Applying Random Sampling methods to data analysis for uncertainty production, with an Open source and Open science outlook
Application de méthodes d’échantillonnage aléatoire à l’analyse de données pour la production d’incertitude, avec une perspective code ouvert et science ouverte.
Résumé
This HDR manuscript discusses the significance of nuclear data for energy applications, with an emphasis on the need for improved accuracy in reaction modeling. It focuses on inelastic neutron scattering reactions and presents findings from experimental studies using the Grapheme setup at the Gelina facility. Specifically, it presents measurements on 183W, with the end goal of constraining reaction models. This study uses a full Monte Carlo analysis approach to produce uncertainties and correlation matrices, aiming for comprehensive documentation. Embracing Open Science principles, the manuscript details the current research practice standards for better publication of research products.
Mots clés
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Cite 10.57745/D7HC3O Jeu de données HENNING, Greg, 2024, "Experimental (n, n' γ) and (n, 2n γ) cross sections for 183W", https://doi.org/10.57745/D7HC3O, Recherche Data Gouv, V1
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Cite 10.57745/QFFRD8 Jeu de données HENNING, Greg, 2025, "Experimental (n, 2n γ) cross sections for 184W", https://doi.org/10.57745/QFFRD8, Recherche Data Gouv, V1
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Est une version de 10.5281/zenodo.13364682 Thèse de doctorat Henning, G. (2024). Applying Random Sampling methods to data analysis for uncertainty production, with an Open source and Open science outlook [Université de Strasbourg]. https://doi.org/10.5281/ZENODO.13364682