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

被引：2
作者：
Mercatali, L. [1 ]
Beydogan, N. [1 ]
Sanchez-Espinoza, V. H. [1 ]
机构：
[1] Karlsruhe Inst Technol, Inst Neutron Phys & Reactor Technol, Hermann von Helmholtz Pl 1, D-76344 Eggenstein Leopoldshafen, Germany
来源：
NUCLEAR ENGINEERING AND TECHNOLOGY | 2021年 / 53卷 / 09期
关键词：
Spent fuel; Burnup calculation; Monte Carlo; Nuclear data libraries; VVER; NUCLEAR-DATA; SPENT FUEL; ENDF/B-VIII.0; PROPAGATION; CRITICALITY; PLUTONIUM;
D O I：
10.1016/j.net.2021.03.014
中图分类号：
TL [原子能技术]; O571 [原子核物理学];
学科分类号：
0827 ; 082701 ;
摘要：
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-100 0 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-100 0 type reactors. (C) 2021 Korean Nuclear Society, Published by Elsevier Korea LLC.
引用
收藏
页码：2830 / 2838
页数：9
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