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 and Yixue Chen
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Chengjian Jin: School of Nuclear Science and Engineering, North China Electric Power University, Beijing 102206, China
Shichang Liu: School of Nuclear Science and Engineering, North China Electric Power University, Beijing 102206, China
Shenghao Zhang: School of Nuclear Science and Engineering, North China Electric Power University, Beijing 102206, China
Jingang Liang: Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China
Yixue Chen: School of Nuclear Science and Engineering, North China Electric Power University, Beijing 102206, China

Energies, 2022, vol. 15, issue 24, 1-16

Abstract: 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 k eff 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 k eff of the first-order uncertainty quantification method are compared with the stochastic sampling method, and the maximum relative deviation of total uncertainties in the k eff is 8.53%. Verification shows that the capabilities of S/U analysis developed in the RMC code has good accuracy.

Keywords: Monte Carlo; TSUNAMI-3D; SAMPLER; RMC; sensitivity and uncertainty (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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