Recent improvement of system reliability analysis code SECOM2-DQFM for seismic probabilistic risk assessment

Muramatsu, Ken; Kubo, Kotaro; Choi, B.; Nishida, Akemi; Takada, Tsuyoshi

Transactions of the 27th International Conference on Structural Mechanics in Reactor Technology (SMiRT 27) (Internet), 10 Pages, 2024/03

no abstracts in English

Application of quasi-Monte Carlo and importance sampling to Monte Carlo-based fault tree quantification for seismic probabilistic risk assessment of nuclear power plants

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

https://doi.org/10.1299/mej.23-00051

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.

Dynamic probabilistic risk assessment of seismic-induced flooding in pressurized water reactor by seismic, flooding, and thermal-hydraulics simulations

Kubo, Kotaro; Jang, S.*; Takata, Takashi*; Yamaguchi, Akira*

Journal of Nuclear Science and Technology, 60(4), p.359 - 373, 2023/04

https://doi.org/10.1080/00223131.2022.2100837

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.

A Scoping study on the use of direct quantification of fault tree using Monte Carlo simulation in seismic probabilistic risk assessments

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

https://doi.org/10.1115/ICONE29-88773

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.

Quasi-Monte Carlo sampling method for simulation-based dynamic probabilistic risk assessment of nuclear power plants

Kubo, Kotaro; Jang, S.*; Takata, Takashi*; Yamaguchi, Akira*

Journal of Nuclear Science and Technology, 59(3), p.357 - 367, 2022/03

https://doi.org/10.1080/00223131.2021.1971119

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.

Evaluation of risk dilution effects in dynamic probabilistic risk assessment of nuclear power plants

Kubo, Kotaro; Tanaka, Yoichi

Proceedings of 31st European Safety and Reliability Conference (ESREL 2021) (Internet), p.810 - 817, 2021/09

https://doi.org/10.3850/978-981-18-2016-8_477-cd

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.

Case study on sampling techniques using machine learning and simplified physical model for simulation-based dynamic probabilistic risk assessment

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.

Neutronic design of basic cores of the new STACY

Izawa, Kazuhiko; Ishii, Junichi; Okubo, Takuya; Ogawa, Kazuhiko; Tonoike, Kotaro

Proceedings of 11th International Conference on Nuclear Criticality Safety (ICNC 2019) (Internet), 9 Pages, 2019/09

Japan Atomic Energy Agency, JAEA, is conducting the renewal program of the heterogeneous water moderated critical assembly STACY (Static Experiment Critical Facility) in order to verify the criticality calculation considering fuel debris which have been produced in the accident of Fukushima Daiichi Nuclear Power Station. The first criticality of the new STACY is scheduled at the beginning of 2021. After the first criticality, it is necessary to perform a series of critical experiments with a series of basic experimental core in order to gain a proficiency of operators and grasp the uncertainty that accompanies the result of critical experiments in STACY. Prior to the construction of the new STACY, a series of neutronic calculation was carried out for licensing and planning first series of critical experiment. In this paper, possible core configuration of the basic experimental core and their limitations are discussed and presented.

Criticality characteristics of MCCI products possibly produced in reactors of Fukushima Daiichi Nuclear Power Station

Tonoike, Kotaro; Okubo, Kiyoshi; Takada, Tomoyuki*

Proceedings of International Conference on Nuclear Criticality Safety (ICNC 2015) (DVD-ROM), p.292 - 300, 2015/09

The damaged Unit 1-3 reactors of the Fukushima Daiichi Nuclear Power Station may contain fuel debris of a significant amount that is in a form of molten-core-concrete-interaction (MCCI) product with porous structure. Such low density MCCI product including fissile material is a great concern for its criticality control, especially under submerged condition, due to its fairly good neutron moderation. This report shows computation results of basic criticality characteristics of the MCCI product, which will facilitate criticality risk assessments during decommissioning of the reactors. The results imply that water bound in concrete may raise the risk from the viewpoints of possibility of criticality events and of effectiveness of mitigation measures such as neutron poison injection into coolant water.

Infinite multiplication factor of low-enriched UO-concrete system

Izawa, Kazuhiko; Uchida, Yuriko; Okubo, Kiyoshi; Totsuka, Masayoshi; Sono, Hiroki; Tonoike, Kotaro

Journal of Nuclear Science and Technology, 49(11), p.1043 - 1047, 2012/11

AA2012-0375.pdf:0.63MB

https://doi.org/10.1080/00223131.2012.730893

Possibility of criticality of fuel debris in a form of UO-concrete mixture is evaluated by calculating infinite multiplication factor () for a study of criticality control on the fuel debris generated through the molten core concrete interaction (MCCI) in a severe accident of a light water reactor (LWR). The infinite multiplication factor can be greater than unity, which means that handling of the mixture is subject to criticality control. This paper shows that concrete have efficient slowing-down capability of neutron and points out the necessity of further investigations on the criticality of low-enriched UO-concrete system for actual handling of fuel debris.