(t)j,p,G ) will be repeated for the next iteration. The computational algorithm of Jaya is shown in Fig. 3. The termination criteria involved in this work consists of two models. Firstly, maximum error should be less than 10–8 , or secondly, the algorithm terminates when the number of iterations satisfied. When measurement errors are present in measured data, the discrepancy principle is used for stopping criteria which is given by Ozisik and Orlande [4], J (h(t)) < Mσ 2 t f

(5)

where σ is standard deviation of measurement errors, M is number of measurement locations, and t f is final time.

3 Results Using MATLAB 2016b, experiments are carried out for 10, 30, and 50 populations. Root mean square error is calculated for each case for the possible comparison.

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 RMS =



[h a (t) − h e (t)]2 n

(6)

where ha (t) is actual contact conductance and he (t) is the estimated value of contact conductance. Figure 4a shows a sample of comparison for the estimation of step contact conductance h(t) profile with different population cases. It is found that RMS error for 30 and 50 populations is nearly similar, but the computational time has a large variation which make 30 populations size good for estimation. Figure 4b shows a sample of comparison for the estimation of step contact conductance h(t) profile with different measurement errors. It is observed that the measurement error is directly proportional to RMS error. Figure 5a, b show the results for the estimation of double triangular profile and linear profile of heat flux, respectively. Satisfactory results were obtained for these profiles also which suggest that the Jaya algorithm can estimate any heat flux profile very accurately.

Fig. 3 JAYA algorithm flowchart

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Fig. 4 Estimation of step conductance profile with a different population sizes, b different measurement errors

Fig. 5 a Estimation for double step profile, b linear profile

4 Conclusions Estimation of thermal contact conductance between two metal rods for onedimensional transient heat conduction problem using Jaya as an inverse algorithm was carried out. Aluminum and brass are chosen as rod materials. Various cases like different population size, different profiles of contact conductance, and altered errors in temperature measurements are considered. The following conclusions were obtained: 1. Jaya is accurately estimating the required values of thermal contact conductance. 2. With increase in population size, accuracy of Jaya algorithm increases. 3. With increase in error in measured temperature data, accuracy of Jaya algorithm decreases. 4. Jaya is promising algorithm to solve inverse heat transfer problems. Acknowledgements This work is supported by the grant of SERB division, Department of Science and Technology, Government of India, and authors greatly appreciate the financial contribution toward this research.

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References 1. Cengel Y (2014) Heat and mass transfer: fundamentals and applications, pp 127–158 2. Gmelin E, Asen-Palmer M, Reuther M, Villar R (1999) Thermal boundary resistance of mechanical contacts between solids at sub-ambient temperatures. J Phys D: Appl Phys 32:R19–R43 3. Berman R (1956) Some experiments on thermal contact at low temperatures. J Appl Phys 27(4) 4. Ozisik MN, Orlande HRB (2000) Inverse heat transfer: fundamentals and applications. Taylor and Francis, New York 5. Ozisik M (1993) Inverse problem of estimating interface conductance between periodically contacting surfaces. J Thermophys Heat Transfer 6. Rao Jaya RV (2016) A simple and new optimization algorithm for solving constrained and unconstrained optimization problems. Int J Ind Eng Comput 7. Rao RV (2017) Design optimization and analysis of selected thermal devices using self-adaptive Jaya algorithm. Energy Convers Manage 8. Patankar SV (2018) Numerical heat transfer and fluid flow, pp 41–75

Emission and Performance Analysis of Four-Stroke Dual-Cylinder Engine Using Waste Plastic Pyrolysis Oil as Biodiesel Milind Dalal, Romin Virani, Pulkit Choudhary, and Ajit Kumar Parwani

Abstract Continuous growth of human population and industrialization has resulted in increased energy demands. It is very much essential for a country like India, where 82% of crude petroleum is imported, to reduce dependency on imported fossil fuel. Besides this, lack of plastic waste management has resulted in a number of environmental problems. Plastic waste shares 9–12% of the total municipal solid waste (MSW) and nearly 30% of it hovers on sea’s surface. Therefore, an approach to convert fuel from waste plastic is proposed to significantly reduce landfilling of single-use plastics and meet energy requirements. The fuel, known as plastic biodiesel, was extracted from plastic waste after chemical treatment and pyrolysis process. Blends of 5–20% of biodiesel with natural diesel were prepared. These blends were tested on a four-stroke direct injection diesel engine of Mahindra Supro. The engine was run at different brake power, and performance and emission characteristics were observed. The CO2 emission was reduced to 6% as compared to diesel. To reduce NOx emission, 10–15% exhaust gas was recirculated in engine. The CO emission remained constant at all engine load throughout the experimentation. Keywords Biodiesel · Plastic pyrolysis oil · Exhaust gas recirculation (EGR)

1 Introduction The world’s energy demand is thriving. In India, 84% of oil demand depends on its imports and is the plan to be reduced to 67% by end of 2022. In order to do that, finding of new oil reserve along with drop in biofuels with conventional fuel is important. Biofuels are major renewable energy source which are produced from M. Dalal (B) · R. Virani · P. Choudhary · A. K. Parwani Department of Mechanical and Aero-Space Engineering, Institute of Infrastructure Technology Research and Management, Ahmedabad 380026, India e-mail: [email protected] A. K. Parwani e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_28

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organic matter and wastes around us. Use of biodiesel lowered carbon dioxide emission. Currently, biofuels are mostly produced from corn, soybean, sugar, vegetable oils and agriculture waste. A series of physical process and chemical treatment might be needed to convert biomass to liquid fuels for automobiles [1]. Biofuels are major renewable energy source which are produced from organic matter and wastes around us. Use of biodiesel lowered carbon dioxide emission [2]. Currently, biofuels are mostly produced from corn, soybean, sugar, vegetable oils and agriculture waste. A series of physical process and chemical treatment might be needed to convert biomass to liquid fuels for automobiles [3]. For the past 2 decades, scientific researches are being done to find the best possible biodiesel and its performance and emission characteristics are being checked on different engines [4]. Increase in the air and land pollution is another big concern. Researchers have found that second- and third-generation biodiesel decrease the CO2 emissions while increases the NOx emissions. Regarding the land pollution, increasing usage of plastic and its accumulation on landfills and ocean are the biggest environmental challenge for the world as most of the plastic degrade at significantly low pace [5–8]. Biodiesel produced from non-edible oil has similar characteristics to diesel and can easily be blended with the pure diesel [9]. At the time when biodiesel blending is mandatory in many parts of the world, plastic pyrolysis oil emerges as a potential fuel to replace diesel. In this waste plastic generated from domestic and industrial use is then converted to fuel oil known as pyrolysis oil by doing thermal pyrolysis process. It involves de-polymerization of long-chain plastic. When high temperature (>500 °C) and high pressure are applied in inert condition, long chains of hydrocarbon in plastic molecule break down into smaller molecule [8]. This thermal pyrolysis of plastics yields on average 45–50% of oil, 35–40% of gases and 10–20% of tar, depending on the type of plastic used [6]. Oil extracted by this has high-energy value than any other edible or non-edible biodiesel [10]. Other properties are also somewhat similar to that of pure diesel and hence can be blended with the conventional diesel [11]. On the other hand, this will increase the amount of NOx in the emission because of the higher oxygen content in the biodiesel. Many researchers have worked with exhaust gas recirculation (EGR) and conclude that it has potential to reduce the NOx emissions significantly. In EGR, a portion of exhaust gas is again introduced with the fresh air drawn by engine. So, there will be less oxygen present in the cylinder for combustion and thus temperature will drop decreasing the nitrogen–oxygen chain reactions [12]. There has been sufficient research done to increase the yield of plastic pyrolysis oil but very little work is done on the direct automotive use of plastic pyrolysis oil. The main objective of this study is to investigate the plastic pyrolysis oil blended fuel for its performance and emissions characteristics and compare it with that of pure diesel as well as soy-based cum waste cooking oil-based biodiesel blended fuel. For this modified dual-cylinder four-stroke direct injection production engine of Mahindra Supro (a mini pickup truck) is used. At the end, to mitigate the access NOx gases, EGR is performed for plastic pyrolysis oil blended fuel.

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2 Materials and Method Pyrolyzed waste plastic oil and combination of soybean and waste cooking oil were chosen as biodiesel. Waste plastic pyrolysis oil which is better known as plastic biodiesel is purchased from waste plastic pyrolysis plant set up by Petlad Nagarpalika, Petlad, Gujarat. The pyrolysis oil was made solely of waste plastics collected from households in Petlad taluka. Biodiesel produced from soybean and waste cooking oil which is currently available for retail use in Ahmedabad was chosen along with the plastic pyrolysis oil for this experiment. Physical and chemical properties such as kinematic viscosity, flash point, pour point and calorific value were checked and compared it with natural diesel. Table 1 shows the comparison of fuel properties for all the three fuels. The total of five different blends were prepared for the experiment which are B0 (pure diesel), B05 (95% diesel + 5% biodiesel), B10 (90% diesel + 10% biodiesel), B10 (90% diesel + 10% plastic pyrolysis oil) and B20 (80% diesel + 20% biodiesel). The most of the chemical and physical characteristics of biodiesel and plastic pyrolysis oil are similar to diesel. Therefore, they can be seen as possible replacement of conventional diesel in future. Although acid number for plastic pyrolysis oil is higher than diesel, it tends to corrode the fuel tank and other components of the engine. Moreover, sulphur content is also higher. This limits the higher percentage of blending. Figure 1 shows the different blends of biodiesel which is prepared for the experiment. Table 1 Chemical and physical properties of fuel Properties Density

(KG/m3 )

Diesel

Soy-based biodiesel

Plastic pyrolysis oil

888.1

932.5

887.5

Kinematic viscosity @40 C (cSt)

2–4.5

4.2

1.802

Flash point (°C)

>66

>120

>79

Fire point (°C)

>70

>124

>79

Water content (% V/V)

0.02

0.0325

0.05

Pour point (°C)

15

14

21

Calorific value (MJ/kg)

45

41.117

44.406

Total sulphur content (mg/kg)

50

3

161

Carbon residue (%m/m)

0.3

0.02

0.01

Ash from petroleum products (%m/m)

0.01

–

0.016

Acid number (mg KOH/g)

0.2

0.28

5.65

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Fig. 1 Sample of biodiesel and natural diesel blends

2.1 Experimental Setup The computerized diesel engine test rig was used to perform all the experiment as shown in Figs. 2 and 3. The engine used for the experiment was the actual working automobile engine built by Mahindra for their mini-truck Supro. Specifications of the engine used are shown in Table 2. Schematic of the diesel engine test rig is shown below. An electric field dynamo was used to apply load for precise control. By choosing different combinations of applied load (w) and speed (N), desired break power (BP) was achieved. Then break-specific fuel consumption and break thermal efficiency were calculated and compared with respect to the break power. This was repeated for all blends. The engine was tested with as low as 1 kW BP to the high of 8.5 kW

Fig. 2 Diesel engine testing rig (schematic)

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Fig. 3 Diesel engine testing rig

Table 2 Engine specifications

Make, model

Mahindra Supro

Type

Toubro charged DI diesel engine

Cylinder

2

Strokes

4

Displacement

909 cc

Bore

83 mm

Stoke

84 mm

Arm length (acting on the dynamo)

440 mm

brake power. All types of measurements of procedure parameters such as pressure, temperature, water flow and fuel-used were measured with well calibrated instruments and sensors and then performance results were generated for all blends. The exhaust gas quality was measured with AVL gas analyzer. At the end, the performance and exhaust gas quality of biodiesel and its blends including plastic pyrolysis oil blends were studied in comparison with pure diesel fuel. Lastly, the exhaust gas recirculation (EGR) was performed for B10 (Plastic) as higher amount of NOx in the exhaust was observed.

3 Results and Discussion 3.1 Brake Thermal Efficiency For all the blends, brake thermal efficiency increases with increase in brake power. For a particular brake power, higher the efficiency, lower fuel will be used to generate the same power. Here B0 outstands all the blends in terms of brake thermal efficiency.

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BRAKE THARMAL EFFICIENCY (%BTEFF)

B0

B05

B20

B10(PLASTIC)

B10

50.00 40.00 30.00 20.00 10.00 0.00 0

2

4

6

8

10

BRAKE POWER (KW)

Fig. 4 Brake power versus brake thermal efficiency

The highest was observed at 8.5 kW brake power (the highest load in the experiment). The maximum brake thermal efficiency for diesel (B0) at high load was 42.80%. The brake thermal efficiency for other blends was observed to be less than that of pure diesel because of the reduction in calorific value of blended fuels. The reduction in brake thermal efficiency for B05, B10, B10 (plastic) at high load was around 45%, while B20 fuel is found to have more brake thermal efficiency than other blends. The reduction for B20 was only 17% at high load. Though, the calorific value of plastic pyrolysis oil is similar to the diesel but just 10% blended fuel of it struggles to keep up with diesel when it comes to brake thermal efficiency. Though soya-based biodiesel has less calorific value but from Fig. 4 it can be noticed that B20 shows better performance than any other blends.

3.2 Brake-Specific Fuel Consumption Figure 5 compares the change in brake-specific fuel consumption with change in brake power between all blends. Brake-specific fuel consumption is the rate of fuel consumption to generate 1 kW of power. This is the measure of fuel efficiency. The brake-specific fuel consumption decreased with increase in power. It was found that for diesel, BSFC is the lowest at all brake powers, while for B05 and B10 it was highest. The brake-specific fuel consumption for diesel at maximum load was noted 0.0515 gm/kW s. The increase in BSFC for other diesel blends was found to be 23.1% for B20 and around 80% for all other blends.

3.3 Carbon Dioxide (CO2 ) Emissions Figure 6 compares the variation of percentage of carbon dioxide emission for all fuel

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Brake specific fuel consumpon (gm/KW-s)

B0 0.3000 0.2500 0.2000 0.1500 0.1000 0.0500 0.0000

B05

0

1

B10

2

3

327

B10 (PLASTIC)

4 5 6 Brake power (KW)

B20

7

8

9

Fig. 5 Brake power versus brake-specific fuel consumption

B0

B10

B05

B20

B10 (plasc)

7 % Volume

6 5 4 3

0

1

2

3

4 5 6 Brake Power (KW)

7

8

9

Fig. 6 Brake power versus CO2

samples, when operated at different brake powers. The CO2 emissions were found to be increasing with increase in brake power. Soy bean-based biodiesel blended fuel tends to emit less CO2 , and for B05 it was 3.5% less than that of pure diesel. However, fuel with 10% of plastic pyrolysis oil showed higher CO2 emission at higher load and speed. It was 4.68% higher at maximum break power.

3.4 Oxides of Nitrogen (NOx ) Emission For all the blends, NOx emission increased with increase in brake power as shown in Fig. 7. It is noted that, at high load, diesel has the least NOx emission and B10 (Plastic) has the highest. At high load, higher NOx emission in biodiesel blends was noted due to the presence of extra oxygen as biodiesels are oxygen-rich fuel, which led to complete combustion of biodiesel better than diesel. This leads to more adiabatic flame temperature for fraction of second inside the cylinder. This encourages the reaction between oxygen and nitrogen and hence more nitrogen oxides are formed.

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B05

B10 (plasc)

B20

B10

NOx (ppm)

2000 1500 1000 500 0 0

1

2

3

4

5

6

7

8

9

Brake power (KW)

Fig. 7 Brake power versus NOx

For medium and high load, B10 (plastic) had higher NOx emissions than any other blend. At maximum break power, B0 and B05 had NOx emission of 1591 ppm, while B10, B20 and B20 (plastic) have 5.09%, 3.16% and 18.76% increase in NOx emission, respectively.

3.5 Exhaust Gas Recirculation (EGR) As resulted, plastic pyrolysis oil blended fuel has almost 20% more NOx emission at high loading conditions. To reduce NOx , 10% and 15% exhaust gas was recirculated into the manifold for higher loads. Tables 3 and 4 depict the emission results of EGR done for B10 (plastic) fuel at 6.8 kW and 8.6 kW brake powers. At brake power 8.6 kW when 10% and 15% of exhaust gas was recirculated, there was 16.89% and 43.11% deduction in NOx emission, respectively. Carbon monoxide (CO) emission, however, increased to 0.02 when 15% of exhaust gas was recirculated. CO2 emission was also increased by Table 3 Exhaust gas recirculation (EGR) for brake power 6.8 kW Fuel

B0 diesel

B10 (plastic pyrolysis oil)

EGR

–

0%

10%

15%

BTeff (%)

40.05

23.1

22

22.4

HC (ppm)

5

5

5

5

CO (vol%)

0

0

0.01

0.02

CO2 (vol%)

5.9

6.05

6.09

7.17

O2 (vol%)

12.2

11.9

12.1

10.59

NOx (ppm)

1400

1590

1400

935

0

11.949

41.194

% decrease in NOx

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Table 4 Exhaust gas recirculation (EGR) for brake power 8.6 kW Fuel

B0 diesel

B10 (plastic pyrolysis oil)

EGR

–

0%

10%

15%

BTeff (%)

42.5

23.55

23.64

24

HC (ppm)

5

5

4

5

CO (vol%)

0

0

0.01

0.02

CO2 (vol%)

6.4

6.74

6.88

7.46

O2 (vol%)

12

11.04

11.26

10.4

NOx (ppm)

1540

1865

1550

1061

0

16.89

43.11

% decrease in NOx

10.68% which limits the further increase in percentage of EGR. Conversely, no increase in unburnt hydrocarbon was noted.

4 Conclusion Following are the conclusions drawn after performing the experiment: 1. At higher brake power, soy-based biodiesel blended fuel has similar emission characteristics as diesel, whereas B10 (plastic) has more CO2 and NOx emissions. 2. Exhaust gas recirculation showed significant drop in NOx emissions but at the same time increased CO2 emissions. 10% EGR is found suitable to bring NOx emission similar to diesel. Further increase in EGR would result in increase in CO2 and CO emissions as well as degrade performance. 3. There was no evidence of increment in CO emissions at higher load except for B10 (plastic) with 15% EGR. Also, that increase is negligible as compared to the idling condition of engine. 4. From economic point of view, plastic pyrolysis oil blended fuel still can be used with diesel for heavy-duty vehicles and earth movers as it is available in abundance, requires minimal effort to produce, and it solves energy and environmental problem at the same time provided it is used with real-time tuning of EGR.

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References 1. The Economic Times Web page, https://economictimes.indiatimes.com/industry/energy/oilgas/indias-oil-import-dependence-jumps-to-84-pc/articleshow, Last accessed 2020/08/08 2. Nair JN, Deepthi J, Kalyani KS (2013) Study of biodiesel blends and emission characteristics of biodiesel. Int J Innov Res Sci Eng Technol 3297 3. Mickevicius T, Slavinskas S, Wierzbicki S, Duda K (2014) The effect of diesel-biodiesel blends on the performance and exhaust emissions of a direct injection off-road diesel engine. Transport 29 4. Xue J, Grift TE, Hansen AC (2011) Effect of biodiesel on engine performances and emissions. Renew Sustain Energy Rev 15(2):1098–1116 5. Ramesha DK, Kumara GP, Lalsaheb, Mohammed AV, Mohammad HA, Kasma MA (2016) An experimental study on usage of plastic oil and B20 algae biodiesel blend as substitute fuel to diesel engine. Environ Sci Pollut Res 23 6. Bezergianni S, Dimitriadis A, Faussone GC, Karonis D (2017) Alternative diesel from waste plastics. Energies10 7. Güngör C, Serin H, Ozcanli M, Serin S, Aydin K (2015) Engine performance and emission characteristics of plastic oil produced from waste polyethylene and its blends with diesel fuel. Int J Green Energy 12(1):98–105 8. Ruban M, Ramasubramanian S, Pugazhenthi R, Sivaganesan (2017) Investigation of performance analysis and emission characteristics of waste plastic fuel. IOP Conf Ser: Mater Sci Eng 183 9. Murthy PVK (2013) Maddali: performance evaluation of a diesel engine fuelled with cotton seed oil in crude form and biodiesel form. J Int Acad Res Multidiscip 1(9):329–349 10. Mohammadi P, Nikbakht AM, Tabatabaei M, Farhadi K, Khatamifar, Mansourpanah Y, Ghorbani H, Hosseini M (2012) Waste plastic-WVO biodiesel as an additive to boost diesel fuel properties 11. Khan ZH, Sultana M, Mamun R, Hasan R (2016) Pyrolytic waste plastic oil and its diesel blend: fuel characterization. J Environ Public Health 12. Sakhare NM, Shelke PS, Lahane S (2016) Experimental investigation of effect of exhaust gas recirculation and cottonseed B20 biodiesel fuel on diesel engine. Procedia Technol 25:869–876

Estimation of Transient Boundary Heat Flux Using Modified JAYA Algorithm in Laminar Duct Flow Ravi Prajapati, Viral Thakkar, Sanil Shah, and Ajit Kumar Parwani

Abstract The major focus of paper is estimation of heat flux varying with time for two-dimensional forced convective laminar duct flow by using inverse heat transfer technique. Simple JAYA and modified JAYA algorithms are used for solving the inverse problem. JAYA is a newly developed algorithm with simple structure and does not require any tuning parameters. Modified JAYA algorithm is a combination of two algorithms where JAYA algorithm is coupled with multi-population JAYA algorithm. In multi-population JAYA algorithm, total population is divided into groups. These groups are used to estimate the required quantity. Solution of simple JAYA algorithm will be the input parameters for multi-population JAYA algorithm. Different types of heat flux profiles like step profile, smooth profile, triangular profile and linearly increasing profile are considered and performance of JAYA and modified JAYA considered. Results show that modified JAYA algorithm is found to be more accurate than JAYA. Keywords Boundary heat flux · Laminar duct flow · Inverse problem · Modified JAYA algorithm

1 Introduction Designing of thermal systems require sound knowledge of boundary conditions like boundary heat flux, heat transfer coefficient, etc., but sometimes, direct measurement of boundary possible is not possible and hence inverse methods are used for this. The objective of the inverse heat transfer problem (IHTP) is to predict one or more unknown characteristics from the knowledge of the temperatures that are measured at some distance from boundary. Inverse methods are used to determine boundary R. Prajapati · V. Thakkar (B) · S. Shah · A. K. Parwani Department of Mechanical and Aero-Space Engineering, Institute of Infrastructure Technology Research and Management, Ahmedabad 380026, India e-mail: [email protected] A. K. Parwani e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_29

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heat flux, convection coefficient, thermo-physical properties, initial condition and intensity of source term [1]. IHTP uses least square-based objective function for minimization, and hence, they are ill posed problems. There are two type of approaches used for IHTP: gradient-based approach and stochastic (population-based) approach. Gradientbased approach uses gradient of an objective function for solution. Among all gradient-based method, conjugated gradient method (CGM) with an adjoint problem is the most popular gradient-based approach. Liu and Ozisik [2] estimated the transient wall heat flux for hydrodynamically developed and thermally developing turbulent forced convection flow in a parallel plate channel and concluded that the accuracy of CGM deteriorates with measurement error and step heat flux profile is difficult to estimate than triangular heat flux profile. Huang and Chen [3] estimated transient boundary heat flux for three-dimensional forced convection flow by using CGM. They used commercial software CFX4.2 for the CGM algorithm and considered the effect of duct height, inlet velocity and measurement errors on flux estimation. The main limitation of CGM is that it is very sensitive to measurement error and sometimes it converges up to local minima. The stochastic methods are more accurate than deterministic methods, and they obtain global solution. Cuckoo search, genetic algorithm (GA), differential evolution (DE) and JAYA algorithm are some examples of stochastic methods. Parwani et al. [4] used the DE approach for estimation of the position and strength of time-varying source in participating medium in a two-dimensional enclosure. They considered conduction and radiation boundary conditions and found that DE is quite reasonable for estimation. Li and Yang [5] used GA for estimation of radiation parameters of the gray participating medium. Above researchers used different stochastic (population-based) approach to estimate the required properties and found that these approaches are quite reasonable for the estimation. For current case, a new stochastic algorithm—JAYA is used for IHTP. JAYA is developed by Rao [6] and successfully implemented for solving benchmark problems. It has simple structure and does not require any tuning parameters. Rao et al. [7] used a multi-objective JAYA algorithm (MO-JAYA) for optimization of modern machining process which includes plasma arc machining (PAM), electro-discharge machining (EDM) and micro electro-discharge machining (μEDM) process. Rao and Saroj [8] used the elitist-JAYA algorithm for constrained economic optimization of shell and tube heat exchanger at different combinations of populations, iterations and elite size. They found that the elitist-JAYA algorithm is better than other optimization methods used for the same problems. As per authors’ knowledge, JAYA never used for IHTP. and due to its simple structure and versatility, it is used for solving IHTP of estimating transient boundary heat flux for the laminar flow through 2D duct. The flow is considered as thermally developing and hydrodynamically developed. After JAYA, modified JAYA algorithm is used to estimate the heat flux where JAYA algorithm is coupled with multi-population JAYA algorithm. In multi-population JAYA algorithm, total population is divided into groups. These groups are used to estimate the required quantity. Solution of simple JAYA algorithm will be the input parameters for multi-population JAYA algorithm. Different types of heat flux profiles like step heat flux profile, smooth heat flux profile,

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triangular heat flux profile and linearly increasing heat flux profile are considered and performance of JAYA and modified JAYA considered. Results show that modified JAYA algorithm is found to be more accurate than JAYA.

2 Methodology The methodology includes: (1) Find the temperature field profile in duct using known value of heat flux by solving direct problem. (2) Estimate the boundary heat flux by JAYA algorithm.

2.1 Direct Problem Hydrodynamically and thermally fully developed transient laminar flow is considered in 2D duct as shown in Fig. 1. Heat flux is applied on the upper surface of duct. Heat flux is varying with respect to time. Length of duct is 1 m. Height of duct is 0.1 m. Air flowing inside duct has mean velocity um = 0.033 m/s. Corresponding Reynolds number Re = 429 (Fig. 2). Parabolic velocity profile has been assumed and is as below: u(y) = 6u m

 y  y 1− H H

(2.1)

The governing equations for energy for the present case with boundary conditions are given by   ∂T ∂ ∂T ∂T + ρC p = k ρC pu ∂x ∂t ∂y ∂y

Fig. 1 2D duct

(2.2)

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Fig. 2 Mesh of geometry

at, y = H,

∂T = q(t) ∂y

y = 0, −k

∂T =0 ∂y

where C p = specific heat of considered fluid (J/kg). ρ = density of considered fluid (kg/m3 ). k = thermal conductivity of fluid (W/mK). In this paper, air is taken as working fluid with ρ = 1.2 kg/m3 , C p = 1005 J/kg K and k = 0.026 W/mK. q(t) is the flux applied. Solution of governing Eq. 2.2 is as below:     n w w n  w n ∂T ∂T ∂T ∂ ρC pu ρC p dxdy + dydx = k dxdy (2.3) ∂x ∂t ∂y ∂y s

e

e

s

e

s

b Here, x = (M−1) and y = (N h−1) where the duct is discretized in M different nodes in x-direction and N different nodes in y-direction. Further solution of Eq. 2.3 is as below. For top surface where flux is applied,

A P ∗ TP = A W ∗ TW + A S ∗ TS + B

(2.4)

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where AW = ρ ∗C p∗ velocity * dy A S = (k ∗ dx)/dy B = q(t) ∗ dx A P = AW + A S For other points, A P ∗ TP = A W ∗ TW + A S ∗ TS + A p0 ∗ T p0

(2.5)

where AW = ρ ∗C p∗ velocity * dy A S = A N = (k ∗ dx)/dy A P0 = (ρ ∗ dx ∗ dy)/dt A P = A W + A S + A P0 To solve the convection term in governing equation, implicit upwind scheme is used.

2.2 Inverse Problem Inverse problem is used to determine heat flux q(t) at boundary of duct. These algorithms estimate the heat flux q(t) by minimizing the least square-based objective function containing measured temperatures and calculated temperatures given by

J (q(t)) =

t=t f  m=M 

[Y (X m , Ym ; q(t)) − T m(X m , Ym )]2 dt

(2.6)

t=0 m=1

Here M are number of sensors used in study region, final time is t f , and estimated heat flux is q(t). Y (X m , Y m ; q(t)) is the temperature calculated from the equations of direct problem (Eq. 2.2) using q(t) as boundary heat flux, while Tm(X m , Y m ) is the temperature by sensors, and (X m , Ym ) shows location in study region. For the whole study, the measured temperatures are also calculated from the equations of direct problem (Eq. 2.2), which leads the study to numerical experiment rather than actual one.

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Simple JAYA Algorithm

The JAYA algorithm starts with random ‘P’ number of solutions (population size, p = 1, 2, …, P), which shows the boundary heat flux q(t), with ‘t n ’ number of design variables (j = 1, 2, …, t n ). Minimum value of objective function J(q(t)) (i.e., J(q(t))best ) shows the best solution and worst solution is the maximum value of objective function J(q(t)) (i.e., J(q(t))worst ) in the whole set of solutions. If qj,p,G is the value of jth variable for pth candidate during Gth iteration, then this value is modified according to following equation:  q(t)j, p,G = q(t) j, p,G + r1 j,G q(t) j,best,G − |q(t) j, p,G |  − r2 j,G q(t) j,worst,G − |q(t) j, p,G |

(2.7)

where q(t)j, p,G is updated value of variable q(t)j,p,G , and q(t)j,best,G and q(t)j,worst,G are best and worst solutions of jth candidate. The r 1j,G and r 2j,G are random numbers for jth variable during Gth iteration with range of [0, 1]. At the end of current iteration, if q(t)j, p,G gives lesser values of objective function than the previous one, it is stored and will be used for the next iteration. Otherwise, it is discarded and old solution (q(t)j,p,G ) will be repeated for the next iteration. The computational algorithm of JAYA is shown in Fig. 3.

2.2.2

Modified JAYA Algorithm

Simple JAYA algorithm is coupled with multi-population-based JAYA algorithm to develop modified JAYA algorithm, where simple JAYA algorithm provides the initial guess solution to multi-population-based JAYA algorithm. The computational algorithm of modified JAYA algorithm is shown in Fig. 5. In order to achieve more accurate results, the objective function for multi-population-based JAYA algorithm is also modified as follows: J (q(t)) =

t=t  j+1m=M  t=t j

[Y (X m , Ym ; q(t)) − T m(X m , Ym )]2 dt

(2.8)

m=1

This implies that now multi-population-based JAYA algorithm minimizes the objective function, which is calculated over each t j th (i.e., j = 1, 2, 3, …, n) design variable. This also leads to update the population ‘P’ by its term by term design variable instead of updating all at once. Figure 4 shows the multi-population-based JAYA algorithm, while Fig. 5 shows the modified JAYA algorithm. Stopping criteria for JAYA and multi-population-based JAYA algorithm are as follows: J (q(x)) < ε

(2.9)

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Fig. 3 Simple JAYA algorithm

where ε is small number. For this work, ε is taken as 10–6 . If Eq. 2.9 is satisfied, then the code moves further in the algorithm. Number of iterations is another criterion for the JAYA and multi-population-based JAYA algorithm. If Eq. 2.9 does not satisfy and the code exceeds 100 iterations, then algorithm moves to further steps.

3 Results and Discussion For numerical analysis, the grid size of 51 elements in x-direction and 101 elements in y-direction and temporal grid size of 20 elements are used. Four different heat flux profiles are selected to verify whether the algorithm is universal for considered problem or not. For study, population size of 20 (i.e., P = 20) with 20 time steps (i.e., n = 20) are considered, where only one sensor is used at the position X m = 0.5 m and Y m = 0.005 m. The range of heat flux is considered as 0 W/m2 to 10,000 W/m2 . To check the accuracy of the estimated values of heat flux, RMS error is calculated by following formula:

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Fig. 4 Multi-population JAYA algorithm

  n 1  2 RMS = [qa (t) − qe (t)] n i=1

(3.1)

From Eq. 3.1, it is clear that the lower values of RMS error imply the higher accuracy. Here, qa (t) shows actual boundary heat flux, while qe (t) shows estimated boundary heat flux. Figure 6 shows the comparison of boundary heat flux qe (t) estimated by simple JAYA, multi-population-based JAYA and modified JAYA algorithm

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Fig. 5 Modified JAYA algorithm

Fig. 6 Comparison for step profile

for step profile of heat flux. The results clearly indicate that for step heat flux profile, RMS error for simple JAYA, multi-population-based JAYA and modified JAYA algorithm is 149.75, 244.0194 and 8.821 × 10–5 , respectively, which means that modified JAYA algorithm has the highest accuracy compared to others. Figures 7, 8 and 9 are similar results derived for smooth, linear and triangular profiles, respectively. For every considered profile, modified JAYA algorithm is proved with more accurate results. Computational time of modified JAYA algorithm is higher compared to other two algorithms.

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Fig. 7 Comparison for smooth profile

Fig. 8 Comparison for linear profile

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Fig. 9 Comparison for triangular profile

4 Conclusion The simple JAYA and multi-population-based JAYA algorithm are new and recently developed algorithm for optimization. The major study of this paper is concentrated on the modified JAYA algorithm which is coupling of the simple JAYA and multi-population-based JAYA algorithm. Such newly developed algorithm is used to estimate the boundary heat flux of two-dimensional convection diffusion inside the square duct with hydrodynamically and thermally fully developed flow. The study vigorously compares estimated values of the boundary heat flux by modified JAYA algorithm with the other two algorithms. Following conclusions are derived from results: • Modified JAYA algorithm is more accurate than simple JAYA and multipopulation-based JAYA algorithm for all cases. • The computational time required for modified JAYA algorithm is more than simple JAYA and multi-population-based JAYA algorithm. Acknowledgements Work of this paper is supported by the grant of SERB division, Department of Science and Technology, Government of India, and authors greatly appreciate the financial contribution toward this research.

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References 1. Ozisik MN, Orland HRB (2000) Inverse heat transfer: fundamentals and applications. Taylor and Francis 2. Liu FB, Ozisik MN (1996) Inverse analysis of transient turbulent forced convection inside parallel ducts. Int Gen Heat Transfer 3. Huang CH, Chen WC (1996) A three-dimensional inverse forced convection problem in estimating surface heat flux by conjugate gradient method. Int Gen Heat Transfer 4. Parwani AK, Talukdar P, Subbarao PMV (2013) Simultaneous estimation of strength and position of heat source in participating medium using DE algorithm. J Quant Spectrosc Radiat Heat Transfer 5. Li HY, Yang CY (1997) A genetic algorithm for inverse radiation problem. Int Gen Heat Mass Transfer 6. Rao R (2016) Jaya: a simple and new optimization algorithm for solving constrained and unconstrained optimization problem. Int J Ind Eng Comput 7. Rao RV, Rai DP, Ramkumar J, Balic J (2016) A new multi objective Jaya algorithm for optimization of modern machining process. Adv Prod Eng Manag 8. Rao RV, Saroj A (2017) Constrained economic optimization of shell-and-tube heat exchanger using elitist-Jaya algorithm. Energy

Estimation of Boundary Heat Flux with Conjugate Gradient Method by Experimental Transient Temperature Data Parth Sathavara, Ajit Kumar Parwani, Maulik Panchal, and Paritosh Chaudhuri

Abstract In this work, the estimation of heat flux for one-dimensional transient heat conduction problem has been done with the help of the search-based conjugate gradient method with an adjoint problem. The finite volume approach is applied to discretize the differential equations which are solved by using developed in-house MATLAB code. The novelty of this paper is justified as the required temperature data to solve the CGM algorithm are obtained by using real-time experimentation instead of performing the numerical simulation. The RMS error of the estimation of heat flow is obtained from that we can conclude that the accuracy is increased by using multiple sensors. The value of estimated heat flux is affected by the measurement errors which is inherently present in the measurement data. Keywords One-dimensional transient heat conduction · Finite volume method · Conjugate gradient method (CGM)

1 Introduction The conventional heat conduction problem generally deals with obtaining the temperature distribution within a heated body when heat flow, the initial and boundary conditions, thermal and physical properties, and geometric specifications are known. However, in some heat transfer situations, few parameters are not available where the inverse method is useful to determine these unknowns. In literature, various works are done in inverse heat transfer areas like the measurement of heat flux [1] during

P. Sathavara (B) · A. K. Parwani Institute of Infrastructure Technology Research and Management, Ahmedabad 380026, India e-mail: [email protected] M. Panchal · P. Chaudhuri Institute for Plasma Research Bhat, Gandhinagar 382008, India P. Chaudhuri Homi Bhabha National Institute (HBNI), Anushaktinagar, Mumbai 400094, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_30

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the heating process and the estimation of heat flux using an inverse technique for slab surface [2]. Different discretization methods [3–6] are available in the literature for solving the direct problems. On the other hand, handling of inverse problems is very strenuous, because these are ill-conditioned from mathematical point of view. Ill-conditioned means small deviation of input data can cause large deviation on output value. Generally, two categories of methods are available in literature one deterministic and other stochastic for the solution of inverse problems [7]. Deterministic methods are gradient-based methods, which are efficient and accurate. A stochastic method is generally used for finding global solution, which usually consumes a large iteration time. Least-squares method [8], genetic algorithm [9], Tikhonov regularization technique [10], particle swarm optimization method [11], Levenberg–Marquardt method [12], and Kalman filter method [13] have been used in literature. In this work, the MATLAB R2018a code has been developed based on the CGM algorithm for inverse problems. The objective of the work is to show that the algorithm is robust, efficient, and accurate, which is justified by comparing it with the actual experiment. The sections of this article are arranged as follows. The one-dimensional transient heat conduction problem is outlined in Sect. 2. The inverse problem is outlined in Sect. 3. The conjugate gradient method (CGM) for optimization is outlined in Sect. 4. The computation procedure for CGM is outlined in Sect. 5. The experiment setup and results are outlined in Sect. 6. Finally, the conclusive remarks are given.

2 One-Dimensional Transient Heat Conduction Problem The governing equations for one-dimensional transient heat conduction (direct) problem are given as ρc

  ∂ ∂ T (x, t) ∂ T (x, t) = k in the domain 0 < x < l, for t > 0 ∂t ∂x ∂x

(1a)

T (x, 0) = T (x) in the domain 0 < x < l, at t = 0

(1b)

k

∂ T (0, t) = q(t) for t > 0, at x = 0 ∂x

(1c)

T (l, t) = T (t) for t > 0, at x = l

(1d)

Here, k is the thermal property of the heated body; ρ is the density; l is the length of the heated body; c is the mass-specific; x is the coordinate along the x-axis; T is the temperature; t is the time; q is the heat flow. It can be shown that thermal properties are not temperature-dependent. The solution of this problem is done using the finite volume approach programmed in MATLAB. FVM is considered as an accurate and

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efficient method than other methods for the inverse problems [14]. After knowing the all limiting conditions, the problem mention in the above Eq. (1a) is solved for obtaining the temperature distribution.

3 The Inverse Problem The heat flux value q(t) on one side of the steel rod (x = 0) is considered as being unknown while considering the inverse heat transfer problem, but all other parameters and the temperature values from the experiment at some particular locations and time are regarded as available. Let the Y (x, t) ≡ Y m (t) represents temperature reading taken from the experiment, where M is the number of locations where temperatures are measured. We know that the measured value of temperature Y m (t) contains errors of measurement. The inverse problem has to be solved by considering the following minimization function:

S[t] =

t f  M

[Ym (t) − Tm (t)]2 dt

(2)

t=0 m=1

Here, Tm (t) is the obtained from the solution of Eq. (1a) with the help of calculated or estimated heat flux q (t). The symbol ‘ ’ represents estimated quantity while t f stands for the final time. 



4 Conjugate Gradient Method (CGM) The calculation of heat flux q(t) is done using the CGM [15] considering minimization of Eq. (2) qˆ i+1 (t) = qˆ i (t) − β i d i (t)

(3a)

Here, β i represents the search step size in the direction of moving from the current position to the next position, d i (t) represents the direction of descent, and the superscript i represents iteration (i = 0, 1, 2…). The direction of descent is given as 

di (t) = S i (t) + ϒ i di−1 (t) 

(3b)

Here, S i (t) is the gradient of S(t) at iteration i and d i−1 (t) is the direction of decent at previous iteration I − 1. Different expressions are available for conjugation coefficient ϒ i in literature [16]

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while in this work Fletcher-Reeves expression is used  tf



[S i (t)]2 dt ϒ =  t t=0 with ϒ 0 = 0 for i = 0  i−1 f 2 dt [S (t)] t=0 i

(3c)

From Eq. (3b), when ϒ i = 0 for any i, the direction of descent d i (t) will be the same as the directioof gradient, i.e., the ‘steepest descent’ method is achieved. We can assure from the expression (3c) that the angle between negative gradient direction and the direction of descent is less than 90°, so that the quantity S(t) is minimized [16] which shows the convergence is guaranteed. To carry out the iteration according to Eq. (3a), we need to calculate β i and the  gradient of the quantity S(t). A sensitivity problem is solved to obtain β i and S i (t).  i An adjoint problem is solved to obtain S (t). These two problems are derived in the next sub-sections.

4.1 Sensitivity Problem and Search Step Size For finding β i and gradient, sensitivity problem needs to be solved. The solution can be done by considering that the temperature T (x, t) is deviated by an amount T (x, t), when the estimated quantity q(x, t) is deviated by q(x, t). Then, substituting T (x, t) by [T (x, t) + T (x, t)] and q(x, t) by [q(x, t) + q(x, t)] in the Eq. (1a), and then subtracting Eq. (1a) from the resulting equations, we obtained the sensitivity problem which is given below:   ∂ ∂T (x, t) ∂T (x, t) = k in the domain in 0 < x < l, for t > 0 ρc ∂t ∂x ∂x (4a) T (x, 0) = 0 in the domain 0 < x < l, for t = 0 k

∂T (0, t) = q(t) at x = 0, for t > 0 ∂x T (l, t) = 0 at x = l, for t > 0

(4b) (4c) (4d)

 The quantity S qˆ i+1 (t) from Eq. (2) is given as  S qˆ i+1 (t) =

t f  M

t=0 m=1

 2 Ym (t) − Tm xmeas , t; qˆ i (t) − β i d i (t) dt

(5a)

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The β i is calculated by minimizing the Eq. (5a) with respect to β i , that is, min  i+1 min S qˆ (t) = i βi β

t f  M

 2 Ym (t) − Tm xmeas , t; qˆ i (t) − β i d i (t) dt

(5b)

t=0 m=1

 The term Tm xmeas , t; qˆ i (t) − β i di (t) is evaluated by a Taylor expansion, Eq. (5b) results in the linearized form min  i+1 min S qˆ (t) = i βi β

t f  M

 Ym (t) − Tm xmeas , t; qˆ i (t)

t=0 m=1

 2 +β i T xmeas , t; d i (t) dt

(5c)

 where T xmeas , t; d i (t) is obtain by solving the sensitivity problem given by Eq. (4a), which is calculated by putting qi (t) = d i (t). Differentiate the Eq. (5c) with respect to β i and compare it with zero for minimization. Finally, we get the following equation for β i after doing some manipulation.  tf βi =

t=0

   Tm xmeas , t; qˆ i (t) − Ym (t) T xmeas , t; d i (t) dt  tf

 2 i dt t=0 T x meas , t; d (t)

(6)

4.2 Adjoint Problem and Gradient Equation The formulation of the adjoint problem is done by multiplication of Lagrange multiplier λ(x, t) with Eq. (1a) and the obtained equation is integrated over the spatial span from x = 0 to x = l, and then over time span from t = 0 to t = t f . After that the obtained equation is summed up with the quantity S[q(t)] given by Eq. (2) to obtain the following new equation.

S[q(t)] =

t f  M

{Y (x, t) − T [xmeas , t; q(t)]}2 dt

t=0 m=1 t f  l

+ t=0 x=0

λ(x, t)

 

∂ ∂ T (x, t) ∂ T (x, t) k − ρc dxdt ∂x ∂x ∂t

(7)

By doing the same procedure as we have done in sensitivity problem, the following new equation is obtained for S[q(t)].

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t f  l 2{T [xmeas , t; q(t)] − Y (x, t)}T (x, t)δ(x − xmeas )dxdt

S[q(t)] =

t=0 x=0 t f  l

+ t=0 x=0



 

∂ ∂T (x, t) ∂T (x, t) λ(x, t) k − ρc dxdt ∂x ∂x ∂t

(8)

Here, δ(.) represents the Dirac delta function. After some mathematical manipulation of Eq. (8) and applying limiting conditions of a sensitivity problem, then in resulting equations vanishing the T (x, t) terms, the expression of the adjoint problem obtained: k

∂λ(x, t) ∂ 2 λ(x, t) = ρc 2 ∂x ∂t + 2{T [xmeas , t; q(t)] − Y (x, t)}δ(x − xmeas ) = 0 for 0 < t < t f , in 0 < x < 1 ∂λ(0, t) = 0 at x = 0, for 0 < t < t f ∂x   λ x, t f = 0 for final time t = t f , in 0 < x < 1

(9a) (9b) (9c)

The condition (9c) demonstrated above is the value of λ(x, t) at time t f (final time). Finally, we get the following integral term: t f S[q(t)] =

λ(0, t)q(t)dt

(10a)

t=0

By considering the hypothesis, the unknown quantity q(t) belongs to space integral quantities in the span 0 < t < t f , we can write[16]: t f S[q(t)] =

S  [q(t)]q(t)dt

(10b)

t=0

From comparing the above Eqs. (10a) and (10b), we obtained the following equation, which is the gradient equation of S[q(t)]. S  [q(t)] = λ(0, t)

(11)

We observed that from Eq. (9c), the gradient S  [q(t)] at final time (t f ) is always leads to zero, so that the accuracy of this method will decrease at the neighborhood

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of final time. This visible pitfall of the method can be easily removed by using a final time considered as large compared to interested time due to this the deviation is not present in output at final time for particular initial value.

4.3 Stopping Criteria  The algorithm will terminate when value of an objective function S qˆ i+1 (t) will be less than ε. Thus, the stopping criterion for current case is [16]:  S qˆ i+1 (t) < ε

(12)

where ε is a small number, and for current case, its value (ε) is taken as 10-9 .

5 Computational Procedure for CGM The step by step procedure for CGM with the adjoint problem is outlined as given below. Suppose we initiate iteration with guess q0 (t). For i = 0 and after that: Step 1. From qi (t), solve the Eq. (1a) for obtaining temperature distribution. Step 2. From Y (t) and T (x meas , t), check the stopping criterion from the Eq. (12). Continue the next iteration if stopping criterion is not satisfied Step 3. After getting Y (t) and T (x meas , t), calculate the adjoint problem from the Eq. (9) and calculate λ(0, t). Step 4. After getting λ(0, t), calculate the S  [q(t)] from the Eq. (11). Step 5. After getting the gradient S  [q(t)], calculate the ϒ i from the Eq. (3c) and the d i (t) from the Eq. (3b). Step 6. Put q = d i (t) in sensitivity problem and calculate the sensitivity problem from Eq. (4) to get T [x meas , t;d i (t)]. Step 7. After getting T [x meas , t;d i (t)], calculate the β i from the Eq. (6). Step 8. After getting β i and the d i (t), calculate the next estimate qi+1 (t) from the Eq. (3a), and again start with first step.

6 Experimental Setup Description and Results The experimental setup is shown in Fig. 1 by schematic diagram. The experiment was performed at the Institute for Plasma Research (IPR) Bhat, Gandhinagar. The test facility was originally developed at IPR to measure the effective thermal conductivity of lithium metatitanate pebble beds [17]. The SS rod of length 40 mm and diameter 45 mm is used in this experiment. For maintaining the one-dimensional heat conduction, the SS rod is insulated by the

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Fig. 1 Schematic diagram of an experimental setup

thermal insulating material made of fused silica. A heater is equipped for heating the rod which is located at the top side of the rod. A heat flux sensor mounted in a disk is used for measuring the heat flux which is installed at the bottom side. The three K-type thermocouples of 1 mm sheath diameter are inserted through the hole up to the center of the rod. The temperature of the rod is measured in a vertical direction (10 mm apart) at three points in the rod as shown in Fig. 2. The inverse code is developed in MATLAB for this one-dimensional heat conduction in the SS rod. In mathematical formulation, only 30 mm length of SS rod is considered because the transient temperature value at location x = 30 mm is considered as the boundary. The iteration starts with an initial guess q0 (t) = 0. The estimation of q(t) present at x = 0 mm is carried out using the measured transient temperature value (Y m (t)) at x = 10 mm and x = 20 mm. However, the measured temperatures have measurement uncertainty associated with the accuracy of the thermocouple that will affect the output value of q(t). The results of estimated heat flux appear in Fig. 3. The RMS error is defined here as   p 1  2   (13) q (ti ) − q(ti ) eRMS = p i=1 

Fig. 2 Dimensions of SS rod and location of thermocouples

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Fig. 3 Estimated heat flux q(t) using CGM with M number of sensors

Here, p is the number of measurements. The RMS errors for the two cases are also shown in Fig. 3. Here, the exact q(t) is considered as constant with the time, but the measured temperature is varying with the time, and hence, the obtained estimated value of heat flux by CGM also varies with the time. Here, only 30 s of time span is considered out of 40 s time span. From Fig. 3, we conclude that when more sensors are used means more information is available then the estimation error will be reduced. The RMS error of estimation is less for using two sensors compared with estimation by one sensor. The estimated values deviate with the exact values due to measurement errors and also due to some radial transfer of heat.

7 Conclusion The MATLAB program based on CGM algorithm was satisfactorily used for estimation of q(t) for an inverse one-dimensional transient heat conduction problem by utilizing the experimental transient temperature data. The finite volume approach is applied satisfactorily for the solution of the problem like direct, sensitivity, and adjoint. The RMS error of 872.204 W/m2 observed while using the one sensor data and the RMS error of 299.034 W/m2 observed while using the two sensors. Acknowledgements This research work has been supported by the Board of Research in Nuclear Science (BRNS).

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References 1. Weisz-Patrault D, Ehrlacher A, Legrand N (2014) Temperature and heat flux fast estimation during rolling process. Int J Therm Sci 75:1–20 2. Cui M, Yang K, Liu YF, Gao XW (2012) Inverse estimation of transient heat flux to slab surface. J Iron Steel Res Int 19(11):13e18 3. Zhou J, Zhang Y, Chen JK, Feng ZC (2010) Inverse heat conduction using measured back surface temperature and heat flux. J. Thermophys. Heat Transfer 24(1):262 4. Yu XC, Bai YG, Cui M, Gao XW (2013) Inverse analysis of thermal conductivities in transient non-homogeneous and non-linear heat conductions using BEM based on complex variable differentiation method. Sci. China Phys. Mech. Astron. 56(5):966–973 5. Lin DTW, Yang CY, Li JC, Wang CC (2011) Inverse estimation of the unknown heat flux boundary with irregular shape fins. Int J Heat Mass Transf 54(25–26):5275–5285 6. Lin SM (2011) A sequential algorithm and error sensitivity analysis for the inverse heat conduction problems with multiple heat sources. Appl Math Model 35(6):2607–2617. https://doi.org/ 10.1016/j.apm.2010.11.015 7. Liu FB (2011) A hybrid method for the inverse heat transfer of estimating fluid thermal conductivity and heat capacity. Int J Therm Sci 50(5):718–724 8. Li HQ, Lei J, Liu QB (2012) An inversion approach for the inverse heat conduction problems. Int J Heat Mass Transf 55(15–16):4442–4452. https://doi.org/10.1016/j.ijheatmasstransfer.2012. 04.014 9. Czel B, Grof G (2012) Inverse identification of temperature-dependent thermal conductivity via genetic algorithm with cost function-based rearrangement of genes. Int J Heat Mass Transf 55(15–16):4254–4263. https://doi.org/10.1016/j.ijheatmasstransfer.2012.03.067 10. Cheng W, Fu CL, Qian Z (2007) A modified Tikhonov regularization method for a spherically symmetric three-dimensional inverse heat conduction problem. Math Comput Simul 75(3– 4):97–112. https://doi.org/10.1016/j.matcom.2006.09.005 11. Liu FB (2012) inverse estimation of wall heat flux by using particle swarm optimization algorithm with Gaussian mutation. Int J Thermal Sci 54(4):62–69, 265–273. https://doi.org/10. 1016/j.ijthermalsci.2011.11.013. https://doi.org/10.1016/j.ijheatmasstransfer.2012.10.036 12. Bideau PL, Ploteau JP, Glouannec P (2009) Heat flux estimation in an infrared experimental furnace using an inverse method. Appl Therm Eng 29(14–15):2977–2982. https://doi.org/10. 1016/j.applthermaleng.2009.03.014 13. Deng S, Hwang Y (2007) Solution of inverse heat conduction problems using Kalman filterenhanced Bayesian back propagation neural network data fusion. Int J Heat Mass Transf 50(11– 12):2089–2100. https://doi.org/10.1016/j.ijheatmasstransfer.2006.11.019 14. Chang C-L, Chang M (2006) Non-iteration estimation of thermal conductivity usingfinite volume method. Int Commun Heat Mass Transfer 33(8):1013–1020 15. Alifanov OM (1974) Solution of an inverse problem of heat conduction by iteration methods. J Eng Phys 26:471±476 16. Ozisik MN, Orlande H, Kassab AJ (2002) Inverse heat transfer: fundamentals and applications. Appl Mech Rev 55(1):B18 17. Panchal M, Saraswat A, Verma S, Chaudhuri P (2019) Estimation of effective thermal conductivity for lithium meta-titanate (Li2 TiO3 ) pebble beds using steady state and axial heat flow methods. J Coupled Syst Multiscale Dyn 6(4):257–265

A Study of Linear Fresnel Solar Collector Reflector Field for Performance Improvement Gunjan Kumar and Hemant Gupta

Abstract Linear Fresnel collector (LFC) is the source of useful energy generation where solar radiations are directed toward a fixed receiver. The operation of the collector is based on line focus technology. In the solar field, the receiver is placed centrally above the linear reflectors. It has less capital cost than parabolic trough collector (PTC) but its optical performance lags behind. However, various efforts are already taken to enhance the performance but still, it has scope to improve. Many kinds of solar field designs of this technology are available, and they are installed in both prototypes and commercial plants until the current time. In this paper, various LFC solar reflector field designs for performance improvement are reviewed. Effect of design parameters, like field orientation, location, numbers, size, focal length, and space between reflectors, is reported. In addition to that, LFC development and future aspects are also studied. Such reviews are useful for researchers pursuing or willing to work in this area. Keywords Linear Fresnel collector · Reflector field · Solar energy · Solar collector

Abbreviations LFC PTC CSP HTF SPT kWth

Linear Fresnel collector; Parabolic trough collector; Concentrating solar power; Heat transfer fluid; Solar power tower; Kilo watt thermal.

G. Kumar (B) · H. Gupta Shroff S R Rotary Institute of Chemical Technology, Ankleshwar, Gujarat Technological University, Ahmedabad, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_31

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1 Introduction In solar thermal technology, line focus collectors are the main contributors where solar energy is effectively harnessed to obtain thermal energy. Thermal energy is generated for process applications and electricity generation [1]. In general, concentrating solar power (CSP) technologies has a reflector field to focus sun rays onto a receiver [2]. The working fluid termed as heat transfer fluid (HTF) is allowed to flow inside the receiver that absorbs the heat energy to high temperature. HTF of high temperature is used either for process work or to generate electricity through a thermodynamic power cycle. HTF can also produce another working fluid at high temperatures with the help of a heat exchanger to run the cycle [3]. CSP technologies are generally classified as parabolic trough collector (PTC) technology, linear Fresnel collector (LFC) technology, solar power tower (SPT) technology, and dish/engine technology as shown in Fig. 1 [4]. PTC and LFC are the classification of line focus technology where radiations are directed to line focused receiver while SPT and dish reflector are known as point focus collectors because sun rays are reflected to point focused receiver [5, 6]. Figure 2 illustrates an LFC that is operated based on line focus technology. LFC technology comprises linear flat reflectors which target the incoming solar rays onto a stationary receiver.

Fig. 1 Classification of CSP technologies [7]

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Fig. 2 Linear Fresnel collector [9]

The tube receiver is surrounded with a face-down cavity, compensates lateral drift losses, and hence expands the absorber effectiveness. The entire receiver is enveloped with a glass cover to minimize the convection loss to the atmosphere. Solar energy is extracted by flowing HTF to thermal energy. The thermal energy is used to meet the process requirements. French researcher Augustin-Jean Fresnel has discovered the Fresnel focal point in the eighteenth century for beacons and thus LFC has been named [8]. PTC technology uses parabolic reflectors, whereas LFC technology uses geometrically flat reflectors to reflect the solar radiations into the receiver. The receiver is positioned at a certain elevation of the reflector field. Sometimes, flat mirrors of LFC are bent by elastic bending. Every reflector is facilitated with a tracking mechanism to track the sun for the entire day. The radiation absorbing capacity of the receiver is increased through the suitable selective coating. The advantages of LFC attracted the academician and researchers, which encouraged installing the more LFC projects around the world as shown in Table 1. Table 1 LFC-based solar power plants around the world Project Names

Output temperatures (°C)

Operation years

References

Solarmundo (Belgium)

–

2001

[5]

Kimberlina STPP (USA)

300

2008

[10]

Puerto Errado 1 (Spain)

270

2009

[11]

Liddell Power Station (Australia)

270

2012

[12]

Llo (France)

285

2015

[13]

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2 Review for Linear Fresnel Collector For LFC technology, mean concentration ratios and maximum operating temperatures are reported between 10 and 30 and below 300 °C, respectively [14–18]. However, Abbas et al. [19] stated that by using high-quality mirrors, this technology could reach as more as 500 °C with superheated water and 550 °C with molten salt. According to the German Aerospace Center, this technology is still not reliable and rated this as low maturity which can be said in a pre-commercial phase. This announcement is an opportunity for the researcher to develop it to the next scale. This happens because of the late improvement of the LFC in the particular CSP advancement periods. Among line focus CSP technologies, LFC has less capital cost because of light and simple structural support, geometrically flat reflectors, and stationary absorber without moving joints. Considering shading and blocking effects, patterns of alternating reflector inclination are established to make closely packed reflectors. The requirement of the land area is less in this case because of its shape and size. Although this technology has many advantages, maximum optical efficiency found is 22% only due to cosine losses. But if the optical efficiency increases, then this technology will give tough competition to PTC technology [14, 16]. Considering the material of collector, LFC has the capability to improve the concentration ratio and absorber temperature easily by putting some more reflectors without changing system design requirements. Despite the ease of increasing the concentration ratio, it is quite challenging to improve the optical efficiency of LFC. Receiver tubes are typically limited to 450–550 °C with high-performance coating materials [9]. In LFC, energy losses caused by the end effect also affect the length to width ratio of the reflector. If the length to width ratio is beyond 1000, end effects are negligible. In LFC, optical performance is significantly affected by energy losses due to cosine [20].

2.1 LFC Development This section describes the development of the LFC system from 1962. Several kinds of prototype and industrial setup have been developed and tested for performance analysis. The geometrical specifications of such an installed LFC prototype are shown in Table 2. The LFC system can be installed either on rooftops or compact areas by altering the length, width, or height of the receiver. It can be used to meet the process heat or cooling demands of various sectors or industries [21]. Giovanni Francia LFC: In 1962, Giovanni Francia had patented his design for the first real-world application as shown in Fig. 3. This design is tested for performance investigation at Marseille, France. This setup has generated steam with an evaporating capacity of 1965.38 kg/h at 450 °C and 100 atm [22].

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Table 2 Geometrical specifications of installed LFC project S.

Projects

Geometrical specifications

Values

Sources

Giovanni Francia LFC

Number of rows

07

[22]

Length of each row

8m

Width of each row

1m

Area of reflector

64.78 m2

Receiver height

6m

Length of receiver

8m

No. 1

2

Seville, Spain LFC

Width of receiver

0.25 m

Number of rows

11

Mirrors per row

16

Row spacing

0.2 m

Total area of field

352m2

Receiver type

Schott PTR 70

Receiver height

4m

Receiver length 3

4

5

6

Freiburg, Germany LFC Number of rows

New Delhi, India

Algeria LFC

Isparta, Turkey

[23]

64 m 11

Reflector width

0.5 m

Aperture width

5.5 m

Total width

7.5 m

Focal length

4m

Total reflector area

22 m2

Receiver type

CPC reflector

Reflector width

0.5 m

Length of mirror

1m

Tilt angle of mirror

15° per hour

Total reflector area

5 m2 and 13 m2

Receiver type

Trapezoidal cover

Number of mirrors

11

Mirror length

1.5 m

Mirror width

0.1 m

Total area of reflector

1.65m2

Receiver type

Trapezoidal type

Receiver length

1.6 m

Number of mirrors

10

[24]

[25]

[26]

[27]

Individual mirror length 1.8 m Individual mirror width

0.38 m (continued)

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Table 2 (continued) S.

Projects No.

7

Geometrical specifications

Values

Receiver type

Trapezoidal type

Telecommunication Number of modules 22 Company, South Africa Number of rows in each 11 module Total reflector area

484m2

Receiver type(Evacuated tube)

Secondary CPC reflector

Sources

[28]

Fig. 3 Francia’s linear Fresnel setup [22]

A layout of the LFC-based solar system had been envisaged the “Solar City Project—Hypothesis for an urban structure” by Francia in 1965. This system is anticipated to meet the basic energy demands of the urban area. LFC setup in Engineering School of Seville, Spain: A large experimental setup of LFC is constructed on the rooftop of the Engineering School of Seville, Spain. This setup is fabricated to serve a double effect lithium bromide water absorption chiller by the steam of thermal energy 174 kW [23]. Additionally, an auxiliary gas boiler is also deployed in the solar steam system. The aim of this work was to analyze the performance of the LFC system for an application. The results of the experiments have been used for possible improvements in future projects. The setup is illustrated in Fig. 4. Prototype installation in Freiburg, Germany: The prototype shown in Fig. 5 is

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Fig. 4 Experimental unit installed in Seville, Spain [23]

Fig. 5 Prototype installed in Freiburg, Germany [24]

installed to meet the energy requirements in the range of 50 kWth to 5 MWth. Ideally, a flat roof is suitable for its installation because of less wind load and more ground coverage. Prototype in Bergano, Italy: Fig. 6 shows the prototype, another unit of the Freiburg LFC system which was installed in Bergamo, Italy, in August 2006. The second unit of 132 m2 was developed to serve an NH3 /H2 O absorption chiller. The largest

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Fig. 6 Experimental setup (Bergamo, Italy) [24]

operational unit has a capacity of 176 kW thermal power, installed in Seville, Spain. This project powers the double effect LiBr chiller. Experimental setup installed in New Delhi, India: The setup is installed on the rooftop of an organization in New Delhi, India. This design is capable of generating the steam at the rate of 2.4 kg/h and 6.3 kg/h at 1.5 bars with a total reflector field area of 5 m2 and 13 m2 , respectively. The setup is shown in Fig. 7. It is equipped with a tracking system of four-bar link mechanism that tracks the sun throughout the day. Experimental unit outside Algeria: A small prototype as shown in Fig. 8 is installed

Fig. 7 Setup installed in New Delhi, India [25]

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Fig. 8 Experimental unit installed in Blinda, Algeria [26]

at Saad Dahlab University, Blinda, Algeria, for experimental analysis. It is tested using tap water as a working fluid in 2015. The thermal investigation was carried out in January and February 2015. Thermal efficiency and maximum exit water temperature were found around 29% and 74 °C, respectively. Experimental setup in Isparta, Turkey: Fig. 9 shows an experimental setup that is

Fig. 9 LFC unit at Isparta, Turkey [27]

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installed in Isparta, Turkey, for performance analysis. The investigation is carried out on August 2, 2012, by taking water as a working fluid. Inlet and exit temperatures of water were recorded to find the maximum temperature difference. Water was allowed to flow at 0.025 kg/s while the peak efficiency of 34.1% was noted during the day. Experimental setup at a telecommunication company of South Africa: Fig. 10 shows an industrial setup, which is in operation at the data center of a telecommunication company. It is installed on the rooftop to meet the peak cooling capacity of 330 kW of a lithium bromide water absorption chiller. It is designed for water heating up to 180 °C and 12 bar pressure while the return temperature is 165 °C. The provision is made to vary the flow rate of the water, and mirrors are focussed or defocused to meet the need. The system is equipped with safety protocols for urgent situations. Experimental setup at the mining site in Aydin, Turkey: Fig. 11 shows an experimental setup that is installed in a mining site of Ayudin, Turkey. It is designed for the

Fig. 10 The rooftop installation in South Africa [28]

Fig. 11 LFC setup installed in mining site of Turkey [29]

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ore drying process to reduce LNG consumption [29]. The plant size is 1 MWth and can produce 1.4 GWh thermal energy per year. Hot pressurized water up to 200 °C can be generated by this system.

3 LFC Reflector Field Configuration In the LFC reflector field design, several parameters such as field orientation, number of reflectors, the width of reflectors, the space between reflectors, and the focal length of reflectors are considered to improve the optical performance of the collector. In this section, the effects of these parameters on the collector performance are reviewed, and important results are tabulated.

3.1 Solar Field Orientation Usually, solar fields are orientated in the direction of North–South and East–West. These directions are studied and discussed by many researchers. It was reported that the higher annual solar energy was obtained for North–South orientation in comparison with the East–West direction [30]. This study makes North–South direction more renowned in research fraternity. Recent solar fields of Fresdemo and Puerto Errado I and II are also designed to be oriented in the North–South direction [31–33]. R. Abbas et al. have reported the dependency of orientation on the latitude of the location. Optimization of the field was done for different altitudes and orientations. It is concluded that East–West orientation is favorable for high latitude locations since this direction obtains better efficiencies with less expense. North–South orientation is proven as a good solution for the solar field which is located in latitudes closer to the tropics. East–West orientation permits the installation of wider reflectors, and hence fewer numbers of reflectors are required. In such orientation, the effect of newly designed configurations, non-uniform width reflectors, and non-uniform shifts between reflectors are more vital than in fields with North–South orientation. For North–South direction, the use of non-uniform width of reflectors across the field does not contribute to increasing efficiency, whereas it adds an extra fabricating cost. Approximately, 20 reflectors are required for North–South direction [33]. Efficiencies with respect to locations, configurations, and orientations are compared and reported in Table 3.

3.2 Reflector Location Shading and blocking of solar radiation are taken care while locating the reflectors. Reflector distances and reflector mounting heights across the field decide reflector

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Table 3 Effect of location, configuration, and orientation on efficiency [33] Orientation

North–South

Latitude(N)

37°

East–West

No. of reflectors

20

Tilt(°C)

0

0

Shift

Variable

Variable

Width

Constant

Constant

Minimum rad., Imin (kW/m2 )

25

25

Energy efficiency, ηen (%)

46.0

46.1

10

Latitude(N)

24°

No. of reflectors

20

10

Tilt(°C)

0

0

Shift

Variable

Variable

Width

Constant

Constant

Minimum radiation, Imin (kW/m2 )

25

25

Energy efficiency, ηen (%)

56.9

50.0

Energy efficiency is emphasized to review the overall solar energy conversion under various circumstances

placement in the transversal plane. Choudhury et al. [34] have recommended the installation of uniform reflector widths at non-uniform reflector distances throughout the field. However, this was concluded to decrease the blocking impact without optimizing the reflector field set of design variables. Thereafter, researchers optimized the reflector distances across the field for no blocking impacts when the sun is at the zenith [32, 35, 36]. Various absorber shapes like tubular, triangular, horizontally flat, or vertically flat with constant reflector width across the field are taken into account for these studies. In 2012, the shading effect was the most important topic for the researchers. They were trying to design a plant in which the shading effect was negligible. Conclusively, they suggested that the shading effects can be minimized by placing the reflector in such a way that it should be appropriate for a given sun orientation with a uniform width across the field [36]. Later simplicity and practicability of the collector design were focussed by other researchers [31, 32, 38]. They incorporated the idea of a uniform reflector distance across the field in their projects. Solar projects of Fresdemo and Puerto Errado were also constructed based on the above idea. In order to match reflector layout with specific patterns, researchers recommended the mounting reflectors at different heights across the field for the ordinate reflector locations in the transversal plane. Considering the improvement of the optical efficiency, Chaves and Collares-Pereira (2009) mentioned the etendue-matched reflector field, paired with a compact linear Fresnel design [39– 41]. However, researches on the ordinate reflector locations in the transversal plane

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Table 4 Optimal configuration for uniformly spaced identical reflectors Distance between centers of consecutive reflectors Semi-width of each reflector Focal length 1.21 m

0.5 m

16.85 m

are under consideration and yet to be constructed. Paola Boito et al. [42] have done the optimization for location, width, and focal length of reflectors. Four different levels of optimization are considered in their work: uniformly spaced similar reflectors; non-uniformly spaced similar reflectors; reflectors of the same width, uniformly spaced, and variable focal lengths, and finally a full optimization. The researcher considered a model in which the receiver is taken as flat, horizontal, and located at a fixed height of 10 m from the ground. The width of the receiver is also kept fixed as 0.4 m, and a total of 25 numbers of reflectors are taken into consideration. The results of their research for different cases are tabulated in Tables 4, 5, 6, and 7. Total 13 reflectors are listed numbered from 13 to 25. The properties of other reflectors could be found by symmetry. The full optimization of a Fresnel plant is Table 5 Optimal configuration for non-uniformly spaced identical reflectors (optimization for reflector position) Reflector 13 14 index Optimum 0 position

15

16

17

18

19

20

21

22

23

24

25

1.14 2.29 3.43 4.57 5.74 6.87 8.03 9.27 10.51 11.73 13.07 14.46

Table 6 Optimal configuration for reflectors of the same width with uniform spacing and variable focal lengths (optimization for focal length) Reflector index

13

14

15

16

17

18

19

20

21

22

23

24

25

Optimum 13.1 12.9 13.0 13.3 13.7 14.0 15.0 16.3 17.5 18.6 11.7 13.0 14.4 focal length

Table 7 Optimal configuration for full optimization (optimization for position, width, and focal length) Reflector 13 index

14

15

16

17

18

Position

0

1.5

3.9

6.3

8.0

9.4

Width

0.37

0.88

1.24

0.82

0.62

0.51

Focal length

15.9 10.5

12.0

13.8

15.4

16.7

19

20

21

22

10.6

11.6

12.6

13.5 14.3 15.1 16.1

0.44 18.0

0.37 19.0

0.35 20.0

0.3

23

0.2

24

0.2

25

0.4

21.0 21.9 22.4 22.7

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proved a better solution for improving efficiency. Incorporation of suitable optimization techniques can have an estimated increment around 12% in case of the initial configuration in which all reflectors are identical and adjacent, and a full optimization shows an increment of 4.5% over a simple uniform optimization [42].

3.3 Width and Shape of Reflectors In the earlier research, it was concluded that the reflector width of the field alongside reflector distances and reflector angles are significant variables [36]. Lots of research have been done in the 1990s to find the optimum locations of the reflectors in the transverse plane. Studies were also conducted to find the widths of reflectors in solar fields [18, 35, 43]. Practically, consistent low concentration was found in the case of flat reflectors fields. Flat reflectors limit the upper bound of the reflector width to the beneficiary gap width just as prompting astigmatism or the off-axis variation in the solar-based field, which decreases the solar concentration of the field [19]. With slightly curved reflectors, LFC achieves better performances [32, 44, 45]. The idea of using curved reflectors in LFC designs which are used is in prototypes as well as commercial plants. For instance, it was introduced for a model in which a 3 m reflector curvature radius was considered for the LFC plant where its absorber was located 1.5 m over the reflector plane [37]. Twenty-five slightly curved reflectors were used in the FRESDEMO project, constructed in Plataforma Solar de Almeria (PSA) in Spain [31]. The researcher claims that the use of slightly bent reflectors gives high focus proportions. Also, it has the advantage of cost reduction over other CSP innovations. They researched for LFC solar field optimization in a flat receiver using different reflector shapes; flat reflector, cylindrical reflector with specific reference, parabolic reflector with specific reference, and parabolic reflector with zenith reference. The result of the above research has been tabulated in Table 8. It was suggested to use cylindrical reflectors with specific reference for LFR. Similar result is found for parabolic shapes also. These curved reflectors show much higher performance than flat reflectors. For the same reference, no actual difference in the concentration features is found between parabolic and cylindrical shapes. If reflectors are slightly bent to aim toward the receiver central point, a higher concentration factor may be obtained [44]. Table 8 Effect of various reflector shapes on LFC technology Reflectors

Solar reference Remarks

Flat

–

Performance is not very good

Cylindrical Specific

Advisable in LFR

Parabolic

Specific

Advisable in LFR

Parabolic

Zenith

Higher concentration ratio but the global difference is negligible

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Table 9 Optimization parameters and their effects Optimization parameters

Effects of parameters

Gap between reflectors

Plant cost increases with increase in space between reflectors

Receiver height

Plant cost increases with increase in receiver height

Mounting height of the receiver

The daily solar power increases with increasing mounting height of the receiver

Number of reflectors

By adding more reflectors the daily solar power increases

Width of reflectors

The daily solar power increases with increase in reflectors width

There is much scope for the optimization of LFR technology. An optimization methodology is introduced that can be applied for any kind of CSP technology. To achieve the optimization goals, a number of reflectors, reflector width, space between reflectors and reflector focal length are taken into account for the reflector field. The researcher optimized the solar field for the number of reflectors, width, and height of the receiver. Their research was focused on harvesting maximum solar energy as well as reducing plant thermal heat loss and plant cost. As a result, it was concluded that by increasing the space between reflectors and receiver height, the plant cost increases. It is mainly due to the increased land requirement and more supportive structure. By increasing the mounting height of the receiver, the daily solar power goes on increasing and solar power also increases by adding more number of reflectors, and by increasing the reflector width [40]. Optimization parameters and their effects are shown in Table 9. Effect of variable width and shift of reflectors was seen, and it is concluded that the lateral drift improves by increasing the horizontal distance to the receiver and the width of the reflectors. There is no meaning to install very narrow reflectors when there is a main error because of distance traveled by the sunrays. Hence, it becomes required to alter the width of the reflector across the solar field [46]. In the zenithal reference configuration, optimum width for a given location is wider. It is because such configuration leads to lower lateral drifts. Fewer reflectors are needed for a given total width of reflector across the field in case of zenithal reference. The best efficiency is achieved with a fixed width but variable shift across the field. The use of variable width reflectors does not contribute to an increase in net efficiency in comparison with the variable shift and constant width design.

4 Future Aspects of Linear Fresnel Collector Among CSP technologies, LFC has many salient features such as low capital cost, easy and low maintenance, and high-ground utilization. However, it has also some serious drawbacks like optical efficiency, exit working fluid temperature, etc.,

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that enable researchers to work further. The performance of this technology is compared with PTC technology and thus future scopes are remarked in Table 10. The late development of LFC technologies has given a chance to researchers for its optimization. LFC technology has scope to improve its optical performance. The opportunities persist to increase optical efficiency and collector outlet temperature. The effort also can be made for receiver material to withstand higher temperatures. Shading and blocking effects still can be minimized. Table 10 Performance comparison of LFC and PTC technology Factors

Technologies

Remarks

Source

Less

Scope persists to increase LFC optical efficiency

Dhyia Aidroos et al. [17]

High

Less

Scope persists to increase LFC Collector outlet temperature

Dhyia Aidroos et al., 2015 and Wang Fuqianga et al.,2017 [17, 18]

High

Less

Distinct feature of Dhyia Aidroos LFC technology et al., 2015 and David R. Mills et al., 2000 [17, 19]

Land requirement High for same amount of power generation

Less

A major Dhyia Aidroos disadvantage with Baharoon PTC technology et al.,2015 [17]

Wind load

High

Less

Wind load could not be minimized for PTC technology

Energy Sector Management Assistance Program (ESMAP) [20]

Blocking and shading effect

Occurs

Occurs

Scope persists for both technologies

Energy Sector Management Assistance Program (ESMAP) [20]

Receiver position

Mobile

Fixed

A major Dhyia Aidroos disadvantage with et al., 2015 [17] PTC technology and could not be eliminated

Material

To be improved To be improved Scope persists for both technologies to sustain higher of

PTC

LFC

Optical efficiency High

Collector outlet temperature

Installation cost

Wang Fuqianga et al., 2017 [18]

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5 Conclusion In this work, an effort is made to show the development of LFC for various process applications. The experimental units of LFC projects are illustrated along with their detailed geometrical specifications. This paper has reviewed various kinds of reflector field configurations. Design aspects such as filed orientation, location, numbers, width, focal length, and space between reflectors are studied. The following effects over the collector performance are concluded on the basis of the study. With regard to field orientation, for high latitudes location, East–West orientation is preferable, whereas, for the low latitude location which is nearer to the tropics, North–South orientation is favorable. East–West orientations permit the installation of wider reflectors. For North–South-oriented solar field, reflectors with variable width do not contribute to increasing efficiency, whereas it adds an extra manufacturing cost. Full optimization, i.e., optimization for the location, width, and focal length of each reflector is required to improve efficiency. Partial optimization provides only marginal efficiency gain. Curved reflector shows higher performance than a flat reflector. The concentration features are almost the same when reflectors of parabolic and cylindrical shapes are taken into consideration for a similar reference. Higher concentrations are achieved if slightly bent reflectors are aimed toward the absorber central line. Daily solar power is improved by increasing the mounting height of the absorber. It also increases by increasing the width of the receiver and adding more reflectors. Plant cost is substantially affected by the gap between reflectors and elevated receiver height.

References 1. Siddharth S, Khan MK, Pathak M (2015) Performance enhancement of solar collectors—a review. Renew Sustain Energy Rev 49:192–210 2. Pushkaraj D, Sonawane VK, Raja B (2017) An overview of concentrated solar energy and its applications. Int J Ambient Energy 39:1–6 3. Kalogirou SA (2004) Solar thermal collectors and applications. Prog Energy Combust Sci 30:231–295 4. El Gharbi N, Derbal H, Bouaichaoui S, Said N (2011) A comparative study between parabolic trough collector and linear Fresnel reflector technologies. Energy Procedia 6:565–572 5. Lovegrove K, Stein WS (2012) Concentrating solar power technology: principles, developments and applications. Woodhead Publishing. ISSN 2044-9364 6. Starke AR, Lemos LFL, Colle S, Reinaldo RF, Cardemil JM, Escobar R (2016) A methodology for simulation and assessment of concentrated solar power plants. Therm Eng 15(1):33–40 7. Fuqiang W, Ziming C, Jianyu T, Yuan Y, Yong S, Linhua L (2017) Progress in concentrated solar power technology with parabolic trough collector system: a comprehensive review. Renew Energy Sustain Energy Rev 79:1314–1328 8. Liddell Power Station, https://www.nrel.gov/csp/solarpaces/project_detail.cfm/projec tID=269. Last accessed 18 April 2020

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9. Zhu G, Wendelin T, Wagner MJ, Kutscher C (2014) History, current state and future of linear Fresnel concentrating solar collectors. Sol Energy 103:639–652 10. Kimberlina STTP, https://www.cspworld.org/cspworldmap/kimberlina-stpp. Last accessed on 12 April 2020 11. Puerto Errado, https://www.cspworld.org/cspworldmap/puerto-errado-1. Last accessed on 12 April 2020 12. Liddell Power Station, https://www.nrel.gov/csp/solarpaces/project_detail.cfm/projec tID=269. Last accessed on 1 April 2020 13. Llo Solar Thermal Project, https://www.nrel.gov/csp/solarpaces/project_detail.cfm/projec tID=266. Last accessed on 12 April 2020 14. Negi BS, Mathur SS, Kandpal TC (1989) Optical and thermal performance evaluation of a linear Fresnel reflector solar concentrator. Solar Wind Technol 6:589–593 15. Abbas R, Martínez-Val JM (2015) Analytic optical design of linear Fresnel collectors with variable widths and shifts of mirrors. Renew Energy 75:81–92 16. Review of CSP and Desalination Technology, DLR. https://www.dlr.de/tt/Portaldata/41/Res ources/dokumente/institut/system/projects/aquacsp. Accessed on 3 May 2020 17. Baharoon DA, Rahman HA, Omar WZW, Fadhl SO (2015) Historical development of concentrating solar power technologies to generate clean electricity efficiently—a review. Renew Sustain Energy Rev 41:996–1027 18. Fuqiang W, Ziming C, Jianyu T, Yuan Y, Yong S, Linhua L (2017) Progress in concentrated solar power technology with parabolic trough collector system: a comprehensive review. Renew Sustain Energy Rev 79:1314–1328 19. David RM, Graham LM (1999) Compact linear Fresnel reflector solar thermal power plants. Sol Energy 68:263–283 20. Review of CSP technology, Energy Sector Management Assistance Programme (ESMAP), Chapter-1 (2010) 21. Schweiger H, Mendes JF, Carvalho MJ, Hennecke K, Krüger D (2015) Solar heat for industrial processes. In: Advances in solar energy: an annual review of research and development in renewable energy technologies, vol 17. Taylor and Francis, pp 216–260 22. Silvi C (2009) The pioneering work on linear Fresnel reflector concentrators in Italy. In: 15th Solar PACES International Symposium 23. Desai NB, Bandyopadhyay S, Nayak JK, Banerjee R, Kedare SB (2014) Simulation of 1 MWe solar thermal power plant. Energy Procedia 57:507–516 24. Rommel M (2008) process Heat collectors. IEA SHC-Task 33 and SolarPACES-Task IV. Solar Heat for Industrial Processes 58 25. Sen PK, Ashutosh K, Bhuwanesh K, Engineer Z, Hegde S, Sen PV, Davies P (2013) Linear Fresnel mirror solar concentrator with tracking. Procedia Eng 56:613–618 26. Mokhtar G, Boussad B, Noureddine S (2016) A linear Fresnel reflector as a solar system for heating water: theoretical and experimental study. Case Stud Therm Eng 8:176–186 27. Dostucok I, Selbas R, Sencan A (2014) Experimental investigation of a linear Fresnel. Thermal Sci Technol 34:77–83 28. Industrial Solar, https://www.industrial-solar.de/content/en. Accessed on 5 May 2020 29. Feranova, https://www.feranova.com. Accessed on 5 May 2020 30. Sharma V, Nayak JK, Kedare SB (2015) Effects of shading and blocking in linear Fresnel reflector field. Sol Energy 113:114–138 31. Zahler et al (2009) Direct steam production in a linear concentrating Fresnel collector. In: Presented at the 4th European solar thermal energy conference (ESTEC), Munich, Germany 32. Bernhard R, Laabs H, Lalaing JD (2008) Linear Fresnel collector demonstration on the PSA, Part I—design, construction and quality control. In: Presented at the 13th Solar PACES International Symposium, Las Vegas, US 33. Morin et al (2006) Road map towards the demonstration of a linear Fresnel collector using a single tube receiver. In: Presented at the 13th Solar PACES international symposium, Las Vegas, US

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Recent Advances in Design Infrastructure

Kinematic Analysis of Planar Mechanisms by Means of Computer-Aided Design Software Amit Talli

and Arunkumar C. Giriyapur

Abstract In this paper, the kinematic analysis of planar mechanisms using a computer-aided application is presented. The kinematics branch deals with the study of motion excluding forces responsible for the motion. The computer-aided design (CAD) is implemented to perform kinematic analysis. There are many advanced commercial CAD software available which are capable of performing the complex simulation. The CAD also helps to understand the working principle of any complex mechanism or synthesis of a mechanism through simulation. The paper focuses on two planar mechanisms with one degree of freedom producing exact straight-line motion. The mechanisms are actuated by applying data points by using a CAD tool. The planar mechanism traces an exact straight line, and the verification is done by measuring the linear displacement by drafting technique and compared with the simulation data provided by the CAD tool. Keywords Computer-aided design · Simulation · Kinematic analysis · Planar mechanisms

1 Introduction The mechanism is the heart of machines, and it is widely used in almost every application. Industrial robots, scissor lift, semi-fowler hospital bed, car jack, door closure, CNC machines, 3D printers, and lathe machines are some of the applications of mechanisms. The mechanism receives force from the input source and transfers the forces from one point to another point through the rigid links. The rigid links are attached by joints which allow relative motion between the rigid links. The mechanism forms a part of a mechanical device, for example, a portable drill machine, the internal part such as rigid links, gears, and joint constitute mechanism. The study related to the mechanisms is also critical in academics such as mechanical A. Talli (B) · A. C. Giriyapur Automation and Robotics, KLE Technological University, Hubli 580031, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_32

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engineering undergraduate course [1]. Undergraduates learn about the concepts of various mechanisms such as four-bar, slider-crank, gears, cams, and governors. The analysis is an essential process to simulate how the design performs in the field [2]. The kinematics and dynamics are the two-fundamental analysis for designing a machine [3]. The kinematic analysis deals with the analysis of motion to determine the displacement, velocity, and acceleration with respect time without considering the forces causing the motion [4, 5]. The dynamic analysis includes the forces causing the motion of the mechanism. The dynamic analysis takes care of determining the force components [6]. The physical prototyping or testing of a new mechanism is a time-consuming, expensive, and unsafe process. The problems could be addressed by using CAD tools, computer-aided design software tools have become more advanced and are equipped with sophisticated libraries with an advanced physics engine to enumerate the real-world scenarios [7]. The usage of CAD tools has increased in many fields, such as automobile, R&D, production, dental, medical, and education. There are many commercial CAD tools such as SolidWorks, Catia, AutoCAD (Autodesk), Fusion 360, PTC Creo, Siemens NX, and Solid Edge (Siemens). These CAD tools offer plenty of features for product development, and some of them also offer cloud-based CAD services for secure collaboration.

2 Overview of SolidWorks Motion Analysis SolidWorks is a computer-aided design tool from Dassault Systemes and widely used in industries and educational institutions. The graphical user interface of motion analysis is shown in Fig. 1. There are three types of motion simulation provided in

Fig. 1 Motion study interface

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SolidWorks. The first type of motion simulation is known as animation; it is the basic and primary level of simulation and does not provide any results. The second level is known as the basic motion, and third level is known as motion analysis. The third level of motion study is used for simulation and plotting the results. Figure 1 shows various options available in the motion analysis, such as actuator, results, time-line, force, spring, gravity, and solid contact. The motion study option is only activated in the assembly module of SolidWorks [7].

2.1 Workflow The workflow of the analysis of the mechanism is shown in Fig. 2. The first step begins with building various rigid parts of the mechanism. The modeling module of SolidWorks is used to create the rigid links of different shapes as per the dimensions and requirements [8]. The material property for the individual link is assigned in the part modeling module. The parts are then imported into the second step, i.e., assembly module of the SolidWorks. The assembly module is the most critical section and adds functionality to the mechanism. In the assembly section, the parts are assembled by applying constraints such as lock mate, concentric mates, coincident mate, gear mate, and cam mate depending upon the functional requirement. The motion study tab is activated for setting up the simulation environment. The gravity value and the direction are also specified in the motion analysis. The actuator provides input to the rigid link, and it is applied by using the motor option. The simulation is performed according to the input provided by the user in the motion study. The simulation time can be adjusted from seconds to hours by using the time-line option. The results are measured after the simulation is wholly performed. The results, such as displacement, velocity, acceleration, torque, power consumption, and energy, are plotted in terms of a graph.

Fig. 2 Workflow in SolidWorks

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3 Kinematic Analysis of Planar Mechanisms 3.1 Peaucellier–Lipkin Linkage The Peaucellier–Lipkin linkage is a planar mechanism which produces a straightline motion from rotary input [9]. The planar mechanism works in a two-dimensional plane (x–y plane). The Peaucellier–Lipkin linkage as shown in Fig. 3 was discovered in 1864 by the French C. Nicolas Peaucellier [10]. The Peaucellier–Lipkin linkage has eight links and ten joints, with mobility or degrees of freedom (DOF) equal to one. The Peaucellier–Lipkin linkage requires only one actuator or motor to precisely position the rigid links with respect to the fixed link. The Gruebler’s equation calculates the mobility for the planar linkages: M = degrees of freedom = 3(n−1)−2 j p − jh

(1)

where, n = total number of links, jp = primary joint, and jh = higher-order joint. There are total eight links and ten joints, substituting the values in Eq. (1) yields the mobility value equal to one. The Peaucellier–Lipkin linkage depends upon the specification of the links. The mechanism has eight links labeled in terms of numbers from 1 to 8 and ten joints labeled as A (counted as two), B, C (counted as two), D (counted as two), E, and F (counted as two). The Peaucellier–Lipkin linkage must satisfy the conditions to generate an exact straight line: AB = BD, AC = AF, and DC = CE = EF = EF. The point A, B, and D should be collinear, and link-1 should be fixed or grounded (does not exhibit any motion). The straight-line path is traced by point E. The input to the actuator is given by using the data points for the actuation of Peaucellier’s exact straight-line mechanism. The data point option is a part of function builder in SolidWorks. The data point option requires two information in terms of time in seconds and the value of displacement in terms in degree. Table 1 shows the data entered in the data point option for the simulation. The simulation starts at 0 s and stops after 35 s. The actuator is applied to the link-4, as shown in Fig. 3.

Fig. 3 Peaucellier–Lipkin linkage

Kinematic Analysis of Planar Mechanisms … Table 1 Data points

379

Time (s)

Value (°)

0

0

5

45

10

−45

15

45

20

−45

25

45

30

−45

35

45

Fig. 4 Simulation of Peaucellier–Lipkin linkage mechanism

The simulation of operation related to the Peaucellier–Lipkin linkage mechanism is shown in Fig. 4. The initial position of the Peaucellier–Lipkin linkage mechanism is shown in Fig. 3. At time t = 5 s, the link-4 of the Peaucellier mechanism rotates in the positive 45-degree counterclockwise direction, and at time t = 10 s, the link-4 of the Peaucellier mechanism rotates in the negative 45° clockwise direction, and point E traces the exact straight line for the given data points as shown in Fig. 4. The input angular displacement graph of link-4 of the Peaucellier–Lipkin mechanism is shown in Fig. 5. The input angular displacement values are entered as a data point, as per Table 1. The intermediate data point is calculated by the linear interpolation function of the motion analysis. The time derivative of the angular displacement of the link-4 yields angular velocity. The angular velocity of the link-4 is calculated by: ωLink-4 = angular displacement/time = 18◦ /s2

(2)

The linear displacement of the point ‘E’ is measured by using the graphical technique. The drafting technique is executed by using the drawing module of SolidWorks. The drafting technique can be carried out by using traditional drafting method,

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Fig. 5 Angular displacement of link-4

Fig. 6 Linear displacement of point ‘E’ and ‘E’

but it is a time-consuming process. The point ‘D’ is displaced to ‘D” by an angle of 45 degree in the counterclockwise direction. The linear displacement of point ‘E’ and ‘E’ is measured graphically, and the value of 136 mm is determined, as shown in Fig. 6. The linear displacement value of ‘E’ is measured by using the SolidWorks motion analysis. Figure 7 shows the linear displacement graph of the Peaucellier–Lipkin linkage mechanism in SolidWorks motion study. The linear displacement is plotted on the y-axis, and time is plotted on the x-axis. The graph shows +137 mm at 5 s and −137 mm at 10 s due to the input data points. The result obtained by the graphical method and SolidWorks motion analysis is found to be consistent.

3.2 Watt’s Straight-Line Mechanism The Watt’s straight-line mechanism is also called a parallel linkage mechanism which produces a straight-line motion from rotary motion, and James Watt discovered it in 1784. Figure 8 shows Watt’s straight-line mechanism, and the construction of the mechanism is straightforward. The mechanism has total of four links and four joints,

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Fig. 7 Linear displacement of Peaucellier—Lipkin linkage in SolidWorks

Fig. 8 Watt’s straight-line mechanism

substituting the values in Eq. (1) yields the mobility equal to one. The mechanism requires one actuator/motor to precisely position all the rigid links with respect to ground. The Watt’s linkage depends upon the specification of the rigid links. The mechanism has four links labeled in terms of numbers from 1 to 4 and joints labeled as A, B, C, and D. The Watt’s linkage must satisfy the following conditions to generate an exact straight line: AB = CD and the distance between point A and D should be equal to the length of the link-3. Link-3 should be perpendicular to link-2 and link-4. The data point option requires two information in terms of time in seconds and the value of displacement in terms of degree. Table 2 shows the data entered in the data point option for the simulation in SolidWorks motion study. The simulation starts at 0 s and stops after 35 s. The actuator is applied to the link-2, as shown in Fig. 8. The simulation of operation related to the Watt’s linkage mechanism is shown in Fig. 9. The initial position of the Watt’s linkage mechanism is shown in Fig. 8. Link-2 of the Watt’s mechanism rotates in the positive 15° counterclockwise direction, and negative 15° clockwise direction. The center of link-3 traces the exact straight line for the given data points is shown in Fig. 9.

382 Table 2 Data points

A. Talli and A. C. Giriyapur Time (s)

Value (°)

0

0

5

15

10

−15

15

15

20

−15

25

15

30

−15

35

15

Fig. 9 Simulation of Watt’s linkage mechanism

The angular displacement of link-2 of the Watt’s linkage mechanism is shown in Fig. 10. The intermediate point is calculated by the interpolation function of the motion analysis. The time derivative of the angular displacement of the link-2 yields angular velocity. The angular velocity of the link-2 is calculated by: ωLink-2 = angular displacement/time = 3◦ /s2

Fig. 10 Angular displacement of link-2

(3)

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383

Fig. 11 Linear displacement of the center of link-3

The linear displacement of the center of link-3 is measured by using the graphical technique. The drafting technique is executed by using the drawing module of SolidWorks. The drafting technique can be carried out by using traditional drafting method, but the traditional method is a time-consuming process. Link-2 or ‘AB’ is rotated by an angle of 15° in the counterclockwise direction. The linear displacement of the center of the link-3 is measured graphically and found to be 102 mm is shown in Fig. 11. The linear displacement value of the center of link-3 is measured by using the SolidWorks motion analysis. Figure 12 shows the linear displacement of Watt’s linkage mechanism. The linear displacement is plotted on y-axis in ‘mm’ and time is plotted on x-axis in ‘seconds.’ The graph starts with an initial value of 30 mm at 0 s and reaches −72 mm at 5 s for the 15° input value set for link-2 or ‘AB’ in the clockwise direction. The negative sign or symbol indicates the direction of motion in SolidWorks.

Fig. 12 Linear displacement of Watt’s linkage mechanism in SolidWorks

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The linear displacement of the center of link-3 of Watt’s straight-line mechanism is given by: Linear displacement = 30 mm + 72 mm = 102 mm

(4)

The result obtained by the drafting method and SolidWorks motion analysis is found to be consistent.

4 Conclusion In this paper, the motion analysis module for kinematic analysis of planar mechanisms in SolidWorks software has been reported. The CAD software can be implemented for analysis, synthesis, and prototyping of mechanisms. Introducing the CAD software for mechanism analysis reinforces the theoretical concepts of mechanisms. The process of kinematic analysis is presented using two planar mechanisms by means of CAD. The kinematic results, such as linear displacement of Peaucellier’s exact straight-line mechanism and Watt’s straight-line mechanism, are measured by using the drafting technique and verified with simulation data obtained from motion analysis. The results obtained by drafting method and simulation method are found to be consistent. In the future, the kinematic and dynamic analysis of spatial mechanisms can be carried out, and data or results can be exchanged between other software for co-simulation.

References 1. Lokesh R, Chittawadigi RG, Saha SK (2015) MechAnalyzer: 3D simulation software to teach kinematics of machines. In: 2nd International and 17th National Conference on Machines and Mechanisms, pp 1–9 2. Anciferov SI, Gaponenko EV, Kulakov LS (2018) Kinematic analysis of robotic complex within the SOLIDWORKS Motion system. In: Proceedings of the international conference “Actual issues of mechanical engineering” (AIME 2018). Atlantis Press, pp 27–31 3. Nedelcu D, Gillich GR, Bloju A, Padurean I (2020) The kinematic and kinetostatic study of the shaker mechanism with SolidWorks Motion. J Phys Conf Ser 1426:12025 4. Hampali S, Chittawadigi RG, Saha SK (2015) MechAnalyzer: 3D model based mechanism learning software. In: 2015 IFToMM World Congress Proceedings, IFToMM 2015, pp 25–30 5. Vavrek EM (2002) Incorporating working model into the lab of an applied kinematics course. In: ASEE Annual Conference Proceedings, pp 7117–7128 6. Vavro J, Vevro J, Kováˇciková P, Bezdedová R (2017) Kinematic and dynamic analysis of planar mechanisms by means of the solid works software. Procedia Eng 177:476–481 ˇ 7. Imamovic M, Hadžikaduni´c F, Tali´c-Cikmiš A, Bošnjak A (2019) Examples of kinematic analysis of complex mechanism using modern software applications. IOP Conf Ser Mater Sci Eng 659

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8. Sousa J, Galvao J, Machado J, Mendonca J, Machado T, Silva P (2018) Modelling and simulation of a straight line motion mechanism for industrial application. In: 2018 5th international conference on control, decision and information technologies (CoDIT 2018), pp 1104–1109 9. Buckley J, Huang MZ (2011) A study on dimension synthesis for the Peaucellier mechanism. In: ASME 2011 International Mechanical Engineering Congress and Exposition (IMECE 2011), vol 7, pp 233–239 10. Calderón J, Juárez I, Anzurez J., Núñez D, Márquez L (2016) Analysis and synthesis Peaucellier mechanism. In: 2016 IEEE international autumn meeting on power, electronics and computing (ROPEC), pp 1–6

Superplasticity: Recent Approaches and Trends Deepika M. Harwani, Vishvesh J. Badheka, and Vivek Patel

Abstract The increasing inclination of manufacturers toward reducing the component count in order to produce the product near to the final net shape has given momentum to superplastic forming. Superplastic forming is based on developing superplasticity in the polycrystalline materials. The capacity of any material to develop uniform plastic elongations more than 200% under tension is termed as superplasticity. It helps in the precise and easy fabrication of complex parts without any joining or welding. The key to achieve large tensile elongations lies in the fine grain size of the material. Fine grain size and subsequent superplastic properties can be developed in metals through various approaches like thermo-mechanical and severe plastic deformation processes. This paper gives a preface to the concept of superplasticity and discusses different methods to induce superplasticity in metals. Highlights of the recent trends and challenges encountered in the field of superplasticity are also presented. Keywords Superplasticity · Fine grain · Severe plastic deformation

1 Introduction Considerable savings in the cost of materials and its machining has become the point of prime importance for the modern industries. This urges the designers and manufacturers across the world to incorporate such processing techniques that lead The original version of this chapter was revised: In this chapter Vivek K. Patel name is replaced with a Vivek Patel. The correction to this chapter is available at https://doi.org/10.1007/978-98133-4176-0_43 D. M. Harwani (B) · V. J. Badheka · V. Patel Department of Mechanical Engineering, School of Technology, Pandit Deendayal Petroleum University, Raisan, Gujarat 382007, India e-mail: [email protected] V. Patel Department of Engineering Science, University West, Trollhättan 46186, Sweden © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021, corrected publication 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_33

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to the final product in less time with less amount of machining. Superplastic forming (SPF) is one such specialist process which is employed in producing thin-walled and complicatedly designed components at high temperatures and low flow stresses [1]. Characterized by low tooling costs and extreme formability, SPF is already in use to fabricate airframes (from aluminum and titanium alloys) and engine components of gas turbines (from nickel alloys) [2]. It also finds applications in aerospace, rail and road transport, medical implants, communication and architecture sectors. Common techniques of SPF are blow forming, hollow cavity forming, diffusion bonding, quick plastic forming and high cycle blow forming [3]. Despite the ability of producing near-to-net-shape unitized parts without use of any joints, SPF has not been commercially popular for many alloys. One reason is its slow forming rates [4]. The other limiting factor is that this metal forming method can be applied only in special materials which have undergone pre-processing for achieving microstructure, consisting of fine grains or dual phases [1]. This paper briefly discusses the concept and pre-requirements for developing superplasticity in metals. An overview of various severe plastic deformation methods to attain ultrafine grains (average grain size of about 1 μm) and nano-sized grains (average grain size of about 10 nm) and subsequent superplastic properties in nonferrous metals has been given. It concludes with the present challenges in the field of SPF and scope for future research studies.

2 Superplasticity The foundation of SPF lies in developing superplastic behavior in materials at elevated temperatures. The capability of any metallic material to get enhanced tensile elongations more than 200% through plastic deformation is called superplasticity [5]. The essence of superplasticity is large permanent deformations before tensile failure. Extremely large elongations of about more than 5000% have been reported in various materials [6]. Superplastically deformed parts exhibit favorable isotropic mechanical properties and extremely good surface finish [7]. The major pre-requisites to induce superplastic features in most of the metals are: • Fine grain size ( 0.3, it can be inferred as the positive sign of superplasticity phenomenon [13]. Efforts have come to the notice in producing superplastic stainless steels, but more attention has been garnered by the advent of superplasticity in non-ferrous metals like Al, Ti, Mg and Ni so as to accomplish the manufacturing of lightweight structures in transportation and aerospace field as monolithic parts [14]. The applications of superplastic components include: • • • •

Producing prosthetic implants [15] Housings of missiles made from SP2004 alloy [16] Aircraft service panel from TiAl6V4 alloy [17] Winglets, engine nacelles, air stairs and engine inlet lip skins for aircraft made from superplastic aluminum by Luxfer Superform, leading manufacturer of USA [18] • Metro and light rail applications [19]

Generally, there are two main categories of techniques for developing ultra-fine grain structure in the non-ferrous metals based on the processing routes, which is the first step toward achieving superplasticity. One is thermo-mechanical processing (TMP), mainly rolling and extrusion and the second category is dynamic recrystallization via severe plastic deformation (SPD). Some other unconventional techniques include consolidation of amorphous or nano-crystalline powder, mechanical alloying and physical vapor deposition (PVD) [6]. The high strength Al 7475 alloy was subjected to thermo-mechanical processing including hot rolling, solution heat treatment and rapid recrystallization in molten salt bath followed by artificial aging and water quenching. These steps helped in reducing the average grain size of the alloy to 10 μm. [20] Similar TMP technique was applied on commercial Al 7075 alloy to obtain grain refinement in the range of 8–14 μm [21]. TMP steps are rigorous and time-consuming and not suitable for modern manufacturing plants having continuous production schedules. This paper mainly discusses the recently trending SPD routes.

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Fig. 1 Schematic of HPT process [27]

3 Severe Plastic Deformation Approaches 3.1 High Pressure Torsion High pressure torsion (HPT) targets for the grain size reduction by both straining and compression. This strategy was employed by Bridgman [22] for the very first time, wherein certain material was subjected to mean hydrostatic pressure up to 50,000 kg/cm2 combined with shearing stresses. As shown in Fig. 1, the material to be deformed is held in between two anvils out of which one is stationary and the other one can rotate. Pressure from the top direction is applied with simultaneous torsion. The dual application of strain and compressive force results in grain size of the order of 200 nm or less [14]. A sample (Al–3%Mg–0.2%Sc) was enclosed in the die and the transverse pressure along with rotational movement was applied, which resulted in the grain size of order of 200 nm [23]. Superplastic elongations of 440% at 0.35 T m were obtained with ultra-fine grain size of about 240 nm in Mg–Li alloy after 200 HPT cycles [24]. Another work for low temperature superplasticity (LTSP) was noted for Al–4Cu– 0.5Zr alloy processed by HPT [25]. Superplastic effect was observed at 623 K for GW94 alloy processed by HPT (16 turns) with the average grain size ~10 nm [26].

3.2 Multi-axial Forging Multi-axial forging (MAF) is a multi-pass forging process in which the specimen to be plastically deformed is rotated by 90º after every pass (as illustrated in Fig. 2) [28]. The consecutive forging in all the directions induces high rate of plastic deformation in the material resulting in fine grain size. In comparison with HPT, this method does not require dies and punches. Weakening of original strong basal texture in WE43 alloy was reported that helped to

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Fig. 2 Schematic of MAF process [31]

attain high elongations of 470% at 375 °C after processing with MAF. [29] Enhanced ductility with excellent strength was obtained by MAF in a Fe3 Al-based intermetallic alloy with average grain size of 2–3 μm after 40 passes when it was heated to 600 °C [30].

3.3 Accumulated Roll Bonding Accumulated roll bonding (ARB) is another SPD technique which is a unique combination of rolling and bonding processes. It was invented by N. Tsuji et al. to overcome the limitations of HPT and ECAP processes [32]. As illustrated in Fig. 3, two sheets are surface treated and then stacked together. Thereafter, these are roll bonded like in conventional rolling process. The rolled material is cut in two halves and the steps are repeated till the ultrafine grain size is achieved. In ARB, the strain after n cycles can be expressed by Eq. (1) [33]. √ 3 t 1 ln(r ), r = 1 − =1− n ε= 2 t0 2

Fig. 3 Schematic of ARB process [36]

(1)

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where t 0 = initial thickness of stacked sheets, t = thickness after roll-bonding and r = reduction in thickness per cycle. More the number of cycles, more will be the accumulated strains in the material, leading to enhanced grain size reduction. The first attempt to induce superplasticity via ARB was for Al 5083 with mean grain size of 10 μm that resulted in about 220% elongations at 473 K [34]. ARB was performed on AZ31 Mg alloy at 300 °C (three repeated cycles) that led to the tensile elongations of about 316% with the average grain size of about 4 μm [35]. The main limitation of this process is the requirement of effective bonding between the sheets which becomes difficult while dealing with high strength alloys.

3.4 Equal Channel Angular Pressing Equal channel angular pressing (ECAP) or equal channel angular extrusion (ECAE) is one of the most researched SPD methods to produce bulk materials with ultra-fine grains [37]. The interesting aspect which makes it different from the conventional extrusion and drawing is that the material undergoes intense plastic strain without any change in its cross-sectional area [14]. The material, in the form of a rod or bar, is pushed through a die inside a channel which later changes abruptly to angle φ, which is mostly an acute angle (as illustrated in Fig. 4). The sample will be subjected to shear when it is forced through the intersection part of the channel [33]. Enhanced ductility with favorable changes in the texture accompanied with grain refinement up to 1 μm of WE43 alloy was reported by adopting ECAP technique

Fig. 4 Schematic of ECAP process [40]

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[38]. Another study noted ultrahigh elongations up to 1000% in commercial Al-1420 alloy with 8-pass ECAP with the final grain size of 1.2 μm [39].

3.5 Friction Stir Processing Friction stir processing (FSP) has gained a lot of popularity as a solid-state technique to obtain fine microstructure in both cast and wrought alloys which lead to enhanced mechanical properties [41]. It is a variant of solid-state welding process friction stir welding (FSW) which consists of a non-consumable rotational tool which is traversed along the material (as illustrated in Fig. 5) [42]. The frictional heat and mechanical stirring of the rotating tool through the workpiece lead to dynamic recrystallization in the region where the tool has passed. This results in fine homogenized equiaxed grains in the stir zone of the material [43, 44]. Friction stir processed AZ91 Mg alloy exhibited the grains of average size of 0.5 μm with the subsequent superplastic elongation of 1251% at strain rate and temperature of 1 × 10−2 /s and 330 °C, respectively [45]. The most recent development to further reduce the heat input during FSP resulting in homogeneously distributed finely sized grains is the novel technique called stationary shoulder FSP (SSFSP) [46–48]. Both FSP and SSFSP methods can be explored further to develop superplastic features in non-ferrous metals [49]. In addition to this, hybrid FSP with active cooling technique may also prove as a good scope for investigating superplastic behavior at lower temperatures [50].

Fig. 5 Schematic of FSP process

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In summary, all the SPD processes can be employed to achieve ultra-fine grained microstructure in order to develop superplasticity, but the grain orientation and distribution as well as the final strength of the microstructure depend upon the number of passes or cycles employed. Initial grain size and texture of the material before SPD processing are also important factors which govern the number of processing passes that will be required to reach the ultra-fine grain size. Thermal stability is very much needed at elevated temperatures for which excessive grain growth during plastic deformation needs to be prohibited [45].

4 Challenges and Future Scope Almost all the above discussed SPD routes are confined to the laboratory experiments and research only. At present, superplastic parts that are complex in design and having low volume of production have been used only in the niche areas like aerospace sector. Automotive field, which strictly depends on high productivity, is yet to commercially implement SPF. Owing to the reason of more time consumption, as these methods require more number of passes to reduce the grain size to the desirable level. To make SPF economical from the industrial viewpoint, high strain rate superplasticity (HSRS) is very appealing. Elongations more than 200% achieved at strain rates above 10−2 /s is coined as HSRS [51]. It will help in increasing the strain rates in less cycle time and thus increasing the productivity. Fine grain size and high deformation temperatures are the major requirements for achieving HSRS [52]. But the industrial sector emphasizes on lower forming temperatures which result in lower material and tooling costs. Hence, it poses a unique challenge to optimize the forming parameters (temperature and strain rate) as well as the processing parameters to obtain superplasticity at higher strain rates and optimum temperatures in order to make SPF more popular in automotive industries. Another challenge is the tendency of formation of inter-granular cavities during hot superplastic deformation [53]. Such cavitations deteriorate the overall properties of the finished part which is undesirable. The temperature and strain rates for superplastic deformation should be optimized in such a way so as to reduce this cavitation tendency. Limited amount of work has been done in the area of superplasticity of nonferrous metals like Cu, Ni and Mg. Composite materials and Zn–Al eutectoids have also caught the attention of the researchers for developing superplasticity. This can become the research prospect for further investigations. Also, more efforts can be directed for simulation and modeling of superplasticity phenomenon so that it can be commercially implemented with the use of techniques like FEM [54]. A very recent study has utilized a combination of ECAE followed by rolling process and achieved 667% elongations with ultra-fine grains in the matrix of AA 5083 sheet [19]. This has clearly opened up new horizons to achieve faster grain

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size reduction and enhanced superplastic behavior with the blend of dissimilar SPD processes.

References 1. Koehler W, Plege B, Sahm KF, Padmapriya N (2016) Metal forming: specialized procedures for the aircraft industry. Ref Module Mater Sci Mater Eng. https://doi.org/10.1016/B978-0-12803581-8.011939-1 2. Mukherjee AK (2006) Superplasticity in metals, ceramics and intermetallics. Mater Sci Technol. https://doi.org/10.1002/9783527603978 3. Bernhart G, Lours P, Cutard V et al (2011) Processes and equipment for superplastic forming of metals. In: Superplastic Forming of advanced metallic materials. Methods & Applications, Metals & Surface Engineering. Woodhead Publishing Ltd., pp 49–71 4. Patel VV, Vora JJ, Gupta K (ed) (2019) Near net shape manufacturing processes. In: Materials forming, machining and tribology. Springer Nature, Switzerland 5. Vol. JIS-H-7007 3 (1995) Glossary of terms used in metallic superplastic materials 6. Mabuchi M, Higashi K (1998) The processing, properties, and applications of high-strain-rate superplastic materials. J Miner Metals Mater Soc 50(6):34–39 7. Dudina DV, Mishra RS, Mukherjee AK (2016) Superplasticity. Mater Sci Technol. https://doi. org/10.1016/B978-0-12-803581-8.02886-1 8. Ma Z, Mishra RS (2005) Friction stir superplasticity for unitized structures. In: Friction stir welding & processing. Elsevier 9. Mishra RS, Bieler TR, Mukherjee AK (1995) Superplasticity in powder metallurgy aluminum alloys and composites. Acta Metall Mater 43(3):877–891 10. Nieh TG, Wadsworth J, Sherby OD (1997) Superplasticity in metals and ceramics. Cambridge University Press. ISBN 0521561051 11. Jain V, Mishra RS, Verma R, Essadiqi E (2013) Superplasticity and microstructural stability in a Mg alloy processed by hot rolling and friction stir processing. Scr Mater 68(7):447–450 12. Ghosh AK (2007) On the measurement of strain-rate sensitivity for deformation mechanism in conventional and ultra-fine grain alloys. Mater Sci Eng A 463(1–2):36–40 13. Raja A, Biswas P, Pancholi V (2018) Effect of layered microstructure on the superplasticity of friction stir processed AZ91 magnesium alloy. Mater Sci Eng A 725:492–502 14. Ridley N (2011) Metals for superplastic forming. In: Giuliano G (ed) Superplastic forming of advanced metallic materials. Methods & Applications. Woodhead Publishing Ltd. 15. Dudina DV, Mishra RS, Mukherjee AK (2016) Superplasticity, Materials Science and Engineering. https://doi.org/10.1016/B978-0-12-803581-8.02886-1 16. Barnes AJ (2001) Industrial applications of superplastic forming: trends & prospects. Mater Sci Forum 357–359:3–16 17. Koehler W, Plege B, Sahm KF, Padmapriya N (2017) Metal forming: specialized procedures for the aircraft industry. Mater Sci Technol. https://doi.org/10.1016/B978-0-12-803581-8.019 39-1 18. LUXFER SUPERFORM Homepage, www.superforming.com. Last accessed 19 Aug 2020 19. Jin H (2017) Improvement of superplasticity in AA5083 by equal channel angular extrusion and rolling. Mater Sci Technol. https://doi.org/10.1080/02670836.2017.1317954 20. Xinggang J, Jianzhong C, Longxiang M (1993) Grain refinement and superplasticity of high strength 7475 aluminium alloy. Mater Sci Technol 9(6), 493–496. https://doi.org/10.1179/mst. 1993.9.6.493 21. Paton NE, Hamilton CH, Wert JA, Mahoney MW (1982) Characterization of fine-grained superplastic aluminum alloys. J Miner Metals Mater Soc (TMS) 34:21–27 22. Bridgman PW (1935) Effects of high shearing stress combined with high hydrostatic pressure. Phys Rev 48(10):825–847

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23. Sakai G, Nakamura K, Horita Z, Langdon TG (2006) Application of high pressure torsion to bulk samples. Mater Sci Forum 503–504:391–398 24. Edalati K, Masuda T, Arita M, Furui M et al (2017) Room-temperature superplasticity in an ultra-fine-grained magnesium alloy. Sci Rep 7(1):1–9 25. Valiev RZ, Korznikov A, Mulyukov R (1993) Structure and properties of ultrafine-grained materials produced by severe plastic deformation. Mater Sci Eng A 168:141–148 26. Alizadeh R, Mahmudi R, Ngan AHW, Huang Y, Langdon TG (2016) Superplasticity of a nanograined Mg-Gd-Y-Zr alloy processed by high-pressure torsion. Mater Sci Eng A 651:786–794 27. Song Y, Wang W, Chen M et al (2017) Ultrafine-grained materials fabrication with high pressure torsion and simulation of plastic deformation inhomogeneous characteristics. In: Cabibbo M (ed) Severe plastic deformation techniques. https://doi.org/10.5772/intechopen.68360 28. Szabó PJ, Bereczki P, Verö B (2011) The effect of multiaxial forging on the grain refinement of low alloyed steel. Periodica Polytechnica 55(1):63–66 29. Kandalam S, Sabat RK, Bibhanshu N, Avadhani GS et al (2017) Superplasticity in high temperature magnesium alloy WE43. Mater Sci Eng A 687:85–92 30. Łyszkowski R, Czujko T, Varin RA (2017) Multi-axial forging of Fe3 Al-base intermetallic alloy and its mechanical properties. J Mater Sci 52:2902–2914 31. Funami K, Noda M (2011) Grain refinement of magnesium alloy by multiaxial alternative forging and hydrogenation treatment. In: Czerwinski F (2011) Magnesium alloys—design, processing and properties. IntechOpen. https://doi.org/10.5772/13189 32. Tsuji N, Saito Y, Lee S, Minamino Y (2003) ARB (Accumulated Roll Bonding) and other new techniques to produce bulk ultrafine grained materials. Adv Eng Mater 5(5):338–344 33. Azushima A, Kopp R, Korhonen A, Yang DY, Micari F et al (2008) Severe plastic deformation (SPD) processes for metals. CIRP Ann—Manuf Technol 57(2):716–735 34. Tsuji N, Shiotsuki K, Utsunomiya H, Saito Y (1999) Low temperature superplasticity of ultrafine grained 5083 aluminium alloy produced by accumulative roll bonding. Mater Sci Forum 304–306:73–78 35. Wang QF, Xiao XP, Hu J (2007) An ultrafine-grained AZ31 magnesium alloy sheet with enhanced superplasticity prepared by accumulative roll bonding, pp 2–7 36. Akbarzadeh A (2011) Nanostructure, texture evolution and mechanical properties of aluminum alloys processed by severe plastic deformation. In: Ahmad Z (ed) Recent trends in processing and degradation of aluminium alloys. https://doi.org/10.5772/18567 37. Lin J, Ren W, Wang Q, Ma L, Chen Y (2014) Influence of grain size and texture on the yield strength of Mg alloys processed by severe plastic deformation. Adv Mater Sci Eng 2014:24–32 38. Martynenko NS, Lukyanova EA, Serebryany VN, Gorshenkov MV et al (2017) Increasing strength and ductility of magnesium alloy WE43 by equal-channel angular pressing. Mater Sci Eng A. https://doi.org/10.1016/j.mesa.2017.12.026 39. Nemoto M, Horita Z, Furukawa M, Langdon TG (1999) Microstructural evolution for superplasticity using equal-channel angular pressing. Mater Sci Forum 304–306:59–66 40. Kunz L (2012) Mechanical properties of copper processed by severe plastic deformation. In: Collini L (ed) Copper alloys—early applications and current performance—enhancing processes. IntechOpen. https://doi.org/10.5772/32634 41. Patel V, Li WY, Vairis A, Badheka VJ (2019) Recent development in friction stir processing as a solid-state grain refinement technique: microstructural evolution and property enhancement. Crit Rev Solid State Mater Sci 44(5):378–426. https://doi.org/10.1080/10408436.2018.149 0251 42. Cavaliere P, Marco PP (2007) Friction stir processing of AM60B magnesium alloy sheets. Mater Sci Eng A 462:393–397 43. Jin Y, Wang K, Wang W, Peng P, Zhou P et al (2019) Microstructure and mechanical properties of AE42 rare earth-containing magnesium alloy prepared by friction stir processing. Mater Characterization 150:52–61 44. Patel V, Li WY, Liu X, Wen Q, Su Y (2019) Through-thickness microstructure and mechanical properties in stationary shoulder friction stir processed AA7075. Mater Sci Technol 35(14):1762–1769

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45. Mohan A, Yuan W, Mishra RS (2013) A High strain rate superplasticity in friction stir processed ultrafine grained Mg–Al–Zn alloys. Mater Sci Eng 562:69–76 46. Patel V, Li W, Xu Y (2018) Stationary shoulder tool in friction stir processing: a novel low heat input tooling system for magnesium alloy. Mater Manuf Process 34(2):1–6 47. Patel V, Li W, Liu X, Wen Q et al (2020) Tailoring grain refinement through thickness in magnesium alloy via stationary shoulder friction stir processing and copper backing plate. Mater Sci Eng A 784:139322 48. Patel V, Li W, Wen Q (2019) Surface analysis of stationary shoulder friction stir processed AZ31B magnesium alloy. Mater Sci Technol 35(5):628–631 49. Patel VV, Badheka VJ, Kumar A (2016) Friction stir processing as a novel technique to achieve superplasticity in aluminum alloys: process variables, variants, and applications. Metallogr Microstruct Anal 5:278–293 50. Patel V, Badheka V, Li W, Akkireddy S (2019) Hybrid friction stir processing with active cooling approach to enhance superplastic behavior of AA7075 aluminum alloy. Arch Civil Mech Eng 19(4):1368–1380. https://doi.org/10.1016/j.acme.2019.08.007 51. Chai F, Zhang D, Li Y, Zhang W (2013) High strain rate superplasticity of a fine-grained AZ91 magnesium alloy prepared by submerged friction stir processing. Mater Sci Eng A 568:40–48 52. Yang Q, Xiao BL, Ma ZY, Chen RS (2011) Achieving high strain rate superplasticity in MgZn-Y-Zr alloy produced by friction stir processing. Scr Mater 65(4):335–338 53. Prabu SB, Padmanabhan KA (2014) Superplasticity in and Superplastic Forming of AluminumLithium Alloys. https://doi.org/10.1016/B978-0-12-401698-9.00008-2 54. Carrino L, Squillace A, Paradiso V, Ciliberto S, Montuori M (2013) Superplastic forming of friction stir processed magnesium alloys for aeronautical applications: a modeling approach. Mater Sci Forum 735:180–191

Design for Retractable Staircase for Buses Kunal Gawhade, Pranav Raj, and PL. Ramkumar

Abstract Demand for efficient public transport has increased over time. Buses are a major part of public transport infrastructure. In India, according to a report by National Sample Survey Office (NSSO), buses on average carry 70 million people daily. This paper proposes designs for retractable staircases in view of the difficulty faced by some commuters (elderly, children, and differently abled) while boarding and deboarding high floor buses to ensure easy accessibility for all. Designs have been developed after identifying and studying the competitors that are already in the market. The selection of optimum design was done by comparing and contrasting the complexity, efficiency, and cost of the concept by the use of Pugh matrix. Keywords Public transport · Retractable staircase · Design · Boarding · Deboarding high floor bus

1 Introduction In Census of 2011, it was recorded that more than 50% of the population had to depend on their own private vehicle, i.e., motorbike, car, jeep, etc., to commute to their destination due to inaccessibility of the public transport [1]. According to report of Ministry of Road Transport and Highway (MoRTH) during 2015–16 in India, average fleet occupancy ratio in the state transport buses was found 69.65% which was 70.74% during 2014–15, and total fleet utilization was recorded 90.4% during 2015–16 [2]. According to survey by Rajamanickam, elderly people face difficulty in moving in and out of the bus due to high floor and step of the bus [3]. Injuries are also reported as elderly people lose their balance while climbing the high bus step or during the pushing and shoving which ensues while they are boarding the bus. Rude behavior of bus staff was seen while boarding of elderly and disabled people due to long time K. Gawhade · P. Raj (B) · PL. Ramkumar Department of Mechanical Engineering, Institute of Infrastructure Technology Research and Management, Ahmedabad, Gujarat, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_34

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taken by them to board the bus [4]. For differently abled people, public transport systems have been inaccessible for a long time, and conditions seem to get no better soon. Pregnant women and women carrying infant faced difficulty while boarding and deboarding buses and required aid of others for the same. High step hinders the movement of normal passenger carrying heavy luggage which often leads to the loss of balance which might lead to injury. These persistent problems of high floor buses have reduced their acceptance as a mode of transport by the above-mentioned sections of society. Suen et al. calls mobility a key for independent living which is a right of every human being and is as important as one’s independence. According to them, mobility involving danger and undignified means is always unacceptable [5]. In India, a large section of the population relies on public transportation for day-to-day journeys due to unaffordability of private vehicles. Most of the Indian population live in rural areas and where the only mode of mass transport is a bus. It was observed in the survey by Rajamanickam that most elderly bus commuters belonged to low income group [3]. Hence, providing accessible transportation methods helps to increase the quality of life especially among the elders and disabled and develops a feeling of freedom [6]. Low floor buses are the recent advancement to enhance the mobility of elderly and disabled people. In these buses, entrances are provided at extremely low heights and have no steps at entrance for easy movement of wheelchair bound travelers and other commuters [7]. It was observed that women carrying their infants and commuters with heavy luggage also preferred low floor bus as the need of external aid required during boarding and deboarding was eliminated. Kneeling buses are the latest development which improves mobility. This bus lowers down to a height on one side by releasing the air from the air suspension which make boarding and deboarding easier for commuters. Air suspension is again filed with air to regain its operating height. This mechanism is controlled by the bus driver through a button on the dashboard. Kneeling buses do not have stairs, and wider doors are present resulting in efficient inflow and outflow of commuters [7]. Standard high floor buses have persistent problem of accessibility due to its high first step. Chassis of high floor bus are at a height above the center of wheel which eliminate the scope of reducing the height of the floor. Limited width of bus is the reason for the steep staircase. According to government guidelines, first step of high floor bus can have maximum height of 400 mm from the ground [8]. Despite of the problems associated with high floor buses, they remain popular as compared to low floor bus and kneeling bus because of their larger seating capacity. High floor buses are easy to maintain in contrast to other alternative bus types which have compact complex system to provide low floor height. High floor buses have a major advantage in the form of high fuel capacity due to high ground clearance which allows transporter to plan long journey and makes them ideal for operating in hilly and rural region where petrol pumps are scarce [9]. According to a global survey of buses, about 68% of the total bus fleet comprises of high floor buses. In some countries like Japan and Finland, more than 90% of the bus fleet are high floor bus in their total bus fleet [10]. Lifespan of a bus is considered to be 12 years on average. Considering the enormous fleet of high floor

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bus, accessibility of buses by all sections of society needs to be improved to provide freedom and mobility to all. To improve accessibility in high floor buses, lift and ramp designs and mechanisms to enhance passenger experience have been developed but the time delay and high installation cost associated with them have negatively impacted their development [7]. These developed systems faced technical problems during operation, and bus crew often refused to use the apparatus to avoid dwell time associated with them. Also, maintenance cost associated with such system increases over the course of their service life [11]. To provide comfortable and safe access to the vehicle, John D Abbott suggested the use of retractable stairs with the help of a hydraulic pneumatic actuating system and parallelogram linkage which extended stairs to provide easy boarding and deboarding [12]. Providing retracting steps in a bus required little investment, and operation was easy and could be operated by anyone. Maintenance involved would be negligible, and minimal dwell time would be associated with such systems. Stairs help to achieve high height in limited width compared to a ramp. Stair mechanisms utilize less space compared to lift systems providing sufficient ground clearance for optimal function of vehicle. Stairs, however, restrain the movement of wheelchairs, but reducing step height will increase the reach of bus. The designs discussed aims at providing a cost-effective retractable staircase system which can be mechanically or electronically driven and will significantly lessen the hardships faced by the children, elderly, and the differently abled people as they board and deboard the bus. The design will smoothen the experience for most commuters and be a small quality of life improvement.

2 Product Development Procedure Product development refers to the collection of all processes required to bring a product to market, from its concept development to making the design as robust as possible. Each industry has its own product development procedure; however, all of them can be characterized by the following three step procedure: 1. Identification of problem/opportunity 2. Generating a concept/solution 3. Implementing the concept/solution. Identification of the problem or opportunity is done via market analysis, understanding customer needs, and studying competitive products present in the market. A concept is developed by product architecture development and functional modeling of the product. Each concept is implemented by robust designing, physical and analytical modeling. These three phases are possible to run in concurrent manner depending upon the product [13].

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2.1 Identification of Opportunity Accessibility to high floor bus in a country like India seem no to get any better any time soon. This type of market demands a low-cost solution to resolve this problem. Any system developed will be required to be compatible with current running fleet of buses with minimal changes to the vehicle, and its operation should not require any professional training. Available products in the market satisfy all conditions except the cost factor. A product consisting fully mechanical component must be able to provide accessibility within the budget. With this insight, we have realized that if our product is to be profitable and disruptive, it must be cheap while also being able to seamlessly integrate as a retrofit in existing buses while following standard norms.

2.2 Concept Generation By studying journals, government norms, and customer needs, concepts were generated through brainstorming the problem which resulted in five possible solution of the problem. The concepts were modeled using Unigraphics NX 12, a PLM software. Designs are based on the standard high floor bus dimension defined by Indian government. Concept 1: In concept 1, the foldable steps are connected to a rod which is attached to the door and the first step. The rod can slide over the edge of the step. This concept utilizes the parallelogram linage to ensure synchronized opening and closing of stairs with the motion of the door. However, the presence of the connecting rod in the mechanism creates a chance of unwanted impact. Additionally, it will also undergo deformation as it will act as a load-bearing component. Concept 1 fulfills the desired output, but its reliability will diminish as its service life increases. Hence, it will have short life span which is undesirable.

Fig. 1 a Orthographic view and b front view of concept 1

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Concept 2: In concept 2, gas springs act as the load-bearing components and the driving force of the motion of the retractable step. To ensure smooth folding of the retractable step, an inversion of a single slider crank mechanism, i.e., Whitworths Quick Return Mechanism, was employed to provide the same. In the mechanism, the slider was connected to the door which provided the requisite input motion in the form of rotation of a slotted link which enabled the folding motion of step. Concept 3: In concept 3, sensors were used to detect the opening and closing of the door. When the door opens, sensors provide signals to a linear actuator which drive a parallelogram linkage to unfold the step. This concept is the most efficient solution to our problem, but components used in this concept are costlier in comparison with those used in other concepts. The delay associated with detection of the opening and closing of the door increase the overall unfolding time of the step.

Fig. 2 Side view of concept 2

Fig. 3 Model of concept 3

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Fig. 4 Model of concept 4

Concept 4: This concept aims to utilize a compact hydraulic pump placed within the luggage compartment which would drive a hydraulic piston. This hydraulic piston would connect to parallelogram linkage to provide unfolding and folding of step. The control of extending the retractable step would either be with the driver or more appropriately with the conductor. The hydraulic pump would default to the case of retracting the staircase when the doors of the bus are closed. Concept 5: In this concept, rather than using an external hydraulic pump, the compressor of the air brakes used in high floor buses will be used to drive the step mechanism. Buses use airbrakes for deceleration and rely on a compressor to provide sufficient air pressure to apply large frictional force using the friction pads. For the concept in discussion, some compressed air would be used from a secondary pressure storage tank to drive a gas piston which would lower the step. The pressure delivery to the gas piston would be controlled by a valve connected at the door of the bus. When the door is closed back, the valve will close, and the pressure will be released to the environment. The secondary pressure tank is used in the emergency brake, and by taking some compressed air from it, we are not affecting the performance of the primary braking system for a negligible difference in performance of the emergency break.

2.3 Selection of Concept Concept selection process aims to gather as much as information and detail of a concept for its evaluation. The Pugh matrix technique has been utilized to determine the most optimum concept to further development. Pugh chart is an efficient tool which helps to select a concept when limited information is available regarding the product. Its flexibility to refine selection criteria with increasing information regarding the product makes it ideal for continuous evaluation of products life cycle [13]. The following parameters have been used to evaluate the viability of the concept:

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Fig. 5 Flowchart of concept 5

1. 2. 3. 4. 5.

Product cost Folding/Unfolding time Ease of operation Compactness Product life.

In the market study, it was determined that if the model were to be available for use in mass transportation system the cost would be the most critical factors. Governments would only apply the suggested design if incorporating the retractable stairs would not eat into the budget allocated toward upgradation or renovation of existing buses in the fleet. This translates to cost factor having significant weight in the Pugh matrix. Similar parallels can be used to explain the decision to provide a large weight to product life. Ease of operation represents another important parameter, the time taken to implement this system should not be so large that the entire operation involved before and after the unfolding of the retractable staircase results in substantial delays and affects the commute of everyone. Such delays could not lead to inculcation of increased animosity toward elderly and children in some regular commuters which could be a cause for increased discomfort especially for the elderly and children over time. The usage of the Pugh matrix has led to the determination of concept 2 as the concept which shall be further developed. Concept 3 was the second best and high very high score in most criteria; however, the additional cost of including the sensors,

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Fig. 6 Orthographic view of the proposed design

regularly calibrating them would translate into increased costs in real-world application. This is the reason for its low score in the cost criteria. If in the future, sensors can be viable, this concept will become the preferred one.

3 Modeling the Solution Our study on the height difference between the first stair and the ground led to the determination of the average height of the first stair to be 400 mm. In concept 2, step height is reduced to 200 mm, as design involved mechanical system installation cost is low and will require minimal maintenance during operation. As system is directly connected to the door, it can be operated by any person with ease. This system provides flexibility to detach door, and system is to provide door opening without unfolding the stairs.

4 Conclusion The above-proposed design aims at utilizing the opportunity to ease and enhance the experience of the children, elderly, and differently abled commuters of buses. The design is aimed to be cheap and simple enough to be easily retrofitted into buses

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Fig. 7 A Detailed view of the inner mechanism of proposed design

forming a part of the public transportation infrastructure. The above-proposed design has been developed after meticulously following the product development process commonly prevalent in industries. The primary benefit of the design is to provide a reduced first step height in high floor buses. This improves the ease of boarding and deboarding of high floor buses (especially for the above-mentioned classes of commuters) which implies that stoppage times will be reduced. The design will reduce the first step height to 200–250 mm which is the average height difference between stairs in most modern buildings. The proposed design when implemented could lead to more comfortable commuting especially for the elderly.

Reference 1. Census of India 2011: Mode of transport 2001–2011 2. Review of the performance of state road transport undertakings for April 2015–March 2016, Government of India Ministry of Road Transport and Highways, Transport Research Wing 3. Manickam R (1995) Mobility of old people. Unpublished thesis, Department of Transport Planning, School of Planning and Architecture, New Delhi 4. Frye A (2013) Disabled and older persons and sustainable urban mobility. Thematic study prepared for Global Report on Human Settlements 5. Ling Suen S, Mitchell CGB (2017) Accessible Transportation and Mobility, Committee on Accessible Transportation and Mobility 6. Shrestha BP, Millonig A, Hounsell NB et al (2017) Review of public transport needs of older people in European context. Population Ageing 10:343–361 7. Wilburt Y, Paul M, Babu Rao G, Abraham G (2016) Conceptual design and analysis of easy lift stairs for elderly and physically challenged passengers. Int. J. Sci. Eng. Res. 7(4) 8. Corrigendum NO. 01, 1st February 2018 to AIS-052 (Rev.1): 2008, Code of practice for bus body design and approval 9. Melaniphy M, Henke C (2008) High-floor buses worth another look. https://www.metro-mag azine.com/10008317/high-floor-buses-worth-another-look?page=2. Last accessed 8 July 2020

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10. Global Bus Survey 2019, https://www.uitp.org/global-bus-survey-2019. Last accessed 9 July 2020 11. Field MJ, Jette AM (2007) The future of disability in America. National Academies Press, Washington, DC, pp 332–335 12. Abbott J (1977) Retractable Transit Coach Step. 4020920 13. Otto K, Wood K, Product design—technique in reverse engineering and new product development. Pearson Publications

Industry 4.0 Technology: Design and Manufacturing of Modular Fixture Pooja Raval, Nirav P. Maniar, Sudhir Thaker, and Pradeep Thanki

Abstract Modular fixtures for component manufacturing are need of current hour in order to boost productivity interest of industries. Varied parts of assorted size and dimensions are to be accurately manufactured which is fulfilled using properly designed modular fixture. Most studied and presented literature focuses on theoretical design of fixtures. This work presents an integral approach for fixture design as well as manufacturing. The component considered in this work is die height platen which is used in plastic injection molding machines. The major operations undertaken are facing and boring which normally requires different set ups. However, the work here presents a modular fixture which proves cost effective as against dedicated fixture. Thus, the work here is setting an example of design for manufacturing. Keywords Modular fixture · Die height platen · Plastic injection molding machine

1 Introduction Injection molding is method to produce variety of plastic products. Machine to perform injection molding consists of pump, barrel with hopper, heater, nozzle, stationary platen, die height platen, tie bar and ejector. Large force is required to inject molten plastic into the die to clamp die parts together. Numerical control P. Raval · N. P. Maniar (B) V. V. P. Engineering College, Virda-Vajdi, Opposite Motel The Village, Kalawad Road, Rajkot, Gujarat 360005, India e-mail: [email protected] P. Raval e-mail: [email protected] S. Thaker · P. Thanki M/S Supra Technology, 51 A Bhaktinagar Industrial Estate, Behind Shaktivan Manufacturers, Rajkot, Gujarat 360002, India e-mail: [email protected] P. Thanki e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_35

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machine tools with proper modular fixture set up offers blend of flexibility and mass production.

2 Related Work Research work on fixture started from 1940. Various manual and handbooks are available giving set of guidelines for fixture design. Illidge and Bright [1] focused on the issues facing the implementation of mass customization; automated flexible fixture system has been designed and manufactured that provided automated setups and setup changeovers, accommodated a large variety of part families and geometries. Fan et al. [2] developed a novel fixture which is reconfigurable and flexible and implemented the design for the aerospace pipelines application. Naidoo and Padayache [3] developed a solution for customized parts with modular fixture and gave the scheduling method in order to recirculate the reconfigurable modular fixture for tailored parts. Yu et al. [4] proposed a design of flexible fixture for the different parts of automotive. This flexible fixture consists of base plate, locating devices along with control devices which can be used for other body parts of automotive with reduced repeating fixture construction cost. Gothwal and Raj [5] proposed conceptual designing of a pneumatically operated flexible fixture that can be used in any manufacturing industry which is dealing in milling and drilling operations. Method to reduce harmful effects due to concentrated loading was developed by Balasuriya et al. [6]. Matezik et al. [7] developed unique solution of design of modular fixture design, which can be applicable for variety of application. Sivasankaran [8] designed and analyzed the modern screw less machine vice using CATIA and ANSYS APDL package. Namdar et al. [9] presented novel meso-scalar modular fixturing system with embedded sensing elements at the conceptual level. Jin et al. [10] integrated modelling method supplying a new way for modular fixture system to be used in heterogeneous environment using object oriented (OO) method. Industry applicable research work of designing and manufacturing modular fixture for widely used industry component i.e. die height platen of plastic injection molding machine is presented in this paper. 3D view of component and 3D assembled view of both set up of fixture are included in relevant section. The work here setting an example of design for manufacturing as fixture is manufactured also. Photograph of manufactured fixture is also included.

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3 Design and Development of Modular Fixture 3.1 Statement of Problem “Design and manufacturing of modular fixture for machining platen of plastic injection molding machine. The major operations undertaken are leg facing, boring, tapping, side milling and back facing. Two set up of fixtures are required to complete all operations.”

3.2 Component Details Die height platen made up of S. G. iron of plastic injection molding machine weighs 540 kg. 3D view of component is shown in Fig. 1. The major operations undertaken in set up I fixture are as under: 1. Mounting leg 2. Making tooling hole for set up II fixture 3. Top and bottom facing The major operations undertaken in set up II fixture are as under. 4. Boring (Stain rod bore, toggle bore and hug arm bore) 5. Facing on all sides 6. Side milling at hug arm bore.

Fig. 1 Component view

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Fig. 2 Set up-I fixture without component

3.3 Design of Fixture Fixtures consist of three primary components: locators, clamps, and a baseplate. The locators accurately and precisely position the workpiece so that repeatability can be achieved; the clamps push the workpiece against the locators to minimize vibration; and the baseplate is the platform to which the locators and clamps are attached. The location and clamping in setup I fixture are achieved by two job locators, resting jacks, and clamp studs. Two job locators are used for locating and orientation, which consist of spring-loaded piston. Resting jacks—four jacks–are used to rest the component. Four clamp studs are used to clamp the component. The clamp assembly consist of resting jack, clamp stud, and clamp support. Dowel pins and M20 bolts are used to locate and clamp the component in set up II fixture. Each M-20 bolt can apply clamping force of 7120 N with torque ranging from 500 to 700 N m. All locators and clamps can be provided with T-slots and adjustable height mechanisms to accommodate variation in part dimensions, eliminating the need of flexible fixtures and thus resulting in cost saving. 3D view of set-up I fixture without component and with component respectively, are shown in Figs. 2 and 3. Figure 4 and 5 show 3D view of set up II fixture and photograph of manufactured fixture, respectively.

4 Conclusions Current fixture technology does not possess the flexibility required for mass customization. Automated flexible fixture system (AFFS) came out with the proof of concept only not as final product. Commercialization of flexible fixture is yet

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Fig. 5 Manufactured fixture

not implemented. Theoretically analyzed design of fixtures for manufacturing automotive parts are proposed by several researchers, but till date very seldom manufacturing of such fixtures are evident. The present work focuses on manufacturing aspect of fixture which not only introduces the design but also suggests a process for its manufacturing and application for the component to be machined. Conventionally, the fixture design process involves lot of deliberations by the designer considering accuracy requirement, high effectiveness, low cost, and most importantly small setup times as fixtures are unequivocally used for high productivity which are achieved by considering a computerized design, the present work utilizes an integral approach of fixture manufacturing keeping in mind the above aspects along with tolerance, stiffness, and machining configurations. A proper approach is suggested in this work which integrates the techniques discussed above. The present industrial scenario demands applications of theoretically proposed research in applicability environment, thereby demanding of utilization of computerized approach integrating several aspects as above. The present work has justified such integrated approach for design along with manufacturing of modular fixture.

References 1. Illidge A, Bright G (2018) An Automated flexible fixture system for mass customization.South Afr J Industrial Eng 29(1): 21–34 2. Fan W, Zheng L, Wang Y (2018) An automated reconfigurable flexible fixture for aerospace pipeline assembly before welding. Int J Adv Manuf Technol https://doi.org/10.1007/s00170018-2120-9 3. Naidoo E, Padayachee J (2018) Scheduling technique for customized parts with modular fixtures in on-demand fixture manufacturing cells. In: IEEE 14th International Conference on Control and Automation 4. Yu K, Wang S, Wang Y, Yang Z (2018) A flexible fixture design method research for similar automotive body parts of different automobiles. Adv Mech Eng 10(2):1–8 5. Gothwal S, Raj T (2018) Conceptual design and development of pneumatically controlled flexible fixture and pallets. Int J Serv Oper Manage 29

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6. Balasuriya BMSCB, Bhanuka HWP, Sampath HRL, Kulasekera AL, Jayaweera ND (2018) An improved fixturing solution for holding complex shaped components. In: Moratuwa engineering research conference 7. Mateic M, Tadic B, Lazarevic M, Misic M, VukelicD (2018) Modelling and simulation of a novel modular fixture for flexible manufacturing system. Int J Simul Model 17 8. Sivasankaran P (2018) Design and analysis of modular fixture for machine vice. Int J Industrial Prod Eng Technol 8:1–6 9. Namdar G, Liu C, Mills J (2014) A reconfigurable modular fixture design for meso-milling. Int J Mechatron Autom 3 10. Jin C, Guolin D, Tao Y, Chen X (2018) Research on integrated modelling method for modular fixture based on OO technology.J Prod Eng

Design and Development of Spoon Bundling Machine Kartik Konkatti and G. D. Bassan

Abstract Packaging machinery is very much important for all packaging operations, involving primary packages as well as distribution packages. This includes many packaging processes which are mainly fabrication, cleaning, filling, sealing, combining, labelling, etc. In the present work, an effort has been made to develop an innovative machine which is fully automated and will stick the wooden ice cream spoons together as per the requirement. With the help of this machine, any number of ice cream spoons can be stick together and the bundles can be prepared. A simple gearbox and stepper motor mechanism used in the machine helps to reduce the labour cost and the time in making the bundles of the spoon. Star wheel, the heart of the machine on which the spoons will be stored in the pockets of the star wheel, and thereafter glue will be applied to these pockets to stick the spoons together. Counting sensor, proximity sensor, storage system, glue mechanism are some important parts of the spoon bundling machine. A heater is used in the glue mechanism to melt the food glue which is mainly named as hot melt glue. Here, in the present work, an effort has been made to develop the machine at the lowest possible manufacturing cost to reduce the overall cost, time and many other factors. Keywords Packaging machinery · Bundles of ice cream wooden spoon · Automation · Star wheel · Glue mechanism · Sensors

1 Introduction Packaging machinery is one of the most important factors used in every department of engineering. Once the product has been manufactured, the problem arises how the product will be packed keeping various factors in mind like attractive look of K. Konkatti (B) · G. D. Bassan Dharmsinh Desai University, Nadiad, GJ 387001, India e-mail: [email protected] G. D. Bassan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_36

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the product, product does not get damaged, etc. So, the packaging of that product in the best possible way is to be optimized. Industrial automation becomes one of the global trends in the field of manufacturing. Packaging process is used in almost every industry as more and more engineering companies are shifting to the automation [1]. Traditionally, packaging design has a subordinate role with respect to the product design and production system designs. Some packaging operations cannot be accomplished without packaging equipment. Various packaging operations can be designed for varying package sizes using PLC [2]. Innovative packaging machines demand a high level of specification. In this present work an effort has been made to develop an innovative machine to make the bundles of the wooden ice cream spoons. Initially, various packaging machinery and their concepts has been studied to get the brief idea about packaging design. Innovative Spoon Bundling Machine will be fully automated machine that will help to reduce the labour cost and time. Packaging also refers to the process of design, evaluation and production of packages. Packaging Machinery is the combination of different types of sensors, pneumatics, various mechanical components, different types of rollers, different types of belts, PLC setup, various electronics devices, compressor etc. Various types of packaging machineries are filling machine, sealing machine, powder filling machine, labelling machine, liquid and paste filling machines etc. The main aim of Spoon Bundling Machine is to make the bundles of the wooden ice cream spoons as per the requirement. Spoon bundling machine consists of storage mechanism, base mechanism, glue mechanism, counting and proximity sensors, star wheel, PLC setup, gear box, stepper motors and the timing belt. Initially, the spoons need to be stored in the storage mechanism of the machine which has the capacity to store 300 spoons at a time. Star wheel is the heart of the spoon bundling machine [3]. Counting Sensor is attached to the exit of the storage mechanism to count the number of spoons. Star wheel will carry these bundles of spoon stored into its pockets to the glue mechanism where glue will be applied and thereafter these glued bundles of spoon will exit the machine.

1.1 Design, Material and Method The entire process of how the machine was developed on the basis of trail and error method. The main aim of the spoon bundling machine is to make the precise bundles of spoon as per the requirement. The Wooden spoons after being manufactured are being stored in the bundles consisting 100–200 spoons in each bundle. This machine will make the use of this 100–200 spoons bundle and make the precise bundles of 6–12 spoons in one bundle. Material used for the entire machine is stainless steel which is best suitable for packaging machines.

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421

1.2 Design of Base Mechanism According to the ergonomics, the average height of the man is 5 ft. As the Spoon Bundling Machine will be operated by the man, by filling the spoon in the storage, the height of the machine is decided as 600 mm. The design of the base of the machine is shown in Fig. 1. Length of the base is 900 mm and width of the base is 600 mm. Now the approximate Length of the Storage Mechanism is 150 mm. Approximate Length of the Star Wheel Mechanism is 400 mm. Approximate Glue Mechanism length is 150 mm. Approximate Length of PLC Setup Mechanism is 150 mm. Now, Total Length of all the mechanism together will be: 150 + 400 + 150 + 150 = 850 mm. Therefore, by considering the above factors of mechanism Base Plate is 900 × 600 mm.

Fig. 1 Base of the machine

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1.3 Design of Star Wheel Star Wheel of the Spoon Bundling Machine can be considered as the heart of this machine. Without this, every other component is of no use. Star Wheel will be operated by stepper motor and the gear box mechanism. Main aim of the Star Wheel is to carry the bundle of the spoon from the storage to glue and then from glue mechanism to the exit of that bundle. As it has been known that Star Wheel will be operated by stepper motor and gear box mechanism its rotation per minute will be very less. As the star wheel has to rotate in terms of pulses provided by the stepper motor its tangential velocity will also be very less [4]. The material selected for the star wheel is aluminum alloy instead of stainless steel. This is because food glue sometimes may fall on the surface of this star wheel which can cause corrosion if stainless steel is used. So, that is the main reason for selecting Aluminum alloy instead of the Stainless Steel. The design of star wheel is shown in Fig. 2. It has been known that the star wheel has to be paused or stop at fixed point for fixed interval of time. So it is assumed that, Tangential Velocity of the Star Wheel will be V = 30 mm/s and Rotation per Minute, N = 1.5 rpm. The calculation of the diameter of the star wheel is done using Eq. 1. V =π×D×

N 60

(1)

So, the diameter of the star wheel i.e. = 382.16 mm. Therefore, the diameter of the star wheel is taken as 400 mm. Below the star wheel a load bearing is placed to bear the load of the star wheel [5].

Fig. 2 Star wheel of the machine

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1.4 Design of Storage Mechanism Storage mechanism is one of the important components of the spoon bundling machine. The spoon bundles of 100–200 spoons will be installed on this storage mechanism. The base of the storage mechanism is shown in Fig. 3. The storage in which the spoons will be stored is shown in Fig. 4. Normally, Storage means simply to store the things or equipment’s or material in a container or in a store room or at any other safe place that we can call as storage. In Spoon Bundling Machine, the main aim of this storage system is to store the bundles of the wooden ice cream spoons in it. There will be a belt drive mechanism which will guide the spoon from this storage to the slots of the star wheel. Height of the storage is 400 mm. Length of the storage is 115 mm. Generally, in one bundle of spoon there are 100–200 spoons in each bundle. These huge bundles of spoon are to be installed in the storage. So according to the availability of the number of spoons in each bundle, the height of the storage is decided i.e. 400 mm As this bundle of spoon will be installed by the man, so as to increase the man’s comfort this height has been decided. Suppose there is the bundle of spoon in which there are total 100 spoons in it. So, the man will easily put two bundles of the spoon at a time. So as a result, the man will not have to repeatedly fill the storage again and again. Thickness of one spoon = 1.5 mm and height of the Storage = 400 mm. Therefore, it can be said that the man can fill at least (400/1.5 = 266.67) 250 spoons at a time. Now, the length of the spoon is 90 mm. And the length of the Storage is 115 mm. From this total length, 90 mm length will be occupied by the

Fig. 3 Base of the storage mechanism

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Fig. 4 Storage mechanism

spoon 11 mm Thickness is occupied by the storage system itself. So, on both the sides 11 mm is being occupied by the storage. So total thickness 11 + 11 = 22 mm And some times during manufacturing of the wooden spoons, length of 3–4 spoons varies from the original length of all the other spoons. Therefore, clearance of 3 mm is given so that the wooden spoons do not get damaged. Therefore, the total length of the storage will be, 90 + 22 + 3 = 115 mm.

2 Design of Glue Mechanism Hot melt glue is used in this glue mechanism of spoon bundling machine. Hot melt glue or hot glue consists of thermoplastic polymers which are initially in the form of granules that are melted and applied as a liquid on the things or parts which are to be stick together. It has one important property that this hot liquid becomes solid again when it gets cooled, resulting in the attachment of the parts on which the melted liquid was applied. The glue mechanism consists of a heater having temperature range of 600 °C. The heater is placed inside the copper pipe because copper has the great tendency for heat conductance. Due to this copper pipe the entire glue tank remains at the constant temperature throughout the surface of the tank. At the bottom of the

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425

Fig. 5 Glue mechanism

tank the brass nozzle is attached from where the liquid glue exits the glue mechanism and gets attached to the bundle of the wooden ice cream spoons [6]. Image of glue mechanism is shown in Fig. 5. The glue tank consists of a heater which will melt the solid glue and copper pipe will conduct the heat throughout the tank at the same temperature. The outer body of the glue tank is made up of stainless steel [6]. An offset of 5 mm is kept between the nozzle and the heater because if the hot melt glue comes in contact with the heater then it may damage the heater. The nozzle is made up of brass due to the good heat conductance property of the brass. The total height of the glue tank is 250 mm and 100 mm internal diameter in which the hot melt glue will be stored. This Heater which is inside the copper pipe is directly connected with the PLC setup through which the temperature of the heater is controlled. Holes of 1 mm are generated on the nozzle through which the glue will exit the tank. The nozzle pipe diameter is of 8 mm. Glue tank has the capacity to store 3 kg of the hot melt glue in it.

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3 Results and Discussion With the help of spoon bundling machine, precise bundles of the wooden ice cream spoon can be easily prepared. PLC setup helps in the temperature control of the heater, and helps for proper and accurate working of the counting sensor and proximity sensors.

3.1 Working and Discussion of the Machine Initially, the spoons will be arranged in the storage mechanism, thereafter the spoon will travel to the star wheel with the help of timing belt and the counting sensor. At the bottom of the storage system there are two rollers attached and there is one timing belt on which the spoons are kept [7]. Roller rotates with the help of the stepper motor attached behind the roller. Star Wheel has total 40 pockets in which the spoons are captured. One 3/2 solenoid operated direction control valve is used to properly arrange the spoons in the pockets of the star wheel. Star Wheel will be operated with the help of gearbox and stepper motor mechanism. Gearbox of ratio 40:1 is used and is attached to the star wheel. Star Wheel has to be paused or stopped after fixed certain degree of rotation for the fix interval of time. So, at the bottom of the star wheel there are bolts inserted at equal interval of the star wheel. Proximity Sensor being kept under the star wheel will detect the bolts and will pause the rotation of the star wheel for the fixed interval of time [8]. When the star wheel gets paused, then the spoons start entering to the pocket of the star wheel. It is completely being monitored and controlled by the PLC setup. Thereafter, the star wheel will rotate and will take these spoons to the glue mechanism where the spoons gets attached together with the help of the hot melted glue. The heater and copper pipe inside the glue tank will take proper care that certain desired temperature is kept constant for the melting of the glue. Thereafter the bundle of the spoon exits the machine and the required number of spoons in the bundle is achieved. Final assembly of machine is shown in Fig. 6. The spoon bundling machine is designed and manufactured successfully on the basis of trial and error method. The design as shown in Fig. 7 has been obtained by several trial and error methods. Before these various designs were prepared which are failed due to some or other reasons. This design is successfully tested and makes bundles of 80 spoons in one minute and is proved experimentally. The sample of the spoon bundled together is shown in Fig. 7.

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Fig. 6 Spoon bundling machine

Fig. 7 Spoons bundled together

3.2 Capacity of One Labour to Make the Bundles of Spoons Now, different calculations are being carried out to know the capacity of the labourers to make the bundles of spoon and the capacity of labourers to make the bundles of

428 Table 1 The table shows the labourers capacity in 1 h to make the bundles of the spoon

Table 2 The table shows the labourers capacity in 6 h to make the bundles of the spoon

K. Konkatti and G. D. Bassan No of persons

No of mins

No of spoon bundles

1

1

8

1

60

480

No of persons

Hours

No of spoon bundles

1

1

480

1

6

2880

spoon in one day was also being carried out. Tables 1 and 2 show the capacity of labourers to make the bundles of spoons in 1 and 6 h (Fig. 8).

Fig. 8 Image of spoon bundling machine

Design and Development of Spoon Bundling Machine Table 3 The table shows the capacity of 100 labourers to make the bundles of the spoon

Table 4 The table shows the average cost of labourers to make the bundles of the spoon

No of persons

429

No of days

No of spoon bundles

1

1

2880

100

1

288,000

100

30

8,640,000

No of persons

No of days

Average cost in rupees

1

1

300

1

30

9000

100

30

900,000

3.3 Capacity of 100 Labour’s to Make the Bundles of Spoons in One Month Initially, the calculation was carried out for only one labour. Now calculating the capacity of one hundred labourers to make the bundles of spoons is shown in Table 3.

3.4 Calculation of Labour Cost After knowing the average capacity of the labourers to make the bundles of spoon, it was important to the amount being spent on the labourers. The average cost of labourers is shown in Table 4.

3.5 Capacity of One Machine to Make the Bundles of Spoons in One Hour Average capacity of the labourers and the labour cost was being calculated. Now, the calculation of machine is being carried out. Average capacity of one machine to make the bundles of spoons is shown in Table 5. Table 5 The table shows the capacity of one machine to make the bundles of the spoon

No of machines

No of mins

No of spoon bundles

1

1

40

1

60

2400

430 Table 6 Capacity of m/c for 8h

Table 7 Capacity of m/c for 24 h

Table 8 Comparison of labourers and machine

K. Konkatti and G. D. Bassan No of Machines

Hours

No of Spoon Bundles

1

1

2400

1

6

14,400

1

8

19,200

No of Machines

Hours

No of Spoon Bundles

1

1

2400

1

24

57,600

No of Machines

No of Days

No of Spoon Bundles

1

1

57,600

5

1

288,000

1

30

1,728,000

5

30

8,640,000

3.6 Capacity of One Machine to Make the Bundles of Spoons in Six Hours Machine is capable of working continuously in three shifts. So the calculation for the capacity of machine according to the shift was carried out which is shown in Tables 6 and 7. Calculation for the capacity of labour, cost of labour, capacity of machine was carried out. Now, the comparison between the labourers and the machine is being carried out which is shown in Table 8. From the above tables, it can be noted that 100 workers in one month can make 8,640,000 bundles of spoon. Whereas, 5 such machines can make 8,640,000 in one month. Only 5 such machines can do the work of 100 workers. In one hour, one person can make 480 bundles whereas, one machine can make 2400 bundles of spoon. In one day, 100 workers can make 288,000 bundles whereas, only 1 machine can make 57,600 bundles. In one month, 100 workers are required to make 8,640,000 bundles whereas, only 5 machines are required to make 8,640,000 bundles.

4 Conclusion It is really very difficult for the ice cream companies to hire the labour and to manually count the number of ice cream spoons and tie a rubber band around it to make the bundle of these spoons as per requirement. So, this innovative spoon bundling

Design and Development of Spoon Bundling Machine

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machine will automatically count the number of spoons and glue it together without any human effort. A person just has to install the spoons in the storage system of the machine and rest all the operations will be performed by the machine itself. With this machine, we can also avoid the use of plastic spoons which will be the great contribution towards the global warming. This is a one-time investment for the ice cream company and it will highly reduce the labour cost and time and was experimentally proved by successful testing of the machine practically.

References 1. Azzi A, Battini D, Persona A, Sgarbossa F (2012) Packaging design: general framework and research agenda. Wiley Online Library 1002-993 2. Algitta AA, Mustafa S, Ibrahim F, Abdalruof N, Yousef M (2015) Automated packaging machine using PLC. Int J Innov Sci Eng Technol 2348-7968 3. Kovara DL (1991) Improved Star Wheel. United States Patent. 5,029,695 4. Ford CP, Stock W, Taute CJ, Merrifield M (1998) Self locating star wheel system for a packaging machine. United States Patent. 5,784,857 5. Bhandari VB (2017) Book on design of machine elements, 4th edn 6. Belanger RA, Kensington NH (2004) Fast response heater for a glue gun. United States Patent. 6,747,251 7. Hisserich CA (1975) Cam shaft belt drive for variable valve timing. United States Patent. 3,888,217 8. Peter WH (1998) Proximity sensor. United States Patent. 5,801,340

Effect of Optimized Slip and Texture Zone on the Performance of Hydrodynamic Journal Bearing Mohammad Arif, Saurabh Kango, Dinesh Kumar Shukla, and Nitin Sharma

Abstract Conventional hydrodynamic bearing material is wettable in nature, and these materials cause high force of friction in small scale micro-electro-mechanical systems. However, selecting any material with non-wettability behavior provides good scope for reduction of high coefficient of friction in MEMS-based applications. Like non-wettability, the micro-scale random or regular surface texturing is also one of the methods to increase the load carrying capacity in MEMS. Therefore, in the present work, the effect of optimize slippage and surface texture zone on one of the mechanical components (hydrodynamic journal bearing) of MEMS device is investigated. The finite difference method with central differencing scheme is used to discretize the generalized Reynolds equation. It is observed from the results that the optimized slip and texture zone has a positive effect on the load carrying capacity and maximum pressure of hydrodynamic journal bearing. Keywords MEMS · Surface texture · Navier no-slip condition · Navier slip condition · Load carrying capacity

Abbreviation B cr R Lz h H h t Ht

dimensionless slip length, (b/cr ) radial clearance bearing radius bearing longitudinal length fluid film thickness dimensionless fluid film thickness (h/cr ) fluid film thickness for cylindrical textures dimensionless fluid film thickness due to cylindrical textures (h t /cr )

M. Arif (B) · S. Kango · D. K. Shukla · N. Sharma Department of Mechanical Engineering, Dr B R Ambedkar National Institute of Technology, Jalandhar, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_37

433

434

b P Pa Pc Pn U N μ α g φ β β x z y θ Z w W Nt θ Nt z γ λ

M. Arif et al.

slip length of fluid pressure atmospheric pressure cavitation pressure dimensionless pressure ((P − Pc )/Pa ) velocity of moving surface number of revolutions per minute dynamic viscosity of lubricants  dimensionless speed 6μU R/cr2 switch function fractional film content bulk modules of fluid dimensionless bulk modules of fluid (β/Pa ) co-ordinate along bearing circumference co-ordinate along bearing length co-ordinate along lubricant film thickness angular co-ordinate along bearing circumference dimensionless co-ordinate along bearing length load carrying capacity dimensionless load carrying capacity (w/Pa R L z ) number of textures along θ direction of bearing umber of textures along Z direction of bearing slip zone coefficient along θ direction of bearing slip zone coefficient along Z direction of bearing.

1 Introduction Micro-electro-mechanical systems (MEMS) have undergone significant development over the last two decades with researchers fabricating a variety of miniaturized devices with dimensions ranging from a couple to a few thousand microns. Many MEMS contain (sliding/rotating) surfaces and thus effective lubrication of these devices is important to reduce friction [1]. The use of wettable surfaces for lubrication purpose in MEMS causes high friction forcer as compared to applied external force. It has been found experimentally [2] that conventional no-slip condition not valid for non-wettable surface. This disagreement with no-slip condition for non-wettable surfaces provides an effective way to reduce friction force in MEMS devices. The work performed by Spikes [3, 4] has shown the advantages of nonwettable surface in MEMS device applications. Fortier et al. [5, 6] used modified Reynolds equation to investigate the effect of slip on slider and journal bearing. They observed significant improvement in load carrying capacity and friction reduction on heterogeneous wettable/non-wettable (slip/no-slip) surfaces. Experimental work performed by Choo et al. [7] also agrees with the result of numerical analysis

Effect of Optimized Slip and Texture Zone …

435

performed on the use of non-wettable surfaces. Wu et al. [8] experimentally showed that the use of slip/no-slip surface effective in producing load carrying capacity during parallel surface condition. There are number of researchers [9–11] who experimentally verify the improvement in bearing performance by use of non-wettable surfaces. Another effective way to improve load carrying capacity and friction in MEMS is use of surface texturing. Recently, many researchers [12–15] use numerical approach to investigate the effect of different types of surface texture on journal bearing performance parameters under steady condition. Their findings show increase in load carrying capacity and decrease in friction force by the use of heterogeneous smooth and texture surface. The previous numerical simulations performed by the number of researchers [12–15] to predict the effect of texture geometrical parameters on the tribological performance of hydrodynamic bearings and provide an excellent set of instructions to optimize texture geometry for the particular application. However, in all the investigations for finite texture journal bearing, the effect of conventional no-slippage surface boundary condition was used. Very few researchers appear to have considered the interplay of surface texturing and slippage effect on short journal bearings [16–18]. The aim of this work is to examine the load carrying capacity and friction force using cylindrical surface texture and non-wettable surface. The role of cavitation on the texture/non-wettable surface also examined. The cavitation models suggested by Elrod [19] and further modified by Khonsari [20] studied for texture and slip/no-slip situation.

2 Mathematical Formulation Figure 1 shows the physical representation of the journal bearing with cylindrical surface texture and slip/no-slip regions. The Navier slip length model was used to consider the effect of non-wettable (slip) region on bearing surface. Figure 2

Fig. 1 Physical representation of journal bearing with cylindrical surface texture and slip/no-slip regions

436

M. Arif et al.

Fig. 2 Computational domain for journal bearing

shows the computation domain of journal bearing used for numerical analysis. The hydrodynamic pressure produced in bearing was obtained with the use of Reynolds’s equation. For incompressible and Newtonian fluid, Reynolds’s equation was derived with neglecting inertia forces. Expressions are given in Eqs. (1) and (2) signify the momentum in x and z directions with the same assumptions as discussed above. dp d2 u = 2 dy μRdθ

(1)

d2 w dp = dy 2 μdz

(2)

Following boundary conditions is used for solving above equations. z = 0, u = U z = 0, w = 0 z = h, u = −b

∂u ∂w z = h, w = −b ∂x ∂z

The modified Reynolds’ equation for non-wettable (slip) surface is shown below:         3b 3b ∂ ∂P ∂P ∂ h3 1 + + h3 1 + ∂x ∂z [h + b] ∂ x [h + b] ∂z    b ∂ 6μU h 1 + = ∂x [h + b]

(3)

Effect of Optimized Slip and Texture Zone …

437

Here, h represents the fluid film thickness value: h = c(1 + ε cos θ ) + h

(4)

Equation (3) is non-dimensionalized by defining the following dimensionless parameters: θ=

z h b 6μU x (P − Pc ) Z= H= B= Pn = α= R L cr cr Pa R Pa



R Cr

2

The non-dimensionalized form of Eq. (3) is:     3B ∂ Pn ∂ 3 H 1+ ∂θ [H + B] ∂θ     3B ∂ Pn ∂ 3 H 1+ + ∂Z [H + B] ∂ Z    B ∂ α H 1+ = ∂θ [H + B]

(5)

To consider the effect of cavitation in bearing, the above equation is further modified by the use of Elrod [19] cavitation algorithm.     3B ∂ ∂φ H3 1 + βg ∂θ ∂θ [H + B]  2     3B R ∂ ∂φ 3 + H 1+ βg Lz ∂ Z ∂Z [H + B]    B ∂ α φH 1 + = ∂θ [H + B]

(6)

where g and ∅ represent the cavitation index and fractional film content. The boundary condition used for the solution of Eq. (6) is shown as below. g(θ, Z ) = 0 φ < 1 g(θ, Z ) = 1 φ ≥ 1 The non-dimensional pressure in form of switch function and fractional film content is defined as: Pn =

(gβ(φ − 1) − Pc ) Pa

(7)

438

M. Arif et al.

Non-dimensional load carrying capacity (W ): 1 2π W =

Pn (θ, Z ) dθ dZ 0

(8)

0

2.1 Computational Procedure For the solution of governing Eqs. (6), the approach adopted by the authors [21] is used here. Gauss–Seidel method is used to calculate the fractional film content (∅) iteratively by using modified algorithm which was proposed by Fesanghary and Khonsari [20] for improving the convergence speed. For reducing the convergence time to compute the value of ∅, Fesanghary and Khonsari [20] introduced the concept of ‘g Factor’. For solution of the current problem, the value of ‘g Factor’ varied between 0 and 0.9. The result obtained from equation was validated with the previous work of Fortier et al. [5] on effect of slip/no-slip condition on journal bearing. The convergence criteria used in the present computation process is as follows:



(∅ik ) I − (∅ik ) I −1

< 10−7 |(∅ik ) I | where I represents number of iterations, i and k represent number of nodes along θ and Z direction. In the present work, the grid size is taken as (223 × 71).

2.2 Validation In order to develop confidence in the results of the proposed model, validations of the numerical results based on the present model have been done using the published results of Fortier and Salant [5] and Kango et al. [15]. Comparison of result has been shown in Fig. 3 and Table 1. Figure 3. presents the comparison of the dimensionless load carrying capacity by the present model, and Fortier et al. [5] for the effect of slip/no-slip boundary condition on smooth journal bearing surface. Table 1 presents the comparison of dimensional load carrying capacity for cylindrical textured journal bearing with the previous work of present author [15]. The results achieved from the proposed model and those of the researchers [5, 15] by using JFO model and the respective boundary conditions of match considerably well.

Effect of Optimized Slip and Texture Zone …

439

Dimensionless load carrying capacity

8 7 6 5 Fortier and Salant [5]

4

Present work

3 2 1 0 0

20

40 60 Dimensionless slip coefficient

80

100

Fig. 3 Comparison of load carrying capacity with the work of Fortier and Salant [5]

Table 1 Comparison of performance parameters with spherical textured journal bearing [D = 0.04 m,

Lz D

= 1, cr = 50 µm, η = 0.08Pa.s, r x = 0.003 m, r z = 0.003 m, r y = 20 µm, ε = 0.3]

Input parameter

Result from paper [15]

Present results

Load carrying capacity (N)

Friction coefficient (μ)

Load carrying capacity (W )

Friction coefficient (μ)

Smooth surface

1316

0.0163

1310

0.0165

Partial texture (0°–180°) N tθ = 7

1281

0.0152

1284

0.0153

Partial texture (180°–360°) N tθ = 7

1238

0.0164

1261

0.0169

Full textured(0°–360°) N tθ = 14

1131

0.0161

1132

0.0162

3 Results and Discussion Kango et al. [15] investigated the influence of the spherical surface texture on a journal bearing and found that the partial surface texturing improves the performance characteristics of bearing at low eccentricity ratio. In the present work, similar case will be investigated with cylinder shape surface textures and additional use of heterogeneous slip/no-slip boundary condition. The value of dimensionless slip length (B) for the present case has taken from the experiment study of Watanabe et al. [2] is taken as 0.5. Figure 4 represents the dimensionless lubricant film thickness for cylindrical textured bearing surface. The optimum dimension of slip region suggested by Fortier and Salant [5] has been used for the present investigation. The three-dimensional pressure distribution for the smooth and cylindrical textured surface with and without using the concept of slip is shown in Fig. 5a–d. It is clearly observed from Fig. 5.

440

M. Arif et al.

Fig. 4 Film thickness for cylindrical textured surface (ε = 0.3, cr = 50 µm, Nt θ = 5, Nt z = 4, L z /D = 1, N = 1500 rpm, L z = 0.04 m, R = 0.02 m, rx = 0.003 m, rz = 0.003 m, ry = 20 µm)

(a) Pressure distribution for smooth surface without slip

(c) Pressure distribution for textured surface without slip

(b) Pressure distribution for smooth surface with slip

(d) Pressure distribution for textured surface with slip

Fig. 5 3D plots of pressure distribution for smooth/textured surface with and without slip (ε = 0.3, cr = 50 µm, Nt θ = 5, Nt z = 4, L z /D = 1, N = 1500 rpm, L z = 0.04 m, R = 0.02 m, r x = 0.003 m, r z = 0.003 m, r y = 20 µm)

Effect of Optimized Slip and Texture Zone …

(a) Dimensionless lubricant pressure

441

(b) Dimensionless load carrying capacity

Fig. 6 Comparison of performance parameters for all four cases (ε = 0.3, cr = 50 µm, Nt θ = 5, Nt z = 4, L z /D = 1, N = 1500 rpm, L z = 0.04 m, R = 0.02 m, r x = 0.003 m, r z = 0.003 m, r y = 20 µm)

that there is a significant improvement in the magnitude of maximum pressure in smooth and textured bearing with slip as compared with smooth case. Figure 6 shows the comparison of circumferential pressure variation for smooth/textured surface with and without slip effect consideration. There is variation in pressure distribution come by introducing cylindrical surface texture on bearing surface without using the concept of slip. However, the variation becomes significant for slip region on smooth and textured surface. The comparison of load carrying capacity for all four cases is presented in Fig. 6b. It is depicted from Fig. 6b that individual concept of slip and surface texturing on hydrodynamic journal bearing improves its performance characteristics; but in small manner. However, combined effect (surface texturing and slip) is significantly enhanced the performance of hydrodynamic journal bearing for mentioned set of initial conditions.

4 Conclusion This study demonstrates the benefit of a well-chosen slip/no-slip surface pattern and cylindrical surface texturing on hydrodynamic journal bearing performance. The result from the current work suggests us that the combine use of slip boundary condition and surface texturing is an effective way to increase the load carrying capacity and reduce the negative pressure zone or cavitation zone by significant amount.

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References 1. Bhushan B (2001) Tribology on the macroscale to nanoscale of microelectromechanical system materials: review. Proc Inst Mech Eng Part J: J Eng Tribol 215(1):1–18 2. Watanabe K, Udagawa Y, Udagawa H (1999) Drag reduction of Newtonian fluid in a circular pipe with a highly water-repellent wall. J Fluid Mech 381:225–238 3. Spikes HA (2003) The half-wetted bearing. Part 2: potential application in low load contacts. Proc Inst Mech Eng Part J: J Eng Tribol 217(1):15–26 4. Spikes HA (2003) The half-wetted bearing. Part 1: extended Reynolds equation. Proc Inst Mech Eng Part J: J Eng Tribol 217(1):1–14 5. Fortier AE, Salant RF (2005) Numerical analysis of a journal bearing with a heterogeneous slip/no-slip surface. J Tribol 127(4):820–825 6. Salant RF, Fortier AE (2004) Numerical analysis of a slider bearing with a heterogeneous slip/no-slip surface. Tribol Trans 47(3):328–334 7. Choo JH, Glovnea RP, Forrest AK, Spikes HA (2007) A low friction bearing based on liquid slip at the wall. J Tribol 129(3):611–620 8. Wu Z, Zeng L, Chen K, Chen J, Zhang Y (2019) Experiments on laminar flow between parallel plates with a heterogeneous slip/no-slip surface. Tribol Trans (just-accepted) 1–15 9. Choo JH, Spikes HA, Ratoi M, Glovnea R, Forrest A (2007) Friction reduction in low-load hydrodynamic lubrication with a hydrophobic surface. Tribol Int 40(2):154–159 10. Liu CL, Guo F, Wong PL, Li XM (2020) Tribological behaviour of surfaces with stepped wettability under limited lubricant supply. Tribol Int 141:105880 11. Xie Z, Rao ZS, Liu L, Chen R (2016) Theoretical and experimental research on the friction coefficient of water lubricated bearing with consideration of wall slip effects. Mech Industry 17(1):106 12. Tala-Ighil N, Maspeyrot P, Fillon M, Bounif A (2007) Effects of surface texture on journalbearing characteristics under steady-state operating conditions. Proc Inst Mech Eng Part J: J Eng Tribol 221(6):623–633 13. Kango S, Singh D, Sharma RK (2012) Numerical investigation on the influence of surface texture on the performance of hydrodynamic journal bearing. Meccanica 47(2):469–482 14. Manser B, Belaidi I, Hamrani A, Khelladi S, Bakir F (2020) Texture shape effects on hydrodynamic journal bearing performances using mass-conserving numerical approach. Tribol Mater Surf Interfaces 14(1):33–50 15. Kango S, Sharma RK, Pandey RK (2014) Thermal analysis of microtextured journal bearing using non-Newtonian rheology of lubricant and JFO boundary conditions. Tribol Int 69:19–29 16. Rao TVVLN, Rani AMA, Nagarajan T, Hashim FM (2012) Analysis of slider and journal bearing using partially textured slip surface. Tribol Int 56:121–128 17. Tauviqirrahman M, Ismail R, Jamari J, Schipper DJ (2013) Combined effect of texturing and boundary slippage in lubricated sliding contacts. Tribol Int 66:274–281 18. Kalavathi GK, Dinesh PA, Gururajan K (2016) Influence of roughness on porous finite journal bearin with heterogeneous slip/no-slip surface. Tribol Int 102:174–181 19. Elrod HG (1981) A cavitation algorithm. J Lubr Technol 103(3):350–354 20. Fesanghary M, Khonsari MM (2011) A modification of the switch function in the Elrod cavitation algorithm. J Tribol 133(2):024501 21. Vijayaraghavan D, Keith Jr TG (1990) An efficient, robust, and time accurate numerical scheme applied to a cavitation algorithm. J Tribol 112(1)

Structural Analysis, Design, and Implementation of Safety Access to High Pressure Helium Gas Storage Vessels at IPR Rajiv Sharma and Vipul Tanna

Abstract There are six numbers of helium gas high pressure vessels installed of gas storage for operation of Steady State Superconducting Tokamak (SST-1). In order to comply with the requirement of the Chief Controller of Explosive (CCOE), Nagpur, it is mandatory requirement that vessels needs to be regularly and periodically tested for hydraulic pressure and inspection under Static and Mobile Pressure Vessel (Unfired) SMPV (U) rule 19. Apart from hydro test, every year safety valves which are installed on the top of the vessel also have to qualify the performance test under Rule 18. To carry out these mandatory tests, cryo division crew members have to go along with instruments to the middle and top of the vessels for regular and breakdown maintenance purpose for helium leak testing, pressure testing, safety valve, rupture disk, etc. Inbuilt monkey straight ladder was used for climbing to vessels. In order to get the operation license approval and renewal of the operation of these vessels at IPR, there is a need of new spiral ladder for ease of climbing-up and descending of vessels. A design, fabrication, installation, and testing has been done as per Petroleum and Explosives Safety Organization (PESO) norms with prior approval of design drawing. This spiral ladder and joint platform structure which facilitate movement of personnel on to any one of the four vessels by a single spiral ladder was designed, fabricated, and installed. The technical challenges were the installation work at 13 meter height, heavy weight of structure, prickling heat, and assembly with existing structure of vessels. In this paper, the innovation solution, design, fabrication, installation, and testing of structure will be presented. Keywords Pressure vessels · Maintenance · Access · Platform metal structure

R. Sharma (B) · V. Tanna Institute for Plasma Research, Near Indira Bridge, Bhat, Gandhinagar, Gujarat 382428, India e-mail: [email protected] V. Tanna Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai 400085, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_38

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1 Introduction For operation of SST-1 superconducting magnet machine, these helium pressure vessels store the helium gas at pressure at 150 bar (g) and 14 bar (g), respectively. Out of these six vessels, four numbers of medium pressure vessels are installed at 2.8 meter diameter and 13 m height as shown in Fig. 1. Regular operation and breakdown maintenance of the vessels are being used by the inbuilt monkey type straight ladder. This ladder is fabricated by a round pipe on which one has to hold the ladder’s pipe to go on the top of the vessels. Considering the safety aspects of manpower and to protect from falling down during climbing by slipping of legs, upgraded structure of spiral ladder and joint platform for ease of access and movement of personnel on the vessels has been designed, fabricated and installed as shown in Fig. 2.

Fig. 1 Helium high pressure vessels

Fig. 2 Pressure vessels with access structure

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2 Technical Requirement of Structure Fabrication During the last periodic hydrostatic test of vessels as per SMPV (U) Rule 19, CCOE has recommended this facility incorporation on the vessels. Conceptual design approval was taken from CCOE, Nagpur before the work commences. The main purpose was to build this structure to the access to all four numbers of medium pressure (MP) vessels by a single ladder. The structure consists of two part (i) spiral ladder and (ii) joint bridge type platform, which were mechanically connected to the existing extended platform at top of all vessels with side pipe railing support. The following are the technical needs and constraints of fabricated structure; fabrication and installation are summarized. (i) The spiral ladder will be installed adjacent to center of all vessels by a distance of 3–4 m as per the CCOE Rule 33 of SMPV (U) Rules, l98l. (ii) The height of the spiral ladder is to be 13 m from the ground; it should match with vessels top platform plane. (iii) No welding to be done on any vessels elements with fabricated structure. (iv) To support the ladder to prevent and mitigate the cantilever aspects, an existing cleat of pressure vessels can be used for support welding. (v) The ladder should be designed to carry maximum of two person load nearly 300 kg and checked for failure due to wind load. (vi) Restriction of extra support provision of the platform structure on the ground level as per the CCOE norms in the vessels premises.

3 Design Parameters and Boundary Conditions for Structure Figure 3 display the top view of vessels and the bridge type platform which is supported and welded over the I-Beam with chequred plate along with the angle beam welded at bottom to prevent bending of platform in width direction. From one vessel to other vessel, the person can easily go to all the vessels and get down from the spiral ladder. The design criteria and parameters of each elements of structure are summarized in Table 1.

4 Fabrication and Installation Procedure All the elements of the structure are separately fabricated. The foundation plate was placed at the required spot levelling with the pressure vessels in the reinforced

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Fig. 3 Schematic top view of platform on the vessels

cement concrete (RCC) plinth and grounded with foundation bolts. The center pipe with welded treads over it fixed and welded to the foundation plate forms a spiral ladder. The platform structure comprises of bridge type structure which joined with existing inbuilt extended platform of vessels. A common platform is a way to all four vessels assembled with spiral ladder top plate. Railing piping and angle support is provided up to appropriate height in spiral ladder and common platform structure for ease and safety of working personnel. The cantilever effect mitigated of spiral ladder structure by installation of the stiffener supports in form of C-channel and angle to the center pipe of ladder. Due to working environment in open atmosphere and rainy seasonal aspects, mild steel structure of grade 2062 with hot dipped galvanizing ENI 461 (50–60µ) coating was applied. The foundation of structure and elements lifting and assembly of structure by crane are shown in Figs. 4 and 5 respectively.

5 Mechanical Analytical Analysis of Structure The mechanical analysis [5] of each elements of structure has been carried out for optimization of material, safe loading, failure aspects and environmental effects.

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Table 1 Structure design and boundary parameters Element of structure

Material used and dimension

Formula/Standards used

Boundary condition

Spiral Ladder Rise Headroom Hand Rail Railing Height Stairs tread loading

Central pipe [1]: IS 3589, 8 × 8 mm thk Galvanized mild steel Tread: IS-2062 Gr. A Chequred plate: ASTM A-5725, 6 mm thickness 160–220 mm >2000 mm 42 mm diameter 1100 mm 3 kN/m2 distributed load or a point load of 3.0 kN

2×H+W= 580–640 H: step height W: Width of step

Centre pipe: cantilever criteria, bending and shear due to moment and forces acts on carry about 300 kg load Maximum moment of 3 kNm acting at 3 m distance each Analyzed for wind loading Treads: Simply supported beam

Foundation

Material: RCC Depth: 0.9 m Minimum depth of foundation as per IS 1080–1982 is 500 mm from Ground Level

Rankine’s theory Sand strength = 18 Minimum depth of Ton/m2 at 1.5 m depth foundation = p/w (1-sin  /1 + sin ) 2 Where p = gross bearing capacity, w = density of soil,  = angle of response of soil

Earthquake loading [3]

Height of spiral ladder structure: 12 m

IBC 2003 simplified analysis in accordance with Section 1617.5 structures under Seismic group 1

Construction not exceeding three stories in height, this limitation ruled out the earthquake loading

Bridge type plaform structure [2]

I-Beam, Chequred plate and Angle beam: IS 2002-2011 Gr. E 250A Start bridge platform: 3.6 m length × 1.0 m wide Joining bridge platform: 4.6 m length × 1.0 m wide

Permissible bending stress = 0.8 × Yield stress of material (As per BS 5950-1:2000 Clause 4.3.8)

Condition for safe structure: Maximum Bending stress < permissible bending stress Allowable deflection (mm) [As per BS 5950-1:2000] = Length (mm)/ 240

The following formulas has been applied for calculation in mechanical analysis of structure displayed in below equations numbered Bending stress = Max. bending moment (Nmm)/Section modulus(mm) Deflection(Simply supported, end fixed, uniformly distributed load)

(1)

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Fig. 4 Foundation of spiral ladder

Fig. 5 Lifting of platform structure

  = 5 × W × L 4 / (384 × E × I )

(2)

Deflection(simply supported, end fixed, point load   = W × L 3 /(198 × E × I )

(3)

Permissible deflection = L(mm)/240 mmas per BS 5950−1 : 2000

(4)

Permissible bending stress of material = 0.8 × yield strength of the material as per BS 5950−1 : 2000 Clause 4.3.8) (5)

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Wind force F = A × P × cd,

449

(6)

[4] where, A = Projected area, P = Wind pressure, cd = Drag coefficient, and UDL (Uniformly distributed load acting on central pipe).

5.1 Spiral Ladder As per the vessels height the stair head room were optimized to 12 m and 2 m diameter. The length of tread is 1 m which is sufficient of human to stand and width is about 260 mm as per standard 2 × H + B = 540 to 680. The total number of steps is optimized to 60 by applying the standard height between treads which is 200 mm.

5.2 Central Pipe As shown in Fig. 6 the central pipe is fixed in the ground and the upper portion is welded with the bridge it forms a fixed beam condition with the following condition applied for central pipe: (a) Maximum bending moment for case of 3 kN/m acting at 3 m distance. (b) If the pipe is considered as cantilever, then maximum bending moment. (c) The pipe is simply supported and checked for wind load to withstand bending moment.

Fig. 6 Central pipe of ladder

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(d) Maximum bending moment acting of pipe from the shear force and bending moment diagram. (e) Central pipe of selected dimension was checked for maximum capacity of load bearing that can carry to know the condition of failure. (g) Checking for thickness of centre pipe of IS 3589 mild steel, yield stress = 310 MPa, E = 201 GPa, acceptable deflection d = L/240 = 12,000/240 = 50 mm by taking maximum weight of 300 kg acting on the pipe. Since 8 inch, 8 mm thickness central pipe have sufficient moment of inertia to resist bending, it is optimized and preferred to select. (h) By applying maximum moment of 3 kNm acting at 3 m distance, length of pipe L = 12 m. By shear force and bending moment diagram, maximum moment of 12 kNm acts at the base portion, bending stress = 12 × 100 × 1000/Section modulus 230,369.2 = 52.0 MPa from Eq. 1. (i) Since the stair case is fixed with bridge platform at the top, the central pipe is considered simply supported. Here, A = 12 × 0.2032 = 2.4384 m2 , wind pressure P = 0.613 × (V 2 ) N/m2 , where V = speed of wind = 35 m/s, P = 750.9 N/m2 [4]. Drag coefficient for long cylindrical tube is taken 1.2. Therefore, Max. Wind force F (or W ) = 2.19 kN calculated from Eq. 6 (maximum design force of 3 kN). By shear force and bending moment diagram, maximum moment of 54 kNm acts at the base portion, bending stress = 54 × 100 × 1000/Section modulus 230,369.2 = 234.0 MPa < 248 MPa of permissible bending stress of material from Eq. 5, hence the structure is safe.

5.3 Tread Design Method and Calculation The tread as shown in Fig. 7 is designed with its cross section welded with angle

Fig. 7 Treads (Chequered plate) of spiral ladder

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Fig. 8 Jointing bridge platform

beam. The maximum bending moment is acting at maximum 300 kg load calculated by shear force diagram and bending moment diagram. The angle beam of dimension 40 × 40 × 6 mm (ISA 4040), 6 mm thick of 1m length and the chequered plate are checked for bending stress that will act on it due to 300 kg load and compared with the yield stress and deflection of the material. Since the tread will be supported at both the end, considering it as simply supported beam, checking for two conditions (a) uniformly distributed load (UDL) and (b) point load. From shear force and bending moment diagram, we can see that maximum moment bending be 0.38 kNm. Bending stress (I-beam): = (0.38 × 1000 × 1000)/5289.94 = 71.83 MPa is under permissible bending stress of 220 MPa from Eq. 5; hence, the structure is safe.

5.4 Platform Bridge Type Structure The platform bridge as shown in Fig. 8 is fabricated with chequered plate with Ibeam on both sides and angle beam to avoid width-wise bending. Thus the bridge forms simply supported structure with fixed end. Length and width-wise condition for maximum load case of 300 kg/m the maximum bending moment from SF and BM diagram will be identified and checked for maximum bending stress on I-beam and chequered plate and compare it with the permissible bending stress of the material. Three types of platforms namely, start bridge which starts from the top of the stair ladder to the vessels extended platform, vessels existing extended platforms and joining platform structure which bridges to the all vessels and start platforms.

6 Analysis of Failure Condition of Different Elements of Structure and Results The failure condition analysis of every element of complete structure was carried out for various uniformly distributed loads and point loads. The maximum bending moment and permissible bending stress factor were considered for safe loading of

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Bending Stress (MPa)

structure elements presented in Figs. 9, 10 and 11 respectively. The analysis and conclusive test results are presented in Table 2. Figure 9 represents the bending stress and deflection in varying load condition of selected central pipe of structure. The bending moment and section modulus were calculated and compared with permissible bending stress and deflection taking yield stress of material account. Table 2 shows the safe limit of bending stress 234 MPa of central pipe which is under permissible limit of 248 MPa at 3 kN/m load. 500 400 300 200 100 0

Bending Stress MPa v/s UD Load KN/m

3

4 UDL kN/m

5

Bending Stress (MPa)

Fig. 9 Bending stress of various load of central pipe 350 300 250 200 150 100 50 0

Bending Stress MPa v/s UD Load (kN/m) Bending Stress MPa v/s Point load (kN)

3

4

5

6

7

UDL Load (kN/m) and Point Load (kN)

Fig. 10 Bending stress at various load of spiral ladder tread

Bending Stress MPa

300 250

Bending Stress MPa v/s Point Load kN

200 150 100 50 0 3kN

4kN

5kN

6kN

7kN

8kN

9kN 10kN 11kN 12kN 13kN

Point Load (kN)

Fig. 11 Bending stress at various loads of vessels joining platform bridge structure

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Table 2 Analysis and conclusive tests result of complete structure Structure

Permissible bending stress (MPa)

Permissible deflection (mm)

Central Pipe

248

Calculated bending stress (MPa)

Calculated deflection (mm)

Loading condition UDL (3 kN/m) and point load 3 kN All the values found in an acceptable limit, hence the design of structure is safe

50

234.4

34.4

Tread of ladder 220

4.16

141.7

0.05

Starting bridge 200 3.6 m length × 1 m width

15.1

120.2

1.90

Pressure vessel 200 bridge 2.1 m length × 1 m width

8.75

26.7

0.212

Joining bridge platform 4.6 m length × 1 m width

19.1

128.6

13.9

200

Similarly, Fig. 10 represents the bending stress and deflection in varying uniform and point load condition of tread of spiral ladder. The tread structure bending stress found 141 MPa which is safer than 220 MPa permissible bending stress at 300 kg loading. Figure 11 represents the joining platform structure, analysis results shows that this structure can carry maximum of 400 kg per meter in case of UDL while in point load of about 1 ton without failure. The analysis was performed in varying load condition to check and confirm for safe permissible bending and deflection condition. All elements of fabricated structure, namely, central pipe, tread, chequered plate, I-beam, and angle beam have been tested for chemical and mechanical test as per standards ASTM E 415-2017 and IS 1608-2018 respectively from government laboratory.

7 Non-destructive Test The dye penetrant test (DPT) was selected of its excellent features of high sensitivity of detecting small discontinuities, rapid inspection of large areas and volumes, and complex shapes and indication of defects on surfaces directly. The procedure for dye penetrant testing comprises of following steps: (i) pre-cleaning, (ii) penetrant application, (iii) removal of excess penetrant, (iv) application of developer, and (v) inspection. The defects will be marked by a deep red indication in line or dotted line marks a crack, lap, forging burst, or cold shut. Porosity, shrinkage, lack of bond, and leaks will appear as dots or local areas of color. The DPT was performed as per standard ASTM E 165 to each part to check any flaw, minor cracks, or defect due to welding as shown in Fig. 12a–c. The DPT was performed by ASNT level 2 indenter

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(a) Chequred plate

(b) Central pipe

(c) Treads of ladder

Fig. 12 Dye penetration test of elements of structure

by government approved laboratory.

8 Technical Challenges and Experience It was difficult task to get the approval from CCOE of installation of spiral ladder and joint platform bridge type structure for renewal of license to operate the high pressure storage vessels. At 13 m height, installation, lifting of heavy elements of structure by crane, welding of structure, painting and assembly were the challenges encountered. As per the CCOE norms, the restriction of welding to vessels elements and installation of supports in vessels premises were the main technical challenge to overcome the bending and cantilever aspects of structure.

9 Result and Discussion This CCOE approved spiral ladder and joint platform structure has been designed; installed at IPR site which facilitated the movement of working personnel to any one of the four vessels by a single spiral ladder. The result shows that the structure is capable of total load of 300 kg on the vessels. Each elements of structure design was acceptable under failure condition. No cantilever and budging effect, bending on chequered plate were observed. The upgraded fabricated structure has been validated practically during our routine maintenance activities and is also very useful for the periodic hydrostatic testing of vessels where the movement on the vessels is frequent to carry out the tasks. The objective of this work has been fulfilled by facilitating a safe working environment to manpower. Acknowledgements The author is very thankful to M/s Round Tech Co., Ahmedabad for completion of fabrication, installation, and assembly of the complete structure at IPR site in dedicated

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manner and endless efforts. The author also acknowledges to civil section and safety division IPR for the structure RCC foundation task and safety guidelines and measures respectively.

References 1. Ibrahim AM, Radwan, TH, Ibrahim, SA, Abdelrahim K (2020) Experimental investigation of bolted hollow section splices using unstiffened circular end plate. J Constr Steel Res 174:1–14 (2020) 2. Skoglund O, Leander J, Karoumi R (2020) Optimizing the steel girders in a high strength steel composite bridge. Elsevier Eng Struct 221:3–10 3. Kang Y-T, Chen X-C-K (2020) Experimental study of an earth quake-resilient prefabricated opening-web steel channel beam-to-column joint with flange cover plates. Elsevier Eng Struct 221:1–17 4. Kim JH, Taghi M, Elaina M, Sutley J, Chowdhury A, Dao TN (2020) Observations and analysis of wind pressures on the floor underside of elevated buildings. Elsevier Eng Struct 221:1–17 (2020) 5. Rethaliya RP (2019) Mechanics of solid book. Atul prakashan, Gujarat

Design and Analysis of Circular and Square Arm for an Articulated Robot Keval Bhavsar, Dharmik Gohel, and Jaimin Panchal

Abstract This paper presents the design and analysis of an intellectual model of a robotic arm. The principal objective is to identify the material and cross section of the robotic arm. In this project by using CREO, two different cross sections of an articulated robotic arm with three-axis rotation, i.e., three degrees of freedom (3-DOF), will be created. One will be a circular arm robot, and another will be a square-shaped arm robot. And both the cross sections will be analyzed with boundary conditions in ANSYS. The material for the analysis will be stainless steel, kevlar epoxy, and carbon epoxy. The forward kinematics of the robot is done using the DH parameters. Also, inverse kinematics is shown in this paper. Keywords Robot · Articulated robot · Circular arm · Square arm · 3-DOF · DH parameter · Forward kinematics · Inverse kinematics · Steel · Kevlar epoxy · Carbon epoxy

1 Introduction An industrial robot is a reprogrammable, multifunctional controller intended to move materials, parts, apparatuses or extraordinary gadgets through factor modified movements for the exhibition of an assortment of undertakings. An articulated robot is a robot with only rotary joints (R-R-R configuration). They can have a basic two-jointed structure to frameworks with ten or more rotating joints. The design of the arms is made in “Creo 5.0” and analyzed in “ANSYS 2019 R3.” The forward kinematics of the robot is carried out using Denavit–Hartenberg parameters. The inverse kinematics model is calculated from the forward kinematics. There will be three motors to control the joints. As it is an articulated robot, it will be having only revolute joints. In this design, there will be three rotating joints that is an R-R-R configuration. The objective is to find the optimum material and cross sections. The cross K. Bhavsar (B) · D. Gohel · J. Panchal Pandit Deendayal Petroleum University, Gandhinagar, Gujarat, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_39

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section analyzed will be a circular section and a square section. Also, the optimum material will be decided from steel, kevlar epoxy, and carbon epoxy [1].

2 Literature Review Jinyi Lee et al. While aluminum structures are commonly used for robot due to their high strength, aluminum ends are prone to breakage due to the low fatigue limit and low vibration restraining of aluminum assemblies under repetitive feet impact loads. On the other hand, in addition to having a much higher common fatigue cap, carbon/epoxy composites also have a higher surface damping than aluminium [2]. Kurt E. Clothier and Ying Shang, this literature presents a geometric method to solve the uncertain joint angles required to position a robotic arm autonomously. Using basic trigonometry in robotic arm modeling, excess and complex mathematical methods are reduced. This modeling and examination method is tested with a five degree of freedom arm mounted on an iRobot Create a mobile platform with a gripperstyle end effector [3]. Mustafa Bugday and Mehmet Karali, Projected torque increases in industrial robots, depending on the length of the extended reach and the payload. It includes a choice of powerful engines on the second axis in particular. When arm stiffness decreases as the anticipated positioning precision increases, fewer elastic materials are used [4]. K.K. Herbert Yeung and K.P. Rao, Current materials are very commonly used in thermoset resins consisting of glass and carbon fibers. Composites with thermoplastic matrix have been recently developed to improve composite laminates’ toughness and damage tolerance. Thermoplastic resins’ ductility means that they take stronger plasticity [5]. Rahul Gautam et al. Based on the functional analysis and criteria specifications, 24 sustainable concepts separated into four assemblies were evaluated [6]. P. Karthikeyan et. al. This paper discusses modeling and study of drive shafts using a composite kevlar/epoxy and glass/epoxy and the possible substitution of the existing kevlar/epoxy/glass/epoxy resin composite drive shaft for conventional steel driveshafts in the sector. CATIA software is used for modeling, and Analytical software ANSYS 10.0 is used to facilitate comprehensiveness. The composite control shafts reduce weight in relation to the standard steel drive shaft by 81.67% in kevlar/epoxy and 72.66% for glass/epoxy [7]. S. Pachaiyappan et al. The aim of this project is to design and analyze a generic joint robot arm. For the application in the traverse and manipulation of nuclear reactor plants, an articulated robot has been noted. The articulated robot is supposed to have a useful small cross-section and the ability to change the height and climb over obstacles [8].

2.1 Research Gap After doing a literature review, many research papers found that no one had used a square section robot for making a robot. Also very few papers are on analysis of

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Fig. 1 Exploded view of circular arm

a square section arm. Most commonly used material for making a robot is usually steel or aluminum, and the usage of composite material in making a part of a robot is very less. After reading all the data, which cross section is best feasible is cannot be determined. This study sets a theoretic basis for an upcoming study into the cross section of arms of an articulated robot.

3 Design In this paper, the rectangular robotic arm is compared with the normal circular arm. Both the cross sections are designed in Creo 5.0 Educational Edition.

3.1 Circular Cross Section • The length of the arm in the X-direction is 1.49 m, in the Y-direction is 0.18 m and in Z-direction is 0.18 m. • The volume of the circular cross section is 1.2*10–2 m3 (Fig. 1).

3.2 Square Cross Section • The length of the arm in the X-direction is 1.44 m, in the Y-direction is 0.18 m and in Z-direction is 0.18 m. • The volume of the square cross section is 1.4*10–2 m3 (Fig. 2).

4 DH Parameter See Fig. 3 and Table 1.

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Fig. 2 Exploded view of square arm

Fig. 3 Kinematic relationship with adjacent linkages

Table 1 DH parameter of robotic arm

θ

d

α

a

θ1

0

−90

0

θ2

0

0

L2

θ3

0

0

L3

5 Forward Kinematics ⎤ Cθi −Sθi Cαi Sθi Sαi ai Cθi ⎢ Sθi Cθi Cαi −Cθi Sαi ai Sθi ⎥ i ⎥ Ti = ⎢ ⎣ 0 Sαi Cαi di ⎦ 0 0 0 1 ⎡ ⎤ Cθ1 0 −Sθ1 0 ⎢ Sθ1 0 Cθ1 0 ⎥ 0 ⎥ T1 = ⎢ ⎣ 0 −1 0 0 ⎦ ⎡

0

0

0

1

(1)

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⎤ Cθ2 −Sθ2 0 L 2 Cθ2 ⎢ Sθ2 Cθ2 0 L 2 Sθ2 ⎥ 1 ⎥ T2 = ⎢ ⎣ 0 0 1 0 ⎦ 0 0 0 1 ⎤ ⎡ Cθ3 −Sθ3 0 L 3 Cθ3 ⎢ Sθ3 Cθ3 0 L 3 Sθ3 ⎥ 2 ⎥ T3 = ⎢ ⎣ 0 0 1 0 ⎦ 0 0 0 1 ⎤ ⎡ Cθ1 Cθ2 −Cθ1 Sθ2 −Sθ1 L 2 Cθ1 Cθ2 ⎢ Sθ1 Cθ2 −Sθ1 Sθ2 Cθ1 L 2 Sθ1 Cθ2 ⎥ 0 ⎥ T2 = 0 T1 ∗ 1 T2 = ⎢ ⎣ −Sθ2 −Cθ2 0 −L 2 Sθ2 ⎦ 0 0 0 1 ⎡

0

(2)

T3 =0 T2 ∗2 T3 ⎤ ⎡ Cθ1 C(θ2 + θ3 ) −Cθ1 S(θ2 + θ3 ) −Sθ1 Cθ1 (L 3 C(θ2 + θ3 ) + L 2 Cθ2 ) ⎢ Sθ1 C(θ2 + θ3 ) −Sθ1 S(θ2 + θ3 ) Cθ1 Sθ1 (L 3 C(θ2 + θ3 ) + L 2 Cθ2 ) ⎥ ⎥ =⎢ ⎣ −S(θ2 + θ3 ) −C(θ2 + θ3 ) 0 −(L 3 S(θ2 + θ3 ) + L 2 Sθ2 ) ⎦ 0 0 0 1 (3)

6 Inverse Kinematics ⎡

r11 ⎢ r21 T =⎢ ⎣ r31 0

r12 r22 r32 0

r13 r23 r33 0

⎤ r14 r24 ⎥ ⎥ r34 ⎦ 1

(4)

From Equating (3) and (4), we get Cθ1 (L 3 C(θ2 + θ3 ) + L 2 Cθ2 ) = r14

(5)

Sθ1 (L 3 C(θ2 + θ3 ) + L 2 Cθ2 ) = r24

(6)

θ1 = tan−1

r24 r14

For finding the value of θ 2 , multiplying both sides by [2 T 3 ]−1

(7)

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2 −1 T3 =

⎡ Cθ3    T 2 ⎢ −Sθ3 R 3 − 2 R 3 ∗ 2 D3 =⎢ ⎣ 0 1 000 0



T

Sθ3 Cθ3 0 0

0 0 1 0

⎤ L3 0 ⎥ ⎥ 0 ⎦ 1

⎤ Cθ3r11 + Sθ3r12 Sθ3 r11 + Cθ3r12 r13 −L 3r11 + r14 ⎢ Cθ3r21 + Sθ3r22 Sθ3 r21 − Cθ3r22 r23 −L 3r21 + r24 ⎥ ⎥ =⎢ ⎣ Cθ3r31 + Sθ3r32 Sθ3 r31 − Cθ3r32 r33 −L 3r31 + r34 ⎦ 0 0 0 1    −1 −1 −1 0 T3 2 T3 = 0 T2 ∗ 2 T3 2 T3 = T 2 T3

(8)

⎡

T∗

2 −1 T3

0

T2 = T ∗

2 −1 T3

(9)

(10)

⎡

⎤ Cθ1 Cθ2 −Cθ1 Sθ2 −Sθ1 L 2 Cθ1 Cθ2 ⎢ Sθ1 Cθ2 −Sθ1 Sθ2 Cθ1 L 2 Sθ1 Cθ2 ⎥ ⎢ ⎥ ⎣ −Sθ2 −Cθ2 0 −L 2 Sθ2 ⎦ 0 0 0 1 ⎡ ⎤ Cθ3r11 + Sθ3 r12 Sθ3 r11 + Cθ3r12 r13 −L 3r11 + r14 ⎢ Cθ3r21 + Sθ3 r22 Sθ3 r21 − Cθ3r22 r23 −L 3r21 + r24 ⎥ ⎥ =⎢ ⎣ Cθ3r31 + Sθ3 r32 Sθ3 r31 − Cθ3r32 r33 −L 3r31 + r34 ⎦ 0 0 0 1 L 2 Cθ1 Cθ2 = −L 3r11 + r14

(11)

L 2 Sθ1 Cθ2 = −L 3r21 + r24

(12)

Squaring and adding Eqs. (11) and (12), we get L 2 Cθ2 = ± (−L 3r11 + r14 )2 + (−L 3r21 + r24 )2

(13)

−L 2 Sθ2 = −L 3r31 + r34

(14)

θ2 = tan−1

−L 3r31 + r34 ∓ (−L 3r11 + r14 )2 + (−L 3r21 + r24 )2

(15)

For finding the value of θ 3 , Equating (3) and (4), we get −S(θ2 + θ3 ) = r31

(16)

−C(θ2 + θ3 ) = r32

(17)

Design and Analysis of Circular and Square Arm …

θ3 = tan−1

r31 + 180 − θ2 r32

463

(18)

From Eq. (7), (15), and (18), the values of θ 1 , θ 2, and θ 3 are found.

7 ANSYS All the analysis on both robotic arms are performed in ANSYS 2019 R3, and they are Total deformation analysis Directional deformation analysis Equivalent elastic strain analysis Equivalent stress analysis. Also, analysis is performed to find the optimum material from stainless steel (SS), carbon epoxy, and aramid (kevlar-49) epoxy.

7.1 Analysis of Circular Robotic Arm Total Deformation Analysis. The total maximum deformation, which will occur in the circular arm robot under maximum applicable load, is comparatively higher for carbon epoxy than the aramid followed by stainless steel (Fig. 4).

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Fig. 4 Results for total deformation for robot made with carbon epoxy, aramid and SS

Direction Deformation Analysis. The total maximum directional deformation, which will occur in the circular arm robot under maximum applicable load, is comparatively higher for carbon epoxy than the aramid followed by stainless steel (Fig. 5).

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Fig. 5 Results for directional deformation for robot made with carbon epoxy, aramid and SS

Equivalent Elastic Strain Analysis. During analysis maximum, elastic strain induced is comparatively higher for carbon epoxy than the aramid followed by stainless steel for a robot (Fig. 6).

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Fig. 6 Results for equivalent elastic strain for robot made with carbon epoxy, aramid and SS

Equivalent Stress Analysis. Results of equivalent stress show that total maximum stress induced is comparatively higher for carbon epoxy than the aramid followed by stainless steel for a robot (Fig. 7).

Design and Analysis of Circular and Square Arm …

Fig. 7 Results for equivalent stress for robot made with carbon epoxy, aramid and SS

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7.2 Analysis of Square Arm Robot Total Deformation Analysis. The total maximum deformation, which will occur in the circular arm robot under maximum applicable load, is comparatively higher for aramid than the carbon epoxy followed by stainless steel (Fig. 8).

Fig. 8 Results for total deformation for robot made with carbon epoxy, aramid and SS

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Directional Deformation Analysis. The total maximum directional deformation, which will occur in the circular arm robot under maximum applicable load, is comparatively higher for aramid than the carbon epoxy followed by stainless steel (Fig. 9).

Fig. 9 Results for directional deformation for robot made with carbon epoxy, aramid and SS

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Equivalent Elastic Strain Analysis. During analysis maximum, elastic strain induced is comparatively higher for aramid than the carbon epoxy followed by stainless steel robot (Fig. 10).

Fig. 10 Results for equivalent elastic strain for robot made with carbon epoxy, aramid and SS

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Equivalent Stress Analysis. Results of equivalent stress show that total maximum stress induced is comparatively higher for carbon epoxy than the aramid followed by stainless steel for a robot (Fig. 11).

Fig. 11 Results for equivalent stress for robot made with carbon epoxy, aramid and SS

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8 Conclusion The robot is made of the two different cross sections: circular cross section arm and square cross section arm. After doing the analysis, square cross section arm made of stainless steel will be the best. After doing the analysis, the circular cross section arm made of carbon epoxy will be the best. Also, the results of static structural analysis conclude that the deformation of a robot of circular cross section arm made with carbon epoxy > aramid > stainless steel at 5 KN. Also, the results of static structural analysis conclude that the deformation of a robot of square cross section arm made with aramid > carbon Epoxy > stainless steel at 5 KN. Stress is usually developed in the joints which are in the permissible limit. A robot with a square cross section arm should be used with any material as it gives better results than circular cross section arm.

References 1. Hull D, Clyne TW (1996) An introduction to composite materials, 2nd edn. Cambridge University Press, Cambridge, New York 2. Lee J et al (2016) Carbon/epoxy composite foot structure for biped robots. Compos Struct 140:344–350 3. Clothier KE, Shang Y (2010) A Geometric approach for robotic arm kinematics with hardware design, electrical design, and implementation. J Robot 2010:1–10 4. Bugday M, Karali M (2019) Design optimization of an industrial robot arm to minimize redundant weight. Eng Sci Technol Int J 22(1):346–352 5. Yeung KKH, Rao KP (2012) Mechanical properties of Kevlar-49 fibre reinforced thermoplastic composites. Polym Polym Compos 20(5):411–424 6. Gautam R, Gedam A, Zade A, Mahawadiwar A (2017) Review on development of industrial robotic arm. Int Res J Eng Technol 04(03):1752–1755 7. Karthikeyan P, Gobinath R, Ajith Kumar L, Xavier Jenish D (2017) Design and analysis of drive shaft using kevlar/epoxy and glass/epoxy as a composite material. IOP Conf Ser Mater Sci Eng 197 8. Pachaiyappan S, Balraj MM, Sridhar T (2014) Design and analysis of an articulated robot arm for various industrial applications. IOSR J Mech Civ Eng, 42–53

Kinematic Analysis and Simulation of Industrial Robot Based on RoboAnalyzer Amit Talli and Arunkumar C. Giriyapur

Abstract In this paper, the kinematic analysis of a six-degree-of-freedom (6-DOF) industrial robot is presented. A six-degree-of-freedom industrial robot is widely used for welding, painting, pick and place, and packaging applications. The forward and inverse kinematic analysis based on Denavit–Hartenberg (D-H) parameters is performed by using RoboAnalyzer tool. RoboAnalyzer is a visualization tool used for learning and teaching the concepts of industrial robots. The forward and inverse kinematic analysis depends upon the joint-link parameters of the robot arm. This paper focuses on the development of kinematic equations for an industrial robot. Two trial tests were conducted for different joint variables to verify the position of the end-effector of the robot arm. The results obtained from forward kinematic equations are compared with simulation data provided by the RoboAnalyzer. The simulation results verify the validity of the developed kinematic equations. Furthermore, the inverse kinematic module of the RoboAnalyzer is used to generate a possible set of solutions for a specified position of the end-effector. Keywords Denavit–Hartenberg · RoboAnalyzer · Kinematic analysis · Visualization

1 Introduction Robot kinematics deals with the motion analysis and its derivatives without considering forces or torque causing the motion [1]. The displacement, velocity, and acceleration of all the links are analyzed under robot kinematics, excluding forces causing the movement. The kinematic model of the robot arm establishes the relation between the position and orientation of the tool or end-effector. The kinematics of the robot is split into two problems as forward and inverse kinematics. The forward kinematics depends upon the joint variables, and it refers to the finding of position values of the end-effector. The inverse kinematics depends upon the position values, and it refers A. Talli (B) · A. C. Giriyapur Automation and Robotics, KLE Technological University, Hubli 580031, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_40

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Fig. 1 Forward and inverse kinematics

to finding the joint values that would bring the end-effector to the specified position and orientation [2]. The problem of manipulator control requires both forward and inverse kinematic model of the manipulators. The block diagram represents the process for forward and inverse kinematics model which is shown in Fig. 1. The forward kinematic analysis yields one unique solution for the specified joint variables and involves matrix operations. The procedure of inverse kinematics is complicated as compared to forward kinematics and yields multiple possible answers or various combination of joint values to reach a particular position. There are different methods or approaches to the kinematic analysis of a six-axis industrial robot arm. In some cases, the entire model of the robot arm is modelled in CAD tool and exported as a Parasolid to CAE tools such as ADAMS for adding constraints and actuators [3]. As reported in [4], the kinematics analysis is performed by using the robotics toolbox in MATLAB. The robotics toolbox is an add-in for MATLAB involving some pre-built functions and models of industrial robots for the analysis. The authors [5] reported about the complete procedure of kinematic and dynamic analysis of a UR5 manipulator. The inverse kinematics procedure involves the determination of joint values for the specified position. The fuzzy logic and particle swarm optimization (PSO) algorithm are some of the methods based on algorithms for inverse kinematics [6]. As compared to the forward kinematics, the procedure of inverse kinematics is complicated and involves rigorous mathematical operations. The visualization of inverse kinematics without any aid/tool is difficult to digest. In this study, RoboAnalyzer has been used for simulation and solving the forward and inverse kinematics [7]. This paper is organized as follows. Section 2 presents a simplified method of kinematic analysis. The Denavit–Hartenberg parameters of

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Fig. 2 Methodology

KUKA KR5 Arc is presented in Sect. 3. The forward kinematic equations are developed, and analytical results are compared with simulation data provided by the RoboAnalyzer is performed in Sect. 4. Section 5 presents the inverse kinematic module of RoboAnalyzer. Finally, Sect. 6 presents the conclusion of this paper.

2 Methodology The steps involved in kinematics analysis and simulation of an industrial robot are divided into a simple process. The simplified process is shown in Fig. 2. The frame allocation is required for any industrial robot according to the D-H parameters. The D-H parameters act as a guideline for establishing the architecture of the industrial robot. Further, D-H parameters are used for the development of a homogeneous transformation matrix for forward and inverse kinematics.

3 Denavit–Hartenberg Parameters of KUKA KR5 Arc Figure 3 shows the KUKA KR5 Arc with six-axis joint is a widely used industrial robot for welding and painting operations. Figure 3 shows the configuration of the KUKA KR5 Arc robot with six revolute joints. The D-H parameters for KUKA KR5 Arc robotic arm are listed in Table 1. The robot has six joint and seven links, as shown in Fig. 3. The D-H table consists of four essential parameters to define the orientation and position of the link [8]. The D-H parameters define the entire architecture of the robot. The two joint parameters d i and θ i , define translation along z-axis and rotation about the z-axis. The other two joint parameters ai and α i , define translation along x-axis and rotation or twist about the xaxis. The d i , ai , and α i parameters are fixed and do not change or cannot be modified. The θ i parameter is variable and defines the rotational/translational displacement of a joint within the specified range, as shown in Table 1. The manufacturer specifies the range/limit of each joint in the product catalogue with specifications[9, 10]. The homogeneous transformation matrix is determined by multiplying the individual transformation matrix by using the data provided in the D-H table. The general homogeneous transformation matrix can be obtained by: T = Trot (θ, z) ∗ Ttrans (d, z) ∗ Ttrans (a, x) ∗ Trot (α, x)

(1)

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Fig. 3 KUKA KR5 arc

Table 1 Joint-link parameters for KUKA KR5 Arc robot θ i (deg)

ai (m)

α i (deg)

Range (deg)

0.4

θ1

0.18

90

±155

0.135

θ2

0.6

180

+65 to −180

3

0.135

θ3

0.12

−90

+158 to −15

4

0.62

θ4

0

90

−350 to 350

5

0

θ5

0

−90

±130

6

0.115

θ6

0

0

±350

Link

d i (m)

1 2

⎤ cos(θ ) − sin(θ ) cos(α) sin(θ ) cos(α) a cos(θ ) ⎢ sin(θ ) cos(θ ) cos(α) − cos(θ ) cos(α) a sin(θ ) ⎥ ⎥ T =⎢ ⎦ ⎣ 0 sin(α) cos(α) d 0 0 0 1 ⎡

(2)

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4 Forward Kinematics Analysis The KUKA KR5 Arc robot, shown in Fig. 4, is characterized by a 6-DOF robot arm. According to the algorithm of D-H parameters, the six joints are labelled from 1 to 6 starting with joint 1 between link 0 (fixed or grounded frame) and link 1. The orientation of each joint axis and joint variables is identified and labelled concerning the home position of the manipulator in which all the joint variables are at default or neutral values [11]. The six link transformation matrices are: ⎤ C1 0 S1 a1 ∗ C1 ⎢ S1 0 −C1 a1 ∗ S1 ⎥ 0 ⎥ T1 (θ1 ) = ⎢ ⎣ 0 1 0 d1 ⎦ 0 0 0 1 ⎤ ⎡ C2 S2 0 a2 ∗ C2 ⎢ S2 −C2 0 a2 ∗ S2 ⎥ 1 ⎥ T2 (θ2 ) = ⎢ ⎣ 0 0 −1 d2 ⎦ 0 0 0 1 ⎡

Fig. 4 Forward kinematics

(3)

(3)

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⎤ C3 0 −S3 a3 ∗ C3 ⎢ S3 0 C3 a3 ∗ S3 ⎥ 2 ⎥ T3 (θ3 ) = ⎢ ⎣ 0 −1 0 d3 ⎦ 0 0 0 1 ⎤ ⎡ C4 0 S4 0 ⎢ S4 0 −C4 0 ⎥ 3 ⎥ T4 (θ4 ) = ⎢ ⎣ 0 1 0 d4 ⎦ 0 0 0 1 ⎤ ⎡ C5 0 −S5 0 ⎢ S5 0 C5 0 ⎥ 4 ⎥ T5 (θ5 ) = ⎢ ⎣ 0 −1 0 0 ⎦ ⎡

0 1 ⎤ C6 −S6 0 0 ⎢ S6 C6 0 0 ⎥ 5 ⎥ T6 (θ6 ) = ⎢ ⎣ 0 0 1 d6 ⎦ 0 0 0 1

(4)

(6)

(7)

0 0

⎡

(8)

Finally, the position of the end-effector is obtained by multiplying the individual transform matrices as follows: 0

T6 =0 T11 T22 T33 T44 T55 T6

(9)

The overall transformation matrix, 0 T 6 depicts the position and orientation of the tool/end-effector. The transformation matrix 0 T 6 is called 4 × 4 homogeneous transformation matrix consisting of 16 elements. Out of the 16 elements, only the last column of the matrix is significant. These equations give the position of the end-effector in the spatial workspace. ⎤ Px ⎢ R Py ⎥ 0 ⎥ T6 = ⎢ ⎣ Pz ⎦ 0 0 0 1 ⎡

(10)

Px = a1 ∗ C1 + d2 ∗ S1 − d3 ∗ S1 − d6  S5 ∗ (S1 ∗ S4 + C4 ∗ (C1 ∗ C2 ∗ C3 + C1 ∗ S2 ∗ S3 )) ∗ +C5 ∗ (C1 ∗ C2 ∗ S3 − C1 ∗ C3 ∗ S2 ) + a3 ∗ (C1 ∗ C2 ∗ C3 + C1 ∗ S2 ∗ S3 ) − d4 ∗ (C1 ∗ C2 ∗ S3 − C1 ∗ C3 ∗ S2 ) + a2 ∗ C 1 ∗ C 2

(11)

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Py = a3 ∗ (S1 ∗ S2 ∗ S3 + C2 ∗ C3 ∗ S1 ) − d4 ∗ (C2 ∗ S1 ∗ S3 − C3 ∗ S1 ∗ S2 ) − d2 ∗ C1 + d3 ∗ C1 + a1 ∗ S1 + d6  S5 ∗ (C1 ∗ S4 − C4 ∗ (S1 ∗ S2 ∗ S3 + C2 ∗ C3 ∗ S1 )) ∗ −C5 ∗ (C2 ∗ S1 ∗ S3 − C3 ∗ S1 ∗ S2 ) + a2 ∗ C2 ∗ S1

(12)

⎤ a3 ∗ (C2 ∗ S3 − C3 ∗ S2 ) − d4 ∗ (C2 ∗ C3 + S2 ∗ S3 ) ⎥ ⎢ Pz = d1 −⎣ − d6 ∗ (C5 ∗ (C2 ∗ C3 + S2 ∗ S3 ) − C4 ∗ S5 ∗ (C2 ∗ S3 − C3 ∗ S2 ))⎦ + a2 ∗ S2 (13) ⎡

where, C i denotes cosθ i , S i denotes sinθ i , C i *C j *S k = (cosθ i *cosθ j *sinθ k ). The short notations of trigonometric identities makes the matrix compact and easy to identify. The ‘R’ denotes the rotation elements of the end-effector in the spatial workspace. Finally, the position of the end-effector, for the given joint variable vector q = [θ 1 θ 2 θ 3 θ 4 θ 5 θ 6 ]T is given by Eqs. (11) (12) and (13) respectively. The kinematic equations are validated by using RoboAnalyzer tool for various joint variables. Figure 5 shows the position of the end-effector of the robot for joint value vector q = [0 90 0 0 0 0]T and Fig. 6 shows the position of the end-effector of the robot

Fig. 5 Simulation pose for q = [0 90 0 0 0 0]T

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Fig. 6 Simulation pose for q = [40 90 60 20 10 350]T

for joint value vector q = [40 90 60 20 10 350]T . The joint values can be directly entered in the RoboAnalyzer in terms of degree or metre depending upon the type of joint. Forward kinematics can be performed by selecting FKin option provided in the RoboAnalyzer, as shown in Figs. 5 and 6. Table 2 shows the comparison between the analytical and RoboAnalyzer results. Two trials were carried out for different joint value vector, q = [0 90 0 0 0 0]T and q = [40 90 60 20 10 350]T and all values of joint variables are specified in terms of degrees and the final position of the end-effector is specified in terms of metre [12]. From the analysis, as shown in Table 2, the forward kinematic solution obtained from the analytical method obtained is similar to the values obtained in RoboAnalyzer and validates the analytical equations obtained by the D-H method. This analysis also proves that the results obtained from RoboAnalyzer are valid and correct for solving the kinematic equations. Figure 5 shows the position vector, P = [0.915 0 1.12]T for joint variable q = [0 90 0 0 0 0]T . The joint values of KUKA KR5 Arc robot can be entered in the interface in terms of degrees within the specified range. Figure 5 shows the final position of the robot after performing the simulation. As reported, the values obtained from the Table 2 KUKA KR5 arc results Trial no

Analytical results

1

P = [0.912 0 1.11]T

2

P = [0.48143 0.412950

RoboAnalyzer results P = [0.915 0 1.12]T 0.415600]T

P = [0.48151 0.412951 0.415602]T

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RoboAnalyzer are found to be consistent with the analytical results. Similarly, Fig. 6 shows the position vector P = [0.48151 0.412951 0.415602]T for joint variable q = [40 90 60 20 10 350]T . Figure 6 shows the final position of the robot, and the results obtained from the RoboAnalyzer tool are also found to be consistent with the analytical results. The comparison of the results is also shown in Table 2 for two different joint values.

5 Inverse Kinematics Analysis The inverse kinematic problem deals with the determining of different possible sets of joint variables, which would attain the specified pose of the end-effector. The inverse kinematic problem becomes complicated as the number of joint or link increases. The joint variables are determined by squaring and adding the position equations. The analytical solutions of the inverse kinematic problem are a time-consuming process and require rigorous mathematics [11]. In such cases, software tool such as RoboAnalyzer can be used to determine the inverse kinematic solution [13]. Figure 7 shows the inverse solution for the specified position. Total of eight possible solutions is

Fig. 7 Inverse kinematic solution

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presented by the RoboAnalyzer tool for 6-DOF manipulator arm. The inverse kinematics for two-link or three-link planar manipulator can be derived by trigonometry, but as the number of link increases then it leads to complications. Inverse kinematics is very useful for planning the trajectory of the robot arm. There are also several methods or algorithms for determining the probable or number of ways to reach a specified pose. However, the method requires an algorithm to generate multiple ways to reach a specified position. The RoboAnalyzer is capable of generating the inverse kinematics from 2-DOF planar to a 6-DOF spatial industrial manipulator. There are some predefined robots included in the library of inverse kinematics module of RoboAnalyzer, which allows quick access to the robot arm such as MTAB mini, MTAB Aristo, KUKA KR5, and 6R generic manipulator. The position vector P = [0.915 0 1.12]T from trial one is specified in RoboAnalyzer, and other link parameters of KUKA KR5 Arc is entered in IKin module. The tool displays eight solutions in terms of joint angles, as shown in Fig. 7. From Fig. 7 it is evident that the solution 8 displays the joint value as, q = [0 90 0 0 0 0]T .

6 Conclusion In this paper, the D-H model of KUKAR KR5 Arc robot is established analytically. The forward and inverse solutions of the robot are calculated by RoboAnalyzer software. The position of the end-effector for different joint variables such as q = [0 90 0 0 0 0]T and q = [40 90 60 20 10 350]T is determined analytically and compared with the simulation results. The analytical results compared with the RoboAnalyzer are found to be similar/consistent and verifies the developed equations. The inverse kinematic analysis in RoboAnalyzer is carried out to determine the possible combination of the joint values to reach a specified position vector, P = [0.915 0 1.12]T . The RoboAnalyzer displayed eight possible ways to get the specified position. The inverse kinematics solution displayed by the RoboAnalyzer is found to be consistent and correct. The RoboAnalyzer tool has dynamic analysis option which can be explored for further research in robot dynamics.

References 1. Nguyen MT, Yuan C, Huang JH (2019) Kinematic analysis of a 6-DOF robotic arm. Presented at the. https://doi.org/10.1007/978-3-030-20131-9_292 2. Talli A (2015) Forward kinematic analysis, simulation & workspace tracing of anthropomorphic robot manipulator by using MSC. ADAMS Int J Innov Res Sci Eng Technol 04. https://doi. org/10.15680/IJIRSET.2015.0401009 3. Ratiu M, Rus A, Balas ML (2019) Kinematic modeling of a 6R industrial robot. IOP Conf Ser Mater Sci Eng 568. https://doi.org/10.1088/1757-899X/568/1/012021 4. Guida R, Simone MC, De Daši´c P, Guida D (2019) Modeling techniques for kinematic analysis of a six-axis robotic arm. IOP Conf Ser Mater Sci Eng 568:0–6. https://doi.org/10.1088/1757-

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899X/568/1/012115 5. Kebria PM, Al-wais S, Abdi H, Nahavandi S (2016) Kinematic and dynamic modelling of UR5 manipulator. In: 2016 IEEE international conference on Systems, Man, and Cybernetics (SMC), pp 4229–4234. https://doi.org/10.1109/SMC.2016.7844896 6. Dewi T, Nurmaini S, Risma P, Oktarina Y, Roriz M (2020) Inverse kinematic analysis of 4 DOF pick and place arm robot manipulator using fuzzy logic controller. Int J Electr Comput Eng 10:1376–1386. https://doi.org/10.11591/ijece.v10i2.pp1376-1386 7. Sadanand R, Joshi RP, Chittawadigi RG, Saha SK (2016) Virtual experiments for integrated teaching and learning of robot mechanics using roboanalyzer. Lect Notes Mech Eng, 59–68. https://doi.org/10.1007/978-81-322-2740-3_7 8. Flanders M, Kavanagh RC (2015) Build-a-robot: using virtual reality to visualize the DenavitHartenberg parameters. Comput Appl Eng Educ 23:846–853. https://doi.org/10.1002/cae. 21656 9. Rajeevlochana CG, Jain A, Shah SV, Saha SK (2011) Recursive robot dynamics in RoboAnalyzer. In: 15th Natl. Conf. Mach. Mech. NaCoMM 2011, pp 1–9 10. RobotWorx - KUKA KR 5 Arc. https://www.robots.com/robots/kuka-kr-5-arc. Last accessed 2020/07/08 11. Ben-Ari M, Mondada F (2018) Kinematics of a robotic manipulator. In: Elements of robotics. Springer International Publishing, Cham, pp. 267–291. https://doi.org/10.1007/978-3-31962533-1_16 12. Verma A, Deshpande V (2011) End-effector position analysis of SCORBOT-ER Vplus robot. Int J Smart Home 5 13. Sinha SS, Chittawadigi RG, Saha SK (2018) Inverse kinematics for general 6R manipulators in RoboAnalyzer, pp 1–9

A Simplified Method for Conversion of Lumbar Spine CT Images into Three-Dimensional Solid Model Pushpdant Jain

and J. Francis Xavier

Abstract The human spinal column is the most complicated part of the human musculoskeletal system. It is susceptible to various injuries caused either by impact loading due to accidents or by multiple sports activities. Different techniques were developed to cure the patients affected by spine injuries, but the prediction of results to spinal injury problems is still controversial. In this study, we have identified the simplest approach to convert the CT images into a three-dimensional solid model. The present work aims to develop the simplest methodology to convert the CT images into a surface model of considered vertebral sections L2-L4. In the next step, the surface model was converted to a solid model. The procedure adopted may be useful to generate the solid model of other vertebral and various body sections. The approach may also be utilized to perform various finite element analyses for the development of novel spinal implants.

1 Introduction Modelling of intricate shape structure like spinal section is still a challenge yet promising, with potential to increase the quality for patient’s care. Bianco et al. [1] compared different screw diameters with variation in length and trajectory in their experimental analysis. Authors have concluded that the screw diameters plays a vital role in the identification of stresses at bone screw interface. Chen et al. [2] investigated Pushpdant Jain would like to dedicate this Chapter to his PhD Supervisor Dr. Mohammed Rajik Khan, National Institute of Technology, Rourkela and NITR management for all the support and guidance through out the study. P. Jain (B) · J. F. Xavier School of Mechanical Engineering, VIT Bhopal University, Bhopal, Madhya Pradesh 464114, India e-mail: [email protected] J. F. Xavier e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_41

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the novel implant like awesome dynamic rod implant was developed and compared with rigid fixation with cage and result contributed in increased range of motion and facet forces. In the context of rigid fixation, Ambati et al. [3] investigated different types of unilateral and bilateral construct to analyse the impact over the lumbar region L4-L5 and increased posterior stresses were observed with the unilateral screws in flexion and extension cases. Divya et al. [4] performed the finite element analysis (FEA) on L1-L5 to find out the mechanical properties of each vertebra and compared relatively to identify the spine disorders. Prior to any analysis or operation, identification of bone trajectory and morphometric study is very essential for proper insertion of pedicle screw, selection of puncture point, disc entry point, and pedicle instrumentation orientation [5]. Finite element method has been proven the effective method and computational tool to represent complex structure, non-regularities in loading, materials in the field of biomechanical engineering [6]. Bone mineral density and insertion of any needle in the bone depend upon the selection of entry points with respect to technical and anatomical aspects [7]. L3-L4-L5 was modelled, and FEA is done to identify the effective diameter of pedicle screw with various loading conditions and various bone material properties [8]. In the same context, Erbulut et al. [9] investigated the effect of various rigid, semi-rigid and dynamic stabilization systems on validated FE model of L1-S1 and concluded with the lesser stress level at adjacent area of vertebrae in case of semirigid and dynamic stabilization as compared to rigid fixation. An effect over the intervertebral disc was identified by Ashtiani et al. [10] using 3 different types of implant and results in the form of stress and displacement. Various authors have also proposed to generate the FE model of vertebra to perform the finite element analysis [11–14]. Various researchers are carrying out research in the field of bio-mechanics and spinal implants, but no one has revealed the method utilized in detail. Hence, the present work aims to elaborate and communicate a simplest method to generate surface model of vertebrae L2-L4 segments followed by solid modelling to perform FE analysis for future studies.

2 Materials and Method 2.1 Inclusion Criteria A 30-year-old healthy Indian male was considered for the study. Fifty-five multisliced (4.975 slice thickness) computed tomography (CT) images (DICOM format) of spinal column with a slice width of 512 pxi and height of 539 pxi, and pixel size was 0.703 mm were considered.

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2.2 CT Image Segmentation in Mimics CT images of the subject were imported in the Materialise’s Interactive Medical Image Control System (MIMICS) software (17.0, Materialise NV, Belgium) and used to generate the 3D surface model of the vertebral column L2-L4. Conversion of CT images into 3D model involves the initial process called “segmentation”. Available CT image slices were further considered for mask generation. Initially, a complete mask of the structure was generated with the help of scanned images, as shown in Fig. 1. Then, further processing of mask generation was carried out as per the user requirement for their analysis. Threshold limit of various bones in the form of Hounsfield units (HU) which was directly associated with the materials density utilized for segmentation. HU value for the material like bone, soft tissue, compact bone (adult/child), spongial bone (adult/child), muscle tissue, fat tissue, skin tissue, tooth and prosthesis was already predefined in the MIMICS. As per the researcher’s requirement, mask can be generated for required region/segments. In our study, HU of bone for patient image were reflecting in the range of 226-1602 instead of predefined 226-3071 for complete hard tissues which includes spinal vertebrae and ribs also. As per our interest area of concern, next step was “edit mask” to segment the vertebrae. Edit mask process follows the sequence of removal or erasing of not interested area as shown in Fig. 2. In the next step, “region growing” was used to generate the remaining vertebrae, which have not been erased and now considered for work. User can check the structure

Fig. 1 Generation of mask in MIMICS: a coronal view, b axial view, c sagittal view, d 3D view

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Fig. 2 Mask of lumbar vertebrae L1-L5: a coronal view, b axial view, c sagittal view, d 3D view

of the vertebrae by “calculating 3D from generated mask” and can check the shape of the vertebrae in 3D window. If any discrepancy with the structure found, can go to edit mask again and fill/erase the data as per the requirement. This process can be carried out for segmentation of all vertebrae of the spinal column, but here our area of concern is L2, L3 and L4 and can be done for the same respect as represented in Fig. 3. The outer core of the vertebral body enveloped by hard cortical bone, which also makes up the other vertebral structure like transverse process and spinous process and inner layer, was made up of spongy bone known as cancellous or trabecular bone. Segmentation of these two bones was also required for three-dimensional modelling. Similar to vertebrae, intervertebral disc was also developed in MIMICS as shown in Fig. 4. For segmentation of L2 vertebrae, the cortical bone mask of L2 is considered, and the duplicate mask was generated to carry out segmentation by “edit mask”. The same method can be adopted for segmentation of cancellous bone of L2, and procedure can be repeated to carry out segmentation of cortical and cancellous of L3 and L4 vertebrae, respectively. After segmentation, smoothing and wrapping of the L2, L3 and L4 model are to be performed to get the surface finish of actual bone as shown in Fig. 5. Three-dimensional surface model of the vertebral sections L2-L4 cortical and cancellous part then exported to 3-Matics 10.0 (FEA Module of MIMICS). The rough surface structure having triangles and lines at the corner edges was still present in the model of L2-L4, which then can be “local smoothened” here to avoid sharp edges of

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Fig. 3 Surface generation of L4 vertebra: a coronal view, b axial view, c sagittal view, d 3D view

Fig. 4 Surface generation of IVD-34: a coronal view, b axial view, c sagittal view, d 3D view

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Fig. 5 Generated vertebral segment L2-L3-L4: a coronal view, b axial view, c sagittal view, d 3D view

the vertebral model. Each part separately worked out and checked for accuracy for resemblance. 3-Matics provides a feature to provide “automatic rectangular patches”, which enables us to convert the surface files into point cloud data format, as shown, respectively, in Fig. 6 for vertebrae and in Fig. 7 for IVD.

Fig. 6 Point cloud data of vertebra L2: a side view and b top view

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Fig. 7 Point cloud data of IVD-23: a side view and b top view

2.3 Surface to Solid Modelling Further point cloud data is imported in SolidWorks 2014 to generate the solid model of vertebrae and IVD. In SolidWorks 2014, we use the scan to 3D option and import the point cloud data of vertebrae L2, L3, L4, intervertebral disc IVD-23 and IVD-34. To generate surfaces through these point cloud data, “Mesh Prep Wizard” option is utilized by selection of respective point cloud of vertebrae and IVD. There is probability of obtaining irregular surfaces after using Mesh Prep Wizard; hence, “Surface Wizard” is further used to smoothen the surface as per the actual geometry of vertebrae and disc. The generated solid models are shown in Figs. 8 and 9. The surface of vertebrae and IVDs are contained of surface patches, which are essential to perform the meshing in finite element software. Uniform surface patches result in uniform meshes. These steps were repeated again to generate the remaining solid model of vertebrae and IVD. Initially, the solid model of cortical bone and annulus fibrosus were created and in next step cancellous bone from solid model of vertebra and nucleus pulposus from IVD were extracted. Each vertebral body consists of inner cancellous surrounded by cortical bone. Posterior elements consist of transverse process, lamina, spinous process, superior articular process, facet and pedicle. Intervertebral disc was modelled considering nucleus pulposus surrounded by annulus fibrosis.

Fig. 8 Solid model of vertebra L2: a side view and b top view

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Fig. 9 Solid model of IVD-23: a side view and b top view

Fig. 10 CAD models of lumbar sections L2-L4

Separate assembly of lumbar sections L2-L4 was carried out in SolidWorks 2014 as depicted in Fig. 10. Intact model of vertebrae (L2, L3 and L4) consists of cancellous enclosed with cortical bone, whereas IVD (IVD-23 and IVD-34) possesses the nucleus pulposus surrounded by annulus fibrosus.

3 Conclusion In the present work, authors considered the CT images of lumbar sections L1-L5 for generation of surface model in the form of point cloud (L2-L4) by utilizing the software MIMICS 17.0. Further, the CAD software SolidWorks was also used to develop the solid model of lumbar segments (L2-L4, IVD 23 and IVD 34). Authors

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found that it is very easy to convert the surface model into solid model with the aid of SolidWorks. The solid model can be further utilized in simulation software such as ANSYS or Abaqus, to perform and calculate von Mises stress, strain as per the researcher’s requirement. The suggested methodology will be very useful for the researchers who are thinking to start their research in the field of spinal implantation. Researchers can also perform the mesh sensitivity analysis to refine the results. Moreover, the same procedure may be adopted to develop the other spinal region, other body part surface and solid model.

References 1. Bianco R, Arnoux JP, Wagnac E, Mac-Thiong JM, Aubin CE (2017) Minimizing pedicle screw pullout risks: a detailed biomechanical analysis of screw design and placement. Clin Spine Surg 30(3):E226–E232 2. Chen C-S, Huang C-H, Shih S-L (2015) Biomechanical evaluation of a new pedicle screwbased posterior dynamic stabilization device (Awesome Rod System)-a finite element analysis. BMC Musculoskelet Disord 16(1):81 3. Ambati DV, Wright Jr EK Lehman Jr RA, Kang DG, Wagner SC, Dmitriev AE (2015) Bilateral pedicle screw fixation provides superior biomechanical stability in transforaminal lumbar interbody fusion: a finite element study. Spine J 15(8):1812–1822 4. Divya V, Anburajan M (2011) Finite element analysis of human lumbar spine. In: 2011 3rd international conference on electronics computer technology, vol 3. IEEE, pp 350–354 5. Wolf A, Shoham M, Michael S, Moshe R (2001) Morphometric study of the human lumbar spine for operation–workspace specifications. Spine 26(22):2472–2477 6. Zhang QH, Teo EC (2008) Finite element application in implant research for treatment of lumbar degenerative disc disease. Med Eng Phys 30(10):1246–1256 7. Teoh SH, Chui CK (2008) Bone material properties and fracture analysis: Needle insertion for spinal surgery. J Mech Behav Biomed Mater 1(2):115–139 8. Biswas JK, Sahu TP, Masud R, Sandipan R, Karmakar SK, Santanu M, Amit R (2019) Design factors of lumbar pedicle screws under bending load: a finite element analysis. Biocybernetics Biomed Eng 39(1):52–62 9. Erbulut DU, Kiapour A, Oktenoglu T, Ozer AF, Goel VK (2014) A computational biomechanical investigation of posterior dynamic instrumentation: combination of dynamic rod and hinged (dynamic) screw. J Biomech Eng 136(5) 10. Najafi-Ashtiani H, Najafi-Ashtiani M (2015) Comparative evaluation between rigid and dynamic spinal fixation systems: a three-dimensional finite element analysis. Zahedan J. Res Med Sci 17(8) 11. Jain P, Rajik Khan M (2019) Prediction of biomechanical behavior of lumbar vertebrae using a novel semi-rigid stabilization device. Proc Inst Mech Eng, Part H: J Eng Med 233(8):849–857 12. Jain P, Rajik Khan M (2018) Biomechanical study of fused lumbar spine considering bone degeneracy using FEA. Arab J Sci Eng 43(3):1325–1334 13. Jain P, Rajik Khan M (2020) Biomechanical study of lumbar spine (L2-L4) using hybrid stabilization device-A finite element analysis. Int J Manuf Mater Mech Eng (IJMMME) 10(1):20–32 14. Jain P, Rana M, Biswas JK, Rajik Khan M (2020) Biomechanics of spinal implants–a review. Biomed Phys Eng Express 6(4). https://doi.org/10.1088/2057-1976/ab9dd2

Design of Automatic Multipurpose Indian Flatbread Maker Shivam Kishore Sinha, Vaibhav Chopde, Kumar Abhishek, and Amit Devani

Abstract Roti is an irreplaceable component of the Indian menu. But the process of roti making is quite tiresome and time consuming. Whether it is a family gathering like weddings or hostel mess, often a problem arises regarding demand and supply of freshly baked roti. There are machines available in the market which can make this task easy for us, but they have certain shortcomings such as expensiveness, lack of quality, lack of taste, extreme low or extreme high rate of production of roti and imbalance between these factors. The main aim was to design and fabricate an efficient, compact, and user-friendly automatic roti machine to serve the needs of people. Also for not alternating the traditional taste, we used LPG flame burners to cook it. This paper describes the design and fabrication of the machine. Each of its modified components is explained and supported by a mathematical calculation and the reason behind its selection/designing. The stress analysis and other technical aspects are also taken into consideration. The cost of the whole project was under Rs. 50,000 and is capable of producing 480 rotis/h. It requires electricity to preheat the dough using G coil. Majority of parts are made up of mild steel and cast iron. Cam follower mechanism is used to flatten the dough balls followed by conveyor mechanism for baking. Whole machine is powered by 1.5 Hp motor attached to 80:1 gearbox. Keywords Roti · Dough ball · Cooking · Automatic roti machine

1 Introduction Wheat is one of the most commonly available daily staple in India and all over the world. Its demand has been increased in recent years due to the abundant health benefits provided. The research has shown us that wheat helps us with reducing the heart rate and treating gallstone, asthma, skin, and cancer diseases due to its S. K. Sinha · V. Chopde · K. Abhishek (B) · A. Devani Department of Mechanical Engineering, Institute of Infrastructure, Technology, Research and Management (IITRAM), Ahmedabad, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_42

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richness in minerals and vitamins (E, B6) [1]. Wheat is consumed as different types of flatbreads such as parotha, phulka, puri, and tandoori roti. Most common thing made from wheat is roti. Indian meal is incomplete without this flatbread. But the traditional process of roti making is quite tiresome and time consuming. It requires abundant amount of physical energy to make the dough from wheat flour, to roll the dough balls into flatten disks, and to cook this flatten disks (roti) on tawa (pan). Also heat coming from the tawa sweats the person. Whether it is a family gathering such as wedding, celebration, and any kind of function, also in institute hostel canteens, we often see the problem of unbalanced demand and supply of rotis. For such kind of problems, roti maker can be a perfect solution. There are many commercial machines available in the market. Prestige stainless steel roti maker and Bajaj roti/chapati maker are manually operated roti makers. These devices can roll and bake the roti. Their key features are nonstick plate, shock-proof body, heat-resistant handles, and automatic cut-off feature with an indicator. They price around Rs. 2000–2500 in the Indian market. But their major drawback is electric heating. Roti gets non-uniformly cooked, becomes hard when dough is inconsistent, and does not tastes good. Also, it is risky to operate with chances of getting your hand burnt. BY-MRM 180 Automatic Roti-i Maker is fully automatic machine with stainless steel body (CE ISO certified). The key feature of this machine is thickness of roti can be customized. It can make 30–60 rotis per minute and is suitable for large-scale roti making for instance in a restaurant. But its parts are exposed hence more susceptible to wear and tear. Its price is around Rs. 60,000–Rs. 90,000. Fortune Engineering Fully Automatic Roti Making Machine is fully automatic machine with soft silicone protector and self-balancing scooter case cover. It can make 800 chapattis per hour and is good for commercial usage. But it takes twenty minutes to warm up, and its size is too big. Also, it does not knead the dough. Its price is around Rs. 2.9 lakhs in the Indian market. Chapati Magic Automatic chapati making machine is fully automatic machine with non-stick plates and is also available with grilling equipment. It has thermostat for temperature control and mechanism to knead the dough. But it is humungous in size and hence not suitable for a small setup. Its price is around Rs. 400,000 in the Indian market. Rotimatic Robotic Roti Maker is a fully automated machine enabled with Al and IOT. It has its own smart app for users to stay connected and seek help. It is a smart kitchen appliance. The key feature of this machine is that it is compatible to flour from different brands performs all functions, includes kneading to rolling and baking rotis. It is designed to create other kinds of flatbread as well. But its drawback is that it is very expensive and can cost around Rs. 240,000. Also, rate of production of roti is very low, about 60 rotis per hour. So, it cannot matchup the demand and supply equilibrium. Greatcity automatic chapatti flatbread maker is a manually operated machine. It works on low energy but is high speed. It is made of stainless steel and can manufacture 900 pieces per hour. The key feature of this machine is its pressing mechanism which is non-stick. But it does not knead the dough or make dough balls and is too large in size and hence not suitable for a regular function. Its price is around Rs. 300,000 [2].

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Fig. 1 Main frame structure showing upper and lower section

From above review, it is clear that rate of production of rotis (per hour), cost effectiveness of the machine, quality of the roti, taste of the roti are important factors. This work takes all the factors into consideration in a balanced way to overcome the disadvantages of the roti makers available in the market. It fulfils the need to produce an efficient machine for small-scale applications.

2 Design of Mechanical Subsystems The design is somewhat based on the design of most roti makers employed for roti making nowadays. Our setup on the other hand has the following configuration.

2.1 Main Frame Structure Main frame structure is made up of mild steel square pipes (25 mm side) as shown in the figure. It consists of two sections • Upper section for cam follower presser mechanism. • Lower section for wire mesh conveyor assembly (Fig. 1).

2.2 Cam Follower Presser Mechanism It is the most important part and holds the key to working of the whole machine. Its basic function is to press and half bake the roti. It mainly consists of following parts:

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Electric motor Worm reduction gearbox Specially designed cast iron cam Bearing as a follower Set of presser plate G-shaped electric heater coil Base to hold all the above parts together.

Electric Motor. Electric motor powers both the cam presser mechanism and conveyor assembly. This type of motor uses electromagnetic induction from the magnetic field of the stator winding to produce an electric current in the rotor and hence torque. These are the most common type of AC motor and important in industry due to their load capacity with single-phase induction motors being used mainly for smaller loads, like used in house hold appliances, whereas three-phase induction motors are used more in industrial applications including like compressors, pumps, conveyor systems, and lifting gear. As our application is household based, we selected single-phase motor. Specifications—1.5 HP, 1440 RPM, single phase, flange mounted. Worm Reduction Gearbox. We needed the minimum rpm to get enough torque and speed for cam follower and to slow down the conveyors for minimum baking time of roti. So, we have chosen worm reduction gearbox with 80:1 reduction ratio. Worm gears are the most minimal sort of framework and give high-proportion speed decrease. They are regularly the favored sort of gearing framework when space is constrained and large speed reduction is required. Worm apparatuses can be utilized to either enormously build torque or extraordinarily diminish speed. They are additionally the smoothest and calmest of the rigging frameworks, as long as they are appropriately mounted and greased up. Specially Designed Cast Iron Cam. Maximum distance from the center to circumference of the cam is 100 mm, and minimum distance from the center to circumference of the cam is 55 mm. Set of Presser Plate. Cam follower presser mechanism consists of a stationary presser plate and a moving presser plate as shown in Fig. Stationary plate is attached to the welded metal strips of the upper section of main frame structure by bolts. Moving presser plate has a hinge at the bottom which can be interlocked with the base of the mechanism. Due to such design, moving plate has only one angular degree of freedom which helps to press the dough ball sandwiched between the two plates (Figs. 2 and 3). Each presser plate is made up of three components: Cast iron plate with circular slot at the center. Casted out in a unique pattern to minimize the weight of mechanism with a circular slot for inserting electric G coil. Electric G coil of 800 w is used to preroast the roti before baking on open flame through conveyors.

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Fig. 2 Stationary plate (in red and blue color)

Fig. 3 Moving presser plate attached to the base

G-shaped electric heater coil. We used coil of same diameter as roti. Shape of the coil gives uniform heating to the roti. Teflon-coated aluminum plate. Aluminum is one of the best conductor of heat. To conduct the heat from the G coil, it was the best option. Plate is coated with food grade Teflon to give it non-sticky nature. It avoids dough to stick on the plate (Figs. 4 and 5). Base. For this machine, its base is an integral component which provides stable foundation to the cam follower presser mechanism. We are using specially designed stationary machine base for this purpose which is hence made up of cast iron for mounting motor–gearbox mechanism as well as provides hinge for the moving presser plate. Screw guide mechanism is provided to the base which consists of two interlocked parts with jack screw at the center. The lower part of base is fixed to the main frame so as to make the upper part adjustable in one direction for tuning

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the distance between presser plates. The high damping property of cast iron is also beneficial here and makes it an obvious choice (Fig. 6).

Fig. 4 Cast iron plate

Fig. 5 Jalebi shaped G coil

Fig. 6 Base mounted with all the components

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Fig. 7 Sprocket and chain mechanism

2.3 Sprocket and Chain Mechanism Power from motor drive is also providing energy to the conveyors. To transfer this power, we needed an integrated sprocket chain mechanism. It required two steps [3]. • To transfer power vertically from the drive to a middle sprocket. • To transfer power horizontally from middle sprocket to conveyor (Fig. 7). So here, sprocket A is mounted on gearbox output shaft (on which cam is also mounted) and sprocket B is mounted on shaft which is further mounted on the two bearings on the lower section of the main frame. This sprocket chain mechanism provides 9.6 RPM speed at the end (Table 1). In the second step, sprocket C mounted on the same shaft as sprocket B transfers the motion to larger sprocket D. Sprocket D is mounted on the shaft connected to the conveyor assembly. So finally, motion is transferred from motor drive to conveyor assembly but at a lower speed 8 RPM. Such a slow speed is required to provide the roti enough time to be baked (30 s).

2.4 Conveyor Assembly For baking chapatti, we are using conveyor mechanism. It is one of the most important part on this machines, not only because it should meet the requirement but also because it is to be chosen such that the price of the product should not raise beyond par.

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Table 1 Sprocket and chain parameters at each stage Parameter

First stage vertical drive

Second stage horizontal drive

Chain link pitch

0.5 ~ 12.7 mm

0.5 ~ 12.7 mm

Sprocket

A

Teeth—25 Pitch diameter—101

C

Teeth—30 Pitch diameter 121 mm

B

Teeth—30 Pitch diameter 121 mm

D

Teeth—48 Pitch diameter 194 mm

Chain links

67

77

Chain length

851 mm

978 mm

Sprocket centers

251 mm

239 mm

Gear ratio

1.2:1

1.6:1

Chain speed

11.52 RPM

9.6 RPM

Output speed

9.6 RPM

8 RPM

First and foremost thing which should be kept in the mind is that this part is going to face flame all the time and it is a moving part. Slat conveyor is one obvious choice which is being widely used but again the budget constraint was there as the machine should be economical. Then, we thought of having wire mesh conveyor which can easily withstand flame, bake the roti while translating and get the job done. We calculated the dimensions which came to be 250 mm wide × 4.125 feet long and contacted an industry which can make customized belt to fit our need. But again, we get to know that the required 37 mm diameter sprocket (with pitch 3/8 inch) available in the market left us with only one material for our conveyor, i.e., mild steel. Finally, we get our mild steel wire mesh conveyor.

3 Design Calculations 3.1 Stress Calculations for Square Pipe Dimensions and properties of square pipes used in main frame structure are given as follows (Fig. 8) [4]: • • • • •

Outer side length(c) = 25 mm Inner side length (d) = 22 mm Modulus of elasticity for mild steel (E) = 210 GPa Compressive strength = 50 MPa Tensile strength = 840 MPa.

Area moment of inertia (I) as stated by Bhandari [5] and by substituting the dimensions given above, we get,

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Fig. 8 Dimensional details of the square pipes used in the main frame design

I =

c4 − d 4 = 13030.75 × 10−12 m4 12

(1)

Maximum compressive stress is at section A– By taking equilibrium of moments about vertical pipe at center, load per pipe can be calculated as following Load per pipe =

Total weight atB × b 54.7 kg × 340 mm = 18.4138 kg = 505 mm × 2 (a + b) × 2 (2)

Now, maximum compressive stress at section A can be given by, σmax =

18.4138 kg Total force acting on section A = = 61.38 KPa Cross sectional area 300 × 10−6 m2

(3)

Taking factor of safety as 4, allowable compressive stress can be calculated as follows, σA =

210 GPa Modulus of elasticity for M.S.(E) = = 52.5 GPa Factor of safety 4

By comparing Eqs. (3) and (4),

(4)

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σ A  σmax

(5)

Maximum Bending Moment at Section B– • Maximum moment at section B (M) is 6.25 Nm • Maximum distance from center (y) = 12.5 × 10−3 m • Area moment of inertia for square pipe (I) = 13,030.75 × 10−12 m4 . Bhandari [5] has given the equation of bending stress for a straight beam subjected to bending moment as follows, σb =

6.25 Nm × 12.5 × 10−3 m M×y = = 6 MPa I 13030.75 × 10−12 m4

(6)

Taking factor of safety as 4, allowable tensile stress can be calculated as follows, σA =

840 MPa Tensile strength of M.S. = = 210 MPa Factor of safety 4

(7)

By comparing Eqs. (6) and (7), σ A  σb

(8)

Maximum Deflection at Section B– • Applied load (assuming all mass as a point load at the center of mass here) (P) = 27.35 kg. • Length of the pipe (L) = 505 mm Using Macaulay method [5] for simply supported beam with point load, the maximum deflection at load application point can be given by δ=

P × a 2 × b2 3 × E × I × L

 2  2 27.35 kg × 165 × 10−3 m × 340 × 10−3 m       = 0.207 mm = 3 × 210 × 109 Pa × 13030.75 × 10−12 m4 × 505 × 10−3 m (9)

3.2 Load Calculations for Bearings For UCP202-10 type bearing (used for mounting shaft holding the sprockets B and C)

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Vertical force (F V ) on bearing, • Bearing inner diameter = 15 mm • Power transmitted from motor = 0.5 Hp = 370 w • Angular speed of sprocket B = 11.52 RPM = 1.2 rad/s Total torque (τ) transmitted is given by, τ= FV =

Power 370 w = = 294.438 Nm Angular speed 1.2 rad./s

294.438 Nm Torque(τ ) = = 2.355 kN Perpendicular distance 0.125 m

(10) (11)

Horizontal force (F H ) on bearing, • Angular speed of sprocket D = 8 RPM = 0.75398 rad/s

τ= FH =

370 w Power = = 490.729 Nm Angular speed 0.75398 red/s 490.729 Nm Torque(τ ) = = 2.453 kN Perpendicular distance 0.2 m

(12) (13)

So, total bearing load, FR =



FV2 + FH2 = 3.404 kN

(14)

For UCT204 type bearing (used for mounting the shaft holding sprocket D) • Horizontal force (FH ) = 2.453 kN • Vertical force (F V ) = 0 N • Total bearing load = 2.453 kN.

3.3 Stress Calculations for Shaft For shaft mounted on UCT 204 type bearing, • • • • •

Diameter = 12 mm Horizontal force acting on the shaft = 2.453 kN Bending moment (M) = 0.460 m × 2.453 kN = 1128.38 Nm. Maximum distance from center (y) = 6 mm Moment of inertia for a shaft (rod) is given by Bhandari [5],

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I =

3.14 × 124 π × d4 = = 1.017 × 10−9 m 4 64 64

(15)

Substituting above values in Eq. (6), σb =

1128.38 × 6 × 10−3 M×y = = 6.651 MPa I 1.017 × 10−9

(16)

Considering factor of safety as 4, maximum allowable tensile stress (σ A ) becomes 210 MPa. Comparing σ A Eq. (16), σb < σ A

(17)

4 Fabrication of Parts Fabrication of parts was the most important part of the project as effort was made to construct the roti maker with locally available raw material procured at an economical rate, and fabrication work was carried out with a semi-skilled approach, all of which was carried out in the college workshop with all necessary tools used being tools that are available at any workshop. Operations carried out are as following:

4.1 Cutting Cutting of the M.S. square pipe was done by accurately measuring the section lengths. Marking was done with the help of L square ruler and scribber, and then cutting operation was performed in a 2200 W cutoff saw machine with no load speed of 3800 RPM. The abrasive cutter was having diameter 14 inches and 2.8 mm thick (Table 2). Table 2 Sections of square pipe

Square pipe of 25 mm side

Square pipe of 20 mm side

5 Sections of 300 mm

2 Sections of 300 mm

2 Sections of 505 mm

2 Sections of 496 mm

6 Sections of 450 mm

2 Sections of 325 mm

2 Sections of 1240 mm 2 Sections of 755 mm 2 Sections of 675 mm Further, two metal strips of 300 mm × 10 mm × 30 mm were cut

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4.2 Grinding Operation Angle grinders with silicon carbide grinding wheels were used for grinding and polishing and often for removing excess metal at sections in the dryer that were otherwise hard to reach or work on.

4.3 Pattern Making The flattening plates which we have designed according to our need have groove to place electric G coil heater in it and also keep in account the metal expansion due to heat. This specially featured component is something which is readily available in the market in required dimension. So we went for casting of these plates. As known, pattern making is the first step to casting, and we had to make the replica of our component. Considering 1% contraction allowance for cast iron, wood pattern was made with standard surface finish in a 0.025 mm resolution CNC.

4.4 Casting It took three days to get our 183 mm × 183 mm × 17 mm and 183 mm × 218 mm × 17 mm (square shape with hinge) plates casted. These plates are casted with gray cast iron using the pattern. We cannot cast small dimensional features during this process, and also we know that surface finish of casting is not very good. So machining is done after casting to achieve desired output.

4.5 Bending Two sections of 20 mm square pipe were needed to be bend at an angle of 19 degrees which holds the stationary presser plate for smooth transfer of flattened dough. This was done in mild steel manual pipe bending machine.

4.6 Drilling Drilling was performed on the square pipe sections of 675 mm length on the radial drilling machine. Holes of 10 mm were drilled with intent of using bolts to hold the pillow bearings to the frame. Four holes of 10 mm were drilled on the metal strip of 300 mm × 10 mm × 30 mm each. Also, four corners of the cast iron plate each

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drilled for holes of 10 mm. All are intended to hold bolts. Drilling was done in step wise manner using drill bits of intermediate sizes first, and all the holes were made in bench drill using HSS drill bits.

4.7 Boring Sprockets of 37 mm diameter has internal diameter of 10 mm, but minimum internal diameter of pillow block bearing and take up bearing available was 12 mm according to the standards. So, four sprockets needed to be bored on lathe to 12 mm. Likewise, sprockets of 106, 125, and 200 mm were bored according to respective internal diameters available for bearings.

4.8 Welding The square pipe sections of required length were then positioned as required and tack welded with precision, and after each joint was tack welded, it was reinforced with the final welding. It was done using horizontal arc welding by keeping current between 75 and 90 A and voltage ranging between 13 and 18 V. Electrode taken was of 3.15 mm diameter.

5 Conclusion Demand for roti in Indian thali is irreplaceable. The amount of time it requires to bake is also considerable especially in institutes or some special events. The problems associated with baking roti in larger number like need for more human force, unhygienic food, hazard, and skill requirement will be solved. The automatic roti maker will not be bulky and affordable. It will produce 480 rotis/h which can easily meet the requirement of small gatherings and functions. The roti will be baked in LPG flame which gives it the taste of traditional one made at home. The mechanism used is simple and cost effective. Further, the provisions for making thepla and paratha can be added to give more dimensions to the machine. Another setup for preparing the dough can also be added in the machine in further phase of fabrication. Due to current COVID-19 lockdown, the final fabrication can only be partially completed. Acknowledgements We are thankful to SSIP cell, IITRAM for providing us the funds for this project.

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References 1. Younas T, Memon MS, Raza H Rehman KU (2020) Design and fabrication of rotimatic machine. In: Environmentally-benign energy solutions 2. Makers R (2018) A Comparative study. The rotimatic blog, October 2018. [Online]. Available: https://rotimatic.com/blog/roti-makers-a-comparative-study-rotimatic-blog/. Accessed 2019 3. RPM and Chain Speeds. Chain and Sprocket Calculator, [Online]. Available: https://www.blo cklayer.com/chain-sprocket.aspx 4. Wittrick WH (1965) A generalization of Macaulay’s method with applications in structural mechanics. AIAA J. 3(2):326–330 5. Bhandari VB (2010) Design of machine elements, 3rd edn. Tata McGraw-Hill Education, New Delhi

Correction to: Superplasticity: Recent Approaches and Trends Deepika M. Harwani, Vishvesh J. Badheka, and Vivek Patel

Correction to: Chapter “Superplasticity: Recent Approaches and Trends” in: A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_33 In the original version of the book, in Chapter “Superplasticity: Recent Approaches and Trends” the author name “Vivek K. Patel” name is replaced with “Vivek Patel”. The chapter and book have been updated with the change.

The updated version of this chapter can be found at https://doi.org/10.1007/978-981-33-4176-0_33 © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0_43

C1

Author Index

A Abhishek, Kumar, 173, 183, 495 Alloli, Mahalaxmi, 305 Alloli, Omkar, 305 Arif, Mohammad, 433

B Babu, M. Sreedhar, 297, 305 Badheka, Kedar, 105 Badheka, Vishvesh J., 13, 45, 67, 105, 211, 223, 387 Bassan, G. D., 419 Behera, Gobinda Chandra, 83 Bhavsar, Keval, 457

C Chatterjee, Suman, 173 Chaudhari, Mrunalkumar D., 157 Chaudhari, Rakesh, 123 Chaudhuri, Paritosh, 343 Chopde, Vaibhav, 495 Choudhary, Pulkit, 321 Chourasia, Sajan, 285

D Dalal, Milind, 321 D’Alessandro, Giampaolo, 235 Dani, Minal S., 197 Daphale, Nikhil P., 297 Darshan, Solanki, 67 Dasurkar, Kshitij, 305 Datta, Saurav, 83

Dave, I. B., 197 Desai, Darshit K., 45 Devani, Amit, 495 Dinbandhu, 173, 183

F Fuse, Kishan, 223

G Gawhade, Kunal, 399 Giriyapur, Arunkumar C., 375, 473 Gohel, Dharmik, 457 Gupta, Hemant, 353 Gupta, Nikita, 3, 37

H Harwani, Deepika M., 387 Hosmani, Anand K., 305

J Jadam, Thrinadh, 83 Jadav, Harshadkumar H., 133, 223 Jain, Neelesh Kumar, 95 Jain, Pushpdant, 145, 485 Jaynish, Idhariya, 67 Jha, Nitesh Kumar, 45

K Kadam, Abhinandan D., 297 Kadam, Akshay A., 297

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. K. Parwani et al. (eds.), Recent Advances in Mechanical Infrastructure, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-981-33-4176-0

511

512 Kango, Saurabh, 257, 433 Khimani, Farhan, 211 Konkatti, Kartik, 419 Kumar, Akshay, 3 Kumar, Gunjan, 353 Kumari, Soni, 83, 183 Kumar, Pradip, 83 L Lakdawala, Absar, 285 M Mahant, Devang, 133 Mahapatra, Siba Sankar, 173 Maniar, Nirav P., 411 Mansaram, Mahajan Vaibhav, 173 Mehta, Kush, 223 Mehta, Manish V., 157 Mekrisuh, Kedumese u, 245 Monte de, Filippo, 235 N Naik, Bharat, 305 Nanavati, Purvesh K., 67 Nandi, Goutam, 83 P Palani, I. A., 95 Panchal, Jaimin, 457 Panchal, Maulik, 343 Pandya, Maharshi, 67 Parikh, D. M., 123 Parikh, Meet, 313 Parmar, Mann P., 265 Parwani, Ajit Kumar, 313, 321, 331, 343 Patel, Chintan, 67 Patel, Deep R., 265 Patel, Naishadh P., 133 Patel, Nisarg, 211 Patel, Rajesh S., 265, 285 Patel, Vivek K., 265 Patel, Vivek, 387 Petare, Anand, 95 Prajapati, Ravi, 331 R Rajkumar, D. R., 55

Author Index Raj, Pranav, 399 Rajput, Chetansingh, 183 Ramkumar, PL., 3, 37, 399 Raval, Pooja, 411

S Sahu, Anshuman Kumar, 173 Sahu, Santosh Kumar, 83 Santhy, K., 55 Sathavara, Parth, 343 Shah, Dhruv, 13 Shah, Sanil, 313, 331 Sharma, Daulat Kumar, 133 Sharma, Nitin, 433 Sharma, Rajiv, 443 Shukla, Aman, 3 Shukla, Dinesh Kumar, 433 Singh, Dushyant, 245, 257 Sinha, Shivam Kishore, 495 Sreedhar Babu, M., 275

T Talli, Amit, 375, 473 Tanna, Vipul, 443 Thaker, Sudhir, 411 Thakkar, Viral, 331 Thanki, Pradeep, 411 Thomas, Merwyn, 305

U Udayraj, 245 Umat, Hemendrasinh, 183 Unni, Rajshekhar V., 275 Upadhyay, Gautam, 133, 223

V Vaghela, Harsh, 313 Varghese, Lijo, 145 Virani, Romin, 321 Vora, Gnanesh, 183 Vora, Jay J., 123, 157

X Xavier, J. Francis, 485