Dynamic probability assessment of urban natural gas pipeline accidents considering integrated external activities

Journal Article (2021)
Authors

Xinhong Li (Xi'an University of Architecture and Technology)

Yi Zhang (Xi'an University of Architecture and Technology)

Rouzbeh Abbassi (Macquarie University)

M. Yang (Safety and Security Science)

Renren Zhang (Xi'an University of Architecture and Technology)

Guoming Chen (China University of Petroleum (East China))

Affiliation
Safety and Security Science
Copyright
© 2021 Xinhong Li, Yi Zhang, Rouzbeh Abbassi, M. Yang, Renren Zhang, Guoming Chen
To reference this document use:
https://doi.org/10.1016/j.jlp.2020.104388
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Publication Year
2021
Language
English
Copyright
© 2021 Xinhong Li, Yi Zhang, Rouzbeh Abbassi, M. Yang, Renren Zhang, Guoming Chen
Affiliation
Safety and Security Science
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Volume number
69
DOI:
https://doi.org/10.1016/j.jlp.2020.104388
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Abstract

Urban gas pipelines usually have high structural vulnerability due to long service time. The locations across urban areas with high population density make the gas pipelines easily exposed to external activities. Recently, urban pipelines may also have been the target of terrorist attacks. Nevertheless, the intentional damage, i.e. terrorist attack, was seldom considered in previous risk analysis of urban gas pipelines. This work presents a dynamic risk analysis of external activities to urban gas pipelines, which integrates unintentional and intentional damage to pipelines in a unified framework. A Bayesian network mapping from the Bow-tie model is used to represent the evolution process of pipeline accidents initiating from intentional and unintentional hazards. The probabilities of basic events and safety barriers are estimated by adopting the Fuzzy set theory and hierarchical Bayesian analysis (HBA). The developed model enables assessment of the dynamic probabilities of consequences and identifies the most credible contributing factors to the risk, given observed evidence. It also captures both data and model uncertainties. Eventually, an industrial case is presented to illustrate the applicability and effectiveness of the developed methodology. It is observed that the proposed methodology helps to more accurately conduct risk assessment and management of urban natural gas pipelines.

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