About AIM

Granular materials exhibit complex, nonsmooth, and multiscale behaviors that pose significant challenges to current predictive models and computing resources. Yet, these materials are central to a wide spectrum of industrial and environmental processes. The inherent complex rheology makes their handling, processing and use highly challenging and energy consuming. They also play a key role in understanding and mitigating natural hazards like landslides and avalanches, whose impacts have been intensifying due to climate change.

AIM’s interdisciplinary methodology bridges applied mathematics, mechanics, and artificial intelligence to better understand, model, and predict the mechanics and dynamics of granular media.
By combining high-fidelity particle-scale simulations, cutting-edge in-operando experiments, and AI methods constrained with the fundamental principles from statistical physics and non-equilibrium thermodynamics, AIM will deliver a proof of principle to robustly and accurately predict the fine- and large-scale behavior of granular systems.

AIM’s research is conducted at the Université Grenoble Alpes (UGA) and the National Institute for Research in Digital Science and Technology (Inria). AIM’s research members are based at TRIPOP and THOTH teams, INRAe-IGE, and 3SR.