Exploration of Ensemble Kalman Filter for parameter estimation with plasma actuators

Abstract

This thesis aims to explore and enable parameter estimation using the data assimilation method of the ensemble Kalman filter (EnKF). More specillically applied to the quasi-steady flow field, measured using particle image velocimetry (PIV), of a plasma actuator in quiescent ow where the parameters to be estimated are those describing the force field generated. The ensemble Kalman filter combines experimental observations together with a prior, created through numerical simulation, in a stochastic framework, to compute a closer estimation of the true state of the system together with an estimation of the error. This method has already proven to be able to improve the spacial and temporal accuracy experimental observations, as well as providing an estimation of the parameters describing the system. The EnKF has not yet been used in the _eld of plasma actuators, and can prove a valuable tool in improving upon existing experimental methods, including the calculation of the pressure field, and the time dependent force field. The calculation of the pressure field has mostly been ignored, and the determination of the time dependent force field has been done with limited success so far using only experimental methods only.