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A probabilistic model for a gas explosion due to leakages in the grey cast iron gas mains

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  • Forys, Monika B.
  • Kurowicka, Dorota
  • Peppelman, Bas

Abstract

In this paper we propose a model for the probability of an explosion caused by a leakage form grey cast iron pipes in the city of Amsterdam as a function of pipeline and environmental characteristics. The parameters in the model are quantified, with uncertainty, using historical data and structured expert judgment, by use of the Classical Model. Eleven experts from Dutch distribution system operators (DSO) and Kiwa Gas Technology participated in the research. The model has to provide the overall probability of an explosion per year and a prioritization of pipes in terms of their potential contribution to the probability of explosion, which can help DSO's to prioritize their replacements.

Suggested Citation

  • Forys, Monika B. & Kurowicka, Dorota & Peppelman, Bas, 2013. "A probabilistic model for a gas explosion due to leakages in the grey cast iron gas mains," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 270-279.
    • Handle: RePEc:eee:reensy:v:119:y:2013:i:c:p:270-279
    DOI: 10.1016/j.ress.2013.06.034
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    References listed on IDEAS

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    1. Cooke, Roger M. & Goossens, Louis L.H.J., 2008. "TU Delft expert judgment data base," Reliability Engineering and System Safety, Elsevier, vol. 93(5), pages 657-674.
    2. Roger Cooke & Eric Jager, 1998. "A Probabilistic Model for the Failure Frequency of Underground Gas Pipelines," Risk Analysis, John Wiley & Sons, vol. 18(4), pages 511-527, August.
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    Cited by:

    1. Hathout, Michel & Vuillet, Marc & Carvajal, Claudio & Peyras, Laurent & Diab, Youssef, 2019. "Expert judgments calibration and combination for assessment of river levee failure probability," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 377-392.
    2. Liu, Shuanglei & Li, Weijun & Gao, Peng & Sun, Yibo, 2022. "Modeling and performance analysis of gas leakage emergency disposal process in gas transmission station based on Stochastic Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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