Modelling soil-rotor blade interaction of vertical axis rotary tiller using discrete element method (DEM)

Prakhar Patidar, Peeyush Soni, Achala Jain, Vijay Mahore

Journal of Terramechanics, Volume 112, 2024, Pages 59-68, ISSN 0022-4898

https://doi.org/10.1016/j.jterra.2024.01.001.(https://www.sciencedirect.com/science/article/pii/S0022489824000016)

Abstract: 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.

Keywords: Discrete element method; Modelling; Rotor blade design; Vertical axis rotary tillage; Draft force; Torque

Co-simulation for optimal working parameter selection during soil vibratory compaction process

Jianjun Shen, Zheng Tang, Feng Jia, Zhen Liu, Jingru Hou

Journal of Terramechanics, Volume 112, 2024, Pages 45-57, ISSN 0022-4898

https://doi.org/10.1016/j.jterra.2023.12.002.(https://www.sciencedirect.com/science/article/pii/S0022489823000988)

Abstract: The working parameters of vibratory rollers have an important effect on the compaction quality. The traditional method of obtaining the best working parameters through field tests is time-consuming and laborious. In order to determine the best working parameters more conveniently and accurately, a mechanical-hydraulic-finite element co-simulation method is proposed in this paper. This method considers the effect of the hydraulic system on vibration compaction and makes the simulation result as close to the actual condition as possible. By analyzing the change of soil stress and settlement, the effect regulation of working parameters on compaction quality is obtained. The results show that the proposed co-simulation method can accurately reflect the real conditions, and the best compaction quality can be achieved when the walking speed is 3 km/h, the vibration frequency is 24 Hz, and the amplitude is 2.5 mm. The research provides a reference for improving the compaction quality and compacting-related simulation.

Keywords: Vibratory compaction; Co-simulation; Hydraulic system; Finite element; Optimal working parameter

Study of passive steering mechanism for small Mars surface exploration rovers

Asahi Oe, Shin-Ichiro Nishida, Shintaro Nakatani

Journal of Terramechanics, Volume 112, 2024, Pages 35-43, ISSN 0022-4898

https://doi.org/10.1016/j.jterra.2023.12.001.(https://www.sciencedirect.com/science/article/pii/S0022489823000976)

Abstract: Planetary surface exploration rovers are required to have the ability to travel over uneven ground such as sandy or rocky terrain. In addition, to maintain long-term functionality under severe mass constraints, the rover must be highly reliable with a simple configuration. The reduction in the number of actuators will also contribute to a reduction in the number of electrical components involved and improve reliability. This paper proposes a lightweight and simple traveling and steering mechanism that combines a path-following system based on the difference in rotational speed of the left and right wheels when traveling in a curve and a passive Ackermann mechanism without an actuator, assuming a small exploration rover of a size and mass that can be mounted on a Japanese launch vehicle. We also propose a correction method to improve the path-following performance. We also developed a prototype wheeled rover of the target size and weight, and tested and evaluated the effectiveness of the proposed method in following the target path and overcoming obstacle on simulated soil.

Keywords: Mars Exploration Rovers; Passive Steering Mechanism; Path Following

Effects of vertical load and inflation pressure on tire-soil interaction on artificial soil

Nisreen Alkhalifa, Mehari Z. Tekeste, Pius Jjagwe, Thomas R. Way

Journal of Terramechanics, Volume 112, 2024, Pages 19-34, ISSN 0022-4898

https://doi.org/10.1016/j.jterra.2023.11.002.(https://www.sciencedirect.com/science/article/pii/S0022489823000897)

Abstract: Instrumented single tire soil bin testing was conducted on a rigid surface and artificial soil by vertically loading a radial tire (LT235/75R15) to two tire vertical loads (6 kN and 8 kN) inflated to three levels of tire inflation pressure (179, 241, and 283 kPa). Lowering the tire inflation pressure by 37 % resulted in 26 % (6 kN vertical load) and 39 % (8 kN vertical load) greater contact lengths (P < 0.05). The 2-D contact area on artificial soil (initial bulk density of 1.51 Mg/m3) was significantly affected (P < 0.05) by tire inflation pressure for each load case. Increasing the load significantly affected the tire’s contact length on soil (P = 0.0010); however, tire inflation pressure did not significantly affect the contact length on soil (P = 0.0609). Soil rut depth and tire-soil deformed volume were not significantly affected by vertical load and tire inflation pressure. Measured tire contact area on soil surface was 3.3 times the contact area on the rigid surface, suggesting tire-soil interaction interface properties on deformable soil are better than using the gross flat plate for evaluating low ground pressure tire technology effects on traction and reducing soil compaction.

Keywords: Artificial soil; Contact area; Contact length; Low-ground pressure (LGP); Deformed soil volume; Radial tire; Rut depth

The running gear construction impact on overcoming obstacles by light high-mobility tracked UGV

Daniela Szpaczyńska, Marian Łopatka, Piotr Krogul

Journal of Terramechanics, Volume 112, 2024, Pages 1-17, ISSN 0022-4898

https://doi.org/10.1016/j.jterra.2023.11.003.(https://www.sciencedirect.com/science/article/pii/S0022489823000903)

Abstract: Rubber tracked running gears are widely used in high-mobility Unmanned Ground Vehicles (UGV) to increase obstacle negotiation possibility in urban and rural terrain. The paper proposes a method of assessing the mobility level of the light UGV‘s tracked running gears in terms of their ability to overcome terrain obstacles. A model of rubber track system was created in the MSC ADAMS environment. A track-ground contact was also modeled, defining the traction force based on the Wong equations. For four different chassis models (rigid construction, bogies solution – rigid and elastically mounted to the frame and rocker-bogie construction), with two track tension variants, the ability to overcome five terrain obstacles was checked, taking into account three different types of soil. The solutions were accessed on the basis of parameters of general efficiency of overcoming obstacles, driving force and slip values, as well as the distribution of track pressures on the ground. The best solutions for each criterion were indicated. The simulation results showed an improvement in the driving properties with the use of elastically suspended elements. The results also emphasized the negative impact of increased track tension on overcoming obstacles and the impact of ground characteristics on the slip values of the running gear.

Keywords: Terrain Mobility; Rubber Track Running Gear; High-Mobility Unmanned Ground Vehicles; Obstacles Overcoming

A review of soil modeling for numerical simulations of soil-tire/agricultural tools interaction,

Dhruvin Jasoliya, Alexandrina Untaroiu, Costin UntaroiuJournal of Terramechanics, Volume 111, 2024, Pages 41-64, ISSN 0022-4898

https://doi.org/10.1016/j.jterra.2023.09.003.

(https://www.sciencedirect.com/science/article/pii/S002248982300085X)

Abstract: The study of deformable soils is one of the key factors in determining the tire, vehicle and/or agricultural tool design parameters. This literature review provides a brief overview of soil classification, soil testing, soil constitutive models, and numerical approaches utilized to model soil-tire/tool interaction. In the past, empirical, semi-empirical, and analytical soil models were used in these studies. However, some limitations occurred in terms of characterization of soil-tire/tool interaction in detail due to a large number of variables such as cohesion, moisture content, etc. In the last few decades, the finite element (FE) method was used with different formulations such as Lagrangian, Eulerian, and Arbitrary Lagrangian Eulerian to simulate the soil-tire/tool interaction. Recently, particle-based methods based on continuum mechanics and discrete mechanics started to be employed and showed good capability in terms of modeling of soil deformation and separation. Overall, this literature review provides simulation researchers insights into soil interaction modeling with tires and agricultural tools.

Keywords: Soil-tire interaction; Soil-tool interaction; Soil classification; Soil testing; Soil constitutive material models; Finite element modeling; Arbitrary Lagrangian Eulerian; Smoothed particle hydrodynamics; Discrete element method

Discrete element contact model and parameter calibration for clayey soil particles in the Southwest hill and mountain region

Le Yang, Junwei Li, Qinghui Lai, Liangliang Zhao, Jianjian Li, Ronghao Zeng, Zhihong Zhang

Journal of Terramechanics, Volume 111, 2024, Pages 73-87, ISSN 0022-4898

https://doi.org/10.1016/j.jterra.2023.10.002.(https://www.sciencedirect.com/science/article/pii/S0022489823000873)

Abstract: Distinct physical properties of red clay soil in hilly and mountainous regions of southwest China, including high adhesiveness and density, challenge the operation of agricultural machinery. A scarcity of accurate discrete element simulation parameters for this soil type restricts computational modeling. The study was focused on red clay soil with a moisture content of 12.50% ± 1% and a measured repose angle of 35.54°. The soil's inherent physical properties were identified through experimental assessments. Soil contact mechanical parameters were obtained from the GEMM database, and optimal contact parameter ranges were determined using Steepest Ascent Experiments, with the simulated soil particle repose angle serving as the response value. A second-order regression model was developed using a quadratic regression rotation orthogonal combination test. By taking the actual repose angle as the optimization criterion, parameters were optimized. The optimal contact mechanical parameters in EDEM simulations were identified as: JKR surface energy at 8.981 J/m2, recovery coefficient at 0.474, dynamic friction coefficient at 0.196, and static friction coefficient at 0.45. The model yielded a repose angle of 36.21°, closely corresponding with the observed value, with a relative error of 1.80%. The parameters calibrated in this study offer a valuable reference for future soil-tool interaction studies and tillage implement optimization in these regions.

Keywords: Red clay; Discrete element method; Repose angle; Computational simulation; Parameter calibration; Response surface methodology

Deep learning-based soil compaction monitoring: A proof-of-concept study

Shota Teramoto, Shinichi Ito, Taizo Kobayashi

Journal of Terramechanics, Volume 111, 2024, Pages 65-72, ISSN 0022-4898

https://doi.org/10.1016/j.jterra.2023.10.001.(https://www.sciencedirect.com/science/article/pii/S0022489823000861)

Abstract: The dynamic behavior of the vibratory drum of a soil compactor for earthworks is known to be affected by soil stiffness. Real-time monitoring techniques measuring the acceleration of vibratory drums have been widely used for soil compaction quality control; however, their accuracy can be affected by soil type and conditions. To resolve this problem, a novel deep learning-based technique is developed. The method allows the regression estimation of soil stiffness from vibration drum acceleration responses. By expanding the range of applicability and improving accuracy, the proposed method provides a more reliable and robust approach to evaluate soil compaction quality. To train the estimation model, numerous datasets of noise-free waveform data are numerically generated by solving the equations of motion of the mass–spring–damper system of a vibratory roller. To validate the effectiveness of the proposed technique, a field experiment is conducted. A good correlation between the estimated and measured values is demonstrated by the experimental results. The correlation coefficient is 0.790, indicating the high potential of the proposed method as a new real-time monitoring technique for soil compaction quality.

Keywords: Soil compaction; Vibratory roller; Intelligent compaction; Deep learning; Soil stiffness; Subgrade reaction coefficient

Machine learning-based draft prediction for mouldboard ploughing in sandy clay loam soil

Vijay Mahore, Peeyush Soni, Arpita Paul, Prakhar Patidar, Rajendra Machavaram

Journal of Terramechanics, Volume 111, 2024, Pages 31-40, ISSN 0022-4898

https://doi.org/10.1016/j.jterra.2023.09.002.(https://www.sciencedirect.com/science/article/pii/S0022489823000836)

Abstract: Machine learning (ML) models are developed to predict draft for mouldboard ploughs operating in sandy-clay-loam soil. The draft of tillage tools is influenced by soil cone-index, tillage-depth, and operating-speed. We used a three-point hitch dynamometer to measure draft force, a cone penetrometer for soil cone-index, rotary potentiometers for tillage-depth, and proximity sensors for operating-speed. Draft requirements were experimentally measured for a two-bottom mouldboard plough at three different tillage-depths and various operating-speeds. We developed prediction models using recent ML algorithms, including Linear-Regression, Ridge-Regression, Support-Vector-Machines, Decision-Trees, k-Nearest-Neighbours, Random-Forests, Adaptive-Boosting, Gradient-Boosting-Regression, Light-Gradient-Boosting-Machine, and Categorical-Boosting. These models were trained and tested using a dataset of field measurements including soil cone-index, tillage-depth, operating-speed, and corresponding draft values. We compared the measured draft with the commonly used ASABE model, which resulted in an R2 of 0.62. Our ML models outperformed the ASABE model with significantly better performance. The test data set achieved R2 values ranging from 0.906 to 0.983. These results demonstrate that the developed ML models effectively capture the complex nonlinear relationship between input parameters and draft of mouldboard plough.

Keywords: Draft prediction; Machine Learning; Mouldboard ploughing; Gradient Boosting; Random Forest; Tillage operation