A NOVEL COMPUTATIONAL PLATFORM FOR THE PROPAGATION OF NUCLEAR DATA UNCERTAINTIES THROUGH THE FUEL CYCLE CODE ANICCA
This paper presents the first results of a computational platform dedicated to the propagation of nuclear data covariances, all the way to fuel cycle scenario observables. Such platform, based on in-house codes developed at SCK•CEN in Belgium, both for the creation of the many-randomized nuclear dat...
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| Autors principals: | , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
EDP Sciences
2021-01-01
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| Col·lecció: | EPJ Web of Conferences |
| Matèries: | |
| Accés en línia: | https://www.epj-conferences.org/articles/epjconf/pdf/2021/01/epjconf_physor2020_13007.pdf |
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