Proceedings of international conference on intelligent manufacturing and automation ICIMA 2018 ( TQL)

Part I DesignMathematical Modeling and Optimization of Process Parameters for Tensile Strength and Nugget Diameter in Resistance Spot Welding of HR E-34 Steel Sheet Joint.. and Optimizat

Lecture Notes in Mechanical Engineering

Hari Vasudevan

Vijaya Kumar N Kottur

Amool A Raina Editors

ICIMA 2018

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Proceedings of International Conference on Intelligent Manufacturing

and Automation

ICIMA 2018

123

Hari Vasudevan

Department of Production Engineering

Dwarkadas J Sanghvi College

of Engineering

Mumbai, Maharashtra, India

Vijaya Kumar N Kottur

Department of Mechanical Engineering

Dwarkadas J Sanghvi College

of Engineering

Mumbai, Maharashtra, India

Amool A RainaAerospace Group, Institute of TextileTechnology

RWTH Aachen UniversityAachen, Germany

Lecture Notes in Mechanical Engineering

https://doi.org/10.1007/978-981-13-2490-1

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This is an exciting time for business and wealth creation in the fields of facturing and automation It is the time when industries are looking up to manu-facturing and automation engineers for their assistance in increasing the overallproductivity in their organisation It is also the time when the governments acrossthe globe have started to focus more on the manufacturing sector The InternationalConference on Intelligent Manufacturing and Automation 2018 (ICIMA 2018) wastherefore designed to encourage discussions and research on advancements andapplications in the areas of manufacturing and automation The primary focus ofthis conference was to bring together academicians, researchers and scientists forknowledge sharing in various areas of manufacturing, automation and other allieddomains The conference covered topics encompassing automation, mechatronics,robotics, manufacturing processes, management and other related areas such asproduct design and development, green manufacturing and smart materials with theobjective of brainstorming and emphasising upon the applications in the field ofintelligent manufacturing and automation The response to call for papers wasoverwhelming with 109 full papers being submitted, covering a wide spectrum oftopics related to the theme of the conference We express our sincere appreciation tothe authors for their contribution to this book We would also like to express oursincere gratitude to all the experts and referees for their valuable comments andsupport extended during the review process.

v

Shri Amrish R Patel, Chief Patron, President, SVKM

Shri Bhupesh R Patel, Joint President, SVKM

Shri Bharat M Sanghvi, Vice President and Trustee, SVKM, and Chairman,Governing Council, DJSCE

Shri Sunandan R Divatia, Hon Secretary, SVKM

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International Advisory Committee

Dr Amit S Jariwala, Georgia Institute of Technology, USA

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Dr Amool Raina, RWTH Aachen University, Germany

Dr Rohan A Shirwaiker, North Carolina State University, USA

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National Advisory Committee

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of Mumbai

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Dr L Ganapathy, NITIE, Mumbai

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Dr K P Karunakaran, IIT Bombay

Dr K Maddulety, NITIE, Mumbai

vii

Dr Suhas S Joshi, IIT Bombay

Dr Tushar Desai, NIT Surat

Dr V R Kalamkar, VNIT Nagpur

Dr P Sakthivel, VIT Vellore

Mr C M Venkateswaran, Aker Solutions

Organising Committee

Dr Hari Vasudevan, General Chair, Convener and Principal, DJSCE

Dr A C Daptardar, General Co-Chair, Vice Principal (Admin.), DJSCE

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Dr Vijaya Kumar N Kottur, Joint Convener, Professor and Head, Department ofMechanical Engineering, DJSCE

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This volume comprises the best-selected papers presented at the InternationalConference on Intelligent Manufacturing and Automation, which was organised bythe Departments of Mechanical Engineering and Production Engineering ofDwarkadas J Sanghvi College of Engineering The volume focuses on narrowedtopics of automation, mechatronics, robotics, CAD/CAM/CAE/CIM/FMS inmanufacturing, product design and development, DFM/DFA/FMEA, MEMS andnanotechnology, rapid prototyping, computational techniques, industrial engineer-ing, manufacturing process management, modelling and optimisation techniques,CRM, MRP and ERP, logistics and supply chain management, quality assuranceand environment protection, advanced materials processing and characterisationand composites and smart materials The papers are divided into four main domainslike design, advanced materials, manufacturing and automation We expect thearticles, being published in the book, would contribute to and reinvigoratethe overall efforts in enhancing manufacturing productivity across various sectors.The content of the book is also expected to be helpful for postgraduate and doctoralstudents in their efforts to enhance the research outcome of their studies.

ix

Part I Design

Mathematical Modeling and Optimization of Process Parameters

for Tensile Strength and Nugget Diameter in Resistance Spot Welding

of HR E-34 Steel Sheet Joint 3

B S Gawai, R L Karwande, Md Irfan and Prafull S Thakare

Numerical Simulation Over Conical Aerospike at Mach 6 15Rahul S Pawar, N R Gilke and Vivek P Warade

Multi-characteristics Optimization in the Turning of GFRP

Composites Based on Grey-Taguchi Method 27Hari Vasudevan, Ramesh Rajguru and Kalpesh Tank

Vibrational Analysis of Single-Point Cutting Tool for Different Tool

Material and Nose Radius Using Design of Experiment 35

C M Choudhari, I A Bhisti, M G Choudhary and A H Mistry

Design of Automated Two-Wheeled Forklift with Retracting

Third Wheel and Dynamic Counterbalance Mechanism 47Abhinav Kshirsagar, Neha Kesarkar and N S Chandrashekhar

Design and Analysis of Piercing and Extrusion Tool 55Gopal B Mudholkar, Girish M Lonare and Sadhana R Hivre

Design and Analysis of Coaxial Rotor Wind Turbine 69Sachin Manohar Shinde, Mohit Chaudhari, Tejas Jeurkar, Sanket Kadam

and Kiran B Salunkhe

Parametric Optimization of MIG Welding on IS 1079

HR 2 by Taguchi Method 81Mayur D Jagtap and Niyati Raut

xi

Design and Prototype of Wireless Robot for Condition Monitoring

of Coal Conveyor Roller Bearings 89Vikesh P Kumawat, Nikhil S Divate, Sangeeta Bansode,

Amit Kumar Patel and Kailas S Jagtap

Design, Analysis and Modification of 3 Stage Helical Gearbox Casing

Using Finite Element Method Considering Different Materials 99Ronak D Gandhi and Nimeshchandra S Patel

Analysis of Cyclone Separator Used for Liquid-Gas Mixing 115Gayatri Malekar and Niyati Raut

Development of Mathematical Model for Top Roller Displacement

of Three-Roller Bending Machine Using Dimensional Analysis 125Prafull S Thakare, Sandip M Salodkar and C C Handa

Design and Analysis of Vertical Vacuum Fryer 133Abhishek Gupta, Amit Choudhari, Taha Kadaka and Pavan Rayar

Design, Manufacture and Testing of an Impact Attenuator

for a FSAE Car 151Parth Thakar, Suyash Ail, Jayraj Ranade and Parshva Mehta

Application of Steady State and Transient Modeling

for Characterization of Vortex in Vertical Pump Intake

for Single Phase 161Rahul Paliwal, Bhola Nagelia, Hrishikesh Pangarkar, Anant Jhaveri

and Channamallikarjun S Mathpati

Design of Feedstock and Liquefier for Printing Aluminium

Parts by Fused Deposition Modeling 171Pravin S Misal and N S Chandrashekhar

Static Structural Analysis of Car Rim by Finite Element

Method 181Suraj L Gondhali, Atul D Dhale and Sunil Pagare

Comparative Thermal Analysis of Fins 195

H A Patel, V S Kale, S U Joshi, S D Jadhav and S N Teli

Design and Development of Small-Capacity Mango

Process Plant 205Nandu Durge, Shankar Mantha and Vikas Phalle

Analysis of Curve Fitting for Case Studies: An Appropriate

or Non-appropriate Method 221Rajkumar P Narkhede and Prabha Rastogi

Posture Assessment Among Waste Loading Workers in India 229Francis J Emmatty and Vinay V Panicker

Evaluation of Performance Characteristics and Bite Condition

of Single Ferrule Bite Fitting by Finite Element Analysis (FEA) 239Akshay Kusneniwar, Prathamesh Potdar and Santosh Rane

Optimization of the Chest Geometry for the Storage

and Transportation of Fruits and Vegetables 253Ajinkya Netake, Rushabh Mutha, Akash Mishra, Aditya Sawant,

Prathamesh Potdar and Nitin Panaskar

Part II Advanced Materials

Experimental Investigations of Mechanical Properties

and Microstructural Characterization of Aluminum–Silicon Alloy

Castings 267

D M Wankhede, B E Narkhede, S K Mahajan and C M Choudhari

Multiobjective Optimization in Drilling of Composites 279Paramjit Thakur, S N Teli and Siddhesh Lad

Evaluation of the Mechanical Properties of Recycled

Jute Fiber–Reinforced Polymer Matrix Composites 287Pullareddy Mekala, Manohar Reddy Kunuthur

and B Chandramohana Reddy

Predictive Modelling of Delamination Factor and Cutting

Forces in the Machining of GFRP Composite Material

Using ANN 301Hari Vasudevan, Ramesh Rajguru and Rajnarayan Yadav

Review of Application of Nitinol in the Manufacture

of Bone Staples 315Neel Sanghvi, Frank Crasta and Vijaya Kumar N Kottur

A Review on Graphene 323Farhan Sayed, Mitesh Parmar and Shashikant Auti

Comparative Wear Analysis of (3 3) PTFE Composite

Materials 333

A D Diwate and S B Thakre

Synthesis of Polyaniline-Vanadium Pentoxide Nanocomposites:

A High-Performance Conducting Material for Energy Storage 345Sugam Shivhare, Praveen Kumar Loharkar, Supriya Vyas,

Vivekanand Bagal and Malvika Sharma

Effect of Benzoxazine on Epoxy Based Carbon Fabric

Reinforced Composites for High Strength Applications 353

C Venkateshwar Reddy, Ch Joseph S Raju, P Ramesh Babu

and R Ramnarayanan

Microwave Assisted Synthesis of Palladium Doped Zinc Oxide

Nanostructures and Their Gas Sensing Applications 369Yogita S Patil, Sushil Charpe, F C Raghuvanshi

and Ramzan Muhammad

Investigation of Moisture Absorption in Jute Fiber

Polymer Matrix Composites 379Manohar Reddy Kunuthur and B Chandramohan Reddy

Experimental Performance and Analysis of Domestic

Refrigeration System Using Nano-Refrigerants 389Deepak Bondre, Apurav Joshi, Tejas Shinde, Apurv Deshmukh

and Kavita Dhanawade

Experimental Investigation and Optimization of End-Milling

Parameters in the Machining of Inconel 825 Using

Carbide-Coated Tool 401Hari Vasudevan, Ramesh Rajguru, Geet Dave, Arun Alva, Vinil Punjani

and Devdatt Bhurke

Optimization of Machining Parameters in the Turning Operation

of Inconel 825 Using Grey Relation Analysis 413Hari Vasudevan, Ramesh Rajguru, Shreyans Jain, Milan Kaklotar,

Jaineel Desai and Sanidhya Mathur

A Review and Analysis of the Machining Process Involving

Nickel-Based Super Alloy 425Ramesh Rajguru and Hari Vasudevan

Part III Manufacturing

Minimization of Shrinkage Porosity in HPDC Process

with Local Squeeze Pin Using Flow Simulation 435Shivkumar Biradar and Prashant T Borlepwar

Optimization of Injection Moulding Process Parameters

Using Response Surface Methodology 445Khavekar Rajendra, Hari Vasudevan and Gosar Vimal

Optimization of Cutting Parameters in Dry Turning of AISI 4140

Hardened Alloy Steel with Coated Carbide Tool 455Sandip Mane and Sanjay Kumar

A Perspective of Integrated Machine Vision Based-Multivariate

Statistical Process Control 463Ketaki N Joshi and Bhushan T Patil

Development of Facility Layout for Medium-Scale Industry

Using Systematic Layout Planning 473Onkar V Potadar and Ganesh S Kadam

Intelligent Unmanned Aerial Vehicles 485Parth Thakkar, Anand Balaji and Vaibhav S Narwane

Study on Power Consumption of Split Air Conditioner Depending

on Distance Between Condenser and Evaporator Units 495Bysani Malakondaiah

Monte Carlo Simulation of Arrival of Materials

on Assembly Line 503Jimit Shelat

Recent Developments in the Field of Rapid Prototyping:

An Overview 511Umesh Sable and Prashant T Borlepwar

Performance Study of Stamping Process Using Condition

Monitoring: A Review 521Tushar Y Badgujar and Vijay P Wani

Application of Discrete-Event Simulation to Increase

Throughput of Manufacturing System—A Case Study 531Prasad V Thete and Ramesh R Lekurwale

Enhancement in Productivity by Integration of 5S Methodology

and Time and Motion Study 541Rushank Sangani and Vijaya Kumar N Kottur

Decision Support System for Failure and Down Time Reporting:

A Tool for Achieving Production Targets from Remote Mining

Equipment 551

V M Kalra, Thakur Tilak and B S Pabla

Reviewing the Problem of ELVs in India and Checking

Possibilities of Pyrolysis as a Solution 565Kaival Rajesh Nayak and Shashikant Auti

Effect of Process Parameters While Machining Using

Abrasive Jet Machine (AJM) 575Shaishav M Jadav and Ramesh R Lekurwale

Identifying Key Success Factors of Sustainability in Supply

Chain Management for Industry 4.0 Using DEMATEL Method 583Malleshappa T Bhagawati, E Manavalan, K Jayakrishna

and P Venkumar

Supplier Selection in Plastic Products Manufacturing MSMEs

Using a Combined Traditional and Green Criteria Based

on AHP and Fuzzy AHP 593Ashish J Deshmukh and Hari Vasudevan

Green Supply Chain Management Practices and Its Impact

on Business Performance 601Meeta Gandhi and Hari Vasudevan

Part IV Automation

Reliability Assessment of Seals Used in Propulsion Module

of an Autonomous Unmanned Vehicle Using Markov Chains 615Prathamesh Mohite, Elroy Rodrigues and Shivani Vartak

Elitist Non-dominated Sorting Genetic Algorithm-Based Heuristic

for Optimizing Rail Freight Transportation 623Vinay V Panicker, C S Aryadutt and K P Anoop

Vibration Control of 6 Dof Three-Wheeler Using Pid

Controller 631Routh Rajesh and S Srinivasa Rao

Automation of Stone Feeding on T8 Honing Machine 651

S J Patil, A S Suryawanshi, O R Choukar and C R Deokate

Performance Optimization of Bias Bar-Type Brake System

Using Data Acquisition System (DAQ) 661Megh Doshi, Suhrid Subramaniam, Sachin Patel and Meet Shah

Simulation for Variable Transmission Using Mono

Level Genetic Algorithm 669Ritwik Dhar and Niti Doshi

Fuzzy Analytic Hierarchy Process (FAHP) for Green

Supplier Selection in Indian Industries 679Samadhan Deshmukh and Vivek Sunnapwar

Crash Simulation of an Automotive Body to Explore

Performance of Different Metallic Materials Using ANSYS 689

C M Choudhari, Jaineel Desai, Shlok Bhavsar

and Dharmendra Choudhary

Condition Monitoring of Rolling Element Bearing by Acoustic

Analysis Using LabVIEW 697Anish Nadar and Rajanarasimha Sangam

Computational Modeling and Analysis of Artificial Flood

Using Automata 711Nabamita Deb and Ashiya Noorie

Author Index 721

Dr Hari Vasudevan has his master’s degree in duction engineering and postgraduate diploma inindustrial engineering from VJTI (University ofMumbai) and Ph.D from IIT Bombay He has alsodone a 3-month full-time certificate programme(ERP-BaaN) from S.P Jain Institute of Managementand Research, Mumbai, under the University SynergyProgramme of the BaaN Institute, Netherlands Hisareas of interest include manufacturing engineering,manufacturing systems and strategy, market orientation

pro-of manufacturingfirms and world-class manufacturing

He is an approved Ph.D guide at the University ofMumbai and NMIMS (Deemed to be University) andhas so far guided three Ph.D students He is the pres-ident of Indian Society of Manufacturing Engineering(ISME); life member of ISTE, New Delhi; fellow of theInstitution of Engineers (India); fellow of ISME andsenior member of IEDRC He has 26 years of experi-ence in teaching and 2 years of experience in theindustry Presently, he is working as the principal ofDwarkadas J Sanghvi College of Engineering,Mumbai He has published over 82 papers in interna-tional and national conferences and journals

xix

Dr Vijaya Kumar N Kottur heads the Department

of Mechanical Engineering at Dwarkadas J SanghviCollege of Engineering, Mumbai He completed hismaster’s degree in engineering management from SJCEMysore, master’s degree in mechanical engineeringwith machine design as specialisation from SPCEMumbai and Ph.D from the University of Mumbai Hehas 28 years of teaching experience and published 48papers in national and international journals andconferences He is an approved Ph.D guide at theUniversity of Mumbai, Pune University and JJTUUniversity and has so far guided two Ph.D students Heworked as a guest faculty at NITIE Mumbai His areas

of interest are quality engineering, world-class facturing, supply chain management and systemdynamics He is the life member of professional bodieslike ISNDT, IIIE, ISTE and ISME

manu-Dr Amool A Raina currently coordinates and headsthe aerospace programme at the Institut für Textiltechnik(ITA) of RWTH Aachen University His doctoral thesis(highest distinction received) majoring in aerospaceengineering at the University of Kansas presentedsolutions for the improvement in wind turbine designand manufacturing He is considered as an expert in windturbine design and engineering and has a work experi-ence of over 6 years in the aerospace and renewableindustry prior to joining ITA He has designed andengineered over 35 wind turbine blades ranging from 2 to

105 m in length with over 16,000 blades successfullyflying worldwide He has also been involved in projectsrelating to design and optimisation of aircraft enginesand other components He is currently developing andpromoting textile-based solutions for several sectorsincluding aerospace, automotive, traditional textiles anddigital solutions as per Industry 4.0 norms for the aboveindustries Apart from his technical responsibilities, healso heads all affairs and activities pertaining to theEuropean Union and European Space Agency at ITA

Part I

Design

and Optimization of Process Parameters

for Tensile Strength and Nugget

Diameter in Resistance Spot Welding

of HR E-34 Steel Sheet Joint

B S Gawai, R L Karwande, Md Irfan and Prafull S Thakare

Abstract In the present investigation, HR E-34 steel sheets are welded by resistance

spot welding The welding current, welding cycle, and pressure are the principalvariables that are controlled in order to provide the necessary combination of heat andpressure to form the weld The effect of various parameters on weld strength of HotRolled E-34 material is determined by using Minitab 16 software and using design

of experiment Response surface methodology (Box-Behnken Design) is chosen todesign the experiments The highly significant factor was determined by analysis ofvariance In the analysis, it was observed that predicted and experimental results were

in good agreement and the coefficient of determination was found to be 0.967 and0.955 for tensile strength and nugget diameter implies adequacy of derived model.The aim of the research is to find out improvement in welds strength and also reducesvarious welding defects

Keywords Response surface method (RSM)·Tensile strength·Nugget diameterAnalysis of variance (ANOVA)·Resistance spot welding (RSW)

B S Gawai

MSS’S, College of Engineering and Technology, Jalna,

Maharashtra, India

e-mail: bimbisargawai@gmail.com

R L Karwande (B) · Md Irfan · P S Thakare

Department of Mechanical Engineering, MSS’S,

College of Engineering and Technology, Jalna, Maharashtra, India

© Springer Nature Singapore Pte Ltd 2019

H Vasudevan et al (eds.), Proceedings of International Conference on Intelligent

Manufacturing and Automation, Lecture Notes in Mechanical Engineering,

https://doi.org/10.1007/978-981-13-2490-1_1

3

1 Introduction

Resistance welding is one of the oldest of the electric welding processes in use

by industry today Resistance welding is group of welding processes which producecoalescence of metals with the heat obtained from resistance offered by the workpiece

to the flow of electrical current through the parts being joined In this process, heavyelectric current is passed through the metals to be joined This causes local heating toincrease temperature to plastic state over limited area of contact Mechanical pressure

is applied to join them completely No additional filler metal is required The current

is passed through the electrodes which incorporate very low resistance in the circuitand the resistance at the joints of metals is very high Thus, maximum heating isproduced at the point of contact where weld is to be made Resistance welding isuse to weld sheet metals of all engineering metals in Steel cabinets, boxes, cans andfurniture automobile industry, air craft industry, and pipe and tubing production It is

an efficient joining process widely used for the fabrication of sheet metal assemblies

2 Literature Review

The review present in this section is related to mathematical modeling and tion of process parameters of resistance spot welding machine The present literaturereview investigates various techniques and methods for improvement in parameterslike nugget diameter and tensile Strength The survey is given as:

optimiza-Kahraman [1] has carried out outcome of experimental investigations to assessthe performance of commercially pure (CP) titanium sheets (ASTM Grade 2) werewelded by resistance spot welding at different welding parameters and under differentwelding environments Aslanlar [2] has experimentally studied the change in Nucleussize ratio for tensile peel strength and Tensile shear strength were investigate andoptimum welding condition for parameters like weld current and time were find out.Vural et al [3] have aimed to analyze the effect of welding nugget diameter on thefatigue strength of the resistance spot welded joints of different steel sheets Han et al.[4] concluded experimental correlation study of mechanical strength of resistancespot welding of AA5754 aluminium alloy

Hamidinejad et al [5] carried out the modeling and process analysis of resistancespot welding on galvanized steel sheets used in car body manufacturing Zhao et al.[6] investigated and optimized process parameter like welding time, welding current,and electrode force for improvement in failure energy and spot weld quality of spotwelded titanium alloy Mathematical model of input parameter and output parameterwas prepared by using response surface methodology

3.1 Resistance Spot Welding Machine Specifications

75 KVA spot welding machine is employed for experimentation Weld, current, andpressure are used for responses like nugget diameter and strength of weld FollowingFig.1shows setup of resistance spot welding

Fig 1 Resistance spot welding machine setup

3.2 Experimentation

Welding is carried out with resistance spot welding machine with supply 415 V,frequency 50 Hz with water-cooled chromium copper electrodes Specimens areprepared of size 100× 20× 2 mm and trial taken by spot welding process with above-mentioned parameters Later on same specimens are tested for tensile strength onUTM machine

Weld strength Breaking Load/Nugget shearing Area  P/2π Dt where D is Nugget diameter and t Thickness of specimen, P Breaking Load

4 Results and Discussion

4.1 Regression Analysis of Nugget Diameter

The mathematical model depicted by equation x is obtained by performing regression

analysis on generated data during experimentation The regression equation isNugget diameter  2.56 + 0.0075 Weld Cycle + 0.330 Current − 0.390 Pressure

4.2 Model Adequacy Test for Nugget Diameter

(See Tables2and3)

S  0.0983377 R − Sq  95.5% R − Sq(adj)  94.3% R − Sq(pred)  92.98%

Table 2 Pre ANOVA model summary statics of nugget diameter

Table 3 ANOVA model summary statics of nugget diameter

significant Pressure 1 12.82 0.3042 0.3042 31.46 0 More

significant Error 11 4.48 0.10637 0.00967

5.0 4.5

0.1

0.0

-0.1

-0.2

Normal Probability Plot of the Residuals Residuals Versus the Fitted Values

Histogram of the Residuals Residuals Versus the Order of the Data

Residual Plots for Nugget Diameter

Graph 1 Residual plots for nugget diameter

4.2.1 Interpretation of Residual Graph

(See Graph1)

Hold Values Weld cycle 10

Surface Plot of Nugget Diameter Vs Current,Pressure

Pressure

5.0 4.8 4.6 4.4 4.2 4.0

14.7 14.2 13.7 13.2 12.7 12.2

Hold Values Weld cycle 10

Nugget

5.0 - 5.2 5.4 Dia

- 5.6 5.6 - 5.8

> 6.0

< 4.8 4.8 - 5.0

Contour plot of Nugget Diameter Vs Current,Pressure

Fig 2 Surface plot showing effect of current and pressure on nugget diameter

Table 4 Pre ANOVA model

summary statics of tensile

strength

Predictor Coef SE coef T P

Constant 159.63 12.11 13.18 0* Weld cycle 3.9069 0.4421 8.84 0* Current −6.5855 0.5895 −11.17 0* Pressure 19.481 1.769 11.01 0*

*Denotes significant term

4.3 Analysis of Nugget Diameter

The responses can be expressed graphically called surface plot or contour plots.Surface and contour plot can be obtained by taking responses in suitable plane againstvariables Figure2depicts a 3-dimensional surface which shows the effect of currentand weld cycle time on the value of nugget diameter under the pressure 4.5

4.4 Regression Analysis of Tensile Strength

The mathematical model depicted by equation x is obtained by performing

regres-sion analysis on generated data during experimentation The generated regresregres-sionequation for tensile strength is given by

Tensile Strength 160 + 3.91 Weld Cycle − 6.59 Current + 9.5 Pressure

4.5 Model Adequacy Test for Tensile Strength

(See Tables4and5)

Table 5 ANOVA model summary statics of tensile strength

significant Pressure 1 36.20 758.98 758.98 121.33 0 More

Hold Values Current 13.5

Surface Plot of Tensile Strength Vs Weld cycle,Pressure

Pressure

5.0 4.8 4.6 4.4 4.2 4.0

Tensile

190- 200

> strength

210

< 180 180- 190

Contour Plot of Tensile Strength Vs Weld cycle,Pressure

Fig 3 Surface plot and contour plot showing effect of pressure and weld cycle on tensile strength

S  2.50113 R − Sq  96.7% R − Sq(adj)  95.8%

R − Sq(pred)  93.12%

4.6 Analysis of Tensile Strength

(See Figs.3and4)

Weld cycle

Hold Values Pressure 4.5

Surface plot of Tensile Strength Vs Weld cycle,Current

Current

14.7 14.2 13.7 13.2 12.7 12.2

210

< 180 180- 190

Contour Plot of Tensile Strength Vs Weld cycle,Current

Fig 4 Surface plot showing effect of current and weld cycle on tensile strength

15.0 8.0

The feasible solution obtained is accepted for production trial on the resistancespot welding machine Trial done on successive product lot and survey done regardingqualitative issues of weld obtained by resistance spot welding

6 Conclusions

In this Investigation, tensile strength and nugget diameter were optimized in theresistance spot welding process of hot rolled E-34 material The generated empiricalmodels yield to the following conclusions:

(1) The outcomes of analysis of variance and coefficient of determination for nuggetdiameter0.95 and for tensile strength0.96 represent that the fitted regressionmodels moderately determine the responses

(2) Optimum results have been found by using response surface method for tensilestrength and nugget diameter are at weld cycle of 12 cycles, current of 15 KA,and pressure of 5 kg/cm2, so by using this combination of input parameter wecan reduce various types of defects and error produced during resistance spotwelding operation

(3) Rationalization of machining parameters is done for the responses in the tance spot welding machine process of Hot Rolled E-34 material Since by usingproper combinations of input parameter values we can overcome various defects

resis-in weldresis-ing and process is improved

(4) The percentage contribution of weld strength and nugget diameter for weldcurrent, pressure, and weld cycle is found as 37.23, 36.2, 23.29% and 82.62,12.82, 0.08%, respectively

Acknowledgements The authors would like to express their sincere gratitude to Mr Pravin

Dhokane, General Manager, Samarth Engineers Industries, MIDC Waluj, Aurangabad, for ing the necessary permissions to carry out this experimental work in their industry The photograph

provid-in Fig 1 was shot by the author himself with due permissions from Mr Pravin Dhokane.

4 L Han, M Thornton, D Boomer, M Shergoldc, “A Correlation Study of Mechanical Strength

of Resistance Spot Welding Of AA5754 Aluminium Alloy”, Journal of Materials Processing Technology 211 (2011), 513–521.

5 S M Hamidinejad, F Kolahan, A H Kokabi, “ The modeling and process analysis of resistance spot welding on galvanized steel sheets used in car body manufacturing”, Materials and Design

34 (2012), 759–767.

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Aerospike at Mach 6

Rahul S Pawar, N R Gilke and Vivek P Warade

Abstract Hypersonic missiles unite the speed of ballistic missiles together with the

precision and maneuverability of cruise missiles By cruising at hypersonic speed

in the atmosphere, the blunt nose of missile encounters large surface heating and

a great amount of drag This drag force can be reduced by employing a structureknown as aerospike This spike is connected in front of the body that changes theflow field and influences aerodynamic drag at hypersonic speeds In the current paper,

the performance of conical aerospike for various L/D (Length to Diameter) ratios is

examined by using computational fluid dynamics (CFD) approach The CFD analysis

is executed to analyze the effect of drag, lift, and pitching moment coefficient onto theblunt body with and without implementation of an aerospike However, the addition

of a conical aerospike in front of the blunt body has an advantage for the reduction

in drag subjected to the angle of attack, but increase in pitching moment has to betaken into consideration

Keywords Conical aerospike·L/D ratios·Angles of attack

1 Introduction

Vehicles traveling at hypersonic speeds need to be constructed to run at the givenaerodynamic conditions The vehicles like space plane, missiles, launch vehicles, etc.usually have a blunt nose bodies traveling at supersonic and hypersonic speeds Due

to this, a huge amount of aerodynamic drag is levied onto these vehicles, thus leading

to the malfunctioning of the vehicle due to the presence of strong bow shock wave

in the vicinity of the blunt nose This aerodynamic drag, in turn, leads to materialdamage to nose body So, it is worthwhile to have a vehicle with a lesser drag in

R S Pawar (B) · N R Gilke

K J Somaiya College of Engineering, Mumbai 400 077, India

e-mail: pawar.rs@somaiya.edu

V P Warade

Zeus Numerix Pvt Ltd., Pune 411 057, India

© Springer Nature Singapore Pte Ltd 2019

H Vasudevan et al (eds.), Proceedings of International Conference on Intelligent

Manufacturing and Automation, Lecture Notes in Mechanical Engineering,

https://doi.org/10.1007/978-981-13-2490-1_2

15

order to decrease the requirement of thrust from the propulsive system It is reliable

to implement an aerospike for the reduction of the drag, since it alters the strong bowshock wave into weaker conical shock waves and thereby forming a low-pressureregion which shields the blunt body from aerodynamic drag [1] Investigations arestill in process to analyze the effects of an aerospike by varying its shape, size, andblunt nose arrangements

An oblique shock wave is emitted from the front portion of aerospike whichrelocates itself from the blunt nose of the body This occurs due to the shape of theaerospike, thereby generating a recirculation region next at the origin of aerospike

up to the reattachment point at the shoulder of the blunt body [2] If this reattachmentpoint is transferred backward or expelled from the blunt body shoulder, it results inthe reduction of drag [3]

Various investigations are processed till date to improve the utility of an aerospikefor reduction of drag Jackson R Stalder and Helmer V Nielsen executed the exam-

ination with the conical-nosed spikes of semi-apex 10° and L/D ratio of 0.5–2.0

[4] Davis H Crawford reported the flow field over a hemispherical spike whichwas scrutinized at a Mach number of 6.8 and at a Re range (established on flowconditions and the diameter of the model) He also described about the pressure cir-culation in the locality of the blunt body related to the region of separation and theregion of reattachment for shock waves [5] Noboru Motoyama et al explained theeffects related to the spike length, form, and nose arrangement at various angles ofattack for reduction of drag, which was experimentally studied with the employment

of a hypersonic wind tunnel at the Department of Aeronautics and Astronautics,University of Tokyo [3]

R Kalimuthu, et al carried out the results for the spike length, form, and nosearrangement at various angles of attack on account for the reduction of drag Thiswas examined experimentally by use of the hypersonic wind tunnel The effects ofthese parameters onto spike at various angles of incidence onto the aerodynamiccoefficients were inspected using schlieren pictures and measuring aerodynamicforces [2] G d’Humières and J L Stollery enlightened about a simple model builtfor reduction of pressure drag generated at blunt cone and showed good settlementwith experimental data They studied about conical aerospike in their research work[6] M Barzegar Gerdroodbary and S M Hosseinalipour described the differentshapes and lengths employed onto aerospike to inspect the effect of the flow field onthe blunt nose of the body [7]

M Y M Ahmed and N Qin explained that aerospikes were efficient for ing drag and heating onto the blunt nose of the body In their survey, the numericalexamination was directed onto the hemispherical body which was equipped with

minimiz-a conicminimiz-al minimiz-aerospike minimiz-and the hemisphericminimiz-al minimiz-aerodisk of vminimiz-arious sizes in hypersonic

freestream conditions for diverse L/D ratios and angles of incidences [1] M Y M.Ahmed and N Qin in another paper discussed that the aerospike substitutes the bowshock with the organization of conical shocks by creating a zone of recirculation flow

in the front portion of the blunt body, thereby reducing both drag and aeroheating by

performing numerical simulations for various L/D ratios and angles of incidences

[8]

The primary objectives of the current study are to visualize the shock wave

struc-ture around the blunt nose with aerospike and to study the influence of different L/D

ratios as well as angles of attack for aerospike on account of drag reduction Theseobjectives are discussed in the succeeding sections

2 Geometric Modeling and Grid Generation

While executing any CFD simulation, there are many constraints needed to be takeninto account Development of the model is the first stage to be considered In thesecond stage, the mesh is to be generated, which is either structured or unstructuredmesh type In the next stage, the boundary conditions for each surface need to bedefined

To safeguard the accuracy of the solution, an accurate boundary condition setup isimportant The meshing process is completed by exporting the mesh file into solversoftware In solver, the turbulence model and fluid properties need to be carefullypicked out to calculate the fluid behavior in the organization

2.1 Geometry Details

The blunt body diameter (D) is considered to be 0.04 m, length of the body (L0) is considered to be 1.25D, and the Reynolds number is considered as 9.79× 106 [2].Details of blunt geometry and conical aerospike geometry relations are illustrated inFigs.1and2, respectively

The shape of fluid domain is considered as cylindrical in shape and length of the

domain is 17D and diameter is 10D The diameter of the domain is considered long

enough for visualization shock wave phenomenon in front of the body and to reducethe backward flow of the velocity

Fig 1 Blunt body geometry

relations [ 2 ]

Fig 2 Conical aerospike geometry relations [2 ]

Fig 3 Surface mesh of

blunt body

2.2 Mesh Generation

Referable to the presence of complexities in the geometry, the unstructured mesh ischosen But to get the behavior of fluid near the wall, prism-layered mesh is used.Prism-layered mesh has been employed for generating the boundary layer elementsaround the whole body Its primary function is to capture the key variables such aspressure, velocity, or temperature which experiences a quick change in the flow field

Hence, the mesh type generated is hybrid mesh The y+ value for generation of prism

layer is treated as 1 (as required by the turbulence model [7]), along with growthratio of 1.2 and number of layers as 18 Tetrahedral and pyramid meshes are usuallyused for generating nodes and components in the fluid domain The surface meshand volume mesh for the blunt body are as shown in Figs.3and4

Fig 4 Prism layer over the

blunt body

Table 1 Solver parameters

Turbulence model Spalart-Allmaras

2.3 Flow Field Conditions

The computational results are reliant on the boundary conditions imposed The flow

of velocity is taking place in positive X-direction and is flowing through the inletface of the domain, then impinged onto the blunt body or aerospike body, and finallycoming out of the outlet face The boundary conditions required for the current studyare: the inlet face as velocity inlet, the cylindrical face and outlet face as pressure farfield and body along with spike are given as no-slip wall boundary condition Thesolver parameters used for numerical simulations are presented in Table1

3 Grid Independence Test and Validation

After simulations, the solutions obtained are having residuals of order three for mass,momentum, and energy equations Also, the pressure and friction forces acting onthe models were monitored and converged Coefficients of drag, lift, and pitchingmoment are calculated using these equations [9]

Table 2 CFD results of grid independence test

Mesh type Number of

an object (m/s); l is the reference length of model (m); C x and C y are coefficient

of forces along X and Y direction; Cd, Cl, and Cmare coefficients of drag, lift, andpitching moment;α is angle of attack/incidence (in degrees).

3.1 Grid Independence Test

The grid independence test is done to study the consequences of mesh size over thecomputation results obtained The grid independence test is implemented on the samebody, same domain, and same boundary conditions Generally, three different kinds

of mesh are used for studying the grid independence, i.e., coarse, medium, and finemesh The usual CFD practices start with the coarse mesh and gradually refines it tillthe fine mesh by changing the element sizing The size of the mesh is refined untilthe results for coefficient of drag approaches the literature experimental value for thecoefficient of drag This computational study is carried out using CFD Expert-Lite™solver (developed by M/s Zeus Numerix Pvt Ltd.) The CFD simulation results forthree types of mesh are shown in Table2 It can be observed that the obtained value

of the coefficient of drag for the medium and fine mesh is nearly similar So mediummesh is preferred for further analysis If the fine mesh is selected, it will increase thenumber of elements which in turn increases the computational time

Fig 5 Validation of CFD result with experimental result

4 Results and Discussion

4.1 Flow Field Visualization

In this section, the numerical flow pattern is validated with the experimental flowpattern In conical aerospike case, the conical shock wave is generated at the tip

of conical aerospike The conical shock wave produced from aerospike is mainlyreliant on the angle of incidence The blunt body is completely enclosed within thezone of recirculation The phenomenon for the shaping of the shock wave is due

to the geometry of the aerospike, which generates an oblique shock wave at thetip of aerospike and thereby generating a recirculation region in between the origin

of aerospike up to the point of reattachment at the shoulder of the nose of bluntbody Hence, if this reattachment point can be shifted backward or expelled from theshoulder of the nose body, there are chances for the reduction in drag

The contour plots describe for reduction of drag due to increase in the separationregion in front of the conical aerospike The oblique shock wave which is generated

Fig 6 Comparison between

CFD and Experimental

Mach plot

in front of the conical aerospike will reduce the drag Motoyama et al [3] alsoexperimentally witnessed that a conical shock wave is produced due to the conicalaerospike and a large recirculation zone developed at the origin of the aerospike Thecomparison between the CFD and Experimental Mach plot for conical aerospike at

an L/D ratio of 1.5 and zero angle of incidence is illustrated in Fig.6

Surface flow contours for Pressure and Mach number over blunt body and conical

aerospike were obtained for the L/D ratios of 1, 1.5, and 2, at zero angle of incidence

and Mach 6, as illustrated in Figs.7and8 Figure7represents pressure distributionover blunt body and conical aerospike at midplane of body For blunt body, there

is a sudden increase in pressure at stagnant point which affects the velocity of thebody This indicates, there is development of bow shock wave in front of the bluntbody In conical aerospike case, the conical shock wave is generated from the tip ofaerospike The pressure acting onto tip of nose body for conical aerospike is lower ascompared to the pressure acting directly on blunt body due to the presence of conicalshock wave and the recirculation region formed due to the shape of aerospike.Figure8represents Mach contour over blunt body and conical aerospike at mid-plane of body For blunt body, there is formation of bow shock wave due to thepresence of stagnant point in front of the blunt body Whereas in case of conicalaerospike, the oblique shock wave generated due to the shape of aerospike which

shields the nose of body and as L/D ratio increases, the reattachment point is shifted

away from the shoulder of the nose body, thereby reducing drag

Fig 7 Pressure contour for blunt body and Conical aerospike at angle of attack = 0°

Fig 8 Mach contour for blunt body and Conical aerospike at angle of attack = 0°

Fig 9 Comparison between the coefficient of drag versus angles of attack

4.2 Effect of Conical Aerospike on Angle of Attack

A comparative study of drag onto the blunt body and aerospike implemented bodyconfigurations for angles of attack ranging from 0° to 8° can be observed in Fig.9 Animportant inference can be made that the implementation of aerospike is beneficialfor the reduction in drag when the body is subjected to an angle of incidence It isobserved that the implementation of aerospike has a smaller coefficient of drag ascompared to the blunt body This is caused due to the existence of recirculation region

in between the origin of aerospike up to the point of reattachment at the shoulder ofthe nose body As the angle of attack increases, the flow over the aerospike becomesuneven and hence changes the intensity of recirculation region

The coefficient of lift tends to rise as angle of attack increases, as shown in Fig.10.Also, a comparative study is performed on pitching moment coefficient on the bluntbody and aerospike implemented body configurations for angles of incidence rangingfrom 0° to 8° It can be observed from Fig.11that when the blunt body with conicalaerospike is at angle of incidence, it is subjected to large pitching moment raisedfrom the aerospike Hence, as the angle of attack increases, the pitching momentcoefficient further increases It is a vital point to be considered for counterbalancingthe added pitching moment for utilization of the aerospike as the angle of attackincreases [6]