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

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

Horstemeyer, Mark F.

244,61 €(IVA inc.)

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. INDICE: List of Contributors xix .Foreword xxvii .Preface xxix .1 Definition of ICME 1Mark 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 21Laalitha 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 49Mohsen 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 71Hojun 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 107Zhichao (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 137Y. 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 199H. 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 237Bi–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 283C.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 337Haley 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 377Marco 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 413Chelsey 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 447T. 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 465S.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 515Chung 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 539Chung 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) 575Tomasz 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 605Nitin 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 633Mark 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

  • ISBN: 978-1-119-01836-0
  • Editorial: Wiley–Blackwell
  • Encuadernacion: Cartoné
  • Páginas: 688
  • Fecha Publicación: 07/05/2018
  • Nº Volúmenes: 1
  • Idioma: Inglés