Title: Extended accident scenario modeling based on Bayesian networks for risk evaluation
Abstract: Conventional risk evaluation technique based on accident scenario such as event tree/fault tree suffer severe limitations of handling event dependencies and uncertainty. These dependencies and uncertainty are cumbersome to take into account when using standard event tree/fault tree modeling due to its clumsy structure and complicated quantitative solution. To make the accident scenario model more realistic, a method is proposed to explicitly represent the failures cascading effect dependency and uncertainty using Bayesian networks (BN). A simplified example of spacecraft hydrazine leak accident taken from literature illustrates the ideas presented above, and concludes that BN is a superior technique to fit a wide variety of accident scenarios profiting from its flexible structure and powerful reasoning.
Publication Year: 2014
Publication Date: 2014-08-01
Language: en
Type: article
Indexed In: ['crossref']
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