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基于动态贝叶斯网络的建筑火灾蔓延多米诺事故风险评估方法研究

孙浩东 叶继红 王恩元 陈伟 姜健

建筑结构学报2026,Vol.47Issue(6):26-36,11.
建筑结构学报2026,Vol.47Issue(6):26-36,11.DOI:10.14006/j.jzjgxb.2025.0473

基于动态贝叶斯网络的建筑火灾蔓延多米诺事故风险评估方法研究

Research on risk assessment method of fire spread domino effect in buildings based on dynamic Bayesian network

孙浩东 1叶继红 2王恩元 3陈伟 2姜健2

作者信息

  • 1. 中国矿业大学 土木工程灾变与智能防控省高校重点实验室,江苏 徐州 221116||中国矿业大学 徐州市工程结构火安全重点实验室,江苏 徐州 221116||中国矿业大学 安全工程学院,江苏 徐州 221116
  • 2. 中国矿业大学 土木工程灾变与智能防控省高校重点实验室,江苏 徐州 221116||中国矿业大学 徐州市工程结构火安全重点实验室,江苏 徐州 221116
  • 3. 中国矿业大学 安全工程学院,江苏 徐州 221116
  • 折叠

摘要

Abstract

The spread of a building fire is a high-impact and low-frequency event,exhibiting domino-like characteristics,often leading to more severe consequences than the initial fire.To accurately describe the domino effect of fire spread in buildings,a risk assessment method based on dynamic Bayesian networks(DBNs)for domino accident scenarios in building fire spread is proposed.The theory of the domino effect is introduced to describe the fire propagation process.By decoupling fire spread,the chain-like escalation process of undesirable events that trigger secondary accidents is analyzed,and a method for calculating escalation probabilities is proposed.Rooms are treated as nodes,and fire spread paths are treated as directed edges to construct the DBN structure.Each node encompasses four states,that is,safe,ignited,fully developed fire,and decay,with escalation probabilities serving as input parameters for the conditional probability tables.The effectiveness of the method is validated through fire spread experiments in confined spaces,and its application to identifying high-risk rooms and simulating fire scenarios during an incident is demonstrated.Results indicate that the proposed method can effectively identify critical units and prioritize risks.By updating the DBN with real-time evidence,the rooms most susceptible to fire spread in future time steps can be determined.The accuracy of DBN inference depends on the precision of the conditional probability tables.However,even if the escalation probabilities are not sufficiently accurate,the dynamic Bayesian network model can still correct simulation results in real time as new evidence emerges,demonstrating good robustness.

关键词

建筑火灾蔓延/多米诺效应/动态贝叶斯网络/火灾蔓延风险/火情推演

Key words

building fire spread/domino effect/dynamic Bayesian network/fire spread risk/fire inference

分类

建筑与水利

引用本文复制引用

孙浩东,叶继红,王恩元,陈伟,姜健..基于动态贝叶斯网络的建筑火灾蔓延多米诺事故风险评估方法研究[J].建筑结构学报,2026,47(6):26-36,11.

基金项目

中央高校基本科研业务专项资金资助项目(2025QN1043),国家自然科学基金面上项目(52478572). (2025QN1043)

建筑结构学报

1000-6869

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