Issue |
EPJ Nuclear Sci. Technol.
Volume 7, 2021
Fuel Cycle Simulation TWoFCS 2021
|
|
---|---|---|
Article Number | 25 | |
Number of page(s) | 13 | |
DOI | https://doi.org/10.1051/epjn/2021023 | |
Published online | 21 December 2021 |
https://doi.org/10.1051/epjn/2021023
Regular Article
Development of a MOX equivalence Python code package for ANICCA
Tractebel (ENGIE), Boulevard Simón Bólivar 34-36,
1000
Brussels,
Belgium
* e-mail: bart.vermeeren@tractebel.engie.com
Received:
15
July
2021
Received in final form:
15
October
2021
Accepted:
10
November
2021
Published online: 21 December 2021
The basis of the MOX (Mixed OXide) energy equivalence principle is keeping the in-core fuel management characteristics (cycle length, feed size, etc.) of a nuclear reactor unchanged when replacing UOX (Uranium OXide) fuel assemblies by MOX. If the effect of the loading pattern is neglected, such an equivalence is obtained by tuning the Pu content in the MOX fuel, while considering the specific Pu isotopic vector at the time of the core reload to obtain a crossing of the reactivity curves of UOX and MOX at the end-of-cycle core average burnup. It is proposed in this work to extend the fuel cycle analysis tool ANICCA (Advanced Nuclear Inventory Cycle Code) with a MOX equivalence Python code package, which automatically governs the supply and demand of Pu vector isotopes required to obtain MOX equivalence. This code package can determine the reactivity evolution for any given Pu vector by means of a multidimensional interpolation on a directive grid of pre-calculated data tables generated by WIMS10, covering the physically accessible Pu vector space. A fuel cycle scenario will be assessed for a representative evolution of the Pu vector inventory available in spent UOX fuel as a demonstration case, defining the interim fuel storage building dimensional requirements for different reprocessing strategies.
© B. Vermeeren and H. Druenne, Published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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