Journal of Terramechanics最新文献

Dynamic simulations of various types of off-road vehicles, from planetary rovers to agricultural equipment, have long relied on well-established semi-empirical terramechanics models. While these models do have drawbacks and reliability issues that have been addressed by numerous works in the decades since the models were first introduced, semi-empirical approaches remain one of the few ways to simulate realistic wheel-soil interaction in real-time. One of their drawbacks is their assumption that the terrain is a flat plane. The models work by integrating normal and shear stresses along the wheel-terrain contact patch. The normal stress at each point along the contact patch is determined using an equation that computes soil pressure based on semi-empirical parameters, the dimensions of the wheel and the sinkage, which is determined based on the distance between the point and the plane that defines the terrain. Other works simplify the rough terrain contact problem by defining an equivalent contact plane at each time step in order to continue to be able to use semi-empirical models - modified to work with slanted planes - to compute the interaction forces. In this work, we propose a new, modified version of the semi-empirical model in which interaction forces for a wheel travelling on rough terrain can be computed without the need to use an equivalent contact plane. To highlight the advantages of our proposed approach, we compare our simulation results to the results of simulations using an existing approach for modelling a wheel travelling over rough terrain using traditional semi-empirical models.

Reducing the position and attitude deviation of the planetary rover while driving is an important issue that needs to be considered in the design and controller development of the new types of planetary rovers at this stage. It is also the basis for whether the rovers can carry out exploration missions with high precision requirements on the complex terrain of planetary surfaces. A systematic study of the deviation problems generated by planetary rovers under the most basic open-loop path control is of great significance to improve the effectiveness of planetary detection. In this study, based on simulated Martian terrain and soil, planetary rover driving experiments under various scenes were conducted to test the resulting position and attitude deviation and evaluation indexes under different path types, terrain distributions, driving speeds and steering radius. By combining the experimental phenomena, the action characteristics of single wheel with ground and its influence on the state of the whole vehicle during the deviation generation process are analyzed. And finally, the discussion and conclusion are directed to how to optimize the planetary rover path control. These systematic experiments and analyses can provide valuable references for researchers engaged in the development of mobile controllers for planetary rovers.

Precision tillage (PT) is an innovative method that aims to take mechanical actions in the soil only where it is needed to curb the impact of heavy machinery usage on the soil. This research explores the use of remote sensing to measure relevant soil parameters to implement a PT strategy. This was achieved by combining traditional soil properties measurements and a non-contact approach based on taking hyperspectral camera (HSC) data in the field. Six methods were generated and divided into two sets to determine soil properties to make PT decisions. The first set includes mathematical functions that were generated from the ground true data (GTD). The second set includes functions that were generated from the remotely sensed HSC data and have a relationship with the methods in the first set. It was possible to tune the functions’ parameters to increase the accuracy. In addition, prediction error categories set at 5 % intervals were used to select the best method. The results show that a tuned method based on the GTD has an overall error below 5 %, and a tuned method based on HSC data has an overall error below 10 %.

The discrete element method (DEM) has been widely used to simulate varied sand particles interacting with earthmoving machines. However, past research using DEM barely addressed accurate verification and validation for different sand moisture content. Therefore, the main purpose of this paper is to reveal the range of key parameters of an adhesive force model used in the DEM simulation corresponding to the specific sand moisture content. We considered the bulldozing phenomenon to be typical earthmoving work and performed the bulldozing experiments under different sand moisture levels to investigate the bulldozing force variations. Subsequently, the DEM simulation with an adhesive force model calculated the bulldozing force corresponding to the experimental results. The values for two adhesive parameters, i.e., a scaling magnitude and the maximum adhesive distance between particles, were adjusted such that the maximum bulldozing force calculated in the DEM coincides with that of the experiments under different moisture contents. The experimental verification of the DEM revealed the relationship curves between these two key parameters corresponding to the different moisture content. The relationship obtained in this paper implies that the DEM simulation carefully adjusting the adhesive force parameters can reproduce machine interaction on moist sand environments accurately.

This paper presents a discrete element/finite element (DE/FE) coupling method to investigate the trafficability of off-road tires on wet granular terrains. Firstly, a DE model of the wet terrain is established, and a linear contact model is adopted to describe the interaction between particles, while the adhesion effect between wet particles is simulated by a liquid bridge force model. An FE model of an off-road tire is then developed, and the Yeoh hyperelastic material model is used to describe the large deformations and nonlinear mechanical behaviors of the off-road tire. Furthermore, numerical simulations of the angle of repose of wet particles are compared with experimental studies to verify the effectiveness of the DE/FE coupling method. Finally, the tire traction behavior under different complex working conditions is predicted by the presented DE/FE coupling approach. The simulation results show that the absolute value of tire sinkage increases almost linearly (the sinkage is 97.1 mm at 25% moisture content) with the rise of moisture content among particles. The rate of change of sinkage is greater for small friction coefficients ($<$ 0.3) than that for large friction coefficients ($⩾$0.3). The drawbar pull experiences a rapid increase for the slide friction coefficient with a range 0.3 and 0.7, after which the rate of change slows down ($⩾$0.7). However, the drawbar pull exhibits an opposite trend as the tire pressure and height of the tread pattern increase. Numerical results also indicate that the smaller the slide friction coefficient, the larger the soil deformation, flow, and failure area in wet granular terrains.

Due to the low gravity environment and the influence of complex terrain condition in deep space exploration, wheeled mobile systems are prone to meet motion abnormalities. The excellent motion performance of walking robot is more suitable for the future deep space exploration, but the robots are prone to occur large sinkage in soft terrain. A mechanical model is built to describe a gait cycle of a walking robot under soft terrain and low gravity environment. The force on the footpad during actual movement in a gait cycle is obtained through a single-legged test bench under the simulated planet terrain. The effects of sizes of footpads, sinkage and other factors are explored. The results indicate that the larger the size of the footpad, the greater the horizontal force on the footpad, the better the motion performance is. But as the size of footpad increase, the vertical force decreases which indicates poor support performance. By comparing and analyzing the model values with the experimental values, for the horizontal force F_T, the average errors for the average force and peak force are 10.05% and 7.76%. The average errors for average force and peak force are 5.19% and 5.86% for vertical force F_N. The values are not significantly different from the model values and experimental values which indicates that the mechanical model has high accuracy. The obtained mechanical model can provide a reference for the motion of walking robots in complex low gravity environment.

In order to study the effect of contact length of tire on tractive performance of tractor, experiments were conducted using a single wheel tester fitted with 13.6–28 bias ply tire in a soil bin in soft soil condition. Contact length and contact width were measured at different normal loads (9.8 kN and 13.72 kN) and inflation pressures (83, 103, 124 and 138 kPa). Results showed that the contact length had higher influence on tire pulling ability and tractive efficiency as compared to contact width of the tire. An equation for predicting contact length was developed using XLSTAT software, with normal load and inflation pressure as an independent variables and contact length as a dependent variable. The model demonstrated high efficiency with a coefficient of determination (R²) 0.96, a percentage of variation 0.76 %, a root mean square error 10.841, and an adjusted R² 0.95. Additionally, a second-order polynomial equation was developed using curve fitter app to estimate drawbar pull of a tractor by keeping wheel slip and contact length as independent parameters. Validation with another set of data obtained for 14.6–28 tire yielded R² 0.93 and less than 4 % variation, thus indicated the model’s accuracy in predicting drawbar pull.

Legged robots exhibit superior adaptability to complex extraterrestrial environments compared to wheeled mobile robots. However, legged robots employed in planetary exploration face challenges in dealing with soft terrains. This paper focuses on investigating the issues of large foot sinkage and slip encountered by legged robots on soft terrain. Extensive experiments on quasi-static loading, loading with impact and tangential force have been carried out for both spherical and cylindrical feet. The variations in normal force, tangential force, and sinkage are meticulously recorded and analyzed. Foot-terrain interaction mechanics models are established to address scenarios involving substantial sinkage and sliding sinkage, leveraging the stress distribution characteristics of deformable soil. Accurate models are obtained through parameter identification utilizing experimental data, which can aid in the foot design of legged robots intended for planetary exploration. Based on the developed models and experimental data, a design optimization scheme for the coronal foot is proposed, leading to performance enhancements that are validated through experimental verification.

We propose a framework for discrete scientific data compression based on the tensor-train (TT) decomposition. Our approach is tailored to handle unstructured output data from discrete element method (DEM) simulations, demonstrating its effectiveness in compressing both raw (e.g. particle position and velocity) and derived (e.g. stress and strain) datasets. We show that geometry-driven “tensorization” coupled with the TT decomposition (known as quantized TT) yields a hierarchical compression scheme, achieving high compression ratios for key variables in these DEM datasets.

Vertical-axis rotary tillers are preferred over other soil-engaging tools for inter-culture operations due to their superiority in avoiding tillage pan formation, facilitating drainage, and operability at higher forward speeds. To optimize their design and operation, and to promote sustainable agricultural practices, a greater understanding of the kinematics, dynamics, and soil-structure interaction of vertical axis rotary tiller is required, along with the optimization of required energy. In this study, discrete element method (DEM) is used to analyse the interaction between soil and rotor blades, by incorporating the Hysteric Spring Contact Model along with linear cohesion model v2. Soil-rotor blade interaction DEM model is developed using Altair® EDEM® to analyse the effect of u/v ratio (2.13, 2.90, 3.70, and 4.44) and average operating depth (30 mm, 50 mm, and 70 mm) on draft and torque requirements for the rotor blade, as well as experimentally validating the simulation in a soil bin. In this study, lower u/v ratios in vertical axis rotary tillers demand higher torque for larger soil volumes. Additionally, torque rises with operating depth, owing to increased soil volume and strength. The simulated results closely followed the measured draft and torque for all combinations of u/v ratio and operating depth (R² 0.96 and 0.99). These findings indicate the DEM model as a dependable approach for modelling the performance of rotary tillers under different soil conditions.