Quantification of Plant-level HCLPF Capacity in Probabilistic Safety Assessment-Based Seismic Margin Assessment
Abstract of the technical paper/presentation presented at:
International Topical Meeting on Probabilistic Safety Assessment and Analysis
September 24–28, 2017
Zhaoliang Wang, Smain Yalaoui, and Yolande Akl
Canadian Nuclear Safety Commission
Probabilistic safety assessment (PSA)-based seismic margin assessment (SMA), compared to the U.S. Nuclear Regulatory Commission SMA and to the Electric Power Research Institute SMA, retains the most similarity to the seismic PSA, where a full-scope systems-analysis is performed to identify the dominant accident sequences leading to severe core damage (SCD). Plant-level seismic fragility, representing the plant seismic capacity and the associated uncertainties, is a function of fragilities of individual structures, systems, and components (SSC), random failure rates, and human error probabilities. The plant-level seismic fragility, based on which the plant-level high-confidence-of-low-probability-of-failure (HCLPF) capacity can be rigorously derived, integrates information from all important accident sequences for SCD.
Two quantification methods have been used for deriving the plant-level HCLPF capacity in the PSA-based SMA: the “min-max” method and the convolution method, respectively. The min-max method is a simplistic method for deriving an approximate plant-level HCLPF capacity from the most important sequence and component-level HCLPF capacities. It provides only a rough approximation and may result in a distorted HCLPF capacity that is higher or lower than the true value. Therefore, the use of the min-max method should be justified and follow certain guidance. The convolution method determines the plant-level capacity by convolving/combining individual SSC fragilities and random failure rates according to the Boolean expression for SCD. It provides an integrative production of the plant-level capacity based on all important accident sequences.
This paper compares the min-max method and the convolution method, in terms of the required input, assumptions, computational complexity, and output plant-level HCLPF capacity. Using simple plant logic models and SSC fragilities, the performance of the following three computational cases are evaluated: (1) convolution method to derive plant-level capacity and Monte Carlo simulation to explicitly consider the two types of uncertainties in SSC capacities; (2) the convolution method and the use of composite uncertainty in SSC capacity; and (3) the simplistic min-max method. The relative accuracy and computational efforts of the three computational cases are evaluated. In addition, current Canadian practice in the quantification of plant-level HCLPF capacity is briefly summarized.
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