Skip to main content

Integrated Computational Materials Engineering (ICME) for Metals: Concepts and Case Studies

Integrated Computational Materials Engineering (ICME) for Metals: Concepts and Case Studies

Mark F. Horstemeyer (Editor)

ISBN: 978-1-119-01836-0

Mar 2018

688 pages

In Stock

$245.00

Description

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.

List of Contributors xix

Foreword xxvii

Preface xxix

1 Definition of ICME 1
Mark F. Horstemeyer and S. S. Sahay

1.1 What ICME Is NOT 1

1.1.1 Adding Defects into a MechanicalTheory 1

1.1.2 Adding Microstructures to Finite Element Analysis (FEA) 2

1.1.3 Comparing Modeling Results to Structure–Property Experimental Results 2

1.1.4 Computational Materials 2

1.1.5 Design Materials for Manufacturing (Process–Structure–Property Relationships) 3

1.1.6 Simulation through the Process Chain 3

1.2 What ICME Is 4

1.2.1 Background 4

1.2.2 ICME Definition 5

1.2.3 Uncertainty 8

1.2.4 ICME Cyberinfrastructure 9

1.3 Industrial Perspective 10

1.4 Summary 15

References 15

Section I Body-Centered Cubic Materials 19

2 From Electrons to Atoms: Designing an Interatomic Potential for Fe–C Alloys 21
Laalitha S. I. Liyanage, Seong-Gon Kim, Jeff Houze, Sungho Kim, Mark A. Tschopp, M. I. Baskes, and Mark F. Horstemeyer

2.1 Introduction 21

2.2 Methods 23

2.2.1 MEAM Calculations 24

2.2.2 DFT Calculations 24

2.3 Single-Element Potentials 25

2.3.1 Energy versus Volume Curves 25

2.3.1.1 Single-Element Material Properties 29

2.4 Construction of Fe–C Alloy Potential 29

2.5 Structural and Elastic Properties of Cementite 35

2.5.1 Single-Crystal Elastic Properties 36

2.5.2 Polycrystalline Elastic Properties 37

2.5.3 Surface Energies 37

2.5.4 Interstitial Energies 38

2.6 Properties of Hypothetical Crystal Structures 38

2.6.1 Energy versus Volume Curves for B1 and L12 Structures 38

2.6.2 Elastic Constants for B1 and L12 Structures 40

2.7 Thermal Properties of Cementite 40

2.7.1 Thermal Stability of Cementite 40

2.7.2 Melting Temperature Simulation 40

2.7.2.1 Preparation of Two-Phase Simulation Box 41

2.7.2.2 Two-Phase Simulation 41

2.8 Summary and Conclusions 44

Acknowledgments 45

References 45

3 Phase-Field Crystal Modeling: Integrating Density Functional Theory, Molecular Dynamics, and Phase-FieldModeling 49
Mohsen Asle Zaeem and Ebrahim Asadi

3.1 Introduction to Phase-Field and Phase-Field Crystal Modeling 49

3.2 Governing Equations of Phase-Field Crystal (PFC) Models Derived from Density FunctionalTheory (DFT) 53

3.2.1 One-Mode PFC model 53

3.2.2 Two-Mode PFC Model 55

3.3 PFC Model Parameters by Molecular Dynamics Simulations 57

3.4 Case Study: Solid–Liquid Interface Properties of Fe 59

3.5 Case Study: Grain Boundary Free Energy of Fe at Its Melting Point 63

3.6 Summary and Future Directions 65

References 66

4 Simulating Dislocation Plasticity in BCCMetals by Integrating Fundamental Concepts with Macroscale Models 71
Hojun Lim, Corbett C. Battaile, and Christopher R.Weinberger

4.1 Introduction 71

4.2 Existing BCC Models 73

4.3 Crystal Plasticity Finite Element Model 85

4.4 Continuum-Scale Model 90

4.5 Engineering Scale Applications 92

4.6 Summary 99

References 101

5 Heat Treatment and Fatigue of a Carburized and Quench Hardened Steel Part 107
Zhichao (Charlie)Li and B. Lynn Ferguson

5.1 Introduction 107

5.2 Modeling Phase Transformations and Mechanics of Steel Heat Treatment 108

5.3 Data Required for Modeling Quench Hardening Process 112

5.3.1 Dilatometry Data 113

5.3.2 Mechanical Property Data 114

5.3.3 Thermal Property Data 114

5.3.4 Process Data 114

5.3.5 Furnace Heating 115

5.3.6 Gas Carburization 116

5.3.7 Immersion Quenching 116

5.4 Heat Treatment Simulation of a Gear 118

5.4.1 Description of Gear Geometry, FEA Model, and Problem Statement 119

5.4.2 Carburization and Air Cooling Modeling 120

5.4.3 Quench Hardening Process Modeling 122

5.4.4 Comparison of Model and Experimental Results 128

5.4.5 Tooth Bending Fatigue Data and LoadingModel 129

5.5 Summary 132

References 134

6 Steel Powder Metal Modeling 137
Y. Hammi, T. Stone, H. Doude, L. Arias Tucker, P. G. Allison, and Mark F. Horstemeyer

6.1 Introduction 137

6.2 Material: Steel Alloy 137

6.3 ICME Modeling Methodology 139

6.3.1 Compaction 139

6.3.1.1 Macroscale Compaction Model 139

6.3.1.2 CompactionModel Calibration 146

6.3.1.3 Validation 146

6.3.1.4 CompactionModel Sensitivity and Uncertainty Analysis 148

6.3.2 Sintering 151

6.3.2.1 Atomistic 152

6.3.2.2 Theory and Simulations 152

6.3.2.3 Sintering Structure–Property Relations 155

6.3.2.4 Sintering ConstitutiveModeling 160

6.3.2.5 SinteringModel Implementation and Calibration 163

6.3.2.6 Sintering Validation for an Automotive Main Bearing Cap 165

6.3.3 Performance/Durability 165

6.3.3.1 Monotonic Conditions 167

6.3.3.2 Plasticity-Damage Structure–Property Relations 167

6.3.3.3 Plasticity-DamageModel and Calibration 168

6.3.3.4 Validation and Uncertainty 173

6.3.3.5 Main Bearing Cap 174

6.3.3.6 Fatigue 176

6.3.4 Optimization 188

6.3.4.1 Design of Experiments (DOE) 189

6.3.4.2 Results and Discussion 191

6.4 Summary 193

References 194

7 Microstructure-Sensitive, History-Dependent Internal State Variable Plasticity-Damage Model for a Sequential Tubing Process 199
H. E. Cho, Y. Hammi, D. K. Francis, T. Stone, Y. Mao, K. Sullivan, J.Wilbanks, R. Zelinka, and Mark F. Horstemeyer

7.1 Introduction 199

7.2 Internal State Variable (ISV) Plasticity-DamageModel 202

7.2.1 History Effects 202

7.2.2 Constitutive Equations 202

7.3 Simulation Setups 207

7.4 Results 209

7.4.1 ISV Plasticity-DamageModel Calibration and Validation 209

7.4.2 Simulations of the Forming Process (Step 1) 210

7.4.3 Simulations of Sizing Process (Step 3) 213

7.4.4 Simulations of First Annealing Process (Step 4) 217

7.4.5 Simulations of Drawing Processes (Steps 5 and 6) 225

7.4.6 Simulations of Second Annealing Process (Step 7) 230

7.5 Conclusions 232

References 233

Section II Hexagonal Close Packed (HCP) Materials 235

8 Electrons to Phases of Magnesium 237
Bi-Cheng Zhou,William YiWang, Zi-Kui Liu, and Raymundo Arroyave

8.1 Introduction 237

8.2 Criteria for the Design of Advanced Mg Alloys 238

8.3 Fundamentals of the ICME Approach Designing the Advanced Mg Alloys 238

8.3.1 Roadmap of ICME Approach 238

8.3.2 Fundamentals of Computational Thermodynamics 239

8.3.3 Electronic Structure Calculations of Materials Properties 241

8.3.3.1 First-Principles Calculations for Finite Temperatures 242

8.3.3.2 First-Principles Calculations of Solid Solution Phase 244

8.3.3.3 First-Principles Calculations of Interfacial (Cohesive) Energy 245

8.3.3.4 Equation of States (EOSs) and Elastic Moduli 245

8.3.3.5 Deformation Electron Density 246

8.3.3.6 Diffusion Coefficient 246

8.4 Data-DrivenMg Alloy Design – Application of ICME Approach 248

8.4.1 Electronic Structure 248

8.4.2 Thermodynamic Properties 253

8.4.3 Phase Stability and Phase Diagrams 253

8.4.3.1 Database Development 253

8.4.3.2 Application of CALPHAD in Mg Alloy Design 255

8.4.4 Kinetic Properties 260

8.4.5 Mechanical Properties 262

8.4.5.1 Elastic Constants 262

8.4.5.2 Stacking Fault Energy and Ideal Strength Impacted by Alloying Elements 265

8.4.5.3 Prismatic and Pyramidal Slips Activated by Lattice Distortion 270

8.5 Outlook/Future Trends 272

Acknowledgments 272

References 273

9 Multiscale Statistical Study of Twinning in HCP Metals 283
C.N. Tomé, I.J. Beyerlein, R.J. McCabe, and J.Wang

9.1 Introduction 283

9.2 Crystal Plasticity Modeling of Slip and Twinning 286

9.2.1 Crystal Plasticity Models 288

9.2.2 Incorporating Twinning Into Crystal Plasticity Formulations 290

9.2.3 Incorporating Hardening into Crystal Plasticity Formulations 294

9.3 Introducing Lower Length Scale Statistics in Twin Modeling 300

9.3.1 The Atomic Scale 301

9.3.2 Mesoscale Statistical Characterization of Twinning 302

9.3.3 Mesoscale StatisticalModeling of Twinning 305

9.3.3.1 Stochastic Model for Twinning 306

9.3.3.2 Stress Associated with Twin Nucleation 308

9.3.3.3 Stress Associated with Twin Growth 311

9.4 Model Implementation 312

9.4.1 Comparison with Bulk Measurements 314

9.4.2 Comparison with Statistical Data from EBSD 318

9.5 The Continuum Scale 322

9.5.1 Bending Simulations of Zr Bars 324

9.6 Summary 330

Acknowledgment 331

References 331

10 Cast Magnesium Alloy Corvette Engine Cradle 337
Haley Doude, David Oglesby, Philipp M. Gullett, Haitham El Kadiri, Bohumir Jelinek,Michael I. Baskes, Andrew Oppedal, Youssef Hammi, and Mark F. Horstemeyer

10.1 Introduction 337

10.2 Modeling Philosophy 338

10.3 Multiscale Continuum Microstructure-Property Internal State Variable (ISV) Model 340

10.4 Electronic Structures 340

10.5 Atomistic Simulations for Magnesium Using the Modified Embedded Atom Method (MEAM) Potential 341

10.5.1 MEAM Calibration for Magnesium 342

10.5.2 MEAM Validation for Magnesium 342

10.5.3 Atomistic Simulations of Mg–Al in Monotonic Loadings 343

10.6 Mesomechanics: Void Growth and Coalescence 347

10.6.1 Mesomechanical Simulation MaterialModel for Cylindrical and Spherical Voids 350

10.6.2 Mesomechanical Finite Element Cylindrical and Spherical Voids Results 350

10.6.3 Discussion of Cylindrical and Spherical Voids 351

10.7 Macroscale Modeling and Experiments 353

10.7.1 Plasticity-Damage Internal State Variable (ISV) Model 353

10.7.2 Macroscale Plasticity-Damage Internal State Variable (ISV) Model Calibration 356

10.7.3 Macroscale Microstructure-Property ISV Model Validation Experiments on AM60B: Notch Specimens 363

10.7.3.1 Finite Element Setup 365

10.7.3.2 ISV Model Validation Simulations with Notch Test Data 365

10.8 Structural-Scale Corvette Engine Cradle Analysis 366

10.8.1 Cradle Finite Element Model 366

10.8.2 Cradle Porosity Distribution Mapping 367

10.8.3 Structural-Scale Modeling Results 369

10.8.4 Corvette Engine Cradle Experiments 370

10.9 Summary 372

References 373

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 377
Marco Lugo,WilburnWhittington, Youssef Hammi, Clémence Bouvard, Bin Li, David K. Francis, Paul T.Wang, and Mark F. Horstemeyer

11.1 Introduction 377

11.2 Integrated Computational Materials Engineering and Design 379

11.2.1 Processing–Structure–Property Relationships and Design 380

11.2.2 Integrated Computational Materials Engineering (ICME) and MultiscaleModeling 382

11.2.3 Overview of the Internal State Variable (ISV)–Multistage Fatigue (MSF) 383

11.3 Mechanical and Microstructure Analysis of a Cast AZ91 Mg Alloy Shock Tower 385

11.3.1 Shock Tower Microstructure Characterization 386

11.3.2 Shock Tower Monotonic Mechanical Behavior 387

11.3.3 Fatigue Behavior of an AZ91 Mg Alloy 389

11.3.3.1 Strain-life Fatigue Behavior for an AZ91 Mg Alloy 389

11.3.3.2 Fractographic Analysis 391

11.4 A Microstructure-Sensitive Internal State Variable (ISV) Plasticity-DamageModel 391

11.5 Microstructure-SensitiveMultistage Fatigue (MSF) Model for an AZ91 Mg Alloy 393

11.5.1 The Multistage Fatigue (MSF) Model 394

11.5.1.1 Incubation Regime 394

11.5.1.2 Microstructurally Small Crack (MSC) Growth Regime 395

11.5.2 Calibration of the MSF Model for the AZ91 Alloy 396

11.6 Internal State Variable (ISV)–Multistage Fatigue (MSF) Model Finite Element Simulations 398

11.6.1 Finite ElementModel 398

11.6.2 Shock Tower Distribution Mapping of Microstructural Properties 399

11.6.3 Finite Element Simulations 401

11.6.3.1 Case 1 Homogeneous Material State Calculation (FEA #1) 401

11.6.3.2 Case 4 Heterogeneous Porosity Calculation (FEA #5) 401

11.6.3.3 Case 3 Heterogeneous Pore Size Calculation (FEA #4) 401

11.6.3.4 Case 2 Heterogeneous Material State Calculation (FEA #2) 402

11.6.4 Fatigue Tests and Finite Element Results 402

11.7 Summary 406

References 407

Section III Face-Centered Cubic (FCC) Materials 411

12 Electronic Structures and Materials Properties Calculations of Ni and Ni-Based Superalloys 413
Chelsey Z. Hargather, ShunLi Shang, and Zi-Kui Liu

12.1 Introduction 413

12.2 Designing the Next Generation of Ni-Base Superalloys Using the ICME Approach 414

12.3 Density FunctionalTheory as the Basis for an ICME Approach to Ni-Base Superalloy Development 416

12.3.1 Fundamental Concepts of Density FunctionalTheory 416

12.3.2 Fundamentals ofThermodynamic Modeling (the CALPHAD Approach) 419

12.4 Theoretical Background and Computational Procedure 421

12.4.1 First-Principles Calculation of Elastic Constants 421

12.4.2 First-Principles Calculations of Stacking Fault Energy 422

12.4.3 First-Principles Calculations of Dilute Impurity Diffusion Coefficients 423

12.4.4 Finite-Temperature First-Principles Calculations 426

12.4.5 Computational Details as Implemented in VASP 427

12.5 Ni-Base Superalloy Design using the ICME Approach 427

12.5.1 Finite Temperature Thermodynamics 427

12.5.1.1 Application to CALPHAD Modeling 428

12.5.2 Mechanical Properties 430

12.5.2.1 Elastic Constants Calculations 430

12.5.2.2 Stacking Fault Energy Calculations 431

12.5.3 Diffusion Coefficients 433

12.5.4 Designing Ni-Base Superalloy Systems Using the ICME Approach 434

12.5.4.1 CALPHAD Modeling used for Ni-Base Superalloy Design 434

12.5.4.2 Using a Mechanistic Model to Predict a Relative Creep Rates in Ni-X Alloys 438

12.6 Conclusions and Future Directions 440

Acknowledgments 441

References 441

13 Nickel Powder Metal Modeling Illustrating Atomistic-Continuum Friction Laws 447
T. Stone and Y. Hammi

13.1 Introduction 447

13.2 ICME Modeling Methodology 447

13.2.1 Compaction 447

13.2.2 Macroscale Plasticity Model for PowderMetals 448

13.3 Atomistic Studies 452

13.3.1 SimulationMethod and Setup 452

13.3.2 Simulation Results and Discussion 455

13.4 Summary 461

References 462

14 Multiscale Modeling of Pure Nickel 465
S.A. Brauer, I. Aslam, A. Bowman, B. Huddleston, J. Hughes, D. Johnson,W.B. Lawrimore II, L.A. Peterson,W. Shelton, and Mark F. Horstemeyer

14.1 Introduction 465

14.2 Bridge 1: Electronics to Atomistics and Bridge 4: Electronics to the Continuum 468

14.2.1 Electronics Principles Calibration Using Density FunctionalTheory (DFT) 470

14.2.2 Density FunctionalTheory Background 470

14.2.3 Upscaling Information from DFT 472

14.2.3.1 Energy–Volume 473

14.2.3.2 Elastic Moduli 473

14.2.3.3 Generalized Stacking Fault Energy (GSFE) 473

14.2.3.4 Vacancy Formation Energy 474

14.2.3.5 Surface Formation Energy 474

14.2.4 MEAM Background and Theory 474

14.2.5 Validation of Atomistic Results Using the MEAM Potential 476

14.3 Bridge 2: Atomistics to Dislocation Dynamics and Bridge 5: Atomistics to the Continuum 478

14.3.1 Upscaling MEAM/LAMMPS to Determine the Dislocation Mobility 480

14.3.2 MEAM/LAMMPS Validation and Uncertainty 481

14.4 Bridge 3: Dislocation Dynamics to Crystal Plasticity and Bridge 6: Dislocation Dynamics to the Continuum 483

14.4.1 Dislocation Dynamics Background 483

14.4.2 Crystal Plasticity Background 487

14.4.3 Crystal Plasticity Voce Hardening Equation Calibration 489

14.4.4 Crystal Plasticity Finite Element Method to Determine the Polycrystalline Stress–strain Behavior 490

14.5 Bridge 7: Crystal Plasticity to the Continuum 493

14.5.1 Macroscale Constitutive Model Calibration 499

14.6 Bridge 8: Macroscale Calibration to Structural Scale Simulations 500

14.6.1 Validation of Multiscale Methodology 503

14.6.2 Experimental and Simulation Results 504

14.7 Summary 505

Acknowledgments 506

References 506

Section IV Design of Materials and Structures 513

15 Predicting Constitutive Equations for Materials Design: A Conceptual Exposition 515
Chung H. Goh, Adam P. Dachowicz, Peter C. Collins, Janet K. Allen, and FarrokhMistree

15.1 Introduction 515

15.2 Frame of Reference 516

15.3 Critical Review of the Literature 518

15.3.1 Constitutive Equation (CEQ) 518

15.3.2 Various Types of Power-Law Flow Rules in CP Algorithm 519

15.3.3 Comparison of FEM versus VFM 520

15.3.4 AI-based KDD Process 521

15.4 Crystal Plasticity-Based Virtual Experiment Model 522

15.4.1 Description of CPVEM 522

15.4.2 Various Types of Power-Law Flow Rules 523

15.5 Hierarchical Strategy for Developing a Constitutive EQuation (CEQ) ExpansionModel 524

15.5.1 ComputationalModel for Developing a CEQ ExpansionModel 524

15.5.1.1 CPVEM for Predicting CEQ Patterns 525

15.5.1.2 Identifying CEQ Patterns for TAV 526

15.5.1.3 Virtual FieldsMethod (VFM) Model for Predicting Material Properties for New Ti-Al-X (TAX) Materials 527

15.5.2 Big Data Control Based on Ontology Integration 528

15.6 Closing Remarks 531 Nomenclature 533

Acknowledgments 534

References 534

16 A Computational Method for the Design of Materials Accounting for the Process–Structure–Property– Performance(PSPP) Relationship 539
Chung H. Goh, Adam P. Dachowicz, Janet K. Allen, and FarrokhMistree

16.1 Introduction 539

16.2 Frame of Reference 540

16.3 IntegratedMultiscale Robust Design (IMRD) 542

16.4 Roll Pass Design 544

16.4.1 Roll Pass Sequence and Design Parameters 545

16.4.2 Flow Stress Prediction Model 548

16.4.3 Wear Coefficient 549

16.5 Microstructure Evolution Model 549

16.5.1 Recrystallization 550

16.5.2 Austenite Grain Size (AGS) Prediction 551

16.5.3 Ferrite Grain Size (FGS) Prediction 554

16.6 Exploring the Feasible Solution Space 555

16.6.1 Developing Roll Pass Design and The Analysis and FE Models 556

16.6.2 DevelopingModules andTheir Corresponding Model Descriptions 557

16.6.2.1 Module 1. AGS Prediction Model (f1) 557

16.6.2.2 Module 2. FGS Prediction Model (f2) 557

16.6.2.3 Module 3. Structure–Property Correlation 557

16.6.2.4 Module 4. Property–Performance Correlation 558

16.6.3 IMRD Step 1 in Figure 16.8: Deductive Exploration 559

16.6.4 IMRD Step 2 in Figure 16.8: Inductive Exploration 560

16.6.5 IMRD Step 3 in Figure 16.8: Trade-offs among Competing Goals 562

16.6.6 Exploration of Solution Space 562

16.7 Results and Discussion 563

16.8 Closing Remarks 568

Acknowledgments 569

Nomenclature 569

References 571

Section V Education 573

17 An Engineering Virtual Organization For CyberDesign (EVOCD): A Cyberinfrastructure for Integrated Computational Materials Engineering (ICME) 575
Tomasz Haupt, Nitin Sukhija, and Mark F. Horstemeyer

17.1 Introduction 575

17.2 Engineering Virtual Organization for CyberDesign 578

17.3 Functionality of EVOCD 580

17.3.1 Knowledge Management:Wiki 580

17.3.2 Repository of Codes 582

17.3.3 Repository of Data 583

17.3.4 OnlineModel Calibration Tools 585

17.3.4.1 DMGfit 588

17.3.4.2 MultiState Fatigue (MSF) 591

17.3.4.3 Modified Embedded Atom Method (MEAM) Parameter Calibration (MPC) 593

17.4 Protection of Intellectual Property 595

17.5 Cyberinfrastructure for EVOCD 598

17.5.1 User Interface 598

17.5.2 EVOCD Services 600

17.5.3 Service Integration 600

17.6 Conclusions 601

References 601

18 Integrated Computational Materials Engineering (ICME) Pedagogy 605
Nitin Sukhija, Tomasz Haupt, and Mark F. Horstemeyer

18.1 Introduction 605

18.2 Methodology 608

18.3 Course Curriculum 610

18.3.1 ICME for Design 611

18.3.2 Presentation and Team Formation 613

18.3.3 ICME Cyberinfrastructure and Basic Skills 613

18.3.4 Bridging Length Scales 614

18.3.4.1 Quantum Methods 614

18.3.4.2 Atomistic Methods 615

18.3.4.3 Dislocation Dynamics Methods 617

18.3.4.4 Crystal Plasticity 618

18.3.4.5 Macroscale Continuum Modeling 619

18.3.5 ICMEWiki Contributions 621

18.3.6 Grading and Evaluation 622

18.4 Assessment 623

18.5 Benefits or Relevance of the LearningMethodology 628

18.6 Conclusions and Future Directions 629

Acknowledgments 630

References 630

19 Summary 633
Mark F. Horstemeyer

19.1 Introduction 633

19.2 Chapter 1 ICME Definition: Takeaway Point 633

19.3 Chapter 2: Takeaway Point 634

19.4 Chapter 3: Takeaway Point 634

19.5 Chapter 4: Takeaway Point 634

19.6 Chapter 5: Takeaway Point 634

19.7 Chapter 6: Takeaway Point 634

19.8 Chapter 7: Takeaway Point 634

19.9 Chapter 8: Takeaway Point 635

19.10 Chapter 9: Takeaway Point 635

19.11 Chapter 10: Takeaway Point 635

19.12 Chapter 11: Takeaway Point 635

19.13 Chapter 12: Takeaway Point 635

19.14 Chapter 13: Takeaway Point 635

19.15 Chapter 14: Takeaway Point 636

19.16 Chapter 15: Takeaway Point 636

19.17 Chapter 16: Takeaway Point 636

19.18 Chapter 17: Takeaway Point 636

19.19 Chapter 18: Takeaway Point 636

19.20 ICME Future 637

19.20.1 ICME Future: Metals 637

19.20.2 ICME Future: Non-Metals 637

19.20.2.1 Polymers 637

19.20.2.2 Ceramics 639

19.20.2.3 Concrete 641

19.20.2.4 Biological Materials 641

19.20.2.5 Earth Materials 643

19.20.2.6 Space Materials 644

19.21 Summary 644

References 645

Index 647