Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Use of Monte Carlo code MCS for multigroup cross section generation for fast reactor analysis

  • Nguyen, Tung Dong Cao (Department of Nuclear Engineering Ulsan National Institute of Science and Technology (UNIST)) ;
  • Lee, Hyunsuk (Department of Nuclear Engineering Ulsan National Institute of Science and Technology (UNIST)) ;
  • Lee, Deokjung (Department of Nuclear Engineering Ulsan National Institute of Science and Technology (UNIST))
  • Received : 2020.09.29
  • Accepted : 2021.03.05
  • Published : 2021.09.25
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Abstract

Multigroup cross section (MG XS) generation by the UNIST in-house Monte Carlo (MC) code MCS for fast reactor analysis using nodal diffusion codes is reported. The feasibility of the approach is quantified for two sodium fast reactors (SFRs) specified in the OECD/NEA SFR benchmark: a 1000 MWth metal-fueled SFR (MET-1000) and a 3600 MWth oxide-fueled SFR (MOX-3600). The accuracy of a few-group XSs generated by MCS is verified using another MC code, Serpent 2. The neutronic steady-state whole-core problem is analyzed using MCS/RAST-K with a 24-group XS set. Various core parameters of interest (core keff, power profiles, and reactivity feedback coefficients) are obtained using both MCS/RAST-K and MCS. A code-to-code comparison indicates excellent agreement between the nodal diffusion solution and stochastic solution; the error in the core keff is less than 110 pcm, the root-mean-square error of the power profiles is within 1.0%, and the error of the reactivity feedback coefficients is within three standard deviations. Furthermore, using the super-homogenization-corrected XSs improves the prediction accuracy of the control rod worth and power profiles with all rods in. Therefore, the results demonstrate that employing the MCS MG XSs for the nodal diffusion code is feasible for high-fidelity analyses of fast reactors.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT). (No.NRF-2017M2A8A2018595).

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