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Developing probabilistic safety performance margins for unknown and underappreciated risks

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  • Benjamin, Allan
  • Dezfuli, Homayoon
  • Everett, Chris

Abstract

Probabilistic safety requirements currently formulated or proposed for space systems, nuclear reactor systems, nuclear weapon systems, and other types of systems that have a low-probability potential for high-consequence accidents depend on showing that the probability of such accidents is below a specified safety threshold or goal. Verification of compliance depends heavily upon synthetic modeling techniques such as PRA. To determine whether or not a system meets its probabilistic requirements, it is necessary to consider whether there are significant risks that are not fully considered in the PRA either because they are not known at the time or because their importance is not fully understood. The ultimate objective is to establish a reasonable margin to account for the difference between known risks and actual risks in attempting to validate compliance with a probabilistic safety threshold or goal. In this paper, we examine data accumulated over the past 60 years primarily from the space program, and secondarily from nuclear reactor experience, aircraft systems, and human reliability experience to formulate guidelines for estimating probabilistic margins to account for risks that are initially unknown or underappreciated. The formulation includes a review of the safety literature to identify the principal causes of such risks.

Suggested Citation

  • Benjamin, Allan & Dezfuli, Homayoon & Everett, Chris, 2016. "Developing probabilistic safety performance margins for unknown and underappreciated risks," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 329-340.
  • Handle: RePEc:eee:reensy:v:145:y:2016:i:c:p:329-340
    DOI: 10.1016/j.ress.2015.07.021
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    Cited by:

    1. Wróbel, Krzysztof & Montewka, Jakub & Kujala, Pentti, 2017. "Towards the assessment of potential impact of unmanned vessels on maritime transportation safety," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 155-169.

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