Dresden 2026 – wissenschaftliches Programm
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DY: Fachverband Dynamik und Statistische Physik
DY 25: Franco-German Session on Granular Matter II
DY 25.4: Vortrag
Dienstag, 10. März 2026, 14:45–15:00, HÜL/S186
Granular gas mixtures: Experiments and numerical simulations — •Dmitry Puzyrev1, Kirsten Harth2,1, Torsten Trittel2,1, Raúl Cruz Hidalgo3, and Ralf Stannarius2,1 — 1Otto von Guericke University, Magdeburg, Germany — 2Brandenburg University of Applied Sciences, Brandenburg an der Havel, Germany — 3University of Navarra, Pamplona, Spain
Granular gases are ensembles of free-moving macroscopic particles which collide inelastically, which leads to effects like unusual heating (gain of mechanical energy from external sources) and cooling (dissipative loss of mechanical energy), clustering, and spontaneous collective movement. Such systems can exist in different dynamical regimes depending on filling fraction, particle shapes and material properties, as well as external energy input. Our investigation is focused on 3D microgravity experiments with ensembles of non-spherical, rod-shaped particles [1] and their mixtures [2]. Machine learning-aided software used for particle detection, 3D matching and tracking is available as an open-source package [3] and can be applied to other multiparticle tracking problems. In addition to previously published results for a mixture of thinner and thicker rods [2], we present the initial results for a short/long rods mixture. Our studies are funded within by the German Aerospace Center (DLR) projects EVA-II, VICKI, KORDYGA and PARADYSE (50WK2348, 50WM2252, 50WM2242, 50WM2542). [1] K. Harth et al., Rev. Lett., 120, 214301 (2018) [2] Puzyrev et al., npj Microgravity, 10, 36 (2024) [3] A. Niemann et al., github.com/ANP-Granular/ParticleTracking, JOSS 10(109), 5986 (2025)
Keywords: Granular gas; Machine learning; Microgravity