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Application of Chernoff bound to passive system reliability evaluation for probabilistic safety assessment of nuclear power plants

  • So, Eunseo (Department of Energy Systems Engineering, Chung-Ang University) ;
  • Kim, Man Cheol (Department of Energy Systems Engineering, Chung-Ang University)
  • Received : 2021.06.29
  • Accepted : 2022.03.08
  • Published : 2022.08.25

Abstract

There is an increasing interest in passive safety systems to minimize the need for operator intervention or external power sources in nuclear power plants. Because a passive system has a weak driving force, there is greater uncertainty in the performance compared with an active system. In previous studies, several methods have been suggested to evaluate passive system reliability, and many of them estimated the failure probability using thermal-hydraulic analyses and the Monte Carlo method. However, if the functional failure of a passive system is rare, it is difficult to estimate the failure probability using conventional methods owing to their high computational time. In this paper, a procedure for the application of the Chernoff bound to the evaluation of passive system reliability is proposed. A feasibility study of the procedure was conducted on a passive decay heat removal system of a micro modular reactor in its conceptual design phase, and it was demonstrated that the passive system reliability can be evaluated without performing a large number of thermal-hydraulic analyses or Monte Carlo simulations when the system has a small failure probability. Accordingly, the advantages and constraints of applying the Chernoff bound for passive system reliability evaluation are discussed in this paper.

Keywords

Acknowledgement

This research was supported by grants from the Nuclear Safety Research Program of the Korea Foundation of Nuclear Safety, with financial resources from the Multi-Unit Risk Research Group (MURRG) and funding from the Korean government's Nuclear Safety and Security Commission (Grant Code: 1705001), and the Nuclear Research & Development Program of the National Research Foundation of Korea, with funding from the Korean government's Ministry of Science and ICT (Grant number NRF-2017M2B2B1071973).

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