Print Email Facebook Twitter Vulnerability of industrial plants to flood-induced natechs: A Bayesian network approach Title Vulnerability of industrial plants to flood-induced natechs: A Bayesian network approach Author Khakzad, N. (TU Delft Safety and Security Science) van Gelder, P.H.A.J.M. (TU Delft Safety and Security Science) Date 2017 Abstract In the context of natural-technological (natech) accidents, flood-induced damage of industrial plants have received relatively less attention mainly due to the scarcity of such accidents compared to those triggered by earthquakes, high winds, and lightnings. The large amount of oil spillage due to floods triggered by the Hurricanes Katrina and Rita in 2005 in the U.S. demonstrated the potential of floods in causing catastrophic natechs. In the present study, we have developed a methodology based on physical reliability models and Bayesian network so as to assess the fragility (probability of failure) of industrial plants to floods. The application of the methodology has been demonstrated for petroleum storage tanks where flotation, shell buckling, and sliding are considered as the prevailing failure modes. Due to scarcity of empirical data and high-resolution field observations prevailing in natechs, the developed methodology can effectively be applied to a wide variety of natechs in industrial plants as long as limit state equations of respective failure modes can reasonably be developed. Subject FloodsNatech accidentsPetroleum storage tankPhysical reliability modelsBayesian network To reference this document use: http://resolver.tudelft.nl/uuid:c35c54d2-298f-4e5a-b3a4-1e05c343acd3 DOI https://doi.org/10.1016/j.ress.2017.09.016 Embargo date 2019-10-28 ISSN 0951-8320 Source Reliability Engineering & System Safety Part of collection Institutional Repository Document type journal article Rights © 2017 N. Khakzad, P.H.A.J.M. van Gelder Files PDF 1_s2.0_S0951832017305045_main.pdf 1.13 MB Close viewer /islandora/object/uuid:c35c54d2-298f-4e5a-b3a4-1e05c343acd3/datastream/OBJ/view