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DEM Analysis of Contact Forces and Tractive Performance of Rigid Wheel in Granular Media

EasyChair Preprint no. 8699

15 pagesDate: August 24, 2022

Abstract

Understanding the interaction between wheel and granular media in variable loading conditions is critical for prediction of traction of wheeled and tracked vehicles in off-road environments. A discrete element method (DEM) is used to predict net and gross traction of a rigid wheel operating in granular subgrade over a broad range of slip conditions, represented by towed, powered, and braked modes. The DEM is routinely used for modeling vehicle performance, but although simulations appear to be realistic, the accuracy of the method is often not fully established. The modeling accuracy, in this study, is assessed by comparison to physical experiments performed over a wide range of slip. The cone index, as a measure of soil strength, is simulated to allow comparison to laboratory test data. Profiles of normal and shear stresses along the contact patch are calculated and correlated with published experimental results. The location of the transition point, at which shear stress transitions from positive to negative values, is determined. In an effort to establish the boundary conditions of the DEM, average displacements, instantaneous velocities of particles, average stress and void ratio in the subgrade are presented demonstrating the greater data resolution provided by the DEM versus physical experiments. Integration of DEM and physical experiments for comprehensive models of vehicle-terrain interaction is discussed.

Keyphrases: Discrete Element Method, Off-Road Mobility, Rigid Wheel, Tractive Performance

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:8699,
  author = {Bohumir Jelinek and George Mason and John Peters and Farshid Vahedifard and Jody Priddy},
  title = {DEM Analysis of Contact Forces and Tractive Performance of Rigid Wheel in Granular Media},
  howpublished = {EasyChair Preprint no. 8699},

  year = {EasyChair, 2022}}
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