Experiments in Fluids

, Volume 48, Issue 4, pp 589–605 | Cite as

Particle tracking velocimetry with an ant colony optimization algorithm

  • Kazuo Ohmi
  • Sanjeeb Prasad Panday
  • Achyut Sapkota
Research Article

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.

Abbreviations

ACO

Ant colony optimization

AS

Ant system

PIV

Particle image velocimetry

PTV

Particle tracking velocimetry

SOM

Self-organizing maps

TSP

Traveling salesman problem

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Kazuo Ohmi
    • 1
  • Sanjeeb Prasad Panday
    • 1
  • Achyut Sapkota
    • 1
  1. 1.Faculty of EngineeringOsaka Sangyo UniversityDaito-shiJapan

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