Time Resolved High Dynamic Range PIV using Local Uncertainty Estimation Methods

Abstract

The dynamic velocity range of particle image velocimetry (PIV) is determined by the ratio of maximum to minimum resolvable particle displacement. Although many techniques have been developed in the past decades to extend the dynamic range, flows with a wide velocity range still challenge conventional PIV methods. Using multiple-pulse-separation acquisition in combination with a new criterion for the local optimal pulse separation, this paper presents a new time-resolved high dynamic range (HDR) PIV methodology. The optimality criterion maximizes a vector quality metric combining the correlation peak ratio with the estimated local displacement uncertainty and magnitude, expressed as a signal-tonoise ratio. Using an axisymmetric turbulent jet as a benchmark case, significant enhancements are shown in the measured turbulence intensity and estimated signal-to-noise ratio throughout the flow field, but especially in the entrainment region and the outer shear layer. For this case, HDR PIV provides an effective increase in dynamic velocity range of 16.5x compared to conventional best practice double-frame PIV. Hot-wire anemometry is used in characteristic locations in the flow field as an independent reference measurement. The results show that the time-resolved HDR method automatically selects the most optimal pulse separation in each vector location, as a function of time. The method is implemented based on readily available data, has a low computational cost and is fully compatible with conventional multi-grid vector evaluation algorithms.