• Nuclear Engineering and Technology
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• 제54권12호
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• pp.4731-4742
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• 2022

RBMK fuel assemblies differ from other LWR FA due to a specific arrangement of the fuel rods, the low enrichment, and the used burnable absorber - erbium. Therefore, there is a challenge to adapt modeling tools, developed for other LWR types, to solve RBMK problems. A set of 10 different depletion simulation schemes were tested to estimate the impact on reactivity and spent fuel composition of possible SCALE code options for the neutron transport modelling and the use of different nuclear data libraries. The simulations were performed using cross-section libraries based on both, VII.0 and VII.1, versions of ENDF/B nuclear data, and assuming continuous energy and multigroup simulation modes, standard and user-defined Dancoff factor values, and employing deterministic and Monte Carlo methods. The criticality analysis with burn-up credit was performed for the SFP loaded with RBMK-1500 FA. Spent fuel compositions were taken from each of 10 performed depletion simulations. The criticality of SFP is found to be overestimated by up to 0.08% in simulation cases using user-defined Dancoff factors comparing the results obtained using the continuous energy library (VII.1 version of ENDF/B nuclear data). It was shown that such discrepancy is determined by the higher U-235 and Pu-239 isotopes concentrations calculated.

• Nuclear Engineering and Technology
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• 제48권3호
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• pp.765-772
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• 2016

In analyzing residual radiation, researchers generally use a two-step Monte Carlo (MC) simulation. The first step (MC1) simulates neutron transport, and the second step (MC2) transports the decay photons emitted from the activated materials. In this process, the stochastic uncertainty estimated by the MC2 appears only as a final result, but it is underestimated because the stochastic error generated in MC1 cannot be directly included in MC2. Hence, estimating the true stochastic uncertainty requires quantifying the propagation degree of the stochastic error in MC1. The brute force technique is a straightforward method to estimate the true uncertainty. However, it is a costly method to obtain reliable results. Another method, called the adjoint-based method, can reduce the computational time needed to evaluate the true uncertainty; however, there are limitations. To address those limitations, we propose a new strategy to estimate uncertainty propagation without any additional calculations in two-step MC simulations. To verify the proposed method, we applied it to activation benchmark problems and compared the results with those of previous methods. The results show that the proposed method increases the applicability and user-friendliness preserving accuracy in quantifying uncertainty propagation. We expect that the proposed strategy will contribute to efficient and accurate two-step MC calculations.