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Three-dimensional finite-time Lyapunov-exponent analysis of fluid dusty plasmas under weightlessness using a machine-learning particle reconstruction technique

André Melzer*, Christina Knapek, Daniel Maier, Daniel Mohr, and Stefan Schütt

  • *Contact author: melzer@physik.uni-greifswald.de
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Phys. Rev. E 111, 045214 – Published 25 April, 2025

DOI: https://doi.org/10.1103/PhysRevE.111.045214

Abstract

We have performed experiments on dusty plasmas under the weightlessness conditions of parabolic flights where the dust particles form an extended homogeneous dust cloud. The three-dimensional (3D) dynamic state of the dust cloud is characterized. Therefore, the particle trajectories have been recorded using a four-camera stereoscopic camera system. From that, the 3D particle trajectories have been determined using both a machine-learning particle reconstruction technique and the deterministic shake-the-box algorithm. From the trajectories, characteristic fluid parameters, such as flow fields and finite-time Lyapunov exponent (FTLE)-based fluid structures have been calculated and analyzed. The FTLE analysis indicates that the fluid is characterized by an incompressible flow with small-scale behavior. Furthermore, it is demonstrated that the machine-learning based approach allows to reliably characterize the dynamic states by comparison with the shake-the-box algorithm.

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Outline

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Phys. Rev. E 111, 045214– Published 25 April, 2025
  • Received 22 November 2024
  • Revised 20 January 2025
  • Accepted 13 March 2025
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