Comparison of discrete element method and traditional modeling methods for steady-state wheel-terrain interaction of small vehicles

Smith, William; Melanz, Daniel; Senatore, Carmine; Iagnemma, Karl; Peng, Huei

doi:10.1016/j.jterra.2014.08.004

Cited by 54 publications

(27 citation statements)

References 41 publications

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“…Interest is increasing in the use of DEM models to improve the physical representation of off-road vehicle mobility in conditions where classical terramechanics models have difficulty (Li et al, 2012;Lichtenheldt and Schäfer, 2013;Nakashima et al, 2010;Smith and Peng, 2013;Smith et al, 2014;Wang et al, 2011). These studies have demonstrated that even 2-D DEM simulations with relatively simple particle geometries can provide useful qualitative representations of off-road vehicle mobility.…”

Section: Dem Models and Their Constraintsmentioning

confidence: 99%

“…Examples include utilizing spherical particles for computational efficiency (Smith et al, 2014), adjusting particle density to achieve a reasonable bulk density but not PD, using uniform particle-size distributions, and using 2-D models to simulate 3-D processes. A comprehensive examination of how closely a DEM model needs to replicate the micro-scale features of a target granular aggregate has yet to be done.…”

Section: Dem Models and Their Constraintsmentioning

confidence: 99%

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Discrete element method simulations of Mars Exploration Rover wheel performance

Johnson

Kulchitsky

Duvoy

et al. 2015

Journal of Terramechanics

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Mars Exploration Rovers (MERs) experienced mobility problems during traverses. Three-dimensional discrete element method (DEM) simulations of MER wheel mobility tests for wheel slips of i = 0, 0.1, 0.3, 0.5, 0.7, 0.9, and 0.99 were done to examine high wheel slip mobility to improve the ARTEMIS MER traverse planning tool. Simulations of wheel drawbar pull and sinkage MIT data for i 6 0.5 were used to determine DEM particle packing density (0.62) and contact friction (0.8) to represent the simulant used in mobility tests. The DEM simulations are in good agreement with MIT data for i = 0.5 and 0.7, with reasonable but less agreement at lower wheel slip. Three mobility stages include low slip (i < 0.3) controlled by soil strength, intermediate slip (i $ 0.3-0.6) controlled by residual soil strength, and high slip (i > 0.6) controlled by residual soil strength and wheel sinkage depth. Equilibrium sinkage occurred for i < 0.9, but continuously increased for i = 0.99. Improved DEM simulation accuracy of low-slip mobility can be achieved using polyhedral particles, rather than tri-sphere particles, to represent soil. The DEM simulations of MER wheel mobility can improve ARTEMIS accuracy.

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Section: Dem Models and Their Constraintsmentioning

confidence: 99%

Section: Dem Models and Their Constraintsmentioning

confidence: 99%

Discrete element method simulations of Mars Exploration Rover wheel performance

Johnson

Kulchitsky

Duvoy

et al. 2015

Journal of Terramechanics

Self Cite

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“…While not specifically addressing gravity, the method promises relevant insight also for the present innovation. Numerical methods like the Discrete Element Method (Smith et al, 2014, Moreland, 2013 provide computational tools to calculate the behavior of regolith under different physical conditions. These tools are useful to design for example the optimal lug height and thickness of a lugged wheel on flat terrain.…”

Section: Introductionmentioning

confidence: 99%

UTOPUS Traction Technology: A new method for planetary exploration of steep and difficult terrain

Nannen¹,

Bover²,

Zöbel³

et al. 2020

Preprint

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After several successful missions to explore the surface of Mars with wheel-based rovers, the exploration of difficult and steep terrain has gained prominence in the field of planetary exploration, calling for new methods of vehicle locomotion which offer stability in steep and difficult terrain. UTOPUS traction technology offers a new method of locomotion which abandons the wheel paradigm for a two-phased anchoring and de-anchoring technique by driving removable crampons into the ground. In agriculture it minimizes soil compaction, reduces energy consumption, and produces a draft force similar to much heavier wheel-based tractors.Here we investigate whether the inherent stability of locomotion based on removable crampons allows exploration of steep and difficult terrain. We present experimental results from climbing and descending a mound of heterogeneous dust, sand, and granular material at the critical angle of repose, at an inclination of 25–40 degrees. The UTOPUS vehicle repeatedly climbed and descended the mound safely. An initial problem when reaching the top of the mound was solved by rebalancing the vehicle. Occasional failure occurred when the vehicle had strong lateral inclination, or on patches of very loose ground, suggesting the need for some design changes to the current model.

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“…These terrain parameters are measured by specific soil tests in laboratory with the soil collected in field tests. The experimental procedure is similar to that found in [ 37 ]. D represents the wheel diameter and b refers to the width of the wheel-soil contact patch.…”

Section: Resultsmentioning

confidence: 90%

Prediction of Military Vehicle’s Drawbar Pull Based on an Improved Relevance Vector Machine and Real Vehicle Tests

Fan

Sun

Lin

et al. 2016

Sensors

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The scientific and effective prediction of drawbar pull is of great importance in the evaluation of military vehicle trafficability. Nevertheless, the existing prediction models have demonstrated lots of inherent limitations. In this framework, a multiple-kernel relevance vector machine model (MkRVM) including Gaussian kernel and polynomial kernel is proposed to predict drawbar pull. Nonlinear decreasing inertia weight particle swarm optimization (NDIWPSO) is employed for parameter optimization. As the relations between drawbar pull and its influencing factors have not been tested on real vehicles, a series of experimental analyses based on real vehicle test data are done to confirm the effective influencing factors. A dynamic testing system is applied to conduct field tests and gain required test data. Gaussian kernel RVM, polynomial kernel RVM, support vector machine (SVM) and generalized regression neural network (GRNN) are also used to compare with the MkRVM model. The results indicate that the MkRVM model is a preferable model in this case. Finally, the proposed novel model is compared to the traditional prediction model of drawbar pull. The results show that the MkRVM model significantly improves the prediction accuracy. A great potential of improved RVM is indicated in further research of wheel-soil interactions.

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Comparison of discrete element method and traditional modeling methods for steady-state wheel-terrain interaction of small vehicles

Cited by 54 publications

References 41 publications

Discrete element method simulations of Mars Exploration Rover wheel performance

Discrete element method simulations of Mars Exploration Rover wheel performance

UTOPUS Traction Technology: A new method for planetary exploration of steep and difficult terrain

Prediction of Military Vehicle’s Drawbar Pull Based on an Improved Relevance Vector Machine and Real Vehicle Tests

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