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Research Papers

Development of a Seismic Probabilistic Safety Assessment Quantification Tool

[+] Author and Article Information
Wei Gao

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

Guofeng Tang

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

Jingyu Zhang

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

Qinfang Zhang

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

1Corresponding author.

Manuscript received October 11, 2017; final manuscript received April 3, 2018; published online September 10, 2018. Assoc. Editor: Jovica R. Riznic.

ASME J of Nuclear Rad Sci 4(4), 041005 (Sep 10, 2018) (6 pages) Paper No: NERS-17-1148; doi: 10.1115/1.4039967 History: Received October 11, 2017; Revised April 03, 2018

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 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 have been made for this software based on a specific nuclear power plant seismic PSA model.

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References

EPRI, 2013, “ Seismic Probabilistic Risk Assessment Implementation Guide,” Electric Power Research Institute, Palo Alto, CA, Report No. 000000000001002989 https://www.epri.com/#/pages/product/1002989/.
GU, T. , and XU, Z. , 2009, Ordered Binary Decision Diagram and Its Application, Science Press, Beijing, pp. 18–19.
Rauzy, A. , 1993, “ New Algorithms for Fault Trees Analysis,” Reliab. Eng. Syst. Saf., 40(3), pp. 2–5. [CrossRef]

Figures

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Fig. 1

Structure of seismic risk quantification tool

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Fig. 2

Binary tree of f = f(x1, x2, x3) = (x1 + x2)x3: (a) after first Shannon decomposition and (b) final binary tree

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Fig. 4

Binary decision diagram form of f = (A + B)(B + C)(C + D)

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Fig. 5

Uncertainty analysis results

Tables

Errata

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