Particle tracking velocimetry with an ant colony optimization algorithm

Particle tracking velocimetry with an ant colony optimization algorithm A new concept algorithm based on the ant colony optimization is developed for the use in 2-D and 3-D particle tracking velocimetry (PTV). In the particle matching process of PTV, the ant colony optimization is usually aimed at minimization of the sum of the distances between the first-frame and second-frame particles. But this type of minimization often goes unsuccessfully in the regions where the particles are located very close to each other. In order to avoid this flaw, a new type of minimization is attempted using a physical property corresponding to the flow consistency or the quasi-rigidity of particle distribution patterns. Specifically, the ant colony optimization is now aimed at minimization of the sum of the relaxation of neighbor particles. In the present study, the new algorithm is applied to sets of 2-D and 3-D synthetic particle images as well as the experimental images with successful results. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Experiments in Fluids Springer Journals

Particle tracking velocimetry with an ant colony optimization algorithm

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Publisher
Springer-Verlag
Copyright
Copyright © 2010 by Springer-Verlag
Subject
Engineering; Engineering Thermodynamics, Heat and Mass Transfer; Fluid- and Aerodynamics; Engineering Fluid Dynamics
ISSN
0723-4864
eISSN
1432-1114
D.O.I.
10.1007/s00348-009-0815-2
Publisher site
See Article on Publisher Site

Abstract

A new concept algorithm based on the ant colony optimization is developed for the use in 2-D and 3-D particle tracking velocimetry (PTV). In the particle matching process of PTV, the ant colony optimization is usually aimed at minimization of the sum of the distances between the first-frame and second-frame particles. But this type of minimization often goes unsuccessfully in the regions where the particles are located very close to each other. In order to avoid this flaw, a new type of minimization is attempted using a physical property corresponding to the flow consistency or the quasi-rigidity of particle distribution patterns. Specifically, the ant colony optimization is now aimed at minimization of the sum of the relaxation of neighbor particles. In the present study, the new algorithm is applied to sets of 2-D and 3-D synthetic particle images as well as the experimental images with successful results.

Journal

Experiments in FluidsSpringer Journals

Published: Jan 10, 2010

References

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