Design space decomposition using support vector machines for reliability-based design optimization

Antonio Harrison Sanchez, Samy Missouri, Juan Pablo Martinez Teuscher

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This article presents a method for the explicit decomposition of the design space using support vector machines (SVM). The decomposition identifies the explicit boundaries of a failure region (limit state function) in terms of deterministic and random design variables. This allows an easy calculation of a probability of failure and enables to associate a specific system behavior with a region of the design space. The explicit expression for a limit state function is then used in a reliability-based design optimization formulation. Two structural problems are presented to demonstrate the efficiency of the approach.

Original languageEnglish (US)
Title of host publicationCollection of Technical Papers - 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
Pages339-353
Number of pages15
ISBN (Print)1563478234, 9781563478239
DOIs
StatePublished - 2006
Event11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference - Portsmouth, VA, United States
Duration: Sep 6 2006Sep 8 2006

Publication series

NameCollection of Technical Papers - 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference
Volume1

Other

Other11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference
CountryUnited States
CityPortsmouth, VA
Period9/6/069/8/06

ASJC Scopus subject areas

  • Engineering(all)

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    Sanchez, A. H., Missouri, S., & Teuscher, J. P. M. (2006). Design space decomposition using support vector machines for reliability-based design optimization. In Collection of Technical Papers - 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference (pp. 339-353). (Collection of Technical Papers - 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference; Vol. 1). American Institute of Aeronautics and Astronautics Inc.. https://doi.org/10.2514/6.2006-6927