دسترسی نامحدود
برای کاربرانی که ثبت نام کرده اند
برای ارتباط با ما می توانید از طریق شماره موبایل زیر از طریق تماس و پیامک با ما در ارتباط باشید
در صورت عدم پاسخ گویی از طریق پیامک با پشتیبان در ارتباط باشید
برای کاربرانی که ثبت نام کرده اند
درصورت عدم همخوانی توضیحات با کتاب
از ساعت 7 صبح تا 10 شب
ویرایش: 1 نویسندگان: Manjaiah M (editor), Shivraman Thapliyal (editor), Adepu Kumar (editor) سری: ISBN (شابک) : 1032356359, 9781032356358 ناشر: CRC Press سال نشر: 2024 تعداد صفحات: 269 زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 17 مگابایت
در صورت تبدیل فایل کتاب Advanced Joining Technologies (Advanced Materials Processing and Manufacturing) 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 فن آوری های پیوستن پیشرفته (فرآوری و ساخت مواد پیشرفته) 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 Table of Contents Preface About the Editors List of Contributors Chapter 1 Underwater Explosive Welding of Tin and Nickel Plates and Characterization of their Interfaces 1.1 Introduction 1.2 Principles of Underwater Explosive Welding 1.3 Design Considerations for Experimentation of Underwater Explosive Welding 1.4 Methodology Adopted to Weld and Characterize Metal Plates 1.5 Discussion on Welded Plates and their Characterization 1.6 Conclusion References Chapter 2 Advances in Gas Tungsten and Gas Metal Arc Welding – A Concise Review 2.1 Introduction 2.2 Advancements in Gas Tungsten Arc Welding 2.2.1 Cold Wire Gas Tungsten Arc Welding Process 2.2.2 Pulsed-Current Gas Tungsten Arc Welding (PCGTAW) 2.2.3 Variable-Polarity GTAW 2.2.4 Ultra High Frequency of Pulsed Gas Tungsten Arc Welding (UHFP-GTAW) 2.2.5 Hot-Wire Gas Tungsten Arc Welding (HW-GTAW) Process 2.2.6 Twin TIG 2.2.7 Keyhole – GTAW Welding 2.2.8 Multicathode GTAW 2.2.9 Active GTAW (A-TIG) 2.2.10 Advanced A-TIG 2.2.11 Flux-Bounded TIG Welding (FBTIG) 2.2.12 Buried Arc GTAW 2.2.13 Ultrasonic GTAW (U-TIG) 2.2.14 TOPTIG 2.2.15 TIPTIG 2.3 Advancements in Gas Metal Arc Welding 2.3.1 Pulsed-Current Gas Metal Arc Welding 2.4 DP-GMAW 2.5 High-Frequency Pulsed Gas Metal Arc Welding 2.6 Ultra-High-Frequency Pulse Metal-Inert Gas Welding (UFP-MIG) 2.6.1 Cold Metal Transfer-GMAW 2.6.2 PCMT-GMAW 2.6.3 CW-GMAW 2.6.4 DCW-GMAW 2.6.5 Hot-Wire GMAW 2.7 Double-Electrode Gas Metal Arc Welding (DE-GMAW) 2.8 Conclusion References Chapter 3 Welding of AISI 304 Steel Using TIG and Pulse TIG: Weld Deposition and Relative Joint Strength Comparisons 3.1 Introduction 3.2 Materials and Methods 3.3 Results and Discussion 3.3.1 Weld Deposition 3.3.2 Relative Joint Strength 3.4 Conclusion References Chapter 4 Processing of Bimetallic Steel–Copper Joint by Beam Welding 4.1 Introduction 4.2 Laser Beam Welding of SS-Copper 4.3 Electron Beam Welding of Steel – Copper 4.4 Conclusion References Chapter 5 Studies on Cold Metal Transfer Welding of Aluminum 5083 Alloy to Pure Titanium 5.1 Introduction 5.2 Experimental Methodology 5.2.1 Materials and Mechanical Characterization 5.2.2 Microstructure Analysis 5.2.3 SEM and EDS Analysis 5.3 Results and Discussion 5.3.1 Ultimate Tensile Strength 5.3.2 Microhardness 5.3.3 SEM and EDS Analysis of the Welded Sample 5.3.4 Fractography 5.4 Conclusion References Chapter 6 Diffusion Bonding for Dissimilar Metals and Alloys 6.1 Introduction 6.2 Diffusion Mechanisms 6.2.1 Vacancy Mechanism 6.2.2 Ring Mechanism 6.2.3 Interstitial Mechanism 6.2.4 Exchange Mechanism 6.3 Process Variables 6.3.1 Bonding Temperature 6.3.2 Bonding Pressure 6.3.3 Bonding Time 6.3.4 Bonding Environment 6.4 Challenges in Joining Dissimilar Metals by Diffusion Bonding 6.4.1 Use of Interlayers in Diffusion Bonding 6.5 Approaches Used to Improve the Effectiveness of Dissimilar Metal Bonding 6.5.1 Diffusion Bonding Using Pressure Pulses 6.5.2 Friction-Assisted Diffusion Bonding 6.5.3 Self-Compressing Diffusion Bonding 6.5.4 Friction Stir Welding-Assisted Diffusion Bonding 6.6 Conclusion References Chapter 7 Friction Stir Welding: A Solution for Dissimilar Material Joining 7.1 Introduction 7.2 Major Parameters 7.2.1 Rotational Speed 7.2.2 Traverse Speed 7.2.3 Dwell Time 7.2.4 Tilt Angle 7.2.5 Advancing Side 7.2.6 Retreating Side 7.2.7 Tool Offset 7.2.8 Shoulder Diameter 7.2.9 Pin Profile 7.2.10 Pitch Ratio 7.3 FSW of Dissimilar Materials 7.3.1 Dissimilar Aluminum Alloys 7.3.2 Aluminum to Non-aluminum Alloys 7.3.3 Aluminum to Non-metals 7.3.4 Miscellaneous 7.4 Major Issues 7.5 Future Scope 7.6 Summary Acknowledgements References Chapter 8 Joining of Metallic Materials Using Microwave Hybrid Heating 8.1 Introduction 8.2 Fundamentals of Microwave Theory 8.2.1 Permittivity and Permeability 8.2.2 Maxwell\'s Equations 8.2.3 Lambert\'s Law 8.3 Heating Mechanisms in Microwave Processing 8.3.1 For Non-magnetic Materials 8.3.2 For Magnetic Materials 8.4 Modes of Heating 8.4.1 Conventional Heating 8.4.2 Microwave Direct Heating (MDH) 8.4.3 Microwave Hybrid Heating (MHH) 8.4.4 Microwave-Selective Heating (MSH) 8.4.5 Selective Microwave Hybrid Heating 8.5 Microwave Joining 8.5.1 Development of Stainless-Steel Joints Using Microwave Hybrid Heating 8.6 Recent Advances in Microwave Processing of Metallic Materials 8.6.1 Microwave Sintering 8.6.2 Microwave Cladding 8.6.3 Microwave Drilling 8.6.4 Microwave Casting 8.6.5 Simulation of Microwave Processing 8.7 Summary 8.8 Future Scope of Microwave Processing 8.8.1 Challenges 8.8.2 Opportunities References Chapter 9 Hybrid Welding Technologies 9.1 Introduction 9.2 Power Source Hybridization 9.2.1 Laser-Arc Hybrid Welding 9.2.2 Laser-FSW Hybrid Welding 9.2.3 Laser-USW Hybrid Welding 9.2.4 Other Hybrid Welding Techniques 9.3 Material Hybridization 9.4 Summary References Chapter 10 Clinching: A Deformation-Based Advanced Joining Technique 10.1 Introduction 10.1.1 Clinching 10.1.2 Types of Clinching 10.2 Variants of Clinching 10.2.1 Flat Clinching 10.2.2 Hole Clinching 10.2.3 Die-less Clinching 10.2.4 Rectangular Clinching 10.2.5 Roller Clinching 10.2.6 Laser Shock Clinching 10.2.7 Hydro Clinching 10.2.8 Injection Clinching 10.2.9 Friction Stir Clinching 10.2.10 Laser-Assisted Clinching 10.2.11 Shear Clinching 10.2.12 Fixed and Extensible Die Clinching 10.2.13 Double-Stroke Clinching 10.3 Clinching-Based Hybrid Joining 10.3.1 Clinch Bonding 10.3.2 Resistance Spot Clinching (RSC) 10.4 Factors Affecting Clinched Joint Formation 10.5 Mechanical and Metallurgical Characteristics of Clinched Joints 10.6 Failure Modes of Clinched Joint 10.7 Numerical Modeling of the Clinching Technique 10.7.1 Modeling 10.7.2 Meshing 10.7.3 Remeshing Method 10.7.4 Contact Modeling 10.8 Conclusion and Future Scope References Chapter 11 Systematic Study of Digital Twins for Welding Processes 11.1 Introduction 11.2 Literature Review 11.2.1 Welding Process 11.2.2 Digital Twin 11.3 Digital Twin in Welding 11.3.1 Weld Joint Expansion and Penetration Regulation of Gas Tungsten Arc Welding Process Using a Digital Twin 11.3.2 Digital Twin-Based Process Monitoring in Laser-Welded Blanks of Light Metal Blanks 11.3.3 Sequence Optimization of Spot Welding for Geometry Assurance Digital Twin 11.3.4 Digital Twin-Based Simulation and Optimization of Robotic Arc Welding Station 11.4 Conclusion References Chapter 12 Application of Machine Learning Techniques for Fault Detection in Friction Stir-Based Advanced Joining Techniques 12.1 Introduction 12.2 Artificial Intelligence in FSW and FSP 12.3 Fault Detection Approach in FSW or FSP Using Artificial Intelligence 12.3.1 Digital Twin Modeling of FSW Process 12.3.2 Surface Defect Detection in FSW Joints Using a Machine Learning Approach 12.3.3 Artificial Intelligence for Detecting Surface Defects in Friction Stir-Welded Joints 12.4 Summary References Chapter 13 Friction Stir Welding Characteristics of Dissimilar/Similar Ti-6Al-4V-Based Alloy and its Machine Learning Techniques 13.1 Introduction 13.2 Friction Stir Welding 13.3 Conventional Optimization Techniques 13.4 Machine Learning 13.5 Advantages of Machine Learning in FSW 13.6 Conclusion References Index