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

Shamsu Hassan, Jin Wang, Christos Kontovas and Musa Bashir

Reliability Engineering and System Safety, 2022, vol. 218, issue PA

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.

Keywords: Bayesian networks; Failure likelihood; Cross-country pipeline system; Risk assessment; Failure factors; Third party damage (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:218:y:2022:i:pa:s0951832021006566

DOI: 10.1016/j.ress.2021.108171

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