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Applying Random Sampling methods to data analysis for uncertainty production, with an Open source and Open science outlook
Greg Henning

Applying Random Sampling methods to data analysis for uncertainty production, with an Open source and Open science outlook

Author / Organization:
Science & Mathematics Published 2024 Verification Pending

Overview & Synopsis

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.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Applying Random Sampling methods to data analysis for uncertainty production, with an Open source and Open science outlook
Author / Organization Greg Henning
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2024
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-185047
Original Source Link Visit Source Page on hal.science »