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Modeling the impact of terrain surface deformation on drag force using discrete element method and empirical formulation.
- Source :
-
Applied Mathematical Modelling . Dec2024, Vol. 136, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- Understanding motion-induced terrain deformation is essential for improving predictive models in geotechnical engineering, infrastructure development, and robotics. The existing analysis assumes a uniform and unchanged environment and lacks a description of the terrain deformation induced by motion, which is particularly significant when the grains are loosely packed. To address this gap, we performed numerical investigations to mathematically model the changes in the surrounding environment and their corresponding effects on resistance. Specifically, we examined the response of granular materials and the energy variation of the particles during motion. Increased energy in the direction of motion was categorized as influences above or below the medium surface. Aligned with the influencing factors, two variables were considered to quantify the impact on the drag force. Building upon the energy analysis and the framework of Resistive Force Theory, we proposed a drag force model for buried motion in loose granular terrain. Compared with the experimental data, the average predictive error decreased from 17.8% to less than 2.7%. Our study provides a feasible approach for incorporating the effects of terrain deformation into a drag force model, thereby enhancing the accuracy and contributing to the development of granular locomotion. • The impact of motion-induced terrain deformation on the surface layer is modeled. • Granular pile formation leads to increased depth of buried objects. • The flow of particles raises local packing density. • A drag force model integrated with environmental changes is established and verified. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0307904X
- Volume :
- 136
- Database :
- Academic Search Index
- Journal :
- Applied Mathematical Modelling
- Publication Type :
- Academic Journal
- Accession number :
- 179601464
- Full Text :
- https://doi.org/10.1016/j.apm.2024.115636