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Tada, Kenichi; Kondo, Ryoichi; Endo, Tomohiro*; Yamamoto, Akio*
Journal of Nuclear Science and Technology, 60(6), p.624 - 631, 2023/06
Times Cited Count：2 Percentile：50.96(Nuclear Science & Technology)The sensitivity analysis and the uncertainty quantification have an important role in improving the evaluated nuclear data library. The current computational performance enables us to the sensitivity analysis and uncertainty quantification using the continuous energy Monte Carlo calculation code. The ACE file perturbation tool was developed for these calculations using modules of FRENDY. This tool perturbs the microscopic cross section, the number of neutrons per fission, and the fission spectrum. The uncertainty quantification using the random sampling method is also available if the user prepares the covariance matrix. The uncertainty of the k-effective using the perturbation tool was compared to the current sensitivity analysis codes SCALE/TSUNAMI and MCNP/KSEN. The comparison results indicated that the random sampling method using this tool accurately estimates the uncertainty of k-effective.
Kondo, Ryoichi*; Endo, Tomohiro*; Yamamoto, Akio*; Tada, Kenichi
Proceedings of International Conference on Mathematics and Computational Methods applied to Nuclear Science and Engineering (M&C 2019) (CD-ROM), p.1493 - 1502, 2019/00
A perturbation capability of ACE formatted cross section files was developed using the modules of FRENDY. Uncertainty quantification using MCNP was carried out for the Godiva critical experiment by the RS method. We verified the results of the RS method by comparing with those obtained by the conventional sensitivity analyses. Moreover, uncertainty reduction using the bias factor method with the RS technique was applied to kinetic parameter, i.e., neutron generation time.
Stankovskiy, A.*; Iwamoto, Hiroki; 
elik, Y.*; Van den Eynde, G.*
Annals of Nuclear Energy, 120, p.207 - 218, 2018/10
Times Cited Count：8 Percentile：62.29(Nuclear Science & Technology)Propagation of high-energy (above 20-MeV) nuclear data uncertainties on the safety related neutronic responses in accelerator driven systems has been assessed. The total core power and production of radionuclides contributing to radiation source terms were focused on. The article features a method based on the Monte Carlo sampling of random nuclear data files from the covariance matrices generated from the sets of reaction cross sections obtained with model calculations of high-energy particle interactions with matter or picked up from already existing nuclear data libraries. It has been demonstrated that nuclear data uncertainties do not need to be propagated through particle transport calculations to obtain uncertainties on the responses. This advantage allowed to investigate the convergence of the sample average to the best estimate. The number of random nuclear data file sets needed to obtain reliable uncertainty on the total core power is around 300 that results in the uncertainty of 14%. The uncertainties on the concentrations of nuclides most important for the safety assessment that are accumulated in lead-bismuth eutectic during irradiation, range from 5 to 60%. Concentrations of some nuclides exemplified by Tritium converge much slower than neutron multiplicities so that several thousands of samples are needed to ensure reliable uncertainty estimates.
Katano, Ryota
no journal, ,
no abstracts in English
Kondo, Ryoichi*; Endo, Tomohiro*; Yamamoto, Akio*; Tada, Kenichi
no journal, ,
The random sampling module for ACE format cross sections are developed using modules of FRENDY. This module perturbs the cross sections and other parameters in ACE format cross section library using covariance data. The GODIVA reactor is used and the calculation results of TSUNAMI-1D are compared to verify this module.
Fujita, Tatsuya
no journal, ,
Past studies have mentioned that the treatment of implicit effect for cross-section perturbation affects the sensitivity coefficients and then the uncertainty analysis results for the k-infinity. The several approaches to consider the above implicit effect has also been discussed for the random-sampling-based uncertainty analysis. In this study, the influence due to implicit effect on typical nuclides and nuclear reactions in PWR 17
17 UO
and MOX fuel assemblies was confirmed prior to treat the implicit effect on the random-sampling-based uncertainty analysis in future studies. In the UO fuel assembly, the influence due to implicit effect on the k-infinity was small, thus the uncertainty quantification only considering the explicit effect would be applicable. On the other hand, further discussion about the influence due to implicit effect was necessary for the MOX fuel assembly.
Maruyama, Shuhei; Yamamoto, Akio*; Endo, Tomohiro*
no journal, ,
no abstracts in English
