Reliability updating with measurements in spatially distributed systems using stochastic simulation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A recently developed method for reliability updating with equality information [Straub D., Probabilistic Engineering Mechanics, under review] is investigated for application to spatially distributed systems. In contrast to existing ones, the novel method enables the use of stochastic simulation (e.g. Monte Carlo or importance sampling) for reliability updating with any type of information. The main benefit of this approach over existing methods is that it is robust and calculations can thus be automated. This is of particular relevance for spatially distributed systems subject to uncertain information (e.g. though measurements, monitoring, observations of system performances), which require a large number of conditional reliability calculations. In the current paper it is shown that for such systems, stochastic simulation in combination with the novel method can provide accurate results for a large number of locations simultaneously.

Original languageEnglish
Title of host publicationReliability and Optimization of Structural Systems - Proceedings of Reliability and Optimization of Structural Systems
PublisherAssociation for Computing Machinery
Pages213-220
Number of pages8
ISBN (Print)9780415881791
DOIs
StatePublished - 2010
Event15th International Federation of Information Processing (IFIP) Working Group 7.5 on Reliability and Optimization of Structural Systems - Munich, Germany
Duration: 7 Apr 201010 Apr 2010

Publication series

NameReliability and Optimization of Structural Systems - Proceedings of Reliability and Optimization of Structural Systems

Conference

Conference15th International Federation of Information Processing (IFIP) Working Group 7.5 on Reliability and Optimization of Structural Systems
Country/TerritoryGermany
CityMunich
Period7/04/1010/04/10

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