Modern natural gas pipeline failures constitute devastating disasters, as they can result in cascading secondary crises. Therefore, reduction of buried gas pipeline's reliability, has become a major concern among stakeholders and researchers in recent years. This study employs a dynamic Bayesian network to investigate the consequences of natural gas pipeline failures. We consider seven parent nodes—age, diameter, length, depth, population, time of occurrence, and land use—and twelve consequence factors to analyze the overall losses stemming from pipeline failure. The proposed model can handle both static and dynamic systems using quantitative and/or qualitative data. To demonstrate the applicability and effectiveness of our developed model, we analyze the gas pipeline network of Regina in Saskatchewan, Canada. The results show that age and diameter are the two most important and sensitive parameters. The developed Bayesian network model will aid decision-makers in effectively managing and improving the reliability of their assets.

现代天然气管道故障构成毁灭性灾难，因为它们可能导致连锁的次生危机。因此，埋地天然气管道可靠性的降低，已成为近年来利益相关者和研究人员关注的主要问题。本研究采用动态贝叶斯网络来研究天然气管道故障的后果。我们考虑七个父节点——年龄、直径、长度、深度、人口、发生时间和土地利用——以及十二个后果因素来分析管道故障引起的总体损失。所提出的模型可以使用定量和/或定性数据处理静态和动态系统。为了证明我们开发的模型的适用性和有效性，我们分析了加拿大萨斯喀彻温省里贾纳的天然气管网。结果表明，年龄和直径是两个最重要和最敏感的参数。开发的贝叶斯网络模型将帮助决策者有效管理和提高资产的可靠性。