Failure probability estimation of a class of series systems by multidomain Line Sampling

Marcos A. Valdebenito, Pengfei Wei, Jingwen Song, Michael Beer, Matteo Broggi

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

This contribution proposes an approach for the assessment of the failure probability associated with a particular class of series systems. The type of systems considered involves components whose response is linear with respect to a number of Gaussian random variables. Component failure occurs whenever this response exceeds prescribed deterministic thresholds. We propose multidomain Line Sampling as an extension of the classical Line Sampling to work with a large number of components at once. By taking advantage of the linearity of the performance functions involved, multidomain Line Sampling explores the interactions that occur between failure domains associated with individual components in order to produce an estimate of the failure probability. The performance and effectiveness of multidomain Line Sampling is illustrated by means of two test problems and an application example, indicating that this technique is amenable for treating problems comprising both a large number of random variables and a large number of components.

Original languageEnglish
Article number107673
JournalReliability Engineering and System Safety
Volume213
DOIs
StatePublished - Sep 2021

Keywords

  • Failure probability
  • Line sampling
  • Linear performance function
  • Multidomain
  • Series system

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