Parallelization of perturbation analysis: application to large-scale engineering problems

Raya Khanin, Matthew Cartmell

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

In this paper we discuss ways of parallelizing methods of perturbation analysis. Application of the perturbation method of multiple scales to vibration problems in engineering is considered, and parallel implementation of this method on a multi-processor computer using the Mathematica Parallel Computing Toolkit is discussed. Potential applications of the proposed approach to other perturbation methods are outlined.
LanguageEnglish
Pages461-473
Number of pages13
JournalJournal of Symbolic Computation
Volume31
Issue number4
DOIs
Publication statusPublished - 2001

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Perturbation Analysis
Perturbation Method
Parallelization
Engineering
Method of multiple Scales
Mathematica
Parallel processing systems
Parallel Computing
Parallel Implementation
Multiprocessor
Vibration

Cite this

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title = "Parallelization of perturbation analysis: application to large-scale engineering problems",
abstract = "In this paper we discuss ways of parallelizing methods of perturbation analysis. Application of the perturbation method of multiple scales to vibration problems in engineering is considered, and parallel implementation of this method on a multi-processor computer using the Mathematica Parallel Computing Toolkit is discussed. Potential applications of the proposed approach to other perturbation methods are outlined.",
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Parallelization of perturbation analysis : application to large-scale engineering problems. / Khanin, Raya; Cartmell, Matthew.

In: Journal of Symbolic Computation, Vol. 31, No. 4, 2001, p. 461-473.

Research output: Contribution to journalArticle

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AB - In this paper we discuss ways of parallelizing methods of perturbation analysis. Application of the perturbation method of multiple scales to vibration problems in engineering is considered, and parallel implementation of this method on a multi-processor computer using the Mathematica Parallel Computing Toolkit is discussed. Potential applications of the proposed approach to other perturbation methods are outlined.

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