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dc.contributor.authorSimpson, CE
dc.contributor.authorBabinsky, H
dc.contributor.authorHarvey, JK
dc.contributor.authorCorkery, S
dc.description.abstractThis paper address problems that arise when investigating vortices within an unsteady flow when a true picture of the velocity field can only be obtained from single-shot PIV surveys (SS-PIV). The implications of noise within data are considered when it is not legitimate to minimise this by averaging the results from repeated tests. An improvement to be applied when there are nearby vortices to the non-localised vortex detection scheme proposed by Graftieaux et al (2001) is presented. This specifically acknowledges the gradients in the background shear due to velocities induced by these neighbours. The errors that arise in estimating the vortex strength and core radius when the laser plane is not perpendicular to the vortex axis are also discussed. The averaging of SS- PIV data from survey planes that are closely separated either in time or space is proposed as a way to improve the signal-to-noise ratio for SS-PIV surveys. Sample results for the flow associated with the front wing-wheel combination of a F1 car are presented to illustrate the effectiveness of the techniques proposed. In this example the wing is located just ahead of the wheel which has a very unsteady wake. Thus, the vortices shed from the wing are perturbed in a random fashion as they interact with this wake, necessitating the use of SS-PIV. The results demonstrate that the techniques proposed here are capable of identifying the vortices and can determine their properties adequately.
dc.publisherSpringer Science and Business Media LLC
dc.rightsAttribution 4.0 International
dc.titleDetecting vortices within unsteady flows when using single-shot PIV
prism.publicationNameExperiments in Fluids
dc.contributor.orcidHarvey, JK [0000-0001-8937-9309]
rioxxterms.typeJournal Article/Review

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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International