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Computational Materials Engineering: Achieving High Accuracy And Efficiency In Metals Processing Simulations

Computational Materials Engineering: Achieving High Accuracy And Efficiency In Metals Processing Simulations

Computational Materials Engineering: Achieving High Accuracy And Efficiency In
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Computational Materials Engineering: Achieving High Accuracy And Efficiency In Metals Processing Simulations Hardback - 2015

by Maciej Pietrzyk, Lukasz Madej ,

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Academic, 2015. 1St. Hardcover. New.
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  • Title Computational Materials Engineering: Achieving High Accuracy And Efficiency In Metals Processing Simulations
  • Author Maciej Pietrzyk, Lukasz Madej ,
  • Binding Hardback
  • Edition 1St
  • Condition New
  • Pages 376
  • Volumes 1
  • Language ENG
  • Publisher Academic
  • Publication date 2015
  • Features Bibliography, Index
  • Bookseller's Inventory # DBS-9780124167070
  • ISBN 9780124167070 / 0124167071
  • Weight 1.65 lbs (0.75 kg)
  • Dimensions 9 x 6.1 x 0.9 in (22.86 x 15.49 x 2.29 cm)
  • Category Computers - Data Base Management
  • Library of Congress subjects Metals - Computer simulation
  • Library of Congress Catalogue Number 2015936068
  • Dewey Decimal Code 669
  • Quantity available 10

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From the publisher

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 CAF 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.

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