The discrete element method (DEM) is crucial for modeling complex particulate systems but is limited by high computational demands. Here, the authors introduce NeuralDEM, a deep learning surrogate that enables real-time simulations by capturing fine-grained particle dynamics using a neural field model, significantly advancing engineering applications and accelerating process cycles across industries.
- Benedikt Alkin
- Tobias Kronlachner
- Johannes Brandstetter
