Calibration of Snow Particle Contact Parameters for Simulation Analysis of Membrane Structure Snow Removal Robot

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Authors: Jiangtao Dong, Fuxiang ZHANG, Fengshan Huang, Xiaofei Man
Cited by: 1
References: 22

Abstract

To enhance the accuracy of discrete element method (DEM) simulation for the snow removal process performed by autonomous robots on membrane structures, this study calibrated the key contact parameters of snow particles used in the simulation. Through literature research, the intrinsic parameters and contact parameter ranges for snow particles and membrane structures were determined. A discrete element model of snow particles was established, and the Hertz–Mindlin with Johnson–Kendall–Robert contact model was selected to simulate the formation process of the repose angle. Using the actual repose angle of snow particles as the target, four significant factors were identified through the P-B experiment, and other factors were set at the intermediate level. Through the steepest slope climbing experiment and response surface design, second-order response equations of the four significant factors were obtained. The optimal parameter combination was calculated as follows: the surface energy of snow particles was 0.23 J/m2; the restitution coefficient, static friction coefficient, and rolling friction coefficient of snow–snow were 0.141, 0.05, and 0.03; and the restitution coefficient, static friction coefficient, and rolling friction coefficient of snow–membrane were 0.2, 0.18, and 0.03. The simulated repose angle was 40.62°, and the relative error with the actual repose angle was 0.32%. These calibration results are reliable and can provide a reliable simulation basis and essential data support for the optimal design of a snow removal robot and the dynamic simulation of the operation process.

Fields of Study & Subjects

Soil Mechanics and Vehicle Dynamics Winter Sports Injuries and Performance Robotic Locomotion and Control

Publication details

Journal / source
Applied Sciences
Publisher
MDPI AG
Volume
16
Issue
2
Pages
610–610
Publication date
7 January 2026
Language
EN