Titre :

Multigrid sequential data assimilation for the Large Eddy Simulation of a massively separated bluff-body flow

Auteur(s) :

Moldovan, Gabriel-Ionut [Auteur]
European Centre for Medium-Range Weather Forecasts [ECMWF]
Mariotti, Alessandro [Auteur]
University of Pisa [Italy] = Università di Pisa [Italia] = Université de Pise [Italie] [UniPi]
Cordier, Laurent [Auteur]
CURIOSITY [Institut Pprime]
Lehnasch, Guillaume [Auteur]
École Nationale Supérieure de Mécanique et d’Aérotechnique [Poitiers] [ISAE-ENSMA]
Acoustique, Aérodynamique, Turbulence [Institut Pprime] [2AT ]
Salvetti, Maria-Vittoria [Auteur]
University of Pisa [Italy] = Università di Pisa [Italia] = Université de Pise [Italie] [UniPi]
Meldi, Marcello [Auteur]
Laboratoire de Mécanique des Fluides de Lille - Kampé de Fériet [LMFL]

Titre de la revue :

Computers and Fluids

Pagination :

106385

Éditeur :

Elsevier

Date de publication :

2024-08

ISSN :

0045-7930

Mot(s)-clé(s) en anglais :

Kalman Filter
Data Assimilation
LES
BARC

Discipline(s) HAL :

Sciences de l'ingénieur [physics]
Sciences de l'ingénieur [physics]/Milieux fluides et réactifs

Résumé en anglais : [en]

The potential of sequential Data Assimilation (DA) techniques to improve the numerical accuracy of Large Eddy Simulation (LES) performed on coarse grid is assessed. Specifically, this paper evaluates the performance of the ...
Lire la suite >The potential of sequential Data Assimilation (DA) techniques to improve the numerical accuracy of Large Eddy Simulation (LES) performed on coarse grid is assessed. Specifically, this paper evaluates the performance of the Multigrid Ensemble Kalman Filter (MGEnKF) method, recently introduced by Moldovan, Lehnasch, Cordier and Meldi (Journal of Computational Physics, 2021). The international benchmark referred to as BARC (Benchmark of the Aerodynamics of a Rectangular 5:1 Cylinder) is chosen as test configuration, as it includes several complex flow dynamics encountered in turbulence studies. The results for the statistical moments of the velocity and pressure flow field show that the data-driven techniques employed are able to significantly improve the predictive features of the solver for reduced grid resolution. In addition, it was observed that, despite the sparse and asymmetric distribution of observation in the data-driven process, the DA augmented LES exhibits symmetric statistics and a significantly improved accuracy also far from the observation zone.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Laboratoire de Mécanique des Fluides de Lille Kampé de Fériet (LMFL) - UMR 9014

Source :

Harvested from HAL