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

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  • ISBN-13: 9781119018391
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Integrated Computational Materials Engineering (ICME) for Metals: Concepts and Case StudiesSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 23-Feb-2018
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119018391
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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(18)
Mark F. Horstemeyer
Satyam Sahay
1.1 What ICME Is NOT
1(3)
1.1.1 Adding Defects into a Mechanical Theory
1(1)
1.1.2 Adding Microstructures to Finite Element Analysis (FEA)
2(1)
1.1.3 Comparing Modeling Results to Structure-Property Experimental Results
2(1)
1.1.4 Computational Materials
2(1)
1.1.5 Design Materials for Manufacturing (Process-Structure-Property Relationships)
3(1)
1.1.6 Simulation through the Process Chain
3(1)
1.2 What ICME Is
4(6)
1.2.1 Background
4(1)
1.2.2 ICME Definition
5(3)
1.2.3 Uncertainty
8(1)
1.2.4 ICME Cyberinfrastructure
9(1)
1.3 Industrial Perspective
10(5)
1.4 Summary
15(1)
References
15(4)
Section I Body-Centered Cubic Materials 19(216)
2 From Electrons to Atoms: Designing an Interatomic Potential for Fe-C Alloys
21(28)
Laalitha S.I. Liyanage
eong-Gon Kim
Jeff Houze
Sungho Kim
Mark A. Tschopp
Michael I. Baskes
Mark F. Horstemeyer
2.1 Introduction
21(2)
2.2 Methods
23(2)
2.2.1 MEAM Calculations
24(1)
2.2.2 DFT Calculations
24(1)
2.3 Single-Element Potentials
25(4)
2.3.1 Energy versus Volume Curves
25(1)
2.3.1.1 Single-Element Material Properties
29(1)
2.4 Construction of Fe-C Alloy Potential
29(6)
2.5 Structural and Elastic Properties of Cementite
35(3)
2.5.1 Single-Crystal Elastic Properties
36(1)
2.5.2 Polycrystalline Elastic Properties
37(1)
2.5.3 Surface Energies
37(1)
2.5.4 Interstitial Energies
38(1)
2.6 Properties of Hypothetical Crystal Structures
38(2)
2.6.1 Energy versus Volume Curves for B1 and L12 Structures
38(2)
2.6.2 Elastic Constants for B1 and L12 Structures
40(1)
2.7 Thermal Properties of Cementite
40(4)
2.7.1 Thermal Stability of Cementite
40(1)
2.7.2 Melting Temperature Simulation
40(1)
2.7.2.1 Preparation of Two-Phase Simulation Box
41(1)
2.7.2.2 Two-Phase Simulation
41(3)
2.8 Summary and Conclusions
44(1)
Acknowledgments
45(1)
References
45(4)
3 Phase-Field Crystal Modeling: Integrating Density Functional Theory, Molecular Dynamics, and Phase-Field Modeling
49(22)
Mohsen Asle Zaeem
Ebrahim Asadi
3.1 Introduction to Phase-Field and Phase-Field Crystal Modeling
49(4)
3.2 Governing Equations of Phase-Field Crystal (PFC) Models Derived from Density Functional Theory (DFT)
53(4)
3.2.1 One-Mode PFC model
53(2)
3.2.2 Two-Mode PFC Model
55(2)
3.3 PFC Model Parameters by Molecular Dynamics Simulations
57(2)
3.4 Case Study: Solid-Liquid Interface Properties of Fe
59(4)
3.5 Case Study: Grain Boundary Free Energy of Fe at Its Melting Point
63(2)
3.6 Summary and Future Directions
65(1)
References
66(5)
4 Simulating Dislocation Plasticity in BCC Metals by Integrating Fundamental Concepts with Macroscale Models
71(36)
Hojun Lim
Corbett C. Battaile
Christopher R. Weinberger
4.1 Introduction
71(2)
4.2 Existing BCC Models
73(12)
4.3 Crystal Plasticity Finite Element Model
85(5)
4.4 Continuum-Scale Model
90(2)
4.5 Engineering Scale Applications
92(7)
4.6 Summary
99(2)
References
101(6)
5 Heat Treatment and Fatigue of a Carburized and Quench Hardened Steel Part
107(30)
Zhichao Li
B. Lynn Ferguson
5.1 Introduction
107(1)
5.2 Modeling Phase Transformations and Mechanics of Steel Heat Treatment
108(4)
5.3 Data Required for Modeling Quench Hardening Process
112(6)
5.3.1 Dilatometry Data
113(1)
5.3.2 Mechanical Property Data
114(1)
5.3.3 Thermal Property Data
114(1)
5.3.4 Process Data
114(1)
5.3.5 Furnace Heating
115(1)
5.3.6 Gas Carburization
116(1)
5.3.7 Immersion Quenching
116(2)
5.4 Heat Treatment Simulation of a Gear
118(14)
5.4.1 Description of Gear Geometry, FEA Model, and Problem Statement
119(1)
5.4.2 Carburization and Air Cooling Modeling
120(2)
5.4.3 Quench Hardening Process Modeling
122(6)
5.4.4 Comparison of Model and Experimental Results
128(1)
5.4.5 Tooth Bending Fatigue Data and Loading Model
129(3)
5.5 Summary
132(2)
References
134(3)
6 Steel Powder Metal Modeling
137(62)
Youssef Hammi
Tonya Stone
Haley Doude
L. Arias Tucker
P.G. Allison
Mark F. Horstemeyer
6.1 Introduction
137(1)
6.2 Material: Steel Alloy
137(2)
6.3 ICME Modeling Methodology
139(54)
6.3.1 Compaction
139(1)
6.3.1.1 Macroscale Compaction Model
139(1)
6.3.1.2 Compaction Model Calibration
146(1)
6.3.1.3 Validation
146(1)
6.3.1.4 Compaction Model Sensitivity and Uncertainty Analysis
148(3)
6.3.2 Sintering
151(1)
6.3.2.1 Atomistic
152(1)
6.3.2.2 Theory and Simulations
152(1)
6.3.2.3 Sintering Structure-Property Relations
155(1)
6.3.2.4 Sintering Constitutive Modeling
160(1)
6.3.2.5 Sintering Model Implementation and Calibration
163(1)
6.3.2.6 Sintering Validation for an Automotive Main Bearing Cap
165(1)
6.3.3 Performance/Durability
165(1)
6.3.3.1 Monotonic Conditions
167(1)
6.3.3.2 Plasticity-Damage Structure-Property Relations
167(1)
6.3.3.3 Plasticity-Damage Model and Calibration
168(1)
6.3.3.4 Validation and Uncertainty
173(1)
6.3.3.5 Main Bearing Cap
174(1)
6.3.3.6 Fatigue
176(12)
6.3.4 Optimization
188(1)
6.3.4.1 Design of Experiments (DOE)
189(1)
6.3.4.2 Results and Discussion
191(2)
6.4 Summary
193(1)
References
194(5)
7 Microstructure-Sensitive, History-Dependent Internal State Variable Plasticity-Damage Model for a Sequential Tubing Process
199(36)
Heechen E. Cho
Youssef Hammi
David K. Francis
Tonya Stone
Yuxiong Mao
Ken Sullivan
John Wilbanks
Robert Zelinka
Mark F. Horstemeyer
7.1 Introduction
199(3)
7.2 Internal State Variable (ISV) Plasticity-Damage Model
202(5)
7.2.1 History Effects
202(1)
7.2.2 Constitutive Equations
202(5)
7.3 Simulation Setups
207(2)
7.4 Results
209(23)
7.4.1 ISV Plasticity-Damage Model Calibration and Validation
209(1)
7.4.2 Simulations of the Forming Process (Step 1)
210(3)
7.4.3 Simulations of Sizing Process (Step 3)
213(4)
7.4.4 Simulations of First Annealing Process (Step 4)
217(8)
7.4.5 Simulations of Drawing Processes (Steps 5 and 6)
225(5)
7.4.6 Simulations of Second Annealing Process (Step 7)
230(2)
7.5 Conclusions
232(1)
References
233(2)
Section II Hexagonal Close Packed (HCP) Materials 235(176)
8 Electrons to Phases of Magnesium
237(46)
Bi-Cheng Zhou
William Yi Wang
Zi-Kui Liu
Raymundo Arroyave
8.1 Introduction
237(1)
8.2 Criteria for the Design of Advanced Mg Alloys
238(1)
8.3 Fundamentals of the ICME Approach Designing the Advanced Mg Alloys
238(10)
8.3.1 Roadmap of ICME Approach
238(1)
8.3.2 Fundamentals of Computational Thermodynamics
239(2)
8.3.3 Electronic Structure Calculations of Materials Properties
241(1)
8.3.3.1 First-Principles Calculations for Finite Temperatures
242(1)
8.3.3.2 First-Principles Calculations of Solid Solution Phase
244(1)
8.3.3.3 First-Principles Calculations of Interfacial Energy
245(1)
8.3.3.4 Equation of States (EOSs) and Elastic Moduli
245(1)
8.3.3.5 Deformation Electron Density
246(1)
8.3.3.6 Diffusion Coefficient
246(2)
8.4 Data-Driven Mg Alloy Design - Application of ICME Approach
248(24)
8.4.1 Electronic Structure
248(5)
8.4.2 Thermodynamic Properties
253(1)
8.4.3 Phase Stability and Phase Diagrams
253(1)
8.4.3.1 Database Development
253(1)
8.4.3.2 Application of CALPHAD in Mg Alloy Design
255(5)
8.4.4 Kinetic Properties
260(2)
8.4.5 Mechanical Properties
262(1)
8.4.5.1 Elastic Constants
262(1)
8.4.5.2 Stacking Fault Energy and Ideal Strength Impacted by Alloying Elements
265(1)
8.4.5.3 Prismatic and Pyramidal Slips Activated by Lattice Distortion
270(2)
8.5 Outlook/Future Trends
272(1)
Acknowledgments
272(1)
References
273(10)
9 Multiscale Statistical Study of Twinning in HCP Metals
283(54)
Carlos N. Tome
Irene J. Beyerlein
Rodney J. McCabe
Jian Wang
9.1 Introduction
283(3)
9.2 Crystal Plasticity Modeling of Slip and Twinning
286(14)
9.2.1 Crystal Plasticity Models
288(2)
9.2.2 Incorporating Twinning Into Crystal Plasticity Formulations
290(4)
9.2.3 Incorporating Hardening into Crystal Plasticity Formulations
294(6)
9.3 Introducing Lower Length Scale Statistics in Twin Modeling
300(12)
9.3.1 The Atomic Scale
301(1)
9.3.2 Mesoscale Statistical Characterization of Twinning
302(3)
9.3.3 Mesoscale Statistical Modeling of Twinning
305(1)
9.3.3.1 Stochastic Model for Twinning
306(1)
9.3.3.2 Stress Associated with Twin Nucleation
308(1)
9.3.3.3 Stress Associated with Twin Growth
311(1)
9.4 Model Implementation
312(10)
9.4.1 Comparison with Bulk Measurements
314(4)
9.4.2 Comparison with Statistical Data from EBSD
318(4)
9.5 The Continuum Scale
322(8)
9.5.1 Bending Simulations of Zr Bars
324(6)
9.6 Summary
330(1)
Acknowledgment
331(1)
References
331(6)
10 Cast Magnesium Alloy Corvette Engine Cradle
337(40)
Haley Doude
David Oglesby
Philipp M. Gullett
Haitham El Kadiri
Bohumir Jelinek
Michael I. Baskes
Andrew Oppedal
Youssef Hammi
Mark F. Horstemeyer
10.1 Introduction
337(1)
10.2 Modeling Philosophy
338(2)
10.3 Multiscale Continuum Microstructure-Property Internal State Variable (ISV) Model
340(1)
10.4 Electronic Structures
340(1)
10.5 Atomistic Simulations for Magnesium Using the Modified Embedded Atom Method (MEAM) Potential
341(6)
10.5.1 MEAM Calibration for Magnesium
342(1)
10.5.2 MEAM Validation for Magnesium
342(1)
10.5.3 Atomistic Simulations of Mg-Al in Monotonic Loadings
343(4)
10.6 Mesomechanics: Void Growth and Coalescence
347(6)
10.6.1 Mesomechanical Simulation Material Model for Cylindrical and Spherical Voids
350(1)
10.6.2 Mesomechanical Finite Element Cylindrical and Spherical Voids Results
350(1)
10.6.3 Discussion of Cylindrical and Spherical Voids
351(2)
10.7 Macroscale Modeling and Experiments
353(13)
10.7.1 Plasticity-Damage Internal State Variable (ISV) Model
353(3)
10.7.2 Macroscale Plasticity-Damage Internal State Variable (ISV) Model Calibration
356(7)
10.7.3 Macroscale Microstructure-Property ISV Model Validation Experiments on AM60B: Notch Specimens
363(1)
10.7.3.1 Finite Element Setup
365(1)
10.7.3.2 ISV Model Validation Simulations with Notch Test Data
365(1)
10.8 Structural-Scale Corvette Engine Cradle Analysis
366(6)
10.8.1 Cradle Finite Element Model
366(1)
10.8.2 Cradle Porosity Distribution Mapping
367(2)
10.8.3 Structural-Scale Modeling Results
369(1)
10.8.4 Corvette Engine Cradle Experiments
370(2)
10.9 Summary
372(1)
References
373(4)
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(34)
Marco Lugo
Wilburn Whittington
Youssef Hammi
Clemence Bouvard
Bin Li
David K. Francis
Paul T. Wang
Mark F. Horstemeyer
11.1 Introduction
377(2)
11.2 Integrated Computational Materials Engineering and Design
379(6)
11.2.1 Processing-Structure-Property Relationships and Design
380(2)
11.2.2 Integrated Computational Materials Engineering (ICME) and Multiscale Modeling
382(1)
11.2.3 Overview of the Internal State Variable (ISV)-Multistage Fatigue (MSF)
383(2)
11.3 Mechanical and Microstructure Analysis of a Cast AZ91 Mg Alloy Shock Tower
385(6)
11.3.1 Shock Tower Microstructure Characterization
386(1)
11.3.2 Shock Tower Monotonic Mechanical Behavior
387(2)
11.3.3 Fatigue Behavior of an AZ91 Mg Alloy
389(1)
11.3.3.1 Strain-life Fatigue Behavior for an AZ91 Mg Alloy
389(1)
11.3.3.2 Fractographic Analysis
391(1)
11.4 A Microstructure-Sensitive Internal State Variable (ISV) Plasticity-Damage Model
391(2)
11.5 Microstructure-Sensitive Multistage Fatigue (MSF) Model for an AZ91 Mg Alloy
393(5)
11.5.1 The Multistage Fatigue (MSF) Model
394(1)
11.5.1.1 Incubation Regime
394(1)
11.5.1.2 Microstructurally Small Crack (MSC) Growth Regime
395(1)
11.5.2 Calibration of the MSF Model for the AZ91 Alloy
396(2)
11.6 Internal State Variable (ISV)-Multistage Fatigue (MSF) Model Finite Element Simulations
398(8)
11.6.1 Finite Element Model
398(1)
11.6.2 Shock Tower Distribution Mapping of Microstructural Properties
399(2)
11.6.3 Finite Element Simulations
401(1)
11.6.3.1 Case 1 Homogeneous Material State Calculation (FEA #1)
401(1)
11.6.3.2 Case 2 Heterogeneous Porosity Calculation (FEA #5)
401(1)
11.6.3.3 Case 3 Heterogeneous Pore Size Calculation (FEA #4)
401(1)
11.6.3.4 Case 4 Heterogeneous Material State Calculation (FEA #2)
402(1)
11.6.4 Fatigue Tests and Finite Element Results
402(4)
11.7 Summary
406(1)
References
407(4)
Section III Face-Centered Cubic (FCC) Materials 411(102)
12 Electronic Structures and Materials Properties Calculations of Ni and Ni-Based Superalloys
413(34)
Chelsey Z. Hargather
ShunLi Shang
Zi-Kui Liu
12.1 Introduction
413(1)
12.2 Designing the Next Generation of Ni-Base Superalloys Using the ICME Approach
414(2)
12.3 Density Functional Theory as the Basis for an ICME Approach to Ni-Base Superalloy Development
416(5)
12.3.1 Fundamental Concepts of Density Functional Theory
416(3)
12.3.2 Fundamentals of Thermodynamic Modeling (the CALPHAD Approach)
419(2)
12.4 Theoretical Background and Computational Procedure
421(6)
12.4.1 First-Principles Calculation of Elastic Constants
421(1)
12.4.2 First-Principles Calculations of Stacking Fault Energy
422(1)
12.4.3 First-Principles Calculations of Dilute Impurity Diffusion Coefficients
423(3)
12.4.4 Finite-Temperature First-Principles Calculations
426(1)
12.4.5 Computational Details as Implemented in VASP
427(1)
12.5 Ni-Base Superalloy Design using the ICME Approach
427(13)
12.5.1 Finite Temperature Thermodynamics
427(1)
12.5.1.1 Application to CALPHAD Modeling
428(2)
12.5.2 Mechanical Properties
430(1)
12.5.2.1 Elastic Constants Calculations
430(1)
12.5.2.2 Stacking Fault Energy Calculations
431(2)
12.5.3 Diffusion Coefficients
433(1)
12.5.4 Designing Ni-Base Superalloy Systems Using the ICME Approach
434(1)
12.5.4.1 CALPHAD Modeling used for Ni-Base Superalloy Design
434(1)
12.5.4.2 Using a Mechanistic Model to Predict a Relative Creep Rates in Ni-X Alloys
438(2)
12.6 Conclusions and Future Directions
440(1)
Acknowledgments
441(1)
References
441(6)
13 Nickel Powder Metal Modeling Illustrating Atomistic-Continuum Friction Laws
447(18)
Tonya Stone
Youssef Hammi
13.1 Introduction
447(1)
13.2 ICME Modeling Methodology
447(5)
13.2.1 Compaction
447(1)
13.2.2 Macroscale Plasticity Model for Powder Metals
448(4)
13.3 Atomistic Studies
452(9)
13.3.1 Simulation Method and Setup
452(3)
13.3.2 Simulation Results and Discussion
455(6)
13.4 Summary
461(1)
References
462(3)
14 Multiscale Modeling of Pure Nickel
465(48)
Shane A. Brauer
Imran Aslam
Andrew Bowman
Bradley Huddleston
Justin Huges
Daniel Johnson
William B. Lawrimore
Luke A. Peterson
William Shelton
Mark F. Horstemeyer
14.1 Introduction
465(3)
14.2 Bridge 1: Electronics to Atomistics and Bridge 4: Electronics to the Continuum
468(10)
14.2.1 Electronics Principles Calibration Using Density Functional Theory (DFT)
470(1)
14.2.2 Density Functional Theory Background
470(2)
14.2.3 Upscaling Information from DFT
472(1)
14.2.3.1 Energy-Volume
473(1)
14.2.3.2 Elastic Moduli
473(1)
14.2.3.3 Generalized Stacking Fault Energy (GSFE)
473(1)
14.2.3.4 Vacancy Formation Energy
474(1)
14.2.3.5 Surface Formation Energy
474(1)
14.2.4 MEAM Background and Theory
474(2)
14.2.5 Validation of Atomistic Results Using the MEAM Potential
476(2)
14.3 Bridge 2: Atomistics to Dislocation Dynamics and Bridge 5: Atomistics to the Continuum
478(5)
14.3.1 Upscaling MEAM/LAMMPS to Determine the Dislocation Mobility
480(1)
14.3.2 MEAM/LAMMPS Validation and Uncertainty
481(2)
14.4 Bridge 3: Dislocation Dynamics to Crystal Plasticity and Bridge 6: Dislocation Dynamics to the Continuum
483(10)
14.4.1 Dislocation Dynamics Background
483(4)
14.4.2 Crystal Plasticity Background
487(2)
14.4.3 Crystal Plasticity Voce Hardening Equation Calibration
489(1)
14.4.4 Crystal Plasticity Finite Element Method to Determine the Polycrystalline Stress-strain Behavior
490(3)
14.5 Bridge 7: Crystal Plasticity to the Continuum
493(7)
14.5.1 Macroscale Constitutive Model Calibration
499(1)
14.6 Bridge 8: Macroscale Calibration to Structural Scale Simulations
500(5)
14.6.1 Validation of Multiscale Methodology
503(1)
14.6.2 Experimental and Simulation Results
504(1)
14.7 Summary
505(1)
Acknowledgments
506(1)
References
506(7)
Section IV Design of Materials and Structures 513(60)
15 Predicting Constitutive Equations for Materials Design: A Conceptual Exposition
515(24)
Chung-Hyun Goh
Adam P. Dachowicz
Peter C. Collins
Janet K. Allen
Farrokh Mistree
15.1 Introduction
515(1)
15.2 Frame of Reference
516(2)
15.3 Critical Review of the Literature
518(4)
15.3.1 Constitutive Equation (CEQ)
518(1)
15.3.2 Various Types of Power-Law Flow Rules in CP Algorithm
519(1)
15.3.3 Comparison of FEM versus VFM
520(1)
15.3.4 AI-based KDD Process
521(1)
15.4 Crystal Plasticity-Based Virtual Experiment Model
522(2)
15.4.1 Description of CPVEM
522(1)
15.4.2 Various Types of Power-Law Flow Rules
523(1)
15.5 Hierarchical Strategy for Developing a Constitutive EQuation (CEQ) Expansion Model
524(7)
15.5.1 Computational Model for Developing a CEQ Expansion Model
524(1)
15.5.1.1 CPVEM for Predicting CEQ Patterns
525(1)
15.5.1.2 Identifying CEQ Patterns for TAV
526(1)
15.5.1.3 Virtual Fields Method (VFM) Model for Predicting Material Properties for New Ti-Al-X (TAX) Materials
527(1)
15.5.2 Big Data Control Based on Ontology Integration
528(3)
15.6 Closing Remarks
531(2)
Nomenclature
533(1)
Acknowledgments
534(1)
References
534(5)
16 A Computational Method for the Design of Materials Accounting for the Process-Structure-Property-Performance (PSPP) Relationship
539(34)
Chung-Hyun Goh
Adam P. Dachowicz
Janet K. Allen
Farrokh Mistree
16.1 Introduction
539(1)
16.2 Frame of Reference
540(2)
16.3 Integrated Multiscale Robust Design (IMRD)
542(2)
16.4 Roll Pass Design
544(5)
16.4.1 Roll Pass Sequence and Design Parameters
545(3)
16.4.2 Flow Stress Prediction Model
548(1)
16.4.3 Wear Coefficient
549(1)
16.5 Microstructure Evolution Model
549(6)
16.5.1 Recrystallization
550(1)
16.5.2 Austenite Grain Size (AGS) Prediction
551(3)
16.5.3 Ferrite Grain Size (FGS) Prediction
554(1)
16.6 Exploring the Feasible Solution Space
555(8)
16.6.1 Developing Roll Pass Design and The Analysis and FE Models
556(1)
16.6.2 Developing Modules and Their Corresponding Model Descriptions
557(1)
16.6.2.1 Module
1. AGS Prediction Model (f1)
557(1)
16.6.2.2 Module
2. FGS Prediction Model (f2)
557(1)
16.6.2.3 Module
3. Structure-Property Correlation
557(1)
16.6.2.4 Module
4. Property-Performance Correlation
558(1)
16.6.3 IMRD Step 1 in Figure 16.8: Deductive Exploration
559(1)
16.6.4 IMRD Step 2 in Figure 16.8: Inductive Exploration
560(2)
16.6.5 IMRD Step 3 in Figure 16.8: Trade-offs among Competing Goals
562(1)
16.6.6 Exploration of Solution Space
562(1)
16.7 Results and Discussion
563(5)
16.8 Closing Remarks
568(1)
Acknowledgments
569(1)
Nomenclature
569(2)
References
571(2)
Section V Education 573(74)
17 An Engineering Virtual Organization for CyberDesign (EVOCD): A Cyberinfrastructure for Integrated Computational Materials Engineering (ICME)
575(30)
Tomasz Haupt
Nitin Sukhija
Mark F. Horstemeyer
17.1 Introduction
575(3)
17.2 Engineering Virtual Organization for CyberDesign
578(2)
17.3 Functionality of EVOCD
580(15)
17.3.1 Knowledge Management: Wiki
580(2)
17.3.2 Repository of Codes
582(1)
17.3.3 Repository of Data
583(2)
17.3.4 Online Model Calibration Tools
585(1)
17.3.4.1 DMGfit
588(1)
17.3.4.2 MultiState Fatigue (MSF)
591(1)
17.3.4.3 Modified Embedded Atom Method (MEAM) Parameter Calibration (MPC)
593(2)
17.4 Protection of Intellectual Property
595(3)
17.5 Cyberinfrastructure for EVOCD
598(3)
17.5.1 User Interface
598(2)
17.5.2 EVOCD Services
600(1)
17.5.3 Service Integration
600(1)
17.6 Conclusions
601(1)
References
601(4)
18 Integrated Computational Materials Engineering (ICME) Pedagogy
605(28)
Nitin Sukhija
Tomasz Haupt
Mark F. Horstemeyer
18.1 Introduction
605(3)
18.2 Methodology
608(2)
18.3 Course Curriculum
610(13)
18.3.1 ICME for Design
611(2)
18.3.2 Presentation and Team Formation
613(1)
18.3.3 ICME Cyberinfrastructure and Basic Skills
613(1)
18.3.4 Bridging Length Scales
614(1)
18.3.4.1 Quantum Methods
614(1)
18.3.4.2 Atomistic Methods
615(1)
18.3.4.3 Dislocation Dynamics Methods
617(1)
18.3.4.4 Crystal Plasticity
618(1)
18.3.4.5 Macroscale Continuum Modeling
619(2)
18.3.5 ICME Wiki Contributions
621(1)
18.3.6 Grading and Evaluation
622(1)
18.4 Assessment
623(5)
18.5 Benefits or Relevance of the Learning Methodology
628(1)
18.6 Conclusions and Future Directions
629(1)
Acknowledgments
630(1)
References
630(3)
19 Summary
633(14)
Mark F. Horstemeyer
19.1 Introduction
633(1)
19.2
Chapter 1: ICME Definition: Takeaway Point
633(1)
19.3
Chapter 2: Takeaway Point
634(1)
19.4
Chapter 3: Takeaway Point
634(1)
19.5
Chapter 4: Takeaway Point
634(1)
19.6
Chapter 5: Takeaway Point
634(1)
19.7
Chapter 6: Takeaway Point
634(1)
19.8
Chapter 7: Takeaway Point
634(1)
19.9
Chapter 8: Takeaway Point
635(1)
19.10
Chapter 9: Takeaway Point
635(1)
19.11
Chapter 10: Takeaway Point
635(1)
19.12
Chapter 11: Takeaway Point
635(1)
19.13
Chapter 12: Takeaway Point
635(1)
19.14
Chapter 13: Takeaway Point
635(1)
19.15
Chapter 14: Takeaway Point
636(1)
19.16
Chapter 15: Takeaway Point
636(1)
19.17
Chapter 16: Takeaway Point
636(1)
19.18
Chapter 17: Takeaway Point
636(1)
19.19
Chapter 18: Takeaway Point
636(1)
19.20 ICME Future
637(7)
19.20.1 ICME Future: Metals
637(1)
19.20.2 ICME Future: Non-Metals
637(1)
19.20.2.1 Polymers
637(1)
19.20.2.2 Ceramics
639(1)
19.20.2.3 Concrete
641(1)
19.20.2.4 Biological Materials
641(1)
19.20.2.5 Earth Materials
643(1)
19.20.2.6 Space Materials
644(1)
19.21 Summary
644(1)
References
645(2)
Index 647
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.
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