Addresses the very topical, crucial and original subject of parameter identification and optimization within multiscale modeling methods
Multiscale Modelling and Optimization of Materials and Structures presents an important and challenging area of research that enables the design of new materials and structures with better quality, strength and performance parameters as well as the creation of reliable models that take into account structural, material and topological properties at different scales. The authors’ approach is four-fold; 1) the basic principles of micro and nano scale modeling techniques; 2) the connection of micro and/or nano scale models with macro simulation software; 3) optimization development in the framework of multiscale engineering and the solution of identification problems; 4) the computer science techniques used in this model and advice for scientists interested in developing their own models and software for multiscale analysis and optimization.
The authors present several approaches such as the bridging and homogenization methods, as well as the general formulation of complex optimization and identification problems in multiscale modelling. They apply global optimization algorithms based on robust bioinspired algorithms, proposing parallel and multi-subpopulation approaches in order to speed-up computations, and discuss several numerical examples of multiscale modeling, optimization and identification of composite and functionally graded engineering materials and bone tissues. Multiscale Modelling and Optimization of Materials and Structures is thereby a valuable source of information for young scientists and students looking to develop their own models, write their own computer programs and implement them into simulation systems.
- Describes micro and nano scale models developed by the authors along with case studies of analysis and optimization
- Discusses the problems of computing costs, efficiency of information transfer, effective use of the computer memory and several other aspects of development of multiscale models
- Includes real physical, chemical and experimental studies with modern experimental techniques
- Provides a valuable source of information for young scientists and students looking to develop their own models, write their own computer programs, and implement them into simulation systems.
Author(s): Tadeusz Burczyński, Maciej Pietrzyk, Wacław Kuś, Łukasz Madej, Adam Mrozek, Łukasz Rauch
Series: Wiley Series in Computational Mechanics
Publisher: Wiley
Year: 2022
Language: English
Pages: 315
City: Hoboken
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
