Validation of nuclide depletion capabilities in Monte Carlo code MCS
Author(s) -
Bamidele Ebiwonjumi,
Hyunsuk Lee,
Wonkyeong Kim,
Deokjung Lee
Publication year - 2020
Publication title -
nuclear engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 40
eISSN - 2234-358X
pISSN - 1738-5733
DOI - 10.1016/j.net.2020.02.017
Subject(s) - nuclide , monte carlo method , nuclear engineering , nuclear data , nuclear transmutation , burnup , actinide , code (set theory) , fission , radiochemistry , computer science , chemistry , nuclear physics , physics , mathematics , engineering , statistics , set (abstract data type) , programming language , neutron
In this work, the depletion capability implemented in Monte Carlo code MCS is investigated to predict the isotopic compositions of spent nuclear fuel (SNF). By comparison of MCS calculation results to post irradiation examination (PIE) data obtained from one pressurized water reactor (PWR), the validation of this capability is conducted. The depletion analysis is performed with the ENDF/B-VII.1 library and a fuel assembly model. The transmutation equation is solved by the Chebyshev Rational Approximation Method (CRAM) with a depletion chain of 3820 isotopes. 18 actinides and 19 fission products are analyzed in 14 SNF samples. The effect of statistical uncertainties on the calculated number densities is discussed. On average, most of the actinides and fission products analyzed are predicted within ± 6 % of the experiment. MCS depletion results are also compared to other depletion codes based on publicly reported information in literature. The code-to-code analysis shows comparable accuracy. Overall, it is demonstrated that the depletion capability in MCS can be reliably applied in the prediction of SNF isotopic inventory.
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