A multivariate representation of compressed pin-by-pin cross sections
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 efficien...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2021-01-01
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| Series: | EPJ Nuclear Sciences & Technologies |
| Online Access: | https://www.epj-n.org/articles/epjn/full_html/2021/01/epjn200019/epjn200019.html |
| _version_ | 1818718462100373504 |
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| author | Tomatis Daniele |
| author_facet | Tomatis Daniele |
| author_sort | Tomatis Daniele |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T19:51:26Z |
| format | Article |
| id | doaj.art-9bbb288a00a44e55b5e72b15f2714ac7 |
| institution | Directory Open Access Journal |
| issn | 2491-9292 |
| language | English |
| last_indexed | 2024-12-17T19:51:26Z |
| publishDate | 2021-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | EPJ Nuclear Sciences & Technologies |
| spelling | doaj.art-9bbb288a00a44e55b5e72b15f2714ac72022-12-21T21:34:43ZengEDP SciencesEPJ Nuclear Sciences & Technologies2491-92922021-01-017810.1051/epjn/2021006epjn200019A multivariate representation of compressed pin-by-pin cross sectionsTomatis Danielehttps://orcid.org/0000-0001-7314-2227Since 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.https://www.epj-n.org/articles/epjn/full_html/2021/01/epjn200019/epjn200019.html |
| spellingShingle | Tomatis Daniele A multivariate representation of compressed pin-by-pin cross sections EPJ Nuclear Sciences & Technologies |
| title | A multivariate representation of compressed pin-by-pin cross sections |
| title_full | A multivariate representation of compressed pin-by-pin cross sections |
| title_fullStr | A multivariate representation of compressed pin-by-pin cross sections |
| title_full_unstemmed | A multivariate representation of compressed pin-by-pin cross sections |
| title_short | A multivariate representation of compressed pin-by-pin cross sections |
| title_sort | multivariate representation of compressed pin by pin cross sections |
| url | https://www.epj-n.org/articles/epjn/full_html/2021/01/epjn200019/epjn200019.html |
| work_keys_str_mv | AT tomatisdaniele amultivariaterepresentationofcompressedpinbypincrosssections AT tomatisdaniele multivariaterepresentationofcompressedpinbypincrosssections |