Search Results (974)

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

The nominal maximum aggregate size (NMAS) plays a critical role in determining the mechanical performance of cement-stabilized macadam (CSM), yet its meso-mechanical influence mechanism remains insufficiently understood. In this study, three skeleton-dense CSM mixtures with different NMAS values were designed, and a combined experimental–numerical approach was adopted to investigate the macro- and meso-scale mechanical behavior. Uniaxial compression tests and aggregate crushing value tests were conducted to evaluate strength development and load-transfer characteristics, while a three-dimensional discrete element method (DEM) model incorporating realistic aggregate morphology was established to analyze the evolution of contact forces and crack propagation. The results show that increasing NMAS significantly improves the mechanical performance of CSM. Compared with CSM-30, the 7-day compressive strength of CSM-40 and CSM-50 increased by approximately 10.3% and 37.3%, respectively. The stress–strain response indicates that mixtures with larger NMAS exhibit higher stiffness and a higher strain. At the meso-scale, a larger NMAS promotes the formation of a more efficient force-chain network dominated by coarse aggregates. Strong contacts were predominantly carried by aggregates larger than 9.5 mm, and in CSM-50, the proportion of strong contacts in the 37.5–53 mm fraction exceeded 90%, indicating that the largest particles likely form the primary load-bearing skeleton. In addition, increasing NMAS delayed crack initiation, reduced crack propagation rate, and decreased the total number of cracks at failure. These findings demonstrate that macroscopic strength improvement is closely associated with meso-scale optimization of the aggregate skeleton and enhanced load-transfer efficiency. This study provides a mechanistic basis for NMAS selection and gradation optimization in semi-rigid base materials. Full article

Fibers in vortex turbulence fields involve complex gas–solid coupling effects, significantly influencing the spinning process within vortex nozzles. This paper utilizes the Discrete Element Method (DEM) to refine the existing rigid bead–elastic rod model describing fiber constitutive behavior. This improved model is used to numerically simulate the dynamic behavior of a single flexible fiber within the vortex field of the nozzle. Based on elastic mechanics, this study establishes mapping functions converting relative displacement and angular displacement between beads into internal forces and torques within the beads. A contact model is also developed to handle fiber–wall interactions. The effects of different nozzle structures on fiber motion are investigated. The improved model successfully simulates the entire motion process of a single fiber during spinning. Its reliability is validated by comparing with experimentally collected fiber motion data. The study reveals that a twist chamber diameter of 6 mm, a conical cavity angle of 55 degrees, and a distance of 1.05 mm between the jet orifice and the hollow spindle yield optimal fiber twist count and wrapping density. This research provides effective insights for developing textile equipment that relies on airflow to drive fiber spinning and contributes to establishing a comprehensive twisting mechanism. Full article

Sugarcane is an important economic crop in southern China. Affected by typhoons, it is prone to lodging, which not only increases the difficulty and loss rate of mechanical harvesting but also reduces the sugar content. The mechanical properties of the sugarcane root–soil system are crucial to its lodging resistance. However, accurate discrete element parameters are still lacking for DEM-based research on the mechanical properties of this system. Therefore, this study adopts a method combining the angle of repose test, shear force test, and discrete element simulation of single roots to calibrate DEM parameters. Using the angle of repose and maximum shear force of a single root as response values, Plackett–Burman, steepest ascent, and Box–Behnken tests are sequentially carried out with Design-Expert 13 software to calibrate the contact and bonding parameters of individual sugarcane roots. The relative errors between the physical and simulation test results for the angle of repose and shear force are 1.29% and 0.66%, respectively. This study provides a reference for the establishment of discrete element simulation models for sugarcane roots and for the subsequent development of sugarcane root–soil composite models. Full article

High-pressure grinding rolls (HPGRs) are critical in mineral processing, making comprehensive research and analysis of their performance of great significance. This study focuses on the HPGR-3516 test prototype and develops an analytical model that combines the discrete element method (DEM) with multi-body dynamics (MBD). The influences of feed top size, roll speed, and specific press force on equipment performance were examined using analysis of variance (ANOVA) in conjunction with response surface methodology (RSM). A performance prediction model was established through regression analysis, followed by multi-objective optimization and experimental validation. The results indicate that increasing roll speed under high specific press force significantly reduces the roll gap, while the effect is negligible under low specific press force. Increasing roll speed improves throughput more substantially for fine feed than for coarse feed. The optimal process parameters were determined to be a feed top size of 8 mm, a roll speed of 0.37 m/s, and a specific press force of $4.84 \mathrm{N}/{\mathrm{m}\mathrm{m}}^2$. In comparison to the original parameters, throughput increased by 15.81%, qualified particle size passing rate (QPR) improved by 7.85%, and roll gap decreased by 10.24%. This study offers valuable insights into predicting the dynamic performance of HPGRs and has significant engineering implications. Full article

To address the issues of high working power consumption and poor structural stability of current ploughing equipment under conditions of straw coverage and heavy clay soil, a 1LFT-450D variable width reversible plough (VWRP) with resistance reduction function is designed. Based on the shark shield scale, a bionic resistance reduction plough body was designed. Through theoretical analysis, the turnover mechanism (TM) and the working width adjustment mechanism (WWAM) were designed, and their main structural parameters were determined. Further research was conducted on key components using simulation software. The discrete element method (DEM) simulation results indicated that arranging bionic ribs on the plough breast achieved the best resistance reduction effect compared with the ploughshare tip and ploughshare. Meanwhile, relative to the conventional plough body, the designed bionic plough body exhibited average reductions in resistance and energy consumption of 12.55% and 12.34%, respectively. The soil bin test further verified the resistance reduction performance of the designed bionic plough body. The kinematic performance of the TM and the WWAM was analyzed using RecurDyn, and their reliability and stability were verified through the mechanism performance test. The results of the field operation performance test showed that under the conditions of forward speed of 8–10 km·h⁻¹ and working width of 1320–2000 mm, the operation performance of the designed VWRP satisfied the requirements of relevant standards. This study can provide a theoretical reference for the resistance reduction optimization of agricultural machinery soil-engaging parts and the design of new ploughs. Full article

Uneven seed spacing, skewed stalk posture, and inconsistent planting depth remain major challenges in horizontal sugarcane planting. To address these issues, a semi-automatic transverse sugarcane planter integrating a supply–buffer–discharge seeder and multiple soil-engaging components was developed. The seed placement process and the interaction between stalk discharge and soil disturbance were investigated through Discrete Element Method (DEM) simulations and experiments. First, the working principle and key component parameters of the whole machine were determined. It integrated the processes of soil crushing, furrowing, seeding, ridge covering. In addition, a dynamic analysis was conducted on the inter-particle disengagement effect during the two-step seed filling process of lifting and discharging. Secondly, a discrete element simulation model for the entire process of soil-engaging seed arrangement operations was established for the machine. The effects of forward speed and seed outlet position were studied using a discrete element method (DEM) simulation model that coupled soil disturbance flow with stalk-seed discharge behaviour. Furthermore, a response surface methodology (RSM) experiment was performed on the seeding test bench to quantify the effects of guiding parameters on seed placement uniformity. The determination coefficient (R²) of the established regression model exceeded 0.9, indicating high prediction accuracy. The optimal collaborative parameter combination was optimized as follows: forward speed of 1.2 m·s⁻¹, buffer inclination angle of 55°and supply roller speed of 26 r·min⁻¹. After verification, the seed placement uniformity coefficient of the seeder reached 91.8 ± 1.4%, which met the expected accuracy requirements for horizontal planting. Full article

The dynamic modulus of asphalt mixtures is a key design parameter in pavement design, which significantly impacts the mechanical properties of asphalt pavements. This study simulated dynamic modulus tests of asphalt mixtures using the three-dimensional (3D) discrete element method (DEM) to investigate mechanical behaviors such as the loading-bearing ratio of individual aggregates. Fine-grained AC-13 and medium-grained AC-20 asphalt mixture models were randomly constructed in the DEM program using user-defined methods. The dynamic modulus and phase angle values of the asphalt mixtures were predicted. By comparing laboratory experiments with DEM simulation results, the model was validated, and the effects of temperature and loading frequency on the dynamic modulus were explored. Further exploration was conducted on the loading-bearing ratio and mechanical interactions among aggregates of different sizes within the mixtures. The results show that the 3D DEM model can accurately predict the dynamic modulus and phase angle of asphalt mixtures. Temperature and frequency have an impact on these parameters, and the increase in gradation has an impact on the loading-bearing ratio, due to the proportion of coarse aggregates. Full article

The performance of ballasted railway tracks under cyclic loading is a critical issue in urban railway systems, where high traffic frequency and geometric constraints accelerate track degradation, leading to the accumulation of plastic deformations that may reduce operational efficiency. This study presents a numerical framework for rail track performance assessment based on two complementary modeling approaches: a fully continuous Finite Difference Method (FDM) model, and a hybrid Discrete Element Method–Finite Difference Method (DEM–FDM) model. The continuous FDM simulations are employed to evaluate the global mechanical response of the track support system and to compute conventional stability indicators, including the factor of safety (FS). In parallel, the hybrid DEM–FDM simulations explicitly represent the ballast layer using DEM to capture inter-particle interactions, accumulation of permanent deformation, and particle fragmentation under cyclic loading, while rails, sleepers, sub-ballast, and subgrade are modeled using FDM to describe system-level load transfer. Ballast performance is assessed by linking safety factors obtained from the continuous models with mechanically derived permanent deformation and stress measures extracted from the hybrid simulations. The proposed dual-modeling framework enables a systematic investigation of the influence of ballast layer thickness and material type on deformation accumulation, stress transmission, and granular degradation mechanisms. The results reveal distinct behavioral trends among different ballast materials, showing that increased ballast thickness generally improves track performance, while material-specific degradation mechanisms govern the evolution of permanent deformation under repeated loading. The proposed approach establishes a quantitative bridge between traditional stability-based design metrics and deformation-based performance indicators, providing a rational basis for performance-based evaluation, comparison, and optimization of ballast configurations through a set of robust numerically derived relationships for railway track design. Full article

Granular deposition and grading strongly influence pore-space topology and hence hydraulic conductivity in natural and engineered porous media, yet quantitative links between deposition sequence, particle-scale morphology, pore-network descriptors, and permeability anisotropy remain incomplete. Here, we develop a process-based digital porous-media framework that couples discrete element method (DEM) deposition with pore-network characterization and Darcy-scale permeability evaluation. Two deposition sequences—normal grading (coarse-to-fine) and reverse grading (fine-to-coarse)—are simulated using bi-disperse particle sets with controlled size ratios. To further isolate the role of particle morphology, particle irregularity is parameterized by a Perlin-noise-based shape perturbation factor and incorporated into the DEM-generated packings. For each packing, pore networks are extracted and quantified in terms of pore/throat size distributions and connectivity, while pore-space complexity is measured via box-counting fractal dimension. Single-phase flow is solved under imposed pressure gradient, and intrinsic permeability is computed along three orthogonal directions to evaluate anisotropy. Results show that increasing size contrast reduces porosity, shifts pore and throat distributions toward smaller characteristic radii, increases pore-space fractal dimension, and yields a monotonic permeability reduction. For identical size ratios, reverse grading consistently yields higher permeability than normal grading, suggesting that deposition sequence exerts a strong control on the continuity and efficiency of effective flow pathways at the sample scale. Increasing particle irregularity decreases permeability and systematically modifies permeability anisotropy, transitioning from weak horizontal anisotropy toward near-isotropy and, at strong irregularity, toward preferential vertical permeability. The proposed framework provides a reproducible route to relate depositional history and particle morphology to pore-network structure and directional permeability, offering implications for filtration, packed-bed design, and sedimentary reservoir characterization. Full article

Airborne electromagnetic (AEM) surveys map subsurface electrical structures by deploying transmitter and receiver coils on an airborne platform. However, platform-induced vibrations are transmitted to the sensors, generating strong motion-induced noise that severely degrades signal quality. To mitigate such noise, this study proposed the use of granular materials as a cushioning medium. An impact model based on the Discrete Element Method (DEM) was developed and validated against drop-weight experiments. Both granular material properties and impactor characteristics were investigated. The study examined the cushioning effects on both the base plate and the impactor under impact loading, and the sensitivity of key parameters was evaluated. The results showed that granular properties had minimal influence on the impactor peak force. Increasing particle Young’s modulus, density, or friction coefficient led to higher peak forces on the base plate, with Young’s modulus and density having significantly stronger effects than friction coefficient. Additionally, both the impactor size and velocity correlate positively with the peak forces transmitted to the base plate and experienced by the impactor. Under thin layer conditions, the impactor force was more sensitive to impact parameters, while in thick layers it was mainly determined by particle rearrangement and energy dissipation mechanisms. These findings reveal the mechanisms governing granular cushioning and provide a theoretical basis for vibration isolation design in AEM systems to preserve high-fidelity signals. Full article

With the expansion of electric vehicle (EV) applications into unstructured sandy terrains such as deserts, accurately characterizing tire–sand dynamic interactions is essential for enhancing off-road performance. However, traditional terramechanics models, the discrete element method (DEM), and purely data-driven neural networks all have inherent limitations, failing to balance physical interpretability and computational efficiency. This study proposes a wheel–sand dynamics prediction model that integrates DEM simulation, semi-physical modeling, and deep learning. A DEM tire–sand contact platform is built to acquire longitudinal slip and cornering properties, and a dimensionless semi-physical tire model is derived using frictional constitutive relations and tire theory. A 3-DOF vehicle dynamics model is then established to generate high-fidelity physics-based datasets, and a residual neural network is adopted to avoid performance degradation in deep networks. The model is validated and optimized via real-vehicle sandy terrain tests, with its performance compared against other network structures. The proposed model achieves high prediction accuracy, with engineering-acceptable errors, and outperforms conventional neural networks. The dimensionless framework improves generality, overcoming the weaknesses of traditional and purely data-driven models. This work provides theoretical and statistical support for EV traction control design and tire structure optimization, promoting driving stability and terrain passability in unstructured sandy environments. Full article

During the transportation and storage of liquefied natural gas (LNG), sloshing in partially filled cargo tanks poses significant risks to structural integrity and operational safety. Conventional anti-sloshing devices, such as internal baffles, are incompatible with membrane-type tanks due to strict requirements on internal geometry and material integrity. To address this challenge, this study proposes an eccentric foam floater (EFF), which enhances energy dissipation through controlled mass asymmetry without modifying the tank’s internal configuration. Building upon the buoyant-ball concept, the EFF introduces an offset between geometric center and center of mass, thereby promoting additional rotational motion, inter-floater and floater–wall friction, and fluid–structure interaction effects. Model experimental investigations using a six-degree-of-freedom motion platform, combined with discrete element method (DEM) simulations, demonstrate that the EFF consistently outperforms its homogeneous counterpart in suppressing sloshing-induced pressure fluctuations across a broad range of excitation conditions. The results highlight the potential of mass eccentricity as a design principle for passive, structure-preserving sloshing mitigation in membrane LNG tanks. Full article

Porous medium combustion technology, renowned for high efficiency and low emissions, is widely applied in industrial and heating fields. This study numerically investigates pore-scale heat transfer, flame morphology, reaction rate distribution during standing combustion in a one-layer randomly packed bed, and flow parameter effects on flame behavior. A 3D randomly packed model (tube-to-particle diameter ratio D/d = 10) is developed using the discrete element method (DEM) and coupled with computational fluid dynamics (CFD) to resolve pore-scale transport processes. Results show that exothermic combustion converts internal energy to kinetic energy, significantly accelerating pore-scale flow velocity in the combustion zone. Increasing the equivalence ratio enhances flame stability, elevating solid–fluid temperatures by 200 K and expanding the combustion zone volume by 20%. The pore Reynolds number promotes inertial mixing and heat redistribution, limiting the solid–fluid temperature difference to 10 K. Local flames evolve from dispersed to wrinkled and undulating. These findings elucidate pore-scale combustion dynamics and guide packed-bed reactor design and optimization. Full article

This work investigated the influence of thickness-direction boundary conditions on the flow characteristics of granular material in a quasi-two-dimensional silo using the discrete element method (DEM). Two types of boundary conditions were considered in the thickness direction: wall conditions and periodic boundary conditions. The simulation results indicate that under wall conditions, velocity waves propagate upward, manifested by the formation of bubble-like sub-flow zones in the velocity field, and the particle motion in the upper bed region exhibits a clear stick–slip feature. In contrast, under periodic boundary conditions, particle motion displays a resonant mode. Further statistical analysis reveals that, despite the distinct macroscopic motion mode under the two boundary conditions, the probability distributions of particle vertical fluctuating velocities share similar characteristics: both exhibit fat-tailed and asymmetric features and deviate from Gaussian distribution. Additionally, under wall conditions, the horizontal distributions of particle vertical velocity conform to the kinematic model throughout the bed, whereas under periodic boundary conditions, the horizontal distributions in the upper bed region display plug flow characteristics. In summary, the results of this work demonstrate that thickness-direction boundary conditions play a crucial role in determining the flow characteristics of granular assembly in silos. Full article