Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe
DY: Fachverband Dynamik und Statistische Physik
DY 21: Granular Matter
DY 21.3: Vortrag
Mittwoch, 19. März 2025, 10:00–10:15, H43
Advances and challenges in experiments with granular gases of rod-like particles — •Dmitry Puzyrev1, Torsten Trittel2,1, Kirsten Harth2,1, Mahdieh Mohammadi2, Raul Cruz Hidalgo3, and Ralf Stannarius2,1 — 1Otto von Guericke University, Magdeburg, Germany — 2Brandenburg University of Applied Sciences, Brandenburg an der Havel, Germany — 3Univerisity of Navarra, Pamplona, Spain
Granular gases, i.e., ensembles of free-moving macroscopic particles which collide inelastically, demonstrate fascinating dynamical effects like unusual cooling properties, violation of energy equipartition, clustering, and spontaneous collective movement. Our investigation is focused on 3D microgravity experiments with ensembles of rod-like particles [1] and their mixtures. With the help of machine learning methods, we have obtained various statistical properties for the mixture of thinner and thicker rods [2]. Kinetic energy partitions and collision numbers were extracted for both vibrational heating and homogeneous cooling regimes. The systems in question pose some conundrums, such as cooling rates larger that theoretically predicted or accumulation of kinetic energy in rotational DOF which is hard to observe in the experiment. Currently, the granular gas mixture of shorter and longer rods is under analysis. Our studies are funded within by the DLR projects VICKI, EVA-II, JACKS, and KORDYGA (50WM2252, 50WK2348, 50WM2340, and 50WM2242). [1] K. Harth et al., Rev. Lett., 120, 214301 (2018) [2] Puzyrev et al., npj Microgravity, 10, 36 (2024)
Keywords: Granular gas; Machine learning; Microgravity