An algorithm for enhancing spatiotemporal resolution of probabilistic risk assessment to address emergent safety concerns in nuclear power plants

Ha Bui, Tatsuya Sakurahara, Justin Pence, Seyed Reihani, Ernie Kee, Zahra Mohaghegh

Research output: Contribution to journalArticle

Abstract

Emergent safety concerns often involve complex spatiotemporal phenomena. In addressing these concerns, the classical Probabilistic Risk Assessment (PRA) of Nuclear Power Plants (NPPs) has limitations in generating the required resolution for risk estimations. The existing dynamic PRAs have yet to demonstrate their feasibility for implementation in a plant. In addition, due to the widespread use of classical PRA in the nuclear industry and by the regulatory agency, a transition to a fully dynamic PRA would require a significant investment of resources. As a more feasible alternative, the authors have developed the Integrated PRA (I-PRA) methodology to add realism to risk estimations by explicitly incorporating time and space into underlying models of the events in the plant PRA while avoiding significant changes to its structure. In I-PRA, the failure mechanisms associated with the areas of concern (e.g., fire, Generic Safety Issue 191) were modeled in separate simulation modules, which were then integrated with the plant PRA through a probabilistic interface. This paper (i) provides theoretical foundations for the incorporation of time and space into PRA and (ii) introduces an algorithm that helps execute I-PRA in a way to gradually enhance spatiotemporal resolution of plant PRAs to efficiently address emergent safety concerns.

Original languageEnglish (US)
Pages (from-to)405-428
Number of pages24
JournalReliability Engineering and System Safety
Volume185
DOIs
StatePublished - May 2019

Keywords

  • Dynamic PRA
  • Fire PRA
  • Generic Safety Issue 191 (GSI-191)
  • Integrated Probabilistic Risk Assessment (I-PRA)
  • Nuclear promise
  • Risk-informed regulation

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering

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