Computational materials engineering : achieving high accuracy and efficiency in metals processing simulations / Maciej Pietrzyk [and three others].

Format:

Book

Author/Creator:

Pietrzyk, Maciej, author.

Language:

English

Subjects (All):

Metallurgy--Computer simulation.

Metallurgy.

Metals--Computer simulation.

Metals.

Physical Description:

1 online resource (388 p.)

Edition:

1st ed.

Place of Publication:

Amsterdam, [Netherlands] : Butterworth-Heinemann, 2015.

Language Note:

English

Summary:

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.- 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

Contents:

Front Cover

Computational Materials Engineering

Copyright Page

Contents

1. Introduction

1.1 Classification of Models

1.2 Review of Problems Connected with Computing Costs

1.3 Content of the Book

2. Toward Increase of the Efficiency of Modeling

2.1 Improvement of Numerical Algorithms

2.1.1 Metamodeling

2.1.2 Inverse analysis

2.1.2.1 General formulation of the inverse problem

2.1.2.2 Regularization

2.1.2.3 Methods of regularizations

2.1.2.4 Numerical computations and regularization in the finite-dimension setting

2.1.3 Sensitivity analysis

2.1.3.1 Local SA

2.1.3.2 Global SA

2.1.3.3 The implementation of SA algorithms

2.1.3.4 A strategy for the identification of the model parameters

2.2 Improvement of Hardware

2.2.1 General idea of high-performance computing

2.2.2 Development of clusters

2.2.3 Development of heterogeneous architectures

2.2.4 Development of grid environments

3. Conventional Modeling

3.1 Conventional Methods of Mechanical Analysis

3.1.1 Slab method

3.1.2 Upper bound method

3.2 Finite Element and Alternative Methods

3.2.1 Principles of computational modeling using FEM

3.2.2 Integral formulation and variational methods

3.2.3 Dynamic explicit time integration scheme

3.2.4 Adaptive remeshing

3.3 Flow Stress

3.3.1 Closed form flow stress equations

3.3.2 Internal variable method

3.4 Microstructure Evolution

3.4.1 Recovery and recrystallization

3.4.2 Model of recrystallization

3.4.3 Precipitation

3.5 Fracture

3.5.1 Fundamentals of FM and classical fracture and failure hypotheses

3.5.2 Empirical fracture criteria

3.5.3 Fracture mechanics

3.5.4 Continuum damage mechanics

3.6 Phase Transformations

3.6.1 Model based on the JMAK equation

3.6.2 Leblond model.

3.6.3 Model based on the ordinary differential equation

3.6.4 Phase-field model (PFM)

3.6.5 Recapitulation on phase transformation models

4. Identification of Material Models and Boundary Conditions

4.1 Experimental Tests

4.1.1 Plastometric tests

4.1.2 Stress relaxation tests

4.1.3 Two-stage compression test

4.1.4 Inhomogeneous deformation compression test

4.1.5 SICO test

4.2 Sensitivity and Inverse Analysis in Materials Processing

4.2.1 SA in materials processing

4.2.1.1 IVM of material

4.2.1.2 A quantitative fracture criterion

4.2.1.3 Phase transformation models

4.2.2 Inverse method-identification and reconstruction problems in materials processing

4.2.2.1 Flow stress

4.2.2.2 Microstructure evolution

4.2.2.3 Sideways compression test

4.2.2.4 Identification of the fracture criteria

4.2.2.5 Phase transformations

5. Increase Model Predictive Capabilities by Multiscale Modeling

5.1 Basic Concept of Multiscale Modeling

5.2 Microscale Models-Discrete CA Method Case Study

5.2.1 Recrystallization

5.2.2 Phase transformations

5.2.3 Fracture

5.2.4 Strain localization and microshear bands

5.3 CA Framework

5.4 Multiscale CAFE Method

6. Trade off Between Accuracy and Efficiency

6.1 Digital Representation of Microstructure

6.1.1 Voronoi

6.1.2 Cellular automata grain growth model

6.2 Reduction of the Computational Domain

6.2.1 Statistical representation of microstructure

6.2.1.1 Idea of SSRVE

6.2.1.2 Shape coefficients

6.2.1.3 Statistical measures of higher order

6.2.1.4 Sensitivity analysis of shape coefficients

6.2.1.5 Construction of the SSRVE

6.2.2 Isogeometric analysis as alternative for the FE method in the SSRVE

6.2.2.1 The general idea of the IGA

6.2.2.2 IGA mesh refinement

6.2.2.3 Mesh refinement

7. Case Studies.

7.1 Manufacturing of Automotive Part

7.1.1 Advanced high strength steels

7.1.2 Manufacturing of automotive part made of DP steel

7.1.3 Conventional modeling of manufacturing of automotive part made of DP steel

7.1.4 Multiscale modeling of manufacturing of automotive part made of DP steel

7.2 Manufacturing of Rails

7.3 Manufacturing of Fasteners

7.3.1 Manufacturing chain for fasteners

7.3.2 Sensitivity analysis and optimization of industrial processes for manufacturing chain for fasteners

7.4 CA model Parallelization

7.5 Case Studies on the CAFE Method

8. Conclusions

References

Index.

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9780124167247

0124167241

9780124167070

0124167071

OCLC:

929530125