摘要
为有效应对危化品事故发生与演变时存在的动态性及不确定性问题,基于事故演变过程中的关键情景状态及对应孕灾环境、应急活动和处置目标等要素,引入动态贝叶斯网络方法,构建危化品事故情景推演网络,并结合复杂网络知识,对孕灾环境和应急活动2类事故影响因素节点进行敏感性和重要度分析。结果表明:情景推演网络计算的情景节点概率符合事故发生的实际情况,能够对危化品事故在不同孕灾环境和应急救援下的演变路径进行推演,并且分析得到燃烧物、消防力量、火场环境和建筑密度等关键影响因素节点,研究结果可为事故处理提供应急辅助决策支持。
In order to effectively deal with the dynamic and uncertain problems existing in the occurrence and evolution of hazardous chemical accidents,based on the key scenario states in the process of accident evolution and their corresponding disaster-pregnant environment,emergency activities,disposal objectives and other elements,the dynamic Bayesian network method was introduced to construct the scenario deduction network of hazardous chemical accidents.Combined with the knowledge of complex network,the sensitivity and importance of two kinds of accident influencing factors nodes,including the disaster-pregnant environment and emergency activities,were analyzed.The results showed that the scenario node probabilities calculated by the scenario deduction network were in line with the actual situation of the accident.It could deduce the evolution paths of hazardous chemical accidents under different disaster-pregnant environments and emergency rescue,and obtain the key influencing factors nodes such as the combustibles,fire-fighting force,fire environment and building density.The results can provide auxiliary emergency decision support for the accident disposal.
作者
赵士翔
胡春春
马兰
ZHAO Shixiang;HU Chunchun;MA Lan(School of Geodesy and Geomatics,Wuhan University,Wuhan Hubei 430070,China;Aisino Corporation,Beijing 100195,China)
出处
《中国安全生产科学技术》
CAS
CSCD
北大核心
2022年第2期36-42,共7页
Journal of Safety Science and Technology
基金
国家重点研发计划项目(2018YFC0809100)。
关键词
危化品事故
情景推演
动态贝叶斯网络
复杂网络
敏感性分析
hazardous chemical accident
scenario deduction
dynamic Bayesian network
complex network
sensitivity analysis
