metadata
license: cc-by-nc-4.0
tags:
- emmi-ai
- physics-simulation
- dem
- cfd-dem
- neural-operator
pretty_name: NeuralDEM Dataset
NeuralDEM Dataset
Dataset repository for NeuralDEM, containing simulation data for training and evaluating deep learning surrogates for industrial particulate flows and particle-fluid coupled systems.
Dataset Summary
The NeuralDEM dataset covers two primary physics benchmarks:
- Hopper Simulations (Particle Systems)
- Setup: Hopper domain with a bottom outlet initially loaded with ~250,000 particles discharging over time.
- Physics: Discrete Element Method (DEM) dynamics across diverse hopper geometry angles and particle friction regimes.
- Fluidized Bed Reactor (Particle-Fluid Coupled Systems)
- Setup: Reactor containing ~500,000 particles with uniform fluid (air) injection from the bottom grid.
- Physics: Coupled CFD-DEM multi-physics system over ~160,000 hexahedral CFD grid cells across varying fluid inlet velocities.
For inference scripts, model checkpoints, and simulation rollouts, visit the NeuralDEM GitHub Repository.
License
This dataset is distributed under the CC-BY-NC 4.0 license.
Citation instructions
@article{alkin2024neuraldem,
title={{NeuralDEM} for real time simulations of industrial particular flows},
author={Benedikt Alkin and Tobias Kronlachner and Samuele Papa and Stefan Pirker and Thomas Lichtenegger and Johannes Brandstetter},
journal={Nature Communications Physics},
year={2025}
doi={10.1038/s42005-025-02342-4},
}