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ویرایش: نویسندگان: Ashwani Kumar, Yatika Gori, Nitesh Dutt, Yogesh Kumar Singla, Ambrish Maurya (eds.) سری: Computational Intelligence Techniques ISBN (شابک) : 9781000483024, 1000483029 ناشر: CRC Press سال نشر: 2021 تعداد صفحات: 343 زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 8 مگابایت
در صورت تبدیل فایل کتاب Advanced Computational Methods in Mechanical and Materials Engineering به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب روشهای محاسباتی پیشرفته در مهندسی مکانیک و مواد نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
Cover Half Title Series Page Title Page Copyright Page Dedication Table of Contents Introduction Preface Editors Acknowledgment Contributors Section A: Manufacturing Engineering Chapter 1: Integration of Technologies to Foster Sustainable Manufacturing 1.1 Introduction 1.2 The Key Technologies of Industries 4.0 1.3 Policy Tools and Smart Approach for Industrial Innovation for Sustainable Manufacturing 1.4 China’s Industry 4.0 Approach 1.5 Germany’s Industry 4.0 Approach 1.6 Singapore: Case Study 1.7 Germany’s Case Study 1.8 Smart Automated Guided Vehicles (AGV) – Industry 4.0 1.9 Indonesia’s Case Study 1.10 New Zealand’s Case Study 1.11 Conclusion and Future Scope References Chapter 2: Intelligence-Assisted Cobots in Smart Manufacturing 2.1 Introduction 2.2 Intelligent-Assist Devices (IADs) 2.3 Human–Robot Collaboration (HRC) and its Classification 2.3.1 HRC in Assembly Line 2.3.2 Classification of the HRC System 2.3.3 Human–Robot Collaboration (HRC) in Assembly Lines 2.4 Symbiotic HRC Requirements 2.5 Cobot Deployment Framework in Assembly Lines 2.5.1 Hybrid Production Requirements 2.5.2 Development Phase Analysis 2.5.3 Production Synthesis 2.6 Cobot Selection Parameters 2.7 Industrial Applications 2.8 Safety Measures 2.9 Results 2.10 Conclusion 2.11 Future Scope References Chapter 3: Machine Learning for Friction Stir Welding 3.1 Introduction 3.2 What is the Friction Stir Welding Process? 3.3 Machine Learning in Friction Stir Welding Process 3.3.1 Defects Identification in Friction Stir Welding Process 3.3.2 Application of Machine Learning to Determine the Mechanical Properties of a Friction Stir-Welded Joint 3.3.3 Application of Machine Learning in Microstructure Study of Friction Stir Welded Joint 3.4 Conclusion References Chapter 4: Mathematical and Intelligent Modeling in Tundish Steelmaking 4.1 Introduction 4.2 Constituents of Mathematical Modeling in Tundish 4.2.1 Fluid Flow Modeling 4.2.1.1 Flow Characteristics 4.2.2 Turbulence Flow Modeling 4.2.2.1 Classic k -ε Model 4.2.2.2 k-ω Model 4.2.2.3 LES Model 4.2.3 Inclusion Transport Modeling 4.2.4 Slag Modeling 4.2.5 Argon Gas Modeling 4.3 Intelligent Modeling in Tundish Steelmaking Nomenclatures References Chapter 5: Analysis of Inclusion Behavior In-Mold During Continuous Casting 5.1 Introduction 5.2 Origin of Inclusions 5.3 Mathematical Modeling 5.3.1 Assumptions and Boundary Conditions 5.3.2 Mathematical Model 5.3.2.1 Electromagnetic Field Model 5.3.2.2 Fluid Flow Model 5.3.2.3 Solidification Model 5.4 Inclusion Tracking 5.5 Criteria for Inclusion Removal 5.6 Parameters Affecting Inclusion Capture 5.7 Inclusion Removal Without EMS 5.8 Inclusion Removal with EMS 5.9 Conclusion References Chapter 6: Modeling of Inclusion Motion Under Interfacial Tension in a Flash Welding Process 6.1 Introduction 6.2 Experiments 6.3 Numerical Modeling 6.3.1 The Governing Equations 6.3.2 Numerical Details 6.4 Results and Discussion 6.4.1 Effect of Flash Butt Welding Parameters and Inclusion Size 6.4.2 Pushing and Engulfment of Inclusions 6.5 Conclusions References Section B: Mechanical Design Engineering Chapter 7: A Robust Approach for Roundness Evaluation 7.1 Introduction 7.1.1 Definition of Circularity 7.1.2 Various Approaches in Roundness Evaluation 7.1.3 Various Computational Methods for Evaluation of Circularity 7.2 Scope of the Chapter 7.3 Proposed Hybrid Method 7.4 Results and Discussion 7.5 Summary Acknowledgment References Chapter 8: Computational Techniques for Predicting Process Parameters in the Magnetorheological Fluid-Assisted Finishing Process 8.1 Introduction 8.2 Analytical Analysis 8.2.1 Flow Mode 8.2.1.1 Analysis of Forces 8.2.1.2 Surface Roughness Model 8.2.2 Squeeze Mode 8.2.2.1 Analysis of Forces 8.2.2.2 Surface Roughness Model 8.3 An Overview of Soft Computing Techniques used in the MFAF Process 8.3.1 Neural Network 8.3.2 Genetic Algorithm 8.3.3 Fuzzy Logic 8.3.4 JAYA 8.3.5 Response Surface Methodology (RSM) 8.3.6 Optimization of Process Parameters Affecting Surface Roughness 8.3.6.1 Squeeze Mode 8.3.6.2 Flow Mode 8.4 Conclusions Acknowledgment References Chapter 9: Numerical Analysis of Limited LOCA Event Involving Deflection of Pressure Tube 9.1 Introduction 9.2 Experimental Work on the Pressure Tube Deflection in Limited Core Damage Condition 9.3 Deflection Mechanism and Model 9.3.1 A Non-elastic Material Flow Model 9.4 Numerical Formulation for Limited PT Deformation 9.4.1 Model-1: With Uniformly Distributed Load 9.4.2 Model-2: With Weight Simulators 9.5 Conclusion References Chapter 10: Application of Configurational Force Concept to Calculate the Crack Driving Force in Presence of an Interface at Various Orientations 10.1 Introduction 10.2 Configurational Forces-Based J -integrals 10.3 Material Inhomogeneity: Influence of Change in Material's Property 10.4 Effect of Orientation of Material Inhomogeneity on Crack Driving Force 10.5 Results and Discussions 10.6 Summary and Conclusions References Chapter 11: Thermal Contact Conductance Prediction Using FEM-Based Computational Techniques 11.1 Introduction 11.1.1 Factors Influencing Thermal Contact Conductance 11.1.2 Importance and Applications 11.2 Literature Review 11.3 Challenges and Objective 11.4 Rough Surface Modeling 11.4.1 Choice of Finite Element Program 11.4.2 Parameterization of Generated Surfaces 11.4.3 Meshing 11.4.4 Grid Independency Test 11.5 Analysis 11.5.1 Evaluating Real Contact Area 11.5.2 Estimating Thermal Contact Conductance 11.6 Results and Discussion 11.6.1 Contact Pressure Plots 11.6.2 Roughness Effect 11.6.2.1 Mild Steel Model 11.6.2.2 Aluminum Model 11.6.3 Loading Effect 11.6.3.1 Mild Steel Model 11.6.3.2 Aluminum Model 11.6.4 Material Effect 11.6.5 Thermal Contact Conductance 11.7 Conclusion References Section C: Materials Engineering Chapter 12: Viscoelastic Composites for Passive Damping of Structural Vibration 12.1 Introduction 12.1.1 Unconstrained/Constrained Layer Damping Treatment 12.1.2 Viscoelastic Composites for UCLD/CLD Treatment 12.2 Mathematical Modeling of CLD Treatment 12.3 Finite Element Formulation 12.4 Numerical Results and Discussion 12.4.1 Properties of the Component Materials 12.4.2 Damping Analysis of the Layered Plate 12.5 Summary References Chapter 13: Thermal Buckling and Post-Buckling Behavior of CNT-Reinforced Composite Laminated Plate 13.1 Introduction 13.2 Mathematical Modeling 13.2.1 Mori–Tanaka Scheme and Rule of Mixture 13.2.2 Mathematical Formulation 13.2.3 Displacement Field 13.2.4 Strain-Displacement Relations 13.2.5 Constitutive Stress-Strain Equations 13.2.6 Governing Differential Equations of Motion 13.2.7 Transformation of Governing Differential Equations into Non-dimensional Form 13.2.8 Boundary Conditions 13.3 Methodology of Solution 13.3.1 Spatial Discretization Technique 13.4 Results and Discussion 13.4.1 Convergence Study 13.4.2 Validation Study 13.4.3 Results and Discussions 13.5 Conclusion References Chapter 14: Mesoscale Analysis of Polymer-CNT Composites for Evaluation of Elasto-Plastic and Thermo-Elastic Properties 14.1 Introduction 14.2 Homogenization and FEM Techniques 14.2.1 Mori–Tanaka Method (MTM) for Thermo-Elastic Composites 14.2.2 Mori–Tanaka Method (MTM) for Elastic Composites 14.2.3 Mesoscale Finite Element Method 14.3 Application of Homogenization and FEM Techniques 14.3.1 Application of Mori–Tanaka to Polymer-CNT Composites 14.3.1.1 Effect of Volume Fraction and Orientation of CNTs on the Elastic Properties 14.3.1.2 Effect of Aspect Ratio and Orientation of CNTs on the Elastic Properties 14.3.2 Application of Mori–Tanaka to Polymer-CNT Composites with a Linear-elastic Coating 14.3.2.1 Effect of Volume Fraction and Orientation of CNTs on the Elastic Properties 14.3.2.2 Effect of Aspect Ratio and Orientation of CNTs on the Elastic Properties 14.3.3 Application of Mesoscale FEM to Polymer-CNT Composites with a Linear-elastic Coating 14.4 Summary References Chapter 15: Analysis of Magnetic Abrasive Flow Machining (MAFM) Process Parameters for Internal Finishing of Al/SiC/Al 2 O 3 /REOs Composites Using Box–Behnken Design 15.1 Introduction 15.2 Experimental Details 15.2.1 Preparation of Hybrid Composites and MAFM Setup 15.2.2 Planning for Experiments 15.3 Experimental Results and Discussions 15.3.1 Results of MAFM 15.3.1.1 Analysis of Variance and Mathematical Model for Surface Roughness 15.3.1.2 Effect of Magnetic Flux Density, Number of Cycles and Extrusion Pressure on Surface Roughness 15.3.1.3 Optimization of Surface Roughness Using Desirability Approach 15.3.1.4 Confirmatory Experiments 15.4 Conclusions References Index