AN OPTIMIZATION OF TURBULENT FLOWS BY USING DATA ASSIMILATION

In this study, the ensemble transform Kalman filter, a sequential advanced data assimilation method, is employed to estimate the angle of attack, the Mach number, and the turbulent viscosity corresponding with the experimental pressure coefficients of the transonic flow around the ONERA M6 wing. As the result, the computation with the angle of attack, the Mach number, and the turbulent viscosity estimated by the ETKF improves discrepancies between original computations and the experiment. This result suggests that data assimilation is effective to estimate proper turbulent flow conditions by combining computational data and experimental data with data assimilation.