Particle tracking velocimetry in liquid gallium flow about a cylindrical obstacle

TL;DR

This study applies particle tracking velocimetry to liquid gallium flow around a cylindrical obstacle, developing image processing and tracking algorithms to analyze flow dynamics with high confidence.

Contribution

It introduces a novel image processing methodology and particle tracking algorithm tailored for liquid metal flows with challenging imaging conditions.

Findings

Effective particle detection despite low contrast

Successful reconstruction of long particle trajectories

Particles exhibit Stokes numbers indicating good tracking accuracy

Abstract

This paper demonstrates particle tracking velocimetry performed for a model system wherein particle-laden liquid metal flow about a cylindrical obstacle was studied. We present the image processing methodology developed for particle detection in images with disparate and often low signal- and contrast-to-noise ratios, and the application of our MHT-X tracing algorithm for particle trajectory reconstruction within and about the wake flow of the obstacle. Preliminary results indicate that the utilized methods enable consistent particle detection and recovery of long, representative particle trajectories with high confidence. However, we also underline the necessity of implementing a more advanced particle position extrapolation approach for increased tracking accuracy. We also show that the utilized particles exhibit the Stokes number range that suggests good flow tracking accuracy, and that the particle time scales extracted from reconstructed trajectories are consistent with expectations based a priori estimates.