Search Results (66)

Rabbit manure with high-moisture content exhibits complex adhesive and flow behaviors, which make accurate parameterization in discrete element method (DEM) simulations difficult. To improve the reliability of DEM modeling for rabbit manure composting processes, this study calibrated the contact parameters of rabbit manure at 65% moisture content using the angle of repose as the target response. A physical angle of repose test was first conducted using the cylindrical lifting method, yielding a measured value of 38.77°. The Hertz–Mindlin with Johnson–Kendall–Roberts (JKR) contact model was then adopted to represent the adhesive behavior of the material, and a three-stage optimization strategy consisting of a Plackett–Burman screening test, a steepest ascent test, and a Box–Behnken design was applied to identify and optimize the key parameters. The results showed that the particle restitution coefficient, rabbit manure–PLA rolling friction coefficient, and surface energy were the dominant factors affecting the angle of repose. The optimal parameter combination was a particle restitution coefficient of 0.56, a rabbit manure–PLA rolling friction coefficient of 0.375, and a surface energy of 0.243 J/m². Under these conditions, the simulated angle of repose was 39.21°, with a relative error of 1.13%. These calibrated parameters provide a reliable basis for DEM simulation and engineering optimization of rabbit manure composting equipment. Full article

Dust pollution has emerged as a critical issue in a wide range of industrial applications, creating an urgent demand for effective strategies to mitigate particle deposition. Recent experimental studies have demonstrated that superhydrophobic coatings represent a promising class of self-cleaning materials, primarily attributed to their hierarchical rough structures and intrinsically low surface energy. Nevertheless, the underlying self-cleaning mechanisms of superhydrophobic surfaces have not yet been fully elucidated. This work examines particle deposition on superhydrophobic surfaces featuring stochastic roughness distributions through computational modeling. Surface topographies were generated using Fast Fourier Transform techniques. An integrated lattice Boltzmann–discrete element method (LBM–DEM) framework simulated particle transport in superhydrophobic-coated channels. Particle–fluid coupling was achieved via the immersed moving boundary approach, while particle–surface interactions employed a modified Johnson–Kendall–Roberts (JKR) adhesion model. Parametric studies quantified effects of particle size, interfacial energy, flow Reynolds number, and topographical statistics on deposition dynamics. Experimental validation demonstrates good agreement between numerical predictions and measurements. Smaller particles exhibit a lower tendency to deposit on superhydrophobic surfaces, whereas increasing surface energy significantly enhances particle deposition due to stronger adhesion forces and the suppression of particle resuspension. In addition, higher Reynolds numbers effectively reduce particle deposition. The revealed self-cleaning mechanisms provide theoretical guidance for the design of high-performance self-cleaning coatings, and the identified effects of particle and surface parameters offer practical insights for anti-pollution engineering applications. Full article

To address the complex dynamic mechanisms and lack of static operation data in trench-digging for transverse planting of Salix psammophila sand barriers, a transverse trench-digging device was designed. Based on the discrete element method, the Hertz–Mindlin with JKR Cohesion model was used to simulate sandy soil. The Box–Behnken experiment was adopted to optimize the single auger structure with helix angle and soil-cutting angle as factors and trench depth and working torque as indices, yielding the optimal parameters of 30° soil-cutting angle and 20.37° helix angle (5.52 cm trench depth, 2.6 N·m maximum torque). The optimized auger was integrated into the device, and a further Box–Behnken experiment was conducted under a 20 cm fixed descending depth of the lifting platform. With auger rotation speed, shaft spacing and lifting speed as factors, and trench depth, soil compaction and Salix psammophila insertion depth as indices, the optimal operating parameters were determined as 257.25 r/min, 7 cm and 9 cm/s, corresponding to 6.7 cm trench depth, 33.37 kPa soil compaction and 14.87 cm insertion depth. This study clarifies the effects of auger and operation parameters on trench-digging quality, provides a basis for the design and parameter matching of dynamic continuous operation equipment, and offers a reference for the R&D of mechanized transverse planting equipment for Salix psammophila sand barriers, which is of practical value for reducing sand control costs and improving efficiency. Full article

Moisture content varies continuously during aerobic composting, which changes material flowability and can limit the use of a single set of discrete element method (DEM) parameters. To address this issue for a multi-component corn straw–pig manure mixture, we developed a rapid calibration workflow covering a moisture content range of 29–80%. Angle of repose (AoR) images were obtained using a cylinder-lifting test. To improve robustness for irregular pile contours, we proposed an AoR extraction method that combines LOESS smoothing with least-squares line fitting. Key DEM contact parameters affecting AoR were screened using a Plackett–Burman design, and their effective ranges were refined using a steepest-ascent test. A Box–Behnken design was then used to establish a response surface linking AoR to the significant DEM parameters. In addition, a polynomial relationship between moisture content and AoR was fitted and coupled with the AoR-parameter response surface to predict key DEM parameters directly from moisture content. Validation results showed that the predicted AoR exhibited a relative error below 10% across the tested moisture contents. An independent baffle-lifting validation test yielded a relative error below 5%. Overall, this workflow provided a practical strategy for setting DEM simulations of composting feedstocks under variable moisture content and supports numerical analysis and structural optimization of composting-related machinery. Full article

This study calibrated discrete element parameters for organic fertilizer (OF) and compost fertilizer (CF) to support spreading equipment design. Using the Hertz–Mindlin with JKR model, DEM simulations were integrated with physical angle of repose measurements. Parameters were systematically optimized via Plackett–Burman screening, steepest ascent, and Box–Behnken response surface methodology. Results indicated distinct moisture-sensitive behaviors: OF exhibited monotonic increases in dynamic friction coefficient (0.223–0.362) and JKR surface energy (0.064–0.166 J/m²), whereas CF showed nonlinear friction trends with surface energy rising from 0.209 to 0.326 J/m². A predictive model directly linking moisture content to DEM parameters was established using the cylinder-lifting method. Validation confirmed model accuracy, with angle of repose errors of 2.57% (OF) and 4.05% (CF). Simulated spreading widths closely matched field data, showing relative errors below 8%. The calibrated DEM framework provides a reliable basis for optimizing organic manure spreader performance. Full article

Cabbage stubble left in fields after harvest forms a mechanically complex stubble–soil composite that hinders subsequent tillage and crop establishment. Although the Discrete Element Method (DEM) is widely used to model soil-root systems, calibrated contact parameters for taproot-dominated vegetables like cabbage remain unreported. This study addresses this gap by calibrating a novel DEM framework that couples the JKR model and the Bonding V2 model to represent adhesion and mechanical interlocking at the stubble–soil interface. Soil intrinsic properties and contact parameters were determined through triaxial tests and angle-of-repose experiments. Physical pullout tests on ‘Zhonggan 21’ cabbage stubble yielded a mean peak force of 165.5 N, used as the calibration target. A three-stage strategy—factor screening, steepest ascent, and Box–Behnken design (BBD)—identified optimal interfacial parameters: shear stiffness per unit area = 4.40 × 10⁸ N·m⁻³, normal strength = 6.26 × 10⁴ Pa, and shear strength = 6.38 × 10⁴ Pa. Simulation predicted a peak pullout force of 162.0 N, showing only a 2.1% deviation from experiments and accurately replicating the force-time trend. This work establishes the first validated DEM framework for cabbage stubble–soil interaction, enabling reliable virtual prototyping of residue management implements and supporting low-resistance, energy-efficient tillage tool development for vegetable production. Full article

Most insects secrete special fluids from their tarsal pads which are essential for the function of their attachment systems. Previous studies investigated several physical and chemical characteristics of this pad fluid in different insect species. However, there is not much known about the mechanical properties of fluid from smooth adhesive pads. In this study, we used the stress–relaxation nanoindentation method to examine the viscoelastic properties of pad fluid from Sungaya aeta. Force–displacement and stress–relaxation curves on single fluid droplets were recorded with an atomic force microscope (AFM) and analyzed using Johnson–Kendall–Roberts (JKR) and generalized Maxwell models for determination of effective elastic modulus (E), work of adhesion (Δγ) and dynamic viscosity (η). In addition, we used white light interferometry (WLI) to measure the maximal height of freshly acquired droplets. Our results revealed three different categories of droplets, which we named “almost inviscid”, “viscous” and “rigid”. They are presumably determined at the moment of secretion and retain their characteristics even for several days. The observed mechanical properties suggest a non-uniform composition of different droplets. These findings provide a basis for advancing our understanding about the requirements for adaptive adhesion-mediating fluids and, hence, aid in advancing technical solutions for soft or liquid temporal adhesives and gripping devices. Full article

This article examines the pressing issue of verifying contact models in the discrete element method (DEM) for modeling soil tillage processes. Due to the lack of a generally accepted methodology for selecting contact models for various soil types, a comprehensive study was conducted combining field experiments and numerical modeling. A verification method was developed and tested based on comparing experimental data on the draft resistance of a plow body with the results of calculations in the Rocky DEM 4.4 software package. The study yielded reliable experimental values for the draft resistance components and established the ranges of variation for their parameters. A comparative analysis of 10 promising combinations of contact models identified in previous studies was conducted. It was found that the improved Hertz-Mindlin model with the JKR adhesion model provides the best fit to the experimental results. Particular attention is paid to analyzing the influence of surface energy in the JKR model on changes in the rheological properties of the soil medium, which opens up the possibility of predicting soil behavior at different moisture levels. The results of the work are of practical value for the design and optimization of agricultural implements at the stage of their numerical modeling. The accuracy of predicting the draft resistance of the plow body during modeling for the studied soils at a moisture content of 18–25% ranged from 80 to 95%. Full article

A critical challenge in the design optimization of subsoiling and deep-fertilization implements for root pruning during the regreening stage of winter wheat lies in the lack of a validated root–soil discrete element (DEM) model. This study analyzed and measured the geometric morphology of winter wheat root systems in soil during the regreening stage and constructed corresponding geometric models. Based on the DEM framework, a Hertz–Mindlin with bonding model (HMBM) for the wheat root system was developed. The parameters of this model were calibrated using Plackett–Burman (PB) and Box–Behnken design (BBD) methods. Soil particles were simplified to spherical shapes according to particle size distribution analysis, and a discrete element model of soil particles using the Johnson–Kendall–Roberts (JKR) contact model was established. Soil model parameters at three different moisture contents were calibrated with the angle of repose (AOR) as the target response. The accuracy of the root bonding model and parameters, as well as the root–soil contact model and parameters, was verified through pull-out tests and corresponding DEM simulations of single roots in soil. Comparison between experimental and simulated pull-out results confirmed the validity of the developed root–soil DEM model for winter wheat during the regreening stage. This study provides a solid theoretical and experimental basis for future research on root cutting and tillage operations in winter wheat. Full article

Accurate determination of soil and contact parameters is crucial for tillage machinery design; however, the interactions among soil, tools, and roots in citrus orchards covered with green manure remain insufficiently defined. This study, therefore, combined physical experiments with DEM simulations to characterize these interactions. Using significance analysis and response surface methodology (RSM), the effects of major factors on angle of repose (AoR) and initial slip angle (ISA) at varying soil depths were evaluated, enabling precise calibration of both external (soil–machinery) and internal (particle–particle) parameters. Subsequently, a GA-BP optimization model was constructed to enhance calibration accuracy, yielding optimal values for the soil-to-soil rolling friction coefficient (γ = 0.125–0.136), soil-to-65Mn static friction coefficient (μ′ = 0.431 − 0.540), and soil surface energy (JKR = 0.952 − 1.091 J·m⁻²). Shear tests using the bonding V2 model were conducted to calibrate the Bonding parameters of green manure stems and roots, while pull-out tests and simulations were used to validate the root–soil parameters. Direct shear tests confirmed the model’s reliability, with errors in internal friction angle and cohesion below 10%. These findings may contribute to improving DEM simulation accuracy for soil improvement under green manure coverage and support the optimization of soil tillage in citrus orchards. Full article

The loading rate of coal is significantly influenced by the number of vanes on shearer drums. However, in actual production, 1400 mm diameter drums feature two-vane and three-vane designs, while 2240 mm diameter ones have three-vane and four-vane designs, with the vane number corresponding to the optimal coal-loading rate remaining unclear. To reveal the correlation between vane number and coal-loading rate for such drums, parameters were calibrated through multiple physical tests in this study. Supported by field data, simulation analyses were conducted via the discrete element method to investigate the effect of the vane number on the drum coal-loading rate under different moisture contents and traction speeds. The results indicated that particle adhesion initially increases and then decreases with the moisture content, with the peak characteristics influenced by the particle size. Particle movement during drum coal mining is jointly governed by multiple factors. For 1400 mm drums, two or three vanes should be selected depending on moisture fluctuations and coal transportation requirements, whereas for 2240 mm drums, three or four vanes are recommended based on the balance between coal-cutting volume, conveying capacity, and traction speed. Full article

In support of sustainable agricultural practices and soil conservation in black soil regions, the accurate modeling of soil–machine interactions is essential for optimizing tillage operations and minimizing environmental impacts. To achieve the precise calibration of interaction parameters between black soil and soil-engaging components, this paper proposes an innovative segmented calibration method to determine the discrete element parameters for interactions between black soil and agricultural machinery parts. The Hertz–Mindlin with Johnson–Kendall–Roberts (JKR) Cohesion contact model in the discrete element method (DEM) software was employed, using a two-stage calibration process. In the first stage, soil particle contact parameters were optimized by combining physical pile angle tests with multi-factor simulations guided by Design-Expert, resulting in the optimal parameter set (JKR surface energy 0.46 J/m², restitution coefficient 0.51, static friction coefficient 0.65, rolling friction coefficient 0.13). In the second stage, based on validated soil parameters, the soil–65Mn steel interaction parameters were precisely calibrated (JKR surface energy 0.29 J/m², restitution coefficient 0.55, static friction coefficient 0.64, rolling friction coefficient 0.07). Simulation results showed that the error between simulated and measured pile angles was less than 0.5%. Additionally, verification through rotary tillage operation tests comparing simulated and measured power consumption demonstrated that within the cutter roller speed range of 150–350 r·min⁻¹, the power error remained below 0.5 kW. Ground surface flatness was introduced as a supplementary validation indicator, and the differences between simulated and measured values were small, further confirming the accuracy of the DEM model in capturing soil–tool interaction and predicting tillage quality. This paper not only enhances the accuracy of DEM-based modeling in agricultural engineering but also contributes to the development of eco-efficient tillage tools, promoting sustainable land management and soil resource protection. Full article

To address the insufficient adaptability of imported peanut harvesting equipment’s soil-engaging components to the specific soil conditions in Xinjiang, this study conducted Discrete Element Method (DEM)-based calibration of soil mechanical parameters using field soil samples with 1–20% moisture content from typical peanut cultivation areas in southern Xinjiang. Through the EDEM simulation platform, a comprehensive approach integrating the Hertz–Mindlin with the JKR adhesion model and Hertz–Mindlin with the Bonding model was employed to systematically calibrate nine key parameters: coefficient of restitution, static friction coefficient, rolling friction coefficient, JKR surface energy, normal/tangential stiffness per unit area, critical normal/tangential force, and soil bonding disk radius. Adopting static angle of repose (SAOR) and unconfined compressive force (UCF) as dual-response indicators, a hybrid experimental design strategy combining Central Composite Design (CCD), Plackett–Burman (PB) screening, and Box–Behnken Design (BBD) optimization was implemented. Regression models for SAOR and UCS were established, yielding six sets of soil parameters optimized for different moisture conditions through parameter optimization. Field validation demonstrated the following: ≤3.27% error in SAOR, ≤1.46% error in UCF, and ≤5.05% error in drawbar resistance validation for field digging shanks. Experimental results confirm that the model demonstrates strong prediction accuracy for soils in typical peanut harvesting regions of southern Xinjiang, thereby providing key parameter references for the future self-developed, highly adaptive soil-engaging components with drag reduction optimization in peanut harvesters for the Xinjiang region. Full article

The discrete element computer simulation method is an effective tool that enables the study of the interaction mechanism between the fertilizer discharge device. However, the lack of accurate fertilizer models for hygroscopic fertilizer particles (HFP) has limited the application and development of the discrete element method in research precision fertilizer discharge device. Taking HFP as the research object, this research aims to establish the discrete element model of different moisture hygroscopic fertilizer particles, and to develop a method for predicting the discrete element parameters of HFP based on moisture content. The Hertz–Mindlin with JKR discrete element model was selected as the contact model for the HFP. The repose angle of HFP was used as the test index to select nine discrete element models for the HFP. Firstly, a mathematical model characterizing the relationship between fertilizer moisture content and the repose angle was established. Subsequently, the Plackett–Burman test identified the surface energy of hygroscopic fertilizer particles (HFP), the restitution coefficient between fertilizer and PC board, and the shear modulus as significant factors influencing the test index. The value range of the above parameters were determined by the steepest ascent test results. The Box–Behnken test obtained the regression model between the significant factors and the test index. The optimal combination of parameters of 2%, 4%, and 6% moisture contents of HFP were predicted based on the regression model and the HFP repose angle. The parameters were optimized using the repose angle error as the target. In order to further verify the accuracy of the HFP discrete element model, a fertilizer discharging simulation test was conducted. The results show that, compared with the actual fertilizer discharge amount, the simulation fertilizer discharge amount error of different moisture HFP was below 8.32%. The collective results indicated this method could reliably and precisely establish the discrete element model of various moisture content HFP. This model can be applied to the analysis of hygroscopic fertilizer discharging processes and the design of precision fertilizer discharge technology devices. Full article

The discrete element method (DEM), based on particle dynamics, is used to simulate the technological process of soil tillage using agricultural machinery. A key aspect of the DEM for obtaining accurate agrotechnical and energy indicators of soil cultivation is the formulation of particle contact rules, determined by normal and tangential interactions as well as cohesion forces. This study presents a comprehensive analysis of discrete element method (DEM) contact models used to simulate soil cultivation processes. This study addresses a key issue—the absence of a systematic approach to selecting adequate contact models, which limits the accuracy of predicting soil behavior during interaction with agricultural machinery. A detailed classification of 17 combinations of contact models implemented in the commercial software Rocky DEM was performed, grouped into three categories: normal force models (Linear Spring [LSP], Hysteresis [HLS], Hertzian [HSD]), tangential force models (Coulomb, linear spring limit [linear], Mindlin–Deresiewicz), and cohesive force models (linear cohesion [linear], constant force [constant], Johnson–Kendall–Roberts [JKR]). Experimental validation was conducted by analyzing the angle of repose for various soil types (sandy loam, light loam, medium loam, and heavy clay) with moisture contents ranging from 11 to 31%. This analysis identified the nine most effective combinations of contact models to describe normal, tangential, and cohesive forces (LSP–Coulomb–linear, HLS–linear–linear, HLS–Coulomb–linear, HSD–linear–linear, HSD–linear–JKR, HSD–Coulomb–linear, HSD–Coulomb–JKR, HSD–Mindlin–Deresiewicz–linear, HSD–Mindlin–Deresiewicz–JKR), which showed reliable agreement with experimental angle of repose measurements at approximately 85% accuracy. This study significantly contributes to advancing computer modeling methods in agriculture by providing a scientifically grounded approach for selecting DEM contact models. Full article