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Li, C.-Y.; 渡部 晃*; 内堀 昭寛; 岡野 靖
Proceedings of 30th International Conference on Nuclear Engineering (ICONE30) (Internet), 10 Pages, 2023/05
Quantitative assessment of the effect of accident management on the various external hazards is essential in the nuclear safety analysis. This study aims to establish the dynamic probabilistic risk assessment methodology for sodium-cooled fast reactors that can consider the transient plant status under continuous external hazards with corresponding countermeasures operating stochastically. Specifically, the Continuous Markov chain Monte Carlo (CMMC) and Deterministic and Stochastic Petri Nets (DSPN) methods are newly applied to the severe accident analysis code, SPECTRA, which can conduct dynamic plant evaluation in the different severe accident conditions of nuclear reactors, to develop an evaluation methodology for typical external hazards. In the DSPN-CMMC-SPECTRA coupled frame, the latest safety functions of the plant components/systems can be stochastically determined by the DSPN-CMMC grounded on the current plant states under continuous hazard and the interaction between the multi-state components/systems; then, SPECTRA can evaluate the following plant state determined by the latest safety function of the components/systems. Therefore, the advantage of this newly developed DSPN-CMMC-SPECTRA frame is having the capability to quantitatively and stochastically evaluate the transient accident progressions that potentially lead to the core damage under the continuous external hazard scenario. As for the preliminary exam on the DSPN-CMMC-SPECTRA frame, one of the typical external hazards of continuous volcanic ashfall is selected in this research. In addition, the numerical investigation of alternative accident management' effects has also been carried out and quantitatively confirmed in this research.
Li, C.-Y.; 渡部 晃*; 内堀 昭寛; 岡野 靖
Journal of Nuclear Science and Technology, 23 Pages, 2023/00
被引用回数：1 パーセンタイル：68.31(Nuclear Science & Technology)For all the nuclear reactor systems, quantitative assessment of the accident management (AM) effects against long-term external hazards became one of the essential issues after the lesson learned from the Fukushima Daiichi Nuclear Power Plant accident. However, the influence from the safety systems' stochastic and dynamic shifting between multiple working states, which is related to the interaction with the adjacent components/systems in general, has not been accounted for yet. Therefore, this research aims to develop a dynamic probability risk assessment tool considering repairable multi-component interdependency for investigating the AM influences on the multi-state safety systems under long-term external hazards. Based on the newly proposed methodology in this research via integrating the Petri Net (PN) model with the continuous Markov chain Monte Carlo (CMMC) method, a framework applying PN-CMMC methodology to a severe accident analysis code, SPECTRA, had been originally constructed. Different AM influences on the multi-state decay heat removal systems against long-term volcanic ashfall were also quantitatively confirmed, indicating that halving the repairing time is more influential in suppressing the core damage frequency than doubling the number of adjacent electricity support systems. Therefore, the PN-CMMC-SPECTRA framework can further assess the uncharted dynamic multi-state concerns, leading to a safer AM strategy.
