{"title":"A Study on Risk Control Methods for Urban Gas Pipeline Leak and Explosion","authors":"Hankun Li, , , Renren Zhang*, , , Runquan Li*, , , Jie Ma, , , Jinhao Wen, , , Songwenbo Chen, , and , Xinhong Li, ","doi":"10.1021/acs.chas.5c00069","DOIUrl":null,"url":null,"abstract":"<p >To prevent explosion accidents arising from urban gas pipeline leaks, it is crucial to understand both the factors that lead to pipeline failure and the mechanisms that govern the evolution of accident consequences, thereby enabling the development of comprehensive preleak risk management and postleak emergency response strategies. This study employs Bayesian networks (BN) and influence diagrams (ID) to establish a robust risk control model for urban gas pipeline leak and explosion incidents. Based on pipeline installation scenarios, the pipelines are segmented to identify failure risk factors in each section, resulting in the construction of a BN model for pipeline failures; subsequently, event sequence diagrams (ESD) are utilized to analyze the evolutionary pathways of accident consequences, which are then translated into a BN model and integrated with the pipeline failure BN model to form a complete framework that captures both failure mechanisms and accident outcomes. Key risk factors are identified and corresponding control measures are proposed, leading to the development of a Bayesian ID model that comprehensively considers the effectiveness and cost implications of these measures in order to select the optimal risk control strategy.</p>","PeriodicalId":73648,"journal":{"name":"Journal of chemical health & safety","volume":"32 5","pages":"612–623"},"PeriodicalIF":3.4000,"publicationDate":"2025-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of chemical health & safety","FirstCategoryId":"1085","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.chas.5c00069","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
To prevent explosion accidents arising from urban gas pipeline leaks, it is crucial to understand both the factors that lead to pipeline failure and the mechanisms that govern the evolution of accident consequences, thereby enabling the development of comprehensive preleak risk management and postleak emergency response strategies. This study employs Bayesian networks (BN) and influence diagrams (ID) to establish a robust risk control model for urban gas pipeline leak and explosion incidents. Based on pipeline installation scenarios, the pipelines are segmented to identify failure risk factors in each section, resulting in the construction of a BN model for pipeline failures; subsequently, event sequence diagrams (ESD) are utilized to analyze the evolutionary pathways of accident consequences, which are then translated into a BN model and integrated with the pipeline failure BN model to form a complete framework that captures both failure mechanisms and accident outcomes. Key risk factors are identified and corresponding control measures are proposed, leading to the development of a Bayesian ID model that comprehensively considers the effectiveness and cost implications of these measures in order to select the optimal risk control strategy.