A Simulation-Based Dynamic Approach for External Flooding Analysis in Nuclear Power Plants

Abstract

All nuclear power plants must consider external flooding hazards such as local intense precipitation, riverine flooding, flooding due to upstream dam failure, and coastal flooding due to storm surge or tsunami. While external flooding events could potentially interrupt off-site power, threaten plant structures, systems and components important to safety, or limit plant access, they have often been qualitatively assessed as risk insignificant and screened out from detailed evaluation and quantification. Recent lessons learned from the Fukushima seismic/tsunami initiated nuclear accident (2011), the Fort Calhoun (2011), Vermont Yankee (2013), Arkansas Nuclear One (2013), and St. Lucie (2014) flooding events have highlighted the need for more detailed risk analysis. However, incorporating an external flood model into the traditional event tree/fault tree approach used in static probabilistic risk assessment (PRA) models is challenging because it is difficult to accurately represent plant system and component behavior and reliability of manual actions during an ever-progressing flood event. The plant response to external flood may be highly spatial and time dependent, subject to the hydrological and hydraulic characteristics of the flood event. Such unique challenges prompt the investigation of using simulation-based dynamic analysis approaches for external flood risk assessment. Simulation methods can better model the performance of structures, systems, and components during an external flooding event. A general framework to perform a simulation-based dynamic flooding analysis is presented in this paper with the subtasks of flood hazard analysis, flood fragility analysis, plant response modeling, safety margin analysis or PRA quantification. A new type of PRA technique, State-based PRA Modeling, is introduced to incorporate time-related interactions such as those from both 3D physical simulations and random failures into traditional PRA logic models.