| Issue |
EPJ Web Conf.
Volume 340, 2025
Powders & Grains 2025 – 10th International Conference on Micromechanics on Granular Media
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|
|---|---|---|
| Article Number | 12012 | |
| Number of page(s) | 4 | |
| Section | Emerging Topics: Additive Manufacturing & Meta Materials, Microgravity, Tribo-Charging, Active Particles, and Artificial Intelligence & Machine Learning | |
| DOI | https://doi.org/10.1051/epjconf/202534012012 | |
| Published online | 01 December 2025 | |
https://doi.org/10.1051/epjconf/202534012012
Machine learning for prediction of dynamical clustering in granular gases
1 IKS, Faculty of Informatics, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany
2 MTRM, Medical Faculty, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany
3 Dept. of Engineering, Brandenburg University of Appl. Sciences, Magdeburger Str. 50, 14770 Brandenburg an der Havel, Germany
4 MARS, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany
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Published online: 1 December 2025
Abstract
Continuously excited dense granular gases in microgravity can develop spatial inhomogeneities of the particle distribution. Dynamical clustering is a phenomenon where a significant share of particles concentrate in strongly overpopulated regions. It is caused by a complex interplay between the energy influx and dissipation in collisions. The overall packing fraction, container geometry, and excitation parameters influence the gas-cluster transition. We perform Discrete Element Method (DEM) simulations for frictional spheres in a cuboid container and apply statistical criteria to the packing fraction profiles. Machine learning (ML) methods are used to study the dependence of the gas-cluster transition on system parameters. It is a promising alternative to predict the state of the system without the need for the time-consuming DEM simulations. We identify the best models for predicting the dynamical clustering of frictional spheres in a specific experimental geometry.
© The Authors, published by EDP Sciences, 2025
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