Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Shimada, Kazumasa; Sakurahara, Tatsuya*; Reihani, S.*; Mohagehgh, Z.*
Proceedings of Asian Symposium on Risk Assessment and Management 2020 (ASRAM 2020) (Internet), 12 Pages, 2020/11
Level 3 Probabilistic Risk Assessment (Level 3 PRA) and Traffic simulation were integrated to evaluate the effects of evacuation more realistically on radiation exposure to residents in the offsite consequence analysis. In this study, WinMACCS was used as the Level 3 PRA code. As a test case, the Sequoyah Nuclear Power Plant(NPP) site, which was targeted by the State-of-the-Art Reactor Consequence Analyzes (SOARCA) issued by U.S. Nuclear Regulatory Commission in 2017, was adopted. The MultiAgent Transport Simulation (MATSim) was used to simulate the evacuation of a Sequoyah NPP's 10-mile Emergency Planning Zone. For the transportation route choice, the route where each vehicle chooses the shortest distance and the route where the total evacuation time is shortened by iterative calculation were chosen. In the calculation of MACCS, the source term with the shortest release start time in the SOARCA report was adopted. As an example of the results, the radiation dose of the residents when the evacuation time was optimized was reduced by about 30% from the dose when the shortest distance was selected. Furthermore, a sensitivity analysis was conducted, and it was shown that the evacuation preparation time was the largest factor that contributed to the radiation dose to residents.
Kubo, Kotaro; Zheng, X.; Ishikawa, Jun; Sugiyama, Tomoyuki; Jang, S.*; Takata, Takashi*; Yamaguchi, Akira*
Proceedings of Asian Symposium on Risk Assessment and Management 2020 (ASRAM 2020) (Internet), 11 Pages, 2020/11
Dynamic probabilistic risk assessment (PRA) enables a more realistic and detailed analysis than classical PRA. However, the trade-off for these improvements is the enormous computational cost associated with performing a large number of thermal-hydraulic (TH) analyses. In this study, based on machine learning (ML), we aim to reduce these costs by skipping the TH analysis. For the ML algorithm, we selected a support vector machine; we built it using a high-fidelity/high-cost detailed model and low-fidelity/low-cost simplified model. As a result, the computational costs could be reduced by approximately 80% without significantly decreasing the accuracy under the assumed conditions.
Nishino, Hiroyuki; Kurisaka, Kenichi; Naruto, Kenichi*; Gondai, Yoji; Yamamoto, Masaya; Yamano, Hidemasa
Proceedings of Asian Symposium on Risk Assessment and Management 2020 (ASRAM 2020) (Internet), 12 Pages, 2020/11
The objective of this study is to evaluate the occurrence frequency of accident sequences which may lead to core damage if provisions in defense in depth (DiD) level 1 to 3 are the only safety measures. For this objective, the existing safety measures in this SFR are categorized into those for the DiD level 1-3 and those for the DiD level 4. The safety measures for the DiD level 1-3 are as follows; (1) main reactor shutdown system, (2) double boundary structure in the primary main and auxiliary cooling system and the reactor vessel, which maintain the reactor coolant level sufficient for coolant circulation in the primary main cooling system, (3) decay heat removal in a forced circulation mode. Accident sequences are categorized into typical SFR-specific groups and station blackout (SBO) in this study. The SFR-specific groups are unprotected loss of flow, unprotected transient over power, unprotected loss of heat sink, loss of reactor level, and protected loss of heat sink (PLOHS). The occurrence frequency of these accident sequence groups was quantified to identify major contributors. As the result, PLOHS excluding SBO was indicated as the dominant contribution of 80% or more in the all accident sequence groups and the annual occurrence frequency of the PLOHS was 1.0E-4 order of magnitude. For the PLOHS, loss of offsite power (LOOP) was indicated as major contribution of 30% in initiating events. In the accident sequences of the PLOHS initiated from LOOP, a dominant sequence was combination of common cause failure of primary pumps in the main cooling system and failure-to-start of the auxiliary cooling system after LOOP. The second dominant contribution (15% or more) in the all accident sequence groups is PLOHS in SBO (i.e., decay heat removal failure due to SBO). Each of the other accident sequence groups was 1%.
Matsumoto, Toshinori; Iwasawa, Yuzuru; Ajima, Kohei*; Sugiyama, Tomoyuki
Proceedings of Asian Symposium on Risk Assessment and Management 2020 (ASRAM 2020) (Internet), 10 Pages, 2020/11
The probability of ex-vessel debris coolability under the wet cavity strategy is analyzed. The first step is the uncertainty analyses by severe accident analysis code MELCOR to obtain the melt condition. Five uncertain parameters which are relating with the core degradation and transfer process were chosen. Input parameter sets were generated by LHS. The analyses were conducted and the conditions of the melt were obtained. The second step is the analyses for the behavior of melt under the water by JASMINE code. The probabilistic distribution of parameters are determined from the results of MELCOR analyses. Fifty-nine parameter sets were generated by LHS. The depth of water pool is set to be 0.5, 1.0 and 2.0 m. Debris height were compared with the criterion to judge the debris coolability. As the result, the success probability of debris cooling was obtained through the sequence of calculations. The technical difficulties of this evaluation method are also discussed.