Reliability assessment with correlated variables using support vector machines

Peng Jiang, Anirban Basudhar, Samy Missoum

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

5 Scopus citations

Abstract

This paper presents an approach to estimate probabilities of failure in cases where the random variables are correlated. An explicit limit state function is constructed in the uncorrelated standard normal space using the Nataf transformation and a support vector machine (SVM). An adaptive sampling strategy is used to build an accurate SVM approximation. Several analytical examples with various distributions and also multiple failure modes are presented.

Original languageEnglish (US)
Title of host publicationCollection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
DOIs
Publication statusPublished - 2011
Event52nd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference - Denver, CO, United States
Duration: Apr 4 2011Apr 7 2011

Other

Other52nd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
CountryUnited States
CityDenver, CO
Period4/4/114/7/11

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ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering
  • Materials Science(all)
  • Aerospace Engineering
  • Architecture

Cite this

Jiang, P., Basudhar, A., & Missoum, S. (2011). Reliability assessment with correlated variables using support vector machines. In Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference [AIAA 2011-1905] https://doi.org/10.2514/6.2011-1905