Spatial Filter Velocimetry Based on Time-Series Particle Images

High spatial and temporal resolutions are required in velocity measurements for turbulent flows to examine turbulence characteristics accurately. In this study, we proposed a spatial filter velocimetry (SFV) based on a frequency analysis of time-series spatially-filtered particle images. Since this method can measure velocity from one particle in a measurement region, it enables us to measure the velocity with high spatial and temporal resolutions. We developed a SFV system and applied it to laminar and turbulent flows in a duct to examine its performance. Through comparisons between the velocities measured by SFV and LDV, we confirmed that SFV accurately measures the mean velocity and turbulent intensity with spatial and temporal resolutions as high as LDV.