Research on data assimilation strategy of turbulent separated flow over airfoil

In order to increase the accuracy of turbulence field reconstruction, this paper combines experimental observation and numerical simulation to develop and establish a data assimilation framework, and apply it to the study of S809 low-speed and high-angle airfoil flow. The method is based on the ensemble transform Kalman filter (ETKF) algorithm, which improves the disturbance strategy of the ensemble members and enhances the richness of the initial members by screening high flow field sensitivity constants, increasing the constant disturbance dimensions and designing a fine disturbance interval. The results show that the pressure distribution on the airfoil surface after assimilation is closer to the experimental value than that of the standard Spalart-Allmaras (S-A) model. The separated vortex estimated by filtering is fuller, and the eddy viscosity field information is more abundant, which is physically consistent with the observation information. Therefore, the data assimilation method based on the improved ensemble strategy can more accurately and effectively describe complex turbulence phenomena.