# Particle tracking velocimetry with an ant colony optimization algorithm

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## 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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