Computational Materials Engineering

Achieving high accuracy and efficiency in metals processing simulations

By: Pietrzyk, Madej, Rauch

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Hardcover | 13 July 2015 | Edition Number 1

At a Glance

Hardcover
376 Pages

Dimensions(cm)
22.9 x 15.2 x 3.18

Hardcover

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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 CAFE 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

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