
Computational Materials Engineering
Achieving High Accuracy and Efficiency in Metals Processing Simulations
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Computational Materials Engineering: Achieving High Accuracy and Efficiency in Metals Processing Simulations describes the most common computer modeling and simulation techniques used in metals processing, from so-called "fast" models to more advanced multiscale models, also evaluating possible methods for improving computational accuracy and efficiency. Beginning with a discussion of conventional fast models like internal variable models for flow stress and microstructure evolution, the book moves on to advanced multiscale models, such as the CAFÉ method, which give insights into the phenomena occurring in materials in lower dimensional scales. The book then delves into the various methods that have been developed to deal with problems, including long computing times, lack of proof of the uniqueness of the solution, difficulties with convergence of numerical procedures, local minima in the objective function, and ill-posed problems. It then concludes with suggestions on how to improve accuracy and efficiency in computational materials modeling, and a best practices guide for selecting the best model for a particular application.
Key Features
- Presents the numerical approaches for high-accuracy calculations
- Provides researchers with essential information on the methods capable of exact representation of microstructure morphology
- Helpful to those working on model classification, computing costs, heterogeneous hardware, modeling efficiency, numerical algorithms, metamodeling, sensitivity analysis, inverse method, clusters, heterogeneous architectures, grid environments, finite element, flow stress, internal variable method, microstructure evolution, and more
- Discusses several techniques to overcome modeling and simulation limitations, including distributed computing methods, (hyper) reduced-order-modeling techniques, regularization, statistical representation of material microstructure, and the Gaussian process
- Covers both software and hardware capabilities in the area of improved computer efficiency and reduction of computing time
Readership
Researchers focused on numerical modeling of microstructure evolution phenomena and materials processing and PhD students of material and applied computer sciences.
Table of Contents
- Chapter One. Introduction
- 1.1 Classification of Models
- 1.2 Review of Problems Connected with Computing Costs
- 1.3 Content of the Book
- Chapter Two. Toward Increase of the Efficiency of Modeling
- 2.1 Improvement of Numerical Algorithms
- 2.2 Improvement of Hardware
- Chapter Three. Conventional Modeling
- 3.1 Conventional Methods of Mechanical Analysis
- 3.2 Finite Element and Alternative Methods
- 3.3 Flow Stress
- 3.4 Microstructure Evolution
- 3.5 Fracture
- 3.6 Phase Transformations
- Chapter Four. Identification of Material Models and Boundary Conditions
- 4.1 Experimental Tests
- 4.2 Sensitivity and Inverse Analysis in Materials Processing
- Chapter Five. Increase Model Predictive Capabilities by Multiscale Modeling
- 5.1 Basic Concept of Multiscale Modeling
- 5.2 Microscale Models—Discrete CA Method Case Study
- 5.3 CA Framework
- 5.4 Multiscale CAFE Method
- Chapter Six. Trade off Between Accuracy and Efficiency
- 6.1 Digital Representation of Microstructure
- 6.2 Reduction of the Computational Domain
- Chapter Seven. Case Studies
- 7.1 Manufacturing of Automotive Part
- 7.2 Manufacturing of Rails
- 7.3 Manufacturing of Fasteners
- 7.4 CA model Parallelization
- 7.5 Case Studies on the CAFE Method
- Chapter Eight. Conclusions
- References
- Index
- Chapter One. Introduction
Product details
- No. of pages: 376
- Language: English
- Copyright: © Butterworth-Heinemann 2015
- Published: July 13, 2015
- Imprint: Butterworth-Heinemann
- eBook ISBN: 9780124167247
- Hardcover ISBN: 9780124167070
About the Authors
Maciej Pietrzyk
Affiliations and Expertise
Dept. of Applied Comp. Sci. and Modelling, Faculty of Metals Eng. and Industrial Comp. Sci., Akademia Górniczo – Hutnicza, Poland
Lukasz Madej
Affiliations and Expertise
Dept. of Applied Comp. Sci. and Modelling, Faculty of Metals Eng. and Industrial Comp. Sci., Akademia Górniczo – Hutnicza, Poland
Lukasz Rauch
Affiliations and Expertise
AGH University of Science and Technology, Krakow, Poland
Danuta Szeliga
Affiliations and Expertise
Dept. of Applied Comp. Sci. and Modelling, Faculty of Metals Eng. and Industrial Comp. Sci., Akademia Górniczo – Hutnicza, Poland
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