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A risk assessment system must be developed to ensure the reliability, environmental, and trouble-free operation of the main gas pipelines (MGP) laid in the territory of the Republic of Sakha (Yakutia). The gas pipelines laid in the northern territories of the Russian Federation under conditions of the permafrost require special reliability, and the risk of catastrophic failure increases with the working service of a gas pipeline. The quantitative risk assessment of gas pipeline failure is complicated since the gas pipeline systems consist of kilometers-long pipes, different materials, and various run lengths of separate sections. In addition, due to the vast territories, their operating conditions are also changing. As the statistical data analysis shows, the reliability and safety of gas pipeline systems are reduced by 2.5–3 times under harsh environments. Using the long-term monitoring data of MGP operation and considering failures and disasters based on Bayesian trust networks, a probabilistic risk assessment model combining quantitative and qualitative expert data is proposed. Timely reaction to an emergency will reduce pipeline damage and minimize economic losses. It plays an important role in mitigating the consequences of emergencies. A reliable gas supply system will increase the level of reliability of service and the safety of infrastructure life support facilities in case of possible emergencies. The dependences of investments’ impact in “emergency response” on economic losses are presented. Using multi-year monitoring data, the paper attempts a probabilistic analysis of accidents on a main gas pipeline laid in permafrost soils based on a Bayesian network. It is received that the most effective and satisfactory accuracy assessment can be achieved with the help of a combination of qualitative and quantitative methods—Bayesian trust networks combining quantitative statistical and qualitative expert methods. The proposed method improves safety and reduces the risk of emergencies in the area next to the object of study. It allows optimal distribution of scarce resources to maintain an acceptable risk level.

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Risk Assessment of Trouble-Free Gas Supply to Consumers Under Cold Climate Conditions

  • 会议论文

  • 发表日期：

    2025年

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  • Galina Struchkova,
  • Tamara Kapitonova

摘要

A risk assessment system must be developed to ensure the reliability, environmental, and trouble-free operation of the main gas pipelines (MGP) laid in the territory of the Republic of Sakha (Yakutia). The gas pipelines laid in the northern territories of the Russian Federation under conditions of the permafrost require special reliability, and the risk of catastrophic failure increases with the working service of a gas pipeline. The quantitative risk assessment of gas pipeline failure is complicated since the gas pipeline systems consist of kilometers-long pipes, different materials, and various run lengths of separate sections. In addition, due to the vast territories, their operating conditions are also changing. As the statistical data analysis shows, the reliability and safety of gas pipeline systems are reduced by 2.5–3 times under harsh environments. Using the long-term monitoring data of MGP operation and considering failures and disasters based on Bayesian trust networks, a probabilistic risk assessment model combining quantitative and qualitative expert data is proposed. Timely reaction to an emergency will reduce pipeline damage and minimize economic losses. It plays an important role in mitigating the consequences of emergencies. A reliable gas supply system will increase the level of reliability of service and the safety of infrastructure life support facilities in case of possible emergencies. The dependences of investments’ impact in “emergency response” on economic losses are presented. Using multi-year monitoring data, the paper attempts a probabilistic analysis of accidents on a main gas pipeline laid in permafrost soils based on a Bayesian network. It is received that the most effective and satisfactory accuracy assessment can be achieved with the help of a combination of qualitative and quantitative methods—Bayesian trust networks combining quantitative statistical and qualitative expert methods. The proposed method improves safety and reduces the risk of emergencies in the area next to the object of study. It allows optimal distribution of scarce resources to maintain an acceptable risk level.