为预防城市埋地燃气管道泄漏及衍生事故, 该文提出一种管道泄漏连锁风险演化评估方法。该文根据城市埋地燃气管道的运行特点, 综合考虑人、 物、 环、 管等风险因素, 结合燃气泄漏事故发展流程和各风险因素之间的逻辑关系, 构建了集成灰数区间(Grey)、 决策试验与评价实验室(decision-making trial and evaluation laboratory, DEMATEL)、 解释结构模型(interpretive structural modeling, ISM)和动态Bayes网络(dynamic Bayesian network, DBN)的风险演化与评估模型。该文利用Grey-DEMATEL-ISM方法分析了各风险因素之间的逻辑关系, 并筛选出关键风险因素; 将各风险因素出现的概率进行量化, 并根据各风险因素之间的逻辑关系建立了管道泄漏风险演化DBN模型; 计算了管道泄漏失效概率, 并实时更新。研究结果表明： 腐蚀和人的因素的原因度、 中心度和敏感性均较高, 是预防埋地燃气管道泄漏的关键风险因素。该文所提方法可实现对埋地燃气管道泄漏风险演化过程的动态分析, 为有效预防和控制城市埋地燃气管道泄漏事故提供参考。
Abstract
[Objective] Currently, the service life of buried gas pipelines in most Chinese cities has exceeded 20 a. Because of the combined effects of third-party damage, corrosion, and human error, the operational safety of these pipelines has decreased, leading to a high probability of accidents. Because gas pipelines are often buried underground, the transported medium is flammable and explosive, and they are located in densely populated areas, they possess characteristics of concealment and high risk. A leaking gas pipeline can easily trigger secondary fire and explosion incidents, causing severe casualties, property damage, and gas supply interruptions. [Methods] To prevent buried gas pipeline leakages and associated accidents in urban areas, a method for assessing the cascading risk evolution of pipeline leakages is proposed. Based on the operational characteristics of urban buried gas pipelines, risk factors, such as human factors, physical elements, environmental factors, and pipeline conditions are comprehensively integrated. These risk factors are further refined into a three-level indicator system. The logical relationships among the development process of leakage accidents and these risk factors are examined, and an integrated risk evolution and assessment model is developed through the Grey decision-making trial and evaluation laboratory (DEMATEL) method, interpretive structural modeling (ISM), and the dynamic Bayesian network (DBN) approach. The Grey-DEMATEL-ISM method is utilized to analyze causal hierarchical relationships among risk factors and identify key risk factors. The introduction of Grey numbers compensates for the subjective uncertainty of expert evaluations in the DEMATEL-ISM method, making the assessment results more aligned with actual conditions. Different types of risk factors are quantified through methods such as expert opinions, historical data, and probability distributions, and a pipeline leakage risk evolution DBN model is established based on the logical relationships among the risk factors. Furthermore, the probability of accident consequences is calculated and updated in real time to predict the potential development paths of accidents, thereby assisting in the safety operation and maintenance decision-making of buried gas pipelines. [Results] The results indicated that the corrosion and human factors exhibited high levels of causality, centrality, and sensitivity, making them critical risk factors for preventing pipeline leakages. A dynamic risk analysis model was conducted the use of the gas pipeline explosion accident in Shiyan, Hubei Province, as a case study. The results showed that the posterior probabilities of corrosion-related nodes were significantly higher than those of other nodes. Based on the assessment results, targeted measures were proposed to prevent initial incidents and cut off the accident propagation paths throughout the entire life cycle during the design and manufacturing phase, laying phase, and operational phase of the buried gas pipeline. The case study verified the feasibility and effectiveness of the proposed method. [Conclusions] The Grey-DEMATEL-ISM-DBN model can comprehensively consider the characteristics and quantitative representation of risk factors relate to humans, machines, environment, and management, even in situations with limited data. Based on historical accident information, it establishes a multi-level hierarchical structure model for the causes of buried gas pipeline leakage accidents. The model quantifies the degree of influence and sensitivity among various risk factors and provides an intuitive display of accident evolution scenarios. The proposed method enables the dynamic analysis of the risk evolution process of buried gas pipeline leakages, providing support for decision-making in safety operations, maintenance, and accident investigations involving urban buried gas pipelines.
关键词
城市埋地燃气管道 /
风险演化 /
泄漏风险 /
动态Bayesian网络
Key words
urban buried gas pipeline /
risk evolution /
leakage risk /
dynamic Bayesian network
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基金
国家重点研发计划项目(2022YFC3006305);安徽省重点研发计划项目(2023g07020001)
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