Identifying Critical Nodes in Fault Tree Safety Models with Limited Data
2024 Integrated Communications, Navigation and Surveillance Conference (ICNS)(2024)
摘要
Decision makers often use fault trees to identify ways to most effectively reduce risk in a system. However, when little data are available, a large degree of uncertainty may exist in the probabilities in the tree. This paper presents a method to quantify uncertainty in a fault tree considering both statistical uncertainty (due to low observed event counts) and unavailable data (events for which no supporting data are available). The uncertainty quantification is integrated with a method to assess importance metrics associated with events in the tree. This provides decision makers with a degree of confidence in identifying the most critical nodes and in allocating resources in the most effective way. The method is applied to a case study on runway incursions for a fault tree from the Integrated Safety Assessment Model.
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关键词
aviation safety,sensitivity analysis,uncertainty analysis,fault tree quantification
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