In the present work, we analyze how fission yields uncertainties can be propagated in a burn-up calculation. The first part of the work is dedicated to the fission yield covariances generation in CONRAD (COde for Nuclear Reaction Analysis and Data Assimilation) to be used in the neutronic code APOLLO2. Fission yield covariance files are in fact unavailable in present nuclear databases such as JEFF-3.2 and ENDFIB-Vll. To propagate such uncertainties, we adopted a statistical method which has a solid theoretical base and a relatively simple implementation. Fission yields have been therefore treated as random variables to be sampled from a normal input parameter multivariate distribution, taking into account correlations. Successively, a statistical representative number of calculations are carried out with the different sampled input data. An output multivariate probability distribution for core characteristics is then inferred. Random variable sampling and statistical post-processing has been performed using URANIE, a sensitivity and uncertainty analysis platform based on ROOT. This methodology is applied on a simplified geometry, leaving further developments for more complicated layout to future works.
Terranova, N., Sumini, M., Archier, P., Serot, O., Bernard, D., De Saint Jean, C. (2015). A model for fission yield uncertainty propagation based on the Uranie platform. ;555 North Kensington Avenue : American Nuclear Society.
A model for fission yield uncertainty propagation based on the Uranie platform
TERRANOVA, NICHOLAS;SUMINI, MARCO;
2015
Abstract
In the present work, we analyze how fission yields uncertainties can be propagated in a burn-up calculation. The first part of the work is dedicated to the fission yield covariances generation in CONRAD (COde for Nuclear Reaction Analysis and Data Assimilation) to be used in the neutronic code APOLLO2. Fission yield covariance files are in fact unavailable in present nuclear databases such as JEFF-3.2 and ENDFIB-Vll. To propagate such uncertainties, we adopted a statistical method which has a solid theoretical base and a relatively simple implementation. Fission yields have been therefore treated as random variables to be sampled from a normal input parameter multivariate distribution, taking into account correlations. Successively, a statistical representative number of calculations are carried out with the different sampled input data. An output multivariate probability distribution for core characteristics is then inferred. Random variable sampling and statistical post-processing has been performed using URANIE, a sensitivity and uncertainty analysis platform based on ROOT. This methodology is applied on a simplified geometry, leaving further developments for more complicated layout to future works.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.