J011011 Reduced-order Kalman-filtered hybrid unsteady-flow simulation combining PTV and DNS

Abstract

We have previously developed hybrid unsteady-flow simulation combining particle tracking velocimetry (PTV) and direct numerical simulation (DNS) and demonstrated its capability at low Reynolds numbers. Applying algorithms of this type, however, becomes more challenging with increasing Reynolds number because the time interval of the PTV frame rate becomes much greater than the required DNS time-step, and the PTV resolution tends to be lower than that necessary for DNS. To extend the applicability to noisy time-resolved PTV data, the proposed algorithm optimizes the data input temporally and spatially by introducing a reduced-order Kalman filter. This study establishes a framework of the Kalman-filtered hybrid simulation and proves the concept based on a planar-jet flow at Re = 2000.