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Simulation of low-enriched uranium burnup in Russian VVER-1000 reactors with the Serpent Monte-Carlo code

  • Mercatali, L. (Karlsruhe Institute of Technology, Institute for Neutron Physics and Reactor Technology) ;
  • Beydogan, N. (Karlsruhe Institute of Technology, Institute for Neutron Physics and Reactor Technology) ;
  • Sanchez-Espinoza, V.H. (Karlsruhe Institute of Technology, Institute for Neutron Physics and Reactor Technology)
  • Received : 2021.02.08
  • Accepted : 2021.03.15
  • Published : 2021.09.25

Abstract

This work deals with the assessment of the burnup capabilities of the Serpent Monte Carlo code to predict spent nuclear fuel (SNF) isotopic concentrations for low-enriched uranium (LEU) fuel at different burnup levels up to 47 MWd/kgU. The irradiation of six UO2 experimental samples in three different VVER-1000 reactor units has been simulated and the predicted concentrations of actinides up to 244Cm have been compared with the corresponding measured values. The results show a global good agreement between calculated and experimental concentrations, in several cases within the margins of the nuclear data uncertainties and in a few cases even within the reported experimental uncertainties. The differences in the performances of the JEFF3.1.1, ENDF/B-VII.1 and ENDF/B-VIII.0 nuclear data libraries (NDLs) have also been assessed and the use of the newly released ENDF/B-VIII.0 library has shown an increased accuracy in the prediction of the C/E's for some of the actinides considered, particularly for the plutonium isotopes. This work represents a step forward towards the validation of advanced simulation tools against post irradiation experimental data and the obtained results provide an evidence of the capabilities of the Serpent Monte-Carlo code with the associated modern NDLs to accurately compute SNF nuclide inventory concentrations for VVER-1000 type reactors.

Keywords

Acknowledgement

The authors would like to thank the Program Nuclear Safety Research (NUSAFE) of the Karlsruhe Institute of Technology (KIT) for the financial support of the research topic "Predisposal".

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