Issue |
EPJ Nuclear Sci. Technol.
Volume 7, 2021
|
|
---|---|---|
Article Number | 8 | |
Number of page(s) | 13 | |
DOI | https://doi.org/10.1051/epjn/2021006 | |
Published online | 07 April 2021 |
https://doi.org/10.1051/epjn/2021006
Regular Article
A multivariate representation of compressed pin-by-pin cross sections
Université Paris-Saclay, CEA, Service d’Études des Réacteurs et de Mathématiques Appliquées,
91191
Gif-sur-Yvette, France
* e-mail: daniele.tomatis@cea.fr
Received:
3
September
2020
Received in final form:
12
February
2021
Accepted:
3
March
2021
Published online: 7 April 2021
Since the 80’s, industrial core calculations employ the two-step scheme based on prior cross sections preparation with few energy groups and in homogenized reference geometries. Spatial homogenization in the fuel assembly quarters is the most frequent calculation option nowadays, relying on efficient nodal solvers using a coarse mesh. Pin-wise reaction rates are then reconstructed by dehomogenization techniques. The future trend of core calculations is moving however toward pin-by-pin explicit representations, where few-group cross sections are homogenized in the single pins at many physical conditions and many nuclides are selected for the simplified depletion chains. The resulting data model requires a considerable memory occupation on disk-files and the time needed to evaluate all data exceeds the limits for practical feasibility of multi-physics reactor calculations. In this work, we study the compression of pin-by-pin homogenized cross sections by the Hotelling transform in typical PWR fuel assemblies. The reconstruction of these quantities at different physical states of the assembly is then addressed by interpolation of only a few compressed coefficients, instead of interpolating separately each homogenized cross section. Savings in memory higher than 90% are observed, which result in important gains in runtime when interpolating the few-group data.
© D. Tomatis, 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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