Discrete element modeling of cultivator sweep-to-soil interaction: Worn and hardened edges effects on soil-tool forces and soil flow

Simulation of tool-to-soil interaction provides opportunities to accelerate new equipment design and evaluate performance of tillage tools. Simulation based evaluation of worn tillage tools performance on soil flow has not been done. Discrete Element Modelling (DEM) has a potential to simulate worn tool to soil interaction problems, where worn tools CAD can be generated using 3D scanning. The DEM parameters of Hertz-Mindlin with Parallel Bond model were calibrated to match draft force and soil failure zone measured from a tool bar moving at 0.22 m/s and 38 mm cutting depth. The draft force and soil forward failure zone were predicted at 7% and 24% relative errors compared to measured values, respectively. Using the optimized DEM soil model, the interaction of three 3D reconstructed sweeps (new sweep, carbide treated-worn, untreated-worn) with soil were simulated to compare their geometric wear dimensional loss, performance on soil forces and soil flow. Results showed that the carbide treated-worn sweep had similar soil draft force and soil forward failure distance as the new sweep. The untreated-worn sweep showed lower vertical force (less suction) and its wing induced soil failure zone (front and lateral) showed poor soil tilth quality compared with the carbide treated-worn sweep and the new sweep

Discrete Element Modeling (DEM) of Cone Penetration Testing on Soil With Varying Relative Soil Density

Modeling soil-tool interaction is essential for equipment design and performance evaluation on soil behavior responses under loading. Computational tools based on particle-based mechanics such as Discrete Element Modeling (DEM) and Smoothed Particle Hydrodynamics (SPH) have potential in modeling large strain soil dynamic behaviors from soil-tool interaction. The objective of this study is to validate the accuracy and robustness of DEM calibration methodology as it relates to soil deformation during cone penetration on varying initial soil relative density. The influence of factors such as DEM material properties and cone to particle size ratio on DEM cone penetration simulation will be investigated. The paper presents a comparison of DEM predicted cone penetration resistance and laboratory measured penetration data on Norfolk sandy loam. Soil mechanical behavior was modeled with Hertz-Mindlin (HM) contact stiffness model and a new coupled frictional law for static and rolling resistance coefficients. The DEM material properties were calibrated using residual strength from direct shear test. DEM simulations were performed using LIGGGHTS, open source DEM code. Cone penetrometer experiments using anÂASABE standard cone with 12.53 mm cone base diameter and 30-degree cone tip were used to validate the calibrated DEM model. DEM prediction of cone penetration resistance trend and steady state values were in close agreement with the laboratory measured data for relative density range from 5 to 30%. At higher dense states (relative density of 90%), DEM calibration requires further improvement

Cap-hardening parameters of Cam-clay model variations with soil moisture content and shape-restricted regression model

Modeling of soil elastic and permanent plastic volumetric strains (compaction) caused by loading from machinery vehicles using the modified Cam-clay soil constitutive model requires understanding the behaviors of compression and rebound parameters under unsaturated soil conditions.  Oedometer tests were conducted on a sandy loam, a loam, and a clay loam soil, all tropical soils, at three initial soil moisture contents and five maximum stress levels (50, 100, 200, 300 and 400 kPa).  The objectives were to investigate the effects of soil moisture content and maximum applied stress on the modified compression index (l*) and modified rebound index (k*) parameters of a modified Cam-clay soil model on the three soils and predict the compressibility indices using the shape-restricted modeling technique.  The clay loam soil showed higher compressibility at lower maximum stress levels and wet moisture conditions (-10 kPa soil moisture potential) but as the maximum applied stress increased (> 200 kPa), the modified compression index (l*) variations with soil moisture content were insignificant (p > 0.05).  A loam soil exhibited similar compression characteristics to a clay loam soil at 26.12% d.b. and 23.67% d.b., respectively.  For a sandy loam soil, both critical state parameters were less sensitive to the variations in soil moisture content.  The loam soil, which had an organic matter content of 6.33%, rebounded more than clay loam and sandy loam soils especially at higher applied stress values.  On average, the modified compression index (l*) was about 23 to 36 times the modified rebound index (k*).  Shape-restricted and quadratic model fittings are presented to explain the relationship between the critical state parameters and maximum applied stresses for each soil moisture content.  The model fitting results indicated that shape-restricted regression predicted the modified Cam-clay model parameters as a function of maximum applied stress (or pre-compression stress) at very low Average Squared Error Loss (ASEL) and did so better than parametric quadratic equations.   Keywords: modified compression index (l*), modified rebound index (k*), axial stress, uniaxial compression cyclic test, soil moisture, soil type

Soil Drying Effects on Soil Strength and Depth of Hardpan Layers as Determined from Cone Index Data

Site-specific detection of a soil hardpan is an important step in precision farming. Different methods have been developed including the ASABE standard soil cone penetrometer to detect presence of hardpan layers. Most of the newly developed methods use results obtained by a soil cone penetrometer as a reference to validate their potential. Soil factors, mainly soil moisture and bulk density, may influence the cone index measurement and the prediction of the relative strength and depth of the hardpan layer. The effects of soil drying on hardpan characterizing attributes of peak cone index, depth to the peak cone index and depth to the top of the hardpan layer were studied for three compaction levels on a Norfolk sandy loam soil in a soil bin. The soil in the bin was wetted to near saturation and then subjected to four levels of soil drying. A multiple-probe soil cone penetrometer (MPSCP) was used to measure soil cone index. The results showed that soil drying had a significant effect on peak cone index for the single pass compaction (1.78 Mg m-3 within hardpan) and the double pass compaction (1.83 Mg m-3 within hardpan). The peak cone index increased two-fold and 1.3 times due to soil drying from ‘day-1’ to ‘day-4’ for the single pass compaction and for the double compaction, respectively. The depths to the top of the hardpan determined from the depth to the peak cone index and the depth to the top of the hardpan showed a statistically significant decreasing trend for the single pass compaction. The differences, however, were too small (< 2 cm) to justify varying prescription tillage depth due to soil drying

Modeling Ground Penetrating Radar (GPR) Technology for Seed Planting Depth Detection using Numerical Scheme based on Finite Difference Time Domain (FDTD) Method

Ground Penetrating Radar (GPR) is an electromagnetic (EM) signal based technology, commonly used as a non-destructive technique to explore subsurface features and identify different depth profiles in materials. The overall goals of this work is to evaluate GPR for non-destructive mapping of seed planting depth. Soils are inherently complex materials and numerous factors affect GPR behavior. The fundamental factors affecting GPR response are dielectric permittivity, magnetic permeability, and electrical conductivity, which are influenced by soil bulk density, texture, salinity, organic matter, volumetric water content, seed properties and physical geometry. To successfully optimize GPR’s ability to detect seed planting depth, the influence of these factors must be evaluated. This paper describes the development of a single dimensional GPR simulation model, based on finite difference time domain (FDTD) method, to evaluate the use of GPR sensing of seed planting depth. The simulation results shows that the EM signal is highly sensitive to high values of the electrical conductivity. High permittivity values decrease the EM signal velocity, wavelength and strength. A combination of these two properties leads to a significant EM signal attenuation ranging from 0 to ~ 800 dBm-1 as the signal traverses through the soil and seed. The lack of sufficient dielectric contrast between soil and seed presents a challenge on the detectability of the reflected signal by the radar receiver, therefore a sufficient dielectric contrast between the soil and seed has to be present to allow the GPR to be a viable tool to map the seed planting depth