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Integrated Computational Materials Engineering (ICME) for Metals: Using Multiscale Modeling to Invigorate Engineering Design with Science [Kõva köide]

, Foreword by (RWTH Aachen, Germany)
  • Formaat: Hardback, 472 pages, kõrgus x laius x paksus: 231x158x33 mm, kaal: 839 g
  • Ilmumisaeg: 17-Aug-2012
  • Kirjastus: Wiley-TMS
  • ISBN-10: 1118022521
  • ISBN-13: 9781118022528
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  • Formaat: Hardback, 472 pages, kõrgus x laius x paksus: 231x158x33 mm, kaal: 839 g
  • Ilmumisaeg: 17-Aug-2012
  • Kirjastus: Wiley-TMS
  • ISBN-10: 1118022521
  • ISBN-13: 9781118022528
Teised raamatud teemal:
Horstemeyer (mechanical engineering, Mississippi State U.) presents a textbook for a senior or graduate course on an area of materials engineering that focuses on the hierarchical multiscale modeling primarily of metal alloys that have structural applications. Besides the textbook, there are on-line lectures in electronic slide show form, a question-and-answer manual, and tutorials to the models and codes. And if this does not suffice, he says, instructors are welcome to call him with questions and comments. His topics include macroscale continuum internal state variable plasticity-damage theory and multistage fatigue, discrete dislocation dynamics simulations, atomistic modeling methods, a case study of a microstructure-property multistage fatigue analysis of a Cadillac control arm, and ICME for creating new materials and structures. Annotation ©2012 Book News, Inc., Portland, OR (booknews.com)

State-of-the-technology tools for designing, optimizing, and manufacturing new materials

Integrated computational materials engineering (ICME) uses computational materials science tools within a holistic system in order to accelerate materials development, improve design optimization, and unify design and manufacturing. Increasingly, ICME is the preferred paradigm for design, development, and manufacturing of structural products.

Written by one of the world's leading ICME experts, this text delivers a comprehensive, practical introduction to the field, guiding readers through multiscale materials processing modeling and simulation with easy-to-follow explanations and examples. Following an introductory chapter exploring the core concepts and the various disciplines that have contributed to the development of ICME, the text covers the following important topics with their associated length scale bridging methodologies:

  • Macroscale continuum internal state variable plasticity and damage theory and multistage fatigue
  • Mesoscale analysis: continuum theory methods with discrete features and methods
  • Discrete dislocation dynamics simulations
  • Atomistic modeling methods
  • Electronics structures calculations

Next, the author provides three chapters dedicated to detailed case studies, including "From Atoms to Autos: A Redesign of a Cadillac Control Arm," that show how the principles and methods of ICME work in practice. The final chapter examines the future of ICME, forecasting the development of new materials and engineering structures with the help of a cyberinfrastructure that has been recently established.

Integrated Computational Materials Engineering (ICME) for Metals is recommended for both students and professionals in engineering and materials science, providing them with new state-of-the-technology tools for selecting, designing, optimizing, and manufacturing new materials. Instructors who adopt this text for coursework can take advantage of PowerPoint lecture notes, a questions and solutions manual, and tutorials to guide students through the models and codes discussed in the text.

Arvustused

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)

Foreword xiii
Preface xv
Acknowledgments xix
1 An Introduction To Integrated Computational Materials Engineering (ICME) 1(44)
1.1 Background
2(1)
1.2 The Application of Multiscale Materials Modeling via ICME
2(2)
1.3 History of Multiscale Modeling
4(18)
1.3.1 Bridging between Scales: A Difference of Disciplines
6(16)
1.4 ICME for Design
22(7)
1.4.1 Design Optimization
23(3)
1.4.2 Metamodeling Approaches
26(1)
1.4.3 Design with Uncertainty Analysis
27(2)
1.5 ICME for Manufacturing
29(1)
1.6 Summary
29(2)
References
31(14)
2 Macroscale Continuum Internal State Variable (ISV) Plasticity-Damage Theory And Multistage Fatigue (MSF) 45(53)
2.1 Introduction
45(1)
2.2 Stress
46(8)
2.3 Kinematics of Deformation and Strain
54(4)
2.4 Continuum Theory Constitutive Equations
58(17)
2.4.1 Thermodynamics of the ISV Constitutive Equations
62(4)
2.4.2 Kinetics of the ISV Constitutive Equations
66(7)
2.4.3 Continuum Theory ISV Constitutive Equations with Discrete Structures Defects
73(1)
2.4.4 Guidelines for the Development of an ISV
74(1)
2.5 Multistage Fatigue (MSF) Modeling
75(5)
2.6 Bridging Strategies for the Macroscale and the Mesoscale
80(5)
2.6.1 Downscaling: Defining the Macroscale Constraints for the Mesoscale Analysis
80(1)
2.6.2 Upscaling: Using Design of Experiments (DOE) for Mesoscale Analysis
80(5)
2.7 Experimental Exploration, Calibration, and Validation at the Macroscale
85(2)
2.8 Summary
87(1)
References
88(10)
3 Mesoscale Analysis: Continuum Theory Methods With Discrete Features Methods 98(30)
3.1 Kinematics of Crystal Plasticity
100(4)
3.2 Kinetics of Crystal Plasticity
104(4)
3.3 Crystal Orientations and Elasticity
108(2)
3.4 Upscaling: Bridging the Crystal Level to the Polycrystalline Continuum Level
110(12)
3.4.1 Upscaling for Plasticity
111(8)
3.4.2 Upscaling for Damage Fracture
119(1)
3.4.3 Upscaling for Fatigue
120(2)
3.5 Downscaling from Crystal Plasticity to Dislocation Dynamics
122(1)
3.5.1 Plasticity
122(1)
3.5.2 Damage
122(1)
3.5.3 Fatigue
122(1)
3.6 Experimental Exploration, Calibration, and Validation at the Mesoscale
123(1)
3.7 Summary
123(1)
References
123(5)
4 Discrete Dislocation Dynamics Simulations 128(18)
4.1 Introduction
128(1)
4.2 Metal Plasticity Modeling
129(2)
4.3 Dislocation Mechanics Basics
131(4)
4.3.1 Geometrical Attributes of Dislocations
131(1)
4.3.2 Dislocation Motion
132(2)
4.3.3 Dislocation Motion and Plastic Strain
134(1)
4.3.4 Dislocations Reactions
135(1)
4.4 Modeling Discrete Dislocations
135(4)
4.4.1 Dislocation Equation of Motion
136(1)
4.4.2 Evaluation of Fdislocation
137(1)
4.4.3 Evaluation of Fself
138(1)
4.5 Boundary Conditions
139(1)
4.6 Upscaling for Plasticity
140(3)
4.6.1 Upscaling for the Macroscopic Plastic Strain
140(1)
4.6.2 Upscaling: Bridging the Dislocation Level to the Macroscale Continuum Level Stresses and Strains
140(3)
4.6.3 Upscaling for Work Hardening
143(1)
4.7 Downscaling from DD to Atomistics
143(1)
4.8 Summary
144(1)
References
144(2)
5 Atomistic Modeling Methods 146(18)
5.1 EAM Potentials
147(1)
5.2 MEAM Potentials
148(5)
5.3 Upscaling; Bridging the Atomic Level to the Dislocation Density Level and the Continuum Level
153(6)
5.3.1 Continuum Quantities for Upscaling
153(2)
5.3.2 Upscaling for Plasticity
155(1)
5.3.3 Upscaling for Damage
156(1)
5.3.4 Upscaling for Fatigue
157(1)
5.3.5 Downscaling from Atomistics to Electronics Structures Calculations
157(2)
5.4 Summary
159(1)
References
159(5)
6 Electronic Structure Calculations 164(23)
6.1 Introduction
164(1)
6.2 Why Quantum Mechanics?
165(1)
6.3 Theoretical Background
166(2)
6.4 Postulates of Quantum Mechanics
168(2)
6.5 Prior to Density Functional Theory (DFT)
170(5)
6.6 DFT
175(1)
6.7 Upscaling: Bridging the Electron Level to the Atom Level
176(8)
6.7.1 Cohesive Energy
177(1)
6.7.2 Lattice Parameter
178(1)
6.7.3 Bulk Moduli
178(1)
6.7.4 Elastic Constants
179(1)
6.7.5 Vacancy Formation Energies
180(1)
6.7.6 Interstitial Defects
180(1)
6.7.7 Surface Formation Energies
181(1)
6.7.8 Surface Adsorption Energies
181(1)
6.7.9 Stacking Fault Energies
182(1)
6.7.10 GSFE Curve
183(1)
6.8 Summary
184(1)
Bibliography
184(3)
Cited References
184(1)
Uncited References
185(2)
7 Case Study: From Atoms To Autos: A Redesign Of A Cadillac Control Arm 187(153)
7.1 Introduction
187(8)
7.1.1 Material: Cast A356 Aluminum Alloy
189(1)
7.1.2 Modeling Philosophy
189(6)
7.2 Macroscale Microstructure-Property Internal State Variable (ISV) Plasticity-Damage Model
195(16)
7.2.1 Kinematics of the Macroscale Model
196(4)
7.2.2 Void Nucleation, Growth, and Coalescence Aspects of the Macroscale Model
200(5)
7.2.3 Elastic-Plastic Aspects of Macroscale Continuum Model
205(4)
7.2.4 Macroscale Continuum Model Summary
209(2)
7.3 Bridges 1 and 5: Electronics Structure Calculations: Connections to the Atomic Scale and Macroscale Continuum Level
211(5)
7.3.1 Atomistic Level Downscaling Requirements
213(3)
7.4 Bridges 2 and 6: Nanoscale Atomistic Simulations: Connections to the Microscale and Macroscale
216(17)
7.4.1 Atomistic Simulation Preliminaries
217(1)
7.4.2 Aluminum-Silicon Interface Structure and Model Sensitivity
218(6)
7.4.3 Aluminum-Silicon Interface Debonding
224(2)
7.4.4 Role of Vacancy-Type Defects
226(3)
7.4.5 Upscaling: Comparison of Continuum Decohesion Models for the Microscale Simulations
229(4)
7.5 Bridges 3 and 7: Microscale Finite Element Simulations: Connections to the Mesoscale and Macroscale
233(14)
7.5.1 Design of Experiment Parameters for Void-Crack Nucleation at the Microscale
236(2)
7.5.2 DOE Methodology
238(2)
7.5.3 Micromechanical DOE Results Using FEA
240(4)
7.5.4 Validation Experiments
244(1)
7.5.5 Bridge 6: From Microscale to Macroscale Modeling: Void Crack Nucleation
245(2)
7.5.6 Summary of Bridges Related to the Microscale
247(1)
7.6 Bridges 4 and 8: Mesoscale 1 Finite Element Simulations: Connections to the Mesoscale 2 and Macroscale
247(12)
7.6.1 Mesoscale 1 Finite Element Simulation Setup and Results for the Realistic Microstructures
251(7)
7.6.2 Bridge 8: From Mesoscale 1 to Macroscale Modeling: Pore Coalescence
258(1)
7.6.3 Summary of Bridges Related to the Mesoscale 1 Finite Element Simulations
258(1)
7.7 Bridge 9: Mesoscale 2 Finite Element Simulations (Idealized Porosity): Connections to the Macroscale
259(17)
7.7.1 Mesoscale 2 Finite Element Simulation Setup and Results for the Idealized Porosity
260(1)
7.7.2 Pore Coalescence Parametric Study
260(6)
7.7.3 Temperature Effects on Pore Coalescence
266(9)
7.7.4 Bridge 9: From Mesoscale 2 to Macroscale Modeling: Pore Coalescence
275(1)
7.7.5 Summary of Bridges Related to Mesoscale 2 Idealized Porosity Simulations
276(1)
7.8 Bridge 10: Macroscale Material Model: Connections to the Macroscale Finite Element Simulations
276(27)
7.8.1 Summary of Bridge Information from the Lower Length Scales into the Macroscale Continuum Model
277(1)
7.8.2 Hierarchical Multiscale Macroscale Continuum ISV Theory: Calibration and Validation
278(1)
7.8.3 Model Calibration of the Continuum ISV Model
279(7)
7.8.4 Model Validation of the Macroscale Continuum ISV Model
286(17)
7.8.5 Summary of Bridges Related to the Macroscale Simulations
303(1)
7.9 Predictive Modeling of Structural Components for the Case Study of the Cast A356 Aluminum Alloy
303(7)
7.9.1 Weapons Carrier Analysis
304(2)
7.9.2 Automotive Control Arm Analysis
306(4)
7.10 Design Optimization with Uncertainty of the Automotive Control Arm
310(17)
7.10.1 Conventional Design Optimization Method
311(1)
7.10.2 Design Optimization Employing Surrogate (Metamodel) Modeling with Probabilistics (Reliability) under Uncertainty with the Macroscale Continuum ISV Model that Included the Hierarchical Multiscale Analysis and Associated Microstructures from the Different Length Scales
312(15)
7.11 Summary
327(1)
References
328(12)
8 Case Study: A Microstructure-Property Multistage Fatigue (MSF) Analysis Of A Cadillac Control Arm 340(39)
8.1 Introduction to the Mechanisms of Fatigue in Cast Alloys
340(6)
8.2 Macroscale MSF Model
346(4)
8.2.1 Incubation
346(1)
8.2.2 MSC Regime
347(3)
8.3 Macroscale MSF Modeling Bridges (Upscaling and Downscaling)
350(23)
8.3.1 Bridge 7 Atomistic Simulations for Determining the Crack Driving Force Coefficient for the MSC Growth Rate in the Macroscale MSF Model
352(2)
8.3.2 Bridge 9 Mesoscale Finite Element Simulations for the Nonlocal Plasticity Parameter in the Incubation Equation: Connections to the Macroscale
354(9)
8.3.3 Bridge 10 Mesoscale Finite Element Simulations for the MSC: Connections to the Macroscale
363(3)
8.3.4 Bridge 12 Macroscale MSF Model Calibration
366(7)
8.4 Summary
373(1)
Bibliography
374(5)
Cited References
374(3)
Uncited References
377(2)
9 Case Study: Conducting A Structural Scale Metal Forming Finite Element Analysis Starting From Electronics Structures Calculations Using ICME Tools 379(31)
9.1 Introduction
379(1)
9.2 Modeling Philosophy
380(2)
9.3 Bridge 1: Electronics Principles to Atomistic Simulation Connection
382(4)
9.3.1 Atomistic Model Calibration Using the Modified Embedded Atom Method (MEAM) Potential
382(1)
9.3.2 Atomistic Model Validation Using the MEAM Potential
382(4)
9.4 Bridge 2: Atomistic Simulation to Dislocation Density Simulation Connection
386(5)
9.5 Bridge 3: Dislocation Density to CP Simulation Connection
391(7)
9.5.1 Model Calibration of Hardening Equations
391(5)
9.5.2 Model Validation of the Hardening Equations
396(2)
9.6 Bridge 9: CP to Macroscale Continuum Simulation Connection
398(4)
9.7 Bridge 12: Macroscale Continuum Model to the Structural Scale Simulation of the Sheet Forming Problem
402(2)
9.8 Summary
404(2)
References
406(4)
10 The Near Future: ICME For The Creation Of New Materials And Structures 410(15)
10.1 Integrating Process, Structure, Property, and Performance
410(7)
10.2 Energy
417(2)
10.3 Infrastructure
419(1)
10.4 Transportation
419(1)
10.5 Nano- and Microstructures Small Devices
419(2)
10.6 Summary
421(1)
References
422(3)
Index 425
Dr. MARK F. HORSTEMEYER earned a BS degree (with honors) from West Virginia University in mechanical engineering in 1985, an MS degree from Ohio State University in engineering mechanics in 1987, and a PhD from Georgia Institute of Technology in mechanical engineering in 1995. He is currently a professor in the Mechanical Engineering Department at Mississippi State University (2002–present), holding the positions of Chief Technical Officer for the Center for Advanced Vehicular Systems as well as the CAVS Chair in Computational Solid Mechanics. Previous to this, he worked 15 years at Sandia National Labs. He is an ASME and ASM Fellow and has won many awards including the R&D 100 Award, AFS Best Paper Award, Sandia Award for Excellence, Ralph E. Powe Research Award, and Ohio State's Thomas French Alumni Achievement Award.