Uncertainty quantification in decay heat calculation of spent nuclear fuel by STREAM/RAST-K

  • Jang, Jaerim (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology) ;
  • Kong, Chidong (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology) ;
  • Ebiwonjumi, Bamidele (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology) ;
  • Cherezov, Alexey (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology) ;
  • Jo, Yunki (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology) ;
  • Lee, Deokjung (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology)
  • Received : 2020.09.15
  • Accepted : 2021.03.08
  • Published : 2021.09.25


This paper addresses the uncertainty quantification and sensitivity analysis of a depleted light-water fuel assembly of the Turkey Point-3 benchmark. The uncertainty of the fuel assembly decay heat and isotopic densities is quantified with respect to three different groups of diverse parameters: nuclear data, assembly design, and reactor core operation. The uncertainty propagation is conducted using a two-step analysis code system comprising the lattice code STREAM, nodal code RAST-K, and spent nuclear fuel module SNF through the random sampling of microscopic cross-sections, fuel rod sizes, number densities, reactor core total power, and temperature distributions. Overall, the statistical analysis of the calculated samples demonstrates that the decay heat uncertainty decreases with the cooling time. The nuclear data and assembly design parameters are proven to be the largest contributors to the decay heat uncertainty, whereas the reactor core power and inlet coolant temperature have a minor effect. The majority of the decay heat uncertainties are delivered by a small number of isotopes such as 241Am, 137Ba, 244Cm, 238Pu, and 90Y.



This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT). (No.NRF-2019M2D1A1067205)


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