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Li, C.-Y.; Watanabe, Akira*; Uchibori, Akihiro; Okano, Yasushi
Proceedings of 30th International Conference on Nuclear Engineering (ICONE30) (Internet), 10 Pages, 2023/05
Nakashima, Risako*; Koike, Akari*; Sakai, Takaaki*; Doda, Norihiro; Tanaka, Masaaki
Proceedings of 29th International Conference on Nuclear Engineering (ICONE 29) (Internet), 6 Pages, 2022/08
In development of a quantitative risk assessment method to the external hazards for a sodium-cooled fast reactor, a dynamic PRA using the Continuous Markov chain Monte Carlo (CMMC) method was performed to evaluate the effect of global warming on the probability of exceeding the temperature limit as a core damage factor. There is a possibility that the amount of snowfall in abnormal snowfall events will increase due to global warming in the future. A hazard curve of snowfall considering global warming was developed. The results show that the probability of exceeding the temperature limit is increased by the abnormal snowfall events due to global warming.
Li, C.-Y.; Watanabe, Akira*; Uchibori, Akihiro; Okano, Yasushi
Dai-26-Kai Doryoku, Enerugi Gijutsu Shimpojiumu Koen Rombunshu (Internet), 4 Pages, 2022/07
Identifying accident scenarios that could lead to severe accidents and evaluating their frequency of occurrence are essential issues. This study aims to establish the methodology of the dynamic Probabilistic Risk Assessment (PRA) for sodium-cooled fast reactors that can consider the time dependency and the interdependence of each event. Specifically, the Continuous Markov chain Monte Carlo (CMMC) method is newly applied to the SPECTRA code, which analyzes the severe accident conditions of nuclear reactors, to develop an evaluation methodology for typical external hazards. Currently, a fault-tree model of air coolers of decay heat removal system is implemented as the CMMC method, and a series of preliminary analysis of the plant's transient characteristics under the scenario of volcanic ashfall has been conducted.
Suzuki, Minoru*; Sakai, Takaaki*; Takata, Takashi; Doda, Norihiro
Proceedings of 27th International Conference on Nuclear Engineering (ICONE-27) (Internet), 7 Pages, 2019/05
With an aim to establish a quantitative risk assessment of accident managements (AMs) for various external hazards, the plant dynamics analyses with Continuous Markov Chain Monte Carlo (CMMC) method were carried out to assess repeatedly occurred multi-failures by volcano ash in volcanic eruption event. AM repetition of the filter exchange to recover the cooling function of the air coolers were considered. The results showed that this method can evaluate the effectiveness of AM measures against volcanic ash fall events with respect to time progress.
Takata, Takashi; Azuma, Emiko*
Journal of Nuclear Science and Technology, 53(11), p.1749 - 1757, 2016/11
Times Cited Count：5 Percentile：43.12(Nuclear Science & Technology)Margin assessment of a nuclear power plant against external hazards is one of the most important issues after Fukushima Dai-ichi Nuclear Power Plant Accident. In this paper, a new approach has been developed to assess the plant status during external hazards and countermeasures against them in operation quantitatively and stochastically. A Continuous Markov chain Monte Carlo (CMMC) method is applied and coupled with a plant dynamics analysis. In the CMMC method, a subsequence plant status is determined by the latest state (Markov chain) and the status is evaluated from the plant dynamics analysis. A failure or success of safety function of plant component is also evaluated stochastically based on a latest state of plant or hazard. A numerical investigation of plant dynamics analysis against a snow hazard is also carried out in a loop type sodium cooled fast reactor so as to assess the margin against the hazard.
Takata, Takashi; Azuma, Emiko*; Nishino, Hiroyuki; Yamano, Hidemasa; Sakai, Takaaki*
Proceedings of 10th Japan-Korea Symposium on Nuclear Thermal Hydraulics and Safety (NTHAS-10) (USB Flash Drive), 6 Pages, 2016/11
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.
Takata, Takashi; Azuma, Emiko*
Proceedings of 13th Probabilistic Safety Assessment and Management Conference (PSAM-13) (USB Flash Drive), 10 Pages, 2016/10
A new approach has been developed to assess event sequences under external hazard 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 tornado and a strong wind are selected as the external hazard to assess the plant safety in a loop type sodium cooled fast reactor (SFR). As a result, it is demonstrated that the various scenarios where the order of the occurrence event and its occurrence time differs from each other can be assessed simultaneously as well as the statistical characteristics of plant parameter such as the coolant temperature. Furthermore, a weight factor is introduced so as to investigate the low failure probability events with a comparative small number of the sampling.
Jang, S.*; Yamaguchi, Akira*; Takata, Takashi
Proceedings of 13th Probabilistic Safety Assessment and Management Conference (PSAM-13) (USB Flash Drive), 11 Pages, 2016/10
The current approach to Level 2 probabilistic risk assessment (PRA) using the conventional event-tree (ET)/fault-tree (FT) methodology requires pre-specifications of event order occurrence and component failure probabilities which may vary significantly in the presence of uncertainties. In the present study, a new methodology is proposed to quantify the level 2 PRA in which the accident progression scenarios are dynamic and interactive with the instantaneous plant state and related phenomena. The accident progression is treated as a continuous Markov process and the transition probabilities are evaluated based on the computation of plant system thermal-hydraulic dynamics. A Monte Carlo method is used to obtain the resultant probability of the radioactive material release scenarios. The methodology is applied to the protected loss of heat sink accident scenario of the level 2 PRA of a generation IV fast reactor.
Takata, Takashi
no journal, ,
In the present paper, a numerical quantification of a plant status in sodium-cooled fast reactor has been carried out based on a continuous Markov chain Monte Carlo (CMMC) method under a strong rainfall hazard. For this purpose, a numerical tool where a water level of each compartment is calculated considering such as a penetration to compartment, a transport via opening or pathway and a drain and is coupled with the CMMC method.
Suzuki, Minoru*; Takase, Yuki*; Sakai, Takaaki*; Takata, Takashi; Doda, Norihiro
no journal, ,
With an aim to establish a quantitative risk assessment of accident managements (AMs) for various external hazards, the plant dynamics analyses with Continuous Markov Chain Monte Carlo (CMMC) method were carried out to assess repeatedly occurred multi-failures by volcano ash in volcanic eruption event. AM repetition of the filter exchange to recover the cooling function of the air coolers were considered. The results showed that this method can evaluate the effectiveness of AM measures against volcanic ash fall events with respect to time progress.
Suzuki, Minoru*; Sakai, Takaaki*; Takata, Takashi; Doda, Norihiro
no journal, ,
With an aim to establish a quantitative risk assessment of accident managements (AMs) for various external hazards, the plant dynamics analyses with Continuous Markov Chain Monte Carlo (CMMC) method were carried out to assess repeatedly occurred multi-failures by volcano ash in volcanic eruption event. AM repetition of the filter exchange to recover the cooling function of the air coolers (ACs) of auxiliary cooling system (ACS) were considered. The uncertainty of AM measure was set as a parameter. The results showed that extending the endurance time of ACS-AC filter was effective as AM measure against volcanic ash hazard.
Suzuki, Minoru*; Kawashima, Masato*; Sakai, Takaaki*; Doda, Norihiro; Tanaka, Masaaki
no journal, ,
With an aim to establish a quantitative risk assessment of accident managements (AMs) for various external hazards, the plant dynamics analyses with Continuous Markov Chain Monte Carlo (CMMC) method were carried out for AM in cases of the filter exchange to recover the cooling function of the air coolers from soot and smoke and the firefighting from ambient temperature rise in forest fire event. The results indicated that this method can use for evaluation of effectiveness of AM measures repeatedly performed against forest fire events with respect to time progress and the AM measures against rising ambient temperature is important for fast reactors using air-cooling system.
Koike, Akari*; Nakashima, Risako*; Sakai, Takaaki*; Doda, Norihiro; Tanaka, Masaaki
no journal, ,
A dynamic PRA using the Continuous Markov chain Monte Carlo (CMMC) method was performed for a sodium-cooled fast reactor to evaluate abnormal snowfall events in which the snowfall amount tends to increase due to global warming. In the analysis, the probability of exceeding the core outlet temperature limit after 24 hours was evaluated. The loss of functions of the emergency diesel generator and the air cooler due to snowfall and the recovery of the functions by the operator's snow removal as an accident management measure were considered. The results show that snow removal as an accident management measure is not effective under abnormal snowfall conditions with considering global warming.
Nakashima, Risako*; Koike, Akari*; Sakai, Takaaki*; Doda, Norihiro; Tanaka, Masaaki
no journal, ,
There is a possibility that the amount of snowfall in abnormal snowfall events will increase due to global warming in the future. A hazard curve of snowfall considering global warming was developed, and a dynamic PRA using the Continuous Markov chain Monte Carlo (CMMC) method was performed for a sodium-cooled fast reactor to evaluate the effect of global warming on the probability of exceeding the temperature limit as a core damage factor. The results show that the amount of snowfall in abnormal snowfall events is likely to increase due to global warming, and the probability of exceeding the temperature limit increases in that case.
Kuwahara, Yuto*; Demachi, Kazuyuki*; Chen, S.*; Kasahara, Naoto*; Nishino, Hiroyuki; Onoda, Yuichi; Kurisaka, Kenichi
no journal, ,
no abstracts in English
Koike, Akari*; Sakai, Takaaki*; Doda, Norihiro; Tanaka, Masaaki
no journal, ,
To evaluate the effect of the operator's recognition of the accident management (AM) necessity on plant safety, the operator's recognition of the AM necessity was modeled as a function of time-dependent success probability, and dynamic PRA analyses using the Continuous Markov chain Monte Carlo method (CMMC) were performed for a sodium-cooled fast reactor during abnormal snowfall event. The analysis results showed that AM was effective in delaying the core damage and that the recognition timing by the operator was an important factor in avoiding the core damage after the accident.
