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Experiments in Fluids

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01-08-2021 | Research Article

Application of clustering and the Hungarian algorithm to the problem of consistent vortex tracking in incompressible flowfields

Authors: P. R. R. J. Stevens, A. Sciacchitano

Published in: Experiments in Fluids | Issue 8/2021

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Abstract

The ability to track vortices spatially and temporally is of great interest for the study of complex and turbulent flows. A methodology to solve the problem of vortex tracking by the application of machine learning approaches is investigated. First a well-known vortex detection algorithm is applied to identify coherent structures. Hierarchical clustering is then conducted followed by a unique application of the Hungarian assignment algorithm. Application to a synthetic flowfield of merging Batchelor vortices results in robust vortex labelling even in a vortex merging event. A robotic PIV experimental dataset of a canonical Ahmed body is used to demonstrate the applicability of the method to three-dimensional flows.

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Title: Application of clustering and the Hungarian algorithm to the problem of consistent vortex tracking in incompressible flowfields
Authors: P. R. R. J. Stevens
A. Sciacchitano
Publication date: 01-08-2021
Publisher: Springer Berlin Heidelberg
Published in: Experiments in Fluids / Issue 8/2021
Print ISSN: 0723-4864
Electronic ISSN: 1432-1114
DOI: https://doi.org/10.1007/s00348-021-03265-w

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