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Modern Materials and Manufacturing Techniques

دانلود کتاب Modern Materials and Manufacturing Techniques

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کتاب مواد مدرن و تکنیک های تولید نسخه زبان اصلی

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توضیحاتی در مورد کتاب Modern Materials and Manufacturing Techniques

نام کتاب : Modern Materials and Manufacturing Techniques
ویرایش : 1
عنوان ترجمه شده به فارسی : مواد مدرن و تکنیک های تولید
سری :
نویسندگان :
ناشر : CRC Press
سال نشر : 2024
تعداد صفحات : 334
ISBN (شابک) : 1032566337 , 9781032566337
زبان کتاب : English
فرمت کتاب : pdf
حجم کتاب : 14 مگابایت



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Cover
Half Title
Title
Copyright
Dedication
Contents
Preface
Acknowledgements
About the editor
List of contributors
1 Green composites for sustainable applications
1.1 Introduction
1.2 Natural polymers and fibres
1.2.1 Natural polymers
1.2.2 Natural fibres
1.3 Comparison with MMCs, CMCs, synthetic NPMCs
1.4 Bio-coatings for the composite
1.5 Biodegradability and environmental aspect
1.6 Developments and applications
1.7 Conclusion
References
2 Metallic functionally graded materials
2.1 Introduction
2.2 Modeling and optimization of FGMs
2.2.1 Microstructurally graded material
2.2.2 Structurally graded material
2.2.3 Compositionally graded material
2.3 Manufacturing techniques of FGM objects
2.3.1 Conventional fabrication processes
2.3.2 Advanced fabrication processes
2.4 Auxiliary aspects of FGM fabrications
2.4.1 Toolpath planning and scanning strategies for advanced fabrication processes
2.4.2 Powder feeding system of PBF-based AM
process
2.4.3 Support structure in AM of FGMs
2.5 Post-processing
2.6 Testing and characterization
2.7 Challenges and future directions
2.7.1 Modeling and design
2.7.2 Alloy incompatibility and insolubility
2.7.3 Process modeling
2.7.4 Advanced characterization
2.8 Summary and concluding remarks
2.8.1 Statements and declarations
2.8.2 Competing interest
2.8.3 Funding
References
3 An overview of power factor correction techniques
3.1 Introduction
3.2 Drawbacks of low power factor
3.3 Low power factor causes
3.4 Importance of increasing power factor
3.5 Power factor correction calculation
3.6 Improving the energy factor techniques
3.7 Static capacitor
3.8 Power factor correction by passive circuit
3.9 Power factor enhancement by active circuit
3.10 Synchronous condensers
3.11 Phase advancers
3.12 Power factor improvement by using active filter
3.13 Power factor improvement by MPPT or DC/DC converter
3.14 Thyristorized automatic power factor improvement unit
3.15 Automatic power factor controller
3.16 Single-phase power factor correction using PSO-based fixed PWM
3.17 Power factor improvement with help of SEPIC DC-DC converter
3.18 The boost power factor correction converter
3.19 PLC-based power factor correction
3.20 Improve power factor through an on-demand tap changer
3.21 Power factor improvement by using dynamic voltage restorer (DVR)
3.22 Power factor improvement by LLC resonant converter
3.23 Latest technology in power factor correction technique is static VAR generators
3.24 Real-time enhancement of reactive power for an intelligent system using a genetic algorithm
3.25 Polymer-based thermoelectric materials used for improving power factor
3.26 Power factor correction’s benefits
3.27 Some energy storage devices
3.28 Works in connection
3.29 Conclusion
References
4 Parametric approach of magnetorheological external finishing tool for its better functionality
4.1 Introduction and background
4.2 Magnetostatic simulation
4.3 Experimental setup and process variables
4.3.1 Workpiece rotational speed (A)
4.3.2 Tool linear speed (B)
4.3.3 Mesh sizes of SiC (C)
4.3.4 Mesh sizes of electrolyte iron powders (D)
4.4 Design of experiments
4.4.1 Regression analysis
4.5 Results and discussion
4.5.1 Effect of workpiece rotational speed (A)
4.5.2 Effect of tool linear speed (B)
4.5.3 Effect of different mesh sizes of SiC (C)
4.5.4 Effect of different mesh sizes of EIPs (D)
4.5.5 Effect of workpiece rotational speed (A) with different mesh sizes of SiC (C)
4.5.6 Effect of workpiece rotational speed (A) with different mesh sizes of EIPs (D)
4.5.7 Effect of tool linear speed (b) with different mesh sizes of SiC (C)
4.5.8 Effect of Tool linear speed (B) with different mesh sizes of EIPs (D)
4.6 Confirmatory experimentation
4.7 Conclusions
References
5 Hybrid energy assisted friction stir welding using secondary heating sources
5.1 Introduction
5.2 Laser-assisted FSW (LaFSW)
5.3 Electrically assisted friction stir welding (EaFSW)
5.4 Induction-assisted friction stir welding (IaFSW)
5.5 Ultrasonic vibration enhanced friction stir welding (UVeFSW)
5.6 Other hybrid assisted friction stir welding processes
5.7 Modelling
5.8 Defects
5.9 Applications
5.10 Conclusion
References
6 An overview of robot assisted additive manufacturing
6.1 Introduction
6.1.1 Additive Manufacturing
6.1.2 Role of robotics in additive manufacturing
6.2 Robotic additive manufacturing: advance processes
6.2.1 Directed energy deposition
6.2.2 Material extrusion
6.2.3 Cold spray additive manufacturing
6.3 Robotic additive manufacturing: advance materials
6.3.1 Carbon fiber-reinforced polymers
6.3.2 Metal matrix composites
6.3.3 Functionally graded materials
6.4 Path-planning strategies in additive manufacturing
6.5 Future perspective of advance robotic systems for additive manufacturing
6.5.1 Collaborative robots
6.5.2 Autonomous robots
6.5.3 Mobile robots
6.6 Conclusions
References
7 A review on fundamentals of cold spray
additive manufacturing
7.1 Introduction
7.2 Bonding mechanism
7.2.1 Adiabatic shear instability
7.2.2 Hydrodynamic plasticity
7.2.3 Rebound phenomenon
7.3 Types of cold spray system
7.3.1 High-pressure cold spray system
7.3.2 Low-pressure cold spray system
7.4 Process parameters
7.4.1 Working gas and process pressure
7.4.2 Temperature
7.4.3 Feed rate, scan speed, spray angle and standoff distance
7.4.4 Powder size and morphology
7.4.5 Substrate
7.5 Nozzle Geometry
7.5.1 Design and mach number
7.5.2 Divergent section
7.6 Post-Processing of CS coatings
7.6.1 Vacuum/inert heat treatment
7.6.2 Friction stir processing
7.6.3 Laser remelting
7.6.4 Shot peening and in situ hammering
7.7 Effect of post-processing on properties of CS coatings
7.7.1 Electrical conductivity
7.7.2 Corrosion resistance
7.7.3 Hardness
7.7.4 Elastic modulus
7.7.5 Fracture
7.8 Summary and scope
References
8 Machine learning and additive manufacturing: a case study for quality control and monitoring
8.1 Introduction
8.2 Machine learning and quality control
8.3 Additive manufacturing in industry 4.0
8.4 Case studies with deep learning
8.4.1 Cold spray
8.4.2 Powder bed fusion
8.4.3 Material extrusion
8.4.4 Binder jetting
8.4.5 Direct energy deposition
8.5 Future scope
8.5.1 Digital twin
8.5.2 Internet of things
8.5.3 Automation
8.6 Conclusion
References
9 An insight into applications of laser in modern era
9.1 Introduction
9.2 Laser in spectroscopy
9.2.1 Laser induced-breakdown spectroscopy
9.2.2 Photoacoustic spectroscopy
9.2.3 Raman spectroscopy
9.3 Laser Sensors
9.3.1 Laser displacement sensor
9.3.2 Time-of-flight sensor
9.3.3 Photoelectric sensor
9.3.4 Laser light grid sensor
9.4 Lasers in the biomedical sector
9.4.1 Laser in dermatology
9.4.2 Laser in ophthalmology
9.4.3 Laser in dentistry
9.5 Lasers in the manufacturing and defence sector
9.5.1 Laser in welding
9.5.2 Laser in forming
9.5.3 Laser in machining
9.5.4 Laser in the defence sector
9.6 Summary
References
10 Utilization of ultrasonic vibration and laser energies during sustainable machining
10.1 Introduction
10.2 Challenges during machining process
10.3 Need for sustainable machining process
10.4 Dry machining
10.5 Minimum quantity lubrication
10.6 Cryogenic machining
10.7 Hybrid machining processes
10.7.1 Thermally assisted machining process
10.7.2 Laser assisted turning process
10.7.3 Ultrasonic vibration assisted turning process
10.7.4 Thermal and ultrasonic vibration assisted turning process
10.8 Summary
References
11 Machining performance and optimization of process parameters of monel alloy 400 using ECM process
11.1 Introduction
11.2 Current status of research
11.3 Experimental methodology
11.4 Results and discussions
11.4.1 Analysis and optimization for MRR, TWR, and SR
11.4.2 Mathematical modelling and regression analysis
11.4.3 Multiresponse optimization
11.5 Conclusions
References
Index




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