# 7125 - A DATA-DRIVEN PARAMETER IDENTIFICATION METHOD OF CHARACTERIZATION OF WHEEL-REGOLITH INTERACTION FOR LUNAR SURFACE VEHICLES {% hint style="info" %} Paper presented at ISTVS 2025 | 55th Conference of the International Society for Terrain-Vehicle Systems {% endhint %} **Authors:** *Hiroaki Kawamura, Tadashi Matsuura, Shinichiro Noda, Kohei Shintani, Nobutaka Tanishima, Natsu Fujioka* **Keywords:** Regolith; Discrete element method; Differential evolution based on adaptive sampling; Soil characteristcs; Vacuum environment **Abstract:** This paper describes a method to clarify the interaction between wheels and regolith particles when a rover runs on the lunar surface. The regolith dust that lifts during movement can adhere to the equipment mounted on the vehicle, potentially causing significant impacts on its functionality. To mitigate the effects of regolith dust on the onboard equipment, it is crucial to understand the behavior of regolith particles that are lifted by the wheels. Additionally, quantitatively understanding the interaction between wheels and regolith particles is important because it affects the wheels' traction and the vehicle's running performance. Many experimental and analytical studies have been published to address this. In the case of numerical analysis, studies using Discrete Element Methods (DEMs) to clarify microscopic interactions have been conducted. To represent the behavior of regolith particles in numerical analysis, it is necessary to identify many parameters that characterize the physical behavior of particles based on test results, which can be time-consuming due to trial and error in deriving these parameters. In this study, a new data-driven set-based searching method, called Differential Evolution Based on Adaptive Sampling (DEBAS), is adopted for the parameter identification of the particles. The proposed method can efficiently find combinations of particle characteristic parameters that match the desired element tests. The parameters obtained through this method will be verified by comparison with several characteristic tests. Furthermore, obtained parameters are validated by comparison with a scaled wheel-regolith simulant interaction test. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://2025.istvs.org/submissions/papers/7125.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.