A multigrid/ensemble Kalman filter strategy for assimilation of unsteady flows

A sequential estimator based on the Ensemble Kalman Filter for Data Assimilation of fluid flows is presented in this research work. The main feature that filter update, which relies determination gain, performed exploiting algorithmic features numerical solver employed as a model. More precisely, multilevel resolution associated with multigrid iterative approach time advancement used to generate several low-resolution simulations. These results are ensemble members determine correction via filter, then projected high-resolution grid correct single simulation corresponds assessment method analysis one-dimensional and two-dimensional test cases, using different dynamical equations. show an efficient trade-off terms accuracy computational costs required. In addition, physical regularization flow, not granted by classical KF approaches, naturally obtained owing calculations. algorithm also well suited unsteady phenomena and, particular, potential application in-streaming techniques.