Simulation-based dynamic probabilistic risk assessment of an internal flooding-initiated accident in nuclear power plant using THALES2 and RAPID

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

https://doi.org/10.1177/1748006X221091604

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%.

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.

Accident sequence precursor analysis of an incident in a Japanese nuclear power plant based on dynamic probabilistic risk assessment

Kubo, Kotaro

Science and Technology of Nuclear Installations, 2023, p.7402217_1 - 7402217_12, 2023/06

https://doi.org/10.1155/2023/7402217

Development of dynamic PRA methodology for external hazards in sodium-cooled fast reactor via applying Markov chain Monte Carlo method to severe accident analysis code; Assessment of accident management of assigning independent emergency diesel generators to each air cooler

Li, C.-Y.; Watanabe, Akira*; Uchibori, Akihiro; Okano, Yasushi

Proceedings of 30th International Conference on Nuclear Engineering (ICONE30) (Internet), 10 Pages, 2023/05

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.

Quantification of risk dilution induced by correlation parameters in dynamic probabilistic risk assessment of nuclear power plants

Kubo, Kotaro; Tanaka, Yoichi*; Ishikawa, Jun

Proceedings of the Institution of Mechanical Engineers, Part O; Journal of Risk and Reliability, 11 Pages, 2023/00

https://doi.org/10.1177/1748006X231167201

Experimental and analytical investigations on aerosol washout in a large vessel with high spray coverage ratio simulating PWR containment spray

Sun, Haomin; Leblois, Y.*; Gelain, T.*; Porcheron, E.*

Journal of Nuclear Science and Technology, 59(11), p.1356 - 1369, 2022/11

https://doi.org/10.1080/00223131.2022.2055673

In severe accident scenarios of PWR, containment spray can be employed to washout the aerosol of radioactive materials, retaining them in the containment. Therefore, it is crucial to correctly predict the washout efficiency for safety assessment. For a PWR, a high spray coverage ratio ( 84%-95%) is required. However, experimental studies on the washout with such a high coverage ratio in a large vessel are quite limited. To understand such a washout phenomenon for model development, aerosol washout experiments are performed in a large vessel with not only aerosol measurements but also spray droplet characterizations. The spray coverage ratios are experimentally confirmed to be compatible with a real PWR. The washout features are investigated in detail. The model in MELCOR is examined using the measured aerosol removal rate, showing the removal rate tendency against particle diameters being reproduced. Although a significant underestimation occurs for large particles, a satisfactory agreement is obtained for smaller ones (0.52 m in diameter) corresponding to the minimum removal rate and around.

Uncertainty analysis of dynamic PRA using nested Monte Carlo simulations and multi-fidelity models

Zheng, X.; Tamaki, Hitoshi; Takahara, Shogo; Sugiyama, Tomoyuki; Maruyama, Yu

Proceedings of Probabilistic Safety Assessment and Management (PSAM16) (Internet), 10 Pages, 2022/09

https://www.iapsam.org/PSAM16/

Quantitative risk assessment with CMMC method on abnormal snowfall incident for a sodium-cooled fast reactor

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.

Identification of the reactor building damage mode for seismic fragility assessment using a three-dimensional finite element model

Choi, B.; Nishida, Akemi; Shiomi, Tadahiko; Kawata, Manabu; Li, Y.

Transactions of the 26th International Conference on Structural Mechanics in Reactor Technology (SMiRT-26) (Internet), 10 Pages, 2022/07

In order to improve the seismic probabilistic risk assessment method, the authors are developing methods related to realistic response, realistic resistance and fragility assessment for buildings and equipment that are important for seismic safety. In this study, in order to identify of building damage mode subjected to large seismic motions, pushover analyses using multiple analysis codes were performed using a 3D FE model of a reactor building. We obtained the analysis results for the identification of local damage mode that contributes to the fragility assessment. In this paper, we report the progress of local damage mode and ultimate strength of the building by the pushover analysis. We also compared this result with the seismic response analysis results.