Work

Framework to model severe accident management guidelines into Level 2 probabilistic safety assessment of a nuclear power plant

Year: 2021

Type: article

Abstract: Severe accident management guidelines (SAMG) play a significant role in mitigating severe accidents in nuclear power plants (NPPs), and thus the modeling of SAMG into Level 2 probabilistic safety assessment (PSA) has become essential to more realistically quantify the safety of NPPs and the effectiveness of SAMG. This study developed a systematic framework to model SAMG into Level 2 PSA, in which SAMG event trees and fault trees are modeled to formulate SAMG in a probabilistic manner. Application results to the internal events of a real plant, the OPR-1000, showed that the inclusion of SAMG in the Level 2 PSA model led to not only a significant increase in the conditional containment intact probability, from 37 to 70%, but also a considerable decrease in NPP risk, namely by 44% compared to the case without SAMG. The method can be used for the estimation of the effectiveness of each mitigation strategy, as well as for the identification of the risk-significant factors regarding SAMG.

Source: Reliability Engineering & System Safety

DOI: 10.1016/j.ress.2021.108076

Authors: Jaehyun Cho, Sang Hun Lee, Jaewhan Kim, Seong Kyu Park

Institution: Korea Atomic Energy Research Institute

Language: English

Topic: Risk and Safety Analysis

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,600

Funders: National Research Foundation, Ministry of Science, ICT and Future Planning, National Research Foundation of Korea, Ministry of Science and ICT, South Korea