Application of quasi-Monte Carlo and importance sampling to Monte Carlo-based fault tree quantification for seismic probabilistic risk assessment of nuclear power plants-Reference-Cited by-同舟云学术

Application of quasi-Monte Carlo and importance sampling to Monte Carlo-based fault tree quantification for seismic probabilistic risk assessment of nuclear power plants

Published:2023 Issue:4 Volume:10 Page:23-00051-23-00051
ISSN:2187-9745
Container-title:Mechanical Engineering Journal
language:en
Short-container-title:

Author:

KUBO Kotaro¹,TANAKA Yoichi¹,HAKUTA Yuto²,ARAKE Daisuke²,UCHIYAMA Tomoaki²,MURAMATSU Ken¹

Affiliation:

1. Japan Atomic Energy Agency

2. Computer Simulation & Analysis of Japan Co., Ltd.

Publisher

Japan Society of Mechanical Engineers

Subject

Process Chemistry and Technology,Economic Geology,Fuel Technology

Link

https://www.jstage.jst.go.jp/article/mej/10/4/10_23-00051/_pdf

Reference36 articles.

1. Atomic Energy Society of Japan, A standard for procedure of seismic probabilistic risk assessment for nuclear power plants, AESJ-SC-P006E:2015 (2020).

2. Box, GEP and. Muller, ME., A note on the generation of random normal deviates, The Annals of Mathematical Statistics, Vol.29, No.2 (2017), pp.610–611.

3. Budnitz, RJ., Hardy, GS., Moore, DL. and Rabindra, MK., Correlation of seismic performance in similar SSCs (Structures, Systems, and Components), NUREG/CR-7237 (2017).

4. Diaconeasa, MA. and Mosleh, A., Discrete dynamic event tree uncertainty quantification in the ADS-IDAC dynamic PSA software platform, Proceedings of 14th International Conference on Probabilistic Safety Assessment and Management (PSAM14) (2018), Paper No. 223.

5. Electric Power Research Institute. CAFTA fault tree analysis system, version 6.0b. Software manual. EPRI Report 3002004316 (2014).

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