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

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

About the Author :
MARK F. HORSTEMEYER, PHD, is currently a professor in the Mechanical Engineering Department at Mississippi State University, holding a Chair position for the Center for Advanced Vehicular Systems (CAVS) in Computational Solid Mechanics, and is also a Giles Distinguished Professor at MSU.

Review :
"This book can serve multiple purposes including a graduate-level text-book on multiscale modeling, a one-stop reference for the practicing researcher, and a great starting point for a researcher who is undertaking the exciting journey of multiscale modeling research." ("Materials & Manufacturing Processes," 11 March 2015)