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Muramatsu, Ken; Kubo, Kotaro; Choi, B.; Nishida, Akemi; Takada, Tsuyoshi
Transactions of 27th International Conference on Structural Mechanics in Reactor Technology (SMiRT 27) (Internet), 10 Pages, 2024/03
no abstracts in English
Kubo, Kotaro; Zheng, X.; Tanaka, Yoichi; Tamaki, Hitoshi; Sugiyama, Tomoyuki; Jang, S.*; Takata, Takashi*; Yamaguchi, Akira*
Proceedings of the Institution of Mechanical Engineers, Part O; Journal of Risk and Reliability, 237(5), p.947 - 957, 2023/10
Times Cited Count：4 Percentile：69.72(Engineering, Multidisciplinary)Probabilistic risk assessment (PRA) is a method used to assess the risks associated with large and complex systems. However, the timing at which nuclear power plant structures, systems, and components are damaged is difficult to estimate if the risk of an external event is evaluated using conventional PRA based on event trees and fault trees. A methodology coupling thermal-hydraulic analysis with external event simulations using Risk Assessment with Plant Interactive Dynamics (RAPID) is therefore proposed to overcome this limitation. A flood propagation model based on Bernoulli's theorem was applied to represent internal flooding in the turbine building of the pressurized water reactor. Uncertainties were also taken into account, including the flow rate of the floodwater source and the failure criteria for the mitigation systems. The simulated recovery actions included the operator isolating the floodwater source and using a drainage pump; these actions were modeled using several simplifications. Overall, the results indicate that combining isolation and drainage can reduce the conditional core damage probability upon the occurrence of flooding by approximately 90%.
Kubo, Kotaro; Tanaka, Yoichi; Hakuta, Yuto*; Arake, Daisuke*; Uchiyama, Tomoaki*; Muramatsu, Ken
Mechanical Engineering Journal (Internet), 10(4), p.23-00051_1 - 23-00051_17, 2023/08
The significance of probabilistic risk assessments (PRAs) of nuclear power plants against external events was re-recognized after the Fukushima Daiichi Nuclear Power Plant accident. Regarding the seismic PRA, handling correlated failures of systems, components, and structures (SSCs) is very important because this type of failure negatively affects the redundancy of accident mitigation systems. The Japan Atomic Energy Research Institute initially developed a fault tree quantification methodology named the direct quantification of fault tree using Monte Carlo simulation (DQFM) to handle SSCs' correlated failures in detail and realistically. This methodology allows quantifying the top event occurrence probability by considering correlated uncertainties related to seismic responses and capacities with Monte Carlo sampling. The usefulness of DQFM has already been demonstrated. However, improving its computational efficiency would allow risk analysts to perform several analyses. Therefore, we applied quasi-Monte Carlo and importance sampling to the DQFM calculation of simplified seismic PRA and examined their effects. Specifically, the conditional core damage probability of a hypothetical pressurized water reactor was analyzed with some assumptions. Applying the quasi-Monte Carlo sampling accelerates the convergence of results at intermediate and high ground motion levels by an order of magnitude over Monte Carlo sampling. The application of importance sampling allows us to obtain a statistically significant result at a low ground motion level, which cannot be obtained through Monte Carlo and quasi-Monte Carlo sampling. These results indicate that these applications provide a notable acceleration of computation and raise the potential for the practical use of DQFM in risk-informed decision-making.
Kubo, Kotaro
Science and Technology of Nuclear Installations, 2023, p.7402217_1 - 7402217_12, 2023/06
Times Cited Count：0 Percentile：0.01(Nuclear Science & Technology)Kubo, Kotaro; Jang, S.*; Takata, Takashi*; Yamaguchi, Akira*
Journal of Nuclear Science and Technology, 60(4), p.359 - 373, 2023/04
Times Cited Count：5 Percentile：78.52(Nuclear Science & Technology)Probabilistic risk assessment (PRA) is an essential approach to improving the safety of nuclear power plants. However, this method includes certain difficulties, such as modeling of combinations of multiple hazards. Seismic-induced flooding scenario includes several core damage sequences, i.e., core damage caused by earthquake, flooding, and combination of earthquake and flooding. The flooding fragility is time-dependent as the flooding water propagates from the water source such as a tank to compartments. Therefore, dynamic PRA should be used to perform a realistic risk analysis and quantification. This study analyzed the risk of seismic-induced flooding events by coupling seismic, flooding, and thermal-hydraulics simulations, considering the dependency between multiple hazards explicitly. For requirements of safety improvement, especially in light of the Fukushima Daiichi Nuclear Power Plant accident, sensitivity analysis was performed on the seismic capacity of systems, and the effectiveness of alternative steam generator injection by a portable pump was estimated. We demonstrate the use of this simulation-based dynamic PRA methodology to evaluate the risk induced by a combination of hazards.
Kubo, Kotaro; Tanaka, Yoichi*; Ishikawa, Jun
Proceedings of the Institution of Mechanical Engineers, Part O; Journal of Risk and Reliability, 11 Pages, 2023/00
Times Cited Count：0 Percentile：0.01(Engineering, Multidisciplinary)Kubo, Kotaro; Fujiwara, Keita*; Tanaka, Yoichi; Hakuta, Yuto*; Arake, Daisuke*; Uchiyama, Tomoaki*; Muramatsu, Ken*
Proceedings of 29th International Conference on Nuclear Engineering (ICONE 29) (Internet), 8 Pages, 2022/08
After the Fukushima Daiichi Nuclear Power Plant accident, the importance of conducting probabilistic risk assessments (PRAs) of external events, especially seismic activities and tsunamis, was recognized. The Japan Atomic Energy Agency has been developing a computational methodology for seismic PRA, called the direct quantification of fault tree using Monte Carlo simulation (DQFM). When appropriate correlation matrices are available for seismic responses and capacities of components, the DQFM makes it possible to consider the effect of correlated failures of components connected through AND and/or OR gates in fault trees, which is practically difficult when methods using analytical solutions or multidimensional numerical integrations are used to obtain minimal cut set probabilities. The usefulness of DQFM has already been demonstrated. Nevertheless, a reduction of the computational time of DQFM would allow the large number of analyses required in PRAs conducted by regulators and/or operators. We; therefore, performed scoping calculations using three different approaches, namely quasi-Monte Carlo sampling, importance sampling, and parallel computing, to improve calculation efficiency. Quasi-Monte Carlo sampling, importance sampling, and parallel computing were applied when calculating the conditional core damage probability of a simplified PRA model of a pressurized water reactor, using the DQFM method. The results indicated that the quasi-Monte Carlo sampling works well at assumed medium and high ground motion levels, importance sampling is suitable for assumed low ground motion level, and that parallel computing enables practical uncertainty and importance analysis. The combined implementation of these improvements in a PRA code is expected to provide a significant acceleration of computation and offers the prospect of practical use of DQFM in risk-informed decision-making.
Brumm, S.*; Gabrielli, F.*; Sanchez-Espinoza, V.*; Groudev, P.*; Ou, P.*; Zhang, W.*; Malkhasyan, A.*; Bocanegra, R.*; Herranz, L. E.*; Berda
, M.*; et al.
Proceedings of 10th European Review Meeting on Severe Accident Research (ERMSAR 2022) (Internet), 13 Pages, 2022/05
Kubo, Kotaro; Jang, S.*; Takata, Takashi*; Yamaguchi, Akira*
Journal of Nuclear Science and Technology, 59(3), p.357 - 367, 2022/03
Times Cited Count：5 Percentile：65.59(Nuclear Science & Technology)Dynamic probabilistic risk assessment (PRA), which handles epistemic and aleatory uncertainties by coupling the thermal-hydraulics simulation and probabilistic sampling, enables a more realistic and detailed analysis than conventional PRA. However, enormous calculation costs are incurred by these improvements. One solution is to select an appropriate sampling method. In this paper, we applied the Monte Carlo, Latin hypercube, grid-point, and quasi-Monte Carlo sampling methods to the dynamic PRA of a station blackout sequence in a boiling water reactor and compared each method. The result indicated that quasi-Monte Carlo sampling method handles the uncertainties most effectively in the assumed scenario.
Kubo, Kotaro; Tanaka, Yoichi
Proceedings of Asian Symposium on Risk Assessment and Management 2021 (ASRAM 2021) (Internet), 13 Pages, 2021/10
Probabilistic risk assessment (PRA) is extensively used, e.g., in periodical safety review and the reactor oversight process, in nuclear regulation systems to improve the safety of nuclear power plants; however, one limitation of classical PRA is the handling of temporal information such as system failure and core damage timings. To resolve this limitation, the dynamic PRA method has been developed and applied for multiple safety issues; however, its improvement is accompanied by considerable computational costs. In this study, we applied the polynomial chaos expansion (PCE) technique to dynamic PRA with the expectation of reduction in computational cost. In particular, to estimate core damage timing, a PCE-based surrogate model was developed. Then, the surrogate model was applied to dynamic PRA to calculate the conditional core damage probability and core damage timing. Consequently, applying the PCE might efficiently perform these analyses without considerable reduction in accuracy.
Kubo, Kotaro; Tanaka, Yoichi
Proceedings of 31st European Safety and Reliability Conference (ESREL 2021) (Internet), p.810 - 817, 2021/09
Probabilistic risk assessment (PRA) is a method of effectively evaluating risks in nuclear power plants and is used in various agencies. Dynamic PRA is attracting considerable attention, as it enables realistic assessment by reducing the assumptions and engineering judgments related to time-dependent failure probability and/or human action reliability. However, it is difficult to remove all assumptions and engineering judgments. Therefore, their effects on assessment results should be understood. This study focuses on the "risk dilution effect," which arises from assumptions about uncertainty. Results showed that this effect causes a difference of about 10% to 20% in the relative change of the conditional core damage probability in the station blackout scenario. This effect should be fully considered when using dynamic PRA in critical decision-making, such as that on regulations.
Kubo, Kotaro; Zheng, X.; Tanaka, Yoichi; Tamaki, Hitoshi; Sugiyama, Tomoyuki; Jang, S.*; Takata, Takashi*; Yamaguchi, Akira*
Proceedings of 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL 2020 and PSAM-15) (Internet), p.2279 - 2286, 2020/11
Probabilistic risk assessment (PRA) is one of the methods used to assess the risks associated with large and complex systems. When the risk of an external event is evaluated using conventional PRA, a particular limitation is the difficulty in considering the timing at which nuclear power plant structures, systems, and components fail. To overcome this limitation, we coupled thermal-hydraulic and external-event simulations using Risk Assessment with Plant Interactive Dynamics (RAPID). Internal flooding was chosen as the representative external event, and a pressurized water reactor plant model was used. Equations based on Bernoulli's theorem were applied to flooding propagation in the turbine building. In the analysis, uncertainties were taken into account, including the flow rate of the flood water source and the failure criteria for the mitigation systems. In terms of recovery action, isolation of the flood water source by the operator and drainage using a pump were modeled based on several assumptions. The results indicate that the isolation action became more effective when combined with drainage.
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.
Kubo, Kotaro; Zheng, X.; Tanaka, Yoichi; Tamaki, Hitoshi; Sugiyama, Tomoyuki; Jang, S.*; Takata, Takashi*; Yamaguchi, Akira*
Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.308 - 315, 2020/10
Dynamic probabilistic risk assessment (PRA) is a method for improving the realism and completeness of conventional PRA. However, enormous calculation costs are incurred by these improvements. One solution is to select an appropriate sampling method. In this paper, we applied the Monte Carlo, Latin hypercube, grid-point, and quasi-Monte Carlo sampling methods to the dynamic PRA of a simplified accident sequence and compared the results for each method. Quasi-Monte Carlo sampling was found to be the most effective method in this case.
Kora, Kazuki*; Nakaya, Hiroyuki*; Kubo, Kotaro*; Matsuura, Hideaki*; Shimakawa, Satoshi; Goto, Minoru; Nakagawa, Shigeaki
Proceedings of International Conference on the Physics of Reactors; The Role of Reactor Physics toward a Sustainable Future (PHYSOR 2014) (CD-ROM), 12 Pages, 2014/09
In this study, the capability of HTGR as LLFP transmuter was evaluated in terms of neutron economy. Considering gas turbine high-temperature reactor with 300 MWe nominal capacity (GTHTR300) as HTGR, transmutations of four types of LLFP nuclide were estimated using Monte Carlo transport code MVP and ORIGEN. In addition, burn-up simulations for whole-core region were carried out using MVP-BURN. It was numerically shown that the neutron fluxes change significantly depending on the arrangement of LLFP in the core. When 15 t of LLFP is placed in an ideal manner, the GTHTR300 can sustain sufficient reactivity for one year while transmuting up to 30 kg per year. Additionally, there are more space available for storing larger amount of LLFP without affecting the reactivity. These results suggest that there is a possibility of using GTHTR300 as both LLFP storage and transmuter.
Ando, Toshinari; Hiyama, Tadao; Takahashi, Yoshikazu; Nakajima, Hideo; Kato, Takashi; Sugimoto, Makoto; Isono, Takaaki; Kawano, Katsumi; Koizumi, Norikiyo; Hamada, Kazuya; et al.
IEEE Transactions on Applied Superconductivity, 9(2), p.628 - 631, 1999/06
Times Cited Count：8 Percentile：51.51(Engineering, Electrical & Electronic)no abstracts in English
Kubo, Kotaro*; Matsuura, Hideaki*; Nakaya, Hiroyuki*; Kawamoto, Yasuko*; Nakao, Yasuyuki*; Shimakawa, Satoshi; Goto, Minoru; Nakagawa, Shigeaki
no journal, ,
The transmutation performance for LLFP and Mainer Actinide (MA) was evaluated when 2t of Tc-99 and 50kg of MA was loaded into GTHTR300 core. The compositions of MA was defined as the same as the spent fuel of a PWR with 12 years cooling. The amounts of transmutation were analyzed by performing the burn-up calculation with MVP-BURN for a fuel block geometry. As a result, the transmutation performance of GTHTR300 was evaluated that 18 kg of Tc-99 and 10 kg of MA were transmutated by one year operation.
Kubo, Kotaro; Zheng, X.; Tanaka, Yoichi; Tamaki, Hitoshi; Sugiyama, Tomoyuki
no journal, ,
Many institutes are developing dynamic PRA as method to improve the completeness and realism of conventional PRA. In the case of the dynamic PRA using the Monte Carlo method, a large number of thermal-hydraulic analyzes need to be performed in order to obtain a highly accurate result, and the calculation cost increases. However, if an appropriate sampling method is applied, it is considered that a result can be efficiently obtained with a small number of trials. Therefore, in addition to the Monte Carlo method, a trial analysis was performed using the Latin Hypercube method, the grid point sampling method, and the quasi-Monte Carlo method.
Zheng, X.; Kubo, Kotaro; Tanaka, Yoichi; Tamaki, Hitoshi; Sugiyama, Tomoyuki; Maruyama, Yu
no journal, ,
no abstracts in English
Tamaki, Hitoshi; Zheng, X.; Tanaka, Yoichi; Kubo, Kotaro; Sugiyama, Tomoyuki; Maruyama, Yu
no journal, ,
no abstracts in English
