Line sampling for assessing structural reliability with imprecise failure probabilities

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

10 Citations (Scopus)

Abstract

In this paper, a novel implementation of the Line Sampling method for computing imprecise probabilities is presented. The model of uncertainty is generalised to include both aleatory and epistemic uncertainties which comprise gaps of knowledge and scarcity of data. The proposed generalised uncertainty model allows for sets of probability distribution functions - also known as credal sets - and sets of bounded variables. The proposed implementation, based on the Adaptive Line Sampling algorithm, not only makes the computation of single probabilities a lot faster but, most importantly, eases the search for lower and upper bounds of the failure probability.

Original languageEnglish
Title of host publicationVulnerability, Uncertainty, and Risk
Subtitle of host publicationQuantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014
EditorsJim W. Hall, Siu-Kui Au, Michael Beer
PublisherAmerican Society of Civil Engineers (ASCE)
Pages915-924
Number of pages10
ISBN (Electronic)9780784413609
DOIs
Publication statusPublished - 7 Jul 2014
Event2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014 - Liverpool, United Kingdom
Duration: 13 Jul 201416 Jul 2014

Publication series

NameVulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014

Conference

Conference2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014
Country/TerritoryUnited Kingdom
CityLiverpool
Period13/07/1416/07/14

Keywords

  • reliability analysis
  • optimization RBDO
  • reliability
  • uncertainty analysis
  • distribution functions
  • probability distributions

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