Risk assessment model for building fires based on a Bayesian network

SHU Xueming; YAN Jun; HU Jun; WU Jinjin; DENG Boyu

doi:10.16511/j.cnki.qhdxxb.2019.26.036

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Journal of Tsinghua University(Science and Technology) ›› 2020, Vol. 60 ›› Issue (4) : 321-327. DOI: 10.16511/j.cnki.qhdxxb.2019.26.036

PHYSICS AND ENGINEERING MECHANICS

Risk assessment model for building fires based on a Bayesian network

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Abstract

The development of building fires was divided into four stages for risk assessment as fire initiation, fire alarm, fire behavior, and fire spreading based on fire engineering theory with analyses of the main risk assessment parameters of each stage. The dynamic risk assessment model was based on a Bayesian network. A sensitivity analysis was then used to evaluate the influences of key parameters on the fire risk. Two typical buildings were then used as examples to evaluate the risk at each fire stage and the overall risk. The results illustrate how the building fire risk is a dynamic process with different risk and impact parameters in each stage. The model nodes and dependencies constitute a causal network. The evaluation model can effectively combine large amounts of fire data collected by a building fire monitoring terminal using artificial intelligence analyses. This research can effectively improve building fire safety management.

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safety engineering / building fire / risk assessment / big data / Bayesian network

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SHU Xueming, YAN Jun, HU Jun, WU Jinjin, DENG Boyu. Risk assessment model for building fires based on a Bayesian network[J]. Journal of Tsinghua University(Science and Technology). 2020, 60(4): 321-327 https://doi.org/10.16511/j.cnki.qhdxxb.2019.26.036

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