摘要
为解决综合管廊燃气管网系统风险因素多、风险状态随时间动态变化等问题,在传统故障树和静态贝叶斯网络等方法的基础上提出了基于动态贝叶斯网络的城市综合管廊燃气泄漏动态风险评价方法。首先利用蝴蝶结模型分析总结了导致综合管廊燃气管网发生泄漏的主要风险源和不同事故后果。然后,引入时间因素与Leaky Noisy-or Gate模型,根据故障树模型的映射规则,建立城市综合管廊燃气泄漏的动态贝叶斯网络模型。最后,利用动态贝叶斯网络的双向推理功能对模型进行求解。由实例分析得到了某综合管廊燃气泄漏概率及各事故后果概率的时序变化曲线,通过反向推理得到了导致燃气泄漏的主要风险源。研究成果可为综合管廊的风险评估、日常维护提供理论支持。
To solve the problems of many risk factors and dynamic change of risk state with time in utility tunnel gas pipeline network system,a dynamic risk assessment method of gas leakage in urban utility tunnel based on Dynamic Bayesian Network(DBN)is proposed based on traditional fault tree and static Bayesian Network.Firstly,this paper analyzes and summarizes the main risk factors and different accident consequences that lead to the leakage of the utility tunnel gas pipeline network by using a Bow-Tie model.Then,the time factor is introduced and according to the mapping rules of the Fault Tree Analysis(FTA)model and the Dynamic Bayesian Network model of urban utility tunnel gas leakage is established.The prior probability of each basic event is determined by referring to the historical database and expert scoring,and the Leaky Noisy-or Gate model is introduced to improve the conditional probability table of the DBN.Finally,combined with GENIE software,the system model is solved by using the bidirectional reasoning function of the DBN model.The time series curve of gas leakage probability and accident consequence probability of a utility tunnel is obtained by case analysis,and the main risk sources leading to gas leakage are obtained by reverse reasoning.The results show that the gas leakage probability of the utility tunnel at the initial moment is 9.296×10-2,and the leakage probability will increase to 2.094×10-1 if the hidden dangers are not checked in time.Compared with the traditional buried gas pipeline,the detection and alarm devices and ventilation facilities of the pipe gallery are very important for the safe and reliable operation of the gas pipeline network in the utility tunnel,which requires regular inspection and daily maintenance.The research results can provide theoretical support for risk assessment and daily maintenance of utility tunnels.
作者
张继信
黄东阳
尤秋菊
康健
刘梦婷
郭遐晖
ZHANG Jixin;HUANG Dongyang;YOU Qiuju;KANG Jian;LIU Mengting;GUO Xiahui(School of Safety Engineering,Beijing Institute of Petrochemical Technology,Beijing 102617,China;Institute of Urban Systems Engineering,Beijing Academy of Science and Technology,Beijing 100195,China;Beijing Institute of Emergency Management Science and Technology,Beijing 101117,China)
出处
《安全与环境学报》
CAS
CSCD
北大核心
2023年第10期3455-3464,共10页
Journal of Safety and Environment
基金
国家自然科学基金青年基金项目(71901029)
北京市教委科技计划项目(KM202010017009)。
关键词
安全工程
动态贝叶斯网络
城市综合管廊
燃气泄漏
风险评价
safety engineering
Dynamic Bayesian Network(DBN)
urban integrated pipeline corridor
gas leakage
risk evaluation
