Variational assimilation for xenon dynamical forecasts in neutronic using advanced background error covariance matrix modelling

Angélique Ponçot (1) , Jean-Philippe Argaud (1) , Bertrand Bouriquet (1) , Patrick Erhard (1) , Serge Gratton (2) , Olivier Thual (2, 3)

1 EDF R&D - EDF R&D
2 CERFACS - Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique
3 IMFT - Institut de mécanique des fluides de Toulouse

Data assimilation method consists in combining all available pieces of information about a system to obtain optimal estimates of initial states. The different sources of information are weighted according to their accuracy by the means of error covariance matrices. Our purpose here is to evaluate the efficiency of variational data assimilation for the xenon induced oscillations forecasts in nuclear cores. In this paper we focus on the comparison between 3DVAR schemes with optimised background error covariance matrix B and a 4DVAR scheme. Tests were made in twin experiments using a simulation code which implements a mono-dimensional coupled model of xenon dynamics, thermal, and thermal-hydraulic processes. We enlighten the very good efficiency of the 4DVAR scheme as well as good results with the 3DVAR one using a careful multivariate modelling of B.

Mots clés: Xenon dynamics; Variational data assimilation; Background error covariance matrix

Domaines: Physique Nucléaire Expérimentale [nucl-ex]

Angélique Ponçot, Jean-Philippe Argaud, Bertrand Bouriquet, Patrick Erhard, Serge Gratton, et al.. Variational assimilation for xenon dynamical forecasts in neutronic using advanced background error covariance matrix modelling. Annals of Nuclear Energy, 2013, vol. 60, pp. 39-50. ⟨10.1016/j.anucene.2013.04.026⟩. ⟨hal-00832455⟩