<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

A new method for extracting spanwise vortex from 2D particle image velocimetry data in open-channel flow

State Key Laboratory of Hydroscience and Engineering

Journal of Hydrology and Hydromechanics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The two-dimensional particle image velocimetry (PIV) data are inevitably contaminated by noise due to various imperfections in instrumentation or algorithm,...

A new method for extracting spanwise vortex from 2D particle image velocimetry data in open-channel flow

Online veröffentlicht: 10. Aug. 2020

Seitenbereich: 242 - 248

Eingereicht: 03. Sept. 2019

Akzeptiert: 28. Apr. 2020

DOI: https://doi.org/10.2478/johh-2020-0020

Schlüsselwörter
Vortex identification, Spanwise vortex, Vorticity filtering, Open-channel flow

© 2020 Peng Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A new method for extracting spanwise vortex from 2D particle image velocimetry data in open-channel flow

Online veröffentlicht: 10. Aug. 2020

Seitenbereich: 242 - 248

Eingereicht: 03. Sept. 2019

Akzeptiert: 28. Apr. 2020

DOI: https://doi.org/10.2478/johh-2020-0020

SchlüsselwörterVortex identification, Spanwise vortex, Vorticity filtering, Open-channel flow

© 2020 Peng Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Vortex identification, Spanwise vortex, Vorticity filtering, Open-channel flow