LAPSE:2023.34709
Published Article
LAPSE:2023.34709
Nuclear Data Sensitivity and Uncertainty Study for the Pressurized Water Reactor (PWR) Benchmark Using RMC and SCALE
Chengjian Jin, Shichang Liu, Shenghao Zhang, Jingang Liang, Yixue Chen
April 27, 2023
In order to improve the safety and economy of nuclear reactors, it is necessary to analyze the sensitivity and uncertainty (S/U) of the nuclear data. The capabilities of S/U analysis has been developed in the Reactor Monte Carlo code RMC, using the iterated fission probability (IFP) method and the superhistory method. In this paper, the S/U capabilities of RMC are applied to a typical PWR benchmark B&W’s Core XI, and compared with the multigroup and continuous-energy S/U capabilities in the SCALE code system. The S/U results of the RMC-IFP method and the RMC-superhistory method are compared with TSUNAMI-CE/MG in SCALE. The sensitivity results and the uncertainty results of major nuclides that contribute a lot to the uncertainties in keff are in good agreement in both RMC and SCALE. The RMC-superhistory method has the same precision as the IFP method, but it reduces the memory footprint by more than 95% and only doubles the running time. The superhistory method has obvious advantages when there are many nuclides and reaction types to be analyzed. In addition, the total uncertainties in the keff of the first-order uncertainty quantification method are compared with the stochastic sampling method, and the maximum relative deviation of total uncertainties in the keff is 8.53%. Verification shows that the capabilities of S/U analysis developed in the RMC code has good accuracy.
Keywords
Monte Carlo, RMC, SAMPLER, sensitivity and uncertainty, TSUNAMI-3D
Suggested Citation
Jin C, Liu S, Zhang S, Liang J, Chen Y. Nuclear Data Sensitivity and Uncertainty Study for the Pressurized Water Reactor (PWR) Benchmark Using RMC and SCALE. (2023). LAPSE:2023.34709
Author Affiliations
Jin C: School of Nuclear Science and Engineering, North China Electric Power University, Beijing 102206, China
Liu S: School of Nuclear Science and Engineering, North China Electric Power University, Beijing 102206, China [ORCID]
Zhang S: School of Nuclear Science and Engineering, North China Electric Power University, Beijing 102206, China
Liang J: Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China [ORCID]
Chen Y: School of Nuclear Science and Engineering, North China Electric Power University, Beijing 102206, China
Journal Name
Energies
Volume
15
Issue
24
First Page
9511
Year
2022
Publication Date
2022-12-15
Published Version
ISSN
1996-1073
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PII: en15249511, Publication Type: Journal Article
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doi:10.3390/en15249511
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Apr 27, 2023
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