Engineering Pedagogy: A Collection of Articles in Honor of Prof. Amitabha Ghosh 9811980152, 9789811980152

Table of contents :
Foreword by Patron of the Symposium on Engineering Pedagogy Held on March 20, 2022
Preface
About Prof. Amitabha Ghosh
Contents
About the Editors
Untitled
1 Distinguishing Features of Engineering Pedagogy
1.1 Introduction
1.2 Challenges in Imparting Technical Education
1.3 Improving the Effectiveness of Lectures
1.4 Importance of Tutorials in Undergraduate Education
1.5 Teaching in a Laboratory
1.6 Importance of Toys and Models
1.7 Preparing a Good Question Paper
1.8 Issues of Intellectual Property Rights
1.9 Supervising a Project
1.10 Teaching of Professional Ethics
1.11 Conclusion
References
2 Pedagogical Teaching—Teachers’ Beliefs, Capabilities, and Examples
2.1 Introduction
2.2 Teaching Pedagogy
2.2.1 Cooperative Training/education [11–13]
2.2.2 “Toys in the Loop” [14–17]
2.2.3 ‘De-rusting’ or Reviewing the Perquisites Knowledge [18, 19]
2.2.4 “Everyday Engineering Examples (E3s)” [20, 21]
2.3 Conclusions
Appendix
References
3 Growth Mindset in Engineering Pedagogy for Attitude Building with Metacognition of Engineering Students
3.1 Introduction
3.2 Growth Mindset Pedagogical Framework: A Vision for Engineering Pedagogy
3.3 Conclusion
References
4 A Combination of Innovative Pedagogical Theories to Enhance the Learning Output—A Case Study with Engineering Students
4.1 Introduction
4.2 Initial Conditions
4.3 Design of Course Content
4.4 Evaluation and Assessment Strategy
4.5 Delivering the Lecture
4.6 Experiments with Examination Patterns
4.7 Reward Policy for Student Motivation
4.8 Gross Outcome of Adopted Pedagogy
4.9 Conclusions
References
5 Effective Online Teaching and Evaluation Methods
5.1 Introduction
5.2 Online Teaching
5.3 Grading
5.3.1 Assignments
5.3.2 Online Examination
5.4 Conclusion
References
6 Internet-Based Learning and Teaching of a Subject by Self-prepared Notebook
6.1 Introduction
6.2 Methodology
6.2.1 Numerical Approaches for Solid Mechanics
6.3 Discussion of IbLT
6.4 Conclusions
References
7 Computational Demonstration for Classroom Teaching of Classical Mechanics
7.1 Introduction
7.2 Problem Definition
7.3 Free Vibration Analysis
7.3.1 Numerical Solution of Ordinary Differential Equation (ODE)
7.3.2 Modal Approach
7.4 Forced Harmonic Vibration
7.4.1 Solution in Physical Coordinates
7.4.2 Solution in Modal Coordinates
7.5 Conclusion
References
8 Ethics in Publishing
8.1 Introduction
8.2 Some Information About Intellectual Property Rights
8.3 Copyright Laws
8.4 Obtaining Permissions for Materials from Other Sources
8.5 When is the Copyright Permission not Needed?
8.6 Issues of Authorship
8.7 Self-plagiarism
8.8 Similarity Checking
8.9 Conclusion
References
9 Innovation and Intellectual Property Rights in Engineering Curriculum: A Pedagogy for Higher Educational Institutes
9.1 Introduction
9.2 Background
9.2.1 Innovations and IPRs
9.3 Problem Formulation
9.3.1 IPR in the Curriculum
9.4 Research Methodology
9.4.1 Course Objectives
9.4.2 Course Outcomes
9.4.3 Contents of the Syllabus
9.4.4 Teaching Methodology
9.5 Discussions
9.6 Conclusion
References
10 A Pedagogical Gadget for Teaching Heat Transfer
10.1 Introduction
10.2 Pedagogical Gadget and Possible Experiments
10.2.1 Newton’s Law of Cooling
10.2.2 Concept of Specific Heat Capacity
10.2.3 Insulation Effect
10.2.4 Absorptivity of Black Color
10.2.5 Change in Diffusion with Temperature
10.3 Survey and Feedback on Pedagogical Gadget
10.3.1 Response to Statement 1
10.3.2 Response to Statement 2
10.3.3 Response to Statement 3 and 4
10.3.4 Response to Statement 5 and Questions 6 and 7
10.3.5 Response of Teachers to MCQ
10.4 Educational Assessment Based on Test
10.5 Conclusion
References
11 Uncertainty Quantification—An Eternal Future of Engineering and Technology
11.1 Introduction
11.2 Uncertainty Quantification in Different Engineering Domains
11.3 Uncertainty in Few Physical Phenomena
11.3.1 Uncertainty in Number System
11.3.2 Uncertain Space–Time Domain
11.4 Design of UQ Course Work
11.4.1 Sampling Techniques
11.4.2 Surrogate Models Construction and Validation
11.4.3 Uncertainty Analysis
11.4.4 Uncertainty Optimization
11.5 Importance of UQ Course for Engineering Undergraduates
11.6 Conclusions
References
12 Introducing the Basic Quantities of Mechanics
12.1 Introduction
12.2 Elementary and composite quantities
12.3 Some simple experiments
12.4 Conclusion
13 Practicing Hydraulic Autofrettage for Strengthening a Gun Barrel: Critical Issues and Challenges
13.1 Introduction
13.2 Mechanics of Hydraulic Autofrettage
13.2.1 Initiation of Yielding
13.2.2 Elastic–plastic Stress Analysis During Pressurization
13.3 The Process of Hydraulic Autofrettage of a Barrel
13.4 Critical Issues in Hydraulic Autofrettage
13.4.1 Selection of Autofrettage Fluid
13.4.2 Preparation of Mandrel and Sealing System
13.4.3 Bore Surface Preparation for Sealing System
13.4.4 Application of Autofrettage Pressure/Test Pressure
13.4.5 Low-Temperature Treatment
13.4.6 Measurement of Pressure Exterior Expansion
13.5 Abnormalities and Causes of Failure
13.6 Dos and Don’ts During the Process of Hydraulic Autofrettage
13.7 Conclusions
References
14 Biointerface Phenomena in Biological Science and Bioengineering: Importance of Engineering Courses
14.1 Introduction
14.2 Thermodynamics of Biointerfacial Aspects
14.3 Biointerfacial Phenomena in Biological Sciences
14.3.1 Molecular Self-Assembly
14.3.2 Formation of Micelles
14.3.3 Bilayers
14.3.4 Vesicles
14.3.5 Protein Folding
14.3.6 Protein Unfolding and Aggregation
14.4 Biointerfacial Phenomena in Bioengineering
14.4.1 Implant Biomaterials
14.4.2 Biosensors
14.4.3 Drug Delivery
14.4.4 Nanomedicine
14.4.5 Tissue Engineering
14.5 Conclusions
References
15 Contact of a Cylindrical Shell with a Flat Frictionless Rigid Substrate
15.1 Introduction
15.2 The Contact Problem
15.2.1 Analysis Using Cosserat Shell Theory
15.2.2 Analysis Using Shear Deformation Shell Theory
15.2.3 Analysis Using Flügge-Lur’e-Byrne Shell Theory
15.2.4 Finite Element Simulation
15.3 Results and Discussion
15.3.1 Comparison Between Displacements
15.3.2 Comparison Between Contact Pressure Distribution
15.3.3 Comparison Between Applied Load Versus Contact Patch Length Plots
15.4 Conclusion
15.5 Future Study
References
16 Kinematics of Mechanisms ain’t an Old Hat!
16.1 Genesis, Early Developments, and Conflicts Therein
16.1.1 Mechanisms
16.1.2 Kinematics
16.1.3 Kinematics, Mechanisms, and Machines
16.2 Pedagogy and Practice
16.2.1 Before Reuleaux
16.2.2 During Reuleaux
16.2.3 After Reuleaux
16.3 Expansion in the Twentieth Century and After
16.3.1 No New Elements!
16.3.2 Open Chains and Robotics
16.3.3 Compliant Mechanisms at Multiple Size Scales
16.4 What Does the Future Hold?
16.4.1 Look Back to Look Forward
16.4.2 Animal as a Machine and Vital Mechanisms
16.4.3 Future Pedagogy in Kinematics and Mechanisms
16.5 Closure
References

Citation preview

Uday Shanker Dixit Raghu Echempati Sudip Dey   Editors

Engineering Pedagogy A Collection of Articles in Honor of Prof. Amitabha Ghosh

Engineering Pedagogy

Uday Shanker Dixit · Raghu Echempati · Sudip Dey Editors

Engineering Pedagogy A Collection of Articles in Honor of Prof. Amitabha Ghosh

Editors Uday Shanker Dixit Department of Mechanical Engineering Indian Institute of Technology Guwahati Guwahati, India

Raghu Echempati Department of Mechanical Engineering Kettering University Flint, MI, USA

Sudip Dey Department of Mechanical Engineering National Institute of Technology Silchar Silchar, India

ISBN 978-981-19-8015-2 ISBN 978-981-19-8016-9 (eBook) https://doi.org/10.1007/978-981-19-8016-9 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 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

Foreword by Patron of the Symposium on Engineering Pedagogy Held on March 20, 2022

It gives me immense pleasure to write a Foreword for the book entitled Engineering Pedagogy—A Collection of Articles in Honor of Prof. Amitabha Ghosh published by Springer Nature. I congratulate Dr. Uday Shanker Dixit, Professor in the Department of Mechanical Engineering, and Head, Center for Indian Knowledge Systems at Indian Institute of Technology (IIT) Guwahati; Dr. Raghu Echempati, Professor in the Department of Mechanical Engineering, Kettering University, and Honorary Professor in the Department of Mechanical Engineering at IIT Guwahati; and Dr. Sudip Dey, Associate Professor in the Department of Mechanical Engineering at National Institute of Technology (NIT), Silchar. They have put a lot of efforts in editing the book and also contributing articles. The book contains 16 chapters authored by senior faculty members of premier institutes of India including IITs, NITs, and Indian Institute of Science. This book is an outcome of a symposium on Engineering Pedagogy that was organized on March 20, 2022, in the honor of Prof. Amitabha Ghosh, former Director of IIT Kharagpur, and Long-time Faculty Member of IIT Kanpur. Even after attaining the age of 80, Prof. Ghosh is actively involved in the education-related activities. He

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Foreword by Patron of the Symposium on Engineering Pedagogy Held …

has been helping IIT Guwahati by delivering lectures and participating in a number of important meetings. Department of Mechanical Engineering, very aptly, organized this symposium in his honor. It was decided in the symposium to bring out a book based on the papers presented and also collecting some other important papers on the subject of pedagogy. This book is informative as well as simulative. Apart from the topics on prevalent teaching methodologies, online teaching, and intellectual property rights, it has several articles suggesting innovative pedagogical techniques. This book will be very useful for budding faculty members of engineering. There are a lot of challenges in educating the engineering students in this century. Engineers have to be trained for becoming the leaders of change with emphasis on sustainability. Compared to the last century, class sizes and variety of students have increased tremendously. Hence, continuous upgradation in the teaching skills in the need of the hour. National Education Policy 2020 of India also gives a lot of emphasis to improving pedagogy. In fact, among Vedang (six auxiliary disciplines) of Ancient India, Siksha, in modern terms pedagogy, is mentioned first. It is important that leading academicians share their experience of best practices in education for the overall improvement of teaching–learning process. This book is an attempt in that direction. T. G. Sitharam Chairman, All India Council for Technical Education New Delhi, India

Preface

Professor Amitabha Ghosh, former Director of the Indian Institute of Technology (IIT) Kharagpur (IITKGP) and former Professor and Head of Mechanical Engineering at IIT Kanpur (IITK), is currently working as Honorary Scientist of the Indian National Science Academy, New Delhi, and the National Academy of Sciences, India, Prayagraj. He was born on December 3, 1941, in a remote village of Birbhum district, West Bengal. As he completed the age of 80 on December 2, 2021, he had served more than 56 years as Teacher. He is Highly Reputed, rather popular, Faculty Member of IITK from 1971 to 2006, which includes his tenure as Director of IITKKGP from April 1997 to April 2002. Professor Ghosh has trained several students, both formally and informally, in the field of classical mechanics. Several of his former students, admirers, and colleagues decided to organize a lecture series and symposium on Engineering Pedagogy to commemorate the accomplishments of Prof. Ghosh and to get benefitted from his teachings. Accordingly, 12 online lectures were arranged on March 5, 6, 12, 13, and 19 in the year 2022. An online symposium on Engineering Pedagogy was also arranged on March 20, 2022, with the august presence of Prof. Ghosh. These online events were organized by the Department of Mechanical Engineering at IIT Guwahati (IITG) under the patronage of Prof. T. G. Sitharam, Director of IITG, and under the chairmanship of Prof. K. S. R. Krishna Murthy, Head of Mechanical Engineering Department at IITG. It was decided to publish selected high-quality papers presented in the symposium in the form of a book. Later, the editors decided to invite a few more chapters from the experts and bring out a nice collection of chapters on teaching pedagogy in the honor of Prof. Ghosh, thus, this book. Engineering Pedagogy has some distinct features, and it is very important for the budding faculty members to learn from the experience of veteran engineering faculty. Sixteen chapters contained in this collection are believed to be highly useful for academicians and, especially, the young faculty members. Chapter 1 “Distinguishing Features of Engineering Pedagogy” highlights many important features of engineering pedagogy. It also highlights the importance of toys in teaching– learning process. Chapter 2 “Pedagogical Teaching—Teachers’ Beliefs, Capabilities, and Examples” elaborates on certain points mentioned in Chap. 1. This chapter vii

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highlights four important aspects in Engineering Pedagogy in which “toys in loop” is also an important aspect. The author has presented a number of practical examples of using demonstration toys in classroom teaching. Chapter 3 “Growth Mindset in Engineering Pedagogy for Attitude Building with Metacognition of Engineering Students” highlights the importance of growth mindset with metacognition in engineering pedagogy. Chapter 4 “A Combination of Innovative Pedagogical Theories to Enhance the Learning Output—A Case Study with Engineering Students” presents an interesting case study of teaching Engineering Mechanics using innovative pedagogical methods. Pedagogical innovations are known to improve the performance of the students. Chapter 5 “Effective Online Teaching and Evaluation Methods” suggests some innovative methods of online teaching and evaluation. These methods were tried and tested by the author. Chapter 6 “Internet-Based Learning and Teaching of a Subject by Self-prepared Notebook” presents a case study of teaching a course on solid mechanics with the help of Internet resources. Chapter 7 “Computational Demonstration for Classroom Teaching of Classical Mechanics” presents an example of teaching of a course on vibrations with the help of computational demonstration. The entire procedure of writing code for a two degree of freedom problem has been explained in detail. Chapters 8 “Ethics in Publishing” and 9 “Innovation and Intellectual Property Rights in Engineering Curriculum: A Pedagogy for Higher Educational Institutes” highlight the importance of students’ awareness regarding intellectual property rights (IPR). As publication and filing patents are the integral part of higher education, engineering students should be made aware about it, so that inadvertently no IPR infringement occurs by them. Chapter 10 “A Pedagogical Gadget for Teaching Heat Transfer” discusses how a simple low-cost pedagogical gadget can be used for conducting several experiments of heat transfer course. Chapter 11 “Uncertainty Quantification—An Eternal Future of Engineering and Technology” argues introducing a course on uncertainty quantification because uncertainty is unavoidable in engineering problems. Understanding uncertainty in quantifiable terms will be helpful in mitigating its adverse effect. Chapter 12 “Introducing the Basic Quantities of Mechanics” discusses how the concepts like kinetic energy and momentum can be explained to students with the help of easy demonstrations. Last four chapters are specialized chapters on engineering pedagogy. Chapter 13 “Practicing Hydraulic Autofrettage for Strengthening a Gun Barrel: Critical Issues and Challenges” lucidly explains the concept of autofrettage. Autofrettage of a gun barrel is an interesting example for explaining the concept of residual stresses in solid mechanics. Jointly authored by persons from industry and academia, this chapter also lists a number of practical aspects, which are normally not available in the textbooks. Chapter 14 “Biointerface Phenomena in Biological Science and Bioengineering: Importance of Engineering Courses” explains the concept of biointerface phenomena and their inclusion in engineering curricula. Chapter 15 “Contact of a Cylindrical Shell with a Flat Frictionless Rigid Substrate” is a topic of shell theory, which students normally find difficult to understand. The authors of this chapter have explained the numerical modeling of contact of cylindrical shell with a flat frictionless rigid substrate in a simplified manner. Last chapter is about the evolution of machines and

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mechanisms. The author discusses how mechanisms topic ought to be taught to the current generation of students as modern topics creep into the curriculum. We are grateful to all the authors for contributing their chapters. Besides the authors, we also thank Dr. M. K. Sinha of NIT Hamirpur, Dr. B. N. Panda and Prof. D. Chakraborty of IIT Guwahati, and Prof. S. Pandey, former Professor of IIT Delhi for helping in reviewing of some chapters. Finally, we are grateful to Prof. T. G. Sitharam, Director, IIT Guwahati, Prof. K. S. R. Krishnamurthy, Head of the Department of Mechanical Engineering, IIT Guwahati, and Prof. S. Bandyopadhyay, Director, NIT Silchar. We await the feedback of the readers. Guwahati, India Flint, USA

Silchar, India

Uday Shanker Dixit [email protected] Raghu Echempati [email protected] [email protected] Sudip Dey [email protected]

About Prof. Amitabha Ghosh

Prof. Amitabha Ghosh, former Director of IIT Kharagpur (1997–2002), former Professor and Head of Mechanical Engineering at IIT Kanpur (1971–2006), and former Honorary Distinguished Professor of IIEST, Shibpur (2007–2021), is currently working as Emeritus Scientist of the Indian National Science Academy (INSA), New Delhi, and Honorary Scientist of the National Academy of Sciences, India (NASI), Allahabad. He was born on December 3, 1941, in a remote village in Birbhum near to the Jharkhand boarder. After finishing his school education from the village high school in 1956, he received his ISc degree from Suri Vidyasagar College under Calcutta University, in 1958. He received his B.E., M.E., and D.Phil. degrees from Calcutta University from Bengal Engineering College, Shibpur (now IIEST Shibpur), in 1962, 1964, and 1969, respectively. He received three Calcutta University Gold Medals for standing first class first with record marks among the students of all branches both at the Bachelors’ and Masters’ levels. He started his teaching career as Lecturer in Mechanical Engineering at Bengal Engineering College in May 1965; then he joined IIT Kanpur as Assistant Professor in January 1971. In June 1975, he became Professor at IIT Kanpur. He spent one and half years at Technical University, Aachen, Germany, (1977–1978) as Senior

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About Prof. Amitabha Ghosh

Fellow of the Alexander von Humboldt Foundation. Subsequently, he visited this university many times as AvH Fellow during 1980–2013. He served IIT Kharagpur as its Director from April 1997 to April 2002. After his retirement from IIT Kanpur in 2006, he was invited to join IIEST Shibpur as Honorary Distinguished Professor. He taught at IIEST Shibpur from January 2007 to December 2021 during which period he also served as Senior Scientist of INSA, New Delhi, and NASI, Allahabad. His primary areas of professional research are basic mechanics, kinematics and mechanisms, robotics, and advanced manufacturing. He has served as Chairman of a number of national institutions like CSIR-CMERI Durgapur (2001–2013), NITTTR Bhopal (2009–2014), and National Level Committees of the Department of Science and Technology, Government of India, and CSIR. He also served as Indian Coordinator of Indo-Japan and Indo-US research collaboration programs of Government of India. He started robotics education in India in 1983 and founded the first Robotics Center of the country in 1986 at IIT Kanpur. He also started the School of Medical Science and Technology at IIT Kharagpur in 2001 bringing medical education into the IIT system for the first time in India. During his tenure as Chairman of Research Council of CMERI Durgapur, he started the country’s first multi-institutional Masters’ program on Mechatronics involving IIEST Shibpur, CMERI Durgapur, CEERI Pilani, and CSIO Chandigarh. This program is still continuing as a popular program for many students interested in robotics. Professor Ghosh was the three-member Anandakrishnan committee formed by the Ministry of Education, Government of India, and based on this committee’s recommendation, the new IIEST system was started. Professor Ghosh has also served in the Ministry’s pay revision committee for the engineering and management institutions of India. After joining IIEST Shibpur, Prof. Ghosh also joined an initiative to start the South Howrah Citizens’ Forum and is still continuing as its Founder President. This civil society forum’s primary objectives were to resolve the age-old “town versus gown” problem by organizing many educational programs of different types in collaboration with IIEST Shibpur and to organize various events and public lectures by eminent personalities from all walks of life. Professor Ghosh also mentored the new and innovative rural healthcare program that was initiated by a group of eminent doctors from Kolkata. Under this program, a number of schools were started for developing skill in healthcare-related expertise at various districts of West Bengal, Assam, and Bihar. It is still expanding, and already more than 3000 young boys and girls have been trained, most of whom are already employed. Apart from setting up of these schools for skill, rural health kiosks have been started in remote rural areas taking primary medical care to the door steps of the people of rural India. He has authored ten books published in India and abroad quite a few of those being very popular as text in India and abroad. He has received many awards including the Distinguished Teacher and Institute Fellow awards of IIT Kanpur, Prof. Jay Krishna Memorial award for Research Excellence of the Indian National Academy of Engineering, Distinguished Alumnus award and D.Sc. (hc) of Bengal Engineering

About Prof. Amitabha Ghosh

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and Science University, Shibpur, and D.Sc. (hc) of NIT Sikkim. Professor Ghosh is Fellow of all the four national science and engineering academies of India. He also writes scientific articles in Bengali in magazines and has published two novels in Bengali. The two dramas written by him on some little known aspects of Galileo’s discovery of telescope and on the unknown life of Aryabhata have been staged and praised extensively.

Contents

1

Distinguishing Features of Engineering Pedagogy . . . . . . . . . . . . . . . . Uday Shanker Dixit

2

Pedagogical Teaching—Teachers’ Beliefs, Capabilities, and Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Raghu Echempati

17

Growth Mindset in Engineering Pedagogy for Attitude Building with Metacognition of Engineering Students . . . . . . . . . . . . Anjali Sharma, Sukanya Singh, and Ram Prakash Sharma

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4

A Combination of Innovative Pedagogical Theories to Enhance the Learning Output—A Case Study with Engineering Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shashank Pathak

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5

Effective Online Teaching and Evaluation Methods . . . . . . . . . . . . . . . Dilip Kumar Pratihar

6

Internet-Based Learning and Teaching of a Subject by Self-prepared Notebook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Arun K. Singh

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Computational Demonstration for Classroom Teaching of Classical Mechanics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Abhijit Sarkar

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7

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8

Ethics in Publishing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Uday Shanker Dixit

9

Innovation and Intellectual Property Rights in Engineering Curriculum: A Pedagogy for Higher Educational Institutes . . . . . . . 113 Saurabh Verma and Sudip Dey

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Contents

10 A Pedagogical Gadget for Teaching Heat Transfer . . . . . . . . . . . . . . . . 127 Nilkamal Mahanta, Uday Shanker Dixit, and J. Paulo Davim 11 Uncertainty Quantification—An Eternal Future of Engineering and Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Sudip Dey and Kritesh Kumar Gupta 12 Introducing the Basic Quantities of Mechanics . . . . . . . . . . . . . . . . . . . 157 Amitabha Ghosh 13 Practicing Hydraulic Autofrettage for Strengthening a Gun Barrel: Critical Issues and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 A. K. Roy, S. M. Kamal, R. U. Patil, and V. V. Rao 14 Biointerface Phenomena in Biological Science and Bioengineering: Importance of Engineering Courses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Rushikesh Fopase, Aquib Jawed, and Lalit M. Pandey 15 Contact of a Cylindrical Shell with a Flat Frictionless Rigid Substrate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Aishwarya Kasarla and Sovan Lal Das 16 Kinematics of Mechanisms ain’t an Old Hat! . . . . . . . . . . . . . . . . . . . . 229 G. K. Ananthasuresh

About the Editors

Dr. Uday Shanker Dixit is presently a professor in the department of mechanical engineering and Head of Center for Indian Knowledge System at Indian Institute of Technology (IIT) Guwahati. He received B.E. from IIT Roorkee in 1987, M.Tech. and Ph.D. in mechanical engineering from IIT Kanpur in 1993 and 1998 respectively. Dr. Dixit is actively engaged in research in various areas of design and manufacturing for last three decades. Most of his research work is focused on modelling of manufacturing processes and involves finite element analysis of elastoplastic problems. He has also contributed in design optimization. He has extensively used finite element and soft computing tools to design and manufacture mechatronic systems. He has authored/co-authored 140 journal papers, 139 conference papers, 42 book chapters, and seven books in mechanical engineering. He has co-edited nine books related to manufacturing and 11 special issues of journals. He has guided 16 doctoral and 54 masters’ students. Dr. Dixit has investigated a number of sponsored projects and developed several courses. He is a Fellow of Indian Welding Society, and National Advisory Committee member of International and All India Manufacturing, Technology and Design Conference. He was a Board Member of Indian Institute of Technology Kanpur during 2018–21. Dr. Raghu Echempati is currently a professor of mechanical engineering at Kettering University, USA. His academic and industrial consulting experiences span over 4 decades. His main areas of interest and expertise are in mechanical engineering design, structural analysis, and manufacturing simulation with real-life applications to automotive and other systems. He received several industrial internships, teaching and research, and professional society awards including the Indian Railways (RDSO), ARDB, Postdoc (University of Florida), Bosch, GM, GEMA (Chrysler), ASME Fellow, McFarland (SAE), Oswald (study abroad), Applied Researcher (KU), Fulbright (India and Thailand), and Oxford-Erskine Fellowship (New Zealand). He has supervised over 250 undergraduate/graduate and research student theses, and reviewed several technical articles, papers, textbooks, and research proposals for various domestic and international conferences, journals, scientific bodies, and

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About the Editors

publishers. He has published over 170 applied research papers in peer-reviewed journals and conference proceedings of repute. Dr. Sudip Dey works as an assistant professor in the mechanical engineering department at National Institute of Technology (NIT) Silchar, India. Previously, he was a post-doctoral researcher at Leibniz-Institut für Polymerforschung Dresden e. V., Germany, worked with Prof. Gert Heinrich (TU Dresden, Germany). He obtained his Bachelor’s and doctoral degree in Mechanical Engineering Degree from Jadavpur University, India. His field of specialization is Mechanics, Design, and Materials. He has more than 20 years of experience in research, teaching, industrial and professional activities. He pioneered the research work on Uncertainty Quantification (UQ), and stochastic mode shapes. He pioneered and introduced the first course on “Uncertainty Quantification” (ME 483) in the syllabus of undergraduate and post-graduate level study globally. His research interests include Classical to Quantum Mechanics, Molecular Dynamics, Tribology, Metamaterials, Multi-scale analysis, Uncertainty Quantification, Digital Twin, Multi-functional Composites and Graded structures, and finite element analyses with an emphasis on computational mechanics and modelling.

Chapter 1

Distinguishing Features of Engineering Pedagogy Uday Shanker Dixit

1.1 Introduction The word pedagogy is a combination of two Greek words—paidos (boy) and agogos (leader). Thus, the pedagogy comprises the techniques of leading or training the students. In the modern age, all nations are trying to educate their citizens. Providing health and education to all has become sacred duty of the governments. However, educating the students of different capabilities and taste is by no means an easy task. Due to this, subject of pedagogy started gaining a lot of importance since last 2–3 decades. In this article, some features of engineering pedagogy, which are distinct form general pedagogy will be discussed. Art of imparting professional education is considerably different from the art of teaching of a particular subject. Engineering is a profession and purpose of engineering education is also to inculcate the professionalism among students. Professionalism comprises ability to carry out the specific tasks as per the expectation of the society as well as ethics. There are several definitions of engineering, but all of them emphasize service to the mankind. As per the Accreditation Board for Engineering and Technology (ABET), “Engineering is the profession in which a knowledge of the mathematical and natural sciences gained by study, experience and practice is applied with judgment to develop ways to utilize economically the materials and forces of nature for the benefit of mankind”. This definition brings out the following salient features of engineering: • Engineering is a profession. A profession comprises disciplined group of individuals adhering to ethics, who are perceived by public as possessing the knowledge and skill in the specialized area. These professionals gain knowledge through special training and education. U. S. Dixit (B) Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_1

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• Engineers apply the scientific and technological knowledge as well as empirical practices for the benefit of mankind. Thus, engineers not only need the knowledge but also some skill. • Engineers have to use natural resources in an economical manner using proper judgment. Although the word “sustainability” is not mentioned in the definition, it is implied that engineer should aim for providing a sustainable solution. Three main pillars of sustainability are environment, economics and society. If one interprets word “economically” in a broader sense in ABET definition, it also means utilizing materials and forces of nature without excessive taxing of the environment. Obviously, benefit to mankind includes societal (as well as cultural) aspects. It is also pertinent to mention that engineering is different from science as well as technology. Science originated from human’s natural quest for knowledge. Often a scientist unravels the secrets of nature without bothering if it will be of some use to society or not. For example, there is a natural curiosity in most of us if we are alone in the universe or there is some form of life in another planet. For this purpose, agencies like National Aeronautics and Space Administration (NASA) focus on space exploration. True, as a by-product space exploration produces some technologies for the direct benefit of mankind, but the mission statement of NASA highlights expansion of human knowledge through new scientific discoveries as its core objective. Similarly, Newton developed three laws of motion not keeping any specific application in mind, but merely for understanding the response of a particle to forces. Same thing can be said about Boyle’s law of gases or E = mc2 equation of Einstein providing equivalence between mas and energy. As distinct from science, technology is the creation of any product, process or method for achieving some purpose. Invariably, technology is developed based on scientific knowledge but it may well be based on craftsmen knowledge, where the scientific principle may not be known precisely. An example of technology is the very commonly found slider-crank mechanism. It is a device to convert a reciprocating motion into rotary motion, which can be fabricated by ‘clever’ arrangement of some links with the help of pin joints. One does not need any specific knowledge of physics to fabricate this mechanism; its motion can be fairly analyzed by geometry graphically. That is another thing that a need for systematic analysis of motion and the influence of force on motion developed a scientific subject, viz. Theory of Machines. Engineering makes use of science, technology, social science, environmental science, economics and traditional practices to develop structures, machines, apparatus, processes and methods for the optimum utilization of resources of the nature. Figure 1.1 distinguishes science, engineering and technology graphically. It is clear that an engineer has to be imparted the knowledge of science, technology as well as social science. At the same time, in order to develop good professionals, the students should be trained in the team work and practice of ethics. In this chapter, some salient features of engineering pedagogy will be highlighted.

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Fig. 1.1 Graphical illustration of the difference between science, technology and engineering

1.2 Challenges in Imparting Technical Education Engineering education aims at imparting theoretical as well as practical education to students. An engineering graduate should be adept at applying theory to practice. At the same time, she/he should be disciplined, dedicated, sincere, hardworking and honest. No matter how much knowledgeable, if the engineer is not able to apply the knowledge in practice, it is of no professional value. Even if engineering student is provided less information, but if she/he is creative, she/he can contribute a lot to society. Thus, an engineering educator’s role does not stop by delivering some lectures and conducting examination on the basis of what has been taught in the class. The instructor has to impart problem-solving skills, team work, sincerity and sense of responsibility in the student. In fact, often the extra-curricular activities help a lot in achieving these goals; hence, they become more important for engineering students than for general student. National Education Policy (NEP) 2020 of India emphasizes that there should not be a hard separation between curricular and extra-curricular activities. Engineer also needs to have good communication skills. Communication is a two-way process. Good communication does not mean the ability to speak well in a particular language. It means that engineer should be able to understand the customer requirement and should be able to disseminate required information to stakeholders. Engineers often interact with a variety of people—from shop floor worker to top-level managers and from layman to well-informed customer. Hence, versatile communications skills are needed with reasonable command over language. In fact, drawing is considered as the language of engineers; hence, engineer should be good in communicating through drawings also. She/he should also be adept in communicating the concept in the form of mathematical equations or expressions; i.e., she/he should be able to communicate through mathematics also.

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There are various other personality traits, which are very important for a successful engineer. These include health, emotional stability and pleasant personality. So far, most of the personality traits were imparted to engineering students by the ambience of the engineering institutes. However, National Education Policy 2020 of India specifically emphasizes on the holistic development. As per Clause 11.3, “a holistic and multidisciplinary education would aim to develop all capacities of human beings—intellectual, aesthetic, social, physical, emotional and moral in an integrated manner. Such an education will help develop well-rounded individuals that possess critical twenty-first century capacities in fields across the arts, humanities, languages, sciences, social sciences, professional, technical and vocational fields; an ethic of social engagement; soft skills, such as communication, discussion and debate; and rigorous specialization in a chosen field or fields. Such a holistic education shall be, in the long term, the approach of all undergraduate programs, including those in professional, technical and vocational disciplines”. To achieve this objective, the engineering curriculum needs to be optimized, because total hours in a day are limited. The present era provides new challenges for engineering sector. Engineering became a lucrative profession all over the world after a few years following World War II. This trend continued till about 1990, after which there was worldwide recession in several sectors of industry. Added with this, there was an increase in the number of engineering colleges, many of them in private sectors. In particular, in India, there was a phenomenal growth in the number of engineering colleges and also increase in the number of engineering students in colleges. With the growth of engineering degree colleges, diploma and skill imparting schools lost importance. Hence, many students with aptitude for vocational certificate courses or diploma level programs started to join degree level programs. This puts tremendous pressure on the engineering instructors as they have to teach several uninterested students. Moreover, variation in the standard of students in a class has enhanced. Instructor has to impart education depending on the aptitude of the students. Bright students need challenging problems, but the poor students have to be taught with simple examples. Failing the poor students is not a solution; it demoralizes them and makes them disinterested. In fact, poor performance and low interest are part of a vicious circle as shown in Fig. 1.2. An instructor has to break this circle. Conventionally, engineering students are imparted education in three modes— lectures, tutorials and laboratory practice. All of them are equally important. In the subsequent sections, each mode of teaching is discussed in detail.

1.3 Improving the Effectiveness of Lectures Although the lecture mode of imparting education is very economical as student– teacher ratio can be kept high; however, it is not an active mode of learning. Several educationists have highlighted the problem of limited effectiveness of traditional

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Fig. 1.2 Vicious circle of low interest and poor performance

lectures [1, 2]. They also have suggested several methods of improving the performance of the lectures. Several of them relate to enhancing the interaction in the classroom. For example, Felder et al. [2] emphasized the importance of cooperative learning in which students carry out some tasks in team, inside or outside the class. Mason et al. [1] highlighted the importance of flipped classroom, in which the learning material is provided to students out of the classroom and class hours are used for discussion and interaction. In a way, it is a cooperative learning facilitated by the instructor. However, the flipped classroom concept can be successful only if the students are mature and more or less of the same level. Academically poor students do not benefit from group learning and feel shy to express their difficulties. Moreover, students may not go through the reading material and video lectures provided to them. Here are some suggestions to improve the effectiveness of conventional lecture classes: • It is noted that attendance is very less in large classes. Obviously, first and foremost task of the instructor should be to ensure proper attendance. Instructors can give some weightage for classroom participation. A common complaint by instructors is that it is not possible in a large class as the instructor cannot track which student has participated more and which has participated less. However, this problem can be solved if finally, the instructor awards the marks based on attendance alone, treating it as a quantitate measure of participation. Students who have attended a threshold number of classes may be given full marks (say 10%) and other students can be provided proportionately less marks depending on their attendance. Nevertheless, for psychological reasons, teacher should call these marks as the marks for participation and not for the attendance, so that students get a feeling that they are supposed to be active in the class and not just attend the class mechanically. Moreover, some instructors are hesitant to provide marks for

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attendance mainly because of their egos and traditional mindset. For them, word ‘participation’ instead of ‘attendance’ will be more respectable. Instructors should try to make the lecture class interactive. They should encourage questions from students. They may also ask questions to students on random basis. It is best to discuss the importance of a topic before delivering lecture. A top-down approach of teaching is more beneficial, in which first the instructor provides an overall picture of the topic and then discusses the details. It is better to provide the lecture material a couple of days before the class. Instructor can also direct the students to go through relevant videos (to be selected by instructor, because several videos may be propagating wrong concepts) available in the web. Instructors can follow a particular textbook but they should not make the students only bookish. Hence, it is important for an instructor to tell something beyond the textbook. Many students tend to become so bookish that they feel very uncomfortable if the notations are changed. Instructor should help the students in not developing this type of habit because later on in their profession they will face a variety of persons and a variety of notations! Considering that variability in the mental levels of students is very high in a typical class, instructor should target the mode, i.e., teach according to the level of majority of students. For very bright and weak students, instructor can provide some extra time separately, may be once after every 3–4 classes. Instructors should not cover a lot of material in one class. Over-teaching may be as harmful as under-teaching. It is also helpful to ask students to solve some problems in the class occasionally. These problems should be solvable in 5–10 min and may also be graded (a type of surprise quiz). Sometimes teacher may ask some students to solve the problem in the board to encourage their participation and also to improve their ability to express. Instructors should portray confidence. Too much modesty, especially in an undergraduate class, may give an impression that instructor is not well-versed with the subject and subconsciously students may lose interest in listening the lecture carefully. In the same light, instructor should not go with the book in the class but may carry notes. It is important for an instructor to be a role model for the students and give an impression that she/he puts effort in making own notes.

1.4 Importance of Tutorials in Undergraduate Education Tutorials are very important components of undergraduate education, especially for first year and second year students, although they can be useful even for senior students. In the tutorial sessions, students are supposed to solve the problems and discuss their difficulties. Concept of flipped classroom can also be practiced in the tutorial class. Educators and administrator should respect the importance of tutorials.

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As far as possible, a tutorial class should not have more than 20 students. Unfortunately, nowadays with large intake of students, size of tutorial classes has swelled considerably. Because of this many instructors handle the tutorial classes like lecture classes. Thus, the very purpose of tutorial classes gets defeated. Instructor should provide assignment sheet to all students in advance. It is better that instructor should prepare own questions. In any case, directing the students to solve the problem from the book is not good for engineering students. Instructor should at least select the good problems, which students can practice in limited time. In the tutorial class, students can solve some problems and the remaining problems can be solved as home assignments. Instructor should discuss the difficulties with the students; she/he should not sit idle in the class. Tutorial classes offer the best opportunity to help weaker students and challenge the brighter students.

1.5 Teaching in a Laboratory Laboratory teaching is not given as importance as the lecture classes, although for engineering students, it is very important. Often laboratory course is considered equivalent to half of a theory course while deciding the teaching load of a faculty member. There is a general perception that laboratory courses are handled by lab technicians and the role of a faculty member is just to conduct viva and quizzes. This attitude needs to be changed. Laboratory courses should be given full weight and instructor should actually motivate students by working with them. It has been seen that students do not pay attention to laboratory classes right from the school days. Most of the time their performance is judged by their ability to get good marks in written examination. Even the competitive examinations for getting admission to engineering are written in nature. Hence, the studious and ambitious students ignore the laboratory classes in favor of improving their theoretical understanding. In fact, an informal survey revealed that more than 75% students have not conducted any experiments in physics at their schools. In a workshop practice course, about 80% students could not use a Vernier caliper. Hence, it is very important that instructor should generate the interest about laboratory observations. Students good in theory courses need special motivation. They should learn to relate theory with experiments. Sometimes some students who are not good at theory show a lot of skill in experiments. Such type of students should be taught to interpret the results of experiments in light of the theory. Often students work in the laboratories in the group and smart students play a dominating role. Instructor should attempt effective involvement of all students; instructor’s presence and interaction can do this. In a random manner, instructor can ask a student to perform a portion of the experiment in his/her presence. Even during the time of viva, students can be asked to demonstrate or perform a portion of the experiment.

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1.6 Importance of Toys and Models In order to generate interest among students, instructors can use toys and models to supplement conventional learning. Toys are deceptively simple, but can teach complicated mechanisms. In the past, toys have been used for teaching the principles of mechanics [3]. Paul and Dixit [4] presented the design of some toys for teaching some concepts of Mechanical Engineering. These toys were developed by engineering trainee, B.Tech. and M.Tech. students. First, the task of designing and fabricating the toys was assigned to summer trainees. As they come for a very short duration ranging from one to two months, they cannot complete bigger projects. Assigning the task of designing and fabricating a couple of toys is more fulfilling for students as they get exposure to almost all aspects of design and fabrication in a short period along with getting a feeling of accomplishment. Getting positive results with trainee students, it was decided to offer development of educational toys as B.Tech. projects, which are of one-year duration. Considering the longer duration, students were supposed to develop several toys. Number of toys to be developed in one year was not pre-decided. Instead, students were given the task of design and fabrication of one toy first within a period of few weeks. Based on the actual time taken to develop the toy, the target for the next toy was fixed. This scheme did not put pressure on students and students could work and learn at their own pace. Moreover, encouraged by their accomplishments in developing toys, they could increase their efficiency. First B.Tech. project of this kind was assigned to students Mr. Naresh Nallamala and Mr. Suman Kumar, supervised by Dr. Uday S. Dixit (author) and Dr. Vinayak Kulakarni in July 2009. Students completed the project entitled “Design and Fabrication of Educational Toys and Models” in April 2010 and developed 9 toys. Examiners liked their efforts and students also got a feeling of satisfaction. Second project entitled “Design and Fabrication of Models of Metal Forming Processes” was completed by Mr. Abhishek Khalkho in 2011 and was supervised by Dr. Uday S. Dixit and Dr. S. N. Joshi. In this project, 5–6 models of various manufacturing processes could be made. Figure 1.3 shows a toy that was developed in an evolutionary manner to teach the concept of siphon. This toy has been named Thirsty doll, in which a wooden doll is kept inside a transparent plastic jar. A siphon is hidden in the hollow portion of the doll, which is made by bending a drinking straw and making it stable with a rubber band. One end of the straw passes through a bottom hole, in which the straw gets tightly pressed and furthermore a sealant is used to prevent any leakage at the interface of straw and jar. The other end of the straw is open insider the jar, such that when the water level rises in the jar, it also rises to the same level in the pipe. When the water is poured in the jar, its level keeps on increasing, but when the level reaches the highest point of the siphon, viz. U-turn point, the siphon action starts and the water is drained out. The lip of the doll is matched with the highest point of siphon; hence, outwardly it appears that as the water touches the lip of the doll, it starts draining from the water and the doll is not able to drink it. Interestingly, when the toy is demonstrated to students (starting from school to postgraduate level), no

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Fig. 1.3 Thirsty doll toy: a complete toy showing a doll, b siphon with doll removed

student could guess that there is a simple siphon inside. Most of them started thinking in terms of a valve that opens at a particular hydrostatic pressure. Figure 1.4 shows another example of an educational toy. It is a cantilever beam of adjustable length. A used hacksaw blade acted as the beam. In fact, first this was developed in 1999 as a part of a B.Tech. second year class assignment on Strength of Materials. The purpose was to verify the cantilever beam deflection formula. Later on, it was noticed that the same toy can be used to teach some concepts of sound and vibration. The beam is freely vibrated by changing its length. As the length is reduced, frequency of vibration increases, which can be observed visibly and from sound. Figure 1.5 shows a wooden model of a rolling mill prepared by Mr. Abhishek Khalkho as a part of his B.Tech. project. Such type of toys and models can be prepared even for school students to generate their interests in Science, Technology Engineering and Mathematics (STEM).

1.7 Preparing a Good Question Paper Examining a student is no less important than teaching. Examinations not only help in the certification of the knowledge gained by the students, but they also provide feedback to teachers and learners. In fact, many times examinations assist the task of learning by motivating the students to prepare the subject in a particular way. An examination is a type of sampling technique, by which the knowledge and skill of a student are judged by asking some random questions. In any sampling technique,

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Fig. 1.4 Cantilever beam of adjustable length

Fig. 1.5 Wooden model of a rolling mill

proper selection of sample is very important, on which the quality of inference about population is dependent. Hence, making a good question paper is not an easy task. In the past, often the question papers used to have a lot of descriptive type questions. As engineering focuses more on the application than on mere possession of knowledge, the trend shifted to asking more numerical type questions. Numerical type questions can assess the overall knowledge of the student as well as his or her ability to use that knowledge. An example of a descriptive type question is as follows:

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Define percentage reduction in wire drawing.

This question can be answered in several ways. Some of the answers may include a formula and some may not. Also, the student does not know in how many sentences, this question should be answered. A simple answer can be The percentage reduction in wire drawing is reduction in the area of wire divided by the initial area.

Now, consider replacing this question by a numerical type question: In a two-stage wire drawing process, 40% reduction is achieved in the first stage and 30% reduction is achieved in the second stage. Find out the overall reduction.

This question can be answered in the following way: Let A0 , A1 and A2 be the areas of wire at the beginning, after first stage and after second stage. Using the definition of percentage reduction: A0 − A1 × 100 = 40 ⇒ A1 = 0.6 A0 A0

(1.1)

A1 − A2 × 100 = 30 ⇒ A2 = 0.7 A1 = 0.42 A0 . A1

(1.2)

and

Now, the overall reduction r is calculated as r=

A0 − 0.42 A0 A0 − A2 × 100 = × 100 = 58%. A0 A0

(1.3)

It is to be noted that several steps are involved in the answer of this question, although the main concept used is just the definition of percentage reduction. In the process, student’s ability to carry out simple arithmetic operations accurately gets also tested. Unless the student knows the basic definition of percentage reduction as well as simple arithmetic, this question cannot be answered correctly. Hence, this question is better than a descriptive type question asking the definition. Only demerit is that student’s ability of communication in plain English is not tested here. Nowadays, many engineering students are very poor in scientific or technical writing. Hence, notwithstanding the importance of numerical type question, some proportion of descriptive questions may also be useful. A question paper should be balanced with respect to types of question and difficulty level. More the variety of difficulty level in a question paper, better resolution in the gradation of students can be obtained. An easy question paper can be answered by almost all student, hence, will fail to identify bright students. Similarly, a difficult question paper will not be able to distinguish mediocre students from poor students. Sometimes a difficult question can be made easier by breaking it into smaller parts. First, it helps in partial marking and second, it also provides a guideline for

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Q.1: During an orthogonal, machining with a tool of zero rake angle, cutting force (the force component in the direction of cutting velocity) is found to be 300 N and the thrust force (the force component normal to the machined surface) is found to be 200 N. (A) Sketch the free body diagram of the chip and calculate the friction and normal forces on the rake face of the tool. (5 marks) (B) By constructing the slip line field, show that for this case Lee and Shaffer relation is given by , where

is the shear angle and

is the friction angle. Find out the value of shear angle. (5 marks)

(C) For the special case of a tool with a zero rake angle, derive a relation between shear angle and chip thickness ratio. Find out the chip thickness ratio for the present case. (5 marks) (D) Find out the shear strain in the chip. (5 marks)

Fig. 1.6 Question on metal cutting broken into subparts

the students. Figure 1.6 shows a question in metal cutting broken into small parts. Such type of questions helps in the better evaluation of students.

1.8 Issues of Intellectual Property Rights Students should also be provided idea about intellectual property rights (IPR), particularly patents and copyright. A patent is an exclusive right granted for an invention. This right for new invention is granted for a limited period of time, generally 20 years from the date of filling application. One cannot exploit the patented invention commercially without paying a mutually agreeable license fee to owner. However, the invention becomes free for public after the validity period. Patent can be cited by listing the name of the inventor, the year when it was issued, the title of the patent, the patent number and the name of the issuing body. Copyright issues should be paid more attention. Copyright is the right of author and copyrighted material cannot be reproduced without the consent of the owner. Of course, there are some works, which do not need copyright permission. For example, sometimes authors can give general permission to use their creations by following some suitable procedure. Government documents in some countries can be freely used by public. Also, the data is not copyrighted; only the style of presenting the data is copyrighted. However, in all cases, the source of cited material must be mentioned. Students should be made aware that a copyrighted material cannot be used even in their reports without prior permission. Student should also be taught to avoid self-plagiarism.

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1.9 Supervising a Project Projects are integral part of technical teaching. There is a famous quote by Confucius (circa 551 BC to circa 479 BC): I hear and I forget. I see and I remember. Classroom teaching cannot impart full education. One gets expertise by doing a job. In Ph.D., thesis is the main component, and in some cases, there is no requirement of coursework at all. In M.Tech., usually one year is spent in the coursework and one year for thesis. In B.Tech. along with course work, there is a final year project. Recently, some institutes have started assigning the B.Tech. project right from the third year. The motive is to get the significant output from the students, which can enable them to set up a startup. Unfortunately, majority of Indian students is not taking projects seriously at M.Tech. or B.Tech. level. There are anomalies in the evaluation of projects and it becomes a subjective affair. Supervising a project is not an easy task. Many supervisors assign a Ph.D. type topic to B.Tech. students also. Planning a good project suitable for B.Tech. students requires some skill. In general, a B.Tech. student needs a wider exposure in order to make him/her fit for any industry. It is always better to assign a B.Tech. project that involves the application of several courses that student has undertaken. In the project, students should learn design, fabrication and material procurement. Most of the faculty members are joining the academic institute just after their Ph.D. and have little industrial experience. Hence, they feel comfortable in assigning academically oriented projects even to B.Tech. students. Sometimes they expect journal publications out of the work of a B.Tech. students because publications are linked with promotions, while there is hardly any methodology to reward a supervisor who could supervise a project that can be useful to industry. Many B.Tech. students also want to execute a Ph.D. type project for getting publication that might help them for getting admission abroad. Now some institutes started realizing the importance of industry-oriented projects and also involve industry professionals in the supervision of B.Tech. and M.Tech. student. Proper planning of the project is very important, which is the first thing to be taught to students. Project evaluation and review technique (PERT) can be very effective in planning and monitoring the project. In this technique, activities, their timings and sequence are optimally decided. Students can prepare a Gantt chart, in which activities are displayed against time. A representative Gantt chart is shown in Fig. 1.7, where starting and end times of 11 activities (a to k) are indicated. It is to be noted that some activities can be carried out concurrently. With Gantt chart, monitoring the progress of a project becomes easier. Changing trends advocate flexibility. Hence, it may not be appropriate to enforce that each project should be a design and fabrication type, but a project must be assigned to students considering their aptitude and it must be executed in a professional manner. Usually, B.Tech. projects are carried out in a team. Supervisor should facilitate proper division of work. Considering the nature of project, co-supervision can also be a good strategy. If there are more than one supervisors, students can benefit from the expertise of different supervisors. It is also good for the growth of

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Fig. 1.7 Typical Gantt chart

institute as it encourages team spirit among faculty members. However, sometimes co-supervisor may create confusion and non-sincere students may take it as an excuse for not doing the work properly.

1.10 Teaching of Professional Ethics Ethics defines the moral principles that governs a person’s behavior. It is the science of right and wrong. There is a difference between law and ethics. Laws are a set of rules that are enforced by an administrative authority of country or society, while ethics imbibes the principles that society expects to be followed by some person. For example, self-plagiarism is not a legal offense but ethically wrong. If a doctor does not pay timely assistance to a patient, it is difficult to sue him in a court, but it is ethically wrong. Institution of Engineers (India) has a code of ethics for its Corporate members [5]. Some of the ethical rules to be followed by them are as follows: 2.8

A Corporate Member shall not directly or indirectly injure the professional reputation of another member.

2.10 A corporate member shall be concerned about and shall act in the best of his abilities for maintenance of sustainability of the process of development. 4.5

A Corporate member should compete on the basis of merit alone.

4.6

A Corporate member should refrain from inducing a client to breach a contract entered into with another duly appointed engineer.

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It is clear that these rules cannot be enforced by laws of the land, but only by self and Professional Society, i.e., the Institution of Engineers (India) in this case. There is a difference between ethics and morality also. Moral indicates individual’s own principles for right and wrong. On the other hand, ethics refers to rules provided by external agency. For example, taking only vegetarian food may be one of the moral standards of an individual, but it is not part of the ethical code of the Institution of Engineers (India). Similarly, ethics and religion are also different. One can say that professional ethics is a kind of religion of a particular professional society. As engineering is a profession, adhering to ethics is mandatory for anyone to be called engineer. It is important for an engineering teacher to impart ethical values in his/her students. As engineering students execute several assignments and projects involving team effort, teachers have ample opportunity to train them on professional ethics.

1.11 Conclusion Engineering is a profession, which requires knowledge, wisdom, skill and ethics. Giving emphasis to all attributes is important. An engineering graduate can choose one of several career paths starting from core factory job to civil administration. Engineering education should prepare the students in an all-encompassing manner. Just classroom lectures and written examinations are not enough. Engineering teachers should develop a mindset of developing ethical, skilled, intelligent and knowledgeable professionals rather than highly educated impractical persons.

References 1. Mason, G. S., Shuman, T. R., & Cook, K. E. (2013). Comparing the effectiveness of an inverted classroom to a traditional classroom in an upper-division engineering course. IEEE Transactions on Education, 56(4), 430–435. 2. Felder, R. M., Woods, D. R., Stice, J. E., & Rugarcia, A. (2000). The future of engineering education: Part 2. Teaching methods that work. Chemical Engineering Education, 34(1), 26–39. 3. Braams, C. M. (1952). On the influence of friction on the motion of a top. Physica, 18(8–9), 503–514. 4. Paul, P., & Dixit, U. S. (2011). Development of toys for teaching and learning of mechanical engineering. In National Conference on Advanced Design and Manufacture. Einstein College of Engineering, January 6–7, 2011. 5. http://ieigsc.org/code-of-ethics. Accessed on May 11, 2022.

Dr. Uday Shanker Dixit is working as a professor (HAG scale) in the Department of Mechanical Engineering, IIT Guwahati. He is also the head of Center of Indian Knowledge Systems (CIKS), IIT Guwahati. He received his bachelor’s degree (Mechanical Engineering) from IIT Roorkee in 1987; and his masters and Ph.D. from IIT Kanpur in 1993 and 1998, respectively. He has published more than 280 scientific papers in international journals and conferences and

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authored/edited more than 20 books and proceedings. He has also undertaken several research and consultancy projects. In addition to developing course material on mechatronics for IGNOU, and on engineering mechanics, mechanics of machining for NPTEL, he has produced QIP course material in the area of “Finite Element Method in Engineering and its application in manufacturing”. He has been visitor’s nominee and board member of some IITs and NITs. His research interests include sustainable manufacturing, optimization, metal forming, pedagogy and teaching– learning technologies.

Chapter 2

Pedagogical Teaching—Teachers’ Beliefs, Capabilities, and Examples Raghu Echempati

2.1 Introduction The term pedagogy, as different from the term ‘pedagogue’ has been assumed in educational terms as simply the overall strategies of instructional delivery and content [1]. Although many primary, secondary, and high school teachers are trained to enhance the development of their professional skills through formal teacher training, many other teachers, especially the engineering teachers acquire knowledge about teaching through their personal teaching experiences and from their peers [2–6]. Some of these training programs include the pre-service and in-service activities such as the centers for educational teaching and learning (CETL). Because teachers spend most of their time in the classroom and in constant discussion with their peers (other educators), it is reasonable to assume that a great deal of their competency and skills develop there too. A wealth of research explores the knowledge, skills, and awareness required of teachers of adult learners and suggests that teacher knowledge is constantly in the process of development [7]. Therefore, in many ways, teachers can be regarded as adult learners themselves. However, little is known about how teachers draw on their experiences in the classroom to develop their teaching practices. This is particularly true with engineering educators who do not necessarily go through a formal teacher training program compared to their primary, middle-school, and high school peers, before being absorbed as an engineering faculty. This also brings up another important issue with reference to if a job-seeking candidate after clearing either a basic bachelor level degree or an advance degree (masters or a doctorate) really understands and likes teaching job (as a career) versus those after landing in the job to start their job career, eventually gains interest in pursuing teaching as their career. This reasoning is also true with non-teaching or any job.

R. Echempati (B) Mechanical Engineering, Kettering University, Flint, MI 48504, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_2

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In countries such as Germany, teachers particularly in engineering, are selected only after they have some years of industrial experience. To reiterate what has been expressed in the previous sentences, majority of engineering teachers lack a formal teacher training, or do not have prior industrial experience to teach the engineering students effectively. They may lack other skills such as working with others, behavior, organization, understanding psychology and how people learn, peopleorientation, etc. Quite a few ‘teachers’ have these talents inherently, and so they motivate the learners quicker than other ‘traditional’ engineering teachers who are absorbed (recruited) soon after they achieve the advance degrees. In other professional careers such as music, sports, entertainment, medicine, finance, literature, etc., however, the ‘teachers’ have gained enough practice and first-hand experience prior to joining a teaching career in those fields to impart the knowledge in those areas.

2.2 Teaching Pedagogy Literature shows that there are five principles of effective teaching and pedagogy. They are (not in any order) inclusion, motivation, quality assurance, consistency and transparency, and innovative approaches [8]. There are other principles cited in the literature. It is well-known that student learning is determined by the different pedagogical methods teachers use when they are in class. Most of the time, delivering an effective pedagogy depends not only on a particular subject matter but also it depends on recognizing and realizing the learner needs, and how students learn. Thus, a teacher needs to adjust the pace and delivery of their talk understanding the surrounding conditions of the classroom, the class schedule, and the minds (psychology) of the learners at a given time of the day and during the class time, to mention a few. We as educators need to realize that every student has equal value and capacity to learn, and therefore, they should have equal opportunities and have access to high-level education. When once we provide such inclusive, socially friendly and student-focused environment, the chances of building trust in teachers enhances creativity and critical thinking skills which in turn, improves learning and better understanding of the material taught. ‘Teaching is the canny art of intellectual temptation’—J Bruner quoted (Ed Tech [9]). As per the motivation, it is not obvious if it comes first or after delivery of instruction of a course material. As instructors, we need to frame the material and teach what is ‘relevant’ in a way that makes sense to the student. This is not to say that we need to limit our teaching to the expectations of the students, rather, we need to move or push the students beyond their limited outlook. They need our help to elevate their knowledge and thinking skills beyond the traditional classroom delivery of material (known as Bloom’s Taxonomy). How do we motivate the students to come to the classroom and to listen to us? Creating that ‘suspense’ at the beginning of a class as in a drama or a novel or a movie, is one of the key elements to motivate the students to become ‘eager’ to know ‘what is coming next’, or will be discussed or covered in the next class. This motivates them to attend each class regularly without being absent, pay attention to

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the class, and participate in classroom discussions. This is believed to improve their ‘attention span’ as an individual and as a group. In the absence of these, the attention spans these days is typically 5–8 min only at best! Why? In contrast, why do they get involved deeply and pay more attention in a drama, or a music, or a sport, or a paralegal, or a medical ‘class’, than an engineering class? Are they ‘skill-based’ only and so are easier than engineering? Why cannot we get them ‘automatically’ motivated to learn in an engineering class? Something seems to be absent in our engineering education! When once we motive the students to learn the material taught, we need to pay attention and assure that that high quality and current material will be delivered. This should be delivered consistently in each and every class using the innovative pedagogical techniques discussed in the literature. We will need to adapt these approaches and transform them to suit the course being taught. There are other pedagogy principles of teaching proposed by many researchers, for example, Howard’s 10 pedagogy principles for service-learning courses [10]. Many of these principles of teaching pedagogy are discussed by the contributors as presented in this book, with a hope that the readers appreciate the complexity of the teaching pedagogy, and how we all learn. As mentioned earlier, the present article covers four focused areas that may be directly linked to the topic of teaching pedagogy. The four areas discussed in the paper are (1) cooperative education or industrial training in an industry or an organization, or internship/apprenticeship (2) ‘toys in the loop’, or using hand-held classroom demonstration apparatus that are different than the well-organized laboratory experiments, (3) ‘de-rusting’ or reviewing the prerequisites knowledge, and (4) discussing everyday examples in the class. These topics may be reordered by the reader according to their preferences. Each of these topics are briefly discussed in the article.

2.2.1 Cooperative Training/education [11–13] Cooperative education, or industrial training, or sandwich curriculum, or internship, etc., are different forms of combining the classroom theory with practice. It helps in supporting and promoting the pedagogical teaching techniques easily both in a classroom, and as observed at work. It ‘makes sense’ to them. Cooperative education is a structured method of combining classroom-based education with practical work experience. Some view this as a ‘community college, associate degree, or polytechnic or engineering technology’ type of education, but that is not completely true! A cooperative education experience, commonly known as a ‘co-op’, provides academic credit for structured job experience and is taking on new importance in helping young people to make the school-to-work transition. It falls under the umbrella of work-integrated learning (alongside internships, service learning, and clinical placements) but is distinct, as it alternates a school term with a work term in a structured manner, involves a partnership between the academic institution and the

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employer, and generally is both paid (usually on an hourly basis), and intended to advance the education of the student [11, 12]. In many cases, the student during their early co-op years is also eligible for availing the retirement benefits offered by the employer! Although many universities, including those in the USA, Canada, Germany, Australia, etc., adapted the co-op education for over 60 years or more, it is always not possible for every country, particularly in Asia. Co-op education is not always possible if there is a no collaboration or partnership between the university and the industries or the R&D organizations in a country. Kettering University, Flint, MI (USA) is one of them that enrolls students in cooperative education from their first year on campus, specializing in engineering, science, and management degree programs, and it is required for completing the degree [13]. In other words, unlike the Internships which may occur only once or last for couple of times during the early (high school/freshmen), mid (junior), or later (senior) years of college, coop is usually a long-term commitment on the part of the employer, the particular university, and the student, until a student graduates, and perhaps be absorbed by the co-op employer. Thus, co-op education invariably guarantees employment right after graduation, since the hiring company do not have to retrain the student as they are already on-the-job trained. In some cases, the concerned industry may sponsor post-bachelor/baccalaureate education by paying the college tuition if the new hire needs further technical training in a specialized area that an industry produces; for example, tamper-resistant and coated lighting panel for automobile lights, etc. On the other hand, a co-op education may also discourage some students to pursue advanced degrees, and/or not appreciate some courses that they think are not relevant to the products and processes of the company they work. As mentioned before, although the topic of pedagogical teaching seems to be not related to co-op education, it offers several benefits, some of which are cited in references [11–13]. In summary, co-op education (which is slightly different than school to work, internships, and service learning): • offers a ‘pool of knowledge’ in one place (classroom) due to the participation of the young and the inquisitive-minded students in co-op education at various industrial settings, • promotes ways to link theory and practice due to hands-on experience in a company, • is based on the philosophy that students engage in active learning while in classrooms due to work experience, • enables them in learning the best practices followed by industries that they can mutually share inside the classroom with their peers, as well as the teachers alike, • helps teachers prepare their instructional materials and use the pedagogical teaching strategies as contextual and apply the knowledge to real-life situations that are usually very complex, • promotes partnerships between the university and the outside entities such as an industry or a R&D organization where the students undergo co-op training, and

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• promotes team-building and develops tolerance, confidence, communication skills, etc. ‘Cooperative education exposes students to worlds of learning that are different but complementary. These complementary worlds have different sociocultural dimensions that afford different learning opportunities to students. Clearly defined integrative pathways are required that allow students to make sense of the learning that they are afforded. The real strength of cooperative education as a strategy of practicebased learning is not that students gain opportunities to learn in the classroom and in the workplace, but that these opportunities are integrated to create learning that is more than the sum of the two parts’. Where co-op education is not possible, a trip outside of class hours to a local industry, or a peek into an on-campus repair workshop, or even a local automobile (or other engineering product) repair shop, immensely helps in understanding how components and processes fail in operation, and how their designs can be improved. This could a faculty-lead activity, or an assigned activity to the students. Online videos produced by the manufacturing and testing industries also help to some extent if the students are engaged in explaining how the concepts covered in the video are related to what was covered in the classroom. However, we all agree from the seventeenth century English clergyman, Thomas Fuller’s quote, ‘Seeing is believing, but feeling is the truth’, really applies to all of us, especially to the young minds. This suggests that believing and truth are two very separate matters altogether. ‘Touch and feel’ helps which can be gained when the students actually get some practical experience. This leads to the second topic covered in this paper, namely ‘toys in the loop’.

2.2.2 “Toys in the Loop” [14–17] Almost all STEM colleges are equipped with some type and some number of handson experimental laboratories, many of which are accessible to the students to understand the theoretical principles covered in the class. However, due to scheduling limitations, students do not get a chance to perform the lab experiments ‘just in time’ (JIT)—that goes hand-in-hand synchronously while the theory is being covered in the classroom. Also, not all theoretical concepts covered in a classroom have a corresponding laboratory experiment. With limited access to, and limited number of experiments available to them, students view the laboratory as ‘another course’ to complete, although the lab instructors review the theory before beginning each experiment. It may be noted that in some/many cases, the lab instructor may not be the same as the one who taught the theory in a classroom. To alleviate some of these problems these days, and with the advancement of, and the availability of a lot of online instructional materials, JIT learning can be supplemented by videos and images of the simple to complex real-life industrial examples. Care should be exercised though to make sure that this type of instructional material is authentic and up to date. Teacher-recorded short videos can also be made

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available to the students to review them again later during outside class hours. To make this type of teaching pedagogy more interesting and active, students may be asked to search online to find out similar or even more relevant information (images and videos, including from their co-op company experience), and present it to the class on the same day or during the next class hour. This is one form of ‘flipped classroom’ model. With avid use of the cellphones during class hours these days, many students find this JIT activity more interesting and instructive to grasp the concepts and principles covered in the class. This follows the proposition to ‘teach (talk) less and explore more’. As instructors, we need to realize that the students take several courses during the same academic term—be it a semester or a quarter system. Depending on their class standing (freshmen, junior, etc.), these courses can be in the STEAM (STEM + Arts) areas. Some teachers follow a ‘traditional teaching’ methodology, while others may use teaching pedagogy techniques, with still some in between. Students often wonder why there is non-uniformity of course delivery among the teachers. But they move on and complete their studies quietly to graduate on time. How do we give them an integrated knowledge based on all the courses they are taking during a given term? Our educational system does not provide an opportunity to team-teach classes due to various obvious and unexplained reasons. This is only one of the road blocks for non-uniform course delivery; there are many others. We as teachers perhaps need to try to be more ‘well-rounded’. Is it not what we do, and are, as parents or siblings of an inquisitive kid who shoots questions at us to seek quick answers? Take for example, a chemistry class ask the students to pick their favorite item from the main-course lunch or dinner menu, plus one item from the dessert menu. Invariably, we get different answers, but some of them may be common, say for example, mixed vegetable curry from the lunch/dinner menu, and ice-cream from the dessert menu. Pick those two items as an example, and now ask them what one type of spices they like on the curry, and the type of topping on the dessert. By this time, the students have no idea what the teacher is doing in a chemistry class, but they are all curious! With the type of the spice they picked (liked), say, ginger, and chocolate, respectively, for the curry and the dessert, ask them what the chemical name of those two ingredients are. By this time, with no clue as to how to answer these questions, the students tend to reach their bags or pockets to remove their cellphones! After the teacher permits the use of cellphones (in fact, we should, because it is a computer tool after all!), the students will yell out to tell the correct answers, namely gingerol for ginger, and theobromine for cacao. By this time, all the students are motivated and curious to know ‘what’s coming next’. For the next part, ask them to describe more about the items—gingerol and theobromine. After an immediate search online, the students will describe that gingerol is a phenol phytochemical compound found in fresh ginger that activates spice receptors on the tongue. Molecularly, gingerol is closely related to capsaicin and piperine, the compounds which are alkaloids, though the bioactive pathways are unconnected [14]. Similarly, theobromine, also known as xantheose, is an alkaloid whose name is derived from the Theobroma family. It is the principal alkaloid of Theobroma cacao (cacao plant). It tastes bitter and has the chemical formula C7 H8 N4 O2 [15]. The teacher can slowly introduce the class to the

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Fig. 2.1 Chemical structures of a Gingerol, and b Theobroma

molecular structure, weight, bonding, reactions, etc., of ginger and chocolate (and other compounds), cover more details in depth (such as toxicity, etc.), following the syllabus, and using the interactive mode of active learning technique. Figure 2.1a, b shows the molecular structure of the ginger root and the chocolate, respectively. Individual or group homework can then be assigned based on the other spices and the toppings on the menu that they selected. They can easily produce unique reports based on their own findings from the literature. They become self-learners! Since a teacher is well-rounded to some extent, they can mention to the students to find out where these spices are grown, the different varieties, health benefits, their processing equipment, cost, packaging, storage, transportation to other places, etc. This will ‘close the loop’ to some extent with the present class (chemistry in this case), but the students will realize that these topics are covered in depth in other classes such as mechanical engineering design of the production machines, CAD, life cycle analysis (LCA), etc., chemical engineering to understand the process and transportation, finance, and business classes to understand the supply chain and logistics, and history, culture, and ethics classes to understand those topics. Students should take lead role to motivate and ask the teachers of the respective classes to use the same or similar examples as applicable to those classes. Another example related to solid mechanics or machine design class is shown in Fig. 2.2, which can be passed around inside the class as a demonstration tool (‘toy’) for a ‘touch and feel’ experience. This wooden model is a shaft assembly showing any combination of three rotating components such gears and pulleys mounted on two bearing supports (containing rolling element or journal bearings), and attached to the base (ground) using some kind of connection method (bolts, welding, etc.). This model is a single overhang simply supported beam loaded as shown. Using the free body diagrams and solid mechanics principles, the teacher can start a discussion of the real-life application(s) of the arrangement shown in this model or of another alternative form of the model by changing the geometric location of each rotating element. The students can perhaps search online or refer to the textbook (using their cellphones) to find the real-life industrial examples such as a lay shaft of a lathe machine, or an automotive or a wind-mill gearbox, etc. Depending on the type of loads acting on the shaft, material, and the geometric dimensions of the real-life application, which can run several meters in length (e.g., for a turbine), self-weight of each rotating element, including the shaft can be included in the analysis. Using the

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Pulley/gear

Stepped shaft

Bearing Supports and Fasteners

Fig. 2.2 Wooden model of a shaft-pulley-gear-bearing-bolt system

dimensions of the model, measured by a randomly selected student of the class, speed (or power) of the machine, and assuming certain material(s) for each component, the teacher can do a class work to find the reaction loads and bending and torsional moments (using statics and solid mechanics), to determine the size of the shaft at various locations along the length of the shaft. Depending on the time available in the class, further analysis can be undertaken for the design of the other components (gears, pulleys, fasteners, bearings, keys, etc.). Individual or group homework can be assigned by changing the data and the type of arrangement of the gear and the pulley assembly. There are many other similar types of ‘toys’ for classroom demo available and published in the literature, for example, the breadboard model [16]. Another toy that interested students with hands-on skills can fabricate using thick paper or cardboard, or plywood, and bring it to a mechanisms class, is a ‘crow’. This toy is operated by a planar linkage mechanism as shown in Fig. 2.3. A YouTube video of this toy is available at: https://youtu.be/cBjRmg2LnPA. The fabricated paper or cardboard or wooden toy can be passed around in the class, and the teacher can ask the students to draw the kinematically equivalent mechanism. They can be assigned a computer-based homework based on this to determine the kinematic characteristics (range of motion, Gruebler’s condition to determine the degrees of freedom, identify if it contains four-bar loops, Grashof’s condition to figure out if it is a Type I or Type II mechanism, etc.). Although this is a slow-moving mechanism for which dynamic analysis is not needed, the students can be challenged to modify the link lengths to find various other kinematic inversions, find possible high-speed applications of this linkage by observing the animation, range and type of paths generated by the mid, moving pivots, etc. Such exercises develop intuition, creativity, critical thinking, and problem-solving skills. Two other table-top models that can be used for measuring deflection of a beam are shown in Fig. 2.4. Both models can be used as classroom demos for solid mechanics or finite element analysis (FEA), or vibrations courses. Both are cantilever type. Students can be asked to fabricate other models with different other types of beam support conditions. The model shown on the left can be used to measure deflection at various locations along the length of the beam and study if the deflection at those locations match closely with the calculated values using the equations available in

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Fig. 2.3 Moving paper crow for mechanisms class [17]

standard beam deflection tables. By joining the measured deflection values at those locations, they will obtain piece-wise linear deflections of the otherwise nonlinear deflection curve. For an advanced CAE class, such models can be analyzed using the CAE/FEA tools, and understand how the support stiffness of the frame members play a role on the overall end deflection and stress of the original cantilever beam. This model can also be used to calculate the stress at different locations of the beam and the supports by using strain gage or other experimental stress analysis instrumentation. Finally, it is possible to perform the modal analysis, etc., for a vibrations course. More ideas about where this model can be used can be thought of by the teacher and the students of the same or different other classes. The model shown on the right shows five cantilever beams of a certain but same length; however, each beam is fabricated out of either a single piece, or two pieces, or three pieces, and so on. The second to the fifth beam is welded at the joints as indicated by the arrows. These individual beams can be supported to study if the end

Fig. 2.4 Cantilever beam models for solid mechanics or FEA courses

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deflections under a given static load are the same for each beam. In FEA course, a beam is split (meshed) into several beam elements and analyzed to improve the deflection and stress results until convergence is reached. Although analogously, the ‘multi-segmented’ and welded beams shown in the figure on the right are not the same as the ‘elements’ used in FEA, students can understand and realize how, if any, the amount and the type of weld materials used at the joints can play a role in the end deflection. An understanding of advanced theory and modeling are required if a CAE/FEA tool is used to analyze these beams to draw any conclusions. This helps the students and the teacher understand the underlying assumptions made in solid mechanics-based courses. A photograph of failed bolts is shown in Appendix at the end of this paper (Fig. 2.5). Students can be asked to bring other failed components that they have access to, such as from a formula car or from their own appliances at home and analyze their failure as a small group project during class hours. If enough failed components or subsystems are available, studying those along with the instructor forms as an ‘active learning’ strategy. This is similar to reconstructing an accident, which in this case is the failed bolts. One of the videos to view is the case study of Sayano Shushenskava hydroelectric dam accident (http://archive.boston.com/bigpic ture/2009/09/the_sayanoshushenskaya_dam_acc.html, posted as ‘The Big Picture’ on September 9, 2009, by boston.com.

2.2.3 ‘De-rusting’ or Reviewing the Perquisites Knowledge [18, 19] Reviewing the prerequisites knowledge is very important to brush-up the forgotten concepts and principles covered in earlier related courses. One of the pedagogical methods is to use the three D’s teaching styles: directing, discussing, and delegating. In the directing method, we tell students what to do. In the discussion mode, we prepare and ask questions related to the needed prerequisites knowledge, and listen to their answers. Some instructors do this by giving a prerequisites knowledge quiz for (extra) credit or for no credit, although giving some credit will motivate the students to take the quiz seriously. Using clickers will also help so that every student gets a chance to ask a question. In the delegate mode, we empower the students by assigning tasks that students work on independently, either individually or in groups inside a classroom. We can follow the intervention method, and ask an individual or a group of students to come in front of the class to write their answers on the board. This encourages student-to-student interaction (or students teaching a student) due to response from the floor, should there be any mistakes committed by the student(s) in the work they showed on the board. In summary, by following these styles of teaching, we build confidence as well as, encourage and inspire students to do their best at all times throughout the semester [18]. The present author published a paper

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on refreshing the free body diagrams required to solve problems in solid mechanics course [19]. The details of this method can be obtained by reading the paper.

2.2.4 “Everyday Engineering Examples (E3 s)” [20, 21] Everyday engineering examples help everyone in understanding how things are made and tested, and how they work. These could be engines, toasters, kitchen grinders, ear phones, potato chip making machines and processes, etc. The National Science Foundation (NSF) under their “Engaging Students in Engineering”, or simply ‘engage’, funded several universities to build short articles and courseware that contain engineering examples and simple (or complex) calculations that are based on a single or multiple-concepts covered in classes [20]. As outlined on their webpage, everyday engineering examples (E3 s) are believed to increase not only student understanding of STEAM education, but also faculty, and even the practicing engineers. One of the examples that Scott Kiefer used for his Solid Mechanics course was an iPOD headphone wire, which got his students’ attention because several students had broken theirs and were curious why [20]. Since the headphone wire is made of both plastic with strings of metal inside, how do we determine the axial stress and deformation if the iPOD is freely suspended (i.e., the composite wire is loaded due to the weight of the iPOD)? Is this a statically determinate or indeterminate bar problem? These wires are actually tested using three to five times the iPOD load since some students carry those that way and the vibrations due to walking or running causes impact loads. After they do the calculations with the help of the teacher, they can be asked (‘directed’) to solve another problem involving the wire of a laptop or a table fan, etc. The students can bring several similar examples of composite bars that are axially loaded (in tension or in compression as in the case of concrete pillars of a building or a bridge), etc., and discuss their findings. The teacher can ‘delegate’ the responsibility by asking them to watch videos of how such wires or columns are fabricated in real life, and tested. An example of how electric cables are made is shown in the video: https://youtu.be/2DBoS3E_ojc [21]. In summary [20], • E3 s are examples that are relevant and familiar to students, • E3 s highlight simple and complex ways that engineers help society, • E3 s increase student engagement and retention of not only engineering and computer science students but perhaps other non-engineering students who have innovative product development ideas, such as business majors, • E3 s can be used in large classes, and • E3 s are effective among all groups of students.

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2.3 Conclusions This paper describes four topics of how pedagogical teaching methods can be put into practice. The first one discussed the role of co-op education or hands-on practical experience during the early years, and how it helps in better understanding of the principles and concepts covered in the class. The second topic covered on how bringing own or student-developed classroom demonstrating models, and broken engineering components give the ‘touch and feel’ and ‘learning from failures’ experience of the scaled engineering models, or from the real-life failed components. The third topic on ‘de-rusting’ or reviewing prerequisites knowledge encourages students to perform well in the current course throughout the semester. Flipped classroom technique in which short videos can be recorded and posted by the instructor covering the prerequisites topics and concepts. The students can be delegated to view these prior to, and when needed, to brush-up their doubts. The final topic covered dealt with how using the everyday engineering examples (E3 s) help in increasing the knowledge about how things that are familiar to them work, how they are made, and tested. These four topics by no means provide complete details about teaching pedagogy, nor they are the only techniques used and assessed in pedagogical teaching. Many rubrics are available online and/or developed by universities where we work to assess students’ learning and acceptance of the pedagogical technique we use in the classrooms. Frequent feedbacks in the form of using standard surveys can be obtained for continuous learning and improving the techniques we use that the particular student groups we engage and teach in a course. Joshua Eyler in his book on “How Humans Learn” [22] emphasizes and identifies five broad themes running through recent scientific inquiry of how we learn— curiosity (which hopefully leads to motivation to learn), sociality (which hopefully leads to being flexible while working in a team), emotion, authenticity (which hopefully leads to developing originality, reasoning and justifying the underlying engineering assumptions), and failure (which helps in understanding that there is nothing perfect in the world, leave alone the theories and things that are human created). After all, behind each success, there are more failures (or trials)! This is never ending. It builds strong foundations for the advancement of scientific knowledge, which in turn is used for the advancement and health of the society we live in. Declaration This author declares that there is no conflict of interest.

Appendix See Fig. 2.5.

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Fig. 2.5 Photograph of failed bolts due to excessive combined axial and torsion loads

References 1. Cuenca, A. (2010). Self-study research: surfacing the art of pedagogy in teacher education. Journal of Inquiry and Action in Education, 3(2). 2. Lund, L. (2011). Adult teachers: Competence development through practice-based learning. Paper presented at The Fourth Nordic Conference on Adult Learning, Trondheim, Norway. 3. Lund, L. (2015). The teacher’s world—Pedagogical reflections on classroom experiences [Doctoral dissertation]. Aarhus University (In Danish: Lærerens verden almendidaktiske refleksioner over klasserumserfaringer). 4. Lund, L. (2020). How teachers reflect on their pedagogy: Learning from teachers’ pedagogical vocabulary. Journal of the International Society for Teacher Education (JISTE) 22(2). 5. Darling-Hammond, L. (1999). Teacher quality and student achievement: A review of state policy evidence (CTP Document R-99-1). University of Washington. 6. Richardson, V. (1996). The role of attitudes and beliefs in learning to teach. In J. Siluka, T. J. Buttery, & E. Guyton (Eds.), Handbook of research on teacher education: A project of the association of teacher educators (2nd ed., Vol. 2, pp. 102–119). Macmillan Library References. 7. Merriam, S. B., Caffarella, R. S., & Baumgartner, L. M. (2007). Learning in adulthood: A comprehensive guide (3rd ed.). Jossey-Bass. 8. Nisai learning. Available at: https://www.nisai.com/, June 28, 2019. 9. Ed Tech Now. (2013). Five principles of pedagogy. Available at: https://edtechnow.net/tag/ped agogy/ 10. Howard, J. (2001). Ten principles of good practice in service learning curriculum and pedagogy. In Michigan Journal of Community Service Learning: Service-Learning Course Design Workbook. University of Michigan, OCSL Press. 11. Cooperative education. Available at: https://en.wikipedia.org/wiki/Cooperative_education 12. Learning through practice (pp. 180–196). Cooperative Education: Integrating Classroom and Workplace Learning.

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13. Co-op/learn as a student. Earn as a professional. (2022). Available at: https://www.kettering. edu/co-op 14. Chemical name and molecular composition of ginger. Available at: https://en.wikipedia.org/ wiki/Gingerol#:~:text=Gingerol%2C%20properly%20as%20%5B6%5D%2D,the%20bioa ctive%20pathways%20are%20unconnected. 15. Chemical name and molecular composition of chocolate. Available at: https://www.ebi.ac.uk/ chebi/searchId.do?chebiId=CHEBI:28946 16. Wood, J., Campbell, M., Wood, K., & Jensen, D. (2005). Enhancing the teaching of machine design by creating a basic hands-on environment with mechanical ‘breadboards’. International Journal of Mechanical Engineering Education, 33(1). 17. Moving paper crow. Available at: http://www.blisskolbautomata.com/store/p2/Moving_Paper_ Crow.html 18. Three teaching styles. Available at: https://www.facultyfocus.com/articles/philosophy-of-tea ching/three-teaching-styles/ 19. Echempati, R. (2020). New idea to enhance better understanding of free body diagrams in solid mechanics course. Journal of Engineering Education Transformations (JEET), 34(2). https:// doi.org/10.16920/jeet/2020/v34i2/144928 20. NSF’s engaging students in engineering. Available at: https://www.engageengineering.org/e3s/ whyitworks 21. How electric cables are made. Available at: https://youtu.be/2DBoS3E_ojc 22. Eyler, J. R. (2018) How humans learn. West Virginia University Press.

Dr. Raghu Echempati Retired Professor of Mechanical Engineering, is a native of India. He received his Bachelors (1970), Masters (1972), and Ph.D. (1978) all in Mechanical Engineering. His research areas included Kinematics, dynamics and vibrations of machinery, mechanical engineering design, computer aided engineering (solid modeling, assembly and finite element analysis), and metal forming simulation. Dr. Echempati has numerous publications and papers to his credit. He has supervised numerous undergraduate, graduate, and research student theses. He is a registered Professional Engineer and a Certified Manufacturing Engineer. In 1979, Dr. Echempati came to U.S.A. and worked as a Post-Doctoral Research Associate on kineto-elastodynamic analysis and synthesis of lower and higher-pair planar mechanisms, a NSF funded research project at the University of Florida, Gainesville, Florida, under the supervision of the renowned professor (Late) Dr. George N. Sandor. Subsequently, he taught at I.I.T. (Delhi), The Ohio State University, Washington State University, Michigan Technological University, University of Mississippi, before joining GMI/Kettering University in 1997. Dr. Echempati served as the program coordinator for several mechanical engineering study abroad programs. These include the programs in Germany at the Universities of Applied Sciences in Esslingen, Konstanz, Munich, Reutlingen, Ulm, and Wiesbaden, and in Australia at Swinburne University of Technology, Melbourne. The primary purpose is to organize and to advise the ME students wishing to do study abroad programs at one of these universities and when possible to teach classes while the students are in exchange program. He was the first faculty recipient of Oswald award for his outstanding contributions for developing policies and study abroad programs in Germany, where he also taught. He also taught at KMUTT, Bangkok, Thailand as a Fulbright Specialist and at UCCH, New Zealand as an Erskine Scholar. After serving for 25 years at Kettering University, he retired on July 1, 2022. However, he teaches online classes and keeps active academically by giving invited and keynote talks at several universities in India and other countries.

Chapter 3

Growth Mindset in Engineering Pedagogy for Attitude Building with Metacognition of Engineering Students Anjali Sharma, Sukanya Singh, and Ram Prakash Sharma

3.1 Introduction Strong demand from the industry advocates the attractiveness and involvement of students in the engineering field. It is a field that is constantly evolving through innovation and invention. [1, 2]. The “big elephant in the living room” spots that engineering increases the student employment opportunities typically centered around the world. The passion for learning new techniques and best practices evolves every day among robust communities. The new tools and solutions are being launched to serve the marketing profession with leading-edge best practices [3–5]. Moreover, cultivating nontechnical skills is the key attribute of engineering students to fit into the job market. Above and beyond tradition, conventional engineering teaching creates a vacuum in which everything is indorsed, and the engineering educators have not placed sufficient emphasis on pedagogy of mindset as avenues for reforms although they give importance to course material with the technical aspects [6–8]. The growth mindset pedagogy improves engineering education as “the rising tide raises all boats”. Therefore, pursuance of a growth mindset is vital for engineering educators to apply psychological principles to change students’ mindsets. Understanding of Mindset or Attitude To understand mindset first, we have to look at the story of failure behind success. Let us take a few examples for the same. James Dyson invented cyclonic vacuum technology, which traveled 5126 times failures. Thomas Edison, ten thousand times, created failed prototype of an electric bulb before succeeding. Sylvester Stallone A. Sharma (B) · S. Singh School of Education, Central University of Rajasthan, Ajmer 305817, India e-mail: [email protected] R. P. Sharma NIT Arunachal Pradesh, Jote 791113, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_3

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was rejected one thousand five hundred times when he tried to sell his script. Steven Spielberg, the Oscar Award winner, faced rejection from the University of Southern California; after that, he accepted to become a creator. All these clearly showed their mindset to struggle for success without thinking about how many times they should try. The goal of the educators should be to the benchmark “mindset” or “attitude” toward the learning ability and intelligence to understand how this attitude toward learning is a critical factor in bringing changes [9, 10]. Dweck’s view on the growth mindset continues to gain momentum in every sphere of education and life worldwide [11]. In terms spurred by the introduction of interdisciplinary focus on new technologies, it is a learner-centered approach radically to learning. It nurtures the belief system by developing a growth mindset seemly opportunities and challenges to build the future and solves problems that enhance the quality of life [12, 13]. Mindset helps someone become proficient and contribute to a constantly changing world. Carol Dweck, a Stanford psychologist, called the mindset a power of belief that distinguished between two different mindsets, a fixed or a growth mindset. “People have fixed mindset tend to believe that their capabilities are set, as though these abilities were out of their control” [14]. “People with a growth mindset believe that capabilities can be developed, improved, and expanded. A growth mindset tolerates risk and failure, while a fixed mindset avoids risk and accompanying frustrations” [14–16]. The component of a growth mindset showed in Table 3.1. Why Growth Mindset in Engineering Pedagogy? It is no longer enough for engineering students to come out of an institution that purely produces technical education. Engineers start the market and business to figure out the margin of society [1]. Engineers’ most significant challenge and enormous opportunity are transforming knowledge into opportunities outside the institution to express and demonstrate themselves. Thus, their talent and the power of belief can be nurtured by engineering educators using the concept of a growth mindset [3, 5, 17]. The term “mindset” in the engineering field is not getting enough importance and is used casually. Although most often used in footings of “engineering mindset”, Table 3.1 Component of the growth mindset from the view of Carol Dweck Fixed mindset

Component of mindset Growth mindset

Performance goals (pick Challenges challenges that are easier to meet)

Mastery goals (always pick more difficult challenges)

View the exertion of effort as a sign of weakness

Obstacles

Perceive effort as an integral component of learning

Avoids feedback acts defensively

Criticism

Seeks feedback proactively

Escape to putting effort

Effort

Put effort as the view of learning; worthwhile learning requires hard work

Feel envious of others’ success

Success of others

Learn and feel inspired by the success of others. “I can try that”

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the engineering educator and research community have not adequately defined it in growth mindset-based engineering pedagogy [6, 7, 18]. Multiple definitions exist regarding the “engineering mindset”, none of which are grounded in the theory of growth mindset owed to confusion surrounding the everyday meaning of mindset and psychological research investigation into a growth mindset. Besides, the vital distinction refers to an individual’s belief that particular talent is innate or learned. Students who have a growth mindset compared to a fixed mindset are more likely ready to put tremendous effort into their work and take on the challenges in all situations [8, 17]. Here are some thoughts for engineering pedagogy with a growth mindset to work in various magnitudes given in Listing 3.1. Listing 3.1. Detailed Representative Points to a Growth Mindset in Engineering Pedagogy 1. To create a milieu that cultivates the engineering mindset, a growth mindset that heartens students to believe they can learn to do anything when faced with more challenges due to the attraction of more people into engineering meets future professional challenges problems. 2. To build a new body of teaching practice in engineering and develop a corps of practitioners. 3. To plan, design, and develop innovative ideas in an assortment of community contexts that assist a diverse group of learners who do not share the all-same resources.

Fig. 3.1 Relationship between mindset, attitude, and success

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Fig. 3.2 Mapping the learning cycle

1. Analysis of learner’s needs and mood/Mindset 5. Designing the assessment and feedback strategies. 4. Develop the instructional Strategies andlearning activity

2. Establish the big idea and framing the learning outcomes

3.Pigeonholin g the content

4. To recognize, sort, categorize, develop, and share a comprehensive framework of ventures and kits based on various tools and materials that connect to engineers’ interests in and out of school. 5. To design a social platform for collaborations among the engineer’s community. 6. To design and develop the programs utterly for young minds that allow them to take a leading role in creating and producing more and more in a community setting. 7. To allow individuals and groups to build a valuable community for academic career advancement and personal development. 8. To develop the educational context that links the practice to sustenance discovery and exploration while exploring new tools for advanced design. The self-belief that underpins the growth mindset in learners is the metacognition for critical thinking and reflective actions. The ultimate goalmouth of Dweck’s concept is to change a fixed mindset to a growth mindset [19]. The mindset directs the power of belief to recognize the opportunity affects the learner’s success [3, 7]. A growth mindset constitutes an attitude with metacognition which is vital for students to thrive in college, in their careers, and lifelong learning. It helps promote autonomy and resiliency. When students develop a growth mindset, they improve their metacognitive skills and attitudes toward that. It is required that students grow into a problem-solvers and critical thinkers, which need to help them in attitude building with metacognition [20]. The relationship between mindset, attitude with metacognition, and success is shown in the following concept map (Fig. 3.1). The relationship between mindset, attitude, and success is visualized in Fig. 3.2 portrays that learner with the growth mindset develops the attitude to accept challenges, resilience toward pressures and unfavorable circumstances,

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mistakes as a pathway to learn, and failures common in life move toward consistent efforts and leads success. Thus, with this understanding, the determination by engineering educators to take a growth mindset includes attitude building with metacognition in engineering pedagogy, which accomplishes learning with concerted efforts over extensive design knowledge and practice concerning scientific knowledge. Engineering pedagogy has to consider its teaching patterns on a growth mindset to influence the engineer’s perspective.

3.2 Growth Mindset Pedagogical Framework: A Vision for Engineering Pedagogy The engineering pedagogies and initiatives promise a practical roadmap that promotes the engineering field as demand. The present growth mindset pedagogical framework is a cohesive, unified, and dynamic guide that establishes a steady epistemological basis for engineering teaching and learning. The framework has been developed based on Carol Dweck’s “Growth mindset” concept, which elucidates the philosophy of “teaching and learning” in response to the learners’ potential. This framework unpacks the “three realms” of growth mindset hold on teaching (i) Focus, (ii) Mode of Operation, (iii) Feedback. Accordingly, the framework provides the specific “steps of process” for attitude building with metacognition among engineers, which is necessary for engineering educators to set a coherent approach. Within Processes, “sub-steps” with guiding principles are given for incorporating new and updated teaching–learning activities within instructions. The details of the framework are in Table 3.2. First Realm: Focus The first realm, “Focus,” is based primarily on worthy chores of success. The central goal of the framework is shifting from a fixed to a growth mindset. Dweck terms (fixed mindset; “fixed mentality stayed on the safe side and rejected a challenging new task” and growth mindset; “wanted the challenging new task for learning from”) describe underlying beliefs that reflect how belief system related to the malleability of intelligence and potential, which fuel behavior and forecast the success. Dweck synthesized her insightful inquiry into the “power of belief,” which profoundly impacts learner mindset and shapes their lives. The focus of the current point on engineering educators needs to bring a shift from fixed to the growth mindset for developing metacognitive skills. Therefore, educators need to create the learning mapping cycle before its implications. Step: 1 Mapping the Learning Cycle

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Table 3.2 Outline of the growth mindset pedagogical framework Realm 1: focus

Realm 2: mode of operation

Realm 3: feedback

Shifting from fixed to the growth Deriving knowledge from mindset different practice or practical’s

Provide feedback by the teacher, peer and self

Step 1: mapping the learning cycle

Step 2: developing the positive and growth mindset-oriented class culture

Step 3: assessment and value feedback

1.1 Analysis of learner’s needs and mood/mindset 1.2 Establish the big idea and frame the learning outcomes 1.3 Pigeonholing the content, task, problem, subject material 1.4 Develop the instructional strategies and learning activity 1.5 Designing the assessment and feedback strategies

2.1 Promote “HOTS” 2.2 Encourage to set personal learning goals and daily success folder 2.3 Tracking the students’ progress 2.4 Celebrating success

3.1 Portfolio assessment 3.2 Value feedback

• Sub-step 1.1 Analysis of learner’s needs and mood/mindset Identifying the engineering students’ needs, such as environmental and psychological, is essential. Engineering educators should set up personalized need analysis orientation to connect with students’ mindset, interests, culture, and experiences to achieve success. • Sub-step 1.2 Establish the big idea and frame the learning outcomes Crafting teaching around the big idea of linking different activities to the learning outcome provides a relevant route to student engagement in learning. Moreover, the pedagogical frame of the big idea is richer than topic headings that posit that proficient teachers extend the thinking of learners. In terms of engineering, learning lived experience pondering several significant intellectual endeavors. Therefore, this framework can help learn engineering concepts and practices more relevant through big ideas contextualized in socially pertinent. • Sub-step 1.3 Pigeonholing the content The content profoundly influences the knowledge structure involving the context orientation to its implementation in learning. The crafting of content in the form of problems and tasks is pigeonholing to create a magnificent symphony in teaching and learning. • Sub-step 1.4 Develop the instructional strategies and learning activity Implementing content in the classroom is entirely different from categorizing. Engineering educators now have questions about imparting knowledge and how to teach engineering content as per its discipline. Furthermore, to create a “technology-oriented activity” that accurately depicts the practice of engineering knowledge, reinforces the learning environment, and excels in developing

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students’ abilities, teachers need to develop teaching strategies and learning activities. This step engages students in different learning activities and assignments and celebrates their successful learning experiences. • Sub-step 1.5 Designing the assessment and feedback strategies In this process, an assessment portfolio has been developed. The engineering educators would assess them on various dimensions of growth mindset and metacognitive skill in terms of knowledge gained and skills acquired. This process can be more meaningful and customized to provide them feedback and reflect on the individual learning process. Consequently, learners get feedback on knowledge gain and metacognition skill development. The assessment portfolio format is given in the feedback section. Second Realm: Mode of Operation The mapping learning cycle determines the concern process of physical structure. However, the second realm organizes the environment to derive knowledge from different practices or practicals and develop a positive and growth mindset-oriented learning culture to set students’ performance and expectations. Creating such an environment helps better democratize engineering education “to know, do, and act for all students” to become more efficient engineers. There are some steps. Step 2: Develop the Positive and Growth Mindset-Oriented Learning Culture The engineer educator should understand that the class is the learning place for making mistakes as part of learning, not fearing efforts even if it might be hard to try. Learning is possible in all ways, and class is the place to enjoy creating something relevant, appreciate others’ efforts, and contribute to bringing out differences. Educators hold their hands and believe that they can do and provide high fives, patting backs, shaking hands, eyes reflection, and avoiding ignorance toward learners. Therefore, the teacher should create an inspiring and playful environment to foster happiness in learning, sharing positive emotions, experiencing success, and accomplishing goals. Figure 3.3 shows the tetrahedral model for mode of operations for developing positive and growth mindset-oriented learning culture. • Sub-step 2.1 Promote higher-order thinking Promoting higher-order thinking (HOTs) means “inspiring to think out of the box” instead of providing the students with far-reaching learning objectives. To develop high-order thinking among learners, engineering educators have to offer them more complex problems to apply the engineering concept and practices in problem-solving. Consequently, allow them to build up flexible and experimental tactics for designing and problem-solving to achieve success as they edifice in their engineering field with confidence.

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Fig. 3.3 Tetrahedral model for the mode of operation (developing growth mindset-oriented class culture)

• Sub-step 2.2 Encourage to set personal learning goals and daily success folder Engineering practices combine “skills and knowledge” that empower students to act or behave like an engineering individual. Engineering educators need to encourage them to set their personal goals and daily success folder to represent the knowledge allied with performing a particular practice well and complete the success folder over time with multiple experiences. To determine personal goal and to make success folder, the Format 3.1 is given below. Format 3.1. Tool or Worksheet for Learners to Set Their Personal Goals and Success Folder

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Learner name Class Subject Unit Teacher My personal goals

Daily success folder

Learning expectations with me for today? (Area for improvement)

Have I fulfilled learning expectations? (Achievement’s reflections (Did I achieve this goal? (Yes/No)

1. I will be listening attentively and thinking logically to turn knowledge into understanding 2. I will practice brain games, solve puzzles, and create mind maps to synthesize information 3. I will search, gather and produce knowledge about a new topic 4. I will pick up new energy through diverse sources 5. I will perform the given task 6. I will work on my plan over 7. I have to improve my learning on my own 8. I will identify difficulties/barriers and overcome these 9. Will I take an interest in the subject matter and enjoy learning? 10. I will be cultivating sources of trusted advice

1. I understand, clarify and accept different viewpoints? (Y/N) 2. Did I produce on my own? (Y/N) 3. I perform the following tasks today? (Y/N) 4. Am I satisfied with what I have learned succeeded? (Y/N) 5. Is my plan work/or not? (Y/N) 6. Did I identify my learning gaps? (Y/N) 7. I understood what I had learned? (Y/N) 8. I overcome my barrier and difficulties during learning? (Y/N) 9. Am I able to apply my newly acquired abilities in different situations? (Y/N) 10. I carry a new, fresh perspective on current realities? (Y/N)

Format 3.1, developed within the growth mindset pedagogical framework, comprises statements related to my personal goal and daily success folder. Personal goals are the learning expectations from the learner in the form of positive goals and stick them with a set of behavior to achieve. Setting goals is great, but in actuality, achieving them is much more challenging. Therefore, the daily success folder helps the learner watch the learning pattern themselves and focus more on the learning process with self-motivation. Personal goals and the daily success folder are daily habits to set a reminder to stay on track with success. This tool is a comprehensive write-up for tackling tangible life goals. • Sub-Step 2.3 Tracking the Students’ Progress The world is full of seemingly insurmountable challenges in engineering practice and daunting problems. However, engineering education needs to track the students’ progress to transform learning and prepare more optimized engineers to resolve such a challenge. The engineering educator would figure out their attitude building to accept challenges, never give up, struggle for hardship, and be ready to learn from mistakes. For tracking the student progress, Format 3.2 has been developed, given below.

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Format 3.2. Tracking Tools (Used by Mentor) for Learner Progress (Note: Educator can make it three points also, or you can make it numeric like 3, 2, 1, 0, and mentor will show the conclusion based on the given three dimensions). • Attitude frailty = (≤10) • Attitude ambivalence = (10–20) • Attitude strength = (20–30). Learner name Class—————————————————— Subject Unit Teacher—————————————————— S. No.

Areas

1.

Aware about personal goals and determine that/understanding learning expectation/fulfilment of learning expectation

2.

Asking queries/evident confusion

3.

Enjoy challenges/struggle for the hardship of a task/see failure as usual, and take a necessary step

4.

Accept challenges/not ready to give up/put efforts to overcome obstacles/never complain about blockers/welcoming obstacles

5.

Maintain their personal success folder happily

6.

Appreciate other’s work/give critical reflections on others’ work/

7.

Taking part in conversation made by mentor or peers regards another story/feel free to share

8.

Don’t feel peer pressure/enjoy doing work with peers

9.

Make mistakes, repeat mistakes but modify mistakes/errors

Mostly

Frequently

Some times

Never

(continued)

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(continued) Learner name Class—————————————————— Subject Unit Teacher—————————————————— S. No.

Areas

10.

Enthusiastic for trying new/finding out the new way or solutions for small things

Mostly

Frequently

Some times

Never

Hence, the tracking tool has played a vital role in shifting from a fixed to a growth mindset. The developed Format 3.2 helps the educators understand and analyze the attitudinal changes within the learners developed through the growth mindset pedagogy. The tool has three levels of attitude, attitude frailty, attitude ambivalence, and attitude strength to make sense of comparison and change students’ attitudes after exposure to growth mindset pedagogy. In this way, the teacher can track the student’s attitudes by giving them numeric like 3, 2, 1, and 0 for each statement. Accordingly, tracking tool records their attitude toward accepting, enjoying, and avoiding challenges, participation in different activities, and behavior toward making mistakes, repeating and modifying them. This tool will help the teacher witness overall growth through attitudinal change. • Sub-step 2.4 Celebrating success As learners of the engineering field deepen their knowledge and skills certainly, they move toward attitude building with metacognition. They should get a chance to work on more realistic, complex problems and show their achievements on various platforms. Celebrating their success influences them to move further and grasp more opportunities to apply more rigorous, abstract, conceptual and procedural knowledge, and metacognitive skills. Third Realm: Feedback The third realm is feedback which provides valuable feedback based on portfolio assessment. It clearly showed the attitude building taking from tracking progress reports made by the teacher, peer, and self in three-level attitude frailty, attitude ambivalence attitude strength which showed that engineer learners move from fixed mindset to growth mindset. Metacognition in terms of knowledge and skills is assessed through portfolio assessment which also informs about attitude building with metacognition. After all this, engineering educator would give valuable feedback to work on again to develop a growth mindset before moving to the new content.

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Step 3: Assessment and Feedback • Sub-step 3.1 Portfolio Assessment The assessment of intact can be done by the teacher, peer, and self. Intended teachers need to use portfolio assessments as presented below. Portfolio assessment addresses the criteria of assessment that demonstrates the growth mindset and metacognition development in terms of knowledge and skills within the learning graph. For the purpose, Format 3.3 is developed. Format 3.3. Portfolio Assessment Portfolio assessment has following criteria: • Criteria of assessment: Challenge, obstacle, effort, criticism, the success of others • Criteria of grading: NI (need to improve) = the student has not met the objective (≤5). PA (Progress adequately) = the student has sufficiently met the goals (6–8). PR (Progress Remarkably) = learner has surpassed the objective (8–9). OP (Outstanding performance) = the student has surpassed the objective and remarkably amplified the activity/goals (9–10). Learner name Class Unit Teacher S. No.

Growth mindset portfolio assessment graph (knowledge and skill)

NI

PA

PR

OP

Feedback (overall reflection)

Challenge 1.

Search for knowledge from different sources—scientific, loci, national. International, etc.

K

2.

Learn new searching tools and sources/reading, writing listening skills

S

Obstacle (continued)

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(continued) Learner name Class Unit Teacher S. No.

Growth mindset portfolio assessment graph (knowledge and skill)

3.

Manage the diverse piece of K information or understanding/organize and transmit the idea clearly and correctly/generate the original idea-driven from the experience of the obstacle related to the problem, task or content

4.

Implementing idea to overcome/maximum use of resources available

NI

PA

PR

OP

Feedback (overall reflection)

S

Effort 5.

Work in a constructive, creative way and innovative way by adopting different ways to solve the problem/putting effort into identifying the adequate data of related theme task content problem which exactly meet the objective

K

6.

Make the interconnection to real-life acquired

S

Response to criticism, adversity and failure 7.

Lineup the thought, problem, K idea, and analyze own inferences and draw a coherent conclusion based on understanding, criticize reflect on the argument

8.

Identify strong points (strength) or weak points (fragilities)

S

Viewpoint on the success of others (continued)

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(continued) Learner name Class Unit Teacher S. No.

Growth mindset portfolio assessment graph (knowledge and skill)

9.

Analyze other’s success K path/create own way of success/make a mind map for mastery content

10

Analytical skills/relook on the attempt made/analyze the factors responsible for a failure/equipping the critical

NI

PA

PR

OP

Feedback (overall reflection)

S

• Sub-step 3.2 Value Feedback The third realm is more vital due to comprehending the beauty of a growth mindset that is “self-reinforcing” and continues through more feedback conversations on academic work. Concerning the growth mindset pedagogy, value feedback positively influences attitude building and metacognition. It reflects upon the three levels of attitude in tracking learner progress; simultaneously, metacognition affluent in portfolio assessment at four level in terms of knowledge and skill development showed the learner’s growth mindset. Based on this, the engineering educator provides valuable feedback. For example, if the learner is at the level of attitude frailty, the educator will provide input on the she/he needs to work on his personal goals and learning expectations and give them more practice for enjoying work and give the reflections that mistakes are usual, feel free in sharing and clear confusion, etc., and in the same manner in other categories of attitude. In terms of portfolio, if the learner is at the needs to improve (NI) on the challenge dimension, the educator provides feedback that the learner needs to work on the search for knowledge more through different resources to gain knowledge and skills development and the same for other dimensions and categories.

3.3 Conclusion The growth mindset pedagogical framework is deep-rooted in the engineering field for learners’ everyday cognition and grow up them as per specific demands of the area. This growth mindset pedagogical framework and its three realms cover a wide range of teaching and learning aspects. It works with an implicit part of the intelligence

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of engineering learners and develops the attitude that the brain is a muscle. Through exercise, it can grow more and more. Before concluding, it is required to summarize the framework. The first realm focus is extensive in creating a learning mapping cycle and following it. Engineering educators focus on the need analysis of learners, getting involved with learners from the beginning and establishing big ideas creating worth to every instructional content accordingly. The pigeonholing makes the content design problem and task oriented. Engineering educator has the autonomy to weave instructional and learning activity inducing learners in inductive way. On the other hand, designing the assessment and feedback strategies supports the learning currency regaining in any field. The second realm mode of operation provides a channel that uses and executes learning activities to foster higher-order thinking, student cohesiveness, and engagement to set their daily personal goals and reflect on the visualization on their daily success folder. In addition, a tracking tool celebrating the success of one’s achievements encourages them and offers future participation and involvement in utilizing the opportunities. The third realm of feedback, embedded portfolio assessment, aims at authentic assessment, providing descriptive feedback of students’ work, showed as overall reflections to make learning visible. Feedback received from the teacher gives a clear hint for the open and welcome culture of best learning based on the clear ground state of the learner. If it is thought why engineering is so essential for the society, the answer would be that it is not just the profession or field which includes scientific and mathematical knowledge and includes technology and experimentations. It ranges from home to office, underground to the sky, serves humankind, ensures new development, and looks for solutions to the crisis. The demand from the engineering field puts a great responsibility on the shoulder of engineering educators to cultivate a growth mindset attitude with metacognition. Therefore, the engineer would become outstanding not only with sound scientific and technological knowledge but with a growth mindset. The growth mindset pedagogy fosters attitude with metacognition among engineering learners.

References 1. Campbell, A. L., Direito, I., & Mokhithi, M. (2021). Developing growth mindsets in engineering students: a systematic literature review of interventions. European Journal of Engineering Education, 46(4), 503–527. https://doi.org/10.1080/03043797.2021.1903835 2. Jamieson, M., & Donald, J. (2020). Building the engineering mindset: Developing leadership and management competencies in the engineering curriculum. In Proceedings of the Canadian Engineering Education Association (CEEA) (pp 1–8). https://doi.org/10.24908/pceea. vi0.14129 3. Frary, M. (2018). Encouraging a growth mindset in engineering students. ASEE Annual Conference and Exposition, Conference Proceedings, June 2018. https://doi.org/10.18260/12--30371

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4. Qadir, J., & Al-Fuqaha, A. (2020). A student primer on how to thrive in engineering education during and beyond COVID-19. Education Sciences, 10(9), 1–22. https://doi.org/10.3390/edu csci10090236 5. Brunhaver, S. R., Bekki, J. M., Carberry, A. R., London, J. S., & McKenna, A. F. (2018). Development of the engineering student entrepreneurial mindset assessment (ESEMA). Advances in Engineering Education, 1–12. 6. Dubbels, B. R. (2016). Pedagogy and play: Creating a playful curriculum for academic achievement and engaged learning. In Learning, education, and games. Curricular and design considerations (Vol. 2, pp. 87–116). 7. Hess, J. L., & Fila, N. D. (2016). The development and growth of empathy among engineering students. In ASEE Annual Conference and Exposition, Conference Proceedings, June 2016. https://doi.org/10.18260/p.26120 8. Riley, D. (2003). Pedagogies of liberation in an engineering thermodynamics class. In ASEE Annual Conference Proceedings (pp. 911–926). https://doi.org/10.18260/1-2--11854 9. Boaler, J. (2015). Mathematical mindsets: Unleashing students’ potential through creative math. Wiley. 10. Dweck, C. S. (2017). The journey to children’s mindsets—and beyond. Child Development Perspectives, 11(2), 139–144. 11. Haimovitz, K., & Dweck, C. S. (2017). The origins of children’s growth and fixed mindsets: New research and a new proposal. Child Development, 88(6), 1849–1859. 12. Li, Y., & Bates, T. C. (2017). Does mindset affect children’s ability, school achievement, or response to challenges? Three failures to replicate (pp, 1–26). Retrieved from https://osf.io/ preprints/socarxiv/tsdwy/download 13. Seaton, F. S. (2018). Empowering teachers to implement a growth mindset. Educational Psychology in Practice, 34(1), 41–57. 14. Dweck, C. S. (2006). Mindset: The new psychology of success. Random House Publishing. ISBN-13: 978 14000627511400062751. https://www.mendocinobookcompany.com/book/978 1400062751 15. Bates, P. (2016). Growth mindset. Access, 30(4), 28–31. https://search.informit.org/doi/10. 3316/informit.528112748596759 16. Mercer, S., & Ryan, S. (2010). A mindset for E F L: Learners’ beliefs about the role of natural talent. ELT Journal, 64, 436–444. https://doi.org/10.1093/elt/ccp083 17. Bashirova, M., & Sattarova, A. (2018). The use of new teaching and learning technologies for professional qualification development in the initial and secondary vocational education system. In Technical and vocational education and training (Vol. 28). https://doi.org/10.1007/ 978-3-319-73093-6_12 18. Campbell, A., Craig, T., & Collier-Reed, B. (2020). A framework for using learning theories to inform ‘growth mindset’ activities. International Journal of Mathematical Education in Science and Technology, 51(1), 26–43. https://doi.org/10.1080/0020739X.2018.1562118 19. Boyd, D. E. (2014). The growth mindset approach: A threshold concept in course redesign. Journal on Centers for Teaching and Learning, 6, 29–44. 20. Dweck, C. S., & Ehrlinger, J. (2006). Implicit theories and conflict resolution. In The Handbook of Conflict Resolution, 2, 317–330.

Dr. Anjali Sharma is an Associate Professor at the School of Education, Central University of Rajasthan. She has twenty-four years of teaching experience and twenty years of research experience. She has published 24 research papers in the UGC care list, Web of Science and Scopus journals and seven chapters in edited books. She has presented around 50 papers at national and international conferences and seminars. She has completed two sponsored research projects under the Ministry of Education, Govt. of India, and a few research projects on state government and published two books. Six Ph.D. Degree have been awarded under her supervision, and four research scholars are pursuing their research with her. She designed an educational game and took

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part in Toycathon 2021. She has contributed a question bank of 200 MCQ on Arunachal Pradesh under the “Ek Bharat Shrestha Bharat” program. She is a UGC nominated Master Trainer for the Community-based Participatory Research Program under Unnat Bharat Abhiyan2.0, Government of India. She is a UGC nominated member of the committee constituted for establishing guidelines for the Department of Education to implement National Education Policy 2020. She has organized National Seminar and an open-house discussion on National Professional Standards for Teachers (NPST, NEP Para 5.2) sponsored by NCTE, New Delhi, Capacity Building and Personality Development Program sponsored by National Women Commission, New Delhi, National Webinar on Inclusive Education and an Awareness Program on Cybersecurity in collaboration with Cyber-Peace Foundation and e-Saksham portal, AICTE. Sukanya Singh is a Ph.D. Scholar in the Department of Education, Central University of Rajasthan. She is awarded UGC senior research fellowship. She presented many papers at the National Seminar and International conferences and published three articles in her research area. Her research interests include Teacher Education and Science Pedagogy. Dr. Ram Prakash Sharma is currently working as a Member of the Board of Governors (BOG), BOS, Senate and Associate Professor, Department of Mechanical Engineering, National Institute of Technology Arunachal Pradesh, Jote, Papum Pare District, Arunachal Pradesh-791113, India. Dr. Sharma has more than 30 Years of UG and PG teaching and research experience. Dr. Sharma has guided one student for a Ph.D. degree, and 6 Ph.D. students are pursuing, and 4 M. Tech. students and 10 B.Tech. are completed M. Tech. and B. Tech. Projects. Besides teaching, he is actively engaged in research in the field of Fluid Mechanics. His research work has covered boundary layer flows, Newtonian and non-Newtonian fluids, and heat and mass transfer in porous/non-porous media. His research interests also covered nanofluids flow problems and many others. Dr. Sharma has published more than 100 publications in peer-reviewed National and International Journals. He is also a reviewer of many important National and International Journals. He is a life member of more than one and a half dozen National and International Academic societies. Dr. Sharma was elected Joint Secretary of the Executive committee of ISTAM (International Society for Theoretical and Applied Mechanics, IIT Kharagpur). He was elected Member of the Executive committee of ISTAM in December 2014 for three years.

Chapter 4

A Combination of Innovative Pedagogical Theories to Enhance the Learning Output—A Case Study with Engineering Students Shashank Pathak

4.1 Introduction There is no doubt that, with increasing population and limited resources, a large expert and specialized manpower equipped with advanced technology is required to solve critical problems. For example, building earthquake resilient houses needs specialized knowledge of engineering concepts. Such specialized concepts can be taught only by expert researchers in the specific field of earthquake engineering. However, generally, the educators, who are researchers and experts in a specific field, usually rely on their in-built teaching aptitude due to the lack of a specialized formal pedagogical training [65]. Thus, these teaching approaches may not be effective enough, and therefore, there is a strong need of translational research between different disciplines in higher education and pedagogy [58]. Pedagogy is referred to the branch of science that focuses on methods of teaching or educating the students. There are various components of pedagogy such as educator, method of knowledge transfer, media through which knowledge is transferred, the class to which knowledge is being transferred, psychological and technical response of the class, feedback generated out of that response, and response of the educator to those feedbacks. A more detailed description on pedagogy of higher education is discussed by Brubacher [10] and Barnett and Hallam [5]. The quality and effectiveness of the education depends upon (i) existing technological advancements and (ii) pedagogical strategies used for transferring the knowledge. Technical development provides effective and modern teaching tools such as Computer-Aided Learning (e.g., [35]), Virtual Reality and Laboratories (e.g., [55, 60, 72]), 3D Printing (e.g., [17]), Flipped Learning Methods (e.g., [34]), Web-Based Real-Time Remote Laboratories (e.g., [1]), Computer Simulation Games (e.g., [19]), S. Pathak (B) School of Civil and Environmental Engineering, Indian Institute of Technology Mandi, Mandi 175075, Himachal Pradesh, India e-mail: [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_4

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Spread-Sheets (e.g., [53]), Educational Data Mining (e.g., [2]), Mobile-Robots (e.g., [49]), E-Learning Technology (e.g., [23]), and so on. In addition to the above, the current pandemic situation has revolutionized the educational technologies (e.g., [12, 54]). Nowadays, most of the classes and research presentations are being conducted in ‘online mode’. There are various effective approaches that can be of help to the educators during online mode of teaching [42] such as voice management, enhanced interaction, flexibility in grading policies, dividing the long lectures into smaller modules, recording the lectures, and digitalization of lecture content. Thus, there exists extraordinary effective teaching tools, which can rapidly advance the quality education. However, pedagogical approaches are quite subjective and still appear to be going through an evolution process [36, 46]. There are also various types of teaching styles such as (i) Montessori method which assumes that students are naturally eager to learn and educator is just supposed to facilitate a good learning environment [50]. For example, A recent phenomenon ‘Maker Movement’ has its roots in Montessori method [45], (ii) Socratic learning method (SLM) emphasizes on systematic and critical thinking [9, 14, 63], (iii) Retrieval practices, which are revision-based learning activities and help in long-term retention of fundamental concepts [30]. This is generally implemented through frequent classroom quizzing in form of short answers, multiple-choice questions, and/or hybrid tests [64], (iv) Problem-oriented and project-based learning (POPBL) in which instructor throws a challenge in form of a project and students implement the project activities either independently or as a team [25, 38, 41, 48], (v) Mantle-of-the-expert approach uses a fictional context in which students play the role of an expert team to solve problems and learn the subject in the process [28, 44, 68]. This approach is especially useful in inculcating the interest in students toward science and engineering at an early age, (vi) Dialogic teaching facilitates learning through questions and reasoning [26] and is the most commonly used method of teaching, and (vii) subject-specific approaches such as case study-based teaching [13, 59, 61]. Though several educational tools and approaches are available but their implementation depends upon overall academic and socio-economic environment of the institute and academic-social background of instructors and students. The social background mainly consists of peers and people who surround the student. For example, if a student is coming from a social environment, which is more technologically oriented, then certainly the student may have more inclination toward modern-day audio–visual and Web-based approaches. Usually, the educators with specific technical background may not have any formal and systematic training in pedagogy or education science and most of them teach in a way that naturally occurs to them. Additionally, the human emotions of educators also govern the teaching approach [70]. Therefore, they may not have a tailor-made answer to the question: ‘which tool and which method to use and how’? Author believes that answer to this critical question can be found through various ‘pedagogy case studies’. As also recommended by Bernstein [6] and Healey et al. [27], it is always an excellent idea to highlight and share the innovative teaching and learning practices with other colleagues because such case studies may play an important role in discussing and evaluating education strategies (e.g., [3, 4, 8]). It is also important to

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note that each case study has its own importance and a certain domain of applicability. For example, Shekhar and Borrego [62] discuss a case study of large-size classes, Clark and Andrews [15] evaluated the effectiveness of the concept of scholarship; McKenna et al. [47] analyzed the effects of teamwork on students’ performance, and so on. Such case studies represent direct application of different pedagogical theories discussed above and may help in effective professional development on teaching skills [22, 29]. Educators usually adopt to conscious or subconscious changes in their teaching methodology to improve the learning output of their class based on the students’ performance and feedback. However, if the learnings from such case studies are also implemented along with those students’ feedback, then educators may design their own optimum teaching approach suiting the needs of their class and subject. In view of the aforesaid discussions, this paper presents an important case study in which the author tried and experimented some interesting methods while teaching a course on ‘Engineering Mechanics’ to a small class consisting of 13 students who had already failed this course in a previous semester at Indian Institute of Technology (IIT) Gandhinagar, Gujarat (India). Thus, this case study specifically deals with pedagogy for a small group of ‘poorly-performing’ and ‘uninterested’ students to enhance their interest and performance in the subject. It is observed that, with the adopted teaching strategies, intended results were obtained. It is also to mention that the discussions based on this case study are of general nature and applicable to other disciplines as well. Thus, the present paper attempts to investigate the Scholarship of Teaching and Learning (SoTL) question from Hutchings [32] taxonomy: ‘what works?’ for students with poor track record.

4.2 Initial Conditions It is quite important to understand the psychology of the students toward education for adopting an appropriate teaching methodology [37]. Personal interview with students is the most effective way to achieve this goal (e.g., [7, 66]). In the beginning of the course, 13 students were interviewed personally. During that interview, following key questions were asked to the students: (1) (2) (3) (4) (5) (6) (7) (8) (9)

What are the career objectives? Do you compare yourself with other students? What are your family circumstances? Why were you not able to perform well in previous semesters? What are your plans after graduation? What if you are not placed from campus? Who is your role-model? What is stopping you from performing well in your academics? Why did you opt for engineering?

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(10) Do you perform well in areas other than academics? (11) What are you good at? Based on their answers, it was observed that these students were (i) anxious of exams, (ii) having significant peer pressure, (iii) low in confidence, and (iv) not interested in such a mathematically demanding course. In addition to this, they also made clear to the instructor that they aspire for such career choices, which may never require the learning outcomes of a course on ‘Engineering Mechanics’. Therefore, initial conditions were not in favor of an effective learning, and available teaching tools were also not of much help. Such interviews are also helpful in studying the additional personality traits linked to student performance and learning curve (e.g., [51]). In present case, students were observed to be anxious of exams, susceptible to peer pressure, and of low self-confidence. Thus, there was a need of carefully chosen teaching approach which should be compatible with students’ personality traits so as to, first-of-all, make them a good receptor of the education.

4.3 Design of Course Content Effective design of course content is the first step toward quality education (e.g., [33, 40]). Based on the interviews, needs of the students were clearly understood, and then, an innovative course content was circulated among the students. It was decided that purpose of the course should not only be to make students capable enough to pass just this course but also to initiate a corrective action in their attitude toward education so that they can do well in other courses and in their respective future career. Thus, the course content was designed in two parts: (a) technical content and (b) non-technical content. The first part discussed about fundamental principles of ‘Engineering Mechanics’ such as forces, moments, energy, equilibrium, conservations, essential mathematics, application of fundamentals in study of linear motion, rotation, and vibrations. However, the second part was aimed at general corrective action in students’ attitude toward education. This part mainly talked about ‘principles of values and ethics’, ‘how to learn on your own’, ‘how to generate interest in your job’, ‘how to write exams effectively’, and ‘how to do well at interviews’ [39]. It is to clarify that for the second part there were no separate classes or lectures. In fact, the second part was amalgamated with the first part as will be seen in the following description.

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Table 4.1 Adopted grading scheme for the course on ‘engineering mechanics’ Item

Grading contribution Description

Quiz

15

Surprise quizzes, announced quizzes, interaction in class, open-book and open-paper quizzes, self-graded quizzes, take home exam

Mid-semester exam

25

General examination

End-semester exam

30

General examination

Interview

10

Similar to technical job interview

Attendance

–

Less than 65% no passing grade

Assignment

5

General homework

Group discussion

5

Solving technical problem in a group

Course file

5

Maintain a course file that students were supposed to bring during the interview so as to check their organizational skills and course notes

Computer assignment 5

Coding, literature review, MATLAB, Excel tools

4.4 Evaluation and Assessment Strategy Performance assessment of students is very crucial part of teaching methodology [18]. It has been observed that learning is directly linked with the assessment methodology [67]. Therefore, in this course, an interesting and innovative grading scheme which was also compatible with the course content was launched as shown in Table 4.1. It is well known that exam anxiety and exam fear may reduce the performance and learning of the students [56, 69]. To overcome such fear and anxiety, number of quizzes was kept significantly high (1 per class). The main reason behind this was to keep students focused during the lecture and to make them believe that exams are the tools to learn the concepts rather than getting stressed. Generally, very simple questions were asked in the quizzes which were direct replica of whatever they have been taught in the same class. This approach is a kind of retrieval practice [30] as discussed in Introduction of this paper. It was observed in the subsequent classes that routine quizzing helped significantly in increasing the confidence of the students, and they did reasonably well in general examinations too. Initial interviewing helped the students to convey their problems personally to the instructor. For example, a few students were having language problem due to which they were not able to understand the course content taught in English. Therefore, such students were treated separately after the classroom and were helped with language skills. They were strategically grouped with their fellow classmates who can explain them the concepts in a language familiar to them after the class. This improved their performance not only in this course but also in other courses that they opted. Class attendance has always been found to be significantly correlated with academic performance of the students (e.g., [57, 74]). Even an effective instructor

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would require a few weeks of continuous contact with students to adopt the effective teaching style. In view of this, attendance was given a significant weightage in the grading scheme by making it mandatory to pass the course. Quite often, peers may know better about the difficulties being faced by fellow classmates in understanding the subject (e.g., [20]). Thus, effective learning can be initiated only if group activities are enhanced in the classroom. This also makes the classroom session very interesting, active, effective, and fun-filled. Therefore, group discussions were introduced in this course to ensure inter-student knowledge transfer just like the concept of co-operative learning [31]. The concept of course file was adopted from school days where students were supposed to prepare files for science experiments. This was done to make sure that students are attentive in the class while taking notes. It was decided that each student would prepare his/her own hand-written notes, and the same would be audited at the time of final interview. This helped them in developing a habit of systematic documentation, and this habit also benefitted them in other courses. Computer assignments were part of a strategy to use technical teaching tools to make the students learn some new computer skills through this course. Thus, it can be noted that the adopted grading scheme was not only focused on the all-around assessment of the students but also was coherent with the effective learning styles.

4.5 Delivering the Lecture Teaching and learning are a two-way transfer of knowledge: from teacher to students and from students to teacher. This knowledge transfer depends significantly on the lecture delivery style (e.g., [43, 52]). For effective transfer of knowledge, it is advisable to decide the pace, content, and style of lecture delivery based on real-time classroom interaction with students which is also supported by a recent study highlighting the fact that the teaching approaches evolve with experience and time [71]. In present case, during the daily classroom interaction with the students, the instructor noted some drawbacks in the lecture delivery style and corrected himself in the next class. For example, initially, the instructor was tempted to cover so many concepts and in a very short time. However, with weaker students, this could not work as the instructor skipped important steps which were obvious to above-average students but not to the weaker students. Therefore, after a few initial classes, an optimum pace of delivering the lecture was adopted based on the collective grasping capability of the class. It is to note that regular classroom quizzing helped the instructor to assess the collective class performance. It is pertinent to mention that each individual (teacher) may face different set of problems while interacting with the students, and therefore, problem-specific pedagogical solutions should be tried.

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4.6 Experiments with Examination Patterns In the present case study, the most important experiment was conducted with the patterns of various examinations (quizzes and semester exams) conducted during the course work. These are briefly described as follows: • Quizzes were conducted almost after every class. The teaching time was set to approximately 45 min, and last 15 min were kept for the surprise quiz. It was directed to the students that they do not need to prepare specially for the quizzes. In fact, they were instructed to remain focused during the class time, and the questions were asked based on the topic discussed in the first 45 min of the class. This helped in three ways: (i) increasing the class attendance, (ii) improving focus of the students, and (iii) eradicating exam-phobia of the students. • The main purpose of examinations was not to judge the students but to enable them to understand and grasp the methodology of solving problems. Therefore, in quizzes and exams, the long questions were broken into small parts or steps so that students were partially guided to find the solutions on their own. • Solutions to the quizzes were sent immediately after the exam so that students can go through the correct solutions. This is required for their self-assessment and learning. • The end-semester examination was conducted in two parts. First part consisted of objective and short-answer-type questions, whereas, second part consisted for long and thought-provoking questions. The purpose was to first reduce the examphobia of the students and then allow them to apply their true capability in solving more serious and longer questions. • Peer-graded quizzes: Some of the quizzes were graded by peers through random exchange of exam papers among them. This was done to make the quiz session an interesting and fun activity. This also provided an opportunity to implement the technique of self-assessment as suggested by Boud and Falchikov [11]. • Group quizzes: Some of the quizzes were designed to solve the problem in a group of two or three. This enhanced the interaction among the students. It is observed that such an activity helped in increasing the performance of the class as a whole. • Peer-designed question papers: In this case, all the students were given a task to set the question paper on their own and submit the answer and the question paper to the instructor. The instructor jumbled up the questions, and a random set of questions were picked up to fix the final question paper. This helped in two ways: (i) students were forced to think on how to create questions which is very important in understanding any subject, and (ii) students learnt about so many questions as they discussed among themselves the question papers set by their fellow peers before appearing for the final question paper. Such an activity enhances the process of self-learning. Thus, it can be seen that adopted examination style was an optimum mix of learning and assessment.

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4.7 Reward Policy for Student Motivation Motivation of students (learners) plays a key role in efficient and effective learning (e.g., [16, 21]). Expectancy value theory (EVT) [73] has previously been used to study the key motivating factors to improve the teaching practices [24]. These studies were mainly concerned with motivation of the educators and teachers but did not focus on motivation of students. Nonetheless, EVT can also be applied to the students as well. For example, in present case, (i) utility value factor and (ii) attainment value factor were used as two key EVT factors for motivation of students. Utility value factors were related to the incentives and rewards such as inviting the topper of the quiz or exam for executive dinner with the instructor where the student was free for informal communication with the instructor just like another friend. On the other hand, attainment value factor was mainly focused on building the friendly and healthy relationship with students through classroom and post-class discussions. Such motivational policies were found to be of great help in long-term performance of the students in the course.

4.8 Gross Outcome of Adopted Pedagogy Outcomes of the adopted teaching styles and pedagogical experiments conducted in this case study were observed in two forms. The first one was in terms of improved perception of students toward education and growth in their confidence. The second one was measured through overall grades obtained by the students as given in Table 4.2. Table 4.2 Performance of the class in the course Item

% Contribution

Coeff. of var. (%)

Class max

Class min

Quiz

15

7.5

31

11.5

3.5

Mid-semester exam

25

15.6

36

23.5

6.3

End-semester exam

30

15.9

33

23.1

8.1

Interview

10

7.7

18

9.3

4.2

Class avg.

Attendance

–

85.6%

11

100%

68%

Assignment

5

3.8

16

4.6

2.7

Group discussion

5

2.3

74

5

0

Course file

5

3.7

26

5

2.5

Computer assignment

5

4.1

16

5

1.7

Total

100

60.6

26

81.6

36.9

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It can be observed that overall performance of the class (60.6% marks) is reasonably good considering the initial conditions of the students. Though there is a huge gap between class maximum (81.6) and class minimum (36.9), a small coefficient of variation (26%) indicates that class performed well as a whole. The pedagogical experiments made the course very interesting, and this is reflected through a high average attendance (85.6%) throughout the semester with very small coefficient of variation (11%). Thus, it can be noticed that adopted teaching styles in this course were successful in achieving the intended results. The high attendance and participation of the students in the various class activities itself is an indicator of improved perception of the students toward education and growth in their confidence.

4.9 Conclusions The educators, who are focused researchers and experts in a specific field of education (science, art, or humanities), usually do not have any formal and systematic training in pedagogy or education science and most of them teach in a way that naturally occurs to them. Thus, they may miss the application of advanced and more effective teaching strategies which can significantly improve the performance of the class. However, author believes that communicating the application of innovative pedagogical approaches through classroom case studies may be of great use to such educators. In view of this, a pedagogical case study is presented which combines several innovative strategies in a class of students who had a previous record of poor performance, and an improved performance of students was demonstrated. Based on this case study, following key recommendations are made that can be conveniently adopted by educators who are not specialists in pedagogical research: • A personal interview (at the start of the course) with each student may provide a direction to the teaching methodology to be adopted for the course. • In the case of poor-performing students, the course content should be designed in two parts: technical and non-technical content. Technical content is supposed to be focused on the conceptual understanding of the subject while the second part should be aimed at general corrective action in students’ attitude toward education. • The assessment strategy should be such that it reduces the exam anxiety and exam fear in students, and it should also provoke self-learning attitude in students. The presented case study provides a variety of options for innovative examination styles which are an optimum mix of learning and assessment. • It is also important to adjust the pace of delivering the lecture based on the collective grasping capability of the class. • In case of poor-performing and demotivated students, a student reward strategy can play a crucial role in long-term performance of the students in the course and building self-motivation.

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In nutshell, this case study emphasizes that the purpose of educating is not only to teach the concepts of a particular topic or subject but also to inculcate the spirit of self-motivation and self-learning in the students. Acknowledgements Author dedicates this article to Prof. Sudhir K. Jain, Former Director of IIT Gandhinagar and currently the Vice-Chancellor of Banaras Hindu University, for encouraging and motivating the author to write this article. Author is also thankful to Dr. Purnima K. Bajre, Visiting Assistant Professor, School of Humanities and Social Sciences, IIT Mandi for critical discussions on the manuscript. Declaration of Conflict of Interest Author declares that there is no conflict of interest.

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41. Lehmann, M., Christensen, P., Du, X., & Thrane, M. (2008). Problem-oriented and projectbased learning (POPBL) as an innovative learning strategy for sustainable development in engineering education. European Journal of Engineering Education, 33(3), 283–295. 42. Mahmood, S. (2021). Instructional strategies for online teaching in COVID-19 pandemic. Human Behavior and Emerging Technologies, 3(1), 199–203. 43. Malik, A. S., & Malik, R. H. (2012). Twelve tips for effective lecturing in a PBL curriculum. Medical Teacher, 34(3), 198–204. 44. Malone, K. L., Tiarani, V., Irving, K. E., Kajfez, R., Lin, H., Giasi, T., & Edmiston, B. W. (2018). Engineering design challenges in early childhood education: Effects on student cognition and interest. European Journal of STEM Education, 3(3), 11. 45. Martin, L. (2015). The promise of the maker movement for education. Journal of Pre-College Engineering Education Research (J-PEER), 5(1), 4. 46. McAuliffe, M., Hargreaves, D., Winter, A., & Chadwick, G. (2009). Does pedagogy still rule? Australasian Journal of Engineering Education, 15(1), 13–18. 47. McKenna, A., Mongia, L., & Agogino, A. (1998). Capturing student’s teamwork and openended design performance in an undergraduate multimedia engineering design class. In Fie’98. 28th Annual Frontiers in Education Conference. Moving from ‘Teacher-Centered’ to ‘LearnerCentered’ Education. Conference Proceedings (Cat. No. 98ch36214) (Vol. 1, pp. 264–269). 48. Mills, J. E., & Treagust, D. F. (2003). Engineering education—Is problem-based or projectbased learning the answer. Australasian Journal of Engineering Education, 3(2), 2–16. 49. Mondada, F., Bonani, M., Raemy, X., Pugh, J., Cianci, C., Klaptocz, A., Magnenat, S., Zufferey, J.C., Floreano, D., Martinoli, A. (2009). The e-puck, a robot designed for education in engineering. In Proceedings of the 9th Conference on Autonomous robot systems and competitions (Vol. 1, pp. 59–65). 50. Montessori, M. (2013). The Montessori method. Transaction Publishers. 51. Núñez-Peña, M. I., Suárez-Pellicioni, M., & Bono, R. (2013). Effects of math anxiety on student success in higher education. International Journal of Educational Research, 58, 36–43. 52. Oberlin, K. E. (2017). Five steps for delivering an effective and educational lecture. Cutis, 99(6), E10–E12. 53. Oke, S. (2004). Spreadsheet applications in engineering education: A review. International Journal of Engineering Education, 20(6), 893–901. 54. Paudel, P. (2021). Online education: Benefits, challenges and strategies during and after COVID-19 in higher education. International Journal on Studies in Education, 3(2), 70–85. 55. Potkonjak, V., Gardner, M., Callaghan, V., Mattila, P., Guetl, C., Petrovi´c, V. M., & Jovanovi´c, K. (2016). Virtual laboratories for education in science, technology, and engineering: A review. Computers and Education, 95, 309–327. 56. Putwain, D. (2008). Examination stress and test anxiety. Psychologist, 21(12), 1026–1029. 57. Romer, D. (1993). Do students go to class? Should they? Journal of Economic Perspectives, 7(3), 167–174. 58. Roxa, T. (2018). Making use of educational research in higher education–academic teachers engaged in translational research. Teaching and Learning Inquiry, 6(2), 67–80. 59. Russell, J. S., & McCullouch, B. G. (1990). Civil engineering education: Case study approach. Journal of professional issues in engineering, 116(2), 164–174. 60. Sampaio, A. Z. (2012). Virtual reality technology applied in teaching and research in civil engineering education. Journal of Information Technology and Application in Education, 1(4), 152–163. 61. Sankar, C. S., Varma, V., & Raju, P. (2008). Use of case studies in engineering education: Assessment of changes in cognitive skills. Journal of Professional Issues in Engineering Education and Practice, 134(3), 287–296. 62. Shekhar, P., & Borrego, M. (2018). ‘Not hard to sway’: A case study of student engagement in two large engineering classes. European Journal of Engineering Education, 43(4), 585–596. 63. Shoop, B. L., & Ressler, E. K. (2011). Developing the critical thinking, creativity and innovation of undergraduate engineering students. International Journal of Engineering Education, 27(5), 1072.

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Shashank Pathak received his B.Tech–M.Tech (Dual Degree) from Indian Institute of Technology (IIT) Kanpur and Ph.D. in Civil Engineering from IIT Delhi, in 2010 and 2019, respectively. From 2010 to 2011, he worked as structural design engineer at Larsen and Toubro Ltd. in Faridabad design office, and from November 2011 to April 2012, he taught Engineering Mechanics at IIT Gandhinagar as an assistant research professor. In June 2012, he joined Central Soil and Material Research Station, New Delhi as a Scientist where he worked mainly in the field of in-situ rock mechanics investigations for various hydropower projects in India, Nepal, and Bhutan. In November 2019, he joined Université Libre de Bruxelles, Belgium as a Postdoctoral researcher in Precision Mechatronics Laboratory, and currently, he is an Assistant Professor in School of Civil and Environmental Engineering of IIT Mandi, Himachal Pradesh since November 2021. His interests lie in the theory of structural dynamics and random vibrations with applications to the fields of Earthquake Engineering and Blast Engineering. Shashank is the author of 17 papers including the reputed international journals, book chapters, and international conference proceedings.

Chapter 5

Effective Online Teaching and Evaluation Methods Dilip Kumar Pratihar

5.1 Introduction According to Swami Vivekananda, education is the manifestation of perfection already in man [1, 2]. Education aims to cultivate good qualities in life like honesty, desire to work hard, leading disciplined life, patience, tolerance, and others. The role of a teacher is to help the students, so that they can reach their goals. In an educational institute, education is imparted through a curriculum, which is considered as its backbone. Curriculum is to be designed in such a way that it can provide the maximum information to the students in a pre-defined duration of one course. At the early stage of a course, curriculum is to be made a structured one to provide the minimum necessary information to all the students, and at the later stage of the course, it is to be made a more flexible one, so that a student gets the opportunity to learn the subjects according to his/her interest. Subjects according to the curriculum are taught by the teachers to the students in physical (face-to-face) classes and/or laboratories. Due to the ongoing COVID situation, face-to-face lecture and/or laboratory class has become an impossibility. To overcome this situation, arranging online lecture and/or laboratory class and taking online examination is the only option left with us. Although the online course was first started in 1981 [3], the introduction of the World Wide Web (WWW) in 1991 could act as a catalyst to make the online courses more popular [4]. Online teaching is found to be more cost-effective and flexible compared to face-to-face teaching. One teacher can teach more number of courses as well, and a student can take the more number of courses, if these are taught in online mode. Moreover, online teaching offers an enhanced interaction between the teacher and students compared to the face-to-face teaching [5], and consequently, the students’ feedback can be collected more easily. Face-to-face teaching offers the D. K. Pratihar (B) Indian Institute of Technology Kharagpur, Kharagpur 721302, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_5

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chance of establishing the eye contact between the teacher and the students, which is missing in online teaching. Thus, educational effectiveness of online teaching is less than that of face-to-face teaching. Both the teacher and students should have sound knowledge of the software used for online teaching. To implement online teaching effectively, a teacher will have to design his/her course materials and its power-point presentation in an optimal sense, so that the maximum information can be given in minimum time.

5.2 Online Teaching To make online teaching more interesting, interactive, and efficient by using the software like Microsoft Teams, Zoom, Google Meet, and others, which is a more difficult task for the teachers [6], the following points may be adopted: • Conventional memory, class notes-based teaching is to be replaced by PPT-based one, in which.pptx files are to be prepared topic-wise in an adaptive way. Thus, different types of.pptx files are to be designed and developed for various topics even for the same subject. Three distinct methods may be followed to design the.pptx files for online teaching of the course on robotics [7], as described below. Type 1: Define the Basic Terms; Explain the Rules/Equation(s); Apply the Rules/Equation(s) to Carry Out Analysis; Solve Numerical Example Examples: To teach robot kinematics efficiently in online mode, slides are to be designed as follows: Two link parameters, namely length of a link and angle of twist of a link, and two joint parameters, such as joint angle and link off-set, are to be defined at first. Denavit–Hartenberg’s (D–H) rules are to be explained with some suitable examples in order to assign coordinate systems at the robotic joints. The D–H parameters’ table is constructed, and frames’ transformation is then carried out to determine the position and orientation of the end-effector with respect to its base coordinate system, which is known as forward-kinematics problem in robotics. Inverse robot dynamics aims to determine the amount of torque, force required for the rotary, linear joints, respectively. The slides for teaching this topic are designed as follows: The inertia tensor is determined at first for the robotic links. The mathematical expressions for kinetic energy and potential energy of the robot are derived. Lagrangian of the robotic system is determined as the difference between its kinetic energy and potential energy. Lagrange–Euler equation is then used to derive the expression for joint torque or force depending on the nature of the joint. For a rotary joint, torque is determined, and joint force is calculated for a linear joint. Type 2: To Explain the Importance of Topic of Discussion, Show a Video/Photograph or Tell a Story/Fact, Before Starting its Discussion Examples: Before teaching the topic on trajectory planning, a photograph and/or video is shown to the students related to the nature of failure of a robotic joint due

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to its jerky movement, as the smooth variation of its angular or linear displacement is not ensured. The slides will be designed to contain the various types of trajectory functions generally used for the robotic joints. To design and develop intelligent and autonomous robots, various systems of a human being, such as sensors, vision system, and motion planning, are copied in an artificial way. Information is collected by the human beings with the help of sensors (both internal and external), and the necessary processing is done to extract it further in the useful form. The photograph of the environment is collected using human eyes; the processing is done in human brain to recognize the objects present in the image. Human brain also carries out multi-sensors data fusion to collect information of the environment. Based on the collected information, the course of actions is decided and implemented. The similar methods are adopted in the artificial way to make the robots intelligent and autonomous. The slides are to be designed in such a way, that these similarities between the human beings and intelligent and autonomous robots are incorporated. Type 3: Solve a Numerical Example and Simultaneously Explain the Working Principle If the working principle of an algorithm involves a large number of steps, it becomes a difficult task for a teacher to explain it clearly to the students, and they get confused. To make this topic understandable to the students, a teacher may explain the algorithm step-wise through solving a numerical example. Example: A DC motor is mounted at the robotic joint to provide the necessary torque, and a suitable controller (say, proportional integral and derivative (PID)) is used to run the motor. It is to be noted that their fixed gain values are determined in various ways, and out of all these, Ziegler–Nichols method [8] is the most popular one. However, this method provides the fixed gain values for this controller, which may not be suitable to generate the movement of the robotic joint in an adaptive way. To determine the said gain values in an adaptive way depending on the requirement, either a fuzzy logic or neural networks-based expert system is to be evolved using an evolutionary tool. This method of evolving an adaptive controller for the motor mounted at the robotic joint can be explained efficiently through a numerical example. • During the online class, the students are asked to put their laptop/mobile cameras on, so that the teaching assistants (TAs) can check their attendance by viewing their photographs captured in Gallery mode. • Doubt-clearing session is to be kept for the last ten minutes of each class.

5.3 Grading During the pandemic periods, physical examination (also known as offline examination) could not be conducted. Moreover, it becomes a difficult task to conduct

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viva-voce examination for a large number of students registered in a subject. Therefore, an alternative method of grading is to be proposed. Grading of a subject may be done through a few assignments and some online tests, and an equal weightage may be given on these two components.

5.3.1 Assignments Assignments are to be designed in two different ways, so that the students will be advised and forced to give their own opinion, as discussed below. • It may be designed based on a conceptual idea like “All autonomous robots are intelligent but not all intelligent robots are autonomous.” The students will be asked to justify this statement within say, 100 words. • It can be on the inference drawn on the results of numerical example, instead of asking the students to solve the numerical example only. For example, each of the problems like inverse kinematics, forward dynamics of a serial manipulator will have multiple solutions, and the student will have to logically arrive at an optimal solution out of all the feasible ones. The student will have to draw this inference within 100 words. It is to be noted that the main idea behind designing this type of assignments is to give the students an opportunity to give their own ideas on the topic of assignment, instead of mechanically solving it. During evaluation, similar solutions are to be clustered and may be penalized for the grading purpose. Therefore, not only the correctness of the answer but also its uniqueness is to be considered for the grading purpose. A correct and outlier type of answer will be getting the maximum grade.

5.3.2 Online Examination Online examinations are conducted in virtual conference (VC) mode using any one of the software mentioned above, for which multiple-choice questions (MCQs) will be designed based on theoretical study and/or numerical example depending on the nature of the subject. The following steps are followed to conduct the online examination in VC mode: • Students are asked to put on the cameras mounted on their laptop/mobile, which is a must for checking their attendance. • Students’ identity is verified through facial recognition using photographs and/or signature verification. • The duration of examination, method of submission of the answer-scripts are then announced, and the question paper is then posted on the VC platform.

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• Online invigilation is arranged in virtual mode by the teacher(s) and/or TA(s). During the invigilation, photographs of the students will be captured in Gallery mode, Large Gallery mode, and Together mode to assess the mental states of the students from their facial expression, eye contact, typing speed, etc., to identify the malpractice case, if any. • Viva-voce examination is to be conducted by the teacher(s) through VC for the suspected malpractice case.

5.4 Conclusion The above methods of online teaching and evaluation had been implemented by the author on six subjects. The students’ feedback was found to be encouraging and even better compared to that of the face-to-face classes. The student’s attendance was seen to increase by about 19%. Malpractice during the examination could be minimized through online invigilation. For a large class, the students’ performance was found to follow the normal distributions. Although online teaching has got a few merits, it suffers from some drawbacks. In online teaching, it becomes difficult for a teacher to understand, whether a student has really understood the topics of discussion, as there is no direct eye-contact between them. Moreover, online teaching may give rise to some problems like mental stress, physical disabilities, etc., for both the teacher and students if it is continued for a long period of time. It is also quite impossible to develop a full-proof online examination method to make it fully error-free. Acknowledgements The author is profoundly grateful to his employer, Indian Institute of Technology Kharagpur, India, for providing him the necessary facilities for conducting online teaching and examination. He is thankful to the National Programme on Technology Enhanced Learning (NPTEL), an initiative of the Ministry of Human Resources Development (MHRD) (now, Ministry of Education), Government of India, for the necessary support, to develop three online courses, namely Robotics, Traditional and Non-Traditional Optimization Tools, Fuzzy Logic, and Neural Networks. He is grateful to the Indian National Science Academy (INSA), New Delhi, for awarding him the INSA Teachers’ Award 2020, for his innovative ideas related to teaching methods. Special thanks are due to the committee of New Code of Education (NCOE) Award, which he received in 2021 for his innovative ideas on online examination and evaluation methods. Declaration of Conflict of Interest Author declares that there is no conflict of interest.

References 1. https://vivekavani.com/education-manifestation-perfection-man/. Accessed on March 29, 2022. 2. https://vivekavani.com/what-we-believe-vivekananda/. Accessed on March 29, 2022. 3. Harasim, L. (2000). Shift happen: Online education as a new paradigm in learning. The Internet and Higher Education, 3, 41–61.

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4. Sun, A., & Chen, X. (2016). Online education and its effective practice: A research review. Journal of Information Technology Education: Research, 15, 157–190. 5. Bell, B. S., & Fedeman, J. E. (2013). E-learning in postsecondary education. The Future of Children, 23(1), 165–185. 6. Sadiku, M. N. O., Adebo, P. O., & Musa, S. M. (2018). Online teaching and learning. International Journals of Advanced Research in Computer Science and Software Engineering, 8(2), 73–75. 7. Pratihar, D. K. (2017). Fundamentals of ROBOTICS. Narosa Publishing House. 8. Ziegler, J. G., & Nichols, N. B. (1942). Optimum settings for automatic controller. Transactions of the American Society of Mechanical Engineers, 64, 759–768.

Dr. Dilip Kumar Pratihar received his B.E. (Hons.) and M.Tech. in Mechanical Engineering from Regional Engineering College (now, National Institute of Technology) Durgapur, India, in 1988 and 1994, respectively. He obtained his Ph.D. from Indian Institute of Technology Kanpur, India, in 2000. He received University Gold Medal, A. M. Das Memorial Medal, Institution of Engineers’ (I) Medal, INSA Teachers’ Award 2020, New Code of Education 2021 Award, Distinguished Alumnus Award 2021 from National Institute of Technology Durgapur, India, and others. He was included among the World’s Top 2% Scientists in the areas of Image Analysis and Artificial Intelligence in a survey carried out by Stanford University, USA, in 2020, 2021. He was declared Outstanding Researcher 2021 in www.research.com. He completed his post-doctoral studies in Japan, and then, in Germany under the Alexander von Humboldt (AvH) Fellowship Program. He received the Shastri Fellowship (Indo-Canadian Fellowship) to work on humanoid robots. He is working now as a Professor (HAG scale) of IIT Kharagpur, India. His research areas include Robotics, Soft Computing, Manufacturing Science, and others. He has made significant contributions in the field of computational intelligence. He has published 179 research papers in peer reviewed international journals and more than 100 papers in conferences and national journals. He has contributed 23 chapters in edited international books. A few of his fundamental contributions published in IEEE, ASME, Elsevier, and Springer journals are being highly cited by researchers in the field. His h-index values are found to be as follows: 40 (Google Scholar), 31 (Scopus), 27 (Web of Science). He has written the textbooks on “Soft Computing,” “Fundamentals of Robotics,” co-authored another textbook on “Analytical Engineering Mechanics,” edited a book on “Intelligent Autonomous Systems,” co-authored four reference books on “Modeling and Analysis of Six-legged Robots,” “Modeling and Simulations of Robotic Systems Using Soft Computing,” “Modeling and Analysis of Laser Metal Forming Processes by Finite Element and Soft Computing Methods,” and “Multi-body dynamic modeling of multi-legged robots.” His textbook on “Soft Computing” has been translated into Chinese language also. He has developed three online NPTEL courses, such as “Traditional and Non-Traditional Optimization Tools,” “Robotics,” and “Fuzzy Logic and Neural Networks.” He has guided 25 Ph.D.s, and 11 more Ph.D. students are working now under his guidance. He has filed two patents. He has completed a number of sponsored projects funded by the DST, DAE, DBT, MHRD of Govt. of India, and two consultancy projects of the industries. He is in editorial board of a few International Journals. He is an Associate Editor of one International Journal. He has been elected as a Fellow of Institution of Engineers (I), MASME, and SMIEEE.

Chapter 6

Internet-Based Learning and Teaching of a Subject by Self-prepared Notebook Arun K. Singh

6.1 Introduction In today’s world, all types of information are easily available everywhere. Thanks to revolution of Internet, computers and smartphones which are practically accessible to everyone. Books, research papers, dedicated videos, experts’ opinions, etc., are readily available on a specific subject [1–5]. Finding the answer to a question is nowadays quite easier on Internet. Yet, managing this plethora of information on a particular subject is a challenging task. In this article, we propose an easy and convenient approach to Internet-based learning and teaching (IbLT) of a topic/subject. Literature survey shows a number of techniques which have been proposed for Webbased learning and teaching of a subject [1–5]. Advantages and limitations of IbLT techniques have also been discussed extensively in literature [6–10]. For example, IbLT resources facilitate continuous and to-and-fro learning process [4, 11]. In other words, it is always possible to go through a video or book in both the directions, unless a doubt gets cleared. In contrast to traditional learning, wherein one has to mainly note down the study materials, Web-technology facilitates rapid search and saving of information [1, 3, 11–14]. The present article adds one more avenue to IbLT in form of self-prepared notebook. Nevertheless, content of the notebook will depend on the learner’s level of understanding of the subject. Hence, a notebook prepared by a learner may not be fully understood by other learner/s. Yet, the notebook facilitates an option to modify the content according to understanding of the learner.

A. K. Singh (B) Department of Mechanical Engineering, Visvesvaraya National Institute of Technology, Nagpur, South Ambazari Road, Nagpur 440010, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_6

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6.2 Methodology The proposed method of IbLT begins with identification of the topic, one wishes to learn or to teach in the class. It is followed by search of the concerned study materials from different sources of Internet. The search may include books, online lecture videos, simulations, animations, etc. One can copy–paste the relevant information on a word/PPT file as an easier collection of information at one place. Later, the study material could be typed in the notebook. At the same time, proper references must be included in the notebook simultaneously to avoid the plagiarism. After that, the notebook should be critically analyzed to correlate the ideas with the existing understanding of the learner. In addition to this, effort should also be made to infer some new conclusions to note down in the notebook. List of queries and doubts could also be compiled in the notebook for next cycle of search, save and study from Internet. Figure 6.1 presents a slide from the self-prepared notebook of solid mechanics. This subject is also known as strength of materials or mechanics of materials, etc. The notebook was prepared by the author on PPT slides for teaching undergraduate students of mechanical engineering students. It is seen that the slide highlights the basic concepts of solid mechanics [15, 16]. For instance, a very basic statement is mentioned in the slide that “Generally, in solid mechanics only four types of forces (normal (tension/compression), shear, bending and torsion) form the cause”. In the next sentence of the slide in Fig. 6.1, it is stated that “these forces cause maximum only two types of effect, namely normal and shear stresses”. This is also elucidated using flow diagram in Fig. 6.1. Stress element in Fig. 6.1 highlights that a normal stress is always shown with a single pair of arrow acting perpendicularly on

Fig. 6.1 PowerPoint presentation (PPT) slide on basic concepts of mechanics from self-prepared notebook of solid mechanics

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Fig. 6.2 PPT slide explaining basic definition of stress and stress tensor matrix

opposite faces of the stress element. Shear/tangential stress, in contrast, is represented with two pairs of arrows acting tangentially on the faces of stress element in clockwise and anticlockwise directions. These fundamental concepts are justified in subsequent chapters of solid mechanics, for example, bending moment and torsion. Nevertheless, for the sake of better understanding of solid mechanics, one needs the background of engineering mechanics which basically deals with analysis of forces and motion of rigid body. Hence, slides concerning the key concepts of Newton’s laws of motion, free-body diagram, etc., could also be included in the notebook [17]. Figure 6.2 illustrates a typical stress matrix which is generally characterized as a tensor quantity [15, 16]. At this stage, a question may also be raised what is tensor? Further, how does a stress/strain matrix defer from a vector/scalar quantity? It is also noted that though a stress matrix has 9 elements, it reduces effectively to 6 elements due to symmetry of shear stress [15, 16]. Figure 6.3 shows a slide that explains a typical strain matrix and its relationship with different displacements (u, v and w) [15, 16]. These displacements, in turn, yield 9 strain components, namely 3 normal strains and 3 shear strains in Fig. 6.3. Similar to stress matrix in Fig. 6.2, in the case of strain matrix too, number of strain components is 6 owing to symmetry of shear strains [15, 16]. Geometrical meaning of stress/strain is often explained by Mohr’s circle diagram in Fig. 6.4. This diagram can be conveniently drawn using online GUI tool [18]. Mohr’s circle is used for analyzing strain at a point of the solid, since stress and strain are analogous physical quantities [15, 16]. Mohr’s circle is also used for studying three-dimensional state of stress/strain [16]. Having learned the basic concepts of stress and strain quantities, it is critical to elucidate the relationship between them as well. This is done in light of constitutive relations of the material. Hook’s law linear elasticity is used for elastic solids [15, 16].

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Fig. 6.3 PPT slide showing definition of strain and strain tensor matrix

Fig. 6.4 A PPT slide depicts Mohr’s circle showing stress a point

Figure 6.5 presents the mathematical relationship between stress and strain quantities by 6 equations which are also known as the generalized Hook’s law of linear elasticity [15, 16]. It is to be noted that the constitutive relations for rubbers and elastomers are quite different from linear solids (Hookean materials). For instance, rubbers and elastomers undergo to finite deformation, thus invalidating the equations of linear elasticity. The next basic foundation of linear elasticity is three stress-equilibrium equations in form of partial differential equations in Fig. 6.6. These equations are derived after considering force equilibrium of the solid body in view of the law of momentum

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Fig. 6.5 PPT slide on stress–strain behavior of a Hookean solid

conservation [17, 18]. While these equations are valid for static equilibrium conditions, the concept could be applied for dynamic conditions after considering inertia of the solid as well. At this stage, an interesting question can also be raised in the notebook concerning the difference between static and dynamic equilibrium and their practical significance. The idea of compatibility (continuity) equations is equally important to have the relationship among 6 components of strains in Fig. 6.7. These equations ensure mathematically the continuity of the solid body having no defect or discontinuity [15, 16]. In order to understand the significance of compatibility equations in solid mechanics, one can cite the analogy of continuity equation in fluid dynamics. One of the objectives of self-prepared note is to understand the whole subject in a unified way. For example, Fig. 6.8 depicts a diagram showing the relationship between force, stress, displacement and strains [16]. A force causes stress, displacement and strains in a deformable body. These are ultimately correlated with equilibrium equations, the generalized Hook’s law and compatibility equations, resulting in 15 equations and 15 unknowns constituting the system of differential–algebraic equations [15, 16]. These are known as boundary value problems in solid mechanics. For unique solution of these equations, certain boundary conditions are required and that is governed by Cauchy stress equation [19]. A learner may also raise question about boundary conditions. There should be discussion in the notebook about the boundary conditions and their role in solving differential equations [15, 16]. More significantly, it must be stated that sound knowledge of mathematical techniques for solving problems of solid mechanics is also prerequisite. As a result, different mathematical techniques relevant to solid

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Fig. 6.6 A PPT slide concerning stress-equilibrium equations from the self-prepared note on solid mechanics

Fig. 6.7 A PPT slide showing compatibility (continuity) equations concerning of an elastic solid

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Fig. 6.8 A PPT slide presenting governing equations of Hookean solids

mechanics, as the role of engineering mechanics in solid mechanics was discussed earlier. Solution of the system of equations could be obtained by different methods such as analytical and numerical methods. Airy stress function is an analytical approach which is often used to solve the system of 15 equations with 15 unknowns in elasticity [15, 16, 18]. The idea of plane stress/strain state of solids was proposed to simplify three-dimensional (3D) problems to two-dimensional (2D) problems. As a result, number of equations and unknowns reduce from 15 to 8 in 2D elasticity and further reduce to 3 unknowns and 3 equations in one-dimensional (1D) elasticity. Practical examples of plane stress are thin bodies, for instance, thin-walled pressurized cylinder. However, if thickness of the solid body is considerable for instance, thick-walled pressurized cylinder and this becomes an example of plane-strain [16].

6.2.1 Numerical Approaches for Solid Mechanics Due to advances in computer technology, numerical methods such as finite difference method (FDM), finite element method (FEM) and boundary element method (BEM) have become quite successful and also popular for solving variety of solid mechanics problems [16]. These problems are solved with more complex and realistic boundary conditions. Most of practical solid mechanics problems are nowadays solved numerically with computers. Hence, some slides should be added in the notebook to highlight the importance of numerical methods in solid mechanics as well. Commercial softwares such as Ansys and Abaqus are fundamentally based on FEM solution of the system of differential–algebraic equations (15 equations and 15 unknowns) in solid mechanics under different boundary conditions [15, 16]. As an illustrative example of the application of FEM in solid mechanics, Fig. 6.8 presents a result concerning stress at the transverse as well as longitudinal tips of the

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Fig. 6.9 Finite element solution of stress around a circular hole located at the center of an elastic plate

circular hole in an elastic plate under uniaxial loading. The numerical simulation is done in Ansys software (student version). It is seen that maximum normal stress at the transverse tips is three times (3.1 MPa) of the nominal stress (1.0 MPa) which is applied externally at the ends of the plane. At the same time, normal stress at the longitudinal tips of the circular hole is −1.02 MPa. Analytical techniques such as Airy stress function and complex variable approach also predict the similar magnitude of normal stress at the transverse and longitudinal tips of the circular hole [15, 16]. Thus, the results predicted by finite element method are quite closed to the analytical results [20].

6.3 Discussion of IbLT The proposed IbLT enables that one can learn and teach a subject in a unified way. As the present methodology emphasizes to develop own strategy to understand the different topics of a subject. For instance, it is proposed in Fig. 6.1 that, in general, solid mechanics deals with four types of forces which may act on a deformable body. But it is ultimately two types of stresses that develop at a point in the solid. This basic idea of solid mechanics is justified by giving the examples of normal, shear, bending and torsional forces which ultimately lead to only normal and shear stresses. Innovative questions to be included in the notebook for better understanding of the subject. For example, a basic question in the notebook of solid mechanics could be raised the difference between linear and nonlinear solid mechanics. In addition, it should also be mentioned in the notebook that linear mechanics is not sufficient to address the mechanics of rubber elasticity. Also, answer to these queries could be explained with practical examples and simulation results in the notebook. More significantly, importance of boundary value problems involving theory of elasticity in

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fracture mechanics and contact mechanics could also be explained with the practical examples. Personal experiences have shown the proposed methodology to be quite fruitful. The author has prepared notebook of solid mechanics for teaching undergraduate students as per level of own understanding of the subject. But the notebook could be constantly modified by an individual learner according to his/her understanding of the subject. The idea of self-prepared notebook has also been extended to subjects like machine design and tribology. Notwithstanding the proposed methodology, we believe that learning and teaching require interest, constant effort, patience and curiosity for the understanding of a topic. Further, it takes considerable time and effort in order to have in-depth understanding of the subject. But Internet has made the learning process quite easier.

6.4 Conclusions The proposed methodology of preparing a notebook is based on search, save and study of information from different sources of Internet. It is also important to cite the source of information in the notebook appropriately. More significantly, critical analysis of content of the notebook must be done to infer some new conclusions. So that these conclusions could enable the learner to understand the subject in a unified manner. New queries and doubts should also be noted down in the notebook. Yet, the queries have to be addressed further by searching the answer from Internet. Finally, this article does not discuss the evaluation and effectiveness of the proposed methodology; nonetheless, it will be worth doing in future.

References 1. French, D. (1999). Internet based learning: An introduction and framework for higher education and business. Stylus Publishing, LLC. 2. Aggarwal, A. (Ed.). (2003). Web-based education: Learning from experience. IGI Global. 3. Ryan, S., Scott, B., Freeman, H., & Patel, D. (2013). The virtual university: The internet and resource-based learning. Routledge. 4. https://www.bbvaopenmind.com/en/articles/the-internet-and-education/ 5. Pritchard, A. (2007). Effective teaching with internet technologies: Pedagogy and practice. SAGE. 6. https://www.educations.com/articles-and-advice/5-reasons-online-learning-is-future-of-edu cation-17146 7. Gernsbacher, M. A. (2015). Why internet-based education? Frontiers in Psychology, 5, 1530. 8. Agarwal, M. K. (2010). Internet-based language learning and teaching. Innovative Infotechnologies for Science, Business, and Education, 1(8), 3–7. 9. Rekkedal, T., Qvist-Eriksen, S., Keegan, D., Súilleabháin, G. Ó., Coughlan, R., & Fritsch, H. (2003). Internet based e-learning, pedagogy and support systems. NKI Distance Education. 10. Thorgersen, K., & Zandén, O. (2014). The Internet as teacher. Journal of Music, Technology and Education, 7(2), 233–244.

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11. Anido, L., Llamas, M., & Fernández, M. J. (2001). Internet-based learning by doing. IEEE Transactions on Education, 44(2), 18 12. Wegner, S. B., Holloway, K. C., & Garton, E. M. (1999). The effects of Internet-based instruction on student learning. Journal of Asynchronous Learning Networks, 3(2), 98–106. 13. https://study.com/blog/strategies-for-taking-effective-notes-while-studying-online.html 14. https://web.archive.org/web/20160330072445/http://www.isoc.org/inet96/proceedings/c1/ c1_4.htm 15. Srinath, L. S. (2003). Advanced mechanics of solids. Tata McGraw-Hill. 16. Timoshenko, S. (1970). Theory of elastic stability (2nd ed.). Tata McGraw-Hill Education. 17. http://ruina.tam.cornell.edu/Book/RuinaPratap-July-12-2019.pdf 18. https://mechanicalc.com/calculators/mohrs-circle/ 19. Saravanan, U. (2013). Advanced solid mechanics. Department of Civil Engineering, Indian Institute of Technology Madras. 20. Chandrupatla, T., & Belegundu, A. (2021). Introduction to finite elements in engineering. Cambridge University Press.

Dr. Arun Kumar Singh is presently an associate professor in Mechanical Engineering Department at VNIT Nagpur. He did B.Engg. in Production and Industrial Engineering from M.L.N.R.E.C. (presently MLNNIT, Allahabad in 1999, M.Tech in Material Science and Technology from IT-BHU (presently, IITBHU), Varanasi in 2001 and Ph.D. in Mechanical Engineering from IIT Bombay in 2009. He has done post-doctoral researches in the Department of Chemical Engineering at Lehigh University (2009–10) and also in the Department of Earth Sciences IIT Bombay (2010–11) for about three years, before joining to VNIT Nagpur as an assistant professor in June, 2012. Dr. Singh mainly works in the areas of friction and fracture of soft and hard materials using theoretical and experimental approaches. His interests are also in modeling and simulations of interdisciplinary problems involving rock mechanics and earthquake processes. He has published over 20 SCI papers in reputed Journals and four book chapters, also contributed over 30 conference papers and abstracts. Dr. Singh has, so far, guided 5 Ph.D., 28 M.Tech. and 20 B.Tech. students for their degree in last 10 years.

Chapter 7

Computational Demonstration for Classroom Teaching of Classical Mechanics Abhijit Sarkar

7.1 Introduction In recent years, the patronage of mechanical engineering as a discipline of choice among the student population has sharply declined. There is ample data supporting the above statement, e.g. the rank-branch data in the Joint Entrance Examination (JEE) [1], the closing down of ME in various engineering colleges, etc. As flagbearers of this discipline, the teaching faculty of mechanical engineering can no longer turn a blind eye and deaf ear towards this very-real phenomenon. We need to reinvent our delivery of mechanical engineering to the present generation of students and thus save the vital DNAs of our breed. Laxity on this task would lead to the slow but sure extinction of mechanical engineering as a branch of study. The flavour of the season among the students seems to be data science, artificial intelligence, machine learning, etc. There are various reasons for this preference. Undoubtedly, the availability of open-source software’s (such as Python) has played an important role in the rapid development and popularity of this field. Diverse communities of students, freelancers and professional experts have contributed to different aspects and as a result, numerous modules and packages have become freely available and widely popular. The students know it better than the faculty members that having Python coding-skills make them more employable. The field of mechanical engineering witnessed a similar surge of interest in computational mechanics about half a century ago. Not fortuitously, the timing coincided with the easy and widespread availability of computational hardware. Rapid strides were made particularly in the fields of finite element method (FEM) and computational fluid dynamics (CFD). FEM and CFD simulations were widely accepted in industries too. The CAE-based approach led to rapid turn-around times for design A. Sarkar (B) Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600036, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_7

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and development. The time and cost of multiple prototyping were cut down. The academia too reciprocated this change. Most graduate level universities and institutions incorporated courses in FEM, CFD, boundary element method, etc., in their curricula. It is understandable that with a history of more than 50 years, the law of diminishing returns has set in for subjects such as FEM and CFD. It is no longer treated as a job-clincher in the placement season. Further, the emphasis seems to have changed to using the GUI-driven commercial software’s rather than learning the theoretical foundation of these methods. Getting under the hood and actual coding implementation are rarely emphasized in most university curricula under the pretext that “it is not required for industrial application”. This practice can in fact be detrimental towards concept building. This lacklustre approach has led to very few popular opensource packages implementing different aspects of computational mechanics. The open-source revolution is here to stay and mechanical engineers should rise up to this challenge. It is regrettable that despite India being the information technology (IT) capital of the globe very few technological software packages have been developed indigenously. This situation can be corrected by incorporating a computation-based approach in teaching different mechanical engineering subjects. Implementing a computational approach for teaching different mechanics-related courses (not just FEM and CFD) will naturally reinforce the core concepts in the minds of the students. In contrast to computational programming-based exercises, the current practice of calculator-based pen and paper problem-solving is laborious and error-prone. Despite the initially steep learning curve, the students will soon realize the utility of computation-based problem-solving. Thus, incorporating computation-based teaching–learning pedagogy in the mechanical engineering discipline is the need of the hour. It is a win– win situation wherein the students will be enthused to learn the computational tools (which surely makes them more employable) and also gain a good grasp on the core concepts of mechanics. This article demonstrates the implementation of computational pedagogy for teaching various concepts related to vibration. A simple but classical and representative problem is chosen for the demonstration. Python is chosen as the computational workhorse for this exercise [2]. The free-to-use philosophy of such open-source programmes has democratized access to quality educational resources as well as changed the rules of the business. The entire work is performed in the JupyterLab environment [3]. The interested reader may download the source file (.ipynb format) from the author’s webpage [4].

7.2 Problem Definition A two-degree of freedom vibrating system as shown in Fig. 7.1 is analysed. This example is motivated from the classical textbook by Den Hartog [5]. Using this example and a hands-on computation approach, different aspects of vibration analysis

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Fig. 7.1 Schematic illustration of a two-degree of freedom vibration system

will be elucidated. In particular, the usage of the modal coordinates in computation and understanding of the vibration concepts will be emphasized. The governing equation of motion for the system shown in Fig. 7.1 is given by =x¨

=x

=F

             x¨1 x1 F1 m1 0 k1 + k −k + = x¨2 x2 F2 0 m2 −k k2 + k       

=M

(7.1)

=K

In Eq. (7.1), M and K represent the mass and stiffness matrices, respectively. The displacement, acceleration and the force vectors are represented by x, x¨ and F, respectively. The following parameters are chosen for demonstration: m 1 = m 2 = 1, k1 = k2 = 1, k = 50 Note, this choice of numerical parameters enforces symmetry in the system. This will be useful in interpreting the mode shapes obtained from subsequent computation. The associated code for defining these parameters is shown as Listing 7.1.

Listing 7.1 Defining the numerical values of the parameters. m1 = 1.0; m2 = 1.0; k1 = 1.0; k2 = 1.0; k = 50.0;

For the present computation, we need the following modules in Python: (1) Numpy (2) Scipy and (3) Matplotlib. Numpy is the package which defines the data structure associated with matrix computation. Matplotlib is used to plot graphs. Scipy is the module containing different in-built routines for scientific computation. In the present work, the linear algebra and integrate module will be used. Accordingly, these specific modules are imported as shown in Listing 7.2. For more information on these packages, the reader is referred to [6].

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Listing 7.2 Importing the relevant modules and packages. import numpy as np import matplotlib.pyplot as plt from scipy import linalg as la from scipy import integrate

Next, we define the mass and stiffness matrices as shown in Listing 7.3.

Listing 7.3 Defining the mass and stiffness matrices. M = np.array([[m1, 0], [0, m2]]) K = np.array([[k1+k, -k], [-k, k2+k]])

7.3 Free Vibration Analysis The natural frequencies and mode shapes of the system are computed in the following manner. We look for a harmonic solution of Eq. (7.1) in absence of external forcing viz. F 1 = F 2 = 0. Due to the above ansatz, we have xn = X n ei ωt , (n = 1, 2). Using these simplifications in Eq. (7.1), we have the following generalized eigenvalue problem K x = ω2 M x. Thus, the natural frequencies are calculated as a solution of the generalized eigenvalues. The corresponding eigenvectors give the mode shapes. The generalized eigenvalue problem is solved using the commands given in Listing 7.4. The output of this step is two matrices (denoted in the listing as eval and evec, respectively). The first of these matrices is a diagonal matrix with the diagonal entries as 1 and 101, respectively. These values denote the square of the natural frequencies, respectively. The second of these matrices carries the eigenvectors in successive columns of the matrix.

Listing 7.4 Solution of the generalized eigenvalue problem K x = ω2 M x. eval, evec = la.eig(K, M)

The eigenvectors or mode shapes are thus given by the matrix evec. Technically, this matrix is called the modal matrix φ. The numerical values of this matrix are given as follows: 

−0.70710678 0.70710678 −0.70710678 −0.70710678



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Note, the first mode represents the condition wherein both the masses have identical vibration and thus the connecting spring remains undeformed. The second mode represents the condition wherein the masses have equal and opposite vibration. In this case, the motion is equivalent to the case wherein the centre of the connecting spring is grounded. For both the above types of motion, it is intuitively clear that the system decouples into two single-degree of freedom systems. The inherent symmetry of the system (associated with the choice of m1 = m2 and k 1 = k 2 ) leads to the above simple visualization of the mode shape. It may be verified that the mode shapes are scalable. In other words, if {x} is a mode shape vector, then c {x} is also a mode shape vector ∀c ∈ R. In the subsequent subsections, the vibration due to different initial disturbances will be discussed. Three different types of initial conditions will be chosen, as follows: (a) initial displacement conforming to first mode, (b) initial displacement conforming to second mode and (c) arbitrary initial displacement. Without loss of generality, the initial velocity is assumed to be zero for all the cases listed above. The computation is performed in two different ways, namely (i) numerical solution of the ordinary differential equation given by Eq. (7.1) and (ii) diagonalizing the stiffness and mass matrices using the mode shapes. The results for these two different methodologies are presented in the following two subsections.

7.3.1 Numerical Solution of Ordinary Differential Equation (ODE) For the numerical solution of ODE using the Scipy module, one needs to write a function which gives the derivative of the state vector. Note, the state vector in physical coordinates is given by the vector {x1 , x2 , x˙1 , x˙2 }T , and thus, the derivative of the state vector is given by {y1 , y2 , y3 , y4 }T , where y1 = x˙1 , y2 = x˙2 , y1 = x¨1 , y2 = x¨2 . Note, x¨1 and x¨2 may be expressed in terms of state variables by using the governing differential Eq. (7.1). This part of the code is shown in Listing 7.5.

Listing 7.5 Function required for numerical solution of the ordinary differential equation. def f(states, t): x1, x2, x1dot, x2dot = states y1 = x1dot y3 = -((k+k1)*x1/m1)+k*x2/m1 y2 = x2dot y4 = -((k+k2)*x2/m2)+k*x1/m1 return [y1, y2, y3, y4]

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Fig. 7.2 Numerical solution of x 1 and x 2 with two masses disturbed identically

Next, an initial condition conforming to the first mode is imposed. Note, due to symmetry, this implies identical disturbance to both the masses. The numerical solution is extracted at 200 equi-spaced points in the time interval [0, 10). Finally, the solutions for x 1 and x 2 are plotted in Fig. 7.2. This part of the code is shown in Listing 7.6.

Listing 7.6 Numerical solution of the ODE with initial disturbance conforming to the first mode and subsequently plotting the resulting solution. tvec = np.linspace(0, 10, 200) # the solution will be obtained at these discrete time points ic1 = np.array([evec[0, 0], evec[1, 0], 0, 0]) # initial condition in the form of first mode sol = integrate.odeint(f, ic1, tvec) x1 = sol[:, 0] x2 = sol[:, 1] # plotting the solution plt.plot(tvec, x1, label="x1") plt.plot(tvec, x2, ’.’, label="x2") plt.legend() plt.xlabel(’Time’) plt.grid()

It is clear that identical initial conditions result in identical responses for all time. This is because of the symmetry of the system. Also, the response is harmonic with the frequency precisely equal to the first natural frequency. In general, disturbing the

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Fig. 7.3 Numerical solution for x 1 and x 2 with two masses disturbed in an equal and opposite manner

system at its first mode ensures that the response is always manifested at the first mode. Further, the response is at the frequency equal to the natural frequency of the first mode. This exercise is repeated for initial conditions corresponding to the second mode. For the second mode, the disturbance in the two masses is equal and opposite. The corresponding code and the results are shown in Listing 7.7 and Fig. 7.3, respectively. Again, it is found that if the initial conditions are in the form of the second mode, then the response stays in the form of the second mode (equal and opposite in this case). Further, the response is harmonic with the frequency equal to the second natural frequency.

Listing 7.7 Numerical solution of the ODE with initial disturbance conforming to the second mode and subsequently plotting the resulting solution. ic2 = np.array([evec[0, 1], evec[1, 1], 0, 0]) # initial condition in the form of the second mode sol = integrate.odeint(f, ic2, tvec) x1 = sol[:, 0] x2 = sol[:, 1] fig, ax = plt.subplots() ax.plot(tvec, x1, label="x1") ax.plot(tvec, x2, ’r’, label="x2") ax.legend() ax.grid() plt.xlabel(’Time’)

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Fig. 7.4 Numerical solution for x 1 and x 2 with initial disturbance x 1 (0) = 1 and x 2 (0) = 2

Next, this exercise is repeated by imparting an arbitrary initial disturbance to the masses. Specifically, we choose the displacement of m1 as one unit and m2 as two units, respectively. The corresponding code and the results are shown in Listing 7.8 and Fig. 7.4, respectively.

Listing 7.8 Numerical solution of the ODE with arbitrary initial disturbance and subsequently plotting the resulting solution. tvec2 = np.linspace(0, 15, 256) # the solution is found in the interval of [0, 15) over 256 points ic3 = np.array([1, 2, 0, 0]) # initial condition chosen sol = integrate.odeint(f, ic3, tvec2) x1 = sol[:, 0] x2 = sol[:, 1] # Generate the plot fig, ax = plt.subplots() ax.plot(tvec2, x1, label="x1") ax.plot(tvec2, x2, ’r’, label="x2") ax.legend() ax.grid() plt.xlabel(’Time’)

The free response due to an arbitrary initial condition manifests multiple frequencies. Through a detailed FFT calculation, it can be checked that there are two dominant frequencies conforming to the two natural frequencies. The FFT calculation procedure is not shown here for brevity.

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7.3.2 Modal Approach In the modal approach, the governing equation of motion given by Eq. (7.1) is transformed into modal coordinates by using the transformation {x} = [φ]{y}. Using this transformation and pre-multiplying Eq. (7.1) by [φ]T , we get [φ]T [M][φ]{ y¨ } + [φ]T [K ][φ]{y} = {0} ⇒ [M]{ y¨ } + [K]{y} = {0},

(7.2)

where M and K are the diagonal modal mass and modal stiffness matrices, respectively. The diagonal nature of these matrices is on account of the characteristics of generalized eigenvalue problems [7]. Since the modal mass and stiffness matrices are diagonal, the equations of motion in y1 and y2 are decoupled. We can easily solve for y1 and y2 as separate second order ODEs. Accordingly, we define two separate functions implementing the state-space form of these two independent second order ODEs. The corresponding code is shown in Listing 7.9. For obtaining the solution in the modal coordinates, the initial conditions in modal coordinates need to be determined. If {x i } and {yi } are the initial conditions in the physical and modal coordinates, then they are related by {yi } = [φ]−1 {xi }. As the mass matrix is chosen as identity, in the present case [φ]−1 = [φ]T . An arbitrary initial condition {x i } = {1, 2, 0, 0}T is used for the demonstration. Using these simplifications, the ODE for the two modes are separately solved. The corresponding code is listed in Listing 7.10. The results are shown in Fig. 7.5.

Fig. 7.5 Numerical solution for the modal coordinates y1 and y2 for the initial condition x 1 (0) = 1 and x 2 (0) = 2

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Fig. 7.6 Comparison of solution obtained using physical and modal coordinates for the initial condition x 1 (0) = 1 and x 2 (0) = 2

Despite the arbitrary initial conditions, the modal displacements are harmonic at frequencies corresponding to the natural frequencies. This observation is generic and applicable to all linear elastodynamic systems. In order to reconstruct the physical displacements, we need to perform the computation {x(t)} = [φ]{y(t)} for all the discrete time instants. In this manner, the solutions obtained using the physical and modal coordinates can be compared. This portion of the code is shown in Listing 7.11. An overlaid plot of the comparison of results obtained using the two approaches is shown in Fig. 7.6. As observed from these results, the two approaches give identical solutions.

Listing 7.9 Two separate functions for ODE solution in the modal coordinates. # Construct the Modal mass and Modal stiffness matrices phi = evec # modal matrix as calculated from the eigenvalue solution Modal_M = np.dot(phi.T, np.dot(M, phi)) Modal_K = np.dot(phi.T, np.dot(K, phi)) # Verify that these matrices are diagonal # Define the modal masses and stiffnesses corresponding to the two # modes mu1 = Modal_M[0, 0] mu2 = Modal_M[1, 1]

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kappa1 = Modal_K[0, 0] kappa2 = Modal_K[1, 1] def firstmode(states, t): x, xdot = states y = xdot ydot = -kappa1*x/mu1 return [y, ydot] def secondmode(states, t): x, xdot = states y = xdot ydot = -kappa2*x/mu2 return [y, ydot]

Listing 7.10 ODE solution for the two modal coordinates. ic_modal = np.dot(phi.T, ic3[0:2]) ic_firstmode = np.array([ic_modal[0], 0]) ic_secondmode = np.array([ic_modal[1], 0]) firstmode_sol = integrate.odeint(firstmode, ic_firstmode, tvec2) secondmode_sol = integrate.odeint(secondmode, ic_secondmode, tvec2) y1 = firstmode_sol[:, 0] y2 = secondmode_sol[:, 0] fig, ax = plt.subplots() ax.plot(tvec2, y1, label=’1st mode’) ax.plot(tvec2, y2, ’r’, label=’2nd mode’) ax.grid() ax.legend() plt.xlabel(’Time’) plt.title(’Modal displacements’)

Listing 7.11 Reconstructing the physical solution from the modal solution. x1modal = np.zeros_like(tvec2) x2modal = np.zeros_like(tvec2) for count in range(len(tvec2)): y = np.array([y1[count], y2[count]] x = np.dot(phi, y) x1modal[count] = x[0] x2modal[count] = x[1] fig, ax = plt.subplots(1, 2, figsize=(12, 6)) ax[0].plot(tvec2, x1modal, label=’Modal’) ax[0].plot(tvec2, x1, ’r.’, label=’Physical’)

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ax[0].grid() ax[0].legend() ax[0].set_xlabel(’Time’) ax[0].set_title(’Displacement of m1’) ax[1].plot(tvec2, x2modal, label=’Modal’) ax[1].plot(tvec2, x2, ’r.’, label=’Physical’) ax[1].grid() ax[1].legend() ax[1].set_xlabel(’Time’) ax[1].set_title(’Displacement of m2’)

7.4 Forced Harmonic Vibration In this section, the response of the system under harmonic excitation of the form {F(t)} = {F} eiωt is computed. The response is computed in the frequency domain and the end result is presented in the form of frequency response function (FRF). In this case too, the solution is performed both in the physical and modal coordinates.

7.4.1 Solution in Physical Coordinates Substitute {x} = {X} eiωt in Eq. (7.1) and then calculate response amplitude {X} as follows:

−1 {X } = −ω2 M + K {F} Thus, X 1 (ω) and X 2 (ω) are determined as shown in Listing 7.12. The forcing amplitudes chosen for this demonstration is F 1 = 1 and F 2 = 2. The FRF results are shown in Fig. 7.7. It is evident from these results that the responses X 1 and X 2 are large when the excitation frequency is near one of the natural frequencies of the system. This phenomenon is known as resonance and is well-documented in the classical literature [5]. Note, there is a sharp drop in response for X 1 at ω ~ 12 and X 2 at ω ~ 9. These frequencies are called anti-resonance. The anti-resonance phenomenon is usually not elaborated in classical textbooks. In the subsequent discussion, this phenomenon will be explained. Towards this end, it is better to look at the solution in modal coordinates.

Listing 7.12 FRF computation for the physical displacements X 1 and X 2 . w = np.arange(0.1, 15, np.pi/50) # discrete frequency points at which the solution is computed f = np.array([1, 2])

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Fig. 7.7 FRFs for the physical displacements computed for F 1 = 1 and F 2 = 2

dsp1 = np.zeros_like(w) dsp2 = np.zeros_like(w) for count in range(len(w)): wval = w[count] wvalsqr = wval*wval D = -(wvalsqr)*M+K Dinv = la.inv(D) disp = np.dot(Dinv, f) dsp1[count] = disp[0] dsp2[count] = disp[1] fig, ax = plt.subplots(1, 2) ax[0].semilogy(w, np.absolute(dsp1)) ax[0].set_xlabel(’Frequency’) ax[0].set_title(’x1’) ax[1].semilogy(w, np.absolute(dsp2)) ax[1].set_xlabel(’Frequency’) ax[1].set_title(’x2’)

7.4.2 Solution in Modal Coordinates Using the same arguments as used in the derivation of Eq. (7.2), the forced vibration equation in modal coordinates is found as follows: [M]{ y¨ } + [K]{y} = [φ]T { f } = {g}

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      k1 0 Y1 G1 2 μ1 0 −ω + = Y2 G2 0 μ2 0 k2

(7.3)

In the above equation, {g} represents the modal force vector; μ1 is the modal mass for the first mode; μ2 is the modal mass for the second mode; κ1 is the modal stiffness for the first mode; κ2 is the modal stiffness for the second mode. Due to the decoupled nature of the above equations, Y 1 and Y 2 can be found as Yi =

Gi 2 −ω μi

+ ki

, i = 1, 2.

After computing the modal displacements, the physical displacements are reconstructed using the transformation {x} = [φ]{y}. These calculations are implemented through the code listed in Listing 7.13. The results of the modal displacement amplitudes as a function of frequency is presented in Fig. 7.8. In contrast to the physical displacements, the modal displacements show a peak only at a single frequency. Further, this peak frequency corresponds to the natural frequency of the associated mode. In Fig. 7.9, the solutions for X 1 and X 2 obtained from the modal displacements are overlaid with the solutions presented in Fig. 7.7. These solutions are referred to as “two mode solution” and “physical solution” in the legends of Fig. 7.9. It is evident that the two approaches give identical results.

Fig. 7.8 FRFs for the modal displacements computed for F 1 = 1 and F 2 = 2

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Fig. 7.9 FRFs for X 1 and X 2 computed for F 1 = 1 and F 2 = 2 using (1) physical coordinates (2) 2 mode solution

Listing 7.13 FRF computation for the modal displacements Y 1 and Y 2 . The physical displacements are then recalculated from the modal displacements. g = np.dot(phi.T,f) y1forced = np.zeros_like(w) y2forced = np.zeros_like(w) x1forced_modal = np.zeros_like(w) x2forced_modal = np.zeros_like(w) for count in range(len(w)): wval = w[count] y1forced[count] = g[0]/((-wval**2)*mu1+kappa1) y2forced[count] = g[1]/((-wval**2)*mu2+kappa2) modal_vec = np.array([y1forced[count], y2forced[count]]) phys_disp = np.dot(phi, modal_vec) x1forced_modal[count] = phys_disp[0] x2forced_modal[count] = phys_disp[1] plt.semilogy(w, np.absolute(y1forced), label=’Mode 1’) plt.semilogy(w, np.absolute(y2forced), ’r’, label=’Mode 2’) plt.legend() plt.grid() plt.xlabel(’Frequency’) plt.title(’Modal Displacements’) fig, ax = plt.subplots(1, 2)

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ax[0].semilogy(w, np.absolute(x1forced_modal), label=’2 Mode tion’) ax[0].semilogy(w, np.absolute(dsp1), ’r.’, label=’Physical tion’) ax[0].grid() ax[0].set_xlabel(’Frequency’) ax[0].legend() ax[0].set_title(’x1’) ax[1].semilogy(w, np.absolute(x2forced_modal), label=’2 Mode tion’) ax[1].semilogy(w, np.absolute(dsp2), ’r.’, label=’Physical tion’) ax[1].grid() ax[1].set_xlabel(’Frequency’) ax[1].legend() ax[1].set_title(’x2’)

Solusolu-

Solusolu-

Next, the physical displacements are found from the modal displacements using only one mode at a time. Thus, the physical displacement vector is calculated as {X } = [φi ]yi i = 1, 2. In the above, φ1 and φ2 are the first and second modal vectors, respectively. The code associated with the above computation is listed in Listing 7.14.

Listing 7.14 FRF computation of the physical displacements from one of the modal displacements. x1forced_mode1 = x1forced_mode2 = x2forced_mode1 = x2forced_mode2 = phi1 = phi[:, 0] phi2 = phi[:, 1]

np.zeros_like(w) np.zeros_like(w) np.zeros_like(w) np.zeros_like(w)

for count in range(len(w)): disp_mode1 = phi1*y1forced[count] disp_mode2 = phi2*y2forced[count] x1forced_mode1[count] = disp_mode1[0] x2forced_mode1[count] = disp_mode1[1] x1forced_mode2[count] = disp_mode2[0] x2forced_mode2[count] = disp_mode2[1]

In Fig. 7.10, the contribution of the individual modes in the response for X 2 is shown. The code used to generate these plots is shown in Listing 7.15. From the results shown in Fig. 7.10, it is noted that due to mode 1, X 2 < 0 for ω > ω1 (the first natural frequency of the system). On the other hand, due to mode 2, X 2 > 0 for ω < ω2 (the second natural frequency of the system). Thus, in the interval ω1 < ω < ω2 , there exists a frequency wherein the positive contribution from mode 2 cancels out the negative contribution due to mode 1, thus producing a net zero displacement. This

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explains the occurrence of the anti-resonance for X 2 in the frequency range between the two natural frequencies. In a similar fashion, the contribution of the two modes in the response X 1 is presented in Fig. 7.11. The code used for generating the plot is listed in Listing 7.16. From this result, it is evident that in the frequency interval between the first and second natural frequencies there is no chance of mutual cancellation of the contribution due to the two modes. However, for ω > ω2 the contribution due to the first mode is negative whereas that due to the second mode is positive. Thus, for ω ~ 12.3, these two contributions nullify each other leading to an anti-resonance. This observation is further. validated by the plot shown in Fig. 7.12. In this figure, the contribution of the two modes in the response X 1 is plotted for the frequency range 11.5 < ω < 15. Further, the sum of the individual modal contributions is overlaid in this figure. It is clear that at ω ~ 12.3 the two modal contributions are equal and opposite. Hence, at this frequency X 1 ~ 0.

Listing 7.15 Plotting the contributions of the individual modal displacements in the response X 2 . # a zoomed in plot near the resonance region of each mode # the plot accounts for the separate contributions # of Mode 1 and Mode 2 in the response X2 fig, ax = plt.subplots(1, 2) ax[0].plot(w[5:25], x2forced_mode1[5:25], ’r’, label=’Mode 1’) ax[1].plot(w[145:170], x2forced_mode2[145:170], label=’Mode 2’) ax[0].set_xlabel(’Frequency’)

Fig. 7.10 FRFs for X 2 computed separately using the individual modal solutions. The plot is presented near the resonance region of each mode

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Fig. 7.11 FRFs for X 1 computed separately using the individual modal contributions. The plot is presented near the resonance region of each mode

Fig. 7.12 FRFs for X 1 computed separately using the individual modal contributions. The plot is presented for frequency range above the second natural frequency. The sum of the individual responses is also overlaid in the figure clearly indicating an anti-resonance at ω ~ 12.3

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ax[0].grid() ax[0].set_title(’x2 due to Mode 1’) ax[1].set_xlabel(’Frequency’) ax[1].grid() ax[1].set_title(’x2 due to Mode 2’)

Listing 7.16 Plotting the contributions of the individual modal displacements in the response X 1 . # a zoomed in plot near the resonance region of each mode # the plot accounts for the separate contributions # of Mode 1 and Mode 2 in the response X1 fig, ax = plt.subplots(1, 2) ax[0].plot(w[5:25], x1forced_mode1[5:25], ’r’, label=’Mode 1’) ax[1].plot(w[145:170], x1forced_mode2[145:170], label=’Mode 2’) ax[0].set_xlabel(’Frequency’) ax[0].grid() ax[0].set_title(’x1 due to Mode 1’) ax[1].set_xlabel(’Frequency’) ax[1].grid() ax[1].set_title(’x1 due to Mode 2’)

7.5 Conclusion In this article, an example of incorporating computation in teaching a classical mechanics problem is demonstrated. Specifically, a two-degree of freedom vibrating system as shown in Fig. 7.1 is chosen for the demonstration. Although this is a classical problem in vibration theory, it aptly demonstrates the physical insights associated with various concepts in vibration such as multiple natural frequencies and mode shapes, computing the natural frequencies and mode shapes through a generalized eigenvalue problem, transformation between physical and modal coordinates, resonances, anti-resonances, etc. The readers will agree that implementation of the computational approach for this seemingly innocuous problem can be very insightful. For example, the explanation of the anti-resonances will be difficult in the conventional pen-paper-calculator approach. Moreover, the pen-paper-calculator approach can be laborious as well as prone to manual errors. The computational approach enables the students to quickly try out various what if scenarios easily and thus facilitates self-learning rather than spoon-feeding. Thus, incorporating computational demonstration will aid theoretical concept building and also foster an application-oriented learning. As a spin-off, the

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students will be able to hone their computational skills, learn new computational tools and thus enhance their employability. In the present work, the computation is implemented using the Jupyter Notebook [3]. Jupyter Notebook is particularly attractive for maintaining an elaborate documentation of not only the code but also the associated theory. The presence of the documentation (including mathematical equations, schematic illustration, etc.), executable Python codes and the result figures all in one place enhances the readability and usefulness of the document. This practice is very useful in ensuring reproducibility of the results by the readers. This form of presentation is trendy in the scientific community (refer [8] for an advanced example). The present demonstration is limited to numerical computation. Similarly, demonstrations using symbolic computation are also effective. Symbolic computation in Python is available through the sympy package. Unlike numerical computation, symbolic computation does not have numerical errors. The author has incorporated similar demonstrations in numerical and symbolic computation in various courses. Although the learning curve has been steep both for the instructor and the students, by and large this practice has been well-received by the student community. In the long term, incorporating computational demonstrations in classroom teaching using open-source platforms (such as JupyterLab) will reinvigorate the subject matter. Additionally, it will enthuse students to develop additional modules and packages which can further automate the analysis and make the process userfriendly for the learners. These steps will go a long way in reviving the interest in the field of classical mechanics.

References 1. JEE opening and closing rank data posted at IIT Roorkee website. https://cutoffs.iitr.ac.in/. Retrieved on June 28, 2022. 2. Python website. https://www.python.org. Retrieved on June 28, 2022. 3. Jupyter website. https://jupyter.org/. Retrieved on June 28, 2022. 4. Author’s website containing the source file (.ipynb format) related to the present computational demonstration. https://sites.google.com/site/abhijitmeiitm/home/teaching. Retrieved on June 28, 2022. 5. Den Hartog JP (1985) Mechanical vibrations. Courier Corporation. 6. Johansson R (2018) Numerical python. Apress. 7. Strang, G. (1993). Introduction to linear algebra (Vol. 3). Wellesley-Cambridge Press. 8. A notebook example posted on the website of the gravitational wave open science center. https://www.gw-openscience.org/GW150914data/GW150914_tutorial.html. Retrieved on June 28, 2022.

Dr. Abhjit Sarkar is currently working as an professor in the Department of Mechanical Engineering, IIT Madras, received his Ph.D. from Indian Institute of Science Bangalore in 2009. He worked at Eaton Corporation (2009) and Tata Motors (2003) before joining IIT Madras. His research is in the broad area of acoustics, vibration. His focus is on mathematical formulation

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and analytical solution of problems in dynamics and acoustics. He has made significant research contributions on the understanding of the dispersion characteristics of structural acoustics waveguides, vortex-induced vibration characteristics, vibration of rotating structures, etc. He is engaged in industrial consultancy activities for leading industries and also conducting continuing education programme for participants from industry and academia.

Chapter 8

Ethics in Publishing Uday Shanker Dixit

8.1 Introduction Publish or perish has become commonly used aphorism in academia. Faculty members are expected to publish their research findings in the form of papers for the growth of their career. They also write books. Research scholars are supposed to publish some journal papers before the submission of their thesis. In fact, several academic institutions have made it a precondition for the submission of the thesis. Students’ theses and reports are also a type of publication and often these are preserved in the library. With tremendous amount of pressure on publication, it is important that faculty members and students should be aware about the legal and ethical issues in publishing. The purpose of this chapter is to sensitize everyone connected with teaching– learning and research about ethics in publishing. Ethics is a system of moral principles guided by the self and society. In fact, as per many scholars, moral indicates individual’s own principles for right and wrong, while ethics refers to rules provided by external agency. Terms legal and ethical are not synonyms. Legal standards are based on law. There are many issues that are not against law but may be unethical. For example, breaking the results of one study in two or more parts and publishing several papers instead of one paper is not a legal issue but ethically unacceptable. One of the requirements of engineering profession is strong adherence to ethics.

U. S. Dixit (B) Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_8

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8.2 Some Information About Intellectual Property Rights Publications are part of intellectual property rights (IPR). Intellectual property is an intangible property. It includes patents, trademarks, industrial designs, layout designs of integrated circuits, geographical indications and copyright. In this chapter, mainly the ethical issues related to copyright will be discussed, but it is pertinent to have a brief discussion about patent. Patent information is disseminated in the form of published patent document. A patent is an exclusive right granted for an invention, which is a product or a process that provides a new way of doing something, or offers a new technical solution to a problem. The limited monopoly right granted by the nation enables an inventor to prohibit another person from manufacturing, using or selling the patented product or from using the patented process, without permission. On January 1, 1995, Word Trade Organization (WTO) introduced the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS). The three main features of TRIPS are standards, enforcements and dispute settlement. IPR is a contract between inventor and government for the protection of the rights of the inventor. However, a balance has to be maintained between the rights of the creator and interest of the public. Usually, the validity of a patent is 20 years from the date of application, after which it becomes open to public. Various types of intellectual properties are patents, trademarks, industrial designs, layout design of integrated circuits, geographical indications, protection of new plant varieties and copyright. In this article primarily, copyright issues will be discussed. In India, first Copyright Act was passed in 1957. The act has been amended in 1983, 1984, 1992, 1994, 1999 and 2012. Section 11 of the Copyright relates to the establishment of a Board. Board has a chairman and two to 14 other members. The Chairman of the Copyright Board shall be a person who is, or has been, a Judge of a High Court or is qualified for appointment as a Judge of a High Court. The Registrar of Copyrights is the Secretary of the Copyright Board. It should be noted that as soon as a document is created, owner gets the copyright on it. Registration for copyright is not mandatory.

8.3 Copyright Laws Copyright laws protect the expression of idea but not the idea itself. One idea can be expressed in several ways, and each can be considered a separate piece of work. For getting a copyright, the work needs to be original and should be expressed in material form. Copyright covers not only articles but also videos. The meaning of original in the context of copyright means that the work should have originated from the author. The form of presentation should be original but not the ideas. For example, several persons can be the authors of “laws of motion” and can get independent copyrights, but everyone’s presentation should be different.

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Copyright grants several rights to owners. Some of them are as follows: 1. 2. 3. 4. 5.

Owner can make copies of the work. Owner can issue copies of the work to the public. Owner can rent or lend the work to the public. Owner can play, perform or show the work in the public. Owner can communicate the work to the public by any means including broadcasting and electronic media.

First owner of the work is the person or group of persons who created the work. Copyright ownership can be transferred from owner to someone else. If the work is created by an employer as a part of duty, the ownership vests on the employer. Similarly, trainer has the right over the work created by an apprentice. For articles, ownership remains active till 50–70 years from the year in which author dies; in India the duration is 60 years after the death of the author. However, in certain countries, the duration is 70 years after the death of the author. For pre-1978 works, copyright is up to 95 years from the date the copyright was originally secured. The creator gets copyright by default. However, by filling up the appropriate forms and paying the required fee, registration can be done in the copyright office. In India, Copyright Act came into force in 1957 and was amended several times.

8.4 Obtaining Permissions for Materials from Other Sources Many times an author may require to include figures, tables or excerpts from other works. For this purpose, authors need to take written permission from copyright holder. It is essential to know who the copyright owner is; in most of the cases, it is the publisher. Many authors think that they can freely take material from their own published articles. The fact is that if the copyright has been transferred to a publisher, permission from the publisher is required. Even if the copyright was not transferred to the publisher, the appropriate credit words should be included in the new article. Obtaining the written permission may take a long time. Hence, author should request for permission to copyright holder well in advance. Nowadays, many publishers have provision to provide online permission. Typically, the procedure works as follows. Step 1: Open the article from where you want to reuse figure or table. Click on “Rights and permissions”.

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Step 2: Fill the required details, then click on “QUICK PRICE” and then “CONTINUE”.

Step 3: If you have already an account, then login with your credentials, otherwise register.

8 Ethics in Publishing

Step 4: Fill the basic details and continue.

Step 5: Fill details of contents you are going to reuse and continue.

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Step 6: Check the two boxes and click on “ACCEPT”.

Step 7: Now you can download the License/Agreement to reuse the content.

The license copy should always be retained by the author. If you are going to use the same material in a new work, then the license should be obtained again. In certain cases, you may have to pay some license fee.

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8.5 When is the Copyright Permission not Needed? There are certain situations when copyright permission is not needed. A global nonprofit organization Creative Commons (CC) is providing licenses with limited rights reserved for creators. CC provides a framework for authors such that their work can be used and shared for free. However, there are various restrictions. One can use the published material under certain circumstances and for certain type of use only. While using the material, proper attribution has to be provided to creator. The creators of the work can waive or retain some of the rights to their work depending on the type of license by CC. Attribution is of the form “Figure 7 by XYZ, licensed under CC BY 4.0”. Version 4.0 is applicable from year 2013. For previous years, other versions exist. There are different types of licenses provided by CC. These are briefly summarized as follows: (i)

(ii)

(iii)

(iv)

(v)

(vi)

(vii)

Public Domain Dedication (CC0): CC0 is not a copyright license. It is a dedication to public domain. Creator gives up all the rights. For example, many creators put the photos in the Internet, which can be used by the public. Under CC0, user can download, copy, distribute, modify and build upon, even for commercial purposes. It is not mandatory to give credits to the creator, but it is always a good ethical practice to give credit to creator. Attribution (CC BY): CC BY permits user to download, copy, distribute, modify and build upon, even for commercial purposes, as long as due credit is given to the original creator. Attribution-Share-Alike (CC BY-SA): It permits the users to download, copy, distribute, modify and build upon, even for commercial purposes, as long as due credit is given to the original creator and the new work is licensed in using the same license as the original work. Attribution-No-Derivatives (CC BY-ND): It permits the user to download and reuse, including for commercial purpose with due credits given to creator; however, no modification is allowed. Attribution-Non-Commercial (CC BY-NC): It permits the user to download, copy, distribute, modify and build upon, but only for non-commercial purposes with due credit given to the original creator. Attribution-Non-Commercial-Share-Alike (CC BY-NC-SA): It permits the user to download, copy, distribute, modify and build upon, only for noncommercial purposes, provided due credit is given to the original creator and the new work is license in the same manner as the original work. Attribution-Non-Commercial-No-Derivatives (CC BY-NC-ND): It permits the user to download and reuse, for non-commercial purpose provided due credit is given to creator; with no modification.

Research scholars should know the type of copyright while using any image from the Internet. While searching some image in Google, click on “Tools”. This will display buttons—Size, Color, Type, Time and Usage Right. Clicking Usage Rights,

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three buttons will be displayed—All, Creative Commons licenses and Commercial and other licenses. By clicking on Creative Commons licenses, you shall get only those images which are under Creative Commons. It is essential to read all the information about the type of license before using the image with due credit. There are certain other circumstances in which copyright permission is not needed. For example, title is not copyrighted. If a quote is of less than 50 words and it is being included within quotation marks with proper reference, then there is no need to take copyright permission. However, if you have taken several quotes from a book and total word count is more than 400, then copyright permission must be obtained. Data per se is not copyrighted, but its form is copyrighted. That means if there is a table containing data in an article, you cannot reproduce the table in a new article without permission. However, if you draw a graph based on that data or use some information from the table in the running text, there is no need to obtain copyright permission. However, the source of data must be mentioned. Some government documents are not copyright protected, and you can use the material with proper citation. It is important to understand that if you have carried out minor modifications to a figure or table, copyright permission is still needed. Only if the modifications convert that figure or table to look entirely new, copyright permission is not needed. A material can be taken from a Ph.D. thesis with courtesy permission from the author.

8.6 Issues of Authorship It is important that only those people should be included in the author list, who have intellectually contributed to the article. Although there are no hard guidelines for the order of author, it is a preferred practice to have the names of authors in order of their contributions. First author is called the lead author, while the corresponding author is usually the group head. In academic institutions, generally the research scholars are the first author and the supervisor is the corresponding author. Supervisor should be the corresponding author because of the two reasons. First, the supervisor is more matured and well aware of the ethical practices in publishing. Second, the supervisor is the permanent member of the institute, while the address of research scholars is likely to change after he/she completes the education. All those intellectuals who have contributed in the research must be included as authors, but it is unethical to include those people who have no intellectual contribution. In fact, nowadays many journals have made it mandatory to mention author contribution. For example, in a five-author (name changed) paper, the contributions were mentioned as follows: Author contribution: Rajkamal Mahanta: Investigation; Methodology; Roles/Writing—original draft. Varun Sharma: Investigation; Writing—review and editing. Sanat Pandey: Conceptualization; Formal analysis; Resources; Software; Supervision; Roles/Writing—original draft; Writing—review and editing. Priyanka

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Saxena: Investigation; Writing—review and editing. U.C. Mishra: Conceptualization; Formal analysis; Resources; Software; Supervision; Roles/Writing—original draft; Writing—review and editing. There is no limit on the number of authors. It can range from one to infinite. A paper related to Higgs Boson has 5154 authors [1]. Paper is of 33 pages, out of which author list (along with affiliations) covers 24 and half pages [2]. A person who contributes to the work but is not listed as an author is called a ghost author. On the other hand, a person whose name is included as author without any contribution is called guest, honorary or gift author [3–5]. Having ghost, guest, honorary or gift author in a paper is unethical. If the contribution of someone is small, then his or her name can be included in the Acknowledgment. A review of literature shows that number of gift authors are increasing but ghost authorship is less prevalent, indicating that authors have become greedy due to various factors. When a senior researcher forces a junior one to include a gift or guest author, it is called coercive authorship [6].

8.7 Self-plagiarism Most of the time an author transfers copyright to a publisher. When the author wants to use some part of the published material in a new book, the permission needs to be obtained from the publisher. Permission is not needed if there is an agreement between publisher and author by which the author retains the right to bring out derivative work from the published material or expand it. Sometimes author retains the copyright of the published work, in that case he/she can use it as per his/her wish. This is the legal position. From the ethical point of view, the author has to observe much caution. The author should avoid self-plagiarism. The new work should not look similar to the previously published work. In scientific community, self-plagiarism brings a lot of disrepute, because peer may interpret that author is desperately trying to enhance publication-count. Several promotions, awards and recognitions are based on the number of publications. One should artificially not increase it. Another unethical practice is salami publishing [7]. When authors break up or slice a large work into two or more smaller publications, it is called salami publication. The data collected from a single study is split into several segments just large enough to gain reasonable results and conclusions, which are called “minimal/least publishable unit”. It may be considered a form of self-plagiarism. Authors indulge in such type of work to increase the publication-count, get more recognition, get faster career growth and receive more funding. It is very difficult to detect salami publications. It is highly subjective also. Opinion may differ on if the two papers of an author can be combined in a single paper or not. Because of this, it is difficult to control salami publication by law. Authors themselves have to care about their conscience and reputation among peers.

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8.8 Similarity Checking Nowadays, there are a number of software that check the similarity in the text. However, they do not check the similarity in figures. Moreover, these software packages check only the similarity in language and cannot figure out if the idea is copied. There are instances when some unethical authors manipulated the language of a totally plagiarized work, such that software package failed to detect the copyright violation. On the other hand, sometimes it becomes a nuisance for a genuine author, because it just starts comparing the language blindly. Phrases like “Figure 4 shows…” and “There is a good agreement between theoretical and experimental…” are accounted in similarity, although they might have been used in totally unrelated papers. Authors have to unnecessarily change the language to reduce similarity index. Instead of “Figure 4 shows…”, they have to write something like “Figure 4 depicts…” and instead of phrase “There is a good agreement between theoretical and experimental…”, author has to write something like “Theoretical and experimental results match well…” or “Deviation between theoretical and experimental results is very small…”. Thus, a lot of productive time of the researchers goes in modifying language to appease the software rather than audience. If the language is changed to make the article lucid for readers, it is justified, but most of the time authors keep spoiling their language for getting low similarity index. In 2018, University Grants Commission of India has published Regulations on Promotion of Academic Integrity and Prevention of Plagiarism in Higher Educational Institutions [8]. The regulations concern students, faculty, researchers and staff of all Higher Educational Institutions (HEI) of India who claim to be creator of an original work. It is applicable to thesis, dissertation, research papers, book chapter, book and other similar work. Any member of the academic community may report suspected case of plagiarism to the Departmental Academic Integrity Panel (DAIP). DAIP will submit its recommendations to the Institutional Academic Integrity Panel (IAIP) of the Higher Education Institute for further action. All the soft copies of dissertations and thesis are to be submitted to Information and Library Network (INFLIBNET) by Higher Education Institute within a month under the “Shodh Ganga-e-repository”. UGC has classified plagiarism into four levels as shown in Table 8.1. The classification is based on the similarity as detected by some software. Different software packages may provide different similarity indexes, and it also depends on the settings of the package. Although some guidelines are provided, largely the UGC regulations are silent regarding the method to obtain similarity index. Moreover, it is not clear that how the similarity in figures should be detected. Academic institutes are supposed to provide the penalties as per the level of plagiarism. Table 8.1 depicts the recommended penalty for each level. For repeat plagiarism, one level higher than the previous level committed by author will be considered. If plagiarism is proved after the degree or credit is awarded, the degree or credit will be temporarily suspended. It is essential to understand that similarity index obtained through a software package alone should not be the basis of judgment. Manual checking is necessary. Although in several cases, similarity checking reveals the original source from where

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Table 8.1 UGC specified level of plagiarism and corresponding penalties Level Similarity index Penalty for thesis and dissertation

Penalty for academic and research publication Minor similarities, no penalty

0

Up to 10%

Minor similarities, no penalty

1

10–40%

A revised script to be submitted Asking to withdraw manuscript within a stipulated time period not exceeding 6 months

2

40–60%

Debarred from submitting a revised script for a period of one year

Asking to withdraw manuscript, denying one annual increment, banning from supervising new Master’s, M.Phil. or Ph.D. student for 2 years

3

Above 60%

Registration of the student shall be canceled

Asking to withdraw manuscript, denying 2 successive annual increments, barring from supervising new Master’s, M.Phil. or Ph.D. student for 3 years

the material might have been copied, intent of the author should be understood properly. Sometimes some material is taken for review or comparison, which does not constitute plagiarism. All quoted work with necessary permission or attribution should be exempted from plagiarism check. References, bibliography, table of content, preface and acknowledgments are also not included in similarity checking. The generic terms, laws, standard symbols and equations are also exempted from plagiarism check. It is also mentioned in UGC regulations that plagiarism check will exclude a common knowledge or coincidental terms, up to fourteen (14) consecutive words only. In nutshell, UGC has attempted to provide guidelines for plagiarism check but onus of fair judgment lies on Academic Integrity Panels.

8.9 Conclusion In this article, a number of issues considering publication ethics have been discussed. Ethical and legal standards are function of space and time. It is important for researchers to be alert about latest intellectual property rights laws. They should also keep abreast with latest ethical standards. Many times publication houses also set ethical standards. Information provided in this article is based on several sources including guidelines for authors of reputed journals. Researchers should keep reading these guidelines very carefully while submitting their papers. Unfortunately, some researchers are over-confident about the ethics in publishing. For example, as an editor, when I asked an author to get a copyright permission for a figure taken from the other source, pat came the reply, “Sir, I have drawn it myself”. Clearly he was not aware that if a figure had similarity with already published figure, it was the case of copyright infringement. Of course, some figures are always very general and nobody

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can claim copyright on that. For example, the figure of a typical circle will always have similarity with many published figures, but in this case, one should not mention in the caption or text that figure is based on some particular reference. If a figure needs referencing, it certainly needs copyright permission. It is also pertinent to mention that sometimes authors violate copyright rules inadvertently. Also, sometimes it is very difficult to establish that really a copyright violation has been done. There is a very thin line between the “fair use” and “copyright infringement”. Therefore, the trial of copyright infringement cases may take a lot of time. However, the reputation of researcher among the research fraternity becomes at stake immediately. Hence, it is very important for researchers to be conscious as well as informed about the ethics in publishing.

References 1. Aad, G., Abbott, B., Abdallah, J., Aben, R., Abolins, M., AbouZeid, O. S., Barnovska, Z., et al. (2015). Combined measurement of the Higgs Boson mass in pp collisions at s = 7 and 8 TeV with the ATLAS and CMS experiments. Physical Review Letters, 114(19), 191803. 2. Castelvecchi, D. (2015). Physics paper sets record with more than 5,000 authors. Nature, 15. 3. Mowatt, G., Shirran, L., Grimshaw, J. M., et al. (2002). Prevalence of honorary and ghost authorship in Cochrane reviews. JAMA, 287(21), 2769–2771. https://doi.org/10.1001/jama.287. 21.2769 4. Gøtzsche, P. C., Hróbjartsson, A., Johansen, H. K., Haahr, M. T., Altman, D. G., & Chan, A. W. (2007). Ghost authorship in industry-initiated randomised trials. PLoS Medicine, 4(1), e19. 5. Gülen, S., Fonnes, S., Andresen, K., & Rosenberg, J. (2020). More than one-third of Cochrane reviews had gift authors, whereas ghost authorship was rare. Journal of Clinical Epidemiology, 128, 13–19. 6. Aliukonis, V., Poškut˙e, M., & Gefenas, E. (2020). Perish or publish dilemma: challenges to responsible authorship. Medicina, 56(3), 123. 7. Šupak Smolˇci´c, V. (2013). Salami publication: Definitions and examples. Biochemia Medica, 23(3), 237–241. 8. UGC. (2018). The Gazette of India; REGD. NO. D. L.-33004/99 F. 1-18/2010(CPP-II), July 23, 2018.

Dr. Uday Shanker Dixit is working as a professor (HAG scale) in the Department of Mechanical Engineering, IIT Guwahati. He is also the head of Center of Indian Knowledge Systems (CIKS), IIT Guwahati. He received his bachelor’s degree (mechanical engineering) from IIT Roorkee in 1987; and his masters and Ph.D. from IIT Kanpur in 1993 and 1998, respectively. He has published more than 280 scientific papers in international journals and conferences and authored/edited more than 20 books and proceedings. He has also undertaken several research and consultancy projects. In addition to developing course material on mechatronics for IGNOU, and on engineering mechanics, mechanics of machining for NPTEL, he has produced QIP course material in the area of “Finite Element Method in Engineering and its application in manufacturing”. He has been visitor’s nominee and board member of some IITs and NITs. His research interests include sustainable manufacturing, optimization, metal forming, pedagogy and teachinglearning technologies.

Chapter 9

Innovation and Intellectual Property Rights in Engineering Curriculum: A Pedagogy for Higher Educational Institutes Saurabh Verma and Sudip Dey

9.1 Introduction The term “pedagogy” has become common in educational jargon as a replacement for “methods of instruction” or “teaching strategies” [1, 2]. This instrumental perspective of pedagogy rationalizes and simplifies the labour of teaching to a universally applicable skill set, which is based in part on the misconception that teaching is a technological activity. As a result, the personal decisions and interactions that eventually make up education are frequently left out of the scientific study of pedagogy. However, because teaching is a situated and reflexive activity that calls for teachers’ judgement in interpreting practice-related events [3], the reasons behind curricular and instructional decisions are just as important to pedagogy as the method or approach that is ultimately chosen. It is crucial to educate intellectual property to students who lack a legal background because of the significant role that IP plays in knowledge-based economies and society [4]. In addition to the proactive assistance of the government, civil society and academia, an effective IP value chain also requires the attitude of innovators, entrepreneurs, inventors, writers and performers who are the true producers of IP assets [5]. The ongoing drivers of economic progress and national development in today’s globe are creativity and innovation. The ability of the nations to innovate continuously has contributed to the development of the knowledge economy. Any nation’s ability to expand its industries sustainably depends heavily on innovation [6]. It is also seen as a key source of competitive advantage for businesses looking to enter and dominate the global market. Although admirable and kind, this does not conform to S. Verma (B) Department of Management Studies, National Institute of Technology Silchar, Silchar, India e-mail: [email protected] S. Dey Department of Mechanical Engineering, National Institute of Technology Silchar, Silchar, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_9

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the international framework of jealously protected IPRs. So, it is important to spread the word about how valuable it is to turn knowledge into intellectual property [7]. Many IP owners are ignorant of the advantages of IP rights, as well as their own capacity to produce IP assets and the worth of their original ideas [8]. The difficulties involved in establishing defendable IP rights frequently deter them. In order to promote national economic progress, the Indian government launched the Make in India initiative. One of the three pillars in this program’s structure is the protection of intellectual property rights. The Indian government has actively developed rules and guidelines for the proper application of IPR throughout the nation in light of these recent advancements. This decade has been dubbed “the decade of innovation” by India. With a goal statement to encourage creativity and innovation in order to boost entrepreneurship and balance the socioeconomic and cultural growth of the country, the Indian government launched its IPR policy on May 12th, 2016. The programme’s overarching tagline, “Creative India; Innovative India,” serves as its clarion cry. One of the key objectives of National IPR policy talks about the creation of suitable course materials for: • Educational institutions at all levels to emphasize the importance of IP rights; • Online and distance learning programmes for all categories of users; • Including IPRs in school curriculum at appropriate level. Teaching IPR and innovation at higher education institutions in India is urgently needed in order to teach innovators how to safeguard their intellectual outputs. Graduates in management should learn the fundamentals of intellectual property rights, just like engineers [9]. The National Academy of Inventors (NAI) was established in 2010 to mentor and educate creative youngsters, as well as to use its members’ innovations to improve society, according to the NAI website. Teaching pupils about creativity, intellectual property and its commercialization is a duty that goes along with this objective. The current study offers guidance for creating a pedagogical framework in the areas of innovation and IPRS as well as for having particular courses and curricula to partially accomplish the aforementioned NAI purpose [10].

9.2 Background The idea of intellectual property is not new since the intellectual property system is believed to have its roots in northern Italy during the Renaissance. The first systematic effort to safeguard innovations in the form of a patent was undertaken in a Venetian Law in 1474, which granted the first individual right. Around the year 1450, Johannes Gutenberg invented the printing press and moveable type, which contributed to the creation of the first copyright system ever. By the end of the nineteenth century, contemporary intellectual property laws had been established in many nations as a result of large-scale industrialization, quick urbanization, capital investment, the expansion of railway networks and nationalism.

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With the establishment of the Paris Convention for the Protection of Industrial Property in 1883 and the Berne Convention for the protection of Literary and Artistic Works in 1886, the International Intellectual Property system also started to take shape at this time. The justification for intellectual property has always been that the benefits and recognition that come with ownership of inventions and artistic creations inspire more creative and imaginative effort, which drives economic progress [11]. The following list of the topics covered by intellectual property rights is provided by the 1967 Convention creating the World Intellectual Property Organization: • • • • •

trademarks, service marks and commercial names and designations; inventions in all fields of human endeavour; industrial designs; protection against unfair competition and “all other rights resulting from intellectual activity in the industrial, scientific, literary or artistic fields”; • literary, artistic and scientific works; scientific discoveries; • performances of performing artists, phonograms and broadcasts. With the creation of the World Trade Organization (WTO), the Trade-Related Intellectual Property Systems (TRIPSs) Agreement formalized the function and significance of intellectual property protection (IPP). It was negotiated at the conclusion of the Uruguay Round of the General Agreement on Tariffs and Trade (GATT) agreement in 1994.

9.2.1 Innovations and IPRs According to a yearly assessment created by the prominent US Chambers of Commerce, India’s total IP score increased from 38.4 to 38.6%, and the nation is currently rated 43 out of 55 on the International Intellectual Property Index. India reached another milestone in the IP innovation ecosystem when, for the first time in the previous 11 years, more domestic than foreign patent applications were filed at the Indian Patent Office. The total number of patents submitted for the quarter of January through March 2022 was 19,796. Of these, 10,706 were submitted by Indian candidates, while 9090 were submitted by non-Indian applicants (Economic Times, June 2022). Refer to Tables 9.1 and 9.2 and Figs. 9.1, 9.2 and 9.3. In future, an economy that leverages information as a powerful weapon for growth will be successful. As a result, knowledge creation and protection become crucial. The importance of intellectual property rights (IPRs), which gained attention during the Uruguay Round of the GATT and were included in the final agreement as TradeRelated Aspects of Intellectual Property Rights (TRIPS), is highlighted by this [13]. Being a party to the agreement, India was required to put its house in right in terms of laws and administrative practises to meet the requirements of the global IPR system. India fought to overcome its hesitancy and misgivings throughout the ten-year transition period of 1995–2004, but it was able to meet the deadline of 31 December

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Table 9.1 IP filings (resident + abroad, including regional) and economy Year

Patent

Trademark (class count)

Industrial design (design count)

GDP (constant 2017 US$)

2011

15,914

194,796

8180

5501.13

2012

18,250

197,877

7139

5801.29

2013

20,945

204,982

7010

6171.77

2014

22,476

237,484

8032

6629.11

2015

24,018

283,493

9264

7159.19

2016

25,887

294,412

7885

7750.27

2017

28,010

272,765

10,382

8276.93

2018

30,035

333,443

15,216

8817.67

2019

34,051

369,903

12,753

9174.04

2020

37,880

418,560

11,849

8443.36

Source WIPO Statistics [12]

Table 9.2 PCT top applicants filed by Indian organizations PCT top applicants Applicant

2018

2019

2020

Indian Institute of Technology

48

58

78

TVS Motor Company Limited

76

11

51

Council of Scientific and Industrial Research

48

45

46

9

11

35

18

22

30

15

29

18

22

25

7

13

21

24

22

18

7

5

13

Tata Consultancy Services Ltd. UPL Limited Hero Motocorp. Limited Dr. Reddy’s Laboratories Ltd. PI Industries Ltd. Indian Institute of Science Mahindra and Mahindra Ltd. Source WIPO Statistics [12]

2004 [14]. Despite ongoing scepticism in certain areas, there is enough proof that intellectual property rights (IPRs) may be a powerful weapon for speeding India’s transformation into a knowledge powerhouse, which is now crucial for promoting economic growth and social development [15]. The Global Innovation Index (GII) assigns a ranking to the world’s economies based on how innovative they are. The GII, which consists of over 80 indicators divided into innovation inputs and outputs, tries to capture the many aspects of innovation. Among the 132 economies included in the GII 2021, India is ranked 46th (Table 9.3). Refer to Figs. 9.4, 9.5, 9.6, 9.7 and 9.8 for other related detail.

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Fig. 9.1 Intellectual property laws in Indian context

Fig. 9.2 IPR ecosystem in India. Source Author’s own contribution

The association between income levels (GDP per capita) and innovation performance is seen in the bubble chart below (GII score). According to income level, the trend line indicates the projected innovation performance. Economies that show above the trend line are outperforming expectations, while those that appear below

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Fig. 9.3 Graphical representation of IP fillings in India. Source WIPO Statistics [12]

Table 9.3 India Global Innovation Index Ranking 2021

GII

Innovation inputs

Innovation outputs

2021

46

57

45

2020

48

57

45

2019

52

61

51

Source Global Innovation Index Report [16]

Fig. 9.4 Graphical representation of patent applications filed in India. Source WIPO Statistics [12]

it are underperforming them. It is discovered that India’s performance exceeds expectations for its stage of development when compared to GDP.

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Fig. 9.5 Graphical representation of patents granted in India. Source WIPO Statistics [12]

Fig. 9.6 Graphical representation of number of designs in industrial designs applications. Source WIPO Statistics [12]

9.3 Problem Formulation 9.3.1 IPR in the Curriculum IP principles are starting to be introduced to students at school. The importance of IP education in schools is highlighted in Japan because, according to the Japanese Patent Office Annual Report, “Knowledge about the protection and utilization of intellectual property rights is important to every citizen in order to ensure that Japan establishes for the twenty-first century a society based on creative science and technology” [17].

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Fig. 9.7 Number of designs in industrial designs registrations in India. Source WIPO Statistics [12]

Fig. 9.8 Positive relationship between Innovation and Development of India in GII (Global Innovation Index). Source Global Innovation Index Report [16]

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Given that India is a developing country with abundant intellectual synergies flowing throughout its ecosystem, students in the country should receive a thorough education on the steps to protect these intellectual outcomes and to obtain commercial benefits in the form of licencing and technology transfers.

9.4 Research Methodology In order to respond to the study question, “How did the universities build the course curriculum to teach IP law and innovation to engineering students,” the research design is exploratory. The goal of the current study is to offer a conceptual framework for the inclusion of an innovation and IPR course in the undergraduate engineering curriculum at India’s top university.

9.4.1 Course Objectives 1. The students will get familiarized with the fundamental aspects of intellectual property rights (IPRs) and their implications in research, development and commercialization. 2. The students shall get an adequate knowledge on the laws relating to patent, copyrights, trademarks, industrial designs, trade secrets and geographical indications along with their registration aspects. 3. The learning gained in the course paves the way for the students to catch up intellectual property (IP) as a career option.

9.4.2 Course Outcomes 1. This course is available for third-year undergraduate engineering students with sound writing and conceptualize skills. 2. This course will be conducted using experiential learning approach to immerse students in the processes involved in managing intellectual asset portfolio. 3. This course prepares the students with the skills necessary in the management of innovation and launching of entrepreneurial and innovative ventures. 4. This course equips the students with innovative problem-solving skills and problem-solving solution. 5. The course is designed to equip the students with the basic knowledge of the laws of intellectual property rights and its various forms available. 6. This course will enable the students to differentiate between the different laws of IPRs and to know that what type of intellectual outcome will be protected by which form of IPRs.

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9.4.3 Contents of the Syllabus Syllabus content outlines the subject and topics explored. Based on the comparative analysis, the syllabus contents comprised of various topics on the subjects of IP law such as: Module 1 Innovation; Analysing the Current Business Scenario, An introduction to Innovation and Creativity, Innovation in Current Environment, Types of Innovation, School of Innovation. Module 2 Scope of Innovation; Challenges of Innovation, Steps in Innovation Management, Divergent Versus Convergent Thinking, Levers of Idea Management, Innovation in Indian context-Case studies. Module 3 Experimentation in Innovation Management; Idea Championship, Participation for Innovation, Co-creation for Innovation, Proto-typing to Incubation, Technology Innovation Process, Technological Innovation Management. Module 4 Intellectual Property Rights: Historical Background, Concept, Forms and Relevance, Types of Intellectual Property, Indian Patent Act 1970; Terms and definitions, Patent rights and its scope, Patentability criteria with case studies, Patent application and Registration process, Module 5 Law of Copyrights: Fundamental of Copy Right law, Different Rights: rights of Reproduction, rights to Distribute, rights to publicly perform, Broadcasting rights, Moral rights, copyright ownership issues, copyright registration, ownership and duration, Case studies related to Infringements, remedies and penalties. Plagiarism: types and forms. Module 6 Trademark, Designs, Geographical Indication and other IPR laws: Purpose and function of trademarks, Scope of Industrial Design Protection, Current scenario of Geographical Indications, Issues and Challenges, Legal protection of GI, Trade secretes law.

9.4.4 Teaching Methodology The delivery style and strategy a lecturer, tutor or course instructor uses to facilitate student learning are known as their teaching methodologies. The following teaching

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strategy is suggested for the syllabus of the innovation and IPR course for engineering undergraduates: Teaching Methodology • Lecture (Face to Face, In Person) • Tutorial/Class Discussion (e-Learning) • Clinical (Problem based).

9.5 Discussions With the exception of individuals who study law, undergraduate students in higher education are not often provided courses on intellectual property in significant depth. One should keep in mind while presenting IP principles that some of these notions are counterintuitive and difficult to understand, while some of the practical parts are overly technical and difficult to master. There is a common belief that educational institutions should provide students with the knowledge and abilities needed to adapt to a world that is always changing. Skills like critical thinking, problem solving, teamwork, creativity, digital literacy and flexibility are frequently mentioned. IP training has several advantages for engineers and scientists. The most important is that he should be able to use the proper instruments to protect his ideas in case he ever decides to become an inventor in the course of his life or job. In addition, because they are completely given to the public, he will be able to exploit this enormous amount of technical inventions as a source of information. Although IP is protected by a number of regulations in every nation, only those with an expertise in science and engineering can recognize and utilize them.

9.6 Conclusion With its large intellectual capital pool, India is well positioned to lead all other countries in the developing knowledge economy. However, in order to reach this prestigious position, it must devise efficient tactics to control its knowledge potential in order to promote innovation and competitiveness and, in turn, leverage economic and social progress. In order to manage knowledge, a favourable environment for knowledge creation and protection must be established. Although engineering may account for the bulk of patents among all academic fields, some engineering students never receive IP training, according to Kaplan and Kaplan [18]. If IP education is introduced to students early in their freshman year and regularly during their undergraduate degree, it will become ingrained in their creative thought process. Additionally, it will provide undergraduate engineering students additional

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career options after graduation, such as technology transfer or patent law. A new engineer will use patent material frequently since he is already familiar with it if he comes into contact with it early in his career, ideally during his training.

References 1. Korthagen, F., Loughran, J., & Russell, T. (2006). Developing fundamental principles for teacher education programs and practices. Teaching and Teacher Education, 22(8), 1020–1041. 2. Van Manen, M. (1999). Knowledge, reflection and complexity. In Changing schools, changing practices: Perspectives on educational reform and teacher professionalism (Vol. 1, p. 65). 3. Grimmett, P. P., & MacKinnon, A. M. (1992). Craft knowledge and the education of teachers. Review of Research in Education, 18(1), 385–456 (Chapter 9). 4. Takagi, Y. (2004). World Intellectual Property Organisation, Teaching of Intellectual Property, WIPO Arab Regional Conference on the Teach of Intellectual Property, Dubai. www.wipo.org 5. WIPO Academy. (2016). World Intellectual Property Organization. Available at http://www. wipo.int/academy/en/teaching/teaching_research/. Accessed on June 2022. 6. Hennessey, W. (1999). The place of intellectual property teaching in the curricula of universities and technical institutes [Online paper]. Franklin Pierce Law Center. 7. De la Harpe, B., Radloff, A., & Wyber, J. (2000). What do professional skills mean for different disciplines in a business school? Lessons learned from integrating professional skills across the curriculum. In Improving student learning through the disciplines (pp. 9–23). Oxford Centre for Staff Development, Oxford Brookes University. 8. Dodridge, M. (1999). Learning outcomes and their assessment in higher education. Engineering Science and Education Journal, 8(4), 161–168. 9. Soetendorp, R., Childs, B. I. L. L., Roach, J., & Maclaughlan, R. (2005). Engineering enterprise through intellectual property education-pedagogic approaches. WSEAS Transactions on Advances in Engineering Education, 4(2), 359–367. 10. Mission and Goals of the NAI. (2017). National Academy of Inventors. http://www.academyof nventors.org/about.asp#mission. Accessed on September 1, 2017 11. Kumar, R., Saurabh, V., Sunil, Y. (2016). National IPR policy and make in India: An analysis. In International Conference on Management of Intellectual Property Rights and Strategy. MIPS 2016 (Vol. 1, pp. 14–21). National Institute of Industrial Engineering in Association with Indian Institute of Technology, Bombay. 12. WIPO Statistics. World Intellectual; Property Organization. Available at https://www.wipo. int/ipstats/en/. Accessed on March 21, 2022. 13. Naskus, K. E., Yang, G. (1999). Intellectual property rights, foreign direct investment, and competition issues in developing countries. International Journal of Technology Management, 19(1–2). 14. Das Gupta, R. (2017). Fostering innovation and entrepreneurship. Technology and Innovation, 19(1), 345. 15. Nachane, D. M. (1998). Intellectual property rights in the uruguay round: An Indian perspective. Economic Liberalization in India. 16. Global Innovation Index Report. (2021). Available at https://www.globalinnovationindex.org/ Home. Accessed on January 12, 2022. 17. Japanese Patent Office Annual Report. (2001). Nationwide promotion of intellectual property education (Chapter 4) 18. Kaplan, J., & Kaplan, K. (2003, June). Incorporating intellectual property into engineering education. In 2003 Annual Conference (pp. 8–686).

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Dr. Saurabh Verma is a certified IP professional from World Intellectual Property Organization (WIPO) and working as an Assistant Professor Grade-I in the Department of Management Studies (DOMS) at National Institute of Technology (NIT) Silchar, Assam since 2018. He did his Ph.D. in Intellectual Property Rights and Consumer Psychology in 2017 from National Institute of Technology, Kurukshetra. He has also acquired Post-Graduate Diploma in Intellectual Property Rights (PGDIPR). His area of interests are Intellectual Property Rights (IPRs), Consumer Psychology, Organizational and workplace Psychology. At present, 04 Ph.D. Scholars are pursuing their Ph.D. under his esteemed supervision. Dr. Saurabh Verma has also guided more than 60 Masters’ dissertations. He has conducted and attended a number of workshops and International conferences in the domain of Intellectual Property Rights and Consumer Psychology. He has also published a number of research papers/articles in the journals of National and International repute. Presently, he is acting as a Principal Investigator of a Research Project on IPR funded by Department of Science and Technology (DST). He has delivered a number of expert talks on Intellectual Property Rights and related area of interests in different reputed organizations. Dr. Sudip Dey is presently working as an Associate Professor at the Mechanical Engineering Department of National Institute of Technology Silchar, India. Prior to that, he was a Post-doctoral Researcher at Leibniz-Institut für Polymerforschung Dresden e.V., Germany. Before that, he was a Post-doctoral Researcher at the College of Engineering, Swansea University, United Kingdom. He received Bachelor in Mechanical Engineering (B.M.E) and Ph.D. degree from Jadavpur University, India. He has more than 20 years working experiences in academics, research and industry. His research interests start from classical mechanics to Quantum mechanics and Design and Innovation considering inter-disciplinary areas encircling the domains of applied mathematics, applied physics, applied chemistry and applied biology. His research outcomes are published in worldclass reputed journals (Elsevier, Wiley, IOP, Sage, Taylor and Francis and Springer), conferences and books. He pioneered research work on Uncertainty Quantification (UQ), stochastic mode shapes. His book on UQ entitled “Uncertainty quantification in laminated composites: A metamodel based approach,” Pub. CRC Press is globally recommended. He framed and introduced globally “Uncertainty Quantification” (ME 483) as a new course in of Undergraduate and Postgraduate level study. His research domains include molecular dynamics, tribology of bearing, mechanical metamaterials, advanced multi-functional composites dealing with novel aspects of mechanics, design, materials and structures. He is enlisted as in top 2% scientists and researchers in Global ranking by Stanford University. He published patents, several reputed journal papers, book chapters.

Chapter 10

A Pedagogical Gadget for Teaching Heat Transfer Nilkamal Mahanta, Uday Shanker Dixit, and J. Paulo Davim

10.1 Introduction In recent years, there have been intense research activities in the field of engineering pedagogy. Pedagogy is the art and science of teaching–learning approaches. It refers to the interaction between teachers and students, learning environment, and learning task. In November 1951, Hans Lohmann established the Institute for Engineering Pedagogy for teaching and research in this field [1]. In a sense, engineering pedagogy is more challenging than pedagogy of other disciplines, because of unique nature of engineering education. An engineer needs to be adept both in theory and in practice. In addition, leadership, creativity, self-initiative, and resource optimization are the required qualities for an engineer. It is not easy to impart these qualities only through lectures or well-structured plan of laboratory experiments. Education needs to be supplemented by means to encourage hands-on practices. Engineering is basically an experiential profession. Students should inculcate the habit of learning through hands-on practices and relating their experiences with theory. Training the students through hands-on practices requires sufficient resources and efforts. Lectures can be delivered in classroom or through online mode, whereas hands-on practices are performed only in physical laboratories. Laboratories in science and engineering education are paramount for imparting knowledge and honing skills. Feisel and Rosa [2] highlighted the importance of a laboratory in engineering and science education for undergraduate students. They mentioned three objectives of laboratory in undergraduate engineering—(a) student should gain the knowledge for becoming a researcher , (b) laboratory should be a platform for N. Mahanta (B) · U. S. Dixit Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, India e-mail: [email protected] J. P. Davim Department of Mechanical Engineering, University of Aveiro, Aveiro, Portugal © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_10

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the student to learn a subject, and (c) laboratory course should help the student to get an insight knowledge of real world. However, despite the presence of experimental facilities in laboratory, a student may not be able to take part in experiments as he or she has to work in a large group. To mitigate this problem, Tiwari and Singh [3] mentioned the usefulness of well-developed Internet-based remote laboratory experiments into an engineering curriculum. They collected the feedback for further improvements of the content with effective learning and knowledge transfer. Gadzhanov and Nafalski [4] described the pedagogical effectiveness of remote laboratories (RL). RL contributed to learning by doing with the involvement of students in the entire teaching process. Collaborative, cooperative and non-competitive learning motivates the students toward teamwork and decision making. Gamification, e-learning, and flipped classrooms can be important tools for imparting such type of learning. Main purpose of gamifying a course is to motivate students and inspire them to engage with the course in learning surroundings. Markopoulos et al. [5] observed a beneficial effect of gamification in engineering education by making difficult subjects more enjoyable and interesting. “Learning by doing” played an important role in both teaching and learning process with gamification. Menandro and Arnab [6] presented a review on gamification techniques for teaching–learning, which reflects the importance of introducing easy-to-conduct experiments in learning phase. Baker [7] mentioned that hands-on laboratory experiments and active participation improved girls’ achievement in physical sciences. It is also essential to obtain proper feedback regarding the students’ experience. Hands-on learning is also called “experiential learning”, “learning by doing”, and “active learning” in engineering and science education. Renner et al. [8] interviewed students about their interest in learning physics using laboratory work. Students mentioned hands-on experience in laboratory as interesting method of learning as compared to listening to teachers in classroom. Thompson and Soyibo [9] experimented in chemistry classes to teach electrolysis with two different methods. Method comprising practical work enhanced the students’ attitude, interest and enjoyment to learn chemistry than the method devoid of practical work. Ato and Wilkinson [10] found that school students using science equipment showed more interest in science as well as a positive attitude toward scientific inquiry and science profession than students with low usage of science equipment. Holstermann et al. [11] focused on hands-on experience in four different activities related to biology and observed that students with hands-on experience reported higher interest in the respective activity than students without hands-on experience. Experts attempted to provide this type of learning experience by organizing competitive events. Gadola and Chindamo [12] carried out a case study in designing a motorbike for a small racing competition. This design competition provided all the knowledge and exposure that define the idea of experiential learning. Researchers also attempted to provide a feel of engineering to school level children by organizing engineering Work Experience Week (WEW) sessions, in which students learn by doing. Gonzalez-Buelga et al. [13] studied the impact of WEW program at the University of Bristol, UK. Engineering WEW created opportunities for

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the participants to work as engineering researchers by experiencing hands-on activities. Main objective of WEW program was to motivate secondary school students toward engineering profession. Results from the student-feedback in the form of response to questionnaire were used to analyze the impact of WEW program. Tauro et al. [14] developed a problem-based learning (PBL) program based on mechatronics for Malaysian high school students and carried out pre- and post-assessment surveys to examine the impact of the program on engagement of students in science, technology, engineering, and mathematics (STEM) fields. Before attending the program, 21% of the participants showed their willingness to work as an engineer, whereas it increased to 34.55% after attending the program. Karkoub and Abdulla [15] divided the result outcomes of the teaching procedure into three categories, viz., flipped classrooms, interactions of student, and technology used in the classroom, i.e., gadgets. An increase of 44% student-enrollment in mechanical engineering program was reported after starting STEM event in high school [15]. Using solid modeling, software and hands-on experimental activities, researchers tried to attract high school children toward mechanical engineering [16]. A pedagogical innovation, combining two learning methods, viz., problem-based learning (PBL) and examplebased learning (EBL) was used to improve the learning outcomes [17]. Cirenza et al. [18] conducted hands-on workshops to help undergraduate mechanical engineering students for conceptual understanding of heat transfer. Students reported that workshop enhanced their learning abilities by offering real, hands-on experience. Penney and Clausen [19] described a number of hands-on experiments on fluid mechanics or heat transfer that can be carried out either in engineering laboratory or as classroom demonstration. Researchers also explored the usage of toys and simple models in teaching– learning practices. Billard [20] developed a doll-shaped robot to use in the introductory classes of robotics. Paul and Dixit [21] developed simple toys for understanding some basic concepts of mechanical engineering, e.g., vibration, coefficient of friction, functioning of mechanisms. Meng et al. [22] fabricated inexpensive and easy to use experimental setup for undergraduate students to carry out two fluid mechanicsbased experiments; one was related to venturimeter experiment and another was for studying frictional losses in flow through pipes. They used computer-aided design, vacuum forming, and 3D printers to develop the experimental hardware. Such pedagogical gadgets help in developing scientific spirit among the students. Unfortunately, there is a dearth of consumer products in the form of pedagogical gadgets. Educational institutions have either high-cost experimental setups in the laboratories or no experimental setup for clarifying certain concepts. There is a strong need for developing easily affordable products for teaching the scientific principles in a simplified manner. In this work, a pedagogical gadget is developed for conducting a number of handson experiments related to heat transfer. The gadget can be useful for pre-engineering as well as engineering students. Feedback obtained from different groups of students and teachers was analyzed. The main purpose of collecting feedback was to check the pedagogical effectiveness of the gadget and obtain the feedback for its improvement. Educational assessment of the gadget was carried out among the newly graduated

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students to check its efficacy for learning heat transfer concept. These students were doing preparation for graduate aptitude test in engineering and had taken a course on heat transfer during their B.Tech. program.

10.2 Pedagogical Gadget and Possible Experiments A simple, easy to handle, and low-cost pedagogical gadget was developed at Indian Institute of Technology Guwahati for teaching the concepts of heat transfer. The gadget was made of a wooden box containing a 100 W incandescent bulb, a mercuryfree liquid in glass thermometer for measuring the temperature and a detachable box made of aluminum to act as inner layer of the wooden box. Air-gap between the inner wooden surfaces and outer surfaces of the aluminum box acted as insulator. An incandescent bulb was used for heating. A data acquisition (DAQ) system and thermocouple were used to measure and download the temperature data at the center and surface of the aluminum sample. A schematic of the pedagogical gadget is shown in Fig. 10.1. Two versions of the gadget were prepared. One version was of cubical shape with a = b; among the rectangular parallelepipeds, cube has the highest ratio of volume to surface area. In another version, a = 1.618 b; thus, the two sides were in golden ratio. In the sequel, some possible experiments are described.

Thermometer

b

b

Bulb

a Fig. 10.1 Schematic of the pedagogical gadget

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10.2.1 Newton’s Law of Cooling Newton’s law of cooling states that the rate of heat loss from a body is directly proportional to the difference in the temperatures of the body and its surrounding. This means that a hot body will initially cool rapidly and then the rate of cooling gets slower. To demonstrate this law, the air inside the wooden box is first heated to a temperature above the ambient temperature. Temperature inside the box is measured using type K thermocouple connected with a DAQ. After reaching a pre-decided temperature, the bulb is switched off. Temperature readings are recorded after a fixed interval of time using DAQ, till the temperature inside the box reaches almost the ambient temperature. Students were asked to plot a graph to show the variation of temperature with time. A typical plot obtained from this gadget is shown in Fig. 10.2. In the case of lumped mass, variation of temperature with time is given by the following expression [23]: ) ( t , θ = θi exp − τt

(10.1)

where the temperature differences θ and θ i are given by θ = T − T∞ and θi = Ti − T∞ .

(10.2)

In Eq. (10.2), T is the temperature at time t, T i is the initial temperature, and T ∞ is the ambient temperature. In Eq. (10.1), τ t is called thermal time constant given by

Fig. 10.2 Variation of temperature with time during cooling

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τt =

ρV c , h As

(10.3)

where ρ is the density of the material, V the volume, c the specific heat, h the convective heat transfer coefficient, and As is the surface area. In the present case, density and specific heat are not uniform thorough out the box. Moreover, the convective heat transfer coefficient varies with temperature. Hence, Eq. (10.1) is only an approximate representation of true variation of temperature with time. In Fig. 10.2, solid curve depicts experimental results. Students were asked to fit an exponential curve based on this experimental data of the form given in Eq. (10.1). During a typical demonstration day, ambient temperature was 29 °C. The air inside the box was heated up to 90 °C and was allowed to cool. Hence, θ i is 61 °C. Thus, Eq. (10.1) contains only one parameter, i.e., τ t . This parameter was obtained matching the experimental and fitted temperature at 5 min, 35 min, and 65 min. Accordingly, three exponential curves were obtained as shown in Fig. 10.2. It is observed that when experimental and fitted temperatures are matched at 5 min, there is a good agreement between fitted and experimental temperatures up to 5 min. However, later on, fitted temperature values are much less than experimental values. In other words, this type of fitting provides faster-than-actual cooling. It indicates that actual convective heat transfer coefficient reduces with temperature, thus slowing the cooling rate. When the fitting was done based on the matching of fitted and experimental temperature at 35 min, the overall agreement between fitted and experimental curves is better. Nevertheless, actual cooling rate is faster up to 35 min and slower afterward. This again ascertains that actual convective heat transfer coefficient is high at high temperature and low at low temperature. When the fitting was done based on the matching of fitted and experimental temperature at 65 min, the fitted curve shows slower cooling, i.e., it underestimates the convective heat transfer coefficient. Students were encouraged to discuss their observations and describe what they learnt. Some academically bright students pointed out the following lessons they learnt through this experiment: (i) In general, the natural convective heat transfer coefficient for air is a function of temperature; it is high at high temperature. (ii) By taking some representative average value of thermal time constant, an exponential curve can still be fitted to describe the variation of temperature with time. For obtaining overall good fitting, time constant should not be calculated based on the early or late data during cooling.

10.2.2 Concept of Specific Heat Capacity Specific heat capacity of a body is defined as the amount of heat required per unit mass of the body to raise its temperature by one unit. This means that for a given value of heat, temperature rise in the same amount of two different types of substance will be different. It is due to the difference in specific heat capacities of the two substances. To

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Temperature (ºC)

Fig. 10.3 Variation of temperature with time during heating

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empty box

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box with aluminum pieces

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400

500

600

700

Time (s)

understand this concept, air inside the wooden box was heated to a temperature above the room temperature. Using stopwatch, time required to raise the temperature of air from the room temperature to pre-decided temperature was noted. After reaching the pre-decided temperature, heating was stopped. After cooling the wooden box to room temperature, keeping some aluminum pieces inside the wooden box, similar experiment was repeated. Time required to raise same amount of temperature in the latter case was more. Figure 10.3 shows the temperature–time graph of a typical experiment of heating empty box and aluminum-filled box to illustrate the concept of specific heat. Using this gadget, a rough estimate of specific heat capacity of a substance could be made. For example, both empty box and box filled with aluminum pieces were heated to 90 °C from room temperature and time required to raise the temperature was noted in both the cases. For empty box, time t 1 required to reach 90 °C from room temperature of 30 °C is 319 s using a 100 W incandescent bulb. For empty box, ( ) m eq C p eq ΔT = 100t1 ,

(10.4)

where meq is the equivalent mass corresponding to empty box, (C p )eq is the equivalent specific heat capacity and ΔT is the increase in temperature. Now, similar experiment was repeated by keeping 0.7 kg amount of aluminum pieces inside the wooden box. Seven pieces of an aluminum cylinder of diameter 19 mm and length 135 mm made up a mass of 0.7 kg. Time t 2 required to reach 90 °C from room temperature was 700 s using the same 100 W incandescent bulb. For box with aluminum pieces, ( ) ( ) m eq C p eq ΔT + m al C p al ΔT = 100 t2

(10.5)

Substituting Eq. (10.4) in Eq. (10.5), ( ) 100(t2 − t1 ) = m al C p al ΔT ,

(10.6)

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which provides the specific heat capacity of aluminum as 907 J/(kg °C). The value of specific heat of AA6061 (which was similar to aluminum used in the experiments) is 900 J/(kg °C) at 25 °C, [24] which is very close to experimental observation. Similarly, specific heat value of steel was experimentally measured as 478 J/(kg °C), which is close to specific heat capacity of hot rolled AISI 1018 as 475 J/(kg °C) [25]. Generally, the specific heat of metals increased with temperature. This effect can also be studied by varying the maximum temperature during heating. This experiment was repeated by several groups of students and there was some small variation in the results. However, one group obtained the specific heat capacity of aluminum as 411 J/(kg °C), which is quite different from the values reported in literature and obtained by other groups. A brainstorming session was held between instructor and students to identify the cause of this variation. It was observed that this particular group used different pieces of aluminum, although the total mass was 0.7 kg only. The students used a single piece of aluminum of diameter 60 mm and length 95 mm. To raise the temperature of the box to 90 °C from room temperature of 30 °C, it required 492 s against about 700 s required by other groups. It was decided to calculate Biot number for different types of aluminum pieces. The Biot number is a non-dimensional parameter defined by Bi =

h Lc , k

(10.7)

where k is the thermal conductivity and L c is the characteristic length, often taken as ratio of volume of solid to its surface area. Taking typical value of h as 10 W/(m2 °C) and k as 200 W/(m °C), Bi is obtained as 0.57 × 10−3 for aluminum piece of diameter 60 mm and length 95 mm. On the other hand, for aluminum pieces of diameter 19 mm and length 135 mm, Bi is obtained as 0.22 × 10−3 . Larger the Biot number, the more is the deviation from the lumped capacitance method. Hence, in the second case, with Bi of 0.57 × 10−3 , a large error is introduced. Using type K thermocouple, temperatures at surface and center of the aluminum sample were measured. For temperature measurement at the center, a 47.5 mm deep and 1.5 mm diameter hole were made in the center of the circular part to insert the thermocouple in the aluminum piece of 60 mm diameter. A temperature difference was found in both the places of bigger diameter aluminum piece. Temperature reading of 88 °C and 45.2 °C was recorded at surface and center, respectively. Thus, internal temperature of the solid was quite low, although the surface temperature became close to 90 °C. It showed the presence of temperature gradient inside the aluminum piece with bigger diameter, which violated the assumption of lumped capacitance. Hence, a deceptively small value of specific heat capacity was obtained. However, temperature gradient was not present in case of smaller diameter aluminum pieces. Position of the samples inside the box was also important. The samples should be kept near to heat source, i.e., incandescent bulb.

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Fig. 10.4 Temperature–time graph during heating the normal box and box with detachable aluminum box

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10.2.3 Insulation Effect Thermal insulators are used to prevent the flow of heat. To demonstrate the effect of the insulator, air inside the wooden box (without a detachable insulating aluminum box) was first heated to a temperature well-above the ambient temperature. Time to reach a pre-decided temperature (90 °C) was recorded through a stopwatch. The experiment was repeated by placing the detachable box made of highly polished thin aluminum sheet inside the wooden box. The temperature of the air inside the detachable box fitted within the wooden box was recorded. A thin layer of air between wooden and detachable box acted as a thermal insulator, avoiding heat loss. This reduced the time to achieve the pre-decided temperature. It also enhanced the time of cooling from the maximum temperature to room temperature. Figure 10.4 shows the results of a typical experiment of heating wooden box and wooden box with thermal insulator to illustrate the concept of insulation effect. It is clearly seen that with detachable box (i.e., with enhanced insulation), the temperature of 90 °C could be attained in 320 s, while normally it took 920 s.

10.2.4 Absorptivity of Black Color Black color absorbs almost all the visible radiation incident on it. To describe the absorptivity of black color, two measuring cylinders of same amount of water (3 mL each) were heated inside the wooden box. One cylinder contained normal water, while the other cylinder contained black colored water. Measuring cylinder with normal water was first heated to 100 °C and time to raise the temperature was recorded using a stopwatch. Thermometer was dipped under water to record the temperature of water in the measuring cylinder. The experiment was repeated by heating the black colored water to reach 100 °C and the time was recorded. It was observed that the black

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Temperature (°C)

Fig. 10.5 Temperature–time graph during heating normal water and black water

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normal water black water

0

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colored water required less time to reach 100 °C temperature than the normal water. Figure 10.5 shows the results of a typical experiment of heating normal water and black colored water in a measuring cylinder to illustrate the concept of absorptivity of black color.

10.2.5 Change in Diffusion with Temperature Diffusion is defined as the movement of molecules from an area of high concentration to an area of low concentration. To describe the effect of temperature on diffusion, following experiment was carried out. Same amount of water (200 mL each) was taken in two identical glass beakers. In both the beakers, same amount of ink is added without stirring. One beaker is heated inside the wooden box above the room temperature and the other one is kept at room temperature. Temperature was recorded through a thermometer. After reaching a pre-decided temperature of 45 °C, heating is stopped. It was observed that the ink in the heated beaker was mixed properly with water while the ink in beaker at room temperature did not mix properly. The movement of the water molecules inside the heated beaker increases due to conversion of heat energy into kinetic energy. This helps in faster intermixing of fluids in the heated beaker as compared to the beaker at room temperature. Figure 10.6 shows the mixing of ink with water kept in room temperature and heated wooden box. In beaker kept in room temperature, ink got settled down at the bottom of the beaker, whereas proper mixing of ink was observed in the case of beaker kept in heated wooden box.

10.3 Survey and Feedback on Pedagogical Gadget A survey was carried out for collecting the information regarding the pedagogical effectiveness of the gadget among the students and teachers. Many researchers

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Fig. 10.6 Water added with ink kept in a room temperature b heated pedagogical gadget

conducted survey to confirm the effectiveness of their pedagogical tools, viz., projectbased learning (PjBL), remote laboratory (RL), engineering WEW, and experiential learning for improvement of teaching–learning methods in engineering education [12–14, 16]. The main purpose of this survey was to gauge the capability of the gadget to help the students in learning some basic heat transfer concepts, engaging in hands-on practices, developing interest in engineering, developing a team spirit, and developing collaborative skills. The survey helped the researchers by providing feedback of pedagogical gadget and its utilization. This survey was designed for different groups of student. A feedback form with a set of written statements and questions was made for the survey purpose. The feedback forms were made in local language (Assamese) as well as in English. Table 10.1 gives the statements that participants had to rate between 1 and 10 and questions that were asked in the survey. The rating scale varies from 1 to 10, where 1 meant “totally disagree” and 10 meant “totally agree”. Feedback statements and questions were related to various aspects of the gadget, e.g., its pedagogical effectiveness and differing views of the researchers. A feedback about product design requiring further modifications and opportunities to use such gadgets was also obtained. Additionally, a multiple-choice question (MCQ)—“This gadget is suitable for (a) High school students (b) Higher secondary students (c) Undergraduate science and engineering students” was added for teachers to know the suitability of the gadget within the framework of course curricula. Total 712 people comprising teachers and students from different institutes, viz., (1) Indian Institute of Technology Guwahati, (2) Nowgong Polytechnic, Nagaon, (3) Ganesh Das High School, Sualkuchi, (4) Sankardev Sishu Vidya Niketan, Sualkuchi, (5) Gateway Academy, Baihata Chariali, (6) Ram Saraswati Academy, Pachim Dadara, and (7) Sualkuchi

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N. Mahanta et al. Q1. This gadget is useful for the improvement of teaching–learning process. (Answer in a scale of 1 to 10.) Q2. I did not carry out this type of experiment before. (Answer in a scale of 1 to 10.) Q3. I learnt something new from it. (Answer in a scale of 1 to 10.) Q4. It is an effective way of learning the basic concepts. (Answer in a scale of 1 to 10.) Q5. Other similar types of pedagogical gadgets should be made. (Answer in a scale of 1 to 10.) Q6. Have you come across this type of pedagogical gadgets before? (Yes/No) Q7. Any suggestions for further modifications of this gadget? (Answer in a paragraph.)

Budram Madhab Satradhikar College, Sualkuchi, participated in this survey. Participants were requested to carry out the experiments to promote hands-on practices and rigorous engagement with experiment. Students were grouped into five categories—undergraduate (23 Mechanical Engineering and 125 Bachelor of Science students), diploma (157 Mechanical Engineering students), high school (150 ninth and tenth class students), higher secondary (152 eleventh and twelfth class students), and post-graduate (72 Mechanical Engineering students). Experiments were carried out in groups of participants, i.e., one group comprising three participants was asked to carry out experiment with the help of pedagogical gadget. Main purpose of survey conducted among high school and higher secondary level students was to attract them toward careers in engineering education and develop aptitude for experimental science in general and engineering in particular. In the past also, several researchers and educationist conducted WEW program mainly to attract high school and higher secondary students; they conducted sessions on mechatronics in PjBL and solid modeling related to mechanical engineering [13–16]. Table 10.2 lists the number of respondents in different groups. Table 10.2 Number of respondents from different groups

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Undergraduate mechanical engineering and science student

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Diploma mechanical engineering student

157

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152

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10.3.1 Response to Statement 1 Statement 1 was “this gadget is useful for the improvement of teaching–learning process”. Out of a total of 712 respondents, 312 respondents provided 10 points to this statement. It means that 42.4% respondents totally agreed with this statement. They found this gadget to be a useful one for the improvement of teaching–learning process. On an average, this statement got 8.76 point out of 10. Only two high school students, two higher secondary students, and 4 diploma students rated the product as less than 5 point without providing any reason. The response to this statement should be interpreted with caution as this statement related to pedagogical aspect of the gadget. Usually the respondents participating in the survey have a friendly attitude toward the pedagogical gadget and its designer and tend to give positive feedbacks and comments. However, authors could gauge the enthusiasm of the participants during hands-on practices and accordingly assessed the worth of the pedagogical gadget. In this case, participants showed great interest and enthusiasm toward teamwork (working in a group of 3), thus affirming that gadget can be indeed useful as a pedagogical tool.

10.3.2 Response to Statement 2 Statement 2 was “I did not carry out this type of experiment before”. Overall, 278 respondents entered 10 points for this statement. It means that 39.04% respondents totally agreed with statement 2. On an average, this statement earned 8.28 point out of 10. Among all the teachers participated in survey, only 12 out of 33 had carried out similar experiments. Only 4 out of 150 high school students and 19 out of 152 higher secondary students did not agree with this statement. Among the graduation level, diploma level and post-graduate level students, about 14.9%, 12.1%, and 23.6% students had rated the statement below 5. This indicates huge potential to introduce such type of pedagogical gadgets in the science education curriculum.

10.3.3 Response to Statement 3 and 4 Statement 3 was “I learnt something new from it” and Statement 4 was “It is an effective way of learning these basic concepts”. A total of 36.7% participants responded that they had totally agreed with statement 3, i.e., they had learnt something new from this pedagogical approach. On an average, statement 3 got 8.67 point out of 10. Most of the high school and higher secondary students mentioned about their interest in experiments related to the black body radiation and concept of specific heat. Undergraduate and post-graduate students were also amazed with the fact that time required for heating equal amount of aluminum but of different dimension

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was different. Some of the post-graduate students shared the idea of pedagogical approach related to their research work to make it easily understandable and attractive to undergraduate students. Total 80.9% of the respondents totally agreed with the statement 4 by giving 10 point in the rating scale. Students and teachers showed their satisfaction for learning the basic concepts of heat transfer experimentally using this gadget as a pedagogical tool. On an average, statement 4 got 9.36 point. The feedback established the gadget as effective one for learning basic heat transfer concepts by improving student-instructor engagement level.

10.3.4 Response to Statement 5 and Questions 6 and 7 Statement 5 was “other similar types of pedagogical gadgets should be made”. Following two questions were asked: Question 6: Have you come across this type of pedagogical gadgets before? Question 7: Any suggestions for further modifications of this gadget? Overall 84.7% respondents totally agreed with the statement 5. This statement earned 9.36 point on an average. However, high school and higher secondary level students gave more 10 points on rating scale as compared to undergraduate and postgraduate students. Maximum number of respondents wanted the authors to develop similar type of other pedagogical gadgets for better understanding of science and engineering education. A 87.4% of total respondents agreed that they did not use this type of pedagogical gadgets in their teaching–learning processes. Hence, it is concluded that there is sufficient originality in the developed gadget. However, very few participants provided any useful suggestions. Only teachers and post-graduate students could provide some useful suggestions. One suggestion was regarding enhancing the safety; it may be of concern to very small children, not for high school and onwards level students. For younger children, the maximum temperature can easily be limited to 35 °C. Other two suggestions were replacing the mercury thermometer with a digital thermometer and use of glass instead of wood in one side of the box for better visualization of interior of the box. Responses for Statement 5, Questions 6 and 7 showed the necessity of design and utilization of such pedagogical gadget for the improvement of teaching–learning process.

10.3.5 Response of Teachers to MCQ Teachers were asked to provide response to following MCQ: This gadget is suitable for (a) high school students, (b) higher secondary students, and (c) undergraduate engineering and science students. They could choose more than two options. Among all the teachers (from high school, higher secondary, diploma, and undergraduate levels) who responded to this question, 30% teachers felt that this product is suitable for undergraduate students. On the other hand, 80% of all the teachers felt that it can

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be useful for higher secondary level students and 90% felt that it can be useful for high school level students. In contrast to it, all undergraduate students felt that this product can be useful for them in the learning process. This brings out the difference in the perception of teachers and students. In this case, need for this type of pedagogical gadget was overlooked to some extent by the teachers; however, the undergraduate students strongly recommended its use in their learning process.

10.4 Educational Assessment Based on Test To check the effectiveness of the pedagogical gadget for learning outcomes, a written test was conducted among the newly graduated engineering students. These students were doing preparation for a graduate aptitude test in engineering, which include the topics from heat transfer. Students had studied the subject during their B.Tech. program as a full course of 3 one-hour lecture per week (total 42 lectures). Students were divided in two groups with 6 students in each group. In one group, heat transfer was taught by providing the theoretical study material, while the other group was provided with additional hands-on experiment in the pedagogical gadget along with the study material. Questions based on the concepts, viz., lumped capacitance method, Biot number, calculation of cooling time were asked in the test. It was observed that students provided with only theoretical study material scored less marks than the students exposed to hands-on experiential learning. Out of 20 marks, students with the pedagogical gadget scored an average mark of 16 with a standard deviation of 2.19 marks, while the student from other group scored 11.83 mark on an average with a standard deviation of 2.93 marks. It is clear that the students exposed to pedagogical gadgets scored better in an average sense. A test of significance was also conducted. For this purpose, a null hypothesis is made: “There is no impact of the pedagogical gadget”. The alternative hypothesis is “The pedagogical gadget improves the average test score”. The test statistic is calculated using the following formula: x−y , t= / s n11 + n12

(10.8)

where x is the average mark of first group, i.e., 16 and y is the average mark of second group, i.e., 11.83. In both the groups, the sample size is 6, i.e., n1 = n2 = 6. The parameter s is computed from the following equation: s2 =

(n 1 − 1)s12 + (n 2 − 1)s22 , n1 + n2 − 2

(10.9)

where s1 and s2 are the sample standard deviations, 2.19 and 2.93, respectively; the denominator is degree of freedom. This provides a student’s t value of 2.79. From

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the table of one-tailed critical values of t, for degree of freedom equal to 10, at 1% level of significance, the critical value is 2.764 [26]. As the obtained t value is more than the critical value, the null hypothesis is rejected. Thus, it can be said with 99% confidence that pedagogical gadget improves learning. This educational assessment shows the importance of hands-on activities using pedagogical gadget for better learning of heat transfer concepts.

10.5 Conclusion In this work, a pedagogical gadget was designed and its effectiveness for providing a better teaching–learning was assessed through a survey. Considering the survey results as well as the enthusiasm shown by the participants toward engagement with experiential learning using the gadget, it is concluded that this gadget can be quite successful in enhancing the interest of engineering students in heat transfer. Further, it can motivate school students to learn mechanical engineering. Educational assessment was also carried out by conducting a test among newly graduated students. On an average, students exposed to hands-on experiential learning scored more marks than students without hands-on experience. Standard branded laboratory instruments make the experimental study monotonous and boring. On the other hand, this gadget is more amenable to carry out a number of hands-on activities and add several innovative experiments. In the process of conducting survey, it was realized that learning is more enjoyable and effective if experimental gadgets have some imperfection because student learn from errors. For example, in the estimation of specific heat capacity of solid, freedom was provided to students in choosing the samples. In the process, they learnt the importance of Biot number in the applicability of lumped capacitance method. Also, being simple, inexpensive and portable, gadget looked like a toy, which attracted the interest of the students toward experimental field. In the future, it is planned to develop similar other pedagogical gadgets. As a part of outreach activity and for disseminating the knowledge, some institutes were given offer to purchase the gadget. Total twelve numbers of gadgets were procured by technical institutes. Institutes were also provided with a video demonstrating the experiments. The faculty members showed their satisfaction with the gadgets. Feedback from the learners is awaited. Declaration Authors declare that there is no conflict of interest.

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References 1. Kersten, S., et al. (2018). Approaches of engineering pedagogy to improve the quality of teaching in engineering education. In J. Dummer (Ed.), Vocational Teacher Education in Central Asia (pp. 129–139). Springer. 2. Feisel, L. D., & Rosa, A. J. (2005). The role of the laboratory in undergraduate engineering education. Journal of Engineering Education, 94(1), 121–130. 3. Tiwari, R., & Singh, K. (2011). Virtualisation of engineering discipline experiments for an Internet-based remote laboratory. Australasian Journal of Educational Technology, 27(4), 671– 692. 4. Gadzhanov, S., & Nafalski, A. (2010). Pedagogical effectiveness of remote laboratories for measurement and control. World Transactions on Engineering and Technology Education, 8(2), 162–167. 5. Markopoulos, A. P., Fragkou, A., Kasidiaris, P. D., et al. (2015). Gamification in engineering education and professional training. International Journal of Mechanical Engineering Education, 3(2), 118–131. 6. Menandro, F. C., & Arnab, S. (2020). Game-based mechanical engineering teaching and learning—A review. Smart and Sustainable Manufacturing Systems, 5(2), 45–59. https://doi. org/10.1520/SSMS20200003 7. Baker, D. (2013). What works: using curriculum and pedagogy to increase girls interest and participation in science. Theory Into Practice, 52(1), 14–20. 8. Renner, J. W., Abraham, M. R., & Birnie, H. H. (1985). Secondary school students beliefs about the physics laboratory. Science Education, 69(5), 649–663. 9. Thompson, J., & Soyibo, K. (2002). Effects of lecture, teacher demonstrations, discussion and practical work on 10th graders attitudes to chemistry and understanding of electrolysis. Research in Science and Technological Education, 20(1), 25–37. 10. Ato, T., & Wilkinson, W. J. (1986). Relationships between the availability and use of science equipment and attitudes to both science and sources of scientific information in Benue State, Nigeria. Research in Science and Technological Education, 4(1), 19–28. 11. Holstermann, N., Grube, D., & Bögeholz, S. (2010). Hands-on activities and their influence on students interest. Research in Science Education, 40(5), 743–757. 12. Gadola, M., & Chindamo, D. (2019). Experiential learning in engineering education: the role of student design competitions and a case study. International Journal of Mechanical Engineering Education, 47(1), 3–22. 13. Gonzalez-Buelga, A., Renaud-Assemat, I., Selwyn, B., et al. (2020). Development and delivery of a work experience week programme for mechanical engineering. International Journal of Mechanical Engineering Education, 0306419020981043. 14. Tauro, F., Cha, Y., Rahim, F., et al. (2017). Integrating mechatronics in project-based learning of Malaysian high school students and teachers. International Journal of Mechanical Engineering Education, 45(4), 297–320. 15. Karkoub, M., & Abdulla, S. (2020). Transformative learning experiences in mechanical engineering through mechatronics: From high school to college. International Journal of Mechanical Engineering Education, 48(1), 3–31. 16. Musto, J. C., Howard, W. E., & Rather, S. S. (2004). Using solid modeling and rapid prototyping in a mechanical engineering outreach program of high school students. International Journal of Mechanical Engineering Education, 32(4), 283–291. 17. Sanchez-Gomez, C. A. (2022). Implementing a joint learning method (PBL and EBL) to innovate the development of mechanical engineering technical and non-technical skills. International Journal of Mechanical Engineering Education, 50(1), 176–196. https://doi.org/10.1177/ 0306419020950751 18. Cirenza, C. F., Diller, T. E., Williams, C. B. (2018). Hands-on workshops to assist in students conceptual understanding of heat transfer. Journal of Heat Transfer, 140(9), 092001 (10 pages). 19. Penney, W. R., & Clausen, E. C. (Eds.). (2018). Fluid mechanics and heat transfer: Inexpensive demonstrations and laboratory exercises. CRC Press.

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20. Billard, A. (2003). Robota: Clever toy and educational tool. Robotics and Autonomous Systems, 42(3–4), 259–269. 21. Paul, P., & Dixit, U.S. Development of toys for teaching and learning of mechanical engineering. National conference on advanced design and manufacture, January 6–7, 2011, Einstein college of engineering, Tirunelveli, Tamil Nadu, India. 22. Meng, F., Van Wie, B. J., Thiessen, D. B., et al. (2019). Design and fabrication of very-lowcost engineering experiments via 3-D printing and vacuum forming. International Journal of Mechanical Engineering Education, 47(3), 246–274. 23. Bergman, T. L., Lavine, A. S., Incropera, F. P., & Dewitt, D. P. (2011). Introduction to heat transfer (6th ed., pp. 280–285). Wiley. 24. Aval, H. J., Serajzadeh, S., & Kokabi, A. H. (2012). Experimental and theoretical evaluations of thermal histories and residual stresses in dissimilar friction stir welding of AA5086-AA6061. The International Journal of Advanced Manufacturing Technology, 61(1), 149–160. 25. Nandan, R. G., Roy, G. G., Lienert, T. J., et al. (2007). Three-dimensional heat and material flow during friction stir welding of mild steel. Acta Materialia, 55(3), 883–895. 26. Mendenhall, W., Beaver, R. J., & Beaver, B. M. (2009). Probability and statistics (p. 525). Cengage Learning.

Nilkamal Mahanta is a Research Scholar in the Department of Mechanical Engineering at Indian Institute of Technology (IIT) Guwahati, India. He received his Bachelor of Engineering (Hons) degree in mechanical engineering from Gauhati University. Presently, he is working in the field of product design and engineering pedagogy for his doctoral research. Dr. Uday Shanker Dixit is working as a professor (HAG scale) in the Department of Mechanical Engineering, IIT Guwahati. He is also the head of Center of Indian Knowledge Systems (CIKS), IIT Guwahati. He received his bachelor’s degree (Mechanical Engineering) from IIT Roorkee in 1987; and his masters and Ph.D. from IIT Kanpur in 1993 and 1998, respectively. He has published more than 280 scientific papers in international journals and conferences and authored/edited more than 20 books and proceedings. He has also undertaken several research and consultancy projects. In addition to developing course material on mechatronics for IGNOU, and on engineering mechanics, mechanics of machining for NPTEL, he has produced QIP course material in the area of “Finite Element Method in Engineering and its application in manufacturing”. He has been visitor’s nominee and board member of some IITs and NITs. His research interests include sustainable manufacturing, optimization, metal forming, pedagogy, and teaching– learning technologies. Dr. J. Paulo Davim is a Full Professor at the University of Aveiro, Portugal. He is also distinguished as honorary professor in several universities/colleges/institutes in China, India, and Spain. He received his Ph.D. degree in Mechanical Engineering, M.Sc. degree in Mechanical Engineering (materials and manufacturing processes), Mechanical Engineering degree (5 years), from the University of Porto (FEUP), the Aggregate title (Full Habilitation) from the University of Coimbra and the D.Sc. (Higher Doctorate) from London Metropolitan University. He is Senior Chartered Engineer by the Portuguese Institution of Engineers with an MBA and Specialist titles in Engineering and Industrial Management as well as in Metrology. He is also Eur Ing by FEANI-Brussels and Fellow (FIET) of IET-London. He has more than 35 years of teaching and research experience in Manufacturing, Materials, Mechanical and Industrial Engineering, with special emphasis in Machining and Tribology. He has also interest in Management, Engineering Education, and Higher Education for Sustainability.

Chapter 11

Uncertainty Quantification—An Eternal Future of Engineering and Technology Sudip Dey and Kritesh Kumar Gupta

11.1 Introduction Uncertainty is unavoidable and essentially always associated with the state of the unknown in any system dealing with a practical problem. The scientific history until the nineteenth century suggests that the idea of uncertainty is not framed as it represented an undesirable state and it is avoided and eliminated from academic courses. This, in general, restricted the scientific analysis to the superficial level. Post-nineteenth century, when it is realized that the Newtonian mechanics has the limitation in addressing the problems at the molecular level, the novel approaches aligned with relativistic mechanics are developed. The utilization of probabilistic methods in the statistical mechanics inspired the scientific community to address the system’s behavior under the uncertain environment [1]. The ongoing practices in the quantum theory till the early 1920s realized the atomic model by having the electrons in the fixed quantized orbits around the nucleus. The inter-orbital movements of electrons are subjected to absorbing or emitting the photons of the correct wavelength. Although this model demonstrated remarkable promise in the case of hydrogen, but it could not be extended successfully for the larger atoms. Owing to this, in 1927, the German physicist Werner Heisenberg came up with the first scientific breakthrough in materializing the uncertainty by devising the Heisenberg uncertainty principle. He stated that the position and velocity of particles cannot be measured exactly at the same time. Along with the Heisenberg uncertainty principle, in 1926 the AustrianIrish physicist Erwin Schrödinger devised the Schrödinger’s wave formulation to interpret the probability of finding a particle in exact state. Later on, Schrödinger also mathematically proved the equivalence of Schrödinger’s equation to the Heisenberg uncertainty principle [2]. The progress of uncertainty analysis in the early twentieth century also shifted the paradigms in addressing different kinds of uncertainty other S. Dey (B) · K. K. Gupta Department of Mechanical Engineering, National Institute of Technology Silchar, Silchar, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_11

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than the random kind by utilizing the classic Aristotelian logic. For instance, in 1930, Jan Lukasiewicz came up with a multi-valued discrete logic [1]. Arthur Dempster [3] devised the theory of evidence which was a pioneer in addressing the assessment of missing information. In 1965, Zadeh [4] developed the fuzzy set theory based on continuous-valued logic. Later in the 1980s, other researchers demonstrated the correlation between evidence theory, probability theory, and possibility theory by utilizing fuzzy measures (now known as monotone measures) [5]. The exceptional advancement in computational technologies started in the early twenty-first century paved the way to address the uncertainty in a detailed manner. The evolution of high-dimensional models to address the multi-variate uncertainties in the scientific problems has moved the problem analysis to a different level. Moreover, the recent advent of data science and machine learning has also contributed to the complete characterization of systems of interest. The source-based uncertainty can be categorized as aleatory, epistemic, and prejudicial. The internal parametric uncertainty can be associated with the aleatory, whereas the uncertainty due to lack of knowledge in systems behavior can be associated with epistemic uncertainty. The prejudicial uncertainty can be understood by the absence of variability characterization of the system. In general, the aleatory uncertainty is captured by employing the probabilistic framework; on the contrary, the only way to address the epistemic uncertainty is to gather more information about the system’s behavior [6]. The source-based uncertainty is practically relevant to any physical phenomenon; this can be understood by the increasing degree of impreciseness in the observations with respect to different time frames. The quantification of the effect of source-based uncertainty in the engineering domain has its importance, to ascertain the range of safe zone for any engineering system [7]. With this understanding, it is realized that uncertainty plays a major role in determining the fluctuation in the operational behavior of the real systems (refer to Fig. 11.1). Figure 11.1 illustrates that unintentional variabilities in the process parameters result in uncertain responses. A similar understanding can be gained by the illustration shown in Fig. 11.2, where the designed outcomes in various domains of engineering lead to real outcomes due to the presence of unavoidable uncertainties in the system. In this regard, this article investigates various engineering domains that are susceptible to source-based uncertainties and discusses the methods for quantifying them. A course on uncertainty quantification is also proposed, along with a brief discussion of key UQ concepts. Following that, the potential importance of learning about UQ for engineering students is discussed.

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Fig. 11.1 Influence of parametric uncertainties of the response of physical systems. X refers to the input parameter, ‘p’ refers to the uncertainty in input parameters, Y denotes the desirable response, and ‘q’ denotes the undesirable variation in response

Fig. 11.2 The significance of uncertainty in various branches of engineering

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11.2 Uncertainty Quantification in Different Engineering Domains The mathematical modeling of different engineering problems is a widely utilized method to analyze, design, and predict the behavior of the system in the desired conditions. The integration of such models with the engineering problems allows us to dive deep into the cause of problems and find the methods to eradicate the concerning issues. The sound generalization capability of the computationally developed models provides deep insights into the impact of parametric and source-based variability and uncertainty on the desired behavior of engineering systems. The critical information retrieved from such models plays a pivotal role in decision-making. The effective use of probabilistic approaches in the characterization of engineering systems reveals the likelihood of engineering systems malfunctioning in a given zone of uncertainty. Furthermore, the use of such approaches significantly reduces the time and cost associated with large-scale manual experiments and simulations. For instance, if we consider the domain of computational quantum mechanical modeling and simulation, conduction density functional theory (DFT) simulations on the large scale can be challenging and time-consuming. Similar to the DFT, the atomistic modeling and simulations are also computationally expensive and intensive. The limitations associated with such studies prohibit the possibility of performing simulations on large scale and thus hinder the complete characterization of the desired phenomenon. In this regard, Hanke [8] in his study performed the uncertainty and sensitivity analysis on the binding energy calculations derived from the dispersion corrected density functional theory (DFT-D). He propagated the error associated with the DFT-D binding energies calculations to define the approach’s uncertainty and reported the relative significance of involved parameters to highlight the most significant parameters in the binding energies calculation. He also realized that such a study increases the numerical effort about 10–20 times, but it is significantly lower than the DFT calculations. Similarly, Gupta et al. [9, 10] coupled machine learning approaches with conventional molecular dynamics simulation to highlight the uncertainty associated with the external and internal parameters of interest in evaluating the in-plane strength and stiffness of monolayer graphene. The few studies mentioned in the preceding paragraph showcase the uncertainty on the quantum and nanoscales. The concept of uncertainty is not limited to such small scales; it is practically applicable to any engineering domain at any scale. For instance, Saha et al. [11] in their study illustrated the effect of parametric uncertainties on the performance of wire electric discharge machining of Inconel 718. Similarly, Roy and Dey [12, 13] performed a stochastic analysis to illustrate the effect of parametric uncertainties on the performance of hydrodynamic journal bearing, wherein they carried out the data-driven uncertainty analysis to ascertain the loadbearing capacity of bearing subjected to uncertain input parameters. In the context of material systems, Vaishali et al. [14, 15] investigated the dynamic behavior of functionally graded material (FGM) subjected to uncertain stochastic material and geometric configurations. They utilized advanced machine learning algorithms for

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model construction and validation. The vibrational behavior of the FGM is captured in light of uncertain material properties and geometrical irregularities. In another study, Yaseen et al. [16] explored rainfall forecasting and carried out the uncertainty analysis in the predictions of the different evolutionary algorithms used for the forecasting. They reported that a computationally efficient ANFIS model integrated with the particle swarm optimization (PSO) indicates the minimum degree of uncertainty in the prediction of rainfall. Islam and Soares [17] investigated the uncertainty in the ship’s computational fluid dynamics (CFD) model’s resistance, sinkage, and trim utilizing two different methods, viz. safety factor-based approach and correction factor-based approach. They observed that the safety factor-based approach results in a lower level of uncertainty compared to the correction factor-based approach. Hou et al. [18] used a random distribution model to address uncertainty in the magnitude of ice load and water velocity in the ice zone, and they reported the optimized energy efficiency operation index (EEOI) of a vessel operating in the ice zone. Probst et al. [19] integrated the design of experiments (DOE), CFD, and genetic algorithm (GA) to optimize the diesel engine operating point. They also propagated the uncertainty in the input parameters to find the suitable operation zone of the diesel engine. The analysis of Scopus data shows that the number of manuscripts based on uncertainty analysis has risen exponentially from 1990 to 2021 (refer to Fig. 11.3a). According to the pie chart shown in Fig. 11.3b, the researchers from the engineering background published the maximum manuscripts based on uncertainty analysis during the specified time period. The concise literature review is presented in the preceding paragraphs illustrating the application and importance of uncertainty quantification (UQ) in several engineering domains. The amalgamation of UQ in engineering practices can efficiently change the course of action in the design and analysis of practical problems.

Fig. 11.3 Scopus data. a The increase in manuscripts based on uncertainty analysis from the year 1990 to 2021. b The subject-wise distribution of manuscripts on uncertainty analysis from the year 1990 to 2021. (Figures drawn based on data accessed on Feb 11, 2022 from ref. [20])

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Fig. 11.4 Implementation of uncertainty in the number system

11.3 Uncertainty in Few Physical Phenomena 11.3.1 Uncertainty in Number System In order to make the point of uncertainty more clear, in this section, the idea of uncertainty is implemented in the conventional number system. In general, the number system is framed as a two-dimensional one wherein the two axes are real number axis (X) and imaginary number axis (Y ), and the number is represented as R = X + i Y (where i2 = −1). But considering uncertainty in reality (due to lack of knowledge on a class of variables, values, and steps, unknown interactive scale effect, intrusive variabilities within variabilities exist), the new number system can be framed as Dey’s three-dimensional number system [conceptualized by Sudip Dey (2020)] wherein the three axes are real number axis (x) and imaginary number axis (y) and uncertain number axis (z) (refer to Fig. 11.4) and the number is represented as r = x + i y + u z (where u = co-efficient of uncertainty and its value varies from (−) ∞ to (+) ∞).

11.3.2 Uncertain Space–Time Domain From Aristotle’s geocentric solar model (300 BC) to Copernicus’s heliocentric solar model (1543 AD), it is presumed that the solar system is based on the thoughtexperiments considering a fixed frame of reference of solar system itself. However, in reality, the trajectories of motions of Sun and Earth with other planets are based on a frame of reference which are also moved by its own trajectory in the domain of space and time considering the interactions between our solar system with outside part of our solar system. Hence, all these motions are relative until and unless it is considered

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Fig. 11.5 Solar model in the domain of uncertain space and time

as the universal fixed frame of reference and all these motions are observed from its origin. However, in reality, due to continuous disorder (exchange of energy and mass in relativistic domain) of the universe, it is observed to exert the continuous change in the domain of space and time. Hence, in light of uncertainty in space and time scale, a new Dey’s solar model [pioneered by Sudip Dey (2021)] is conceptualized considering all the trajectories of all interactive-motions of Sun, Earth, Moon and all other planets follow an uncertain path in the domain of space and time within its volumetric band (which is coined as “Tunnel of Uncertainty”). Here f e (s, t), ge (A, t), and he (V, t) are the uncertain point–space–time function, uncertain area-space–time function, and volume–space–time function, respectively (refer to Fig. 11.5).

11.4 Design of UQ Course Work In this section, different UQ-associated concepts are presented which are essential to have a fundamental understanding of uncertainty analysis. The integration of conventional analysis approaches with the UQ framework is also explained in a detailed fashion. To inculcate the understanding of UQ in the undergraduate students, the following concepts are essential to involve in the course curriculum.

11.4.1 Sampling Techniques In real engineering practice, the variation in the control variables is ought to random. To induce this randomness in the parametric variation different random sampling approaches are used. Hence, different concepts of sampling techniques are based on the simple design of experiments (DOE) and complex random sampling such as Monte Carlo sampling, Latin hypercube sampling, Sobol sequence sampling. Such sampling techniques are useful in propagating uncertainty in the system and evaluating the influence of uncertainty distribution in input parameters on the desired responses of the system.

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11.4.2 Surrogate Models Construction and Validation In the next stage of sampling, the model formation takes place. The responses gathered for the sampled input parameters settings are correlated mathematically with the random variations in the input parameters. The understanding of mathematical model formation is essential to conduct the data-driven analysis. Hence, the foundations of fundamental and complex regression approaches have to be induced in the UQ course curriculum. The model verification and validation is an important part of constructing the efficient computational model, and thus, it is essential to include different cross-validation approaches such as hold-out cross-validation, k-fold crossvalidation, and leave p out cross-validation in the curriculum. The factors on which the generalization capability of the developed model is judged such as relative error, relative accuracy have to be addressed properly.

11.4.3 Uncertainty Analysis The large-scale predictions of constructed surrogate models are utilized to highlight the influence of parametric uncertainty on the desired response of the considered system. In this regard, the probabilistic distributions of responses under the individual and combined parametric uncertainty are compared to ensure which parameters are highly susceptible to producing uncertain responses. Hence, to accommodate this domain in the course curriculum, the understanding of different sampling distributions is essential. Along with the sampling distributions, the understanding of sensitivity analysis is also critical. The sensitivity analysis is utilized to exactly pinpoint the relative significance of considered input parameters on the desired behavior of the system. Hence, the curriculum must also include the concepts of local and global sensitivity analysis.

11.4.4 Uncertainty Optimization The ultimate objective of uncertainty quantification is to highlight the influence of uncertainty on the desired response of the system and perform the parametric optimization to maintain the system’s behavior within the safe zone. Hence, the concepts of optimization are also critical in the UQ course curriculum. Furthermore, it is essential for the students to understand how sampling, surrogate modeling, uncertainty analysis, and optimization are integrated altogether to conclude any engineering problem holistically.

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11.5 Importance of UQ Course for Engineering Undergraduates The career pathway of engineering graduates leads them into the industry or research; on both platforms, they deal with practical problems. The effect of uncertainty in the control variables, environmental conditions, material, and geometrical conditions is ought to be present on the concerned response of the system. The understanding to tackle such uncertainties and decision-making is critical in that condition. Especially for the design engineers, the successful implementation of the concepts of UQ can greatly reduce the product cost. For instance, by propagating the uncertainty in the control parameters of the system, the factor of safety can be significantly reduced without altering the strength, which lowers the product cost to a great extent. In the same way, there are domains in civil engineering such as structural health monitoring, water resource, environmental science, geotechnical engineering, where the understanding of UQ concepts can greatly help the engineering undergraduates to find the safe zone of working and increase the life cycle of the system. With this understanding, it is proposed that the course work on uncertainty quantification is essential to include in the curriculum of engineering undergraduate studies, especially for core branches such as mechanical, civil, electrical engineering courses. It is to be noted that the proposed course work is designed, included, and implemented in the curriculum of the Bachelor of Technology course of Uncertainty Quantification with the course code as ME 483 as an open elective II of Seventh Semester in B.Tech-Mechanical Engineering of National Institute of Technology Silchar, India from July 2021.

11.6 Conclusions In the present article, the importance of uncertainty quantification for engineering undergraduates is explored. We initiated the article by presenting the evolution of uncertainty analysis from the early twentieth century to the present day. Further, a brief literature review for demonstrating the importance of uncertainty analysis in different engineering domains is carried out. With the understanding to this end, the design of UQ course work is proposed, wherein we emphasized the concepts which are critical to have a basic and applied understanding of UQ analysis. Finally, the rationale for including a UQ course in the undergraduate engineering curriculum is reported. The inclusion of a UQ course in the engineering curriculum will undoubtedly prepare students to deal with practically relevant uncertain conditions in engineering design and analysis on an industrial or research platform. Acknowledgements The authors are sincerely thankful to Prof Asok Kumar Mallik (Retired Professor, IIT Kanpur, FNAE, FNA, FNASc.) and Prof. Sivaji Bandopadhyay, Director of NIT Silchar for encouraging and motivating the authors to write this article.

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References 1. Booker, J. M., & Ross, T. J. (2011). An evolution of uncertainty assessment and quantification. Scientia Iranica., 18(3), 669–676. 2. Cassidy, D. C. (1992). Uncertainty. The life and science of Werner Heisenberg. Freeman. 3. Dempster, A. P. (1968). A generalization of Bayesian inference. Journal of the Royal Statistical Society: Series B (Methodological), 30(2), 205–232. 4. Zadeh, L.A. (1996). Fuzzy sets. In Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A Zadeh (pp. 394–432). 5. Klir, G., & Wierman, M. (1999, October 19). Uncertainty-based information: Elements of generalized information theory. Springer Science and Business Media. 6. Volodina, V., & Challenor, P. (2021). The importance of uncertainty quantification in model reproducibility. Philosophical Transactions of the Royal Society A, 379(2197), 20200071. 7. Dey, S., Mukhopadhyay, T., Adhikari, S. (2018, September 19). Uncertainty quantification in laminated composites: A meta-model based approach. CRC Press. 8. Hanke, F. (2011). Sensitivity analysis and uncertainty calculation for dispersion corrected density functional theory. Journal of Computational Chemistry, 32(7), 1424–1430. 9. Gupta, K. K., Mukhopadhyay, T., Roy, A., Roy, L., & Dey, S. (2021). Sparse machine learning assisted deep computational insights on the mechanical properties of graphene with intrinsic defects and doping. Journal of Physics and Chemistry of Solids, 1(155), 110111. 10. Gupta, K.K., Mukhopadhyay, T., Roy, L., & Dey, S. (2022). Hybrid machine-learning-assisted quantification of the compound internal and external uncertainties of graphene: towards inclusive analysis and design. Materials Advances. 11. Saha, S., Gupta, K.K., Maity, S.R., & Dey, S. (2021). Data-driven probabilistic performance of Wire EDM: A machine learning based approach. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 12. Roy, B., & Dey, S. (2021). Machine learning-based performance analysis of two-axial-groove hydrodynamic journal bearings. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 235(10), 2211–2224. 13. Roy, B., & Dey, S. (2021). Comparative evaluation on probabilistic performance of journal bearing: A surrogate-based approach. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 43(6), 1–20. 14. Vaishali, Mukhopadhyay, T., Karsh, P.K., Basu, B., & Dey, S. (2020, April 1). Machine learning based stochastic dynamic analysis of functionally graded shells. Composite Structures, 237, 111870. 15. Mukhopadhyay, T., Kumar, R. R., & Dey, S. (2021). Probing the multi-physical probabilistic dynamics of a novel functional class of hybrid composite shells. Composite Structures, 15(262), 113294. 16. Yaseen, Z.M., Ebtehaj, I., Kim, S., Sanikhani, H., Asadi, H., Ghareb, M.I., Bonakdari, H., Wan Mohtar, W.H., Al-Ansari, N., Shahid, S. (2019 March). Novel hybrid data-intelligence model for forecasting monthly rainfall with uncertainty analysis. Water, 11(3):502. 17. Islam, H., & Soares, C. G. (2019). Uncertainty analysis in ship resistance prediction using OpenFOAM. Ocean Engineering, 1(191), 105805. 18. Hou, Y., Xiong, Y., Zhang, Y., Liang, X., & Su, L. (2021). Vessel energy efficiency uncertainty optimization analysis in ice zone considering interval parameters. Ocean Engineering, 15(232), 109114. 19. Probst, D.M., Senecal, P.K., Chien, P.Z., Xu, M.X., & Leyde, B.P. (2018 October 1). Optimization and uncertainty analysis of a diesel engine operating point using computational fluid dynamics. Journal of Engineering for Gas Turbines and Power. 140(10). 20. https://www.scopus.com/term/analyzer.uri?sid=78e7664ce0b9b5e207175efed60cc4ec&ori gin=resultslist&src=s&s=TITLE-ABS-KEY%28uncertainty%29&sort=plf-f&sdt=b&sot= b&sl=26&count=747380&analyzeResults=Analyze+results&txGid=725ffb2c8d0ce21b2c 6de81496874d99. (Figures drawn based on data accessed on February 11, 2022).

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Dr. Sudip Dey is presently working as an Associate Professor at the Mechanical Engineering Department of National Institute of Technology Silchar, India. Prior to that, he was a Postdoctoral Researcher at Leibniz-Institut für Polymerforschung Dresden e. V., Germany. Before that, he was a Post-Doctoral Researcher at the College of Engineering, Swansea University, United Kingdom. He received Bachelor in Mechanical Engineering (B.M.E) and Ph.D. degree from Jadavpur University, India. He has more than 20 years working experiences in academics, research and industry. His research interests start from classical mechanics to Quantum mechanics and Design and Innovation considering inter-disciplinary areas encircling the domains of applied mathematics, applied physics, applied chemistry and applied biology. His research outcomes are published in world-class reputed journals (Elsevier, Wiley, IOP, Sage, Taylor & Francis and Springer), conferences and books. He pioneered research work on Uncertainty Quantification (UQ), stochastic mode shapes. His book on UQ entitled “Uncertainty quantification in laminated composites: A meta-model based approach”, Pub. CRC Press is globally recommended. He framed and introduced globally “Uncertainty Quantification” (ME 483) as a new course in of Undergraduate and Post-graduate level study. His research domains include molecular dynamics, tribology of bearing, mechanical metamaterials, advanced multi-functional composites dealing with novel aspects of mechanics, design, materials and structures. He is enlisted as in top 2% scientists and researchers in Global ranking by Stanford University. He published patents, several reputed journal papers and book chapters.

Chapter 12

Introducing the Basic Quantities of Mechanics Amitabha Ghosh

12.1 Introduction When I find nowadays high school students solving mechanics problems involving pulleys, inclined planes, rockets, cars, etc., I cannot but help think of the early summer days of 1956 in a remote village on the Bengal-Jharkhand border. I had just completed my high school from my village school and was waiting for my admission to the district college for the Intermediate Science (ISc) programme of Calcutta University. ISc was equivalent to today’s 11 and 12 classes. My father thought that the time might be better utilized if I were to get some prior exposure to science. In those days, almost NO science topics of mechanics were taught up to class 10! And even the terms like velocity, acceleration and momentum were completely unknown to high school students. One of my cousins had just finished his Intermediate Science and was an apprentice in a steel plant. He came for a few weeks to spend with us in our village. He was the first to introduce me to the name of Newton and the terms like velocity and acceleration; he also tried his best to teach me parallelogram law of addition of velocities, etc. Besides, there was a law student from the village who already got his MSc in mathematics from Calcutta University and was spending his summer at his village home. Being requested by my father he also started giving me basic lessons on mechanics and introduced me to the laws of motion. I can still remember the tremendous mental block I experienced in conceiving the basic concepts. By then I could understand multiplying a physical quantity by a number; somehow I could also understand the concept of speed involving two quantities like distance and time. But I faced tremendous difficulty in understanding one physical quantity being multiplied by another physical quantity. For me the stumbling block was to conceive ‘momentum’!! A product of ‘mass’ and ‘velocity’. I can still remember the utterly exasperated look on the face of the law student who A. Ghosh (B) Emeritus Scientist, Indian National Science Academy, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_12

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was already an MSc in mathematics. He could not understand my difficulty and was totally baffled. It took a long time for me to somehow accept the concept of momentum and start solving mechanics problems. For me a bigger hurdle was to understand the special status of acceleration vis a vis velocity. Why only acceleration faced resistance and not velocity I could not understand. Much later when I read the history of mechanics I realized that my difficulties were not totally unfounded. Scientists of the past also faced both the problems mentioned above. The second problem is still not clearly understood even today. I think that if proper care by the teachers while introducing students to the subject of mechanics is taken the difficulty in conceptualizing the composite quantities like momentum and energy can be substantially reduced.

12.2 Elementary and composite quantities As is known to us there are three basic quantities in nature which are at the root of all phenomena. These three quantities are (i) mass (M), (ii) length (L) and (iii) time (T). All other quantities can be expressed in terms of these three basic quantities. It is not difficult to grasp the meaning when a basic quantity is multiplied by a number as that implies an increase (or decrease) of the magnitude of the quantity under consideration. In SI system, the units of these three basic quantities are kg, metre and second. Thus, when one writes a mass as 6 kg the meaning is clear to all. The composite quantities are those which involve more than one basic quantity. The composite quantities of first order involve two basic quantities. In mechanics, quantities like velocity, density, etc., are common examples of composite quantities of first order as these can be written as V = Distance(L)/Duration(T )and   ρ = Mass(M)/Unit volume L 3 .

(12.1)

Acceleration also involves only distance and time but when expressed as the change in velocity during a period it is expressed as A = V /T = L/T 2 .

(12.2)

Difficulty arises when the young students are introduced to physical quantities which are of composite nature involving M, L and T. Therefore, the first stumbling block for most of them is grasping the physical implications of a quantity like momentum that is the product of the mass and the velocity when they are introduced to the term for the first time. Or, P = M × V = M L/T .

(12.3)

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Similarly, the next physical quantity that presents difficulty in grasping the concepts are force and energy. These are also composite quantities of second order involving M, L and T. It should be remembered that true learning of the subject mechanics depends on a complete understanding of the nature of the basic quantities on which the subject mechanics stands.

12.3 Some simple experiments Although nowadays the students are whisked over these issues and are forced to solve mechanics problems the learning can be much deeper if some simple experiments are designed to impress upon the minds of the students the physical implications of the quantities like momentum and energy. Many experiments can be designed but only two are being presented here. Although chronologically the concept of energy emerged later, it is easier to demonstrate the quantity through a simple experiment. It should be impressed upon the minds of the students that only the effect of the composite quantities can be easily seen, not the quantity itself under consideration. Through a simple experiment a student can be shown the effect of a quantity like kinetic energy. Figure 12.1 shows the basic idea behind this experiment. The set up consists of a pendulum that can hit a soft target like a block of soap. The crater that is produced is an indicator of the amount of energy lost. The mass of the pendulum bob ‘m’ can be varied as is the case with the height ‘h’ of the bob from which it is released. Once the pendulum bob is released it comes down and impacts the bar of soft soap with a speed v. It is known that v∝

√

Fig. 12.1 Scheme of demonstrating kinetic energy

h

(12.4)

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Fig. 12.2 Demonstration of momentum

The crater that is developed due to the impact of the hemispherical ball depends on the energy that the soap bar absorbs which is equal to the kinetic energy of the impacting bob of the pendulum. Various tests can be done by adjusting the bob mass m and the speed of impact v so that the quantity mv2 remains unchanged. This can be achieved if the product mh remains unchanged. It should be possible to show to the students that the crater size in all the cases remain more or less unchanged implying the amount of energy that is absorbed is proportional to the quantity mh (or, in other words the quantity mv2 is proportional to the kinetic energy of the impacting bob). Demonstrating a quantity like momentum is more difficult. Momentum as such does not produce any effect but the change in momentum can be felt and its effect can be demonstrated. Besides, change in momentum results in an impulse. The rate of change of momentum results in force whose effects one can observe. Thus, momentum is a more subtle quantity and to demonstrate the implication of the quantity mv (momentum) is somewhat involved when compared to the demonstration of kinetic energy represented by ½mv2 . Figure 12.2 shows the scheme of an experiment very similar to that described in Fig. 12.1. The only difference is that the bob impacts on a piezoelectric impulse sensor. In the case of momentum what can be demonstrated is that the√effect (i.e. the impulse signal in the oscilloscope screen) depends on the product m h. Conducting the experiment several times by adjusting the height h and the mass m keeping the above-mentioned quantity unchanged the significance of the quantity represented by the product mv can be impressed upon the minds of young students. However, as mentioned before, demonstrating momentum is far more difficult than that in the case of kinetic energy that is proportional to mv2 .

12.4 Conclusion The main issue that needs to be pointed out is that the very basic concepts which are imposed upon the minds of young students of high school are not easy to comprehend. However, the pressure of examination forces them to just accept the basic concepts

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without fully understanding those. Teachers of mechanics should take them through the same path which the great scientists followed while developing this branch of physical science in the past. Experiments using inclined planes, pendulums, etc., should be repeated so that the basic concepts get enough time to sink into the brains of young students. Since the ‘science of motion’ takes the role of the foundation for most areas of engineering and physical sciences it is desirable that the students’ concepts do not remain half baked. Major thrust is needed in organizing extensive events where all aspects of teaching mechanics at the school level be discussed and analysed.

Prof. Amitabha Ghosh former Director of the Indian Institute of Technology (IIT) Kharagpur (IITKGP) and former Professor and Head of Mechanical Engineering at IIT Kanpur (IITK), is currently working as an Honorary Scientist of the Indian National Science Academy, New Delhi and the National Academy of Sciences, India, Prayagraj. He was born on 3 December 1941 in a remote village of Birbhum district, West Bengal. As he completed the age of 80 on 2 December 2021 he had served more than 56 years as a teacher. He is a highly reputed, rather popular, faculty member of IITK from 1971 to 2006, which includes his tenure as Director of IITKGP from April 1997 to April 2002. Prof. Ghosh has trained several students, both formally and informally, in the field of classical mechanics.

Chapter 13

Practicing Hydraulic Autofrettage for Strengthening a Gun Barrel: Critical Issues and Challenges A. K. Roy, S. M. Kamal, R. U. Patil, and V. V. Rao

13.1 Introduction Autofrettage is the process of creating compressive residual stresses in the vicinity of the inner surface of a monobloc cylinder through the loading and unloading of a plastically deforming load [1]. The process is widely practiced for strengthening gun barrels, vessels used in oil and chemical industries, high-pressure pipelines, reactor vessels in nuclear power plants, submarine hauls, etc., which are intended to withstand very high pressure in service. Despite the process being widely practiced in industries, the generic term ‘autofrettage’ is not very popular among students. Therefore, this chapter aims to familiarize the autofrettage process among students in general, and also, emphasis is given on how a typical autofrettage process, viz., the hydraulic autofrettage is practiced for industrial application. To provide an understanding of the autofrettage principle, a general autofrettage process is depicted schematically in Fig. 13.1. As shown in Fig. 13.1, the autofrettage process is accomplished in two stages—the loading stage and the unloading stage. In the loading stage, the cylinder is subjected to a uniformly applied load (e.g., hydraulic pressure, mechanical interference, thermal gradient, centrifugal load, etc.) that stresses

A. K. Roy · V. V. Rao Armament Research and Development Establishment, DRDO, Pune 411 021, India S. M. Kamal (B) Department of Mechanical Engineering, Tezpur University, Tezpur, Assam 784028, India e-mail: [email protected] A. K. Roy · R. U. Patil Department of Mechanical Engineering, Indian Institute of Technology Jammu, Jammu, Jammu and Kashmir 181221, India V. V. Rao Department of Aerospace Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, Maharashtra 400076, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_13

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the material beyond its elastic limit and propagates outwards to a certain intermediate radial location. The material beyond that remains in the elastic state up to the outer radius. Thus, the cylinder wall in the vicinity of the inner radius contains a plastic zone, and an elastic zone is formed toward the outer surface of the cylinder as shown in Fig. 13.1a. The boundary between the plastic and elastic zone is called the elastic–plastic interface. The load is applied at a certain rate till it reaches the desired value that causes the estimated level of plastic deformation. The corresponding load is referred to as the autofrettage load. During the loading stage, the inner diameter of the cylinder is enlarged slightly. This enlargement is shown in Fig. 13.1a in an exaggerated way for the sake of understanding. Next, the unloading stage is performed by gradually releasing the autofrettage load to zero. During unloading, the plastically deformed material in the plastic zone tries to remain in the deformed state, while the elastically deformed material in the outer portion tries to spring back to its original state. Thus, the outer elastic zone applies pressure on the inner plastically deformed zone inducing compressive residual stresses to a certain depth. As the residual stresses are self-equilibrating, the outer portion contains the tensile residual stresses as shown in Fig. 13.1b. At this point in time, autofrettage is said to be achieved in the cylinder. It is to be noted that the achievable level of compressive residual stresses at the inner side is much larger than the tensile residual stresses at the outer side. The large compressive residual stresses at the inner side of the cylinder will help in offsetting the tensile stresses in the next phase of loading. This increases the load-carrying capacity of the cylinder, the fatigue life as well as the stress corrosion cracking resistance. The development of the autofrettage process dates back to the early nineteenth century and is credited to L. Jacob, a French artillery officer [3]. He first attempted to make a cannon barrel by automatic shrinkages induced by the loading and unloading of a sufficiently high internal hydraulic pressure in 1907. The process is popularly known as hydraulic autofrettage as it is achieved by means of hydraulic pressure.

Fig. 13.1 Schematic of an autofrettage process. With permission from Shufen and Dixit [2]. Copyright ASME

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Later, autofrettage was also attempted to achieve by forcing an oversized mandrel through the cylinder bore, known as swage autofrettage [4], and by detonating an explosive charge inside the cylinder called explosive autofrettage [5]. In recent times, researchers have conceived some novel methods of achieving autofrettage in cylindrical vessels, viz., thermal autofrettage [6, 7] and rotational autofrettage [8, 9]. In thermal autofrettage, the beneficial residual stresses are induced in the cylinder by generating a temperature difference across its wall thickness deforming inner wall plastically and subsequently cooling the entire cylinder to room temperature. The rotational autofrettage can be achieved by causing plastic deformation at the inner wall of the cylinder rotating it at sufficiently high angular velocity about its own axis and then bringing back the cylinder to a complete rest. Among all the known autofrettage processes, the hydraulic and swage autofrettage are widely practiced processes in industries. The new thermal autofrettage process is yet to find its place in industries despite its practical validation. The rotational autofrettage is still in its nascent stage of development, and there is no experimental evidence of the process so far. The hydraulic autofrettage is an effective procedure, widely practiced for strengthening higher caliber gun barrels. In practicing hydraulic autofrettage for gun barrels, the monobloc barrel tube is first filled with hydraulic fluid and pressurized to the required level such that it causes plastic deformation of the inner layer to the desired extent of the tube material across its wall thickness. A certain thickness of the material at the outer portion remains in the elastic state. Usually, the gun barrel prepared for autofrettage is inserted with a mandrel having a channel for hydraulic fluid in its bore. The diameter of the mandrel is less than the barrel bore diameter. There are two benefits of inserting the mandrel; firstly, the volume of the hydraulic fluid required for internal pressurization is reduced significantly, and secondly, the desired pressurization rate can be achieved easily. The end supports/restraints and suitable seals are provided at desired locations to the barrel forging under the test in order to ensure no leakage of the hydraulic fluid. Upon withdrawal of the hydraulic pressure, the outer layer tries to reclaim its initial position as being deformed elastically, whereas the permanent deformation at the inner layer does not allow the material to recover to its initial position. Thus, it introduces compressive residual stresses of high magnitude at the inner layer of the barrel. The autofrettage effect is similar to shrinking together a very large number of very thin tubes increasing the elastic strength of the gun tube. This enables the gun tube to sustain higher pressure for the same wall thickness ratio. A tube of wall thickness ratio 1.5 by autofrettage the elastic limit can be raised by 45% (approx.) [10]. To achieve the same by using a thicker tube would involve an increase in weight by 240% [10]. The process also inhibits the probability of crack propagation due to the compressive layers at the inner side and slows down the crack growth in service. This increases the fatigue life of the gun tube. Moreover, the residual compressive stresses between the layers of the monobloc barrel also increase resistance to stress corrosion cracking, i.e., non-mechanically-assisted cracking that occurs when a material is placed in a corrosive environment in the presence of tensile stress.

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In order to attain the advantages of hydraulic autofrettage in gun tubes, the entire procedure of autofrettage is to be operated precisely in sequence. There are several crucial issues that need the attention of the operator for the successful achievement of the effect of autofrettage. The present chapter addresses the critical issues and challenges related to the practical operating procedure of the hydraulic autofrettage for gun barrels. Before addressing the critical issues related to the operation of hydraulic autofrettage, one needs to understand the mechanics of the process as well as the apparatus/equipment required along with the sequence of procedures involved to achieve it in practice. The mechanics of the process is briefly summarized in Sect. 13.2 through the stress analysis in the loading and after unloading of the hydraulic autofrettage. For better learning by the students, the detailed stress analysis in an autofrettage process may be included in courses like solid mechanics of their respective curriculum. Next, in order to give a clear idea of the practical aspects of the process to the reader, the procedure of hydraulic autofrettage of a barrel is described in Sect. 13.3 with the help of a real industrial autofrettage plant. The critical issues and challenges are addressed in Sect. 13.4 followed by the abnormalities and cause of failure of the barrel during autofrettage in Sect. 13.5. Section 13.6 highlights the safety measures that need to be followed during the operation of hydraulic autofrettage. The chapter is concluded in Sect. 13.7.

13.2 Mechanics of Hydraulic Autofrettage In this section, the mechanics of hydraulic autofrettage is briefly presented. For detailed analysis, the reader may refer to the Ref [1]. For the analysis of hydraulic autofrettage, a thick cylinder with inner radius a and outer radius b under internal pressure is considered. The end conditions of the cylinder are taken as open ended, and the cylinder is assumed to be axisymmetric for the purpose of analysis. When the cylinder is loaded with an internal pressure of sufficiently smaller magnitude, the entire wall thickness remains in the elastic state. Under open end condition (axial stress σ z = 0), the elastic stresses induced in an axisymmetric cylinder subjected to internal pressure p as a function of radial position across its wall thickness are given by well-known Lamé’s equations: σr = A +

B , r2

(13.1)

σθ = A −

B , r2

(13.2)

where σ r and σ θ denote the radial and hoop components of stress tensor, respectively. The constants A and B can be obtained by employing the boundary condition of vanishing radial stress at r = b and σr |r =a = − p. The constants thus obtained are substituted back in Eqs. (13.1) and (13.2) to yield the following resulting elastic

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stress distribution  σr = − p  σθ = p

b2 r2 b2 a2

b2 r2 b2 a2

−1



−1  +1 . −1

,

(13.3)

(13.4)

To achieve hydraulic autofrettage, the cylinder needs to be subjected to a sufficiently high internal pressure that causes desired level of plastic deformation at the inner wall. In order to analyze hydraulic autofrettage, one should first obtain the threshold internal pressure for the initiation of yielding in the cylinder using some yield criterion. In the following subsection, the initiation of yielding in the cylinder is investigated using Tresca yield criterion followed by the elastic–plastic stress analysis during pressurization and residual stress analysis after depressurization in hydraulic autofrettage.

13.2.1 Initiation of Yielding The stress distribution in Eqs. (13.3) and (13.4) shows that σ θ remains being the maximum principal stress, and σ r remains being the minimum principal stress across the wall thickness of the cylinder. The magnitude of σ θ is positive at every radial position with its maximum magnitude appearing at the inner radius a, and σ r is negative at every radial position vanishing at r = b. Now, if one gradually increases the internal pressure to reach a certain threshold, yielding first initiates at the inner radius as per Tresca yield criterion given by σθ − σr = σY ,

(13.5)

where σ Y is the yield stress of the cylinder material. At the onset of yielding, Eqs. (13.3) and (13.4) remain valid. Thus, using Eqs. (13.3) and (13.4) in Eq. (13.5) and evaluating them at the inner radius, one obtains the internal pressure pY required to initiate the yielding at the inner radius of the cylinder as   a2 σY 1− 2 . pY = 2 b

(13.6)

For achieving hydraulic autofrettage, one has to induce an internal pressure which is more than pY . The process of hydraulic autofrettage can be analyzed first by internally pressurizing the cylinder with a pressure p > pY (loading stage) and subsequently depressurizing the cylinder (unloading stage).

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13.2.2 Elastic–plastic Stress Analysis During Pressurization When the cylinder is subjected to an internal pressure p > pY , the yielding propagates from inner radius to a certain intermediate radial position c creating an inner plastic zone a ≤ r ≤ c. The portion from radius c to outer radius b remains in elastic state forming the outer elastic zone c ≤ r ≤ b. Here, c is the elastic–plastic interface radius. The cross section of the cylinder during pressurization in hydraulic autofrettage with elastic and plastic zones is schematically shown in Fig. 13.2.

13.2.2.1

The Elastic Zone, c ≤ r ≤ b

The stresses in the elastic zone c ≤ r ≤ b can be obtained by applying boundary conditions: (σr )r = b = 0 and (σθ − σr )r = c = σY to Lamé’s equations (Eqs. (13.3) and (13.4)). The resulting radial and hoop stress distribution as a function of radial position in the elastic zone thus obtained are given by   σY c 2 b 2 σr = − 2 −1 , 2b r2   σY c 2 b 2 + 1 . σθ = 2b2 r 2

Fig. 13.2 Cross section of the cylinder with inner plastic zone and outer elastic zone

(13.7)

(13.8)

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The Plastic Zone, a ≤ r ≤ c

To derive the stresses in the plastic zone, a ≤ r ≤ c, it is considered that the material yields as per Tresca criterion without strain hardening. The Tresca yield criterion in the vicinity of the inner radius of the cylinder then takes up the form given by Eq. (13.5). The solution for radial stress in the plastic zone can be obtained by using Eq. (13.5) in the axisymmetric equilibrium equation, which remain valid in all stages of deformation given by dσr . dr

(13.9)

σr = σY ln r + C,

(13.10)

σθ − σr = r This provides

where C is an integration constant. The constant C can be estimated using the boundary condition of continuity of radial stress at the elastic–plastic interface radius c. Substitution of the constant C in Eq. (13.10) yields the following solution for radial stress distribution:   c2 σY c2 (13.11) 1 − 2 + ln 2 , σr = − 2 b r Using Eq. (13.11) in Tresca yield criterion (Eq. (13.5)), the hoop stress distribution is obtained as   c2 σY c2 (13.12) 1 + 2 − ln 2 . σθ = 2 b r For a given autofrettage pressure, p > pY , the elastic–plastic interface radius c can be determined by using the boundary condition: σr |r =a = − p. Thus, Eq. (13.11) provides p=

  c2 c2 σY 1 − 2 + ln 2 . 2 b a

(13.13)

The above equation can be solved for the unknown radius c using numerical technique such as bisection method.

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Residual Stress Distribution in the Cylinder After Depressurization

After depressurization of the autofrettage pressure p, residual stresses are induced within the wall of the cylinder. It is assumed that the process of depressurization is purely elastic. Thus, the residual stresses in the elastic zone c ≤ r ≤ b are obtained by subtracting Eqs. (13.3) and (13.4) from Eqs. (13.7) and (13.8), respectively, and are given by  2   a σY c 2 p a2 σr = − − − 2 , 2 a2 pY r2 b  2   a σY c 2 p a2 . σθ = − + 2 a2 pY r2 b2

(13.14)

(13.15)

Similarly, by subtracting Eqs. (13.3) and (13.4) from Eqs. (13.11) and (13.12), the residual stresses in the plastic zone a ≤ r ≤ c are obtained as     a2 r2 σY p 1 − 2 − ln 2 , 2 pY r a      a2 r2 σY p 1 + 2 − 2 + ln 2 . σθ = − 2 pY r a σr = −

(13.16)

(13.17)

By plotting the residual stress distributions in a typical cylinder given by Eqs. (13.14)–(13.17), it can be seen that the residual stresses in the vicinity of the inner radius of the cylinder are compressive spreading up to a certain depth. The maximum compressive hoop stress induces at the inner radius of the cylinder. Tensile residual hoop stresses of very small magnitudes are generated toward the outer radius of the cylinder. Now, the cylinder is hydraulically autofrettaged with beneficial compressive residual stresses at and around the inner radius of the cylinder, which will offset the net tensile stresses in the next phase of pressurization. This leads to the enhancement in the pressure carrying capacity of the cylinder in service. It is to be noted that depending upon the level of overstrain induced during autofrettage, the generated compressive residual stresses in the autofrettaged cylinder may cause reyielding in compression at the inner radius. Thus, to predict reyielding, the Tresca yield criterion given by Eq. (13.5) is employed at the inner radius using Eqs. (13.16) and (13.17). This provides   pa 2 . σθ − σr = σY 1 − pY r 2

(13.18)

It can be inferred from the above equation that reyielding at r = a will take place if the applied internal pressure is at least twice the yield onset pressure of the cylinder, i.e.,

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(13.19)

Substituting the expression of pY from Eq. (13.6) in Eq. (13.19), one obtains   a2 p ≥ σY 1 − 2 b

(13.20)

For plastic deformation of the entire cylinder wall, the required autofrettage pressure po can be determined by substituting c = b in Eq. (13.13). This provides po = σY ln

  b . a

(13.21)

The smallest wall ratio (b/a) for which the secondary yielding can initiate on unloading can be determined by substituting the value of po from Eq. (13.21) in Eq. (13.20) for p. Thus, one obtains the following inequality: ln

    b a2 ≥ 1− 2 . a b

(13.22)

Solving Eq. (13.22), one gets (b/a) ≥ 2.22. The fully plastic pressure corresponding to (b/a) = 2.22 is obtained from Eq. (13.21) as po = 0.8 σ Y . Thus, it can be concluded that for a cylinder with (b/a) ≥ 2.22, reyielding will take place in the cylinder during the unloading for an autofrettage pressure in the range 2pY ≤ p ≤ po . For p < 2pY , there will be no reverse yielding upon reloading in the cylinder irrespective of the wall thickness ratio. The mechanics of hydraulic autofrettage presented above will be useful while practicing the process for strengthening pressure vessels in industries. The analysis will provide some insight to the practicing engineers and scientists to carefully select an autofrettage pressure for a given cylinder based on the desired level of autofrettage to be achieved for the intended application. In the subsequent sections, the hydraulic autofrettage practiced for a real gun barrel.

13.3 The Process of Hydraulic Autofrettage of a Barrel There are three methods of hydraulic autofrettage of a gun barrel. They are: (i)

Full-length autofrettage, where the gun barrel is autofrettaged throughout the length. The gun is filled with liquid placing the sealing at both ends which are then pressurized to the required level. (ii) Partial length autofrettage, a selected portion of the gun barrel is autofrettaged by placing the sealing at the end of predetermined length, and

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(iii) Full-length deferential autofrettage, where multiple times different autofrettage pressure is applied on different sections to meet the strength requirements. The schematic of the hydraulic autofrettage plant layout with different units is shown in Fig. 13.3. Correspondingly, a photograph of the actual layout being used for the gun barrel autofrettage is shown in Fig. 13.4. The gun tube is machined to special dimensions which are determined by autofrettage calculation and is termed as ‘forging prepared for autofrettage’ [9]. Now, the monobloc gun tube with dimensions of the forging prepared for autofrettage is placed on the job loading frame for internal pressurization. Before placing forging prepared for autofrettage on the loading frame, the mandrel is checked for its required length and sealing systems on it. The length between the two seals on the mandrel gives the autofrettage length. However, the effective autofrettage length is determined after discarding the end effect. Generally, one and a half calibers are discarded from both ends to arrive at the effective length of autofrettage in the finished barrel for full-length autofrettage and from one end for partial length autofrettage. The discarding length also depends on the loading frame length to accommodate the barrel. After placing the barrel in the frame, the mandrel is inserted in the barrel aligning it with the bore axis of the barrel. The exact position of the mandrel is controlled by the mandrel operating desk. The strain gauges are then mounted on the barrel at a predefined position to measure the exterior expansion of the barrel with pressure rise to know the correctness of the autofrettage process and material characteristics. The gauges used for the measurement of exterior expansion are calibrated before mounting. After mounting strain gauges, hydraulic lines (inlet and outlet) are connected to the mandrel through the intensifier for pressurization of the barrel bore. After that control panel is checked, graph paper is fed in pressure exterior expansion (PEE) recorder, and the recorder pen is filled with the ink. Before starting the pressurization of the barrel, it is required to be confirmed that none is near the plant. The pressurization is controlled from the control room, and the eye is kept on the site through closed-circuit television (CCTV). The pressurization is carried out such that the stable readings can be obtained at the predefined intervals.

Fig. 13.3 Schematic layout of autofrettage plant

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Fig. 13.4 Hydraulic autofrettage setup for gun barrel (Courtesy: Bharat Forge Ltd., Pune, India)

The level of pressurization achieved during autofrettage operation is limited by the plant capacity and sealing arrangement. A minimum autofrettage pressure (MAP) is achieved at a predetermined pressure rate. The rate of increase in pressure is reduced steadily as the internal pressure approaches the MAP. The expansion of the barrel on some pre-selected external locations is measured during pressurization and recorded for comparison with the theoretical pressure exterior expansion (PEE) curve. After achieving the desired MAP, it is held constant for only a minute. The pressure is then slowly released, and residual strains are measured using a suitable technique. After releasing the autofrettage pressure, the gun forging is subjected to low-temperature treatment (LTT) to iron out the undue internal stresses. After LTT, the gun barrel is again subjected to MAP at a similar pressure rate and is termed as the test pressure. During test pressure, the PEE curve should exhibit linear behavior. The successful completion of the autofrettage process ensures the soundness of the material with an enhanced pressure carrying capacity for the same wall thickness ratio.

13.4 Critical Issues in Hydraulic Autofrettage The hydraulic autofrettage is one of the most effective ways of strengthening gun barrels, albeit the procedure is critical in terms of certain issues related to the preparation of arrangement and operational parameters. The barrel bore is loaded with very high pressure with a hydraulic power pack through intensifier units. The required high pressure needs to be precisely controlled in order to achieve the desired level of overstraining at the inner side of the barrel tube. Otherwise, the tube may burst during autofrettage causing hazards to the operator or anyone near the autofrettage plant. Thus, in order to contain the required pressure inside the barrel bore, one needs to critically consider certain aspects during autofrettage. There are certain post autofrettage aspects, which also need careful attention to retain the beneficial

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effects of autofrettage. All such critical aspects are highlighted and discussed in the following subsections from the experimentalist point of view.

13.4.1 Selection of Autofrettage Fluid Generally, two types of fluids are used in hydraulic autofrettage—low-pressure fluid and high-pressure fluid. The low-pressure fluid is used for boosting up the pressure to a high value in the intensifier unit, whereas the high-pressure fluid is a working fluid for the application of high-pressure in the intensifier unit as well as in the barrel [12, 13]. The autofrettage is a typical high-pressure implication in a shorter duration, and any normal fluid will not be suitable. Thus, the selection of autofrettage fluid for creating the desired pressure is critical. The desired characteristics/properties of the low and high-pressure fluids are briefly highlighted in the following subsections.

13.4.1.1

Low-Pressure Fluid

The fluid used in the intensifier unit to boost up high pressure should be well-refined petroleum containing no kerosene and foreign matters. It should have a viscosity of about 150 ssu (Seconds Saybolt Universal) (31.875 cst) at 65.5 °C and be dewaxed, desludged, neutralized, and anti-foaming. Its viscosity index should be more than 100 with low detergency to keep gums and varnish, etc., low. The fluid should not contain particles higher than 10 microns. Some well-known brands of low-pressure fluids are listed below for ready reference to the practicing scientists and engineers. • • • • • • • • • •

Aloco Hydraulics (Pennsylvania) Eureka Oil C (Atlantic Refining Co.) Gargoyle-Dte-Light (Socony-Vacuum) Gulf Crest 44 (Gulf Oil Co.) Hydro Drive 150 (EF Houghton & Co.) Pacemaker 1 (Cities Service) Regal-A (Texas oil Co.) Solnus Light (Sun Oil Co.) Super Hydraulic (White Bagley Co.) Tellus 27 (Shev Oil Co.)

13.4.1.2

High-Pressure Fluid

Most liquids shrink greatly under pressure, 90 to 200 times as much as steel. Water, for instance, of 690 MPa compresses about 16% of its free volume. In all liquids, the rate of compression grows progressively less as pressure increases, that is, they grow stiffer. This is always accompanied by an increase in density (or specific weight) and viscosity. High-pressure fluid should not solidify at higher pressure as the free flow

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of liquid is required at high pressure for the transmittal of pressure in autofrettage. High-pressure fluid for autofrettage should have the following properties: • • • • • • • • • • • • •

Minimum compressibility at high pressure, Higher flashpoint, Non-coagulative, Non-foaming, Non-acidic, Non-corrosive, Good lubricating properties, High cleanliness, Higher viscosity index, Fire resistant, Higher freezing point at high pressure, Non-toxic, Low viscosity at ambient condition, etc. Some well-known high-pressure autofrettage fluids are listed below:

• • • •

DTE light—for less than 345 MPa autofrettage pressure, No. 10 motor oil—for less than 345 MPa autofrettage pressure, PLEXSOL-201—for less than 690 MPa autofrettage pressure, 50% ethylene glycol + clean tap water + rust inhibitor + anti-freezing agent + anti-foaming agent—for less than 1378 MPa autofrettage pressure.

One of the better-known commercial glycol anti-freezing compounds TELLAR (EI Du Pont) with built-in rust inhibitor and the anti-foaming agent has been used successfully up to a pressure level of 1378 MPa.

13.4.2 Preparation of Mandrel and Sealing System The function of the mandrel is to reduce the quantity of the autofrettage fluid in the barrel by decreasing the bore space to be filled by the fluid. Thus, there are two benefits of using the mandrel—the volume of fluid required for pressurization is reduced significantly, and desired pressurization rate can be achieved easily. For autofrettage (partial length/full length), a suitable mandrel is selected. The sealing system is provided on the mandrel for containing fluid inside the barrel to generate the required autofrettage pressure. Generally, two to three stages of sealing are provided on either side of the mandrel. For lower autofrettage pressure ( 1.5 or b = 0.22 K + 0.78 for K < 1.5.

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1000

8000

6000

D Line

AFPR (Bar)

AFPR (MPa)

800

600

400

4000

2000

200

0 0.0

0.2

0.4

0.6

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1.0

0 0.0

EE (mm)

(a) Theoretical Curve

0.2

0.4

0.6

0.8

1.0

EE (mm)

(b) Experimental Curve

Fig. 13.6 PEE curve for a typical gun barrel during the application of autofrettage pressure: a theoretical, b experimental

If the minimum autofrettage pressure is calculated based on the minimum strength of the barrel material and wall thickness ratio, the autofrettage pressure is kept the same for any change in the material properties. This process does not conform precisely to the desired degree of autofrettage and is considered a conservative autofrettage process. In the modern autofrettage process, the minimum autofrettage pressure is calculated based on the achieved strength of the barrel material and wall thickness ratio. In this case, the minimum autofrettage pressure changes with the material strength, and the degree of autofrettage remains the same for all barrels. Thus, the modern autofrettage process conforms precisely to the desired degree of autofrettage.

13.4.4.2

Leakage if Any During Autofrettage

Leakage during autofrettage leaves the material in an uneasy state. To relieve the stress, low-temperature treatment (LTT) becomes essential if leakage occurs beyond the linear elastic limit of the barrel material. If leakage occurs below the linear elastic limit and the leakage problem can be addressed within one hour, then no LTT is required. However, LTT becomes essential if the repair of leakage takes more than one hour. This is to avoid stress quenching in the barrel material for its stable characteristics.

13.4.4.3

Minimum Test Pressure

After successful autofrettage and low-temperature treatment, the barrel is pressurized for a test pressure (equal to autofrettage pressure) to check the characteristic stability of the barrel. The increment in the linear elastic limit is also verified, but this time

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8000

AFPR (Bar)

6000

4000

2000

0 0.00

0.15

0.30

0.45

0.60

EE (mm) Fig. 13.7 PEE curve for a typical gun barrel during the application of test pressure

care is taken so that the inner layers do not stretch beyond the new linear elastic limit. The rate of application of pressure is maintained the same as the application of the autofrettage pressure. The difference in exterior expansion in pressure ‘on condition’, i.e., between the autofrettage pressure and test pressure should be less than 50 µm. The test pressure is also held constant for one minute after its application. Thereafter, pressure is released, and the barrel is left to settle down. The pressure ‘off’ readings are taken and compared with autofrettage readings approximately after 15 min. The difference in the pressure off readings should be less than ID/10000 (ID represents inner diameter). If the difference is more than the specified, test pressure should be reapplied, and the difference should be checked for the consecutive test pressures TP1 and TP2 . Maximum three test pressures can be applied to the barrel. If the difference in exterior expansion between TP2 and TP3 is beyond the specified limit, then the barrel is rejected. A PEE curve obtained during the application of test pressure for a typical gun barrel is shown in Fig. 13.7.

13.4.5 Low-Temperature Treatment A suitable low-temperature treatment (LTT) is required to be given to the forging immediately after the application of the autofrettage pressure and test pressure. This treatment varies with the type of steel in consideration. The barrel as a result of autofrettage becomes work hardened. A new linear elastic range is induced accompanied by a permanent increase in internal as well as external diameter. LTT irons

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out local inequalities of strain by its effect on the crystal structure. Thus, it brings the material in less uneasy condition. It acts beneficially toward stabilizing the barrel characteristics.

13.4.5.1

Heat Treatment Furnace for LTT

The furnace required for the LTT of the barrel should be calibrated for its performance according to the International Organization for Standardization (ISO) requirement. The thermocouples readings should not vary more than ±3 °C. It is to be ensured that all the thermocouples are calibrated on the date, the furnace is suitable for LTT, and the barrel is transported from the autofrettage site to the furnace in a short time so that LTT can be initiated within one hour of autofrettage. LTT may be carried out in a vertical furnace to avoid any bending to the barrel.

13.4.5.2

LTT Cycle

The LTT depends on the chemical composition of the barrel steel and wall thickness ratio. If the barrel steel contains Ni–Cr or Ni–Cr–Mo, and the wall thickness ratio is less than four, then LTT is carried out at 300 °C. The heating of the barrel should be at a slower rate, i.e., 60–70 °C/h, and reach 300 °C in 4 h 30 min. At this temperature, the barrel is to be kept for 2 h, and then it is to be taken out from the furnace. The barrel is left for cooling in the air. Similarly, LTT is carried out at 250 °C for barrel steel containing not containing Cr and Mo.

13.4.6 Measurement of Pressure Exterior Expansion For exterior expansion measurement during the autofrettage process, LVDTs are used. An LVDT is mounted on the barrel using LVDT calipers having magnetic holding pads. On each caliper, one/two LVDT(s) are mounted for exterior expansion measurement. The number of LVDTs is based on the wall thickness variations in the critical area of the barrel. Generally, at three locations, LVDTs are placed for exterior expansion measurement. The proper mounting of LVDTS plays important role in measurement. Mounting of a minimum of two LVDTs at one location also reflects the variations if any in the properties of the barrel section if different expansions are observed by LVDTs at the locations. An LVDT mounted on the barrel for exterior expansion is shown in Fig. 13.8a, and details of the LVDT Caliper and resting pad are shown in Fig. 13.8b and c respectively.

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LVDT Calliper

LVDT Magnetic Mountings

LVDT at ‘W Location

LVDT at ‘Y’

LVDT at ‘X’ Location

(a)

Resting Pads Resting Pads

Magnets

(b)

(c)

Fig. 13.8 Measurement of external expansion: a LVDTs mounted on gun barrel, b LVDT caliper, and c LVDT supporting pads

13.5 Abnormalities and Causes of Failure During autofrettage, pressure is stopped before MAP is reached if the barrel is behaving abnormally. The usual symptom of abnormality is either (a) excessive expansion or (b) bending [11, 12]. The standard PEE curve is generated for standard properties of the barrel for a given wall thickness ratio, but such type of barrel is not easy to find. Most barrels deviate to some extent from the standard PEE curve. If the barrel is stronger than the standard barrel, then the curve will deviate toward the left, and expansion will be less at the pressure corresponding to standard barrels, whereas the curve will shift toward the right if the barrel is weaker than the standard barrel. Again, if the barrel is too weak, the curve will depart in the right well before the elastic limit and it is called running away or overrun of the barrel, and the barrel is rejected. If, in this condition, pressurization is not stopped, it will lead to bursting of the barrel during autofrettage. Sometimes, deficiency in properties of barrel material leads to the ballooning/irregular expansion/ bursting/bending of the

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barrel. The ballooning takes place due to a weaker section of the barrel or irregular expansion at the section, and the barrel is rejected. Due to cracks in the barrel sometimes, abnormal expansion is observed, and if the pressurization will not be stopped, then bursting will take place in the barrel during autofrettage. Generally, the pressurization is stopped before MAP if the bending exceeds 7 mm [14]. Such type of barrel is not accepted for further processing without LTT. Even after LTT, the characteristics of the behavior of the barrel does not change, then the barrel is rejected.

13.6 Dos and Don’ts During the Process of Hydraulic Autofrettage Following necessary safety measures should be followed in the whole process of hydraulic autofrettage: i.

Barrel dimensions to be conformed before accepting the barrel for autofrettage as per autofrettage drawing of the barrel. ii. During the application of pressure, the plant is screened for the protection of personnel. iii. Person working on the process should aware of plant protective equipments (PPEs) and should follow the same during barrel mounting/dismounting for autofrettage. iv. If any heavy pressure leakage is observed during pressurization of the barrel, the process should be stopped immediately and should rectify the problem only after pressure is reduced to zero. v. During the autofrettage/test pressure process, personnel movement in the autofrettage plant is strictly prohibited, and personnel can be allowed to enter the autofrettage plant only after pressure is reduced to zero. vi. During autofrettage if any abnormal expansion is noticed, the pressurization is to be stopped immediately. vii. If irregular expansion is noticed at the section, the pressurization is required to be stopped before reaching MAP. viii. If bending is noticed, the pressurization is to be stopped before reaching MAP. ix. External dimensions of the barrel are to be measured before dismounting the barrel from the autofrettage frame unit.

13.7 Conclusions It is very important for engineering students to know about the process like autofrettage, which is widely practiced in industries for strengthening pressure vessels by inducing compressive residual stresses at and around the inner side of the vessel. Keeping this in view, in this chapter, the autofrettage process is introduced in a simple

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way. Moreover, a mathematical analysis of hydraulic autofrettage is briefly presented considering elastic-perfectly plastic material behavior and Tresca yield criterion. It is desirable for students to know the basic principles of the process and equations for the purpose of analysis. Nevertheless, they should also be aware of the engineering practices. Thus, in the present consideration, more emphasis is given on the practical aspects of the process. As an example, the process of hydraulic autofrettage is explained from the practical point of view of autofrettage a real gun barrel. The critical issues and challenges associated with the entire autofrettage process are also highlighted. The successful autofrettage of a gun barrel depends on several crucial factors such as the selection of autofrettage fluid for pressurization, preparation of mandrel and sealing system, bore surface preparation, application of autofrettage pressure, material properties of the barrel, difference in ultimate strength, and 0.2% proof stress of the material. The role of all such factors is discussed briefly addressing associated critical issues that need to be taken care of during autofrettage. After autofrettage, the need for low-temperature treatment of the barrel is also discussed. Moreover, the abnormalities and causes of the failure of the barrel during autofrettage are also addressed. Understanding the aforementioned critical issues is very important for an autofrettage experimentalist for the successful completion of the entire operation of the process. At the same time, one must follow certain safety measures during the entire operation of the process, which is also discussed in this chapter. The chapter will provide some insight to the senior undergraduate and postgraduate students how autofrettage is practiced in industries for strengthening thick-walled cylinders. Even the practicing scientists and engineers will find certain minute details of the process, which need attention during its operation. It is recommended to include the detailed analysis of autofrettage as an example of stress analysis in the courses like mechanics of solids or theory of elasticity and plasticity for the purpose of students learning.

References 1. Dixit, U. S., Kamal, S. M., & Shufen, R. (2020). Autofrettage processes: Technology and modeling. CRC Press. 2. Shufen, R., & Dixit, U. S. (2018). A review of theoretical and experimental research on various autofrettage processes. ASME. Journal of Pressure Vessel Technology, 140(5), 050802. 3. Jacob, L. (1907). La Résistance et L’équilibre Elastique des Tubes Frettés. Mémoire de L’artillerie Navale, 1(5), 43–155. (in French). 4. Davidson, T. E., Barton, C. S., Reiner, A. N., & Kendall, D. P. (1962). New approach to the autofrettage of high-strength cylinders. Experimental Mechanics, 2, 33–40. 5. Ezra, A., Glick, H., Howell, W., & Kaplan, M. (1973). Method and apparatus for explosive autofrettage. U.S. Patent No. 3,751,954. 6. Kamal, S. M., & Dixit, U. S. (2015). Feasibility study of thermal autofrettage of thick-walled cylinders. ASME Journal of Pressure Vessel Technology, 137(6), 061207–1−061207–18 7. Kamal, S. M., Borsaikia, A. C., & Dixit, U. S. (2016). Experimental assessment of residual stresses induced by the thermal autofrettage of thick-walled cylinders. The Journal of Strain Analysis for Engineering Design, 51(2), 144–160. 8. Zare, H. R., & Darijani, H. (2016). A novel autofrettage method for strengthening and design of thick-walled cylinders. Materials and Design, 105, 366–374.

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9. Kamal, S. M., Perl, M., & Bharali, D. (2019). Generalized plane strain study of rotational autofrettage of thick-walled cylinders- Part I: Theoretical analysis. ASME Journal of Pressure Vessel Technology, 141(5), 051201–1–051201–11. 10. Roy, A. K., Kulkarni, R., & Madas, S. (2018, June 8–9). A hydraulic autofrettage process of large calibre gun barrel. National conference on advances in armament technology. 11. Moss, L.T.J. (1958). The design of gun barrels, A description of the working method, Part 2: Design of Monobloc autofrettaged barrel. ARDE Report. 12. Macrae, A.E. (1930). Over strain of metals and its application to autofrettage process of cylinder and gun construction, His Majesty’s Stationary Office. 13. Inspection instruction ‘Autofrettage’ issued by inspectorate of armaments, Woolwich. (1955). 14. Manning, W.R.D., & Labrow, S. (1971). High pressure engineering. Leonard Hill.

Mr. A. K. Roy is working at Armament Research and Development Establishment, DRDO, Pune, India as Scientist F and heading the Ordnance Group (ATAGS). He obtained his M.Tech from IIT Bombay and currently pursuing Ph.D. from IIT Jammu in the area of thermal autofrettage. His areas of research include autofrettage of the gun barrel, surface engineering, high strength and high toughness clean steel, high pressure obturation mechanism and Adaptive Recoil systems. Dr. Seikh Mustafa Kamal is working as an Assistant Professor in the Department of Mechanical Engineering, Tezpur University, India. He received his Ph.D. in Mechanical Engineering from IIT Guwahati and B.E. in Mechanical Engineering from Jorhat Engineering College, Jorhat, Assam. His research interest includes stress analysis, plasticity, autofrettage, theoretical and experimental residual stresses, computational solid mechanics, finite element method, fatigue, and fracture processes in thick-walled autofrettaged cylinders. He has published several articles in international journals and conferences. Dr. R. U. Patil is working as an assistant professor in the Department of Mechanical Engineering, IIT Jammu. He obtained his Ph.D. and M. Tech from IIT Roorkee. His research interest includes XFEM, phase field method, multi-scale method, machine design, mechanics of solids, theory of machines, finite element method. He has published several articles in international journals and conferences. Dr. V. V. Rao is working as Professor of Practice in the Department of Aerospace Engineering, IIT Bombay. Formerly he was the director at Armament Research and Development Establishment, DRDO, Pune, India. He also served ISRO for a period of 10 years. He is the recipient of ISRO Chairman award for PSLV in 1996, DRDO Path Breaking Research awards for Agni-3 in 2007, Best Ph.D. Thesis award by Indian Welding Society in 2010.

Chapter 14

Biointerface Phenomena in Biological Science and Bioengineering: Importance of Engineering Courses Rushikesh Fopase, Aquib Jawed, and Lalit M. Pandey

14.1 Introduction Interfacial interactions in biological systems, i.e. biomolecule-biomolecule, cellbiomolecule, cell–cell or body fluids–foreign materials, refer to biointerfacial interactions. The biological systems experience mainly three interfaces: liquid–liquid, solid–liquid and liquid–air. These interfacial interactions are regulated by different intermolecular forces such as coulomb, entropic and quantum mechanical forces. The driving forces for these interactions include chemical, electrical and gravitational potentials [1]. The resulting interaction energy is related to different physical and chemical properties like surface tension, solubility and rheology. The role of biointerface appears in various branches of biosciences and bioengineering like biochemistry, microbiology, genomics, proteomics, cellular biology, biomaterials, biosensors, drug delivery and tissue engineering [2–5]. The principles of colloids and interface sciences and surface and interface sciences are explored to understand underlying biointerfacial behaviour in these biological processes. A few examples in biological sciences include self-assembly, micelles, bilayers and vesicles [6, 7]. These structures are formed a minimum value of Gibbs free energy (ΔG). Protein folding, unfolding and aggregation are regulated by different kinds of intramolecular and intermolecular interactions. The difference in ΔG between a native folded and unfolded protein lies in the range of 3–5 kJ/mol [8]. Various bioengineering applications like biomaterials, biosensors, drug delivery and tissue engineering involve biointerfaces [9]. Absorption of proteins, cell-surface interactions (cell adhesion) and biofilm formation is a few key steps during these applications. These interactions are regulated by surface wettability, surface charge, roughness (morphology) and surface chemistry [3, 10, 11]. This allows the design of R. Fopase · A. Jawed · L. M. Pandey (B) Bio-Interface and Environmental Engineering Lab, Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati, Assam 781039, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_14

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engineered surfaces for better/desired biointerfacial interactions. For example, the formation of self-assembled monolayers has been found to tune the surface chemistry and wettability, which in turn regulated the protein adsorption and cell adhesion. The coating of different biocompatible materials like bioceramics, biopolymers and biomacromolecules has also been explored to design biomaterial implants [12]. This chapter mainly focuses on the biointerfacial aspects of a few selected Biological Science and Bioengineering phenomena. It highlights the key interfacial properties which affect the particular biological interaction. Theoretical concepts of interaction energies have been discussed. The role of biointerface engineering in tuning the biointerfacial interactions for different biomedical applications like the design of biocompatible surfaces, biosensors, drug delivery, nanomedicine and tissue engineering has been outlined. Basic principles of engineering courses needed to understand biointerfacial interactions are discussed.

14.2 Thermodynamics of Biointerfacial Aspects Interfacial phenomena are correlated to the different intermolecular forces or interaction energy. Based on physical and chemical origin, the intermolecular forces are classified as coulomb, entropic and quantum mechanical forces. Considering the complex nature of biological systems, many intermolecular forces work simultaneously. The resultant interaction energy is related to different interfacial aspects like surface energy, wettability, surface charge and self-assembly. These interfacial aspects are linked with the thermodynamic properties of a system. The first law of thermodynamics can (Σ ) be extended to incorporate other works like μi dn i and electrical (ψdQ) apart from mechanical interfacial (γ dA), chemical work (dW ), which is expressed as dU = dQ + dW dU = T dS − PdV + γ dA +

Σ

(14.1) μi dn i + ψdQ

(14.2)

Here, U, q and W refer to the internal energy, heat and mechanical work. P and V denote pressure and volume, respectively. A is the interfacial area, and γ is the interfacial energy. Q and ψ refer to electric charge and potential, respectively. μi is the chemical potential, and ni denotes the number of moles of component i. dW is defined as −PdV . The heat q is related to irreversible change in entropy (dS) using the second law of thermodynamics as dq = T dS. Further, internal energy is related to enthalpy (H) and Gibbs free energy (G) as follows: H = U + PV

(14.3)

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dH = dU + PdV + V dP

(14.4)

G = H −TS

(14.5)

dG = dH − T dS − SdT

(14.6)

The corresponding integration may yield dH = T dS + V d p + γ d A + ψd Q +

Σ

μi dn i

(14.7)

i

dG = −SdT + V d p + γ d A + ψd Q +

Σ

μi dn i

(14.8)

i

Using the Eqs. (14.2), (14.7) and (14.8), the surface energy (γ ), chemical potential (μi ) and electric potential (ψ) are related to the thermodynamic properties like U, H and G. For example, γ is defined as the change in the free energy for a unit change in the interfacial area at the constant T, V, Q and n i ; i.e. ( Surface energy/tension γ =

δG δA

) (14.9) T ,V ,Q,n i

Similarly, μi and ψ are correlated with the free energy as ) δG δn i T,P,A,Q ) ( δG Electric potential ψ = δ Q T,P, A,ni (

Chemical potential μi =

(14.10) (14.11)

14.3 Biointerfacial Phenomena in Biological Sciences This section highlights the biointerfaces in the biological sciences, including selfassemblies, protein folding and aggregation.

14.3.1 Molecular Self-Assembly In the biological system, biointerfacial science plays a highly influential role in maintaining stability and functionality. Biological systems contain amphiphilic molecules

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which interact with each other and form various thermodynamically stable assemblies. The formation of self-assembly is carried out at the thermodynamic equilibrium of the system, which leads to the formation of aggregate structures in the solution. The required chemical potential of these involved molecules needs to be the same, which can be given as [13] μ = μN =

μ0N

( ) XN kT log = Constant, + N N

N = 1, 2, 3 . . .

(14.12)

where μ N is the mean chemical potential of the molecules with the aggregation number N, μ0N is the standard part of the chemical potential of aggregate N, X N is the concentration of the molecules in the aggregate N. For N = 1, μ1 and X 1 correspond to monomers in the solution. The aggregate formation occurs when the aggregated and dispersed molecules have different cohesive energies. When the molecules in the aggregates experience the same interaction with their surrounding, the value of μ0N will be constant as X N = N X 1N for μ01 = μ02 = μ03 = . . . = μ0N

(14.13)

As X 1 < 1, so X N ≪ X 1 and most of the molecules will be in monomers. The value of μ0N increases with increase in N, which may result in the formation of larger aggregates.

14.3.2 Formation of Micelles The formation of micelles occurs at the critical micelle concentration (CMC). Selfassembly occurs at a particular concentration of the monomers, leading to the formation of aggregates. In the biological system, amphiphilic structures mostly show soft or fluid properties with constant thermal motion. The intermolecular interactions between these molecules lead to the aggregate. The micelles can be of spherical, nonspherical or cylindrical shape. The formation of spherical micelles requires optimal surface area a0 sufficiently large and hydrocarbon volume v small enough so that the micelle radius should not exceed the critical chain length lc . The mean aggregation number M for micellar radius R is given as M=

4π R 2 4π R 3 = a0 3v

(14.14)

3v a0

(14.15)

Thus, R=

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If l c > R, then, v 1 < a0 l c 3

(14.16)

Thus, the amphiphiles form spherical micelles with the given radius R. The micelle size is independent of surfactant concentration above the CMC.

14.3.3 Bilayers The amphiphiles with small headgroup area a0 of bulky chains form bilayers, wherein headgroups fit into micelle structure. For the bilayer formations, the value of a0vlc is approximately equal to 1 for headgroup area a0 and chain length l c (Eq. 14.16). Biological membranes are typically composed of the dual chained phospho or glyoco lipid bilayers that function for motility, food entrapment, transportation and various cellular processes. Phosphatidylcholine and phosphatidylethanolamine are the common phospholipids in animal cells, whilst glycolipids digalactosyl diglyceride and monogalactosyl diglyceride are common for plant cells. These lipids have a very low CMC value to maintain the intact membrane. Also, these membranes stay in a fluid state at physiological temperature. The membrane lipids bilayers allow the incorporation of the different proteins within the layers whilst remaining in the curvature. The typical interaction of these lipids is non-specific, although the specific interactions may occur through the ionic interactions. The electrostatic interactions cause a change in the packing geometry and the structure of the lipids. The unstressed membrane bilayers interact through the van der Waals forces. Also, repulsion and hydrophobic attractive forces act for the interactions between the bilayers. The shortrange repulsion forces do not allow the interacting layers to come together. Besides this, the bilayer membrane interacts through the biospecific interactions involving complementary, ligand-receptor and site-specific interactions.

14.3.4 Vesicles In some instances, the lipid bilayer forms a closed spherical structure instead of forming planar bilayers. The entropically unfavoured edges are eliminated at finite entropically favoured aggregation numbers. Thus, the formation of vesicles is preferred till the curved bilayers maintain their areas at optimum value. The ratio v is less than 1 to form the vesicles. a0 l c

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14.3.5 Protein Folding Being a building block of life, proteins play a crucial role in almost all biological processes. The interactions of proteins with the various biomolecules occur through various intermolecular forces at the interface, and thus, the study of these biointerfacial interactions is essential. The protein functionality is structure-dependent, and thus, proper folding of the polypeptide chain of amino acids is crucial for the regular functioning of biological systems. Protein folding requires the sum of enthalpies and entropies of factors affecting the stability of the folded structure and overweighing the conformational entropy opposing the folded state. The Gibbs free energy is related to the changes in the enthalpies and entropies as ΔG = ΔH − T ΔS. The native folded (equilibrium) structure corresponds to the minimum free energy state. The process evades the Gibbs energy barriers and kinetic traps and proceeds along the narrow paths. The biological systems have well-defined machineries to achieve the proper folding of proteins. For example, molecular chaperones act as guiding molecules during the folding process by binding to certain sites to avoid misfolding or undesired interactions of peptide chains [7]. There are several models conceptualized based on various approaches to explain protein folding. The framework model suggests the involvement of local interaction leading to the formation of secondary structures. Stable tertiary structures were obtained following the random collision-diffusion of the secondary structures. Another mechanism of hydrophobic collapses suggests the beginning of protein folding through entropy-driven clustering of the hydrophobic amino acids, which leads to secondary structures and thus the tertiary structures [14]. The recently proposed mechanism is the energy landscape model, which postulates that the driving force leads to energetically downhill folding of the protein and thus shrinking proteins to the conformational extent [15]. Protein folding is a complex process, and various intramolecular and intermolecular forces support the folded structure. The major forces involve in the structure stability which are hydrophobic interactions and hydrogen bonds. The folded protein structure is stabilized by intramolecular bonds involving hydrogen, sulphide and hydrophobic interactions. The secondary structure of proteins (α-helix and β-sheets) plays a role in their structure and functions. After emerging from the ribosomes, protein gets folded to its native state, and over its lifetime, they unfold and refold. The folding process is coupled with the various biological processes such as transportation, cell growth and proliferation. The functionality of the protein depends on its sequence, and thus its misfolding results in various conformational diseases due to amyloid formations [16].

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14.3.6 Protein Unfolding and Aggregation The denaturation and unfolding of protein may occur due to various physicochemical factors, including shear, thermal fluctuations, change in the ionic strength and molecular crowding [17]. The surrounding environment of the protein affects the protein stability and may lead to unfolding. In addition, during the adsorption of proteins on a surface, the proteins tend to reorient, which causes conformational changes. These changes expose hydrophobic core groups and result in the formation of protein multilayers that act as nuclei, a starting point for aggregation. The aggregation can be reversible or irreversible. The unfolding of protein proceeds from the native structure to dimers and oligomers, followed by the insoluble and soluble aggregates [17]. The higher-order structures like oligomers and fibrils are rich in βsheets. The aggregated structures are functionally inactive and may cause problems with regular biochemical processes. The amyloid protein aggregations lead to the diseases like Parkinson’s, Huntington’s and diabetes like diseases [8].

14.3.6.1

Kinetics of Aggregation

The protein molecules colloid to form nuclei. The growth of nuclei continues with the incoming protein molecules and leads to fibrils at the surface [18]. This process can be explained by a simple theory based on the number of molecules. For example, when two single particles collide and form a doublet, this doublet attaches to another doublet forming quadruplets, leading to macroscopic aggregation formation. Hence, the number of particles in bulk decreases with the increase in aggregates. Thus aggregation is explained by the second-order kinetics as −

dN = kN2 dt

(14.17)

where k is the rate constant of the aggregation process. Integrating this equation explains the kinetics of the aggregation process as follows: Nt =

N0 1 + N0 kt

(14.18)

The half time of aggregation can be given as t1/2 =

1 k N0

(14.19)

Equation (14.19) confirms that colloidal dispersion stability is inversely proportional to the initial particle concentration. Further, for two identical spherical particles (radius a), the rate constant of aggregation (k) can be related to the diffusion constant (D) as k = 8π Da. The diffusivity is directly proportional to the thermal energy and

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inversely related to the solution viscosity as D = k B T /6π μa. Here, k B is the Boltzmann constant, and μ is the viscosity of the medium. This leads to the following equation k=

4k B T 3μ

(14.20)

which suggests that the rate of aggregation is inversely proportional to the medium viscosity. In recent studies, the aggregation rates of proteins (Aβ peptide and bovine serum albumin) were found to decrease with an increase in the solution viscosity [8, 18].

14.4 Biointerfacial Phenomena in Bioengineering This section highlights the biointerfacial interactions in a few bioengineering applications like implant biomaterials, biosensors, drug delivery, nanomedicine and tissue engineering.

14.4.1 Implant Biomaterials Biomaterials are the components of medical devices that come into direct contact with the human body for diagnostic and therapeutic purposes. When a foreign molecule encounters biological fluid, the subsequent biointerfacial interactions take place in the following order according to the diffusivity of the components of body fluids (water, macromolecules and cells) [19]. (a) Surface-water interactions (b) Surface-macromolecules, i.e. protein interactions (c) Cell-surface interactions. These interactions are regulated by the surface chemistry, wettability, surface charge and roughness, as shown in Fig. 14.1. The surface-water interactions depend on the surface wettability, which is determined by the contact angle (θ ). A hydrophobic surface (θ > 90°) exhibits non-wetting behaviour, whilst hydrophilic surface (θ < 90°) is wetted by water [20]. The resultant contact angle is a function of the surface energy of the surface (γ SV ), surface tension of liquid (γ L V ) and interfacial tension between surface-liquid (γ SL ). The Young’s equation [13] relates the interfacial tension with contact angle as depicted in Fig. 14.2 and represented by cosθ =

γ SV − γ SL γL V

(14.21)

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Fig. 14.1 Factors affecting the biointerfacial interactions between biomaterials and body fluids

Further, the surface roughness affects the wettability of a surface as described by the Wenzel equation: cosθr ough = r f cosθtr ue . Here, r f is the roughness factor and defined as the ratio of actual to the projected surface area (r f = Actual surface area/Project surface area). For a rough surface, the value of r f is greater than 1.0. The next step includes protein-surface interactions, which are vital in biomedical applications involving biomaterials, implants and drug delivery systems [21]. The adsorption of protein from the solution on a surface is a two-step process, as shown

Vapour

LV

Liquid SL

SV

Surface Fig. 14.2 Schematic representation of contact angle between surface and liquid

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Fig. 14.3 Modelling of protein adsorption on the surface depicting two steps: attachment followed by reorientation

in Fig. 14.3 [22]. In the first step, protein molecules from the bulk solution come to the boundary layer at the interface. At the surface, a thin layer called the surface layer is formed, which thickness equals the largest dimension of the molecule attached. Protein molecules get reversibly attached to the surface, referred as (P1 S)I . In the second step, the protein molecules reorient themselves to achieve the most stable state with the maximum coverage on the surface, referred as (P1 S)II . The events occurring at the interface during the protein adsorption are explained by [23]. k1 P1 + S ↔ (P1 S)I k2

(14.22)

k3 (P1 S)1 + cS ↔ (P1 S)II k4

(14.23)

where k 1 is the rate of protein adsorption, and k 2 is the rate of dissociation from the surface. k 1 depends on the diffusivity of protein molecules and is related to film mass transfer coefficient. k 3 and k 4 are the rate constants during the reorientation or rearrangement process. The protein forms (P1 S 1 )I and (P1 S 1 )II which occupy the S area and (1 + cS) area per molecule, respectively, and c is a constant. The surface-protein interaction is a complex process that involves multiple intermolecular forces due to the various polar, non-polar and charged moieties of a protein. Thus, surface chemistry, surface charge and hydrophobicity control the proteinsurface interactions. Generally, a hydrophobic surface favours the adsorption of proteins [24–26]. An electrical double layer is formed on the outermost surface of the biomaterials depending on the surface charge, which includes the electrostatic interactions [11]. The interactions occurring at the surface result in conformational changes in the adsorbed protein molecules. The adsorption may be reversible or irreversible [27]. The irreversible adsorption of protein causes functional loss and biofouling and may lead to the failure of implants. Further, the adsorbed protein layers reportedly possess viscoelastic behaviour, which is explained by the Voigt model [28]. The model considers the viscous damper and elastic spring connected in parallel. For the applied shear stress σ xy on the layer of protein adsorbed on the surface, the resistance of the spring (η) and the viscosity

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of dashpot (μ) is related as follows: σx y = η

δvx (y, t) δu x (y, t) +μ δy δy

(14.24)

where ux and vx are the displacement in the x-direction and corresponding velocity, respectively. The viscoelasticity of the adsorbed protein can be determined using the quartz crystal microbalance (QCM) [22]. The viscoelastic nature of the adsorbed protein layer is an important consideration from the biological perspective [29]. The adsorbed layer displays varying dissipation energy. Higher dissipation energy corresponds to the soft layer of adsorbed proteins, whilst a lower value of dissipation energy refers to the formation of a rigid layer [24, 30]. The subsequent step after the surface-protein interactions is cell-surface interactions, which are majorly regulated by the kind of surface-protein interactions. Cell adhesion is the most common phenomenon on the surface of biomaterials. Adhesion of the cells over any surface can be modelled theoretically as expressed as [3] ka N B k f NI + S ↔ NS − → kd

(14.25)

where k f is the film mass transfer coefficient, k a is the rate constant for cell adhesion, and k d is the rate constant of cell detachment. During the adhesion process, the N number of cells present in bulk suspension (B), interface (I) and the surface (S). The surface energy is the critical factor in cellular adhesion and spreading. The higher surface energy enhances the cell spreading [31]. An increase in the hydrophilicity of the surface increases the surface energy, and hence, the surface favours cell adhesion. Higher surface energy surfaces were found to have increased human cells (fibroblastic and endothelial) attachment [32, 33]. On the other hand, hydrophobic surfaces support better protein adsorption [26]. Thus, hybrid or mixed surfaces with moderate wettability have been designed to facilitate protein-surface as well as cell-surface interactions [24, 34]. Figure 14.4 illustrates the favourable adhesion of cells on the surface with moderate wettability [3]. Various self-assembled monolayers (SAMs) have been explored to tune the surface wettability and design biocompatible surfaces [3, 26, 34]. In another approach, the coating of biocompatible materials like bioceramics, e.g. hydroxyapatite, has been applied on the metallic implant surfaces to improve the biointerfacial interactions [35–38].

14.4.2 Biosensors Biosensors are the formulate (Fig. 14.5) for the detection of a concerned substance through surface-biomolecular interactions. The measured interactions are further transmitted to a transducer and amplified, followed by a display device. The major

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Fig. 14.4 Effect of surface hydrophobicity in cell adhesion over Ti6Al4V surfaces. Adapted from Ref. [3]

hurdle for developing a biosensor is to construct of steady arrangement for specific elemental recognition with the maximum sensitivity to detect biological compounds [39]. This problem can be tackled by tuning the surface chemistry at the biointerface level. The optimum performance of a biosensor is the ability to detect/measure a noticeable signal at the biointerface when a substance of concerned interest is present. In this view, the precise surface topography design was found to enhance the surface area, which alters the physio-chemical behaviour of the substrate surface and immobilized biomolecules for achieving an optimum performance [2]. A recent study by Dutta et al. revealed that controlling the roughness factor of disk-shaped gold electrodes provided a repeatable surface for detecting C-reactive protein (CRP). The surface roughness value of less than 40 nm showed a sound reversible electrochemical activity for gold electrodes to detect the CRP [40]. Also, recognizing elements like enzymes and antibodies (Fig. 14.5) responsible for interacting with interested substances plays a crucial role in the optimum performance of a biosensor. The immobilized molecules in a biointerface must retain their biological activity and the antifouling properties of a surface, which resist the non-specific interactions with the analyte sample [41]. In this regard, self-assembled monolayers (SAMs) were found to be an efficient candidate for the modification of interfacial properties of substrate surfaces [6].

Fig. 14.5 Biosensor configuration with biorecognition, interface and transduction elements. Adapted from [41]

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14.4.3 Drug Delivery The drug delivery system includes micro and nanoscale delivery systems of the drugs for enhancing the bio-distribution, control release and targeting to the site of interest [42]. The efficiencies of the drug delivery system were enhanced through the attachment of ligands on the synthesized particle surface [4]. This attachment helps to achieve the targeted drug delivery; however, there are certain biological barriers in the immune system that must first be overcome for effective drug transport [43]. The biointerface engineering of the drug carrier helps to overcome the biological barriers [9]. The biointerface of a material depends upon its structural features like morphology, size and rigidity. For example, the morphology of the particles regulates their travel in the bloodstream to form protein corona [44]. The shape of the particles determines the contact area between the drug carrier and the biological system. Also, the material stiffness affects its response with the immune cells (macrophages) in the body [45]. A drug delivery system should consider the surface chemistry of both drug carriers and biological barriers to maintain desired intermolecular, e.g. electrostatic interactions. The proper engineering of a surface through ligands attachment over the particles was employed for enhanced cellular activities [4]. The surface chemistry alteration can be done by varying the core material and surface modification after the fabrication of the drug carrier [46]. Likewise, the drug carrier’s core should be hydrophobic, whilst the outer shell should be hydrophilic to interact with the hydrophilic body fluid. The post-fabrication modification of the synthesized particles was done through conjugation chemistry by attaching interested chemical groups. The thiol mediated silanization techniques were employed for the chemical modification of the surface [47]. Another approach of layer-by-layer assembly for surface modification was employed by utilizing the surface electrostatic interactions and hydrogen bonds to deposit the interested polymers over the surface [48].

14.4.4 Nanomedicine The application of nanotechnology towards therapeutics is termed as nanomedicine. The nanomaterials in the dimension range of 1–100 nm possess unique properties required for various biological applications [49, 50]. The concept of biointerface plays a crucial role in the field of nanomedicine. The interaction between nanoparticles and the surrounding body fluids occurred at a nano-biointerface. The behaviour and efficacy of nanomedicine pharmaceuticals at the nano-biointerface were influenced by various factors such as size, shape, surface area, surface charge, porosity and hydrophobicity [51]. These factors affect the intermolecular forces and thus tune the interfacial interactions. The size and shape of the nanoparticles affect their degree of penetration through vascular obstacles [52]. The surface charge on a biointerface of nanomedicine

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and pathogens affects the antibacterial performance [53]. The hydrophobic forces at the nano-biointerface were found to enhance the adsorption of cell adhesive proteins (CAP) over the synthesized nanoparticles [54]. Further, the interaction between proteins of hydrophobic nature and single-walled carbon nanotubes (SWCNTs) served as a driving force for CAP towards the surface of SWCNTs [55].

14.4.5 Tissue Engineering Tissue engineering is an interdisciplinary field that combines engineering and life science ideas to create biological alternatives that restore and preserve health or enhance tissue function [56]. Biomaterials played an essential role in tissue engineering as they served as matrices for cellular ingrowth, proliferation and the development of new artificial tissue in three dimensions (scaffolds) [57]. Scaffolds play an important role in cell support, growth and the formation of extracellular matrices to facilitate the progress of tissues [10]. The various design parameters of a scaffold for its proper functioning include shape, size, porosity, surface area, mechanical strength, biocompatibility and degradation rate [58]. When a biomaterial comes in contact with a body fluid, microbial contamination takes place over its surface, which creates a problem that leads to the biofilm formation and failure of implants [59]. Therefore, the successful functioning of the implants mainly depends upon the biointerface between a biomaterial and the body fluid. In this direction, surface modification and antifouling coatings over the implant surfaces were found to be efficient in preventing the surfaces’ microbial invasion [12]. The nanocomposites also offer multifunctionality depending on their constituents. Hasan et al. [5] developed a scaffold (SCA) of chitosan and carboxymethyl cellulose with varying nanocomposite (0–5 wt%) of carboxylated cellulose nanowhiskerssilver nanoparticles for enhanced antimicrobial activity and cell adhesion. The samples SCA-2.5 and SCA-5 showed 100% antibacterial performance for E. coli and E. hirae strains, respectively. Also, the SCA-2.5 sample showed the attachment and penetration of MG63 cells inside the prepared scaffold after 24 h of incubation. In a recent study, Saxena et al. [60] synthesized a scaffold of Fe(III) doped ZnO integrated hydroxyapatite nanoparticles (ZFHAp) (0–5 wt %) and chitosan for bone tissue engineering applications. The prepared sample of ZFHAp-5 showed enhanced antibacterial and cell proliferation activities [60]. In summary, the above biointerfacial phenomena in biological science and bioengineering apply the theory of engineering courses. Flow behaviour and rheology of body fluids follow the theory of fluid mechanics. Thermodynamics explains the self-assembly of biomacromolecules. Transport through the membrane, protein adsorption and protein aggregation follows the principles of mass transfer and reaction engineering. Wetting and adhesion processes apply the theory of colloids and surface science. Viscoelastic properties and mechanical strength of biomaterials follow the concepts of applied mechanics. In fact, many scientists/researchers

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working in the domain of biological science and bioengineering are having nonbiology backgrounds. Therefore, the above engineering courses are essential to understand biointerfacial interactions in a better manner.

14.5 Conclusions The concept of biointerface phenomena in various biological science and bioengineering was depicted in the current chapter. The thermodynamic aspect of biointerfacial phenomena in terms of surface tension (γ ), chemical potential (μi ) and electrical potential (ψ) was depicted. The interfacial forces play a key role in various biochemical processes such as self-assembly, protein folding and stability. The variation in the system energies due to environmental factors such as temperature, pH, ionic strength, shear and surface adsorption alters the interfacial forces, which cause the unfolding of the protein. The protein adsorption model depicted the role of the interfacial layer during the adsorption process. The unfolding of proteins leads to the formation of nuclei over the surface, which may lead to the formation of aggregates through the various intermediates. The protein adsorption and cell adhesion are regulated by surface chemistry, wettability, surface charge and roughness (interfacial area). The formation of specific self-assembly of biomolecules depends on the surface area, volume and chain length. From a bioengineering perspective, the interfacial phenomena govern the various biological-surface interactions for optimum performance of therapeutic devices. Like, the performance of a biosensor can be enhanced by tuning the surface properties of the biorecognition element. The biointerface parameters such as surface tension, charge, roughness and wettability affect the interactions of biomaterial with the body fluids. Furthermore, the attachment of surface ligands enhances the target efficiencies in the case of drug delivery. Various surface properties of nanoparticles, i.e. size, shape, surface area, surface charge, porosity and hydrophobicity, play a key role in nanomedicine. Moreover, in tissue engineering, the role of biointerface tissue engineering includes enhancing cell attachment and growth along with restricting the undesired interactions like bacterial contamination. Summarily, this chapter highlights the biointerfaces in biological science and bioengineering. The theories and concepts of engineering subjects like thermodynamics, fluid mechanics, mass transfer, reaction engineering, applied mechanics and colloids and surface science applied in biointerfacial phenomena have been summarized. Therefore, teaching of these courses is essential to gain better insights into biointerfacial interactions in biological science and bioengineering. The understanding of biointerfacial phenomena may enable to engineer the biological systems.

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Glossary Amyloid: An aggregated form of proteins deposited in animal organs under some diseased conditions such as Alzheimer’s. Antibacterial agent: Any material that is mainly used against bacteria to either kill or suppress their growth. Bilayers: A two-layered membrane of phospholipid molecules, the primary component of the cell membrane. Bioceramics: A type of inorganic biomaterial used to heal or replace damaged bone tissues Biocompatibility: A property of material not to induce any immunological or toxicity to the living cells. Bioengineering: The use of ideas from biology, physics, arithmetic and engineering to identify and solve issues in biology, medicine and healthcare. Biofilm: The collection of surface-associated microbial cells encased in an extracellular polymeric material matrix. Biointerface: A region of contact between a biological system or biomolecules with another biological system or any other materials. Biointerfacial interactions: The interfacial interactions take place between any two phases in biological systems, i.e. interface between biomaterial and body fluid. Biological fluid: All the liquids in the body that help transfer nutrients or remove waste from cells. Biological science: Comprises all-natural science divisions that study diverse elements of living activities. Biomacromolecules: Large biological polymers made up of monomers such as nucleic acids, carbohydrates and proteins. Biomaterials: Any material showing no toxicity to the biological system and come into direct contact with the human body for diagnostic and therapeutic purposes. Biomedical Engineering: Engineering ideas and design concepts for medicine and biology to achieve the goal of healthcare. Biosensors: Formulate for the detection of a concerned substance through surfacebiomolecular interactions. Cell adhesion proteins: A group of cell-surface proteins responsible for the binding of cells with other cells or any external surface (foreign material). Cell proliferation: The process by which a cell divides and matures into two daughter cells. Cell spreading: A process of cells in suspension flattening out on a surface from their previously spherical shape. Cellular adhesion: A process by which cells communicate with one another and bind to one other via specialized cell-surface chemicals. Critical micellar concentration: A minimum concentration of surfactant required to form micelle structure.

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Drug delivery system: A system includes micro and nanoscale delivery vehicles for any drugs for enhancing the bio-distribution, control release and targeting to the site of interest. Fibrils: An assembled protein insoluble complex to form insoluble fibres leading to amyloid formation. Immune cells: Different types of white blood cells arise from stem cells in the bone marrow. Implants: A medical device that replaces or supports a lost biological structure and function. Micelles: A self-assembled colloidal dispersion of the amphiphilic molecules. Microbial invasion: The colonization of a resident community by a foreign microbial kind. Molecular chaperones: A group of proteins which help to proper folding of protein to be functional. Protein corona: A layer of proteins adsorbed on the nanoparticles or biomaterials from plasma and/or intracellular fluid. Ribosomes: A site of protein synthesis within the cell. Scaffolds: A tissue engineering supportive materials offering support or adhesion to the cells for growth and proliferation. Tissue engineering: An interdisciplinary field that combines engineering and life science ideas to create biological alternatives that restore and preserve health or enhance tissue function. Vesicles: A small lipid bilayer enclosed structures within the cells and responsible for cell buoyancy, transport and storage of biomolecules.

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Rushikesh Fopase is a research scholar in the Department of Biosciences and Bioengineeing, IIT Guwahati. Aquib Jawed is a research scholar in the Centre for the Environment, IIT Guwahati. Lalit M. Pandey is working as an Associate Professor in the Department of Biosciences and Bioengineeing, IIT Guwahati. He obtained his Ph.D. in Chemical Engineering from Indian Institute of Technology, Delhi. He was awarded IEI Young Engineers Award 2017–2018 in Environmental Engineering discipline by Institution of Engineers (India). He has published more than 100 research articles in journals and conferences in the area of surface and interfacial science, protein’s adsorption and aggregation, nanocomposites for biomedical applications and environmental biotechnology.

Chapter 15

Contact of a Cylindrical Shell with a Flat Frictionless Rigid Substrate Aishwarya Kasarla and Sovan Lal Das

Notations Symbol H R1 R2 R r E μ∗ ν ∗  θ1 − θ2 − θ3 {e r − eθ − e z } w v δr δθ , β2 θc

Description Thickness of the shell Inner radius of the shell Outer radius of the shell Middle surface radius of the shell Thickness coordinate, - H2 < r < H2 Young’s modulus of the shell material Modulus of rigidity of the shell material Poisson’s ratio of the shell material Local coordinates at any point on the middle surface of the shell Unit vectors along r, θ, and z directions at a point on the middle surface of the shell Radial displacement of any point on the middle surface of the shell Tangential displacement of any point on the middle surface of the shell Change in the length of the normal Rotation of the normal with respect to local z-axis, symbol δθ is used in the Cosserat theory while symbol β2 is used in the shear deformation and Flügge-Lur’e-Byrne theories. θ Coordinate of the last contact point.

Note: If there is any additional symbol used other than those included in the above list or if there is repeated use of any of the above symbols, then such symbols are explicitly described at that specific place in the following sections. A. Kasarla (B) · S. L. Das Physical and Chemical Biology Laboratory, Department of Mechanical Engineering, Indian Institute of Technology Palakkad, Palakkad 678623, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_15

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Stress resultant vectors obtained upon integrating threedimensional stress components. Intrinsic director moment obtained upon integrating threedimensional stress component. Couple stress resultant vectors obtained upon integrating moments due to three-dimensional stress components. Stress resultant Transverse shear stress resultant Moment resultant Contact patch length Applied load Contact pressure

15.1 Introduction Shell is a three-dimensional body consisting of two major surfaces and a lateral one with the thickness being very small compared to the other two typical dimensions. The shell can be assumed to be constructed by adding material above and below the middle surface. Therefore, the middle surface becomes the reference surface in the analysis of shells. Shells find their application in several fields due to their high strength to weight ratio, high stiffness, high degree of structural rigidity, high load carrying capacity, and lastly due to their attractive shapes [1]. Shells are used in structures like submarines, ships, aircraft, missiles, piping systems, arc domes, and many others [1]. In spite of its importance, the shell theory is often not properly treated in the courses on solid mechanics. Many engineering students find the shell theory quite complex due to the involvement of differential geometry and tensors. This chapter discusses a nonconventional approach of solving the shell problem in the framework of existing theories and the finite element method (FEM). It is envisaged that this chapter will help in a better understanding of the shell theory and will motivate further study in this direction. Shell theory is an area of structural mechanics which aims to describe the stresses and deformations due to external loading on the shell. The very first theory was Love’s theory for the bending of shells [1] based on classical linear elasticity. To simplify the strain–displacement relationships, Love applied Kirchhoff’s hypotheses which were actually for bending of plates. After this, many versions of this theory came with modifications mainly in the constitutive relations. However, none of them was able to describe the exact general behavior of the shell. About a hundred years ago, the E. and F. Cosserat brothers [2] published a monograph in which they additionally considered the couple stresses and the rotational degrees of freedom as independent variables [3, 4]. In this continuum, each material point is associated with ‘n’ vectors called the director vectors. These directors are allowed to rotate and stretch independently (the

15 Contact of a Cylindrical Shell with a Flat Frictionless Rigid Substrate

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idea that a body is a collection of not only points but also directions associated with the points was originally given by Duhem [5]). Because of this ability of director vectors to deform independently, the deformation of a material point in that particular direction can be accurately captured. The most important feature of their work was the involvement of couple stresses in the equilibrium equations. However, their work did not receive much attention until Ericksen and Truesdell [6] developed the exact theory for rods and shells using Cosserat’s approach. Following this, Cosserat’s approach soon found applications in shells, rods, and point theories. For shells, which are thin in one of their dimensions, to accurately capture the deformation of a material point in this (thickness) direction one director vector is associated at each point. Therefore, in the case of shells, the use of Cosserat’s approach allows us to study the physics of shells by considering all the six degrees of freedom at every point on the middle surface of the shell unlike the case with most other shell theories. As far as contact mechanics is concerned, there are well-established theories such as the Hertz theory (1882), the JKR theory (1971), and the DMT theory (1975) [7]. However, all these theories are for the contact between solids (geometrically thicker structures), having higher structural stiffness. As far as thin shells are concerned, these theories do not quite suit such structures. Also, in the literature many studies on contact involving thin shells encountered issues like obtaining shear stress discontinuity at the junction of the contact and free regions, obtaining a finite value of contact pressure at the edge of the contact area, obtaining a physically inconsistent distribution of contact pressure, etc., see for example work by Essenburg [8], Christopher and Essenburg [9], and by Kulkarni and Frederick [10], as a result of which most of these studies emphasized the importance of inclusion of transverse normal strain (that is the normal deformation through the thickness). However, very few studies are available which verify this fact. For example, Essenburg [11] studied the effect of transverse normal strain for the contact of an isotropic beam of rectangular cross-section with a smooth rigid surface. Gasmi et al. [12] extended the study to the contact of orthotropic beams. Naghdi and Rubin [13] solved the contact problem of an isotropic beam with a smooth rigid surface using the Cosserat rod theory and compared the results with three other constrained theories which exclude either transverse normal strain or transverse shear strains or both and concluded that the one which includes transverse normal strain outperforms all other constrained theories. El-Abbasi and Meguid [14] developed a variational inequality-based formulation for frictional contact of shell structures which included the transverse normal stress and strain and were thereby able to accurately solve the contact problems of shell structures. This work attempts to verify the importance of inclusion of transverse shear strains and transverse normal stress and strain in contact problems involving shells like structures (in a way we are following the same footsteps as Naghdi and Rubin [13] but for shells!). In this work, the contact problem is solved considering an additional condition on the shell that is the ‘impenetrability condition’. The shell will be restricted from moving further once it comes in contact with the rigid substrate. This causes the vertical displacement of the points within the contact to have some limited value. Also as the deformation proceeds, the shell is assumed to conform to the substrate geometry. The contact and free regions have been solved separately and then the

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appropriate continuity conditions for displacements and stresses at the intersection of the two regions are used. The contact problem is solved using the linear Cosserat shell theory [4], shear deformation theory [15], and Flügge-Lur’e-Byrne shell theory [15], and the results from all three theories are then compared with finite element simulation using ABAQUS. Contact being a nonlinear problem, it is expected that the Cosserat theory will perform better than the other two. The details are in subsequent sections. For our convenience, we will follow the rules regarding notations as stated below: • • • •

Greek indices will take values 1, 2 (e.g., α = 1, 2). Latin indices will take values 1, 2, and 3 (e.g., i = 1, 2, 3). All bold letters define vector or tensor quantities. All capital letters are for shell in reference configuration, whereas all small letters are used for quantities for shell in the deformed configuration.

15.2 The Contact Problem The contact problem considered is that of a cylindrical shell with a planar frictionless rigid substrate. Statement of the problem: A cylindrical shell, in contact with a smooth planar rigid substrate, is subjected to uniform line load F applied at the top as shown in Fig. 15.1. Let the cross-section of the shell lie in the x − y plane, the thickness of the shell be denoted by H , the shell middle surface radius be denoted by R, and the length be denoted by L. Let the length be sufficiently large such that the plane strain condition is applicable. Due to symmetry, only one-half of the shell is considered as shown in Fig. 15.2. Let R1 and R2 be the inner and outer radii of the shell, then: H = R2 − R1 and R =

R1 + R2 . 2

(15.2.1)

Fig. 15.1 Cylindrical shell, subjected to uniform line load F, is resting on a rigid substrate

15 Contact of a Cylindrical Shell with a Flat Frictionless Rigid Substrate

(i) Reference configuration of the shell

209

(ii) Deformed configuration of the shell

Fig. 15.2 Configurations of the shell

The shell material is assumed to be linearly elastic and let μ∗ and ν ∗ be the shear modulus and Poisson’s ratio of the shell, respectively. As already stated, the shell is assumed to conform to the substrate geometry (which is plane in our problem) during deformation. Therefore, the deformed configuration can be assumed to look something like Fig. 15.2 (ii). Let the contact pressure be denoted by q(θ ) whose distribution is not known to us.

15.2.1 Analysis Using Cosserat Shell Theory As already stated in the introduction, in this theory an additional vector is associated with each point on the middle surface, called the director vector, to accurately measure the deformation in the thickness direction. It is taken to be same as the normal at any point on the middle surface in the reference configuration, while its deformed form is unknown to us. The director vector can change in the length as well as rotate and thereby we are incorporating the transverse normal strain and transverse shear strains at a point on the middle surface. That is all the six degrees offreedom at a point on  the middle surface are considered. A local coordinate system θ 1 − θ 2 − θ 3 at any point on the middle surface is defined to be along {θ − z − R}, respectively (see Fig. 15.2(i)). For any point on the middle surface, let w, v, δr , and δθ be the radial deformation, tangential deformation, change in the length of the normal, and rotation of the normal about the tangent to the coordinate line θ 2 = z, respectively. Referring [4], the final equilibrium equations in free and contact regions are obtained as follows: In the free region, the equilibrium equations are

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t (1) ,1 = 0, (3) m(1) = 0. ,1 − t

(15.2.1.1)

In the contact region, the equilibrium equations are 

 H R+ (−q(θ )cosθ e r + q(θ )sinθ eθ ) + t (1) ,1 = 0, 2    H H (3) R+ = 0. (−q(θ )cosθ e r + q(θ )sinθ eθ ) + m(1) ,1 − t 2 2

(15.2.1.2)

Note: (),α , where α = 1,2, denotes the partial differentiation with respect to coordinate θ α . The stress vector (t (α) ) and couple stress vectors (m(α) and t (3) ) are resultants obtained upon integrating the three-dimensional stress components (see [4]) and they are expressed in terms of deformation quantities as          1 dw α+1 dv − v + δθ e r + 2μ∗ H w+ + αδr R dθ R dθ    3 ∗ 1 dv H μ dδθ − w+ eθ , δr + − 2 6R (1 − ν ∗ ) dθ R dθ    dv dδθ H 3 μ∗ 1 w+ eθ , δr + = − ∗ 6R(1 − ν ) dθ R dθ         dv 1 dw α ∗ ∗ w+ + (α + 1)δr e r + μ R H − v + δθ eθ , = 2μ R H R dθ R dθ (15.2.1.3)

t (1) = μ∗ H

m(1) t (3)

∗

ν where α = 1−2ν ∗. Note: Only those resultants, which appear in the equilibrium equations, are presented.

• The corresponding boundary conditions are as follows: – At θ = 0: v = 0, δθ = 0 , dw = 0. dθ – At θ = θc : w|contact = w|free , v|contact = v|free , δr |contact = δr |free ,

(15.2.1.4)

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211

δθ |contact = δθ |free , t1r |contact = t1r |free , t1θ |contact = t1θ |free , m 1θ |contact = m 1θ |free .

(15.2.1.5)

Note: It has been observed that the continuity of the intrinsic director couple stress (t (3) ) at θ = θc is automatically satisfied with the above conditions. – At θ = π: v = 0, dw = 0, dθ t1r = −

F . 2

(15.2.1.6)

• The scaling of deformation quantities and stress resultants is done as follows: – The dimensionless radial and tangential displacements, denoted by w and v, respectively, are defined as: w=

w v and v = . R R

– The dimensionless stress and couple stress resultant vectors are defined as:

.

˜t (2) ˜t (1) ˜ (1) m ˜t (2) ˜ (1) , = , m , tl tl = ∗ ∗ 2 μ R μ R μ∗ R 2 . ˜t (3) ˜ (2) m (3) = ∗ 3 , and ˜t tl = ∗ 2 . μ R μ R

˜t (1) tl = ˜ (2) m tl

– The dimensionless contact length, denoted by atl , is defined as: atl =

a . R

– The dimensionless contact pressure, denoted by qtl , is defined as: qtl (θ ) =

q(θ ) . μ∗

• Lastly, the applied load is scaled as: Ftl =

F . μ∗ R

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15.2.2 Analysis Using Shear Deformation Shell Theory In this theory, the transverse shear strains at any point on the middle surface of the shell are considered but the change in the length of the normal is neglected, thus each point on the middle surface will have five degrees of freedom (so from six DOF in the case of Cosserat theory, the change in lengthof the normal is neglected thus five  DOF). A local coordinate system θ 1 − θ 2 − θ 3 at any point on the middle surface is defined to be along {z − θ − R}, respectively. Let again w and v be the radial and tangential displacements at a point on the middle surface, respectively and β2 be the rotation of the normal about the tangent to the coordinate line θ 1 = z at a point on the middle surface (though earlier we had used θ 2 = z, it does not make any difference as long as we are alert about the choice of local coordinates!). This theory has the following assumptions [15]:

 • The shell is thin, such that Rr 2  1. This thinness assumption is not as strict

 as what is considered in the classical thin shell theory, which is Rr  1, where − H2 < r < H2 is the thickness coordinate. • The normal to the middle surface in the reference configuration will not necessarily remain normal to it in the deformed configuration that is the transverse shear strains are not necessarily zero. However, there will not be any change in its length. • The strain components are sufficiently small as a result of which linear elasticity is applicable. • The normal stress at any point on the middle surface is negligible as compared to the other components. Referring [15], the governing equilibrium equations in free and contact regions are obtained as follows: In the free region, the equilibrium equations are dNθθ + Q θ = 0, dθ dQ θ − Nθθ = 0, dθ dMθθ − R Q θ = 0. dθ

(15.2.2.1)

In the contact region, the equilibrium equations are

dMθθ dθ

  dNθθ H + Qθ + R 1 + q(θ )sinθ = 0, dθ 2R   dQ θ H − Nθθ − R 1 + q(θ )cosθ = 0, dθ 2R    H H − R Qθ + R 1+ q(θ )sinθ = 0. 2 2R

(15.2.2.2)

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213

The stress and moment resultants are expressed in terms of deformation quantities as    1 dv EH w H 2 dβ2 1 dv w , + − − − 1 − ν ∗2 R dθ R 12R 2 dθ R dθ R   1 dv w 1 dβ2 − 2 − 2 , Mθθ = D R dθ R dθ R   2 

 1 dw v 5 H (15.2.2.3) − + β Q θ = μ∗ H 1 − 2 , 6 28R 2 R dθ R Nθθ =

where D =

E H3 12(1−ν ∗2 )

is the bending rigidity of the shell.

• The corresponding boundary conditions are as follows: – At θ = 0: v = 0, β2 = 0.

(15.2.2.4)

Note: With these boundary conditions at θ = 0, it follows that w = 0 and w  (θ ) = 0 at θ = 0 from the impenetrability condition (it is defined at the end of this section). Thus, the shear deformation theory is automatically fixing the first contact point. – At θ = θc : w|contact = w|free , v|contact = v|free , β2 |contact = β2 |free , Nθθ |contact = Nθθ |free , Q θ |contact = Q θ |free , Mθθ |contact = Mθθ |free .

(15.2.2.5)

– At θ = π: v = 0, dw = 0, dθ Qθ = −

F . 2

(15.2.2.6)

• The scaling of deformation quantities and stress resultants is done as follows:

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The scaling of displacements, contact length, contact pressure, and applied load is same as described in the previous section of Cosserat theory, however, the stress and moment resultants are scaled as follows: Dimensionless stress vector, Dimensionless transverse stress vector, Dimensionless moment vector,

Nθθ , μ∗ R Qθ = ∗ , μ R Mθθ = ∗ 2. μ R

Nθθ tl = Q θ tl Mθθtl

15.2.3 Analysis Using Flügge-Lur’e-Byrne Shell Theory This theory is the same as the classical thin shell theory with the thinness assumption slightly modified, i.e., the transverse shear strains and transverse normal stress and strain are neglected, thus each point on the middle surface has only three degrees of freedom (these are the three translations), the rotations of the normal are no longer independent quantities and are functions of the three translations. The local coordinates definition and notations for the kinematic quantities are same as defined in the case of shear deformation theory. This theory has all the assumptions exactly same as those for the shear deformation theory but only the assumption regarding the deformation of normal is different and it is given as [15]: • The normal to the middle surface in the reference configuration remains normal to it in the deformed configuration also without any change in its length. Referring [15], the equilibrium equations in free and contact regions are obtained as follows: In the free region, the equilibrium equations are 1 d Mθθ d Nθθ + = 0, dθ R dθ 1 d 2 Mθθ − Nθθ = 0. R dθ 2

(15.2.3.1)

In the contact region, the equilibrium equations are 1 d Mθθ d Nθθ + + R(q(θ )sinθ ) = 0, dθ R dθ 1 d 2 Mθθ − Nθθ − R(q(θ )cosθ ) = 0, R dθ 2 where β2 =

v R

−

1 dw . R dθ

(15.2.3.2)

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215

• The boundary conditions for Flügge-Lur’e-Byrne theory are same as for the case of shear deformation theory at θ = θc and at θ = π. However, at θ = 0, the boundary conditions are w = 0, dw = 0. dθ

(15.2.3.3)

• The scaling of all the quantities is exactly same as defined in the case of shear deformation theory. One more additional equation is required in the contact region as there is an additional unknown quantity there that is the contact pressure. This additional equation will be obtained by equating the vertical displacement for any point in the contact region to the initial gap between that point and the rigid surface. That is the impenetrability condition for any point on the outermost surface of the shell, which lies within the contact region can be written as  wouter cosθ − vouter sinθ =

 H R+ (1 − cosθ ), 2

(15.2.3.4)

where wouter and vouter are the radial and tangential displacements for any point on the outer surface of the shell. The extra condition for contact length (a) can be obtained from the circumferential strain (θθ ) equation. The average circumferential strain at a point on the middle surface can be calculated as θθ =



1 dv R dθ

 +w .

(15.2.3.5)

The initial arc length of Rθc has become length a in the deformed configuration and thus the total circumferential strain for the last contact point can be written as θc

Total εθθ |θc = ∫ 0



1 dv R dθ

 + w dθ =

a−Rθc . Rθc

(15.2.3.6)

Note that the contact length is calculated from the middle surface and there can be a slight difference when it is calculated from the outer surface. The equilibrium equations, boundary conditions, impenetrability condition along with the total circumferential strain equation complete the contact problem formulation for all the three theories. Lastly, the equilibrium equations are made dimensionless with the use of scaled quantities defined for each of the theories and then the boundary value problem was solved in MATLAB using bvp4c solver with a relative tolerance of 1E-10. bvp4c solver is a finite difference collocation method and gives

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C 1 continuous solutions. The collocation polynomial is fourth-order and the selection of mesh and control of the error in each step are based on the residual of the continuous solution [16].

15.2.4 Finite Element Simulation A two-dimensional shell structure in contact with an analytical rigid surface is studied in the ABAQUS software. The frictionless contact problem is modeled with surfaceto-surface discretization with a finite sliding tracking approach and hard contact pressure over-closure. The shell is allowed to separate from the substrate during deformation. The shell is meshed with CPE8 elements, which are 8 noded plane strain quadratic full integration elements. The convergence study for dimensionless displacements (radial and tangential), contact pressure, and contact area (contact patch length) for HR = 0.05, 0.1, and 0.2 has been carried out and the results are as shown in Figs. 15.3, 15.4, and 15.5, respectively. It has been observed that the convergence of displacements and contact area is satisfactory for all three thickness values considered, however, for contact pressure, a high variation in the values has been observed for higher thickness values at coarser mesh. The variations reduce considerably as the mesh is refined and thus eventually show convergence. Still, a more detailed study of the convergence of contact pressure for thick shells needs to be done. One solution for this can be to go for a deformable rigid substrate but with very high stiffness. From the convergence study, it can be concluded that the contact pressure is highly sensitive to the thickness of the shell. A finite element size of 0.0025 (dimensionless) was finalized as there is no considerable change in the values of any of the four quantities (peak displacements, peak contact pressure, and contact area) when the mesh is made finer.

15.3 Results and Discussion For generating the results, the load value obtained from the Cosserat theory for a particular contact angle is given as an input to the other theories and ABAQUS.

15.3.1 Comparison Between Displacements The results for radial and tangential displacements when combined, the deformed shape of the shell can be obtained. Only the results for HR = 0.05 are presented here for three different load values, see Fig. 15.6. It is observed that, in the contact region, the displacements obtained from all three theories and FE simulation are exactly

15 Contact of a Cylindrical Shell with a Flat Frictionless Rigid Substrate

(i) Convergence study for dimensionless maximum radial displacement

217

(ii) Convergence study for dimensionless maximum tangential displacement

(iii) Convergence study for dimensionless (iv) Convergence study for dimensionless contact maximum contact pressure area Fig. 15.3 Mesh convergence study for

H R

= 0.05

same, whereas FE simulation predicts very high value of displacements in the free region than any other theory considered. For HR = 0.1 an HR = 0.2 the same behavior has been observed and thus they are not presented here. The reason for such high deformation in the free region in FE simulation is not clear to us at this point of time and thus further study is required to be done.

15.3.2 Comparison Between Contact Pressure Distribution In Figs. 15.7, 15.8, and 15.9, the contact pressure distribution for three different thickness to radius ratios at three different contact angles has been presented. The

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(i) Convergence study for dimensionless maximum radial displacement

(ii) Convergence study for dimensionless maximum tangential displacement

(iii) Convergence study for dimensionless (iv) Convergence study for dimensionless contact maximum contact pressure area

Fig. 15.4 Mesh convergence study for

H R

= 0.1

inset in all of them presents the contact pressure omitting the result from the FlüggeLur’e-Byrne theory so that the other results can be clearly seen. Note that since in the formulation, there is no restriction imposed on the contact pressure and also it has been assumed that the shell will conform to the rigid substrate during deformation, the negative contact pressure at any point will indicate the possibility of a loss of contact at that point. Referring Figs. 15.7 and 15.8, which are for HR = 0.05 and HR = 0.1, it has been observed that the contact pressure obtained from the Cosserat theory is in excellent agreement with that obtained from FE simulation for smaller values of the applied load. However, as the load increases, the difference between them also increases. In contrast, for HR = 0.2 (Fig. 15.9), the contact pressure obtained from the Cosserat theory does match to FE simulation for higher values of the applied load. As far as shear deformation and Flügge-Lur’e-Byrne theories are concerned, the contact pressure has a non-zero value at the contact edge that is there is a discontinuity in contact pressure at the contact edge. The contact pressure distribution obtained from

15 Contact of a Cylindrical Shell with a Flat Frictionless Rigid Substrate

219

(i) Convergence study for dimensionless maximum radial displacement

(ii) Convergence study for dimensionless maximum tangential displacement

(iii) Convergence study for dimensionless maximum contact pressure

(iv) Convergence study for dimensionless contact area

Fig. 15.5 Mesh convergence study for

H R

= 0.2.

the Flügge-Lur’e-Byrne theory indicates that the contact region is a thin strip away from the center (point of first contact). Table 15.1 presents the comparison between the contact angle calculated by the three considered theories and FE simulation. The second column shows the input contact angle in Cosserat theory and the corresponding load output. The next three columns show the contact angle calculated by the shear deformation shell theory, the Flügge-Lur’e-Byrne shell theory, and FE simulation for the same load values, respectively. It can be seen that while the contact angle calculated by the shear deformation and the Flügge-Lur’e-Byrne theories is always lower than the contact angle as per Cosserat theory, and the angle calculated by FE simulation is observed to be varying within the range of ±2o from the angle from Cosserat theory. The difference between contact angles calculated by a theory and FE simulation is the least for the Cosserat theory.

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with load (i) Contact angle F=901.9991 N/m

(ii) Contact angle with load F=1080.6143 N/m

(iii) Contact angle with load F=1314.8448 N/m Fig. 15.6 The deformed shape of the shell obtained from Cosserat, shear deformation, FlüggeLur’e-Byrne theories, and FE simulation for HR = 0.05. The analytical solutions are getting merged

15.3.3 Comparison Between Applied Load Versus Contact Patch Length Plots . The boundary value problem will have any two unknown parameters: (a) Contact angle and contact patch length or (b) Applied load and contact patch length. For case (a), applied load is taken as input and for case (b) Contact angle (θc ) is taken as input. Thus, for generating load versus contact patch length results, contact angle has been given as an input in all the theories. For generating the ABAQUS plot, since it does not allow us to give contact angle as input, the load output obtained from the Cosserat theory has been taken as the input and thereby the load versus contact patch length plots were generated.

15 Contact of a Cylindrical Shell with a Flat Frictionless Rigid Substrate

with load (i) Contact angle F=901.9991 N/m

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with load (ii) Contact angle F=1080.6143 N/m

(iii) Contact angle with load F=1314.8448 N/m

Fig. 15.7 The dimensionless contact pressure distribution obtained from Cosserat, shear deformation, Flügge-Lur’e-Byrne theories, and FE simulation for HR = 0.05.

From load vs contact length plots, as shown in Fig. 15.10(i, ii, iii), it has been observed that for HR = 0.05, the result obtained from Cosserat theory matches well with that obtained from FE simulation. As the thickness increases that is HR = 0.1 and HR = 0.2, there occurs a small difference in the results from Cosserat theory and FE simulation, but still, the Cosserat theory performs much better than the other two considered theories that are the shear deformation and Flügge-Lur’e-Byrne. As far as Flügge-Lur’e-Byrne theory is concerned, it does not start from origin, because the formulation does not allow us to give zero contact angle as input, we need to start computing from some small non-zero contact angle value (Fig. 15.10).

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Table 15.1 Comparison of contact angle calculated from Cosserat, shear deformation, FlüggeLur’e-Byrne theories, and FE simulation for Thickness to radius ratio

(i)

= 0.05

H R

(ii)

(iii)

H R

H R

= 0.1

= 0.2

Contact angle (θc ) and the corresponding load (F) output as per Cosserat theory

H R

= 0.05, 0.1, and 0.2

Contact angle (θc ) as per shear deformation theory

Contact angle (θc ) as Contact angle per (θc ) as per FE Flügge-Lur’e-Byrne simulation theory

θc = 10 and F = 901.9991 N/m

9.4556

8.2242

9.9522

θc = 15 and F = 1080.6143 N/m

14.4907

13.3633

15.1074

θc = 20 and F = 1314.8448 N/m

19.5019

18.4987

20.1193

θc = 10 and F = 6.6394 kN/m

8.9435

6.4505

9.8091

θc = 15 and F = 7.6923 kN/m

13.1082

10.8740

14.1050

θc = 20 and F = 9.2308 kN/m

17.9222

15.9249

18.9737

θc = 10 and F = 45.3846 kN/m

8.1813

2.7288

9.5943

θc = 15 and F = 53.8461 kN/m

12.8016

8.3311

14.4630

θc = 20 and F = 65.3845 kN/m

17.9847

14.0644

19.7613

15.4 Conclusion The contact problem of a cylindrical shell with a smooth flat rigid substrate is studied using the Cosserat, shear deformation, and Flügge-Lur’e-Byrne shell theories and finite element simulation using ABAQUS. The conclusions drawn from the results presented in this chapter are: i.

As far as displacements are concerned, FE simulation predicts higher displacements in the free region than what is predicted by the three considered theories. It requires further study to understand the reason for such discrepancy. ii. The contact pressure results, for HR = 0.05, obtained from Cosserat theory match excellently to that obtained from FE simulation, however for thick shells, for example, HR = 0.2, such good agreement between Cosserat and FE simulation is obtained at higher load values. On the contrary, we have obtained a non-zero value of contact pressure at the contact edge in the case of Flügge-Lur’e-Byrne and shear deformation theories. Also, the respective difference between the contact angles calculated from a theory and FE simulation is the least for the Cosserat shell theory as can be observed from Table 15.1.

15 Contact of a Cylindrical Shell with a Flat Frictionless Rigid Substrate

(i) Contact angle with load F=6.6394 kN/m

223

with load (ii) Contact angle F=7.6923 kN/m

(iii) Contact angle with load F=9.2308 kN/m

Fig. 15.8 The dimensionless contact pressure distribution obtained from Cosserat, shear deformation, Flügge-Lur’e-Byrne theories, and FE simulation for HR = 0.1

iii. The load versus contact length plots clearly show the excellent agreement between Cosserat and FE simulation results for thin shells. Therefore, we conclude that in order to accurately capture the physics of the contact problems including thin or thick shells, the inclusion of transverse shear strains along with transverse normal stress and strain is necessary, especially in the case of problems where the accurate measurement of traction between the contacting bodies is of primary concern. We can arguably be more precise and conclude that it is the transverse normal strain (that is the deformation through the thickness) that is important for the contact of shell-like structures.

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(i) Contact angle with load F=45.3846 kN/m

(ii) Contact angle with load F=53.8461 kN/m

with load (iii) Contact angle F=65.3845 kN/m

Fig. 15.9 The dimensionless contact pressure distribution obtained from Cosserat, shear deformation, Flügge-Lur’e-Byrne theories, and FE simulation for HR = 0.2.

15.5 Future Study i. The high value of displacements in the free region in the ABAQUS contact model and also the high variation in the contact pressure values at coarser mesh for high thickness values need to be studied in more detail. ii. This study has focused on non-adhesive contact and from the history of contact mechanics following the contact theories for elastic solids such as JKR and DMT, the adhesive forces may play an important role in the contact of shell-like structures also. According to JKR and DMT theories for the contact between elastic solids, the contact area is non-zero even when the applied load is zero. The same might be true in the case of contact involving shell-like structures also. This marks the need to consider the adhesion within the contact region and also outside the contact region for the contact of shell-like structures.

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(i)

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Fig. 15.10 The dimensionless load versus contact length plots obtained from Cosserat, shear deformation, Flügge-Lur’e-Byrne theories, and FE simulation for three different thickness values

The study of contact of thin structures has wide applications such as in the fields of pneumatic tires, designing tires for lunar vehicles where accurate measurement of traction between the contacting bodies is of primary importance, in the applications of pressure vessels, etc., as far as adhesive contact is concerned, then in the fields of life sciences, biomechanics, soft matter, etc., the processes such as cell crawling, endocytosis, exocytosis, are all examples of adhesive contact of the cell membrane, also the adhesion of contact lens, etc. It is expected that the current study is of interest to readers and motivates them to further study the contact mechanics of thin structures and extend this work to reach the desired goals and thereby make remarkable contributions to the field of contact mechanics.

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Acknowledgements Financial support from the Science and Engineering Research Board, Department of Science and Technology, Government of India through grant no EMR/2016/001385 and Indian Institute of Technology Palakkad are greatly acknowledged. Declaration of Conflict of Interest Authors declare that there is no conflict of interest.

References 1. Ventsel, E., & Krauthammer, T. (2001). Thin plates and shells: Theory, analysis, and applications (1st ed.). CRC Press. 2. Cosserat, E., & Cosserat, F. (1909). Théorie des corps déformables. A. Hermann et Fils. 3. Altenbach, J., Altenbach, H., & Eremeyev, V. A. (2010). On generalized Cosserat-type theories of plates and shells: A short review and bibliography. Archive of Applied Mechanics, 80, 73–92. 4. Rubin, M. B. (2000). Cosserat theories: shells, rods and points (1st edn, vol. 79). Springer Science & Business Media. 5. Duhem, P. (1893). Le potentiel thermodynamique et la pression hydrostatique. Annales scientifiques de l’École Normale Supérieure, 10, 183–230. 6. Ericksen, J. L., & Truesdell, C. (1957). Exact theory of stress and strain in rods and shells. Archive for Rational Mechanics and Analysis, 1, 295–323. 7. Maugis, D. (2000). Contact, adhesion and rupture of elastic solids (1 ed., Vol. 130). Springer Berlin Heidelberg. 8. Essenburg, F. (1960). On a class of nonlinear axisymmetric plate problems. Journal of Application Mechanica, 27. 9. Christopher, R. A., & Essenburg, F. (1971). The contact of axisymmetric cylindrical shells with smooth rigid surfaces. In Proceeding twelfth Midwestern mechanics conference (pp. 773–786). 10. Kulkarni, S. V., & Frederick, D. (1973). The contact problem of two coaxial cylindrical shells. International Journal of Mechanical Sciences, 15, 367–379. 11. Essenburg, F. (1975). On the significance of the inclusion of the effect of transverse normal strain in problems involving beams with surface constraints. Journal Application Mechanica, 42. 12. Gasmi, A., Joseph, P. F., Rhyne, T. B., & Cron, S. M. (2012). The effect of transverse normal strain in contact of an orthotropic beam pressed against a circular surface. International Journal of Solids and Structures, 49, 2604–2616. 13. Naghdi, P. M., & Rubin, M. B. (1989). On the significance of normal cross-sectional extension in beam theory with application to contact problems. International Journal of Solids and Structures, 25, 249–265. 14. El-Abbasi, N., & Meguid, S. A. (1999). Modeling frictional contact in shell structures using variational inequalities. Finite Elements in Analysis and Design, 33, 317–334. 15. Kraus, H. (1967). Thin elastic shells: An introduction to the theoretical foundations and the analysis of their static and dynamic behavior. Wiley. 16. MATLAB, version 9.8.0.1380330 (R2020a). (2020). The MathWorks Inc. 17. Jagadish, R. (2010). A computational investigation of contact pressure for a non-pneumatic wheel with a meta-material shear band.

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Aishwarya Kasarla completed her master’s degree (MS by research) in mechanical engineering from the Indian Institute of Technology, Palakkad in 2022 and is currently pursuing a doctoral study in the aerospace engineering department at IIT, Bombay. The current chapter describes her work during her master’s. She is mainly interested in theoretical mechanics, solid mechanics, and mathematics. Sovan Lal Das is currently an Associate Professor of Mechanical Engineering at IIT Palakkad. His research interests include developing and/or applying continuum theory based models and performing experiments to elucidate the role of the cell membrane and its mechanical properties in various cell-biological processes, mechanics of granular media, and contact mechanics of soft and thin structures.

Chapter 16

Kinematics of Mechanisms ain’t an Old Hat! G. K. Ananthasuresh

16.1 Genesis, Early Developments, and Conflicts Therein 16.1.1 Mechanisms Constrained motion of solids and fluids is inherent to machines. Mechanisms are the building blocks of machines. By deliberate design of mechanisms, solids and fluids are commanded to move as desired to transmit force, motion, and energy. Human civilization started and prospered with the development of tools, implements, instruments, and machines for the purposes of agriculture, buildings, transportation, manufacturing, medicine, and weaponry. From pumping water and milling grains, efficient lifting of weights, animal-drawn carriages, pottery and smithy, surgical instruments, to bows and arrows, there was a need to study and design mechanisms of various kinds. Madrid Codices I and II dating back to 1490–1499 and 1503–1505 contain drawings of machines conceived by Leonardo da Vinci and the Various and Ingenious Machines of Agostino Ramelli (1588) contain illustrations of nearly two hundred machines known in the sixteenth century. With the proliferation of steam power and the beginning of the first industrial revolution, the need for mechanisms started to grow. Ferguson [1] notes that James Watt (1736–1819) was a pioneer in the field of mechanisms. Watt’s work was empirical and holistic. He focused on synthesis more than analysis. Many ingenious mechanisms were invented by Watt [2, 3] for practical applications. Kinematics, which is the science behind mechanisms, developed subsequently.

G. K. Ananthasuresh (B) Department of Mechanical Engineering, Indian Institute of Science, Bengaluru, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 U. S. Dixit et al. (eds.), Engineering Pedagogy, https://doi.org/10.1007/978-981-19-8016-9_16

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16.1.2 Kinematics Even though there is no explicit ambiguity today, at the inception there were some differing opinions with regard to defining what kinematics really is or isn’t. In a thought-provoking analogy, Koetsier [4] urges us to imagine maps of three countries with mutual overlaps: mechanics, geometry, and machines (see Fig. 16.1). Kinematics, he says, lies at the intersection of these three as per a classification of sciences done by André-Marie Ampére in 1829. Kinematics as interpreted by Ampére, Ferguson [1] quotes, is as follows: …derived from cinematique (the Greek word for movement) as a science in which movements are considered in themselves (independent of the forces that produce them), as we observe them in solid bodies all about us, and especially in the assemblages called machines.

This definition of kinematics is widely followed today when we say that kinematics is the study of motion without regard to the forces that caused it. This view was apparently suggested to Ampére by Lazare Carnot (1753–1823), a French mathematician, physicist, and politician (not to be confused with Sadi Carnot, the father of thermodynamics), who thought that: …there is a need for a new kind of science that deserves the attention of scholars to study the movements that an arbitrary system of bodies can make in such a way that they do not hinder each other or exert some action or reaction on each other.

The partial dissociation of kinematics from its three allied disciplines has had tremendous implications, both positive and negative. As Koetsier [4] explains, the positive outcome was that many nineteenth century mathematicians took to kinematics because of its closeness to geometry; Cayley, Cremona, Poncelet, Chasles, Möbius, Plücker, Steiner, Darboux, Koenigs, Chebyshev, Sylvester, Burmester, and Fig. 16.1 The place of kinematics in the three disciplines it intersects as per Ampére’s classification

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Klein to name a few. The works of Chebyshev and Burmester are well-known in linkage analysis and synthesis. This should be contrasted with geometers (mathematicians who study geometry) much before nineteenth century and going back to the ancient Greek mathematicians and philosophers, who dreaded to introduce motion into geometric analysis as it brings the fourth dimension—the time. In contrast, that kinematics is much more than geometry is well captured in what Chebyshev said to Sylvester [1]: Take to kinematics. It will repay you. It is more fecund than geometry; it adds a fourth dimension to space.

Thus, the field of kinematics owes much to the mathematicians from Euler (1707– 1783) to many more after him in establishing it as a scientific sub-discipline on its own. This can be seen as the positive outcome of Ampére’s definition of kinematics. There are two arguably negative outcomes of Ampére’s definition of kinematics as purely “geometry in motion but without regard to forces”. The first is the departure of kinematicians from the study of mechanics of solids that includes deformable bodies. Sadly, much of the development of kinematics of mechanisms excluded deformable bodies and considered only the ideal rigid bodies. But there is kinematics in elastic and plastic deformations as well as fluids. And there is kinematics in biological growth [5]. As a result of the restricted definition of kinematics, since the latter half of the twentieth century, kinematics got dissociated with the so-called “solid mechanics”.1 Fortunately, this oversight is being corrected with fortuitous developments in the areas of compliant mechanisms, metamaterials, etc., as we shall return to later. The second negative impact of Ampére’s definition of kinematics is the inadvertent distancing from the comprehensive approach to the theory of machines itself. Among those who objected to the restricted definition was Franz Reuleaux (1829–1905), who is regarded as the father of kinematics. Moon [6] compares him with Theodore von Kármán. That is, Reuleaux enriched the field of kinematics and theory of machines just as von Kármán did to the fields of aeronautics and astronautics. Incidentally, Reuleaux was born in the year when Ampére relegated kinematics to a 3rd order science (Fig. 16.2) and gave its restrictive definition. We more or less follow a similar classification of subfields of mechanics even today without the use of elementary and transcendental notions.

1

Rigid-body mechanics should also come under solid mechanics as rigid bodies are indeed solids. But today’s interpretation of “solid mechanics” restricts it to only deformable bodies. An unfortunate consequence of this is that most solid mechanicians of today are mostly interested in failure of materials and the constitutive behavior of materials rather than how solids can be used to analyze and design machines.

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Astronomy

Mechanics

Geometry

Elementary Statics

Kinematics

Arithmetic Transcendental

Dynamics

28 others… (2nd order sciences)

Molecular dynamics

(3rd order sciences)

Fig. 16.2 The place of kinematics as a 3rd order science as classified by Ampére in 1829

16.1.3 Kinematics, Mechanisms, and Machines Reuleaux’s contributions to mechanisms are many. It is pertinent to note them before we contrast his distinctive view of kinematics of mechanisms with those before and after him. Reuleaux’s book in German (Theoretische Kinematik: Grundzuge eniner Theorie des Machinenwesens, 1874–75) [7] was perhaps his most significant contribution. It was translated into English as “The Kinematics of Machinery: Outline of a Theory of Machines” by Prof. A. B. W. Kennedy of University College of London, in 1876. The introductory chapter of this book delves deep into the philosophy of machines. Its content is rich with some aspects that have influenced the field of kinematics and many aspects that ought to enrich the field further but have not happened until now. Reuleaux not only built nearly 800 exquisite models of mechanisms but also classified them. More importantly, he developed symbols for mechanisms and machines as chemists did it for elements and compounds. Like Carl Linnaeus (1707–1778) did for plant and animal kingdoms, Reuleaux attempted a nomenclature for machines. He also developed a language of invention so that a really new mechanism could be easily spotted. He foresaw the importance of topology in machines much before mathematical concepts of topology were developed. Although Jacob Leupold (1674– 1727) was the first to separate mechanisms from machines in 1724, it was Reuleaux who firmly established the concept of kinematic pairs for joints and mechanisms as elements of machines that are composed as open and closed chains, simple and compound chains. Deformable bodies and fluids were not excluded by Reuleaux when he thought of mechanisms. It is also worth noting that Reuleaux had published a handbook of machines (the Constructor) in 1861 [8]. He held clear and strong views on synthesis and invention, which are still relevant today. Prof. Francis Moon [6], who had studied Reuleaux’s works recently, notes: …it was his view that both kinematics and strength of materials should be studied in the context of machines. He was also the first to attempt to place invention, kinematic synthesis and design of the machine as a whole on a mathematical and scientific basis.

Most notably, Reuleaux established kinematics of mechanisms as a topic in the mechanical engineering curriculum.

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We now come to the subtle point on which Reuleaux differed with Ampére’s definition of kinematics. As we read Reuleaux’s book translated by Kennedy, we come to understand that Reuleaux largely agreed with Ampére and Robert Willis (1800–1875). The latter was a distinguished British Mechanical Engineer who wrote a book with the title Principles of Mechanism (1841) and is thought to be the most influential early mechanisms researcher before Reuleaux. Willis too tried to classify mechanisms and attempted symbolic notation like his Cambridge colleague, Charles Babbage (1791–1871). However, Kennedy, in the preface to the English translation of Reuleaux’s book, says: With the growth of clear ideas in physical science, it became possible to separate the ideas of force, time, and motion, and to consider the latter merely for its own sake without reference to the other two. Prof. Willis adopted this treatment unreservedly in his Principles of Mechanism—a work too well-known to need any characterization here—calling the study thus marked out the “science of pure mechanism.

Here is where Reuleaux disagreed with Ampére and Willis: …it is best called Phoronomy. Frequently it is simply called Kinematics, but this seems to be a misunderstanding of the word. Ampere at least, who invented the name, did not intend it to be used in this sense. It is at the same time unnecessary so to employ it, for Phoronomy is quite sufficient, and is besides more distinctive than Kinematics…

Phoronomy is a strange word for modern kinematicians. It was Immanuel Kant (1724–1804), the philosopher, who used it in the Metaphysical Foundations of Natural Science (1786) to denote “the study of the motions of bodies, without regard to forces or the nature of the bodies”. This is how we understand kinematics today. But for Reuleaux, it was different. …Kinematics is not an absolutely isolated science, as it would be under Ampére’s definition, but works in consciousness of the neighborhood of other systems of investigation having a common object with it. On the other hand, we have in our own way arrived at the same conclusion with Ampere, that Kinematics observes changes of position only. Only we do not thereby shut out the actions of forces, as Ampere does; we take the problems connected with them as solved in every case, and consider the conditions imposed by them, which is a real and important difference.

This shows that Reuleaux was against studying machines and mechanisms without consideration of forces that caused them. He had not excluded deformable bodies or even fluids from consideration. Therefore, he was careful when he defined a machine as follows, which all modern books on machines and mechanisms diligently quote: A machine is a combination of resistant bodies so arranged that by their means the mechanical forces of nature can be compelled to do work accompanied by certain determinate motions.

Reuleaux loathed earlier works that showed each machine merely as a drawing instead of identifying how it is composed or how it could be systematically analyzed. It is unfortunate that even now a machine is usually shown as a drawing or a photograph rather than with its elements delineated as a chemical compound with its

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elements connected in specific arrangements. It is ironical that Reuleaux’s reductionism led to what he did not like “The endless isolation of efforts must be detrimental to the whole” in studying machines holistically. Kennedy ends his preface to Reuleaux’s book with these words of wisdom: It is unfortunate that we have as yet no word for the study of motion as change of position merely. Phoronomy, which is used in Germany very nearly in this sense, is very unprepossessing; —I would suggest metastatics for the purpose, unless a better word can be found. It has at least the merit of expressing the idea clearly, and with philologic and scientific accuracy.

But Kennedy’s advice went unheeded. He goes on to add that Ampére could have used “kinetics” rather than “kinematics”. Thus, even though Reuleaux was quite clear in his view of kinematics and the translator of Reuleaux’s book was even more careful about this, the field of kinematics excluded force and time. This has helped the field grow in some ways but also hindered it to lose in another ways. We examine this next.

16.2 Pedagogy and Practice 16.2.1 Before Reuleaux In the ancient times and early periods of industrial revolution, engineering was practised and taught in a workshop where students mostly learnt by doing apprenticeship. This was true of machinery in general. Each machine was described and studied as if it were new and different from the earlier ones. So, catalogs, handbooks, and manuals of machines were published, including “Manual of Machinery and Millwork” by Rankine in 1869 [9]. Various classifications were attempted to delineate common features of machines [10]. The notable among them was a course on “Elements of Machines”, initiated by Gaspard Monge (1746–1818) and conducted by Jean Nicolas Pierre Hachette (1769–1834) at Ecole Polytechnique in Paris around 1794. Hachette’s scheme of classification was based on how one type of motion (rectilinear, circular, oscillatory) can be converted to another. A little later, José Maria Lanz2 (1764–1839) and Augustíne de Betancourt (1760–1826) filled in gaps in Hachette’s classification in a book “Essai sur la compositions des machines” published in 1808. Ferguson [1] comments that this was probably the first book on kinematics of mechanisms. An influential book published after that was by Robert Willis (1800–1875) with the title “Principles of Mechanism” [11] in 1841 with a second edition in 1870. The subtitle of the book explicitly states its purpose: “Designed for the Use of Students in the Universities, and for Engineering Students Generally”. Even though Willis’s book begins with a classification of machines based on joint types, it dwells more on analysis of gears, linkages, and cams. As suggested by Ampére, Willis separated 2

Sometimes written as Phillippe Louis Lanz.

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kinematics from the general study of machinery. He notes that it was Euler who, in 1775, first argued for separation of force and time to study machinery purely as kinematics. The investigation of the motion of a rigid body may be conveniently separated into two parts, the one geometrical, and the other mechanical. In the first part, the transference of the body from a given position to any other position must be investigated without respect to the causes of the motion, and must be represented by analytical formulae, which will define the position of each point of the body after the transference with respect to its initial place. This investigation will therefore be referable solely to geometry, or rather stereotomy. It is clear that by the separation of this part of the question from the other, which belongs to properly to mechanics, the determination of the motion from dynamical principles will be made much easier than if the two parts were undertaken conjointly.

Thus, the pedagogy in kinematics of machinery commenced with books by LanzBetancourt and Willis. There was much scope to use geometry and graphical methods in their approach because emphasis was on the motion of rigid bodies. Willis deemphasized synthesis saying in his preface that: When the mind of a mechanician is occupied with the contrivance of a machine, he must wait until, in the midst of his meditations, some happy combination presents itself to his mind which may answer his purpose.

But he recognized that: …it will be generally observed that the motions of the machine are the principal subject of contemplation, rather than the forces applied to it or the work it has to do.

Thus, right from the beginning, kinematics of machinery has been taught with emphasis exclusively on rigid bodies, on analysis much more than synthesis, and without taking forces into account. However, the relief from this restrictive thinking came from Reuleaux when he wrote his book in 1875 [7].

16.2.2 During Reuleaux Reuleaux was influenced by his teacher Ferdinand Redtenbacher (1809–1869), who was a professor of mechanical engineering in the Polytechnique School at Karlsruhe and considered to be the father of mechanical engineering in Germany. Reuleaux credited Redtenbacher for separating the “questions connected to machinery from the branches of science related to it” but also critiqued that Redtenbacher held the view that “…no true system of the study of mechanisms was possible, that they could be arranged only according to their practical usefulness, and for the rest must be treated mathematically.” Reuleaux appreciated the fact that Redtenbacher considered many aspects of machine design including strength of materials, thermodynamics, hydraulics, friction, turbines, and steam engines. Inspired by this, Reuleaux wrote a machine design book before writing his kinematics book. Like his teacher’s 80 kinematic models, Reuleaux built 800 models.

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Reuleaux’s 1875 book on kinematics is amazingly comprehensive. He firmed up the notions of lower and higher kinematic pairs, developed the notion of kinematic chains, proposed kinematic notation for mechanisms and machines, presented kinematic analysis methods, and postulated kinematic synthesis methods. Figure 16.3, taken from his 1875 book, illustrates how he perceived kinematic synthesis. His genius is evident from his open-mindedness of synthesizing new machines with hitherto unknown kinematic pairs and unknown kinematic chains. The most notable feature of Reuleaux’s book, in his own words, is that he “begins and ends with [the matters concerning] the machine itself”. This book influenced many great kinematics researchers and left a lasting impact on pedagogy and practice of the field. Moon’s observation about Reuleaux’s influence is worth noting: His own books and ideas of kinematics of machines influenced many late 19th C. texts such as Kennedy (1886), Burmester (1888), and the early 20th C. texts of Hartmann (1913), Barr and Wood (1916), Durley (1907) and Hartenberg and Denavit (1964). What distinguished Reuleaux’s work from later 20th century works, was his view that both kinematics and strength of materials should be studied in the context of machines. He was also the first to attempt to place invention, kinematic synthesis and design of the machine as a whole on a mathematical and scientific basis.

Remarkably, Reuleaux was able to see whole machines as compositions of abstract entities and concluded that they are nothing but six kinematic chains, namely, the screw chain, the wheel chain, the crank chain, the cam chain, the ratchet chain, and pulley chain. He noted that they suffice in practice and instruction. This is akin to 20 amino acids and two types of secondary structures present in a huge variety of proteins. Reuleaux exuded confidence when he said that “the problems not covered by these chains are all more or less inferior in importance”. Furthermore, Reuleaux left a tantalizing sentence in his summary that in all of those chains flectional elements may take the place of rigid ones. The word “flectional” needs elaboration as most of his successors missed this. Reuleaux included non-rigid elements such a ropes, wires, chains, bands, and other wrapping elements and springs of various kinds within the constructive elements of mechanisms and machines and called them tension organs. As noted earlier, he also included what he called pressure organs brought in by fluids—liquids, gases, water, oil, air, and steam. His perspicacity and foresight were evident when viewed them as higher pairs taking into account the pliability of tension organs and fluidity of pressure organs.

16.2.3 After Reuleaux With hindsight, we can say that today the field of kinematics would have taken an entirely different trajectory had we followed Reuleaux’s thinking in its entirety. However, in all parts of the world, kinematics of mechanisms got restricted to mostly rigid bodies and dissociated with the larger field of mechanics. Bottemma in 1953 [12] and Freudenstein in 1959 [13] wrote brief but compelling reviews of the developments in the field, citing important advances in research and major books such as those by

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Fig. 16.3 Reuleax’s vide of kinematic synthesis; it is still unmatched in terms of depth and foresight (reproduced from [7])

Hain [14]. These reviews indicate that only a small portion of Reuleaux’s vision had been followed. Despite major strides in graphical, analytical computational advances in treating and teaching kinematics, it fell short of Reuleaux’s vision. Moon [6] noted that the study of machines became a victim of reductionism, which was also propounded by Reuleaux himself. It is ironical. Barring a few exceptions, teaching of kinematics of mechanisms in the twentieth century, moved farther from industrial practice and, sadly, saw a decline as a coveted scientific discipline. Thus, teaching, research, and practice began to lose shine. This was partly compensated by a few developments in the later part of twentieth century and afterwards, as we will discuss next.

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16.3 Expansion in the Twentieth Century and After 16.3.1 No New Elements! As we look back, it is hard to not miss that the elements of mechanisms and machines have remained largely unchanged since Reuleaux’s time. Cams, gears, linkages, belts, pulleys, chains, bearings, shafts, brakes, fasteners, springs, intermittent-motion elements, etc., were all there. Are new elements added to this repertoire since 1875? The answer is disappointingly negative. Furthermore, by excluding Reuleaux’s flectional elements, the list of elements of mechanisms has rather diminished. This is surprising because the field of mechanisms has flourished in terms of rigor and mathematical maturity, although has reached a state of saturation in terms of industrial practice. Today, we do not see a new graduate well versed in kinematic analysis and synthesis being sought after by the industry, or for that matter by academia too. Fortunately, all is not all gloomy because a few new topics have arisen in the later part of twentieth century and after. Notable among them are open-chain manipulators and compliant mechanisms.

16.3.2 Open Chains and Robotics With the emergence of robots, open-chain manipulators with multiple degrees of freedom came into prominence. Forward and inverse kinematics, dynamic analysis, under actuated chains, singularities, etc., gave rise to challenging problems as well as applications. Interest in parallel manipulators and cable-driven robots increased. Reconfigurable machines also opened up new opportunities. All of these spurred interest in spatial kinematics unlike any other period before. All these developments are so vast that we refrain from any discussion of those in this article. There are excellent books that describe them, [15–17] to cite a few. It is worth noting that the field of robotics quickly slipped away from kinematicians because actuation, sensing, control, path and trajectory planning, and most importantly, the need for automation made robotics a multidisciplinary field. This continues today as cyber physical systems and re-birth of artificial intelligence have begun to have immense influence on the way robots are studied. It is worth debating if there are any kinematics problems left in the field of robotics.

16.3.3 Compliant Mechanisms at Multiple Size Scales From Reuleaux [6] to Hain [14] and Phillips [18], kinematicians have commented on the additional degrees of freedom in generating desired motions with elastic

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deformations. And there have been interesting uses of elastic deformations in mechanisms. Insightful studies were carried out by Prof. F. R. E. Crossley and his coresearchers [19, 20]. Systematic treatment of elastic deformation used in mechanisms commenced with Prof. Ashok Midha, who coined “compliant mechanisms” to unambiguously describe them [21]. The genesis of this topic was described by him in [22] where we see that a lecture in chemical engineering department at Purdue University highlighted that the time has come to use plastics as load-bearing elements. Prof. Midha set the foundations for the new field by initiating mobility analysis and nomenclature [23], deformation analysis [24], identification of inherent kinematics [25], synthesis [26], and compelling applications. All these developments are well captured by Prof. Larry Howell in his book [27]. Alongside, direct synthesis of compliant mechanisms using topology optimization began at the University of Michigan in Prof. Sridhar Kota’s research group [28–30]. Close connection between compliant mechanisms and microelectromechanical systems (MEMS) was also noticed and nurtured in his group [31]. Synthesis of compliant mechanisms in the context of MEMS can be seen in [32, 33] and some novel mechanism designs of microsystems devices are described in [34]. Following the tradition of compiling existing mechanisms into a handbook has also been undertaken [35]. A digital collection of about 80 compliant mechanisms is also created [36]. Compliant mechanisms have now been realized not only using plastics but also with metals, silicon, elastomers, ceramics, and a wide variety of materials. Applications in aerospace, automotive, biomedical, and consumer products have been explored. A new facet of mechanisms and kinematics was thus born. Compliant mechanisms fill the continuum between stiff structures and rigid-body mechanisms (see Fig. 16.4). We now have elastic pairs (flexural joints) and elastic chains to add to Reuleax’s constructive elements. When a compliant mechanism is made of elastic pairs, we see relatively rigid segments connected with flexural joints. We then have discrete compliance. But when elastic pairs too are absent, elastic segments alone can form an elastic chain, giving rise to distributed compliant mechanisms. As shown, Fig. 16.5, the serial, parallel, discrete, and distributed chains, both rigid and elastic, point to unlimited possibilities for kinematics of mechanisms. With the pace of the development of novel design methods, modern manufacturing techniques (additive manufacturing in particular), and newer materials, this field is poised to grow much more. Compliant mechanisms are also playing a crucial

Fig. 16.4 The wide gap filled by compliant mechanisms between stiff structures and rigid-body mechanisms

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Fig. 16.5 Extended constructive elements for mechanisms with the addition of elastic pairs and elastic segments

role in designing metamaterials [37] or what are being re-invented as architected or architectured materials [38].

16.4 What Does the Future Hold? 16.4.1 Look Back to Look Forward “Engineers are future oriented, rarely looking back on the history of their craft and science”, says Prof. Francis Moon, who has extensively studied Reuleaux works and the history around them [6]. This is mostly true as engineers are most often concerned with solving the current problems and engineering future technologies. Eugene Ferguson’s comment is pertinent here: While we look to the future, one may ask how a lengthy view of the past can be justified. It seems to me that there is inherent in the almost feverish activity of the present the danger of becoming so preoccupied with operational theory that the goals may become clouded and the synthesis (let us put it less elegantly: the design) of mechanisms may never quite come into focus. If one knows nothing of the past, I wonder how he can with any confidence decide in what direction one must turn in order to face the future.

A look at the past is indeed necessary to look into the future. As we noticed in the thought processes of some of the early kinematicians such as Redtenbacher and Reuleaux, they certainly had the foresight to look beyond what we have achieved in 150 years. Kinematics should not be divorced from the larger areas of mechanics and machines. While this oversight might be corrected now with the emergence and

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proliferation of micro and nano technologies where integration of multiple disciplines is inescapable. A new horizon awaits kinematicians when they examine the natural world. Interestingly, this too was eminently contemplated by mechanical engineers more than a century ago.

16.4.2 Animal as a Machine and Vital Mechanisms It is widely known that Robert Hooke (1635–1703) was the first one to notice that the living matter is composed of tiny compartments that he called cells. He was also the first one to give us the simplest relation in elastic mechanics (stress is proportional to strain). Thus, both cell biology and elastic mechanics originated from the same person. So, we are not surprised today when mechanical engineers study biological cells. We are also well aware of biomechanics of bones and muscles. Yet, it is surprising that mechanical engineers had deeply thought about living beings as much as biologists do. Robert Henry Thurston (1839–1903, incidentally born and died on Oct. 25th) was one such engineer. Thurston was an American engineer who was also the first Mechanical Engineering professor at Stevens Institute of Technology, Hoboken, New Jersey, USA. He was the first President of the American Society of Mechanical Engineers (ASME). He was an accomplished researcher in the areas of materials, steam engines, thermodynamics, and tribology. He was a pioneer in formulating mechanical engineering curriculum. He also wrote many books. One of them had the title “The Animal as a Machine and a Prime Motor, and the Laws of Energetics” [39]. It was written in 1894. Thurston also wrote a short article in Science a year later [40]. An excerpt from this article is shown in Fig. 16.6. The six postulates summarize the considered opinion of Thurston after he thought much about living animals by comparing them with steam engines and other machines. His conclusion that animal prime mover is a chemical-dynamic motor and not a thermodynamic heat motor nor electro-dynamic motor, is insightful. He also observed that energy is generated and applied locally in a living creature as opposed to engineered machines, which is very insightful for his time. He also contemplated on how signals work in nerves and knew that how brain works was yet to be discovered. The experiments he describes in his article and the book are very revealing. In spite of advances in cell biology and recent understanding of mechanobiology, we are yet to address the questions that Thurston had posed. Thurston gave much importance to energetics and wondered how heat is produced by cells and tissues. He thought that the energy efficiency of the animals is much more than that of the heat engines, if at all they can be thought of as heat engines. Considering that the body temperature is more or less uniform throughout, he thought that Carnot-function is evaded by living systems. He concluded that “Every living creature, man and worm alike, shows him that his great task is but half accomplished; that his grandest inventions are but crudest and remote imitations; that his best work is wasteful and awkward”. This holds true even today. This means that machines need to improve a lot before we reach the perfection that living machines have attained.

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Fig. 16.6 Thurston’s observations about vital machines (reproduced from [40])

Thurston’s book and ideas impressed upon Reuleaux so much that he translated it into German. Reuleaux devoted an entire chapter to kinematics of the skeletal system and its analogy with kinematic chains in machines. He also discussed a model for muscle actuation. Moon [6] wrote that Redtenbacher too had a section on animal and human forces in his “Machinenbau” that may have influenced both Thurston and Reuleaux to write about machines and biomechanics decades later. If we were to set out to build machines that compete with or surpass the living machines, how and where should we begin? Can we think of machines of the future to have: • local and distributed actuation everywhere? • local and distributed sensing all through? • localized control with remote instruction? If we are successful in doing so, we would have what Thurston had called “vital mechanisms”. Then, we must redefine kinematics and the notions of degrees of freedom and bring in energetics, sensing, actuation, and control in a much more integrated manner than is possible today. Figure 16.7 then illustrates past, present, and possible future of mechanisms and machines. What is to come is the age of living machines [41]. Biohybrid mechanisms are already on the horizon. For example, human heart cells have been recently combined with engineered mechanisms to make a biohybrid fish with the G-node too incorporated [42]. Bionic limbs, neural prostheses, and artificial organs are but the humble beginnings. Engineered machines seamlessly integrated with living systems would be fascinating and frightening at the same time. It is the next frontier for kinematics of mechanisms. What should change in the way we teach? We discuss that next.

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Fig. 16.7 Constructive elements of machines and mechanisms: past, present, and future

16.4.3 Future Pedagogy in Kinematics and Mechanisms The field of kinematics of mechanisms has paid a heavy price for restricting it to rigid-body mechanisms. This should change. The change should happen in pedagogy so that future mechanical engineers are not constrained in their thinking and practice. This idea is not new as we have seen since the time of Reuleaux. We find in Kurt Hain’s 1951 book “Applied Kinematics” [14], the following: In reality no machine element is completely rigid, and any deformation, either elastic or plastic, results in a small additional motion. More significant than the additional motion itself is the resulting change in the force equilibrium as compared with the assumption of rigid bodies. But elastic deformations, at least, need not be regarded as a disadvantage. They offer the advantage that unforeseen peak forces can be carried by the mechanism without damage. However, a rigorous treatment of these effects is not yet possible with the present status of scientific knowledge, and therefore, there is nothing to do but assume rigid members, and then make an estimate of the elastic effects. In any case, the elastic deformations make a possible additional, welcome, degrees of freedom for problems of kinematic design.

Therefore, just as Reuleaux had shown the way for composing machines with kinematic pairs, rigid and flectional, with the advances in compliant mechanisms in mind, we should educate a beginner with this integrated notion. As shown in Fig. 16.7,

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we must include elastic pairs and elastic chains. This means that kinematics cannot divorce itself from forces entirely. In fact, when kinematics of deformable bodies is considered, the notion of forces and material properties can still be separated out. Pseudo rigid-body model [25] and spring-lever [43], and spring-mass-lever [44] models are steps in the right direction. As an example, consider Grübler’s formula that counts rigid bodies and kinematic pairs to arrive at the degrees of freedom (DoF). DoF = 6(n − 1) − 5 f 1 − 4 f 2 − 3 f 3 − 2 f 4 − f 5

(16.1)

This has already been extended for compliant mechanisms by introducing elastic pairs and segment compliance of elastic segments [23] and introducing the concept of virtual rigid segments to account for force-application points [45]. DoF = 6(n seg − 1) −

5 Σ j=1

(6 − j )n K j −

5 Σ

(6 − j )n C j −6n f i x +

j=1

6 Σ

j n scj

j=1

(16.2) n seg nK j nC j n f ix n scj

number of segments (rigid or compliant) number of kinematic pairs allowing j relative dof. number of elastic pairs allowing j relative dof. number of fixed connections. number of segments with segment compliance of j.

Since compliant mechanisms occupy the large continuous spectrum between stiff structures and compliant mechanisms, it is useful to integrate mechanics of deformable solids and rigid solids. It is interesting to note that Maxwell’s rule for static determinacy is consistent with Grübler’s formula if we consider Calladine’s extension [46] of it. Maxwell’s formula for static determinacy of trusses : 3v − 6 − b = 0

(16.3)

where v = number of vertices and b = number of bars. Calladine’s extension to Maxwell’s formula : 3v − 6 − b = DoF − SoSS (16.4) Here, DoF is the usual kinematic notion of degrees of freedom (instantaneously for a truss) and SoSS is the number of states of self-stress. SoSS for a truss means that a change in length of a bar induces that many independent eigenstresses into the truss members. To understand this, it is useful to consider the force equilibrium and compatibility conditions for planar trusses (see Fig. 16.8). If denote the displacements of vertices of a truss with u (a column array) and elongations with e (another column array), the compatibility matrix relates the two column arrays. Likewise, the external forces at vertices and the internal forces are

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Fig. 16.8 Conjugacy of forces and displacements in trusses: kinematic compatibility and force equilibrium

related by the force equilibrium matrix. In Fig. 16.8, these relationships are shown with the sizes indicated for the 2D trusses with v vertices and b bars. Also indicated in Fig. 16.8 is that the two matrices are transpose of each other as can be understood from the principle of virtual work. Furthermore, the rank-deficiency of the force equilibrium matrix and displacement-compatibility matrix, respectively, indicate the DoF and SoSS. This reinforces that the forces and displacements are conjugate and that it holds for rigid bodies and deformable bodies alike. If this is taught, along with Grübler’s and Maxwell’s formulae, students would understand instantaneous DoF and SoSS. Then, the inherent relationship between structures and mechanisms could be appreciated at the outset. Consequently, analysis of deformable-body structures and rigid-body mechanisms could be considered together. Another advantage of this is that the special geometric conditions under which Grübler’s and Maxwell’s formulae fail can also be handled easily. Special configurations will no longer be special, opening up the possibilities for understanding the symmetries of well-known over-constrained linkages. Keeping the focus on synthesis is crucial. Kinematics books (e.g., [47, 48]) do include synthesis but there should be conscious efforts to include it in the curriculum. Limiting it to four-bar, slider-crank, and cam-follower mechanisms is not enough today. It will be nice to take contemporary applications as examples. Humanaugmentation devices such as prostheses and orthoses, assistive devices, surgical tools, MEMS, consumer products, and many others still include ingenious mechanisms despite increasing incorporation of sensors, actuators, and electronics. More importantly, the curriculum should not stop with only kinematic analysis, it must incorporate force and time to provide an overall view of a complete machine or a device.

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While bringing in elastic bodies into kinematics is a welcome addition, accounting for fluidic effects (pressure organs of Reuleaux) needs new developments in pedagogy. Transduction should come into the ambit of teaching mechanisms. Microsystems devices makes it imperative to combine elastic body mechanics with other energy domains including acoustic, electrical, magnetic, optical, thermal, and other domains. There is kinematics in all of this and Euler’s suggestion of separating the study of motion is still relevant but not complete disassociation. Analyzing kinematics when materials undergo phase change or growth is also possible. In all of these, there is relative motion at multiple levels. Molecular motions (as noted by Ampére, Reuleaux and others) and atomic displacements do involve kinematics. None of it is farfetched because there are sporadic studies on all these aspects. For example, protein kinematics is already well researched [49, 50]. By expanding the scope of kinematics, we can keep it alive and thriving. Mechanisms is not just about four-bar linkages, gear trains, and cam-follower assemblies. They are ubiquitous in all fields at many size scales, astronomic and atomic.

16.5 Closure The elaboration of the rich history of kinematics of mechanisms is deliberate in this article because the past always has many lessons for us. Inclusion of a much wider range of elements, deformable and fluidic in particular, was missed while rigidbody kinematics progressed in the twentieth century. Fortunately, deformable-body mechanisms are being pursued with much vigor in the field of compliant mechanisms alongside the thriving field of robotics, which too has taken the elastic turn as soft robotics. Miniaturization has nudged kinematicians to probe the biological world at small scales. The fields of biohybrid mechanisms have taken root and human augmentation aids are on the rise. With all these in view, divorcing force and time from kinematics does much injustice to the three allied fields that Koetsier noted in his imaginative intersection of geometry, mechanics, and machines. There is a need to add a fourth entity—the materials. Only a passing mention has been made to metamaterials and architected materials in this article but there are a lot of opportunities to join hands with materials engineers as they are embarking on the quest for designing tailor-made materials and creating material genomics. Kinematics of mechanisms thus encompasses four fundamental fields today and has limitless applications both in the inanimate and animate worlds around us. It won’t become obsolete anytime soon. A personal note “Ain’t kinematics of mechanisms an old hat?” was the cautionary advice given by a distinguished American professor to me when I was looking for a doctoral program in the United States of America. I neither understood the purport of that caution nor was I dissuaded by it. A few circumstances led me in the direction of microelectromechanical systems (MEMS) while pursuing interests in kinematics. Investigating synthesis

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problems in the emerging areas of MEMS and compliant mechanisms was exciting. It pulled me to pioneering works in structural optimization as much as it dragged me back to kinematics. Noticing the role of kinematics in elastic structures did not escape me. Gradually, the parallels between stiff structures and rigid-body mechanisms became apparent and so did their differences. Compliant mechanisms straddle between the two. It is inspiring to note that great scientists and engineers had never ignored the important role of elastic deformation in mechanisms and machines. With more aspects, including biomechanical and biological as well as materials, added to it, kinematics of mechanisms would remain relevant as an active area of academic research and attractive area of industrial practice. Incidentally, my doctoral adviser, Prof. Sridhar Kota, was asked the same old hat question by another distinguished professor at the University of Michigan, Ann Arbor, when he (Kota) began his faculty career there. He was advised to work on more contemporary topics to get tenure! Clearly, it did not dissuade him, and that spirit got passed on to me. He noted in an email sent to me at the time of writing this: “The fundamental understanding of relative motion cannot be an old hat as long as relative motion exists.” And that is for as long as there is movement in the universe. Acknowledgements This article would not have been written but for the encouragement and patience of Prof. Uday Shankar Dixit. I am indebted to him and I am gratified that I got the opportunity to closely examine the history and development of kinematics. Sage advice from Prof. Amitabh Ghosh and Prof. Asok Mallik is also gratefully acknowledged.

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G. K. Ananthasuresh is a Professor of Mechanical Engineering at Indian Institute of Science, Bengaluru. A BTech from IIT-Madars, MS from University of Toledo and PhD from the University of Michigan, Ann Arbor, Prof. Ananthasuresh has been researching and teaching mechanisms for over a quarter century. Presently he is Dean of the Division of Mechanical Sciences at Indian Institute of Science. He is widely known for his work in the areas of Compliant Mechanisms, Topology Optimization, Microelectromechanical Systems, and bio-medical devices and mechanics.