PIV data reconstruction via proper orthogonal decomposition with a cross validation approach

In this research, unsteady particle image velocimetry (PIV) data are reconstructed / analyzed by a proper orthogonal decomposition (POD) with a cross validation approach. At unsteady PIV flow measurements we have interests, it is sometimes difficult to gather the PIV velocity vector in its entire flow field, mainly due to the lack of particles and/or low (even) contrasting density in the flow field. A POD-based gappy data reconstruction approach is applied to recover the gappy PIV data. The appropriate numbers of iterations as well as considering POD modes are determined by the cross validation approach. The PIV measurements are performed for the wake of a rectangular cylinder as well as for a self-developed flapping wing object. Especially in the case of the flapping wing object, the PIV measurement is performed at a hovering condition in which it is difficult to scatter the particles appropriately in its entire flow field. It results in the failures of PIV measurement at some regions of flow field, and then those incomplete PIV data are reconstructed by the developed approach. The flow/vortex structures can be discussed reasonably well by using the recovered PIV data.