Fluctuations of particle motion in granular avalanches - from the microscopic to the macroscopic scales

The prediction of dynamical quantities in granular avalanches based on graph neural networks

The study of granular avalanches in rotating drums is not only essential to understanding various complex behaviors of interest in granular media from a scientific perspective; it also has valuable applications in regard to industrial processes and geological catastrophes. Despite decades of research studies on avalanches, a proper understanding of their dynamic properties still remains a great challenge to scientists due to a lack of state-of-the-art techniques. In this study, we accurately predict the avalanche dynamic features of three-dimensional granular materials in rotating drums, by using graph neural networks on the basis of their initial static microstructures alone. We find that our method is robust to changes in various model parameters, such as the interaction potential, size polydispersity, and noise in particle coordinates. In addition, with the grain-scale velocities obtained either from our network or from numerical simulations, we find an approximately equal and strong correlation between the global velocity and global velocity fluctuation in our 3D granular avalanche systems, which further demonstrates the predictive power of our trained graph neural networks to uncover the fundamental physics of granular avalanches. We expect our method to provide more insight into the avalanche dynamics of granular materials and other amorphous systems in the future.

Onset and dynamics of avalanches in a rotating cylinder: From experimental data to a geometric model

Particle image velocimetry has been applied to measure particle velocities on the free surface of a bed of particles within a rotating cylinder during avalanching. The particle velocities were used to examine the validity of existing avalanche models and to propose an alternative model. The movement of particles depends on their location on the surface of the bed: Particles located near the center of the bed travel the farthest, while the distance traveled decreases at an increasing rate for particles located farther from the center. The start of an avalanche can be determined to a single initiation point that can be located on the bottom half of the bed; the avalanche quickly propagates through the entire free surface with 90% of the surface in motion within 257 ms (approximately 20% of the total duration of an avalanche). The experimental insight is used to formulate a geometric model, in which three equal-sized sections flow down the bed surface during an avalanch. The predictions of the model are validated by experimental mixing measurements.