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Vulnerability analysis method based on risk assessment for gas transmission capabilities of natural gas pipeline networks

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  • Wang, WuChang
  • Zhang, Yi
  • Li, YuXing
  • Hu, Qihui
  • Liu, Chengsong
  • Liu, Cuiwei

Abstract

The crucial part of vulnerability analysis is identifying the critical components of a pipeline network. In this study, we proposed a novel analysis method- “Risk-Vulnerability,†which combines the characteristics of risk assessments and vulnerability analyses methods. Risk-Vulnerability identifies the critical components of a pipeline network from three perspectives: pipeline operating status, transmission performance, and network characteristics. The formulas of the importance value of each component were established. Then the component risk indicators were established, and the component risk values were calculated. And a utility theory was introduced to calculate the severity of the consequences. Finally, the component importance and risk values were multiplied to obtain the vulnerability of the component. The feasibility and effectiveness of the method were verified by comparing the identification results of this method to those from the weighted flow capacity rate (WFCR). The Risk-Vulnerability method provides an improved insight into the pipeline criticality compared to the WFCR and improves the calculation formulae based on the identification content, which can not only be used to identify critical components, but also can be used to formulate research on risk reduction measures for pipeline network systems.

Suggested Citation

  • Wang, WuChang & Zhang, Yi & Li, YuXing & Hu, Qihui & Liu, Chengsong & Liu, Cuiwei, 2022. "Vulnerability analysis method based on risk assessment for gas transmission capabilities of natural gas pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    • Handle: RePEc:eee:reensy:v:218:y:2022:i:pb:s0951832021006384
    DOI: 10.1016/j.ress.2021.108150
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    Cited by:

    1. Sergey Vorobev & Anton Kolosnitsyn & Ilya Minarchenko, 2022. "Determination of the Most Interconnected Sections of Main Gas Pipelines Using the Maximum Clique Method," Energies, MDPI, vol. 15(2), pages 1-14, January.
    2. Li, Yuntao & Wang, Yumeng & Lai, Yuying & Shuai, Jian & Zhang, Laibin, 2023. "Monte Carlo-based quantitative risk assessment of parking areas for vehicles carrying hazardous chemicals," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    3. Jiang, Qiangqiang & Cai, Baoping & Zhang, Yanping & Xie, Min & Liu, Cuiwei, 2023. "Resilience assessment methodology of natural gas network system under random leakage," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Hao, Yucheng & Jia, Limin & Zio, Enrico & Wang, Yanhui & He, Zhichao, 2023. "A multi-objective optimization model for identifying groups of critical elements in a high-speed train," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    5. Senderov, Sergey M. & Vorobev, Sergey V. & Smirnova, Elena M., 2022. "Peak underground gas storage efficiency in reducing the vulnerability of gas supply to consumers in an extensive gas transmission system," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    6. Yang, Kai & Hou, Lei & Man, Jianfeng & Yu, Qiaoyan & Li, Yu & Zhang, Xinru & Liu, Jiaquan, 2023. "Supply reliability analysis of natural gas pipeline network based on demand-side economic loss risk," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. Jian Guo & Jun Wang & Baikang Zhu & Bingyuan Hong & Cuicui Li & Jianhui He, 2022. "A Risk Evaluation Method of Coastal Oil Depots for Heavy Rainfall Vulnerability Assessment," Sustainability, MDPI, vol. 14(11), pages 1-12, June.

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