Muutke küpsiste eelistusi

E-raamat: Multiscale Analysis of Deformation and Failure of Materials [Wiley Online]

(Alfred University)
Teised raamatud teemal:
  • Wiley Online
  • Hind: 153,31 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
Multiscale Analysis of Deformation and Failure of MaterialsSuurem pilt
Teised raamatud teemal:
Wiley Online e-raamatudRohkem infot Wiley Online kohta
Raamatu kodulehekülg: https://onlinelibrary.wiley.com/doi/book/10.1002/9780470972281
Presenting cutting-edge research and development within multiscale modeling techniques and frameworks, Multiscale Analysis of Deformation and Failure of Materials systematically describes the background, principles and methods within this exciting new & interdisciplinary field. The author’s approach emphasizes the principles and methods of atomistic simulation and its transition to the nano and sub-micron scale of a continuum, which is technically important for nanotechnology and biotechnology. He also pays close attention to multiscale analysis across the micro/meso/macroscopy of a continuum, which has a broad scope of applications encompassing different disciplines and practices, and is an essential extension of mesomechanics. Of equal interest to engineers, scientists, academics and students, Multiscale Analysis of Deformation and Failure of Materials is a multidisciplinary text relevant to those working in the areas of materials science, solid and computational mechanics, bioengineering and biomaterials, and aerospace, automotive, civil, and environmental engineering.   Provides a deep understanding of multiscale analysis and its implementation Shows in detail how multiscale models can be developed from practical problems and how to use the multiscale methods and software to carry out simulations Discusses two interlinked categories of multiscale analysis; analysis spanning from the atomistic to the micro-continuum scales, and analysis across the micro/meso/macro scale of continuum.
About the Author xxi
Series Preface xxiii
Preface xxv
Abbreviations xxvii
1 Introduction
1(14)
1.1 Material Properties Based on Hierarchy of Material Structure
1(3)
1.1.1 Property-structure Relationship at Fundamental Scale
1(1)
1.1.2 Property-structure Relationship at Different Scales
2(1)
1.1.3 Upgrading Products Based on Material Structure-property Relationships
2(1)
1.1.4 Exploration of In-depth Mechanisms for Deformation and Failure by Multiscale Modeling and Simulation
3(1)
1.2 Overview of Multiscale Analysis
4(2)
1.2.1 Objectives, Contents and Significance of Multiscale Analysis
4(1)
1.2.2 Classification Based on Multiscale Modeling Schemes
4(1)
1.2.3 Classification Based on the Linkage Feature at the Interface Between Different Scales
5(1)
1.3 Framework of Multiscale Analysis Covering a Large Range of Spatial Scales
6(1)
1.3.1 Two Classes of Spatial Multiscale Analysis
6(1)
1.3.2 Links Between the Two Classes of Multiscale Analysis
6(1)
1.3.3 Different Characteristics of Two Classes of Multiscale Analysis
7(1)
1.3.4 Minimum Size of Continuum
7(1)
1.4 Examples in Formulating Multiscale Models from Practice
7(5)
1.4.1 Cyclic Creep (Ratcheting) Analysis of Pearlitic Steel Across Micro/meso/macroscopic Scales
8(2)
1.4.2 Multiscale Analysis for Brittle-ductile Transition of Material Failure
10(2)
1.5 Concluding Remarks
12(1)
References
13(2)
2 Basics of Atomistic Simulation
15(38)
2.1 The Role of Atomistic Simulation
15(4)
2.1.1 Characteristics, History and Trends
15(1)
2.1.2 Application Areas of Atomistic Simulation
16(1)
2.1.3 An Outline of Atomistic Simulation Process
17(2)
2.1.4 An Expression of Atomistic System
19(1)
2.2 Interatomic Force and Potential Function
19(2)
2.2.1 The Relation Between Interatomic Force and Potential Function
19(1)
2.2.2 Physical Background and Classifications of Potential Functions
20(1)
2.3 Pair Potential
21(6)
2.3.1 Lennard-Jones (LJ) Potential
22(1)
2.3.2 The 6-12 Pair Potential
23(1)
2.3.3 Morse Potential
24(1)
2.3.4 Units for Atomistic Analysis and Atomic Units (au)
25(2)
2.4 Numerical Algorithms for Integration and Error Estimation
27(4)
2.4.1 Motion Equation of Particles
27(2)
2.4.2 Verlet Numerical Algorithm
29(1)
2.4.3 Velocity Verlet (VV) Algorithm
30(1)
2.4.4 Other Algorithms
31(1)
2.5 Geometric Model Development of Atomistic System
31(4)
2.6 Boundary Conditions
35(2)
2.6.1 Periodic Boundary Conditions (PBC)
35(1)
2.6.2 Non-PBC and Mixed Boundary Conditions
36(1)
2.7 Statistical Ensembles
37(2)
2.7.1 Nve Ensemble
37(1)
2.7.2 Nvt Ensemble
37(1)
2.7.3 Npt Ensemble
38(1)
2.8 Energy Minimization for Preprocessing and Statistical Mechanics Data Analyses
39(1)
2.8.1 Energy Minimization
39(1)
2.8.2 Data Analysis Based on Statistical Mechanics
39(1)
2.9 Statistical Simulation Using Monte Carlo Methods
40(10)
2.9.1 Introduction of Statistical Method
41(1)
2.9.2 Metropolis-Hastings Algorithm for Statics Problem
42(1)
2.9.3 Dynamical Monte Carlo Simulations
43(1)
2.9.4 Adsorption-desorption Equilibrium
43(7)
2.10 Concluding Remarks
50(1)
References
51(2)
3 Applications of Atomistic Simulation in Ceramics and Metals
53(52)
Part 3.1 Applications in Ceramics and Materials with Ionic and Covalent Bonds
53(1)
3.1 Covalent and Ionic Potentials and Atomistic Simulation for Ceramics
53(2)
3.1.1 Applications of High-performance Ceramics
53(1)
3.1.2 Ceramic Atomic Bonds in Terms of Electronegativity
54(1)
3.2 Born Solid Model for Ionic-bonding Materials
55(1)
3.2.1 Born Model
55(1)
3.2.2 Born-Mayer and Buckingham Potentials
55(1)
3.3 Shell Model
56(2)
3.4 Determination of Parameters of Short-distance Potential for Oxides
58(3)
3.4.1 Basic Assumptions
58(1)
3.4.2 General Methods in Determining Potential Parameters
59(1)
3.4.3 Three Basic Methods for Potential Parameter Determination by Experiments
60(1)
3.5 Applications in Ceramics: Defect Structure in Scandium Doped Ceria Using Static Lattice Calculation
61(3)
3.6 Applications in Ceramics: Combined Study of Atomistic Simulation with XRD for Nonstoichiometry Mechanisms in Y3A15O12 (YAG) Garnets
64(4)
3.6.1 Background
64(1)
3.6.2 Structure and Defect Mechanisms of YAG Garnets
65(1)
3.6.3 Simulation Method and Results
66(2)
3.7 Applications in Ceramics: Conductivity of the YSZ Oxide Fuel Electrolyte and Domain Switching of Ferroelectric Ceramics Using MD
68(3)
3.7.1 MD Simulation of the Motion of Oxygen Ions in SOFC
68(3)
3.8 Tersoff and Brenner Potentials for Covalent Materials
71(4)
3.8.1 Introduction of the Abell-Tersoff Bonder-order Approach
71(1)
3.8.2 Tersoff and Brenner Potential
72(3)
3.9 The Atomistic Stress and Atomistic-based Stress Measure
75(4)
3.9.1 The Virial Stress Measure
76(1)
3.9.2 The Computation Form for the Virial Stress
76(2)
3.9.3 The Atomistic-based Stress Measure for Continuum
78(1)
Part 3.2 Applications in Metallic Materials and Alloys
79(1)
3.10 Metallic Potentials and Atomistic Simulation for Metals
79(1)
3.11 Embedded Atom Methods EAM and MEAM
79(8)
3.11.1 Basic EAM Formulation
79(2)
3.11.2 EAM Physical Background
81(1)
3.11.3 EAM Application for Hydrogen Embrittlement
82(1)
3.11.4 Modified Embedded Atom Method (MEAM)
83(2)
3.11.5 Summary and Discussions
85(2)
3.12 Constructing Binary and High Order Potentials from Monoatomic Potentials
87(3)
3.12.1 Determination of Parameters in LJ Pair Function for Unlike Atoms by Lorentz-Berthelet Mixing Rule
88(1)
3.12.2 Determination of Parameters in Morse and Exponential Potentials for Unlike Atoms
88(1)
3.12.3 Determination of Parameters in EAM Potentials for Alloys
89(1)
3.12.4 Determination of Parameters in MEAM Potentials for Alloys
90(1)
3.13 Application Examples of Metals: MD Simulation Reveals Yield Mechanism of Metallic Nanowires
90(2)
3.14 Collecting Data of Atomistic Potentials from the Internet Based on a Specific Technical Requirement
92(4)
3.14.1 Background About Galvanic Corrosion of Magnesium and Nano-Ceramics Coating on Steel
93(1)
3.14.2 Physical and Chemical Vapor Deposition to Produce Ceramics Thin Coating Layers on Steel Substrate
93(1)
3.14.3 Technical Requirement for Potentials and Searching Results
94(1)
3.14.4 Using Obtained Data for Potential Development and Atomistic Simulation
95(1)
Appendix 3 A Potential Tables for Oxides and Thin-Film Coating Layers
96(5)
References
101(4)
4 Quantum Mechanics and Its Energy Linkage with Atomistic Analysis
105(28)
4.1 Determination of Uranium Dioxide Atomistic Potential and the Significance of QM
105(1)
4.2 Some Basic Concepts of QM
106(1)
4.3 Postulates of QM
107(6)
4.4 The Steady State Schrodinger Equation of a Single Particle
113(1)
4.5 Example Solution: Square Potential Well with Infinite Depth
114(2)
4.5.1 Observations and Discussions
115(1)
4.6 Schrodinger Equation of Multi-body Systems and Characteristics of its Eigenvalues and Ground State Energy
116(3)
4.6.1 General Expression of the Schrodinger Equation and Expectation Value of Multi-body Systems
116(1)
4.6.2 Example: Schrodinger Equation for Hydrogen Atom Systems
117(1)
4.6.3 Variation Principle to Determine Approximate Ground State Energy
118(1)
4.7 Three Basic Solution Methods for Multi-body Problems in QM
119(2)
4.7.1 First-principle or ab initio Methods
120(1)
4.7.2 An Approximate Method
120(1)
4.8 Tight Binding Method
121(2)
4.9 Hartree-Fock (HF) Methods
123(2)
4.9.1 Hartree Method for a Multi-body Problem
123(1)
4.9.2 Hartree-Fock (HF) Method for the Multi-body Problem
124(1)
4.10 Electronic Density Functional Theory (DFT)
125(2)
4.11 Brief Introduction on Developing Interatomic Potentials by DFT Calculations
127(3)
4.11.1 Energy Linkage Between QM and Atomistic Simulation
127(1)
4.11.2 More Information about Basis Set and Plane-wave Pseudopotential Method for Determining Atomistic Potential
128(1)
4.11.3 Using Spline Functions to Express Potential Energy Functions
128(1)
4.11.4 A Systematic Method to Determine Potential Functions by First-principle Calculations and Experimental Data
129(1)
4.12 Concluding Remarks
130(1)
Appendix 4 A Solution to Isolated Hydrogen Atom
131(1)
References
132(1)
5 Concurrent Multiscale Analysis by Generalized Particle Dynamics Methods
133(34)
5.1 Introduction
133(2)
5.1.1 Existing Needs for Concurrent Multiscale Modeling
134(1)
5.1.2 Expanding Model Size by Concurrent Multiscale Methods
134(1)
5.1.3 Applications to Nanotechnology and Biotechnology
134(1)
5.1.4 Plan for Study of Concurrent Multiscale Methods
134(1)
5.2 The Geometric Model of the GP Method
135(3)
5.3 Developing Natural Boundaries Between Domains of Different Scales
138(3)
5.3.1 Two Imaginary Domains Next to the Scale Boundary
138(1)
5.3.2 Neighbor-link Cells (NLC) of Imaginary Particles
139(1)
5.3.3 Mechanisms for Seamless Transition
139(1)
5.3.4 Linkage of Position Vectors at Different Scales by Spatial and Temporal Averaging
140(1)
5.3.5 Discussions
141(1)
5.4 Verification of Seamless Transition via ID Model
141(5)
5.5 An Inverse Mapping Method for Dynamics Analysis of Generalized Particles
146(4)
5.6 Applications of GP Method
150(1)
5.7 Validation by Comparison of Dislocation Initiation and Evolution Predicted by MD and GP
151(4)
5.8 Validation by Comparison of Slip Patterns Predicted by MD and GP
155(1)
5.9 Summary and Discussions
156(3)
5.10 States of Art of Concurrent Multiscale Analysis
159(5)
5.10.1 MAAD Concurrent Multiscale Method
159(1)
5.10.2 Incompatibility Problems at Scale Boundary Illustrated with the MAAD Method
160(1)
5.10.3 Quasicontinuum (QC) Method
161(1)
5.10.4 Coupling Atomistic Analysis with Discrete Dislocation (CADD) Method
161(1)
5.10.5 Existing Efforts to Eliminate Artificial Phenomena at the Boundary
162(1)
5.10.6 Embedded Statistical Coupling Method (ESCM) with Comments on Direct Coupling (DC) Methods
162(1)
5.10.7 Conclusion
163(1)
5.11 Concluding Remarks
164(1)
References
164(3)
6 Quasicontinuum Concurrent and Semi-analytical Hierarchical Multiscale Methods Across Atoms/Continuum
167(60)
6.1 Introduction
167(1)
Part 6.1 Basic Energy Principle and Numerical Solution Techniques in Solid Mechanics
168(1)
6.2 Principle of Minimum Potential Energy of Solids and Structures
168(2)
6.2.1 Strain Energy Density
169(1)
6.2.2 Work Potential
169(1)
6.3 Essential Points of Finite Element Methods
170(8)
6.3.1 Discretization of Continuum Domain BC into Finite Elements
170(1)
6.3.2 Using Gaussian Quadrature to Calculate Element Energy
171(1)
6.3.3 Work Potential Expressed by Node Displacement Matrix
172(1)
6.3.4 Total Potential Energy II Expressed by Node Displacement Matrix
173(2)
6.3.5 Developing Simultaneous Algebraic Equations for Nodal Displacement Matrix
175(3)
Part 6.2 Quasicontinuum (QC) Concurrent Method of Multiscale Analysis
178(1)
6.4 The Idea and Features of the QC Method
178(9)
6.4.1 Formulation of Representative Atoms and Total Potential Energy in the QC Method
178(1)
6.4.2 Using Interpolation Functions to Reduce Degrees of Freedom
179(1)
6.4.2 Model Division
180(1)
6.4.4 Using the Cauchy-Born Rule to Calculate Energy Density Function W from Interatomic Potential Energy
181(2)
6.4.5 The Solution Scheme of the QC Method
183(1)
6.4.6 Subroutine to Determine Energy Density W for Each Element
184(1)
6.4.7 Treatment of the Interface
184(1)
6.4.8 Ghost Force
184(3)
6.5 Fully Non-localized QC Method
187(1)
6.5.1 Energy-based Non-local QC Model (CQC(m)-E)
187(1)
6.5.2 Dead Ghost Force Correction in Energy-based Non-local QC
188(1)
6.6 Applications of the QC Method
188(5)
6.6.1 Nanoindentation
189(1)
6.6.2 Crack-tip Deformation
190(2)
6.6.3 Deformation and Fracture of Grain Boundaries
192(1)
6.6.4 Dislocation Interactions
192(1)
6.6.5 Polarizations Switching in Ferroelectrics
192(1)
6.7 Short Discussion about the QC Method
193(1)
Part 6.3 Analytical and Semi-analytical Multiscale Methods Across Atomic/Continuum Scales
194(1)
6.8 More Discussions about Deformation Gradient and the Cauchy-Born Rule
195(6)
6.8.1 Mathematical Definition of Deformation Gradient F(X)
195(1)
6.8.2 Determination of Lattice Vectors and Atom Positions by the Cauchy-Born Rule through Deformation Gradient F(X)
196(1)
6.8.3 Physical Explanations of Components of Deformation Gradient F
197(1)
6.8.4 Expressions of F and Components in Terms of Displacement Vector
198(2)
6.8.5 The Relationship Between Deformation Gradient, Strain and Stress Tensors
200(1)
6.9 Analytical/Semi-analytical Methods Across Atom/Continuum Scales Based on the Cauchy-Born Rule
201(4)
6.9.1 Application of the Cauchy-Born Rule in a Centro-symmetric Structure
201(1)
6.9.2 Determination of Interatomic Length rij and Angle 0ijk of the Crystal after Deformation by the Cauchy-Born Rule
202(2)
6.9.3 A Short Discussion on the Precision of the Cauchy-Born Rule
204(1)
6.10 Atomistic-based Continuum Model of Hydrogen Storage with Carbon Nanotubes
205(13)
6.10.1 Introduction of Technical Background and Three Types of Nanotubes
205(1)
6.10.2 Interatomic Potentials Used for Atom/Continuum Transition
205(1)
6.10.3 The Atomistic-based Continuum Theory of Hydrogen Storage
206(5)
6.10.4 Atomistic-based Continuum Modeling to Determine the Hydrogen Density and Pressure
211(1)
6.10.5 Continuum Model of Interactions Between the CNT and Hydrogen Molecules and Concentration of Hydrogen
212(4)
6.10.6 Analytical Solution for the Concentration of Hydrogen Molecules
216(1)
6.10.7 The Double Wall Effects on Hydrogen Storage
217(1)
6.11 Atomistic-based Model for Mechanical, Electrical and Thermal Properties Of Nanotubes
218(4)
6.11.1 Highlights of the Methods
219(1)
6.11.2 Mechanical Properties
219(1)
6.11.3 Electrical Property Change in Deformable Conductors
220(1)
6.11.4 Thermal Properties
221(1)
6.11.5 Other Work in Atomistic-based Continuum Model
222(1)
6.12 A Proof of 3D Inverse Mapping Rule of the GP Method
222(1)
6.13 Concluding Remarks
223(1)
References
223(4)
7 Further Introduction to Concurrent Multiscale Methods
227(34)
7.1 General Feature in Geometry of Concurrent Multiscale Modeling
227(2)
7.1.1 Interface Design of the DC Multiscale Models
227(1)
7.1.2 Connection and Compatibility Between Atom/Continuum at the Interface
228(1)
7.2 Physical Features of Concurrent Multiscale Models
229(2)
7.2.1 Energy-based and Force-based Formulation
229(1)
7.2.2 Constitutive Laws in the Formulation
230(1)
7.3 MAAD Method for Analysis Across ab initio, Atomic and Macroscopic Scales
231(4)
7.3.1 Partitioning and Coupling of Model Region
231(2)
7.3.2 System Energy and Hamiltonian in Different Regions
233(1)
7.3.3 Handshake Region Design
234(1)
7.3.4 Short Discussion on the MAAD Method
235(1)
7.4 Force-based Formulation of Concurrent Multiscale Modeling
235(1)
7.5 Coupled Atom Discrete Dislocation Dynamics (CADD) Multiscale Method
236(4)
7.5.1 Realization of Force-based Formulation for CADD/FEAt
236(1)
7.5.2 Basic Model for CADD
237(1)
7.5.3 Solution Scheme: A Superposition of Three Types of Boundary Value Problems
238(2)
7.6 ID Model for a Multiscale Dynamic Analysis
240(6)
7.6.1 The Internal Force and Equivalent Mass of a Dynamic System
240(2)
7.6.2 Derivation of the FE/MD Coupled Motion Equation
242(2)
7.6.3 Numerical Example of the Coupling Between MD and FE
244(1)
7.6.4 Results and Discussion
245(1)
7.7 Bridging Domains Method
246(2)
7.8 ID Benchmark Tests of Interface Compatibility for DC Methods
248(3)
7.9 Systematic Performance Benchmark of Most DC Atomistic/Continuum Coupling Methods
251(3)
7.9.1 The Benchmark Computation Test
251(3)
7.9.2 Summary and Conclusion of the Benchmark Test
254(1)
7.10 The Embedded Statistical Coupling Method (ESCM)
254(4)
7.10.1 Why Does ESCM Use Statistical Averaging to Replace DCs Direct Linkage?
255(1)
7.10.2 The ESCM Model
255(1)
7.10.3 MD/FE Interface
255(2)
7.10.4 Surface MD Region
257(1)
7.10.5 Validation
258(1)
References
258(3)
8 Hierarchical Multiscale Methods for Plasticity
261(38)
8.1 A Methodology of Hierarchical Multiscale Analysis Across Micro/meso/macroscopic Scales and Information Transformation Between These Scales
261(2)
8.1.1 Schematic View of Hierarchical Multiscale Analysis
261(2)
8.1.2 Using Two-face Feature of Meso-cell to Link Both Microscopic and Macroscopic Scales
263(1)
8.2 Quantitative Meso-macro Bridging Based on Self-consistent Schemes
263(4)
8.2.1 Basic Assumption
263(1)
8.2.2 Introduction to Self-consistent Schemes (SCS)
264(1)
8.2.3 Weakening Constraint Effect of Aggregate on Inclusion with Increase of Plastic Deformation
265(1)
8.2.4 Quantitative Linkage of Variables Between Mesoscopic and Macroscopic Scales
266(1)
8.3 Basics of Continuum Plasticity Theory
267(3)
8.3.1 Several Basic Elements of Continuum Plasticity Theory
267(1)
8.3.2 Description of Continuum Plasticity Theory Within Deviatoric Stress Space
268(2)
8.4 Internal Variable Theory, Back Stress and Elastoplastic Constitutive Equations
270(4)
8.4.1 Internal Variable Theory Expressed by a Mechanical Model
270(2)
8.4.2 Calculation of Back Stress Rij in Terms of Plastic Strain
272(1)
8.4.3 Expressing Elastoplastic Constitutive Equations for Each Constituent Phase
273(1)
8.5 Quantitative Micro-meso Bridging by Developing Meso-cell Constitutive Equations Based on Microscopic Analysis
274(2)
8.5.1 Developing Meso-cell (Inclusion) Constitutive Equations
274(1)
8.5.2 Bridging Micro and Macroscopic Variables via the Meso-cell Constitutive Equation
275(1)
8.5.3 Solution Technique
276(1)
8.6 Determining Size Effect on Yield Stress and Kinematic Hardening Through Dislocation Analysis
276(5)
8.6.1 Basic Idea to Introduce Size Effects in Plasticity
277(1)
8.6.2 Expressing Size Effects on Yielding and Hardening Behavior by Dislocation Pile-up Theory
277(2)
8.6.3 Tangential Modulus and Hardening Behavior Under Shear Force by Continuum Plasticity Theory
279(1)
8.6.4 Equating Dislocation-obtained Shear Stress Increment with that Obtained by Continuum Plasticity Theory
279(1)
8.6.5 Explicit Expressions of Size Effects on Tangential Modulus and Kinematic Hardening Behavior
280(1)
8.7 Numerical Methods to Link Plastic Strains at the Mesoscopic and Macroscopic Scales
281(2)
8.7.1 Bridging Plastic Variables at Different Scales from Bottom-up and Top-down to Complete the Iterative Process
281(1)
8.7.2 Numerical Procedure for the Iterative Process
281(1)
8.7.3 How to Carrying on the Volume Averaging of Meso-cell Plastic Strain to Find Macroscopic Strain
282(1)
8.8 Experimental Study on Layer-thickness Effects on Cyclic Creep (Ratcheting)
283(1)
8.9 Numerical Results and Comparison Between Experiments and Multiscale Simulation
284(4)
8.9.1 General Features of the Numerical Simulation
284(1)
8.9.2 Determination of Basic Material Parameters
285(1)
8.9.3 Determining Size Effects on Material Parameters by Size Laws
286(1)
8.9.4 Comparison Between the Results of Three-scale Multiscale Simulation with Data of Cyclic Experiments
286(2)
8.10 Findings in Microscopic Scale by Multiscale Analysis
288(3)
8.11 Summary and Conclusions
291(2)
8.11.1 Methods for Bridging Three Scales
291(1)
8.11.2 Methods in Bridging Atomistic Dislocation Analysis and the Second Class of Multiscale Analysis
292(1)
8.11.3 Size Effects on Yield Stress and Kinematic Hardening of Plasticity
292(1)
8.11.4 Experimental Validation for the Size Effects on Ratcheting
292(1)
8.11.5 Failure Mechanisms of Thicker Layer
292(1)
8.11.6 The Formulation and Important Role of Residual Stress
292(1)
8.11.7 Wide Scope of Applications of the Proposed Multiscale Methodology
293(1)
Appendix
8. A Constitutive Equations and Expressions of Parameters
293(2)
Appendix 8.B Derivation of Equation (8.12e) and Matrix Elements
295(2)
References
297(2)
9 Topics in Materials Design, Temporal Multiscale Problems and Bio-materials
299(44)
Part 9.1 Materials Design
299(1)
9.1 Multiscale Modeling in Materials Design
299(2)
9.1.1 The Role of Multiscale Analysis in Materials Design
299(1)
9.1.2 Issues of Bottom-up Multiscale Modeling in Deductive Material Design Process
300(1)
9.1.3 Choices of Multiscale Methods in Materials Design
301(1)
Part 9.2 Temporal Multiscale Problems
301(1)
9.2 Introduction to Temporal Multiscale Problems
301(3)
9.2.1 Material Behavior Versus Time Scales
302(1)
9.2.2 Brief Introduction to Methods for Temporal Multiscale Problems
302(2)
9.3 Concepts of Infrequent Events
304(1)
9.4 Minimum Energy Path (MEP) and Transition State Theory in Atomistic Simulation
305(13)
9.4.1 Minimum Energy Path (MEP) and Saddle Point
305(1)
9.4.2 Nudged Elastic Band (NEB) Method for Finding MEP and Saddle Point
306(4)
9.4.3 Mathematical Description of the NEB Method
310(1)
9.4.4 Finding MEP and Saddle Point for a 2D Test Problem of LEPS Potential via Implementation of the NEB Method
311(7)
9.5 Applications and Impacts of NEB Methods
318(6)
9.5.1 Governing Equations and Methods for Considering Strain Rate and Temperature Effects on Dislocation Nucleation
318(1)
9.5.2 Examples and Impact (1): Strain Rate and Temperature Effects on Dislocation Nucleation from Free Surface of Nanowires
318(2)
9.5.3 Examples and Impact (2): Departure Between Plasticity and Creep Based on Activation Energy and Activation Volume
320(1)
9.5.4 Examples and Impact (3): Findings for Mechanisms of High Strength and High Ductility of Twin Nanostructured Metals
321(1)
9.5.5 Other Methods in Extending Time Scale in Atomistic Analysis
322(2)
Part 9.3 Multiscale Analysis of Protein Materials and Medical Implant Problems
324(1)
9.6 Multiscale Analysis of Protein Materials
324(5)
9.6.1 Hierarchical Structure of Protein Materials
324(1)
9.6.2 Large Deformation and Dynamic Characteristics of Protein Material
325(1)
9.6.3 At Molecular (Nano) Scale: Molecular Dynamics Simulation of Dimer and the Modified Bell Theorem
326(2)
9.6.4 Unique Features of Deformation, Failure and Multiscale Analysis of Biomaterials with Hierarchical Structure
328(1)
9.7 Multiscale Analysis of Medical Implants
329(8)
9.7.1 Background
329(1)
9.7.2 At Atom-nano and Submicron scale: Selection of Implant Chemical Composition Based on Maximum Bonding Energy
329(1)
9.7.3 At Mesoscopic Scale (pm): Cell Adhesion Strength is Calculated and Characterized
330(6)
9.7.4 Discussion
336(1)
9.8 Concluding Remarks
337(1)
Appendix 9 A Derivation of Governing Equation (9.11) for Implicit Relationship of Stress, Strain Rate, Temperature in Terms of Activation Energy and Activation Volume
337(1)
References
338(5)
10 Simulation Schemes, Softwares, Lab Practice and Applications
343(130)
Part 10.1 Basics of Computer Simulations
343(1)
10.1 Basic Knowledge of UNIX System and Shell Commands
343(5)
10.1.1 UNIX Operating System
343(1)
10.1.2 UNIX Shell Commands
344(4)
10.2 A Simple MD Program
348(8)
10.2.1 Five Useful Commands of Fortran 90
349(4)
10.2.2 Module and Subroutine
353(1)
10.2.3 Using crystal_M_simple.f90 to Create Initial Configuration
354(1)
10.2.4 Use multil.f90 to Run a Molecular Dynamics Calculation
355(1)
10.3 Static Lattice Calculations Using GULP
356(11)
10.3.1 Installation and Structure of GULP
357(1)
10.3.2 Input File Structure and Running GULP
357(2)
10.3.3 Structure Optimization and Output File Structure
359(3)
10.3.4 Determining Potential Parameters by Fitting Calculations
362(2)
10.3.5 Shell Model
364(1)
10.3.6 Defect Calculation
365(2)
10.4 Introduction of Visualization Tools and Gnuplot
367(10)
10.4.1 Gnuplot
367(4)
10.4.2 Visual Molecular Dynamics (VMD)
371(3)
10.4.3 AtomEye
374(3)
10.5 Running an Atomistic Simulation Using a Public MD Software DL_POLY
377(12)
10.5.1 Introduction
377(1)
10.5.2 Installation and Structure of DL_POLY_2
378(1)
10.5.3 General Features of DL_POLYJ2 Files
378(1)
10.5.4 Compile and Run
379(2)
10.5.5 Units of Measure
381(1)
10.5.6 Input Files of DL_POLY
382(2)
10.5.7 Output Files
384(2)
10.5.8 Data-Processing for Variable Evolution Versus Time by the ela_STATIS.f90 Code
386(1)
70.5.9 Useful Tools for Operating and Monitoring MD Simulations
387(2)
10.6 Nve and npt Ensemble in MD Simulation
389(8)
10.6.1 Nve Simulation with DL_POLY
390(3)
10.6.2 Npt Simulation with DL_POLY
393(1)
10.6.3 Data Post-processing via STATIS and HISTORY Output Files
394(3)
Part 10.2 Simulation Applications in Metals and Ceramics by MD
397(1)
10.7 Non-equilibrium MD Simulation of One-phase Model Under External Shearing (1)
397(7)
10.7.1 Features and Procedures of MD Simulation Under Shearing Strain Rate
398(1)
10.7.2 Preparation for Input Files and Running 3D npt Equilibration
399(4)
10.7.3 Post-processing Analysis for Equilibration Data
403(1)
10.8 Non-equilibrium MD Simulation of a One-phase Model Under External Shearing (2)
404(8)
10.8.1 Bi-periodic nvt Equilibration in 2D_EQUI_nvt
404(1)
10.8.2 Reference Position Calculation via Producing MEAN.xyz
404(4)
10.8.3 MD simulation Under Shearing Rate on the Top Layer
408(1)
10.8.4 Data Analysis Using elajiistory_2009.f90 for Shearing
409(2)
10.8.5 Tips to Reduce Error When Using ela_history_2009.f90
411(1)
10.9 Non-equilibrium MD Simulation of a Two-phase Model Under External Shearing
412(9)
10.9.1 Dimensional Equilibration of the Individual Phase
412(2)
10.9.2 Developing the Initial Configuration for the Two-phase Model
414(2)
10.9.3 Run the 3D_npt Equilibration in the INI_CONF_coating Directory
416(1)
10.9.4 Non-equilibrium Simulation of the Coating Layer Under Top Shearing Strain Rate
417(1)
10.9.5 Post-data Processing to Determine the Displacement of the Coating Layer Under a Given Shearing Rate
418(3)
Part 10.3 Atomistic Simulation for Protein-Water System and Brief Introduction of Large-scale Atomic/Molecular System (LAMMPS) and the GP Simulation
421(1)
10.10 Using NAMD Software for Biological Atomistic Simulation
421(5)
10.10.1 Introduction
421(1)
10.10.2 A Simple Simulation Using VMD and NAMD
422(3)
10.10.3 Post-processing Data Analysis
425(1)
10.11 Stretching of a Protein Module (1): System Building and Equilibration with VMD/NAMD
426(5)
10.11.1 Preparation of the Initial Configuration with VMD
427(2)
10.11.2 Preparation of the NAMD Input File
429(1)
10.11.3 Run the NAMD Simulation
430(1)
10.11.4 Error Messages and Recommended Action
430(1)
10.12 Stretching of a Protein Module (2): Non-equilibrium MD Simulation with NAMD
431(6)
10.12.1 Preliminary Steps
431(2)
10.12.2 Preparation of the NAMD Input Files
433(2)
10.12.3 Explanation of Important Lines in the fibro_nonequi.conf File
435(1)
10.12.4 Run NAMD Simulation and Data Processing
435(2)
10.13 Brief Introduction to LAMMPS
437(10)
10.13.1 General Features of LAMMPS
437(1)
10.13.2 Structure of LAMMPS Package
438(1)
10.13.3 Building LAMMPS and Run
438(2)
10.13.4 Examples
440(7)
10.14 Multiscale Simulation by Generalized Particle (GP) Dynamics Method
447(5)
10.14.1 Multiscale Model Development
447(3)
10.14.2 Running "Mater_Multi_2010_4.f90" to Produce the Model.MD for Multiscale Simulation
450(1)
10.14.3 Running mpi Simulation for Multiscale Analysis and Data Processing
450(2)
Appendix 10.A Code Installation Guide
452(5)
Prerequisites
452(1)
10.A.1 Introduction
452(1)
10.A.2 Using the KNOPPIX CD to Install the GNU/Linux System
452(1)
10.A.3 ssh and scp
453(1)
10.A.4 Fortran and C Compiler
454(2)
10.A.5 Visual Molecular Dynamics {VMD)
456(1)
10.A.6 Installation of AtomEye
457(1)
Appendix 10.B Brief Introduction to Fortran 90
457(4)
10.B.1 Program Structure, Write to Terminal and Write to File
457(2)
10.B.2 Do Cycle, Formatted Output
459(1)
10.B.3 Arrays and Allocation
460(1)
10.B.4 IF THEN ELSE
461(1)
Appendix 10.C Brief Introduction to VIM
461(2)
10.C.1 Introduction
461(1)
10.C.2 Simple Commands
462(1)
Appendix 10.D Basic Knowledge of Numerical Algorithm for Force Calculation
463(1)
10.D.1 Force Calculation in Atomistic Simulation
463(1)
Appendix 10.E Basic Knowledge of Parallel Numerical Algorithm
464(3)
10.E.1 General Information
464(1)
10.E.2 Atom Decomposition
465(1)
10.E.3 Force Decomposition
466(1)
10.E.4 Domain Decomposition
466(1)
Appendix 10.F Supplemental Materials and Software for Geometric Model Development in Atomistic Simulation
467(6)
10.F.1 Model Development for Model Coordinates Coincident with Main Crystal Axes
468(3)
10.F.2 Model Development for Model Coordinates not Coincident with Crystal Axes
471(2)
References 473(2)
Postface 475(2)
Index 477
Jinghong Fan, Kazuo Inamori School of Engineering, Alfred University, Alfred, New York Dr. Jinghong Fan is a Professor of Mechanical Engineering at the Kazuo Inamori School of Engineering at Alfred University, Alfred, New York, USA. Dr. Fan serves as the Chairman of the Scientific Committee of the Research Center on Materials Mechanics at Chongqing University. He co-chaired the First and Second International Conference on Heterogeneous Materials Mechanics in 2004 and 2008. He has received several awards in his field, including the National Prize for Natural Science in China in 1987. Publications include books such as Foundation of Nonlinear Continuum Mechanics, 1988, and circa140 papers conference and journal papers. Dr. Fan has served as a guest editor of a number of journal special issues.
Püsilink: https://www.kriso.ee/db/9780470972281_pe.html
Märksõnad: