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An assessment of causes and failure likelihood of cross-country pipelines under uncertainty using bayesian networks

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  • Hassan, Shamsu
  • Wang, Jin
  • Kontovas, Christos
  • Bashir, Musa

Abstract

The increased incidents of pipeline failures and resultant consequences of fires, explosions and environmental pollution motivate stakeholders to find solutions in dealing with these emerging threats as part of process safety management. This is further compounded by the absence of reliable failure data, particularly in developing countries. To address such challenges, a Bayesian Network (BN) model has been developed. The aim of the model is to highlight the contributing failure factors to the identified pipeline hazards and their interrelationships. The BN approach is appropriate for this work because it accommodates data uncertainty, or the lack of data, and can integrate the expert's knowledge. The model is especially good at updating the results whenever new data becomes available.

Suggested Citation

  • Hassan, Shamsu & Wang, Jin & Kontovas, Christos & Bashir, Musa, 2022. "An assessment of causes and failure likelihood of cross-country pipelines under uncertainty using bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    • Handle: RePEc:eee:reensy:v:218:y:2022:i:pa:s0951832021006566
    DOI: 10.1016/j.ress.2021.108171
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    3. Bhattacharjee, Pushparenu & Dey, Vidyut & Mandal, U.K. & Paul, Susmita, 2022. "Quantitative risk assessment of submersible pump components using Interval number-based Multinomial Logistic Regression(MLR) model," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
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    5. Li, Pengyu & Wang, Xiufang & Jiang, Chunlei & Bi, Hongbo & Liu, Yongzhi & Yan, Wendi & Zhang, Cong & Dong, Taiji & Sun, Yu, 2024. "Advanced transformer model for simultaneous leakage aperture recognition and localization in gas pipelines," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
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    7. Liu, Jianqiao & Zou, Yanhua & Wang, Wei & Zio, Enrico & Yuan, Chengwei & Wang, Taorui & Jiang, Jianjun, 2022. "A Bayesian belief network framework for nuclear power plant human reliability analysis accounting for dependencies among performance shaping factors," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

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