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Acceleration feature points of unsteady shear flows
IVU Traff Technology AG, Germany; Zuse Institute Berlin, Germany.
IST Austria, Austria.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-7285-0483
Zuse Institute Berlin, Germany.
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2016 (English)In: ARCHIVES OF MECHANICS, ISSN 0373-2029, Vol. 68, no 1, p. 55-80Article in journal (Refereed) Published
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Text
Abstract [en]

A FRAMEWORK FOR EXTRACTING FEATURES IN 2D TRANSIENT FLOWS, based on the acceleration field to ensure Galilean invariance is proposed in this paper. The minima of the acceleration magnitude (a superset of acceleration zeros) are extracted and discriminated into vortices and saddle points, based on the spectral properties of the velocity Jacobian. The extraction of topological features is performed with purely combinatorial algorithms from discrete computational topology. The feature points are prioritized with persistence, as a physically meaningful importance mea sure. These feature points are tracked in time with a robust algorithm for tracking features. Thus, a space-time hierarchy of the minima is built and vortex merging events are detected. We apply the acceleration feature extraction strategy to three two-dimensional shear flows: (1) an incompressible periodic cylinder wake, (2) an incompressible planar mixing layer and (3) a weakly compressible planar jet. The vortex-like acceleration feature points are shown to be well aligned with acceleration zeros, maxima of the vorticity magnitude, minima of the pressure field and minima of lambda(2). Copyright (C) 2016 by IPPT PAN

Place, publisher, year, edition, pages
POLISH ACAD SCIENCES INST FUNDAMENTAL TECHNOLOGICAL RESEARCH , 2016. Vol. 68, no 1, p. 55-80
Keywords [en]
visualization; feature extraction; flow topology
National Category
Fluid Mechanics Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:liu:diva-127064ISI: 000372097000003OAI: oai:DiVA.org:liu-127064DiVA, id: diva2:919367
Note

Funding Agencies|German Research Foundation (DFG) via the Collaborative Research Center "Control of Complex Turbulent Shear Flows" [SFB 557]; Emmy Noether Program; Zuse Institute Berlin (ZIB); DFG-CNRS research group "Noise Generation in Turbulent Flows"; French Agence Nationale de la Recherche (ANR); European Social Fund (ESF) [100098251]; Polish National Centre of Science [2011/01/B/ST8/07264]; Ambrosys Ltd. Society for Complex Systems Management; Bernd R. Noack Cybernetics Foundation; GENCI-[CCRT/CINES/IDRIS] [2011-[x2011020912]]

Available from: 2016-04-13 Created: 2016-04-13 Last updated: 2025-02-05

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