SMuK 2023 – wissenschaftliches Programm

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P: Fachverband Plasmaphysik

P 11: Poster I

P 11.15: Poster

Mittwoch, 22. März 2023, 14:00–15:30, HSZ EG

3D machine-learning reconstruction techniques for particles in dusty plasmas — •Andre Melzer, Michael Himpel, Christina Knapek, Daniel Maier, Daniel Mohr, and Stefan Schütt — Institute of Physics, University Greifswald

Dusty plasmas provide an interesting system to study fundamental processes in many-particle systems since the particles can be imaged and followed on the kinetic individual-particle level.

We have performed experiments with dusty plasmas on parabolic flights using a stereoscopic camera system with four cameras. Under microgravity conditions the dust particles form a dense dust cloud, and a small fraction of the dust cloud is imaged by the four cameras.

In this contribution, techniques to reconstruct the three-dimensional position of the dust particles from the stereoscopic images with the help of machine-learning methods are reviewed and tested. This is important for a future application in the Compact facility planned for the ISS [1].

The work is supported by DLR under 50WM2161/50WM1962.

[1] C. Knapek et al., "COMPACT - A new complex plasma facility for the ISS", Plasma Phys. Control. Fusion 64 (2022) 12400