Multiscale Modelling and Optimisation of Materials and Structures

دانلود کتاب Multiscale Modelling and Optimisation of Materials and Structures

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کتاب مدلسازی چند مقیاسی و بهینه سازی مصالح و سازه ها نسخه زبان اصلی

دانلود کتاب مدلسازی چند مقیاسی و بهینه سازی مصالح و سازه ها بعد از پرداخت مقدور خواهد بود
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توضیحاتی در مورد کتاب Multiscale Modelling and Optimisation of Materials and Structures

نام کتاب : Multiscale Modelling and Optimisation of Materials and Structures
عنوان ترجمه شده به فارسی : مدلسازی چند مقیاسی و بهینه سازی مصالح و سازه ها
سری : Wiley Series in Computational Mechanics
نویسندگان : , , , , ,
ناشر : Wiley
سال نشر : 2022
تعداد صفحات : 317
ISBN (شابک) : 1119975921 , 9781119975922
زبان کتاب : English
فرمت کتاب : pdf
حجم کتاب : 45 مگابایت



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Cover
Title Page
Copyright Page
Contents
Preface
Biography
Chapter 1 Introduction to Multiscale Modelling and Optimization
1.1 Multiscale Modelling
1.1.1 Basic Information on Multiscale Modelling
1.1.2 Review of Problems Connected with Multiscale Modelling Techniques
1.1.3 Prospective Applications of the Multiscale Modelling
1.2 Optimization
1.3 Contents of the Book
References
Chapter 2 Modelling of Phenomena
2.1 Physical Phenomena in Nanoscale
2.1.1 The Linkage Between Quantum and Classical Molecular Mechanics
2.1.2 Atomic Potentials
2.1.2.1 Lennard-Jones Potential
2.1.2.2 Morse Potential
2.1.2.3 Stillinger-Weber Potential
2.1.2.4 Reactive Empirical Bond Order (REBO) Potential
2.1.2.5 Reactive Force Fields (ReaxFF)
2.1.2.6 Murrell-Mottram Potential
2.1.2.7 Embedded Atom Method
2.2 Physical Phenomena in Microscale
2.2.1 Microstructural Aspects of Selection of a Microscale Model
2.2.1.1 Plastometric Tests
2.2.1.2 Inverse Analysis
2.2.2 Flow Stress
2.2.2.1 Procedure to Determine Flow Stress
2.2.2.2 Flow Stress Model
2.2.2.3 Identification of the Flow Stress Model
2.2.3 Recrystallization
2.2.3.1 Static Microstructural Changes
2.2.3.2 Dynamic Softening
2.2.3.3 Grain Growth
2.2.3.4 Effect of Precipitation
2.2.4 Phase Transformations
2.2.4.1 JMAK-Equation-Based Model
2.2.4.2 Differential Equation Model
2.2.4.3 Numerical Solution
2.2.4.4 Additivity Rule
2.2.4.5 Phase Transformation During Heating
2.2.4.6 Identification of the Model
2.2.4.7 Case Studies
2.2.5 Fracture
2.2.5.1 Fundamentals of Fracture Mechanics and Classical Fracture and Failure Hypotheses
2.2.5.2 Empirical Fracture Criteria
2.2.5.3 Fracture Mechanics
2.2.5.4 Continuum Damage Mechanics (CDM)
2.2.6 Creep
2.2.7 Fatigue
References
Chapter 3 Computational Methods
3.1 Computational Methods for Continuum
3.1.1 FEM and XFEM
3.1.1.1 Principles of Computational Modelling Using FEM
3.1.1.2 Principles of Computational Modelling Using FEM
3.1.1.3 Extended Finite Element Method
3.1.2 BEM and FEM/BEM Coupling
3.1.2.1 BEM
3.1.2.2 Coupling FEM and BEM
3.1.3 Computational Homogenization
3.2 Computational Methods for Nano and Micro
3.2.1 Classical Molecular Dynamics
3.2.1.1 Equations of Motion
3.2.1.2 Discretization of Equations of Motion
3.2.1.3 Temperature Controller
3.2.1.4 Evaluation of the Time Step
3.2.1.5 Cutoff Radius and Nearest-Neighbour Lists
3.2.1.6 Boundary Conditions
3.2.1.7 Size of the Atomistic Domain – Limitations of the Molecular Simulations
3.2.2 Molecular Statics
3.2.2.1 Equilibrium of Interatomic Forces
3.2.2.2 Solution of the Molecular Statics Problem
3.2.2.3 Numerical Example of the Molecular Statics
3.2.3 Cellular Automata
3.2.3.1 Cellular Automata Definitions
3.2.4 Monte Carlo Methods
3.3 Methods of Optimization
3.3.1 Optimization Problem Formulation
3.3.2 Methods of Conventional Optimization
3.3.3 Methods of Nonconventional Optimization
3.3.3.1 Evolutionary Algorithm
3.3.3.2 Artificial Immune System
3.3.3.3 Particle Swarm Optimization
3.3.3.4 Hybrid Optimization Algorithms
References
Chapter 4 Preparation of Material Representation
4.1 Generation of Nanostructures
4.1.1 Modelling of Polycrystals and Material Defects
4.1.1.1 Controlled Cooling
4.1.1.2 Adjustable Range of Atomic Interactions
4.1.1.3 Squeezing of the Nanoparticles
4.1.1.4 Modelling of Structures with Voids
4.1.1.5 Material Properties of the Nanostructures
4.1.1.6 Models and Mechanical Properties of 2D Materials with Point Defects
4.2 Microstructure
4.2.1 Generation of Microstructures
4.2.1.1 Voronoi Tessellation
4.2.1.2 Cellular Automata Grain Growth Algorithm
4.2.1.3 Close-Packed Sphere Growth CA-Based Grain Growth Algorithm
4.2.1.4 Monte Carlo Grain Growth Algorithm
4.2.1.5 DigiCore Library
4.2.1.6 Image Processing
4.2.2 Properties of the Microstructure Features
References
Chapter 5 Examples of Multiscale Simulations
5.1 Classification of Multiscale Modelling Methods
5.2 Case Studies
5.2.1 Nano–Micro
5.2.1.1 Multiscale Discrete-Continuum Model
5.2.1.2 Conversion of the Nodal Forces to Tractions
5.2.1.3 Examples of the Nanoscale–Microscale Modelling
5.2.2 Microscale–Macroscale
5.2.2.1 Dynamic Recrystallization
5.2.2.2 Phase Transformation
5.2.2.3 Microshear Bands, Shear Bands, and Strain Localization
References
Chapter 6 Optimization and Identification in Multiscale Modelling
6.1 Multiscale Optimization
6.1.1 Optimization of Atomic Clusters
6.1.1.1 Introduction to Optimization of Atomic Clusters
6.1.1.2 Optimization of Carbon Atomic Clusters
6.1.1.3 New Stable Carbon Networks X and Y
6.1.2 Material, Shape, and Topology Optimization
6.2 Identification in Multiscale Modelling
6.2.1 Material Parameters Identification
6.2.2 Multiscale Identification Problem in Stochastic Conditions
6.2.3 Shape and Topology Identification
6.2.4 Identification of Shape for Multiscale Thermomechanical Problems
References
Chapter 7 Computer Implementation Issues
7.1 Interactions Between the Analysis and Optimization Solutions
7.1.1 Example of Direct Problem Solver File Access
7.1.2 Examples of an Internal Script in Direct Problem Solver
7.2 Visualization of Large Data Sets
7.2.1 Implementation Aspects and Tools
7.2.1.1 Graphical Libraries
7.2.1.2 Software
7.2.1.3 Frameworks
7.2.1.4 Data Storing
7.2.2 High Efficiency of Visualization
7.2.2.1 Dedicated Algorithms
7.2.2.2 Hardware Parallelism
7.2.2.3 Quality Improvement
7.2.2.4 Material Data for Visualization Purposes
7.2.3 Visualization Based on Sectioning
7.2.3.1 Algorithm Idea
7.2.3.2 Background Buffering
7.2.3.3 Preferred Sections
7.2.4 Functional Assumptions
7.2.4.1 Data Preprocessing
7.2.4.2 Visualization
7.2.5 Case Studies
7.2.5.1 Digital Microstructures
7.2.5.2 Performance Tests
References
Chapter 8 Concluding Remarks
Index
EULA




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