Feasibility Study on Real-time Observation of Flow Velocity Field using Sparse Processing Particle Image Velocimetry

Active flow control such as the use of a plasma actuator has been gathering much attention. Its effectiveness in flow separation control has been investigated experimentally and numerically.1) However, the capability during highspeed airflow is limited due to the lack of the flow control effect. Hence, feedback control utilizing the real-time measurement of the flow state is expected to improve applicability.2) Because of the complexity and nonlinearity of the flow phenomena, feedback control based on not the local flow information, but the full-state or global flow information clearly appears to be better for the future feedback control of flows. The use of particle image velocimetry (PIV), which provides the instantaneous velocity field in laboratory measurement can be used for nearly full-state observation. Therefore, real-time PIV measurement of the flow field seems to be a powerful tool for flow control. The velocity field is calculated from the cross-correlation coefficient for each interrogation window of the particle images during the PIV measurement, but the number of windows that can be processed in a short duration is limited. This is because the PIV computational time is too long when real-time PIV measurement is applied to aerodynamic flow-control experiments, which have a shorter time scale than hydrodynamic experiments. In this study, reduced-order modeling is employed and reducing the calculation time is considered. The authors proposed sparse processing PIV (SPPIV) as a method to achieve the real-time nearly full-state estimation. The PIV measurement of the flow field around a NACA0015 airfoil model was conducted and the flow field obtained using SPPIV and the processing time were evaluated.