Feasibility study of PRA for critical infrastructure risk analysis

Caroline A. Johnson, Roger Flage and Seth D. Guikema

Reliability Engineering and System Safety, 2021, vol. 212, issue C

Abstract: Probabilistic Risk Analysis (PRA) has been commonly used by NASA and the nuclear power industry to assess risk since the 1970s. However, PRA is not commonly used to assess risk in networked infrastructure systems such as water, sewer and power systems. Other methods which utilise network models of infrastructure such as random and targeted attack failure analysis, N-k analysis and statistical learning theory are instead used to analyse system performance when a disruption occurs. Such methods have the advantage of being simpler to implement than PRA. This paper explores the feasibility of a full PRA of infrastructure, that is one that analyses all possible scenarios as well as the associated likelihoods and consequences. Such analysis is resource intensive and quickly becomes complex for even small systems. Comparing the previously mentioned more commonly used methods to PRA provides insight into how current practises can be improved, bringing the results closer to those that would be presented from PRA. Although a full PRA of infrastructure systems may not be feasible, PRA should not be discarded. Instead, analysis of such systems should be carried out using the framework of PRA to include vital elements such as scenario likelihood analysis which are often overlooked.

Keywords: Probabilistic Risk Analysis; Critical infrastructure; Network models; Statistical learning theory (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:212:y:2021:i:c:s0951832021001848

DOI: 10.1016/j.ress.2021.107643

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