A quantification methodology of Seismic Probabilistic Safety Assessment for nuclear power plant
Introduction
A Probabilistic Safety Assessment (PSA), together with deterministic safety analysis, is used to assess the risks associated with operating nuclear power plants. The PSA consists largely of internal and external events including fires, seismic events, and floods in the case of external events. Since the Fukushima nuclear accident caused by the Great East Japan Earthquake in 2011, the importance of Seismic Probability Safety Assessment (SPSA) has been emphasized. Seismic events have different characteristics from other external events, which can cause simultaneous failure in many Structures, Systems and Components (SSCs). Because the probability of seismic-induced failure has a value of close to 1 (total failure), the Core Damage Frequency (CDF) can be overestimated with the conventional methodology. Several solutions to this problem have been proposed, but all of them have methodological limitations. In this paper, we examine the seismic quantification methodologies developed so far and propose a new methodology that can overcome the deficiencies of the existing methodologies. In Chapter 2, we examine the seismic event quantification methodologies currently used and compare their strengths and weaknesses. In Chapters 3 and 4, we explain our proposed methodology, discuss the results of its application, and explain the pros and cons of this new methodology. Finally, in Chapter 5, we summarize our results.
Section snippets
Comparison of recent SPSA methodologies
In this chapter, we examine three seismic quantification methodologies used in SPSA. These methods include the Binary Decision Diagram (BDD), the Rare Events Approximation (REA) and Minimal Cutset Upper Bound (MCUB) method, and the Monte Carlo Simulation method.
Monte Carlo Simulation Allocation method (MCSAM) for SPSA
Our proposed method combines the Monte Carlo Simulation and the REA and MCUB methods described above. The Monte Carlo Simulation method is to compute the exact CDF and MCSs generated by the REA and MCUB method are allocated by suggested Allocation Rules. The MCS (Minimal Cut Set) database through the REA and MCUB method represents a general solution for exact MCSs, and the Monte Carlo Simulation method provides an accurate CDF and the combinations of events that cause core damage. The flow
Case study for a seismic-induced loss of offsite power (LOOP) accident
To verify the proposed quantification method, we developed a simplified model for a seismic-induced Loss of Offsite Power (LOOP) and applied it to this case study. The offsite power system is most vulnerable to earthquakes and the LOOP may happen when an earthquake with seismic acceleration exceeding OBE occurs in most nuclear power plant. In addition, LOOP shows the steps required to achieve a typical safety shutdown procedure during normal power plant operation.
Conclusions
In this work, we proposed a new quantification methodology for SPSAs. MCSAM was proposed to overcome the shortcomings of over-estimating the CDF and the inaccuracy of MCS derivation with existing methods. The characteristics of MCSAM are as follows:
- •
Contributes to the accuracy of a Level 2 PSA by deriving the exact probability of each sequence.
- •
Identifies the most vulnerable SSCs by deriving the exact CDF and MCSs.
- •
Intuitive analysis is possible as the number of MCSs is significantly reduced
CRediT authorship contribution statement
Junghyun Ryu: Methodology, Validation, Formal analysis, Investigation, Visualization, Writing - original draft. Moosung Jae: Conceptualization, Methodology, Validation, Writing - review & editing, Supervision.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This work was supported by the Nuclear Safety Research Program through the Korea Foundation of Nuclear Safety (KOFONS), granted financial resource from the Multi-Unit Risk Research Group, Republic of Korea (No. 1705001).
References (12)
- et al.
In-Kil Choi, Jin-Hee Park, Uncertainty analysis of system fragility for seismic safety evaluation of NPP
Nucl. Eng. Des.
(2011) A method to improve cutset probability calculation in probabilistic safety assessment of nuclear power plants
Reliab. Eng. Syst. Saf.
(2015)- et al.
Development of systems reliability analysis code SECOM-2 for seismic PSA
Reliab. Eng. Syst. Saf.
(1998) - EQE International, Inc., 1995. EQESRA, Reference Document, Version...
- EPRI, December 2013. Seismic Probabilistic Risk Assessment Implementation Guide,...
- KOFONS, 2017. Development of High-Performance Minimal Cut Set Analyzer for Nuclear Safety Regulation, N-STAR...
Cited by (1)
Reliability assignment of a heavy-duty CNC machine tool spindle system based on fault tree analysis
2022, International Journal of Reliability and Safety