Print Email Facebook Twitter Modeling wildfire spread in wildland-industrial interfaces using dynamic Bayesian network Title Modeling wildfire spread in wildland-industrial interfaces using dynamic Bayesian network Author Khakzad, N. (TU Delft Safety and Security Science) Date 2019 Abstract Global warming and the subsequent increase in the frequency and severity of wildfires demand for specialized risk assessment and management methodologies to cope with the ever-increasing risk of wildfires in wildland-industrial interfaces (WIIs). Wildfires can jeopardize the safety and integrity of industrial plants, and trigger secondary fires and explosions especially in the case of process plants where large inventory of combustible and flammable substances is present. In the present study, by modeling the WII as a two dimensional lattice, we have developed an innovative methodology for modeling and assessing the risk of wildfire spread in WIIs by combining dynamic Bayesian network and wildfire behavior prediction models. The developed methodology models the spatial and temporal spread of fire, based on the most probable path of fire, both in the wildland and in the industrial area. Subject Wildland-industrial interfaceWildfireNaTech accidentDynamic Bayesian networkFire's most probable pathDomino effect To reference this document use: http://resolver.tudelft.nl/uuid:b27cb6fd-180f-4e45-a5cd-59f8ea24c3a4 DOI https://doi.org/10.1016/j.ress.2019.04.006 Embargo date 2021-04-18 ISSN 0951-8320 Source Reliability Engineering & System Safety, 189, 165-176 Bibliographical note Accepted Author Manuscript Part of collection Institutional Repository Document type journal article Rights © 2019 N. Khakzad Files PDF 1_s2.0_S0951832018313887_main.pdf 2.79 MB Close viewer /islandora/object/uuid:b27cb6fd-180f-4e45-a5cd-59f8ea24c3a4/datastream/OBJ/view