Abstract
Abstract The two-dimensional particle image velocimetry (PIV) data are inevitably contaminated by noise due to various imperfections in instrumentation or algorithm, based on which the well-established vortex identification methods often yield noise or incomplete vortex structure with a jagged boundary. To make up this deficiency, a novel method was proposed in this paper and the efficiency of the new method was demonstrated by its applications in extracting the two-dimensional spanwise vortex structures from 2D PIV data in open-channel flows. The new method takes up a single vortex structure by combining model matching and vorticity filtering, and successfully locates the vortex core and draws a streamlined vortex boundary. The new method shows promise as being more effective than commonly used schemes in open-channel flow applications.
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