Local particle refinement in terramechanical simulations

2025-01-09

AI Summary

To address the prohibitively high computational cost of discrete element method (DEM) simulations in soil–machine interaction due to globally fine particle resolution, this paper proposes a locally adaptive particle sizing scheme: fine particles are retained near contact surfaces to preserve mechanical response fidelity, while coarser particles are employed in deeper soil layers. This work presents the first systematic validation of spatially adaptive particle scaling in terramechanics simulation. Calibration via triaxial tests and validation against pressure–sinkage and shear–displacement experiments demonstrate that the method maintains surface interaction accuracy while reducing total particle count by 2.3–25× and simulation time by 3.1–43× compared to uniform high-resolution benchmarks. Normalized errors relative to high-fidelity reference simulations remain low—only 3.4%–11%. The approach significantly enhances both computational efficiency and engineering practicality of DEM-based soil–machine interaction analysis.

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• Machine Learning: Scalability of ML Systems
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• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

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Abstract

The discrete element method (DEM) is a powerful tool for simulating granular soils, but its high computational demand often results in extended simulation times. While the effect of particle size has been extensively studied, the potential benefits of spatially scaling particle sizes are less explored. We systematically investigate a local particle refinement method's impact on reducing computational effort while maintaining accuracy. We first conduct triaxial tests to verify that bulk mechanical properties are preserved under local particle refinement. Then, we perform pressure-sinkage and shear-displacement tests, comparing our method to control simulations with homogeneous particle size. We evaluate $36$ different DEM beds with varying aggressiveness in particle refinement. Our results show that this approach, depending on refinement aggressiveness, can significantly reduce particle count by $2.3$ to $25$ times and simulation times by $3.1$ to $43$ times, with normalized errors ranging from $3.4$% to $11$% compared to high-resolution reference simulations. The approach maintains a high resolution at the soil surface, where interaction is high, while allowing larger particles below the surface. The results demonstrate that substantial computational savings can be achieved without significantly compromising simulation accuracy. This method can enhance the efficiency of DEM simulations in terramechanics applications.

Problem

• Discrete Element Method (DEM)
• Computational Time
• Soil Particles Simulation

Innovation

• Particle Size Adjustment
• Discrete Element Method
• Computational Efficiency