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المؤلفFerdous, R.
المؤلفKhan, F.
المؤلفSadiq, R.
المؤلفAmyotte, P.
المؤلفVeitch, B.
تاريخ الإتاحة2009-12-27T06:59:13Z
تاريخ النشر2009
اسم المنشورProcess Safety and Environmental Protection
المعرّفhttp://dx.doi.org/10.1016/j.psep.2009.07.003
الاقتباسRefaul 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
معرّف المصادر الموحدhttp://hdl.handle.net/10576/10470
الملخصEvent 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.
اللغةen
الناشرElsevier B.V.
الموضوعData uncertainties
Fuzzy-based approach
Evidence theory
Event tree analysis
Monte Carlo simulations
العنوانHandling data uncertainties in event tree analysis
النوعArticle
dc.accessType Abstract Only


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