Recent Advances in Materials Processing and Characterization: Select Proceedings of ICMPC 2021 (Lecture Notes in Mechanical Engineering) 9811953465, 9789811953460

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Lecture Notes in Mechanical Engineering

A. Arockiarajan · M. Duraiselvam · Ramesh Raju · N. Subba Reddy · K. Satyanarayana   Editors

Recent Advances in Materials Processing and Characterization Select Proceedings of ICMPC 2021

Lecture Notes in Mechanical Engineering Series Editors Fakher Chaari, National School of Engineers, University of Sfax, Sfax, Tunisia Francesco Gherardini , Dipartimento di Ingegneria “Enzo Ferrari”, Università di Modena e Reggio Emilia, Modena, Italy Vitalii Ivanov, Department of Manufacturing Engineering, Machines and Tools, Sumy State University, Sumy, Ukraine Editorial Board Francisco Cavas-Martínez , Departamento de Estructuras, Construcción y Expresión Gráfica Universidad Politécnica de Cartagena, Cartagena, Murcia, Spain Francesca di Mare, Institute of Energy Technology, Ruhr-Universität Bochum, Bochum, Nordrhein-Westfalen, Germany Mohamed Haddar, National School of Engineers of Sfax (ENIS), Sfax, Tunisia Young W. Kwon, Department of Manufacturing Engineering and Aerospace Engineering, Graduate School of Engineering and Applied Science, Monterey, CA, USA Justyna Trojanowska, Poznan University of Technology, Poznan, Poland

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A. Arockiarajan · M. Duraiselvam · Ramesh Raju · N. Subba Reddy · K. Satyanarayana Editors

Recent Advances in Materials Processing and Characterization Select Proceedings of ICMPC 2021

Editors A. Arockiarajan Department of Applied Mechanics Indian Institute of Technology Madras Chennai, Tamil Nadu, India Ramesh Raju Department of Mechanical Engineering Sree Vidyanikethan Engineering College (Autonomous) Tirupati, Andhra Pradesh, India

M. Duraiselvam Department of Production Engineering National Institute of Technology Tiruchirappalli Tiruchirappalli, Tamil Nadu, India N. Subba Reddy Department of Metallurgical and Materials Engineering Gyeongsang National University Jinju, Korea (Republic of)

K. Satyanarayana Department of Mechanical Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad, India

ISSN 2195-4356 ISSN 2195-4364 (electronic) Lecture Notes in Mechanical Engineering ISBN 978-981-19-5346-0 ISBN 978-981-19-5347-7 (eBook) https://doi.org/10.1007/978-981-19-5347-7 © 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

Contents

Productivity and Safety Improvement in Industry Using Ergonomics—A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hanumantu Krishna Murty Dora, L. Siva Rama Krishna, and P. Ravinder Reddy

1

Transmetalation: A Post-synthetic Modification Tool for Functional Metal–Organic Framework Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sathish Kumar Kurapati

15

The 2D and 3D Protein Sequencing Implementation Using Ant Colony Optimization Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Ramya Sree, T. Indira Priyadarshini, and Tejaswi Borra

33

Optimizing the Peak-Ageing Conditions for Microalloyed 2219Al Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sanjib Banerjee and Sanjib Gogoi

43

Optimization of Process Parameters in W-EDM with HCHCR by Using Taguchi Optimization Technique and Grey Relational Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. Sathish Kumar and B. Satyanarayana Future Generation Materials and Techniques for Sustainable Construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rajesh Kumar, Vanita Aggarwal, and Surinder M. Gupta Tribological Characterization of Microalloyed Al-Cu Alloys by Artificial Neural Network Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sanjib Gogoi, Dewesh Kumar, Sanjib Banerjee, Sushen Kirtania, and Satadru Kashyap

55

67

83

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Design and Fabrication of Impression Creep Testing Setup and Experimental Validation with 2219Al Alloys . . . . . . . . . . . . . . . . . . . . . Sanjib Gogoi, Reeturaj Boruah, Mehsana Ahmed, Sanjib Banerjee, Sushen Kirtania, and Satadru Kashyap

93

Theoretical Comparison of Properties and Their Characteristics Features for Additive Manufactured Metal and Ceramic Structures . . . . 107 Utkarshika Chandra, Rajesh Kumar Porwal, Sanjay Mishra, and Basanta Kr Bhuyan Relative Investigation of Thermal Buckling Analysis of Nickel and Functionally Graded Material Rectangular Plate . . . . . . . . . . . . . . . . . 127 Mrinal Gautam and Manish Chaturvedi Aqueous Extract of Colocasia Esculenta Leaves for Prevention of Low Carbon Steel Corrosion in 0.5 M NaCl . . . . . . . . . . . . . . . . . . . . . . . . 137 Vinit Kumar Jha, Vivek Porwal, Gopal Ji, and Rajiv Prakash Alternate Material’s Approach Toward Green Construction . . . . . . . . . . . 149 Nitu, Rajesh Kumar, Vanita Aggarwal, and Surinder M. Gupta Effect of Various Tools on Bone Condensing to Improve the Stability of Dental Implant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Mohit Phadtare, Parth Jain, and Pankaj Dhatrak Investigation on the Microstructure–Corrosion Correlation of Commercially Available AISI 1020 and 304 Steel . . . . . . . . . . . . . . . . . . . 175 Sudesna Roy, Bijaya Bijeta Nayak, and Sasmita Sahu Thermal Buckling Analysis of Tri-directional Functionally Graded Material Plate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Mrinal Gautam and Manish Chaturvedi Investigation of Modal Analysis of Tri-Directional Functionally Graded Material Plate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Mrinal Gautam and Manish Chaturvedi Modelling of Structural Responses for Pineapple Leaf Fibre Epoxy Composite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Partha Pratim Borah, Satadru Kashyap, Sushen Kirtania, and Sanjib Banerjee Investigation of Mechanical Properties of Carbon Fiber/Graphene Nanoplatelet/Epoxy Hybrid Nanocomposites . . . . . . . . . . . . . . . . . . . . . . . . . 211 Mriganan Madhab Bordoloi, Sushen Kirtania, Satadru Kashyap, and Sanjib Banerjee Finite Element Analysis of Natural Hemp Fiber-Based Composite for Semi-elliptical Multi-leaf Spring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 Bitu Moni Das, Sushen Kirtania, Sanjib Banerjee, and Satadru Kashyap

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Fabrication and Testing on Mechanical and Thermal Properties of Jute/Hemp Fiber Hybrid Composites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 K. Venkatarao, K. SivajiBabu, and G. Ranga Janardhana A Review: Investigation of Length Effect in Carbon Nanotube (CNT)-Reinforced Aluminum (Al) Composites . . . . . . . . . . . . . . . . . . . . . . . 253 K. G. Thirugnanasambantham, Devarapalli Sai Charan Reddy, Tadikonda Vishnu Vardhan, and Sama Abhinav Reddy Experimental Investigation on the Performance of Inconel 718 Using MQL Grinding Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263 Farooqui Rizwan Ahmed, Prameet Vats, Rabesh Kumar Singh, and Anuj Kumar Sharma Investigating Machinability of Microalloyed Al-Cu Alloys by Simulation of Cutting Force . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 Sanjib Gogoi, Bhargab Nath, Bhagyashree Konwar, Avinava Bora, Sanjib Banerjee, Satadru Kashyap, and Sushen Kirtania Electrochemical Analysis of Corrosion Inhibition of Low Carbon Steel in 0. 1 N HCl by Bottle Gourd Peels . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287 Pragati Srivastava, Shweta Pal, Vinit Kumar Jha, Gopal Ji, and Rajiv Prakash Study of Rotating Arc Welding Process for Joining of Pipes: An In-Depth Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297 Ahmed Abdul Muneem, P. Laxminarayana, and M. Viquar Mohiuddin A Study of the Coefficient of Friction in DP-590 Steel Sheets Forming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 K. Seshacharyulu and B. Balu Naik Enhancement of Machinability Characteristics of Superalloys Using Textured Tools: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319 Krishna Mohan Buddaraju, G. Ravi Kiran Sastry, Satyanarayana Kosaraju, and G. Sainath Identification of SMAW Surface Weld Defects Using Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 K. Ramesh, E. V. Ramana, L. Srikanth, C. Sri Harsha, and N. Kiran Kumar The Influence of Machine Learning in Additive Manufacturing . . . . . . . . 351 Ramesh Raju, N. Manikandan, D. Palanisamy, P. Thejasree, P. Satheesh Kumar, P. Mohammed Rizwan Ali, and P. Sivakumar Temperature Robust Health Bench-Marking and Monitoring of an Heritage Suspension Bridge Using Coupled IWCM and TBSI Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363 Yeturi Pramod Kumar Reddy and Subhamoy Sen

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Electrical Characterization of Silicon Nitrate-Coated Polycrystalline Solar Cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 Srinivasa Rao Davu, Ramesh Tejavathu, and Suresh Kumar Tummala

About the Editors

Dr. A. Arockiarajan is currently working as professor at Solid Mechanics Division, Department of Applied Mechanics, Indian Institute of Technology (IIT) Madras, India. He obtained his B.E. from M.S. University, Tirunelveli, M.E. from Bharathiyar University and Ph.D. from the University of Kaiserslautern, Germany. His major areas of research interests include smart materials and structures, composites, biomaterials. He has published more than 140 research articles and received nearly 6 crore INR worth of research projects from various funding agencies. Dr. M. Duraiselvam is currently working as professor at the Department of Production Engineering, National Institute of Technology (NIT) Trichy, India. He graduated from CIT, Coimbatore with a bachelor’s degree in mechanical engineering. He has completed master’s degree from NIT Trichy. He has completed Ph.D. from Technical University of Clausthal, Clausthal-Zellerfeld, Germany under DAAD Fellowship. Dr. Durai was also awarded Young Scientist by Department of Science and Technology, Government of India and received nearly 8 crore INR worth of research projects. He has also published nearly 100 research articles. Dr. Ramesh Raju is currently working as Associate Professor at the Department of Mechanical Engineering, Sree Vidyanikethan Engineering College (Autonomous), Tirupati, Andhra Pradesh, India. He graduated from Shanmugha College of Engineering, Thanjavur, Bharathidasan University and obtained his post-graduation from TCE Madurai, Anna University. He obtained his Ph.D. from National Institute of Technology (NIT) Trichy. Dr. Raju has been awarded 2 Indian patents and published more than 60 research articles. His areas of interest are additive manufacturing, laser material processing and surface engineering. Dr. N. Subba Reddy is currently working as professor at School of Materials Science and Engineering, Department of Metallic and Materials Engineering, Gyeongsang National University, South Korea. He graduated from AMIE, IE, Kolkata with a bachelor’s degree in mechanical engineering. He has completed master’s degree and Ph.D. from Indian Institute of Technology (IIT) Kharagpur. Dr. Reddy was also ix

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About the Editors

awarded Greaves Foseco Award by IIT Kharagpur, India and received a patent. He has published more than 80 research articles in respected international and national journals. Dr. K. Satyanarayana is currently working as associate professor at the Department of Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India. He graduated from JPNCE, Mahabubnagar, with a bachelor’s degree in mechanical engineering. He has obtained master’s degree and Ph.D. from National Institute of Technology (NIT), Warangal. Dr. Satyanarayana received nearly 1.5 crore INR worth of research projects from various funding agencies and published more than 30 research articles in respected international and national journals.

Productivity and Safety Improvement in Industry Using Ergonomics—A Case Study Hanumantu Krishna Murty Dora, L. Siva Rama Krishna, and P. Ravinder Reddy

Abstract The goal of fitting task is popularly known to be ergonomics. Enthusiastic superior ergonomics attains improved productivity thereby improving the health and safety of employees, privileged job contentment and better conformity by means of government set of laws. The broad spectrum of ergonomics ideology with the intention of functional to the place of work embraces aiming for energetic in opposition to static work, keeps away from overload of muscles, to make effective use of work surface heights, avoid deviant postures and educate individuals to utilize workplace, ability and apparatus appropriately. This present work aims to determine the productivity rate of the industry and product produced by the company before and after the intervention of the ergonomic principles to the employees of organization working in various departments. Parameters considered as ergonomics are anthropometry, seat design, manual materials handling, and it focuses on most common musculoskeletal disorders (MSDs) such as cumulative trauma disorders and lower back injuries. Keywords Musculoskeletal disorders (MSDs) · Cumulative trauma disorders (CTDs) · Ergonomics · Productivity · Stress

1 Introduction Ergonomics is the sciences of fitting task and design the office, by observance in intellect potentials and boundaries of the worker. Poor work-site intention leads to exhaust, frustrated and hurt workers. This infrequently led to the majority prolific H. K. M. Dora (B) Mechanical Engineering Department, Muffakham Jah College of Engineering & Technology, Hyderabad, India e-mail: [email protected] L. Siva Rama Krishna Mechanical Engineering Department, University College of Engineering (A), Osmania University, Hyderabad, India P. Ravinder Reddy Chaitanya Bharathi Institute of Technology (A), Hyderabad, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_1

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H. K. M. Dora et al.

workers. More liable, it escorts to an aching and expensive injury, inferior productivity and underprivileged product worth. Methodical ergonomics upgrading progressions remove threat factors that escort to musculoskeletal injuries and tolerates for enhanced human presentation and efficiency. By creation enhancement to the work route, one can eliminate barriers to greatest safe work routine. The company is laid with socio-responsibility to see that the worker is surrounded by their body’s abilities and boundaries. Through well, an ergonomics enhancement method can be an entire provider to ones company’s competitiveness in the market and present a better work familiarity for the worker community. Main principle behind the ergonomics is to trim down work stresses that may affect the health consequence and can be stop happening [1]. These work stress hormonal (e.g. extreme replication, vigorous exertion, static positions, vibrations, cold temperature, compression, poor work-station design and awkward movements) support rhythmic or growing injuries and accordingly exaggerate the commonness of common musculoskeletal turmoil like tendonitis, bursitis, epicondylitis, carpal tunnel syndrome, trigger finger, etc. [2]. In accumulation, nonexistence of ergonomically premeditated job has resulted in corporal vulnerability (e.g. light, temperature, vibration, noise and radiations) chemical or biological vulnerability; psychosocial vulnerability; sickness non-attendance; industrial cancers; and accidents [2–4].

2 Literature Review In current scenario, it has been seen a substantial increase of cumulative trauma disorders (CTD) in past decades. In the USA, the digit of statement upper-limit confusions has tripled stuck between 1986 and 1993 by [5]. A comparable inclination is noticed in supplementary mechanized nations. Hagberg et al. [6] designated “Work-related musculo-skeletal disorders (MSD) represent a chief difficulty in countless mechanized countries.” Cumulative trauma disorders (CTDs) accounted in the USA for above 60% of all job-related sickness in 1990 [7]. Fraction of this augment is ascribed to enhanced appreciation and treatment [8]. Also, of significant consequence, is the detail that vocations in a traumatic and exceedingly aggressive global economy tend to be exceedingly rapidity and repetitious [9–11]. Design is capable of trim down the possibility changes and corollary of error [12]. Emergent a structure ample of accepting the users, the paraphernalia to facilitate they utilize and the atmosphere in which the employment survive and are wired to drawn near. [13]. Designed for medical diplomacy, such as concoction pumps, here are numerous cases in spot of revamp that would diminish fault rates [14, 15]. In this gear priceless breaks have been missed: formerly apparatus has been positioned; it is not easy to keep informed or amend it. There comprise been titled for an increase of rate of the amalgamation of Human Factors (HF) and ergonomics in unwearied protection, together with the conception of “market armed forces for producers to generate safer goods that integrate Human Factor Engineering [HFE] principles and performance” [16]. The term HFE is not only applicable to application

Productivity and Safety Improvement in Industry Using Ergonomics …

3

of theory, but also statistics and scheme to propose in classify to optimize human security and largely scheme concert. Modern study tentative to the rapport between healthcare proficient and apparatus contributor has brought into being numerous hurdles to the development of common argument. Money et al. [17] initiate that UE/HFE observed is inhibited by an excess of confidence on partial information of elder healthcare staff. They also originate an escaping of session in the midst of patients or fewer senior staff, and a propensity to craft design alterations on the root of perception somewhat than the more formal approach of user testing. There were biases towards collecting measures of worth to convene the wants of acquiring or valuation agencies [18]. To regulate lessen the encumber of the industrial vulnerability, especially in the health concern sector, here is a necessitate to intents and purposes pay attention to wellbeing of all the stakeholders [19]. On other hand, it is a responsibility to rationalize the complete progression of health care to guarantee facilitation of ergonomically promoter observers [4]. The planned quantify series guarantee the proper outline of the company; creating consciousness between the hospital staff in relation to the livelihood vulnerability and necessitate by means of individual defensive equipment/subsequent the homogeneous code of behaviour; implementing proper procedures to preserve hygiene surrounded by the property and therefore be in command of infectious diseases; mounting a protocol for mannering a medical assessment of the healthcare employees, particularly nursing and maintenance staff, to consent untimely gratitude of signs and indications of occupationinduced sickness; and by approving appropriate engineering events to make possible computerization, diminish human workload and concurrently make certain patient safety [3, 4, 20–22]. Little research work was done on ergonomic factors that affect the productivity rate in the industry. The present work is focused on studying the ergonomic factors affecting the productivity rate in (XYZ) PVT LTD Company. (As per requirement company name not to be mentioned).

3 Productivity and Case Study Productivity can also be determined as the efficiency of the production of the product in the company. It is expressed as ratio of output achieved to the input given in the production process. It is a key parameter in industries and also a performance factor to firm and nation. Living standard is based on the productivity of the goods and services and many more in the nation. It also helps in profitable business to the entrepreneurs. During the productivity, it may incur the risk factors in terms of ergonomics risk like musculoskeletal disorders (MSDs) such as cumulative trauma disorders and lower back injuries and also high task repetition, forceful exertions and repetitive sustained awkward postures.

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H. K. M. Dora et al.

A. Company Profile: It is multibranded company which produces variety ranges of chemicals, unsaturated polyester resins and specialty chemicals. It is located 20 km from Hyderabad. B. Parameters used in evaluating the performance of the employees in organization. Musculoskeletal disorder (MSD) is a disorder which affects the human body movement (i.e. ligaments, discs, blood vessels, tendons and muscles). Apart from this, there are many effects that causes due to MSDs are radial tunnel syndromes, ruptured disc, tension neck syndrome, etc. Cumulative trauma disorder (CTD) is one of the MSDs which cause repetitive strain injuries (RSIs). These injuries mainly occur in joints, moving parts, low back, shoulder, wrist, knee and elbow. The stresses developed in the body parts are assessed based on the age groups, departments, shift system, and the report is submitted to the organization to study the effect of the productivity rate. Sample questionnaires as shown in Figs. 1, 2, 3, 4 and 5 are used for evaluating the process. Number of employees in organization are approximately 200 with 25–40 members in each department including supervisors and labours. In the form, the stresses developed in body parts like hand and wrist, back, neck and knee are determined by following the rating system from 0 to 10. Zero is no

Fig. 1 Assessment sheet used in studying the behaviour of the employee of the organization in storage department morning shift

Productivity and Safety Improvement in Industry Using Ergonomics …

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Fig. 2 Assessment sheet used in studying the behaviour of the employee of the organization in plant D evening shift

Fig. 3 Assessment sheet used in studying the behaviour of the employee of the organization in goods loading morning shift

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Fig. 4 Assessment sheet used in studying the behaviour of the employee of the organization in storage department morning shift

Fig. 5 a Dispatch section and b loading and unloading of the materials

Productivity and Safety Improvement in Industry Using Ergonomics …

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Table 1 Assessment in storage department (February) Employees assessed

Body parts (stress)

Average rating (0–10) before ergonomics intervention (1st Feb)

Average rating (0–10) after ergonomics intervention (28th Feb)

Percentage of change in stress behaviour

30

Hand and wrist

8

4

50

30

Back

7

4

42.8

30

Neck

8

4

50

30

Knee

6

3

50

effect, and 10 is maximum effect. Based on this rating system, the performance is evaluated in various plant locations in the organization. The ratings of the employees are shown in Tables 1, 2, 3, 4, 5 and 6. Table 2 Assessment in plant D department (February) Employees assessed

Body parts (stress)

Average rating (0–10) before ergonomics intervention (1st Feb)

Average rating (0–10) after ergonomics intervention (28th Feb)

Percentage of change in stress behaviour

35

Hand and Wrist

7

3

57.14

35

Back

7

3

57.14

35

Neck

8

4

50

35

Knee

7

3

57.14

Table 3 Assessment in packing department (February) Employees assessed

Body parts (stress)

Average rating (0–10) before ergonomics intervention (1st Feb)

Average rating (0–10) after ergonomics intervention (28th Feb)

Percentage of change in stress behaviour

32

Hand and wrist

8

4

50

32

Back

7

3

57.14

32

Neck

6

4

33.33

32

Knee

7

3

57.14

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H. K. M. Dora et al.

Table 4 Assessment in dispatch department (February) Employees assessed

Body parts (stress)

Average rating (0–10) before ergonomics intervention (1st Feb)

Average rating (0–10) after ergonomics intervention (28th Feb)

Percentage of change in stress behaviour

40

Hand and Wrist

9

4

55.55

40

Back

8

4

50

40

Neck

7

3

57.14

40

Knee

8

3

62.5

Average rating (0–10) after ergonomics intervention (28th Feb)

Percentage of change in stress behaviour

Table 5 Assessment in administrative office (February) Employees assessed

Body parts (stress)

20

Hand and wrist 10

4

60

20

Back

8

5

37.5

20

Neck

9

4

55.55

20

Knee

7

3

57.14

Average rating (0–10) before ergonomics intervention (1st Feb)

Table 6 Productivity Department

Employees

Productivity before ergonomic intervention (January)

Productivity after ergonomic intervention (February)

Percentage of change in stress behaviour

Storage

30

111

127

12.59

Plant D

35

97

116

16.37

Packing

32

130

153

15.03

Dispatch

40

130

159

18.23

Administrative office

20

20

30

33.33

4 Results and Discussions The productivity rate of the company is based on the output that they achieved at the end of the month. In this process, ergonomics principle was used to predict the productivity rate and safety of the employees of the organization. Beginning of the month a report as shown in Fig. 1 is submitted to the employees to rate the stresses that they are undergoing during their various operations in the organization in various

Productivity and Safety Improvement in Industry Using Ergonomics …

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departments. Stresses developed in the body are rated from the scale of 0–10, and the same data is collected by each employees working in the department without ergonomic intervention and with ergonomic intervention. The results are plotted in the graphs from Figs. 6, 7, 8, 9, 10, 11 and 12. From the results, it is observed by following the ergonomic intervention in the company in various departments the health issues in terms of stresses developed

Fig. 6 Stress developed on the body part before and after ergonomic intervention in storage department

Fig. 7 Stress developed on the body part before and after ergonomic intervention in plant D department

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Fig. 8 Stress developed on the body part before and after ergonomic intervention in packing department

Fig. 9 Stress developed on the body part before and after ergonomic intervention in dispatch department

in the body parts have reduced to some extent through which the productivity rate has increased. This increase in productivity rate is because the employees have not availed the medical leaves and they are continuously working in their respectively department.

Productivity and Safety Improvement in Industry Using Ergonomics …

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Fig. 10 Stress developed on the body part before and after ergonomic intervention in administrative office

Fig. 11 Product developed or output achieved by the company before and after ergonomic intervention for February month

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Fig. 12 Product developed or output achieved by the company after ergonomic intervention for February to May months

5 Conclusion An ergonomic intervention was performed in which those relevant anthropometric dimensions involved in man–machine interaction were identified. These improvements to the ergonomics of the workplace increased the productivity and reduced the risk to health issues and accidents. The application of ergonomic principles would help to increase workers performance, productivity and safety. Also it helps human operator to be comfortable and secure. Since at present time, the vast majority of the companies acquired Advanced Manufacturing Technology in order to be competitive, ergonomic and safety aspects must be considered as one of most effective ways to accomplish the improvement in productivity and safety.

References 1. Wilson JR (2014) Fundamentals of systems ergonomics/human factors. Appl Ergon 45:5–13 2. Rehman R, Khan R, Surti A, Khan H (2013) An ounce of discretion is worth a pound of wit—ergonomics is a healthy choice. PLoS One 871–891 3. Park K (2009) Occupational health. In: Park K (ed) Text book of preventive and social medicine, 20th edn. Banarsidas Bhanot Publishers, Jabalpur, pp 708–719 4. Izumi H (2013) The role of ergonomics in occupational health—past and future. J UOEH 35(Suppl):127–131 5. Bureau of Labour Statistics (1993) Occupational injuries and illnesses in the United States by industry, 1991. US Department of Labor, Washington, DC, Bulletin 2424 6. Hagberg M, Silverstein B, Wells R, Smith MJ, Hendrick HW, Carayon P, Pirusse M (1995) Work related musculoskeletal disorders (WMSDs): a reference book for prevention. Taylor & Francis, London

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7. Bureau of Labour Statistics (1994) Workplace injuries and illnesses in 1993. US Department of Labor, Washington, DC, USDL 94–600 8. Brogmus GE, Sorock GS, Webster BS (1996) Recent trends in work-related cumulative trauma disorders of the upper extremities in the United States: an evaluation of possible reasons. J Occup Environ Med 38:401–411 9. Guidotti TL (1992) Occupational repetitive strain injury. Am Earn Phys 45:585–592 10. Putz-Anderson V (1988) Prevention strategies adopted by select countries for work-related musculoskeletal disorders from repetitive trauma. Trends Ergon Hum Fact 5:601–611 11. Yassi A, Sprout J, Tate R (1997) Upper limb repetitive strain injuries in Manitoba. Am J Ind Med 12. Clarkson PJ et al. (2004) Design for patient safety: a scoping study to identify how the effective use of design could help to reduce medical accidents 13. Carayon PASH et al. (2006) Work system design for patient safety: the SEIPS model. BMJ Qual Saf 15(suppl 1):i50–i58 14. Lin L, Isla R, Doniz K, Harkness H, Vicente KJ, Doyle DJ (1998) Applying human factors to the design of medical equipment: patient-controlled analgesia. J Clin Monit Comput 14:253e263 15. Thimbleby H, Cairns P (2010) Reducing number entry errors: solving a widespread, serious problem. J R Soc Interface 7:1429–1439 16. Gurses AP, Ozok AA, Pronovost PJ (2012) Time to accelerate integration of human factors and ergonomics in patient safety. BMJ Qual Saf 21:347–351 17. Money AG, Barnett J, Kuljis J, Craven MP, Martin JL, Young T (2011) The role of the user within the medical device design and development process: medical device manufacturers’ perspectives. BMC Med Inform Decis Mak 11 18. Vincent CJ, Li Y, Blandford A (2014) Integration of human factors and ergonomics during medical device design and development: it’s all about communication. Appl Ergon 45(3):413– 419, ISSN 0003-6870. https://doi.org/10.1016/j.apergo.2013.05.009 19. Vincent CJ, Li Y, Blandford A (2014) Integration of human factors andergonomics during medical device design and development: it’s all about communication. Appl Ergon 45:413–419 20. Rogers B, Buckheit K, Ostendorf J (2013) Ergonomics and nursing in hospital environments. Workplace Health Saf 61:429–439 21. Higne S, Masud T (2006) A review of environmental hazards associated with in-patient falls. Ergonomics 49:605–616 22. Carayon P, Xie A, Kianfar S (2014) Human factors and ergonomics as a patient safety practice. BMJ Qual Saf 23:196–205

Transmetalation: A Post-synthetic Modification Tool for Functional Metal–Organic Framework Materials Sathish Kumar Kurapati

Abstract Post-synthetic modification is a valuable approach to tune the properties of materials after the traditional synthetic protocols without disturbing the core structure. Several post-synthetic methods are adopted for the modification of Metal– Organic Frameworks (MOFs). Transmetalation is a post-synthetic method where new metal ions exchange the metal ions of parent MOFs to tune the chemical and physical properties. Several transmetalation approaches were employed for the complete exchange or partial exchange of parent metal centers to give MOF materials with enhanced properties. In this article, a brief idea about transmetalation and its potential in the making functional MOFs was discussed by listing a few examples of contemporary interest. Keywords Metal–Organic Frameworks · Post-synthetic modification · Transmetalation · Single-crystal to single-crystal transformation · Mixed metal MOFs

1 Introduction Metal–Organic Frameworks (MOFs) secured their place as essential function materials of the decade for their miscellaneous applications in catalysis [1, 2], gas storage [3], gas separation [4–8], sensors [9, 10], drug delivery [11], and solar energyharvesting [12]. Properties of MOFs such as surface area [13], void space [14], luminescence [15], magnetism [16], and thermal and mechanical stability [17, 18] are remarkable. These versatile properties of MOFs are made them as functional materials in a diverse range of applications. The structural symphony of 2D and 3D MOFs is an example of masterpiece artwork and provides cavities and channels [19– 21]. “Node and spacer” [22, 23] and “secondary building unit (SBU)” [24, 25] models are generally adopted to design and synthesize crystalline MOFs. A broad synthetic S. K. Kurapati (B) Department of Chemistry, Chaitanya Bharathi Institute of Technology, Gandipet, Hyderabad 500075, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_2

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protocol for MOFs generally involves adding one or more organic ligand spacers to the metal precursor solution. The reaction mixture is allowed to react under various solvothermal conditions to obtain desired crystalline MOF material. The traditional way to modify the chemical and physical properties of MOFs involves a pre-synthetic modification of organic ligands and the usage of such modified ligands in the preparation of MOFs with expected properties. However, such pre-synthetic modifications may yield a MOF with different topology and undesired properties [26, 27]. On the other hand, the new functional groups of ligands may involve coordination with the metal ion, which is essential to be in its free form to impart the desired chemical and physical properties to the MOF. Sometimes, the desired functional group may not survive the reaction conditions and may undergo functional group transformation [28]. The post-synthetic modification (PSM) of MOFs is an important tool for chemists to synthesize desired MOFs without disturbing the existing network structure. The feasibility of PSM methods is mainly influenced by the stability of metal–ligand bonds in MOFs and the porous nature of MOFs to allow the exchange of guest species [29, 30]. The PSM methods for MOFs are majorly four types: (1) Metal-based, (2) Ligand-based, (3) Guest-based, and (4) Metal and Ligand-based (Fig. 1). The inclusion or replacement, or removal of metal nodes, ligands, guest species, and all together are involved in the PSM of MOFs. However, in the case of ligand-based modifications, the alteration of functional groups is also very often [31]. In general, these PSMs do not alter the topology of original MOFs, and, majorly, the reaction process is a single-crystal to single-crystal (SCSC) transformation [32]. Overall the PSM of MOFs offers the inclusion of a diverse range of functional groups on identical topologies with significant control over the functional groups and degree of modifications. Easy purification procedures are an added advantage since the PSMs involve heterogeneous reactions. Hence, tuning of MOFs’ chemical and physical properties is more facile via a PSM method. PSM is also found in other materials like proteins, carbon nanotubes (CNTs), and porous zeolites and silicates. The modification of proteins after translation is known as a post-translation modification (PTM). This concept observed in nature is very similar to PSM, where proteins are covalently modified for functionalization, and the modifications generally occur on amino acid sidechains of polypeptides [33, 34].

Fig. 1 Classification of post-synthetic modifications of MOFs

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The artificial PTM approach is widely applied to elucidate the function and mechanism of proteins and protein-bound pharmaceuticals in living organisms [35, 36]. PSM approaches extensive studies for carbon nanotubes (CNTs) for functionalization. CNT is a bulky π-conjugated alkene. Hence, the addition reactions (nucleophilic addition, radical addition, cycloaddition, and halogenation) and coordination of transition metal ions are used to modify the CNTs chemically. Such chemically modified CNTs found exciting applications like differentiation of single-walled CNTs with metallic and semi-metallic conductivities [37], chemical and biochemical sensing [38], materials applications [39, 40], and drug discovery and delivery [41, 42]. The replacement of coordinated water ligands with pyridine ligands in HKUST-1 is probably the first reported example for PSM of MOFs. The exchange of aqua ligands with pyridine ligands is facilitated by huge 9 × 9 Å2 square channels [43]. Another significant advancement in the PSM of MOF is the inclusion of ethylenediamine to coordinatively unsaturated Cr(III) metal nodes in MIL-1 MOF. Further, the amines of ethylenediamine groups are protonated to encapsulate the nanoparticles of noble metals like Pt and Pd. These modified MOFs are found to be excellent catalysts in Heck coupling reactions [44]. Coordinatively unsaturated metal centers of a copper-based MOF constructed with 1,3,5-tris(1H-1,2,3-triazol-5-yl)benzene) (H3 BTTri) linkers are functionalized with ethylenediamine via a PSM synthetic protocol. The derived MOF, which shows excellent gas absorption ability toward CO2 over N2, is also a considerable advancement in the PSM of MOF at the early stages [45]. These examples have provoked researchers across the globe to find new strategies in the PSM of MOF toward generating functional materials based on MOFs. As a result, several reports on the PSM of MOFs and their applications are published in a bit of time. Further, the PSM methods are more broadened into specific classes, as discussed above. Transmetalation is one of such classes and scientific communities around the globe exploring such methodology to make functional MOFs. In this regard, we have consolidated the significant results of the transmetalation of MOFs toward application-oriented functional materials. Unlike many elaborated reviews, we briefly discussed the transmetalation approaches, and particular emphasis is given to the applications of MOFs that have been derived via transmetalation. We hope our efforts in the form of this article will help the readers to find a summary of transmetalation PSM methods and applications of modified MOF materials.

2 Post-synthetic Modifications in MOFs PSMs on MOFs can be broadly divided into four classes: (1) Metal node-based PSM of MOFs, (2) Ligand-based PSM of MOFs, (3) Guest-based PSM of MOFs, and (4) Metal and Ligand-based PSM of MOFs. The present section covers some significant and recent examples of transmetalation PSM methods explored on MOFs and applications of such MOFs in various fields.

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3 Metal Node-Based PSM of MOFs The exchange of one metal ion with another (Transmetalation), the addition of ligands on coordinatively unsaturated metal nodes, and incorporation of new metal ions are considered and discussed as metal node-based PSM methods in this subsection. Transmetalation is one of such PSM methods extensively explored on MOFs.

3.1 Transmetalated MOFs and Functional Applications The preparation of desired metal ions containing MOFs from metal ions and corresponding organic linkers often forms undesired structures and topologies, and sometimes, the strategies may also fail. The exchange of metal nodes of existing MOFs with the desired set of metal ions is known as transmetalation. Transmetalation retains the structure and topology of the original MOF and allows us to tune MOFs’ electronic and chemical properties. However, transmetalation suffers four significant drawbacks: (1) loss of crystallinity during the PSM synthesis (which is vital to know the structural consistency after PSM), (2) incomplete exchange of host MOF metal ions with the new metal ions, (3) inability of desired metal ions to replace original metal ions in a PSM of MOF, and (4) stability of resulting MOF [31, 46]. The ability of one metal ion to replace another metal ion from a coordination sphere depends on the relative lability. The Irving–Williams stability order of divalent 3d-metal ions (Mn(II) < Fe(II) < Co(II) < Ni(II) < Cu(II) > Zn(II)) can help us to predict whether the desired transmetalation reaction can be possible or not (Scheme 1). Replacement of Mn(II) ions from the MOF, Mn3 [(Mn4 Cl)3 (BTT)8 (CH3 OH)10 ]2 , using Li+ , Cu+ , Fe2+ , Co2+ , Ni2+ , Cu2+ , and Zn2+ ions is believed to be the first example of transmetalation PSM [6, 47, 48]. In this example, the transmetalated MOFs are isostructural and structurally identical with the parent MOF irrespective of the type and oxidation state of exchanged metal ions. The study revealed that Mn(II) ions had been replaced by about 91%, by Ni(II) ions, from their parent MOF. The lowest replacement of parent metal ions was observed by univalent metal ions,

Scheme 1 Schematic representation of transmetalation in MOFs

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Li(I) and Cu(I). Transmetalated MOFs along with parent MOF were explored for their application as H2 sorption materials. It is found that the H2 sorption ability of MOFs is metal ion dependent. The MOF generated from Co(II) ions transmetalation reaction shows maximum H2 sorption capability compared to other transmetalated MOFs (T-MOFs) [48].

3.1.1

Sensing Applications of T-MOFs

Synthesis of a Ba(II)-based MOF formulated as [H2 N(CH3 )2 ][Ba(H2 O)(BTB)], where BTB is 1,3,5-benzenetricaboxylicacid, was reported by Asha and coworkers. The edge-shared BaO9 polyhedra forms 1D polymeric chains, and BTB linkers further connect these 1D polymers to give a 3D network. This MOF platform was transmetalated by Tb(III) ions in a (SCSC) transformation reaction. The crystalline material was soaked for 24 h in a dimethylformamide solution of Tb(NO3 )3 .7H2 O to exchange Ba(II) ions with Tb(III) ions completely. The process is monitored in real time by fluorescence microscope and Fe-SEM–EDX spectroscopy to know the complete metal ion exchange. Upon excitation at 320 nm, the transmetalated Tb(III) MOF shows emissions in the UV–visible region at various wavelengths (370, 486, 541, 583, and 618 nm). The emission at 370 nm is due to an LMCT transition. The emission intensity of this LMCT band shows an enhancement when dispersed in an aqueous solution of PO4 3− ions. This unique fluorescent emission property enables this MOF to work as an optical sensor to detect phosphate ions among the other common ions selectively Cl− , Br− , F− , I− , OAc− , ClO4 − , SO4 2− , S2− , NO2 − , NO3 − , and CO3 2− in the biological fluids [49] (Figs. 2 and 3).

3.1.2

Catalytic Applications of T-MOFs

Nonquantitative transmetalation of parent MOF can achieve mixed metal MOFs. These partially transmetalated MOFs show excellent catalytic properties due to the synergetic effect of two metal ions. A Ni(II)-based MOF derived from 2,4dihydroxyterpthalicacid linker was transmetalated with Co(II) by suspending the Ni-MOF in a dimethylformamide solution of Co(NO3 )2 .6H2 O for 4–5 days to yield transmetalated Co–Ni-MOF. The powder X-RD patterns of Ni-MOF and Co–NiMOF indicate structural similarity in both MOFs. About 60% of the Ni(II) ions were replaced by Co(II) in the synthesis, and the amount of Ni(II) ions released into reaction solution, analyzed by ICPMS analysis, confirms the % of Co(II) ions loading into the MOF. The original Ni-MOF was inactive as a catalyst in the catalytic oxidation of cyclohexene. However, the Co–Ni-MOF shows improved catalytic activity in the catalytic oxidation of cyclohexene. The improvement is also dependent on the Co(II) loading in the MOF. The authors explained that the cobalt ions could cycle between oxidation states Co(II) and Co(III), an essential property for the catalyst in oxidation reactions [50] (Fig. 4).

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Fig. 2 Analysis of transmetalation process in single crystals of [H2 N(CH3 )2 ][Ba(H2 O)(BTB)] by fluorescent emission microscope (top). The plausible mechanism of transmetalation in crystals of [H2 N(CH3 )2 ][Ba(H2 O)(BTB)] OL and Ow coordinated ligands from acid linkers and water molecules, respectively; OD is the oxygen from the solvent molecule. Adapted with permission [49]. Copy right 2016, Wiley–VCH

Metalloporphyrins are known for their excellent catalytic properties [51– 53]. Incorporation of such metalloporphyrins into rigid MOFs is an outstanding achievement. A synthesis of Cd(II)-based MOF, porph@MOM-10, derived from CdCl2 , biphenyl-3,4' ,5-tricarboxylate (H3 BPT), and meso-tetra (N-methyl4-pyridyl) porphinetetratosylate (TMPyP) was reported by Zhang et al. [54] Porph@MOM-10 was found to exhibit transmetalation with Mn(II) and Cu(II) ions and forms corresponding transmetalated MOFs Mnporph@MOM-10-Mn and Cuporph@MOM-10-CdCu. The transmetalation process is carried out in methanolic solutions of MnCl2 and CuCl2 , and the reaction solution is replaced with a fresh solution for every 24 h. The process monitored by spectral methods, UV–Visible spectroscopy, and AAS spectroscopy revealed that Mn(II) ions replaced the Cd(II) ions of porphyrin moiety in one week, and for the network Cd(II) ions, it took one month for the complete exchange. At the same time, Cu(II) ions replaced the Cd(II) ions of porphyrin moiety in 3 days. However, the network Cd(II) ions are partially replaced, 73%, even after one month. The catalytic performances of these MOFs were studied for the trans-stilbene epoxidation reactions. The results indicated that the parent Porph@MOM-10 shows only 7% of the conversion of stilbene to stilbene oxide and benzaldehyde. Under similar reaction conditions, the transmetalated MOFs, Mnporph@MOM-10-Mn, and Cuporph@MOM-10-CdCu, show

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Fig. 3 The response of fluorescence intensity of compound 2 a with the change in concentration of phosphate anion, b specific detection of H2 PO4 − anion over other common anions with compound 2, and c with the change in contact time with phosphate anion. Adapted with permission [49]. Copy right 2016, Wiley–VCH

Fig. 4 a Transmetalation of Ni-MOF to Co–Ni-MOF (top) and cyclohexene oxidation catalyzed by Co–Ni-MOF (bottom) and b transmetalation profile over incubation period and change of MOF color over a period reaction time. Adapted with permission [50]. Copy right (2015), American Chemical Society

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75% and 78% of conversions, respectively. The transmetalated MOFs are found to be active even after six reaction cycles of 12 h duration. A Zn(II)-based MOF prepared from a bent organic tetracarboxylic acid linker, 2' -amino-[1,1' :3' ,1'' -terphenyl]-3,3'' ,5,5'' -tetracarboxylic acid, and Zn(NO3 )2 .6H2 O also shows transmetalation with Cu(II) ions. The transmetalation process was performed by suspending the colorless crystals of Zn-MOF in a dimethylformamide solution of Cu(NO3 )2 .3H2 O for six days. The transmetalated MOF obtained was a greenish-blue crystalline substance. The X-ray fluorescence spectrum of transmetalated MOF indicates that no significant Zn(II) ions remain in the PSM-MOF framework. The transmetalated Cu(II) MOF shows significant catalytic activity in Knoevenagel condensation reactions. The reactions of benzene-based aromatic aldehydes and dinitromethane in the presence of 10 wt% of MOF catalyst yielded 90–95% of condensation product in 2 h. The fused ring polyaromatic aldehydes (naphthyl and anthryl) show little or no conversion under similar reaction conditions. This observation indicates that the MOF is acting as a molecular catalytic reactor for benzaldehyde derivatives since the pore of MOF can accommodate these benzaldehydes. Whereas the bulky aromatics cannot be intercalated into the pores of MOFs, hence showing lower or no conversions in the said condensation reaction [55] (Fig. 5).

Fig. 5 a Transmetalation of Porph@MOM-10 to Mnporph@MOM-10-Mn. b Catalytic activity profiles of trans-stilbene by Porph@MOM-10, Mnporph@MOM-10-Mn, and Cuporph@MOM-10-CdCu. Adapted with permission [54]. Copy right (2012), American Chemical Society

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Electrochemical Applications of T-MOFs

Zeolite-Imidazole frameworks (ZIFs) are one of few materials with high porosity, surface area, and excellent catalytic activity in various reactions. ZIFs are highly functional materials which found many applications in recent scientific advances [56–58]. ZIF-8 is a Zn-Methylimidazole zeolite MOF. Zhao et al. reported the transmetalation of ZIF-8 using Ni(II) ions and the pyrolysis of resulting PSM-MOF to produce an N-doped carbon skeleton incorporated with Ni single-atom sites (Ni NPs/N–C) [59]. The XPS spectroscopy suggested that Ni atoms are in their zero oxidation state in Ni NPs/N–C. Electrocatalytic CO2 reductions were carried out in a two-compartment and three-electrode electrolytic cell in 0.5 M potassium bicarbonate electrolyte solution, and Ni NPs/N–C was used as cathodic material. The CO2 was continuously purged into the electrolytic cell, and the effluents were pumped into the gas chromatographic instrument via a gas loop injector to monitor the gas-phase products. The resulting material shows excellent electrocatalytic activity toward reducing CO2 to CO, whereas the bulk Ni metallic foam shows a hydrogen evolution reaction under similar conditions (Fig. 6).

3.1.4

Photocatalytic Applications of T-MOFs

Similar to ZIF-MOFs, Uio-66 is another critical class of Zr-based MOFs. Many Uio-66 derivatives and analogs were synthesized and explored for their properties and applications, such as gas absorption, redox catalyst, and optical sensors [60–63]. NH2 -Uio-66(Zr) is an amine group-functionalized Ui-66 MOF. Transmetalation of NH2 -Uio-66(Zr) with Ti(IV) ions is achieved through a PSM method which involves immersion of NH2 -Uio-66(Zr) in dimethylformamide solution of TiCl4 (THF)2 for 4–16 days to yield NH2 -Uio-66(Zr/Ti). The maximum exchange was achieved after 16 days. It is also found that the rate and extent of Ti(IV) ions exchange are temperature-dependent, and at high temperature (120 °C), the rate and extent of Ti ions exchange are high in contrast to the similar process carried out at lower temperature (100 °C). The PXRD patterns of parent MOF and transmetalated NH2 -Uio-66(Zr/Ti) indicate that the original topology of parent MOF remains even after transmetalation. The transmetalation of Ti(IV) into NH2 -Uio-66(Zr/Ti) is further suggested by X-ray Absorption Fine Structure (XAFS) analysis. The geometry and type of coordinated atoms around newly incorporated Ti centers are similar to that of Zr metal centers of parent MOF. This observation suggests a true transmetalation of Zr with Ti into the MOF. The influence of Ti centers on photocatalytic reduction of CO2 to HCOO− studied. Photocatalytic reactions were performed using triethanolamine as sacrificial electron and proton donor and parent and 50 mg of transmetalated MOFs as photocatalyst in acetonitrile solvent. The results show that NH2 Uio-66(Zr/Ti) (prepared at 120 °C, reaction period 16 days) shows better activity over NH2 -Uio-66(Zr/Ti) (prepared at 100 °C, reaction period 16 days) and NH2 -Uio66(Zr). Similar results were observed for photocatalytic hydrogen evolution reactions (HERs) in water using triethanolamine electron donor and the three MOFs on

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Fig. 6 a Tafel plots of CO2 reduction catalytic current density for Ni SAs/N–C at different applied over-potentials. b Partial CO current density of Ni SAs/N–C versus potassium bicarbonate concentration at a constant potential. c The most acceptable reaction paths for CO2 reduction on Ni SAs/N– C immobilized electrode. Adapted with permission [59]. Copy right (2017), American Chemical Society

Pt support. NH2 -Uio-66(Zr/Ti) (prepared at 120 °C, reaction period 16 days) shows 1.5 times higher HER over the original NH2 -Uio-66(Zr). The post-catalytic analysis of MOFs with powder X-RD and N2 adsorption isotherms indicates no decomposition of catalysts during photocatalytic reactions [64]. A similar transmetalation approach on NH2 -Ui-66(Zr) was also performed by Lee et al. with Ti metal centers. Additionally, the authors reported mixed ligand MOF NH2 /(NH2 )2 -Ui-66(Zr) and its Ti(IV)-incorporated transmetalated MOF, NH2 /(NH2 )2 -Ui-66(Zr/Ti), where the two amine groups are present on one of the 1,4-dibenzoic acid linkers. They also extended the approach to NH2 -MIL-125. All the transmetalated MOFs show an enhancement in photocatalytic activity in CO2 reduction reactions compared to their parent MOFs. Among all transmetalated mixed metal MOFs, the mixed ligand-mixed metal MOF, NH2 /(NH2 )2 -Ui-66(Zr/Ti), shows better photocatalytic activity. The

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Fig. 7 Synthesis of MOFs UiO-66(Zr/Ti)-NH2 and UiO-66(Zr/Ti)-NH2 /(NH2 )2 via postsynthetic transmetalation. Adapted with permission [65]. Copy right (2015), Royal Society of Chemistry

GC–MS analysis of gas effluents of photoreactor indicates that no gas-phase CO2 reduction products are observed in these photocatalytic reactions [65] (Fig. 7). Many polyaromatic dye molecules are highly toxic for life forms on earth, even in low concentration levels. The polluted water bodies containing toxic drug molecules should be made free from dye molecules. The oxidation reagents can be used to oxidize the toxic dye molecules to CO2 . However, the removal of the excess oxidizing agent afterward is a hectic task. Heterogeneous photocatalytic dye degradation is one of the best choices, where the photocatalyst can be separated by simple filtration [66, 67]. A Zr-based UiO-67 MOF decorated with {Ru(bipy)2 } active centers was reported by Amador et al. from a mixer of dicarboxylic acids (Biphenyldicarboxylicacid (BPDC) and bipyridyldicarboxalicacid (BPYDC)) [68]. The zirconium centers in parent MOF {Ru(bipy)2 }-UiO-67(Zr) were transmetalated with titanium metal centers to yield {Ru(bipy)2 }-UiO-67(Zr/Ti). The transmetalation process was performed by dipping parent MOF in a DMF solution of TiCl4 .THF at 120 °C for six days. The influence of TiCL4 concentration on the amount of metal exchange is evident after performing the transmetalation at different TiCl4 concentrations. The exchange process was monitored with ICP-AES and X-ray fluorescence spectroscopic methods. At higher TiCl4 concentrations, a high amount of metal exchange was observed, and a maximum of 54.5% of Zr was exchanged with Ti when TiCl4 concentration was maintained at 9 mg/mL. The MOFs are explored as the photocatalyst for methylene blue (MB) degradation in water. The results revealed that all the MOFs show MB degradation under visible light at 419 nm. However, the transmetalated MOF {Ru(bipy)2 }-UiO-67(Zr/Ti) shows a significant enhancement in MB degradation amount and kinetics (Fig. 8).

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Fig. 8 Synthesis and transmutation of photoactive MOF {Ru(bipy)2 }-UiO-67(Zr/Ti). Adapted with permission [68]. Copy right (2017), Royal Society of Chemistry

3.1.5

Gas Adsorption and Separation by T-MOFs

Along with photocatalytic applications, UiO-66(Zr)-based MOFs also display gas sorption and separation abilities due to the presence of substantial accessible voids and channels [62, 63]. MOFs contain tunable high ordered pores and channels along with their frameworks. This property facilitates us to apply such Metal–Organic Frameworks in selective uptake and separation of gas-phase molecules. The transmetalation of UiO-66 with Ti metal centers produced a series of transmetalated MOFs with the general formula UiO-66(TiX ). The number of Ti metal centers incorporated into UiO-66 MOFs can be varied by varying TiCl4 concentrations used in the reactions. The BET surface area of transmetalated MOFs is significantly increased with Ti ion loading into the UiO-66 MOF. The CO2 gas adsorption isotherms of parent and transmetalated MOFs with different Ti ion loadings revealed that the CO2 uptake capacity was considerably enhanced in transmetalated MOFs, and it increases with the increase in Ti metal loading in the final MOFs [63]. In another study, the transmetalated UiO-66 MOFs with Ti ions display an enhanced selective permeability toward carbon dioxide in a polymer membrane with intrinsic porosity (PIM) for a mixer of CO2 and N2 . The transmetalation process was similar to the methods discussed above to produce UiO-66(Zr/Ti) [69] (Fig. 9). A cadmium-based MOF derived from 1,3,5-benzenetristetrzolate (BTT) has been synthesized and explored for transmetalation with Co(II) and Ni(II) ions [70]. This transmetalation process required 30 days period time and 80 °C of temperature. DMF solutions of MCl2 (M = Co or Ni) were used for the transmetalation protocols. The

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Fig. 9 Schematic depiction of differences in CO2 permeability in Ti-incorporated UiO-66 and UiO-66. Adapted with permission [69]. Copy right (2015), Copyright 2015, Springer Nature

PSM MOFs are isostructural with parent MOF, and the isostructurality was evident by molecular structures determined by single-crystal X-ray diffraction (SCXRD) analysis and PXRD patterns. Except at the surface cavities, all the framework and core cavity Cd(II) ions are exchanged by Co(II) and Ni(II) ions. The BET surface areas measured from N2 adsorption and desorption isotherms of MOFs activated at 150 °C revealed that the transmetalated MOFs have more significant surface areas than their parent MOF. However, the methanol exchange parent MOF shows a higher surface area compared to all the MOFs. The H2 uptake capacity determined from H2 adsorption isotherms indicates that the Co(II) transmetalated MOF shows a higher H2 uptake capacity even compared to the methanol exchanged parent MOF. This observation indicates that free uncoordinated metal sites are more in Co(II) transmetalated MOF.

4 Conclusion The importance of MOFs as functional materials is evident by several hundreds of scientific reports on MOFs and their application. It is found that post-synthetic modification is a synthetic approach for tuning the physical and chemical properties of MOFs toward functional materials to apply in various fields of sciences without disturbing the structural integrity of MOFs. Transmetalation of MOFs evolved as

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a tool for such PSM methods. As discussed in the above sections, transmetalation methods have the potential to make several MOFs in the future with unique properties, and such MOFs will find unbelievable applications, which will not only be limited to the applications discussed in this brief article.

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The 2D and 3D Protein Sequencing Implementation Using Ant Colony Optimization Algorithm B. Ramya Sree, T. Indira Priyadarshini, and Tejaswi Borra

Abstract The application of protein sequence is widely used to compare the hidden sequence with all the similar protein sequences and revert index of the highest similarity scored protein. Therefore, it is necessary to construct efficient protein sequence system. This paper represents how to improve the protein sequencing algorithm theoretically. This paper includes the introduction to ant colony algorithm and 2D and 3D hydrophobic–hydrophilic models. Continuation with construction of model is with ant colony algorithm. The conclusion of the paper is with improving the protein sequencing theoretical calculation by using ant colony optimization algorithm. Keywords Ant colony algorithm · 2D model · 3D model · Hydrophobic · Hydrophilic · Partial search updating method · Point mutation on plane · Point mutation on direction · Local update · Global update

1 Introduction Protein is a polypeptide of amino acids, in which alpha carbon is connected to amino group, hydrogen atom, and carboxyl group. Proteins inherit the properties of a polymer; proteins are arranged in 3D amino acids. Protein sequencing is a practical implementation to find the amino acid sequence [1]. Figure 1 shows the protein structure. Initially, protein sequencing is done by modeled atomic force field. The drawback of this model is due to strong atomic force field, the folded protein sequence is disturbed; therefore, we use ant colony algorithm. Ant colony algorithm is an optimization probabilistic analysis to find the optimal path in the graph; this algorithm is coined by Italian scholar Dorigo in 1992 in his PhD thesis. The ant colony algorithm is applicable only for theoretical calculation [2]. In 2D-HP model, there are 20 amino acids which are represented using hydrophobic and hydrophilic amino acids. The upcoming amino acid is inserted B. Ramya Sree (B) · T. Indira Priyadarshini · T. Borra Department of CSE, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_3

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Fig. 1 Multiple protein structures

in three ways, i.e., left, right, or in current direction of the current amino acid. The initial solution is found by traversing all the paths in the graph [3]. The optimal solution for this model is done by partial search updating method [4] which updates the pheromone level. Like 2D-HP model, 3D-HP model has 20 amino acids, and the upcoming amino acid is inserted in five ways, i.e., straight, left, right, up, and down of the current amino acid. The initial solution is done using local update method which calculates the pheromone level of all the ants [5]. The optimal solution is done using global update in which free energy is calculated. This paper is concluded by proving the ant colony algorithm is the best and gives very accurate and efficient solution for big numerical values [6–8].

2 Related Work Aimoerfu et al. [2] had worked on “Implementation of the protein sequence model based on ant colony optimization algorithm” in the year 2017. This paper talks about the theoretical calculation of the 2D-HP model using ant colony optimization algorithm.

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Colorni et al. [3] had published a Belgian Journal of Operations Research in the year 1994 called “Ant system for job-shop scheduling”. In this paper, he concluded that searching task is disturbed to many agents, i.e., ants over many loosely interacting agents to find an optimal solution using job-shop scheduling algorithm. Dorigo et al. [4] had done their first workshop in “Ant colonies for the traveling salesman problem” in the year 1996. In this workshop, they have briefed on ants of the artificial colony that they can perform feasible solution in very less time using pheromone trail deposited on the edges of the graph using traveling salesman problem. Chu et al. [5] had done research on “Parallel Ant Colony Optimization for 3D Protein Structure Prediction using the HP Lattice Model” in the year 2005. This paper tells us about the study of protein fold in amino acids. They mainly done research to treat the diseases like Alzheimer’s, etc. In this paper, they have done final confirmation of protein using HP method. They have developed a framework for testing ant colony algorithm for HP protein folding [6]. They used IBM blade to compile program for 9 nodes. But due to master/slave method implementations, two processors functioned as the single processor version.

3 Protein Sequence Protein structure consists of multiple folds; these multi-folded amino acids are represented in 2D and 3D graph. Therefore, ant colony algorithm is used to find the path in the graph optimally. Ant colony algorithm must control the pheromone. Ant colony optimization (ACO) algorithm must adjust three key parameters in practical implementation namely α: pheromone density, β: visibility, and ρ: evaporation rate.

4 Ant Colony Algorithm Ant colony algorithm is proposed by Marco Dorigo in 1992. This was proposed in his PhD thesis. It is a probability algorithm to find the good path in the weighted graph. Its aim is to traverse all the paths, and ant with high pheromone level is the best path. This algorithm is discovered to solve huge numerical problems; as a result, many problems arise based on behavior of ants. Ant colony algorithm is a model-based search (Figs. 2 and 3).

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Fig. 2 Ant colony model flowchart Fig. 3 Ant colony algorithm

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5 Two-Dimensional (2D) Hydrophobic–Hydrophilic (HP) Grid Model Two-dimensional hydrophobic–hydrophilic is a grid model that shows the simplified abstract of 3D model. In hydrophobic–hydrophilic, they are classified using 20 amino acids. Proteins are 2D grind points; suppose let us consider the protein sequence as S and length as N and represented in Eq. (1). S = S1 S2 . . . Sn ∀Si = {H, P}

(1)

The relation between two H–H bonds is found using topology nearness relation. The conformation of 2D-HP model is counted by H–H bonds. The directional sequence of protein sequence can be expressed as RSRRLRRLRSLRRLRRLSSRRSS for the protein sequence HHPPHPPHPPHPPHPPHPPHPPHH shown in Fig. 4. • R is the upcoming amino acid to be inserted to the right side of the present amino acid • L is the upcoming amino acid to be inserted to the left side of the present amino acid • S the upcoming amino acid is in current direction.

5.1 Initial Solution Initially, let us assume the path as Pi,d , where i is defined as ith amino acid and d is defined as property of next amino acid. The parameters required for calculating initial basic feasible solution are ηi,d , τ i,d , α, and β, where τ i,d is defined by the amount of pheromone deposited for the transition from ith to next amino acid and ηi,d is defined as desirability of state transition. The path construction can be calculated by selection function as shown in Eq. (2). Fig. 4 2D-HP lattice

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Fig. 5 Point mutation on direction

Pi.d

( α )( β ) τi,d ηi,d = ∑ ( α )( β ) ηi,d e∈L ,R,S τi,d

(2)

5.2 Optimal Solution For protein sequencing in ACO, we use partial search updating method to find the optimal path than the initial solution. Firstly, in this method, we find the total number of topological H–H bonds in from the initial solution. Secondly, an ant finds a new sequence by adding sequence by adding the number of topological H–H bonds, and next upcoming ants will modify the path according to the predecessor ant, which shows the path is optimal solution. There are two modes for updating the path, • Point mutation on place • Point mutation on direction. 5.2.1

Point Mutation on Direction

Point mutation on direction is a technique, where only hydrophobic amino acids are mutated so that the free energy between them is calculated. But in this process, hydrophobic amino acids get overlapped, so the initial feasible solution is not found which is shown in Fig. 5.

5.2.2

Point Mutation on Place

Point mutation on place means deletion, insertion, or changing the amino acids. Suppose consider S i where i = 0, 1, 2…N is the protein sequence, then S i , S i+1

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Fig. 6 Point mutation on place

connection is not changed, but the connection between S i+2 and S i+1 is disconnected, but the absolute direction of the S i+2 is not changed which is shown in Fig. 6.

6 Three-Dimensional (3D) Hydrophobic–Hydrophilic (HP) Grid Model Similarly like 2D-HP model, 3D model also has 20 amino acids. It is represented in the form of hydrophobic amino bond and hydrophilic amino bond. The 3D-HP model hydrophobic amino acids are represented using solid black, whereas hydrophilic is represented as hallow. Like 2D model, 3D-HP model as specific direction to insert the upcoming amino acid, they are as directions shown in Fig. 7.

Fig. 7 3D-HP model in lattice representation

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Fig. 8 3D-HP model in lattice insertion representation

• • • • •

U refers to next amino acid in upward direction. D refers to next amino acid in downward direction. S refers to next amino acid in straight ahead. L refers to next amino acid in left direction. R refers to next amino acid in right direction (Fig. 8).

In 3D model, it is like a graph and it only visits each lattice only once. In 3D-HP model the hydrophobic amino acid is likely to tend to the inner of the lattice, whereas hydrophilic amino acid behaves to be in the boundaries of the lattice.

6.1 Initial Solution The initial solution for the 3D-HP model is by the method local update. This method updates the pheromone sequence optimally by the edge value. τi j = 1 − ρτi j + ρτ0

(3)

τ ij is pheromone deposit on the 3D model edge, τ 0 is initial pheromone value which is a low constant value, and ρ is the trial evaporation.

6.2 Optimal Solution The optimal solution for the 3D-HP model is by the method global update. In this method, all ants travel the 3D lattice, and completely, the best solution is fetched by best protein folding, i.e., the more density pheromone on the visited path is the best optimal solution. { ∆τi j =

−E gb if(i, j ) ∈ best solution 0 otherwise

(4)

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7 Conclusion Protein sequencing is fetched by hydrophobic and hydrophilic. This protein structure consists of multiple of protein folds. Ant colony algorithm is used to perform theoretical calculation effectively. This algorithm’s main aim is to calculate the data with high numerical and fetched result most efficiently. The results are more accurate and having more efficiency when compared to hydrophobic zipper (HZ) algorithm, the constraint-based hydrophobic core construction method (CHCC), the core-directed chain growth algorithm (CG), the contact interactions (CI) algorithm, and the prunedenriched Rosenbluth method (PERM). In the 2D-HP model, the initial solution is done by inserting the amino acids in the three directions. The optimal solution is by updating the strategy of the initial feasible solution by partial search updating. In 3DHP model, the initial solution is by local update method. This method updates the pheromone sequence by the edge value. The optimal solution is done by global update; it calculates the global energy. In this method, every ant completes the traversal in the 3D lattice by visiting each amino acids only once and fetches the best solution by best protein fold and more amount of pheromone density on the visited path.

References 1. Colorni A, Dorigo M, Maniezzo V (1994) Ant system for job-shop scheduling. Belg J Oper Res Stat Comput Sci 5(2):39–54 2. Dorigo M, Gambardella LM (1996) Ant colonies for the traveling salesman problem In: The first international workshop on ant algorithms, pp 319–324 3. Aimoerfu, Shi M, Li C, Wang D, Hairihan (2017) Implementation of the protein sequence model based on ant colony optimization algorithm. In: IEEE/ACIS 16th International conference on computer and information science (ICIS), Wuhan, pp 661–665 4. Chu D, Till M, Zomaya A (2015) Parallel ant colony optimization for 3D protein structure prediction using the HP lattice model. In: Proceedings of the 19th IEEE international parallel and distributed processing symposium (IPDPS’05), pp 1530–2075 5. Soto C (2017) Protein Misfolding and disease; protein refolding and therapy. FEBS Lett 498:204–207 6. Islam M, Chetty M, Murshed M (2011) Novel local improvement techniques in clustered memetic algorithm for protein structure prediction. In: Proceedings IEEE congress on evolutionary computation, pp 1003–1011 7. Raju R, Manikandan N, Palanisamy D, Arulkirubakaran D, Sampath Kumar S, Bhanu Prakash P (2018) Optimization of process parameters in electrical discharge machining of haste alloy C276 using Taguchi’s method. Mater Today Proc 5(6):14432–14439 8. Manikandan N, Raju R, Palanisamy D, Arulkirubakaran D, Kumar S (2018) Investigation on Ti6Al4V laser metal deposition using Taguchi based grey approach. Mater Today Proc 5(6):14375–14383

Optimizing the Peak-Ageing Conditions for Microalloyed 2219Al Alloys Sanjib Banerjee

and Sanjib Gogoi

Abstract The 2219Al alloy system microalloyed with varying contents (0–0.1 wt%) of Sn and Cd was separately processed through casting route. Overall age-hardening behaviour of cast and solutionized alloy with trace contents of Sn and Cd was individually studied, by generating the age-hardening curves at given precipitation temperature of 170 °C. Independent influences of elemental Sn and Cd on the peak-hardness, peak-ageing time, and thermal stability were investigated. For all investigated alloys, hardness increased with ageing time up to peak-hardness corresponding to peakageing time. Hardness dropped during over-ageing. Peak-ageing times of 2219Al alloy were evaluated to be 24 h and 40 h, when microalloyed, respectively, with Sn and Cd. The peak-hardness was achieved more steadily and faster, when microalloyed with Sn, indicating an accelerated precipitation kinetics. Trace contents of either Sn or Cd had no appreciable effect on peak-ageing time. But, trace additions of both Sn and Cd can potentially induce a higher thermal stability on the strengthening effect at elevated temperatures. For a constant peak-ageing time, the peak-hardness increased with adding either Sn or Cd up to 0.06 wt%, while further contents of the microalloying elements decreased the peak-hardness. Peak-ageing conditions to achieve best possible hardness or mechanical strength could be optimized for 2219Al alloys microalloyed with Sn and Cd. The influences of the individual microalloying elements Sn and Cd on the peak-ageing characteristics of the alloy were compared and correlated with available literature. Keywords Aluminium alloys · Microalloying · Age-hardening · Peak-ageing · Peak-hardness

S. Banerjee (B) · S. Gogoi Department of Mechanical Engineering, Tezpur University, Tezpur 784028, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_4

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1 Introduction Aluminium (Al) and its alloys are used for versatile engineering products and applications, because of their broad spectrum of superior and attractive mechanical characteristics. Reasonable high strength may still be archived by these relatively lightweight and low-cost materials, through proper heat treatment routes. Especially due to enhanced specific strength and many other unique combinations of properties, there is a remarkable increase ε in design considerations of Al alloys, for strong lightweight structures, typically that moves, including all ranges of land and water-borne vehicles as well as aerospace [1, 2]. Specifically, the ε wrought and age-hardenable 2xxx series was focused during recent years, for automobile, marine, aircraft, and space applications. Among 2xxx series, 2219Al alloy is a two-phase hypoeutectic Al-Cu alloy system, with exemplary blend of elevated strength-to-weight ratio, ductility, fracture toughness, resistance to corrosion, weldability, production efficiency along with improved properties at cryogenic temperatures. Subsequently, 2219Al alloy is used in the fabrication of supersonic aircraft skin and structural members like space boosters, rocket fuel tanks, and fins, etc. [3, 4]. Recent trend in alloy development is to microalloy (adding trace contents < 0.1 wt%) with elements like Ag, In, Sn, Cd, etc. Microalloying may actually combine elevated mechanical strength with significant toughness, while still maintaining lower density [5]. Precipitation hardening is commonly employed as a strengthening mechanism for high-strength 2xxx series Al-Cu alloys [6]. The pioneering work on improving the strength of Al alloys by precipitation hardening can be traced back to a patent on an Al 3.5–5.5 wt% Cu alloy containing < 1 wt% Mg and Mn by Wilm in 1906 [2]. A typical precipitation hardening procedure involves three stages [7]: (a) solution heat treatment to form uniform solid solution, (b) rapid quenching at room temperature by restricting diffusion, and (c) precipitation or ageing heat treatment finally to generate fine and uniformly dispersion of precipitates. The equilibrium precipitate and the major hardening phase of Al–Cu–Mg alloy are CuAl2 (θ ) [6]. Typically, during the precipitation stage, several transition phases may sequentially form, before arriving at the equilibrium θ phase. 2219Al–Cu alloy on precipitation and ageing follows the sequence [7]: SSSS → α + Guinier–Preston (GP) zones → α + θ '' → α + θ ' → α + θ. Supersaturated solid solution is indicated by SSSS, the Al– Cu solid solution by α and the metastable phases are indicated by θ ' and θ '' , and the stable precipitate is by θ. Artificial ageing at sufficiently elevated precipitation temperatures exhibits a different characteristic feature, where hardness first increases to a maximum level before decreasing with further ageing time [6]. With overageing, precipitates become coarser, and consequently, the strength and hardness decrease [7]. Again, the strengthening process is accelerated as the precipitation temperature is increased, which has been experimentally demonstrated for 2014Al alloys at several different temperatures [5]. Thus, the strength and ductility depend on the alloy composition, precipitation temperature, and ageing duration. Time and temperature of the age-hardening heat treatment cycle should be ideally designed to achieve strength or hardness in the vicinity of maximum level. Optimum precipitation

Optimizing the Peak-Ageing Conditions for Microalloyed …

45

temperature and response of the mechanical properties to the ageing time are the areas with much needed attention and required to be experimentally studied for the Al–Cu alloys with different compositional modifications. The θ ' as well as S or S ' (CuAl2 Mg) phases are generally formed during precipitation of 2219Al alloys having high Cu:Mg ratios [8]. For Al–Mg–Si alloys, Cu contents enhanced ageing kinetics, changed precipitation sequence, increased peakhardness, and promoted grain refinement [9]. Again, adding minor contents of Mg formed Mg/Cu/vacancy complexes (in atomic scale), promoting nucleation of GP zones [8]. These Mg/Cu/vacancy complex clusters interact with the moving dislocations, which cause accelerated strengthening effect at lower temperatures and shorter ageing times [6]. Maksimovic et al. performed ageing of 2219S (with Si only) and 2219SG (containing both Si and Ge) alloys at 190 °C within time range 10 min-256 h [10]. Under identical microalloying content, Ge-containing material attained peakhardness thrice faster compared to the material devoid of Ge. Accelerated ageing kinetics because of trace contents of Ge is a consequence of the formation of fine particles of Si–Ge, which in turn favour nucleation of θ ' particles [10]. The effect of Si and Ge on the precipitation reaction was experimentally studied using quaternary Al–Cu–Si–Ge alloy system. Mitlin et al. tried to modify the precipitation reaction in Al-Cu alloy by adding trace contents (0.5–2 at.%) of Ge and Si simultaneously, aiming to control ageing kinetics [9]. Microalloying elements may change the properties of Al alloys, by altering chemistry, structure, morphology, size, and spatial distribution of the precipitates [3]. Literatures are available on precipitation kinetics and behaviour for some commercial aluminium alloys. However, literature is limited regarding influence of microalloying with In, Sn, or Cd over nucleation and growth of θ ' in Al–Cu–Mg alloys. In particular, effect of variation in trace contents of these elements on peak-ageing characteristics of 2219Al alloys was not reported. Hence, in order to optimize the overall processing and age-hardening conditions of these heat-treatable alloys, the proper precipitation temperature needs to be investigated, the age-hardening curves need to be generated, and the peak-hardness and peak-ageing time are required to be evaluated, with different contents of the trace elements. The present research work was hence aimed at studying the age-hardening behaviour of cast and solutionized alloy individually with varying trace contents of Sn and Cd (0–0.1 wt%), by generating age-hardening curves at a given precipitation temperature. The independent influences of elemental Sn and Cd, on the peak-hardness, peak-ageing time, and thermal stability were investigated. The peak-ageing conditions for achieving best possible hardness or mechanical strength could be optimized for 2219Al alloys microalloyed with Sn and Cd. The influences of the individual microalloying elements Sn and Cd on the peak-ageing characteristics of the alloy were compared and correlated with available literature.

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2 Experimental Procedure Present alloys have been processed following the standard foundry practice, as shown in Fig. 1. Casting was done in a clay-graphite crucible, pre-sintered for 3 h at 800 °C. At first stage, Cu powder (99% pure) was melted with commercially pure Al (99.5% pure) to prepare a master alloy (Al-33 wt% Cu), to bring down the melting point. Then, Al ingots were melted with proper amount of Al–Cu master alloy, to achieve final composition of Al-6.3%Cu by weight, as per the standard compositional ranges of 2219Al alloy. At 700 °C, appropriate amounts of other elements, viz., Si, Fe, Zn, Ti, and Mn were subsequently added in the form of high purity metallic powders, while stirring simultaneously. Appropriate amounts of Mg powder and high-purity Sn (or Cd) grains (99% pure) were then added and stirred to ensure compositional homogeneity. It was super-heated and held at 750 °C for 15 min before pouring the same into the pre-heated permanent metallic moulds for solidification. Thus, base alloy was casted as standard 2219Al alloy. Six different alloys were prepared by this casting procedure, separately microalloyed with each of varying Sn and Cd contents (0, 0.02, 0.04, 0.06, 0.08, and 0.1 wt%). Presence of metastable phases along with coring and segregation are expected in as-cast alloys [11, 12]. These result in chemical in-homogeneities, microstructural non-uniformity, and variation of mechanical properties across the casting section. To ensure compositional and structural homogeneity, the as-cast alloys were homogenized (10 h at 510 °C) at a resistance heated muffle furnace, followed by furnace cooling [11].

Fig. 1 Melting and casting of investigated alloys

Optimizing the Peak-Ageing Conditions for Microalloyed …

47

The highest strength for the base alloy is obtained by solutionizing and then precipitation heat treatment. Age-hardening conditions become necessary to be optimized due to lack of open literature and information relevant to peak-ageing time of 2219Al alloy microalloyed with Sn or Cd. Age-hardening behaviour was therefore studied to estimate the corresponding ageing time to achieve peak-hardness. Now, in case of Al–Cu and Al–Cu–Mg alloys, initial (hardening) stages corresponding to decomposition of supersaturated solid solution generally occur within temperature ranges of 160–190 °C and 20–190 °C, respectively [12]. For majority Al–Cu alloys, precipitation temperature range of 160–190 °C has been used to study agehardening behaviour. For the present alloys, a precipitation temperature of 170 °C has been adopted to obtain isothermal age-hardening curves. Following precipitation hardening protocol, the cast alloys were first solutionized (10 h at 525 °C), then quenched, and lastly age-hardened (up to 52 h at 170 °C). At regular time intervals of 5 h, specimens were withdrawn from the furnace and subsequently quenched to retain the hardness attained at the given ageing time. For these different ageing times, Vickers hardness (VHN) was evaluated to determine ageing time necessary for each alloy to achieve maximum hardness. VHN was evaluated using Vickers hardness testing machine (Make: Ratnakar, Model: RVM-500) having a diamond indenter with 136° included angle. Load and dwell time used were, respectively, 5 kg and 20 s, and impression diagonal length was measured. Such identical loading conditions were repeated for 15 independent indentations, average of which registered the hardness value of each sample.

3 Results and Discussion 3.1 Isothermal Age-Hardening Curves Figures 2 and 3 reveal isothermal age-hardening curves of presently investigated alloys, microalloyed with different compositions of Sn and Cd, respectively, demonstrating the variations in hardness as function of ageing time under constant precipitation temperature at 170 °C. In the pre-ageing stage, the hardness of all the alloys increased with ageing time. Then, the hardness attained a maximum value termed as peak-hardness, a condition termed as peak-ageing. The corresponding particular ageing time termed as peak-ageing time. Later, the hardness dropped with further increase in ageing time, a phenomenon termed as over-ageing. The above trend in hardness is in agreement with the typical age-hardening behaviour of Al–Cu alloys [1, 2]. However, for the alloys microalloyed with Sn, the hardness was observed to increase more steadily and faster towards its peak value. While with trace contents of Cd, during the initial ageing stage within time periods ranging 10–20 h, hardness of the present alloys increased at a comparatively slower rate. It is during this period and before reaching the major peak-hardness, another minor peak may be observed in the variation of hardness, which corresponds with the formation of GP zones [2].

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This peak was however more prominently observed in case of the alloys with Cd contents, as compared to base alloy. High binding energy between Cd atoms and vacancies may have possibly facilitated rapid diffusion promoting the formation of GP zones. Following to this initial stage of age-hardening, sharp increase in hardness was exhibited, until peak-hardness was achieved. Practically, around 50% of peak-hardness was attained by the Cd-containing alloys only after ageing time of 30 h. Fig. 2 Isothermal age-hardening curves of 2219Al alloys microalloyed with Sn

Fig. 3 Isothermal age-hardening curves of 2219Al alloys microalloyed with Cd

Optimizing the Peak-Ageing Conditions for Microalloyed …

49

3.2 Peak-Hardness and Peak-Ageing Time While analysing the peak-ageing time, the peak-hardness was recorded to have achieved at an ageing time of around 24 h for all the investigated alloys microalloyed with Sn and 40 h in case of all the alloys with trace additions of Cd. Actually, for both the cases, marginal variations in hardness could be observed during ageing time periods closer to the peak-ageing time. Therefore, it may be concluded from Figs. 2 and 3 that trace contents Sn result in an accelerated precipitation kinetics for 2219Al alloy, compared to the microalloying element of Cd. Moreover, the same results additionally establish the fact that trace contents of either Sn or Cd even though individually influenced the hardness of the present 2219Al alloy, but no significant effect on peak-ageing time could be observed for both the cases. About 24 h of peak-ageing time was observed for 2219Al alloy having trace content of Si at precipitation temperature of 190 °C [1], and also for Al–5.9%Cu– 0.2%Mg alloy at 180 °C [3]. The inability of Sn to influence ageing acceleration was attributed to reaction of Sn with Mg content forming Mg2 Sn. Consequently, θ ' could not directly precipitate by formation of Sn clusters. On the other hand, when 2219Al alloy was studied with trace contents of Ag, the maximum hardness was achieved when aged for 45 h [6], which is very close to 40 h in case of present alloys when microalloyed with Cd. Murayama and Hono also investigated for Al–Cu–Mg– Ag alloy that although Mg necessarily enhances nucleation kinetics, content of Ag had no significant influence on the same [6]. Since for substitutional solid solution alloys, the primary diffusion is generally due to Zener ring mechanism or direct interchange mechanism, elemental Ag or Cd undergoes rugged diffusion within Al. Consequently, addition of Ag or Cd ≤ 0.1 wt% may not impose mentionable effect on ageing kinetics of 2219Al alloy.

3.3 Thermal Stability of Hardening Effect As revealed from Figs. 2 and 3, after attaining the peak-hardness, the slope of decrease in hardness during the over-ageing stage was lower for the Sn and Cd-containing alloys, in contrast to the base 2219Al alloy. This indicates that microalloying elements Sn or Cd can potentially induce a better thermal stability at elevated temperatures to strengthening effect resulted from the age-hardening treatment. During the overageing stage, trace additions of Sn, especially at and above 0.04 wt%, caused higher thermal stability to strengthening. Identical to influences of Sn and Cd, elemental Ag was also reported to increase peak-hardness (with 0.48 wt% of Ag content) and provide superior thermal stability to strengthening of Al–Cu–Mg–Mn–Zr alloys [6].

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Fig. 4 Variations in peak-hardness with Sn and Cd contents

3.4 Variations in Peak-Hardness The variations of peak-hardness with Sn and Cd contents are shown in Fig. 4. In case of Sn and Cd-containing alloys, for the constant peak-ageing time of, respectively, 24 h and 40 h, the peak-hardness increased with adding either Sn or Cd up to 0.06 wt%. Concentrations of Sn or Cd above this 0.06 wt% actually decreased the peak-hardness. However, microalloying element Cd was observed to induce a higher level of peak-hardness compared to elemental Sn, by around 12%. Peak-hardness of 2519Al alloy also increased by adding minor contents of Ag [6]. When Al–Cu– Mg–Mn–Zr alloy was aged up to a peak-ageing time of 45 h, the peak-hardness increased up to 0.07 wt% of Ag content and decreased with further Ag additions [7]. Thus, the peak-ageing conditions for achieving peak-hardness value could be optimized for 2219Al alloys microalloyed with Sn and Cd. The respective alloys attaining peak-hardness under proper processing conditions generally also exhibit best possible mechanical strength and both yield and tensile [11–19].

3.5 Influences of Microalloying Elements Microalloying elements may change the properties of Al alloys, by altering chemistry, structure, morphology, size, and spatial distribution of the precipitates [1]. However, literature is limited regarding influence of minor additions of In, Sn, or Cd over nucleation and growth of θ ' in Al–Cu–Mg alloys. As proposed by Silcock et al., two different mechanisms which can possibly operate at separate temperature ranges are [6]: (a) tiny particles of trace element undergoing heterogeneous nucleation at 200 °C or above, and (b) atoms of trace element enter inside θ ' nuclei eliminating misfit with Al matrix, mainly at lower temperatures. In the former case, prior to

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51

θ ' formation, high contents of large and spherical particles of Sn or Cd precipitate at an early stage (before ~ 3 min at 200 °C) [7, 8]. These stable particles of Sn or Cd are unable to incorporate inside the θ ' phase but still serve as active nucleation sites. Precipitation hardening behaviour of In, Sn, and Cd-containing alloys revealed identical phenomenon [2]. In the latter mechanism, Sn or Cd incorporates inside the edges of θ ' , reducing misfit on the particle rim along with the interfacial energy. In the current research, precipitation temperature being 170 °C, this second mechanism appears to be the possible reason behind higher hardness attained by the presently investigated alloys with Sn and Cd additions. Since, coherent particles of GP zones are actually responsible for peak-hardness, before growing further to significantly loose coherency. Such presumption is evidently supported by TEM studies at the peak-hardness, revealing the platelets present to be of smaller diameter. Although precipitation kinetics at lower temperatures was reportedly retarded by minor contents of In, Sn, or Cd, but the same was enhanced at higher temperatures for many Al–Cu alloys, following the precipitation of uniformly dispersed θ ' phase [7, 8]. Therefore, trace contents of Sn or Cd may have promoted finer and more uniformly dispersed θ ' precipitation, which enhanced particle–matrix coherency by potentially eliminating the misfit. As a consequence of this, the growth of the precipitates is suppressed, inducing superior thermal stability to the strengthening of the alloys.

4 Conclusions Standard 2219Al alloy system microalloyed with varying trace contents (0–0.1 wt%) of Sn and Cd was separately processed through casting route. Overall age-hardening behaviour of cast and solutionized alloy with trace contents of Sn and Cd was individually studied, by generating the age-hardening curves at given precipitation temperature. Independent influences of elemental Sn and Cd, on the peak-hardness, peak-ageing time, and thermal stability were studied. 1. For all investigated alloys, hardness increased with ageing time up to peakhardness corresponding to peak-ageing time. Hardness dropped during overageing. 2. At given precipitation temperature of 170 °C, peak-ageing times of 2219Al alloy were evaluated to be 24 h and 40 h, when microalloyed, respectively, with Sn and Cd. The peak-hardness was achieved more steadily and faster, when microalloyed with Sn, indicating an accelerated precipitation kinetics compared to the microalloying element of Cd. 3. Although trace contents of either Sn or Cd individually influenced the hardness of the investigated alloy, but no appreciable effect on peak-ageing time or agehardening kinetics could be observed for both the cases. 4. After attaining the peak-hardness, the slope of decrease in hardness during the over-ageing stage was lower for the Sn and Cd-containing alloys, in contrast

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to the base 2219Al alloy. This indicates that microalloying elements Sn or Cd can potentially induce a higher thermal stability to strengthening at elevated temperatures. 5. In case of Sn and Cd-containing alloys, for the constant peak-ageing times of, respectively, 24 h and 40 h, the peak-hardness increased with adding either Sn or Cd up to 0.06 wt%. Further contents of the microalloying elements decreased the peak-hardness. 6. Thus, the peak-ageing conditions for achieving best possible hardness or mechanical strength could be optimized for 2219Al alloys microalloyed with Sn and Cd. The influences of the individual microalloying elements Sn and Cd on the peakageing characteristics of the alloy were compared and correlated with available literature.

References 1. Rana RS, Purohit R, Das S (2012) Reviews on the influences of alloying elements on the microstructure and mechanical properties of aluminium alloys and aluminium alloy Composites. Int J Sci Res Publ 2(6):2250–3153 2. Wilm A (1906) German patent. Patent no: DRP244554 3. Rao KS (2010) Microstructure of age hardenable AA2219 aluminium alloy modified by Sc, Mg and Zr additions. Trans Indian Inst Met 63(2):379–384 4. Kaibyshev R, Kazakulov I, Gromov D, Muskin F, Lesuer DR, Neih TG (2001) Superplasticity in 2219 Al-alloys. Scr Matterilla 44:2411–2417 5. Sercombe TB, Schaffer GB (1999) On the use of trace additions of Sn to enhance sintered 2xxx series Al powder alloys. Mater Sci Eng A 268:32–39 6. Murayama M, Hono K (2001) Role of Ag and Mg on precipitation of T1 phase in an Al–Cu– Li–Mg–Ag alloy. Scr Materilla 44(4):701–706 7. Miao WF, Laughlin DE (2000) Effects of Cu content and presaging on precipitation characteristics in aluminium alloy 6022. Metall Mater Trans A 31(A):361–371 8. Chakrabarti DJ, Cheong BK, Laughlin DE (1998) Precipitation strengthening of aluminium alloys AA6111. In: Automotive alloys II, pp 27–44 9. Mitlin D, Radmilovic V, Dahmen U, Morris JW (2003) On the influence of Si–Ge additions on the aging response of Al–Cu alloys. Metall Mater Trans A 32(A):735–742 10. Maksimovic V, Slavicazec V, Radmilovic M, Jovanovic T (2003) The effect of microalloying with silicon and germanium on microstructure and hardness of a commercial aluminium alloy. J Serb Chem Soc 68(11):893–901 11. Gogoi S (2017) Effect of rolling and age-hardening on the mechanical properties of microalloyed 2219 Al alloy. MTech Thesis, Department of Mechanical Engineering, Tezpur University 12. Banerjee S (2011) Mechanical properties and high temperature deformation behaviour of Al– Cu–Mg alloys microalloyed with tin. Doctoral Thesis, IIT Guwahati, Assam, pp 1–176 13. Banerjee S, Robi PS, Srinivasan A (2010) Calorimetric study of precipitation kinetics of Al– Cu–Mg and Al–Cu–Mg-0.06 wt% Sn alloys. Metals Mater Int 16(4):523–531 14. Banerjee S, Robi PS, Srinivasan A (2012) Prediction of hot deformation behaviour of Al5.9%Cu-0.5%Mg alloys with trace additions of Sn. J Mater Sci 47(2):929–948 15. Banerjee S, Robi PS, Srinivasan A (2012) Deformation processing maps for control of microstructure in Al–Cu–Mg alloys microalloyed with Sn. Metall Mater Trans A 43:3834–3849

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16. Banerjee S, Bhadra R, Gogoi S, Dutta RS (2020) Investigating weldability in microalloyed Al alloys. In: Advances in mechanical engineering, p 271 17. Banerjee S, Gogoi S (2016) Influence of trace addition of Cd on the hardness and impact properties of 2219 Al alloy. J Appl Eng Res 13(3):1202 18. Jeyaprakash N, Duraiselvam M, Raju R (2018) Modelling of Cr3 C2 –25% NiCr laser alloyed cast iron in high temperature sliding wear condition using response surface methodology. Arch Metall Mater 63(3):1303–1315 19. Raju R, Manikandan N, Palanisamy D, Arulkirubakaran D, Sampath Kumar S, Bhanu Prakash P (2018) Optimization of process parameters in electrical discharge machining of haste alloy C276 using Taguchi’s method. Mater Today Proc 5(6):14432–14439

Optimization of Process Parameters in W-EDM with HCHCR by Using Taguchi Optimization Technique and Grey Relational Analysis M. Sathish Kumar and B. Satyanarayana

Abstract Wire-cut electrical discharge machine (W-EDM) is a precision machining approach that produces geometrically complex structures with a high level of accuracy and a smooth surface finish. The W-EDM is an unconventional machining technique which is also characterized by longer machining times which affect the machining characteristics. As it is modified process, still research is going on to find out optimum settings of pulse parameters which will improve the machining rates. HCHCR (High Carbon High Chromium) contains the minimum of 1.5–2.35% carbon and 12% of chromium widely used in thread rolling dies, hobs, and extrusion tools and therefore chosen as work piece material. In this present work, the HCHCR is taken as work piece, 0.25 mm diameter of brass wire used as the tool. For the experimentation, L-16 orthogonal array (OA) has been applied. The I/P process parameters chosen for optimizations are pulse on time (T on ), pulse off time (T off ), Servo Voltage (SV), Wire Feed (WF), Material Removal Rate (MRR), Surface Roughness (SR), and Kerf width (KW) as the performance characteristics. In the present study, Grey Relational Analysis (GRA) and Taguchi optimization method and ANOVA are used to analyze the results. The present work focuses on to develop and simulate an optimization model using Taguchi, GRA, and ANOVA for attaining higher MRR, lower SR, and KW. Hence, this work deals with the multi-objective optimization of process parameters in W-EDM with HCHCR as work material. Keywords Wire-EDM · Taguchi optimization method · GRA · HCHCR

1 Introduction W-EDM is a non-conventional machining technique which is based upon EDM machine and is also known as electro erosion machining. Traditional machining methods create substantial tool wear when used to machine new metals with extremely high stiffness and strictness. These materials (metals) are difficult M. Sathish Kumar (B) · B. Satyanarayana VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_5

55

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to machine using traditional production technique as drilling, milling, and turning, among other unconventional machining methods as ECM (electro-chemical machining), ultrasonic machining, and W-EDM. The W-EDM machining technique is a modified version of classical machining that may be used to produce electrically conductive objects regardless of their shape, hardness, or toughness [1]. HCHCR (high carbon high chromium) is a combination of carbon and chromium that is frequently used in thread rolling dies, holes, and other applications. When compared to copper wires, brass wires are formed by two alloys of copper and zinc. It has a good conductivity and a high tensile strength. The brass used in this experiment had a 35% of zinc content and a 65% of copper content. It was chosen as a tool because of its excellent qualities, availability, and inexpensive cost [1, 2]. The space between the work piece and the wire is normally between 0.005 mm and 0.075 mm, and it is supported by the computer controlling lay system at all times. And choosing the best machining input process settings in W-EDM is a key stage in the experiment. The Taguchi Optimization method is using individual parameter and it is depending on S/N ratio. The GRA is used to develop process variables while also allowing for multi-response via the Grey Relational Grade [3].

2 Experiment Concept The Taguchi approach is used to design the experiment in this work [4]. The orthogonal array (OA) was first proposed in the 1940s, it is now commonly utilized in the design of experiments, and it is used to minimize the number of trails [5]. The input parameters and their levels were determined in these experiments evolved from the cutting tool, machine tool, and capabilities of the work material, as given in Table 1. Performance measures depend upon the i/p parameters, i.e., T off , T on , SV, and WF. By using these input process parameter values, the performance results, i.e., SR, MRR, and KW values, are shown in Table 2. Table 1 Input parameters and levels S. No.

Input parameters

Unit

L-1

L-2

L-3

L-4

1

T on

µs

110

115

120

125

2

T off

µs

44

48

52

56

3

SV

V

35

40

45

50

4

WF

mm/min

5

7

9

11

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Table 2 Experimental results Input parameters Exp. No. T on [µs] T off [µs] SV [V] WF [mm/min] MRR SR [µm] KW [mm] [mm3 /mim] 1

110

44

35

5

8.14

2.825

0.259

2

110

48

40

7

7.24

2.702

0.264

3

110

52

45

9

6.78

2.592

0.271

4

110

56

50

11

5.40

2.315

0.257

5

115

44

45

7

13.98

3.305

0.332

6

115

48

50

11

12.84

3.112

0.295

7

115

52

35

9

11.82

2.979

0.314

8

115

56

40

5

10.62

2.836

0.375

9

120

44

50

5

20.76

3.656

0.264

10

120

48

45

7

19.68

3.597

0.278

11

120

52

35

11

17.16

3.418

0.291

12

120

56

40

9

15.06

3.316

0.334

13

125

44

35

11

24.72

3.914

0.289

14

125

48

45

7

23.53

3.806

0.317

15

125

52

40

5

22.74

3.725

0.241

16

125

56

50

9

21.30

3.692

0.371

3 Taguchi’s Optimization Method The Taguchi optimization technique proposes the quality engineering method, it provides the novel approaches for testing [1], and this method is used to design parameter performs to reduce the different causes of variation on the main quality of features of the product [4]. The S/N ratio has been derived using the Taguchi method, and in this S/N ratio, signal shows the preferable value and noise shows the unpreferable value [1]. In this optimization technique, the S/N ratio is calculated for all three output parameters, i.e., MRR, SR, and KW. The measured values (results) are transformed into the S/N ratio [5]. Here, the MRR is desired to be at higher so, larger the better characteristics used and SR and KW should be kept to a minimum so, smaller the better characteristics used in the calculation of S/N ratio. Table 3 shows that S/N ratio has been evaluated for main results. ( r ) 1 ∑ 1 S LB = −10 log N r i=1 y 2 where tests.

S LB N

is S/N ratio (Larger the better), yi —output features, and r—number of

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Table 3 Relevant S/N ratio for MRR, SR, and KW

Exp. No.

S/N ratio for MRR

S/N ratio for SR

S/N ratio for KW

1

18.212

−9.02

11.734

2

17.194

−8.63

11.561

3

16.624

−8.058

11.340

4

14.64

−7.291

11.801

5

22.910

−10.383

9.557

6

22.171

−9.860

10.603

7

21.452

−9.481

10.061

8

20.522

−9.05

8.519

9

26.34

−11.260

11.569

10

25.880

−11.118

11.119

11

24.690

−10.675

10.722

12

23.556

−10.412

9.525

13

27.860

−11.852

10.782

14

27.432

−11.609

9.978

15

27.135

−11.422

12.359

16

26.567

−11.345

8.612

( r ) 1 ∑ 2 S SB = −10 log y N r i=1 where NS SB is S/N ratio (Smaller the better), yi —output features, and r—number of tests. The mean value of S/N ratio values for MRR, SR, and KW has been evaluated for 4 levels as given in Tables 4, 5 and 6, respectively. From Fig. 1, the S/N ratio increases for a limited time and then after reduces as the T on and T off increase. Here, S/N ratio will be distracted when the SV and WF increase and decrease. From Fig. 2, the S/N ratio grows for short time before decreasing, when T on and T off increase and the SV reduces. The S/N ratio will be deflected when the WF is increased or decreased. Table 4 S/N ratio mean for MRR S. No.

Input parameters

L-1

L-2

L-3

L-4

1

T on

16.67

21.76

25.25

27.25

2

T off

23.83

23.17

22.48

21.32

3

SV

22.91

22.70

22.73

22.46

4

WF

22.66

22.57

23.00

22.57

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Table 5 S/N ratio mean for SR S. No.

Input parameters

L-3

L-4

1

T on

L-1 8.250

L-2 9.694

10.866

11.55

2

T off

10.629

10.304

9.909

9.524

3

SV

10.225

10.212

9.994

9.936

4

WF

10.130

10.052

10.226

9.958

L-2

L-3

L-4 10.433

Table 6 S/N ratio mean for KW S. No.

Input parameters

L-1

1

T on

11.609

9.685

10.734

2

T off

10.910

10.815

11.120

9.614

3

SV

10.418

10.751

10.352

10.941

4

WF

10.325

10.396

10.157

10.583

Fig. 1 Results of input variables on mean S/N ratio (MRR)

From Fig. 3, it is seen that when the T on grows, S/N ratio rises for a short time before decreasing and the S/N ratio drops when WF increases. The S/N ratio will be diverted when T off and SV are increased and decreased.

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Fig. 2 Results of input variables on mean S/N ratio (SR)

Fig. 3 Results of input variables on mean S/N ratio (KW)

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4 GRA—Grey Relational Analysis The Grey Incidence Analysis Theory, commonly known as Grey Relational Analysis (GRA), was first created by Chinese scientist “julongdeng.” Is a frequently used Grey System Theory Optimization model [6]. GRA theory is mostly utilized in analysis of engineering, and this analysis indicates the potential to tackle the problem of determining the best machining input factors for a process and many output variables [7–14]. The points carried out are, 1. 2. 3. 4. Step 1:

GR-Normalization (GRN) GR-Deviation Sequence (GRDS) GR-Coefficients (GRC) GR-Grade (GRG). Normalize the required results of MRR, SR, and KW measurement scaling from 0 to 1. This method is called as GRN. Step 2: Through the GRN values, the GRDS has been calculated using required characteristics. Step 3: The GRC is evaluated to show the co-relation between required value and the actual value. Step 4: Here, the average value of MRR, SR, and KW in GRC is known as GRG. Now, this model has been used to transform various objective optimization issues into one objective function problem [4]. From the GRG values acquired, the following four values are displayed in Tables 7 and 8. The investigation was completed by using L-16 OA. Here, influence of each machining parameter on GRG at various levels is given in Table 9 (Fig. 4) .

5 Anova ANOVA is the statistical selection-making device for discovering distinction in the mean effect of categories of things evaluated [1, 4] and the main goal of ANOVA to figure out which input variable has greatest impact on performance [1]

5.1 S/N Ratio for MRR The results are obtained by using ANOVA to regulate the percentage contributions of all input factors to the MRR displayed in Table 10. And it can also be noticed that the servo voltage (V) has a most significant factor impact on the MRR.

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Table 7 Grey relational normalization (GRN), grey relational deviation sequence (GRDS) values Exp. No.

GR-normalized (GRN) values

GR-deviation sequence (GRDS) values

MRR

MRR

SR

KW

SR

KW

1

0.139

0.318

0.134

0.861

0.682

0.866

2

0.094

0.242

0.171

0.906

0.758

0.829

3

0.070

0.173

0.224

0.932

0.827

0.776

4

0.000

0.000

0.119

1.000

1.000

0.881

5

0.443

0.619

0.679

0.557

0.381

0.321

6

0.384

0.498

0.403

0.616

0.502

0.597

7

0.331

0.415

0.544

0.649

0.585

0.456

8

0.269

0.325

1.000

0.731

0.675

0.000

9

0.794

0.836

0.179

0.206

0.164

0.828

10

0.738

0.801

0.276

0.262

0.120

0.724

11

0.608

0.689

0.373

0.392

0.311

0.627

12

0.499

0.626

0.694

0.501

0.374

0.306

13

1.000

1.000

0.358

0.000

0.000

0.642

14

0.937

0.932

0.567

0.063

0.068

0.433

15

0.897

0.881

0.000

0.103

0.119

1.000

16

0.822

0.861

0.970

0.178

0.139

0.031

Table 8 Grey relational co-efficient (GRC), grey relational grade (GRG) values Exp. No.

GRC values MRR

GRG values SR

Rank

KW

1

0.367

0.423

0.366

0.385

13

2

0.356

0.397

0.376

0.376

14

3

0.349

0.376

0.391

0.372

15

4

0.333

0.333

0.362

0.343

16

5

0.473

0.567

0.609

0.5499

9

6

0.448

0.499

0.456

0.468

12

7

0.435

0.460

0.523

0.473

11

8

0.406

0.425

1.000

0.610

7

9

0.708

0.753

0.376

0.612

6

10

0.656

0.806

0.408

0.0.623

5

11

0.560

0.616

0.443

0.539

10

12

0.499

0.572

0.620

0.564

8

13

1.000

1.000

0.437

0.812

2

14

0.888

0.882

0.536

0.769

3

15

0.829

0.807

0.333

0.656

4

16

0.737

0.782

0.942

0.820

1

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Table 9 GR-grade (GRG) mean values S. No.

Input parameters

L-1

L-2

L-3

L-4

1

T on

0.3690

0.5250

0.585

0.7642

2

T off

0.5895

0.5590

0.5100

0.5842

3

SV

0.5530

0.5363

0.5907

0.5628

4

WF

0.5477

0.5842

0.5910

0.5198

Fig. 4 Effects of input variables on mean GR-grade (GRG)

Table 10 ANOVA for MRR S. No.

Factors

Sum of squares

DF

Mean squares

% (Percentage contribution)

1

T on

255.184

3

85.061

0.0

2

T off

13.799

3

4.599

2.0

3

SV

0.414

3

0.138

68.9

4

WF

0.491

3

0.163

64.0

5.2 S/N Ratio for SR The % contribution of all input component on SR was determined using ANOVA, and results are provided in Table 11. It can be seen that the servo voltage has the greatest impact on SR.

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Table 11 ANOVA for SR S. No.

Factors

Sum of squares

DF

Mean squares

1

T on

23.321

3

7.773

% (Percentage contribution) 0.0

2

T off

2.615

3

0.871

1.2

3

SV

0.213

3

0.071

27.1

4

WF

0.347

3

0.115

16.4

DF

Mean squares

% (Percentage contribution)

Table 12 ANOVA for KW S. No.

Factors

Sum of squares

1

T on

7.601

3

2.533

3.0

2

T off

5.537

3

1.845

4.6

3

SV

0.931

3

0.310

34.5

4

WF

5.116

3

1.705

5.1

5.3 S/N Ratio for KW The results of the ANOVA to determine the % contribution of each i/p component on KW are displayed in Table 12, and it can be seen that the servo voltage (V) has the greatest impact on the KW.

5.4 Grey Relational Grade By using the ANOVA, the results obtained to find the percentage contribution on each input variable on MRR, SR, and KW are shown in Table 13. This is seen that Servo voltage (V) is the major influence factor on all output parameters, i.e., MRR, SR, and KW. Table 13 ANOVA table for MRR, SR, and KW S. No.

Factors

Sum of squares

DF

Mean squares

% (Percentage contribution)

1

T on

0.320

3

0.106

0.0

2

T off

0.015

3

0.005

3.3

3

SV

0.006

3

0.002

10.9

4

WF

0.013

3

0.004

4.2

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Table 14 Best order by using Taguchi technique S. No.

Input parameters

Units

MRR

SR

KW

Value

Top level

Value

Top level

Value

Top level

1

T on

µs

125

4

110

1

115

2

2

T off

µs

44

1

56

4

56

4

3

SV

V

35

1

50

4

45

3

4

WF

mm/min

9

3

11

4

9

3

Table 15 Best order by using GRA S. No.

Input parameters

Units

Value

Top level

1

T on

µs

125

4

2

T off

µs

44

1

3

SV

V

45

3

4

WF

mm/min

9

3

6 Results and Analysis The result was obtained by using Taguchi method to find the maximum MRR, minimum SR, and KW as appeared in Table 14. By using GRA results, we have found higher MRR, lower SR, and small KW (Table 15).

7 Conclusion Using Brass wire of 0.25 mm diameter, the investigational study on W-EDM with HCHCR was carried out. The following are the conclusions made. • Evaluated from the Taguchi model, the improved i/p parameter combinations to find the higher MRR are SV 35 V, WF 9 mm/min, T on 125 µs, and T off 44 µs, and similarly, optimized circumstances to get lower SR are SV 50 V, WF 11 mm/min, T on 110 µs, and T off 56 µs and also optimized form to get the minimum KW are SV 45 V, WF 9 mm/min, T on 115 µs, and T off 56 µs. • Based on GRA, the optimum conditions achieved through the applications of GRA are T on 125 µs, T off 44 µs, SV 45 V, and WF 9 mm/min. • By using the ANOVA, it has resulted that SV is the great influence factor on output parameters, i.e., MRR, SR, and KW in both Taguchi method and GRA.

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References 1. Durairaj M, Sudharsun D, Swamynathan N (2013) Analysis of process parameters in wire EDM with stainless steel using single objective Taguchi method and multi objective grey relational grade. Proc Eng 64:868–877 2. Kumar A, Singh DK (2012) Performance analysis of wire electric discharge machining (WEDM). Int J Eng Res Technol (IJERT) 1(4):1–9 3. Kumar S, Kumar P (2016) Investigation of material removal rate for wire-cut EDM of EN-31 alloy steel using Taguchi technique. Int J Sci Eng Res 7(12):155–161 4. Lal S, Sudhir Kumar ZA, Siddiquee AN (2013) Research and developments in wire electrical discharge machining (WEDM): a state of art 5. Singh P et al (2015) Experimental investigation of wire EDM to optimize dimensional deviation of EN8 steel through Taguchi’s technique. Int Res J Eng Technol (IRJET) 2(3):1753–1757 6. Karabulut S¸ et al (2018) Study on the wire electrical discharge machining of AA 7075 aluminum alloy. In: 2018 9th international conference on mechanical and aerospace engineering (ICMAE). IEEE 7. Mukhuti A, Rout A, Tripathy S (2016) Optimization of INCONEL 600 using wire EDM by MOORA and Taguchi’s method. In: 2016 international conference on electrical, electronics, and optimization techniques (ICEEOT). IEEE 8. Raju R, Sivalingam V, Sun J, Natarajan M, Zhao Y (2019) Experimental and Taguchi-based grey approach of laser metal deposition technique on nickel-based superalloy. Trans Indian Inst Met 72(1):205–214 9. Raju R, Manikandan N, Palanisamy D, Arulkirubakaran D, Sampath Kumar S, Bhanu Prakash P (2018) Optimization of process parameters in electrical discharge machining of haste alloy C276 using Taguchi’s method. Mater Today Proc 5(6):14432–14439 10. Rao PS, Ramji K, Satyanarayana B (2014) Experimental investigation and optimization of wire EDM parameters for surface roughness, MRR and white layer in machining of aluminium alloy. Proc Mater Sci 5:2197–2206 11. Manikandan N, Raju R, Palanisamy D, Arulkirubakaran D, Sampath Kumar S (2018) Investigation on Ti6Al4V laser metal deposition using Taguchi based grey approach. Mater Today Proc 5(6):14375–14383 12. Mandal K et al (2019) Analysis of wire-EDM input parameters on kerf width and surface integrity for Al 6061 alloy. In: Innovation in materials science and engineering. Springer, Singapore, pp 35–41 13. Palanisamy D, Manikandan N, Raju R, Arul Kirubakaran D, Binoj JS (2020) Prediction of performance measures in wire electrical discharge machining of aluminum–fly ash composites using regression analysis. In: Advances in industrial automation and smart manufacturing. Lecture notes in mechanical engineering. Springer, pp 387–396 14. Dastagiri M, Srinivasa Rao P, Madar Valli P (2016) TOPSIS, GRA methods for parametric optimization on wire electrical discharge machining (WEDM) process. In: Design and research conference (AIMTDR–2016) College of Engineering-India

Future Generation Materials and Techniques for Sustainable Construction Rajesh Kumar, Vanita Aggarwal, and Surinder M. Gupta

Abstract Future generation materials are multi-dimensional, broadly, content involving future generation, social, environmental, and economic aspects for construction research. Even though many claims to the benefits that sustainable construction can bring, sustainable materials still seem not mainstreamed in the construction industry. This article provides a detailed overview on the subject of future generation materials and techniques for sustainable construction. Sustainable materials protect the environment, climate, and natural resources. A sustainable housing apartment uses less water, natural resources, and energy, creates little qty waste, and is beneficial for the humans residing in the building compared to a standard or conventional building. Future generation techniques provide suitable atmosphere by controlling temperature of solar radiations, conservation of water using domestic plant of treatment, energy efficiency, and quality of indoor air. This study examines all elements of future generation techniques such as plant for rainwater harvesting plant, plant for biogas, filtration of gray water, and cooling tunnel. Future generation materials come together as a vast number of exercises, skills, and techniques to eliminate the building’s impacts on the human health and environment. The Globe is in an urgent need of sustainability, and a smart future development as the pollution and global warming problem is rapidly increasing all over the world. This paper suggests some future generation materials and techniques to opt the concept of sustainable construction with minimum changes in cost needed for construction as compared to the conventional building.

R. Kumar (B) M.M. Engineering College, M.M (Deemed to Be University), Mullana, Ambala, Haryana 133207, India e-mail: [email protected] V. Aggarwal Civil Engineering Department, M.M. Engineering College, M.M (Deemed to Be University), Mullana, Ambala, Haryana 133207, India S. M. Gupta Department of Civil Engineering, NIT Kurukshetra, Haryana 136119, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_6

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Keywords Future generation materials · Alternate materials · Sustainable techniques · Green building

1 Introduction Future generation materials or sustainable materials have gained rapidly rising importance in the construction industry. “Humanity has the ability to make sustainable development—to ensure that it meets the present needs without compromising the future generation’s ability to meet their own needs” [1]. Any construction project of building involves the choice of selecting building materials by incorporating the design scheme, and careful consideration of preconditions is essential to choose perfect building materials. In selection of right material, there are several standards for selection. Therefore, the data available and expertise on building material must constantly be evaluated to make the right decision [2]. Future generation techniques of building construction can be classified majorly into five categories, which include the structure’s location, indoor air quality, water conservation, onsite construction practices, and energy efficiency [3, 4].

1.1 Location A location of building is much more important to consider as it is directly concerned to the residents who come to the location live. Urban planners with green issues awareness must decide for new buildings to be most environmentally efficient sites.

1.2 Indoor Air Quality Good heating, ventilation, and air-conditioning (HVAC) systems improve the quality of indoor air. HVAC units are used to eliminate the harmful particles from air supply of the building [3].

1.3 Energy Efficiency Architects who design future generation buildings use several advanced techniques to enhance energy efficiency. One of the techniques is daylighting, which illuminates a building with natural light and conserves the energy.

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1.4 Water Conservation Sustainable buildings consider to design for lessen water usage for indoors as well as outdoors. Gray water can be collected from bathroom sinks, showers, washing machines and fountains, landscapes work, or flush toilets. Rainwater, unhealthier to drink, can be collected in basins or runoff channels [5].

1.5 Onsite Practices Construction companies which are dedicated to sustainable construction implement complete plans of recycling, in which identification of disposed materials would be done at regular basis and reused for new construction purposes. Many common constructions recycled materials can be reused in other projects. As an example, recycled concrete is most commonly used as the first initial layer for construction of new roads.

2 Designing Occupations in Future Generation Techniques Future generation buildings are using new ideas and technologies to make it more effective, so the team members who design the future buildings are required always to be open for innovating ideas and techniques [6, 7]. The job duties of various team members which adopt future generation techniques are as follows: • Architects design buildings and supported structures in such a way that it must match the people’s needs who use them. Architect’s designed sustainable building might come up with the ways to enhance the efficiency of building’s energy. • Civil engineers are fully responsible to supervise the construction of airports, roads, buildings, bridges, water supply, and sewage systems. They consider a lot of factors, from the cost of construction to the supposed lifetime of a project to environmental hazards and government regulations. • Electrical engineers frequently play the role to design the building’s lighting system. The energy efficiency importance in green buildings can be controlled by highly expert electrical engineers. • Landscape architects analyze the site’s natural elements like climate, irrigation, vegetation, soil, and slope of the land. They examine the project’s impact on the local ecosystem. • Mechanical engineers can have expertise in several different types of mechanical equipment. • Urban planners can conclude ecologically sensitive regions. They are involved in futuristic approach of environmental issues.

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Future generation materials are designed to reduce whole impact on health and environment by the following: i. Proper use of water, energy, and other resources. ii. Improving productivity and protecting occupant health. iii. Reducing trash, degradation of environment and pollution. Future generation techniques using environment-friendly materials from beginning to entire life cycle in its design, construction, execution, operation, and maintenance are used to sustain the environment [8–10].

3 Future Generation Materials The rapid increase in consumption of energy is due to increase in construction of buildings in today’s scenarios. The materials are used in a conventional building these days, which majorly consist of non-renewable standard materials, whereas sustainable materials or you can say future generation materials recommend particular advantages to the building clients and residents by decreasing maintenance costs during the life cycle of the building and improved occupant health and energy efficiency [11–13]. Some sustainable materials are as follows.

3.1 Dimension Stone Dimension stones like marble, granite, limestone, sandstone, and slate, etc., can be used in indoor flooring, facades, and outdoor pathways, it is broadly considered as one of the most favorable, durable, and sustainable types of building materials.

3.2 Engineering Wood Product The uses of engineering wood in sustainable buildings can vary from the range of fine floor finish to rough framing as per requirement. These wood products have allowed, for the harvested trees, optimized use by maximizing structural capacities and minimizing defects.

3.3 Concrete As a conventional building material, concrete is considered as sustainable by several standards, although the CO2 emissions arising issue is released during production

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of cement [4]. One treatment to that concern has been to interchange some PPC cementious content needed in the mix or by using of fly ash content, which is generally recycled from burning of coal in power plants. Additionally, we can use harvested and recycled concrete as filling element in future concrete products.

3.4 Recycled Steel Steel production involves releases of emissions and huge energy at high extent, and the recycled material having credibility for 66% of new steel production use is preferred. The recycled materials decrease the required amount of energy which is needed to produce steel product.

3.5 Green Roof and Reflective Roofs As green roof transfers low radiations of heat to the building, remains cooler and uses little energy for air conditioning, minimizing greenhouse gas emissions and pollution. By less energy use, cool roofs improve human health and comfort.

3.6 Glass Glass is a totally recyclable material; glass plays an important role in competing quality of indoor environmental and energy efficiency. Glass permits the natural light due to its design and placement.

3.7 Aluminum Paint Aluminum paint reflects the sunrays falling on the surface which mainly minimizes the heat intake and creates a better atmosphere to live in.

3.8 LED Lighting LED lights are 80% more efficient than traditional lighting. LED lights have advantage to convert high percentage of the energy approx. 95% into light, and remaining very low percentage of approx. 5% is wasted only as heat, whereas fluorescent lights give totally opposite to LED lights.

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Architects mainly use high-performance laminated glass double-sized glaze, to control internal temperatures by controlling heat. In summer environment, control glass is the best alternative to decreasing solar heat gain.

3.9 Recycled Shingles The shingles are made from waste materials (recycled) like rubber, plastic, or wood fiber. They are also made from post-industrial waste (factory waste), others from clean post-consumer waste (waste from homes). Recycled content shingles are fantastically durable and have an attractive look, too.

3.10 Rubber Roofing A major advantage of rubber roofing material is a very long life having warranty of 50 years, including against extreme weather.

3.11 Waterless Urinals These urinals system uses a chemical led known as blue seal which is used to store and recycle urine without any odor. These urinals completely eliminate the water usage. This proves to be more efficient when used in office spaces.

4 Innovative Future Generation Ideas and Technologies 4.1 Water Waste Technologies The water which comes from slab can collected in the water tank at the lower end of the building, and the surplus water is channeled to nearby pond or reservoir. This water can be used for water irrigation process and can also use potable water when it goes through the process of proper water treatment system. The process of water treatment is known where the collected green water is treated and can be reused to save the natural system and used as potable water also.

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4.2 Under Floor Air Distribution The produced ice during geothermal heat pump system has been used to lower the temperature of the building during the daytime. Cool air is also scattered through the radiant flooring systems to the zone, while the diffusers evaporate the hot air out of the atmosphere.

4.3 Solar Energy System A solar energy system converts the solar energy into lighting electricity which is used to get operational to the building [14–18]. This kind of energy renewable decreases impacts on environment such as destruction of natural resource, water pollution, and air pollution. Figure 1 shows the solar energy system.

Fig. 1 Solar energy system

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4.4 Geo-Thermal Air-Conditioning System This air-conditioning system which refrigerant spreads through copper tubing placed in the exchanges at ground directly heats the soil through the copper tubing walls which is generally used to diversify the water to ice in the ice storage box [19].

4.5 Rapidly Renewable Materials These materials are made from planks such as bamboo or any other similar materials. They are generally harvested within a span of 10 years of cycle or lesser and are used in sustainable building [10].

4.6 Low Emitting Materials Low VOC products are helpful to enhance indoor air quality during the construction stage as well as entire life cycle of the building [12].

4.7 Simulation The building information model of the structure is created to understand the climate conditions of the region. A building orientation analysis determines the best building orientation [13]. A solar analysis and living analysis can also perform at this stage. Energy analysis estimates the total use of energy in the building, and acoustic analysis determines the sound flow intensity within the building. A fluid dynamics analysis determines the building airflow pattern. A life cycle analysis determines the buildings environmental and economic performance throughout its entire life.

4.8 Storage and Collection of Recyclables The waste particles are generated by humans during building, and future generation building is committed to the segregation and storage of materials which can be recycled and reused.

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Fig. 2 Vertical gardening

4.9 Vertical Gardening A vertical garden grows vertically by using a MS or any other similar support system, instead on the ground (horizontally). Green walls are attached to the interior or exterior of a building. Vertical gardens are differed from green façades in that the plants root in a structural support which is fastened to the wall itself. Vertical garden improves both indoor and outdoor air quality by absorbing pollutant and eliminating harmful volatile organic compounds. Figure 2 shows vertical gardening.

4.10 Vermin Composting Vermin composting is a process, in which earthworms are used to ensure higherquality compost and to enhance the composting process speed. To enhance production capacity, solid waste which comes from kitchen and apartments like raw paper waste, cow dung, food waste, coconut waste, and egg waste by mainly enhancing production speed in vermin compost is used [9] (Fig. 3).

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Fig. 3 Vermin composting

4.11 Grass Pavers Grass pavers have big number of quadrilateral-shaped openings to penetrate water through ground and to increase the groundwater table. Grass pavers allow surface water to seep into the aggregate. Grass pavers are mainly used, where water drainage or soil erosion is of major concern [16]. Grass pavers allow surface water to drain free and clear and thus represent paving solution and water free driveway. Figure 4 shows the concrete grass pavers with lawn view.

4.12 Rainwater Harvesting Rainwater harvesting collects and distributes the rainwater for using in human’s daily life, instead of allowing it to waste [15]. Rainwater is generally sustained from roof slab tops. Then it is collected in a sufficient capacity reservoir with penetration. It is used for domestic uses, gardening, and irrigation and as groundwater recharge. Shortage of water is caused by gap in planning of water uses, climate changes, rapidly growing population, and water pollution. Under these critical conditions, some important steps toward water saving shall be taken. Rainwater can be collected, treated, and can be used as potable water. It is a simple and economical technology, so it can be smoothly installed in normal housing, and a huge quantity of water can be saved. Figure 5 shows the rainwater harvesting system.

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Fig. 4 Concrete grass pavers with lawn view

4.13 Biogas Plant Biogas is a combination of different gases generated by the disintegration of organic matter in oxygen’s absence [20]. It can be generated from agricultural waste, sewage, food waste, or green waste. It is a renewable source of energy. Biogas can be used as a fuel. Biogas energy can be converted into heat and electricity.

5 Features of Future Generation Materials and Techniques Future generation materials and techniques have many extreme features. Some of them are as follows: • Energy-efficient equipment for lighting systems and air-conditioning system and onsite renewable energy use. • Providing natural daylight for visibility. • Measurement plan to ensure water and energy savings. • Minimization of building footprints to reduce the impact on environment. • Minimal disturbance to site conditions and landscapes. • Reuse of environmentally friendly and recycled building materials. • Use off non-toxic materials and recyclable materials. • Water recycling efficient use. • Indoor air quality enhancement for human health, safety, and comfort. • Use of rapidly renewable materials.

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Fig. 5 Rainwater harvesting

6 Comparative Analysis Between Sustainable Material and Techniques Over Conventional Techniques See Table 1.

7 Conclusion Future generation construction describes sustainable future development applications in the construction industry. Future generation techniques always integrate different dimensions, including economic, social, and environmental dimensions. We have concluded that the sustainable building is eco-friendly as well as economical. In future generation techniques opted for sustainable building, debris (waste material) is used as plinth filling and bigger size windows are provided for light ventilation to minimize energy waste. Plumbing low water pressure tapes are used to reduce water wastage. Hence, future generation techniques are more energy efficient than

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Table 1 Comparative analysis between sustainable techniques over conventional techniques S. No.

Description

1

Site selection

A

Location

Conventional techniques

Sustainable techniques

Very low consideration for community approach

Infill, brownfield site, reclaimed, close proximity to community approach

B

Zoning

Low density

High density compact design

C

Infrastructure

Only cost consideration

Infill, resources, cost, and density are considered

No consideration

Excellent solar access

D

Solar access

2

Site design and landscaping

a

Site protection

No site protection

Protecting natural top soil, developing landscape and site preservation plan

b

Reducing heat island effect

No consideration

Reducing paving areas, using heat defecting materials, planting canopy trees

c

Water-efficient landscaping

Standard landscaping planning

Intentional landscape plan, low water use irrigation practices

d

Storm and surface water

Only law fulfillment consideration

Storage of gray water, channeling storm water

3

Material resource efficiency

a

Passive solar heating

No consideration

Proper window placement, increased solar glazing area

b

Passive solar cooling

No consideration

Strategic placement of vented window, landscaping of windows

c

Daylighting

No intentional strategies

Intentional daylighting design and clearstory windows

d

Concrete formwork

Standard plywood formwork

Aluminum formwork

e

Fly ash content concrete

No fly ash content

High content fly ash concrete

f

Panelized wall system Standard framing

Closed wall structural insulated panel, floor, and roof system

g

Cool roofs

Standard roof

Green roofs

h

Wall finishes

Non-recycled content

Fiber cement siding, corrugated metal, and native stone (continued)

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Table 1 (continued) S. No.

Description

Conventional techniques

Sustainable techniques

i

Flooring

Standard carpet and vinyl hard surfaces

Certified natural fiber, natural linoleum, or bamboo hard surfaces

j

Wall insulation

Fiberglass batts

Cell spray foam, insulation quality control verification

k

Windows and doors

No air/moisture sealing

Properly installed window and door sealing

l

Lighting

Standard lighting with incandescent bulb

Advanced daylighting with tubular skylights, advanced lighting controls

m

Solar photovoltaic

No orientation and roof, no pre-wiring

Proper orientation of roof, PV wiring, and installation of solar PV system

n

Water conservation

Standard faucets with no Low flow faucets aerators, aerators, no consideration for dual flush pressure, landscape water saving landscape plan based on water budget, gray water system

o

Finish materials

Standard toxic finish materials

Non-toxic and durable finish materials

p

Indoor air quality

No whole house ventilation

Heat recovery whole house ventilation system

q

Recycled and reuse materials

No recycled and reuse materials used

Specify and source of recycled and reuse materials for both structural elements and finish elements

r

Waste management

No waste management program

Set up construction waste management plan and provide sufficient bins for collection and grinding services

conventional techniques. From the study, it may be concluded that future generation materials and techniques save energy, natural resources and minimize environmental impact. The operational cost of sustainable building is very less rather than a conventional building. These techniques provide warm effect in winter and cooling effect in summer. Nowadays, energy sources are decreasing rapidly and also their uses are increasing rapidly. The landscaping in planned way will also give an attractive look to the building and its surrounding areas. The green roof techniques can reduce the heat island effect in residing areas, reduce the dust particles, and improve the air quality. The rainwater harvesting techniques will increase the groundwater level which will be utilized accordingly in the period of demand.

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From this research, we have seen that future building is not just about architectural design but the future generation materials play a major role to protect the environment and health. The study considered strategies of passive design and the system of energy-efficient building to improve performance of building and decreasing energy consumption. Based on efficient energy modeling and simulations, multidimensional design aspects were investigated, such as improvements to building envelope, selection of materials, retrofitting of HVAC, and lighting systems as well as application of renewable energy sources.

References 1. Sourani A, Sohail M (2005) A review of sustainability in construction and its dimensions. Combining Forces Adv Facil Manage Constr Innov Ser 4:536–547 2. Samih H (2018) An investigation of sustainability issue for building construction in North Cyprus. J Environ Sustain 6(1):5 3. Liming D (2011) Careers in green construction. US Bureau of Labor Statistic, US 4. Shams S, Mahmud K, Al-Amin M (2011) A comparative analysis of building materials for sustainable construction with emphasis on CO2 reduction. Int J Environ Sustain Dev 10(4):364– 374 5. Neha S, Ali D, Bhutekar SB (2017) Comparative study of estimate between conventional building and green building. Int J Adv Res Sci Eng 6(9):467–471 6. Kanika SK, Rana K, Dahiya M (2016) A comparative study on green and conventional buildings. Int J Home Sci 2(2):338–343 7. Vijayan V, Thomas GE, Madhu A (2018) A comparative study on sustainable building construction with conventional residential building. Int J Curr Eng Sci Res 5(4):2394–2697 8. Nasser A, Ashraf A, Salim DK, Gayathri P, Vishnu N (2017) Comparative study of conventional and green residential building. Int J Innov Sci Res Technol 2(4):174–237 9. Misra S, Prasad GS, Kumar N, Sah SK, Kumar S, Maurya R (2016) Comparison analysis of green building materials and conventional materials in energy efficiency performance. Int Res J Eng Technol (IRJET) 3(05):80–84 10. Balramdas P, Meher S, Behera B, Rath S, Dash P (2016) A comparison between normal buildings and green buildings: a case study approach. Int Res J Eng Technol 2372–2395 11. Parashar AK, Parashar R (2012) Construction of an eco-friendly building using green building approach. Int J Sci Eng Res 3(6) 12. Windapo A, Machaka M (2018) Conventional and sustainable buildings: a comparative benefit and cost analysis. J Constr Proj Manage Innov 8(1):1696–1710 13. Pathak C, Kumar S (2019) Conversion and comparison of a conventional building to a green building. Int Res J Eng Technol 6(12):1430–1434 14. Abbas ZA (2021) Conversion of conventional building to net zero energy building. IOSR J Mech Civ Eng (IOSR-JMCE) 9:38–41 15. Choudhary P, Gupta J, Nagar B (2018) Conversion of existing building into green building. Int Res J Eng Technol 5(9):1474–1483 16. Nagrale SS, Sabihuddin S (2020) Cost comparison between normal building and green building considering its construction and maintenance phase. Int J Sci Res Eng Dev 3(4):77–80 17. Bragança L, Vieira SM, Andrade JB (2014) Early stage design decisions: the way to achieve sustainable buildings at lower costs. Sci World J 2014(365364):1–8 18. Mokal AB, Shaikh AI, Raundal SS, Prajapati SJ, Phatak UJ (2015) Green building materials—a way towards sustainable construction. Int J Appl Innov Eng Manage 4(4):244–249

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19. Noor S, Nazim SY, Ati R, Muhammaz Azzam I (2014) Green buildings in campus: an assessment of green potential for existing conventional buildings. In: 1st regional conference on campus sustainability, April 2014. Sabah, Malaysia 20. Singh CS (2018) Green construction: analysis on green and sustainable building techniques. Civ Eng Res J 4(3):555638

Tribological Characterization of Microalloyed Al-Cu Alloys by Artificial Neural Network Modeling Sanjib Gogoi , Dewesh Kumar , Sanjib Banerjee , Sushen Kirtania , and Satadru Kashyap

Abstract High strength-to-weight ratio, as well as enhanced fracture toughness and corrosion resistance, has made 2219Al–Cu alloys prospective structural materials for automobile, marine, aircraft and aerospace engineering. Microalloying (< 0.1 wt%) with trace elements such as Sn, In, Cd, Ag, Si, etc. is currently being explored for achieving even better mechanical properties, while maintaining lower density. Present research is aimed at investigating tribological behavior of rolled and peakaged 2219Al alloy and same alloy with trace contents (0.06 wt%) of Cd. Dry sliding wear tests were conducted on pin-on-disk tribometer with four different loads and linearly reciprocating frequency, and the volumetric wear rates (W v ) were evaluated. Wear rate increased with increase in either load or frequency, while trace content of Cd improved the surface wear resistance of 2219Al alloy system. The W v of both alloys was further modeled as a function of two independent and external working parameters of load and frequency, by artificial neural network (ANN). Wear rate values subsequently predicted under various processing conditions were compared and correlated with experimental results within satisfactory accuracy limits. Best-fit network architecture yielded excellent prediction of 100% wear rate values, within a percentage deviation of ± 10%, and with RMS error values of 2.44 and 1.42 for the investigated alloys. Such observation highlights the superior prediction capability of ANN technique in tribological modeling and characterization. Resulting from the intelligent processing and manufacturing system with ANN, working parameters may be subsequently formulated and optimized, based on tribological behavior of the material. Keywords Aluminum alloys · Microalloying · Wear behavior · Tribology · Artificial neural network

S. Gogoi (B) · D. Kumar · S. Banerjee · S. Kirtania · S. Kashyap Department of Mechanical Engineering, Tezpur University, Tezpur 784028, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_7

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1 Introduction Aluminum (Al) and its alloys are used for versatile engineering products and applications, because of their broad spectrum of superior and attractive mechanical characteristics. Reasonable high strength may still be archived by these relatively lightweight and low-cost materials, through proper heat-treatment routes. Especially due to enhanced specific strength and many other unique combinations of properties, there is a remarkable increase in design considerations of Al alloys, for strong light-weight structures, typically that moves, including all ranges of land- and water-borne vehicles as well as aerospace [1–3]. Specifically, the wrought and age-hardenable 2xxx series was focused during recent years, for automobile, marine, aircraft and space applications. Among 2xxx series, 2219Al alloy is a two-phase hypoeutectic Al–Cu alloy system, with exemplary blend of elevated strength-to-weight ratio, ductility, fracture toughness, resistance to corrosion, weldability and production efficiency along with improved properties at cryogenic temperatures. Subsequently, 2219Al alloy is used in the fabrication of supersonic aircraft skin and structural members like space boosters, rocket fuel tanks and fins, etc. Recent trend in alloy development is to microalloy (adding trace contents < 0.1 wt%) with elements like Ag, In, Sn, Cd, etc. Microalloying may actually combine elevated mechanical strength with significant toughness, while still maintaining lower density [1–3]. Wear is a mechanism in which a material on one surface is removed and deformed, as a result of mechanical abrasion or pressure from the opposite surface, when two solid surfaces interact in a working environment. In industries, wear amounts to high maintenance costs and in aerospace applications, it can be sometimes the deciding factor in failure of a component or a whole mission. Hence, material scientists have been in constant search for materials with higher wear resistance. One major problem of Al alloys is their poor wear characteristics. Researchers have presently focused their attention in developing new advanced materials like metal matrix composites for overcoming such poor wear behavior of Al alloys. Subsequently, Al-matrix composite materials have demonstrated reasonable efficacy in different engineering applications, due to enhanced stiffness, wear resistance, specific weight and hightemperature behavior over their matrix alloys. Since microalloying has evidentially been observed to exhibit better mechanical properties, exhaustive research regarding its influence on wear performances also becomes essential [4]. Experiments on the effect of load and sliding speed on wear behavior and friction coefficient of a pin of 7075Al-Fly Ash composite material revealed that metal composites had much better properties than alloys or any other metal [5]. However, it was also observed that strength and hardness of 2219Al alloy enhanced significantly with a concomitant reduction in ductility, due to trace additions of 0.06 wt% Cd [5– 7]. Microalloying with 0.06 wt% Sn could also successfully increase the mechanical strength and hardness of 2219Al alloy, with a consequential improvement in wear resistance [8–12]. Artificial neural network (ANN) is a data-driven method that predicts the solution, even when the specific input–output correlation is unknown [11]. Now, during a

Tribological Characterization of Microalloyed Al-Cu Alloys …

85

tribological modeling, wear rate of the material may be considered as a function of different independent working parameters, viz. load and sliding speed or frequency. Such wear rate value may therefore be modeled and can be accurately predicted for any set of input factors inside the process domain, by using ANN. An investigation on the use of ANN in examining and predicting the mechanical properties of A413 Al alloys generated accurate predictions and considered ANN as a boon in terms of cost and time savings [11–18]. Microalloying elements may change the properties of Al alloys, by altering composition and morphology of the microstructural phases, entire range of mechanical behavior, failure mechanisms, including the tribological characteristics [1–3]. Information available regarding effect of microalloying on structure and characteristics of Al alloys is quite limited. Influence of trace Cd additions, in particular, on heat-treatable Al alloys of 2xxx series, is yet to be documented. In a parallel research work, although mechanical properties have been presently investigated for these alloys, lack of literature still exists in several fields, including tribology or wear behavior [4]. The wear behavior is thereby a significant area, which needs to be investigated for these alloys, for proper design and fabricating of both static and dynamic machine elements. The present research is aimed at investigating the tribological behavior of rolled and peak-aged 2219Al alloy and same alloy with trace contents (0.06 wt%) of Cd. The trace content of 0.06 wt% Cd was selected because in a parallel research work, strength and hardness were observed to be higher for this alloy [5– 7]. Dry sliding wear tests were performed on a pin-on-disk tribometer, at varying conditions of load and linearly reciprocating frequency. The influences of working parameters, as well as microalloying composition on the volumetric wear rate, were studied. Wear rate of both the alloys was modeled and predicted as a function of two independent externally controllable parameters of load and linearly reciprocating frequency, by using ANN. The wear rate values subsequently predicted at various working conditions were compared and correlated with experimental results within satisfactory accuracy limits. Statistical error analysis was performed, which highlights the superior prediction capability of ANN technique in tribological modeling. Moreover, such intelligent modeling and prediction with ANN can provide immense industrial help in formulating and optimizing the working parameters on the basis of material wear behavior.

2 Experimental Procedure 2219Al alloy with 6.3 wt% Cu (Alloy-A) and same alloy with trace contents (0.06 wt%) of Cd (Alloy-B) were processed by standard foundry technique, in a resistance heated melting furnace [5]. Generally, the high-performance mechanical properties of Al alloys can be attained through thermo-mechanical treatment (TMT), constituting three major sequential stages of solid solution heat treatment followed by quenching, then plastic deformation and lastly aging. This TMT process can impose highest strength and hence wear resistance of a material by the combined effect of

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deformation strengthening during metal forming and transformation strengthening during age-hardening heat treatment. TMT process can significantly refine the precipitates and produce mesh substructure by intertwined dislocation with the precipitated phase, which can enhance the mechanical properties of Al alloys to a much higher extent. Therefore, following precipitation-hardening protocol, the cast alloys were first solutionized (10 h at 525 °C) and quenched. The cast and solutionized machined alloy strips were preheated at 200 °C for 2 h and subsequently warm-rolled at the same temperature in a laboratory-scale rolling mill. Rolling operation was carried out in eight number of passes, to achieve a final reduction in strip thickness from 10 to 6 mm (i.e., 40% reduction). Now, age-hardening conditions become necessary to be optimized due to lack of open literature and information relevant to peak-aging time of 2219Al alloy microalloyed with Cd. In a parallel research, age-hardening behavior was therefore separately studied to estimate the corresponding aging time to achieve peak-hardness. Most of the 2xxx series Al alloys were age-hardened at temperatures between 160 and 190 °C [8]. For present alloys, a precipitation temperature of 170 °C has been adopted to obtain isothermal age-hardening curves. For different aging times Vickers hardness (VHN) was evaluated, to determine aging time necessary for each alloy to achieve maximum hardness. This peak-aging time was evaluated to be 40 h for the investigated solutionized alloys, at the given precipitation temperature of 170 °C. As compared to the cast alloys, an average increase in hardness value by around 147% could be observed, due to this peak-aging treatment. Therefore, during the current study, the solutionized and rolled samples were further age-hardened for a period of 40 h at 170 °C. Cubical samples of size 10 × 10 × 6 mm3 were machined from the rolled and peak-aged alloys, for conducting the dry sliding wear tests. Dry sliding wear tests of the rolled and peak-aged samples were performed on a pin-on-disk tribometer (Make: ASTM G133, Model: DUCOM POD-4). The machined cubical samples were used as pins and tested against an 8-mm-thick disk of diameter 165 mm made of hardened ground steel (En31 hardened to 62HRc) under ambient conditions. The specimen was held stationary in the sample holder, while the disk was reciprocated against it. As the disk reciprocated, loads were simultaneously applied through a lever mechanism. Sixteen tribological experiments were conducted on each material at room temperature, under four different loads of 5, 20, 35 and 50 N, and four different reciprocating frequencies of 0.5, 2, 3.5 and 5 Hz as shown in Table 1. A constant abrading time of 150 s and stroke length of 10 mm were maintained for all the experiments conducted. During each test, the volumetric wear rate (W v ) was calculated by mass change method, i.e., by evaluating the decrease in weight of the test specimen, using an electronic balance. The influences of working conditions, as well as microalloying composition on the volumetric wear rate, were studied. The W v of both the alloys was modeled and predicted by ANN. In present modeling, two input parameters, i.e., load and frequency, were represented by two neurons in the input layer, a single layer of hidden neurons and one neuron in the output layer corresponding to the output parameter of W v , which generated the datasets for the network’s training. Present modeling was performed by using

Tribological Characterization of Microalloyed Al-Cu Alloys … Table 1 Selected values of load and frequency for wear tests

S. No.

Load (N)

1

5

2

20

87 Frequency (Hz) 0.5 2

3

35

3.5

4

50

5

‘ANN tool kit’ at ‘MATLAB’ software package, and ‘TRAINLM’ function following ‘Levenberg–Marquardt optimization’ [13, 14]. During training and testing phases of each trial, the mean square error (MSE) was determined. The least MSE value acquired during training and testing stages was used to identify the best-fit network architecture. Once proper network architectures are arrived at for the alloys, the wear rate can be accurately predicted for any set of input parameters within the given domain range.

3 Results and Discussion 3.1 Variations in Wear Rate Figures 1 and 2 show the variations of W v with load and linearly reciprocating frequency, for Alloy-A and Alloy-B respectively. In these plots, solid lines represent the trends observed for the experimental data of wear rate with variation in different test conditions, while the dashed lines represent the variations of the predicted data (by ANN) of the corresponding wear rate values. For both the investigated alloys, the experimental values of W v were observed to increase with increase in either load or frequency, for given test conditions. For most of the test conditions, the increase is not significant under the load of 5 N. However, the volumetric wear rate indicated a steep increase with a higher rate at and above 3.5 Hz frequency, for both the alloys. The average % decrease in volumetric wear rate was estimated as 19.7%, due to trace additions of 0.06 wt% Cd. Such decreasing trend in W v can be attributed to the increasing mechanical strength and surface hardness for the examined alloys, resulting from trace additions of Cd, as revealed from a parallel research work [5–7]. A similar increase in strength, hardness and wear resistance was also reported with 2219Al alloy, due to adding trace contents of Sn [8–12].

3.2 Artificial Neural Network (ANN) Modeling of Wear Rate To predict the values of W v at various combinations of load and reciprocating frequency, and thus to study the wear behavior at any given condition, ANN modeling

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Fig. 1 Comparison of experimental and predicted trend of volumetric wear rate with a load and b frequency for alloy-A

Fig. 2 Comparison of experimental and predicted trend of volumetric wear rate with a load and b frequency for alloy-B

was performed. This is based on the concept that W v is a function of load and frequency, as per the following equation: Wv = f (load, frequency)

(1)

The suitable weights and bias of ANN network were evaluated by training it with various datasets. For modeling of W v , under different conditions of loads and reciprocating frequency, a total number of 16 input–output data sets were used from the experimental results of each alloy. Following the Pareto principle, 80% data was chosen for training and the rest 20% data has been used for performing testing and validation. Training and testing of the network were carried out independently. RMS error was employed as a criterion to decide on the network performance, for selecting the best network architecture, and which can be expressed as: / RMSerr=

∑ ⌈

(Wv )exp −(Wv )pre n

⏋2 (2)

Tribological Characterization of Microalloyed Al-Cu Alloys … Table 2 Final neural network architectures

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Sample-ID

Hidden neurons

First transfer function

Second transfer function

Alloy-A

3

Logsig

Purelin

Alloy-B

5

Tansig

Purelin

where (Wv )exp is experimental volumetric wear rate value and (Wv )pre is predicted value of corresponding volumetric wear rate. RMSerr values were calculated separately both for training and testing stages. Table 2 shows the neural network architectures that best fitted with the alloys studied. After finalizing the architecture, the trained network was used to predict W v using the validation datasets. Figures 1 and 2 reveal the superimposition of experimental and predicted trends (by ANN) observed in the variations of W v for the alloys, with different test conditions of load and frequency. For both the investigated alloys, the predicted trends of W v were observed to maintain a close conformity with the experimental data, almost overlapping each other. Similar to the experimental trends for both the alloys, predicted W v was also observed to increase with increase in either load or reciprocating frequency. Furthermore, the predicted W v of Alloy-A was also observed to decrease due to trace additions of 0.06 wt% Cd, in proportion with the experimental results.

3.3 Statistical Error Analysis Predicted versus experimental wear rate values for training, testing and validation datasets of the alloys are shown in Fig. 3. All the points should be on solid line at angle 45° to X-axis, to represent perfect prediction. The same figure also includes sets of dotted lines that indicate the boundaries of ± 10% deviations. The figures reveal that majority of points are quite close to perfect prediction. Percentage error estimated during W v prediction was less than ± 10%, for all the data values considered for both the alloys. Further, Table 3 shows the error values while prediction of wear rate, as obtained during testing and validation stages of ANN modeling for the investigated alloys. The results reveal that although the predicted values slightly deviate from the experimental results, the percentage and RMS errors are within the satisfactory limits. RMS errors for testing were registered to be 2.44 and 1.42 respectively for Alloy-A and Alloy-B. Although highest absolute error in prediction for Alloy-A was estimated to be 3.28 × 10−14 m3 /s, the error percentage is just 8.47%. The absolute error shows a relatively higher value, since the magnitude of W v is also in the higher side. Consequently, for low values of W v (viz. 13.58 × 10−14 m3 /s), although the absolute error is only 1.08 × 10−14 m3 /s, the percentage error registers comparatively a high value of 6.46%. For Alloy-B, the maximum absolute error during prediction was 1.80 × 10−14 m3 /s, where the percentage error was evaluated to be only 3.47%.

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Fig. 3 Variation of predicted with experimental volumetric wear rate for a alloy-A and b alloy-B

Table 3 Maximum % and RMS errors evaluated during testing and validation Testing

Validation

Sample-ID Max % error RMS error × 10−14 m3 /s Max % error RMS error × 10−14 m3 /s Alloy-A

8.46

2.44

0.95

0.10

Alloy-B

3.93

1.42

6.94

0.76

Figure 4 shows the bar graph representations of the percentage errors, during prediction of W v for the investigated alloys, as compared to their corresponding experimental values, during testing and validation stages. It was observed for both the alloys that majority of error points lie within the range of ± 5% deviations, confirming the prediction by ANN to be reasonably accurate. Above observation along with the low RMS error values registered, not only highlight the superior prediction capability of ANN technique in tribological modeling, while such intelligent modeling and prediction with ANN may formulate and optimize the working parameters based on the material wear behavior.

Fig. 4 Distribution of percentage errors during prediction of volumetric wear rate for a alloy-A and b alloy-B

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4 Conclusions 1. 2219Al alloy and same alloy with trace contents (0.06 wt%) of Cd were processed by standard foundry technique, and subsequently rolled and peak-aged. 2. The wear behavior of both the alloys was investigated under varying conditions of load and linearly reciprocating frequency, on a pin-on-disk tribometer. The influences of working conditions, as well as microalloying composition on the volumetric wear rate, were studied. 3. Wear rate of both the investigated alloys increased with increasing load or frequency. The alloy with trace contents of Cd exhibited higher wear resistance by 19.7%, thus imparting superior tribological characteristics to the base 2219Al alloy. 4. Wear rate of both the alloys was modeled and predicted as a function of two independent externally controllable parameters of load and reciprocating frequency, by using Artificial neural network. 5. The predicted wear rate values were correlated with the corresponding experimental results under different processing conditions, with fairly good accuracy. 6. Statistical error analysis was performed. The final and best-fit network architecture yielded excellent prediction of 100% wear rate values of both the alloys, within a percentage deviation of ± 10%, and with RMS values of 2.44 and 1.42, respectively for the base alloy and alloy containing trace additions of Cd. 7. This highlights superior prediction capability of ANN technique in tribological modeling. Such intelligent processing and manufacturing system with ANN is capable to formulate and optimize the working parameters based on the tribological behavior of the material.

References 1. Rao KS (2010) Microstructure and impression creep of age hardenable AA2219 aluminium alloy modified by Sc, Mg and Zr additions. Trans Indian Inst Met 63(2):379–384 2. Rana RS, Purohit R, Das S (2012) Reviews on the influences of alloying elements on the microstructure and mechanical properties of aluminium alloys and aluminium alloy composites. Int J Sci Res Publ 2(6):2250–3153 3. Hornbogen E (2001) Hundred years of precipitation hardening. J Light Met 1:127–132 4. Basavarajappa S, Chandramohan G (2005) Dry sliding wear behavior of hybrid metal matrix composites. Mater Sci 11(3):253–257 5. Gogoi S (2017) Effect of rolling and age-hardening on the mechanical properties of microalloyed 2219 Al Alloy, MTech Thesis, Department of Mechanical Engineering, Tezpur University 6. Banerjee S, Bhadra R, Gogoi S, Dutta RS (2020) Investigating weldability in microalloyed Al alloys. In: Advances in mechanical engineering, p 271 7. Banerjee S, Gogoi S (2016) Influence of trace addition of Cd on the hardness and impact properties of 2219 Al alloy. J Basis Appl Eng Res 13(3):1202 8. Banerjee S, Robi PS, Srinivasan A, Lakavath PK (2010) Effect of trace additions of Sn on microstructure and mechanical properties of Al-Cu-Mg alloys. Mater Des 31:4007–4015

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9. Banerjee S, Robi PS, Srinivasan A (2010) Calorimetric study of precipitation kinetics of AlCu-Mg and Al-Cu-Mg-0.06 wt% Sn alloys. Met Mater Int 16(4):523–531 10. Banerjee S (2011) Mechanical properties and high temperature deformation behaviour of AlCu-Mg alloys microalloyed with tin. Doctoral Thesis, IIT Guwahati, Assam, pp 1–176 11. Banerjee S, Robi PS, Srinivasan A (2012) Prediction of hot deformation behaviour of Al-5.9% Cu-0.5% Mg alloys with trace additions of Sn. J Mater Sci 47(2):929–948 12. Banerjee S, Robi PS, Srinivasan A (2012) Deformation processing maps for control of microstructure in Al-Cu-Mg alloys microalloyed with Sn. Metall Mater Trans A 43A:3834– 3849 13. Robi PS, Dixit US (2003) Application of neural networks in generating processing map for hot working. J Mater Process Technol 142(2):289–294 14. Redappa HN (2011) Dry sliding friction and wear behaviour of aluminium/beryl composites. Int J Appl Eng Res 32(2):502–511 15. Vinothkumar S, Jie S, Bin Y, Kai L, Ramesh R (2018) Machining performance and tool wear analysis on cryogenic treated insert during end milling of Ti-6Al-4V alloy. J Manuf Process 36:188–196 16. Jeyaprakash N, Muthukannan D, Ramesh R (2018) Modelling of Cr3C2–25% NiCr laser alloyed cast iron in high temperature sliding wear condition using response surface methodology. Arch Metall Mater 63(3):1303–1315 17. Thirugnanasambantham KG, Ramesh R, Sankaramoorthy T, Velmurugan P, Kannagi A, Chaitanya KRM, Sai KCV, Mustafa MA, Ramesh CV (2018) Degradation mechanism for high-temperature sliding wear in surface-modified In 718 superalloy. Cogent Eng 5:1501864 18. Giridhar D, Ramesh R (2020) Contact stress evaluation of micro-grooving process of alumina ceramic and validation with acoustic emission parameters. In: Advances in industrial automation and smart manufacturing, Springer, Lecture notes in mechanical engineering), pp 597–617

Design and Fabrication of Impression Creep Testing Setup and Experimental Validation with 2219Al Alloys Sanjib Gogoi , Reeturaj Boruah , Mehsana Ahmed , Sanjib Banerjee , Sushen Kirtania , and Satadru Kashyap

Abstract Thermo-mechanical treatments are essentially performed on wrought heat-treatable metallic alloys, before final application as structural materials. High homologous temperatures are maintained while plastically deforming the alloys, to eliminate defects induced while casting. Many of these alloys are also exposed to high temperature applications, encountering creep failure mechanism. Hence, high temperature deformation and creep behavior of different materials is an area of increased interest, using different methodologies. The present research aims to design and fabricate a laboratory-scale experimental setup, to substitute commercial hi-end equipment, for high temperature impression creep testing. Heating arrangement for desired temperatures and provision for variable load application have been combined into one single desktop unit. Impression creep indentation on a material can be estimated, for various combinations of loads and temperatures, generating creep curves, homologous to conventional tensile creep tests. The functionality and compatibility of the setup were successfully validated by conducting impression creep experiments on 2219Al alloys, under varying conditions of loads and temperatures. The generated creep curves with three distinct creep stages, as well as creep rates, were analyzed with respect to time, and compared with the theoretical models. The individual influences of load and temperature on creep properties of the alloy were investigated. Different creep parameters of minimum creep rate, penetration depth, penetration velocity, stress exponent, and activation energy were further evaluated and successfully compared and correlated with the reported literatures. Keywords Aluminum alloys · Impression creep · High temperature deformation

S. Gogoi (B) · R. Boruah · M. Ahmed · S. Banerjee · S. Kirtania · S. Kashyap Department of Mechanical Engineering, Tezpur University, Tezpur 784028, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_8

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1 Introduction Many metallic alloys for structural applications need to undergo thermo-mechanical treatments during their manufacturing stage and prior to their final usage. The chemistry, microstructure, and strain history induced from these thermo-mechanical treatments have final impact on mechanical characteristics. In order to eliminate casting defects, the wrought alloys must be plastically deformed. High homologous temperatures (i.e., T /T m > 0.5) are generally used during the deformation procedure, where T and T m represent, respectively, the operating temperature and material’s melting temperatures. Many of these alloys are additionally exposed to high temperature applications. The 2xxx series Al–Cu alloys, such as 2124, 2219, and 2618, are widely used in aviation components, which require high heat resistance up to 150 °C [1– 4]. 2219Al alloy is used in the fabrication of supersonic aircraft skin and structural members like space boosters, rocket fuel tanks and fins, etc., due to its exceptional combination of unique characteristics. The alloys having long-term exposure to high temperatures and stresses frequently encounter creep deformation as the major failure mechanism. Study of fatigue and creep behaviors is majorly significant for certain aerospace applications. Under high temperatures, a material’s strength is generally affected by both strain rate and exposure time. Creep is time-dependent deformation of a metal, subjected to a constant mechanical stress at an elevated temperature [5]. Generally, creep becomes engineering significance at high homologous temperatures. It can occur as a consequence of prolonged exposure to high levels of stress values, that are yet below the material’s yield strength. Proper creep testing procedures are chosen judicially to estimate material creep performance, depending on ability to withstand different time scales under elevated-temperature services [5]. It may be a high temperature tensile test to evaluate creep properties of a short-lived item. Dimensional changes from high temperature exposure are measured by creep tests, while influence of temperature on long-term load-bearing capacities is estimated by stress-rupture tests. The increased risk of material failure while operating under load at high temperatures necessitates the technologies for predicting creep lifetime. The variation in stress is the primary factor which affects the creep strain, and also the rupture life of the material. Higher magnitudes of stress impose significant impact on the creep strain and subsequently shorten the lifetime to failure of a material. Creep crack initiation and growth models were taken into account, when developing the creep model and predicting creep damage behavior. With increase in temperature, steady state creep rate is accelerated, and rupture time constituting of primary, secondary, and tertiary creep stages is decreased [4]. Creep properties were investigated for extruded Al-6 Mg-2Sc-1Zr alloy, considering temperatures 423–533 K. During the creep phenomenon, the development of the dislocation structure with strain is similar for pure Al and its alloys, when the differences in stress are taken into account. The dislocation structure and the creep rate of pure Al, as well as solute and particle strengthened Al alloys, are characterized by their development with strain at constant stress, and their stress dependence during the steady state [6]. The creep performance, illustrated by the

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total amount of strain over the duration of the creep test, was compared for different materials tested. M4032 and 332RR alloy reported, respectively, the highest and least resistance to creep, over the experimented domain of stress and temperature [7]. Impression creep technology is an altered indentation creep testing method, in which a cylindrical, flat-bottomed punch replaces the conical or ball indenter. The high temperature impression curves resemble the conventional tensile creep curves, in exhibiting a steady state, after an initial transient period [8]. Stress and temperature were reported to have significant effects on impression velocity and steady state creep rate. The estimations of stress exponent n and activation energy Q reveal that creep mechanism is not the same at all temperature and stress ranges [9]. Parameters of creep exponent n and creep co-efficient k were estimated corresponding to varying creep damage ratios, using high temperature indentation creep tests [4, 5]. Based on analytical relation of these two parameters, an alternative creep life prediction approach could be suggested. Impression creep determines the local creep properties as a function of position in weldments. The apparent Q of the equiaxed ferrite grain structure within the heat-affected zone (HAZ) was observed to be consistent with values obtained from conventional creep testing [10–12]. Impression creep methodology was successfully utilized to evaluate creep deformation behavior of creep-resistant austenite stainless steel in a quicker and non-destructive manner, and corresponding results were compared to those of conventional uniaxial creep experiments on the same material. The impression creep curves were characterized by a loading strain and primary and secondary stages; however, the tertiary stage that appears in conventional creep curves was not so prominent [13]. In overall, impression creep testing is a practical tool to generate data from comparatively smaller specimens and so lesser quantities of material. It may thus be considered a useful tool for assessment of both remaining life to creep rupture and creep behavior of a newly developed material [14–18]. High temperature deformation and creep behavior of different materials is an area which has encountered a recent increase in interest, using different methodologies. Conventional creep properties of several commercial alloys have been documented in literatures. However, detailed investigations regarding the impression creep testing on wrought and heat-treatable 2xxx series Al alloys are still limited in number [2, 7]. In particular, most of these experiments have been conducted with commercial hi-end and multi-functional apparatus. Such equipment is generally highly expensive, which includes hydraulic loading system, inbuilt hi-end heating chamber, and sophisticated automatic system for measuring deformation or strain as a function of time. The prospect from the study on impression creep, while the general lack of information regarding similar studies on laboratory-scale setup, motivated the present investigation. The present research therefore aims to design and fabricate a cheaper and simpler experimental setup, which will substitute the hi-end expensive equipment, although in a smaller scale, but may still serve similar research purposes in the area of high temperature creep testing. Heating arrangement for desired temperatures up to 1200 °C and provision for variable load application on a testing specimen have been combined into one single desktop unit. By using the setup, impression creep indentation on a material can be estimated, at various combinations of loads

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and temperatures, generating creep curves, homologous to conventional tensile creep tests. The functionality and compatibility of the setup were successfully validated by conducting impression creep experiments on 2219Al alloys, under varying conditions of loads and temperatures. The generated creep curves with three distinct creep stages, as well as creep rates, were analyzed with respect to time, and compared with the theoretical models. Individual influences of load and temperature on creep characteristics of these alloys were studied. Different creep parameters like the minimum creep rate, penetration depth, penetration velocity, stress exponent, and activation energy were further evaluated, and successfully compared and correlated with the reported literatures.

2 Design and Fabrication of Impression Creep Testing Setup Figures 1 and 2 show, respectively, the schematic of the proposed design and actual fabrication of the heating furnace assembly. The resistance-heated furnace has an alumina tube acting as the main heating chamber, which is enclosed by a mild steel cylindrical casing. Ceramic wool placed in between the alumina tube and steel casing provides the necessary insulation to the furnace chamber. High melting Kanthal coil was used as the heating element, which was fixed around the alumina tube. The entire furnace assembly is placed on a rectangular metallic base plate. A small circular ceramic alumina plate was provided on the base plate and inside the furnace chamber, to place the testing specimen on it. The load is transmitted to the specimen through a solid alumina rod, which is arranged to vertically reciprocate through the heating chamber, and serves as the loading bar. The alumina rod is fitted with a metallic sleeve at the bottom, where a

Fig. 1 Schematic diagram of the proposed design

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Fig. 2 Section of the resistance heating furnace

cylindrical tungsten carbide indenter (3 mm dia and 5 mm height) is further cemented, while the alumina tube has a flat metallic flange attached at the top through a metallic sleeve. The flange has its provision to carry multiple dead weights. The entire assembly of flange, alumina rod, and the indenter constitute the loading system, and the desired loads from dead weights are transferred down to the indenter. Alumina being an insulator and having a high strength and service temperature up to 1650 °C was selected as the desired material in several components of the loading system, to minimize the heat transfer and uncounted deformation at high temperatures. An alternate and optional mechanism of lever arm may also be assembled, to multiply the applied loads. The supporting structure consists of the metallic rectangular base plate and a rectangular guiding plate above the furnace, which actually guides the vertical movement of the alumina rod through a metallic bush. The guiding plate is supported with the base plate through four supporting bars. The primary design consideration was to estimate the total length and number of turns of the Kanthal heating element around the resistance heated furnace chamber, to attain the specified temperature range up to 1200 °C. Amount of heat required was calculated separately for rise in temperature in each of the items (viz. the alumina tube, alumina rod, air inside the furnace chamber, and the sample itself), by considering the mass, specific heat, and difference in temperature, by using the empirical formulae: Q = m × c × ΔT

(1)

where Q, m, c, and ΔT indicate, respectively, the heat required, mass, specific heat, and rise in temperature of the item. Total heat to be generated was evaluated by adding up the total amount of heat required for all the items. Total heat generated by the heating element is given by: Q = R × η × i2 × t

(2)

where R is electrical resistance of the heating element, η is the heating efficiency considering the losses, i is the supplied current, and t indicates the time duration.

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From above equation, the total resistance of the heating element required to generate the total required heat may be calculated. Subsequently, the desirable length (l) of the heating element may be estimated by: Length(l) =

R×A ρ

(3)

where A and ρ stand for, respectively, the cross-sectional area and resistivity of the heating element. The heating element around the furnace chamber is connected with the external electrical circuit, which consists of the rheostat, ammeter, relay, and thermocouple. The block diagram of the electrical circuit is shown in Fig. 3. Proper electrical circuit design is of significance, as it not only supplies electricity to the furnace, while any malfunction in the electrical circuit may lead to major error in experimental results. Current is supplied to the heating element through a rheostat or variac, which acts as a two-terminal variable resistor. The variac varies the voltage to obtain a desired value of current which would generate a pre-set temperature in the furnace. A controller consisted of an ammeter to measure the current, along with a relay, which was used to pre-fix a desirable temperature and further to disconnect the circuit after the same is achieved. Specimen temperature is measured using a K-type thermocouple, and the probe of the same is inserted from top of the furnace chamber. The rise in temperature within the furnace is sensed by the thermocouple and when it exceeds the pre-set temperature, it conveys signal to the relay switch, which in turn breaks the circuit. The consequent decrease in temperature below the pre-set value is again sensed by the thermocouple, which sends command to the relay to reconnect the circuit. This loop mechanism ensures the furnace temperature to have a minimum variation range, around its desired value. Figure 4 shows the entire experimental setup, including the heating furnace, loading system, and the external electrical circuitry. In order to validate the ability of the designed setup to attain a stable desired temperature, variation of furnace temperature was plotted with time for different desired temperature values. Figure 5 shows one such stable temperature trend, for the given test temperature of 450 °C.

3 Impression Creep Testing 2219Al alloy was processed by a standard casting route. Specimens of dimension 22 × 22 × 20 mm3 were machined from the cast sample plates. Polishing was performed on the sample surface following standard metallographic technique, to achieve proper and clear indentations. The sample was placed inside the alumina tube, on top of the ceramic plate. The indenter attached to the alumina rod was placed above the sample, and the thermocouple was inserted into the furnace cavity. Dry weights were placed on top of the flange, attached with the alumina rod, to give variable loads on the testing specimen. Temperature was set in the relay at a desired value, and resistance was increased slowly in stepped manner, to further increase

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Fig. 3 Block diagram of the electrical circuit

Fig. 4 The impression creep testing setup Fig. 5 Stability of furnace temperature with time, for set temperatures of 450 °C

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Table 1 Values of creep parameters under different test conditions S. No.

Load (kg)

Stress, σ (MPa)

Temperature, T (°C)

Minimum creep rate (mm/min)

Penetration depth, h (mm)

Penetration velocity × 10−3 , Δ (mm/s) 2.69

Strain rate × 10−4 , ε (s−1 )

1

25

34.7

400

0.350

2.30

2

25

34.7

450

0.549

3.71

14.5

48.5

8.95

3

25

34.7

500

0.941

3.59

61.35

204.5

4

30

41.6

400

0.125

2.41

5.01

16.7

5

35

48.6

400

0.341

3.78

4.11

13.7

6

35

48.6

450

4.355

3.97

38.065

126.88

the temperature inside the furnace. A dial gauge touching the extended portion of the flange was used to measure the indentation (impression) depth, once the desired temperature attained saturation. The testing and validation of the experimental setup were thus carried out under selected values of loads and temperatures, as given in Table 1. For each experiment, the impression depth versus time curve was plotted to further generate the creep and creep rate curves. After analyzing the data, the high temperature impression creep behavior of the material may be investigated.

4 Results and Discussion 4.1 Creep Curve Analysis Figure 6a reveals impression creep curve of the 2219Al alloy, obtained at 450 °C and stress of 34.7 MPa. It is evident from the figure that the impression creep curve resembles a conventional and typical tensile creep curve, consisting of three separate stages [4]. The primary creep stage is characterized by decreasing creep rate. Primary creep is a relatively short phase of mostly transient creep, during which material’s creep resistance gradually increases due to its own plastic deformation or strain hardening. For low temperatures and stresses, primary creep is a predominant creep process. The second creep stage, also known as secondary creep, continues for a comparatively longer time duration, and with almost steady creep rate actually caused by a balance between competing processes of strain hardening and recovery. The waviness or humps in the experimental creep curves, as revealed in Fig. 6a, are actually caused by a quick indenter penetration followed by a reduction in impression depth with time. As a result, secondary creep is also termed as steady state creep. The third and the last stage is also known as tertiary creep, which is predominant under high stress and temperature values. In Fig. 6a, it was observed to initiate at around 450 °C. Metallurgical phenomenon like precipitate particle coarsening, internal void generation, recrystallization, or diffusional alterations inside microstructure and phases

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Fig. 6 a Creep curve and b variation of creep rate with time, obtained at 450 °C and stress of 34.7 MPa

are frequently related with tertiary creep [4]. However, due to practical limit of the maximum permissible indentation depth caused by fixed indenter height, the tertiary stage could not be achieved in several experiments, consequently only the transient region becomes dominant. Subsequently, a third order polynomial function was fitted with the creep curve experimentally obtained, having co-efficient of determination (R2 ) value as 0.979, as mentioned in Fig. 6a. Differentiating the above polynomial equation estimates the creep rate at different instant of times. Figure 6b reveals variation of this creep rate with respect to time, under the same given conditions of temperature and load. It was observed that during primary creep, creep rate decreased with time, up to a certain limit or minimum creep rate, due to constant work hardening. During secondary stage, creep rate attained saturation and steady state. After entering into the tertiary creep stage, the creep rate once again started to increase with time.

4.2 Comparative Study of Creep Curve Under Isothermal and Iso-Stress Conditions Figure 7 depicts, respectively, the creep curve and variation of creep rate with time, under isothermal condition at 400 °C, with varying stress values of 41.65 and 48.60 MPa. The secondary stage or steady state creep region was observed to be longer with a decreased creep rate, at lower stress values under given temperature. Figure 8 shows variations of impression depth and creep rate with respect to time, under iso-stress condition of 34.7 MPa, for varying temperatures of 400 and 450 °C. It was observed that under iso-stress condition, the secondary creep or steady state creep region was once again longer with a lower creep rate, at lower temperatures. Faster rate of creep deformation with increase in test temperature is attributed to the rise in homologous temperature, which actually represents ratio of test temperature with melting temperature of the material. The minimum creep rate values for

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Fig. 7 a Creep curves and b variations of creep rate with time, under isothermal condition at 400 °C

Fig. 8 a Creep curves and b variations of creep rate with time, under iso-stress condition at 34.7 MPa

different test conditions are shown in Table 1. Moreover, it is to be noted that under iso-stress condition and with increasing temperatures, the shape of the creep curve may alter from steady state to sigmoidal, which implies the presence of a prominent tertiary stage creep. Similar trends may also be observed under isothermal condition and with increasing stress values.

4.3 Computation of Creep Parameters The pressure under the indenter at a given load (P) and indenter diameter (d) is taken into consideration. The impression depth (h) versus time (t) curve was obtained for each test, and thus, steady state velocity of indenter (V s ) was obtained from its indentation rate (dh/dt). Again, Creep rate (˙ε) can be evaluated from the relation: ε˙ =

Vs d

(4)

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where V s is steady state velocity of the punch, and d is depth of plastic zone beneath the punch, which is approximately equal to diameter of the indenter. Uniaxial tensile stress (σ ) is given by: σ =η× p

(5)

where η is constant conversion parameter, and p is mean pressure under the indenter. The uniaxial tensile creep strain (εc ) and the indenter displacement (Δc ) can be correlated by equation as shown below: εc =

Δc β ×d

(6)

where β is a constant conversion parameter. Further, the power law creep deformation can be expressed in the form: ε˙ c = A × σ n

(7)

where ε˙ c is uniaxial tensile creep strain rate. A and n are material constants. Thus, strain rate can be calculated using experimental data. Table 1 lists the values of the penetration depth, penetration velocity, and uniaxial tensile creep strain rate for the different testing conditions. The uniaxial tensile creep strain rate and penetration velocity increased with increasing stress value at constant temperature, as well as increased with increasing temperature under a given stress. Figure 9 shows the plots of log (ε) versus log (σ ) generated from experimental results, at temperatures of 400 and 450 °C, where ε represents the steady state creep rate (SSCR). The average slope of each curve estimates the stress exponent for a given temperature. Figure 10 shows plots of log (ε) versus 1000/T, under given stress values of 34.7 and 48.6 MPa. The average slope of each curve estimates the activation energy (Q) under a given load. The values of n and Q thus evaluated under different test conditions are given, respectively, in Tables 2 and 3. Stress exponent was observed to increase with increasing temperature, while activation energy increased with increase in stress. Present experimental results were compared with the impression creep testing data of Al and its alloys, as reported in literature [3, 10, 11]. When studied with 5052 Al and 2014 Al alloy, stress exponent values were registered to be 4.201, 3.653, and 4.359, for the test temperatures of 330 °C, 350 °C, and 370 °C, respectively. Similarly, activation energy was reported as 68 kJ/mol, 72 kJ/mol, and 77 kJ/mol, under the stresses of 40 MPa, 45 MPa, and 50 MPa, respectively. The values of different creep parameters experimentally obtained by the present setup for 2219Al alloys were successfully corelated with the reported creep data on similar Al alloys. Thus, the functionality and compatibility of the impression creep testing setup were experimentally validated.

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Fig. 9 log (ε) versus log (σ ) for different temperatures

Fig. 10 log (ε) versus 1000/T for different stress values

Table 2 Values of stress exponent for different temperatures

Table 3 Values of activation energy for different stresses

S. No.

Temperature, T (°C)

Stress exponent, n

1

400

1.186

2

450

5.933

S. No.

Stress, σ (MPa)

1

34.7

11.47

2

48.6

22.20

Activation energy, Q (kJ/mol)

5 Conclusions 1. A laboratory-scale experimental setup was designed and fabricated, to substitute commercial hi-end equipment, for high temperature creep testing. Heating

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2.

3.

4.

5.

6.

7.

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arrangement for desired temperatures and provision for variable load application have been combined into one single desktop unit. Impression creep indentation on a material can be estimated by using the setup, for various combinations of loads and temperatures, generating creep curves, homologous to conventional tensile creep tests. The functionality and compatibility of the setup were successfully validated by conducting impression creep experiments on 2219Al alloys, under varying conditions of loads and temperatures. Creep curves were generated with three distinct creep stages, namely primary, secondary, and tertiary creep. Creep curves as well as creep rates were analyzed with respect to time and compared with the theoretical models. During primary creep stage, the creep rate decreased with time, up to a minimum creep rate, due to constant strain hardening. During secondary creep, creep rate attained saturation and steady state, due to balance between rate of work hardening and softening. After entering the tertiary creep stage, the creep rate once again increased with time. The individual influences of load and temperature on creep properties of the alloy were investigated. The secondary creep region was observed to be longer with a lower creep rate and absence of tertiary creep, in case of lower temperatures under iso-stress condition, and for lower stress values under isothermal conditions. Different creep parameters of minimum creep rate, penetration depth, penetration velocity, stress exponent, and activation energy were further evaluated, and successfully compared and corelated with the reported literatures. The uniaxial tensile creep strain rate and penetration velocity increased with increasing stress value at constant temperature, as well as increased with increasing temperature under a given stress. Stress exponent was observed to increase with increase in temperature, while activation energy increased with increase in stress.

References 1. Callister WD (1997) Material science and engineering: an introduction. 4th edn. John Wiley & Sons 2. Mishra RS, Mukherjee AK (1995) Lightweight aluminum alloys for aerospace applications III. TMS Warrendale, Pennsylvania, pp 319–332 3. Dieter GE (1988) Engineering materials: mechanical metallurgy. In: 4th edn. John Wiley & Sons 4. Matsunaga T, Sato E (2013) Creep mechanism in several grades of aluminum at low temperatures. Mater Trans-Jpn Inst Light Met 54(12):2202–2208 5. Rashid AB, Khan MA, Kader MF (2019) Performance evaluation of a low cost creep testing machine. Am J Mech Eng 7(1):41–44 6. Deshmukh SP, Mishra RS, Kendig KL (2004) Creep behavior and threshold stress of an extruded Al–6Mg–2Sc–1Zr alloy. Mater Sci Eng 381:381–385 7. Blum W (1991) Creep of aluminium and aluminium alloys. Institut Fuel 5, D 8520 ErIangen, Germany

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8. Dandrea JC, Lakes R (2009) Creep and creep recovery of cast aluminium alloys. Mech TimeDepend Mater 13:303–315 9. Thenambika V, Jayalakshmia S, Singh RA, Nidhia JK, Gupta M (2016) Impression creep behaviour of extruded Mg-Sn Alloy. Int J Veh Struct Syst 8(3):174–178 10. Wang SH (1994) Impression creep behavior in weldments. J Mar Sci Technol 2(1):17–24 11. Naveena, Vijayanand VD, Ganeshan V, Laha K, Mathew MD (2013) Application of impression creep technique for development of creep resistant Austenitic stainless steel. In: 6th International conference on creep, fatigue and creep-fatigue interaction 2013, [CF-6] vol 55, pp 585–590 12. Brett SJ, Kuhn B, Rantala J, Hyde CJ (2014) Impression creep testing for material characterization in development and application. Master’s thesis, Dept. Mechanical, Materials & Manufacturing Engineering, University of Nottingham 13. Asif S, Auradi V, Nagaral M, Kodanda C (2018) A review on fatigue and creep, behavior of aluminium composites. J Eng Res Appl 8(10):2248–9622 14. Yang F, Li JCM (2013) Impression test-a review. Mater Sci Eng R 74(8):233–253 15. Kumar A (2018) A study of impression creep behavior of friction stir welded Al-5052 and Al-2014 Alloys. In: Technical report, department of mechanical engineering, Indian Institute of Technology, Guwahati, India 16. Dehnavi M, Vafaeenezhad H, Khakzadi M, Nayebpashaee N, Eivani AR (2016) Modelling and prediction impression creep behavior of Al-Cu cast. Int J Cast Met Res 30 17. Ramesh R, Muthukannan D, Vijay P, Shweta V, Rajendran R (2015) Microstructural and mechanical characterization of Ti6Al4V refurbished parts obtained by laser metal deposition. Mater Sci Eng, A 643:64–71 18. Ramesh R, Vinothkumar S, Jie S, Manikandan N, Yanzhe Z (2019) Experimental and Taguchibased grey approach of laser metal deposition technique on nickel-based superalloy. Trans Indian Inst Met 72(1):205–214

Theoretical Comparison of Properties and Their Characteristics Features for Additive Manufactured Metal and Ceramic Structures Utkarshika Chandra, Rajesh Kumar Porwal, Sanjay Mishra, and Basanta Kr Bhuyan Abstract Additive manufacturing being the most desirable manufacturing process is important to keep a track on how the process affects the physical properties of the material. Additive manufacturing is still in its early stages of research for ceramics and metals. Both ceramics and metals have contrasting properties, for example, while metals are generally highly ductile and thermally conductive, ceramics is mostly brittle and very low in thermal conduction. Additive manufacturing has branched out to different sub-manufacturing processes; the problem however lies that the cost efficiency of setting up the system and churning out the products is still low when it comes to industrial production. A variation of the technology so that it can easily adapt to polymers, metals, and ceramics simultaneously while producing optimal property characteristics for all is required. The paper deals with a comparative study on the effect of additive manufacturing on properties such as flexural strength, tensile strength, compressive strength, hardness, bending strength, and fracture toughness for both metals and ceramics having their characteristics poles apart. Keywords Comparative study · Flexural strength · Hardness · Compressive strength · Fracture toughness · Tensile strength

U. Chandra · R. K. Porwal (B) Faculty of Mechanical Engineering, Institute of Technology, Shri Ramswaroop Memorial University, Lucknow, India e-mail: [email protected]; [email protected] S. Mishra Department of Mechanical Engineering, Madam Mohan Malaviya University of Technology, Gorakhpur, India B. K. Bhuyan Mechanical Engineering Department, Manav Rachna International Institute of Research and Studies, Faridabad, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_9

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1 Introduction Additive manufacturing has become the most desirable manufacturing technique which makes the work of both the producer and the customer easy by allowing producing designs closest to the requirement in limited time frame. A 3D printing arena basically has a design carefully created and critically analyzed by various designing models most prominent of them being computer-aided designing (CAD), followed by feeding the design into the slicer which then slices the design into layers which are fed into the printing machine one over the other so as to convert an otherwise 2D model stacked upon one another into a 3D model. Additive manufacturing has gained special affection of the media due to its efficient and adaptive characteristic features. DIY at home 3D printing models attracted enough attention and curiosity of the masses to tag it as a mass favorite method. From solid-based printing processes like fused deposition modeling, laminated object manufacturing, free form extrusion to powder-based manufacturing such as selective laser melting, selective laser sintering, and electron beam melting along with liquid-based production technique such as stereo lithography, rapid freeze prototyping, and free form extrusion additive manufacturing seems to have covered all possible manufacturing materials in the area of polymers, metals, and ceramics. Manufacturing sectors are heavily investing into research and development of additive manufacturing due to its low to no waste characteristic feature. Additive manufacturing has become a competitive tool as it reduces the time frame of production as well as can provide customer preferences [1, 2, 3, 4, 5].

1.1 Brief Discussion on Types of Additive Manufacturing Processes Additive manufacturing basically consists of a variety of manufacturing techniques and processes. For both metal and ceramic, some common additive manufacturing techniques are available and some of them are explained and the classification is based upon the existence of base material state, as given below. Solid-based additive manufacturing: This kind of additive manufacturing process includes the raw material inputted in the form of a solid block. There have been many sub-classifications of the manufacturing according to the needs that were devised. Some being. Laminated object manufacturing (LOM) wherein sheets of metal are glued to one another the lamination is glued by a thermoplastic adhesive which comes into its active state when agitated by a hot roller. This process can be considered a hybrid model of additive mad subtractive manufacturing bringing low yield and strength with less geometric freedom. Then, the solid-based additive manufacturing process is fused deposition modeling wherein the heated material is made to pass through a heated nozzle so that it loosens up a bit and can be deformed into shapes easily.

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Fused deposition modeling cuts off the manufacturing time of machine parts manufacturing by 85%. It is ideal for polymers and used in automotive, aerospace, and defense industries. Then comes Freeze form extrusion (FFEF) fabrication wherein the material is frozen just after being extruded to stiffen its shape to the required design. This kind of process is very helpful in producing ceramic components and is used in abundance in defense industry. The last of this particular classification is direct ink writing where a colloidal suspension is created which is deposited over the predefined design though a dropper [6, 7, 8, 9, 10]. This kind of process is highly useful for multi-material printing and is implied in manufacturing industries, and pharmaceutical industries. The second classification of additive manufacturing processes is liquid-based additive manufacturing wherein the initial form of material is either in the form of liquid or being converted into liquid through the application of heat. The further classifications are as follows: The first type of liquid additive manufacturing is stereo lithography (SLA) used highly in many additive manufacturing units; stereo lithography uses photo polymerization as its basic reaction mechanism wherein a photo polymeric resin is mixed with the material to be manufactured and on application of light beam over it. The photopolymer resin sacrifices itself and helps in joining the particles together. It has an accuracy of up to 20 μm. Structures are built in a bottomup manner with the resin resting below it. The second kind of manufacturing process is Rapid freeze prototyping (RFP) wherein mostly it is made for modeling purposes. Small replicas of big structures are easily made that help in correct visualization and testing. Mostly, water or brine solution is used, and it gets instantly frozen as it is extruded from the nozzle. The third semi-classification of the process is digital light processing (DLP) wherein local photo polymerization takes place on exposure to ultraviolet radiation. Photopolymer composed of a liquid monomer, oligomer, and photo initiator is used to complete the reaction and hardened by resins. The process is widely useful to produce complex structures especially for ceramics [11, 12, 13, 14, 15, 16, 17]. It is useful in electrically conductive components and nano composites. Lastly, we come to the most recognized structures of all the powder-based technologies where the base material is procured and fed in powder form. It is very common in industrial practices due to its agility and design openness. Selective laser melting (SLM) and selective laser sintering (SLS) are the two stars of the process wherein the basic concept behind both of them is to maneuver the laser beam over the predesigned structures and let the particles fuse together. The only difference between both the technologies is that selective laser melting has complete fusion of the particles whereas selective laser sintering has partial melting just enough for the particles to fuse with each other. Developed by laser institute of technology, selective laser melting can produce fully dense homogenous parts and is used in industries for both metals and ceramics. Selective laser sintering can produce good grain growth and reduction of porosity used extensively in biomedical appliances. Going on the same footsteps, we have Electron beam melting (EBM) which produces less residual stress and improves the ductility and strength of the part with no thermal cracks and a very refined structure [18, 19, 20, 21, 22, 23, 24, 25, 26]. The only drawback is that it is an expensive process and is not compatible with all materials. Some additive

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Fig. 1 Diagrammatic representation of stereo lithography

manufacturing processes are illustrated with the help of diagrams in Figs. 1, 2, 3 and 4.

2 Comparison of Physical Properties of Additively Manufactured Metals and Ceramics As we know, additive manufacturing alters the microstructure and hence properties related to it by bringing grain refinement and temperature gradient. These altercations put direct effect on the physical properties of the materials; thus, it is important to know what kind of impact the additive manufacturing has on these properties. Below is a detailed comparative study on six of those properties for both additively manufactured metals and ceramics.

Theoretical Comparison of Properties and Their Characteristics …

Fig. 2 Diagrammatic representation of selective laser sintering

Fig. 3 Diagrammatic representation of electron beam melting

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Fig. 4 Diagrammatic representation of selective laser melting

2.1 Study on Flexural Strength Flexural strength, the strength the material exhibits just before it, is about to rupture in flexural test. It is also referred to as modulus of rupture or bends strength. A threepoint bending flexural testing is used to determine the flexural strength of the material in possession. Both ceramics and metals show contrasting features when tested upon for flexural strength. Chaolin et al. saw that on additively manufactured steel-copper bimetal the flexural strength improved and depended on laser speed [27]. Pappas et al. however saw that that laser-deposited ceramic had flexural strength reduced when compared to traditional ceramics. Flexural strength helps in determining the stability of the structure thus formed and its load nearing capacity [28]. It thus helps in designing cantilevers and beams for columnar structures and is of great importance in construction industries. Table 1 citing the flexural strength of metals when in comparison with ceramics. On analyzing the above comparative study, it can be seen that for metals the additive manufacturing helps in improving the flexural strength and rigidity when compared to the traditional methods while in the case of ceramics the property does show a considerable improvement but is subjective to processing conditions like pressure and sintering temperature; additive manufacturing is very helpful for metallic structures for flexural properties but in the case of ceramics better analysis has to be done between traditional and additive manufacturing methods.

SLM

SLM

Wire arc additive manufacturing

SLM

Steel copper bimetal

AlSi10Mg

Zinc-coated steel sheet

High speed steel

Flexural strength

AM process

Metal

Property

28

27

Ref. no.

Flexural strength of 250 MPa was observed parallel to scanning direction

30

AM method helps 29 to increase flexural rigidity

AM metal was 10% more stiffer than conventionally (wrought or machined) metal

Flexural strength of 557 MPa was observed, improvement with high laser scanning speed

Characteristic feature

ZrO2 ceramic

Ultra-high temperature ceramic

Zirconia

Alumina ceramic

Ceramic

Table 1 Comparative study of flexural strength of additively manufactured ceramics and metals

SLA sintered

Additive manufacturing robocasting

Extrusion-based additive manufacturing

Laser direct deposition

AM process

32

31

Ref. no.

Improved 34 flexural strength due to uniformity in grain size

Varies along with 33 the application pressure with sintering

When compared to binder jetting extrusion-based AM had better flexural strength

Lower than traditionally manufactured alumina

Characteristic feature

Theoretical Comparison of Properties and Their Characteristics … 113

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2.2 The Impact of Additive Manufacturing on Hardness Any form of resistance that a structure shows when it is subjected to external force and plastic deformation is called hardness. Brinell, Rockwell, Vickers, Tukon, Scleroscope, and the Leeb rebound hardness test are the tests that can be performed to test the hardness of the material. Hardness to metal provides wear resistance and abrasion protection when subjected to high mechanical forces. Hardness of ceramics preferably by Vickers hardness and hardness for ceramics is in the form of micro, macro, and nano. Macro being hardness over 10 N and micro being below 10 N. Below is the tabular comparison of hardness of metal and ceramics. When metal and ceramics came to a comparison in additive manufacturing technology, it was observed that in case of metals hardness increased but in case of ceramics it showed a varying trend. Zhang et al. saw that in metals hardness improved along with tempering and was higher than conventional ones [29]. Li et al. saw that as the layer thickness increased, the hardness decreased [30]. Further comparison is given in detailed basis in Table 2. Hardness as seen in various discussions is a very important factor in analyzing the performance of the material. In case of metals although additive manufacturing improves the hardness to a significant pace but lower columnar grains, thermal gradient along with high laser power is required. In case of ceramics, the hardness is dependent on the density of the ceramic structure so formed and increased only after a certain threshold value of density is achieved. Thus, additive manufacturing is suitable for both ceramics and metals for hardness-centered structures given the additional conditions are met.

2.3 An Analytical Overview of Compressive Strength Compressive strength of a material is the characteristic feature of the material to resist any failure on application of load placed over the material. Compressive strength is tested by applying loads to the material till a failure occurs preferably on the top of the material. Compressive strength of metals is tested by a Universal testing machine (UTM). Ceramics are considered to be higher in compressive strength as compared to tensile strength. Unlike the previous comparative studies in case of compressive properties, it was seen that both metals and ceramics show a significant improvement in compressive strength. Fujieda et al. saw that while electron beam melting of high entropy alloy had high or very high compressive strength and is high in the direction parallel to building direction [31]. Lakhdar et al. also found that while binder jetting of aluminum oxide the compressive strength almost doubled while increasing the time of sintering [32]. Further comparative studies are listed in Table 3. Additive manufacturing induces the compression hardening in the metallic samples and helps in improving the compressive strength. But the dislocation glide and twinning cause a glitch and adversely affect the compressive strength. In case

Metal

50.7 HRC high 37 hardness is observed and improves with increase in laser power

Selective laser melting

Direct energy Hardness decreased 38 deposition (DED) with formation of columnar grains due to the presence of thermal gradient which reduced the density of metal

AISI 420

Inconel - steel

36

AM process

Zirconia

JJy tablets

Alumina

39

Ref. no.

Hardness does not 40 increase till high densification was not achieved

Reduced hardness with increase in layer thickness

Characteristic feature

DOD material jetting

Hardness value of 42 1516 HV max reached and depended on density (directly), porosity (indirectly)

Extrusion-based 3D Hardness was 41 printing directly dependent on filling density and war page

SLA

Alumina ceramic SLA

Ref. no. Ceramic

Micro hardness 35 688 V was observed, and variation was seen with tempering

Characteristic feature

Hardness of 440–480 V was observed, and this was very high than injection-molded samples

Laser additive manufacturing

AM process

P20 Mold steel Selective laser melting

Hardness M2 HSS

Property

Table 2 Comparative study of hardness of additively manufactured ceramics and metals

Theoretical Comparison of Properties and Their Characteristics … 115

AM process

Electron beam melting

Direct metal laser sintering (DMLS)

DMLS

Metal

High entropy alloy

Austenitic 316 L stainless steel

Maraging steel

Property

Compressive strength

Ref. no.

Approximately 1400 MPa, AM samples have better compressive strength than tensile due to compression hardening

Compressive strength ranged from 180 to 200 MPa and was dependent on orientation of the metal 45

44

Superior to 43 traditional methods and higher in direction parallel to built direction

Characteristic feature

Hydroxyapatite

SiOC ceramic

Alumina

Ceramic

Table 3 Comparative study of compressive strength of additively manufactured ceramics and metals

DLP

stereo lithography

Binder jetting

AM process 47

Ref. no.

High 4.09 MPa comparable to human bone was formed due to desired internal aperture and homogeneity

(continued)

49

High 48 compressive strength 216 MPa was seen due to special honeycomb structure by SLA

Compressive strength doubled with increase in sintering time

Characteristic feature

116 U. Chandra et al.

Property

AM process

EBM

Metal

Ti4822

Table 3 (continued) Ref. no.

Plasma melted 46 Ti4822 had better compressive strength than EBM as EBM had dislocation glide and deformation twinning

Characteristic feature TiO2 ceramic

Ceramic DLP

AM process The compressive strength reduced from 1.15 to 1.13 MPa as porosity increased

Characteristic feature 50

Ref. no.

Theoretical Comparison of Properties and Their Characteristics … 117

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of ceramics, compressive strength was high due to special structure formations but was dependent on the porosity of the structures. Thus, on analysis it is seen that the additive manufacturing is suitable for ceramics when it comes to compression properties while a little adjustment is required for metals.

2.4 Comparative Analysis for Fracture Toughness Fracture toughness is the ability of the material to soak in the strain energy just before the crack occurs. High fracture toughness of the material indicates the ability of the material to resist crack propagation. But high fracture toughness makes the material victim to ductile fracture. Fracture strength is a very important factor in shaping the physical performance of the material. In both metal as well as ceramics, there is no specific fracture toughness increment or decrement guarantee. It depends on a lot of other parameters. Deirminaa et al. found that fracture toughness was dependent on built direction and lower when placed parallel to built direction while testing [33]. Lakhdar et al. also reported that for ceramics too fracture toughness needed heat treatment post-processes to bring out a significant impact [34]. Further comparison is listed in Table 4. Fracture toughness in case of additively manufactured metals is highly anisotropic and depends highly on the direction of built. In case of ceramics, the additive manufacturing improves the toughness wherein the support of other processes is required. Thus, for both metals and ceramics adjustment and additions are required.

2.5 Analyzing the Impact on Tensile Strength Tensile force is the force responsible for stretching of the material. Tensile strength refers to the ability of the material to withstand tensile stretch before rupture occurs. Tensile test is carried out in a UTM wherein the tensile force is applied till necking or breaking occurs. Tensile strength exists in the form of ultimate tensile strength, yield strength, and breaking strength. Most of the performance checking characteristics come by analyzing the tensile strength of the material, and similar observation when made on additive manufactured metals and ceramics was made; it was seen that in case of metals the tensile strength was highly improved due to some kind of grain refinement at some level while in case of ceramics although there was an improvement in tensile behavior but mostly the strength succumbed to either tensile cracking or high porosity. More is explained in Table 5. Bian et al. saw that the tensile strength of aluminum improved by SLM as through additive manufacturing grain boundary refinement was achieved [35]. Xuesong et al. saw the tensile strength subjected to tensile cracking due to high solid loading [36]. Unlike expected, the tensile strength of metallic additive manufacturing structures does not go magically above the expected but is

Metal

H13 TOOL STEEL

300 M Steel

Ti6Al4 V

Steel

Property

Fracture toughness

–

–

–

Additive manufacturing

SLM

DED

SLM

AM process

Ref. no.

Multiple reviews show that fracture toughness is highly anisotropic in nature

54

Highest was 53 reported as 28 MPa, and fracture toughness is highly dependent on direction of built

V notch impact 52 toughness initially at 9 J/cm2 increases 3 times when heat treated as ductility improves

Fracture toughness 51 of around 70 MPa was observed which is lower when the notch was placed parallel to build direction as crack propagation is easier

Characteristic feature

ZTA ceramic

zirconia containing 8 wt% Y2O3 (5Y-TPZ)

Alumina

Al2 O3

Ceramic

Table 4 Comparative study of fracture toughness of additively manufactured ceramics and metals

SLA

Drop on demand material jetting

Comparative study in various AM

Comparison between many AM techniques

AM process

Ref. no.

57

56

High value of 58 about 7.5 MPa, addition of toughing phase and optimal particle distribution

Approx 5.14 MPa toughness reported, influenced by high density

Highest value of 4.5 MPa found in CODE, extrusion helps toughness

General toughness 55 was found between 3 and 4.5 MPa and improved with heat treatment, best in LENS

Characteristic feature

Theoretical Comparison of Properties and Their Characteristics … 119

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highly dependent on microstructure and its refinement. While as we know there is very little to negligible tensile strength of ceramics, tensile cracking does exist. The little there is tensile strength, and it depends on the porosity of the structure.

2.6 A Closer Look on Bending and Its Strength with Respect to Additive Manufacturing Bending helps in initiating a plastic deformation in the structure thus making it easy to mold it according to our requirements without causing failure. The strength is exhibited by a structure enduring plastic deformation; just before failure occurs, bending strength and flexural strength have a very close definition and are often used as synonyms for each other. Bending strength is recorded by a bending test. Bending usually occurs due to tensile stretching of the material. The bending strength of additively manufactured metallic parts improved due to their dendrite structure but also was highly dependent on the laser scanning speed and time. While for ceramic although there is negligible bending, still the improvement was solely direction dependent and highly anisotropic in nature. More discussion over the following property is given in Table 6. Refined dendrite structures with optimized laser scanning speed and temperatures help in improving the bending without failure for metals while in case of ceramics although negligible bending is present but is desirable; thus, it can be improved by working on the direction of built for the specimen [37, 38]. Thus, additive manufacturing for both metal and ceramic is manageable and optimal when it comes to bending.

3 Conclusions Following conclusions were made from present study: 1. Flexural strength of metals is enhanced by AM due to uniform grain distribution and high laser scanning speed. Ceramic flexural strength has no significant improvement. 2. Extrusion-based better scanning speed and laser power AM methods improve the hardness of metal, but high thermal gradient and formation of columnar grains affect adversely. 3. High filling densification causes the hardness to improve for ceramics which is lowered by porosity. 4. Compression being anisotropic for metals is highest toward side parallel to building direction. Further improvement due to dislocation glide, twinning, and compression hardening. In ceramics, there is high compression due to honeycomb structure.

SLM

EBM

Various AM methods

Laser beam melting

Aluminum

AlSi10Mg

steels

AMPO maraging steel

Tensile strength

AM process

Metal

Property

60

59

Ref no.

Tensile strength of up to 2000 MPa is seen as powder is spherodized, compactly packed and optimal range

62

Tensile strength is 61 equal to or more of AM produces structures due to grain refinement and precipitation

Tensile strength of 135–138 MPa was achieved due to microstructure refinement

Tensile strength up to 486 MPa can be reached if grain refinement and boundary strengthening is achieved

Characteristic feature

Alumina

Alumina

Polyamide 12 powder (PA2200) with zirconia

Ceramic polymer nano scale bar

Ceramic

Table 5 Comparative study of tensile strength of additively manufactured ceramics and metals

Tensile strength of 27–36 MPa was seen

Tensile strength of 550 MPa was seen

Characteristic feature

Lithography-based Ceramic Manufacturing (LCM

65

64

63

Ref no.

Pores present within 66 the surface reduce the tensile strength of the material

Freeform fabrication If solid loading exceeds 60%, tensile cracking is observed

FDM

3D Direct laser writing

AM process

Theoretical Comparison of Properties and Their Characteristics … 121

AM process

Wire arc additive manufacturing

Powder bed fusion

Laser beam melting

Wire arc additive manufacturing

Metal

Haste alloy

316L Stainless steel

Ti-6Al-4 V

Aluminum alloy

Property

Bending strength

68

67

Ref. no.

Extrusion-aided AM 70 methods help in closing cracks and producing strain hardening which improves the bending strength

Bending infused 69 with high temperatures lowers the shear bonding strength

Bending strength was observed and reduced with increase in laser beam density

Plastic deformation and bending are seen, better than conventional due to refined dendrite granular structure

Characteristic feature

Zirconia

Yttria-stabilized tetragonal zirconia poly crystal (Y-TZP)

lithium disilicate glass

Alumina cores

Ceramic

Table 6 Comparative study of bending strength of additively manufactured ceramics and metals

Lithography-based ceramic manufacturing

digital light processing (DLP)

Stereo lithography

Binder jetting

AM process

Bending strength of 850–860 MPa was seen and is dependent in built direction

Bending strength is anisotropic property and depends on the direction of built

430 MPa of biaxial bending strength obtained which was of polished surface

Bending strength increases from 60 to 80 MPa with increasing concentration of zirconia as binder

Characteristic feature

74

73

72

71

Ref. no.

122 U. Chandra et al.

Theoretical Comparison of Properties and Their Characteristics …

123

5. Fracture toughness optimization for additively manufactured metals depends on built direction and for ceramics presence of extrusion in process. 6. Good tensile strength in AM processes of metal due to grain refinement, uniformity, and boundary strengthening. Low tensile strength in ceramics due to porosity, tensile cracking in specimens with solid loading of 60% and above.

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Relative Investigation of Thermal Buckling Analysis of Nickel and Functionally Graded Material Rectangular Plate Mrinal Gautam and Manish Chaturvedi

Abstract Functionally graded materials (FGM) provide a number of advantages, particularly in temperature settings, and have been used in a variety of technical applications in recent years. An inhomogeneous composite is made up a FGM plate of two parts (typically ceramic and metal), the composition and material qualities of which vary smoothly across the plate’s thickness. In the current work, Relative Study of Thermal buckling of Nickel and FG rectangular plate is investigated. As far as the volume fractions for metal and ceramic parts, characteristics of material of the FG plate are considered to be graded according to a power-law distribution in the thickness direction. The finding analyses for clamped rectangular plates of a thermal buckling are presented. When comparing the Nickel plate to the FGM plate, there is a lot of agreement. The FEA software tool COMSOL Multiphysics was used for the entire work. Keywords Rectangular plate · Functionally graded material · Power law · Finite element method · Uniform temperature profile · Thermal buckling analysis · Power law function · Finite element method

1 Introduction FGMs are a relatively narrative class of materials with constantly changing material properties in the thickness direction, from metal to ceramic surface. For the reason that of its limited thermal conductivity, the ceramic component of the material can withstand high temperatures and shield metal from oxidation. Metal ductile component resists cracking generated with high-temperature gradient stresses. This innovative material has an advantage over standard composite materials in that it eliminates inter-laminar delamination and thermal stress concentration. FGM constituents are suitable on behalf of thermal barrier applications during the medicine [1], energy M. Gautam (B) · M. Chaturvedi Mechanical Engineering, University Department, Rajasthan Technical University, Akelgarh, Kota, Rajasthan 324010, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_10

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[2], and defence industries [3], among others, due to their innovative characteristics. When FGM structures are exposed to high temperatures, they lose structural integrity as a result of the thermal load, resulting in geometrical variability. As a result, many researchers are interested in determining how FGM systems buckle in a heat environment. Zenkour and Mashat [4] examined using the sinusoidal SPT, functionally graded plates thermal buckling response. Zenkour and Shoby [5] used to get the closedform solution for each loading case’s critical buckling load. Ghannadpour et al. [6] presented the FG plate of buckling reaction. Valizadeh et al. [7] studied NURBSbased iso-geometric was accustomed to investigate Reissner–Mindlin plate’s static and dynamic features. Yaghoobi and Fereidoon [8] determined the three theories CPT, FSDT and HSDT, i.e. the current assumption be able to attain the similar exactness as obtainable HSDT with a larger number of unknowns. Zhang and Zhou [9] analysed the Winkler–Pasternak model used to investigate the plate/foundation interaction and the impact of the foundation’s elasticity. Sobhy [10] investigated lying the Winkler–Pasternak elastic foundations on FG sandwich plates experience hygrothermal vibration. Xing and Wang [11] focussed on the critical buckling temperature of thin FG rectangular plates as the subject of this study. It was discovered volume fraction component rises and the natural frequency of FGM sandwich plates decreases. Daikh and Megueni [12] presented system geometric factors all have an impact on the thermal buckling properties of FGM sandwich plates. Trabelsi et al. [13] determined using a modified FSDT to investigate the reaction of heat buckling of FG plates and cylindrical shells. Gautam and Chaturvedi [14] focussed the composition of FGM to optimize for better environmental material. Gautam and Chaturvedi [15] investigated to optimize the FGM plate under thermal stresses. Nguyen et al. [16] analysed the structural reactions of FG plates as a function of material characteristics. Based on existing literature, it appears that very few studies have been conducted on Relative Study of Thermal Buckling Analysis of Nickel and Functionally Graded Material Rectangular Plate. With the finite element programme COMSOL, this investigation tries to determine the buckling strength under uniform temperature material parameters of FGM plate. The impact of variables like the power-law index on the critical buckling temperature of functionally graded flat plates is investigated and addressed in depth.

2 Functionally Graded Plate Formulation FGMs are inhomogeneous non-nature, with material qualities gradually changing in the thickness direction from one surface to the next. The bottom of the part is metal-rich, whereas the top is ceramic-rich. P(z) = (Pc − Pm )Vc + Pm

(1)

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( / ) ( / )n Vc = z h + 1 2

129

(2)

where P denotes for effective properties of one of the materials, for example Young’s modulus E, thermal conductivity κ, Poisson’s ratio ν, density ρ, or thermal expansion α; the subscripts c and m stand for ceramic and metal, respectively; the ceramic’s volume fraction is V C , and the volume fraction exponent is n [16].

3 Thermal Buckling Analysis The smallest positive and negative eigenvalues are often of relevance in thermal buckling analysis in order to get the critical temperatures related with heating and cooling.

3.1 Buckling of FG Plates Under Uniform Temperature The temperature is gradually increased until it reaches T f , at which point the plate buckles. The initial temperature of the plate is assumed to be T i ΔT = T f −T i is the temperature change. The resultant thermal force is calculated as follows [17]: h

(2 Ncr = − h2

(P(z) α(z) ΔT ) dz (1 − u)

(3)

4 Analysis of Nickel Rectangular Plate The isotropic material employed in the thermal buckling analysis is Nickel. Nickel high density allows it to be used in a variety of applications in the aerospace a chemical and food processing equipment and Aircraft turbines components. As a result, Nickel plate was taken into consideration for the thermal buckling study (Table 1). For the thermal buckling study, the contour plots for the clamped (CCCC) Nickel plate are presented in Fig. 1.

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Table 1 Nickel thermal and mechanical properties [18] Material

Young’s modulus, E (Pa)

Poisson’s ratio, (ν)

Nickel

199.5 × 109 0.3

Coefficient of thermal expansion (α) (1/K)

Thermal conductivity (κ) W/(m·K)

Density (ρ) (kg/m3 )

Specific heat (C P ) J/(kg·K)

15.4 × 10(−6)

67

8890

452

Fig. 1 Nickel plate critical buckling temperature (ΔT )

5 Investigation of Functionally Graded Material Plate Bottom surface is pure metal of the plate in this study, i.e. Nickel (Ni), and the top surface is ceramic, i.e. alumina (Al2 O3 ). The volume fraction index is n = 0, 0.5, 1, 2, 5 and so on. Below are the contours of the following volume fraction index (Table 2 and Figs 2, 3, 4, 5 and 6). Volume fraction exponent varied from n = 0 to n = 5 during analysis thermal buckling of FGM rectangular plate. When can be seen, as the volume fraction index rises, metal-rich characteristics FGM exhibit [19, 20]. As the volume friction exponent (n) increases, critical buckling temperature (ΔT ) falls in this investigation, as illustrated in Fig. 7.

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Table 2 FG rectangular plate thermal and mechanical properties [18] Material

Young’s modulus, E (Pa)

Poisson’s ratio, (ν)

Nickel Alumina (Al2 O3 ) (Ceramic)

199.5 × 109 0.3 393 × 109 0.25

Coefficient of thermal expansion (α) (1/K)

Thermal conductivity (κ) W/(m·K)

Density (ρ) (kg/m3 )

Specific heat (C P ) J/(kg·K)

15.4 × 10(−6) 7.4 × 10(−6)

67 27

8890 3900

452 900

Fig. 2 FG rectangular plate critical buckling temperature (ΔT ) at n = 0

6 Conclusion FEA software package COMSOL Multiphysics was used to investigate critical buckling temperatures (ΔT ) by first-order shear deformation theory of clamped (CCCC) rectangular FG plates and Nickel plate. The following observations can be drawn from a comparison of Nickel and FGM plates. 1. The (ΔT ) of Nickel plate is shown to be low in Fig. 1, implying that thermal buckling in Nickel plate is easily accommodated. 2. Volume fraction exponent (n) grows, and then, functionally graded plates decreases the critical buckling temperature difference (ΔT ). 3. For analysis thermal buckling, this study suggests that ceramic-rich FGM is stronger than metal-rich FGM.

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Fig. 3 FG rectangular plate critical buckling temperature (ΔT ) at n = 0.5

Fig. 4 FG rectangular plate critical buckling temperature (ΔT ) at n = 1

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Fig. 5 FG rectangular plate critical buckling temperature (ΔT ) at n = 2

Fig. 6 FG rectangular plate critical buckling temperature (ΔT ) at n = 5

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Critical Buckling Temperature

6

5.9915

5

4.302

4

3.545

3.324

3.825

3 2 1 0

0

1

2

3

4

5

6

Volume Fraction exponent (n)

Fig. 7 Volume fraction exponent and critical buckling temperature (ΔT ) graphical representation

4. When comparing Nickel and FGM plates, ceramic-rich FGM is more resistant to thermal buckling than Nickel plate.

References 1. Li Y, Yang C, Zhao H, Qu S, Li X, Li Y (2014) New developments of Ti-based alloys for biomedical applications. Materials 7:1709–1800 2. Niino M, Kisara K, Mori M (2005) Feasibility study of FGM technology in space solar power systems (SPSS). Mater Sci Forum 492:163–168 3. Lu L, Chekroun M, Abraham O, Maupin V, Villain G (2011) Mechanical properties estimation of functionally graded materials using surface waves recorded with a laser interferometer. NDT E Int 44:169–177 4. Zenkour AM, Mashat DS (2010) Thermal buckling analysis of ceramic-metal functionally graded plates. Nat Sci 2(9):968–978 5. Zenkour AM, Shoby M (2011) Thermal buckling of functionally graded plates resting on elastic foundations using the trigonometric theory 2011. J Therm Stresses 34:1119–1138 6. Ghannadpour SAM, Ovesy HR, Nassirnia M (2012) Buckling analysis of functionally graded plates under thermal loadings using the finite strip method. Comput Struct 108–109:93–99 7. Valizadeh N, Natarajan S, Gonzalez EOA, Rabczuk T, Bui TQ, Bordas SPA (2013) NURBS based finite element analysis of functionally graded plates: Static bending, vibration, buckling and flutter. Compos Struct 99:309–326 8. Yaghoobi H, Fereidoon A (2014) Mechanical and thermal buckling analysis of functionally graded plates resting on elastic foundations: An assessment of a simple refined nth-order shear deformation theory. Compos Part B Eng 62:54–64 9. Zhang DG, Zhou HM (2015) Mechanical and thermal post-buckling analysis of FGM rectangular plates with various supported boundaries resting on nonlinear elastic foundations. Thin-Wall Struct 89:142–151 10. Sobhy M (2016) An accurate shear deformation theory for vibration and buckling of FGM sandwich plates in hygrothermal environment. Int J Mech Sci 110:62–77 11. Xing Y, Wang Z (2017) Closed form solutions for thermal buckling of functionally graded rectangular thin plates. Appl Sci 7:1256 12. Daikh AA, Megueni A (2018) Thermal buckling analysis of functionally graded sandwich plates. J Therm Stresses 41(2):139–159

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13. Trabelsi S, Frikha A, Zghal S, Dammak F (2019) A modified FSDT-based four nodes finite shell element for thermal buckling analysis of functionally graded plates and cylindrical shells. Eng Struct 178:444–459 14. Gautam M, Chaturvedi M (2021) Optimization of FGM composition for better environment material. In: IOP conference series: materials science and engineering, vol 1017. No 1. IOP Publishing 15. Gautam M, Chaturvedi M (2021) Optimization of functionally graded material under thermal stresses. Mater Today Proc 44:1520–1523 16. Nguyen T-K, Thai H-T, Thuc PV (2020) A novel general higher-order shear deformation theory for static, vibration and thermal buckling analysis of the functionally graded plates. J Therm Stresses 44(3):377–394 17. Bouhadra A, Benyoucef S, Tounsi A, Bernard F, Bouiadjra RB, Sid Ahmed Houari M (2015) Thermal buckling response of functionally graded plates with clamped boundary conditions. J Therm Stresses 38(6):630–650 18. Reddy JN (2000) Analysis of functionally graded plates. Int J Numer Methods Eng 47:663–684 19. Cho JR, Ha DY (2002) Volume fraction optimization for minimizing thermal stress in Ni-Al2O3 functionally graded materials. Mater Sci Eng A 334:147–155 20. Karpagaraj A, Ramesh R, Kumar TAS, Kumar NR (2020) The role of laser in manufacturing of shape memory alloy (SMA). IOP Conf Ser Mater Sci Eng 912(3):032008

Aqueous Extract of Colocasia Esculenta Leaves for Prevention of Low Carbon Steel Corrosion in 0.5 M NaCl Vinit Kumar Jha, Vivek Porwal, Gopal Ji, and Rajiv Prakash

Abstract Every year, corrosion of metals causes a great loss to the economy and puts many lives in danger. These losses can be avoided by a variety of ways; however, use of a biodegradable inhibitor can be a better option for this purpose. The present work reports a similar kind of biodegradable inhibitor (Colocasia esculenta leaves) for low carbon steel (LCS) prevention in 0.5 M NaCl. Colocasia esculenta leaves aqueous extract (AECEL) is examined by UV–visible spectroscopy (UVS) and FTIR spectroscopy (FTIRS), weight loss measurements (WL), open circuit potential (OCP) curves, Tafel polarization curves (TPC), electrochemical impedance spectroscopy (EIS), and scanning electron microscopy (SEM). The analysis of AECEL by UVS and FTIRS discloses that AECEL possesses several biomolecules. These biomolecules have the ability to be adsorbed on LCS and thus can provide immunity to LCS against corrosion. Based on examination, the maximum inhibition achieved is 76% (TPC). The inhibition is also noticed in SEM images. Based on total investigation, the most probable reasons for inhibition are also shown in a schematic diagram. Keywords Steel · Corrosion · Inhibition · Colocasia esculenta · EIS · SEM

1 Introduction Metals are the main ingredients required for various technological and commercial applications. In some applications, metals have to face aggressive environments. These environments attack on metal and try to demolish them. Thus, the metals are subjected to high risk of corrosion in these environments [1, 2]. To avoid any possible destruction, corrosion of the metals should be kept under control. Regarding V. K. Jha · V. Porwal · G. Ji (B) Centre for Advanced Studies, Centre for Advanced Studies, Lucknow, Uttar Pradesh 226031, India e-mail: [email protected] R. Prakash School of Materials Science and Technology, IIT BHU Varanasi, Varanasi, Uttar Pradesh 221005, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_11

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this, there are various successful methods [3, 4]. However, use of biodegradable material has been one of the verified, efficient, and economic methods of corrosion prevention [5, 6]. On the top, if waste and biodegradable material are used, it will be revolutionary. There are many reports available in which waste and biodegradable materials are used for corrosion inhibition [7–9]. These materials have managed to retard the corrosion due to their phytochemical molecules that can be linked with metal via adsorption [10]. In this work, a waste biodegradable material namely Colocasia esculenta leaves have been used to check its corrosion inhibition properties against LCS corrosion. Colocasia esculenta is also recognized as ‘Arbi/Taro’ in India and associated with Araceae family. Colocasia esculenta leaves show hydrophobicity and contain several biomolecules [11]. It is a logical fact that hydrophobicity can easily retard corrosion losses [12, 13]. The biomolecules of Colocasia esculenta leaves are chemically active and hence can accumulate on metal surfaces via adsorption. In addition, Colocasia esculenta leaves are biodegradable, economically available and not toxic at all. These all qualities make Colocasia esculenta a suitable candidate to be studied for corrosion inhibition. Furthermore, the LCS is selected for this work because LCS possesses good structural strength, easy to transport, low in cost, and widely used in many engineering applications [14]. The single aim set for this work is to find out LCS corrosion inhibition in 0.5 M NaCl by AECEL through UVS, FTIRS, WL, OCP, TPC, EIS, and SEM. The examination results are stimulating and discussed in detail in various sections of the report. Based on the results, it is proposed that AECEL can be a good inhibitor for corrosion of LCS in NaCl.

2 Experimental Details 2.1 Extraction Green Colocasia Esculenta leaves were fetched from a home garden in Lucknow, India. Then, the leaves were cleaned with tap water and a paper towel. Then, Green Colocasia Esculenta leaves were cut into many pieces and kept on drying at 35 °C for 8 h in electricity-operated oven. The desiccated leaves were then crushed by a kitchen grinder. The powder of leaves (5 gm) was soaked in 1000 mL of water and put on stirring at 600 rpm for 2 days followed by filtration. It was observed that the powder was not dissolved completely and a residue equivalent to 2 gm (in dried state) was received after filtration. Based on that, it was calculated that the resultant solution was having leaves concentration of approximately 3 mg mL−1 . This solution was used without any further purification for the examination. The schematic diagram of extraction method is illustrated in Fig. 1.

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Fig. 1 Illustration of the extract preparation

2.2 Testing of the Extract The extract was examined by BioTek spectrophotometer (UVS) and Thermo Scientific Nicolet 6700 (FTIS). A 200 μL of AECEL was examined in ranges of 200– 900 nm in UVS and 400–4000 cm−1 in FTIS. The obtained spectrum was compared with other reports and standard database, and different biomolecules were predicted.

2.3 Test Specimen The LCS test strips used in weight loss measurements were 5 × 1.5 cm in size. LCS strips were scrubbed by abrasive paper (2/0 and 3/0) of Sianor B and cleaned with ethanol. For electrochemical experiments, the strips were masked to provide effective area of 1 × 1 cm2 .

2.4 WL Details The LCS strips were immersed in NaCl and in NaCl + AECEL solutions, and weight losses in the strips were recorded. Accordingly, the inhibition efficiency (µwl ) was calculated with the formula [15]:

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µwl (%) =

W0 − Wi × 100 W0

(1)

where W 0 belongs to weight loss in NaCl solutions and W i belongs to weight loss in NaCl + AECEL solutions. The other details are given in the work of Ji et al. [15].

2.5 Electrochemical Tests All the electrochemical work was done on CH workstation (7041C). Silver/silver chloride as reference (Metrohm), platinum foil as counter (Metrohm), and LCS specimen as working electrodes were used in the experiments. The first electrochemical test done on the strips was OCP monitoring for 900 s. At the end, EIS was done with a sinusoidal AC signal of 0.005 V (R.M.S) in the range of 100,000–0.01 Hz. After that, Tafel test was conducted in the voltage range of 0.5 V with respect to OCP of the electrodes at 0.005 V s−1 . The obtained Tafel curves were individually analyzed by extrapolation, and various parameters like corrosion potential (E corr ) and corrosion current density (I corr ) were determined. The efficiencies of protection (µp ) were calculated by the equation given below [16]: µp (%) =

o i − Icorr Icorr × 100 o Icorr

(2)

where superscripts ‘o’ and ‘i’ denote I corr in pure NaCl and in NaCl with different amounts of AECEL, respectively.

2.6 Surface Analysis The prepared LCS strips were cut into the sizes of 1.5 × 1.5 cm2 and immersed in 20 mL of pure 0.5 M NaCl without and with optimum amount of AECEL for 6 h. After that, the solutions were drained and the strips were cleaned by distilled water. The strips were de-moisturized in vacuum desiccators for one day and after that examined by ZEISS GEMINI FESEM. The details are given in the work of Ji et al. [15].

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Fig. 2 a UV–visible and b FTIR spectra of AECEL

3 Results and Discussion 3.1 AECEL Synthesis The major compounds usually found in Colocasia Esculenta are flavonoids, saponins, and phenols [17]. UV–visible spectra of AECEL (Fig. 2a) showed one major and broad absorption peaks indicating that some of the aforesaid biomolecules could be present in the extract. A peak at 270 nm could show the presence of Catechin (a flavonoid) in the extract [18]. However, the presence of other molecules could not be neglected because a broad peak was observed. Also, it was possible that other molecules were very low in concentrations. Through FTIRS, many peaks emerged in the spectra of AECEL (Fig. 2b). These peaks could belong to vibration frequencies of various active compounds of the extract. The peaks and their correspondence could be given as: 3434 cm−1 , O–H/N– H stretching; 2916 cm−1 , C–H stretching; 2102 cm−1 , aromatic C–H stretching; 1619 cm−1 , C = C stretching; 1413 cm−1 , C–H bending; 1055 cm−1 , C–O stretching, and 605 cm−1 for C–H bending of aromatic rings of the compounds [19–21]. Based on the results, it could be said that AECEL was successfully prepared and was having biomolecules, which could impart good protection properties to the extract.

3.2 WL Examination The WL examination revealed that weight loss values got diminished with the concentration-wise addition of AECEL in NaCl (Fig. 3b). As a result, µwl values hiked with the AECEL concentration in NaCl because µwl is inversely proportional

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Fig. 3 a Inhibition efficiency and b weight loss data for LCS corrosion in 0.5 M NaCl at RT

with the WL values (Eq. 1). The possible reason could be increased surface coverage of LCS by AECEL molecules [22]. Due to this, NaCl could not react with LCS aggressively and corrosion was retarded. However, saturation in µwl value was observed at 1000 mg L−1 of AECEL and it could not go beyond 70%. Now, the AECEL molecules could not cover more area, and hence, protection was hindered.

3.3 Electrochemical Corrosion Measurements Figure 4 shows OCP variation of LCS substrates immersed in NaCl and NaCl + AECEL solution in first 900 s of immersion. It was evident that OCPs were not perfectly stable in 900 s; however, it was observed that it was tending toward stability. It was noticeable that OCP shifted to negative potential with increase in AECEL concentration. This fact indicated that AECEL could act as cathodic inhibitors [23]. After 900 s of immersion, EIS test was performed using end OCP voltage. The EIS test results are shown in Fig. 5. It was evident that impedance (usually denoted by dia. of depressed semicircles) of LCS substrates was increasing with the AECEL concentration. This fact showed that greater protection of LCS was achieved by AECEL [24]. Figure 5b illustrated that phase angle was the lowest for bare LCS and the highest for 1000 mg L−1 of AECEL, which revealed the fact that AECEL was providing protection to LCS [25]. One of the reasons for better performance of LCS substrates immersed in NaCl + AECEL solutions could be given as hydrophobicity of the leaves. The increased hydrophobicity of the LCS surface could amplify the barrier properties of AECEL. The other reason could be mentioned as LCS surface blockage by AECEL molecules. The inhibitive molecules could be adsorbed on various locations of LCS surface and block the access of LCS for dangerous chloride ions. As a result, the LCS corrosion was slowed down and it was evidenced by increased impedance of LCS in NaCl + AECEL solutions. However, AECEL could

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Fig. 4 OCPs for LCS substrates in 0.5 NaCl at 25 ± 2 °C for 900 s

not completely block the access of LCS for NaCl, that was why 100% protection was not achieved. Figure 6 shows Tafel curves for LCS immersed in NaCl and NaCl + AECEL solutions. In initial analysis, it was recognized that corrosion currents and corrosion potentials (obtained by cross section of the curves) were moving toward lower current region and negative potential, respectively. This information announced that AECEL was protecting LCS in NaCl by blocking cathodic reactions (major), which was in agreement with OCP shift toward negative potentials [26]. However, it was recognized by vigilant analysis of the curves that both polarization curves were showing shift, which suggested that AECEL was blocking both cathodic and anodic reactions of LCS in NaCl [27].

Fig. 5 a Nyquist and b Bode phase curves showing impedance date for LCS in 0.5 M NaCl and NaCl + AECEL at 25 ± 2 °C

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Fig. 6 Tafel polarization curves for LCS and LCS + AECEL in 0.5 NaCl at 25 ± 2 °C

The E corr , I corr , and %µp were calculated from the curves and written in Table 1. Based on Table 1, it could be claimed that E corr was moving toward negative values with the AECEL concentration increased, which confirmed that protection of LCS by AECEL was achieved through more suppression of cathodic reactions occurring at LCS surface in NaCl [28, 29]. However, E corr shift with respect to LCS in 0.5 M NaCl was not greater than 85 mV, which claimed that AECEL acted as a mixed effect inhibitor. Furthermore, it was recognized that I corr of LCS was lesser in NaCl + AECEL solutions. Also, LCS in NaCl with 1000 mg L−1 AECEL was showing more inhibition (76%) in comparison with 500 mg L−1 AECEL (60%). This fact indicated that maximum protection of LCS was realized with 1000 mg L−1 AECEL. The proposed cause for protection was that AECEL was adsorbed on LCS surface and covered different active locations on LCS surface. The chloride molecules could not reach those passive locations, and thus, LCS corrosion was slowed down. However, the 100% protection was not achieved because AECEL could not deactivate all the active locations on LCS surface. Table 1 Major parameters extracted from polarization curves shown in Fig. 6

Coatings

−E corr (V)

I corr (μA cm−2 )

%µp

0.5 M NaCl

0.712

50

–

500 mg L−1

0.723

30

60

1000 mg L−1

0.736

12

76

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Fig. 7 Showing SEM images of a prepared test specimen of LCS, b corroded in 0.5 M NaCl, and c LCS + AECEL corroded in 0.5 M NaCl at room temperature

3.4 SEM Analysis of the Test Specimen Figure 7 shows SEM surface images of LCS, LCS immersed in NaCl and NaCl + 1000 mg L−1 AECEL solutions. It was self-explanatory after inspection of SEM images that AECEL was protecting LCS in NaCl. Figure 7a showed surface of the bare LCS, which suggested that some small cracks, small abraded particles, and stretch marks were generated on the surface due to rough scrubbing. However, the surface was still not looking very rough. The NaCl reacted with the surface and interrupted smoothness of the surface by increasing irregularities, which was clearly observable in Fig. 7b. The excessive rough surface showed high degradation [30] of LCS surface in NaCl. In contrast, AECEL-protected LCS surface (Fig. 7c) was showing very less damage in comparison with the surface in Fig. 7b. This fact indicated that NaCl could slightly damage LCS surface in the presence of AECEL.

3.5 Proposed Mechanism of Corrosion Inhibition Figure 8 shows a schematic diagram for inhibition of LCS corrosion in 0.5 M NaCl by AECEL based on the results acknowledged. The LCS immersed in NaCl could

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Fig. 8 Proposed mechanism for corrosion inhibition by AECEL

be corroded easily because there was nothing to protect bare LCS. After some time of immersion, different corrosion products of iron could be formed and could cover the LCS surface. Due to this, a slight reduction in corrosion could be observed. However, the layers of corrosion products could not provide long-term protection (more than a few hours) because of its high dissolubility in NaCl [31]. In contrast, a layer of AECEL molecules could easily protect LCS in NaCl because of its low solubility in NaCl. These AECEL molecules could cover LCS surface via adsorption and remain at adsorbed location for a long time. However, AECEL molecules could not be adsorbed at each location on LCS surface, and hence, 100% protection is not achieved.

4 Conclusion In this work, a biodegradable material (Colocasia esculenta leaves) was used to protect LCS in sodium chloride. The AECEL was examined for availability of biomolecules by UVS and FTIRS, which revealed that AECEL was containing active biomolecules. The inhibition by AECEL was checked with WL, electrochemical measurements, and SEM. The WL and the electrochemical measurements claimed that LCS corrosion was suppressed by AECEL with more than 70% efficiency. The inhibition was also clearly evidenced in SEM images. Based on the results, a mechanism of inhibition was also proposed, which includes that adsorption for AECEL molecules on LCS and coverage of LCS by those molecules were the prime reason for inhibition. Based on overall analysis, it could be recommended that AECEL provided protection to LCS in 0.5 M NaCl. Acknowledgements Vinit Kumar Jha is thankful to Dr. Piyush Jaisawal and Dr. Anuj kumar Sharma (Both from CAS Lucknow) for their guidance during this work. Conflict of Interests Authors declare null conflict of interests.

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Alternate Material’s Approach Toward Green Construction Nitu, Rajesh Kumar, Vanita Aggarwal, and Surinder M. Gupta

Abstract This paper discusses the alternate materials used in construction of green buildings. It focuses on their physical, chemical, and engineering qualities of materials. Without further study, rules and apparatuses employed in the design of green constructions, it is difficult to reduce energy consumption. Biodegradable materials and solar electricity have been used to make green buildings. Eco-friendly construction methods include the use of biodegradable materials. For the creation of green structures, this study compares and contrasts the use of alternative sustainable building materials with other standard conventional building materials. Determining the best way to use feasible sustainable development materials and comparing it to the traditional development materials used in the present without compromising their accessibility is another goal of this article. The goal of the study is to research and demonstrate how feasible structure materials might help to reduce the impact on the environment and investigate how practical construction materials may reduce the impact of ecological degradation and create sturdy structures that are sustainable for both the occupants and the environment. Keywords Sustainable materials · Sustainable building construction · Environmental impact assessment · Green architecture

Nitu · R. Kumar M.M. Engineering College, M.M (Deemed to be University), Mullana, Ambala, Haryana 133207, India V. Aggarwal (B) Civil Engineering Department, M.M. Engineering College, M.M (Deemed to be University), Mullana, Ambala, Haryana 133207, India e-mail: [email protected] S. M. Gupta Department of Civil Engineering, NIT Kurukshetra, Kurukshetra, Haryana 136119, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_12

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1 Introduction Materials are essential to the development of structures. The mechanical strength of structure is based on the quality of materials as well as its physical and chemical tracts used in construction. Materials that are similar to or preferable to conventional structure materials should be used in eco-friendly constructions [1–4]. Although manageability has been a big issue in recent years, the construction industry has a responsibility to developing an eco-friendlier method of development for constructing buildings and infrastructures. Making arrangements for reusing, repurposing, and new material applications, manageable creation of products or green assets is possible. This could be the fastest way for developers to implement sensible design ideas in structures by using environmentally friendly materials. Accepting alternate materials for sustainable building is a good way to achieve this goal. In this sense, choosing development materials with the lowest environmental impact is beneficial to a country’s improvement. An important goal of this research is to demonstrate how structurally sound materials can help to mitigate environmental degradation and produce strong structures that can be supported by residents, just as in our current situation. In India, excessive use of energy and resources by the construction sector, as well as the release of significant amounts of rubbish and CO2 emissions [5–14], is seen as a pressing issue that has to be addressed. Since the designs are based on environmental sustainability, they also consider the bigger building ramifications. Energy-efficient and environmentally friendly homes and structures are designed with careful consideration to green architecture principles. Sustainable architecture relies on natural ecology as a foundation for its construction model. Poor indoor air quality is also a problem, can cause health problems for workers, resulting in decreased productivity [5]. Additionally, every year, the construction industry consumes 25% of the wood and 40% of the sand, stone, and rock used in the construction industry around the world. For natural effects, there is a large influence of structure area on the climate. Material and format selections are crucial for the general maintainability of private organizations. Development materials with low ecological footprints should be chosen for the sake of a country’s sustainable development. Existing technologies for low-sway construction materials are urgently needed, although there are a few that are already in use [8]. A lot of people have started from a previous flood of sustainable and reasonable development, while still adhering to the fundamental rules today. The smart materials that are used in building construction is a great approach to achieve this goal, as they are environmentally friendly. A country’s growth can be improved by determining which development materials have the least environmental impact. A fantastic way to support a structure’s ecological performance is by selecting naturally suitable structure parts. A few frameworks have been selected to as being more efficient in spreading best practices among committed sustainability parameters, developers, and people looking for an alternative method of material-determination measures and utilization of reused fabricating materials [10].

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1.1 Building Materials Problems Compared to 2001–2002, its contribution to the Gross Domestic Product (GDP) has increased from 1.5 billion to 4 billion in 2011–2012, which is about 8% of the nation’s Gross Domestic Product (GDP). In India, the real estate and construction industry is predicted to create 75 million employments by 2022, according to estimates. As a matter of fact, between 1997 and 2007, material consumed by construction industries grew at the fastest rate. Buildings will overtake agriculture by 2022 if current growth rates continue. In this way, the amount of energy consumed by a building may be broken down into two main categories: operational and embodied energy. It is estimated that the construction sector in India contributes 30% of the country’s GHG emissions and 20–25% of energy consumption in India [11]. It is important to rethink construction materials in light of resource and energy use. The use of raw materials must be kept to a minimum as per requirements. Construction materials must be as energy efficient as possible. These measures include reusing building materials, reducing the use of materials that have high embodied energy and sourcing materials from local area whenever possible.

2 Material Conservation in Green Building Construction The construction of sustainable buildings uses a variety of materials that are environmentally favorable. Selected structural materials that are environmentally friendly at the design phase of building contribute to more sustainable construction [15–25]. Materials used in green design are therefore those that support good thermal performance, efficiency in energy, efficiency in water, managing the use of resources, and lower overall construction costs [12]. A long-term view of environmental consequences of materials is a crucial selection factor. A guide to green building materials can be found in the following list. Many of these characteristics can be found in materials such as Accoya modified wood. This product is eco-friendly, long lasting, resource efficient, and toxic free. For LEED certification, these materials are essential because they support environmentally friendly construction.

2.1 Recycled Products For green construction, recyclable materials are ideal because they conserve resources. There are many examples of recycled materials, such as the paper insulation made from recycled cardboard and newspapers, the cotton insulation made from denim. They are cost effective due to their low chemical and energy requirements. In addition, they use fewer natural resources.

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2.2 Materials Produced Using Environmentally Friendly Procedures Ecologically friendly building uses these materials above others because they take less energy to create and reduce resource waste and greenhouse gas emissions. Making sustainable concrete can be done with crushed glass as well as slag and wood chips.

2.3 Natural or Renewable Materials Naturally occurring and sustainably managed resources can provide these materials. They must also be self-renewing and be abundant in the natural environment in order to be effective. Examples include solar tiles and certified wood [6].

2.4 Refurbished or Salvaged All materials that have been repaired, recovered, or rebuilt fall into one of these categories. For example, they are necessary because of their natural ability to produce value and prevent materials from being wasted. Renovation, repair, or enhancement of the material’s functioning or quality. Plastic ceilings are a good example.

2.5 Reusable and Recyclable Products This is a collection of materials that have been used in the past. However, they are still in good condition and can be reused for new construction and make the environment eco-friendly. Examples include as old plumbing and old doors and windows.

2.6 Durable Materials Less frequent replacements and maintenance are required with materials that endure longer, reducing the environmental impact of the product. By doing so, they also help to cut down the overall cost of upgrading an already built structure or dwelling. Durable materials are also very reusable and recyclable.

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2.7 Use of Water and Energy-Saving Technologies Building materials that conserve water can help reduce the amount of water used in construction and over time. Reduce water waste by using materials designed to reduce water loss and improve water quality [7]. In contrast, energy-saving materials reduce energy expenses and increase the efficiency of buildings. Energy-efficient materials include solar panels and wind turbines, because it reduces shipping costs, greenhouse gas emissions, and environmental impact by using locally available materials in green design.

2.8 Non-toxic Materials In green building, the use of non-toxic materials is highly advocated. They improve indoor air quality and contain very little carcinogens, irritants, or reproductive toxins. So we use such type of material that is not harmful for environmental activities as well as human health.

3 Principles of Sustainable Building Construction As the world shifts toward a more sustainable future, architecture faces a significant challenge in designing models that reduce the negative effects of building on our environment. Sustainable design principles are employed to make this possible. Let us take a look at some of the fundamentals.

3.1 Efficiency in Energy Use Through a variety of measures, energy-saving techniques are integrated into the concepts of green design. Efforts to use of less energy have been made, including using energy-efficient appliances and renewable energy sources such as solar and wind power sources [17]. Environmentally friendly green architecture reduces energy consumption through using natural air flow patterns and sunlight, as an example. Heating, lighting, and air-conditioning costs must be kept as low as possible over a building’s lifespan.

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3.2 Efficient Use of Water With the help of nature, green architecture aims to safeguard water quality and reduce water use. As part of the sustainable principles of green construction, the effective use of water is encouraged. While the building is being constructed this green design technique ensures that water is captured, utilized, cleaned, and reused. Architectural design makes sure that during the whole life cycle, not only does the building support efficient water consumption but that the quality of neighboring water systems is preserved and that water recycling devices are utilized.

3.3 Efficiency in the Use of Land Architecture that encourages environmentally friendly site development and reuse of local materials is referred to as land use efficiency. A roof garden, earth shelters, and substantial landscaping around the structure are advocated.

3.4 Efficiency of the Materials In addition, the proper management and usage of materials in building are a major challenge as well. That is where green architecture comes in, with the right construction approaches. By improving building procedures, it generates designs that inspire sustainable construction by maximizing material efficiency [2]. It is a green architecture philosophy to use materials in a way that makes the building more efficient over its lifetime. The designs include energy efficiency and resource conservation to ensure overall material efficiency.

3.5 Less Maintenance Costs Because of the high operational and construction expenses, conventional construction methods are also very resource intensive. Material and building processes that are cost effective are used in green architectural design, reducing operational and construction costs by almost half. Because of this, non-toxic products such as recycled metal and stone must be used. High-performance goods made from renewable and reusable materials save maintenance expenses over the long run.

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3.6 Eco-Friendly Architecture Accordingly, the adoption of eco-friendly designs to decrease these environmental repercussions is one of the core ideas of green architecture in this regard. Preventing site deterioration during construction, managing sprawl, and conserving resources are all parts of this green approach. Ecosystems and biodiversity are protected and improved by the design [18].

4 Alternate Materials Used in Sustainable Construction Using green building materials for sustainable construction generally depends on the sources of materials.

4.1 Bamboo Bamboo is an eco-friendly building material. There is an exceptionally rapid rate of self-generation, with some plants growing up to three feet in 24 h, according to reports. After harvest, it continues to spread and flourish without needing to be replanted. On every continent with the exception of Europe and the Antarctica, it is a perennial grass. You can build with it for a long time for its high strength to weight ratio, as well as its superior overall strength to concrete and bricks. As a result, it is the ideal material for flooring and cabinetry [3]. Bamboo, on the other hand, must be treated to prevent insects and decay. As a result, it is the ideal material for flooring and cabinetry. Bamboo, on the other hand, must be treated to prevent insects and decay. When treatment is left or not to be done properly, then untreated bamboo contains a starch that is poisonous and can cause swelling and cracking after absorbing water from the air.

4.2 Straw Bale You can also use it to frame your home. Good soundproofing and insulating capabilities make them ideal for this purpose. Also, because they do not allow air to get through, they can have some fire-resistant capabilities. Straw may be gathered and replanted with minimum influence on the environment. Straw baling has a negligible impact as well. Additionally, they can be installed in the house’s walls and ceilings to help keep the house cool during hot weather, while keeping it warm during the colder months.

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4.3 The Use of Recycled Materials Recycling plastics and other waste is being used in concrete production instead of mining and milling new components from the earth. As a result, greenhouse gas emissions are reduced, and plastic waste is repurposed instead of contributes to plastic pollution by filling up landfills [19]. Also, polymeric timbers are made from a mixture of recycled and virgin plastics, which helps to conserve forests. It is possible to spin carpet fibers from two-liter bottle plastic. There are a number of other items that can be made from recycled plastic in addition to cable pipes.

4.4 Reclaimed and Recycled Steel A structure can be strengthened against earthquakes and severe winds by using steel instead of wood for framing. It takes 50 trees to build a 2000 ft2 house, but it only takes six discarded vehicles to build a steel frame. Recyclability of steel reduces environmental effect of new building by up to 90%. Energy is required to mine, heat, and shape aluminum and steel products; however, reusing or recycling them into new products reduces energy consumption and makes the material more sustainable. Therefore, it uses less energy because it lasts a long time without having to be replaced. Therefore, it may be used for roofing as well as building facades and structural support because it does not burn or wrap. In addition, repurposed steel is resistant to water and pests.

4.5 Rigid Foam Made from Polyurethane Foam that is rigid has been utilized in construction for a long time as an insulating material. They were introduced after a major surfboard material manufacturer was penalized by the Environmental Protection Agency and forced out of business for using a toxin-filled product. Surfboards manufactured from bamboo, kelp, and hemp polyurethane hard foam are now a thing of the past. Currently, it is used in the production of turbine blades and furniture. Materials such as these can be utilized as insulation because they are hard and generally immobile. As an added bonus, it protects against mold and bugs as well. For sound insulation, it can be used as well as a heat-resistant material [16].

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4.6 The Wool of Sheep This natural insulation material is an excellent alternative to chemical-laden alternatives. When used as a residential insulation material, it performs equally as well as conventional materials, plus it uses less energy to produce. Energy efficiency and sound proofing are two benefits of sheep’s wool. As an insulation material, sheep’s wool does not disintegrate nearly as quickly as other materials. Unfortunately, it is not the most cost-effective insulation. To keep insects at bay and prevent fungus growth, it must be treated.

4.7 Hempcrete Concrete-like material can be created by utilizing the hemp plant’s inner woody fibers that can be used in construction. Lime is used to bind the threads together, resulting in strong and lightweight concrete-like structures. Hemp concrete blocks are extremely light, lowering the amount of energy required to transport them. In addition to being strong, hempcrete has excellent insulation properties from heat and sound, and it is fire retardant. Furthermore, hemp is CO2 negative, which means that it absorbs more CO2 than its emissions. That is because hemp grows quickly that is also renewable.

5 Comparison Between Conventional and Alternative Building Materials Compared to the conventional building materials, sustainable green buildings are more energy efficient, have lower operating and maintenance costs, improve occupant comfort and well-being, have lower risk possible, and reduce harmful impact on the environment [9]. The following are some of the benefits of sustainable green buildings. For example, an eco-friendly building is the most efficient way to use resources like land and water while maintaining a comfortable climate for its residents [20]. Compared to traditional buildings, green constructions make better use of energy, water, materials, and land. Sometimes the traditional design and building techniques lead to the use of natural resources (Table 1).

5.1 Accoya Wood Highly rot-resistant, Accoya wood has a long lifespan in a variety of climates. As the process only enhances the quantities of already present components within the

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Table 1 Comparison between conventional and alternative materials Parameters of comparison

Conventional building materials

Alternative building materials

Aim

Does not have any environmental goals

Aims to reduce environmental pollution

Concrete

Uses cement and other substances harmful to the environment

Uses ‘green concrete,’ which contains recycled items Crushed glass, wood chips, or slag

Flooring

Uses concrete flooring

Uses wood flooring

Reinforcement

Steel reinforcement

Bamboo reinforcement

Wall system

Brick walls

Walls are made of straw or bale

molecular structure of the wood, no harmful compounds are produced. Since every piece of Accoya has been adjusted down to the core, no matter how the wood is cut, planed, drilled, or shaped, it will function and protect the same. Without the use of preservatives, Accoya is perfect for a wide range of applications such as window frames and doors as well as façades, cladding, and decking. Teak and old growth tropical hardwoods are outclassed by Accoya’s durability. Wood acetylation is used to produce Accoya. That means less water absorption in the cells of the wood and less need for maintenance. For this reason, insects and fungi avoid Accoya wood. It has no any termites or other wood eating critters. It provides more strength and long life durable and no any color change during the process, but as in teak wood, there will be a change in color through aging. You can find the change in the color of the wood. The initial color of the wood will be honey brown, and the final color will be silvery gray.

5.2 Marble Slurry Bricks This type of brick can be used as an alternative to clay bricks for building a wall. Using marble as a building material has been used for a very long time. Marmor’s processing leaves behind a waste at the quarries or the sizing business that is often ignored. It is estimated that the amount of waste marble slurry is in the billions of tones. Rajasthan, India, marble processing units are to be contacted to collect marble slurry waste from their processing operations. For example, bricks made from marble slurry cost 10% less than clay bricks made from a standard mortar mix. In addition to helping to reduce the environmental concerns posed by the disposal of waste marble slurry, this will also aid in the construction of sustainable infrastructure and low-cost housing. Marble slurry bricks provide more strength than clay bricks. It has fire resistance technology, and it has high load bearing capacity and high energy efficiency. Construction expenses and soil extraction go up because of the clay brick

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masonry wall material’s enormous size. Because of this, soil and vegetation are damaged, and soil erosion is increased as a result of this.

5.3 Concrete Roofing of Tiles Traditional roof tiles are produced from locally accessible materials, such as terracotta or slate, and are meant to keep rain out. Clay tiles with a waterproof finish are also used, generally used for protective covering that protects the outside of a building, i.e., cladding for sloping roofs of different types of buildings. These tiles are highly cost effective and more durable and stronger in different climate. There is no noise during rain. But thatching included as one of the crafting activities for the roofing process and built with dry vegetation materials including water reed, heather, straw, rushes, and also palm branches. You need to layer the vegetation to make sure if the shed would help the water run away.

5.4 Construction with Straw Bale As non-load-bearing filler, straw bales can be used as structural components of a wall (load bearing.). As a renewable resource, straw is a great insulator that may be easily constructed. As a rule, stucco, plaster, clay, or other treatments are applied to the inner and external surfaces of bale walls. It is possible for this form of construction to have structural qualities that are superior to the sum of its parts. Structural straw bales can be made to carry loads or not by employing agricultural waste from the dump as a building material with a number of remarkable properties. It is true that straw bales are more resistant to termites and vermin than stick building, but as with any style of construction, it is crucial to seal any gaps or holes. It is necessary to offer nailing surfaces for straw bales because they do not hold nails as effectively as wood does. Isolation is excellent in terms of thermal and auditory. Chemically sensitive individuals benefit from the fact that straw bales do not need to be toxically treated before use. It has the potential to be cost effective as well. Because straw is a waste product, it decreases construction costs, and the leftover straw is compostable or can be used as a soil-protecting ground cover.

5.5 Fly Ash Sand Lime Gypsum Bricks Bricks made of fly ash are commonly used for walls in dwellings and other sorts of construction, including boundary barriers. Fifty-five percent (55%) is the optimal mix of fly ash, 30 percent (30%) is sand with 15 percent (15%) of lime, and 14 percent of gypsum (14%) is the optimal combination. Bricks made from it have

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outstanding strength and dry quickly. The fly ash sand lime gypsum bricks have low water absorption and shrinkage, unit volume weight, apparent porosity and reduction in mortar consumption, and utilization of industrial waste and volcanic ash than while usage of bricks in construction of sustainable buildings because there is large-scale environmental damage, more water absorption, and primary cause of soil degradation and destruction of plants.

5.6 Insulation Materials In this, we will compare renewable thermal building insulation with traditional materials. When it comes to sustainable thermal energy, solar collectors are most popular. They use solar energy to heat water [13], buildings and swimming pools, among other things. It is also possible to use geothermal or ground source heat pumps (GHP) to heat a building in another season. Hence, energy conservation has become a global strategic aim, which will contribute to environmental protection and natural resource conservation. In many countries, the energy used to heat and cool buildings is regarded to be a substantial source of energy consumption. In order to preserve energy and decrease energy losses, there is a constant search for suitable alternatives. Building components such as insulation are becoming increasingly important as an energy-saving measure. Polymer-based compounds, such as polystyrene and polyurethane foam, are the most common insulating materials utilized in the building industry today. But these materials are too much costly and required more maintenance. Despite their strong thermal insulation performance, these materials have considerable environmental implications throughout their manufacturing processes.

6 Sustainability Criteria in Construction In the future, building technologies that adhere to certain principles could be more environmentally friendly, allowing for more efficient sharing of resources such as energy. There are four criteria in this section (Table 2).

7 Conclusion As a result, alternate building materials can be readily available materials, recycled and reclaimed materials, or construction waste that has been repurposed. They are lower in harmful emissions, and they are economically sustainable. They have a lower environmental impact, are thermally efficient, require less energy than conventional materials, make use of renewable resources, more utilization of produced waste from industries, emit fewer harmful emissions, and are economically feasible. They are

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Table 2 Sustainable building materials criteria [18] Number of criteria

Name of criteria

Maximum points

Criterion 18

Reduction of construction’s environmental impact

6

Criterion 19

Low-impact building materials

5

Criterion 20

Use of recycled content in roads and pavements

4

Criterion 21

A variety of low-VOC paints, adhesives, sealants, and wood composites

2

Criterion 22

No ODP material is used

Mandatory

Total weightage

17

durable, cost effective, and require little maintenance, so they are a great choice. For the construction business, sustainable buildings are seen as a step in the direction of environmental stewardship. To achieve a good balance between social, environmental performance, economic and sustainable building approaches are promoted. On the basis of this premise, it becomes clear that construction has a direct relationship to sustainable development. Construction has a high economic impact as well as significant environmental and social impacts. In every community development, a green building material must be utilized appropriately and contingent. Materials that are made from renewable resources are less expensive to transport and emit less carbon dioxide than those that are made from non-sustainable resources. Local residents benefit from job opportunities, as well as the opportunity to enhance their talents. The local economy also benefits. Because of it, this research suggested that applying alternate building construction materials is recommended as a way forward in order to support growth and development in the construction industry while reducing damage on the environment.

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Effect of Various Tools on Bone Condensing to Improve the Stability of Dental Implant Mohit Phadtare, Parth Jain, and Pankaj Dhatrak

Abstract Dental implants are getting common these days and have become alternate to orthodox techniques. A dental implant is a surgical component that interfaces with the bone to support a dental prosthetic device such as a crown, bridge, or to act as an orthodontic anchor. The result of any implant process relies on bone density, implant design, and surgical techniques. During surgery to place the dental implant, the oral surgeon makes a cut to open gum and expose the bone. Holes are drilled into the bone, where the dental implant post will be placed. In the dentistry techniques such as conventional drilling, osteotome technique and osseodensification are used to prepare the site for implant. Among these techniques, conventional drilling is widely used. However, it has drawbacks such as longer bone healing periods, lower primary stability, and high heat generation. The main aim of our review is to put forward a detailed description of better and alternative surgical techniques for implant site preparation. A systematic description and categorization of these methods are given along with their benefits. Surgical procedures like osteotome technique (bone condensation) and osseodensification (bone expansion) have been studied for this review. These methods have demonstrated to improve osseointegration which in turn increases the implant stability as well as the healing period. Thus, adopting these methods will significantly improve the stability and quality of the implant. Nevertheless, additional research is needed to study more efficient techniques which will make the process of implant site preparation easier and quicker. Keywords Bone condensing · Dental implant · Implant stability · Osseodensification · Osseointegration · Osteotome technique M. Phadtare (B) · P. Jain School of Mechanical Engineering, Dr. Vishwanath Karad, MIT-World Peace University, Pune, India e-mail: [email protected] P. Dhatrak Faculty of Mechanical Engineering, Dr. Vishwanath Karad, MIT-World Peace University, Pune, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_13

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1 Introduction Dental implants are in demand currently because of their superiority over orthodox techniques like dentures and dental bridges [1]. The result of any implant procedure depends on many parameters such as surgical method, bone quality, and implant design. Dental implant stability helps us understand the success of dental implants [2]. This parameter can be split up into primary stability and biological secondary stability. At the time of surgery, the stability established between the implant and the interfacing bone is called primary or mechanical stability [3]. To support the masticatory loading, osseointegration is essential. To obtain this osseointegration, primary stability is extremely important [4–6]. The preservation and maintenance of bone during osteotomy preparation improve primary mechanical stability, increase bone to implant contact, and hence improve the secondary stability of the implant [7]. Secondary implant stability is defined as biological stability gained through osseointegration and bone remodeling during the course of the implant’s life [3]. The direct mechanical and functional link between organized bone and the surface of an implant is known as osseointegration [8]. Osseointegration is described as a direct bone anchoring to an implant body that can serve as a basis for prosthetic support [9]. Osseointegration is critical for implant predictability [10]. This treatment improves the quality of the osteotomy and aids in bone densification. Implant parameters such as material, implant design, host variables, surgical procedures, and biomechanical considerations all play a part in osseointegration [10]. When primary stability is enhanced and bone mineral is maintained, the implant site heals more quickly [11, 12]. Summers proposed a strategy in 1994 that includes osteotomy site condensation to promote primary stability by increasing bone density [13]. He had suggested employing osteotomes to condense the cortical bone at the implant location. However, osteotomes have the disadvantage of limited accessibility and instrumentation. Huwais presented osseodensification [14] as a new technique for densification of the cortical bone using a customized bur in 2013. The osseodensification treatment is a novel technique for enhancing primary stability in low-density bone. This approach was recommended to increase osteotomy quality, implant bed densification, indirect sinus augmentation, and bone expansion [15, 16]. The purpose of this approach is to create a situation in which the bur design enhances primary stability (IPS) by densifying the osteotomy site walls through bone autografting. Conventional drilling is the most common implant site preparation technique for implant fixture but during it compromises the implant stability and strength with longer healing periods. The aim of this review is to show alternative concepts, mechanisms, procedures like bone condensing and osseodensification and its benefits over the conventional techniques comprehensively.

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2 Primary and Secondary Stability Primary implant stability is a necessity for successful osseointegration and is a requirement for functional dental implants. Poor implant stability could lead to fibrous encapsulation with resultant failure. Implant failure occurs if there is micromotion of the implant more than 50–100 µm during healing period which may harm osseointegration, and this may lead to fibrous integration of the implant [17]. The implant is said to be stable if its micromovement is within these limits [18]. The measurement of implant stability which can occur is divided into two stages: primary mechanical stability and secondary biological stability [3, 9]. Primary stability is generally linked with successful integration of the implant when there is negligible micromovement by permitting mechanically interlinked between the implant and the bone tissue until biological stability is obtained [11]. Initially, this contact between the two materials does not have biological connection characteristics but has only mechanical connection characteristics but as bone being a tissue, while this surgical process periphery surrounding the implant is devitalized and remodeled [10, 19]. This biological process will usually soften the bone to implant contact which in turn reduces the mechanical stability. Luckily, the bone eventually forms surrounding the implant due to osseointegration. This is biological stability. This stability is affected by factors like the implant category, bone density, torque of insertion, and surgical techniques [20, 21]. Bone condensing and osseodensification have lately been established as innovative osteotomy techniques, which improve general implant stability [1].

2.1 Measurement of Stability It is critical to check the implant’s mechanical stability before it is loaded. Resonance frequency analysis has been a popular approach for determining implant stability because of its non-invasiveness and reliability [22]. Because of its soundness and great reproducibility, the RFA approach has gradually outperformed the various methods for assessing implant stability [23, 24]. This is a non-invasive technique for assessing the bone-implant interface and, as a result, assisting in the acquisition of clinical evidence of stability [25–27]. RFA has also been demonstrated to be quite reliable in determining implant stability after insertion in the jawbone [28, 29]. RFA applies a modest magnitude bending force to the implant-bone system via a transducer. By providing a constant force in the lateral direction of the implant and measuring the subsequent displacement, this bending force simulates the loading state clinically [30]. Any change in stiffness is expected to correspond to a change in osseointegration at the bone-implant interface [31]. As the implant’s bonding level with the surrounding tissue complex increases, so does the resonant frequency [32]. The resonance frequency will eventually stabilize, indicating implant stability after osseointegration [33, 34] (Table 1).

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Table 1 Different RFA technologies used for implant stability measurement

RFA technique

Contact/non-contact

Electronic RFA

Contact

Impulse-triggered RFA

Contact

EMI RFA

Contact

Electromagnetic RFA

Non-contact

3 Surgical Site Preparation for Implants One of the essential aspects affecting the implant stability is the implant surgical method. This process is useful to ready the implant bed for the insertion of the implant. Traditional implant site preparation includes using dental drills having ascending diameters; the last instrument size corresponds to the implant diameter [35]. This technique has some drawbacks like longer healing periods and high heat generation due to friction. We are going to study upcoming techniques such as osteotome technique and osseodensification.

3.1 Osteotome Technique Bone condensing was proposed to improve the posterior maxilla region’s overall dental implant stability. This technique includes bone condensers, shaped like implants by which the bone is condensed apically and horizontally instead of removing the bone. This technique helps preserve a major volume of bone. Bone condensing improves maxillary bone’s density to enhance the mechanical stability present in bone having low density [36] (Fig. 1).

3.1.1

Geometry of Osteotomes

In 1994, Summers [36, 37] advocated condensing of cortical bone for implant site by using expansion osteotomes which are cylindrical–conical with successive diameter increase from one instrument to the next, but the base of each osteotome coincides with the next instrument’s operating portion. Condensation of the osteotomy site enables us to place the osteotome in the bone, compressing the latter, increasing density of the bone and then primary stability. The top part of the osteotome is concave and at different lengths and different diameters. The implant surgical technique has been modified by this instrumentation in the upper maxilla. This is because of existence of excessive spongy bone and its anatomical features [38] (Fig. 2).

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Fig. 1 Osteotome manages more compact bone both in horizontal direction and in apical direction

Fig. 2 Osteotome having varying diameter

3.1.2

Working of Osteotomes

As mentioned above, the tools used in this technique are called osteotomes. These concave-shaped osteotomes save the walls of the bone eventually pushing them toward the sinus floor. Initially, radiographs are used to take accurate measurements made from the osseous crest to the sinus floor. First step is being short in length and tapered tip of the osteotome entering the osteotomy site. With the use of a surgical guide, the first osteotome of least diameter is tapped about 1–2 mm from the sinus base. Then, we use the pilot osteotome; the entrance of the osteotomy is widened to accept a second osteotome of slightly greater diameter. Now with the surgical guide in place, the second osteotome is tapped to the recommended size. At this moment, a radiograph is measured with parallel pins in place if we have to make any changes in measurements if essential. The doorway of the osteotomy is further widened and compacted to accept the third osteotome with the usage of

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countersink (second) osteotome. Now, the third osteotome is driven to the final length. Osseous graft material is now located within the osteotomy, and the third osteotome is pushed to the last depth measurement. With the addition of osseous graft material, the elevation continues to the preferred final depth. Implants are selected and placed into the osteotomy [39].

3.2 Osseodensification Huwais aimed to innovate a new procedure and instrument to preserve bone health while preparing the osteotomies rather than excavating the bone. This gave rise to the invention of Densah bur and osseodensification; the bur is manufactured by Versah [8, 14]. Traditionally, implant osteotomy depends on excavation of bone from the implant site using bone-cutting burs, but it is often restricted by the density of the bone. In 2013, Huwais came up with a surgical technique using bur specially designed to densify the adjacent bone [14].

3.2.1

Geometry of Densah Burs

The design incorporates multiple helical flutes separated by lands, each having a rubbing face and a cutting face within tapered geometry. This design produces a quick feed rate with minimum heat rise [40]. There is a minimum of one lip located at the topmost end of the bone. The bone gets grinded when the bur is moving in the non-drilling direction and cuts the bone walls when turning in the cutting direction. For the burs to easily enter deeper into the osteotomy, these burs have tapered shank and cutting chisel edge pattern, which also helps to control expansion process. To create an opposing axial reaction force at least one of the lands and the lips is configured, when regularly rotated in a burnishing direction. This leads into a pushback situation that gives better regulation over the bone expansion approach. The helical flute of the bur having a burnishing face is rotating in the burnishing direction the face burnishes bone. Similarly, this flute has a cutting face which when rotated in cutting direction cuts the bone, the bur has numerous large negative rake angle lands, increasing the bone density, therefore, increasing the secondary (biomechanical) stability of implant. Densah burs have a minimum of four lands along with drills which are twisted flutes or straight flutes to lead them along the osteotomy and smoothly condense the bone (Fig. 3).

3.2.2

Working of Densah Bur

The Densah bur has two modes: densifying mode and cutting mode. When the bur rotates in a clockwise manner, the bur cuts the bone and densifies the bone when rotated in an anti-clockwise direction during the site preparation procedure [41–44].

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Fig. 3 Salient features of Densah burs

In these burs when rotating anti-clockwise, osseodensification occurs due to the flute back rake angle. Along with that, operating at these counterclockwise speeds in the reverse direction, it can expand the bone to ready the osteotomy site for implant installation and preserve bone. The tapered shank of the bur helps in the expansion of the site. This feature gives a chance to the operator of the tool to lift away from contact at a faster rate to allow for irrigation. Densah bur creates an outward pressure that produces a wave consisting of hydrodynamic compression when integrated with irrigation at the point of contact. This drives the bone debris and bone chips into the implant bed instead of removing it [10]. This approach for implant site osteotomy is called non-subtractive drilling. This technique increases the implant torque and bone density in the peri-implant region which in turn guarantees a rise in implant mechanical stability and decrease in micromotion [45]. Throughout this surgical procedure, the burs progressively increase in diameter, and at 800–1500 rpm, the bone condenses in anti-clockwise direction and maintains the bone and precisely removes bone at the same speed in a clockwise direction [41] (Fig. 4).

4 Parameters of Studies Included See Tables 2 and 3.

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Fig. 4 Different modes of Densah burs which help in increasing stability

Table 2 Synopsis of the osteotome technique studies Author

Type of study

Study conducted

Outcome

Padmanabhan and Gupta [45]

A clinical study (sample size-5)

10 implants of unit screw-type self-tapping threads with 3.7 mm diameter and 13 mm length

A standard bone loss of around 1.2 mm compared to 0.99 mm bone loss with conventional procedure

48 SLA Straumann implants of 4.1 mm diameter and 10 mm length were sited into edentulous maxillary posterior region. Data was analyzed using Mann–Whitney U and Wilcoxon tests

Significant improvement in implant stability was observed

Markovic´ et al. [46] Clinical trial (sample size-48)

5 Conclusion The surgical technique plays a crucial role during the insertion of dental implants. The goal of this paper is to review the two upcoming surgical techniques which provide advantages over conventional drilling techniques. Osteotome technique developed by Summers was introduced in 1994. Osteotome technique conserves the bone mass and improves the quality and preserves the bone. Heat is an important parameter which affects the osseointegration; however, during osteotome technique, no heat is generated preserving the bone cells. Osteotome method has been proven to be reliable, cost-effective, and easy to implement. Osseodensification using Huwais’s Densah bur is a new technique which compresses the bone; it includes less cutting and decrease microgaps and micromovement increasing the primary stability and decreasing healing time. This increases bone bulk and density. The burs provide

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Table 3 Synopsis of the osseodensification technique studies Author

Type of study

Study conducted

Outcome

Lahens et al. [47]

In vivo study (sample size-5)

Total implants = 30; 15 parallel, 15 conical in low-density bone

Significantly higher bone to implant contact

Erich Meyer et al.

In vivo study (sample size-12)

Three preparation techniques: standard drilling with rotary bur, extraction drilling with Densah bur, osseodensification with Densah bur rotating in reversed, and non-cutting direction (total sites = 72)

No differences in ISQ between the groups, but bone to implant contact was increased to 3 times for osseodensification versus standard drilling

Trisi et al. [41]

In vivo study (sample size-2)

Ten implants with diameter of 3.8 mm and length 10 mm using conventional drilling versus ten implants with diameter of 5 mm and length 10 mm using osseodensification

No implant failures were reported. Significant increase of ridge width was detected in the test group and better stability in osseodensification

Tian et al. [48]

In vivo study (sample size-12)

Twelve endosteal implants of diameter 4 mm and length 13 mm were studied

Higher mean bone to implant contact percentage was observed

I¸sık et al. [49]

Clinical trial (sample size-12)

Total 54 implants (28 using osseodensification and 26 using conventional drilling) test used independent and Mann–Whitney U

The residual bone height indicated no statistically significant difference between the groups but enhanced primary stability in osseodensification

advantages of the osteotome method while also providing the advantages and speed of drill. Since these methods are relatively new, a lot of more studies and observations need to be conducted before it can prove itself to be economically viable. The literature available with us is not sufficient to deduce tangible conclusion; additional clinical trials and studies are suggested to get more concrete results.

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Investigation on the Microstructure–Corrosion Correlation of Commercially Available AISI 1020 and 304 Steel Sudesna Roy , Bijaya Bijeta Nayak, and Sasmita Sahu

Abstract Low carbon steel materials are commonly used for numerous applications for both scientific as well as practical purposes. These materials can be easily welded and forged and shaped. The two most common grades of commercially available low carbon steel are AISI 1020 and 304 grades. They are used as substrates for coating thin films to improve their performance. There are both low carbon, but differ substantially in their chemical compositions, structure, mechanical properties, and also their corrosion performance. The selection of the material for different applications usually involves an initial assessment of their structure–property correlation. Although there are a number of articles that have evaluated performance and characterized their properties of these commercially available materials for their applications, the structure–property–performance correlation of the materials is not available. This work correlates the chemical composition, microstructure, mechanical properties, and corrosion performance (by construction of Tafel plots through potentiodynamic polarization tests) of AISI 1020 and 304 steel and compares them. The work shows that while the mechanical properties of AISI 1020 are superior, the corrosion performance in 3.5 wt% NaCl solution is actually poor. The corrosion degradation AISI 1020 is observed to occur due to pitting corrosion aggravated by microcracks. The improved corrosion performance of AISI 304 steel is due to the presence of appreciable amounts of chromium and nickel in its chemical composition. Keywords 304 stainless steel · AISI 1020 steel · Corrosion · Tafel plot · Pitting corrosion

1 Introduction Steel is an important structural material that has numerous applications. Most applications of steel are particularly in the marine, civil, and automobile industries. Based S. Roy · B. B. Nayak · S. Sahu (B) School of Mechanical Engineering, KIIT Deemed to Be University, Bhubaneswar, Odisha 751024, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_14

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on its composition, steel may be classified as low carbon, medium carbon, and high carbon steel. Although medium and high carbon compositions are available for most high-end applications, low carbon steel remains the most suitable composition for most applications. The low carbon composition is easily machinable and can be conveniently forged and shaped. Moreover, it is a cheap alternative to most other machinable metals and frequently used for many applications. It is conveniently used in many applications that require to reduce cost as well as be shaped or machined. In this context, steel is a common substrate material that has been conveniently used in many coatings and thin film applications. There are different grades of steel that may be suitable for different applications. In this context, this paper aims to identify common grades of commercially available steel and elucidate their structure–property correlate. The two most commonly used grades of steel as substrates for deposition are AISI 304 and 304 grades. These are commonly used for welding [1] tribological components [2] and for coating application used in thin film applications [3]. Coatings on low carbon steel are done to improve the corrosion resistance of low carbon steel [4, 5]. The corrosion performance of low carbon steel has been explored to be poor which will eventually lead to stress corrosion cracking and failure [6, 7]. The poor performance of the coatings is mostly responsible for advanced material coatings that can be provided on these cheap substrates to improve their performance. The method of fabrication of the coatings may be varied as dip coating [8], sol–gel [9], powder metallurgy [10, 11], thermal spraying [12], plasma coatings [13], laser cladding [14], sputtering/physical vapor deposition [15, 16], chemical vapor deposition [17], and electrochemical deposition [18]. The selection of the right low steel carbon component for the different applications, mentioned above, depends entirely on the properties of the carbon steel. While Malik et al. [6] and Mohammadi [7] have discussed the effects of erosion-corrosion of AISI 1020, they have not correlated the microstructure–property–performance of the low carbon [19–27]. The structure–property–performance of a material will provide a complete correlation of the material, so that it may be easily selected for different application, either as substrates for coatings or welding or even tribological aspects. This paper thus aims to carry out a complete structure–property–performance correlation for commercially available AISI 1020 and 304 low carbon steel. Therefore, the steel was cleaned and its structure and mechanical properties were evaluated. Then, the corrosion performance of the material (in the form of coupons) was evaluated by the potentiodynamic polarization testing in simulated salt water-like conditions, i.e., 3.5 wt% NaCl solution at ambient temperature and pressure. These results were then correlated and discussed.

2 Materials and Method The composition of the commonly used steel substrates, i.e., AISI 1020 and 304, is given in Table 1. The steel substrates were cleaned with 1500 grit emery paper

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Table 1 The composition of the steel substrates Composition (wt%)

C

Si

Mn

P

S

Ni

AISI 1020

0.17

0.17

0.78

0.04

0.05

0.05

Cr 0.03

Bal

Fe

AISI 304

0.08

0.26

1.76

0.034

0.025

8.01

18.64

Bal

and cleaned in alcohol and ultrasonicated before the potentiodynamic polarization test. The samples were characterized for the microstructure by scanning electron microscopy (SEM, Carl Zeiss, Germany Merlin Compact). The tensile strength of the samples was measured universal testing machine in uniaxial tensile testing mode. The hardness of the samples was evaluated by Vickers indenter (Zwick Roell ZHU), and the roughness of the samples was evaluated by a 3D profilometer (Mitutoyo). The corrosion performance of the sample was analyzed by potentiodynamic polarization test (Metrohms Autolab PGSTAT 302 N). The potentiodynamic scans were done at 0.17 mV/s with Ag/AgCl and Pt wire as the reference electrode and counter electrode, respectively. The mechanism for corrosion was evaluated by scanning the steel surfaces after the potentiodynamic polarization test.

3 Results 3.1 Structure and Mechanical Property Figure 1 shows the microstructure of the steel substrates before corrosion. Similarly, Fig. 2 shows the corresponding microstructure of the sample after the potentiodynamic polarization corrosion test. The surface roughness, Ra , of the steel surfaces, after polishing was 0.2 µm. The hardness of the AISI 1020 steel surface was evaluated to be 195 HV. Similarly, the hardness of AISI 304 was evaluated to be 129 HV. The ultimate tensile strength of the AISI 1020 and 304 samples was evaluated to be 500 MPa and 356 MPa, respectively.

3.2 Corrosion Figures 3 and 4 show the Tafel plot of the AISI 1020 and 304 substrates tested in 3.5 wt% NaCl solution. The corrosion parameters evaluated by the Tafel plot are given in Table 2. The table shows the open circuit potential (OCP), the corrosion potential (E corr ), the corrosion current (icorr ), and the polarization resistance (Rp ) of the steel substrates.

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Fig. 1 SEM micrograph of the a AISI 304SS and b AISI 1020 steel substrate before corrosion

Fig. 2 SEM micrograph of the a AISI 304 and b AISI 1020 steel substrate after corrosion Fig. 3 Tafel plot for AISI 304 substrate in 3.5 wt% NaCl solution

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Fig. 4 Tafel plot for AISI 1020 steel substrate in 3.5 wt% NaCl solution

Table 2 Corrosion parameters obtained from the Tafel plot Sample

OCP (V)

E corr (V)

βa (V dec−1 )

βc (V dec−1 )

icorr (A cm−2 )

Rp (Ω)

AISI 1020

−0.85

−0.81

0.52

−0.91

4.54 × 10–3

114.26

AISI 304

−0.24

−0.38

0.5

−0.8

4.68 × 10–4

80.3

4 Discussion In AISI 304, a stable chromium and nickel composition is always important for maintaining microstructure characteristics and passivity. By passivation, the amount of chromium is tuned to improve corrosion resistance. The creation of an impermeable layer of chromium oxide that protects it against corrosion is known as passivation. Because nickel acts as an austenite phase stabilizer, the steel becomes non-magnetic, making it unsuitable for everyday use. Manganese is an austenite stabilizer as well. Manganese increases its hot working properties while also increasing its hardness, strength, and hardenability. Its machinability is improved with phosphorous and sulfur, but only in small concentrations (0.05 wt%) because these also weaken its corrosion characteristics. In comparison, AISI 1020 is a low carbon steel that negligible amounts of chromium and nickel. Although it does contain some amount of manganese, the relatively low amounts of nickel and chromium render the material susceptible to high degree of corrosion in aqueous and aqueous salt medium. The microstructure of the steel samples before corrosion Figs. 1 and 2 shows uniform dense structure, without the presence of any secondary phases and noticeable porosity. The presence of scratch marks is due to the polishing done to remove any rust, scales, and debris present on the surface. The microstructure after corrosion, shown in Figs. 1 and 2, indicates a high degree of surface degradation for both the

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samples. The AISI 304 samples show degradation of the sample with the presence of debris on the surface due to corrosion. The AISI 1020 steel surface shows the presence of pits that has cracked completely. The AISI 1020 steel surface appears to be more corroded than the AISI 304 surface. This is probably due to the passivation of the AISI 304 surface that reduces the corrosion. The Tafel curves in Figs. 3 and 4 indicate that both the steel samples show active behavior in both anodic as well as cathodic environments. However, the AISI 304 shows a more passive behavior in both the cathodic as well as anodic environments. The AISI 1020 surfaces degrade due to initiation of pits on the surface. Pitting initiates at the surface due to active metal dissolution. The pits increase in size with time and leads to the appearance of microcracks at the site. The microcracks propagate along the grain boundary leading to localized failure. Table 2 shows that the corrosion potential of 304SS is − 0.4 V, whereas that of AISI 1020 is −0.8 V. The higher corrosion potential of 304SS indicates improved corrosion resistance of the material. Moreover, AISI 304 also has lower corrosion current density than AISI 1020, by one order, that indicates its superior corrosion performance. However, the mechanical properties like hardness and ultimate tensile strength of AISI 1020 are appreciably higher than that of 304SS. These mechanical properties in the steel samples are dependent on the degree of plastic deformation of the material. The composition of AISI 1020 samples is favorable for higher amount of plastic deformation in the material, as compared to AISI 304.

5 Conclusion Steel substrates are commonly used for many applications that require structural as well as corrosion properties. There are many commercially available grades of steel that are used for such applications. In these applications, it is imperative that cheaper material, even with poor corrosion resistance, be used that can be coated with corrosion-resistant materials to improve its properties. Among these, two grades of commercially available low carbon steel, i.e., SAE 304SS and AISI 1020 steel, have been identified. These steel surfaces have been evaluated on the basis of microstructure, mechanical properties, and corrosion performance in 3.5 wt% NaCl solution. The mechanical properties, i.e., ultimate tensile strength and hardness, of the samples were evaluated in ambient conditions. It was observed that both the strength and the hardness of the AISI 1020 samples were superior to 304SS. The corrosion performance of the steel samples was evaluated by potentiodynamic polarization test in 3.5 wt% NaCl solution. The corrosion behavior was analyzed by constructing a Tafel plot for the samples. It was observed that the corrosion performance of 304SS was appreciably improved with higher corrosion potential as well as lower corrosion current density. The microstructure of the material examined after the corrosion test shows formation of aggressive corrosion pits leading to localized microcracks on the

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surface for the AISI 1020. Therefore, it suggests that 304SS may be used for marine applications that are subjected to saline conditions.

References 1. Chuaiphan W, Somrerk CA, Niltawach S, Sornil B (2012) Appl Mech Mater 268–270:283–290. https://doi.org/10.4028/www.scientific.net/AMM.268-270.283 2. Masanta M, Shariff SM, Roy Choudhury A (2011) Wear 271(7–8):1124–1133. https://doi.org/ 10.1016/j.wear.2011.05.009 3. Zhang J, Li S, Chenfeng L, Sun C, Shuai P, Xue Q, Lin Y, Huang M (2019) Surf Coat Technol 364(25):265–272. https://doi.org/10.1016/j.surfcoat.2019.02.085 4. Ye Y, Zhang D, Liu T, Liu Z, Pub J, Liu W, Zhao H, Li X, Wang L (2019) Carbon 142:164–176. https://doi.org/10.1016/j.carbon.2018.10.050 5. Zhang D, Wang M, Jiang N, Liu Y, Yu X, Zhang H (2020) Int J Electrochem Sci 15(2):4117– 4126. 10.20962020.05.25 6. Malik J, Toor IH, Ahmed WH, Gasem ZM, Habib MA, Ben-Mansour R, Badr HM (2014) Int J Electrochem Sci 9:6765–6780 7. Mohammadi F (2011) Erosion-corrosion of 304 stainless steel. Doctoral thesis, University of Alberta 8. Cao C, Cheng J (2018) Surf Coat Technol 349:296–302. https://doi.org/10.1016/j.surfcoat. 2018.06.001 9. Alibakhshi E, Akbarian M, Ramezanzadeh M, Ramezanzadeh B, Mahdavian M (2018) Prog Org Coat 123:190–200. https://doi.org/10.1016/j.porgcoat.2018.07.008 10. Martinez MA, Abenojar J, Bahrami M, Velasco F (2021) Metals 11:1007. https://doi.org/10. 3390/met11071007 11. Sathish Sharma G, Sugavaneswaran M, Vijayalakshmi U, Prakash R (2019) Ceram Int 45(10):13456–13463. https://doi.org/10.1016/j.ceramint.2019.04.046 12. Lee H-S, Singh JK (2019) Corros Sci 146:254–268. https://doi.org/10.1016/j.corsci.2018. 10.035 13. Bijalwan P, Kumar A, Nayak SK, Banerjee A, Dutta M, Laha T (2019) J Alloy Compd 796(5):47–54. https://doi.org/10.1016/j.jallcom.2019.05.046 14. Bartkowski D, Bartkowska A, Jurˇci P (2021) Opt Laser Technol 136:106784. https://doi.org/ 10.1016/j.optlastec.2020.106784 15. Zamani MR, Meymiana, Ghaffarinej A, Fazli R, Mehr AK (2020) Colloids Surf A Physicochem Eng Aspects 593:124617. https://doi.org/10.1016/j.colsurfa.2020.124617 16. Calderon S, Almeida Alves CF, Manninen NK, Cavaleiro A, Carvalho S (2019) Coatings 9(10):682. https://doi.org/10.3390/coatings9100682 17. Siddiqui AR, Maurya R, Katiyar PK, Balani K (2020) Surf Coat Technol 404:126421. https:// doi.org/10.1016/j.surfcoat.2020.126421 18. Chanda UK, Behera A, Roy S, Pati S (2018) Int J Hydrogen Energy 43(52):23430–23440. https://doi.org/10.1016/j.ijhydene.2018.10.218 19. Palani V, Kumar A, Vijaya Kumar KR, Kumaran P (2021) Int J Precis Eng Manuf 22:365–372. https://doi.org/10.1007/s12541-020-00458-x 20. He S, Qiu Y, Sun Y, Zhang Z, Cheng J, Gao C, Zhao Z (2020) Int J Greenhouse Gas Control 94:102931. https://doi.org/10.1016/j.ijggc.2019.102931 21. Mandal P, Usha Kiran N, Chanda UK, Pati S, Roy S (2021) SN Appl Sci 3:715. https://doi. org/10.1007/s42452-021-04710-5 22. Abioyeab TE, Ariwoolac OE, Ogedengbec TI, Farayibib PK, Gbadeyan OO (2019) Mater Today Proc 17(3):871–877. https://doi.org/10.1016/j.matpr.2019.06.383 23. Bermeo F, Quintana JP, Kleiman A, Sequeda F, Márquez A (2017) J Phys Conf Ser 792:012061. https://doi.org/10.1088/1742-6596/792/1/012061

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Thermal Buckling Analysis of Tri-directional Functionally Graded Material Plate Mrinal Gautam and Manish Chaturvedi

Abstract Thermal buckling analysis is performed for tri-directional functionally graded material. It is expected that each plate’s material property varies in axial, longitudinal and thickness direction by power law distribution. COMSOL software was used to calculate the thermal buckling behaviour of tri-directional FGM plate. Different boundary conditions, i.e. CCCC and CFCF, are considered. The effect on critical buckling temperature such as power exponent and boundary conditions on FGM plate is considered. Keywords Functionally graded material plate · Thermal buckling analysis · Power law · Finite element method

1 Introduction FGMs (functionally graded materials) are advanced composites with material qualities that vary continuously and smoothly across a structure. In addition, the gradual change of attributes can be adjusted to suit various applications and service situations. The idea of functionally graded material was born out of a need to reduce thermal stresses. FGM applications are in aerospace, sensor and energy, medicine, biomedical, thermal barrier coating and other areas [1–5]. As a result, FGM is employed in this investigation. Kiani and Eslami [6] focused on various types of thermal pressure and buckling of FG beams. Malekzadeh [7] carried out thermal buckling study of arbitrary straightsided quadrilateral plates that have been functionally graded (FG). Tran et al. [8] presented combination of IGA and TSDT for study of FGM under thermal buckling. Shariyat and Asgari [9] performed an adequate distribution of material qualities which can compensate for a reduction in thickness in the axial direction. Gao et al. [10] proposed nonlinear thermal buckling of BFG beams using nonlocal strain graded M. Gautam (B) · M. Chaturvedi University Department, Mechanical Engineering, Rajasthan Technical University, Akelgarh, Kota, Rajasthan 324010, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_15

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theory. Attia and Mohamed [11] determined functionally graded tapered microbeams in bidirectional. Tran et al. [8] investigated to demonstrate the efficiency of the suggested technology and circular and rectangular plates. There is a detailed research on FGM structures available [12–23]. The goal of this task is to analyse the thermal buckling of tri-directional functionally graded material plate.

2 Property Distribution Consider a tri-directional FGM plate with width b, length a and thickness h. The FG plate is made up of two parts: metal and ceramic. In present work, property distribution of the plate continuously varies through all directions, i.e. in x, y and z directions. In this work, the ceramic volume fraction distribution varying according to a power-law form which is represented by the following model. P(z) = (Pc − Pm ) ∗ Vc + Pm Vc =

( x )kx ( y )k y ( z a

b

1 + h 2

(1)

)k z (2)

where a, b and h are the length, width and thickness of the plate. In the axial, longitudinal and thickness directions, the modulus of elasticity P, coefficient of thermal expansion α, mass density p and thermal conductivity κ are expected to vary [25].

3 FEM Modelling In present study, tri-directional FGM plate dimensions are taken, i.e. width b = 1 m, length a = 1 m and thickness h = 0.01 m. Material properties are for metal phase (Aluminium) E m = 70 × 109 Pa, ρ m = 2700 kg/m3 , αm = 23 × 10(−6) 1/K and κ m = 204 W/m.K and for ceramic phase (Alumina (Al2 O3 )) E c = 380 × 109 Pa, ρ c = 3900 kg/m3 , αc = 7.4 × 10(−6) 1/K and κ c = 10.4 W/m.K. Poisson’s ratio and heat capacity for specific heat are taken ν = 0.3 and C p = 900 J/kg.K. There are two types of boundary conditions which are applied on FGM plate. The boundary conditions are clamed. These are CFCF and CCCC. For this FG plate, reference temperature is considered T = 300 K [26].

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4 Results The FGM plate is being considered for the validation research for reference [26] (Fig. 1). In present study, we have taken tri-directional FGM plate dimensions, i.e. width b = 1 m, length a = 1 m and thickness h = 0.01 m. Two materials, i.e. Aluminium and Alumina are taken. Table 1 and Figs. 2 and 3 show the validation for different gradient index under uniform temperature field for clamped FGM plate (a = b = 1 m and h = 0.01 m and h = 0.02 m). In this work, when increase in gradient index (k) than critical buckling temperature (∆T cr ) decrease. As a results shown (Tables 2 and 3 and Figs. 4, 5, 6 and 7), thermal buckling mode shapes for functionally graded plate (a/b = 1 and k x = 2, k y = 2, k z = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 100 and a/h = 50). In that results, CCCC boundary conditions have higher critical buckling temperature than CFCF in first two mode shapes and lower critical buckling temperature than CFCF in 3 and 4 mode shapes. In Tables 4 and 5, when the gradient index in the x and y direction is constant i.e. k x = 0, k y = 0 and gradient index increase 1 to 3 in the z direction i.e. k z = 1 and 3, than critical buckling temperature decrease. For gradient index increase in z direction 3–5 for modes than critical buckling temperature is constant. Fig. 1 Geometry of FGM plate

Table 1 For tri-directional Al2 O3 /Al clamped FG plate (a/b = 1), critical buckling temperature (∆T cr) Boundary conditions

a/h

Present study

CCCC

Zhao et al. [26]

CCCC

(∆T cr) k=0

k = 0.5

k=1

k=2

k=5

50 100

180.12 45.236

103.03 25.876

83.821 21.026

74.256 18.636

74.61 18.716

50 100

175.817 44.171

99.162 24.899

82.357 20.771

71.013 18.489

74.591 19.150

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Fig. 2 Thermal buckling mode shapes for CCCC functionally graded plate (k = 0, 0.5, 1, 2, 5 and a/b = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 50)

5 Conclusion Under uniform temperature loading, the behaviour of thermal buckling of a CCCC and CFCF functionally graded plate is investigated. Property distributions are in thickness, length and width direction in functionally graded plate by power law. Current representation is performed in FEM software COMSOL Multiphysics. Present values are measure up to published value. We have shown that in CCCC FG plate when gradient index increases critical buckling temperature decreases i.e. when gradient index increase 1 to 3 in the z direction i.e. k z = 1 and 3, than critical buckling temperature decrease. In tri-directional functionally graded plate, when the gradient index in the x and y direction is constant i.e. k x = 0, k y = 0 and gradient

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Fig. 3 Thermal buckling mode shapes for CCCC functionally graded plate (k = 0, 0.5, 1, 2, 5 and a/b = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 100) Table 2 Thermal buckling mode shapes for functionally graded plate (a/b = 1 and k x = 2, k y = 2, k z = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 50) Mode shapes 1

CCCC 57.913

CFCF 55.456

2

101.5

3

101.54

112.36

4

140.91

143.88

83.033

Table 3 Thermal buckling mode shapes for functionally graded plate (a/b = 1 and k x = 2, k y = 2, k z = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 100) Mode shapes

CCCC

CFCF

1

14.544

13.916

2

25.561

20.902

3

25.562

28.273

4

35.576

36.265

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Fig. 4 Thermal buckling mode shapes for CCCC functionally graded plate (a/b = 1 and k x = 2, k y = 2, k z = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 50)

Fig. 5 Thermal buckling mode shapes for CFCF functionally graded plate (a/b = 1 and k x = 2, k y = 2, k z = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 50)

Fig. 6 Thermal buckling mode shapes for CCCC functionally graded plate (a/b = 1 and k x = 2, k y = 2, k z = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 100)

Fig. 7 Thermal buckling mode shapes for CFCF functionally graded plate (a/b = 1 and k x = 2, k y = 2, k z = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 100)

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Table 4 Thermal buckling mode shapes for clamped functionally graded plate (a/b = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 50) Mode shapes

k x = 0, k y = 0, k z = 1

kz = 3

kz = 5

1

83.821

73.776

74.61

2

147.12

129.34

130.65

3

147.14

129.4

130.77

4

204.22

179.38

181.04

Table 5 Thermal buckling mode shapes for clamped functionally graded plate (a/b = 1) at critical buckling temperature (∆T cr ) and the thickness ratios (a/h = 100) Mode shapes

k x = 0, k y = 0, k z = 1

kz = 3

kz = 5

1

21.026

18.531

18.716

2

36.981

32.584

32.9

3

36.982

32.585

32.91

4

51.435

45.307

45.757

index increase 1–3 in the z direction i.e. k z = 1 and 3, than critical buckling temperature decrease. For gradient index increase in z direction 3–5 for modes than critical buckling temperature is constant.

References 1. Safri SNA, Sultan MTH, Jawaid M, Jayakrishna K (2018) Impact behaviour of hybrid composites for structural applications: a review. Compos B Eng 133:112–121 2. Mueller E et al (2003) Functionally graded materials for sensor and energy applications. Mater Sci Eng A 362(1–2):17–39 3. Sola A, Bellucci D, Cannillo V (2016) Functionally graded materials for orthopedic applications–an update on design and manufacturing. Biotechnol Adv 34(5):504–531 4. Pompe W et al (2003) Functionally graded materials for biomedical applications. Mater Sci Eng A 362(1–2):40–60 5. Lee WY et al (1996) Concept of functionally graded materials for advanced thermal barrier coating applications. J Am Ceram Soc 79(12):3003–3012 6. Kiani Y, Eslami MR (2010) Thermal buckling analysis of functionally graded material beams. Int J Mech Mater Des 6(3):229–238 7. Malekzadeh P (2011) Three-dimensional thermal buckling analysis of functionally graded arbitrary straight-sided quadrilateral plates using differential quadrature method. Compos Struct 93(4):1246–1254 8. Tran LV, Thai CH, Nguyen-Xuan H (2013) An isogeometric finite element formulation for thermal buckling analysis of functionally graded plates. Finite Elem Anal Des 73:65–76 9. Shariyat M, Asgari D (2013) Nonlinear thermal buckling and postbuckling analyses of imperfect variable thickness temperature-dependent bidirectional functionally graded cylindrical shells. Int J Press Vessels Pip 111:310–320 10. Gao Y, Xiao W-S, Zhu H (2019) Nonlinear thermal buckling of bidirectional functionally graded nanobeams. Struct Eng Mech 71(6):669–682

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11. Attia MA, Mohamed SA (2020) Nonlinear thermal buckling and post-buckling analysis of bidirectional functionally graded tapered microbeams based on Reddy beam theory. Eng Comput 1–30 12. Yu T et al (2016) On the thermal buckling analysis of functionally graded plates with internal defects using extended isogeometric analysis. Compos Struct 136:684–695 13. She G-L, Yuan F-G, Ren Y-R (2017) Thermal buckling and post-buckling analysis of functionally graded beams based on a general higher-order shear deformation theory. Appl Math Model 47:340–357 14. Trabelsi S et al (2019) A modified FSDT-based four nodes finite shell element for thermal buckling analysis of functionally graded plates and cylindrical shells. Eng Struct 178:444–459 15. Daikh AA, Megueni A (2018) Thermal buckling analysis of functionally graded sandwich plates. J Therm Stresses 41(2):139–159 16. Zhang J, Chen S, Zheng W (2020) Dynamic buckling analysis of functionally graded material cylindrical shells under thermal shock. Continuum Mech Thermodyn 32(4):1095–1108 17. Hajlaoui A, Chebbim E, Dammak F (2021) Three-dimensional thermal buckling analysis of functionally graded material structures using a modified FSDT-based solid-shell element. Int J Press Vessels Pip 104547 18. Gautam M, Chaturvedi M (2021) Optimization of FGM composition for better environment material. IOP Conf Ser Mater Sci Eng 1017(1) 19. Gautam M, Chaturvedi M (2021) Optimization of functionally graded material under thermal stresses. Mater Today Proc 44:1520–1523 20. Karpagaraj A et al (2020) The role of laser in manufacturing of shape memory alloy (SMA). IOP Conf Ser Mater Sci Eng 912(3):032008 21. Van Do T et al (2017) Analysis of bi-directional functionally graded plates by FEM and a new third-order shear deformation plate theory. Thin-Walled Struct 119:687–699 22. Chen X et al (2019) Static and dynamic analysis of the postbuckling of bidirectional functionally graded material microbeams. Int J Mech Sci 151:424–443 23. Chen X et al (2019) Nonlinear resonant behaviors of bi-directional functionally graded material microbeams: one-/two-parameter bifurcation analyses. Compos Struct 223:110896 24. Li J, Tang F, Habibi M (2020) Bi-directional thermal buckling and resonance frequency characteristics of a GNP-reinforced composite nanostructure. Eng Comput 1–22 25. Do DTT, Nguyen-Xuan H, Lee J (2020) Material optimization of tri-directional functionally graded plates by using deep neural network and isogeometric multimesh design approach. Appl Math Model 87:501–533 26. Zhao X, Lee YY, Liew KM (2009) Mechanical and thermal buckling analysis of functionally graded plates. Compos Struct 90(2):161–171

Investigation of Modal Analysis of Tri-Directional Functionally Graded Material Plate Mrinal Gautam and Manish Chaturvedi

Abstract The composition and structure of FGM are varied progressively over its volume, resulting in commensurate transforms in the material elements. The COMSOL 5.5 software has created a finite element technique of FGM plate for modal analysis. The thickness, longitudinal, and axial directions of the material properties vary by power law distribution. Primarily, a simulation was run using a model developed by another researcher. The research was carried out on square FGM plates for different boundary conditions. A FEM was used to do modal analysis for various values of power index for different modes. In this study, CCCC boundary condition natural frequencies are higher than CFCF and CFFF. Keywords Functionally graded material plate · Natural frequency · Modal analysis · Finite element method

1 Introduction Functionally graded materials are a relatively new technology that is being investigated for application in components that are subjected to high-temperature gradients. FGMs are composite materials with mechanical properties that change in a smooth and consistent manner along specified axes with meet design criteria such as modulus of elasticity, conductive heat transfer coefficient, density, and other qualities. Modal analysis is a technique for determining the vibration characteristics of a structure: mode forms and natural frequencies. FGM plates are used in thin-walled structural components in spacecraft, nuclear reactors, and other high-temperature applications [1]. The ability of FGMs to alleviate residual stresses is one of the main reasons for their extensive use [2]. Wei et al. [3] examined with axial loading, rotating inertia, and shear deformation, addressing the free vibration of cracked functionally graded material (FGM) beams. M. Gautam (B) · M. Chaturvedi University Department, Mechanical Engineering, Rajasthan Technical University, Akelgarh, Kota, Rajasthan 324010, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_16

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Tornabene and Reddy [4] performed a static analysis of different types of FGM. Hebali et al. [5] developed analysis of FGM plate for static and free vibration using SDT. Attia et al. [6] performed using various four variable refined plate theories, free vibration analysis of functionally graded plates with temperature-dependent features. Bennoun et al. [7] presented FG sandwich plates for vibration analysis. Akba¸s [8] analyzed functionally graded porous plates: vibration and static analysis. In present literature, there is a detailed analysis of FGM structures [9–25]. The primary purpose of this research is to develop a finite element method for modal analysis of tri-directional FGM plates.

2 Material Properties of FGM Functionally graded material plate has two phase, i.e., ceramic and metal. The material properties vary in x, y, and z directions. nx , ny , and nz are power indexes, and h, a, and b are plate thickness, length, and width. (Z ) = (E c − E m ) Vc + E m

(1)

( / )n ( / / )n Vc (x, y, z) = (x / a)n x · y b y · 1 2 + z h z

(2)

wherever E indicates Young’s modulus, ν indicates the Poisson’s ratio, and ρ indicates density [13].

3 FG Plate Modal Analysis In present work, dimensions of the tri-directional FG plate are a = 1 m, b = 1 m, and h = 0.01 m and mechanical property values are as follows: for ceramic part (Alumina (Al2 O3 )) E c = 380 × 109 Pa, ν c = 0.3, and ρ c = 3800 kg/m3 and for metal part (SUS304 stainless steel) E m = 207 × 109 Pa, ν m = 0.3, and ρ m = 8166 kg/m3 in that order [26] (Fig. 1). In current analysis, three types of boundary conditions are applied, i.e., CCCC, CFCF, and CFFF, respectively.

4 Results The results of reference [26] were used to validate the numerical results produced in this investigation (Fig. 2 and Table 1).

Investigation of Modal Analysis of Tri-Directional Functionally …

193

Fig. 1 Model of FGM plate

Fig. 2 For n = 5, for CCCC boundary condition first four mode shapes Table 1 For n = 5, for CCCC boundary condition first four natural frequencies (Hz) of FG plate

Mode shapes

Ref. [13]

Present study

1st

96

100.54

2nd

190

204.89

3rd

190

204.9

4th

282

301.89

194 Table 2 For nx = 2, ny = 2, nz = 3, for different boundary condition, first four natural frequencies (Hz) of tri-directional FG plate

M. Gautam and M. Chaturvedi Mode shapes

CCCC

CFCF

CFFF

1st

51.61

31.897

2nd

105.21

37.869

12.02

3rd

105.21

62.144

30.299

4th

155.3

87.913

38.692

4.9794

As a result of the foregoing findings (Table 2 and Figs. 3, 4 and 5), natural frequency was higher in the CCCC mode than in the CFCF and CFFF modes in each of the first four vibration modes, indicating that increasing the fixturing on a structure also increases natural frequency for power index n. As shown in Tables 3, 4 and 5, the natural frequencies decrease when the power index increases in the z direction, and for every mode, the power index is constant in the x and y directions.

Fig. 3 For nx = 2, ny = 2, nz = 3, CCCC boundary condition first four mode shapes

Fig. 4 For nx = 2, ny = 2, nz = 3, CFCF boundary condition first four mode shapes

Fig. 5 For nx = 2, ny = 2, nz = 3, CFFF boundary condition first four mode shapes

Investigation of Modal Analysis of Tri-Directional Functionally … Table 3 For nx = 0, ny = 0, for CCCC boundary condition, comparison of first four natural frequencies (Hz) of tri-directional FG plate

Table 4 For nx = 0, ny = 0, for CFCF boundary condition, comparison of first four natural frequencies (Hz) of tri-directional FG plate

Table 5 For nx = 0, ny = 0, for CFFF boundary condition, comparison of first four natural frequencies (Hz) of tri-directional FG plate

Mode

nz

1st

105.47

1

3 78.677

195

5 72.637

2nd

215.01

160.37

148.04

3rd

215.01

160.37

148.05

4th

316.87

236.3

218.14

Mode

nz

1st

64.81

48.349

44.646

2nd

76.696

57.212

52.831

3rd

126.46

94.332

87.098

4th

178.79

133.36

123.13

Mode

nz

1st

10.122

7.5531

6.975

2nd

24.421

18.22

16.824

3rd

61.696

46.034

42.509

4th

78.976

58.929

54.414

5 Conclusion Initially, a FEM analysis was performed in the same way as other studies. COMSOL Multiphysics was used to do a modal analysis of a tri-directional FGM plate. Investigation of modal analysis of tri-directional functionally graded material plate is taken into account. Mechanical properties varied in x, y, and z directions in that order. Natural frequencies decrease as the power index increases in the z direction, and for every mode, the power index is constant in the x and y directions. Natural frequencies were higher in the CCCC mode than in the CFCF and CFFF modes.

References 1. Bendine K, Boukhoulda BF, Nouari M, Satla Z (2016) Structural modeling and active vibration control of smart FGM plate through ANSYS. Int J Comput Methods 14(2):1750042–1750059 2. Lee YD, Erdogan F (1994) Residual/thermal stresses in FGM and laminated thermal barrier coatings. Int J Fract 69:145–165 3. Wei D, Liu Y, Xiang Z (2012) An analytical method for free vibration analysis of functionally graded beams with edge cracks. J Sound Vibr 331:1686–1700

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4. Tornabene F, Reddy JN (2013) FGM and laminated doubly-curved and degenerate shells resting on nonlinear elastic foundations: a GDQ solution for static analysis with a posteriori stress and strain recovery. World J Mech 93(4):635–688 5. Hebali H et al (2014) New quasi-3D hyperbolic shear deformation theory for the static and free vibration analysis of functionally graded plates. J Eng Mech 140(2):374–383 6. Attia A et al (2015) Free vibration analysis of functionally graded plates with temperaturedependent properties using various four variable refined plate theories. Steel Compos Struct 18(1):187–212 7. Bennoun M, Houari MSA, Tounsi A (2016) A novel five-variable refined plate theory for vibration analysis of functionally graded sandwich plates. Mech Adv Mater Struct 23(4):423– 431 8. Akba¸s SD ¸ (2017) Vibration and static analysis of functionally graded porous plates. J Appl Comput Mech 3(3):199–207 9. Wang YQ (2018) Electro-mechanical vibration analysis of functionally graded piezoelectric porous plates in the translation state. Acta Astronaut 143:263–271 10. Tu TM, Quoc TH, Long NV (2019) Vibration analysis of functionally graded plates using the eight-unknown higher order shear deformation theory in thermal environments. Aerosp Sci Technol 84:698–711 11. Karami B, Shahsavari D (2020) On the forced resonant vibration analysis of functionally graded polymer composite doubly-curved nanoshells reinforced with graphene-nanoplatelets. Comput Methods Appl Mech Eng 359:112767 12. Pham Q-H et al (2021) A nonlocal quasi-3D theory for thermal free vibration analysis of functionally graded material nanoplates resting on elastic foundation. Case Stud Therm Eng 26:101170 13. Do DTT, Nguyen-Xuan H, Lee J (2020) Material optimization of tri-directional functionally graded plates by using deep neural network and isogeometric multimesh design approach. Appl Math Model 87:501–533 14. Sim¸ ¸ sek M (2015) Bi-directional functionally graded materials (BDFGMs) for free and forced vibration of Timoshenko beams with various boundary conditions. Compos Struct 133:968–978 15. Nejad MZ, Hadi A (2016) Non-local analysis of free vibration of bi-directional functionally graded Euler–Bernoulli nano-beams. Int J Eng Sci 105:1–11 16. Van Do T et al (2017) Analysis of bi-directional functionally graded plates by FEM and a new third-order shear deformation plate theory. Thin-Walled Struct 119:687–699 17. Lieu QX et al (2018) Bending and free vibration analyses of in-plane bi-directional functionally graded plates with variable thickness using isogeometric analysis. Compos Struct 192:434–451 18. Karpagaraj A et al (2020) The role of laser in manufacturing of shape memory alloy (SMA). IOP Conf Ser Mater Sci Eng 912(3):032008 19. Tang Y, Ding Q (2019) Nonlinear vibration analysis of a bi-directional functionally graded beam under hygro-thermal loads. Compos Struct 225:111076 20. Tang Y, Lv X, Yang T (2019) Bi-directional functionally graded beams: asymmetric modes and nonlinear free vibration. Compos Part B Eng 156:319–331 21. Wang C et al (2020) Material and shape optimization of bi-directional functionally graded plates by GIGA and an improved multi-objective particle swarm optimization algorithm. Comput Methods Appl Mech Eng 366:113017 22. Saleh B et al (2020) 30 years of functionally graded materials: an overview of manufacturing methods, applications and future challenges. Compos Part B Eng 108376 23. Vinh PV (2021) Analysis of bi-directional functionally graded sandwich plates via higherorder shear deformation theory and finite element method. J Sandwich Struct Mater. 10.1177.10996362211025811 24. Gautam M, Chaturvedi M (2021) Optimization of FGM composition for better environment material. IOP Conf Ser Mater Sci Eng 1017(1)

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25. Gautam M, Chaturvedi M (2021) Optimization of functionally graded material under thermal stresses. Mater Today Proc 44:1520–1523 26. Tabatabaei SJS, Fattahi AM (2020) A finite element method for modal analysis of FGM plates. Mech Based Des Struct Mach 1–12

Modelling of Structural Responses for Pineapple Leaf Fibre Epoxy Composite Partha Pratim Borah , Satadru Kashyap , Sushen Kirtania , and Sanjib Banerjee

Abstract Pineapple leaves are natural fibres with good mechanical properties which are used as the reinforcing phase in natural fibre-based composites. Composites in general sustain a variety of vibrations during their service. This investigation puts forward the modal analysis of pineapple fibre reinforced epoxy composites. The variation of fibre volume fraction has also been studied to see the effect on the mechanical properties. The elastic properties have been determined analytically, while the frequency studies have been made with the aid of finite element modelling. It was observed that volume fraction and aspect played significant effect on the frequency. Lower frequency can cause more fatigue damage to the composite. Keywords Modal analysis · Pineapple fibre reinforced epoxy composite · Finite element modelling

1 Introduction The abusive use of synthetic fibres has caused a lot of recent environmental impact on the living beings. Though there has been recent use of natural fibres for industrial and automation purposes, it still lacks some of the qualities that a synthetic fibre can provide. Cotton, jute and wool are well-established natural fibres that have been used extensively for decades, but slowly new natural fibres are being used widely in medical, aviation and automobile sectors. Alhijari et al. reviewed the properties P. P. Borah (B) · S. Kashyap · S. Kirtania · S. Banerjee Dist.: Sonitpur, Tezpur University, Pin: 784028, P.O: Napaam, Assam, India e-mail: [email protected] S. Kashyap e-mail: [email protected] S. Kirtania e-mail: [email protected] S. Banerjee e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_17

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of luffa fibre while increasing the surface area of fibre by chemical treatments and reducing the water uptake by fibre [1]. Koruk et al. studied the acoustics, sound absorption, transmission losses and damping properties of luffa fibre reinforced composite [2]. Luffa has been extensively used in packaging industries without much processing done to the fibre. Bisen et al. studied luffa fibre composite as an isotropic material calculating the mode shapes for different boundary conditions [3]. Mishra et al. examined the fibre loading condition and its impact resistance for different weight fraction. It was found that for 30% weight fraction, the pineapple leaf fibre exhibits about 80.29 J/m of impact strength [4]. Mohammed et al. presented the physical and mechanical properties of various fibres including pineapple leaf fibres [5]. Pecas et al. reviewed several papers and stated the different fibre properties [6]. Biancolini et al. studied the free vibrations of thin orthotropic rectangular plates for different boundary conditions [7]. Kazanci et al. investigated the nonlinear dynamic behaviour of simply supported laminated composite plates subjected to a load [8]. This research investigates the structural responses generated when a pineapple leaf fibre is reinforced in an epoxy matrix. There has been a lot of studies that have been carried out for the mechanical and thermal properties of natural fibres, but very less attention has been given to the acoustics and vibrational characteristics of a natural fibre composites. Pineapple leaf fibres are also used as acoustic absorber and damping material. For this study, pineapple leaf fibres are used as it is abundantsly available in the Northeast India like Karbi Anglong, North Cachar hills, West and East Garo hills and Barak valley which produce almost 40% of the total pineapple of the country [9]. Pineapple leaf fibres are extensively used in textile industries and automation industries [11]. They are also used in V-belt cord, conveyor belt cord, transmission cloth, air-bag tying cords [11–16]. This research conducts the modal analysis of the pineapple fibre reinforced composites.

2 Methodology To determine the mechanical properties of a unidirectional lamina composite, the density, volume fraction or mass fractions of the composite were calculated analytically [12]. For a conventional homogeneous material, the stress and strain relationship follows Hooke’s law. But in case of composite material, the material becomes heterogeneous as a result of multi-phase composition or laminates.

2.1 Rule of Mixture The elastic constants for the natural fibre composite are found out using rule of mixture method [12]. The longitudinal E 11 and transverse E 22 Young’s modulus of fibre-reinforced composites can be calculated using the following equations.

Modelling of Structural Responses …

201

E 11 = E f V f + E m Vm

(1)

E f Em E m V f + E f Vm

(2)

E 22 =

Major Poisson’s ratio (ν12 ) and minor Poisson’s ratio (ν21 ) can be obtained as; ( ν12 = ν f V f + νm Vm ; ν21 = ν12

E 22 E 11

) (3)

In-plane shear modulus (G 12 ) of the composite can be obtained as; G 12 =

Gm G f G m V f + G f Vm

(4)

where G f , G m are the shear modulus of fibre and matrix, respectively, and can be calculated as; Ef Em ) ; Gm = Gf = ( 2(1 + νm ) 2 1 + νf

(5)

2.2 Stress–Strain Relationship for Two-Dimensional (2D) Unidirectional Lamina and Angle Lamina Most of the structural applications use composite materials in the form of thin laminates. When these thin laminates are considered and if there is no out-of-plane loads applied, then the lamina is under plane state of stress. So, all the out-of-plane stresses are zero under plane stress condition, i.e. σ3 = 0, τ31 = 0 and τ23 = 0 = 0. This gives the Si j values which are called reduced compliance coefficients, and by the compliance matrix [S] and inverting the compliance matrix [S], the reduced stiffness matrix [Q] is obtained as [12]; ⎡

⎤ ⎡ ⎤⎡ ⎤ σ1 Q 11 Q 12 0 ∈1 ⎣ σ2 ⎦ = ⎣ Q 12 Q 22 0 ⎦⎣ ∈2 ⎦ τ12 γ12 0 0 Q 66

(6)

where Q i j is called reduced stiffness coefficients and is related to elastic constants as; Q 11 =

E 11 ν12 E 22 E 22 ; Q 12 = ; Q 22 = ; Q 66 = G 12 1 − ν12 ν21 1 − ν12 ν21 1 − ν12 ν21

(7)

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P. P. Borah et al.

Fig. 1 Local and global axes of an angle lamina

When a 2D angle lamina is considered, the coordinate system used for an angle lamina is shown in Fig. 1. The axes used in 1–2 coordinate systems are known as local axes, and the axes used in x–y coordinate system are called global axes. The angle between two axes is given as θ . . The local and global stresses are related through transformation matrix (T ) as described in Ref. [12]. The expression of global stress and global strain can be written as [12]; ⎡

⎤ ⎡ ⎤⎡ ⎤ Q 11 Q 12 Q 16 σx ∈x ⎣ σ y ⎦ = ⎣ Q 12 Q 22 Q 26 ⎦⎣ ∈ y ⎦ τx y Q 16 Q 26 Q 66 γx y

(8)

where Q i j elements are called transformed reduced stiffness matrix. Jones earlier had discussed the calculations for determining the Q i j elements [12]. For a stack up of laminas in different direction, flexural stiffness Di j and bending stiffness matrix [D] are calculated as follows [8]; ⏋ ( ) 1 ∑⌈ Q i j k h 3k − h 3k−1 3 k=1 n

Di j = ⌈

(9)

⎡

⎤ D11 D12 D16 D = ⎣ D12 D22 D26 ⎦ D16 D26 D66 ⏋

(10)

◦

◦

Since the laminate stack-up considered is cross-ply, i.e. [0/90 /90 /0], hence, the values of D16 = D26 = 0. Figure 2 represents the thickness or height of each lamina in stack-up for calculation of Di j values from Eq. (9).

Modelling of Structural Responses …

203

Fig. 2 Locations of laminas in a laminate

2.3 Kirchhoff–Love Plate Theory The equation of motion using Kirchhoff–love hypothesis for cross-ply orthotropic symmetrically laminated rectangular plates can be written as [10]; D11

∂ 4w ∂ 4w ∂ 2w ∂ 4w + 2(D12 + 2D66 ) 2 2 + D22 4 + ρ 2 = 0 4 ∂x ∂x ∂y ∂y ∂t

(11)

where D11 , D22 , D12 and D66 are flexural stiffness values and can be calculated from Eq. (9). Considering a solution in general form, where A and B are amplitudes [7]; w = W (x, y)(Acosωt + Bsinωt)

(12)

where W is transverse displacement of a point on the plate (along z direction) and ρ, ω, t are mass density of the material, frequency and time, respectively. The following equation in terms of spatial variables only [7], D11

∂4W ∂4W ∂4W + 2D y) + 2(D y) + D (x, ) (x, (x, y) + ∆4 W = 0 12 66 22 ∂x4 ∂ x 2∂ y2 ∂ y4 (13)

where √ ∆2 = ω ρh

(14)

For a rectangular plate simply supported at the four edges, the function for transverse displacement can be expressed by [7];

204

P. P. Borah et al.

W (x, y) =

∞ ∑ ∞ ∑

amn sin(αx)sin(βy)

(15)

m=1 n=1

where α=

nπ mπ ;β = a b

(16)

Here, amn is a mode shape factor, and a and b are length and breadth along x and y axes, respectively. After manipulating Eq. (13) and substituting into Eq. (15), the eigen value equation is obtained as [7]; α 4 D11 + β 4 D22 + 2(D12 + 2D66 )α 2 β 2 = ω2 ρh

(17)

This equation can be used to calculate mode shapes of an orthotropic rectangular plate. For isotropic plate, D11 = D22 = D66 = D12 = D. Then, D is calculated as [7]; D=

E 11 h 3 ( ) 12 1 − ν 2

(18)

Then, the eigen value equation for isotropic plate is obtained as [7]; / ω=

} { D ( mπ )2 ( nπ )2 + ρh a b

(19)

And finally, frequency is calculated as; f =

ω 2π

(20)

3 Finite Element Modelling The modelling of pineapple leaf fibre composite was performed in ANSYS composite PrePost for the design of laminated composite. For the laminates, SHELL181-type element is used in the present FE analysis as the SHELL181 is suitable for the analysis of thin to moderately thick shell structures. The SHELL181 is a four-noded element with six degrees of freedom at each node. For the stack-up cross-ply setup, ◦ ◦ [0/90 /90 /0] is taken as shown in Fig. 3 considering bi-axial loading conditions. The boundary condition for the modal analysis was considered as simply supported

Modelling of Structural Responses …

(a)

205

(b)

Fig. 3 Model of laminated composite material, a stack-up of cross-ply lamina’s, b FE mesh of laminated composite

in all four edges (SSSS). The edges of the plate were selected and were converted to nodal named selection; this helped in applying the boundary condition by selecting a particular set of nodes along the boundary of plate. The nodal displacement along z direction was zero for all four edges of plate, rotation along y was fixed for top and bottom nodal edges, and rotation along x was fixed for left and right nodal edges of plate. Two extra nodes were selected on the plate one at middle (considering plate coordinates), where displacement along x, y was zero and a node at top edge along the y axis where displacement along x was zero.

4 Results and Discussion Modal analysis is done to determine the natural frequencies, mode shapes and mode participation factors. Resonance occurs when natural frequency of the structure matches with the excitation frequency, for some force or load applied, and hence the structure is modified so as to shift the natural frequencies out of the range of excitation frequencies. This helps in conditions where a member is continuous, rather the welding which would cause high stress as it can affect the fatigue life of the structure. High value of participation factors in a direction indicates that mode will likely be excited by the forces or loads in that direction. Participation factor can be found out in the solver output settings. The output also shows effective mass which measures how much mass is associated with each mode; this helps in figuring out which modes are most likely to get excited in the direction of force or loads applied. Bisen et al. [3] experimentally found out the mechanical properties of the luffa mixed with epoxy composite and classified three different classes as based on density and Young’s modulus for each weight fractions. Bisen et al. [3] considered the material to be isotropic and found the mode shapes, which are actually not the precise way of considering the composite. The stacking sequence of lamina is considered as

206

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Table 1 Comparison of present results with Bisen et al. [3] Luffa fibre composite (isotropic), a/b = 1 Simply supported boundary condition Weight fraction

Mode shape

Earlier study

Present study

Natural frequency [3]

Numerical

FEM

3.2

m = 1, n = 1

298.856

298.51

297.93

6.4

m = 1, n = 1

308.005

307.63

307.03

9.6

m = 1, n = 1

328.039

327.73

327.09

◦

◦

[ 0/90 /90 /0] for bi-axial loading conditions of composite. The reason for taking less number of layers (i.e. 4) is to reduce numerical calculation, and this will result in faster yet accurate result while consuming less energy. Finite element analysis has been carried out, and numerical analysis via MATLAB was used to validate the present mode shape result with earlier published paper by Bisen et al. [3] as shown in Table 1. The dimensions of the composite taken by Bisen et al. [3] were 180 × 180 × 5 mm. Here, a/b = 1 denotes the length and breadth of the composite plate, and m, n represents the wave number in x, y directions, respectively. The results generated through numerical analysis (via MATLAB) and the FE analysis (via ANSYS composite PrePost) in the present study satisfactorily correlated well with the results report in Bisen et al. [3]. Hence, the same process is carried out for pineapple leaf fibre composite, where the values of fibre and matrix properties (E f , E m , ρ f , ρm , ν f , νm ) are used to calculate the mechanical properties of composite (E 11 , E 22 , G 12 , ρc , ν12 , ν21 ) numerically via MATLAB code, but in the present study, the volume fraction of pineapple fibre has been considered as 20, 25 and 30%. The obtained values are then used in as the engineering data of composite for further analysis in ANSYS composite PrePost. The reason for considering the same dimension and boundary condition of the composite is that Bisen et al. [3] performed vibration test experimentally for luffabased composite; hence, the modal analysis is performed for pineapple leaf fibre composite with same dimensions. Pineapple leaf fibres have a higher Young’s modulus of 82 (GPa) and a density of 1500 (Kg/m3 ) [5, 6, 11]. Having these values, the orthotropic properties are calculated from above methodology using MATLAB and then the elastic constants found are used in modal analysis to find the mode shapes through FEM analysis (ANSYS) and numerically (MATLAB). Mishra et al. [4] found that for pineapple leaf fibre composite, the maximum impact strength was observed at a weight fraction of 30% (volume fraction of 25%); hence, the volume fraction taken for this study was considered from 20 to 30%. The mesh convergence of composite plate was also performed, it was found that for an element size of 15 mm, mesh has better mesh metric quality with aspect ratio of 1 (best), and by default, the mesh element size was 22.5 mm for the study. The maximum error was found to be 1.25%. The error might be due to the boundary condition used which might have distorted the plate in some orientation. From Table 2, it can be seen that increasing the volume fraction results in increasing the frequency values. The frequency values obtained are likely to get excited by a load or force in

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Table 2 Mode shape results of pineapple leaf fibre composites for different volume fractions Pineapple leaf fibre composite (orthotropic), a/b = 1 Mode shape (1 × 1)

Mode shape (1 × 2)

Mode shape (2 × 2)

Numerical

FEM

Numerical

FEM

Numerical

FEM

20

366.23

368.99

798.80

798.45

1464.9

1483.5

25

388.58

390.99

835.68

834.45

1554.3

1568.4

30

409.83

412.1

872.29

870.5

1639.3

1651.5

Volume fraction (%)

particular direction of mode considering the mode shape obtained; this load or force compared to the luffa fibre composite will be more as the frequency values are more for pineapple leaf fibre composite. Hence, modifying the composite structure as per need will shift the natural frequencies out of phase of excitation frequencies. Considering same volume fractions, the aspect ratio of the composite was increased. Table 3 shows the mode shapes values for an aspect ratio of (a/b = 2) and for (a/b = 3). Figures 4a, 5a and 6a show the isometric view of mode shape 1 × 1, 1 × 2 and 2 × 2, respectively, for 25% volume fraction of fibre composite plate, generated in MATLAB. Figures 4b, 5b and 6b show the front view of mode shape 1 × 1, 1 × 2 and 2 × 2, respectively, for 25% volume fraction of fibre composite plate, generated in finite element modelling. The results that can be drawn out of the above modal analysis are that increasing the volume fraction also increases the Young’s modulus of the composite, as fibre percentage increases and matrix percentage drops [11]. It can be stated that the stiffness of composite also increases with the increase in Young’s modulus. Luffa has a lesser density and Young’s modulus [2] compared to pineapple leaf fibre, also considering less weight fractions, and isotropic behaviour of luffa composite [3] yields a lower frequency value; the lower frequencies have higher displacement or deflection for any component that incurs higher fatigue damage to the component this is likely to get effected easily with smaller value of load or force. Table 3 shows the results of mode shapes (1 × 1) obtained for different aspect ratio. It can be said that as the aspect ratio increases for any component, the frequency decreases. Table 3 Shows the mode shape values for an aspect ratios of (a/b = 2) and for (a/b = 3) Pineapple leaf fibre composite (orthotropic), mode shape (1 × 1) Volume fraction (%)

a/b = 2 Numerical

a/b = 3 FEM

Numerical

FEM

20

199.70

201.5

176.32

177.78

25

208.92

210.7

184.33

185.79

30

218.07

219.8

192.31

193.79

208

P. P. Borah et al.

(a)

(b)

Fig. 4 Mode 1 × 1 for 25% pineapple fibre reinforced composite, a Isometric view of mode 1 × 1 in MATLAB, b Front view of mode 1 × 1 in ANSYS

(a)

(b)

Fig. 5 Mode 1 × 2 for 25% pineapple fibre reinforced composite, a Isometric view of mode 1 × 2 in MATLAB, b Front view of mode 1 × 2 in ANSYS

The research contributes towards finding a possible natural fibre for their use in different industries as a better damping or vibration absorbing material for different structures by reducing the uses of non-renewable-based composites. The future scope of the analysis can be on the dynamic loading of members and studying its vibrational characteristics. Moreover, there are different fibres which have better mechanical and physical properties that can be studied under this domain.

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(a)

209

(b)

Fig. 6 Mode 2 × 2 for 25% pineapple fibre reinforced composite a Isometric view of mode 2 × 2 in MATLAB, b Front view of mode 2 × 2 in ANSYS

5 Conclusions The work presents the fundamental frequency calculations of pineapple leaf fibre reinforced epoxy composite using finite element analysis. Further, the model accuracy has been established by comparing the results numerically with MATLAB code. The generalized conclusions that can be drawn are as follows; • Unlike luffa fibre composite, the addition of the 20, 25 and 30% volume fraction of pineapple leaf fibre in the matrix increases the density of composite. • The stiffness of the pineapple leaf fibre composite increases with the increase of pineapple fibre volume fraction. • The frequency responses for pineapple leaf fibre composite has an increasing trend with increasing volume fraction of fibre. • The lower frequencies yield higher displacement or deflection for any component that incurs higher fatigue damage to the component, and same is true for excessively higher frequencies. • The aspect ratio of composite has a larger effect to frequency output, as aspect ratio increases the frequency decreases.

References 1. Alhijazi M, Safaei B, Zeeshan Q, Asmael M, Eyvazian A, Qin Z (2020) Recent developments in luffa natural fibre composites. Sustainability 12(18):7683. https://doi.org/10.3390/su1218 7683 2. Koruk H, Genç G (2019) Acoustic and mechanical properties of luffa fibre-reinforced biocomposites. In: Mechanical and physical testing of biocomposites, fibre-reinforced composites

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P. P. Borah et al. and hybrid composites. Woodhead Publishing, pp 325–341. https://doi.org/10.1016/B978-008-102292-4.00017-5 Bisen HB, Hirwani CK, Satankar RK, Panda SK, Mehar K, Patel B (2018) Numerical study of frequency and deflection responses of natural fibre (Luffa) reinforced polymer composite and experimental validation. J Nat Fibres. https://doi.org/10.1080/15440478.2018.1503129 Mishra S, Misra M, Tripathy SS, Nayak SK, Mohanty AK (2001) Potentiality of pineapple leaf fibre as reinforcement in PALF-polyester composite: Surface modification and mechanical performance. J Reinf Plast Compos 20(4):321–334. https://doi.org/10.1177/073168401 772678779 Mohammed L, Ansari MN, Pua G, Jawaid M, Islam MS (2015) A review on natural fibre reinforced polymer composite and its applications. Int J Polymer Sci https://doi.org/10.1155/ 2015/243947 Peças P, Carvalho H, Salman H, Leite M (2018) Natural fibre composites and their applications: a review. J Compos Sci 2(4):66. https://doi.org/10.3390/jcs2040066 Biancolini ME, Brutti C, Reccia L (2005) Approximate solution for free vibrations of thin orthotropic rectangular plates. J Sound Vib 288(1–2):321–344. https://doi.org/10.1016/j.jsv. 2005.01.005 Kazancı Z, Mecito˘glu Z (2008) Nonlinear dynamic behavior of simply supported laminated composite plates subjected to blast load. J Sound Vib 317(3–5):883–897. https://doi.org/10. 1016/j.jsv.2008.03.033 Sema A, Maiti CS (2010) Pineapple cultivation in North East India-a prospective venture. In VII International Pineapple Symposium, vol 902, pp 69–78. https://doi.org/10.17660/Act aHortic.2011.902.4 Qatu MS (2004) Vibration of laminated shells and plates. Elsevier Jawaid M, Asim M, Tahir PM, Nasir M (eds) (2020) Pineapple leaf fibres: processing, properties and applications. Springer Nature. https://doi.org/10.1007/978-981-15-1416-6 Jones RM (1999) Mechanics of composite materials. Taylor and Francis. Inc., USA Ramesh R, Arun ST, Mohammed RAP, Satheesh KP, Giridhar D (2020) Experimentation and process parametric optimization of 3d printing of abs-based polymer parts. In: Lecture notes in mechanical engineering, advances in industrial automation and smart manufacturing. Springer, pp 487–496. Ramesh R, Manikandan N, Binoj JS, Palanisamy D, Arulkirubakaran D, Thejasree P, Pavan KA, Subhash RG (2020) Optimization and performance evaluation of PLA polymer material in situ carbon particles on structural properties. Mater Today Proc 39(1):223–229 Thirugnanasambantham KG, Ramesh R, Sankaramoorthy P, Velmurugan A, Kannagi MC, Kishore Reddy V, Chary SK, Mustafa MA, Ramesh Chandra V (2018) Degradation mechanism for high-temperature sliding wear in surface-modified In718 superalloy. Cogent Eng 5:1501864. https://doi.org/10.1080/23311916.2018.1501864 Giridhar D, Ramesh R. (2020) Contact stress evaluation of micro-grooving process of alumina ceramic and validation with acoustic emission parameters. In: Lecture notes in mechanical engineering, advances in industrial automation and smart manufacturing. Springer, pp 597–617

Investigation of Mechanical Properties of Carbon Fiber/Graphene Nanoplatelet/Epoxy Hybrid Nanocomposites Mriganan Madhab Bordoloi , Sushen Kirtania , Satadru Kashyap , and Sanjib Banerjee Abstract Graphene nanoplatelets (GNPs) inherently possess excellent mechanical properties, and this may be employed in the enhancement of the mechanical properties of carbon fiber (CF)/epoxy composites by using them as an additional reinforcing agent. The present work puts forward the investigation of the mechanical properties of CF/GNP/epoxy hybrid nanocomposites. The mechanical properties have been determined for different volume fractions (VF ) of CF and GNP by using the modified Halpin–Tsai model and rule of mixture. It was observed that the mechanical properties such as longitudinal Young’s modulus, transverse Young’s modulus, inplane shear modulus and out-of-plane shear modulus of the CF/GNP/epoxy hybrid nanocomposites increased with increase in VF of GNP in the CF/epoxy composite. On the contrary, the major and minor Poisson’s ratio decreased with increase in VF of GNP in the CF/GNP-epoxy hybrid nanocomposites. However, the minor Poisson’s ratio increases and reaches its maximum value, then decreases with the increase in VF of CF. The analytical results show that for CF/epoxy composite having 45% VF of CF, the longitudinal Young’s modulus, transverse Young’s, in-plane shear modulus and out-of-plane shear modulus increased by 36.79%, 686.84%, 994.53% and 687.18%, respectively, due to adding 9% VF of GNP. However, the major and minor Poisson’s ratio of CF/epoxy composites decreased by 2.75% and 14.47%, respectively for same VF of GNP. Thus, inclusion of GNP significantly improves most of the mechanical properties of the nanocomposites creating a superior material for structural applications. M. M. Bordoloi (B) · S. Kirtania · S. Kashyap · S. Banerjee Department of Mechanical Engineering, Dist.: Sonitpur, Tezpur University, Pin: 784028, P. O: Napaam, Assam, India e-mail: [email protected] S. Kirtania e-mail: [email protected] S. Kashyap e-mail: [email protected] S. Banerjee e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_18

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Keywords Graphene nanoplatelets · Carbon fiber · Hybrid nanocomposites · Mechanical properties

1 Introduction Graphene is an advanced material, known for its distinctive mechanical, electrical, thermal and optical properties. It has a honeycomb structure consisting of repeating design of hexagons, where carbon atoms are covalently bonded by sp2 hybridizations. Graphene has become one of the important researched materials since its discovery by Geim et al. in 2004 [1]. It possesses extraordinary properties. The Young’s modulus, tensile strength and thermal conductivity of graphene are 1 Tpa, 130 Gpa and 5000 Wm−1 K−1 respectively [2]. Therefore, graphene can be used in many applications such as electronics, sensors, automobile and aerospace [2]. Graphene nanoplatelets (GNPs) are the recently invent carbon nanoparticles which consist of small piles of layers of graphene. GNP can have 3 to 45 layers of graphene. Its thickness differ from 1 to 15 nm. The lateral dimension can have maximum value of 50 μm [3]. Mechanical properties could be improved by addition of GNP in matrix since it gets easily disperse into a matrix because of its lesser tendency to get twisted and enhanced specific surface area. GNP can be used as an ideal component for structural nanocomposites due to its good electrical and thermal conductivities, nanometric size, high aspect ratio and lightweight. Hybrid nanocomposites form effective network in strain transferring [4]. Hybrid nanocomposites can be used in high-technology exercises in which high mechanical resilience, efficient energy uses, strength and energy storage are required [5]. Carbon fiber (CF) is a cylindrical fiber having diameter of 5–10 μ m and made mostly out of carbon atom. It has high strength-to-volume ratio because of the crystallization of carbon atoms along the longitudinal direction of the fiber. Carbon fiber reinforced polymer matrix composites (CFRPMCs) exhibit many desirable characteristics such as higher corrosion resistant, lower servicing costs in structural uses. CFRPMCs are now used in different fields such as aerospace, civil and electronic.[6, 7]. CF/epoxy composite materials can be used in aerospace applications as a structural component due to its high mechanical properties. Its mechanical properties are improved by inclusion of GNP. Hadden et al. [8] reported that the volume fraction and dispersion quality of GNP have strong effect on the transverse tensile properties of hybrid composites. Nagar et al. [9] evaluated the mechanical properties of graphene/CNT-epoxy nanocomposites using Halpin–Tsai and Mori–Tanaka models. Mechanical properties of nanocomposites were also evaluated experimentally. Li et al. [10] examined the mechanical and electrical properties of CNT/GNP-epoxy hybrid nanocomposites. Chatterjee et al. [11] studied mechanical reinforcements in epoxy matrix with the addition of CNTs and GNPs. It was reported that the fracture toughness and the flexural modulus increased with increase in weight fraction of GNP in the composites. Giannopoulos et al. [12] investigated the mechanical properties of graphene nanocomposites consist of a hybrid interphase region in between

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matrix and reinforcement. The overall stiffness of the matrix material was observed to increase significantly with the addition of minor volume fraction of graphene. Cho et al. [13] examined the effect of graphite nanoplatelets on the mechanical properties of CF reinforced epoxy nanocomposites and reported the improvement of in-plane shear properties and compressive strength. Many literatures are available on CF, CNT and GNP reinforced composites. However, limited study has been made on the domain of on GNP reinforced hybrid nanocomposites [14–18]. Therefore, the present research investigates the mechanical properties of CF/GNP/epoxy hybrid nanocomposite by using modified Halpin–Tsai model and rule of mixture by considering the VF of CF up to 45% and GNP volume fraction up to 9%.

2 Methodology In this study, the GNP/epoxy is considered as matrix matter, while CF is considered as reinforcing material. It is assumed that in the GNP/epoxy matrix, GNP is randomly aligned and uniformly spread within the epoxy matrix. 2.5 μm, 1.5 μm and 1.5 nm are respectively considered as GNP’s length, width and thickness. The mechanical properties of GNP, CF and epoxy are as in Table 1 [14].

2.1 Mechanical Properties of GNP/Epoxy Nanocomposites The effective Young’s modulus, Poisson’s ratio and shear modulus of the GNP/epoxy composites have been derived by using micromechanical equations [14]. The effective Young’s module (EGM ) of the GNP/epoxy nanocomposite is determined by the modified Halpin–Tsai model as E GM =

) )} ( { ( 5 1 + ξw ηw VGNP 3 1 + ξ L η L VGNP + × EM 8 1 − η L VGNP 8 1 − ηw VGNP

(1)

where E M is the Young’s modulus of the epoxy matrix. VGNP is the volume fraction of graphene nanoplatelets, which can be calculated as: Table 1 Properties of GNP, CF and epoxy Materials Longitudinal Young’s Transverse Young’s Shear modulus (GPa) Poisson’s ratio modulus (GPa) modulus (GPa) GNP

1010

1010

CF

263

19

Epoxy

3

3

425.801

0.186

27.60

0.20

1.119

0.34

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VGNP =

f GNP f GNP + (ρGNP /ρ M )(1 − f GNP )

(2)

where f GNP is the weight fraction of graphene nanoplatelets; ρGNP and ρM are the mass density of GNP and epoxy matrix respectively, and ξ is a measure of fiber reinforcement of the composite materials. The ξ L and ξw are expressed as: (

( ) ) lGNP wGNP ξL = 2 ; ξw = 2 tGNP tGNP

(3)

where lGNP , wGNP and tGNP are the length, width and thickness of GNP. The parameters ηL and ηw are calculated using the following equations: ηL =

(E GNP /E M ) − 1 (E GNP /E M ) − 1 ; ηw = (E GNP /E M ) + ξ L (E GNP /E M ) + ξw

(4)

The Poisson’s ratio (νGM ) of the GNP/epoxy nanocomposite is determined using rule of mixture as: νGM = νGNP VGNP + ν M (1 − VGNP )

(5)

where νGNP and νM are the Poisson’s ratio of GNP and epoxy matrix respectively. The shear modulus (GGM ) of GNP/epoxy nanocomposite is calculated using the following equation: G GM =

E GM 2(1 + νGM )

(6)

2.2 Mechanical Properties of CF/GNP/Epoxy Hybrid Nanocomposite The mechanical properties of CF/GNP/epoxy hybrid nanocomposites are determined using the following micromechanical relations [14]: The longitudinal Young’s modulus can be calculated as: E 11 = E f 11 V f + E GM VGM

(7)

The transverse Young’s modulus can be calculated as: ( E 22 = E GM

) ) ( E f 22 + E GM + E f 22 − E GM V f ) ( E f 22 + E GM − E f 22 − E GM V f

(8)

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The major Poisson’s ratio is given by: ν12 = ν f 12 V f + νGM VGM

(9)

The minor Poisson’s ratio is given by: ( ν23 = ν f 12 V f + νGM VGM

1 + νGM − ν12 E GM /E 11 2 1 − νGM + ν12 νGM E GM /E 11

) (10)

The in-plane shear modulus can be calculated as: ( G 12 = G 13 = G GM

) ) ( G f 12 + G GM + G f 12 − G GM V f ) ( G f 12 + G GM − G f 12 − G GM V f

(11)

The out-of-plane shear modulus can be calculated as: G 23 =

E 22 2(1 + ν23 )

(12)

where E f 11 , E f 22 , ν f 12 , G f 12 and V f are respectively the longitudinal Young’s modulus, transverse Young’s modulus, Poisson’s ratio, shear modulus and the volume fraction of the CF, while VGM is the VF of the GNP/epoxy nanocomposite.

3 Results and Discussion At first, the mechanical properties of carbon fiber( (CF)/epoxy composite have been ) determined for different volume fractions of CF V f . Then the mechanical properties of the CF/GNP/epoxy hybrid nanocomposites were determined by preparing the hybrid composite with different volume fractions of GNP (VGNP ) and then comparing the results between CF/epoxy composites and CF/GNP/epoxy hybrid nanocomposites. In the present study, the V f is considered up to 45% and the VGNP taken as 1%, 3%, 5%, 7% and 9%.

3.1 Longitudinal Young’s Modulus (E11 ) The E 11 of CF/GNP/epoxy hybrid nanocomposite has been determined for different V f and VGNP using Eq. (7) and shown in Table 2. Figure 1 shows the alteration of E 11 of CF/GNP/epoxy hybrid nanocomposite with V f at different given VGNP . It can be observed from Fig. 1 that E 11 increases when CF is added to the pristine epoxy. E 11 further increases upon additions of

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Table 2 Longitudinal Young’s modulus of CF/GNP-epoxy hybrid nanocomposites (GPa) Vf

VGNP 0

0.01

0.03

0.05

0.07

0

3

11.83124

29.55934

47.3755

65.28039

0.05

16

24.38968

41.23137

58.15673

75.16637

0.15

42

49.50655

64.57544

79.71918

94.93833

0.25

68

74.62343

0.35

94

99.74031

0.45

120

124.8572

87.91951

0.09 83.27472 92.26098 110.2335

101.2816

114.7103

128.206

111.2636

122.8441

134.4823

146.1786

134.6076

144.4065

154.2542

164.1511

GNP in the CF/epoxy composite. The pattern of increase is linear. The longitudinal Young’s modulus increases by 433.33% when 5% V f is added to the pristine epoxy. This Young’s modulus further increases when GNP is added to it. In the CF/epoxy composite having 45% CF volume fraction, E 11 increases by 4.03%, 12.17%, 20.34%, 28.55% and 36.79% upon additions of respectively 1%, 3%, 5%, 7% and 9% of GNP in CF/epoxy composites. So, it could be concluded that the E 11 of CF/epoxy composite linearly increases with the inclusions of GNP in the composites.

Fig. 1 Longitudinal Young’s modulus of CF/GNP/epoxy hybrid nanocomposite with varying CF and GNP volume fractions

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3.2 Transverse Young’s Modulus (E22 ) The E 22 of CF/GNP/epoxy hybrid nanocomposite has been determined for different V f and VGNP using Eq. (8). Figure 2 shows the alteration of E 22 in CF/GNP/epoxy hybrid nanocomposite with V f at different given VGNP . It is revealed from Fig. 2 that the E 22 increases when CF is added to the pristine epoxy. E 22 further increases when 1% VGNP is added to the CF/epoxy composite. However, for VGNP above 3%, the E 22 decreases as the V f increases. It may be due to the fact that at higher VGNP , the equivalent Young’s modulus of the GNP/ epoxy matrix (E GM ) has a negative impact on the computation of E 22 . The E 22 is increased by 97.30% when 45% V f is added to the pristine epoxy. The E 22 is further increased by 146.60%, 310.38%, 442.14%, 565.84% and 686.54%, resulting from the additions of respectively 1%, 3%, 5%, 7% and 9%VGNP in CF/epoxy composites for given 45% V f . So, it could be concluded that with the increase of GNP in CF/epoxy composites, the E 22 of CF/GNP/epoxy hybrid nanocomposite increases, however at a particular VGNP in the CF/GNP-epoxy hybrid nanocomposite, the E 22 decreases with the increase in V f .

Fig. 2 Transverse Young’s modulus of CF/GNP/epoxy hybrid nanocomposite with varying CF and GNP volume fractions

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Fig. 3 Major Poisson’s ratio of CF/GNP/epoxy hybrid nanocomposite with varying CF and GNP volume fractions

3.3 Major Poisson’s Ratio (ν12 ) The ν12 of CF/GNP/epoxy hybrid nanocomposite has been determined for different V f and VGNP using Eq. (9). Figure 3 shows the alteration of ν12 in CF/GNP/epoxy hybrid nanocomposite with V f at different given VGNP . It is revealed from the Fig. 3 that the ν12 decreases when CF is added to the pristine epoxy. It is further decreased when GNP is added to the CF/epoxy composite. However, the margin of decrease is insignificant, and the pattern is linear. The ν12 decreases by 18.52% when 45% V f is added to the pristine epoxy. The ratio is further decreased by 0.31%, 0.92%, 1.52%, 2.16% and 2.75% for the addition of respectively 1%, 3%, 5%, 7% and 9% of GNP in CF/epoxy composites for 45% V f . So, it could be concluded that ν12 decreases when GNP is added to CF/epoxy composites.

3.4 Minor Poisson’s Ratio (ν23 ) The ν23 of CF/GNP/epoxy hybrid nanocomposite has been determined for different V f and VGNP using Eq. (10). Figure 4 shows the alteration of minor Poisson’s ratio of CF/GNP/epoxy hybrid nanocomposite with V f at different given VGNP .

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Fig. 4 Minor Poisson’s ratio of CF/GNP/epoxy hybrid nanocomposite with varying CF and GNP volume fractions

It is revealed from Fig. 4 that the ν23 initially increases, and later decreases with the inclusion of CF to the pristine epoxy. It is also revealed that the ν23 decreases with the inclusion of GNP in CF/epoxy composites. This is due to the fact that as ν23 depends on the E 11 of the hybrid nanocomposite, with the increase in V f , E 11 have negative impact on the computation of minor Poisson’s ratio. The ν23 increases by 9.15% when 45% V f is added to the pristine epoxy. The ratio is decreased by 2.14%, 5.93%, 9.17%, 11.99% and 14.47% for the additions of respectively 1%, 3%, 5%, 7% and 9% of GNP in CF/epoxy composites for the given 45% V f . So, it could be concluded that the ν23 decreases when GNP is added to CF/epoxy composite. But for a particular volume fraction of GNP, the ν23 initially increases, until it reaches its maximum value, and lastly decreases with the increase in V f in CF/GNP/epoxy hybrid nanocomposites.

3.5 In-Plane Shear Modulus (G 12 ) The G 12 of CF/GNP/epoxy hybrid nanocomposite has been determined for different V f and VG N P using Eq. (11). Figure 5 shows the alteration of G 12 of CF/GNP/epoxy hybrid nanocomposite with V f at different VG N P .

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Fig. 5 In-plane shear modulus of CF/GNP/epoxy hybrid nanocomposite with varying CF and GNP volume fractions

It is revealed from the Fig. 5 that the G 12 increases when CF is added to the pristine epoxy, and this modulus increases further when GNP is added to the CF/epoxy composite. Up to 7% VGNP , the G 12 of the hybrid composite increases with the rise in V f . But, at 9% VGNP , the in-plane shear modulus decreases as the V f increases. It is due to the fact that at higher GNP volume fractions, the equivalent shear modulus of GNP/epoxy matrix has a negative impact in the calculation of the G 12 . The G 12 is increased by 141.83% when 45% V f is added to the pristine epoxy. This modulus is further increased by 221.04%, 503.64%, 698.50%, 856.03% and 994.53% for the additions of respectively 1%, 3%, 5%, 7% and 9% VGNP in CF/epoxy composites for a given 45% V f . So, it could be concluded that the G 12 is also increased when GNP is added to CF/epoxy composites.

3.6 Out-of-Plane Shear Modulus (G 23 ) The G 23 of CF/GNP/epoxy hybrid nanocomposite has been determined for different V f and VG N P using Eq. (12). Figure 6 shows the alteration of G 23 of CF/GNP/epoxy hybrid nanocomposite with V f at different VGNP . It may be observed from the Fig. 6 that the G 23 increases when CF is added to the pristine epoxy. This modulus further increases when 1% VGNP is added to the

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Fig. 6 Out-of-plane shear modulus of CF/GNP/epoxy hybrid nanocomposite with varying CF and GNP volume fractions

CF/epoxy composite. But for VGNP above 3%, the G 23 decreases as the V f increases in CF/GNP-epoxy hybrid nanocomposite. It is due to the fact that as the G 23 depends upon the E 22 and ν23 , at higher GNP volume fraction, as the CF volume fraction increases, both E 22 and ν23 decrease. The G 23 is increased by 92.41% when 45% V f is added to the pristine epoxy. This modulus further increases by 146.60%, 310.51%, 442.68%, 567.16% and 687.18% with the additions of respectively 1%, 3%, 5%, 7% and 9% VGNP in CF/epoxy composites for given 45% V f . So, it could be concluded that with the inclusion of GNP in CF/epoxy composites, the G 23 of CF/GNP/epoxy hybrid nanocomposite increases, however at VGNP in the CF/GNP-epoxy hybrid nanocomposite, the G 23 decreases with the increase in V f . Limited research has been reported on hybrid nanocomposites and even fewer on on CF/GNP/epoxy hybrid nanocomposites. The present study determined all the mechanical properties of CF/GNP/epoxy hybrid nanocomposites as a function of volume fraction of the reinforcing agents, i.e. effect of volume fraction of CF and GNP on the mechanical properties of CF/GNP/epoxy hybrid nanocomposites has been investigated. Hence, these calculated mechanical properties of CF/GNP/epoxy hybrid nanocomposite could be further used for stress analysis of hybrid nanocomposites.

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4 Conclusions The evaluation of the mechanical properties ( ) of CF/GNP/epoxy hybrid nanocomposite with different volume fractions of CF V f and GNP (VGNP ) is presented in this study. The CF is considered as the fiber, while GNP/epoxy is considered as the matrix matter. The important conclusions found from the present study on the mechanical properties of the hybrid nanocomposites are listed below: • The longitudinal Young’s modulus (E 11 ) increases linearly with the inclusion of CF in the CF/epoxy composite for different VGNP . It is further increased due to addition of GNP in CF/epoxy composite. • The transverse Young’s modulus (E 22 ) increases with the inclusion of GNP in the CF/epoxy composite, however, for a given VGNP in the CF/GNP/epoxy hybrid nanocomposite, the E 22 decreases with the increase in V f . • The major Poisson’s ratio (ν12 ) decreases with the inclusion of GNP in the CF/epoxy composite. • The minor Poisson’s ratio (ν23 ) decreases with the inclusion of GNP in the CF/epoxy composite. But for a given VGNP , the ν23 initially increases, until it reaches its maximum value, and later decreases with the increase in V f in CF/GNP/epoxy hybrid nanocomposites. • The in-plane shear modulus (G 12 ) increases with the inclusion of GNP in the CF/epoxy composite. • The out-of-plane shear modulus (G 23 ) increases with the inclusion of GNP in the CF/epoxy composite. However, at high VGNP , the G 23 decreases with the increase in Vf .

References 1. Geim AK, Novoselov KS (2007) The rise of graphene. Nat Mater 6:183–191 2. Wang TY, Tseng PY, Tsai JL (2019) Characterization of Young’s modulus and thermal conductivity of graphene/epoxy nanocomposites. J Compos Mater 53(6):835–847 3. Bhadauria A, Singh LK, Laha T (2019) Combined strengthening effect of nanocrystalline matrix and graphene nanoplatelet reinforcement on the mechanical properties of spark plasma sintered aluminium based nanocomposites. Material Science & Engineering A 749:14–26 4. Zarasvand KA, Golestanian H (2017) Investigating the effects of number and distribution of GNP layers on graphene reinforced polymer properties: physical, numerical and micromechanical methods. Compos Sci Technol 139:117–126 5. Dusoe KJ, Ye X, Kisslinger K, Stein A, Lee SW, Nam CY (2017) Ultrahigh elastic strain energy storage in metal-oxide-infiltrated patterned hybrid polymer nanocomposites. Nano Lett 17:7416–7423 6. Yancey RN, Pindera MJ (1990) Micromechanical analysis of the creep response of unidirectional composites. J Eng Mater Technol 112:157–163 7. Gibson RF (1992) Damping characteristics of composite materials and structures. J Mater Eng Perform 1(1):11–20

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8. Hadden CM, McDonald DRK, Pineda EJ, King JA, Reichanadter AM, Miskioglu I, Gowtham S, Odegard GM (2015) Mechanical properties of graphene nanoplatelet/carbon fiber/epoxy hybrid composites: Multiscale modeling and experiments. Carbon 95:100–112 9. Nagar S, Sharma K, Kukreja N, Shukla MK (2020) Micromechanical and experimental analysis of mechanical properties of graphene/CNT epoxy composites. Materials Today: Proceedings 26:1855–1863 10. Li J, Wong PS, Kim JK (2008) Hybrid nanocomposites containing carbon nanotubes and graphite nanoplatelets. Material Science and Engineering A 483–484:660–663 11. Chatterjee, S., Nafezarefi, F., Tai, N. H., Schlagenhauf, L., Nuesch, F. A., Chu. B. T. T.: Size and synergy effects of nanofiller hybrids including graphene nanoplatelets and carbon nanotubes in mechanical properties of epoxy composites. Carbon 50, 5380–5386 (2012). 12. Giannopoulos GI, Kallivokas IG (2014) Mechanical properties of graphene based nanocomposites incorporating a hybrid interphase. Finite Elem Anal Des 90:31–40 13. Cho J, Chen JY, Daniel IM (2007) Mechanical enhancement of carbon fiber/epoxy composites by graphite nanoplatelet reinforcement. Scripta Mater 56:685–688 14. Jeawon Y, Drosopoulos GA, Foutsitzi G, Stravroulakis GE, Adali S (2021) Optimization and analysis of frequencies of multi-scale graphene/fibre reinforced nanocomposite laminates with non-uniform distributions of reinforcements. Eng Struct 228:111525 15. Ramesh, R., Arun, S. T., Mohammed R. A. P., Satheesh, K.P., Giridhar, D. (2020). Experimentation and Process Parametric Optimization of 3D Printing of ABS-Based Polymer Parts, Springer - Lecture Notes in Mechanical Engineering, Advances in Industrial Automation and Smart Manufacturing, 487–496. 16. Ramesh R, Manikandan N, Binoj JS, Palanisamy D, Arulkirubakaran D, Thejasree P, Pavan KA, Subhash RG (2020) Optimization and performance evaluation of PLA polymer material in situ carbon particles on structural properties. Materials Today proceedings 39(1):223–229 17. Thirugnanasambantham KG, Ramesh R, Sankaramoorthy P, Velmurugan A, Kannagi MC, Kishore Reddy V, Chary SK, Mustafa MA, Ramesh Chandra V (2018) Degradation mechanism for high-temperature sliding wear in surface-modified In718 superalloy. Cogent Engineering 5:1501864. https://doi.org/10.1080/23311916.2018.1501864 18. Giridhar, D., Ramesh, R., (2020). Contact Stress Evaluation of Micro-Grooving Process of Alumina Ceramic and Validation with Acoustic Emission Parameters, Springer - Lecture Notes in Mechanical Engineering, Advances in Industrial Automation and Smart Manufacturing, 597–617.

Finite Element Analysis of Natural Hemp Fiber-Based Composite for Semi-elliptical Multi-leaf Spring Bitu Moni Das , Sushen Kirtania , Sanjib Banerjee , and Satadru Kashyap

Abstract Leaf spring is the most integral part of suspension system in a commercial heavy-duty vehicle, which is used to absorb the energy caused by unevenness of the road. One of the most commonly used materials for leaf spring is 55Si2Mn90 grade steel. However, by employing light-weight composite materials, fuel consumption of vehicles can be improved. In this research work, a new model of leaf spring is proposed with four leaves and its stress analysis is carried out using finite element method. The proposed composite leaf spring consists of conventional steel material (grade 55Si2Mn90) at the top and bottom, while the other two leaves at the middle are made of hemp fiber/epoxy composite material. From the finite element analysis, it is found that there is a weight reduction of 37% when composite material is used. The stresses produced by the full capacity loaded vehicle are less than the yield strength of the composite leaf. Moreover, the maximum permissible load is four times than the load carrying capacity of the vehicle. Such observation highlights the capability and applicability of the present proposed design of the composite leaf spring, for safely incorporating in the vehicle. Keywords Leaf spring · Finite element analysis · Natural fiber · Hemp fiber/epoxy composite

B. M. Das (B) · S. Kirtania · S. Banerjee · S. Kashyap Department of Mechanical Engineering, Sonitpur, Tezpur University, 784028, Napam, Assam, India e-mail: [email protected] S. Kirtania e-mail: [email protected] S. Banerjee e-mail: [email protected] S. Kashyap e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_19

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1 Introduction In today’s automobile industries, the reduction in weight while maintaining the safety and strength of components is of prime importance and hence has a major impact in the design. Composite materials are attracting manufacturers due to its high strengthto-weight ratio and light weight. Hence, many industries nowadays are showing greater interest in using composite materials instead of conventional steel. In today’s world, conservation of natural non-renewable fuel resources is of great need. To meet this requirement, automobile industries have been trying to reduce the weight of vehicles. However, it is also necessary to use materials with high strength-to-weight ratio, so that reduction in weight does not lead to lower mechanical properties. The suspension springs of a vehicle are a potential candidate for weight reduction in automobiles as it results in reducing the unsprung weight of the vehicle. Tanabe et al. [1] reported that leaf springs contribute 10 to 20% of the unsprung weight. Ride characteristics and fuel efficiency can be improved by reducing this weight. Rajendran and Vijayaranjan [2] used genetic algorithm to optimize the design parameters of a leaf spring made of glass fiber and reported that by using composite materials, the overall weight of the vehicle can be reduced without tempering the performance. Many researchers used synthetic glass or hybrid fibers in designing leaf springs for light to moderate capacity vehicles. Seralathan et al. [3] performed FE analysis of three leaf springs, i.e. steel, fiber glass and a hybrid composite material, with glass and steel as reinforcement. They reported 34% and 60% reduction in mass and principal stress, respectively, in case of the hybrid material. Soliman [4] investigated the modal and the static analysis of a carbon fiber composite leaf spring and reported that the carbon fiber composite leaf spring shows better characteristics such as less weight, lower stress and higher frequencies as compared to steel leaf spring. In recent years, natural fibers are getting more attention because of its light weight, low cost and better environmental impact compared to synthetic fibers. Natural fiberbased composite materials have been widely applied in society due to their environmental sustainability. The most accountable reason for using natural fibers is that they are renewable as well as biodegradable. This is in contrast with petroleum-based reinforcing agents, which are non-renewable and substantially have a high carbon footprint. Lofti et al. [5] show promising implementation of natural fiber composites replacing synthetic and non-renewable fibers with the use of proper processing techniques, because of its encouraging high strength-to-weight and stiffness-to-weight ratios, lower density, excellent insulation and, above all, biodegradability. Although there are many works on leaf spring made with synthetic fibers composites, little has been done on natural fiber-based composites. Varma et al. [6] used hybrid flax/carbon fibers to design a leaf spring and observed 93% increase in natural frequency and also reported that the introduction of natural flax fibers increases the factor of safety and strain energy. Kumar et al. [7] fabricated a composite mono-leaf spring using hand layup technique. They reported that composite leaf spring reduced the weight up to 75% compared to steel. Shahzad [8] investigated the suitability

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of hemp fiber as an alternative material for glass fiber in light-weight applications and reported the aspect ratio (length/diameter) of hemp fiber as 549. Saba et al. [9] reported that natural fiber reinforced epoxy resin provides better performance for automobile products and their components. The authors also emphasized on implementing natural fiber reinforcement as an alternative material to synthetic fibers due to its lesser density, weight and cost. Also, natural fiber composites are renewable and biodegradable. Thus, the aim of this work is to design a leaf spring implementing hemp fiber reinforced epoxy composite leaves in the inner middle, along with steel leaves at the outer, together satisfying the recommended strength but reduced weight to improve the vehicle efficiency.

2 Materials and Methods In this present work, hemp fiber is considered as the reinforcement and epoxy resin is considered as the matrix material. This hemp fiber reinforced epoxy composite is chosen as the two inner layers of the leaf spring, while conventional steel (grade 55Si2Mn90) is chosen as the two outer layers of the four-layer leaf spring. The properties of steel, epoxy resin and hemp fiber [3, 8, 10, 11] are listed in Table 1. The composite chosen consists of hemp fiber with a volume fraction of 45% as the reinforcement in an epoxy resin matrix. Kalaprasad et al. [12] investigated that to determine the mechanical properties of continuous unidirectional composite, the Halpin–Tsai model shows good correlation with the experimental results. Hence, for the present study, Halpin–Tsai model has been used to determine the properties of composite material. According to Halpin–Tsai model, Young’s modulus and the yield strength of the composite can be evaluated using the following relations: ( Mc = Mm ( Tc = Tm

Table 1 Properties of steel, epoxy resin and hemp fiber

1 + Aη1 V f 1 − η1 V f

1 + A η2 V f 1 − η2 V f

Properties

) (1) ) (2)

55Si2Mn90 steel Hemp fiber Epoxy

Young’s modulus 210 [3] (GPa)

70 [10]

5 [11]

Yield strength (MPa)

920 [8]

73 [11]

1500 [3]

Poisson’s ratio

0.3 [3]

0.34 [10]

0.3 [11]

Density (kg/m3 )

7860 [3]

1480 [10]

1160 [11]

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where ( η1 = ( η2 =

Mf Mm Mf Mm Tf Tm Tf Tm

A=

−1

) (3)

+A −1

)

+A 2l d

(4)

(5)

where Mc , Mm and M f denote the modulus of elasticity (Young’s modulus) of composite material, matrix material and fiber, respectively; Tc , Tm and T f denote the yield strength of the composite material, matrix material and fiber, respectively; V f denotes the fiber volume fraction; and l and d denote the fiber length and diameter, respectively. A is the measure of fiber geometry. Poisson’s ratio and density are computed using rule of mixture: νc = ν f V f + νm Vm

(6)

ρc = ρ f V f + ρm Vm

(7)

where ρc , ρ f and ρm represent density of composite, fiber and matrix, respectively; νc , ν f and νm represent Poisson’s ratio of composite material, fiber and matrix, respectively. The aspect ratio (l/d) for hemp fiber is taken as 549 [8]. Implementing the required data in Eq. (1) to (7), the properties of the hemp/epoxy composite with 45% volume fraction of fiber are calculated. Mc , Tc , νc and ρc of the composite are evaluated as, respectively, 34.08 GPa, 453.87 MPa, 0.318 and 1304 kg/m3 .

3 Finite Element Modeling The proposed model of the leaf spring is considered for TATA ACE commercial vehicle [13]. The curb weight, maximum gross vehicle weight and force on one wheel are 865 kg, 1615 kg and 3961 N, respectively. For safety purpose, the load on one wheel is taken as 4010 N. The 3D model of the spring is designed in AutoCAD and imported as STEP file in ANSYS for finite element (FE) analysis [14–19]. The element used for FE analysis is SOLID 186, which is a 20-node higher order 3D element [4]. This element can be used for large deflection, stress stiffening, plasticity and creep. The element is defined by three degrees of freedom per node: translations along nodal x, y and z directions. For FE simulation of contact surfaces, no separate condition is used. In no separation condition, sliding between two contact

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surfaces is allowed but the surfaces do not get separated when load is applied. For the contact surfaces, CONTA174 and TARGE170 elements are used. These are 3D surface elements and are used to represent sliding between 3D contact surfaces. An isometric view of the spring leaf is shown in Fig. 1. The boundary conditions applied for FE analysis [14] are listed in Table 2. The load applied is 4010 N, which is applied on the bottom leaf. The design parameters of TATA ACE commercial vehicle [13] are listed in Table 3.

Fig. 1 Isometric view of the steel leaf spring

Table 2 Boundary conditions

Table 3 Design specifications of conventional steel leaf spring

Degree of freedom

Left eye

Right eye (shackle)

Translation constrained

x, y and z directions

y and z directions

Rotation constrained

x and y directions

x and y directions

Translation free

–

x direction

Rotation free

z direction

z direction

Parameters (mm)

Value

Parameters

Value

Full length

930

Number of leaves

4

Width

60

Eye diameter (mm)

40

Thickness (for steel)

8

Camber height (mm)

83

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Fig. 2 Front view of the leaf spring along with boundary conditions

Fig. 3 Finite element meshing of the leaf spring

Figure 2 shows front view of the leaf spring along with the boundary conditions. The mesh convergence study is done, and the element size is obtained as 5 mm. Figure 3 shows FE meshing of the leaf spring. There are 22,968 numbers of elements and 1,20,780 numbers of nodes.

4 Results and Discussion For the present work,s conventional steel (55Si2Mn90) leaf spring and a hemp fiberbased composite leaf spring have been considered, and FE analysis has been done to examine the von Misses stress and the deformation on the leaf springs.

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4.1 Conventional Steel Leaf Spring The von Misses stresses on the conventional steel leaf spring are shown in Fig. 4. It can be observed from Fig. 4 that the maximum von Misses stress produced on the steel leaf spring is 310.61 MPa. It is also observed from the Fig. 4 that the stresses are evenly distributed among the four leaves. The mass of the conventional steel leaf is 10.981 kg as obtained from ANSYS. Figure 5 shows the deformation in y direction of the conventional steel leaf spring. From Fig. 5, it can be observed that the maximum deformation along y direction is 31.395 mm. It is also observed that the maximum deformation is on the center region of the leaf spring.

Fig. 4 The von Misses stresses on steel leaf spring

Fig. 5 Deformation along y-axis on steel leaf spring

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4.2 Composite Leaf Spring Figure 6 shows the proposed model where the leaves 2 and 3 are replaced with hemp/epoxy composite material. The steel leaves at the bottom and top are used to prevent chipping and protect the composite as natural fiber composites are susceptible to abrasion. The outer steel leaves will protect the inner composite leaves from harsh road conditions also. The thickness of the hemp/epoxy leaves is determined using the following relation [15], which gives the maximum stress produced in a leaf spring: σ =

6F L nbt 2

(8)

where F = load , L = maximum span (distance from eye to eye), n = number of 2 leaves, b = width and t = thickness. Using Eq. (8) and specification of the leaf spring as listed in Table 3, thickness of the composite leaves is found as 10.03 mm, based on the yield strength of the composite material. The von Misses stress produced on the composite leaf spring is shown in Fig. 7. It can be observed that the maximum von Misses stress produced on composite leaf spring is 384.48 MPa. The mass of the hemp/epoxy composite model is 6.908 kg as obtained from ANSYS. It can also be observed that the von Misses stresses are concentrated on the steel leaves. The maximum vertical deformation along y-axis on the composite leaf spring is shown in Fig. 8. It can be observed that the maximum deformation along y-axis is 43.142 mm. It can also be observed that maximum deformation occurs mostly at the center region.

Fig. 6 Proposed model with hemp/epoxy composite leaf spring

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Fig. 7 The von Misses stress on composite leaf spring

Fig. 8 Deformation of composite leaf spring along y direction

4.3 Hemp/Epoxy Composite Leaves Finite element analysis of the individual hemp/epoxy composite leaves was also performed for the same loading condition. Figures 9 and 10 show the von Misses stress of hemp/epoxy composite for leaf numbers 2 and 3, respectively. From these figures, it can be observed that von Misses stresses on composite leaves are 88.689 MPa and 100.48 MPa on leaf numbers 2 and 3, respectively. But the Tc of the hemp/epoxy composite material is 453.87 MPa. Therefore, von Misses stress produced in the composites is less than the yield strength of the composite. So, it can be concluded that the present hemp/epoxy composite leaves are safe for further applications.

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Fig. 9 The von Misses stress on leaf number 2 of the composite leaf spring

Fig. 10 The von Misses stress on leaf number 3 of the composite leaf spring

4.4 Maximum Permissible Load Finite element analysis is also done to determine the maximum permissible load for the composite leaf spring. It is done by increasing the load gradually until the leaf fails. It is observed that for a load of 15,650 N, the von Misses stress at the top leaf exceeds the yield strength of conventional steel, but for the hemp/composite leaves, it is less than Tc of the hemp/epoxy composite material. The maximum von Misses stress on the leaf spring is equal to 1500.5 MPa when 15,650 N load is applied. But the yield strength of conventional steel is 1500 MPa. So, the steel leaf fails. It is observed that at 15,000 N load, the von Misses stresses produced on both conventional steel leaves and hemp/epoxy composite leaves are less than the respective yield strengths. Therefore, the maximum permissible load of the composite leaf

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450 384.48

400 350

310.61

300 250 200 150 100

31.195 43.142

50 0

10.981 6.908

Von-misses stress (MPa)

Deformation along y Mass (kg) direction (mm) Conventional steel leaf spring Hemp/epoxy composite leaf spring

Fig. 11 Comparison of conventional steel and hemp/epoxy composite leaf springs

spring is 15,000 N, which is approximately four times than the load carrying capacity of TATA ACE commercial vehicle (3961 N). A comparison between the conventional steel (55Si2Mn90) and the proposed composite leaf spring is shown in Fig. 11. It can be observed that the von Misses stress and vertical deformation produced in composite leaf spring are more than the conventional steel leaf. Also, the von Misses stresses produced on the hemp composite leaves are less than the yield strength of hemp/epoxy composite; hence, the design may be considered as safe. The mass of the proposed composite leaf spring is 6.908 kg, which is 37% less than the conventional steel leaf spring. This will help to reduce the unsprung weight, which in turn will increase the fuel efficiency. As in this work, instead of using synthetic glass fiber natural hemp fiber is used, the leaf springs are environment friendly and the hemp composite leaves are also biodegradable.

5 Conclusions In this work, two leaf spring elements from a conventional steel leaf spring are replaced with two natural hemp fiber/epoxy composite leaf spring elements of increased thickness. The proposed hybrid leaf spring is modeled to be used in the suspension system of a commercial vehicle. The FE analysis is done using commercial ANSYS software. Important conclusions that can be drawn from the analysis are as follows: • Weight of the composite leaf spring is reduced by 37% with respect to the conventional steel leaf spring, which will eventually increase the fuel efficiency as well as decrease overall unsprung weight.

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• The maximum von Misses stress developed on the hemp/epoxy composite leaf is 100.48 MPa which is less than the Tc (yield strength) of the hemp/epoxy composite material; hence, the design is safe based on maximum von Misses stress criteria. • The maximum permissible load on the composite leaf spring is up to 15,000 N, which is approximately four times more than the load carrying capacity of TATA ACE commercial vehicle. • Such hybrid model composed of a combination of composite material and conventional steel may be tested experimentally in future for commercial vehicles, since it exhibited many advantages during the FEM analysis.

References 1. Tanabe K, Seino T, Kajio Y (1982) Characteristics of carbon/glass fiber reinforced plastic leaf spring. SAE Transactions 1628–1636 2. Rajendran I, Vijayarangan S (2001) Optimal design of a composite leaf spring using genetic algorithms. Comput Struct 79:1121–1129 3. Seralathan S, Prasanna H, Arun J, Guhanesh B, Prasanth D, Hariram V, Premkumar TM (2020) Finite element analysis of hybrid composite material based leaf spring at various load conditions. Mater Today Proc 33:3540–3548 4. Soliman ESMM (2021) Evaluation of modal parameters and static characteristics for composite mono leaf spring. Noise Vib Worldwide 52(3):33–47 5. Lotfi A, Li H, Dao DV, Prusty G (2021) Natural fiber–reinforced composites: a review on material, manufacturing, and machinability. J Thermoplast Compos Mater 34(2):238–284 6. Varma N, Ahuja R, Vijayakumar T, Kannan C (2021) Design and analysis of composite mono leaf spring for passenger cars. Mater Today Proc 46(8):7090–7098 7. Kumar KP, Sekaran ASJ, Dinesh L, Prasad DH, Kumar K (2021) D, Natural sisal fiber-based woven glass hybrid polymer composites for mono leaf spring: experimental and numerical analysis. Progress Rubber Plast Recycl Technol 37:32–48 8. Shahzad A (2012) Hemp fiber and its composites–a review. J Compos Mater 46:973–986 9. Saba N, Jawaid M, Alothman OY, Paridah M, Hassan A (2016) Recent advances in epoxy resin, natural fiber-reinforced epoxy composites and their applications. J Reinf Plast Compos 35(6):447–470 10. Gupta US, Dharkar A, Dhamarikar M, Choudhary A, Wasnik D, Chouhan P, Tiwari S, Namdeo R (2021) Study on the effects of fiber orientation on the mechanical properties of natural fiber reinforced epoxy composite by finite element method. Mater Today Proc 45:7885–7893 11. Prasad S, Mishra V, Khoj V, Kukshal V (2021) Finite element modeling and analysis of natural fiber-reinforced composite (2021) In: Rakesh PK, Sharma AK, Singh I (eds) Advances in engineering design. Lecture notes in mechanical engineering. Springer, Singapore, pp 321–327 12. Kalaprasad G, Joseph K, Thomas S, Pavithran C (1997) Theoretical modelling of tensile properties of short sisal fiber-reinforced low-density polyethylene composites. J Mater Sci 32:4261–4267 13. TATA ACE Gold petrol mini truck specifications. https://ace.tatamotors.com/mini-truck/tataace-gold/tata-ace-gold-petrol/tata-ace-gold-petrol-specifications.aspx 14. Jamadar NI, Kivade SB, Tati P (2018) Prediction of residual fatigue life of composite mono leaf spring based on stiffness degradation. J Fail Anal Prev 18:1516–1525 15. Bhandari VB (2010) Design of machine elements. Third edition, McGraw-Hill Education, (India) Pvt. Ltd., New Delhi

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16. Thirugnanasambantham KG, Ramesh R, Sankaramoorthy P, Velmurugan A, Kannagi MC, Kishore Reddy V, Chary SK, Mustafa MA, Ramesh Chandra V (2018) Degradation mechanism for high-temperature sliding wear in surface-modified In718 superalloy. Cogent Eng 5:1501864. https://doi.org/10.1080/23311916.2018.1501864 17. Giridhar D, Ramesh R (2020) Contact Stress evaluation of micro-grooving process of alumina ceramic and validation with acoustic emission parameters. In: Lecture notes in mechanical engineering, advances in industrial automation and smart manufacturing. Springer, pp 597–617 18. Ramesh R, Arun ST, Mohammed RAP, Satheesh KP, Giridhar D (2020) Experimentation and process parametric optimization of 3D printing of ABS-based polymer parts. In: Lecture notes in mechanical engineering, advances in industrial automation and smart manufacturing. Springer, pp 487–496 19. Ramesh R, Manikandan N, Binoj JS, Palanisamy D, Arulkirubakaran D, Thejasree P, Pavan KA, Subhash RG (2020) Optimization and performance evaluation of PLA polymer material in situ carbon particles on structural properties. Mater Today Proc 39(1):223–229

Fabrication and Testing on Mechanical and Thermal Properties of Jute/Hemp Fiber Hybrid Composites K. Venkatarao, K. SivajiBabu, and G. Ranga Janardhana

Abstract The natural fiber reinforced composites are playing prominent role in many applications because of its various advantages such as eco-friendly, low cost, etc., with good mechanical properties. This article presents the effects of alkali treatment (NaOH) on mechanical and thermal properties of natural fiber reinforced polyester composites. Fibers were manually extracted followed by cleaning and drying at 80 °C. Fibers were treated using NaOH for four hours. Composite specimens were prepared using treated and untreated jute fiber and hemp fiber with varying weights such as 0, 2.5, 5 and 10 as reinforcement phase and polyester resin as matrix through hand lay-up technique. Tensile, flexural and impact tests were conducted on untreated and treated composites at room temperature as per ASTM standards. Fractographic analyses were reported using scanning electron microscopy (SEM). Thermal behavior of composites was studied using differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). Composites treated with NaOH showed improvement of mechanical and thermal properties. Keywords Mechanical properties · Thermal properties · Jute fiber · Hemp fiber · SEM

1 Introduction Increasing the awareness on the biodegradability, the researchers are focusing their studies on plant-based natural composites. The application of natural fiber reinforced composites is found in aircraft, transportation, building, musical, sports and household applications [1–5]. Jute, hemp, banana, Sisal, bamboo are commonly used natural fibers to prepare the natural composites. Karimah et al. [6] selection of the K. Venkatarao (B) · K. SivajiBabu Prasad V. Potluri Institute, Siddhartha Institute of Technology, Vijayawada 520007, India e-mail: [email protected] G. Ranga Janardhana JNTUA Ananthapur, Ananthapuramu 515002, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_20

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fiber is very important while addressing the application of these fiber reinforced composites. Combination of dissimilar natural fibers is used by many authors to further progress the properties of natural composite to make them to competitor for synthetic fibers. In this line, Subrata C. Das suggested to use mixture of natural and man-made fiber to improve the composite laminate performance by following correct stacking sequence [7]. Combining banana and jute fibers with dissimilar stacking order, the tensile, flexural and impact strength is identified by conducting suitable experiments and found the importance of hybridization of these fibers [8]. For improving the toughness of natural fibers hybridization with man-made fibers is vital [9]. Automotive brake friction composites containing 5 to 20 weight fractions of natural fibers (hemp, ramie and pineapple) were established [10]. Hybridization of jute, sisal and curaua fibers were chosen as natural fiber reinforcements for the epoxy matrix-based composites, and tensile, flexural and impact strength of the new hybrid composite was explored [11]. Recent advances in manufacturing hybrid natural fiber composites and highlight their importance by Hassani [12]. Basket-type and intra-ply crossed composites improve the properties of the composites due to the improvement in modulus by the reinforcement [13]. Waviness of sisal fiber on the elastic modulus also presented [14]. Considerable studies are performed on thermogravimetric analysis (TGA) of natural fiber reinforced composites to know the thermal behavior of plant-based composite, and a DFT study of compounds is of interest in order to gain a deeper insight on their action and thus helping in the design of new materials [15]. The weight loss in the natural composite due to increase in the temperature is presented by using TG analysis. For jute, sisal hybrid composite, three significant regions of weight loss with respect to temperature observed [16]. Thermal decomposition of jute and bamboo fiber is observed in the temperature range of 240–2600 °C [17]. Chemical composition of jute fiber is also observed [18]. From the above studies, it important to make different combination of natural fibers to make them to competitor to the synthetic fibers reinforced composite. In this work, efforts are made to identify the hybridization effect of jute and hemp fiber reinforced composite by hand layup technique and identified, tensile, flexural and impact strength along with SEM images.

2 Methodology 2.1 Materials Selection Process To study the mechanical behavior of fiber composites, specimen was prepared in the varied percentage of fiber content as shown in Table 1. One preliminary study was conducted on the specimen to find out the effect of alkali treatment. It was confirmed the alkali treatment will increase the mechanical properties. By this result, all specimen was treated with sodium hydroxide solution. In these experiments, jute and hemp fibers are treated by soaking in sodium hydroxide having different

Fabrication and Testing on Mechanical and Thermal Properties … Table 1 Preparation of composites with various percentages of fibers

241

Experiment name

Hemp (%)

Jute (%)

E1

0

2.5

E2

0

5

E3

0

10

E4

2.5

2.5

E5

2.5

5

E6

2.5

10

E7

5

2.5

E8

5

5

E9

5

10

concentrations of 2 and 4% for two hours. Later to remove all the dust particles, fibers are cleansed with water and dried in an oven maintained at a temperature of 80 °C for removing moister content in the fibers. The tensile and flexural tests were conducted with speed of 2 mm/min. The SEM analysis was conducted to find the failure nature of the samples.

2.2 Preparation of Fiber The jute and hemp fibers collected form the natural environment may contain dust and sand as pollutants. So they are thoroughly washed with detergent after soaking for 20 h in water. These fibers were dried for one week in sunlight and 10 h in an oven maintained at 80 °C, and they are cut into the required length for composite preparation. Fibers are then soaked in NaOH solution having different concentrations of 2 and 4% for 2 h at ambient temperature. Later these fibers are made free from the foreign particles or residual NaOH by cleaning with water. Also, to remove moisture content, fibers are dried at 80 °C in an oven for one day.

2.3 Composites Preparation Composites are made in a unidirectional pattern by adopting hand lay-up technique. Unsaturated polyester resin having a density of 1242 kg/m3 with specified grade name of ECMALON 4422 is procured from Bindu Agencies, Vijayawada. Resin is cured by adding 1.5% in volume of accelerator and catalyst at room temperature. The polyester resin, catalyst and accelerator are mixed and stirred thoroughly with the stirrer. Polyester resin is then poured into the mold in two layers at the top and the bottom with unidirectional fibers kept in between. In order to obtain quality composite material, moment and deformation of the fibers are prevented by applying

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compressive pressure of 0.05 MPa on the mold while being cured for 24 h. After being removed from the mold moisture from the composite is eliminated by curing the specimens for 4 h at a temperature of 80 °C. The fiber content in terms of weight of untreated fiber was 5 and 20%. Treated fibers are using 10% volume fraction for both 2 and 4% NaOH concentration.

2.4 Tensile Testing of Composite The tensile properties of the jute and hemp fiber composite are determined as per ASTM D638 according to which specimens are prepared with the length is 160 mm, width is 12.5 mm and thickness is 3 mm. The preparation of the specimens was done with 50 mm gauge length while being mounted on a cardboard. The specimen ends are fixed in the cardboard using epoxy resin, and the tests were conducted at a speed of 5 mm/min of the crosshead. An optical microscope is used in order to measure the fiber diameter at different parts of the gauge length. The gripping of the specimen into the jaws is done effectively by providing aluminum tabs which are glued to the using epoxy resin exempting the gauge length that also prevent compression of the specimen. The test was repeated on 20 specimens in order to validate the results. The density of the fiber is measured by adopting pycnometric procedure.

2.5 Specimen Preparation for Flexural Strength Test Flexural strength composite specimens were prepared as per ASTMD790M. Test specimen dimensions 100 mm long, 25 mm wide and 3 mm thick were prepared. Measurement of flexural strength and its modulus is done by conducting a 3-point bending test on UTM. Specimens are loaded till the fracture occurs.

2.6 Specimen Preparation for Impact Test In order to measure the impact strength of the composite material, Izod impact test was carried out for which specimens are prepared as per ASTM D256-88. According to which the specimens are of 63.5 × 12.7 × 10 size, a crack was included in the specimen having a sharp inclined angle of 45° taken across the centre of the saw cut at 90° to the simple axis.

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2.7 Scanning Electron Microscopy (SEM) For all the samples of the untreated and treated fiber composite, the SEM micrographs are captured using JEOL 6400F model. For better evaluation, gold layer was coated on all the samples and the acceleration voltage is set as 5 kV. After tensile testing of the composite, the fracture surfaces are coated with Au–Pd alloy and examined for their morphology using Zeiss Ultra Plus scanning electron microscope at 5 kV.

2.8 Thermal Analysis of Composites Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) are conducted in order to study the thermal behavior of the fiber composites. DSC and TGA are performed using thermal analyzer of Q100 model and Q500 model thermogravimetric analyzer respectively. The quantity of fiber taken was 6 and 10 mg that are heated up to 500 °C at a rate of 10 °C/min in nitrogen and helium environments for DSC and TG analysis, respectively. The study of thermal analysis is to understand thermal stability of the composites how much they lose weight for varying temperatures during TG analysis. Same was done for the untreated and treated jute and hemp fiber reinforced polyester reinforced composite by conducting DSC and TG analysis in this work. This analysis helps in comparing the thermal behavior of the untreated and treated fiber composites. The maximum temperature for the analysis is taken as 485 °C and its rate of heating as 10 °C/min. It is observed from the analysis that the temperature is found maximum for treated fibers compared with untreated fibers (Fig. 1).

3 Results and Discussions 3.1 Mechanical Performance The chemical treatment effect on composites specimens shows an important role in tensile behavior of polyester composites, and it was gradually increased with increase with reinforcement phase. The higher tensile load bearing capacity was recorded for E9 specimen because of excellent bonding strength and combination of jute fiber and hemp fiber. In maximum cases, the specimen shows high level strength after chemical treatment because of surface roughness of fiber enhances the superior bonding strength, and it is observed from scanning electronic micrographs. The composite samples are exhibited lower-level displacement with irrespective load and chemical treatment. The tensile properties of the specimen with various percentage of fiber are obtained from the tensile test. The properties of the specimen pure jute and with different

244 Fig. 1 a Jute fiber, b hemp fiber, c chemical treatment, d mold preparation, e specimen for impact test, f specimen for tensile test

K. Venkatarao et al. a

b

c

d

e

f

percentage of hemp were compared with each other. The combined hemp and jute composite specimens show the better tensile strength compared to jute composites. A prominent increment is observed at each increment of hemp percentage. The tensile strength is effected by agglomerations, it is observed from E4, E5 to E7, E8 specimens (Fig. 2). From Fig. 3, the flexural behavior of the specimens was explored. The highest flexural strength was observed at E9 specimen, and it was 186.39 MPa. And the lower stage identified as E1. The variation between higher and lower stages of flexural strength was calculated as 200%. The tensile behavior is highly effected on the specimen behavior, and it was observed from SEM images. The impact graph of specimens declared that the amount of fiber content shows the nominal effect on the impact load. The variation between maximum and minimum impact is low. This observation reveals the most effecting factor of on the impact strength was bonding strength. By increasing the fiber content in composites, the ductility behavior of the specimen was increased (Fig. 4).

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Fig. 2 Tensile strength of specimen with various percentages of fibers

Fig. 3 Flexural strength of specimen with various percentages of fibers

Fig. 4 Impact strength of specimen with various percentages of fibers

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3.2 Fractography The fractured surfaces of the fiber composite obtained after tensile, flexural and impact tests are analyzed by SEM in order to predict the fracture behavior along with bonding between the fiber-matrix and their interaction. The SEM analysis was conducted to give justification to variation in mechanical properties of the composite specimens. From Fig. 5a, b the uniform nature of the resin and fiber was clearly observed. It is found that the fracture is brittle in nature for the matrix and the fiber breaks near the matrix which indicates the interfacial bond is strong. The flexural load effect on the flexural samples was identified from Fig. 5c, d and it denotes the compression nature on the specimen was less. The mechanism by which few fibers are released is pull-out due to lack of adhesion between fiber-matrix and others are broken near to the matrix. Fiber pull-out means that it is a sign of a weak bond. The strong bonding of fiber also observed from the same images. The impact fracture is found to be a sudden failure with some internal cracks as seen in Fig. 5e, f. The factors due to which the impact energy dissipates are debonding, fiber pull-out and fracture. It is also observed that impact load causes some voids in the material. So, fracture and voids in the matrix are seen as the evidence of fiber pull-out.

3.3 DSC Analysis The occurrence of material transitions with respect to time and temperature is measured using DSC analysis in the form of temperature and heat flux. In this analysis, the qualitative and quantitative changes related to physical and chemical processes in which absorption or release of heat is provided. This shows the thermal phase transformation of the composite with the help peaks and magnitude obtained from the endothermic and exothermic processes. The study of endothermic and exothermic processes of the fiber composites using DSC curves is shown in Fig. 6. It is found that fiber composite gets dehydration during endothermic process ranging from room temperature to a peak of 260 °C which is relatively low compared with non-hybrid composites. The reason for lower peak is that the fiber quantity in the composite possesses higher water absorption capability. Furthermore, the peak of exothermic is found to be 380 °C due to the degradation of cellulose/lignin and the resin. An endothermic peak is observed between 30 and 270 °C, whereas for exothermic process peak was found between 270 and 380 °C for both untreated and treated fibers. Heat absorption is indicated by first endothermic peak resulting in the moisture evaporation by the fiber composite. As the fibers are treated with different alkali concentrations, certain differences of thermal energy are observed during endothermic peak.

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a

b

c

d

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Jute fiber /Hemp fiber

e

f

Damage free Jute fiber/ hemp fiber

Fig. 5 SEM images of fractured surfaces from tensile a, b, flexural c, d and impact e, f specimens

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Fig. 6 DSC curves of composites for hybridization

The main reason being different alkali concentrations in fiber absorb different quantities of moisture. Some constituents like lignin decompose at 270 °C, whereas hemicellulose and cellulose that form other constituents require even higher temperatures to decompose. Therefore, another peak is found in the DSC analysis that indicates exothermic peak at which these constituents decompose. The exothermic peaks found to be different for the untreated and treated fibers which are between temperature range from 270–380 °C and 350–380 °C respectively for degradation of lignin, hemicelluloses and cellulose from the fibers. This is because the above said constituents are already removed partially during alkali treatment of the fibers. It is also observed that among all the treated fibers 4% NaOH-treated fibers possess high thermal stability as shown in Fig. 6. It will improve the hydrophobic nature and thus good adhesion properties are achieved by the fibers. So, it can be concluded from this analysis that decomposition temperature is less for untreated fibers compared with treated fibers which are thermally more stable.

3.4 TGA Analysis The purpose of TGA analysis is to see whether the fibers lose their weight when subjected to varying temperatures. It is observed that fibers lose weight in three stages with extended range of temperature as seen from Fig. 7. In the first stage, the moisture available in the fiber is released during the temperature range of 30–310 °C which reduces the weight. Degradation of constituents like lignin and hemicelluloses is considered as second stage of weight loss during temperature range of 310–430 °C.

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Fig. 7 TGA curves of composites for hybridization

The final stage happens to be from 430–520 °C wherein weight loss is due to degradation of cellulose. Also, thermal stability is high for the fibers which have under gone alkali treatment because treated fibers degrade at higher temperature compared to untreated fibers ensures lower weight loss. Alkali treatment of fibers removes the lignin and hemicellulose and thus increases the degradation temperature.

4 Conclusions The tensile, flexural and impact tests are conducted to analyze the mechanical response of the composite specimen prepared with varied percentage of hemp and jute fiber. The SEM analysis was conducted to investigate failure nature of the specimens. Based on the results and discussions, the following conclusions are drawn. The high amount of fiber content mostly effecting the tensile behavior the samples. Tensile load was most effecting factor on the flexural strength. The tensile strength is highly increased by increasing the fiber content. The internal cracks and ductility nature of the specimens were observed from the SEM images of fractured surfaces. Orientation of fiber and its bonding with matrix is visualized by SEM and found to be good for both jute and hemp fibers. The investigation of thermal properties for jute fiber and hemp fiber showed that composite has high glass transition temperature that could bring an improvement of using natural fiber composites.

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References 1. Prabhu L, Krishnaraj V, Sathish S, Gokulkumar S, Karthi N, Rajeshkumar L, Balaji D, Vigneshkumar N, Elango KS (2021) A review on natural fiber reinforced hybrid composites: chemical treatments, manufacturing methods and potential applications. Mater Today Proc 45(9):8080–8085 2. Khalid MY, Rashid AA, Arif ZU, Ahmed W, Arshad H, Zaidi AA (2021) Natural fiber reinforced composites: sustainable materials for emerging applications. Results Eng 11:100263 3. Reddy PV, Reddy RVS, Rao JL, Krishnudu DM, Prasad PR (2021) An overview on natural fiber reinforced composites for structural and non-structural applications. Mater Today Proc 45(7):6210–6215 4. Raju R, Selvakumar TA, Ali PMR, Kumar PS, Giridhar D (2020) Experimentation and process parametric optimization of 3D printing of ABS-Based Polymer Parts. In: Advances in industrial automation and smart manufacturing. Lecture notes in mechanical engineering. Springer, pp 487–496 5. Raju R, Manikandan N, Binoj JS, Palanisamy D, Arulkirubakaran D, Thejasree P, Kalyan AP, Reddy SR (2021) Optimization and performance evaluation of PLA polymer material in situ carbon particles on structural properties. Mater Today Proc 39(1):223–229 6. Karimah A, Ridho MR, Munawar SS, Adi DS, Ismadi, Damayanti R, Subiyanto B, Fatriasari W, Fudholi A (2021) A review on natural fibers for development of eco-friendly bio-composite: characteristics, and utilizations. J Mater Res Technol 13:2442–2458 7. Das SC, Paul D, Grammatikos SA, Siddiquee MAB, Papatzani S, Koralli P, Islam JMM, Khan MA, Shauddin SM, Khan RA, Vidakis N, Petousis M (2021) Effect of stacking sequence on the performance of hybrid natural/synthetic fiber reinforced polymer composite laminates. Compos Struct 276:114525 8. Ravindran S, Sozhamannan GG, Saravanan L, Venkatachalapathy VSK (2021) Study on mechanical behaviour of natural fiber reinforced vinylester hybrid composites. Mater Today Proc 45(6):4526–4530 9. Ahmed MM, Dhakal HN, Zhang ZY, Barouni A, Zahari R (2021) Enhancement of impact toughness and damage behaviour of natural fibre reinforced composites and their hybrids through novel improvement techniques: a critical review. Compos Struct 259:113496 10. Singh T (2021) Optimum design based on fabricated natural fiber reinforced automotive brake friction composites using hybrid CRITIC-MEW approach. J Mater Res Technol 14:81–92 11. Cavalcanti DKK, Banea MD, Neto JSS, Lima RAA, da Silva LFM, Carbas RJC (2019) Mechanical characterization of intralaminar natural fibre-reinforced hybrid composites. Compos B Eng 175:107149 12. Hassani FZSA, Bouhfid R, Qaiss A (2021) Recent advances in the fabrication of hybrid natural fiber composites. In: Khan A, Sanjay MR, Siengchin S, Jawaid M, Abdullah MA (eds) Woodhead publishing series in composites science and engineering. Woodhead Publishing; Hybrid Nat Fiber Compos 113–131 13. Rajesh M, Jayakrishna K, Sultan MTH, Manikandan M, Mugeshkannan V, Shah AUM, Safri SNA (2020) The hydroscopic effect on dynamic and thermal properties of woven jute, banana, and intra-ply hybrid natural fiber composites. J Mater Res Technol 9(5):10305–10315 14. Prasanthi PP, Babu KS, Niranjan Kumar MSR, Kumar AE (2019) Analysis of sisal fiber waviness effect on the elastic properties of natural composites using analytical and experimental methods. J Nat Fibers 18(11):1–14 15. Anidha S, Latha N, Muthukkumar M (2019) Reinforcement of Aramid fiber with bagasse epoxy bio-degradable composite: investigations on mechanical properties and surface morphology. J Mater Res Technol 8(3):3198–3212 16. Gupta MK, Srivastava RK (2016) Mechanical, thermal and water absorption properties of hybrid sisal/jute fiber reinforced polymer composite. Indian J Eng Mater Sci 23:231–238 17. Biswas S, Shahinur S, Hasan M, Ahsan, Q (2015) Physical, mechanical and thermal properties of jute and bamboo fiber reinforced unidirectional epoxy composites. In: 6th BSME international conference on thermal engineering (ICTE 2014)

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18. Shahinur S, Hasan M, Ahsan Q, Haider J (2020) Effect of chemical treatment on thermal properties of jute fiber used in polymer composites. J Compos Sci 4:132

A Review: Investigation of Length Effect in Carbon Nanotube (CNT)-Reinforced Aluminum (Al) Composites K. G. Thirugnanasambantham, Devarapalli Sai Charan Reddy, Tadikonda Vishnu Vardhan, and Sama Abhinav Reddy

Abstract Carbon nanotubes (CNTs) are a groundbreaking innovation in nanotechnology. CNTs have exceptional fabric properties, making them an ideal reinforcement for Al-based composites. Al-CNT composites are expected to be used in aircraft applications due to their unique properties, as well as beneficial materials due to their energizing mechanical properties. The mechanical characteristic changes are accomplished by varying the length of CNT in Al lattice. Although length effects of CNT are important aspects of the development of Al-CNT composites, no systematic review analysis of composites has been done to examine the length effect of CNT in the AI/CNT composites. Hence, the primary objective of this review is to address the CNT’s length influence on the Al/CNT composites. Keywords CNT · Aluminum · Length effect · Reinforcement

1 Introduction In recent times, carbon nanotube (CNT) due to their outstanding mechanical qualities and significant potential for application as reinforcement inside structures have piqued the curiosity of researchers within metal matrix. Aluminum-matrix composites have gone a long way and are now widely used in a number of industries [1–3]. CNT is recognized as future reinforcing agent due to their exceptional mechanical characteristics in aluminum matrix. In recent times, Al/CNT have involved especially inside the aerospace enterprise, because of the superb mechanical qualities of the CNT. Al nanocomposites enhanced with help of CNTs have been extensively researched in terms of mechanical characteristics [4–14]. The mechanical characteristic changes are accomplished by varying the length of CNT in Al lattice. Although length effects of CNT are important aspects of the development of Al-CNT composites, there is no systematic review analysis of composites has been done to examine K. G. Thirugnanasambantham (B) · D. S. C. Reddy · T. V. Vardhan · S. A. Reddy Department of Mechanical Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Coimbatore, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_21

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the length effect of CNT in the AI/CNT composites. Hence, the primary objective of this review is to address the length and CNT’s influence on the Al/CNT composites.

2 The Impact of Length of CNT in Al-CNT Composites Length of the reinforcement is also important in obtaining the composite’s exceptional and superior mechanical characteristics [15, 16]. Depending on the CNT length, characteristics of Al-CNT composites can vary significantly. Shear lag models forecast the composite’s eventual overall strength based on the principle of the load transmission from lattice to reinforcement [17–22]. Load with standing capacity of Al composites enhances with increment in CNT length, and therefore, efficiency of composite property usage improves as well. Load may be communicated from the lattice to CNT in CNT-reinforced Al composites by developing interfacial shear stresses along the CNT–matrix contact. As a result, the strength of the CNT varies with its length [i.e., the strength proportionately rises as the length of the CNT increases] [23]. Shortening the CNTs limits the effectiveness of load transmission from the lattice to the CNT in CNT/Al composites [24]. Wan et al. [25] explained, if the length exceeds the critical length, the failure mode changes to breaking mode [26]. As a result, the failure of CNT in most Al-CNT composite experiments is pull out from the matrix.

2.1 Impact of CNT Length on the Mechanical Characteristics of CNT-Al By altering length of Carbon nanotube, Hassanzadeh [27] measured the properties of the CNT-Al. In Fig. 1a–c, the fluctuation characteristics of CNTs are illustrated with respect to CNT length variation. As the length of the CNT grows, the elastic modulus increases asymptotically, as shown in Fig. 1a. The value of elastic modulus converges to a steady value beyond a certain length of CNTs. The ultimate tensile strength follows a similar pattern, as seen in Fig. 1c. On the other hand, as the length of CNTs grows, the yield strength approximately linearly increases (Fig. 1b). According to Nardon and Prewo, composites are strengthened by transferring force from the lattice to the tougher fortification [28]. Load transmission necessitates a high aspect ratio [AS] of nanoparticles to provide a strong strengthening effect. Chen et al. [15] looked into the impact of CNT length on composite characteristics and the interaction of dislocations. CNTs of various aspect ratios were used. The mechanical characteristics of CNT-Al composites with varying CNT length/aspect ratios are shown in Table 1. [15]

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Fig. 1 a–c Characteristics of Al-CNT with varying CNT length [27] Table 1 Microstructural Al-CNT composites with varying CNT aspect ratios [AS] have structural and its mechanical characteristics [15] Materials

CNT length (nm)/Aspect ratio

0.2% YS (MPa)

UTS (MPa)

Elongation (%)

Raw Al

–

118

133

29

Al

–

127

168

25

Al-1% CNT

717/ 55

151

210

15

Al-1% CNT

561/ 42

128

172

19

Al-1% CNT

324/ 25

172

250

14

A1-1% CNT

185/ 14

225

271

15

Al-1% CNT

145/ 11

241

301

14

Al-1% CNT

122/ 9.2

278

324

14

Al-1% CNT

92.5/ 7.0

305

339

15

Al-1% CNT

856/ 6.5

312

368

16

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Fig. 2 Fracture morphology of Al-1%CNT composites after tensile tests [15]

2.2 Effect of Length on CNT Pullout Figure 2 the rupture morphology of the CNT-Al after elongation testing is depicted. On the fracture surface of the Al-1 percent CNT sample (Fig. 2), CNT pull-out events can be noticed, signifying that the CNT offers a successful stress transmission. Other researchers have also discovered CNT pullout for undersized dimension. Jiang and colleagues reported [22]. During tension, the contact between the lattice and CNT subjected to high strain results in fractures. The CNT tube–Al contact, on the other hand, was tightly bound [22].

2.3 Influence of CNT Length on Strengthening Mechanisms of Al-CNT This review also analyzes the effect of various CNT lengths on strengthening mechanisms in MMC. Figure 3 illustrates the CNT length is modified, and the principal strengthening mode transitions. If lattice crystal is greater than CNT size, Orowan strengthening [OS] and load transfer [LT] processes can help CNT-reinforced AlMMC to be stronger. In three separate regimes, the load transfer and Orowan strengthening exhibit an opposing tendency, as illustrated in Fig. 3. Figure 3 depicts the actual data as well as forecasted curves for the strengthening effect vs. CNT aspect ratio. The strength contribution of CNTs is influenced by the CNTs length. When the [AS] fraction of CNT fluctuates, Orowan strengthening and load transfer processes display fronting tendencies, and the strengthening behavior displayed in 3 regions. In Region I, the characteristics of CNT-Al composites are determined by the [OS]. In Region III, load transfer becomes the most important strengthening process (high CNT lengths or aspect ratios). The observed strength levels in Regime II are in the middle of the range anticipated by the load transfer model and Orowan strengthening.

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Fig. 3 Strengthening mechanisms versus CNT length [15]

The abilities are not as strong as Orowan’s expectations, but significantly greater than the load transfer model’s projections. Another important topic is why, for intermediate CNT aspect ratios (Region II), [OS] induced by CNTs turn into modest, and even non-existent, for aspect ratios beyond 40. (Regime III). Imperfections in the region of lengthy CNT might explain this. In normal conditions [29, 30], dislocations having a length almost the same to the diameter of a lattice crystal [31] can bend between two rigid particles, resulting in [OS]. If the CNT length is significantly undersized than the imperfection size, CNTs will perform as elements capable of capturing loops while imperfections pass by (Figs. 4a and 5). However, when CNT length surpasses a critical threshold (Lcr), which is roughly half the dislocation length, dislocations find it difficult to space out through the lengthy CNT. The imperfections eventually sank at the CNT–Al contact without producing Orowan loops (Fig. 4b) [15]. The authors determined that Orowan strengthening is the primary reinforcing effect at small aspect ratios. This is because, when shorter CNTs interact with dislocations, the reinforcement behaves as particle and trap loops, as seen in Fig. 4a. It should be emphasized that CNTs have a substantially higher strength than Al matrix, making dislocation shearing more difficult. When the length of the CNTs exceeds the length of the dislocation, the dislocation finds it difficult to travel through the lengthy CNTs. As a result, as illustrated in Fig. 4b, the dislocations sank at the contact. The dislocation sink surrounding the long CNTs causes Orowan strengthening to have a little or no effect on strength. The buried dislocations were tough to move farther in this situation. When long CNTs are added to Al-1% CNT [15] a composite, the ductility is considerably reduced with improved strength on a macroscopic level. Dislocations travel via small CNTs and are still mobile in the matrix in the Orowan mechanism (Fig. 4a). As a result, the Al matrix can be deformed further.

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Fig. 4 a and b Contact among imperfections and CNT [15]

Fig. 5 TEM analyses of Al-1%CNT composites after tensile tests [15]

Table 2 the aspect ratio of CNT [15] has a significant impact on the strengthening mechanism. When long CNTs are added to Al-1% CNT composites, the ductility is considerably reduced with improved strength on a macroscopic level. This is what the current research has discovered (Table 2).

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Table 2 Comparison of strength enhancement of CNT-Al composites with raw Al [15] Materials

CNT aspect ratio

Orowan strengthening by alumina

Strengthening by CNTs

Prediction by Orowan looping by CNTs

Load transfer by CNTs

Raw Al

–

33.4 (95.4%)

–

–

–

Al-1% CNT

55

37.5 (48.7%)

36.1 (46.8%)

99.6

36.2

Al-1% CNT

42

11.6 (29.7%)

25.1 (64.4%)

104.5

28.6

Al-1% CNT

25

41.4 (35.4%)

70.4 (60.1%)

122.3

1.3

A1-1% CNT

14

42.9 (31.1%)

87.8 (63.7%)

141.1

9.4

Al-1% CNT

11

46.0 (27.4%)

113.2 (67.4%)

149.9

7.3

Al-1% CNT

7.0

49.5 (24.0%)

141.5 (68.7%)

167.8

4.6

3 Conclusion Length of the CNT plays a significant role in obtaining the composite’s exceptional and superior mechanical characteristics. Depending on the CNT length, characteristics of Al-CNT composites can vary significantly. The value of elastic modulus converges to a constant value beyond a certain length of CNTs. On the other hand, the yield strength approximately linearly increases as the length of CNT grows. Load with standing capacity of Al composites increases as the length of the CNT increases, and therefore, the efficiency of composite property usage improves as well. Load may be communicated from lattice to the CNT in CNT-reinforced Al composites by developing interfacial shear stresses along the CNT–matrix contact. Shortening the CNTs limits the effectiveness of force transmission from the metal lattice to the CNT, which reduces the performance of CNT/Al composites. CNT length affects the strengthening mechanisms of Al-CNT composites. When the aspect ratio of the CNTs is greater than forty, strengthening effect is mostly due to load transfer; however, when the aspect ratio is less than ten, strengthening effect is due to the Orowan mechanism.

References 1. Sam M, Radhika N (2019) Mechanical and tribological analysis of functionally graded aluminium hybrid composite using RSM approach. Mater Res Express 6(9):096595 2. Raju R, Manikandan N, Binoj JS, Palanisamy D, Arulkirubakaran D, Thejasree P, Kalyan AP, Reddy GS (2020) Optimization and performance evaluation of PLA polymer material in situ carbon particles on structural properties. Mater Today Proc 46:695–701 3. Raju R, Selvakumar TA, Ali PMR, Kumar PS, Giridhar D (2020) Experimentation and process parametric optimization of 3D printing of ABS-based polymer parts. In: Arockiarajan A, Duraiselvam M, Raju R (eds) Advances in industrial automation and smart manufacturing. Lecture notes in mechanical engineering. Springer, Singapore, pp 487–496

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Experimental Investigation on the Performance of Inconel 718 Using MQL Grinding Operation Farooqui Rizwan Ahmed, Prameet Vats, Rabesh Kumar Singh, and Anuj Kumar Sharma

Abstract The superior properties like corrosion resistant, high-temperature resistance, high strength of nickel-based superalloys make them very challenging to machine. This paper focusses on the investigating of grindability of Inconel 718 under dry and MQL environment considering different response parameters like temperature, forces, and surface roughness. Experimental results indicated that the grinding performance was superior for minimum quantity lubrication environment. A FEM model was also developed for the thermal analysis of Inconel 718 grinding. To test the reliability of the FEM model, simulated data was then compared with the experimental data for optimum condition under dry and MQL condition. The average variation of 10.13% was noted between the simulated data and experimental data, which ultimately proves that anticipated FEM model is reliable. Keywords MQL · FEM · Inconel 718

1 Introduction Grinding is known as the bulk material removal process which mainly uses abrasive particles embedded into the grinding wheel for removing material from the surface of the workpiece. In the current advanced market and more aware customers, the demand of better finished products with close tolerance and dimensional accuracy is increasing every day, and to fulfil these demands, industries are investing a considerable amount of their total budget. Grinding plays a vital role in meeting surface finishing demands while keeping the budget in control as it provides an economical alternative. Grinding is the only traditional machining process that provides better surface finish while maintaining the dimensional accuracy. Though, there are some challenges affiliated with grinding as well such as surface degradation, surface burning, surface cracks [1]. In order to overcome these challenges up to an extent, lubrication can be used. The application of lubricants at the contact surface of F. R. Ahmed · P. Vats · R. K. Singh (B) · A. K. Sharma Centre for Advanced Studies, Lucknow 226031, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_22

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grinding wheel and work material reduces the friction which results in dropping the temperature of grinding zone [2]. Lubrication can be achieved via different methods, namely dry lubrication, wet lubrication, minimum quantity lubrication (MQL). Wet lubrication utilizes liquid lubricants such as mineral oil to reduce friction. Though some chemical liquid lubricants used in grinding such as polyether are hazardous in nature, discharge of these hazardous lubricants in nature causes various environmental issues. In order to tackle this problem, minimum quantity lubrication (MQL) technique is used [3]. In the current market, the demand of Inconel superalloy is increasing every day because of its superior properties like corrosion resistant, high-temperature resistance, high strength while maintaining its weight in tolerance limit. Nickel (Ni)-based superalloys such as Inconel 718 are now widely appreciated and utilized globally. It is stated by Ezugwu et al. [4] that Ni-based alloys fulfil a significant amount of the total material required for the fabrication of aircraft engine, and this is the reason that they are widely mentioned as aerospace materials. It has variety of applications in the aerospace industry because of its strong resistance to corrosion, fracture, and creep. According to Thakur et al. [5], Inconel 718 is among most widely used superalloys. Inconel 718 has a capability of retaining its strength even at higher temperatures (approximately 700 °C), which makes it ideal for high-temperature applications such as gas turbine blades, nozzles, pistons, piston rings, and combustion chambers. Though, the machining of Inconel is a very challenging task [6]. By varying the grinding parameters along with the incorporation of lubricants, finishing of Inconel can be achieved. Balan et al. [7] executed the grinding of Inconel 751 under different lubrication environments and found that the MQL and Cryo-MQL provide superior surface finishing while consuming lesser specific energy in comparison to dry lubrication and wet lubrication. To perform the grinding of superalloys, Li et al. [8] used dry mineral oil and cryogenic cooling as lubricating environments and found that the lowest grinding temperature was observed in the case of cryogenic cooling, and it was also found that cryogenic cooling also enhances the surface quality as well as the integrity of grinding surface. While performing the grinding of Inconel 751, Balan et al. [9] focused the study on the grinding parameters under different lubrication environment and found that the lower temperature and improved surface finish was found under MQL conditions, and there were hardly any grinding burns visible on the surface. Pashmforoush et al. [10] evaluated the efficiency of nanofluid on different grinding parameters using ANNOVA analysis with the help of image processing. It was noted that the application of copper nanofluid provides better results in comparison to dry grinding and conventional fluid grinding. Sinha et al. [11] optimizes nozzle position, air pressure, flow rate, droplet quality to enhance the MQL effectiveness with the help of combination of microscopy and image processing technique, and it was found that air pressure 8 bar, horizontal nozzle stand-off distance 72 mm, and cutting fluid flow rate 150 ml/h provide the optimum parameters for grinding. Naskar et al. [12] used the MQCL mode with neat oil, etc. to grind the Inconel 718 using a single-layer super-abrasive CBN to investigate integrity of surface. Flood mitigation was also a considered as benchmark. It was also observed that MQCL

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plain oil outperformed all other lubricants. Virdi et al. [6] explored the possibility of developing the environment-friendly of Inconel 718 alloy by the application of NFMQL technique using base oil (vegetable oil). It was observed that ability of the vegetable oil NFMQL method to produce a thin stable lubrication layer at the interface of workpiece and tool improved the grindability of Inconel 718 alloy. Balan et al. [13] evaluated the impact of MQL factors on Inconel 751 grinding performance. In terms of reduced temperature and grinding force, it was discovered that the ideal minimum quantity lubrication condition in grinding produced superior outcomes. Jia et al. [14] focus on finding the best combination of nanoparticles and vegetablebased oil for improving the grindability of Ni-based alloys with the least amount of lubrication. Force ratio, grinding force, and surface roughness were used to assess the oil’s lubricating properties. In comparison to castor oil and other mixed base oils, it was discovered that soybean oil produced the best results. Li et al. [15] focused his study on assessing the grindability of superalloys (nickel based) under the presence of cryogenic cooling. For grinding of nickel-based superalloys without polluting the environment, cryogenic cooling has been demonstrated to be a viable alternative to traditional cooling. Results showed that grinding under liquid nitrogen does, in fact, resulted in significant increase in surface integrity when compared to other lubrication conditions. Researchers have worked on various methodologies to determine the temperature distribution over the surface of superalloy using thermal or mathematical modelling in the past mostly for economic reasons, as it avoids a large initial investment cost to set up the machinery and also allows for multiple iterations without having to create new setups. The evidence for same can be sought from different literature with experimental validations. Kundrák et al. [16] presented a thermal model of finite volumes with a clear representation of workpiece and grinding wheel. Different machining condition experiments and simulations were carried out to determine temperature and heat-affected zones. Lan et al. [17] established a heat source model for the contact zone during actual grinding. Zhang et al. [18] simulate the thermal deformation during grinding by using the ANSYS thermomechanical coupling module and compared the simulated results with the test results. Only limited literatures are available concerning the FEM modelling of grinding under dry and MQL environment which makes thermal analysis difficult. Hence, this study focuses on developing a FEM model for grinding using ANSYS simulation software and comparing the obtained thermal results for dry and MQL environment with the experimental results.

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Table 1 Detailed experimental condition

Parameters

Conditions

Parameters

Grinding machine

Horizontal axis surface grinding

Grinding machine

Grinding wheel material

CBN

Grinding wheel material

Work piece material

Inconel 718

Work piece material

Work material size

250 × 50 × 10 mm

Work material size

Work feed rate

1 m/min

Work feed rate

MQL Nozzle

Grinding wheel

Force dynamometer

Workpiece

Magnetic table

Fig. 1 Experimental setup

2 Material and Methodology 2.1 Experimentation Inconel 718 is used to perform grinding. To perform the experiments, rectangular billet of Inconel 718 (having dimensions of length of 250, width 50 and 10 mm thickness) is considered as subjected material. The workpiece was fixed on horizontal axis surface CNC grinding machine with disc-type resin-bonded CBN grinding wheel. Dry grinding was performed without application of any lubricant, while for MQL grinding, base fluid (88 water + 10 vegetable oil + 2% surfactant) was applied directly onto the concentrated area using an MQL system. Table 1 mentions the detailed specifications of material, equipment, and details of experiments (Fig. 1).

2.2 Finite Element Modelling A 3D grinding fluent model was developed using ANSYS 19.2. The workpiece model has a dimension of 250 long, 50 wide, and 10 mm thick. Meshed part of workpiece and the fluid domain are shown in Fig. 2. The workpiece material is composed of Inconel 718, and properties were defined in the software database. Two different simulations using ANSYS CFD fluent solver were performed for dry and MQL environment. For dry environment, effect of air was taken into account, while for

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Fig. 2 Meshing of workpiece (a) and fluid domain (b)

MQL, the effect of mist flow was taken into consideration. At the upper surface of workpiece, heat-flux was provided. Initial temperature of the model was kept at room temperature (293 K). The wheel was considered as the mixture of source of heat and pressure which was stimulated over the surface of workpiece at the a given feed rate [19]. To design the heat source, the heat-flux density transferred from the heat source to the workpiece must be known. Mainly, the thermal models are based on the theory of Carlsaw/Jaeger [20]. To calculate the unchanging heat-flux density (qw ), Eq. (1) was used: qw = K v · K w ·

vc · Ft l g · bk

(1)

Here, qw is the density of heat-flux which mainly relies on two factors of proportionality (dissipation of energy K v, which represents the mechanical energy percentage which is converted into heat and K w, the heat distribution factor). F t represents tangential component of force and can be determined using the dynamometer, bk is the width of grinding wheel, and V c is the cutting velocity. The value of K v can be set as 1 [19]; for input (heat-flux), the value of K w can be set as 0.5 [21]. Then, l g is the contact length and can be determined using Eq. (2). lg =

√

dw. a

(2)

Here, d w represents the diameter of the grinding wheel, while a represents the cutting depth for grinding.

2.3 Design of Experiments It is an important method for improving product design and solving production problems [22]. Three levels and two factors were considered for this work while

268 Table 2 Control parameters and levels

F. R. Ahmed et al. −1

0

1

Work feed rate, f (m/min)

1.0

1.0

1.0

Depth of cut, a (µm)

10

20

20

Wheel velocity, V (m/min)

500

1500

3000

Levels Parameters

keeping the one factor (work feed rate) constant. The grinding parameters considered are mentioned in Table 2. For the experiments, three levels and two factors were considered for which degree of freedom associated will be 9. So, L9 orthogonal array which meets the requirement of nine rows (representing nine trials) and two columns was selected according to Taguchi approach. The design of experiments of variables formed according to Taguchi L9 array.

3 Results and Discussions 3.1 Input Parameters Effects on Temperature The effect of input parameters on the temperature during grinding under different lubrication conditions and its different experimental values was noted. It was observed (Fig. 3) that MQL condition resulted in lower surface temperature than dry condition. From experimental results, it was also noted that the temperature during grinding increases as the cutting depth and grinding speed increases. From experimental data, it was observed that temperature tends to drop at cutting depth of 20 microns and grinding velocity of 1500 m/min, after which an increase can be seen. This is because the workpiece undergoes thermal softening at temperatures corresponding to higher speed (causing wheel load). This may be due to the softening of wheel bond, resulting in increased friction and heating [23]. Furthermore, simulations were also carried out for optimum parameters (Table 3) for the grinding of Inconel 718 under the effect of dry and MQL environment. The experimental values of temperature for optimum parameters were chosen for comparison with simulation as from the point of view of response parameters, temperature is the most important input among all process parameters [24]. The heat generated by the interference between the workpiece and the particles of grinding wheel surface during wear is expressed by the help of source of heat corresponding to the model developed by Jaeger. The heat source moves in straight line along the surface of the workpiece [16]. The simulation is finished once heat source travels away from the workpiece, and the results were generated. Figure 4 represents the simulated temperature results for dry and for MQL grinding for optimum

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Fig. 3 Variation of temperature for each run of experiment

Table 3 Optimum simulation parameters

Input parameter

Symbol

Value

Work feed rate

f (m/min)

1

DOC

a (µm)

10

Wheel velocity

V (m/min)

500

grinding parameters. The maximum temperature reported for dry and MQL was around 424.47 °C and 250.84 °C, respectively. Furthermore, variation of temperature of the workpiece for dry grinding and MQL grinding with respect to contact time under optimum grinding parameters is shown in Fig. 5a. Figure 5b shows the comparison of simulated results with the experimental results for optimum grinding parameters. The maximum difference between the simulated

Fig. 4 Temperature profile of Inconel 718 workpiece under a dry environment and b MQL environment

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Fig. 5 Comparison of simulated temperature variation along the workpiece surface for dry and MQL grinding

and experimental data recorded was approximately 8.283% for dry and 11.982% for MQL environment.

3.2 Input Parameter Effects on Forces Different experimental values of forces, tangential (F t ) and normal (F n ), were recorded. It was noted from the experimental results that as the depth of cut increases, both the tangential and normal forces increase. As the wheel velocity increases, the grinding method changes to steady state from ploughing, due to which both the normal and tangential grinding forces decrease [25]. The possibility of thermal softening of the grinding wheel additives and degradation of the abrasive at elevated temperatures, resulting in more friction and ploughing, dry environment records higher forces (tangential and normal) during grinding as compared to minimum quantity lubrication environment (Fig. 6). In the minimum quantity lubrication environment, the interface of wheel workpiece undergoes limited lubrication, which results in improved abrasion effect.

3.3 Input Parameters Effects on Surface Roughness The different experimental values for surface roughness were noted for grinding under dry and MQL environments. From the experimental and analytical results, it was observed that the value of the roughness of workpiece decreases with the increase in grinding (grinding wheel) speed (Fig. 7). It was also noted that with the increase in grinding depth, the decrease in surface roughness occurs. Associated temperature rise promotes bond softening, abrasive haze, and wheel loading which ultimately

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Fig. 6 Tangential force (a) and normal force (b) variation for each run of experiment

Fig. 7 Variation of surface roughness for each run of experiment

results in the degradation of surface finish. The best surface was obtained in the minimum quantity lubrication environment, which is mainly because of the efficient cooling and proper lubrication of the abrasive particles on the working interface of the grinding wheel [26–28].

4 Conclusion The conclusion drawn from the analytical and experimental analysis of surface grinding of Inconel 718 superalloy in dry as well as in MQL environment is:

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• Maximum temperature difference between the experimental and simulated results noted was on average 10.13% for dry and MQL condition which is quite satisfactory. • Tangential and normal grinding forces recorded at various depth of cuts for MQL grinding are approximately, respectively, 34.04% and 21.5% lower than the tangential forces recorded for dry grinding. • Grinding temperature recorded at various depth of cuts for MQL grinding is approximately 47.71% lower than the temperature recorded for grinding under dry environment. • From the results obtained, it can be concluded that performance of grinding under MQL environment was better than under dry condition. From the mentioned findings, it can be concluded that the minimum quantity lubrication can improve the grinding performance of Inconel 718 superalloy.

References 1. Kovach JA, Malkin S (1988) Thermally induced grinding damage in superalloy materials. CIRP Ann Manuf Technol 37(1):309–313. https://doi.org/10.1016/S0007-8506(07)61642-4 2. Barczak LM, Batako ADL, Morgan MN (2010) A study of plane surface grinding under minimum quantity lubrication (MQL) conditions. Int J Mach Tools Manuf 50:977–985 3. Weinert K, Inasaki I, Sutherland JW, Wakabayashi T (2004) Dry machining and minimum quantity lubrication. CIRP Ann Manuf Technol. 53:511–537 4. Ezugwu EO, Wang ZM, Machado AR (1998) The machinability of nickel-based alloys: a review. J Mater Process Technol 86:1–16 5. Thakur DG, Ramamoorthy B, Vijayaraghavan L (2009) Machinability investigation of Inconel 718 in high-speed turning. Int J Adv Manuf Technol 45:421–429 6. Virdi RL, Chatha SS, Singh H (2021) Experimental investigations on the tribological and lubrication behaviour of minimum quantity lubrication technique in grinding of Inconel 718 alloy. Tribol Int 153:106581 7. Balan ASS, Vijayaraghavan L, Krishnamurthy R, Kuppan P, Oyyaravelu R (2016) An experimental assessment on the performance of different lubrication techniques in grinding of Inconel 751. J Adv Res 7:709–718 8. Li CH, Ding YC, Lu BH, Cai GQ (2009) Analytical and experimental investigation of the nickel based superalloy using cryogenic cooling grinding. Adv Mater Res 69–70:354–358 9. Balan ASS, Vijayaraghavan L, Krishnamurthy R (2014) Experimental investigation on the influence of oil mist parameters on minimum quantity lubricated grinding of Inconel 751. Int J Precis Technol 4:96 10. Pashmforoush F, Delir Bagherinia R (2018) Influence of water-based copper nanofluid on wheel loading and surface roughness during grinding of Inconel 738 superalloy. J Clean Prod 178:363–372 11. Sinha MK, Setti D, Ghosh S, Rao PV (2016) An alternate method for optimisation of minimum quantity lubrication parameters in surface grinding. Int J Mach Mach Mater 18 12. Naskar A, Singh BB, Choudhary A, Paul S (2018) Effect of different grinding fluids applied in minimum quantity cooling-lubrication mode on surface integrity in cBN grinding of Inconel 718. J Manuf Process 36:44–50 13. Balan ASS, Vijayaraghavan L, Krishnamurthy R (2013) Minimum quantity lubricated grinding of inconel 751 alloy. Mater Manuf Process 28:430–435

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14. Jia D et al (2017) Specific energy and surface roughness of minimum quantity lubrication grinding Ni-based alloy with mixed vegetable oil-based nanofluids. Precis Eng 50:248–262 15. Li CH, Lu BH, Ding YC, Cai GQ (2009) Innovative technology investigation into cryogenic cooling green grinding using liquid nitrogen jet. In: Proceedings of International Conference on Management and Service Science MASS, pp 1–4. https://doi.org/10.1109/ICMSS.2009.530 2527 16. Kundrák J, Markopoulos AP, Karkalos NE (2017) Numerical simulation of grinding with realistic representation of grinding wheel and workpiece movements: a finite volumes study. Proc CIRP 58:275–280 17. Lan S, Jiao F (2019) Modeling of heat source in grinding zone and numerical simulation for grinding temperature field. Int J Adv Manuf Technol 103:3077–3086 18. Zhang Y, Ge P, Lei Z, Jiang J (2012) The numerical simulation for thermal deformation in grinding hardening thin workpiece. Key Eng Mater 501:500–504 19. Brinksmeier E et al (2006) Advances in modeling and simulation of grinding processes. CIRP Ann Manuf Technol 55:667–696 20. Wang L, Qin Y, Liu ZC, Ge PQ, Gao W (2003) Computer simulation of a workpiece temperature field during the grinding process. Proc Inst Mech Eng Part B J Eng Manuf 217:953–959 21. Kuschel S, Kolkwitz B, Sölter J, Brinksmeier E, Heinzel C (2016) Experimental and numerical analysis of residual stress change caused by thermal loads during grinding. Proc CIRP 45:51–54 22. Ganesan M, Karthikeyan S, Karthikeyan N (2013) Prediction and optimization of cylindrical grinding parameters for surface roughness using Taguchi method. IOSR J Mech Civ Eng 39–46 23. Wenfeng D, Jiuhua X, Zhenzhen C, Honghua S, Yucan F (2010) Grindability and surface integrity of cast nickel-based superalloy in creep feed grinding with brazed CBN abrasive wheels. Chin J Aeronaut 23:501–510 24. Sharma AK, Tiwari AK, Dixit AR (2018) Prediction of temperature distribution over cutting tool with alumina-MWCNT hybrid nanofluid using computational fluid dynamics (CFD) analysis 25. Virdi RL, Chatha SS, Singh H (2019) Performance evaluation of inconel 718 under vegetable oils based nanofluids using minimum quantity lubrication grinding. Mater Today Proc 33:1538– 1545 26. Tawakoli T et al (2009) An experimental investigation of the effects of workpiece and grinding parameters on minimum quantity lubrication-MQL grinding. Int J Mach Tools Manuf 49:924– 932 27. Ramesh R, Vinothkumar S, Jie S, Manikandan N, Yanzhe Z (2019) Experimental and Taguchibased grey approach of laser metal deposition technique on nickel-based superalloy. Trans Indian Inst Met 72(1):205–214 28. Thirugnanasambantham KG, Ramesh R, Sankaramoorthy T, Velmurugan P, Kannagi A, Chaitanya KRM, Sai KCV, Mustafa MA, Ramesh CV (2018) Degradation mechanism for high-temperature sliding wear in surface-modified In718 superalloy. Cogent Eng 5:1501864

Investigating Machinability of Microalloyed Al-Cu Alloys by Simulation of Cutting Force Sanjib Gogoi , Bhargab Nath , Bhagyashree Konwar , Avinava Bora , Sanjib Banerjee , Satadru Kashyap , and Sushen Kirtania

Abstract Due to unique combinations of properties, and mainly high specific strength, Al alloys are manifesting remarkable increase in strong lightweight structural applications, including all ranges of land and water-borne vehicles, as well as aerospace. 2219Al alloy is a precipitation-hardenable high-strength alloy, exhibiting superior machinability, weldability, fracture toughness and corrosion resistance. It can be microalloyed (< 0.1 wt.%) with elements like Sn, In, Cd, Ag, Si, etc.to further improve its structure and property, without compromising on material weight. Present research is aimed at investigating machinability of rolled and peak-aged 2219Al alloy and same alloy with trace additions (0.06 wt.%) of Cd. Machinability was estimated based on criteria of three mutually perpendicular cutting force components, under different cutting conditions of feed, speed and depth of cut. Individual influences of cutting parameters, as well as microalloying on machinability of the alloy were characterized. Artificial neural network (ANN) modeling was employed to further predict cutting force components, as a function of three independent and external cutting parameters. Cutting force values subsequently predicted at different cutting conditions were compared and correlated with experimental results within satisfactory accuracy limits, yielding excellent prediction of 100% datasets within ± 15% deviation, and with RMS error values of 0.01 and 0.19 for the investigated alloys. Such observation highlights the superior prediction capability of ANN technique in modeling and characterizing machinability. The intelligent manufacturing system with ANN is capable to estimate cutting forces, and hence formulate and optimize cutting parameters based on material machinability. Keywords Aluminum alloys · Microalloying · Machinability · Cutting force · Artificial neural network

S. Gogoi (B) · B. Nath · B. Konwar · A. Bora · S. Banerjee · S. Kashyap · S. Kirtania Department of Mechanical Engineering, Tezpur University, Tezpur 784028, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_23

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1 Introduction It has been realized by the manufacturing engineers and researchers that the metallic alloys must possess light weight and superior mechanical properties, suitable for automobile, marine and aeronautical industries [1]. In this perspective, aluminum (Al) alloys are gaining huge industrial significance due to their light weight, along with superior mechanical and physical properties. These mechanical properties can be enhanced by means of numerous processing techniques, precipitation strengthening being one of the most significant of them [2, 3]. Precipitation strengthening can majorly increase the hardness and overall mechanical strength in heattreatable Al alloys. Aluminum (Al) alloys, particularly the wrought and precipitationstrengthened 2xxx, 6xxx and 7xxx series of Al alloys, were widely studied in this regard [4]. The composition, microstructure, strain history and thermomechanical treatments affect the structure and characteristics of these wrought Al alloys. Among 2xxx series, 2219Al alloy is a two-phase hypoeutectic Al-Cu alloy system, with exemplary blend of elevated strength-to-weight ratio, ductility, fracture toughness, resistance to corrosion, weldability, production efficiency along with improved properties at cryogenic temperatures. Subsequently, 2219Al alloy is used in the fabrication of supersonic aircraft skin and structural members like space boosters, rocket fuel tanks and fins, etc. Recent trend in alloy development is to microalloy (adding trace contents < 0.1 wt.%) with elements like Ag, In, Sn, Cd, etc. Microalloying may actually combine elevated mechanical strength with significant toughness, while still maintaining lower density [5, 6]. Machinability is important from an industrial perspective, because easily machinable alloys with considerable strength are desired, which actually saves machining cost without compromising on performance of the alloys. Al alloys can be made more brittle to increase their machinability, which is evidently observed in 2007Al, 2011Al and 6020Al alloys having superior machinability [7]. Higher cutting speeds, as well as higher rake and relief angles, are generally appropriate for machining wrought Al alloys. It is also necessary to determine optimum cutting conditions to maximize tool life and subsequently reduce the cutting cost. Tool life and power consumed are proportional to the cutting forces experienced, hence cutting force is one of the most important criteria to measure machinability of a material. A clear mapping of variation of cutting force components with cutting conditions helps to estimate the power requirement of the machining process and thus the machinability of the work material. The effect of microalloying with various elements on microstructure and mechanical properties of several commercialized Al alloys has been studied. It was reported that for trace addition of Sn (0.15 wt.%) to Al–Si–Mg alloy, ductility and toughness increased with a concomitant decrease in strength and hardness [7]. Adding 0.05 wt.% of Sn assisted Al-7wt.%Si-0.35wt.%Mg alloy to attain its best mechanical properties. The mechanical strength and hardness of 2219Al alloys increased due to microalloying with 0.06 wt.% Sn, and later decreased with further Sn contents

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[8–12]. Increase in strength and hardness resulted in a subsequent decrease in machinability for the alloys. It has been observed that the strength and hardness of 2219Al alloy increased considerably with a reduction in ductility, on adding 0.06 wt.% of Cd content [13–15]. Another study on Al-Cu-Mg-Mn-Zr alloy with 0.48 wt.% Ag revealed that age-hardening was accelerated, and peak hardness level was increased, while improving the thermal stability [5]. Microalloying with both Si and Ge revealed that the Al alloy 2219SG achieved maximum hardness 3 times faster, compared to the alloy 2219S (containing only Si) for the same degree of microalloying [6]. Investigations on machining of Al alloys reported that it involves low cutting forces and relatively high tool life without built-up edge or material adhesion, attributing to easier machinability [7]. A study on cutting forces of A97075 Al alloy shows that the cutting force components are more sensible to the variations in cutting conditions, compared to rest of the parameters analyzed [6]. Al alloys have been overall reported to have comparatively higher machinability than steel, due to the lower amount of power involved during machining operation [7]. The current research trend has prime focus on applications of artificial neural networks (ANNs) for modeling machinability by achieving a precise network architecture. ANN is just a data-driven method that predicts the solution even when the specific input–output correlation is unknown [12]. An investigation on the use of ANN in examining and predicting the mechanical properties of A413 Al alloys generated accurate predictions and considered ANN as a boon in terms of cost and time savings [11, 12]. Microalloying elements may change the properties of Al alloys, by altering composition and morphology of the microstructural phases, entire range of mechanical behavior, including the machinability [5, 6]. Information available regarding effect of microalloying on structure and characteristics of Al alloys is quite limited. Influence of trace Cd additions, in particular, on heat-treatable Al alloys of 2xxx series, is yet to be documented. Therefore, in the present research work, the influences of trace contents of Cd, as well as various external parameters (viz. feed, speed and depth of cut) on components of cutting force have been investigated, as criteria for measuring machinability of 2219Al alloy. It is aimed at characterizing the machinability of rolled and peak-aged 2219Al alloy and same alloy with trace contents (0.06 wt.%) of Cd, by measuring the cutting forces under varying cutting conditions during facing operation. The trace content of 0.06 wt.% Cd was selected because in a parallel research work, strength and hardness were observed to be higher for this alloy [13–18]. Cutting force of both the alloys was modeled and predicted as a function of three independent externally controllable cutting parameters, by using artificial neural network (ANN). The cutting force values subsequently predicted at various cutting conditions were compared and correlated with experimental results within satisfactory accuracy limits. Statistical error analysis was performed, which highlights the superior prediction capability of ANN technique in modeling machinability. Moreover, such intelligent modeling and prediction with ANN can provide immense industrial help by estimating the cutting forces and hence machinability, and thus formulating and optimizing the cutting parameters based on material machinability.

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2 Experimental Methodology 2219Al alloy with 6.3 wt.% Cu (Alloy-A) and same alloy with trace contents (0.06 wt.%) of Cd (Alloy-B) were processed by standard foundry technique, in a resistance heated melting furnace [5]. Generally, the high-performance mechanical properties of Al alloys can be attained through thermomechanical treatment (TMT), constituting three major sequential stages of solid solution heat treatment followed by quenching, then plastic deformation and lastly aging. This TMT process can impose highest strength and hence wear resistance of a material by the combined effect of deformation strengthening during metal forming and transformation strengthening during age-hardening heat treatment. TMT process can significantly refine the precipitates and produce mesh substructure by intertwined dislocation with the precipitated phase, which can enhance the mechanical properties of Al alloys to a much higher extent. Therefore, following precipitation hardening protocol, the cast alloys were first solutionized (10 h at 525 °C) and quenched. The cast and solutionized machined alloy strips were preheated at 200 °C for 2 h and subsequently warm-rolled at the same temperature in a laboratory-scale rolling mill. Rolling operation was carried out in eight number of passes, to achieve a final reduction in strip thickness from 10 to 6 mm (i.e. 40% reduction). Now, age-hardening conditions become necessary to be optimized due to lack of open literature and information relevant to peak-aging time of 2219Al alloy microalloyed with Cd. In a parallel research, age-hardening behavior was therefore separately studied to estimate the corresponding aging time to achieve peak hardness. Most of the 2xxx series Al alloys were age-hardened at temperatures between 160 and 190 °C [8]. For present alloys, a precipitation temperature of 170 °C has been adopted to obtain isothermal age-hardening curves. For different aging times, Vickers hardness (VHN) was evaluated, to determine aging time necessary for each alloy to achieve maximum hardness. This peak-aging time was evaluated to be 40 h for the investigated solutionized alloys, at the given precipitation temperature of 170 °C. As compared to the cast alloys, an average increase in hardness value by around 147% could be observed, due to this peak-aging treatment. Therefore, during the current study, the solutionized and rolled samples were further age-hardened for a period of 40 h at 170 °C. Cubical samples of size 10 × 10 × 6 mm3 were machined from the rolled and peak-aged alloys, for conducting the facing operation. A three-jaw metal-working lathe (Model: NH26, Make: HMT MACHINE TOOLS LTD) was used to investigate the machinability of the samples, by performing facing operation on the cubical samples. Cutting tools made of high-speed steel were used. During the experiments, instead of the tool holder, a piezoelectric tool dynamometer (Model: 620B, Make: IEICOS LATHE TOOL DYNAMOMETER) was used in the carriage, which actually calculated the cutting force components using the piezoelectric principle. The dynamometer was further coupled with a multi-component force monitor, which reported the magnitude of the cutting forces in all three mutually perpendicular directions. Forty-eight facing operations were performed on each of the investigated alloys, using four different speeds, four feed rates and three different

Investigating Machinability of Microalloyed … Table 1 Selected values of cutting speed, feed rate and depth of cut for facing operation

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S. No.

Cutting speed (rpm)

Feed (mm/rev)

Depth of cut (mm)

1

119

0.1

0.2

2

290

0.32

0.4

3

550

0.64

0.6

4

840

1.04

depth of cuts, as shown in Table 1. The cutting force components were calculated during each facing operation, under given set of cutting conditions. The influences of cutting conditions, as well as microalloying composition on the cutting force component, were studied, and machinability was further estimated. ANN simulation was used to model and further predict the cutting forces of the investigated alloys, within the experimented domain. In the present modeling, three input parameters, i.e. feed, speed and depth of cut, were represented by three neurons in the input layer, a single layer of hidden neurons and one neuron in the output layer corresponding to the output parameter of cutting force, which generated the data sets for the network’s training. Present modeling was performed by using ‘ANN tool kit’ at ‘MATLAB’ software package and ‘TRAINLM’ function following ‘Levenberg– Marquardt optimization’ [16]. During training and testing phases of each trial, the mean square error (MSE) was determined. The least MSE value acquired during training and testing stages was used to identify the best-fit network architecture. Once proper network architectures are arrived at for the alloys, the cutting force can be accurately predicted for any set of input parameters within the given domain range.

3 Results and Discussion 3.1 Variations in Cutting Force Taking into account that during the facing operation, larger magnitude of cutting force was experienced in Y-direction, and the effect of cutting parameters on the cutting force component F y in particular was considered to evaluate the experimental trends. Figures 1 and 2 reveal the variations of cutting force component F y with the cutting parameters of feed, speed and depth of cut, respectively for Alloy-A and Alloy-B. In these plots, solid lines represent the trends observed for the experimental data of cutting force with variation in different cutting conditions, while the dashed lines represent the variations of the predicted cutting force data (by ANN). It was observed that up to a certain speed of 550 rpm, the variation in experimental cutting force component (F y ) was insignificant. However, with further increase in spindle speed, cutting force increased rapidly at given values of feed and depth of cut. Such variation

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was especially observed to be prominent toward the higher feed ranges, as the vibration of work piece is also comparatively higher. At higher speeds, the temperature of the work material also increases due to faster rate of shearing, and as such, built-up edges are formed. In order to break these built-up edges, the experimental cutting force slightly increases with increasing cutting speed. F y increased with increasing feed rate for the investigated alloys, at given values of speed and depth of cut, indicating lower machinability. As the feed rate is increased, volume of the sheared chip increases along with higher resistance to metal fracture, consequently necessitating higher chip removal efforts. Hence, the estimated cutting force increased significantly, with an average of around 19.1%, with increasing feed rate values. Further as the depth of cut increases, F y of both the alloys was observed to increase drastically, and such increasing trend was reported at various given conditions of cutting speed and feed. Under higher depth of cut, the chip thickness significantly increases, which actually increases the metal volume deformed (metal removal rate, MMR), subsequently requiring enormous cutting forces to cut the chips. The cutting force component increased significantly by an average of around 15.4%, with increasing depth of cut. However, this dependence was observed to be almost linear. Therefore, in contrast to cutting speed, depth of cut and feed rate were reported to have significant impacts on cutting force.

Fig. 1 Comparison of experimental and predicted trend of cutting force with, a speed, b feed and c depth of cut for alloy-A

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Fig. 2 Comparison of experimental and predicted trend of cutting force with (a) speed, (b) feed and (c) depth of cut for Alloy-B

Analogous to Alloy-A, the cutting force of Alloy-B increased with increase in different cutting parameters of feed, speed and depth of cut. Nevertheless, such increases were observed to be steeper and more significant for Alloy-B, conforming it to have a lower machinability, as compared to Alloy-A. The experimental results further revealed that for any given set of cutting conditions, the average % increase in F y was 25.3%, due to trace additions of 0.06 wt.% of Cd. In a parallel research work, it has been observed that the strength and hardness of 2219Al alloy increased considerably with a reduction in ductility, due to adding trace contents of 0.06 wt.% Cd [13–15]. Similar increases in strength and hardness, as well as cutting force of this alloy system, were also reported due to adding trace contents of Sn [8–12]. As such, although the mechanical property of 2219Al alloy improved due to microalloying with Cd, a considerable increase in cutting force and hence cutting power could be observed for the alloy system. Therefore, while machinability is evaluated with cutting force or cutting power as the criteria, microalloying with Cd imparted a lower machinability to the 2219Al alloy system, which may in turn affect the manufacturing efficiency of this alloy. In other words, the given alloy may be microalloyed only with a clear objective of either higher mechanical strength or machinability.

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3.2 Artificial Neural Network (ANN) Modeling of Cutting Force To predict the values of cutting force at various combinations of cutting conditions, and thus to investigate the machinability of the alloy at any given condition, ANN modeling was performed. The idea behind this is that cutting force is a function of cutting parameters, as per the following equation: Fy = f (feed, cutting speed, depth of cut)

(1)

The suitable weights and bias of ANN network were evaluated by training it with various datasets. For modeling of F y under different cutting conditions, a total number of 48 input–output datasets were used from the experimental results of each alloy. Following the Pareto principle [11, 12], 80% data was chosen for training, and the rest 20% data has been used for performing testing and validation. Training and testing of the network were carried out independently. The RMS error was employed as a criterion for evaluating effectiveness, for selecting the best network architectures, which can be expressed as: / RMSerr =

⏋2 ∑ ⌈ (Fy )exp −(Fy )pre n

(2)

where (F y )exp is experimental cutting force value and (F y )pre is predicted value of corresponding cutting force. RMSerr values were calculated separately both for training and testing stages. Table 2 shows the neural network architectures that best fitted with the alloys studied. After finalizing the architecture, the trained network was used to predict F y using the validation datasets. Figures 1 and 2 reveal the superimposition of experimental and predicted trends (by ANN) observed in the variations of F y for the alloys, with different cutting conditions. For both the investigated alloys, a close conformity is observed between the predicted cutting force values and the experimental data in their trend lines, almost overlapping each other. However, at higher speeds and feed rates, the predicted trend deviates slightly from the experimental results due to higher magnitudes of experimental F y caused by vibrations. Similar to the experimental trends for both the alloys, predicted F y was also observed to increase with increasing cutting parameters of feed, speed and depth of cut. Furthermore, predicted F y of the base alloy was also Table 2 Final neural network architectures

Sample-ID

Hidden neurons

First transfer function

Second transfer function

Alloy-A

3

Logsig

Purelin

Alloy-B

4

Tansig

Purelin

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observed to increase due to trace additions of 0.06 wt.% Cd, in proportion with the experimental results.

3.3 Statistical Error Analysis Table 3 shows the error values during prediction of cutting force component, as obtained during testing and validation stages of ANN modeling for the investigated alloys. The results reveal that although the predicted values slightly deviate from the experimental results, the percentage and RMS errors are within the satisfactory limits. RMS errors for testing were registered to be 0.01 and 0.19 respectively for Alloy-A and Alloy-B. Although highest absolute error in prediction for Alloy-A was estimated to be 0.72, the error percentage is just 10.74%. The absolute error shows a relatively higher value, since the magnitude of F y is also in the higher side. Subsequently, for low values of F y (viz. 1), although the absolute error is only 0.03, the percentage error registers comparatively a high value of 2.75%. For Alloy-B, the maximum absolute error during prediction was 2.19, where the percentage error was evaluated to be only 13.56%. This can be confirmed from Fig. 3, where predicted vs. experimental cutting force values are shown for testing and validation datasets of the alloys studied. All the points should be on solid line at angle 45° to X-axis, to represent perfect prediction. The same figure also includes sets of dotted lines that indicate the boundaries of ± 15% deviations. The figures reveal that majority of points are quite close to perfect prediction. These plots conform the accuracy of prediction by ANN technique, with all data points lying within percentage deviation of ± 15%. However, the percentage deviation was reported slightly higher for very few cases, due to fluctuating and unpredictable experimental results obtained at higher values of cutting parameters. Figure 4 presents the distribution of percentage errors for the data points of the investigated alloys, obtained during testing and validation stages. The bar graphs confirm the capability of the ANN architectures in accurately predicting the cutting forces of both the alloys. The maximum percentage errors considering testing and validation phases combined were reported to be 13.5% and 13.6%, respectively for Alloy-A and Alloy-B. This observation along with the low values of RMS errors registered determines the superior prediction capability of ANN modeling. Further, resulting from the intelligent processing and manufacturing system with ANN, cutting parameters may be subsequently formulated and optimized, based on the machinability of the material. Table 3 Maximum % and RMS errors evaluated during testing and validation Testing

Validation

Sample-ID

Max % error

RMS error (kgf)

Max % error

RMS error (kgf)

Alloy-A

13.53

0.01

10.74

0.57

Alloy-B

13.56

0.19

4.06

0.05

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Fig. 3 Variation of predicted with experimental cutting force for, a alloy-A and b alloy-B

Fig. 4 Distribution of percentage errors during prediction of cutting force for, a alloy-A and b alloy-B

4 Conclusions 1. 2219Al alloy and same alloy with trace contents (0.06 wt.%) of Cd were processed by standard foundry technique, and subsequently rolled and peak-aged. 2. The machinability of both the alloys was investigated during facing operation, under varying cutting parameters of feed, speed and depth of cut. The influences of cutting conditions, as well as microalloying composition on the cutting force component, were studied. 3. The cutting force of the investigated alloys increased with increasing feed and depth of cut. The variation of cutting force was observed to be initially negligible at lower cutting speed values, however cutting force increased with higher levels of cutting speed. 4. The cutting forces of the investigated 2219Al alloy system were observed to increase by 25.3%, attributing lower machinability, due to trace addition of Cd,

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5.

6. 7.

8.

285

for almost all the experimented cutting conditions. Thus, there was a pronounced impact of microalloying with Cd, on the machinability of the base alloy. Cutting force of both the alloys was modeled and predicted as a function of three independent externally controllable cutting parameters of feed, speed and depth of cut, by using ANN. Cutting force values predicted using ANN were correlated with experimental results under various cutting conditions, with fair good accuracy. Statistical error analysis was performed. The final and best-fit network architecture yielded excellent prediction of 100% cutting force values of both the alloys, within a percentage deviation of ± 15%, and with RMS values of 0.01 and 0.19, respectively for the base alloy and alloy containing trace additions of Cd. This highlights superior prediction capability of ANN technique in modeling machinability. Resulting from the intelligent processing and manufacturing system with ANN, cutting parameters may be subsequently formulated and optimized, based on the machinability of the material.

References 1. Dieter GE (1988) Engineering design: a materials and processing approach, 2nd edn. McGrawHill Books Company, Japan 2. Callister WD (1997) Material science and engineering: an introduction. 4th edn John Wiley & Sons 3. Rana RS, Purohit R, Das S (2012) Reviews on the influences of alloying elements on the microstructure and mechanical properties of aluminium alloys and aluminium alloy composites. Int J Sci Res Publ 2(6):2250–3153 4. ASM handbook (1990) Properties and selection: nonferrous alloys and special-purpose materials. ASM Int 2 5. Hirosawa S (2000) Classification of the role of microalloying elements in phase decomposition of Al based alloys. Acta Mater 48(2):1797–1806 6. Sercombe TB (1999) On the use of trace additions of Sn to enhance sintered 2xxx series Al powder alloys. Mater Sci Eng 7. Schneider G (2009) Machinability of metals. Am Mach 9 8. Banerjee S, Robi PS, Srinivasan A, Lakavath PK (2010) Effect of trace additions of Sn on microstructure and mechanical properties of Al-Cu-Mg alloys. Mater Des 31:4007–4015 9. Banerjee S, Robi PS, Srinivasan A (2010) Calorimetric study of precipitation kinetics of AlCu-Mg and Al-Cu-Mg-0.06 wt.% Sn Alloys. Met Mater Int 16(4):523–531 10. Banerjee S (2011) Mechanical properties and high temperature deformation behaviour of AlCu-Mg alloys microalloyed with Tin. Doctoral Thesis, IIT Guwahati, Assam, pp 1–176 11. Banerjee S, Robi PS, Srinivasan A (2012) Prediction of hot deformation behavior of Al-5.9%Cu-0.5%Mg alloys with trace additions of Sn. J Mater Sci 47(2):929–948 12. Banerjee S, Robi PS, Srinivasan A (2012) Deformation processing maps for control of microstructure in Al-Cu-Mg alloys microalloyed with Sn. Metall Mater Trans A 43A:3834– 3849 13. Gogoi S (2017) Effect of rolling and age-hardening on the mechanical properties of microalloyed 2219 Al alloy. M.Tech Thesis, Department of Mechanical Engineering, Tezpur University 14. Banerjee S, Bhadra R, Gogoi S, Dutta RS (2020) Investigating weldability in microalloyed Al alloys. Adv Mech Eng 271

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15. Banerjee S, Gogoi S (2016) Influence of trace addition of Cd on the hardness and impact properties of 2219 Al alloy. J Basis Appl Eng Res 13(3):1202 16. Robi PS, Dixit US (2003) Application of neural networks in generating processing map for hot working. J Mater Process Technol 142(2):289–294 17. Jeyaprakash N, Muthukannan D, Ramesh R (2018) Modelling of Cr3C2–25% NiCr laser alloyed cast iron in high temperature sliding wear condition using response surface methodology. Arch Metall Mater 63(3):1303–1315 18. Giridhar D, Ramesh R (2020) Contact stress evaluation of micro-grooving process of alumina ceramic and validation with acoustic emission parameters. Lecture notes in mechanical engineering, advances in industrial automation and smart manufacturing. Springer, pp 597–617

Electrochemical Analysis of Corrosion Inhibition of Low Carbon Steel in 0. 1 N HCl by Bottle Gourd Peels Pragati Srivastava, Shweta Pal, Vinit Kumar Jha, Gopal Ji, and Rajiv Prakash

Abstract Corrosion of metals greatly affects its efficacy of being functional in the surrounding environment. This can have a big impact on the economy and can cause risk to the humans. These negative effects of corrosion can be minimized in different ways; however, use of a biodegradable and cheap inhibitor is a better choice for this purpose. This work discusses use of a similar kind of biodegradable inhibitor (Bottle Gourd peels) for low carbon steel (LCS) corrosion prevention in 0.1 N HCl. Aqueous extract of Bottle Gourd peels (AEBGP) is tested by UV–visible spectroscopy (UVS), FTIR spectroscopy (FTIRS), open circuit potential (OCP) curves, electrochemical impedance spectroscopy (EIS), Tafel polarization curves (TPC), and scanning electron microscopy (SEM). The analysis of AEBGP by UVS and FTIRS reveals that AEBGP possesses several biomolecules. These biomolecules may adsorb on LCS and thus can protect LCS from corrosion. Based on investigation in this work, the maximum inhibition received is 83% (TPC). The inhibition is also realized in SEM images. Keywords Steel · Corrosion · Bottle gourd · Inhibition · EIS · SEM

1 Introduction Metals are the necessary items required for various technological and commercial applications. In most of the applications, metals have to withstand aggressive environments. These environments try to demolish metals. Thus, the metals are vulnerable to high risk of failure in these environments [1, 2]. To avoid any possible demolition, corrosion of the metals should be effectively controlled. Regarding this, there are several established methods [3, 4]. However, inhibitors obtained from biodegradable P. Srivastava · V. K. Jha · G. Ji (B) Centre for Advanced Studies, Lucknow 226031, India e-mail: [email protected] S. Pal · R. Prakash School of Materials Science and Technology, IIT BHU Varanasi, U.P, Varanasi 221005, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_24

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sources have been one of the efficient, demonstrated, and low cost methods for corrosion prevention [5, 6]. There are many reports that claim that waste and biodegradable materials can provide good degree of corrosion inhibition [7–9]. These materials show great attraction toward metallic surface and cover them via adsorption of its phytoconstituents over metal surface [10]. In this work, Bottle Gourd peels have been used to evaluate its corrosion inhibition properties against LCS corrosion. Bottle Gourd is also recognized as ‘Loki/Dudhi’ in India and associated with Cucurbitaceae family. The scientific name of Bottle Gourd is Lagenaria Siceraria. The Bottle Gourd peels are rich in flavonoids and terpenoids like molecules [11–13]. These molecules are quite chemically active and can mount up on metal surfaces via adsorption. In addition, Bottle Gourd peels are waste and biodegradable material, and hence not toxic. These all virtues make Bottle Gourd peels a perfect candidate for corrosion inhibition. As far as selection of LCS is concerned, the LCS is selected for its good structural strength, low cost, wide application, and easiness in transportation [14]. The aim set for this work is to find out LCS corrosion inhibition in 0.1 N HCl by AEBGP through UVS, FTIRS, OCP, TPC, EIS, and SEM. The results are stimulating and discussed in detail in corresponding sections of the work. Based on the results, it can be recommended that AEBGP can be a good inhibitor for LCS corrosion in HCl.

2 Experimental Details 2.1 Extraction Green Bottle gourd was fetched from a local vegetable shop in Lucknow, India. The bottle gourd was rinsed, and the peels were collected by careful scarping of the bottle gourd. Then, the peels were cut into many pieces and kept on drying at 35 °C for 6 h in electricity-operated oven. The desiccated peels were then powdered in a kitchen grinder. The powder of leaves (5 gm) was soaked in 500 mL of water and put on stirring at 600 rpm for 2 days followed by filtration. It was observed that the powder was not dissolved completely and a residue equivalent to 1.5 gm (in dried state) was received after filtration. Based on that, it was calculated that the resultant solution was having peels concentration of approximately 7 mg mL−1 . This solution was used without any further purification for the examination. The schematic diagram of extraction method is illustrated in Fig. 1.

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Fig. 1 Illustration of the extract preparation

2.2 Testing of the Extract The extract was examined by BioTek spectrophotometer (UVS) and Thermo Scientific Nicolet 6700 (FTIRS). A 100μL of AEBGP was examined in ranges of 200– 900 nm in UVS and 400–4000 cm−1 in FTIRS. The obtained spectrum was compared with other reports and standard database, and different biomolecules were predicted.

2.3 Test Specimen The LCS test strips used in this work were initially 5 × 1.5 cm in size. LCS strips were scrubbed by abrasive paper (2/0 and 3/0) of Sianor B and cleaned with ethanol. For electrochemical experiments, the strips were masked to provide effective area of 1 × 1cm2 .

2.4 Electrochemical Tests All the electrochemical work was done on CH workstation (7041C). Silver/silver chloride as reference (Metrohm), platinum foil as counter (Metrohm), and LCS specimen as working electrodes were used in the experiments. The first electrochemical test done on the strips was OCP monitoring for 400 s. At the end, EIS was done with a sinusoidal AC signal of 0.005 V (R.M.S) in the range of 100,000–0.01 Hz. After that, Tafel test was conducted in the voltage range of 0.5 V with respect to OCP of the electrodes at 0.005 V s−1 . The obtained Tafel curves were individually analyzed by extrapolation, and various parameters like corrosion potential (E corr ) and corrosion current density (I corr ) were determined. The efficiencies of protection (µp ) were calculated by the equation given below [15, 16].

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µ p (%) =

o i − Icorr Icorr × 100 o Icorr

(1)

where superscripts ‘o’ and ‘i’ denote I corr in pure HCl and in HCl with different amounts of AEBGP, respectively.

2.5 Surface Analysis The prepared LCS strips were cut into the sizes of 1.5 × 1.5 cm and immersed in 15 mL of pure 0.1 N HCl without and with optimum amount of AEBGP for 5 h. After that, the solutions were drained and the strips were cleaned by distilled water. The strips were de-moisturized in vacuum desiccators for one day and after that examined by ZEISS GEMINI FESEM. The details are given in the work of Ji et al. [15, 16].

3 Results and Discussion 3.1 AEBGP Synthesis The major compounds usually found in bottle gourd peels are flavonoids and terpenoids [11–13]. UV-visible spectra of AEBGP (Fig. 2a) showed three absorption peaks indicating that some of the aforesaid biomolecules could be present in the extract. A peak at 272 nm could show the presence of Catechin-like flavonoid in the extract [17, 18]. A peak at 205 nm could indicate the presence of terpenoids in the extract [19, 20]. A peak at 334 nm could correspond to aromatic ring-containing compounds [21, 22].

Fig. 2 a UV-visible and b FTIR spectra of AEBGP

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Through FTIRS, many peaks emerged in the spectra of AEBGP (Fig. 2b). These peaks could belong to vibration frequencies of various active compounds of the extract. The peaks and their correspondence could be given as: 3412 cm−1 , O– H/N–H stretching; 2927 cm−1 , C-H stretching; 2351 cm−1 , aromatic C-H stretching; 1600 cm−1 , C = C stretching; 1381 cm−1 ; C-H bending; 1248 cm−1 , C-O stretching of alcohols; 1071 cm−1 , C-O stretching; and 551 cm−1 and 776 cm−1 for C-H bending of aromatic rings of the compounds [11, 13, 22]. Based on the results, it could be said that AEBGP was successfully synthesized and was having various biomolecules, which could impart good protection properties to the extract.

3.2 Electrochemical Corrosion Measurements Figure 3 shows OCPs variation of LCS substrates immersed in HCl and HCl + AEBGP solution in first 400 s of immersion. It was evident that OCPs were looking quite stable in 400 s; however, careful observation revealed that it was tending toward stability. It was noticeable that OCP shifted to positive potential with increase in AEBGP concentration. This fact indicated that AEBGP could act as anodic inhibitors [23]. After 400 s of immersion, EIS test was performed using end OCP voltage. The EIS test results are shown in Fig. 4. The impedance can be defined as the distance between first and last cross section of the curve with X axis, in case of one time constant. It was evident that impedance of LCS substrates was increasing with the AEBGP concentration. This fact showed that greater protection of LCS was achieved by AEBGP [24]. Figure 4b illustrated that phase angle was the lowest for bare LCS and the highest for 800 mg L−1 of AEBGP, which revealed the fact that AEBGP was providing protection to LCS [25]. The reason of the protection could be mentioned as LCS surface blockage by AEBGP molecules. The inhibitive molecules could be adsorbed on various locations of LCS surface and block the access of LCS for Fig. 3 OCPs for LCS substrates in 0.1 N HCl at 25 ± 2 °C for 400 s

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dangerous chloride ions. As a result, the LCS corrosion was slowed down and it was evidenced by increased impedance of LCS in HCl + AEBGP solutions. However, AEBGP could not completely block the access of LCS for HCl that was why 100% protection was not achieved. Figure 5 shows Tafel curves for LCS immersed in HCl and HCl + AEBGP solutions. In initial analysis, it was recognized that corrosion currents and corrosion potentials (obtained by cross section of the curves) were moving toward lower current region and slightly positive potential, respectively. This information claimed that AEBGP was protecting LCS in HCl by blocking anodic reactions (major), which was in agreement with OCP shift toward positive potentials [26]. However, it was recognized by vigilant analysis of the curves that both polarization curves were showing shift, which suggested that AEBGP was blocking both cathodic and anodic reactions of LCS in HCl [27]. The E corr , I corr , and %µp were calculated from the curves and written in Table 1. Based on Table 1, it could be claimed that E corr was moving toward positive values

Fig. 4 a Nyquist and b bode phase curves showing impedance date for LCS in 0.1 N HCl and HCl + AEBGP at 25 ± 2 °C Fig. 5 Tafel polarization curves and zoom view (inset) for LCS and LCS + AEBGP in 0.1 N HCl at 25 ± 2 °C

Electrochemical Analysis of Corrosion … Table 1 Major parameters extracted from polarization curves shown in Fig. 5

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Coatings

−Ecorr (V)

Icorr (μA cm−2 )

%μp

0.1 M HCl

0.500

66

–

0.1 M HCl + 200 mg L−1

0.494

37

44

0.1 M HCl + 400 mg L−1

0.496

25

62

0.1 M HCl + 800 mg L−1

0.495

11

83

with the AEBGP concentration increased, which confirmed that protection of LCS by AEBGP was achieved through more suppression of anodic reactions occurring at LCS surface in HCl [28, 29]. However, E corr shift with respect to LCS in 0.1 N HCl was not greater than 85 mV, which claimed that AEBGP acted as a mixed effect inhibitor. Furthermore, it was recognized that I corr of LCS was lesser in HCl + AEBGP solutions. Also, LCS in HCl with 800 mg L −1 AEBGP was showing more inhibition (83%) in comparison with 400 mg L −1 AEBGP (62%). This fact indicated that maximum protection of LCS was realized with 800 mg L −1 AEBGP. The proposed cause for protection was that AEBGP was adsorbed on LCS surface and covered different active locations on LCS surface. The chloride molecules could not reach those passive locations, and thus, LCS corrosion was slowed down. However, the 100% protection was not achieved because AEBGP could not deactivate all the active locations on LCS surface.

3.3 SEM Analysis Figure 6 shows SEM surface images of LCS, LCS immersed in HCl and HCl + 800 mg L −1 AEBGP solutions. It was evident after inspection of SEM images that AEBGP was protecting LCS in HCl. Figure 6a showed surface of the bare LCS, which suggested that eradication and stretch marks were appeared on the surface due to rough scrubbing. However, the surface was still looking in better condition. The HCl reacted with the surface and introduced lot of irregularities with cracks and holes, which was clearly observable in Fig. 6b. The rough surface showed high damage of LCS surface in HCl [30]. In contrast, AEBGP-covered LCS surface (Fig. 6c) was not showing serious damage in comparison with the surface in Fig. 6b. However, the surface was showing some damage that indicated that 100% protection of LCS in HCl was not possible with AEBGP.

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Fig. 6 Showing SEM images of, a prepared test specimen of LCS, b corroded in 0.1 N HCl and c LCS + 800 mg L −1 AEBGP corroded in 0.1 N HCl at room temperature

3.4 Proposed Mechanism of Corrosion Inhibition The LCS immersed in HCl could be destroyed easily because there was nothing to protect LCS. In this situation, different corrosion products of iron could form and cover the LCS surface after some time of immersion. Due to this, a minute reduction in corrosion could be observed for some period. However, the films of corrosion products formed over LCS surface could not offer long-term protection (more than a few hours) because of its high solubility in HCl. In contrast, a layer of AEBGP molecules could protect LCS in HCl easily because of its low solubility in HCl. These AEBGP molecules could cover LCS surface via adsorption and remain at adsorbed location for a long time. However, AEBGP molecules could not be adsorbed at each location on LCS surface, and hence, 100% protection is not achieved.

4 Conclusion In this work, a biodegradable material (Bottle Gourd peels) was used to protect LCS in hydrochloric acid. The AEBGP was examined for availability of biomolecules by

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UVS and FTIRS, which revealed that AEBGP was containing active biomolecules. The inhibition by AEBGP was checked with electrochemical measurements and SEM. The electrochemical measurements claimed that LCS corrosion was suppressed by AEBGP with more than 80% efficiency. The inhibition was also clearly evidenced in SEM images. Based on the results, a mechanism of inhibition was also proposed, which include that adsorption for AEBGP molecules on LCS and coverage of LCS by those molecules were the prime reason for inhibition. Based on overall analysis, it could be recommended that AEBGP provided protection to LCS in 0.1 N HCl. Acknowledgements Er. Pragati Srivastava is thankful to Dr. Piyush Jaisawal and Dr. Anuj kumar Sharma (Both from CAS Lucknow) for their guidance during this work. Conflict of Interests Authors declare null conflict of interests.

References 1. M. G. Fontana, Corrosion engineering, Second Edition, (1968). 2. Liu Y, Song Z, Wang W, Jiang L, Zhang Y, Guo M, Song F, Xu N (2019) Effect of ginger extract as green inhibitor on chloride-induced corrosion of carbon steel in simulated concrete pore solutions. J cleaner Prod 214:298–307 3. Cachet C, Ganne F, Joiret S, Maurin G, Petitjean J, Vivier V, Wiart R (2002) EIS investigation of Zinc dissolution in aerated sulphates medium. Part II: Zinc Coat Electrochim Acta 47:3409– 3422 4. Pandey RK, Mishra R, Ji G, Prakash R (2019) Corrosion prevention of commercial alloys by air-water interface grown, edge on oriented, ultrathin squaraine film. Sci Rep 9:1–12 5. Srivastava M, Tiwari P, Srivastava SK, Kumar A, Ji G, Prakash R (2018) Low cost aqueous extract of Pisum Sativum peels for inhibition of mild steel corrosion. J Mol Liq 254:357–368 6. Pal S, Ji G, Lgaz H, Chung IM, Prakash R (2020) Lemon seeds as green coating material for mitigation of mild steel corrosion in acid media: molecular dynamics simulations, quantum chemical calculations and electrochemical studies. J Moleq Liq 316:113797 7. Ji G, Anjum S, Sundaram S, Prakash R (2015) Musa Paradisica peel extract as green corrosion inhibitor for mild steel in HCl solution. Corros Sci 90:107–117 8. Maurya S, Jaiswal A, Ji G, Prakash R (2021) Waste Solanum melongena stem extract for corrosion inhibition of mild steel in 1M HCl. Mater Today Proc 44:2716–2720 9. Shekhar C, Jaiswal A, Ji G, Prakash R (2021) Ethanol extract of waste potato peels for corrosion inhibition of low carbon steel in chloride medium. Mater Today Proc 44:2267–2272 10. Ji G, Shukla SK, Ebenso EE, Prakash R (2013) Argemone mexicana leaf extract for inhibition of mild steel corrosion in sulfuric acid solutions. Int J Electrochem Sci 8:10878–10889 11. Nath D, Banerjee P, Shaw M, Mukhopadhyay MK (2018) Bottle gourd (Lagenaria Siceraria), fruit and vegetable phytochemicals: chemistry and human health. vol II, Second Edition. In Yahia EM (ed) John Wiley & Sons Ltd, Chapter 42 12. Prajapati RP, Kalariya M, Parmar SK, Sheth NR (2010) Phytochemical and pharmacological review of Lagenaria Siceraria. J Ayurveda Integr Med 4:266–272 13. Prasad C, Karlapudi S, Rao CN, Venkateswarlu P, bahadur I (2017) A highly resourceful magnetically separable magnetic nanoparticles from aqueous peel extracts of Bottle gourds for organic dye degradation. J Mol Liq 243:611–615 14. Moretti G, Guidi F, Fabris F (2013) Corrosion inhibition of the mild steel in 0.1 N HCl by 2-butyl-hexahydropyrrolo[1,2-b][1,2]oxazole. Corros Sci 76:206–218

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15. JI G, Shukla SK, Dwivedi P, Sundaram S, Ebenso EE, Prakash R (2012) Green Capsicum annuum fruit extract for inhibition of mild steel corrosion in hydrochloric acid solution. Int J Electrochem Sci 7:12146–12158 16. Thirugnanasambantham KG, Ramesh R, Sankaramoorthy T, Velmurugan P, Kannagi A, Chaitanya KRM, Sai KCV, Mustafa MA, Ramesh CV (2018) Degradation mechanism for high-temperature sliding wear in surface-modified In718 superalloy. Cogent Eng 5:1501864 17. Atommsa T, Gholap AP (2015) Characterization and determination of catechins in green tea leaves using UV-visible spectrometer. J Eng Technol Res 7:22–31 18. Amarowiczub R, Shahid F (1996) A rapid chromatographic method for separation of individual catechins from green tea. Food Res Int 29:71–76 19. Onyeike EN, Ikewuchi JC, Ikewuchi CC, Uwakwe AA (2010) Quantitative high performance liquid chromatographic analysis of simple terpenes, carotenoids, phytosterols and flavonoids in the leaves of acalypha wilkesiana muell arg. Pacific J Sci Tech 11:480–487 20. Herring T (2004) Rapid determination of terpene lactones in Ginkgo Biloba commercial products by hplc with evaporative light-scattering detection. LCGC North Am 22:456–462 21. Silverstein RM, Webster FX, Kiemle DJ Bryce DL (2014) Spectrometric identification of organic compounds. In: 8th Edn Robert M. ISBN: 978-0-470-61637-6464 22. Ji G, Dwivedi P, Sundaram S, Prakash R (2016) Aqueous extract of Argemone mexicana roots for effective protection of mild steel in an HCl environment. Res Chem Intermed 42:439–459 23. Tiwari M, Gupta VK, Singh RA, Ji G, Prakash R (2018) Donor−π−acceptor-type configured, dimethylamino-based organic push−pull chromophores for effective reduction of mild steel corrosion loss in 1 M HCl. ACS Omega 3:4081−4093 24. Guo L, Zhang R, Tan B, Li W, Liu H, Wu S (2020) Locust bean gum as a green and novel corrosion inhibitor for Q235 steel in 0.1 N H2SO4 medium. J Moleq Liq 310:113239 25. Tiwari P, Srivastava M, Mishra R, Ji G, Prakash R (2018) Economic Use of waste musa paradisica peels for effective control of mild steel loss in aggressive acid solutions. J Environ Chem Eng 6:4773–4783 26. Farhadian A, Rahimi A, Safaei N, Shaabani A, Abdouss M, Alavi A (2020) A Theoretical and experimental study of castor oil-based inhibitor for corrosion inhibition of mild steel in acidic medium at elevated temperatures. Corros Sci 175:108871 27. Sanaei Z, Ramezanzadeh M, Bahlakeh G, Ramezanzadeh B (2019) Use of rosa canina fruit extract as a green corrosion inhibitor for mild steel in 1 M HCl solution: a complementary experimental, molecular dynamics and quantum mechanics investigation. J Ind Engg Chem 69:18–31 28. Ferreira ES, Giancomelli C, Giacomelli FC, Spinelli A (2004) Evaluation of inhibitor effect of L-Ascorbic acid on the corrosion of mild steel. Mater Chem Phys 83:129–134 29. Haddadi SA, Alibakshi E, Bahlakeh G, Ramezanzadeh B, Mahdavian M (2019) A detailed atomic level computational and electrochemical exploration of the juglans regia green fruit shell extract as a sustainable and highly efficient green corrosion inhibitor for mild steel in 3.5 wt% HCl solution. J Moleq Liq 284:682–699 30. Ji G, Shukla SK, Dwivedi P, Sundaram S, Prakash R (2011) Inhibitive effect of argimone mexicana plant extract on acid corrosion of mild steel. Ind Eng Chem Res 50:11954–11959

Study of Rotating Arc Welding Process for Joining of Pipes: An In-Depth Review Ahmed Abdul Muneem, P. Laxminarayana, and M. Viquar Mohiuddin

Abstract Circumferential welding is most commonly used for joining of pipes in construction, fuel transportation, firefighting, automobile and power plant industry. This study is carried out for better understanding of a newly developed technique used for performing circumferential welding of tubes and pipes. The technique is termed as rotating arc welding or magnetically impelled arc butt (MIAB) welding. It is a unique welding process where an electric arc rapidly rotates on the periphery of the pipes because of electromagnetic force produced by the interaction of magnetic field and the arc current. This rotating arc is sufficient enough for generating uniform heat all around the periphery of the adjoining pipes. When welding temperature is reached on the faying surfaces, the upsetting pressure is applied on the pipes end to form a rigid joint. The joint will be formed in few seconds, which exhibits the strength similar to that of parent material. The joint is formed without the use of filler metal, flux material and shielding gases and is free from weld inclusions because of upsetting force which pushes out the impurities. Having many benefits, the process is under vast research to correctly identify and set the process parameters for welding of different materials. This paper explores an in-depth review of previous works carried out by the researchers that would provide information for the further development of the process to obtain quality weld. Keywords Pipe welding · Rotating arc welding · Magnetically impelled arc butt welding

A. A. Muneem · M. Viquar Mohiuddin (B) Muffakham Jah College of Engineering and Technology, Hyderabad, India e-mail: [email protected] P. Laxminarayana Osmania University, Hyderabad, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_25

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Fig. 1 Principle of the MIAB welding process (Kachinskiy et al. [5])

1 Introduction Magnetically impelled arc butt (MIAB) welding, also known as rotating arc welding, is an extraordinary pressure welding process employed for welding of pipes and tubes. This process follows the principle of forge welding for the joining of pipes in the solid state. An electric arc is used for carrying out heating of pipes face, and an upsetting force is applied after sufficient heating of these surfaces. A schematic of MIAB welding with two pipes set coaxially with a magnetic system along with the arc rotating in the gap between the two pipe edges is shown in Fig. 1. The arc rotates along the pipe circumference due to the interaction between the external magnetic field and the arcing current. Upon actuation of the arc, electromagnetic force (F L ) is produced on the arc. This force is due to the axial component of current flow in the arc (I L ), crossing the radial component of applied magnetic field (BL ). This electromagnetic force on the flowing current is referred as a Lorentz force and given by f = J×B, where f is electromagnetic force density, J is current density, and B is magnetic flux density. The magnitude of the force (F) is proportional to the magnetic flux density (B), the arc current I, and the arc length L and given by F α B×I×L. Acceleration of the spinning arc is influenced by the exerted force. This force can be varied by tuning the magnetic field intensity, the intensity of arcing current or the span of the arc gap. During the arc spinning, the arc acquires a speed of 200 m/s and above, causing uniform heating of surfaces. Arcing current plays a crucial role in variation of the arc speed. By sharply increasing the arcing current for a short duration just before upsetting, a rapid expulsion of molten metal takes place, which causes cleaning action and eliminates the requirement of shielding gas. Finally, upsetting force is applied after sufficient heating of the periphery, forming a solid-state bond with the appearance of a flash which can be removed by grinding operation.

2 Literature Review Taneko et al. [1], conducted experiments using MIAB welding on carbon steel pipes of SGP50 with an outer diameter 60.5 mm and wall thickness 3.8 mm. The current

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used for carrying out welding was in the range of 460–500 A with input magnetic flux density 8.0 × 10−2 T and gap between pipes as 2.5 mm. Using an oscilloscope and a high-speed camera, the arc rotation velocity was analyzed during the welding operation. The author studied the methods for supplying welding current to the pipes, the relationship between the velocity of arc rotation, the cause for the extinction of arc and excessive local bonding. Kuchuk-Yatsenko [2], carried out welding of tubes with the heat generated by moving arc in the presence of magnetic field. In this research, two tubes of grade 20 steel with diameter 42 mm and wall thickness of 5 mm were welded; a steel plate of thickness 4 mm was welded to a tube of grade 10 steel with diameter 51 mm and wall thickness 2.5 mm. It was observed in both the cases that during the joint formation, magnetic blow produced by the interaction of induced magnetic field and the arc current pushes the arc from ID to the OD much faster. This was due to the increased concentration of magnetic lines of force on the OD of the tube. Hence, concluding that high-quality weld is produced by controlling the radial movement of arc. Mori et al. [3], studied the possibility of welding non-magnetic materials using MIAB welding process and obtained the feasible conditions that result in producing high-quality weld joint. The materials used for welding were aluminum 1050 with bore 16 mm, wall thickness 1.4 mm and copper with bore 16 mm, wall thickness 1.2 mm. Similar and dissimilar welding operations were performed using Al-Al and Al-Cu, respectively. For carrying out welding, an iron core was inserted into the pipe to generate sufficient magnetic field density to enable welding. It was observed that in welding of Al-Al joint, melting takes place at both the pipe ends resulting in uniform weld bead. During welding of Al-Cu joints, it was found that setting aluminum on negative side and copper on positive side was effective. Sato et al. [4], investigated the welding of pipes of different materials such as carbon steel, aluminum alloy and copper alloy using MIAB welding technique. The dimensions of the pipes used while carrying out research are external diameter 60 mm with varying wall thickness as 0.6, 1.0, 1.4, 1.8, 2.2, 2.6, 3 mm. During welding, it was found that as heating time passes, the arc moves from the inner surface at a lower speed due to low magnetic flux density. Because of magnetic blow, the arc moves to the outer surface with high speed due to high magnetic flux density. For this investigation, phototransistors were used to assess the motion of the arc, thermocouples to measure temperature and Gauss meter to measure magnetic flux density. Kachinskiyet al. [5], investigated the arc behavior during welding of pipes with wall thickness greater than 6 mm. Steel rods and pipes of various grades with different diameters and thicknesses were used for studying the joint formation. A series of experiments was carried out on both rods and pipes considering specific parameters. During welding of thick-walled components, the arc concentrates on the ID of the component thus resulting in uneven heating. Upon further heating, the arc column moves to the OD, but the large wall thicknesses prevent stable movement of the arc to the region of higher magnetic field induction leading to non-uniform heating. Adjustments in the position of the magnetic field were done to improve this situation. It was concluded that this welding method provided uniform and concentrated heating

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on the welding surface with shorter welding time. The weldments had no pores, inclusions or any other defects generally seen in fusion welding. Kuchuk-Yatsenko et al. [6], carried out welding on pipes with larger diameters and thicknesses for two different materials, steel grade (St.20) and steel grade (St.35). For steel grade (St.35), the pipe had outer diameters as 89 mm and 108 mm with thickness 12 mm, 8 mm, and steel grade (St.35) pipes had outer diameters as 219 mm and 76 mm with thicknesses 8 mm, 16 mm, respectively. The gap between the pipes was kept as 1.5 mm, 2.8 mm during welding. Metallurgical studies were carried out, which exhibited excellent results. Kim et al. [7], conducted experiments on steel tube with 48.1 mm outer diameter and 2 mm thickness to investigate the relationship among the magnetic flux density, the exciting current, the position of the coil, the relative permeability and the gap between the pipes. It was concluded that out of the above factors, magnetic flux density is one of the important factors on which the behavior of the arc depends, so the electromagnetic system was designed, and analysis of this was done on 2D FE model to obtain the optimized and effective design. The results obtained from the experimentation and the numerical analysis revealed that the magnetic flux density increases when the exciting current and relative permeability are increased and when the distance between the pipes and the coils is decreased. Vendan et al. [8], performed experiments on steel tube of T11 grade with outer diameter 47 mm and thickness 2 mm. The factors responsible for the arc rotation are magnetic flux density, the arcing current and the gap size, but the magnetic field density was the crucial factor for obtaining uniform arc rotation and the weld quality. For this purpose, a laboratory module was designed and various trials were performed with modifying the magnetic coil system to obtain uniform and continuous arc rotation. A 3D FE model was used to perform a nonlinear electromagnetic analysis for determining magnetic flux density distribution and its magnitude for further optimizing the existing design of electromagnetic system and developing it. The magnetic flux distribution for various exciting and welding currents was analyzed from the above model, and it was found that as the exciting current increases, the magnetic flux density between the pipes also increases. The simulation results generated from this analysis were compared with the experimental data, establishing the relation that magnetic flux density is linearly proportional to exciting current. Vendan et al. [9], developed a 3D FE model to study the distribution of magnetic flux density which is the mainly responsible for the rotation of arc in MIAB welding process. Using ANSYS, a nonlinear electromagnetic analysis was performed to know the effects of welding parameter on magnetic field and weld quality since it is essential to develop efficient electromagnetic system to carry out welding. The results of this analysis were compared with the existing data generated from the experimentations performed on the steel tubes of 50 mm outer diameter with 2 mm thickness which showed excellent relation. It was also known that the magnetic flux density is directly proportional to the exciting current, the distance between the coils located from weld center and the arc speed. Therefore, the rotation of the arc with a higher speed leads to a uniform heating of periphery of tubes, enhancing the weld quality.

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Vendan et al. [10], conducted trials on tube of steel grade T11 with outer diameter 45 mm and 3 mm thickness. The speed of the arc was analyzed by varying the parameters like welding current and voltage, magnetic coil current and voltage. Statistical software (STATA) was used to obtain the most significant input parameter. Finite element software ANSYS was used to explore the effect of magnetic flux density distribution in the gap region. It was stated that magnetic coil current which generates magnetic flux density and the welding current are the most important factors that control the arc speed. Vendan et al. [11], performed simulation using finite element software package ANSYS on the steel pipe of outer diameter 50 mm and thickness 2 mm by generating a 3D FE model to study magnetic flux distribution in MIAB welding process since the radial magnetic flux density is an important factor along with the arc current and the gap, for the rotation of arc and weld quality. The results fetched from the proposed model are compared with the experimental data available from the previously done study, and it emphasized that as magnetic flux density increases by increasing exciting current. Vendan et al. [12], studied the design and development required for MIAB welding process and investigated the process parameters by carrying out experimental trails on steel tube of grade T11. The welding current was varied from 200 to 420 Amps along with an upset force of 30–100 N/mm2 which was adequate for joining the tubes. In the initial design, magnetic coil systems were used to generate magnetic field and trials were conducted. The results obtained were studied using statistical software packages (SPSS and STSTA) for analyzing the parameters. It was concluded that along with the welding current, the magnetic coil current is also an important parameter for governing the speed of the arc. This coil system makes the welding more complex since it increases the input parameters, so it was replaced with the permanent magnets supplying constant magnetic flux density making it simple. Further, trials were conducted using these modified arrangements by varying welding current and voltage. Iordachescu et al. [13], conducted a study on pipes of carbon steel grade ST37 whose outer diameter was 25.4 mm and thickness 3 mm. A longitudinal magnetizing system was used for observing the relationship between the arc and the magnetic field. The welding process was defined in six phases. The essential processing parameter for producing quality joints was considered as pipe gap, magnetic flux density, duration of arc rotation, the welding current and the upsetting force. The microstructure analysis of the welded joints exhibited in hardness. Kuchuk-Yatsenko et al. [14], investigated the weldability of pipes of 168 mm outer diameter and wall thickness 7 mm for steel X70 material. The parameters considered during welding were power 28.7 KW, upsetting force 247 KN and welding time as 34.7 s. The welded joints were tested for their mechanical properties and found to be good, as compared to the parent material. Vendan et al. [15], conducted trials on alloy steel tubes of 47.6 mm diameter and 6 mm thickness by varying welding current (400–500 A), welding voltage (90– 120 V), upset force (30–100 N/mm2 ) and the gap between tubes as 2 and 4 mm for carrying out welding. It was observed that the establishment of arc between the tubes

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could not take place when the gap was 4 mm and above despite of providing a high welding current of about 600 A. When the gap of about 1 mm was kept between the tubes, they got shorted. Hence, it was concluded that the gap between the tubes is also an important parameter for generating the arc and its propagation. Trails were also conducted by categorizing the welding current into three various stages and welding time into four various stages. The current I 2 if about 200 A when supplied for a longer time yielded good-quality weld bead and penetration for the time T3 of about 20 s. Similarly, the current I 2 of about 300 A for a time T3 of 18 s resulted in uniform bead and full penetration. A good-quality weld was produced when a high current of about 1100 A was maintained before forging for few milliseconds. Iordachescu et al. [16], carried out the welding of thin-walled tubes using MIAB welding technique. The tube material was low carbon steel of grade ST37 with outer diameter 25.4 and 3 mm thickness. New magnetization system comprising of peripheral solenoids was used to provide magnetic field density. The parameters considered are the welding current, the magnetic field, the gap between the pipes, duration of arc rotation and the upsetting force. For the measurement of the temperature and visualization, infrared thermography was used. During welding, it was found that influence of magnetic field on rotation of arc/heating duration and gap between the pipes are the two important operational windows. Joint characterization was done using macro- and microstructural analysis and hardness test. Vendan et al. [17], conducted experimental trials on a MIAB machine (MD1) using a carbon steel tube of SA210 Grade A for 51 mm outer diameter, thickness 6 and 44 mm outer diameter, 5 mm thickness. Welding current was considered in three stages and the welding time in four stages. The welded joints were tested for their mechanical properties like tensile strength, hardness and metallurgical analysis such as macro- and microanalysis, SEM Fractography. The results obtained from the above testing showed good weld integrity and high strength as prescribed by AWS B4 Standards. Vendan et al. [18], performed welding on T11 steel pipes with an outer diameter of 47.6 mm and 6.6 mm thickness. The welding current was considered in three stages and welding time in four stages. It was found that when welding current I 2 was supplied as 200–250 A for the time of T3 as 20–23 s, the joint had uniform weld bead and full penetration. Mechanical tests like tensile, bend, impact, SEM Fractography, microhardness were conducted to assess the quality of the weld joint. A comparative study was done with various solid-state welding processes like flash butt welding and induction pressure welding in terms of quality evaluation, productivity, time for each welding, its costs, material loss, heat-affected zone, etc. It was concluded that out of these three solid-state welding processes, the MIAB welding process was the most efficient in every considered aspect. Vendan et al. [19], conducted number of trails on alloy steel tube T11 with 47.6 mm outer diameter and 6.6 mm thickness. The parameters were considered as welding current in three stages and welding time in four stages. The upsetting pressure applied was kept constant as 150 N/mm2 . From the trails conducted, it was found that the welding current of I 2 as 200–220 A and the welding time T3 ranging from 17–23 s produced uniform weld bead, and full penetration was observed. The welded

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joints were tested for metallurgical analysis comprising of macroanalysis and microanalysis. Radiography test using X-ray was performed to evaluate the defects in the welded joints. For performing the test, the surface of the test specimen was grinded to remove the unwanted spatter and then buffing operation is performed to clean the surface impurities. Small numbers of pores were observed which arose due to entrapment of gas molecules during welding. X-ray diffraction was carried out, and the result showed good crystalline structure as that of base metal. Sivasankari et al. [20], conducted trials on steel tubes of SA210 Grade A for an outer diameter of 44 and 4.5 mm thickness. Varying upsetting current and welding time were categorized for various stages of the process. The high upsetting current was applied for a shorter time before upsetting since it expels impurities and decarburized layer from weld surface. Microstructure analysis was done on the base material and on the thermo-mechanically affected zone (TMAZ) which was categorized into three regions from the weld center. The upsetting current had a notable effect on the microstructure of the weld. Tensile tests were performed on the specimens to determine the tensile strength of the weldments as per ASTM E8-M. Vendan et al. [21], made an important attempt to study the temperature distribution in the faying surface because of the arc movement during the welding since the arc moves along the circumference as well as in zigzag motion between inside and outside diameter. For this purpose, a FE model was developed to study the zigzag movement of arc, and the temperature distribution in butt ends to be joined as this moving arc generates sufficient heat that is required for the welding. During the simulation for compensating the speed of the arc, multiple arc factors were considered. Initially, two arc systems were taken into consideration and then four arc systems were used for enhancing the accuracy. Uniform temperature distribution was found, and the penetration was likely to be higher in the welded region. The results compared with available experimental data for steel pipe of outer diameter 47.6 mm and thickness 6.6 mm exhibited acceptable coherence. Sivasankari et al. [22], carried out welding on low alloy steel tubes of T11 material with outer diameter of 48 mm and thickness as 6 mm. For conducting trials, the process parameters considered were welding current in three stages ranging from 310-1000A, welding time in four stages and upset pressure as 16 MPa, respectively. Thermocouples were used to measure the temperature across the pipes to be welded. Mechanical testing like tensile and bend test was conducted to assess the strength. Hardness test was carried out along with microstructural analysis which categorized thermomechanically effected zone into four sections. It was stated that TMAZ exhibited greater hardness, tensile strength, ductility than that of base metal due to bainitic transformation and the arc rotation, current is the most significant parameter in obtaining defect-free weld surface. Piwowarczyk et al. [23], performed welding of pipes (steel C22) to form entire tubular shaft assembly comprising of tube with wall thickness of 1.5 mm. After carrying out welding, the welded joints were tested through visual inspection, macroscopic test, microscopic test and hardness test were performed. The results obtained from the above tests were satisfactory.

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Panda et al. [24], carried out experimentation on steel of grade T11 considering the input parameters as welding current and voltage, magnetic coil current and voltage to measure the speed the arc during welding. To achieve the working relationship between the given input parameters and the arc speed, a numerical method of multigene genetic programming was formulated. This model provided the best combination of the input parameters to optimize the speed of the arc which affects the weld quality. It was found that the predictions obtained were in good agreement with the data obtained from the experimentation. The statistical error methods were used to justify the performance of the generated model. A 2D analysis was conducted which revealed that the current supply during welding influences the speed of the arc than followed by the welding voltage. The variations in the current and voltage of the magnetic coil had negligible effect on the speed of the arc. Vignesh et al. [25], explore the effect of welding parameters on T91 steel tubes with 44.5 mm outer diameter. The parameters which were considered for welding are varying thicknesses (3.5, 4.5, 5.5) mm, welding current (900, 1000, 1100) A, welding time (6, 9, 12) s and upsetting pressure of 150 N/mm2 . The tensile strength, hardness, micro- and macro-images were recorded which showed the failure took place in the chromium-enriched regions. Further, the weldments were analyzed using CT and RT images to check the weld quality. Kachinsky and Kuchuk-Yatsenko [26], investigate the welding of pipes of up to 320 mm outer diameters with wall thickness varying from 10–20 mm to form butt joint. Pipes of different steel materials in particular St35, 01star520, X60, X70, X80, STPG 410 were used. Welding was performed on the machines developed by PWI of model MD1, MD205. The parameters which were controlled during welding were welding current, welding voltage and force during upsetting. A high-speed video filming of the arc and oscillographing was done during the welding. Metallographic studies were performed on the welded joints using optical microscope. The mechanical testing of joints was done which conformed high strength, high-impact toughness and ductile properties of the welded joint similar to that of base metal. Kustron et al. [27], studied the quality of welded joints formed by MIAB welding using ultrasound testing. Several experimental and numerical studies were done which proved the effectiveness of this method. The simulations were performed using LS-DYNA which assisted in selection of parameters of the transducer, the angle of ultrasonic beam ensuring the highest error detection. It allowed better understanding of the process and wave propagation method. When the transducer was kept at an orientation of 31.5° angle, it enabled the conversion of longitudinal wave into a subsurface wave, providing the opportunity to study the welded joint without the flash removal; thus, the ultrasonic subsurface wave was used for testing thin-walled pipes and component for the inspection of the welded joint. Sivasankari et al. [28], MIAB welding was performed on steel pipes with 44 mm outer diameter and 4.5 mm thickness. The welded joint exhibited an average tensile strength and yield strength of about 442 MPa and 258 MPa, respectively, with average hardness of about 147HV at 100 g load. The aim was to study the effects of formation of light band zone on the weldment. Microstructural analysis performed to understand the transformations taking place in thermomechanically affected zone leading

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to formation of light band zone showed three distinct TMAZs between the weld interface and unaffected base metal. Welded samples showed better ductile and tensile properties due to acicular ferrite formation with higher upsetting current as there is no light band zone formation at welded joint interface and lower tensile strength with lower upsetting current as a distinct white zone (fully ferritic structure), i.e. light band zone at the welded joint interface emerges is due to the incomplete homogenization and incomplete expulsion of decarburized region. At TMAZ I, welding parameters showed considerable effect on microstructural transformations. Patel et al. [29], carried out MIAB welding on tube of 22 mm outer diameter and 2 mm wall thickness. The joint was formed between a tube and Tenon which are made of mild steel. For carrying out welding, an arcing current of 250A for about 10 s and upsetting current 400A for 1 s were applied keeping the arc voltage as 50 V and magnetic field as 3000 Gauss. SEM and optical microscopy were carried out on the joint whose results showed four TMAZ with higher hardness; it was also concluded that arcing current plays significant role informing defect-free welded joint. Low arcing current effects the arc rotation causing defects like voids in the weld surface and degradation of weld properties. Muhammed et al. [30], studied the MIAB welding properties on pipe of ASTM A106/API5L Grade B with outer diameter 42.2 mm and thickness 3.56 mm. The welding current was considered in three stages from 170–600 A and welding time in four stages keeping the upset pressure as 4.2–4.5 bars. It was found that the welding current of 230 A and welding time of 8 s with upset pressure of 4.2 bars resulted in good welded joints with full penetration. Mechanical testing was done on to the welded joint comprising tensile test, hardness test, neck break test, bend test and macro-etch examination. The results obtained from the above tests were excellent exhibiting properties better than the base metal. Dhivyasri et al. [31], performed study on welding of alloy steel tubes of material T11 with outer diameter 47.6 and 6.6 mm thickness. The welding current was considered in three stages and welding time in four stages. The effect of varying current was studied by examining bead width and through tensile test. For maintaining the welding current and time at the specified range, a double PI-PID control system was upgraded from the previous existing system. Conventional PID controller was used for validating the upgraded controller. The designed controller was effective and maintained the desired values of the controllable parameters. The weldments obtained using this system possessed good ultimate tensile strength. Sedighi et al. [32], performed welding of pipes of low alloy steel SA335 grade 11 with outer diameter 33 and thickness as 3 mm. Experimentation was carried out to study the influence of various parameters on the welding. Numerical simulations were performed to verify the results obtained from the experiment. It was found that the welding time was directly proportional to residual stresses and welding pressure was inversely proportional to residual stresses. Thus from the comparison of welding, experimental results with simulation results showed that the weldments obtained from the MIAB welding had lower residual stresses near the weld bead compared to other conventional welding methods.

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Mosayebnezhad et al. [33], performed MIAB welding of low alloy tubes of steel SA335 grade 11 by considering various parameters. A FE model was proposed for the simulation study of residual stresses, heat transfer and phase transformation. Mechanical analysis was also performed by considering and neglecting the effect of plasticity induced due to transformation and volumetric dilatation. Since the transformationinduced plasticity and volumetric dilatation were the important factors, the numerical analysis was done to obtain results, with and without considering their effects. When the influence of phase transformation was neglected, maximum circumferential stresses reached 260 MPa, and by consideration the phase volume changes, it is reduced to −60 MPa, and also when the transformation-induced plasticity was considered, it is decreased to −70 MPa. Contrarily when the influence of phase transformation was neglected, the residual stress was + 5 MPa, and by considering the phase volume changes, it is reduced to −90 MPa, and further when the transformation-induced plasticity was considered, it is changed to −25 MPa. The results generated from phase transformation simulations were similar to experimental metallography [34]. Suresh Isravel et al. [35], carried out welding on ASTM standard material SA210 Grade A carbon steel thick-walled pipes with larger diameters. The effect of welding current on arc rotation was studied and concluded that stabilized arc was observed when the current was ranging from 450–550 A, and the joint executed very good strength and integrity when the upsetting pressure was about 180 bars. It was also concluded that the specimen failure was due to improper eccentricity or the current generated was insufficient. Ramesh Kumar et al. [36], used MIAB welding to join two dissimilar metal tubes of ASTM A213 (T11 and T91) with 44.5 mm outer diameter and thickness varying from 3.5 to 5.5 mm. The process parameters considered were welding current ranging from 310 to 1000 A, welding time as 14–15 s. The welded joints were studied for their hardness, microstructure and SEM micrography. It was found that T91 material required more time for melting as compared to T11 due to high Cr content and less Fe. The hardness and wear resistance when compared to T91 is more in T11 due to the presence of Mo and Mn in T11. Since the vanadium content is more in T91, it has fine grain distribution as compared to T11. Kustron et al. [37], carried out a study to determine the weld quality of the transmission and drive components of vehicles welded through MIAB technique by ultrasonic testing method to perform reliable and quick validation (test duration around 3 s) of the welded element using scanning acoustic microscope (SAM). When the ultrasonic transducer was positioned at a critical angle of 31.5°, it was possible to detect the defects with diameter of about 0.3 mm. Finite elements method was used for verifying the frequency of transducer and the angle of incident of the ultrasonic beam that was used on the tested. X-ray computed tomography was also performed on components which provided very accurate view of the joint structure but is expensive, hazardous and time-consuming [38]. So, B-scan image can be used instead as it provides data in very short time with low cost, but it is less precise. The results obtained from the experimentation were in good relation with the performed numerical analysis.

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3 Conclusions From the above study, following conclusions may be recorded. • Rotating arc welding method is most suitable for joining pipes as it provides uniform and concentrated heat on the welding surfaces in shorter time. • The rotation of the arc with higher speed leads to uniform heating of periphery of pipes, enhancing the weld quality. • Low arcing current affects the rotation of arc causing defects like voids in welded joint which degrades the weld quality. • The magnetic blow produced from the interaction of the induced magnetic field and the arcing current pushes the arc from ID to the OD much faster. • During welding, as heating time passes, the arc moves from the inner surface at a lower speed due to low magnetic flux density and then moves to the outer surface with high speed due to high magnetic flux density at the outer side. • The temperature distribution in the faying surface is because of the arc movement along the circumference as well as in zigzag motion between inside and outside diameter. This moving arc generates sufficient heat that is required for the welding. • The essential processing parameter for producing quality joints was considered as pipe gap, magnetic flux density, duration of arc rotation, the welding current and the upsetting force. Out of these factors, the magnetic flux density is one of the crucial factors for obtaining uniform arc rotation and the weld quality. • The magnetic flux density increases when the exciting current and relative permeability is increased and when the distance between the pipes and the coils is decreased. Thus, magnetic flux density is linearly proportional to exciting current. • Along with the welding current, the magnetic coil current is also an important parameter for governing the speed of the arc. • The magnetic coil system makes the welding more complex since it increases the input parameters; hence, it was replaced with the permanent magnets supplying constant magnetic flux density making it simple. • The establishment of arc between the tubes could not take place when the gap was 4 mm and above despite of high welding current of about 600 A. When the gap of about 1 mm was kept between the tubes, they got shorted. Thus, the gap between the tubes is also an important parameter for generating the arc and its propagation. • The welding current I 2 as 200–220 A and the welding time T3 ranging from 17 to 23 s produced uniform weld bead and full penetration. Also, an upset force of 30–100 N/mm2 was adequate for joining the tubes. • The high upsetting current of about 1100 A is applied for a shorter time before upsetting which expels impurities and decarburized layer from weld surface producing a good-quality weld. It also has notable effect on the microstructure of the weld. • The welding time is directly proportional to residual stresses, and welding pressure is inversely proportional to residual stresses.

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• TMAZ exhibited greater hardness, tensile strength, ductility than that of base metal due to metallurgical transformations. • The weldment had no pores, inclusions or any other defects as generally seen in fusion welding processes. • During welding of thick-walled components, the arc concentrates on the ID of the component, thus resulting in uneven heating. Upon further heating, the arc column moves to the OD, but the large wall thicknesses prevent stable movement of the arc to the region of higher magnetic field leading to non-uniform heating. • This welding process can also be used to join two dissimilar metal tubes. • Non-magnetic materials like aluminum can also be joined by inserting an iron core into the pipe to generate sufficient magnetic field density to enable welding operation. • During welding of hard material with soft material, connecting the hard material on the negative side and the soft on the positive side was found more effective. • This welding process is the most efficient among various solid-state welding processes like flash butt welding, friction welding and induction pressure welding in terms of quality evaluation, productivity, time for each welding, costs, material loss, heat-affected zone, etc.

References 1. Taneko A, Arakida F, Takagi K (1987) Analysis of arc rotation velocity in magnetically impelled arc butt welding. Quart J Japan Weld Soc 1(3):570–576 2. Kuchuk-Yatsenko SI (1988) Control of the arc moving in a narrow gap under the effect of a magnetic field in press welding of pipes. Weld Int 2(11):965–968 3. Mori S, Yasuda K (1989) Magnetically impelled arc butt welding of aluminum pipes. Weld Int 3(11):941–946 4. Sato T, Katayama J, Ioka S, Otani M (1991) An experimental study of rotational behaviour of the arc during magnetically impelled arc butt welding. Weld Int 5(1):5–10 5. Kachinskiy VS, Krivenko VG, Ignatenko VY (2002) Magnetically impelled arc butt welding of hollow and solid parts. Weld World 46(7–8):49–56 6. Kuchuk-Yatsenko SI, Kachinsky VS, Ignatenko VY (2002) Magnetically impelled arc butt welding of thick walled pipes. Paton Weld J 24–28 7. Kim J-W, Choi D-H (2003) A study on the numerical analysis of magnetic flux density by a solenoid for magnetically impelled arc butt welding. In: Proceedings of the institution of mechanical engineers. Part B, vol 217, pp.1401–1407 8. Vendan SA, Manoharan S, Buvanashekaran G, Nagamani C (2008) Design and development of MIAB welding module-investigation and validation of electromagnetic force using finite element analysis. In: The 6th international conference on manufacturing research, pp 693–701 9. Vendan SA, Manoharan S, Buvanashekaran G, Nagamani C (2008) Magnetic flux distribute on modelling of magnetically-impelled arc butt-welding of steel tubes using finite element analysis. J Mech Eng Sci Part C 222:1783–1790 10. Vendan SA, Manoharan S, Buvanashekaran G, Nagamani C (2009) Some studies on the electromagnetic aspects governing the magnetically impelled arcs through experimentation finite element simulation and statistical analysis. Int J Appl Electromag Mech 31:113–126

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11. Vendan SA, Manoharan S, Buvanashekaran G, Nagamani C (2009) Simulation of magnetic flux distribution for magnetically impelled arc butt welding of steel tubes. Multidiscipline Model Mater Struct 5(3):229–234 12. Vendan SA, Manoharan S, Buvanashekaran G, Nagamani C (2010) Experimental and statistical analysis of impact of various parameters on arc rotation in MIAB welding process by developing a laboratory module. Society of experimental mechanics, pp.40–48 13. Iordachescu D, Iordachescu M, Georgescu B, Miranda RM, Ruiz- Hervias J, Ocana JL (2010) Technological windows for MIAB welding of tubes featuring original longitudinal magnetization system with peripheral solenoids. J Mater Process Technol 210:951–960 14. Kuchuk- Yatsenko SI, Kachinsky VS, Ignatenko YV, Goncharenko EI, Koval MP (2010) Magnetically impelled arc butt welding of pipes of steel X70. Paton Weld J 29–31 15. Vendan SA, Manoharan S, Buvanashekaran G, Nagamani C (2011) Magnetically impelled arc butt welding of alloy steel tubes in boilers–establishment of parameter window. J Mechatron 21:30–37 16. Iordachescu D, Georgescu B, Lordachescu M, Lopez R, Miranda RM, Garcia Beltran A (2011) Characteristics of MIAB welding process and joints. Weld World 55:25–31 17. Vendan SA, Mundla SR, Buvanashekaran G (2012) Feasibility of magnetically impelled arc butt (MIAB) welding of high thickness tubes for pressure parts. Mater Manuf Processes 27(5):573– 579 18. Vendan SA, Manoharan S, Buvanashekaran G, Nagamani C (2012) Strength assessment using destructive testing on MIAB welded alloy steel tube and subsequent techno-economical evaluation. J Manuf Processes 14:328–335 19. Vendan SA, Manoharan S, Nagamani C (2012) MIAB welding of alloy steel tubes in pressure parts metallurgical characterization and non-destructive testing. J Manuf Processes 14:82–88 20. Sivasankari R, Balusamy V, Buvanashekaran G (2014) Effect of upset current in magnetically impelled arc butt (MIAB) welding of carbon steel tubes. Appl Mech Mater 592–594:240–244 21. Vendan SA, Thangadurai V, Vasudevan A, Senthil Kumar A (2014) Investigations on temperature distribution during revolutionary and zigzag movement of arc in magnetically impelled arc butt welding of tubes. Int J Appl Electromag Mech 46:155–163 22. Sivasankari R, Balusamy V, Venkateswaran PR, Buvanashekaran G, Ganesh Kumar K (2015) Characterization of magnetically impelled arc butt welded T11 tubes for high pressure applications. J Defence Technol 11:244–254 23. Piwowarczyk T, Korzeniowski M, Ambroziak A () Effect of pipe face preperation on the quality of magnetically impelled arc welded joints. Inst Weld Bull 5(15):111–119 24. Panda BN, Vendan SA, Garg A (2016) Experimental-and numerical-based studies for magnetically impelled arc butt welding of T11 chromium alloy tubes. Int J Adv Manuf Technol 25. Vignesh S, Dinesh Babu P, Prasanna Venkatesh V, Martin Vinoth S, Marimuthu P (2017) Experimental investigations on magnetically impelled arc butt welded T91 steel tubes. Indian Inst Met 70(3):741–748 26. Kachinsky VS, Kuchuk-Yatsenko SI (2017) Joint formation in magnetically impelled arc butt welding of thick walled pipes from high strength steels. Paton Weld J 8:39–45 27. Kustron P, Korzeniowski M, Piwowarczyk T, Sokołowski P (2017) Application of immersion ultrasonic testing for non-contact quality evaluation of magnetically impelled arc butt welded drive shafts of motor vehicles. Adv Automob Eng 6(1):1–7 28. Sivasankari R, Balusamy V, Venkateswaran PR, Ganesh Kumar K, Buvanashekaran G (2017) Light band zone formation and its influence on properties of magnetically impelled arc butt (MIAB) welded carbon steel tubes. Indian Inst Met 29. Patel VC, Patel DH (2017) Microstructure analyses of magnetic impaled arc beam (MIAB) welding specimen. Int J Adv Eng Res Dev 5(4):677–682 30. Muhammad N, Manurung YHP, Kuchuk-Yatsenko S, Kachynskyi V, Abdul Rahman O, Kassim K, Abidin AZ (2018) Investigation on joint quality of material ASTM A106/API 5L using magnetic impelled arc butt (MIAB) welding. Int J Eng Technol 7:1597–1601 31. Dhivyasri G, Rahul SG, Kavitha P, Vendan SA, Kumar KR, Gao L, Garg A (2018) Dynamic control of welding current and welding time to investigate ultimate tensile strength of Miab welded T11 tubes. J Manuf Processes 32:564–581

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A Study of the Coefficient of Friction in DP-590 Steel Sheets Forming K. Seshacharyulu and B. Balu Naik

Abstract The objective of this study was to evaluate the tribological properties of stretching steel sheets using the friction test method. An especially designed friction simulator has been used to conduct all tests. Steel sheet DP-590, commonly used in auto manufacturing, was used as the test material. In order to characterize the mechanical properties of the specimens, uniaxial tensile tests were conducted. Additionally, the specimens were characterized by measuring their topographic surfaces in order to identify their tribological properties. Obtaining frictional results under different conditions such as lubrication, temperature variations, and specimen orientation according to the direction of sheet rolling has been conducted within different angles (0,41,67). Friction values across the tests were different, as revealed by the comparative analysis. In both dry and lubricated conditions, the coefficient of friction increases with increasing temperature. Keywords Material properties · Coefficient of friction · Lubrication · Bend angle · Stretching · Formability

1 Introduction Friction is a highly influential technological phenomenon that largely influences the flow characteristics of material deformed under force. Metal forming produces friction primarily because of friction connections [1, 2]. Material combination and surface roughness are the main determinants of the type of friction joint created. Many factors and phenomena contribute to friction, including lubrication, normal pressure, the surface roughness of the tool and sheet, sliding speed, the materials K. Seshacharyulu (B) Mechanical Engineering Department, Sphoorthy Engineering College, Hyderabad, Telangana 501510, India e-mail: [email protected] B. Balu Naik Mechanical Engineering Department, Jawaharlal Nehru Technological University Hyderabad, Hyderabad, Telangana 500085, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_26

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of the contact pair, and temperature [3]. In warm or hot forming, friction between the bodies is usually greater than in cold forming because the bodies adhere to each other more tightly. The increase in surface roughness and plastic deformation of the material during lubrication results in a transition from a hydrodynamic to an increased mixed friction regime [4, 5], causing the increased metal to metal contact under lubricated conditions. In sheet metal forming, the friction conditions occurring at different areas of the workpiece are changing as well as the drawing force. The friction forces that occur between the deformed material and the tool are mainly responsible for the nonuniform deformation of the draw piece. Normal pressure, temperature, friction, and frictional losses influence the contact phenomena. The material grade, its surface topography, the type of lubricant, and the ambient temperature [6]. As low friction reduces stress on tooling and forming loads in most forming operations, it is beneficial. However, in sheet metal forming, friction is crucial to control metal flow, impacting both product quality and tool wear (such as surface finish and geometry). A large, deep drawing operation increases the importance of friction. Increasing friction within the die cavity is used to reduce metal flow into the cavity of complex parts, thereby preventing wrinkles [7]. In addition to adding another variable to the already complex stamping process, lubricants are frequently applied to assist metal flow and reduce wear. If the lubricant was processed insensitive, it could be applied to stamping of any part [8]. Steels with coatings can also pose complications. The literature so far has shown inconsistent results for coated blanks. Overby and Zeng [9] found that galvanized sheet steel caused increased friction. In contrast, Keeler and Dwyer found that coating processes and interactions with other process variables had a significant effect on effects of coated steel [10]. In order to design insensitive drawing compounds, it is crucial to determine the interaction between such parameters and the lubricant system. Forming complex shapes requires information about friction and the material flow to prepare a proper die tool and forecast the flow of materials. If you use the right simulator to plan friction tests properly, this serves as a good justification. There are three typical friction tests in this paper: the flat strip, the pulley test, and the bending under tension test. These tests are used to determine the friction under both dry friction and lubricated friction conditions for the sheet of DP-590 steel.

2 Experimental Procedure 2.1 Materials and Methods In the automotive industry, advanced high-strength steels are used because of their exceptional combination of ductility and strength, making them incredibly popular [11]. Martensite, ferrite, and retained austenite components are mainly controlled

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Table 1 Chemical composition of investigated DP-590 steel (wt. %) Element

C

Mn

Cr

Al

Si

Mo

Fe

In wt %

0.113

1.785

0.024

0.036

0.387

0.03

Rest

by careful microstructure control [12–14]. Vehicle chassis and structural elements are made primarily from steels of the dual-phase (DP) family. The martensite phase of DP steel is much stronger than the ferrite phase, which is made up of soft ferrite phases. During martensitic phases, the steel material retains its tensile strength, while the ferrite phases provide ductility [15, 16]. The investigated composition of DP-590 steel is shown in Table 1. Steel sheets of stretching quality were tested for friction on cup-shaped draw pieces forming from steel sheets of 1 mm thickness. Each specimen orientation was tested with three samples. Therefore, specimens were cut at angles of 0°, 30°, 60°, and 90° in relation to the rolling direction. Three different bend angles of 0°, 41°, and 67°, respectively, were tested three times under a constant temperature, and constant speed and load with different temperatures and lubricants (molykote, plastic) were also used for better results. In the uniaxial tensile test, the following mechanical properties can be in the Hollomon equation, the strain hardening coefficient, strain hardening exponent, and yield strength are determined for ASTM E08/E8M-11.

2.2 Friction Test To study friction characteristics and effects on sheet metal forming, we designed and fabricated this twin clamp friction testing machine shown in Fig. 1. The load cell and hydraulic cylinders are powered by a power pack with the apparatus available as a floor model. It has a maximum of 2000 kg capacity. This machine has a maximum heating capacity of 1500 °C with a 10 °C accuracy and is computer controlled. An electronic pyrometer and Dyna therm controller controlled the temperature of the specimen during the friction tests. As per the above setup, we can see that the friction sample size of 500 × 30 mm after and before testing at 800 °C is shown in Fig. 2. The contact pin was manufactured with an Inconel material diameter of 50 mm. Lubricants were applied to the contact area between the sample and pin.

3 Results and Discussions Littlewood and Wallace [17] developed the friction test (bending under tension) based on friction modeling on the edge of the die. To perform the test, the metal strip is drawn around a cylinder counter-sample (Fig. 3). A bending under tension test (BUT)

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Dyna Therm

Heating coil Pyro meter dyna therm controller

Fig. 1 Experimental equipment (friction tests)

Fig. 2 Friction test samples size of 500 × 30 mm a before testing and b after testing at 800 °C

(a)

(b)

enables the measurement of coefficients of friction and their changes, resulting from stretching specimens over a roller. Changes in the topography and normal pressure caused by sheet deformation [18, 19], as well as shifting contact conditions that are caused by strain hardening, may be responsible for this change. / ( / ) μ = 2 π ln F1 F2

(1)

As a result of friction between the roller and the sheet, F1 > F2 (Fig. 2). During the test, we measure F1 and F2 simultaneously. Deforming the sample until a fracture occurs increases with increasing upper grip displacement. During deformation, if the wrap angle γ is constant, and the coefficient of friction is the same for all surfaces, its value can be determined. Equation 1 gives the coefficient of friction and bending force to be subtracted from the actual force for an accurate value.

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Fig. 3 Interaction between a strip and an elementary force [17]

The coefficient of friction (μ) is evaluated at two different test temperatures with various lubricants. It was observed from Table 2 that the μ value increasing with increasing temperature in both the cases with lubricant or without lubricant. The lubricant molykote gives a low friction value compare to plastic. At 800 °C with the molykote lubricant having better formability. Then, 0 and 30° orientation specimens are having low friction value compared to other and also observed that 45%, 36%, and 3 of friction value increased with increase in temperature in no lubricant, molykote, and plastic cases, respectively. It was observed that friction values changed slightly with changes in bend angle. In the simulation, the average value was used as the input for the FE code. Furthermore, examining the effects of temperature on the friction value, it was found that the friction value increased. However, friction values will differ depending on what lubricant is used. Between work and pin, we used molykote. Figure 4 showing load decreasing with an increase in temperature, and Fig. 5 shows the variation of friction Table 2 Mechanical properties and coefficient of friction of DP-590 steel in 0° bend angle and 100 kg load S. Temperature Orientation UTS (Mpa) YTS (Mpa) n No. (°C)

Lubricant Coefficient type of friction (μ)

1

RT

0°, 30°, 60°, 90°

966 ± 31

758 ± 21

0.174 – Molykote Plastic

0.51 ± 0.09 0.31 ± 0.02 0.38 ± 0.09

2

500

0°, 30°, 60°, 90°

477 ± 21

319 ± 15

0.113 – Molykote Plastic

0.82 ± 0.12 0.44 ± 0.06 0.52 ± 0.05

3

700

0°, 30°, 60°, 90°

177 ± 9

149 ± 12

0.089 – Molykote Plastic

0.91 ± 0.09 0.62 ± 0.07 0.61 ± 0.03

4

800

0°, 30°, 60°, 90°

121 ± 11

89 ± 10

0.093 – Molykote Plastic

0.96 ± 0.03 0.67 ± 0.05 0.71 ± 0.04

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Fig. 4 Load versus displacement graphs at (100 kg) and test angles 41.8° and a RT, b 800 °C

value at various bend angles w.r.t lubricant. Using molykote, the coefficient of friction was observed to be 0.67 at 800 °C and to be 0.51 at room temperature. In addition to friction, a die’s material plays a role. We use Inconel material for our dies in the present instance. From Fig. 5, it was clear that molykote lubricant gives the lower friction value of almost 15–25% variation, and in the case of plastic, it was 20–25%. At an angle of 67°, lower friction values were observed, and in rolling direction, higher was observed.

4 Conclusions Based on the results of the experiments, here are some conclusions: • After going from room temperature to 800 °C, the DP-590 steel’s was 45% higher friction value. Therefore, to reduce this effect, lubricants are applied to the contact surfaces for better results. • Molykote lubricant gives lower friction values almost 15–25%, and in the case of plastic, 20–25%. At 67° angles, lower friction values were achieved; in rolling directions, higher values were attained. • It is proven that lubricants are effective in mitigating roughness asperities direct contact between tooling and workpiece. Better formability and good surface finish achieved with molykote at elevated temperature in the stretching process

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Fig. 5 μ versus temperature graphs at (100 kg) load different lubricants and bend angles a 0, b 41, and c 67°

References 1. Altan T, Tekkaya AE (eds) (2012) Sheet metal forming: processes and applications. ASM Int 2. Dharavath B, Varma D, Singh SK, Naik MT (2021) Understanding frictional behaviour of ASS316L in sheet metal forming. Mater Today Proc. 1(44):2855–2858 3. Nielsen CV, Bay N (2017) Overview of friction modelling in metal forming processes. Proc Eng 1(207):2257–2262 4. Trzepieci´nski T, Bazan A, Lemu HG (2015) Frictional characteristics of steel sheets used in automotive industry. Int J Automot Technol 16(5):849–863 5. Masters IG, Williams DK, Roy R (2013) Friction behaviour in strip draw test of pre-stretched high strength automotive aluminium alloys. Int J Mach Tools Manuf 1(73):17–24 6. Trzepiecinski T, Lemu HG (2017) Effect of computational parameters on spring back prediction by numerical simulation. Metals 7(9):380 7. Wilson WRD (1991) Friction models for metal forming in the boundary lubricant regime. J Eng Mater Technol 113:60–68 8. Keeler SP, Nine HD, Sikrik JF (1996) Formability criteria for selecting sheet metal lubricants. SAE technical paper series, No. 880366 9. Zeng B, Overby D (1988) Strip experimental study on galvanised steel sheet, 15th Biennial Congr. In: International deep drawing research group. Dearborn, MI, USA, pp 85–90 10. Keeler SP, Dwyer TE (1986) Frictional characteristics of galvanised steels evaluated with a draw bead simulator. SAE technical paper series, No. 860433

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Enhancement of Machinability Characteristics of Superalloys Using Textured Tools: A Review Krishna Mohan Buddaraju , G. Ravi Kiran Sastry, Satyanarayana Kosaraju , and G. Sainath

Abstract Modern industry demands low cost, high productivity and ability to create complex geometries with good product quality. Even though 3D printing or additive manufacturing is getting popular in manufacturing sector, it is still quite difficult to replace traditional machining processes. Heat generation at the tool chip interface due to friction is the major concern with conventional machining processes. Cooling techniques like minimum quantity lubrication (MQL) and nanofluid-based minimum quantity lubrication (NMQL) have replaced flood cooling technique based on mineral oils which are hazardous to operators as well as to the environment. Coated carbide inserts like AlTiN, TiAlN are preferred to machine difficult-to-machine materials like titanium- and nickel-based alloys. Cryogenic cooling techniques using fluids like liquid nitrogen are also employed. This article presents recent advances in design of textured cutting inserts employed under dry, solid lubricant, MQL, NMQL cutting environment. Creation of textures like dimples, linear grooves parallel and perpendicular to chip flow, linear grooves inclined to cutting edge, combination of dimples and linear grooves on the rake and/or flank face will reduce the chip–tool contact area. They also act as reservoir for the supply of cutting fluid. With the use of textured cutting inserts, there is a significant improvement in machining characteristics which include better surface finish, reduction in cutting forces and cutting zone temperature and increase in tool life. Keywords Dimple texture · Dry machining · Minimum quantity lubrication · Graphene

K. M. Buddaraju (B) · S. Kosaraju · G. Sainath Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad 500090, India e-mail: [email protected] K. M. Buddaraju · G. Ravi Kiran Sastry National Institute of Technology Andhra Pradesh, Tadepalligudem 534101, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_27

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1 Introduction Superalloys like titanium and nickel alloys have widespread applications in the field of defense, aerospace, chemical processing, nuclear, food processing industries due to their superior thermomechanical properties such as high toughness, high tensile stress, high temperature strength, resistance against thermal creep deformation and resistance to corrosion or oxidation. Since these alloys possess high hot-hardness and strength, high dynamic shear strength, poor thermal conductivity, they are considered as difficult-to-cut materials [1, 2]. Dry machining is the best method from the environmental and working conditions point of view as it eliminates the hazardous cutting fluids. However, dry machining has limitations since large amount of heat is generated (low heat dissipation) which results in poor surface finish and limited tool life [3]. The mineral-based cutting fluids reduce the friction between the chip–tool interface, which in turn reduces the cutting temperature, resulting in improvement of tool life. These cutting fluids serve as a coolant/lubricant, as well as a means of transporting debris generated during machining [4]. But, mineral-based cutting fluids are hazardous compounds that can cause a variety of skin and lung problems, including dermatitis [5]. Furthermore, it is quite difficult to dispose of these cutting fluids, and the expense of recycling is extremely high [6]. Biodegradable vegetable oils can replace mineral based cutting fluids but have limitation due to their low thermal and oxidation stability, high freezing points and limited protection against corrosion. Vegetable oil MQL and nanomaterial mixed vegetable oil MQL processes minimize the effect of cutting fluids on the environment and workers as these processes employ very little amount of cutting fluid in mist form. Cryogenic fluid reduces coefficient of friction at the interface of the tool and chip over the rake face resulting in generation of less cutting forces when compared to dry turning [7]. Texturing on tools improve the tool life of the inserts. The textures created on the rake face reduce the wear of cutting insert due to a reduction in contact area between tool and chip. Texture patterns act as reservoir for cutting fluid and ensure continuous supply of lubricant to the chip–tool interface. Trapped lubricant can provide hydrodynamic lift force resulting in reduction of tool wear thereby improving the tool life [8].

2 Turning Based on Dimple Textured Inserts 2.1 Turning of Titanium Alloys Using Dimple Textured Inserts Singh et al. studied the textured tool wear behavior while machining of Grade 5 Ti alloy (Ti–6Al–4 V) under dry, canola-oil MQL and NMQL using graphene (GnP)

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blended in canola-oil conditions. The textured tool’s performance was evaluated based on characteristics of tool wear and surface roughness. Figure 1 shows the texture parameters with dimple profile along with properties of GnP. Experiments were performed at cutting speed of 80, 130, 180 m/min, whereas feed rate and depth of cut were kept constant at 0.15 mm/rev and 0.2 mm respectively. Air supply in MQL was kept at 6 bar, and flow rate was controlled at 120 ml/h. A distance of 30 mm was maintained between the nozzle tip and the cutting edge of the insert, and nozzle was aligned at 45° with horizontal. 1 wt% of GnP cutting fluid (NMQL) was preferred as 1 wt% of GnP improved thermal conductivity by 24.03% w.r.t. base oil. Figure 2 depicts the coefficient of thermal conductivity of canola oil with varying GnP wt% blended in oil. Results from their studies indicate that the MQL using GnP mixed in canola oil showed optimum results when compared with MQL using only canola oil [8]. Table 1 depicts the machining parameters related to turning of superalloys using textured inserts. Singh et al. investigated machining of Grade 5 Ti alloy using dimple textured insert under dry, textures filled with graphene particles (GnP), vegetable oil MQL and GnP -mixed NMQL environment. 1 wt% of GnP mixed with vegetable oil was considered for NMQL as it was found to be optimum based on the thermal conductivity test and suspension stability tests. Textured inserts filled with GnP were obtained by pressing the mixture of graphene and isopropyl alcohol solvent into the dimples. Based on the results, they found that under NMQL conditions tool life was maximum, cutting forces were lower and cutting temperature was minimum. Tool life under NMQL was found to increase nearly twice than that of tool life at various cutting speeds. In case of textured inserts filled with GnP, due to the shearing and deformation of GnP layers, friction was low resulting in effective lubrication. At highest cutting speed

Fig. 1 Texture parameters with dimple profile and properties of graphene [8]

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Fig. 2 Coefficient of thermal conductivity of canola oil with varying GnP wt% blended in oil [8]

of 180 m/min under dry cutting environment, the tool failed catastrophically due to absence of any lubrication [9].

2.2 Turning of Aluminum Alloys Using Dimple Textured Inserts Experimental studies by Durairaj et al. were related to the influence of dimpletextures during turning of aluminum (Al6061) alloy. Textures were engraved with picosecond laser on the rake surface of uncoated WC cutting tools. Circular dimples were favored, as they were symmetrical and provide independent chip flow direction. Dimple diameter (150, 100, 50 µm), distance from the cutting edge (175, 125, 75 µm), pitch (150, 100, 50 µm), depth (50, 25, 10 µm) were machining parameters. Figure 3 shows configuration of textured tools used for the studies. Highly refined Ondina oil lubricant (flow rate 2.6L/min at pressure 0.6 MPa) was used as the coolant. Taguchi L9 orthogonal design with 4-factor, 3-level was employed for testing. Based on the signal-to-noise ratio and analysis of variance analysis, tool with dimple texture parameters (µm) of 50 depth, 150 diameter, 50 pitch and 75 distance from the cutting edge was optimum configuration for all the machining characteristics [10].

Cutting tools

Uncoated WC, TNMA160408THM (WIDIA)

Uncoated WC, TNMA160408THM (WIDIA)

Uncoated WC, TNMA 160,408-THMF (Kennametal India Limited)

AlTiN, CNMA432 KC 910 (Kennametal India Limited)

Material/machining process

Grade 5 Ti alloy/turning

Ti–6Al–4 V alloy/turning

Inconel 718 alloy/turning

Inconel 718 alloy/turning 17, 33, 49, 66

80, 120, 180

80, 130, 180

80, 130, 180

0.1, 0.12, 0.14, 0.16

0.16

0.1

0.15

0.2, 0.4, 0.6, 0.8

0.5

0.2

0.2

MQL, 80 ml/h

Dry 0.5 wt% (MoS2 + canola oil)

Dry canola oil 1 wt% (graphene + canola oil) Textures filled graphene

Dry 1 wt% (graphene + canola oil) canola oil

Dry/MQL

Depth of cut (mm)

Cutting speed (m/min)

Feed (mm/rev)

Cutting environment

Process parameters

Table 1 Machining parameters related to turning of superalloys using textured inserts

(continued)

hybrid texture tool considerably reduced the flank wear, tool–chip interface temperature [12]

Broken type of chips was formed under NMQL better surface finish with MoS2 particle-assisted NMQL [11]

Tool life with NMQL was doubled At high cutting speed (180 m/min) under dry cutting, the tool failed catastrophically due to absence of any lubrication [9]

Surface finish under NMQL environment was better than dry turning environment [8]

Findings [reference]

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Cutting tools

TNMA 160,408-THMF

Material/machining process

Inconel 718 alloy/turning

Table 1 (continued)

80, 120, 180

0.16

0.5

Dry machining

Dry/MQL

Depth of cut (mm)

Cutting speed (m/min)

Feed (mm/rev)

Cutting environment

Process parameters

Adhesion, abrasion, chipping and BUE were the most dominating wear mechanisms [13]

Findings [reference]

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Fig. 3 Types of textures [10]

2.3 Turning of Inconel Alloys Using Dimple Textured Inserts Darshan et al. studied the impact of cutting speed, machining time and tool texturing on machinability characteristics which include chip morphology, tool wear, surface finish and cutting forces while machining of Inconel 718 alloy using dimple textured inserts under dry and NMQL environment. Figure 4 depicts the methodology employed by the authors. Experiments were performed using textured tools at cutting speeds 80, 120 and 180 m/min (constant feed rate of 0.16 mm/rev and cutting depth of 0.5 mm). Dimple texture of diameter 50 µm and pitch of 100 µm were created on the rake face of uncoated WC, TNMA160408-THMF (Kennametal India Limited) inserts. 0.5% wt MoS2 canola oil-based nanofluids were used in NMQL environment. They found that with increase in cutting speed, the surface roughness was higher under dry turning environment when compared to a NMQL environment. Coefficient of friction was low due to the presence of MoS2. Figures 5, 6 and 7 show flank wear, crater wear and cutting temperature variation under dry and NMQL against machining time respectively [11].

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Fig. 4 Methodology employed by Darshan et al. in machining of Inconel718 using dimple-textured inserts under dry and NMQL environment [11]

Sivaiah et al. compared the machinability of untextured tool, tools with dimple texture and hybrid texture tool (dimples + grooves). They found that hybrid texture tool significantly reduced the flank wear, tool–chip interface temperature and surface roughness to a maximum of 59%, 36% and 46%, respectively when compared with untextured tool [12]. The dimples on tool, minimize the effective tool–chip contact area to cause low friction and also, act as fins to improve the heat transfer efficiency at the cutting zone [13].

3 Simulation of Turning Process Using Textured Inserts Mishra et al. studies were related to FE analysis of different texture shapes to predict cutting forces during turning of Grade 5 Ti alloy under dry environmental conditions.

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Fig. 5 Flank wear vs machining time curves with textured tool under dry (TT) and NMQL (TT + SL): a 80 m/min, b 120 m/min and c 180 m/min [11]

Figure 8 shows the details of the equipment used in machining of Ti alloy with textured tools. The texture shapes included circular, square, triangular and elliptical. Different types of textures were modeled with in a constant area of rake face (Fig. 9). Results from their studies indicate that area density was having significant effect on the cutting forces when compared to texture shape under dry condition (Fig. 10). However, as there was no fluid involvement in dry turning, depth of the texture had minute or no effect on the cutting forces. Usage of textured tools was limited under dry turning of Ti alloys at high feed and cutting speeds. Figure 11 depicts variation in apparent friction coefficient for different texture-shaped cutting tools with varying area density [14]. The FE modeling-based studies by Olleak and Oezel were related to the effects of textured turning tool on the temperatures, cutting forces, stresses under dry turning of Grade 5 Ti alloy. Microgrooves were engraved on the rake face as shown in Fig. 12. They found that perpendicular and diagonal grooved microtextured tools showed significant reduction in the cutting forces when compared with other designs. Figures 13 and 14 depict normal stresses and cutting temperature distribution on different textured tools along with the histograms respectively. Figure 15 illustrates the tool wear depth in mm on different textured tools [15].

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Fig. 6 Variation in crater wear w.r.t machining time: a 80 m/min, b 120 m/min and c 180 m/min [11]

Ma et al. used FE modeling to simulate dry turning of Grade 5 Ti-alloy using microgroove textured inserts. Figure 16 represents model of microgrooves fabricated on the rake surface of an insert. They investigated the effects of groove width, distance from the cutting edge and groove width/depth fraction on the cutting forces along with chip formation. They found that microgrooved cutting tool effectively reduced the cutting forces. Minimum cutting force was observed at groove width values around 40 and 60 µm. Optimum edge distance was in the range 70–90 µm, and optimum groove width-to-depth ratio was around 10 and 16 [16].

4 Turning Based on Textured Inserts with Twin-Jet Nozzle Investigation by Singh et al. showed machining under MQL and NMQL environmental conditions with mist supplied by two nozzles on the rake face and flank face simultaneously has better machinability characteristics when compared to mist applied on the rake surface with a single nozzle during turning of hardened steel (AISI 4340). The effectiveness of textured tool was studied based on flank wear, cutting forces, cutting temperature and chip morphology. Best tool life was achieved using twin-jet nozzle under NMQL. Figure 17 illustrates the twin-jet nozzle setup used in the experimentation [17].

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Fig. 7 Variation in cutting temperature w.r.t the machining: a 80 m/min, b 120 m/min and c 180 m/min [11]

5 Turning Based on Grooved Textured Inserts Fang and Obikawa fabricated different types of textures as shown in Fig. 18 on the flank surface of PVD-coated TiAlN, CNMG120408 inserts to enhance heat transfer from the tool face to coolant under the condition of high pressure jet delivered through a specially designed L nozzle (Fig. 19) in machining of Inconel718 alloy. Tool wear, adhesion wear and chip formation were related between the textured and untextured tools. They observed that microtextured tools had less flank and crater wear when related to the untextured tool, and the rate of tool wear was influenced by the pattern type and texture height [18–20]. The tool with 10 µm deep pit array showed the best performance minimizing flank wear by half when matched with non-patterned tool [18]. Sharma and Pandey fabricated hybrid textures (Fig. 20) on uncoated CNMA120404 THM carbide inserts to machine hardened steel (4340). CaF2 solid lubricant was used. They found that perpendicular textures reduced the tool–chip interaction area and act as lubrication storage locations [21]. Arulkirubakaran and Senthilkumar conducted turning experiments on Grade 5 Ti alloy with textured TiN, TiAlN and uncoated cutting tool inserts. Linear texture

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Fig. 8 Equipment related to machining with textured tools [14]

Fig. 9 Textures fabricated on the rake surface of the tools with laser micromachining [14]

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Fig. 10 Main cutting force observed while machining with texture cutting tools at varying density (Sp) [14]

Fig. 11 Coefficient of friction for different texture-shaped cutting tools with varying density [14]

grooves (250 µm wide and 100 µm deep) parallel and perpendicular to cutting edge, cross-texture were created over the rake surface of CNMA120408 tungsten carbide insert. Then the inserts were coated (4 µm thick) with TiN, TiAlN materials using physical vapor deposition method (Fig. 21). Experimental results revealed that TiAlN perpendicular textured turning inserts performed better in comparison with remaining inserts [22].

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Fig. 12 Different texture created on the rake surface of cutting tool insert with design parameters [15]

Fig. 13 Contour plot depicting normal stresses on different textured tools along with the histogram [15]

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Fig. 14 Contour plot depicting cutting temperature distribution on different textured tools along with the histogram [15]

Khan et al. studied the sustainability of turning of Ti alloy under Al-graphene particle nanoparticle-based MQL and conventional emulsion cutting environment. Al-graphene particles with 85:15 volume ratio were used to synthesize hybrid nanofluid (with a base fluid 1.2% vol). The flow rate of the MQL and coolant was 200 mL/h and 5 L/min respectively. Linear pattern (line)-type texture was engraved on the rake face using YLP-F20 pulsed fibre laser (1064 nm and a pulse of 10 ns). Results from the studies indicated that line-textured carbide cutting tools under Al-graphene particle nanoparticle-based MQL machining proved to be sustainable [23].

6 Conclusion In this review, we presented the latest designs of textures fabricated on the rake/flank surface of cutting inserts used in the turning of superalloys. From the studies, we

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Fig. 15 Contour plot depicting tool wear depth (mm) on different textured tools [15]

Fig. 16 Model representing design parameters of microgrooves fabricated on the rake surface of an insert [16]

concluded that circular dimples texture design was better when compared to groove textures because of symmetry. Due to high thermal coefficient and its ability shear makes graphene an excellent lubricant in turning processes. But, the effectiveness of graphene was good at low

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Fig. 17 Twin jet nozzles setup [17]

Fig. 18 Texture arrays and shapes on the flank face with design parameters. a Parallel groove, b perpendicular groove, c rectangular dimple, d circular and e cross-hatch [18] Fig. 19 Tool holder with specially made L-nozzle [18]

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Fig. 20 SEM images of different textured tools (38X and 100 µm), a perpendicular linear texture with multiple dimples, b cross-hatched, c parallel linear texture with multiple dimples and d multiple dimples [21]

and medium cutting speeds. Due to disordered graphitization, the role of graphene is limited at high cutting speeds. Machining with circular dimple-type textured inserts the effect of diameter of the dimple on the machinability is far greater than the effect of the depth of the dimple. Machining under NMQL environment and dry environment results in the formation serrated and continuous chips respectively. Continuous chips generally struck in between tool and the newly formed work surface resulting in inferior surface finish under dry environment. Under MQL and NMQL environmental conditions with mist supplied by two nozzles, on the rake face and flank surface simultaneously, have better machinability characteristics when compared to mist applied on the rake surface with a single nozzle. TiAlN-coated inserts with linear grooves perpendicular to the cutting edge performed effectively (continuous with evenly spaced serrated chips) when compared

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Fig. 21 Microgram with EDS examination, a TiN insert, b TiAlN insert [22]

with the other inserts in turning of Ti alloys. Simulation results agree with the experimental values. Grooved textured carbide cutting tools, under Al-GnP nanoparticle-based MQLassisted machining, were sustainable environmentally and economically.

References 1. Kishawy HA, Hosseini A (2019) Machining Difficult-to-Cut Materials. Springer International Publishing, Cham 2. Buddaraju KM, Ravi Kiran Sastry G, Kosaraju S (2021) A review on turning of Inconel alloys. Mater Today Proc 44:2645–2652 3. Sreejith PS, Ngoi BKA (2000) Dry machining: machining of the future. J Mater Process Technol 101:287–291 4. Niketh S, Samuel GL (2017) Surface texturing for tribology enhancement and its application on drill tool for the sustainable machining of titanium alloy. J Clean Prod 167:253–270 5. Yang Z, Tian YL, Yang CJ et al (2017) Modification of wetting property of Inconel 718 surface by nanosecond laser texturing. Appl Surf Sci 414:313–324

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6. Ma J, Duong NH, Lei S (2015) Numerical investigation of the performance of microbump textured cutting tool in dry machining of AISI 1045 steel. J Manuf Process 19:194–204 7. Debnath S, Reddy MM, Yi QS (2014) Environmental friendly cutting fluids and cooling techniques in machining: a review. J Clean Prod 83:33–47 8. Singh R, Dureja JS, Dogra M et al (2020) Wear behavior of textured tools under grapheneassisted minimum quantity lubrication system in machining Ti-6Al-4V alloy. Tribol Int 145:106183 9. Singh R, Dureja JS, Dogra M et al (2019) Influence of graphene-enriched nanofluids and textured tool on machining behavior of Ti-6Al-4V alloy. Int J Adv Manuf Technol 105:1685– 1697 10. Durairaj S, Guo J, Aramcharoen A, Castagne S (2018) An experimental study into the effect of micro-textures on the performance of cutting tool. Int J Adv Manuf Technol 98:1011–1030 11. Darshan C, Jain S, Dogra M et al (2019) Influence of dry and solid lubricant-assisted MQL cooling conditions on the machinability of Inconel 718 alloy with textured tool. Int J Adv Manuf Technol 105:1835–1849 12. Sivaiah P, Ajay Kumar GV, Singh MM, Kumar H (2020) Effect of novel hybrid texture tool on turning process performance in MQL machining of Inconel 718 superalloy. Mater Manuf Process 35:61–71 13. Darshan C, Jain S, Dogra M et al (2019) Machinability improvement in Inconel-718 by enhanced tribological and thermal environment using textured tool. J Therm Anal Calorim 138:273–285 14. Mishra SK, Ghosh S, Aravindan S (2018) 3D finite element investigations on textured tools with different geometrical shapes for dry machining of titanium alloys. Int J Mech Sci 141:424–449 15. Olleak A, Özel T (2017) 3D Finite element modeling based investigations of micro-textured tool designs in machining titanium alloy Ti-6Al-4V. Proc Manuf 10:536–545 16. Ma J, Duong NH, Lei S (2015) 3D numerical investigation of the performance of microgroove textured cutting tool in dry machining of Ti-6Al-4V. Int J Adv Manuf Technol 79:1313–1323 17. Singh R, Dureja JS, Dogra M (2019) Performance evaluation of textured carbide tools under environment-friendly minimum quantity lubrication turning strategies. J Brazilian Soc Mech Sci Eng 41 18. Fang Z, Obikawa T (2017) Cooling performance of micro-texture at the tool flank face under high pressure jet coolant assistance. Precis Eng 49:41–51 19. Ramesh R, Vinothkumar S, Jie S, Manikandan N, Yanzhe Z (2019) Experimental and Taguchibased grey approach of laser metal deposition technique on Nickel-based superalloy. Trans Indian Inst Met 72(1):205–214 20. Ramesh R, Muthukannan D, Vijay P, Shweta V, Rajendran R (2015) Microstructural and mechanical characterization of Ti6Al4V refurbished parts obtained by laser metal deposition. Mater Sci Eng A 643:64–71 21. Sharma V, Pandey PM (2016) Comparative Study of Turning of 4340 Hardened Steel with Hybrid Textured Self-Lubricating Cutting Inserts. Mater Manuf Process 31:1904–1916 22. Arulkirubakaran D, Senthilkumar V (2017) Performance of TiN and TiAlN coated microgrooved tools during machining of Ti-6Al-4V alloy. Int J Refract Metal Hard Mater 62:47–57 23. Khan AM, Hussain G, Alkahtani M et al (2021) Holistic sustainability assessment of hybrid Al–GnP-enriched nanofluids and textured tool in machining of Ti–6Al–4V alloy. Int J Adv Manuf Technol 112:731–743

Identification of SMAW Surface Weld Defects Using Machine Learning K. Ramesh , E. V. Ramana , L. Srikanth , C. Sri Harsha , and N. Kiran Kumar

Abstract The images of spatter, incomplete fusion, and acceptable beads by shielded metal arc welding (SMAW) process are captured through a digital camera with high resolution. Image processing techniques like blurring, thresholding, morphological operations, and contouring techniques are applied on the images to extract the geometrical shapes of surface defects and acceptable beads. The convolutional neural network (CNN) and ResNet50 are used in building machine learning models on contour dataset. In the present work, the classifiers identify the surface defect by image processing to produce better weldments. CNN and ResNet50 models are similar exhibiting prediction accuracies of 98.37% and 98.64%, respectively, in classifying the surface weld defects and the acceptable beads. Keywords Machine learning · Image processing · Surface weld defects · Convolutional neural network · ResNet50

1 Introduction Shielded metal arc welding (SMAW) is a manual arc welding process in which coalescence is generated by heating base metal and filler metal. The flux covering the electrode melts and protects the weld area from oxygen and other atmospheric gases. SMAW weldments considered in the current study are labeled into three classes as spatter, incomplete fusion, and acceptable. Spatter occurs when small metal particles are thrown out by the action of an arc during welding and attach to the surrounding work surface. Incomplete fusion is a weld discontinuity that occurs when there is no proper fusion between weld metal and adjoining weld bead(s) [1]. Mahapatra et al. [2] K. Ramesh Department of Mechanical Engineering, Birla Institute of Technology and Science, Hyderabad Campus, Pilani, Telangana, India E. V. Ramana (B) · L. Srikanth · C. Sri Harsha · N. Kiran Kumar Department of Mechanical Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_28

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discussed finite element analysis to theoretically predict the effect of welding parameters such as current, voltage, electrode diameter, and speed of travel on various zones of the weldments produced using shielded metal arc welding and experimentally verified. Image processing is a technique to analyze and perform manipulations on an image to improve its quality or excerpt helpful information. Guobo and Wen [3] introduced a method of image edge detection using thresholding, smoothing, morphological operations, and contour tracking techniques to determine the number of copper wires. Kumar et al. [4] recommended a method for detecting and tracking objects in the presence of cluttered backgrounds by extracting the foreground and representing objects through contours. Uma and Yuvarani [5] proposed a method for identifying and segregating shapes of toys by Ramer–Douglas–Peucker algorithm using image processing. Shishira et al. [6] proposed a solution for examining metal rods on a conveyer platform by characterizing the shape of rods using GrabCut segmentation and clustering-based image thresholding methods. Proximity contours were used to identify and track the movement of rods. Thien et al. [7] applied image processing techniques like normalization, Gaussian filter, and contouring to specify the defect region on an image, whereas Vilar et al. [8] applied Canny edge detection additionally to extract the geometrical shapes of the defects and finally developed an ANN model to predict the defects. Ranjan et al. [9] identified and classified the surface defects in friction stir welding using image pyramids and image reconstruction techniques. Machine learning algorithms are used to analyze the data, train from that data, and predict new data. Supervised learning is a method in which the algorithm learns from labeled data. There are different types of supervised machine learning algorithms available, among which CNN is most popular for image classification. CNN contains series of convolutional and pooling layers before the fully connected hidden layer. Residual neural network (ResNet) is a subclass of CNN, which can be manipulated easily and can achieve precision from increased depth. ResNet50 is a CNN that consists of 50 layers [10]. Khumaidi et al. [11] developed a CNN model to identify the welding defects such as spatter, porosity, and undercut and applied Gaussian kernel to extract the actual features from the captured images and achieved 96% validation accuracy. Zidek et al. [12] presented a method to identify assembly parts (screws, nuts) using CNN. Hough circle transformation was used to identify the assembly features (holes). Pre-trained COCO dataset weights were used to classify the images with R-CNN and MobileNet V 1. Jin et al. [13] developed a machine learning model and a responsive loop for real-time monitoring to modify 3D-printing process parameters iteratively and adaptively resulted in a prediction accuracy of 98%. Birlutiu et al. [14] presented ML algorithms to classify porcelain products automatically. The accuracies of ML algorithms such as CART decision tree (CART), k-nearest neighbors (KNN), linear discriminant analysis (LDA), logistic regression (LR), Naive Bayes, random forest (RF), support vector machines (SVM), and convolutional neural networks (CNN) were compared of which CNN gave the best results. Wang et al. [15] proposed a CNN-based element segmentation method combined with mask-based background filtering, faster R-CNN, and ResNet50 for high classification accuracy to extract the key features to sort the parts. Wen et al.

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Table 1 Weld current for classes Number of samples in each class

Weld current (A) Incomplete fusion

Acceptable

Spatter

30

75

115

135

20

80

120

140

20

85

125

145

30

90

130

150

[16] proposed transfer CNN based on ResNet50 to extract the features and improve validation accuracy on fault diagnosis. Hassan et al. [17] proposed an ANN model to detect the welding defects using radiographic images and achieved a prediction accuracy of 96%. In the present work, CNN and ResNet50 were implemented for image classification to detect surface weld defects of SMAW. The captured digital images of weldments were processed with Gaussian blurring, thresholding, and contouring techniques to extract the contours of defects. The dataset of three classes, such as acceptable, incomplete fusion, and spatter, was used to train the classification models. The models were evaluated on the contoured image dataset for higher prediction accuracy.

2 Experimental Work Low-carbon AISI 1019 (MS) rolled metal plates of 120 × 40 × 5 mm, 2.5 mm diameter electrode (E6013) are used with DCEP for specimen preparation. The welding is carried out on 100 weldments of each class, maintaining a constant voltage of 415 V with varying current, as shown in Table 1. The surface of the weldments is cleaned by the abrasive cloth of different grit sizes followed by microfiber cloth to capture quality images.

3 Methodology The methodology followed to detect SMAW surface defects through the machine learning approach is presented in Fig. 1. The material is cut into the required size of 120 × 40 × 5 mm, and the sides of the specimen are cleaned and straightened to make a square-groove joint. The images of weldments of each class are captured using a digital camera of 48MP resolution (Sony make EXMOR-RS TM with CMOS sensor) under suitable lighting conditions, as shown in Fig. 2. The region of interest in the images is cropped and resized to 400 × 2400 pixels without changing its aspect ratio, symmetric concerning weld bead,

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Fig. 1 Methodology

and avoiding loss of any information to build the dataset. The resized images (400 × 2400) are further divided into six blocks to avoid resource errors during training, as shown in Fig. 3. The source images contain RGB channels which are converted into single channel (grayscale) images, as shown in Fig. 4. The grayscale images are processed by blurring, thresholding, morphological operations, and contouring techniques for extracting the features of defects and acceptable bead. Blurring is done to reduce the noise in grayscale images and to enhance contour detection accuracy. The average filter function is applied in which the central element is replaced by the average of all

Fig. 2 Images of weldments, a acceptable, b incomplete fusion, c spatter

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Fig. 3 Resized images (400 × 400), a acceptable, b incomplete fusion and c spatter

pixels under the kernel area. It takes two arguments: the original image and the kernel. Kernel size (8 × 8) arrived after many trials with varied kernel sizes to distinguish the defects effectively from the background. An 8 × 8 kernel is selected in this filter to represent the pixels in computation, followed by thresholding on blurred images, as shown in Fig. 5. The thresholded images are shown in Fig. 6. Simple and adaptive thresholding failed to classify spatter, and incomplete fusion images of weldments as their threshold values are different for each image. Otsu’s thresholding is used for these two classes to get an automatic threshold value for the images and failed to produce the desired contours of the acceptable beads. Adaptive thresholding with a neighborhood area of 25 and constant 2 is used, in which the threshold value is the mean of the neighborhood area by considering the constant [18]. In morphology, the geometrical and topological structure of the thresholded images is examined by probing with the structuring element (in this case, a kernel of size 5 × 5 NumPy array of ones is considered). The closing operation is performed on the thresholded images with morphological operators (erosion followed by dilation). The contour tracking is applied on morphological images shown in Fig. 7 to extract the sequence of boundary points that identified and highlighted the edges of

Fig. 4 Grayscale images, a acceptable, b incomplete fusion and c spatter

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Fig. 5 Blurred images, a acceptable, b incomplete fusion, c spatter

Fig. 6 Thresholded images, a acceptable, b incomplete fusion, and c spatter

the acceptable beads and the weld defects. The tree retrieval mode is used to find contours to retrieve all the contour points with a full family hierarchy and approximation parameter to store the contour points without any omission. The contours are subsequently drawn with green color with an appropriate thickness on the edges of the acceptable beads and weld defects, as shown in Fig. 8. The images are converted into arrays using pre-defined image data generator functions from TensorFlow to be compatible with CNN and ResNet50. The values of color components (0–255) of the pixels in the image are normalized using the ImageDataGenerator function available in Keras to avoid resource errors and save compilation time. In CNN, a 3 × 3 kernel size is used with a pool size of 2 × 2 for feature extraction in each layer with a dropout of 0.5. CNN and ResNet50 models are trained for 15 epochs with a batch size of 5 for each iteration. Activation function ‘ReLU’ is applied for all layers and ‘softmax’ for the output layer. Log loss function (cross-entropy) determines the training and test losses for the models considered. The image dataset comprising 1845 contoured images is distributed into training and test datasets in the ratio of 80%:20%. Each epoch handles 295 training and 74

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Fig. 7 Morphological images, a acceptable, b incomplete fusion and c spatter

Fig. 8 Contoured images, a acceptable, b incomplete fusion and c spatter

validation iterations, computed by dividing the number of training and validation samples, respectively, by the batch size. The TensorBoard is used for plotting the logs of training and validation accuracies and losses of CNN and ResNet50 models.

4 Results and Discussion It is discovered that changing the ResNet50 and CNN algorithms’ hyperparameters affected training and validation accuracy. The training times per epoch for CNN and ResNet50 models are approximately 169 and 335 s, respectively. Figures 9 and 10 display the training and validation accuracy plots produced by TensorBoard for CNN and ResNet50, respectively. At the 15th epoch in CNN, the training and validation accuracies have declined, whereas the training and validation losses have risen, indicating that the model is overfitting. Consequently, further training of the CNN model is stopped. Figures 11 and 12 shows the representation of the sample

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images from the external dataset and prediction accuracies by CNN and ResNet50 models, respectively. The models are evaluated on the test dataset containing 369 images (111—acceptable, 119—incomplete fusion, and 139—spatter). The performance metrics of the models are illustrated in Tables 2 and 3. The F1-scores are computed considering the imbalance in the training and test dataset signifying the robustness of the models.

Fig. 9 CNN—accuracy and loss vs. epochs

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Fig. 10 ResNet50—accuracy and loss versus epochs

5 Conclusions Adaptive thresholding failed in the classification of spatter and incomplete fusion as their threshold values are different for each image. Otsu’s thresholding is selected for these two classes to get an automatic threshold value for the images successfully and failed to produce the desired contours of the acceptable beads. Morphological operation with a kernel size of 5 × 5 yielded better contoured images among other iterative kernel sizes.

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Predicted as acceptable with 100.00% probability

Predicted as spatter with 99.66% probability

Predicted as an incomplete fusion with 99.54% probability

Fig. 11 Prediction accuracies of acceptable bead, spatter, and incomplete fusion using CNN

Predicted as acceptable with 100.00% probability

Predicted as spatter with 99.92% probability

Predicted as an incomplete fusion with 99.94% probability

Fig. 12 Prediction accuracies of acceptable bead, spatter, and incomplete fusion using ResNet50 Table 2 Model performance of CNN True positive

False positive

False negative

True negative

Precision

Recall

F1-score

Acceptable

111

0

2

256

1

0.98

0.99

Incomplete fusion

118

1

4

246

0.99

0.97

0.98

Spatter

134

5

0

230

0.96

1

0.98

Table 3 Model performance of ResNet50 True positive

False positive

False negative

True negative

Precision

Recall

F1-score

Acceptable

111

0

0

258

1

1

1

Incomplete fusion

114

5

0

250

0.96

1

0.98

Spatter

139

0

5

225

1

0.97

0.98

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CNN and ResNet50 models are giving 100% prediction accuracy for acceptable beads. CNN was better in predicting incomplete fusion, whereas ResNet50 showed better results in predicting spatter. The training and validation times per epoch of CNN were approximately half of the time taken by the ResNet50 model, whereas both the models performed with similar prediction accuracies of 98.37% and 98.64%, respectively. The computed F1-scores and other performance metrics shows the robustness of the models.

References 1. Parmar RS (1996) Welding engineering and technology. Khanna Publications 2. Mahapatra MM, Datta GL, Pradhan B (2006) Three-dimensional finite element analysis to predict the effects of shielded metal arc welding process parameters on temperature distributions and weldment zones in butt and one-sided fillet welds. Proc Inst Mech Eng Part B: J Eng Manuf 220(6):837–845 3. Xie G, Lu W (2013) Image edge detection based on Opencv. Int J Electron Electr Eng 1(2):104– 106 4. Kumar P, Chakraborty R, Sarkar A (2014) Robust object tracking under cluttered environment. Int J Emerging Technol Adv Eng (IJETAE) 4(2) 5. Uma J, Yuvarani P (2017) Detection of shapes and counting in toy manufacturing industry with help of Phython. In: 2017 IEEE international conference on electrical, instrumentation and communication engineering (ICEICE). IEEE, pp 1–5 6. Shishira S, Rao V, Sudarsan SD (2019) Proximity contours: vision based detection and tracking of objects in manufacturing plants using industrial control systems. In: 2019 IEEE 17th international conference on industrial informatics (INDIN). IEEE, vol 1, pp 1021–1026 7. Thien ND, Le Chi C, Ngoc HN (2017) An approach to the automatic detection of weld defects in radiography films using digital image processing. In: 2017 International conference on system science and engineering (ICSSE). IEEE, pp 371–374 8. Vilar R, Zapata J, Ruiz R (2009) An automatic system of classification of weld defects in radiographic images. NDT and E Int 42(5):467–476 9. Ranjan R, Khan AR, Parikh C, Jain R, Mahto RP, Pal S, Pal SK, Chakravarty D (2016) Classification and identification of surface defects in friction stir welding: An image processing approach. J Manuf Process 22:237–253 10. Joshi P (2016) Python machine learning cookbook. PACKT Publishing Limited 11. Khumaidi A, Yuniarno EM, Purnomo MH (2017) Welding defect classification based on convolution neural network (CNN) and Gaussian kernel. In: 2017 International seminar on intelligent technology and its applications (ISITIA). IEEE, pp 261–265 12. Zidek K, Hosovsky A, Piteˇl J, Bednár S (2019) Recognition of assembly parts by convolutional neural networks. In: Advances in manufacturing engineering and materials. Springer, Cham, pp 281–289 13. Jin Z, Zhang Z, Gu GX (2019) Autonomous in-situ correction of fused deposition modeling printers using computer vision and deep Learning. Manuf Lett 1(22):11–15 14. Birlutiu A, Burlacu A, Kadar M, Onita D (2017) Defect detection in porcelain industry based on deep learning techniques. In: 2017 19th International symposium on symbolic and numeric algorithms for scientific computing (SYNASC). IEEE, pp 263–270 15. Wang Y, Hong K, Zou J, Peng T, Yang H (2019) A CNN-based visual sorting system with cloud-edge computing for flexible manufacturing systems. IEEE Trans Ind Inf 16(7):4726– 4735 16. Wen L, Li X, Gao L (2019) A transfer convolutional neural network for fault diagnosis based on ResNet-50. Neural Comput Appl 26:1–4

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17. Hassan J, Awan AM, Jalil A (2012) Welding defect detection and classification using geometric features. In: 2012 10th International Conference on frontiers of information technology. IEEE, pp 139–144 18. Dillibabu V, Muthukannan D, Chandrasekar U, Ramesh R (2016) Microstructural studies on laser dissimilar welded ni and steel alloys for aeronautical turbine applications. Lasers Eng 37:247–260

The Influence of Machine Learning in Additive Manufacturing Ramesh Raju, N. Manikandan, D. Palanisamy, P. Thejasree, P. Satheesh Kumar, P. Mohammed Rizwan Ali, and P. Sivakumar

Abstract Additive manufacturing gives possibilities to fabricate complex parts up to its near final net shape through layer-by-layer deposition on top. The process involves proper understanding of the underpinning physics involved in the selection of processing parameters as well as materials used. It elucidates the implementation of artificial intelligence technique in additive manufacturing concepts. Machine learning is one among the artificial intelligence technique and can be synchronized with additive manufacturing to have a control over automatic decision-making processes. The manufacturing of constituent structures can be defect-free as machine learning algorithms have a greater influence in optimizing the additive manufacturing process parameters as well as control over defect monitoring system. The present article mainly discusses about such perspective of machine learning in the additive manufacturing concept. The findings from various researchers are used to illustrate some interesting features of machine learning synchronized additive manufacturing. Keywords Additive manufacturing · Machine learning · Design data set · Part model · Regression analysis

R. Raju (B) · N. Manikandan · P. Thejasree Department of Mechanical Engineering, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh 517102, India e-mail: [email protected] D. Palanisamy Dr. APJ Abdul Kalam Research Centre, Adhi College of Engineering and Technology, Kancheepuram, Tamil Nadu 631605, India P. Satheesh Kumar Defence Research and Development Organisation, New Delhi, India P. Mohammed Rizwan Ali WeWork ReshaMandi, Bengaluru, Karnataka, India P. Sivakumar Mechanical and Industrial Engineering, University of Applied Sciences, Muscat, Oman © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_29

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1 Introduction Machine learning (ML) has gained widespread interest from group of research community as a promising digital technique for the modern additive manufacturing (AM) process. The AM technique comes under the group of fabrication techniques involving layer-by-layer manufacturing controlled through computer-aided design process. This process demands proper selection of processing parameters to achieve better fabrication of the designed components. The optimization process was performed in many ways reported by many researchers in recent times [1, 2]. Among all these processes, ML technique attracted major attention as part of integrated computational process. ML which is predominately a subset of artificial intelligence (AI) technique makes the machines suitable for extracting and accessing the data to predict the future data. The combination of AM with AI paves a pathway to intelligent manufacturing coupled with smart decision-making system to accelerate upgraded decisionmaking-based AM processes. The ML improves the performance of AM design aspects, and the taxonomy of the ML with respect to AM process falls under three categories, naming supervised learning, unsupervised learning and reinforcement learning. These learnings have to be used to train the data set which in turn helps to improve the accuracy level in the AM processing [3, 4]. The accuracy of AM process was influenced by data manipulation process of ML system. The processing parameters as well as respective data were analyzed and utilized for improvising the accuracy level of the AM process after every single machining. The major processing parameters of the AM include 3D printing speed, temperature of the working table as well as extruder nozzle, thickness of the print layer, power source intensity and so on. The data set of all these processing parameters was used by ML toward printing of part accuracy. The training data set further was enhanced by considering the feedback on acoustic emission which guarantees continuous improvement of ML system and ensures defect-free printing of components in real time [5]. Many researchers made an attempt to convert their design models into the intelligent one, and the attempts yielded highly appreciable results. The set-based conceptual design was used while modeling the support structures for the tissue engineering [6, 7]. The conceptual models were fine-tuned to adopt in the multistage design options for various problems [8–10]. The most successfully used model was Bayesian surrogate models by many researchers, and it was also proved that the model yields higher accuracy rate for the complicated design parts [11–13]. The intelligent systems help to overcome the issues on adjustments and corrections in the processing parameters while producing the parts through AM process. The process also helped to avoid the tedious and inefficient practices undergone during the previous time through trial and error methods while designing and printing of components [14, 15]. It illustrates that the process parameters are in line with the part quality and both are directly propositional to each other; hence, the relationship between these two is inevitable to achieve best printed products. ML systems already

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proved its significant impact on optimizing process and are intensely desirable for the AM processes. The present article is mainly focused to discuss the connectivity between AM and ML processes. It also intended to discuss the ML algorithms used in various articles by researchers and their significant impact on AM processing.

2 Artificial Neural Network for AM The parameter optimization as well as defect-free manufacturing both together can be achieved through adopting the ML technique in AM processes. It was evident that many techniques and algorithms like artificial neural network (ANN), back propagation neural network (BPNN), support vector machine (SVM) and so on were used in the previous days to achieve improved efficiency in the AM process. The ANN technique is effectively used as an optimization tool by many researchers in their work; more often, ANN algorithms like genetic algorithm (GA) [16] and particle swarm optimization (PSO) [17] have proven records against playing a significant role in simulation part as well as behavioral data approach. The AM process parameter experimental data were collected and used to train and test the ANN developed models. The trained model further manages the input and output responses along with other controlling factors. The surface finish of fused deposition modeling (FDM) component was improved by adopting ANN technique. The input and output processing parameters like print layer thickness, part orientation, surface finish and so on were used as data to be processed through developed ANN model. The schematic of ANN architecture is illustrated in Fig. 1, which contains main three layers of input layer, hidden layer and output layers. Bayesian regularization was adopted to process the optimal parameters, and Levenberg–Marquardt algorithm was used to train the selected ANN model. The probability distribution function of Bayesian regularization was specified in the Fig. 1 Architecture of neural network model

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Eq. (1) [18]. P(w/D, α, βη) = (P(D/w, βη)P(w/α, η))/(P(P/α, βη))

(1)

where the data set, network model and weight were represented as D, η and w, respectively. Other functions P(D/w, βη), P(w/α, η) and P(D/α, βη) represent the probability of data set with respect to weight function, prior to weight and normalized factors. The formulated function was used to define and train the data set which consists of both input and output machining parameters. It also contains the details about the targeted values mainly dependable with the processing parameters. The network training assures the predictability of the developed model should always come out with improved efficiency. The trained model set is ready to work to predict the optimal processing parameters, and one such response for the FDM process is illustrated in Fig. 2. It clearly indicates that the coefficient of correlation is higher in all three cases of predicted values against the targeted values. The process of ANN assures multifunctions in the AM techniques like part recognition, regression analysis, control systems and so on. The process model always learns from the data set which made it as unique process compared to other conventional optimization techniques. A bracket and flange were experimented for its suitability for AM process and ANN-assisted simulation [19]. The part models were created and evaluated for the performance in terms of preand post-compensation conformity scores. Figure 3 illustrates two part models of simple bracket and flange and different color shades of red and blue used to perform comparative analysis between simulated and CAD models.

Fig. 2 Network model prediction of surface roughness against the targeted values a top, b bottom and c side roughness values [18]

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Fig. 3 Part models and respective simulated models a simple bracket, b simulated bracket part model (red) CAD model (blue), c flange part model and d simulated flange part model (red) CAD model (blue) [19]

The selected part models responded well with ANN specific geometry methodology; the trained neural network was used to communicate with the required modeling to fabricate the final part model. ANN has a proven record in data fitting as well as capability estimations [20–22]. The trained data sets reveal the influencing process parameters as well as strong interaction between processing parameters. The sensitive analysis helps to find the variation of influence between processing and predicts the most and least sensitive processing parameters.

3 Back Propagation Neural Network for AM The BPNN was constructed with back propagation (BP) algorithm, and its architecture follows the same set of procedures as in the ANN; input layer followed with hidden and output layers also determines the connection weightage values. The input values do process to generate respective output values and compared against the actual outputs. The error values between both the output values were calculated and back propagated again to the input layer. The back propagated values were used to redefine the weightage values such that the error percentage between the output values reduced further and the process gets repeated after every weightage corrections until the error values go down to very minimum. The BP process suits well to train the data set with higher accuracy rate [23].

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The optimization of AM process parameters assures improved part quality; also, the optimization of AM part orientations assures cost efficiency of the printed components. Part orientation mainly depends on the type of support material used and the support structure required. As the support structures are intended toward stabilizing the print components as well as providing support against gravitational forces. The process is more important while considering the multi-part production process. Optimizing the part orientation results in most cost effective as well as higher production rate [24–28]. The optimization process starts with generating the individual part orientation of each part in the multi-part models. Later, two parts among the multi-part model do combine with each other with respect to their best optimal part position. In similar way one after one, all the parts used to be combined with each other. Finally, BPNN predicts the best optimal position with respect to the minimal support structure usage as well as no surface decoration. Figure 4 illustrates one such multi-part model optimization process mainly backed with BPNN strategy. Figure 4a illustrates the usual grouping of multi-parts in the AM processes. The optimized grouping model and respective printed parts are shown in Fig. 4b, c, respectively. The process can also be used for printing of group of components simultaneously with lesser printing time with least material consumption.

4 Support Vector Machine for AM The SVM is a statistical learning theory-based algorithm, which is capable to solve problems related to quadratic programming (QP) with undergoing minimum risk factors. The training data sets in this method do decide the size of the matrix to be used in the QP problems. Also, SVM method is having flexibility to re-modification of the algorithm as per requirements. The compactable algorithm can also be used against nonlinear regression models. The training of SVM network is similar to the BPNN, and the first stage of training will be done as per BPNN training procedure; later, the trained set will be normalized in accordance with the customized equations. In the process of normalization, kernel width and regularization parameters were initialized and optimized according to the modification recommended in the equations. The weightage values were also attained in this process and used against the error prediction and subsequent performance measures [29–32]. The SVM network can perform very well to overcome any dimensional difficulties. AM process part dimensions may vary with the source cloud data, which leads to complications in differentiating the dimensional specifications between AM parts and cloud data. The SVM process initializes the training of data set without weightage values and directional specifications. The scenario will help to correct the data set and create proper samples for further training, and the process continues until achieving the least possible deviations in the dimensional specifications of AM components. Figure 5 illustrates the dimensional variation occurred between cloud

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Fig. 4 Grouping the multi-part model a simple part position, b optimal way of multi-part positioning and c final printed parts [27]

data and AM part model for the circle, square and diamond part. The deviations in the cloud data set were greatly reduced by the researchers through adopting SVM algorithm, and also, the optimization approach helped to diagnosis the malfunctions and defects in the machining processes.

5 Other Methods for AM There are many algorithms developed and substituted as a class of deep neural network in the AM processes. The inheritance of ML in AM process is to ultimately reduce the data processing time duration and avoid any malfunctions and defects during the printing of components. The algorithms like ANN, BPNN and SVM already proved the importance of ML approach, and still, lot more algorithms are available for the similar processing. The other algorithms like neural network [33], self-organizing map [34], multi-layer perception, conventional neural network

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Fig. 5 Design of part model a simple part model, b sample as per cloud data and c SVM sampling process of final part model [31]

[35], gradient boost [36] and so on are also available to perform similar operations in AM processes.

6 Conclusion The paper discussed many ML models with respect to the manufacturing of part models in AM processes. The algorithms used in these ML models are more interpretable and can be adopted to detect the defects and for other quality assessments. The application of ML in the field of AM is inevitable for many reasons. The optimization of the AM processing parameters, optimizing the AM part orientation and optimizing the feature recognition to overcome dimensional variances are few among all other reasons. Regression analysis was framed one over another and used to avoid any geometrical deviations during the AM processes. The adequacy of development of nonlinear prediction models is also insisted while predicting the mechanical properties of the AM printed parts. The prediction accuracy is also more compared with conventional optimization techniques. Significance of multi-layer perception demanded the importance of advanced ML models to outperform against conventional models and stood more beneficial to avoid any dimensional deviations in the AM.

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References 1. Raju R, Arun Selvakumar T, Mohammed Rizwan Ali P, Satheesh Kumar P, Giridhar D (2020) Experimentation and process parametric optimization of 3D printing of ABS-based polymer parts. In: Springer-lecture notes in mechanical engineering, advances in industrial automation and smart manufacturing, pp 487–496 2. Raju R, Manikandan N, Binoj JS, Palanisamy D, Arulkirubakaran D, Thejasree P, PavanKalyan A, Subhash Reddy G (2020) Optimization and performance evaluation of PLA polymer material in situ carbon particles on structural properties. Mater Today Proc 39(1):223–229 3. Thompson MK, Moroni G, Vaneker T, Fadel G, Campbell RI, Gibson I, Bernard A, Schulz J, Graf P, Ahuja B, Martina F (2016) Design for additive manufacturing: trends, opportunities, considerations, and constraints. CIRP Ann Manuf Techn 65(2):737–760 4. Allison J, Sharpe C, Seepersad CC (2019) Powder bed fusion metrology for additive manufacturing design guidance. Addit Manuf 25:239–251 5. Haeseong J, Paul W (2017) A method for modularity in design rules for additive manufacturing. Rapid Protot J. 23(6):1107–1118 6. Malak RJ, Aughenbaugh JM, Paredis CJJ (2009) Multiattribute utility analysis in set-based conceptual design. CAD Comput Aided Des 41(3):214–227. https://doi.org/10.1016/j.cad. 2008.06.004 7. Weiss LE, Amon CH, Finger S, Miller ED, Romero D, Verdinelli I (2005) Bayesian computeraided experimental design of heterogeneous scaffolds for tissue engineering. CAD Comput Aided Des 37(11):1127–1139. https://doi.org/10.1016/j.cad.2005.02.004 8. Pacheco JE, Amon CH, Finger S (2003) Bayesian surrogates applied to conceptual stages of the engineering design process. J Mech Des Trans ASME 125(4):664–672. https://doi.org/10. 1115/1.1631580 9. Morris C, Bekker L, Haberman MR, Seepersad CC (2018) Design exploration of reliablymanufacturable materials and structures with applications to negative stiffness metamaterials and microstereolithography. J Mech Des Trans ASME. https://doi.org/10.1115/1.4041251 10. Matthews J, Klatt T, Morris C, Seepersad CC, Haberman M, Shahan D (2016) Hierarchical design of negative stiffness metamaterials using a Bayesian network classifier. J Mech Des Trans ASME. https://doi.org/10.1115/1.4032774 11. Shahan DW, Seepersad CC (2012) Bayesian network classifiers for set-based collaborative design. J Mech Des Trans ASME. https://doi.org/10.1115/1.4006323 12. Unal M, Miller SW, Chhabra JPS, Warn GP, Yukish MA, Simpson TW (2017) A sequential decision process for the system-level design of structural frames. Struct Multidiscip Optim 56(5):991–1011. https://doi.org/10.1007/s00158-017-1697-1 13. Choi H,McDowell DL, Allen JK, Rosen D, Mistree F (2008) An inductive design exploration method for robust multiscale materials design. J Mech Des Trans ASME. https://doi.org/10. 1115/1.2829860 14. Kim S, Rosen DW, Witherell P, Ko H (2019) A design for additive manufacturing ontology to support manufacturability analysis. J Comput Inform Sci Eng 19(4):041014 15. Ferguson M, Lee Y, Narayanan A, Law K (2019) A standardized PMML format for representing convolutional neural networks with application to defect detection. Smart Sustain Manuf Syst 3(1):79–97 16. Debabrata M, Pal Surjya K, Partha S (2007) Modeling of electrical discharge machining process using back propagation neural network and multi-objective optimization using non dominating sorting genetic algorithm-II. J Mater Process Technol 186:154–162 17. Chun-Yao L, Yi-Xing S, Jung-Cheng C, Yi-Yin L, Chih-Wen C (2009) Neural networks and particle swarm optimization based MPPT for small wind power generator. World AcadSci Eng Technol 60:17–23 18. Mahapatra SS, Sood AK (2012) Bayesian regularization based Levenberg–Marquardt neural model combined with BFOA for improving surface finish of FDM processed part. Int J Adv Manuf Technol 60(9–12):1223–1235. https://doi.org/10.1007/s00170-011-3675-x

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19. Chowdhury S, Anand S (2016) Artificial neural network based geometric compensation for thermal deformation in additive manufacturing processes. In: Joint MSECNAMRC symposia 3:V003T08A006. https://doi.org/10.1115/MSEC2016-8784 20. Negi S, Sharma RK (2016) Study on shrinkage behaviour of laser sintered PA 3200GF specimens using RSM and ANN. Rapid Protot J 22(4):645–659. https://doi.org/10.1108/RPJ-082014-0090 21. Mohamed OA, Masood SH, Bhowmik JL (2017) Influence of processing parameters on creep and recovery behavior of FDM manufactured part using definitive screening design and ANN. Rapid Protot J 23(6):998–1010. https://doi.org/10.1108/RPJ-12-2015-0198 22. Lao W, Li M, Wong TN, Tan MJ, Tjahjowidodo T (2020) Improving surface finish quality in extrusion-based 3D concrete printing using machine learning-based extrudate geometry control. Virtual Phys Protot. https://doi.org/10.1080/17452759.2020.1713580 23. Garg A, Tai K, Savalani M (2014) State-of-the-art in empirical modelling of rapid prototyping processes. Rapid Protot J 20(2):164–178 24. Chen H, Zhao YF (2015) Learning algorithm based modeling and process parameters recommendation system for binder jetting additive manufacturing process. In: Proceedings of the ASME design engineering technical conference, vol 1A. American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/detc2015-47627 25. Jiang J, Hu G, Li X, Xu X, Zheng P, Stringer J (2019) Analysis and prediction of printable bridge length in fused deposition modelling based on back propagation neural network. Virtual Phys Protot 14(3):253–266. https://doi.org/10.1080/17452759.2019.1576010 26. Jiang J, Weng F, Gao S, Stringer J, Xu X, Guo P (2019) A support interface method for easy part removal in direct metal deposition. Manuf Lett 20:30–33. https://doi.org/10.1016/j.mfg let.2019.04.002 27. Jiang J, Xu X, Stringer J (2019) Optimisation of multi-part production in additive manufacturing for reducing support waste. Virtual Phys Protot 14(3):219–228. https://doi.org/10.1080/174 52759.2019.1585555 28. Jiang J, Xu X, Stringer J (2019) Optimization of process planning for reducing material waste in extrusion based additive manufacturing. Robot Comput Integr Manuf 59:317–325. https:// doi.org/10.1016/j.rcim.2019.05.007 29. Lu ZL, Li DC, Lu BH, Zhang AF, Zhu GX, Pi G (2010) The prediction of the building precision in the laser engineered net shaping process using advanced networks. Opt Lasers Eng 48(5):519–525. https://doi.org/10.1016/j.optlaseng.2010.01.002 30. Vijayaraghavan V, Garg A, Lam JSL, Panda B, Mahapatra SS (2015) Process characterisation of 3D-printed FDM components using improved evolutionary computational approach. Int J Adv Manuf Technol 78(5–8):781–793. https://doi.org/10.1007/s00170-014-6679-5 31. Tootooni MS, Dsouza A, Donovan R, Rao PK, Kong ZJ, Borgesen P (2017) Classifying the dimensional variation in additive manufactured parts from laser-scanned three-dimensional point cloud data using machine learning approaches. J Manuf Sci Eng Trans ASME. https:// doi.org/10.1115/1.4036641 32. Li Z, Zhang Z, Shi J, Wu D (2019) Prediction of surface roughness in extrusion-based additive manufacturing with machine learning. Robot Comput Integr Manuf 57:488–495. https://doi. org/10.1016/j.rcim.2019.01.004 33. Xiong J, Zhang G, Hu J, Wu L (2014) Bead geometry prediction for robotic GMAW-based rapid manufacturing through a neural network and a second-order regression analysis. J Intell Manuf 25(1):157–163. https://doi.org/10.1007/s10845-012-0682-1 34. Khanzadeh M, Rao P, Jafari-Marandi R, Smith BK, Tschopp MA, Bian L (2018) Quantifying geometric accuracy with unsupervised machine learning: using self-organizing map on fused filament fabrication additive manufacturing parts. J Manuf Sci Eng Trans ASME. https://doi. org/10.1115/1.4038598 35. Baturynska I, Semeniuta O, Wang K (2019) Application of machine learning methods to improve dimensional accuracy in additive manufacturing. Lect Notes Electr Eng 484:245–252. https://doi.org/10.1007/978-981-13-2375-1_31

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Temperature Robust Health Bench-Marking and Monitoring of an Heritage Suspension Bridge Using Coupled IWCM and TBSI Method Yeturi Pramod Kumar Reddy and Subhamoy Sen

Abstract Bridges play a crucial role in transportation across water bodies, junctions, etc., minimizing the distance and traffic in a route. With ageing and continuous use, the bridges deteriorate and may even collapse if not monitored. With the gradual deterioration of its health, the dynamic properties alter with time. This damage-sensitive feature is therefore exploited by several techniques for damage quantification, and localization, which is in general categorized as vibration-based structural health monitoring (VBSHM). However, these features also change in an environment of varying temperature quite substantially that may mask the damage effect. This eventually entails inclusion of temperature information within the SHM procedure. This study undertakes Temperature-Based Structural Identification (TBSI) to locate and quantify structural faults in terms of fixity damage, material degradation, etc. Further, to dilute the effect of ambient noises and bias errors in the estimation procedure, Iterative Windowed Curve Fitting Method (IWCM) has been opted that supplies cleaner modal domain information for the TBSI to work. The investigation is undertaken simultaneously through numerical as well as real experimentation. Keywords IWCM · TBSI · SHM · Finite element modelling

1 Introduction Sudden damage in the structures leads to economic losses, uncertain downtime and sociopolitical chaos besides the possibility of human causality. Bridges may often be irreplaceable or even unaffordable to be stopped due to historical, political and economical reasons. Eventually, the old bridges need to be monitored continually and rigorously for structural faults, and accordingly, retrofitting has to be adopted whenever necessary. Further, the success of the SHM approach depends on how the investigator is interpreting the knowledge gathered from the structure in the form of its Y. Pramod Kumar Reddy (B) · S. Sen Indian Institute of Technology Mandi, Suran, Himachal Pradesh 175005, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_30

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responses. Eventually, without proper knowledge of the structure and its functioning, any SHM approach is bound to fail. One such aspect which most SHM approaches ignore is the impact of temperature on the dynamics of structures. Temperature affects the dynamic properties much like the damages in the same scale of damage and sometimes even more significantly. Eventually, excluding the thermal information from the SHM approach may lead to an incorrect and may at times to an infeasible solution. A substantial amount of research has been conducted to understand the impact of temperature on modal properties [1–6]. Obviously, such temperature-induced changes may often mask damageinduced alterations [5]. For instance, it may result in support movements or changes in boundary conditions or may induce thermal prestress in the structure which can, in turn, have an effect on modal parameters [7]. Lately, researchers have focused on removing the temperature effects from the response so that alteration can be attributed solely to damage [5]. Temperature also affects the fixity of the boundary conditions which, in turn, affect the modal parameters in bridges. In order to consider all possible impacts of temperature on a structure, Temperature-Based Structural Identification (TBSI) method has been introduced [8]. Further, while performing field experimentation, there may be chances of acquiring bias errors. Noise of unknown magnitude may at times contaminate the modal domain estimation. IWCM is typical frequency domain approach for modal parameter estimation, only improved to handle spectral bias errors that attenuate the values around frequencies causing spectral resonance [9]. IWCM converts the modal PSDs around resonating frequencies to theoretical PSDs before it is fitted to measured PSD. IWCM employs same window function in time domain for the measured data and in frequency domain for the theoretical PSD, diluting the effect of bias error and thereby improving the estimation accuracy. IWCM can be found as a good option in this endeavour that is capable of removing bias error while diluting the noise effect. IWCM has been experimented with ambient responses collected from the Second Severn Crossing (SSC) bridge, to obtain the filtered spectral densities and associated modal properties [9]. This method has also been used to reduce bias error from the measured data in [9]. In this study, the motivation has been to exploit the benefits of TBSI and IWCM method in order to develop a practical solution for the real-life monitoring of bridge infrastructure under thermal variability. It has already been discussed that TBSI method is susceptible to noise contamination, and therefore, a sufficiently clean information source is required to ensure perfect estimation. This study couples IWCM approach to remove the noise effect and bias errors from the measured modal response which is subsequently used in the TBSI framework. To determine the true damage in the structure, it is imperative to distinguish between the temperature-induced change and the actual damage which is possible with TBSI as long as the supplied information is free of noise and bias at sufficient extent. Details of IWCM method are explicitly described in [9]. The approach has been employed on a heritage bridge infrastructure in order to prepare the framework for its health estimation. The Victoria Bridge (cf. Fig. 1) is a 140-year-old heritage suspended type bridge in Northern India that was built in

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Fig. 1 The Victoria Bridge, Mandi

the year of 1877. Heavy vehicles have been banned from using the bridge since its condition has deteriorated significantly. There are four towers of 24 m height each that are supporting the main cables. The suspenders are connected 2 m apart from each other throughout the length of the bridge. The other relevant details are presented later in this article.

2 Experimentation on the Real Bridge The ambient vibration response of the bridge is recorded at a constant sampling frequency. In this process, a series of experiments were conducted on the bridge in January 2020. As the bridge was allowed to be used only by the pedestrians after the traffic was completely halted, ambient vibrations caused by pedestrians served as an excitation source. Sensors are utilized to acquire the corresponding response data and ambient temperature. Strain sensors are placed in those areas where the strain is likely to be maximum under usual service loading. The accelerometers, on the other hand, are placed at equidistant from each other along the bridge in its unsupported middle part. A total of 12 tri-axial wireless accelerometers were placed on the cross-girders along the length of the bridge (cf. Fig. 2) from which acceleration response data were aggregated from the wireless sensor nodes in a base station placed at east side of the bridge. The temperature of the structure is averaged over temperature measurements recorded across 12 locations of the bridge using an infrared thermometer. In each sampling event, vibration response was recorded for 15 min at a sampling frequency of 128 Hz recording 115,200 data samples in a time series. A total of ten experiments were undertaken at different parts of the day to consider the impact of temperature (cf. Fig. 5). A sample of the acceleration time series is presented in (cf. Fig. 4).

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Fig. 2 Sensor location

3 Creating the Digital Twin of The Victoria Bridge The objective of this study is to prepare a framework for The Victoria Bridge for damage identification under possible variability in thermal environment. Eventually, the responses from the damaged system will be an imperative requirement. Nevertheless, damaging a real structure, that too of historic value, is neither possible nor practical. A digital twin of the bridge is therefore developed that can showcase similar behaviour to the actual one. The use of field-measured responses to inform and update an apriori developed analytical model, and subsequently using this twin for damage detection or health assessment purposes, has produced a significant improvement in simulation reliability and accuracy in previous studies [4, 10– 13]. In this regard, firstly a high-fidelity Finite Element Model (FEM) is prepared with ABAQUS commercial FEM software with apriori assumed material properties and exact geometries as measured from the real bridge (also detailed in Table 1). B31 beam element is used for modelling floor beams and four main towers, and wire element is used to model suspenders. The main runner cable assembly of six component cables on either side of the bridge is replicated with a single cable of equivalent diameter allowing same axial stiffness. Similarly, the suspender cable assembly of two cables are replicated with single cable of equivalent stiffness. The suspender-floor beam connections are modelled with Multiple Point Constraints (MPC) (cf. Fig. 3). The east side connection of the bridge deck with the tower is modelled as link-to-link connection with an MPC. The west side tower-deck connection is in actual placed on an expansion bearings which has been modelled as spring supported (four linear springs for two nodes in two orthogonal directions) allowing the flexibility to be modelled to replicate any possible boundary behaviour through tuning their stiffnesses. (cf. Fig. 3). Since in reality the cable ends are embedded into concrete retaining walls, the end support of both the sides is assumed to be fixed supported. Following the ambient temperature during the real experiment, 10 °C has been maintained during the modelling as well.

Temperature Robust Health Bench-Marking and Monitoring … Table 1 Dimensions of The Victoria Bridge

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Dimensions of The Victoria Bridge Length

76.00 m

Width

4.16 m

Main cables

Y0.07 m @ 6 nos

Vertical suspenders

Y0.03 m @ 76 nos

Floor beam dimensions Floor beams

39 nos

Depth

0.45 m

Thickness (top flange)

0.10 m

Thickness (bottom flange)

0.10 m

Breadth (top flange)

0.30 m

Breadth (bottom flange)

0.30 m

Fig. 3 Schematic diagram of suspension bridge

Fig. 4 Acceleration data of The Victoria Bridge

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Fig. 5 Experimental results

4 TBSI-Based System Health Estimation With the apriori developed digital twin model and the measured temperature, response is simulated under a white Gaussian noise excitation. Next, an elaborate optimization is undertaken with the material elasticity and spring stiffness as control parameters in order to minimize the following objective function:

min E C ,E s ,E d

⌈ |∑ nf nd ∑ ∑ | ns | r2∈ (i ) + r2 ( j) + r2 (k) ,E s f

i=1

j=1

d

k=1

(1)

s.t{E c , E s , E d , K s } > 0 where r stands for residual in model predicted response measures to corresponding measured values. ∈, f and d denote mean strain, frequency and displacement values, while ns , nf and nd are the corresponding numbers of measurement collection points. E c , E s and E d are the elasticity of the main cable, suspenders and the beams in the deck slab, respectively. K s collectively stands as an array of stiffnesses of the six springs connecting the west side deck to the tower (cf. Fig. 3). The schematic diagram of The Victoria Bridge is shown in (cf. Fig. 3). An initial calibration study is firstly performed on the model to reach at the actual spring stiffness approximately. These spring stiffnesses are later used as the initial guesses for an elaborate optimization algorithm to obtain sufficiently optimized digital twin of the structure. In this attempt, the model strain profile is tried to be matched with the experimental strain profile obtained from the structure. Starting from a sufficiently good initial guess reduces the ill-posedness of the optimization algorithm. The spring stiffnesses, Young’s modulus of the cables, suspenders and the deck structure are thereby estimated through this approach (cf. Figs. 6and7). With the undamaged state of the bridge being benchmarked for a particular temperature, the temperature dependency of the material and structural dynamics has to be

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Fig. 6 Optimized spring stiffness

Fig. 7 Optimized Young’s modulus

included in the model (cf. Fig. 5). The material elasticity is assumed to be linearly varying with temperature. For that, the material elasticity is calibrated in order to match the frequency variation with temperature. The calibrated elasticity is further fitted with a linear graph, and the temperature-elasticity correlation is included in the twin model. After this model updating, it has been confirmed that the digital twin should marginally replicate the real structure both in time and frequency domain and also over ambient temperature band. From this point onwards, this digital twin represented the real structure as its proxy. Also, based on the simulation experience, the locations of the strain gauges on the twin model are re-adjusted for future usage.

5 Conclusions As a consequence of this study, the measured modal response is corrected for noise effects and bias errors with IWCM and then fed into the TBSI framework. The

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following key findings emerged during the research. In terms of evaluation of longspan bridges, IWCM and TBSI are complementary methods. The TBSI technique provides an in-depth description of the underlying movement mechanism and its material properties, while IWCM can be used to identify the structural frequencies and their damping ratios with better accuracy. TBSI is relatively straightforward to implement because it only requires small data storage and limited data processing and there is no need to worry about time synchronization.

References 1. Zhou H, Ni Y, Ko J (2010) Constructing input to neural networks for modeling temperaturecaused modal variability: mean temperatures, effective temperatures, and principal components of temperatures. Eng Struct 32(6):1747–1759 2. Ni Y, Zhou H, Ko J (2009) Generalization capability of neural network models for temperaturefrequency correlation using monitoring data. J Struct Eng 135(10):1290–1300 3. Hua X, Ni Y, Ko J, Wong K (2007) Modeling of temperature–frequency correlation using combined principal component analysis and support vector regression technique. J Comput Civ Eng 21(2):122–135 4. Peeters B, De Roeck G (2001) One-year monitoring of the Z24-bridge: environmental effects versus damage events. Earthq Eng Struct Dynam 30(2):149–171 5. Sohn H, Dzwonczyk M, Straser EG, Kiremidjian AS, Law KH, Meng T (1999) An experimental study of temperature effect on modal parameters of the Alamosa Canyon Bridge. Earthq Eng Struct Dynam 28(8):879–897 6. Cornwell P, Farrar CR, Doebling SW, Sohn H (1999) Environmental variability of modal properties. Exp Tech 23(6):45–48 7. Alampalli S (1998) Influence of in-service environment on modal parameters. Proc SPIE Int Soc Opt Eng 1:111–116 8. Yarnold MT, Moon FL, Emin Aktan A (2015) Temperature-based structural identification of long-span bridges. J Struct Eng 141(11):04015027 9. Macdonald JHG (2000) Identification of the dynamic behaviour of a cable-stayed bridge from full scale testing during and after construction. Ph.D. thesis University of Bristol 10. Brownjohn JMW, Moyo P, Omenzetter P, Lu Y (2003) Assessment of highway bridge upgrading by dynamic testing and finite-element model updating. J Bridg Eng 8(3):162–172 11. Aktan AE, Farhey DN, Helmicki AJ, Brown DL, Hunt VJ, Lee K-L, Levi A (1997) Structural identification for condition assessment: experimental arts. J Struct Eng 123(12):1674–1684 12. Abdel-Ghaffar AM, Scanlan RH (1985) Ambient vibration studies of golden gate bridge: I. suspended structure. J Eng Mech 111(4):463–482 13. Beck JL, Jennings PC (1980) Structural identification using linear models and earthquake records. Earthq Eng Struct Dynam 8(2):145–160

Electrical Characterization of Silicon Nitrate-Coated Polycrystalline Solar Cell Srinivasa Rao Davu, Ramesh Tejavathu, and Suresh Kumar Tummala

Abstract Solar energy is one of the most viable and renowned energy sources for reduced carbon emission and greenhouse effect. However, efficiency of solar cells is the most upsetting factor leading to advanced research in solar materials and their characterization. Today, solar cells are perceived not just as a method for giving force and expanded quality satisfaction to the people who do not have grid access; however, they are likewise a method for fundamentally lessening the effect of natural harm brought about by customary power age in cutting edge modern nations. In view of heavy competition in the local and global market, cost-effective manufacturing of reliable solar cells is not gaining attention. In this paper, electrical characterization and analysis of silicon nitrate-coated polycrystalline solar cell are simulated. Illuminated IV, Dark IV, open circuit voltage and short circuit current of the samples are analysed before and after coating with SiNx. Real-time simulation is performed on Corescan to validate the results obtained. This analysis is aimed to find the root cause for lesser efficiency in cells. Keywords Illuminated IV · Dark IV · SiNx · LBIC

Nomenclature C Si nC-Si SiO2 SiC SiNx

Carbon Silicon Nanocrystalline silicon Silicon dioxide Silicon carbide Silicon nitride

S. R. Davu (B) · R. Tejavathu EEE Department, National Institute of Technology Andhra Pradesh, Tadepalligudem, India e-mail: [email protected] S. K. Tummala Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad 500090, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Arockiarajan et al. (eds.), Recent Advances in Materials Processing and Characterization, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-19-5347-7_31

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QE SEM Al Ag O eV SR λ

S. R. Davu et al.

Quantum efficiency Scanning electron microscopy Aluminium Silver Oxygen Electron volt Spectral response Wavelength (nm)

1 Introduction Solar cell setup incorporates deciding the boundaries of a solar cell construction to expand adequacy, given a particular course of action of objectives. These objectives will be described by the work environment where solar cells are made [1]. For example, in a business space where the objective is to convey a forcefully assessed solar cell, the cost of making a particular solar cell structure should be contemplated [2]. Apart from the mechanical design and material characterization of any solar cell, electrical characterization has its own place in improving the overall cell efficiency. In any case, electrical characterization is classified into three categories which are referred as Mapping of the Cell, Imaging of the Cell and Cell Full Area Measurement. In full area measurement, the whole cell or enormous portion wafer is estimated giving one information point for every wafer [3, 4]. The estimations are normally quick enough for inline portrayal on each wafer going through a creation line, and the information delivered is reasonable for measurable interaction control. The weakness of full region estimations is that it does not uncover region-related issues like helpless imprinting on piece of a wafer. Planning strategies depend on direct by-guide estimations to filter across a wafer surface [5]. They might give a lot of precision about each point on the wafer and uncover deformities, for example, grain limits or different defects. The downside of planning strategies is the time taken to cover a whole wafer. For instance, if an estimation requires 0.1 s and a goal of 100 μm is needed for a 1500 × 1500 cluster of information guides, then the time to map a whole wafer will be 62 h. The long example times normally makes wafer planning unsatisfactory for in-line portrayal. An illustration of wafer planning is a LBIC framework where a laser is examined across the outer layer of the wafer and the current is perused out of every information point. Because of the occasions needed for two-dimensional pictures, planning procedures are frequently streamlined by utilizing line filters [6, 7]. Imaging away for is to some degree like snapping a picture the estimation procedure utilizes a sensor cluster to test various focuses all the while. The upside of imaging methods is that enormous varieties of information focus can be taken in tiny brief timeframes. The impediment is the expense of the sensors [8, 9]. The job of imaging procedures is expanding because of the presence of

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minimal expense silicon CCD cameras like those utilized in computerized cameras [10, 11]. The most basic of cell characterization methods is the estimation of cell proficiency. State-administered testing permits the correlation of gadgets made at various organizations and research centres with various advances to be analysed. The principles for cell testing are as follows: 1. 2. 3. 4.

Air mass 1.5 spectrum (AM1.5). Intensity of 100 mW/cm2 (1 kW/m2 ). Cell temperature of 25 °C. Four-point probe.

The standard lighting source will have the following features: 1. Longitudinal non-uniformity < 1%. 2. Irradiance variation with time < 1%. 3. Spectral mismatch error for a given reference < 1%. These requirements are essential in obtaining an accuracy of > 2%. One-sun enlightenment is very exceptional so there must be some instrument to eliminate the overabundance heat. Commonly, the cell is put on an enormous metal square and water goes through the square to keep it cool. A thermocouple is embedded in the square, and the control framework is acclimated to the necessary 25 °C. The cell light IV bend can be followed by modifying a variable resistor across the cell and recording the voltage and current at the cell terminals. While this is very straightforward, it is tedious so practically speaking more complex gadgets are utilized. The most widely recognized strategy is to utilize a variable voltage source that is likewise fit for sinking current. To further develop precision, I sc and V oc are typically estimated independently (by separately setting the voltage to nothing and the current to nothing) from the remainder of the bend. Cell testing utilizes a four direct tests to contact the cell: a current and voltage test on top of the cell and a current and voltage test on the lower part of the cell. The most widely recognized game plan is to have the metal of the square go about as the back current test and afterwards to have a voltage pin through it.

2 Methodology and IV Trace There are no idealities in solar cells so that contrasting the estimations under conditions empowers the assurance of cell boundaries. The IV bend of a solar cell is the superposition of the IV bend of the sun powered cell diode in obscurity with the light-created current. The light moves the IV bend down into the fourth quadrant where force can be extricated from the diode. Enlightening a cell adds to the typical “dim” flows in the diode with the goal that the diode law becomes:

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⌈ ( ) ⏋ qV − 1 − IL I = I O exp nkT

(1)

Without illumination, a solar cell has the same electrical characteristics as a large diode. When light shines on the cell, the IV curve shifts as the cell begins to generate power. The greater the light intensity, the greater the amount of shift. The solar cell curve is flipped by convention. The −1 term in the above condition can typically be disregarded. The outstanding term is generally >>1 except for voltages under 100 mV. Further, at low voltages, the light-produced current I L rules the I 0 (…) term so the −1 term is not required under brightening. ⌈ ( )⏋ qV I = I L − I O exp nkT

(2)

Since cells convert light to power, it may appear to be odd to quantify the photovoltaic cells in obscurity. Be that as it may, dim IV estimations are significant in inspecting the diode properties. Under brightening, little vacillations in the light power add impressive measures of noise to the framework making it hard to create. Dull IV estimations use infuse transporters into the circuit with electrical means as opposed to with light-created transporters. As a rule, the two are same and the Dark IV estimations give additional data about the cell for analytic purposes. Indeed, even without any noise, there is an abundance of data in contrasting the enlightened and dim IV bends. The best wave to investigate IV curve when series resistance of the cell is absent is plotting J SC -V OC curve. The brightening on a cell is differed and the cell J SC and V OC estimated at every light level. The series obstruction has no impact on the V OC , since no current is drawn from the cell; thus, there is no voltage drop across the series opposition. Inasmuch as the series obstruction is under 10 Ω cm2 , it has little impact on J SC as the IV bend is level around JSC . Illumination on the cell is varied from 0.01 to 1 suns, and respective J SC and V OC are plotted. Standard Dark IV measurement in linear scale is shown in Fig. 1. Graph 1 of Figs. 2, 3 and 4 shows the more recognizable enlightened one-sun IV bend in blue for reference. At the point when the slider is set to one-sun brightening, the J SC and V OC esteems lie on the one-sun bend. Changing the light gives another pair of J SC V OC esteems that are then plotted on different diagrams. Chart 2 is an immediate plot of the deliberate J SC V OC estimation. The J SC V OC is basically the same as the dull IV aside from the impact of series obstruction, which influences the dim IV bend yet not the J SC V OC bend. The shunt opposition influences both the Dark IV and the J SC V OC estimations. Figure 2 shows the J SC V OC curve with illumination of 1 sun, and J SC V OC curve with illumination of 0.5 suns and 0.011 suns is shown in Figs. 3 and 4, respectively.

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Fig. 1 Dark IV measurement in linear scale

Fig. 2 J SC V OC curve with illumination of 1 suns

3 Measurement of Series Resistance There are a few strategies to gauge series obstruction and the correlations of the precision for explicit cell types. The least difficult way of estimating series obstruction is to fit the enlightened IV bend with either the best diode condition or the twofold diode condition. While this is theoretically exceptionally straightforward, there are

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Fig. 3 J SC V OC curve with illumination of 0.5 suns

Fig. 4 J SC V OC curve with illumination of 0.011 suns

regularly issues by and by. Probably, the most concerning issue is that the cell series opposition is a lumped boundary made from numerous protections inside the gadget. A solar cell is a three-dimensional gadget and can be considered as an organization of resistors and diodes. As the degree of current changes, so does the evident series opposition. A Thevenin or Norton identical circuit must be developed without even a trace of non-straight components like diodes. With just piece of the cell influenced by Rs, an assortment of bends is created. In the reproduction underneath take a stab

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Fig. 5 IV characteristics of solar cell with series resistance of 2 Ω cm2 and affected area fraction of 1

at setting the part to 1 and changing the inward Rs. Its ledge follows the basic onedimensional case. The have a go at setting the part to 0.5, it creates an adjusting around the greatest force point like a high J02. In the last case have a go at setting the negligible part of the cell influenced by Rs to 0.1. For this situation, the IV bend looks basically the same as a phone with a low Rshunt . The IV characteristics of solar cell are analysed and compared with the standard IV characteristics of an ideal cell by varying series resistance and affected area fraction of the cell. Initially, the series resistance of the cell is considered as 2 Ω cm2 and the affected area fraction on the cell is changed and considered at 0.5 and 1. The resultant IV characteristics of these values are plotted in Figs. 5 and 6, respectively. Similarly, the same affected area fraction is considered for two intervals of 1 and 0.5 and the series resistance of the cell is increased to 4 Ω cm2 . The resultant IV characteristics are plotted in Figs. 7 and 8, respectively. It is observed that as the series resistance of the cell increases, the IV characteristics will be reduced. It is viable to always increase the shunt resistance rather than increasing the series resistance for efficient output.

4 Methodology and Experimentation The proposed methodology is based on a mixed-mode simulation approach, which allows evaluating the solar cell properties. One of the samples is tested before coating with SiNx and after coating with SiNx. Using Corescan, the samples are analysed to find the responsivity of the cells. Wavelengths of 300–1100 nm are focused on the cells. Figure 9 shows the responsivity graph when the solar cell is coated with and

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Fig. 6 IV characteristics of solar cell with series resistance of 2 Ω cm2 and affected area fraction of 0.5

Fig. 7 IV characteristics of solar cell with series resistance of 4 Ω cm2 and affected area fraction of 1

without silicon nitrate. It is observed in all the wavelengths that when the cell is coated with silicon nitrate, the detector responsivity is much better than the cell without silicon nitrate coating. The quantum efficiency of the cells shows improvement when coated with silicon nitrate; this improvement can be observed from Fig. 9. The colour of the light at various wavelengths is shown in Table 1.

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Fig. 8 IV characteristics of solar cell with series resistance of 4 Ω cm2 and affected area fraction of 0.5

Detector Responsivity

0.7 0.6 0.5 0.4 0.3 0.2 0.1 300 335 370 405 440 475 510 545 580 615 650 685 720 755 790 825 860 895 930 965 1000 1035 1070

0 Wave Length (nm) Without SiNx

With SiNx

Fig. 9 Detector responsivity of solar cell at different wavelengths

5 Conclusions Electrical characterization and analysis of silicon nitrate-coated polycrystalline solar cell are simulated. Solar cell samples are analysed before and after coating with SiNx. Illuminated IV, Dark IV, Open Circuit Voltage and short circuit current of the samples are also analysed. It is observed that for wavelengths of 300–1100 nm, the responsivity graph when the solar cell is coated with and without silicon nitrate has

380 Table 1 Colour of light for various wavelength

S. R. Davu et al. Colour

Wavelength Colour (nm)

Wavelength (nm)

Violetish

393.72

640.48

Red

Violetish

420.42

Bloody red

671.92

Duller blue

426.16

Reddish pink

688.28

Blue

442.72

Dull red

708.73

Yellow

448.8

More vis phone

791.77

Yellow

448.8

More vis phone

819.08

Blue

475.42

Vis phone

843.35 851.76

Greenish blue

491.09

Vis phone

Green

497.66

Very mild phone 918.66

Greenish yellow

510.84

Very mild phone 967.37

Brownish orange 601.17

Invisible

Red

Very mild phone 990.73

637

Invisible

985.13 1000.6

improvement in the quantum efficiency, when the solar cell is coated with silicon nitrate. It is observed in all the wavelengths that when the cell is coated with silicon nitrate, the detector responsivity is much better than the cell without silicon nitrate coating. Real-time simulation was performed on Corescan to validate the results obtained of the sample considered.

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