Toward improvement of sampling-based seismic probabilistic safety assessment method for nuclear facilities using composite distribution and adaptive discretization

Shinyoung Kwag, Eujeong Choi, Seunghyun Eem, Jeong-Gon Ha and Daegi Hahm

Reliability Engineering and System Safety, 2021, vol. 215, issue C

Abstract: As a seismic probabilistic safety assessment (SPSA) method for nuclear facilities, direct quantification of fault tree using the Monte Carlo simulation (DQFM) was developed to accurately consider the partial dependency between components. However, since this is a sampling-based method, there is a disadvantage in that a large number of samples must be extracted for accurate seismic risk estimation. Accordingly, this study develops an efficient SPSA method by improving the existing DQFM method. We replace the method of extracting samples from both seismic response and capacity at each component by that of taking samples only from a single response distribution with a composite deviation. Also, a method of adaptive discretization for seismic intensity (ADSI) is devised by linking the seismic intensity subdivision with the convergence of the final seismic risk. The Monte-Carlo sampling technique is replaced by the Latin hypercube sampling. As an application result to nuclear facilities, the proposed method requires only half samples for every seismic intensity than the existing DQFM method, while the accuracy of results was almost similar. Besides, through the ADSI method, the proposed method was able to secure approximately three times efficiency more than the existing DQFM method, without losing the accuracy of the results.

Keywords: Seismic probabilistic safety assessment; Sampling; Nuclear power plant; DQFM; Seismic correlation; Latin Hypercube Sampling (LHS) (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:215:y:2021:i:c:s095183202100332x

DOI: 10.1016/j.ress.2021.107809

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