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.

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.

Application of Bayesian approaches to nuclear reactor severe accident analysis

Zheng, X.; Tamaki, Hitoshi; Shiotsu, Hiroyuki; Sugiyama, Tomoyuki; Maruyama, Yu

Proceedings of Asian Symposium on Risk Assessment and Management 2017 (ASRAM 2017) (USB Flash Drive), 11 Pages, 2017/11

Probabilistic accident consequence assessment codes; Second international comparison technical report

W.Nixon*; P.J.Cooper*; C.M.Bone*; S.Acharya*; U.Baeverstam*; J.Ehrhardt*; I.Hasemann*; Steinhauer, C.*; E.G.Diaz*; J.C.Glynn*; et al.

EUR-15109, 0, 338 Pages, 1994/00

no abstracts in English

LISA Package user guide, Part 2: LISA(Long Term Isolation Safety Assessment) program description and user guide

P.Prado*; A.Saltelli*; Homma, Toshimitsu

EUR-13923, 47 Pages, 1992/00

no abstracts in English

The Selection of Safety Evaluation Accident Baced on the Probabilistic Method for VHTR Design

Suzuki, Katsuo

JAERI-M 8736, 151 Pages, 1980/03

JAERI-M-8736.pdf:3.68MB

no abstracts in English