Probabilistic optimal design in the presence of random fields

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

This article describes a methodology to incorporate a random field in a probabilistic optimization problem. The approach is based on the extraction of the features of a random field using a reduced number of experimental observations. This is achieved by proper orthogonal decomposition. Using Lagrange interpolation, a modified random field is obtained by changing the contribution of each feature. The contributions are controlled using scalar parameters, which can be considered as random variables. This allows one to perform a random-field-based probabilistic optimization with few random variables. The methodology is demonstrated on a tube impacting a rigid wall for which a random field modifies the planarity of the tube's wall.

Original languageEnglish (US)
Pages (from-to)523-530
Number of pages8
JournalStructural and Multidisciplinary Optimization
Volume35
Issue number6
DOIs
StatePublished - Jun 2008

Fingerprint

Random variables
Random Field
Interpolation
Decomposition
Tube
Random variable
Planarity
Lagrange Interpolation
Methodology
Orthogonal Decomposition
Optimal design
Scalar
Optimization Problem
Optimization

Keywords

  • Probabilistic optimal design
  • Proper orthogonal decomposition
  • Random fields

ASJC Scopus subject areas

  • Engineering (miscellaneous)
  • Mechanics of Materials
  • Computational Mechanics
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

Probabilistic optimal design in the presence of random fields. / Missoum, Samy.

In: Structural and Multidisciplinary Optimization, Vol. 35, No. 6, 06.2008, p. 523-530.

Research output: Contribution to journalArticle

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