An algorithm for enhancing spatiotemporal resolution of probabilistic risk assessment to address emergent safety concerns in nuclear power plants. (May 2019) - Bui, Ha; Sakurahara, Tatsuya; Pence, Justin; Reihani, Seyed; Kee, Ernie; Mohaghegh, Zahra
Highlights: Theoretical foundations for the incorporation of time and space into Probabilistic Risk Assessment (PRA). Integrated PRA (I-PRA) methodology to add realism to risk estimations while avoiding significant changes to the plant PRA structure and the associated costs. Explicit incorporation of time and space into underlying models of the events in the plant PRA. An algorithm that helps execute I-PRA in a way to gradually enhance spatiotemporal resolution of the plant PRA to efficiently address emergent safety concerns. The algorithm is illustrated with Fire PRA and Generic Safety Issue 191 (GSI-191) applications. 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.