Granular Matter最新文献

Particle characteristics (particle shape and size), along with relative density, significantly influence the frictional characteristics and liquefaction behavior of granular materials, particularly sand. While many studies have examined the individual effects of particle shape, gradation, and relative density on the frictional characteristics and liquefaction behavior of sand, they have often overlooked the combined effects of these soil parameters. In this study, the individual effect of these three soil parameters on the strength characteristics (angle of internal friction) and liquefaction resistance has been quantified by analyzing the data available in the literature. A novel dimensionless parameter, the ‘packing index ((alpha )),’ was developed to account for the bulk characteristics (relative density - RD) and grain properties (gradation, represented by the coefficient of uniformity ((C_u)), and particle shape represented by the shape descriptor regularity ((rho ))) of the granular soils. Through statistical analysis, a power law-based equation was proposed and validated to relate the cyclic resistance ratio (CRR) and angle of internal friction ((phi )) with the packing index. Finally, an approach to assess the liquefaction resistance was detailed considering the intrinsic soil parameters, aiming to bridge the gap between field observations and laboratory analysis to facilitate a comprehensive understanding of soil behavior under cyclic loading.

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Hydraulic structures such as embankments and dams are essential for water storages, flood control, and transportation, but are vulnerable to suffusion under complex loading conditions. This study investigates the effect of suffusion on the cyclic shear behavior of gap-graded soils using the coupled computational fluid dynamics and discrete element method (CFD-DEM). A series of seepage infiltration and drained cyclic shear tests are conducted on specimens with varying mean stresses and initial stress anisotropy to systematically evaluate the mechanical consequences of suffusion. The findings reveal that the higher mean stress and initial stress anisotropy significantly exacerbate fines loss and deformation, particularly along principal seepage directions during suffusion. Furthermore, the eroded specimens exhibit substantial stiffness degradation and microstructural changes, including the deteriorated interparticle contacts and more pronounced fabric anisotropy. Notably, fines loss intensifies the load-bearing reliance on coarse particles during cyclic loading. These results provide new micromechanical insights into suffusion-induced degradation, offering valuable implications for developing advanced constitutive model of gap-graded soils accounting for suffusion-induced fines loss and cyclic loading conditions.

Entangled matter provides intriguing perspectives in terms of deformation mechanisms, mechanical properties, assembly and disassembly. However, collective entanglement mechanisms are complex, occur over multiple length scales, and they are not fully understood to this day. In this report, we propose a simple pick-up test to measure entanglement in staple-like particles with various leg lengths, crown-leg angles, and backbone thickness. We also present a new “throw-bounce-tangle” model based on a 3D geometrical entanglement criterion between two staples, and a Monte Carlo approach to predict the probabilities of entanglement in a bundle of staples. This relatively simple model is computationally efficient, and it predicts an average density of entanglement which is consistent with the entanglement strength measured experimentally. Entanglement is very sensitive to the thickness of the backbone of the staples, even in regimes where that thickness is a small fraction (< 0.04) of the other dimensions. We finally demonstrate an interesting use for this model to optimize staple-like particles for maximum entanglement. New designs of tunable “entangled granular metamaterials” can produce attractive combinations of strength, extensibility, and toughness that may soon outperform lightweight engineering materials such as solid foams and lattices.

The flow characteristics of granular materials under gravity represent the primary scientific challenge involved in caving mining. Conducting in-depth research in this area contributes to improving ore recovery results. This study introduces an innovative discrete particle dynamics model that combines the advantages of soft-sphere and hard-sphere algorithms to significantly improve the simulation of granular flow in caving mining. The proposed soft-hard sphere coupling model achieves remarkable computational efficiency while accurately capturing the influence of particle shape on flow behavior. By developing a specialized collision resolution algorithm and implementing advanced contact detection methods, the model successfully simulates the isolated draw process for particles of various shapes, including circular, polygonal and elliptical particles. The reliability of the model is thoroughly validated through comparison with physical experiments and theoretical models. Furthermore, the study demonstrates how the rolling resistance coefficient can effectively characterize particle shape effects in circular particle simulations, providing a practical approach to balance computational efficiency and accuracy. These developments offer valuable insights for optimizing ore recovery in caving mining operations.

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Geogrid is one of the most widely used geoinclusions in railway engineering to improve the bearing capacity of ballasted tracks. However, its effectiveness in mitigating ballast degradation, recognized as the most critical engineering challenge, remains limited, particularly in the context of the increasing demand for faster and heavier haul transportation nowadays. Rubber granules (RG), manufactured from waste rubber tires, possess high energy-absorbing properties that dampen vibration, reducing the stresses on ballast particles and helping to prevent ballast degradation. In order to explore the practical methods to delay the degradation of ballast and improve the performance of track bed, in this study, a series of large-scale direct shear tests were conducted on ballast aggregates with different geogrid-inclusion conditions and various RG content to investigate the shear behavior and performance of ballast under different configurations. The results show that while the RG effectively reduces the breakage of ballast particles, it negatively impacts the development of shear strength in aggregates, with or without geogrid reinforcement. As RG content increases, ballast aggregate exhibits lower peak shear strength, smaller maximum volumetric dilation, and greater volumetric contraction during shearing. For geogrid-reinforced ballast, incorporating 5% rubber granules (by volume) results in a reduction of aggregate shear strength by approximately 12%, while simultaneously mitigating ballast breakage by more than 30%. By balancing the enhancement of ballast durability with the maintenance of adequate shear strength, a 5% RG content by volume is recommended as a suitable proportion for practical applications. Based on experimental observations, a set of empirical equations has been proposed to estimate the shear strength and volumetric deformation of geogrid-reinforced ballast in the presence of RG. The findings from this study provide valuable insights for improving the design and performance of ballasted railway tracks, particularly in addressing ballast degradation and ensuring track resilience under modern loading demands.

Graphical Abstract

The microstructure of sheared unsaturated wet granular materials, comprising solid particles, liquid phases, and void spaces, is explored using X-ray micro-tomography. Advanced segmentation techniques are employed to overcome challenges in distinguishing phases within the material, utilizing a combination of Random Forest and U-Net models for accurate segmentation of the X-ray images. This methodology enables the quantification of the solid and liquid fractions within the sample, revealing the effects of shear deformation on their distribution. Additionally, an automated tool is designed to characterize the local geometry of small liquid domains, classified according to the number of connected liquid bridges joining grain pairs and the shape of such clusters. It is shown that deformation redistributes the liquid phase, which tends to be excluded from the strongly sheared regions. Coordination number estimates agree with published numerical simulation results. The study also addresses some limitations related to voxel size. The robust tools to analyse complex three-phase microstructure of wet granular materials are expected to improve the modeling of their rheology under different conditions.

Graphical Abstract

"Exploring the microstructure of sheared unsaturated wet granular materials using X-ray micro-tomography. Advanced segmentation with Random Forest and U-Net models enables quantitative analysis of liquid morphologies, after automatic classification, and their evolution under shear, revealing redistribution patterns and coordination changes

Granular materials are typically state-dependent materials, with their strength and deformation behaviors being dependent on density and stress state. Although some studies have adopted the state parameter-based scaling law for application in model tests, their applicability has not been systematically investigated. This paper employs Discrete Element Method (DEM) to conduct drained and undrained monotonic triaxial tests, and undrained cyclic triaxial tests, to investigate the validity of Rocha’s assumption and applicability of the state parameter-based scaling law. The simulation results indicate that the state parameter-based scaling law is suitable for physical modeling of geotechnical problems that prioritize peak or instability strength. The state parameter can roughly determine the liquefaction resistance, supporting its applicability to soil liquefaction problems. However, to ensure the accuracy of the model tests, the overburden stress ratio between the prototype and the model should be chosen within 5 to 10 times.

It is well established that placing an obstacle near a silo outlet reduces the clogging probability in systems approaching the jamming zone, even enhancing the flow rate when the obstacle is optimally positioned. Typically, studies have focused on fixed obstacles in 2D-silo models, using spherical particles, and the underlying mechanisms driving flow rate improvements remain a topic of ongoing research. We investigate experimentally the impact of a pendant mobile obstacle on the discharge flow of lentils using a rectangular flat-bottomed silo with a thickness of several particles. Even when the silo is inside the continuous flow regime, we still observe flow maximization for an optimal obstacle height. By selecting appropriate scaling lengths, we achieve a collapse of the flow rate curves for all aperture sizes studied. Our results indicate that different silo configurations exhibit distinct flow correlations, whose type and extent are crucial for flow rate maximization. Velocity profiles indicate that the obstacle increases particle velocity in the lateral channels surrounding the obstacle. Beyond the optimal height, this effect diminishes, and a sharp drop in velocity is found. This is the first experimental confirmation of previous numerical studies. An analytical model using free-fall particle behavior to describe the flow in the lateral channels provides a good representation of the discharge rate.

Graphical Abstract

Granular gouge is commonplace in natural faults. Revealing the particle motion and rearrangement inside the granular gouge during stick–slip cycles can help better understand the complex processes involved in tectonic earthquakes. Here, the microscopic kinematics and collective response of a granular gouge during the two distinctive states—stick and slip phases—are analyzed based on a numerically simulated sheared granular fault system using the combined finite-discrete element method. During stick phases, the gouge locks the fault plane like a solid, but a few tiny active particle clusters exist due to scattered local contact failures between particles. When slips occur, part of the gouge flows like a liquid, and the particles in the principal slip zone are the most chaotic. The correlation of the collective response of granular particles is weak during stick phases, and the particles barely rearrange themselves, which gives opportunities for storing potential energy in the system. However, when fault slips, the gouge particles’ collective response is strongly correlated, and the stored energy is released, indicating that the particles are effectively rearranged. The rearrangement of the gouge can be explained by the stress chain structures. These stress chains facilitate the cascade of the slips, which reveals why granular gouge inhibits pre-slips. Our study shows how the granular gouge reacts and rearranges during stick–slip cycles from a microscopic viewpoint and may shed light on the dynamic nucleation process of natural earthquakes.

Graphical Abstract

Laboratory-scale research on railway ballast often fails to produce parameters reflecting real-world conditions, while real-scale research incurs high costs. Advancements in computational capacity allowed for discrete element method (DEM) to simulate ballast behavior with three-dimensional, irregularly shaped particles. This research focuses on developing virtual 3D particles for DEM based on digital image processing (DIP) from the use of the Aggregate Imaging Measurement System (AIMS). This can potentially provide a rationale for taking full advantage of databases of aggregate properties obtained with this equipment over more than a decade across various regions worldwide. Quarry-produced aggregates were characterized in terms of shape properties in three orthogonal positions using AIMS. Virtual 3D particles were generated from one, two, or three real 2D images, with strong correlations between real and virtual particles results obtained for sphericity, flatness, elongation, and flatness/elongation ratio. This study shows that generating virtual 3D particles from one single real 2D image from AIMS is an effective and time-efficient process. Furthermore, shape properties classification of virtual particles closely matched real ones, with minimal variation near classification boundaries, confirming the method’s consistency. This approach can be an alternative to more computationally expensive 3D modeling, as well as allowing for the virtual reproduction of aggregates not locally available by sharing AIMS databases. Finally, numerical simulations were proven to be sensitive to real particle shapes, allowing for better understanding of ballast performance, leading to optimization of maintenance and reducing track wear and elements’ failure.