Three-dimensional particle tracking velocimetry for turbulence applications: Case of a jet flow

Jin Tae Kim, David Kim, Alex Liberzon, Leonardo P. Chamorro

Research output: Contribution to journalArticle

Abstract

3D-PTV is a quantitative flow measurement technique that aims to track the Lagrangian paths of a set of particles in three dimensions using stereoscopic recording of image sequences. The basic components, features, constraints and optimization tips of a 3D-PTV topology consisting of a high-speed camera with a four-view splitter are described and discussed in this article. The technique is applied to the intermediate flow field (5 <x/d <25) of a circular jet at Re ≈ 7,000. Lagrangian flow features and turbulence quantities in an Eulerian frame are estimated around ten diameters downstream of the jet origin and at various radial distances from the jet core. Lagrangian properties include trajectory, velocity and acceleration of selected particles as well as curvature of the flow path, which are obtained from the Frenet-Serret equation. Estimation of the 3D velocity and turbulence fields around the jet core axis at a cross-plane located at ten diameters downstream of the jet is compared with literature, and the power spectrum of the large-scale streamwise velocity motions is obtained at various radial distances from the jet core.

Original languageEnglish (US)
Article numbere53745
JournalJournal of Visualized Experiments
Volume2016
Issue number108
DOIs
StatePublished - Feb 27 2016

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Rheology
Velocity measurement
Turbulence
High speed cameras
Flow measurement
Power spectrum
Flow fields
Trajectories
Topology

ASJC Scopus subject areas

  • Neuroscience(all)
  • Chemical Engineering(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

Cite this

Three-dimensional particle tracking velocimetry for turbulence applications : Case of a jet flow. / Kim, Jin Tae; Kim, David; Liberzon, Alex; Chamorro, Leonardo P.

In: Journal of Visualized Experiments, Vol. 2016, No. 108, e53745, 27.02.2016.

Research output: Contribution to journalArticle

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