Computational Particle Mechanics最新文献

To determine the desirable bonding parameters of the soybean-bonded particle model for accidentally simulating the working process of a pneumatic soybean seed-metering device. Taking the compressive destructive force (F_c,p) derived from the uniaxial compression test of soybean seeds as the evaluation index for the compression simulation tests. The Plackett–Burman and the steepest ascent tests were executed to identify the centroids of the influential factors that substantially affect the bonding force of the soybean-bonded particle model. The optimal values of the significance influencing variables were determined based on the Box–Behnken response surface test. The results indicated that the effect of bonded disk radius (R_B,p) between fraction particles on the F_c,p was extremely significant, and the effects of the restitution coefficient (e_p-steel) and static friction coefficient (μ_p-steel) of soybean-steel, normal stiffness per unit area (k_n,p) and critical normal stress (σ_max,p) were found to be statistically significant. The preferred values identified by Box–Behnken response surface test were 0.520 for e_p-steel, 0.274 for μ_p-steel, 4.082 × 10⁷ N/m³ for k_n,p, 3.517 × 10⁵ Pa for σ_max,p, and 0.982 mm for R_B,p, respectively. The compressive destructive force of soybean seeds was 211.32 N at this point, which was 0.2% less than the measured value of 211.74 N. The results of comparing the grain morphologies during the actual and simulated compressions indicated that the compression states had a superior consistency. It was determined that the DEM simulation input parameters for the soybean-bonded particle model calibrated were proven to be effective and dependable. The investigation presented in this paper can be utilized to effectively analyze the working process of the pneumatic soybean seed-metering devices through coupled simulation. It can also serve as a reference for other researchers to construct a particle model for DEM simulation using the BPM approach.

Existing literature on true triaxial and torsional shear tests indicate that the mechanical response of a granular assembly is significantly influenced by the magnitude of the intermediate principal stress ratio. The present study aims to explore the mechanism behind such effects in reference to the particle-level interaction using 3D DEM simulations. In this regard, true triaxial numerical simulations have been carried out with constant minor principal stress and varying (b) values employing rolling resistance-type contact model to mimic particle shape. The numerical simulations have been validated against the true triaxial experiments reported in the literature for dense Santa Monica beach sand. The macro-level shearing response of the granular assembly has been examined in terms of the evolution of stress ratio and volumetric strain for different rolling resistance coefficients. Further, such macro-level response has been assessed in reference to the micro-scale attributes, e.g. average contact force, number of interparticle contacts, mechanical coordination number, contact normal orientation, and fabric tensor as well as meso-scale attribute like strong contact force network. Lade’s failure surface has been adopted to represent the stress and fabric at peak state in the octahedral plane, and mathematical expressions have been proposed relating the failure surface parameters to the rolling resistance coefficient.

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Discrete element method (DEM) is a powerful tool for the dynamic simulation of irregular non-spherical particle systems. The efficient integration of the rotational motions of numerous particles in DEM poses a big challenge. This paper presents six explicit time integration algorithms, comprising three first-order algorithms and three second-order algorithms, for the rotational motions of non-spherical particles based on the theory of unit quaternion group S(3). The proposed algorithms based on Cayley map do not contain any transcendental function and have high efficiency. The numerical examples underscore the superiority of the first-order symplectic Euler Cayley algorithm (SECay) and the second-order central difference Cayley algorithm (CDCay) in terms of both efficiency and accuracy. In the testing cases of granular systems, SECay and CDCay demonstrate approximately 80% reduction in computational time for the time integration part, compared to the improved predictor–corrector direct multiplication method (IPCDM). Therefore, SECay and CDCay emerge as promising tools for non-spherical DEM simulations.

Motivated by the spatial variability observed in geological profiles, this study explored the feasibility of using discrete element method (DEM) to capture the effect of layered spatial variability into overall soil performance. The spatial variability of packing densities, particle Young’s modulus (E), and frictional properties (μ) within specimens was studied. It was observed that samples with similar overall void ratios exhibited comparable small-strain stiffness and shearing behaviors. In contrast, the coordination number and particle stress transmission demonstrated significant sensitivity to the layer-wise spatial variability in packing densities. Regarding the spatial variability effect of particle-scale E values, this study illustrates that spatial variability strongly affects the stiffness contributions of individual layers. Specifically, layers with higher E values are capable of transferring much stress and stiffness. For the spatial variability effect of frictional property, a degree of consistency in shearing behaviors was observed among specimens with similar average frictional characteristics, while layers with lower frictional property were identified as potential initial failure junctures. Overall, this study validates the utility of employing a DEM code for analyzing both the macroscopic behavior and localized vulnerabilities within complex granular systems, presenting profound implications for engineering practices.

The discrete element method (DEM) is suitable to investigate problems where large deformations occur especially in granular material. The fitting of reliable DEM parameters is crucial and a challenge which is caused by the high number of DEM parameters and the computational effort. Despite its drawbacks, a trial and error approach is often used for the DEM parameter calibration. The knowledge of the DEM parameter influence on the model response is necessary to improve the calibration and to check whether the experiment is suitable to calibrate specific parameters or not. It is possible to reduce the dimensionality of the optimisation problem by omitting parameters whose influence on the model response is negligibly small. One approach is to perform a global sensitivity analysis based on Sobol’ indices. A frequently used calibration experiment in literature is the pile experiment. The deviation between the experiment and the simulation is evaluated with the angle of repose. In the present paper, an algorithm to determine the angle of repose considering the three-dimensional shape of the heap is discussed. The global sensitivity analysis is performed for two different experimental heap set-ups. To decrease the computational effort of the sensitivity analysis, the model response is approximated with metamodels whose predictability is evaluated using the root mean squared error (RMSE) based on a separate sampling point set.

Railway operation in desert areas faces unique challenges due to wind-blown sand penetration on the safety of the line. In-depth research on the impact of wind-blown sand penetration on the shear performance of the railway ballast is crucial for understanding potential problems in sandy railways and formulating effective maintenance strategies. This paper conducts a series of direct shear tests under various sand contents and load conditions using an independently developed automatic control loading direct shear test apparatus suitable for railway ballast. By accurately considering the interaction between sand and ballast particles, some direct shear numerical models of different sand-containing ballast boxes based on refined particle simulation are established based on the discrete element method (DEM) and particle scaling method, exploring the variation in shear strength, shear deformation, contact relationships, and rotational characteristics of railway sand-containing ballast from macroscopic and microscopic perspectives. The results show that with the increase in shear strain, the shear stress of the ballast with various sand contents increases first and then tends to stabilize, and the phenomenon of dilation occurs in all cases. When the normal load is constant, the shear strength and cohesion of the ballast show a trend of first decreasing and then increasing with the increase in sand content. The wind-blown sand penetration inhibits the rotational deformation during shearing, enhancing particle aggregation. With the increase in sand content, the contact coordination number, powerful force chain number, and total force chain number all increase continuously. However, the average contact force shows a trend of gradually decreasing and then increasing. This study provides theoretical support and experimental backing for the operation and maintenance of the ballast bed in sandy railways.