Fission Product Yields Covariance Generation Methodologies and Uncertainty Propagation Using the URANIE Platform

N. Terranova (1) , M. Sumini (1) , P. Archier (2) , Olivier Serot (2) , D. Bernard (2) , C. de Saint-Jean (2)

1 University of Bologna/Università di Bologna
2 SPRC - Service de Physique des Réacteurs et du Cycle

In modern nuclear technology, integral reactor parameter uncertainty evaluation plays a crucial role for both economical and safety purposes. Recent safety-by-design standards require strict margins of uncertainty, then intense activities of verification and validation are therefore necessary to ensure the precision needed for safe and sustainable modern technologies exploitation. The uncertainty associated to nuclear data plays a relevant role in this sense and many efforts have been recently spent to improve the whole input chain we provide to reactor code design procedures. Since some of them are not sufficiently detailed or even do not exist in modern nuclear data libraries yet, in this work we propose a methodology to generate, test and propagate covariance matrices for fission product yields. The main goal is to reproduce the JEFF-3.1.1 fission yields library and find associated covariances to be propagated using Monte Carlo and deterministic techniques in burnup test-case calculations. Some results on the reactivity and decay heat uncertainty are presented for simple cases. Finally, a whole reactor geometries such as the Jules Horowitz Reactor (JHR), amaterial testing reactor under construction at CEA-Cadarache, is treated.

Keywords: Fission Yields; Covariance; Uncertainty Propagation

Domains: Physics [physics]; Nuclear Experiment [nucl-ex]; Physics [physics]; Nuclear Theory [nucl-th]

N. Terranova, M. Sumini, P. Archier, Olivier Serot, D. Bernard, et al.. Fission Product Yields Covariance Generation Methodologies and Uncertainty Propagation Using the URANIE Platform. PHYSOR 2016 - The Physics of Reactors Meeting: Unifying Theory and Experiments in the 21st Century, May 2016, Sun Valley, United States. ⟨hal-02442277⟩