Convergence behavior of statistical uncertainty in probability table for cross section in unresolved resonance region

Tada, Kenichi; Endo, Tomohiro*

Journal of Nuclear Science and Technology, 60(11), p.1397 - 1405, 2023/11

https://doi.org/10.1080/00223131.2023.2204102

The probability table method is a well-known method for addressing self-shielding effects in the unresolved resonance region. A long computational time is required to generate the probability table. The effective way to reduce the generation time of the probability table is the reduction of the number of ladders. The purpose of this study is the estimation of the optimal number of ladders using the statistical uncertainty in the probability table. To this end, the statistical uncertainty quantification method of the probability table was developed and the convergence behavior of the statistical uncertainty was investigated. The product of the probability table and the average cross section was considered the target of the statistical uncertainty. The convergence rate was affected by the average level spacing and reduced neutron width. The generation time of the probability table was less than half when the input parameter was changed from the number of ladders to the tolerance value.

Hierarchical Bayesian modeling to quantify fracture limit uncertainty of high-burnup advanced fuel cladding tubes under loss-of-coolant accident conditions

Narukawa, Takafumi; Hamaguchi, Shusuke*; Takata, Takashi*; Udagawa, Yutaka

Nuclear Engineering and Design, 411, p.112443_1 - 112443_12, 2023/09

https://doi.org/10.1016/j.nucengdes.2023.112443

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.

Hierarchical Bayes model to quantify fracture limit uncertainty of high-burnup advanced fuel cladding tubes under LOCA conditions

Narukawa, Takafumi; Hamaguchi, Shusuke*; Takata, Takashi*; Udagawa, Yutaka

Proceedings of Asian Symposium on Risk Assessment and Management 2022 (ASRAM 2022) (Internet), 11 Pages, 2022/12

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.

Uncertainty quantification of lead and bismuth sample reactivity worth at Kyoto University Critical Assembly

Pyeon, C. H.*; Yamanaka, Masao*; Fukushima, Masahiro

Nuclear Science and Engineering, 195(8), p.877 - 889, 2021/08

https://doi.org/10.1080/00295639.2020.1870861

Uncertainty quantification of lead (Pb) and bismuth (Bi) sample reactivity worth is numerically determined using the SCALE6.2 code system and experimental results obtained from the solid-moderated and solid-reflected core at the Kyoto University Critical Assembly (KUCA) to demonstrate the sensitivity coefficients of aluminum (Al) and Bi scattering reactions. From the results of the numerical analyses, the impact of Al and Bi scattering cross sections obtained using SCALE6.2/TSAR is disclosed on the Bi sample reactivity worth using Al reference and Bi test samples, although the uncertainty itself is small in the Bi sample reactivity worth.

Stochastic estimation of radionuclide composition in wastes generated at Fukushima Daiichi Nuclear Power Station using Bayesian inference

Sugiyama, Daisuke*; Nakabayashi, Ryo*; Tanaka, Shingo*; Koma, Yoshikazu; Takahatake, Yoko

Journal of Nuclear Science and Technology, 58(4), p.493 - 506, 2021/04

https://doi.org/10.1080/00223131.2021.1884137

Enhancement of the treatment of system interactions in a dynamic PRA tool

Tanaka, Yoichi; Tamaki, Hitoshi; Zheng, X.; Sugiyama, Tomoyuki

Proceedings of 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL 2020 and PSAM-15) (Internet), p.2195 - 2201, 2020/11

https://www.rpsonline.com.sg/proceedings/esrel2020/html/3854.xml

Uncertainty quantification of seismic response of reactor building considering different modeling methods

Choi, B.; Nishida, Akemi; Muramatsu, Ken*; Itoi, Tatsuya*; Takada, Tsuyoshi*

Proceedings of 2020 International Conference on Nuclear Engineering (ICONE 2020) (Internet), 5 Pages, 2020/08

https://doi.org/10.1115/ICONE2020-16862

After the 2011 Fukushima accident, the seismic regulation for Nuclear Power Plants (NPP) have been strengthened to take countermeasures against accidents beyond design basis conditions. Therefore, the importance of seismic probabilistic risk assessment has drawn much attention. Uncertainty quantification is a very important issue in the fragility assessment for NPP buildings. In this study, the authors focus on the epistemic uncertainty that can be reduced, and aims to clarify the effects due to different modeling methods of NPP buildings on seismic response results. As the first step of this study, the authors compared the effects on seismic response using two kinds of modeling methods. In order to evaluate the effect, seismic response analysis was performed on two types of building models; the three dimensional finite element model and the conventional lumped mass with sway-rocking model. As the input ground motion, the authors adopted 200 types of simulated seismic ground motions generated by fault rupture models with stochastic seismic source characteristics. For the uncertainty quantification, the authors conducted statistical analyses of the effects on seismic response results of two kinds of modeling methods on building response for each input ground motions, and quantitatively evaluated the uncertainty of response considering different modeling methods. In particular, the difference in modeling methods clearly appeared near the openings of the floors and walls. The authors also report on the knowledge about these three-dimensional effects in seismic response analysis.

Estimation of uncertainty in lead spallation particle multiplicity and its propagation to a neutron energy spectrum

Iwamoto, Hiroki; Meigo, Shinichiro

Journal of Nuclear Science and Technology, 57(3), p.276 - 290, 2020/03

https://doi.org/10.1080/00223131.2019.1671912

This paper presents an approach to uncertainty estimation of spallation particle multiplicity of lead (Pb), primarily focusing on proton-induced spallation neutron multiplicity () and its propagation to a neutron energy spectrum. The uncertainty is estimated from experimental proton-induced neutron-production double-differential cross sections (DDXs) and model calculations with the Particle and Heavy Ion Transport code System (PHITS). Uncertainties in multiplicities for , , and reactions are then inferred from the estimated uncertainty and the PHITS calculation. Using these uncertainties, uncertainty in a neutron energy spectrum produced from a thick Pb target bombarded with 500 MeV proton beams, measured in a previous experiment, is quantified by a random sampling technique, and propagation to the neutron energy spectrum is examined. Relatively large uncertainty intervals (UIs) were observed outside the lower limit of the measurement range, which is prominent in the backward directions. Our findings suggest that a reliable assessment of spallation neutron energy spectra requires systematic DDX experiments for detector angles and incident energies below 100 MeV as well as neutron energy spectrum measurements at lower energies below 1.4 MeV with an accuracy below the quantified UIs.