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

Jae‐Hyun Cho · Sang Hun Lee · Jaewhan Kim · Seong Kyu Park

24 citations0/0 files storedReliability Engineering & System Safety

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Risk and Safety Analysis Nuclear and radioactivity studies Nuclear Engineering Thermal-Hydraulics

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.

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References

1981On The Quantitative Definition of Risk 1998Use of importance measures in risk-informed regulatory applications 2007DEPEND-HRA—A method for consideration of dependency in human reliability analysis 2018Multi-unit Level 1 probabilistic safety assessment: Approaches and their application to a six-unit nuclear power plant site 2018Multi-unit Level 2 probabilistic safety assessment: Approaches and their application to a six-unit nuclear power plant site 2000Quantifying human and organizational factors in accident management using decision trees: the HORAAM method

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