Granular Matter最新文献

The mechanical properties of rockfill materials degrade markedly under dry–wet cycles, leading to uneven settlement of rockfill dams over time. To elucidate the underlying mechanisms, this study utilizes the particle discrete element method (DEM) to conduct numerical simulations of triaxial compression on crushable rockfill samples under various dry–wet cycle scenarios. This computational approach facilitates a comprehensive analysis of the material's macroscopic mechanical behavior while simultaneously revealing its microscopic degradation processes. The research findings are presented in detail below: (1) Macroscopic law: The results indicate that an increase in the number of dry–wet cycles (N) corresponds with a decrease in peak stress and an increase in volume strain. However, these parameters tend to stabilize, showing minimal change once N exceeds a certain threshold. Furthermore, the analysis reveals an exponential relationship between N and the key shear strength parameters: the apparent cohesion (c) and the internal friction angle (φ). Concurrently, as the cycles progress, both the rate of particle breakage (B_r) and the net increase in particle count progressively diminish. (2) Microscopic mechanism: An increase in N leads to the expansion of force chain networks, a wider distribution of particle fractures, and a more extensive displacement field within the sample, accompanied by a significant rise in the average coordination number. Mirroring the macroscopic behavior, these microscopic changes also become less pronounced after N surpasses the established threshold, suggesting the sample is approaching a state of mechanical stability. (3) Damage evolution: Analysis of the modified Duncan-Chang model reveals that its constitutive parameters (A, B, and C) demonstrate an exponential relationship with the number of dry–wet cycles (N). These parameters undergo a phase of rapid exponential growth during the initial cycles, which subsequently transitions to a stable state as the cycling progresses.

To systematically investigate the mechanical behaviors of rockfill materials under the combined influence of particle shape and sample size, a stochastic algorithm that incorporates three-dimensional shape parameters such as elongation, flatness, sphericity, and convexity, was employed to generate irregularly shaped rockfill particles. A triaxial numerical simulation method was proposed for rockfill materials, which comprehensively accounts for both particle shape and sample size. Discrete element numerical simulations of rockfill materials with varying particle shapes and sample sizes were conducted to investigate the effects of these two factors on the mechanical properties and nonlinear constitutive models from both macroscopic and microscopic perspectives. The evolution of microscopic characteristics including coordination number, Euler angles, and fabric anisotropy of rockfill bodies were examined, and the stress–strain and volumetric strain responses of various particle samples were analyzed, revealing the correlation mechanisms of particle shape and sample size on their macro- micro properties of rockfill materials. Based on these findings, a novel constitutive model that integrates both particle shape and sample size was presented, aiming to offer a more accurate and comprehensive theoretical framework for understanding the mechanical behavior of rockfill materials.

Graphical Abstract

This study examines the interaction between granular flows and barrier systems in landslides, employing both a landslide model test and PFC^3D discrete element simulations. The investigation focuses on the temporal evolution of the granular flow front velocity and changes in flow states, with an emphasis on slope angles and lateral blockage ratios. The results demonstrate that the front velocity of granular flows exhibits a generally increasing trend. More pronounced acceleration occurs on steeper slopes with moderate blockage ratios, while lower slopes or higher blockage ratios lead to slower acceleration. Despite this, an overall increase in velocity is consistently observed across all scenarios. A critical transition is identified at the 0.2-s mark, where slope angle plays a pivotal role, and interactions with barriers cause the flow to split and deflect, resulting in energy dissipation. Furthermore, under controlled single-variable conditions, the study reveals that the average flow velocity is inversely proportional to the lateral blockage ratio and directly proportional to the slope angle. The barrier system significantly influences the flow velocity: for the first row of barriers, the total average velocity attenuation increases with steeper slopes and higher blockage ratios, while for the second row, the attenuation shows a proportional relationship with the lateral blockage ratio. These findings contribute to the understanding of granular flow dynamics in landslides, providing valuable insights for debris flow mitigation, landslide risk management, and engineering applications involving barrier systems.

Graphical Abstract

Granular flows are widely present in engineering and natural phenomena, and their interactions with obstacles represent a critical research direction in flow dynamics, with significant implications for disaster prediction and engineering optimization. This study focuses on the shock wave interference phenomenon in gravity-driven granular flows interacting with parallel cylindrical obstacles, aiming to explore its physical mechanisms and influencing factors. The experimental design incorporates varying obstacle spacings and slope angles to systematically investigate the impact of shock wave interference on flow structure, geometric characteristics, and velocity field distribution. The results indicate that decreasing obstacle spacing significantly enhances shock wave interactions, leading to an increase in the standoff distance (D_standoff) of the shock wave front and greater upstream flow obstruction. Conversely, increasing slope angle accelerates the free-stream velocity, further intensifying the shock wave strength. Analysis using a convection–diffusion model reveals that diffusion intensity has a critical influence on the curvature radius of the shock wave, with larger spacings reducing convective effects and thereby increasing the shock wave curvature. Additionally, velocity field profile analysis highlights a dual mechanism of particle velocity reduction and deflection, where the number of deflection peaks and total deflection area increase with obstacle spacing. These findings provide new insights into the dynamic mechanisms underlying granular flow-obstacle interactions and offer theoretical support for controlling granular flows in related engineering applications.

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To acquire the ability to numerically study the rheology of particulate two-phase flows that lack scale separation, we present a general method to average or coarse-grain the equations of motion of a mixture of a continuous fluid of arbitrary rheology and non-Brownian particles, interacting via contacts, of arbitrary shapes and compositions. It universally covers ensemble and typical spatio-temporal averaging procedures and overcomes two shortcomings of existing methods. First, the derived micromechanical expressions for the coarse-grained fields are mathematically exact and formulated in a manner that allows a computationally cheap extraction from Direct Numerical Simulation–Discrete Element Method (DNS–DEM) simulations, avoiding the unlimited-order derivatives appearing in previous exact formulations. Second, the microscopic volume fraction of each particle is its corresponding indicator function, rather than the traditional volume-weighted delta distribution at its center of mass, to ensure that the resulting macroscopic fluid and solid volume fractions add precisely to unity. This leads to an additional contact stress contribution not seen in standard coarse-grained expressions for granular matter, and, for non-spherical particles, to particle-rotational contributions to translational solid phase balance equations. Many implementations of DNS–DEM simulations are based on Immersed Boundary Methods (IBMs), for which modifications of the coarse-graining method are necessary due to certain peculiarities of IBMs, such as the replacement of the particles’ interiors by pseudo-fluid. We therefore derive mathematically exact adaptations of the coarse-graining method for two distinct common IBM versions, implement one version to obtain coarse-grained fields from sediment transport simulations based on this version, and validate the implementation.

Screening units, which are essential machines across industries where improvement studies are needed today, have gained importance efficiency and energy saving. In this study, the screening process of the copper ore pile was analysed using the discrete element method (DEM) employing the geometry and feeding conditions of the mobile screening unit. Using initialanalyses, the effects of screen rotation speed and pile volume for different mass distributions are evaluated to identify the most effective configuration. The effect of hole geometry and mass distribution was examined by modifying the size distribution of the pile. Efficiency and capacity calculations were performed by increasing the pile’s feeding volume with equal mass distribution. In this study, which aims to identify the conditions under which the most efficient and highest-capacity screening operation occurs, improvements were made to the screen design. In addition, the wear analysis was simulated, and the effect of changes in feeding conditions on the screen life was investigated. The results highlighted that the screen design to be used in the screening operation is directly affected by the pile characteristics, demonstrating the significance of DEM-based modelling in industrial screening optimization.

Graphical Abstract

Moisture content critically influences the matric suction and stress distribution within subgrade soils, directly affecting their load-bearing capacity. Understanding the internal mechanisms by which moisture variations degrade subgrade performance is essential. This study proposes a novel coupled simulation method based on the Volume of Fluid (VOF) theory to fully resolve the relationship between matric suction and stress conditions among the air–water–solid phases in unsaturated subgrades. By coupling Computational Fluid Dynamics (CFD) with the Discrete Element Method (DEM), the proposed approach incorporates phase fraction modeling to capture particle interactions and quantify the drag forces between phases. The results demonstrate that using phase fractions enables effective modeling of matric suction variations at the pore scale. The proposed method accurately captures the intermediate suction range (10⁴–10⁶ kPa), with errors below 2% in low suction scenarios. It provides detailed insights into particle-scale stress redistribution under varying moisture conditions. Furthermore, the numerical simulations of resilient modulus of subgrade soils matches well laboratory measurements, with deviations within 3–5%, confirming the reliability and predictive capability of the proposed numerical approach.

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Understanding the strength and deformation behavior of recompacted loess is essential for the stability assessment of man-made geotechnical structures in loess regions. While numerous studies have examined the macroscopic mechanical properties of unsaturated recompacted loess, the underlying particle-scale micromechanical deformation mechanisms remain inadequately explored. In this study, a series of drained triaxial tests were conducted on unsaturated recompacted loess under varying matric suctions and mean net stresses to investigate their effects on strength and deformation behavior. The experimental results indicate that higher matric suction increases deviatoric stress due to suction-induced apparent cohesion, whose influence weakens with increasing mean net stress. Moreover, all specimens exhibit continuous volumetric contraction during shearing, consistent with the strain-hardening behavior observed in the stress–strain curves. To interpret these observations from a micromechanical perspective, the original Hill contact model within the discrete element method (DEM) framework was modified by incorporating suction-dependent micromechanical parameters. The modified model was calibrated and validated against laboratory data, showing good agreement in reproducing both stress–strain and volumetric deformation behaviors. Further micromechanical analysis reveals that suction enhances capillary bonding at low net stress, but its influence diminishes as the mean net stress increases. Specifically, at low net stress, higher suction results in a greater proportion of tensile (i.e., capillary) contacts and slightly reduced particle displacements, indicating stronger interparticle bonding. As the mean net stress increases, particle displacements become slightly larger and contact stability is primarily governed by vertical contact forces rather than suction effects. These micromechanical insights are consistent with the experimental observations, thereby establishing a clear link between particle-scale interactions and macroscopic mechanical responses.

Graphical Abstract

Predicting partial coordination numbers and contact proportions among different contact types is essential for developing theoretical models that link local contact characteristics to the macroscopic mechanical behavior of disordered multicomponent packings. The original Dodds model performs well for binary mixtures with small size ratios but has limited applicability to systems with large size ratios (α > 6.46). This study systematically analyzes the range of small-particle area fractions (f_{s}) over which the two-dimensional (2D) Dodds model remains valid for binary mixtures with α > 6.46 under gravity-free packing conditions. The results indicate the model provides reliable predictions when (f_{s}) exceeds the optimal value (f_{s}^{{{text{opt}}}}), which corresponds to the maximum packing density, but exhibits large errors when (f_{s} < f_{s}^{{{text{opt}}}}), where the discrepancies between the theoretical configuration and the actual packing structure become non-negligible. To address this limitation, a two-stage modification of the Dodds model is introduced. First, a portion of non-rattler small particles is distributed, followed by the redistribution of the remaining ones around the initially placed particles to approximate realistic local configurations. The modified contact statistics are then derived under simplified assumptions. Predictions from both the original and modified models are validated against discrete element method simulations for 2D dense binary assemblies with α = 7, 9, 12, and 16, and experimental data for α = 7, 9. The modified model improves predictions for α > 6.46 and (f_{s} < f_{s}^{{{text{opt}}}}), providing a framework for extending structural modeling approaches to multicomponent mixtures with large size ratios and to more complex three-dimensional systems.

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The dispersion of granulated particles in a liquid is an important process that significantly affects the quality, stability, and functionality of industrial products. It is also a phenomenon of interest in fundamental science. Changes in the particle size distribution (PSD) in a suspension of granules are widely used as indicators of the progression of various dispersion behaviors. In this study, we used the time-domain laser diffraction method to observe dispersion in a granular suspension. We then applied principal component analysis (PCA) to analyze the measurement data, which were obtained as a time series, and extract the characteristic changes in particle size during the dispersion. By extracting the principal components from multidimensional data using PCA, we could characterize the dispersion-phase behavior and separate the peak components, which could not be captured by conventional analyses using representative values such as percentiles. In particular, by applying the PCA method—commonly used in spectroscopy—to PSD data, we obtained new insights suggesting the presence of complex dispersion pathways and intermediates. The findings of this study advance our understanding of granule dispersion dynamics and help establish a new framework for analyzing particle dispersion processes, which can assist in particle design, formulation optimization, and extending scientific knowledge in this area.