Abstract

Nuclear data uncertainties are provided as covariance matrices in standard nuclear data libraries and propagating them trough neutronics simulations helps quantify the associated uncertainties on the final result. However, processing these matrices often poses challenges. Currently, the IRSN nuclear data processing code GAIA processes cross sections via several modules like DOP (Reconstruction and Doppler), TOP (URR), and SAB (TSL), but lacks the capability to process covariances. This paper introduces a new module named COP (COvariance Processing). The COP module aims to process covariance matrices comprehensively, including cross section (File 33), angular distribution (File 34), and resonance parameters (File 32). The preliminary results obtained using the COP module of GAIA in comparison with the ERRORR module of NJOY and PUFF module of AMPX are presented.

Details

Title
Assesment of covariance processing with GAIA for nuclear data uncertainty propagation
Author
Sole, Pierre; Jaiswal, Vaibhav; Jouanne, Cédric; Salino, Vivian
Section
Uncertainties and Covariance Matrices
Publication year
2024
Publication date
2024
Publisher
EDP Sciences
ISSN
21016275
e-ISSN
2100014X
Source type
Conference Paper
Language of publication
English
ProQuest document ID
3041482439
Copyright
© 2024. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License.