Three-dimensional particle tracking velocimetry for turbulence applications

Kim, Jin-Tae

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https://hdl.handle.net/2142/88245 Copy

Description

Title

Three-dimensional particle tracking velocimetry for turbulence applications

Author(s)

Kim, Jin-Tae

Issue Date

2015-06-09

Director of Research (if dissertation) or Advisor (if thesis)

Chamorro, Leonardo P

Department of Study

Mechanical Science & Engineering

Discipline

Theoretical & Applied Mechanics

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Flow visualization
• Jet flow
• Lagrangian frame
• Particle tracking velocimetry
• Turbulence

Abstract

Three-dimensional particle tracking velocimetry (3D-PTV) is a flow measure- ment technique that tracks the Lagrangian paths of a set of particles using photogrammetric principles. This technique allows to investigate complex fluid flows by measuring velocity and acceleration along particle trajectories. Implementing and optimizing the technique is, however, a somewhat di - cult task involving accurate optical set-up, volumetric illumination, precise calibration and rigorous post-processing. This thesis explains thorough guidelines to accomplish an optimal system set-up by discussing the hardware configuration, software operation, and post processing methods. First, this paper describes the system background for an e cient experimental set-up, such as the required camera specification, an accurate calibration method, an appropriate type of tracer particles and the illumination source. Then, the detailed usage of the 3D-PTV software, including the compilation and operation, with a description of file structures are discussed. To further utilize the output data, post-processing methods developed by Dr.Alex Liberzon, Dr.Beat Luthi and the author, which in- terpret the data both in Eulerian and Lagrangian frames, are explained. A circular jet flow is analyzed as demonstration of the technique.

Graduation Semester

2015-8

Type of Resource

text

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http://hdl.handle.net/2142/88245

Copyright and License Information

Copyright 2015 Jin-Tae Kim

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