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research-article

RESEARCH AND DEVELOPMENT OF A SEISMIC PROBABILISTIC SAFETY ANALYSIS QUANTIFICATION TOOL

[+] Author and Article Information
Wei Gao

Shanghai Nuclear Engineering Research & Design Institute, No.29 Hongcao Road, Shanghai, China, 200233
gaowei@snerdi.com.cn

Guofeng Tang

Shanghai Nuclear Engineering Research & Design Institute, No.29 Hongcao Road, Shanghai, China, 200233
tangguofeng@snerdi.com.cn

Jingyu Zhang

Shanghai Nuclear Engineering Research & Design Institute, No.29 Hongcao Road, Shanghai, China, 200233
zhangjy@snerdi.com.cn

Qinfang Zhang

Shanghai Nuclear Engineering Research & Design Institute, No.29 Hongcao Road, Shanghai, China, 200233
zhangqf@snerdi.com.cn

1Corresponding author.

ASME doi:10.1115/1.4039967 History: Received October 11, 2017; Revised April 03, 2018

Abstract

Shanghai Nuclear Engineering Research and Design Institute (SNERDI) has been studying seismic risk analysis for nuclear power plant for a long time, and completed Seismic Margin Analysis (SMA) for several plants. After Fukushima accident, seismic risk has drawn an increasing attention worldwide, and the regulatory body in China has also required the utilities to conduct a detailed analysis for seismic risk. So we turned our focus on a more intensive study of Seismic Probabilistic Safety Assessment (PSA/PRA) for nuclear power plant in recent years. Since quantification of seismic risk is a key part in Seismic PSA, lots of efforts have been devoted to its research by SNERDI. The quantification tool is the main product of this research, and will be discussed in detail in this paper. First, a brief introduction to Seismic PSA quantification methodology is presented in this paper, including fragility analysis on system or plant level, convolution of seismic hazard curves and fragility curves, and uncertainty analysis as well. To derive more accurate quantification results, the binary decision diagram (BDD) algorithm was introduced into the quantification process, which effectively reduces the deficiency of the conventional method on coping with large probability events and negated logic. Finally, this paper introduced the development of the seismic PSA quantification tool based on the algorithms discussed in this paper. Tests and application has been made for this software based on a specific nuclear power plant seismic PSA model.

Copyright (c) 2018 by ASME
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