0448 / Lunar rover discrete element method study and calibration

Paper presented at the 16th European-African Regional Conference of the ISTVS

https://doi.org/10.56884/XUAC7188

Title: Lunar rover discrete element method study and calibration

Authors: James Hurrell, Keisuke Takehana, Kentaro Uno, and Kazuya Yoshida

Abstract: Context. The Discrete Element Method (DEM) is a high-fidelity simulation tool to study the interaction of granular material. The single-wheel interaction of a lunar rover wheel with Toyoura sand is studied. Traditionally Toyoura sand is considered cohesionless but is measured to have a cohesion similar to Lunar soil. Aims. Develop a well-calibrated DEM wheel-soil simulation with and without cohesion for an equivalent angle of repose (AoR). Methods. 3D DEM single-wheel simulations are performed for Toyoura sand in Earth conditions. Separate calibration for the simulation parameters uses AoR. The Johnson–Kendall–Roberts (JKR) model is used, allowing for particle cohesion modelling. Simulations are kept homogeneous and use spherical particles. A comparison is made between non-cohesive and cohesive simulations. Traction coefficient, wheel sinkage, wheel trace and soil flow under the wheel are measured. Results. The static friction coefficient, rolling friction coefficient and cohesion have the most significant influence on an AoR. The optimisation model determines ideal parameters for simulating AoR that match experimental values. When applied to single-wheel simulations, there is a slight reduction in traction coefficient for cohesive soil. Differences in sinkage, wheel trace and soil motion are negligible. Conclusions. Alongside the parameter calibration performed, the results of the simulations are considered suitable for traction performance. Improvements can be made with soil depth and consideration of void ratio. For a homogenous soil, cohesion may not be critical to the soil response. Future studies will use direct comparison to experiment, reduced gravity experiments and lunar simulant results to refine the simulations.

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