Data recovery and reconstruction methods for unsteady flow fields with spatio-temporal missing data are studied based on proper orthogonal decomposition (POD) and on Kriging interpolation. It is found that for sufficient temporal resolution, POD-based methods outperform Kriging interpolation. However, for insufficient temporal resolution, large spatial gappiness or for flow fields with black zones, Kriging interpolation is more effective. The comparison is performed based on randomly generated laminar and turbulent flow fields obtained from simulations of uniform flow past a circular cylinder.
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