Integrated Computational Materials Engineering (ICME) for Metals

Name: Integrated Computational Materials Engineering (ICME) for Metals | Concepts and Case Studies
Brand: Wiley-Blackwell
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Concepts and Case Studies

Mark F. Horstemeyer(Herausgeber*in)

Wiley-Blackwell (Verlag)

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Erschienen am 23. Februar 2018

688 Seiten

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Beschreibung

Focuses entirely on demystifying the field and subject of ICME and provides step-by-step guidance on its industrial application via case studies

This highly-anticipated follow-up to Mark F. Horstemeyer's pedagogical book on Integrated Computational Materials Engineering (ICME) concepts includes engineering practice case studies related to the analysis, design, and use of structural metal alloys. A welcome supplement to the first book--which includes the theory and methods required for teaching the subject in the classroom--Integrated Computational Materials Engineering (ICME) For Metals: Concepts and Case Studies focuses on engineering applications that have occurred in industries demonstrating the ICME methodologies, and aims to catalyze industrial diffusion of ICME technologies throughout the world.

The recent confluence of smaller desktop computers with enhanced computing power coupled with the emergence of physically-based material models has created the clear trend for modeling and simulation in product design, which helped create a need to integrate more knowledge into materials processing and product performance. Integrated Computational Materials Engineering (ICME) For Metals: Case Studies educates those seeking that knowledge with chapters covering: Body Centered Cubic Materials; Designing An Interatomic Potential For Fe-C Alloys; Phase-Field Crystal Modeling; Simulating Dislocation Plasticity in BCC Metals by Integrating Fundamental Concepts with Macroscale Models; Steel Powder Metal Modeling; Hexagonal Close Packed Materials; Multiscale Modeling of Pure Nickel; Predicting Constitutive Equations for Materials Design; and more.

* Presents case studies that connect modeling and simulation for different materials' processing methods for metal alloys

* Demonstrates several practical engineering problems to encourage industry to employ ICME ideas

* Introduces a new simulation-based design paradigm

* Provides web access to microstructure-sensitive models and experimental database

Integrated Computational Materials Engineering (ICME) For Metals: Case Studies is a must-have book for researchers and industry professionals aiming to comprehend and employ ICME in the design and development of new materials.

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Inhalt

Cover
Title Page
Copyright
Contents
List of Contributors
Foreword
Preface
Chapter 1 Definition of ICME
1.1 What ICME Is NOT
1.1.1 Adding Defects into a Mechanical Theory
1.1.2 Adding Microstructures to Finite Element Analysis (FEA)
1.1.3 Comparing Modeling Results to Structure-Property Experimental Results
1.1.4 Computational Materials
1.1.5 Design Materials for Manufacturing (Process-Structure-Property Relationships)
1.1.6 Simulation through the Process Chain
1.2 What ICME Is
1.2.1 Background
1.2.2 ICME Definition
1.2.3 Uncertainty
1.2.4 ICME Cyberinfrastructure
1.3 Industrial Perspective
1.4 Summary
References
Section I Body-Centered Cubic Materials
Chapter 2 From Electrons to Atoms: Designing an Interatomic Potential for Fe-C Alloys
2.1 Introduction
2.2 Methods
2.2.1 MEAM Calculations
2.2.2 DFT Calculations
2.3 Single-Element Potentials
2.3.1 Energy versus Volume Curves
2.3.1.1 Single-Element Material Properties
2.4 Construction of Fe-C Alloy Potential
2.5 Structural and Elastic Properties of Cementite
2.5.1 Single-Crystal Elastic Properties
2.5.2 Polycrystalline Elastic Properties
2.5.3 Surface Energies
2.5.4 Interstitial Energies
2.6 Properties of Hypothetical Crystal Structures
2.6.1 Energy versus Volume Curves for B1 and L12 Structures
2.6.2 Elastic Constants for B1 and L12 Structures
2.7 Thermal Properties of Cementite
2.7.1 Thermal Stability of Cementite
2.7.2 Melting Temperature Simulation
2.7.2.1 Preparation of Two-Phase Simulation Box
2.7.2.2 Two-Phase Simulation
2.8 Summary and Conclusions
Acknowledgments
References
Chapter 3 Phase-Field Crystal Modeling: Integrating Density Functional Theory, Molecular Dynamics, and Phase-Field Modeling
3.1 Introduction to Phase-Field and Phase-Field Crystal Modeling
3.2 Governing Equations of Phase-Field Crystal (PFC) Models Derived from Density Functional Theory (DFT)
3.2.1 One-Mode PFC model
3.2.2 Two-Mode PFC Model
3.3 PFC Model Parameters by Molecular Dynamics Simulations
3.4 Case Study: Solid-Liquid Interface Properties of Fe
3.5 Case Study: Grain Boundary Free Energy of Fe at Its Melting Point
3.6 Summary and Future Directions
References
Chapter 4 Simulating Dislocation Plasticity in BCC Metals by Integrating Fundamental Concepts with Macroscale Models
4.1 Introduction
4.2 Existing BCC Models
4.3 Crystal Plasticity Finite Element Model
4.4 Continuum-Scale Model
4.5 Engineering Scale Applications
4.6 Summary
References
Chapter 5 Heat Treatment and Fatigue of a Carburized and Quench Hardened Steel Part
5.1 Introduction
5.2 Modeling Phase Transformations and Mechanics of Steel Heat Treatment
5.3 Data Required for Modeling Quench Hardening Process
5.3.1 Dilatometry Data
5.3.2 Mechanical Property Data
5.3.3 Thermal Property Data
5.3.4 Process Data
5.3.5 Furnace Heating
5.3.6 Gas Carburization
5.3.7 Immersion Quenching
5.4 Heat Treatment Simulation of a Gear
5.4.1 Description of Gear Geometry, FEA Model, and Problem Statement
5.4.2 Carburization and Air Cooling Modeling
5.4.3 Quench Hardening Process Modeling
5.4.4 Comparison of Model and Experimental Results
5.4.5 Tooth Bending Fatigue Data and Loading Model
5.5 Summary
References
Chapter 6 Steel Powder Metal Modeling
6.1 Introduction
6.2 Material: Steel Alloy
6.3 ICME Modeling Methodology
6.3.1 Compaction
6.3.1.1 Macroscale Compaction Model
6.3.1.2 Compaction Model Calibration
6.3.1.3 Validation
6.3.1.4 Compaction Model Sensitivity and Uncertainty Analysis
6.3.2 Sintering
6.3.2.1 Atomistic
6.3.2.2 Theory and Simulations
6.3.2.3 Sintering Structure-Property Relations
6.3.2.4 Sintering Constitutive Modeling
6.3.2.5 Sintering Model Implementation and Calibration
6.3.2.6 Sintering Validation for an Automotive Main Bearing Cap
6.3.3 Performance/Durability
6.3.3.1 Monotonic Conditions
6.3.3.2 Plasticity-Damage Structure-Property Relations
6.3.3.3 Plasticity-Damage Model and Calibration
6.3.3.4 Validation and Uncertainty
6.3.3.5 Main Bearing Cap
6.3.3.6 Fatigue
6.3.4 Optimization
6.3.4.1 Design of Experiments (DOE)
6.3.4.2 Results and Discussion
6.4 Summary
References
Chapter 7 Microstructure-Sensitive, History-Dependent Internal State Variable Plasticity-Damage Model for a Sequential Tubing Process
7.1 Introduction
7.2 Internal State Variable (ISV) Plasticity-Damage Model
7.2.1 History Effects
7.2.2 Constitutive Equations
7.3 Simulation Setups
7.4 Results
7.4.1 ISV Plasticity-Damage Model Calibration and Validation
7.4.2 Simulations of the Forming Process (Step 1)
7.4.3 Simulations of Sizing Process (Step 3)
7.4.4 Simulations of First Annealing Process (Step 4)
7.4.5 Simulations of Drawing Processes (Steps 5 and 6)
7.4.6 Simulations of Second Annealing Process (Step 7)
7.5 Conclusions
References
Section II Hexagonal Close Packed (HCP) Materials
Chapter 8 Electrons to Phases of Magnesium
8.1 Introduction
8.2 Criteria for the Design of Advanced Mg Alloys
8.3 Fundamentals of the ICME Approach Designing the Advanced Mg Alloys
8.3.1 Roadmap of ICME Approach
8.3.2 Fundamentals of Computational Thermodynamics
8.3.3 Electronic Structure Calculations of Materials Properties
8.3.3.1 First-Principles Calculations for Finite Temperatures
8.3.3.2 First-Principles Calculations of Solid Solution Phase
8.3.3.3 First-Principles Calculations of Interfacial Energy
8.3.3.4 Equation of States (EOSs) and Elastic Moduli
8.3.3.5 Deformation Electron Density
8.3.3.6 Diffusion Coefficient
8.4 Data-Driven Mg Alloy Design - Application of ICME Approach
8.4.1 Electronic Structure
8.4.2 Thermodynamic Properties
8.4.3 Phase Stability and Phase Diagrams
8.4.3.1 Database Development
8.4.3.2 Application of CALPHAD in Mg Alloy Design
8.4.4 Kinetic Properties
8.4.5 Mechanical Properties
8.4.5.1 Elastic Constants
8.4.5.2 Stacking Fault Energy and Ideal Strength Impacted by Alloying Elements
8.4.5.3 Prismatic and Pyramidal Slips Activated by Lattice Distortion
8.5 Outlook/Future Trends
Acknowledgments
References
Chapter 9 Multiscale Statistical Study of Twinning in HCP Metals
9.1 Introduction
9.2 Crystal Plasticity Modeling of Slip and Twinning
9.2.1 Crystal Plasticity Models
9.2.2 Incorporating Twinning Into Crystal Plasticity Formulations
9.2.3 Incorporating Hardening into Crystal Plasticity Formulations
9.3 Introducing Lower Length Scale Statistics in Twin Modeling
9.3.1 The Atomic Scale
9.3.2 Mesoscale Statistical Characterization of Twinning
9.3.3 Mesoscale Statistical Modeling of Twinning
9.3.3.1 Stochastic Model for Twinning
9.3.3.2 Stress Associated with Twin Nucleation
9.3.3.3 Stress Associated with Twin Growth
9.4 Model Implementation
9.4.1 Comparison with Bulk Measurements
9.4.2 Comparison with Statistical Data from EBSD
9.5 The Continuum Scale
9.5.1 Bending Simulations of Zr Bars
9.6 Summary
Acknowledgment
References
Chapter 10 Cast Magnesium Alloy Corvette Engine Cradle
10.1 Introduction
10.2 Modeling Philosophy
10.3 Multiscale Continuum Microstructure-Property Internal State Variable (ISV) Model
10.4 Electronic Structures
10.5 Atomistic Simulations for Magnesium Using the Modified Embedded Atom Method (MEAM) Potential
10.5.1 MEAM Calibration for Magnesium
10.5.2 MEAM Validation for Magnesium
10.5.3 Atomistic Simulations of Mg-Al in Monotonic Loadings
10.6 Mesomechanics: Void Growth and Coalescence
10.6.1 Mesomechanical Simulation Material Model for Cylindrical and Spherical Voids
10.6.2 Mesomechanical Finite Element Cylindrical and Spherical Voids Results
10.6.3 Discussion of Cylindrical and Spherical Voids
10.7 Macroscale Modeling and Experiments
10.7.1 Plasticity-Damage Internal State Variable (ISV) Model
10.7.2 Macroscale Plasticity-Damage Internal State Variable (ISV) Model Calibration
10.7.3 Macroscale Microstructure-Property ISV Model Validation Experiments on AM60B: Notch Specimens
10.7.3.1 Finite Element Setup
10.7.3.2 ISV Model Validation Simulations with Notch Test Data
10.8 Structural-Scale Corvette Engine Cradle Analysis
10.8.1 Cradle Finite Element Model
10.8.2 Cradle Porosity Distribution Mapping
10.8.3 Structural-Scale Modeling Results
10.8.4 Corvette Engine Cradle Experiments
10.9 Summary
References
Chapter 11 Using an Internal State Variable (ISV)-Multistage Fatigue (MSF) Sequential Analysis for the Design of a Cast AZ91 Magnesium Alloy Front-End Automotive Component
11.1 Introduction
11.2 Integrated Computational Materials Engineering and Design
11.2.1 Processing-Structure-Property Relationships and Design
11.2.2 Integrated Computational Materials Engineering (ICME) and Multiscale Modeling
11.2.3 Overview of the Internal State Variable (ISV)-Multistage Fatigue (MSF)
11.3 Mechanical and Microstructure Analysis of a Cast AZ91 Mg Alloy Shock Tower
11.3.1 Shock Tower Microstructure Characterization
11.3.2 Shock Tower Monotonic Mechanical Behavior
11.3.3 Fatigue Behavior of an AZ91 Mg Alloy
11.3.3.1 Strain-life Fatigue Behavior for an AZ91 Mg Alloy
11.3.3.2 Fractographic Analysis
11.4 A Microstructure-Sensitive Internal State Variable (ISV) Plasticity-Damage Model
11.5 Microstructure-Sensitive Multistage Fatigue (MSF) Model for an AZ91 Mg Alloy
11.5.1 The Multistage Fatigue (MSF) Model
11.5.1.1 Incubation Regime
11.5.1.2 Microstructurally Small Crack (MSC) Growth Regime
11.5.2 Calibration of the MSF Model for the AZ91 Alloy
11.6 Internal State Variable (ISV)-Multistage Fatigue (MSF) Model Finite Element Simulations
11.6.1 Finite Element Model
11.6.2 Shock Tower Distribution Mapping of Microstructural Properties
11.6.3 Finite Element Simulations
11.6.3.1 Case 1 Homogeneous Material State Calculation (FEA #1)
11.6.3.2 Case 2 Heterogeneous Porosity Calculation (FEA #5)
11.6.3.3 Case 3 Heterogeneous Pore Size Calculation (FEA #4)
11.6.3.4 Case 4 Heterogeneous Material State Calculation (FEA #2)
11.6.4 Fatigue Tests and Finite Element Results
11.7 Summary
References
Section III Face-Centered Cubic (FCC) Materials
Chapter 12 Electronic Structures and Materials Properties Calculations of Ni and Ni-Based Superalloys
12.1 Introduction
12.2 Designing the Next Generation of Ni-Base Superalloys Using the ICME Approach
12.3 Density Functional Theory as the Basis for an ICME Approach to Ni-Base Superalloy Development
12.3.1 Fundamental Concepts of Density Functional Theory
12.3.2 Fundamentals of Thermodynamic Modeling (the CALPHAD Approach)
12.4 Theoretical Background and Computational Procedure
12.4.1 First-Principles Calculation of Elastic Constants
12.4.2 First-Principles Calculations of Stacking Fault Energy
12.4.3 First-Principles Calculations of Dilute Impurity Diffusion Coefficients
12.4.4 Finite-Temperature First-Principles Calculations
12.4.5 Computational Details as Implemented in VASP
12.5 Ni-Base Superalloy Design using the ICME Approach
12.5.1 Finite Temperature Thermodynamics
12.5.1.1 Application to CALPHAD Modeling
12.5.2 Mechanical Properties
12.5.2.1 Elastic Constants Calculations
12.5.2.2 Stacking Fault Energy Calculations
12.5.3 Diffusion Coefficients
12.5.4 Designing Ni-Base Superalloy Systems Using the ICME Approach
12.5.4.1 CALPHAD Modeling used for Ni-Base Superalloy Design
12.5.4.2 Using a Mechanistic Model to Predict a Relative Creep Rates in Ni-X Alloys
12.6 Conclusions and Future Directions
Acknowledgments
References
Chapter 13 Nickel Powder Metal Modeling Illustrating Atomistic-Continuum Friction Laws
13.1 Introduction
13.2 ICME Modeling Methodology
13.2.1 Compaction
13.2.2 Macroscale Plasticity Model for Powder Metals
13.3 Atomistic Studies
13.3.1 Simulation Method and Setup
13.3.2 Simulation Results and Discussion
13.4 Summary
References
Chapter 14 Multiscale Modeling of Pure Nickel
14.1 Introduction
14.2 Bridge 1: Electronics to Atomistics and Bridge 4: Electronics to the Continuum
14.2.1 Electronics Principles Calibration Using Density Functional Theory (DFT)
14.2.2 Density Functional Theory Background
14.2.3 Upscaling Information from DFT
14.2.3.1 Energy-Volume
14.2.3.2 Elastic Moduli
14.2.3.3 Generalized Stacking Fault Energy (GSFE)
14.2.3.4 Vacancy Formation Energy
14.2.3.5 Surface Formation Energy
14.2.4 MEAM Background and Theory
14.2.5 Validation of Atomistic Results Using the MEAM Potential
14.3 Bridge 2: Atomistics to Dislocation Dynamics and Bridge 5: Atomistics to the Continuum
14.3.1 Upscaling MEAM/LAMMPS to Determine the Dislocation Mobility
14.3.2 MEAM/LAMMPS Validation and Uncertainty
14.4 Bridge 3: Dislocation Dynamics to Crystal Plasticity and Bridge 6: Dislocation Dynamics to the Continuum
14.4.1 Dislocation Dynamics Background
14.4.2 Crystal Plasticity Background
14.4.3 Crystal Plasticity Voce Hardening Equation Calibration
14.4.4 Crystal Plasticity Finite Element Method to Determine the Polycrystalline Stress-strain Behavior
14.5 Bridge 7: Crystal Plasticity to the Continuum
14.5.1 Macroscale Constitutive Model Calibration
14.6 Bridge 8: Macroscale Calibration to Structural Scale Simulations
14.6.1 Validation of Multiscale Methodology
14.6.2 Experimental and Simulation Results
14.7 Summary
Acknowledgments
References
Section IV Design of Materials and Structures
Chapter 15 Predicting Constitutive Equations for Materials Design: A Conceptual Exposition
15.1 Introduction
15.2 Frame of Reference
15.3 Critical Review of the Literature
15.3.1 Constitutive Equation (CEQ)
15.3.2 Various Types of Power-Law Flow Rules in CP Algorithm
15.3.3 Comparison of FEM versus VFM
15.3.4 AI-based KDD Process
15.4 Crystal Plasticity-Based Virtual Experiment Model
15.4.1 Description of CPVEM
15.4.2 Various Types of Power-Law Flow Rules
15.5 Hierarchical Strategy for Developing a Constitutive EQuation (CEQ) Expansion Model
15.5.1 Computational Model for Developing a CEQ Expansion Model
15.5.1.1 CPVEM for Predicting CEQ Patterns
15.5.1.2 Identifying CEQ Patterns for TAV
15.5.1.3 Virtual Fields Method (VFM) Model for Predicting Material Properties for New Ti-Al-X (TAX) Materials
15.5.2 Big Data Control Based on Ontology Integration
15.6 Closing Remarks
Nomenclature
Acknowledgments
References
Chapter 16 A Computational Method for the Design of Materials Accounting for the Process-Structure-Property- Performance (PSPP) Relationship
16.1 Introduction
16.2 Frame of Reference
16.3 Integrated Multiscale Robust Design (IMRD)
16.4 Roll Pass Design
16.4.1 Roll Pass Sequence and Design Parameters
16.4.2 Flow Stress Prediction Model
16.4.3 Wear Coefficient
16.5 Microstructure Evolution Model
16.5.1 Recrystallization
16.5.2 Austenite Grain Size (AGS) Prediction
16.5.3 Ferrite Grain Size (FGS) Prediction
16.6 Exploring the Feasible Solution Space
16.6.1 Developing Roll Pass Design and The Analysis and FE Models
16.6.2 Developing Modules and Their Corresponding Model Descriptions
16.6.2.1 Module 1. AGS Prediction Model (f1)
16.6.2.2 Module 2. FGS Prediction Model (f2)
16.6.2.3 Module 3. Structure-Property Correlation
16.6.2.4 Module 4. Property-Performance Correlation
16.6.3 IMRD Step 1 in Figure 16.8: Deductive Exploration
16.6.4 IMRD Step 2 in Figure 16.8: Inductive Exploration
16.6.5 IMRD Step 3 in Figure 16.8: Trade-offs among Competing Goals
16.6.6 Exploration of Solution Space
16.7 Results and Discussion
16.8 Closing Remarks
Acknowledgments
Nomenclature
References
Section V Education
Chapter 17 An Engineering Virtual Organization for CyberDesign (EVOCD): A Cyberinfrastructure for Integrated Computational Materials Engineering (ICME)
17.1 Introduction
17.2 Engineering Virtual Organization for CyberDesign
17.3 Functionality of EVOCD
17.3.1 Knowledge Management: Wiki
17.3.2 Repository of Codes
17.3.3 Repository of Data
17.3.4 Online Model Calibration Tools
17.3.4.1 DMGfit
17.3.4.2 MultiState Fatigue (MSF)
17.3.4.3 Modified Embedded Atom Method (MEAM) Parameter Calibration (MPC)
17.4 Protection of Intellectual Property
17.5 Cyberinfrastructure for EVOCD
17.5.1 User Interface
17.5.2 EVOCD Services
17.5.3 Service Integration
17.6 Conclusions
References
Chapter 18 Integrated Computational Materials Engineering (ICME) Pedagogy
18.1 Introduction
18.2 Methodology
18.3 Course Curriculum
18.3.1 ICME for Design
18.3.2 Presentation and Team Formation
18.3.3 ICME Cyberinfrastructure and Basic Skills
18.3.4 Bridging Length Scales
18.3.4.1 Quantum Methods
18.3.4.2 Atomistic Methods
18.3.4.3 Dislocation Dynamics Methods
18.3.4.4 Crystal Plasticity
18.3.4.5 Macroscale Continuum Modeling
18.3.5 ICME Wiki Contributions
18.3.6 Grading and Evaluation
18.4 Assessment
18.5 Benefits or Relevance of the Learning Methodology
18.6 Conclusions and Future Directions
Acknowledgments
References
Chapter 19 Summary
19.1 Introduction
19.2 Chapter 1 ICME Definition: Takeaway Point
19.3 Chapter 2: Takeaway Point
19.4 Chapter 3: Takeaway Point
19.5 Chapter 4: Takeaway Point
19.6 Chapter 5: Takeaway Point
19.7 Chapter 6: Takeaway Point
19.8 Chapter 7: Takeaway Point
19.9 Chapter 8: Takeaway Point
19.10 Chapter 9: Takeaway Point
19.11 Chapter 10: Takeaway Point
19.12 Chapter 11: Takeaway Point
19.13 Chapter 12: Takeaway Point
19.14 Chapter 13: Takeaway Point
19.15 Chapter 14: Takeaway Point
19.16 Chapter 15: Takeaway Point
19.17 Chapter 16: Takeaway Point
19.18 Chapter 17: Takeaway Point
19.19 Chapter 18: Takeaway Point
19.20 ICME Future
19.20.1 ICME Future: Metals
19.20.2 ICME Future: Non-Metals
19.20.2.1 Polymers
19.20.2.2 Ceramics
19.20.2.3 Concrete
19.20.2.4 Biological Materials
19.20.2.5 Earth Materials
19.20.2.6 Space Materials
19.21 Summary
References
Index
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