Development of a Two-Stage DQFM to Improve Efficiency of Single- and Multi-Hazard Risk Quantification for Nuclear Facilities

Eujeong Choi, Shinyoung Kwag, Jeong-Gon Ha and Daegi Hahm
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Eujeong Choi: Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute (KAERI), Daejeon 34057, Korea
Shinyoung Kwag: Department of Civil and Environmental Engineering, Hanbat National University, 125 Dongseo-daero, Yuseong-gu, Daejeon 34158, Korea
Jeong-Gon Ha: Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute (KAERI), Daejeon 34057, Korea
Daegi Hahm: Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute (KAERI), Daejeon 34057, Korea

Energies, 2021, vol. 14, issue 4, 1-21

Abstract: The probabilistic safety assessment (PSA) of a nuclear power plant (NPP) under single and multiple hazards is one of the most important tasks for disaster risk management of nuclear facilities. To date, various approaches—including the direct quantification of the fault tree using the Monte Carlo simulation (DQFM) method—have been employed to quantify single- and multi-hazard risks to nuclear facilities. The major advantage of the DQFM method is its applicability to a partially correlated system. Other methods can represent only an independent or a fully correlated system, but DQFM can quantify the risk of partially correlated system components by the sampling process. However, as a sampling-based approach, DQFM involves computational costs which increase as the size of the system and the number of hazards increase. Therefore, to improve the computational efficiency of the conventional DQFM, a two-stage DQFM method is proposed in this paper. By assigning enough samples to each hazard point according to its contribution to the final risk, the proposed two-stage DQFM can effectively reduce computational costs for both single- and multi-hazard risk quantification. Using examples of single- and multi-hazard threats to nuclear facilities, the effectiveness of the proposed two-stage DQFM is successfully demonstrated. Especially, two-stage DQFM saves computation time of conventional DQFM up to 72% for multi-hazard example.

Keywords: single hazard; multi-hazard; risk quantification; nuclear power plant (NPP); direct quantification of the fault tree using Monte Carlo simulation (DQFM) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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