Granular Matter最新文献

This study presents a discrete element numerical model for the unidirectional compaction of microfine magnesite powder, designed to enhance the green body density based on laboratory apparatus configurations. The research demonstrated that as particle size decreased, porosity significantly reduced and density increased, resulting in a more uniform internal distribution within the green body. This led to closer particle contacts and an increased coordination number, which in turn intensified inter-particle interactions and the effectiveness of force transmission. During compaction, the distribution of force chains became more uniform, reducing localized stress concentrations and enhancing the mechanical integrity of the green body. The stress–strain relationship followed a polynomial pattern, highlighting the significant influence of particle size on the mechanical behavior during compaction. These findings provide a valuable theoretical basis for optimizing the compression molding process of microfine magnesite powder, facilitating the production of high-density, high-performance molded products.

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Accurate simulation of laboratory undrained and cyclic triaxial tests on granular materials using the Discrete Element Method (DEM) is a crucial concern. The evolution of shear bands and non-uniform stress distribution, affected by the membrane boundary condition, can significantly impact the mechanical behavior of samples. In this work, the flexible membrane is simulated by using the Finite Element Method coupled with DEM. In addition, we introduce a hydro-mechanical coupling scheme with a compressible fluid to reproduce the different undrained laboratory tests by using the membrane boundary. The evolution of pore pressure is computed incrementally based on the variation of volumetric strain inside the sample. The results of the membrane boundary condition are compared with more classical DEM simulations such as rigid wall and periodic boundaries. The comparison at different scales reveals many differences, such as the initial anisotropic value for a given preparation procedure, fabric evolution, volumetric strain and the formation of shear bands. Notably, the flexible boundary exhibits more benefits and better aligns with experimental data. As for the undrained condition, the results of the membrane condition are compared with experimental data of Toyoura sand and rigid wall boundary with constant volume. Finally, stress heterogeneity during undrained monotonic and cyclic conditions using the membrane boundary is highlighted.

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The deformation of expansive soil in seasonally frozen regions caused by freeze–thaw cycles has severely affected the long-term performance of engineering applications. The alteration of expansive soil microstructure has resulted in many geotechnical engineering failures, such as soil cracking and settlement. Consequently, the micropore contraction and expansion mechanisms of expansive soil have drawn extensive attention. Nuclear Magnetic Resonance (NMR) is widely used as a rapid, non-destructive detection technique for moisture monitoring and microstructure evolution characterization in porous media. In addition, Magnetic Resonance Imaging (MRI) can visualize the migration pattern of pore water under different numbers of freeze–thaw cycles. SEM is the most effective and direct method to reveal the structure of particle and micropore arrangement. This paper investigates the pore size evolution and pore structure distribution characteristics of saturated expansive soil via 6 freeze–thaw cycle tests using NMR and SEM techniques. The evolution law of saturated expansive soil under freeze–thaw cycles is obtained. The results show that pore water migrates from the center to the periphery under freeze–thaw cycles. The pore size decreases as the number of freeze–thaw cycles increases and small particles increase significantly. During the freeze–thaw cycle, the arrangement pattern changed from surface-surface contact to stacking.

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Aggregates consisting of submicron-sized cohesive dust grains are ubiquitous, and understanding the collisional behavior of dust aggregates is essential. It is known that low-speed collisions of dust aggregates result in either sticking or bouncing, and local and permanent compaction occurs near the contact area upon collision. In this study, we perform numerical simulations of collisions between two aggregates and investigate their compressive behavior. We find that the maximum compression length is proportional to the radius of aggregates and increases with the collision velocity. We also reveal that a theoretical model of contact between two elastoplastic spheres successfully reproduces the size- and velocity-dependence of the maximum compression length observed in our numerical simulations. Our findings on the plastic deformation of aggregates during collisional compression provide a clue to understanding the collisional growth process of aggregates.

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To enhance our understanding of soil behavior at critical states, considering that natural soil is composed of granular matter, a quasi-static inertia number taking soil compaction into account is proposed. In analyzing classical triaxial test data of soil, the scaling law of quasi-statically deforming grains at the critical state is explored; a simple linear relationship is found between the coefficient of friction and the proposed number. This scaling law describes quantitatively the influence of initial compaction, shear rate, confining pressure, and particle size on the frictional strength of granular soils when they reach the critical state. The number proposed is employed to describe the scaling of volumetric behavior of granular soils undergoing quasi-static deformation. The difference between the particle volume fraction at the critical state and that at the initial compacted state is also found to be linearly correlated with the quasi-static inertia number, for soil at the critical state.

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The generation of artificial granular media to investigate micro-to-macro correlations in sands is one of the innovations inspired by the recent advancements in 3D printing technology. While several 3D printing techniques exist to print granular particles, the basis for the selection of a specific technique and the relative accuracy in mimicking the morphological features are yet to be investigated. This paper investigates the accuracy of the reproduction of granular morphology by three widely used 3D printing techniques. Polyjet, Digital Light Processing (DLP), and Stereolithography (SLA) printing techniques are used to generate the analogues of reference sand particles of size range 1.76–6.39 mm. Subsequently, the 3D morphological indices of the printed grains are computed using X-ray micro-computed tomography (µCT) imaging followed by spherical harmonic (SH) particle reconstruction and computational analysis. These indices are compared with those of the reference particles, and the errors in the computed morphological parameters are obtained for the three different 3D printing techniques. The errors are found to be the lowest for polyjet-printed particles and the highest for SLA-printed particles. The accuracy of the reproduction of morphology is found to increase with an increase in the particle size.

Rotary mills aim to effectively reduce the size of particles through a process called comminution. Modelling comminution in rotary mills is a challenging task due to substantial material deformation and the intricate interplay of particle kinematics of segregation, mixing, crushing, and abrasion. Existing particle-based simulations tend to provide predictions that cannot cope with the large number of particles within rotary mills, their wide range of sizes, and the physics dictating the crushing of individual particles. Similarly, there is currently no deterministic modelling means to determine the evolving population of particle sizes at any point in time and space within the mill. The aim of this two-part contribution is to address these gaps by advancing a framework for a novel stochastic comminution model for rotary mills, which has a well-defined deterministic continuum limit and can cope with arbitrarily large numbers of particles. This work describes the basic physics and structure of the new model within a heterarchical framework for ball and autogenous grinding mills. The primary focus of this Part I paper is to develop a computational model for the integration of motion of material along streamlines inside a mill. Coupled to this process is the kinetic physics dictating particle crushing. In a subsequent work, Part II, segregation and mixing will be added to this model such that realistic behaviour from the mill can be observed.

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