A Critical Look at the Need for Performing Multi-Hazard Probabilistic Risk Assessment for Nuclear Power Plants

Abstract

Probabilistic Risk Assessment (PRA) is one of the technologies that is used to inform the design, licensing, operation, and maintenance activities of nuclear power plants (NPPs). A PRA can be performed by considering the single hazard (e.g., earthquake, flood, high wind, landslide) or by considering multi-hazards (e.g., earthquake and tsunami, high wind and internal fire). Single hazard PRA was thought sufficient to cover the analysis of a severe accident until the Fukushima Daiichi NPP accident in 2011. Since then, efforts were made to consider multi-hazards as well; thus, multi-hazard PRAs are starting to be seen as being indispensable for NPPs. In addition to the changing frequency of global and local natural hazards, other reasons to be highlighted are that the number and diversity of NPPs will probably increase. Moreover, advanced reactors are close to becoming a reality by designing them with passive safety systems, smaller, standardized, and even transportable to make them cheaper across the design, licensing construction, and operation stages. Thus, multi-hazards should be addressed in any future full-scope PRA. Although we found a few studies discussing multi-hazards, a general framework for multi-hazard PRA is still missing. In this paper, we argue that the starting point for any multi-hazard PRA general framework should be the Advanced Non-LWR Licensing Basis Event Selection (LBE) Approach and Probabilistic Risk Assessment Standard for Non-Light Water Reactor (non-LWR) Nuclear Power Plants. For Probabilistic Risk Assessment (PRA), history has shown us the path forward before, with Three Mile Accident being seen as one milestone to understand the necessity of PRA. The Fukushima Daiichi NPP Accident is another milestone in the development of PRA, showing the need for performing multi-hazard PRA for the current and future NPPs.

An Integration of Deep Learning and Transfer Learning for Earthquake-Risk Assessment in the Eurasian Region

“…Third, the test was conducted with 2 million points to derive the SPA. The model parameters that were used to predict and optimize the model included Adam optimizer, batch size (100), and verbose (1). Finally, predicted values were converted into pixels after post-processing and the SPM was generated.…”

“…Earthquakes are the most catastrophic phenomena to seriously threaten urban areas. Recently, the importance of earthquake-risk analysis has increased, particularly the analysis of the safety of the design of structures associated with nuclear power plants and chemical industries [1]. Consequently, several studies have attempted to provide different techniques to assess and manage earthquake risk around the world.…”