Integrated Computational Materials Engineering (ICME) for Metals

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.

• List of Contributors xixForeword xxviiPreface xxix1 Definition of ICME 1Mark F. Horstemeyer and S. S. Sahay1.1 What ICME Is NOT 11.1.1 Adding Defects into a MechanicalTheory 11.1.2 Adding Microstructures to Finite Element Analysis (FEA) 21.1.3 Comparing Modeling Results to Structure–Property Experimental Results 21.1.4 Computational Materials 21.1.5 Design Materials for Manufacturing (Process–Structure–Property Relationships) 31.1.6 Simulation through the Process Chain 31.2 What ICME Is 41.2.1 Background 41.2.2 ICME Definition 51.2.3 Uncertainty 81.2.4 ICME Cyberinfrastructure 91.3 Industrial Perspective 101.4 Summary 15References 15Section I Body-Centered Cubic Materials 192 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. Horstemeyer2.1 Introduction 212.2 Methods 232.2.1 MEAM Calculations 242.2.2 DFT Calculations 242.3 Single-Element Potentials 252.3.1 Energy versus Volume Curves 252.3.1.1 Single-Element Material Properties 292.4 Construction of Fe–C Alloy Potential 292.5 Structural and Elastic Properties of Cementite 352.5.1 Single-Crystal Elastic Properties 362.5.2 Polycrystalline Elastic Properties 372.5.3 Surface Energies 372.5.4 Interstitial Energies 382.6 Properties of Hypothetical Crystal Structures 382.6.1 Energy versus Volume Curves for B1 and L12 Structures 382.6.2 Elastic Constants for B1 and L12 Structures 402.7 Thermal Properties of Cementite 402.7.1 Thermal Stability of Cementite 402.7.2 Melting Temperature Simulation 402.7.2.1 Preparation of Two-Phase Simulation Box 412.7.2.2 Two-Phase Simulation 412.8 Summary and Conclusions 44Acknowledgments 45References 453 Phase-Field Crystal Modeling: Integrating Density Functional Theory, Molecular Dynamics, and Phase-FieldModeling 49Mohsen Asle Zaeem and Ebrahim Asadi3.1 Introduction to Phase-Field and Phase-Field Crystal Modeling 493.2 Governing Equations of Phase-Field Crystal (PFC) Models Derived from Density FunctionalTheory (DFT) 533.2.1 One-Mode PFC model 533.2.2 Two-Mode PFC Model 553.3 PFC Model Parameters by Molecular Dynamics Simulations 573.4 Case Study: Solid–Liquid Interface Properties of Fe 593.5 Case Study: Grain Boundary Free Energy of Fe at Its Melting Point 633.6 Summary and Future Directions 65References 664 Simulating Dislocation Plasticity in BCCMetals by Integrating Fundamental Concepts with Macroscale Models 71Hojun Lim, Corbett C. Battaile, and Christopher R.Weinberger4.1 Introduction 714.2 Existing BCC Models 734.3 Crystal Plasticity Finite Element Model 854.4 Continuum-Scale Model 904.5 Engineering Scale Applications 924.6 Summary 99References 1015 Heat Treatment and Fatigue of a Carburized and Quench Hardened Steel Part 107Zhichao (Charlie)Li and B. Lynn Ferguson5.1 Introduction 1075.2 Modeling Phase Transformations and Mechanics of Steel Heat Treatment 1085.3 Data Required for Modeling Quench Hardening Process 1125.3.1 Dilatometry Data 1135.3.2 Mechanical Property Data 1145.3.3 Thermal Property Data 1145.3.4 Process Data 1145.3.5 Furnace Heating 1155.3.6 Gas Carburization 1165.3.7 Immersion Quenching 1165.4 Heat Treatment Simulation of a Gear 1185.4.1 Description of Gear Geometry, FEA Model, and Problem Statement 1195.4.2 Carburization and Air Cooling Modeling 1205.4.3 Quench Hardening Process Modeling 1225.4.4 Comparison of Model and Experimental Results 1285.4.5 Tooth Bending Fatigue Data and LoadingModel 1295.5 Summary 132References 1346 Steel Powder Metal Modeling 137Y. Hammi, T. Stone, H. Doude, L. Arias Tucker, P. G. Allison, and Mark F. Horstemeyer6.1 Introduction 1376.2 Material: Steel Alloy 1376.3 ICME Modeling Methodology 1396.3.1 Compaction 1396.3.1.1 Macroscale Compaction Model 1396.3.1.2 CompactionModel Calibration 1466.3.1.3 Validation 1466.3.1.4 CompactionModel Sensitivity and Uncertainty Analysis 1486.3.2 Sintering 1516.3.2.1 Atomistic 1526.3.2.2 Theory and Simulations 1526.3.2.3 Sintering Structure–Property Relations 1556.3.2.4 Sintering ConstitutiveModeling 1606.3.2.5 SinteringModel Implementation and Calibration 1636.3.2.6 Sintering Validation for an Automotive Main Bearing Cap 1656.3.3 Performance/Durability 1656.3.3.1 Monotonic Conditions 1676.3.3.2 Plasticity-Damage Structure–Property Relations 1676.3.3.3 Plasticity-DamageModel and Calibration 1686.3.3.4 Validation and Uncertainty 1736.3.3.5 Main Bearing Cap 1746.3.3.6 Fatigue 1766.3.4 Optimization 1886.3.4.1 Design of Experiments (DOE) 1896.3.4.2 Results and Discussion 1916.4 Summary 193References 1947 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. Horstemeyer7.1 Introduction 1997.2 Internal State Variable (ISV) Plasticity-DamageModel 2027.2.1 History Effects 2027.2.2 Constitutive Equations 2027.3 Simulation Setups 2077.4 Results 2097.4.1 ISV Plasticity-DamageModel Calibration and Validation 2097.4.2 Simulations of the Forming Process (Step 1) 2107.4.3 Simulations of Sizing Process (Step 3) 2137.4.4 Simulations of First Annealing Process (Step 4) 2177.4.5 Simulations of Drawing Processes (Steps 5 and 6) 2257.4.6 Simulations of Second Annealing Process (Step 7) 2307.5 Conclusions 232References 233Section II Hexagonal Close Packed (HCP) Materials 2358 Electrons to Phases of Magnesium 237Bi-Cheng Zhou,William YiWang, Zi-Kui Liu, and Raymundo Arroyave8.1 Introduction 2378.2 Criteria for the Design of Advanced Mg Alloys 2388.3 Fundamentals of the ICME Approach Designing the Advanced Mg Alloys 2388.3.1 Roadmap of ICME Approach 2388.3.2 Fundamentals of Computational Thermodynamics 2398.3.3 Electronic Structure Calculations of Materials Properties 2418.3.3.1 First-Principles Calculations for Finite Temperatures 2428.3.3.2 First-Principles Calculations of Solid Solution Phase 2448.3.3.3 First-Principles Calculations of Interfacial (Cohesive) Energy 2458.3.3.4 Equation of States (EOSs) and Elastic Moduli 2458.3.3.5 Deformation Electron Density 2468.3.3.6 Diffusion Coefficient 2468.4 Data-DrivenMg Alloy Design – Application of ICME Approach 2488.4.1 Electronic Structure 2488.4.2 Thermodynamic Properties 2538.4.3 Phase Stability and Phase Diagrams 2538.4.3.1 Database Development 2538.4.3.2 Application of CALPHAD in Mg Alloy Design 2558.4.4 Kinetic Properties 2608.4.5 Mechanical Properties 2628.4.5.1 Elastic Constants 2628.4.5.2 Stacking Fault Energy and Ideal Strength Impacted by Alloying Elements 2658.4.5.3 Prismatic and Pyramidal Slips Activated by Lattice Distortion 2708.5 Outlook/Future Trends 272Acknowledgments 272References 2739 Multiscale Statistical Study of Twinning in HCP Metals 283C.N. Tomé, I.J. Beyerlein, R.J. McCabe, and J.Wang9.1 Introduction 2839.2 Crystal Plasticity Modeling of Slip and Twinning 2869.2.1 Crystal Plasticity Models 2889.2.2 Incorporating Twinning Into Crystal Plasticity Formulations 2909.2.3 Incorporating Hardening into Crystal Plasticity Formulations 2949.3 Introducing Lower Length Scale Statistics in Twin Modeling 3009.3.1 The Atomic Scale 3019.3.2 Mesoscale Statistical Characterization of Twinning 3029.3.3 Mesoscale StatisticalModeling of Twinning 3059.3.3.1 Stochastic Model for Twinning 3069.3.3.2 Stress Associated with Twin Nucleation 3089.3.3.3 Stress Associated with Twin Growth 3119.4 Model Implementation 3129.4.1 Comparison with Bulk Measurements 3149.4.2 Comparison with Statistical Data from EBSD 3189.5 The Continuum Scale 3229.5.1 Bending Simulations of Zr Bars 3249.6 Summary 330Acknowledgment 331References 33110 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. Horstemeyer10.1 Introduction 33710.2 Modeling Philosophy 33810.3 Multiscale Continuum Microstructure-Property Internal State Variable (ISV) Model 34010.4 Electronic Structures 34010.5 Atomistic Simulations for Magnesium Using the Modified Embedded Atom Method (MEAM) Potential 34110.5.1 MEAM Calibration for Magnesium 34210.5.2 MEAM Validation for Magnesium 34210.5.3 Atomistic Simulations of Mg–Al in Monotonic Loadings 34310.6 Mesomechanics: Void Growth and Coalescence 34710.6.1 Mesomechanical Simulation MaterialModel for Cylindrical and Spherical Voids 35010.6.2 Mesomechanical Finite Element Cylindrical and Spherical Voids Results 35010.6.3 Discussion of Cylindrical and Spherical Voids 35110.7 Macroscale Modeling and Experiments 35310.7.1 Plasticity-Damage Internal State Variable (ISV) Model 35310.7.2 Macroscale Plasticity-Damage Internal State Variable (ISV) Model Calibration 35610.7.3 Macroscale Microstructure-Property ISV Model Validation Experiments on AM60B: Notch Specimens 36310.7.3.1 Finite Element Setup 36510.7.3.2 ISV Model Validation Simulations with Notch Test Data 36510.8 Structural-Scale Corvette Engine Cradle Analysis 36610.8.1 Cradle Finite Element Model 36610.8.2 Cradle Porosity Distribution Mapping 36710.8.3 Structural-Scale Modeling Results 36910.8.4 Corvette Engine Cradle Experiments 37010.9 Summary 372References 37311 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. Horstemeyer11.1 Introduction 37711.2 Integrated Computational Materials Engineering and Design 37911.2.1 Processing–Structure–Property Relationships and Design 38011.2.2 Integrated Computational Materials Engineering (ICME) and MultiscaleModeling 38211.2.3 Overview of the Internal State Variable (ISV)–Multistage Fatigue (MSF) 38311.3 Mechanical and Microstructure Analysis of a Cast AZ91 Mg Alloy Shock Tower 38511.3.1 Shock Tower Microstructure Characterization 38611.3.2 Shock Tower Monotonic Mechanical Behavior 38711.3.3 Fatigue Behavior of an AZ91 Mg Alloy 38911.3.3.1 Strain-life Fatigue Behavior for an AZ91 Mg Alloy 38911.3.3.2 Fractographic Analysis 39111.4 A Microstructure-Sensitive Internal State Variable (ISV) Plasticity-DamageModel 39111.5 Microstructure-SensitiveMultistage Fatigue (MSF) Model for an AZ91 Mg Alloy 39311.5.1 The Multistage Fatigue (MSF) Model 39411.5.1.1 Incubation Regime 39411.5.1.2 Microstructurally Small Crack (MSC) Growth Regime 39511.5.2 Calibration of the MSF Model for the AZ91 Alloy 39611.6 Internal State Variable (ISV)–Multistage Fatigue (MSF) Model Finite Element Simulations 39811.6.1 Finite ElementModel 39811.6.2 Shock Tower Distribution Mapping of Microstructural Properties 39911.6.3 Finite Element Simulations 40111.6.3.1 Case 1 Homogeneous Material State Calculation (FEA #1) 40111.6.3.2 Case 4 Heterogeneous Porosity Calculation (FEA #5) 40111.6.3.3 Case 3 Heterogeneous Pore Size Calculation (FEA #4) 40111.6.3.4 Case 2 Heterogeneous Material State Calculation (FEA #2) 40211.6.4 Fatigue Tests and Finite Element Results 40211.7 Summary 406References 407Section III Face-Centered Cubic (FCC) Materials 41112 Electronic Structures and Materials Properties Calculations of Ni and Ni-Based Superalloys 413Chelsey Z. Hargather, ShunLi Shang, and Zi-Kui Liu12.1 Introduction 41312.2 Designing the Next Generation of Ni-Base Superalloys Using the ICME Approach 41412.3 Density FunctionalTheory as the Basis for an ICME Approach to Ni-Base Superalloy Development 41612.3.1 Fundamental Concepts of Density FunctionalTheory 41612.3.2 Fundamentals ofThermodynamic Modeling (the CALPHAD Approach) 41912.4 Theoretical Background and Computational Procedure 42112.4.1 First-Principles Calculation of Elastic Constants 42112.4.2 First-Principles Calculations of Stacking Fault Energy 42212.4.3 First-Principles Calculations of Dilute Impurity Diffusion Coefficients 42312.4.4 Finite-Temperature First-Principles Calculations 42612.4.5 Computational Details as Implemented in VASP 42712.5 Ni-Base Superalloy Design using the ICME Approach 42712.5.1 Finite Temperature Thermodynamics 42712.5.1.1 Application to CALPHAD Modeling 42812.5.2 Mechanical Properties 43012.5.2.1 Elastic Constants Calculations 43012.5.2.2 Stacking Fault Energy Calculations 43112.5.3 Diffusion Coefficients 43312.5.4 Designing Ni-Base Superalloy Systems Using the ICME Approach 43412.5.4.1 CALPHAD Modeling used for Ni-Base Superalloy Design 43412.5.4.2 Using a Mechanistic Model to Predict a Relative Creep Rates in Ni-X Alloys 43812.6 Conclusions and Future Directions 440Acknowledgments 441References 44113 Nickel Powder Metal Modeling Illustrating Atomistic-Continuum Friction Laws 447T. Stone and Y. Hammi13.1 Introduction 44713.2 ICME Modeling Methodology 44713.2.1 Compaction 44713.2.2 Macroscale Plasticity Model for PowderMetals 44813.3 Atomistic Studies 45213.3.1 SimulationMethod and Setup 45213.3.2 Simulation Results and Discussion 45513.4 Summary 461References 46214 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. Horstemeyer14.1 Introduction 46514.2 Bridge 1: Electronics to Atomistics and Bridge 4: Electronics to the Continuum 46814.2.1 Electronics Principles Calibration Using Density FunctionalTheory (DFT) 47014.2.2 Density FunctionalTheory Background 47014.2.3 Upscaling Information from DFT 47214.2.3.1 Energy–Volume 47314.2.3.2 Elastic Moduli 47314.2.3.3 Generalized Stacking Fault Energy (GSFE) 47314.2.3.4 Vacancy Formation Energy 47414.2.3.5 Surface Formation Energy 47414.2.4 MEAM Background and Theory 47414.2.5 Validation of Atomistic Results Using the MEAM Potential 47614.3 Bridge 2: Atomistics to Dislocation Dynamics and Bridge 5: Atomistics to the Continuum 47814.3.1 Upscaling MEAM/LAMMPS to Determine the Dislocation Mobility 48014.3.2 MEAM/LAMMPS Validation and Uncertainty 48114.4 Bridge 3: Dislocation Dynamics to Crystal Plasticity and Bridge 6: Dislocation Dynamics to the Continuum 48314.4.1 Dislocation Dynamics Background 48314.4.2 Crystal Plasticity Background 48714.4.3 Crystal Plasticity Voce Hardening Equation Calibration 48914.4.4 Crystal Plasticity Finite Element Method to Determine the Polycrystalline Stress–strain Behavior 49014.5 Bridge 7: Crystal Plasticity to the Continuum 49314.5.1 Macroscale Constitutive Model Calibration 49914.6 Bridge 8: Macroscale Calibration to Structural Scale Simulations 50014.6.1 Validation of Multiscale Methodology 50314.6.2 Experimental and Simulation Results 50414.7 Summary 505Acknowledgments 506References 506Section IV Design of Materials and Structures 51315 Predicting Constitutive Equations for Materials Design: A Conceptual Exposition 515Chung H. Goh, Adam P. Dachowicz, Peter C. Collins, Janet K. Allen, and FarrokhMistree15.1 Introduction 51515.2 Frame of Reference 51615.3 Critical Review of the Literature 51815.3.1 Constitutive Equation (CEQ) 51815.3.2 Various Types of Power-Law Flow Rules in CP Algorithm 51915.3.3 Comparison of FEM versus VFM 52015.3.4 AI-based KDD Process 52115.4 Crystal Plasticity-Based Virtual Experiment Model 52215.4.1 Description of CPVEM 52215.4.2 Various Types of Power-Law Flow Rules 52315.5 Hierarchical Strategy for Developing a Constitutive EQuation (CEQ) ExpansionModel 52415.5.1 ComputationalModel for Developing a CEQ ExpansionModel 52415.5.1.1 CPVEM for Predicting CEQ Patterns 52515.5.1.2 Identifying CEQ Patterns for TAV 52615.5.1.3 Virtual FieldsMethod (VFM) Model for Predicting Material Properties for New Ti-Al-X (TAX) Materials 52715.5.2 Big Data Control Based on Ontology Integration 52815.6 Closing Remarks 531 Nomenclature 533Acknowledgments 534References 53416 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 FarrokhMistree16.1 Introduction 53916.2 Frame of Reference 54016.3 IntegratedMultiscale Robust Design (IMRD) 54216.4 Roll Pass Design 54416.4.1 Roll Pass Sequence and Design Parameters 54516.4.2 Flow Stress Prediction Model 54816.4.3 Wear Coefficient 54916.5 Microstructure Evolution Model 54916.5.1 Recrystallization 55016.5.2 Austenite Grain Size (AGS) Prediction 55116.5.3 Ferrite Grain Size (FGS) Prediction 55416.6 Exploring the Feasible Solution Space 55516.6.1 Developing Roll Pass Design and The Analysis and FE Models 55616.6.2 DevelopingModules andTheir Corresponding Model Descriptions 55716.6.2.1 Module 1. AGS Prediction Model (f1) 55716.6.2.2 Module 2. FGS Prediction Model (f2) 55716.6.2.3 Module 3. Structure–Property Correlation 55716.6.2.4 Module 4. Property–Performance Correlation 55816.6.3 IMRD Step 1 in Figure 16.8: Deductive Exploration 55916.6.4 IMRD Step 2 in Figure 16.8: Inductive Exploration 56016.6.5 IMRD Step 3 in Figure 16.8: Trade-offs among Competing Goals 56216.6.6 Exploration of Solution Space 56216.7 Results and Discussion 56316.8 Closing Remarks 568Acknowledgments 569Nomenclature 569References 571Section V Education 57317 An Engineering Virtual Organization For CyberDesign (EVOCD): A Cyberinfrastructure for Integrated Computational Materials Engineering (ICME) 575Tomasz Haupt, Nitin Sukhija, and Mark F. Horstemeyer17.1 Introduction 57517.2 Engineering Virtual Organization for CyberDesign 57817.3 Functionality of EVOCD 58017.3.1 Knowledge Management:Wiki 58017.3.2 Repository of Codes 58217.3.3 Repository of Data 58317.3.4 OnlineModel Calibration Tools 58517.3.4.1 DMGfit 58817.3.4.2 MultiState Fatigue (MSF) 59117.3.4.3 Modified Embedded Atom Method (MEAM) Parameter Calibration (MPC) 59317.4 Protection of Intellectual Property 59517.5 Cyberinfrastructure for EVOCD 59817.5.1 User Interface 59817.5.2 EVOCD Services 60017.5.3 Service Integration 60017.6 Conclusions 601References 60118 Integrated Computational Materials Engineering (ICME) Pedagogy 605Nitin Sukhija, Tomasz Haupt, and Mark F. Horstemeyer18.1 Introduction 60518.2 Methodology 60818.3 Course Curriculum 61018.3.1 ICME for Design 61118.3.2 Presentation and Team Formation 61318.3.3 ICME Cyberinfrastructure and Basic Skills 61318.3.4 Bridging Length Scales 61418.3.4.1 Quantum Methods 61418.3.4.2 Atomistic Methods 61518.3.4.3 Dislocation Dynamics Methods 61718.3.4.4 Crystal Plasticity 61818.3.4.5 Macroscale Continuum Modeling 61918.3.5 ICMEWiki Contributions 62118.3.6 Grading and Evaluation 62218.4 Assessment 62318.5 Benefits or Relevance of the LearningMethodology 62818.6 Conclusions and Future Directions 629Acknowledgments 630References 63019 Summary 633Mark F. Horstemeyer19.1 Introduction 63319.2 Chapter 1 ICME Definition: Takeaway Point 63319.3 Chapter 2: Takeaway Point 63419.4 Chapter 3: Takeaway Point 63419.5 Chapter 4: Takeaway Point 63419.6 Chapter 5: Takeaway Point 63419.7 Chapter 6: Takeaway Point 63419.8 Chapter 7: Takeaway Point 63419.9 Chapter 8: Takeaway Point 63519.10 Chapter 9: Takeaway Point 63519.11 Chapter 10: Takeaway Point 63519.12 Chapter 11: Takeaway Point 63519.13 Chapter 12: Takeaway Point 63519.14 Chapter 13: Takeaway Point 63519.15 Chapter 14: Takeaway Point 63619.16 Chapter 15: Takeaway Point 63619.17 Chapter 16: Takeaway Point 63619.18 Chapter 17: Takeaway Point 63619.19 Chapter 18: Takeaway Point 63619.20 ICME Future 63719.20.1 ICME Future: Metals 63719.20.2 ICME Future: Non-Metals 63719.20.2.1 Polymers 63719.20.2.2 Ceramics 63919.20.2.3 Concrete 64119.20.2.4 Biological Materials 64119.20.2.5 Earth Materials 64319.20.2.6 Space Materials 64419.21 Summary 644References 645Index 647