The aim of the article is to propose a simple engineering method for identifying and characterizing vortical structures within a flow field measured with a classic two-component PIV measurement system. Some of the most popular vortex-detection systems are briefly presented. Of these, many fail if spurious vectors are present within the flow field due to poor PIV image quality. The investigated method is robust and reliable. The method is tested on synthetic images of ideal vortices and on real PIV images of a four-bladed rotor wake. The synthetic images have different spatial resolution and different noise level in order to perform a parametric assessment. Other vortex-identification schemes are applied for comparison.

PIV data: Vortex Detection and Characterization / Coletta, Manuela; Fabrizio De Gregorio, ; Antonio, Visingardi; Iuso, Gaetano. - International Symposium on Particle Image Velocimetry – ISPIV 2019:(2019), pp. 1-11. (Intervento presentato al convegno 13th International Symposium on Particle Image Velocimetry – ISPIV 2019 tenutosi a Munich nel July 22-24, 2019).

PIV data: Vortex Detection and Characterization

COLETTA, MANUELA;Gaetano Iuso
2019

Abstract

The aim of the article is to propose a simple engineering method for identifying and characterizing vortical structures within a flow field measured with a classic two-component PIV measurement system. Some of the most popular vortex-detection systems are briefly presented. Of these, many fail if spurious vectors are present within the flow field due to poor PIV image quality. The investigated method is robust and reliable. The method is tested on synthetic images of ideal vortices and on real PIV images of a four-bladed rotor wake. The synthetic images have different spatial resolution and different noise level in order to perform a parametric assessment. Other vortex-identification schemes are applied for comparison.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2736882
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