A GPU-accelerated simulator for the DEM analysis of granular systems composed of clump-shaped elements

TL;DR

This paper introduces a GPU-accelerated Discrete Element Method simulator capable of modeling complex-shaped granular elements with diverse material properties, validated through lunar simulant and rover simulations, and made openly accessible.

Contribution

The paper presents a novel GPU-accelerated DEM simulator that handles complex, non-spherical elements with variable material properties, enabling large-scale granular system simulations.

Findings

Validated the simulator with lunar simulant and rover tests.

Demonstrated the simulator's scalability with over 11 million elements.

Confirmed a granular scaling law through VIPER rover simulation.

Abstract

We discuss the use of the Discrete Element Method (DEM) to simulate the dynamics of granular systems made up of elements with nontrivial geometries. The DEM simulator is GPU accelerated and can handle elements whose shape is defined as the union with overlap of diverse sets of spheres with user-specified radii. The simulator can also handle complex materials since each sphere in an element can have its own Young's modulus $E$, Poisson ratio $\nu$, friction coefficient $\mu$, and coefficient of restitution CoR. To demonstrate the simulator, we produce a "digital simulant" (DS), a replica of the GRC-1 lunar simulant. The DS follows an element size distribution similar but not identical to that of GRC-1. We validate the predictive attributes of the simulator via several numerical experiments: repose angle, cone penetration, drawbar pull, and rover incline-climbing tests. Subsequently, we carry out a sensitivity analysis to gauge how the slope vs. slip curves change when the element shape, element size, and friction coefficient change. The paper concludes with a VIPER rover simulation that confirms a recently proposed granular scaling law. The simulation involves more than 11 million elements composed of more than 34 million spheres of different radii. The simulator works in the Chrono framework and utilizes two GPUs concurrently. The GPU code for the simulator and all numerical experiments discussed are open-source and available on GitHub for reproducibility studies and unfettered use and distribution.