Development of a GPU-based DEM solver for parameter optimization in the simulations of soil-sweep tool interactions

The Discrete Element Method (DEM) is a powerful technique for simulating granular materials in agricultural applications, yet it is notoriously computationally and memory-intensive. A typical DEM simulation of soil-sweep tool interactions involves tens of thousands of particles, each of which may potentially interact with many others. This results in hundreds of thousands of interactions being computed at every time step, while the need for numerical stability often requires very small time steps. Despite these challenges, DEM holds significant promise to allow the design of more efficient agricultural tools. This paper introduces an in-house-developed modular library based on CUDA C++ for GPUs, aimed at accelerating DEM simulations using a single GPU. The library is designed to facilitate efficient memory usage, employing a per-thread approach where each GPU thread computes one discrete-element particle. To accelerate particle–particle contact searches, we implemented a cell-linked-list algorithm. Our library utilizes the Hertz–Mindlin contact model, which has been widely adopted in agricultural DEM applications. Validation of the code was performed through comparisons with commercial software. Using our software, experimental measurements of a sweep tool moving through sandy soil were replicated with high accuracy by employing differential evolution for parameter calibration, achieving these results using 38 912 particles and running 2 700 instances within 16 h on a single GPU. • GPU-based DEM library for the simulation of soil-sweep tool interactions. • Soil-sweep tool DEM simulations involving 38912 particles run in 20 s on a GPU. • High-resolution parameter sensitivity analysis of micromechanical DEM parameters. • Micromechanical parameter fitting of a soil using an evolutionary algorithm on a GPU.