検索対象:     
報告書番号:
※ 半角英数字
 年 ~ 
 年

Event sequence assessment using plant dynamics analysis based on continuous Markov chain process with Monte Carlo sampling assessment of strong wind hazard in sodium cooled fast reactor

ナトリウム冷却高速炉における連続マルコフ過程モンテカルロ法を用いたプラント状態定量化研究

高田 孝; 東 恵美子*; 西野 裕之; 山野 秀将; 堺 公明*

Takata, Takashi; Azuma, Emiko*; Nishino, Hiroyuki; Yamano, Hidemasa; Sakai, Takaaki*

外部ハザード事象におけるプラントの様々な状態を定量化することを目的に、連続マルコフ過程モンテカルロ(CMMC)法と動特性解析手法とのカップリングを行った。本論文では強風事象を対象とし、開発手法を用いた定量化を行った結果、対象としたプラントにおける強風事象への耐性が高いことを明らかにした。また低頻度事象に対する手法適用拡張として、重み付けを用いたサンプル方法について提案した。

A new approach has been developed to assess event sequences under external hazard condition considering a plant status quantitatively and stochastically so as to take various scenarios into account automatically by applying a Continuous Markov Chain Monte Carlo (CMMC) method coupled with a plant dynamics analysis. In the paper, a strong wind is selected as the external hazard to assess the plant safety in a loop type sodium cooled fast reactor. As a result, it is demonstrated that the plant state is quite safe in case of the strong wind because multiple failures of the air coolers in the auxiliary cooling system (ACS) has a quite low probability. Furthermore, a weight factor is introduced so as to investigate the low failure probability events with a comparative small number of the sampling.

Access

:

- Accesses

InCites™

:

Altmetrics

:

[CLARIVATE ANALYTICS], [WEB OF SCIENCE], [HIGHLY CITED PAPER & CUP LOGO] and [HOT PAPER & FIRE LOGO] are trademarks of Clarivate Analytics, and/or its affiliated company or companies, and used herein by permission and/or license.