Lagrangian tracking of colliding droplets

Abstract

We introduce a new Lagrangian particle tracking algorithm that tracks particles in three dimensions to separations between trajectories approaching contact. The algorithm also detects low Weber number binary collisions that result in coalescence as well as droplet breakup. Particles are identified in two-dimensional high-resolution digital images by finding sets of circles to describe the edge of each body. This allows identification of particles that overlap in projection by over 80% even for noisy images and without invoking additional temporal data. The algorithm builds trajectories from three-dimensional particle coordinates by minimizing a penalty function that is a weighted sum of deviations from the expected particle coordinates using information from four moments in time. This new hybrid algorithm is validated against synthetic data and found to perfectly reproduce more trajectories than other commonly used methods. Collisions are detected with 95% accuracy for particles that move on average less than one tenth the distance to their nearest neighbor.

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Acknowledgements

We would like to thank Melanie Li Sing How and Lance Collins of Cornell University for providing DNS data of inertial coalescing particles in turbulence for testing the tracking algorithm presented here.

Funding

This material is based upon work supported by the National Science Foundation under Grant No. 1605195.

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Correspondence to R. V. Kearney.

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Kearney, R.V., Bewley, G.P. Lagrangian tracking of colliding droplets. Exp Fluids 61, 155 (2020). https://doi.org/10.1007/s00348-020-02991-x

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