Citation

Rongshui QIN, Chenchen SHI, Chao C, Meng LN, Xiaoyong LIU, Junfeng X. China Saf. Sci. J. 2023; 33(12): 176-182.

Copyright

(Copyright © 2023, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2023.12.0879

PMID

unavailable

Abstract

To effectively reduce the risk of fire accidents in urban commercial complexes, firstly, based on the causal analysis of the evolution process of fire accidents and influencing factors, the corresponding Fault Tree (FT) and Event Tree (ET) models were constructed. Then they were mapped into Bayesian networks (BN) to determine the conditional relationships between influencing factors. Secondly, fuzzy theory based on expert judgment was used to determine the prior probabilities of basic events. The FBN model was constructed to overcome the uncertainty of failure probabilities of risk factors. Finally, the FBN-established risk assessment model was utilized to perform bidirectional inference and sensitivity analysis for fire accidents of urban commercial complexes, identifying the key influencing factors leading to fire accidents at different severity levels. The study indicates that strengthening fire and smoke zoning design, increasing the fire resistance rating of fire separation facilities, installing fire separation facilities reasonably and reducing the failure rate of smoke exhaust systems can effectively prevent the occurrence of high-loss risk-level fire accidents.

Key words: fire accident, urban commercial complex, fuzzy Bayesian network (FBN), risk analysis, prior probability

Language: en