| Issue |
EPJ Web Conf.
Volume 239, 2020
ND 2019: International Conference on Nuclear Data for Science and Technology
|
|
|---|---|---|
| Article Number | 18004 | |
| Number of page(s) | 4 | |
| Section | Integral Experiments | |
| DOI | https://doi.org/10.1051/epjconf/202023918004 | |
| Published online | 30 September 2020 | |
https://doi.org/10.1051/epjconf/202023918004
Bayesian Monte Carlo assimilation for the PETALE experimental programme using inter-dosimeter correlation
1 Laboratory for Reactor Physics and Systems behaviour (LRS), Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
2 Laboratory for Reactor Physics and Thermal Hydraulics (LRT), Paul Scherrer Institut (PSI), CH-5232 Villigen, Switzerland
3 Nuclear Energy and Safety Research Division (NES), Paul Scherrer Institut (PSI), CH-5232 Villigen, Switzerland
* e-mail: axel.laureau@epfl.ch
Published online: 30 September 2020
This article presents the methodology developed to generate and use dosimeter covariances and to estimate nuisance parameters for the PETALE experimental programme. In anticipation of the final experimental results, this work investigates the consideration of these experimental correlations in the Bayesian assimilation process on nuclear data. Results show that the assimilation of a given set of dosimeters provides a strong constraint on some of the posterior reaction rate predictions of the other dosimeters. It confirms that, regarding the assimilation process, the different sets of dosimeters are correlated.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.