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.
Table of Contents
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
