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Solution of Superlarge Problems in Computational Mechanics

Solution of Superlarge Problems in Computational Mechanics

Solution of Superlarge Problems in Computational Mechanics
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Solution of Superlarge Problems in Computational Mechanics Paperback - 2011

by Kane, James H

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Details

  • Title Solution of Superlarge Problems in Computational Mechanics
  • Author Kane, James H
  • Binding Paperback
  • Condition Used - Good
  • Pages 306
  • Volumes 1
  • Language ENG
  • Publisher Springer
  • Publication date 2011-09-22
  • Illustrated Yes
  • Features Illustrated
  • Bookseller's Inventory # 1461278546.G
  • ISBN 9781461278542 / 1461278546
  • Weight 1.11 lbs (0.50 kg)
  • Dimensions 9.61 x 6.69 x 0.66 in (24.41 x 16.99 x 1.68 cm)
  • Category Technology & Industrial Arts
  • Dewey Decimal Code 620.11
  • Quantity available 1

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Reader reviews for Solution of Superlarge Problems in Computational Mechanics

From the publisher

There is a need to solve problems in solid and fluid mechanics that currently exceed the resources of current and foreseeable supercomputers. The issue revolves around the number of degrees of freedom of simultaneous equations that one needs to accurately describe the problem, and the computer storage and speed limitations which prohibit such solutions. The goals of tHis symposium were to explore some of the latest work being done in both industry and academia to solve such extremely large problems, and to provide a forum for the discussion and prognostication of necessary future direc- tions of both man and machine. As evidenced in this proceedings we believe these goals were met. Contained in this volume are discussions of: iterative solvers, and their application to a variety of problems, e.g. structures, fluid dynamics, and structural acoustics; iterative dynamic substructuring and its use in structural acoustics; the use of the boundary element method both alone and in conjunction with the finite element method; the application of finite difference methods to problems of incompressible, turbulent flow; and algorithms amenable to concurrent computations and their applications. Furthermore, discussions of existing computational shortcomings from the big picture point of view are presented that include recommendations for future work.
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