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AuthorFerdous, R.
AuthorKhan, F.
AuthorSadiq, R.
AuthorAmyotte, P.
AuthorVeitch, B.
Available date2009-12-27T06:59:13Z
Publication Date2009
Publication NameProcess Safety and Environmental Protection
Identifierhttp://dx.doi.org/10.1016/j.psep.2009.07.003
CitationRefaul Ferdous, Faisal Khan, Rehan Sadiq, Paul Amyotte, Brian Veitch, Handling data uncertainties in event tree analysis, Process Safety and Environmental Protection, Volume 87, Issue 5, September 2009, Pages 283-292
URIhttp://hdl.handle.net/10576/10470
AbstractEvent tree analysis (ETA) is an established risk analysis technique to assess likelihood (in a probabilistic context) of an accident. The objective data available to estimate the likelihood is often missing (or sparse), and even if available, is subject to incompleteness (partial ignorance) and imprecision (vagueness). Without addressing incompleteness and imprecision in the available data, ETA and subsequent risk analysis give a false impression of precision and correctness that undermines the overall credibility of the process. This paper explores two approaches to address data uncertainties, namely, fuzzy sets and evidence theory, and compares the results with Monte Carlo simulations. A fuzzy-based approach is used for handling imprecision and subjectivity, whereas evidence theory is used for handling inconsistent, incomplete and conflicting data. Application of these approaches in ETA is demonstrated using the example of an LPG release near a processing facility.
Languageen
PublisherElsevier B.V.
SubjectData uncertainties
SubjectFuzzy-based approach
SubjectEvidence theory
SubjectEvent tree analysis
SubjectMonte Carlo simulations
TitleHandling data uncertainties in event tree analysis
TypeArticle


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