Comparative Study of Established DPIV Algorithms for Planar Velocity Measurements

Abstract

This paper represents a continuation of our effort to develop a velocity evaluation scheme optimized to resolve multiphase flows. An improved adaptive hybrid scheme that integrates the dynamically adaptive cross-correlation method with a particle tracking velocimetry algorithm is developed, presented and evaluated in this paper. A detailed description of the methodology, error analysis using Monte-Carlo simulations and elaborate comparisons with established schemes and robust commercial packages are presented. Improvements were guided towards increased accuracy for resolving vortical and poly-dispersed multi-phase flows. We introduce a novel iterative scheme that localizes the cross-correlation. We incorporate state of the art elaborate image processing techniques that allow increased particle densities. A new particle pairing method based on an adaptive cross-correlation masking is introduced. Finally, a refined gaussian estimation scheme that involves only four non-saturated pixels for the particle centroid detection is proposed. Overall, the dynamically adaptive hybrid velocity evaluation scheme presented here allows superior resolution of high velocity gradients, minimizes the loss of the rotational motion of the particles, and eliminates the spatial averaging effects inherent from the cross-correlation.