Integrated Computational Materials Engineering (ICME): Advancing Computational and Experimental Methods

✍ Scribed by Somnath Ghosh (editor), Christopher Woodward (editor), Craig Przybyla (editor)

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 416
• Category: Library

✦ Synopsis

​This book introduces research advances in Integrated Computational Materials Engineering (ICME) that have taken place under the aegis of the AFOSR/AFRL sponsored Center of Excellence on Integrated Materials Modeling (CEIMM) at Johns Hopkins University. Its author team consists of leading researchers in ICME from prominent academic institutions and the Air Force Research Laboratory. The book examines state-of-the-art advances in physics-based, multi-scale, computational-experimental methods and models for structural materials like polymer-matrix composites and metallic alloys. The book emphasizes Ni-based superalloys and epoxy matrix carbon-fiber composites and encompasses atomistic scales, meso-scales of coarse-grained models and discrete dislocations, and micro-scales of poly-phase and polycrystalline microstructures. Other critical phenomena investigated include the relationship between microstructural morphology, crystallography, and mechanisms to the material response at different scales; methods of identifying representative volume elements using microstructure and material characterization, and robust deterministic and probabilistic modeling of deformation and damage.

Encompassing a slate of topics that enable readers to comprehend and approach ICME-related issues involved in predicting material performance and failure, the book is ideal for mechanical, civil, and aerospace engineers, and materials scientists, in in academic, government, and industrial laboratories.

✦ Table of Contents

Preface
Acknowledgment
Contents
Contributors
Acquisition of 3D Data for Prediction of Monotonic and Cyclic Properties of Superalloys
1 Superalloys and Fatigue
2 Importance of 3D Data
3 The TriBeam
4 Targeted 3D Data
5 Future Needs
Appendix
References
Data Structures and Workflows for ICME
1 Introduction
2 ICME Software Tools
3 Simulation Tools
3.1 Analytic Tools
3.2 Example Tools from Other Fields
4 Building an Extensible ICME Data Schema and Workflow Tool
4.1 Data Handling Requirements
4.2 Modular Workflow Requirements
4.3 Data Access and Metadata Labeling Requirements
5 SIMPL and DREAM.3D: Enabling ICME Workflows
5.1 SIMPL Data Structure
5.2 Filters, Pipelines, and Plugins
5.3 SIMPLView: The Standard SIMPL Graphical Interface
5.4 DREAM.3D: An ICME Workflow Tool
6 Case Study: Ti-6242Si Pancake Forging
6.1 Zoning Process Histories
6.2 Processing Characterization Data
6.3 Registration and Fusion
7 Summary
References
Multi-scale Microstructure and Property-Based Statistically Equivalent RVEs for Modeling Nickel-Based Superalloys
1 Introduction
2 M-SERVE and P-SERVE for Intragranular Microstructures at the Subgrain Scale
2.1 Experimental Data Acquisition and Image Processing
2.2 Parametric Representation of Precipitate Morphology and Statistical Distributions
2.3 Generating Intragranular Statistically Equivalent Virtual Microstructures
2.3.1 Finalizing SEVMs Through Optimization of the Two-Point Correlation Function
2.3.2 Validation of SEVM Generation Method by Convergence Tests
2.4 Determining the M-SERVE from Statistical Convergence
2.4.1 Convergence of Morphological Distributions
2.4.2 Convergence of Spatial Distributions
2.5 Determining the Property-Based Statistically Equivalent RVE (P-SERVE)
2.5.1 Crystal Plasticity Models for Ni-Based Superalloys
2.5.2 CPFE Simulations for Analyzing Response Variables
2.5.3 Spatially Averaged Mechanical Fields
2.5.4 Local Response Field Variables
2.6 Summary of the Subgrain-Scale Analysis
3 M-SERVE and P-SERVE for Polycrystalline Microstructures of Ni-Based Superalloys
3.1 Image Extraction from Electron Backscattered Diffraction Maps
3.2 Statistically Equivalent Virtual Microstructure (SEVM) Generation from Characterization and Statistical Analysis
3.2.1 Validation of the SEVM Generation Method
3.3 Estimating M-SERVEs for Polycrystalline Microstructure with Twins
3.4 Estimating the P-SERVE Through Convergence Studies
3.4.1 P-SERVE Convergence Studies with the Crystal Plasticity Model
3.5 Summary of the Polycrystalline Scale Analysis
References
Microscale Testing and Characterization Techniques for Benchmarking Crystal Plasticity Models at Microstructural Length Scales
1 Introduction
2 Background
3 Machining Methods for Microscale Samples
3.1 Focused Ion Beam Machining
3.2 Wire EDM Machining
3.3 Femtosecond Laser Machining
3.4 Comparison of Machining Techniques
4 Sample Size Effects on Strength in René 88DT
5 Orientation and Deformation Maps
6 Chapter Summary
References
Computational Micromechanics Modeling of Polycrystalline Superalloys Application to Inconel 718
1 Introduction
2 Material Description
3 Experimental Characterization
3.1 Micromechanical Characterization
3.1.1 Experimental Procedure
3.1.2 Results
3.2 Macromechanical Characterization
3.2.1 Uniaxial Monotonic Tests
3.2.2 Low Cycle Fatigue Tests
4 Polycrystalline Homogenization Framework
4.1 Boundary Value Problem and Boundary Conditions
4.2 Microstructure Representation
4.3 Single Crystal Behavior
5 Monotonic Behavior
5.1 Elastic Behavior
5.2 Elastoplastic Behavior
5.3 Grain Size-Dependent Model
6 Cyclic Behavior
6.1 Crystal Plasticity Model for Cyclic Behavior
6.1.1 Model Parameter Identification
6.2 Simulation of the Cyclic Behavior
6.3 Grain Size-Dependent Cyclic Behavior
7 Microstructure-Dependent Fatigue Life Simulation
7.1 Microstructure-Sensitive Crack Initiation Model
7.2 Results
8 Conclusions
References
Non-deterministic Calibration of Crystal Plasticity ModelParameters
1 Introduction
2 Acquiring and Processing Experiment Data
2.1 Global Data
2.2 Local Data
2.2.1 Digital Image Correlation
2.2.2 High-Resolution EBSD
2.2.3 Combining DIC and HREBSD
3 Crystal Plasticity
3.1 Concepts
4 Calibration
4.1 General Process
4.2 Global Methods
4.2.1 Data Flow
4.2.2 Computational Model
4.3 Global-Local Methods
4.3.1 Data Flow
4.3.2 Computational Model
4.4 Local Methods
4.4.1 Data Flow
4.4.2 Computational Model
5 Uncertainty Quantification Model for Calibration
6 Demonstration Using Simulated Experiments
6.1 Using Global Calibration
6.2 Using Global-Local Calibration
6.3 Using Local Calibration
7 Summary
8 Outlook
References
Local Stress and Damage Response of Polycrystal Materials to Light Shock Loading Conditions via Soft Scale-Coupling
1 Introduction
2 Nomenclature
3 Experimental Overview
4 Macroscale Damage Modeling
4.1 Damage Constitutive Model
4.2 Numerical Simulation Results
5 Local-Scale Modeling
5.1 Single Crystal Model
5.2 Polycrystal Numerical Results
6 Conclusion
References
A Framework for Quantifying Effects of Characterization Error on the Predicted Local Elastic Response in Polycrystalline Materials
1 Introduction
2 Methods
2.1 Step 1: Synthetic Material Generation – Phantoms
2.2 Step 2: Simulation of Data Collection
2.2.1 Resolution
2.2.2 Interaction Volume
2.2.3 Random Noise
2.2.4 Summary of Data Collection Model
2.3 Additional Notes on Methodology
3 Individual Parameter Variation Examples
3.1 Step 3: Error Measurements
3.2 Resolution
3.2.1 Analytical Model of Error Associated with Sample Spacing
3.3 Interaction Volume
3.4 Unindexed Pixels
3.5 Data Processing Parameters
3.6 Brief Discussion on Data Collection and Processing Error
4 Case Study: Application to Finite Element Model
4.1 Conclusions from the Case Study
5 Conclusions
References
Material Agnostic Data-Driven Framework to Develop Structure-Property Linkages
1 Introduction
2 Material Agnostic Data-Driven Framework to Process-Structure-Property Linkages
2.1 Microstructure Quantification
2.2 Data-Driven Workflow for Extracting P-S-P Linkages
3 Application of the Material Agnostic Framework to Different Material Systems
3.1 Composites
3.2 Polycrystalline Metallic Materials
4 Challenges
5 Summary
References
Multiscale Modeling of Epoxies and Epoxy-Based Composites
1 Introduction
2 Overview of Multiscale Simulation Methods for Epoxies
2.1 Molecular Dynamics Simulation
2.2 Coarse-Grained Molecular Dynamics Methods
2.3 Finite Element Method
3 Multiscale Simulations of Epoxies and Their Properties
3.1 Modeling the Curing Process of Epoxies
3.2 Epoxy Density and Volume Shrinkage
3.3 Glass Transition Temperature
3.4 Free Volume Distribution
3.5 Elastic Modulus
3.6 Failure Properties
4 Multiscale Simulations of Epoxy Interfacial Properties
4.1 Epoxy-Based Composites and the Interphase Region
4.2 Coatings and Adhesives
5 Summary and Conclusions
References
Microstructural Statistics Informed Boundary Conditions for Statistically Equivalent Representative Volume Elements (SERVEs) of Polydispersed Elastic Composites
1 Introduction
2 Formulation of the Exterior Statistics-Based Boundary Conditions for a SERVE
2.1 Exterior Statistics-Based Perturbed Fields
2.2 Implementation of the Exterior Statistics-Based Boundary Conditions (ESBCs)
3 Validation of ESBCs for SERVEs in Nonhomogeneous Microstructures with Clustering
3.1 Comparing ESBCs Generated by the 2-Point Correlation and Radial Distribution Functions
3.2 ESBCs for SERVEs Intersecting Clustered Regions
4 Convergence of Elastic Homogenized Stiffness
4.1 Selection of SERVE Size from Convergence Characteristics
4.2 Comparing Convergence of ESBC-Based SERVE with Statistical Volume Elements (SVEs)
5 ESBCs for Polydispersed Microstructures of Carbon Fiber Polymer Matrix Composites
5.1 Microstructure Imaging, Characterization, and Mechanical Testing
5.2 Statistical Characterization of the Polydispersed Microstructure
5.3 Creating Statistically Equivalent MVEs from Experimental Micrographs
5.4 Micromechanical Analysis of the Polydispersed SERVE with ESBCs
5.5 Candidate SERVE Selection from Stiffness Convergence
5.6 Comparing the SERVE and SVE Stiffness with Experimental Observations
6 Summary and Conclusions
Appendix: Eshelby Tensors for Circular Cylindrical Fibers
References
Transverse Failure of Unidirectional Composites: Sensitivity to Interfacial Properties
1 Introduction
2 Experimental Observations
3 Modeling
3.1 Cohesive Zone Model
3.2 Interface-Enriched Generalized Finite Element Method (IGFEM)
3.3 Mesoscale Simulations
3.4 Validation
4 Sensitivity Analysis: Formulation
5 Sensitivity Analysis: Verification
6 Sensitivity Analysis: Results
7 Conclusion
Appendix: Sensitivity to Critical Displacement Jumps
References
Geometric Modeling of Transverse Cracking of Composites
1 Introduction
2 Problem Description
3 Fiber-Pair Stress Concentration
4 Stress Shielding from Transverse Cracks
5 Model Testing and Calibration
6 Statistical Analysis of the Impact of the Interface Strength Distribution
7 Conclusion
References
Challenges in Understanding the Dynamic Behavior of Heterogeneous Materials
1 Introduction
1.1 The Challenge of Dynamic Property Measurements
1.2 ICMSE Approaches to Probing Dynamic Behavior of Materials
1.2.1 Molecular Dynamics and Coarse-Grained Methods
1.2.2 Meso-scale and Microstructure-Based Simulation at the Continuum Scale
1.3 Outline of Chapter
2 Background on Shock Compression Science
2.1 Shock Compression Science and Theory
2.2 Conservation Relations for a Shock Wave
2.2.1 Theoretical Equations of State for Reactive Powders
2.3 Reactive Powder Mixtures and Explosives
3 Case Study: Dynamic Behavior of Reactive Powder Mixtures
3.1 Impact-Induced Chemical Reactions
3.2 Shock-Induced Chemical Reactions
4 Summary and Conclusions: Where Can ICMSE Continue to Provide Value in Understanding Dynamic Behavior of Heterogeneous Materials?
References
Correction to: Transverse Failure of Unidirectional Composites: Sensitivity to Interfacial Properties
Index