Granular Matter最新文献

A method to measure rolling friction coefficients for spheres rolling down an inclined two-cylinder track is described. The estimated coefficients of rolling friction are correlated with the equivalent radius of the deformation in the contact region, which can be calculated from Hertz’s contact model using available values of Young’s modulus and Poisson’s coefficient. The values of the coefficients of rolling friction determined in prior literature and those obtained here for steel spheres moving on a steel two-cylinder track show a variation in the sphere radius consistent with that expected from the contact model. The transition from pure rolling to rolling plus sliding regimes is also studied.

The mechanisms of granular flow-structure interactions and impact dynamics serve as a foundation for bridge engineering design. However, the design of bridge piers to counter granular flow continues to be influenced by the particle size distribution and the Froude characteristics’ impact on pier performance. A three-dimensional numerical model is established in this study, using the Discrete Element Method (DEM), and its reliability is confirmed through flume tests. The interaction mechanisms and dynamic impact characteristics of granular flow, coupling with particle size and Froude number (Fr), and pier’s shapes, were explored. The flow characteristics of granular flow have been revealed, as well as the interplay mechanism between granular flow and pier, the energy evolution mechanism, and escalation. The impact force distribution of granular flow on pier was clarified. A comparative analysis was conducted on the peak impact force resistance coefficient (C_d) for pier of assorted cross-sectional shapes. We have further developed a unified particle size-bridge pier-special design diagram, quantifying the influence of particle size and Fr on the hydrodynamic α. The analysis indicates that the existing models calibrated by limited experiments may overestimate the peak impact force on round and round-end bridge piers, while underestimating it for square bridge piers.

Graphical Abstract

When granular gases in microgravity are continuously excited mechanically, spatial inhomogeneities of the particle distribution can emerge. At a sufficiently large overall packing fraction, a significant share of particles tend to concentrate in strongly overpopulated regions, so-called clusters, far from the excitation sources. This dynamical clustering is caused by a complex balance between energy influx and dissipation. The mean number density of particles, the geometry of the container, and the excitation strength influence cluster formation. A quantification of clustering thresholds is not trivial. We generate ‘synthetic’ data sets by Discrete Element Method simulations of frictional spheres in a cuboid container and apply established criteria to classify the local packing fraction profiles. Machine learning approaches that predict dynamic clustering from known system parameters on the basis of classical test criteria areoposed and tested. It avoids the necessity of complex numerical simulations.

Because of its unique structure, graded porous materials are widely utilized in filtration, separation, energy and catalysis. However, there are many defects in the traditional manufacturing methods, and the manufacturing process is much complicated. It is of great significance to realize the orderly separation and arrangement of different size particles quickly and conveniently, so as to realize the construction of graded porous materials. In this paper, the discrete element method (DEM) was employed to simulate the vibration process of fine particles with continuous size distribution, and the influences of vibration amplitude (A) and frequency (f) on the segregation behavior and related properties of packing structure were systematically investigated. The dynamics and mechanism of vibration segregation were analyzed through packing morphology, particle trajectory and velocity information. Finally, the graded pore structure could be obtained by appropriate vibration. The results show that for the 316L stainless steel powder used in this paper, the graded particle structure is prone to be gained within a range of large vibration intensities (e.g., A = 13.5 μm and f = 600 Hz). Simultaneously, the overall porosity (ε) is also higher (ε = 0.44). The difference in size between large and small particles causes the difference in motion behavior during movement, which makes it easier for small particles to drill into the pores formed by large particles, and directly leads to particle segregation. In the typical graded porous structure (e.g., A = 13.5 μm and f = 600 Hz), the pore volume distribution of the bottom particles is narrow, and its volume is only 0–0.2 × 10^–13 m³. Along the + Z direction, the size distribution width of the pores increases, the peak position moves to the right, and the average pore volume becomes larger. The exploration results of this paper will provide a novel idea and theoretical basis for the construction of graded porous materials.

Measuring a temperature rise in tapered bearings is very important. This paper proposes a model for calculating the rise in temperature of bearings that considers the presence of contaminants in the lubrication. This study develops a discrete lubrication model for the Hertzian contact zone of a bearing using the Lattice Boltzmann method (LBM). The model analyzes the effect of particles on grease film flow and pressure. The temperature rise of the bearing was then calculated. Meanwhile, the study solved the bearing temperature rise in the lubricating grease using the finite difference method (FDM). The results of the LBM calculations were compared with those of the FDM calculations. Finally, an experimental study is conducted to investigate the temperature increase of the raceway in the presence of particulate matter in sealed grease lubrication. The results of the study show that the presence of particulate matter has little effect on the temperature rise of the bearings. The study results show that burnout is caused by a lack of grease rather than particles.

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The post-Darwinian era has been marked by a long-term effort to lay the foundations for a generalized theory of evolution in the broad sense. We suggest throughout this article that most of biological systems, including living species, could stand as multiscale complex systems due to microscopic or mesoscopic properties of the entity interacting with its environment. Intriguing commonalties which exist between the living and non-living species as complex systems give a strong hint that a unified approach could be developed. The paper explores this hypothesis by analyzing how complex systems, such as granular matter, evolve and adapt when brought out of equilibrium. The inherent disorder in most of granular materials gives way to a wide spectrum of structural patterns that can transform according to the external conditions applied. When brought out of equilibrium, phase transitions can occur spontaneously, leading to profound configurational reorganizations where new and unexpected structures can emerge. Using most of the fundamentals derived for granular systems, a material approach of evolution is proposed, whereby living and non-living architectures can be brought together within a rational framework whereby key concepts such as self-organization, emergence, scale effects, fluctuations and memory storage are at the very forefront.

This paper focuses on the study of a vertical spiral stirred mill, thoroughly analyzing the dynamic behavior of the grinding media within the mill barrel, aiming to achieve a comprehensive understanding of the internal operating mechanisms of this type of equipment. Firstly, based on the working principles of the vertical spiral stirred mill, a discrete element method (DEM) simulation model was constructed, and its validity was verified through experiments. Then, to explore the kinematic characteristics of the grinding media in multi-dimensional space, a refined velocity model of the grinding media was developed using vector decomposition techniques. On this basis, key control parameters such as the pitch of the spiral agitator, blade diameter, rotation speed, and grinding media filling were systematically analyzed for their effects on the motion patterns of the grinding media, relying on the validated DEM model. The results indicate that in the axial dimension, the axial velocity of the grinding media, along with the circumferential velocity in the central region of the mill, exhibits high stability, revealing the uniformity of the motion state in this region. Simultaneously, in the radial region between the outer edge of the spiral blades and the mill wall, the grinding media present significant gradients in both circumferential and axial velocities, indicating this area as a crucial grinding zone. Further analysis shows that the pitch of the spiral agitator, blade diameter, and rotation speed significantly affect the circumferential velocity in the radial direction, while both blade diameter and rotation speed also play a dominant role in the axial velocity. In contrast, the filling of the grinding media has a minimal effect on the overall motion patterns, suggesting that the dynamic characteristics of the grinding media are primarily influenced by the mechanical structure design and operational parameters.

This study presents the first experimental investigation of stress wave propagation in 1D granular chains of closed-cell PVC foam disks. Average impact velocities for H130 and H250 foams ranged from 17.6 to 38.1 m/s. The analysis focuses solely on the incident stress wave, excluding the reflected wave. The mid-planes of the disks were chosen for analysis due to their uniaxial force components along the chain's length. The results show that the stress wave speed is faster in the H250 foam chain due to its higher stiffness. Wave speed increases with impact velocity but decreases as it travels along the chain, with a more pronounced reduction in the H130 foam compared to the H250 foam. The peak normal forces in the H250 foam chain disks are approximately three times greater than those observed in the H130 foam chain disks at comparable impact velocities. The peak normal forces in both foam chains decrease rapidly with increasing impact velocity, especially over the first few disks. As the wave propagates further from the impact source, the attenuation rate slows, with a more gradual force reduction in the H250 foam due to its higher density and stiffness. Energy loss is governed by viscoelastic and plastic dissipation at disk contacts, which becomes more significant at higher impact velocities. This study provides new insight into dissipative wave phenomena in granular systems of deformable elements and offers experimental data for future modeling of strongly nonlinear, dissipative granular media.

Recent advances in image-based particle shape characterization allow reliably and rapidly determining particle roundness and sphericity of a statistically significant large number of particles, which enables systematic investigation of the influence of roundness and sphericity on macroscopic engineering behaviors such as strength and dilatancy of sands. This study collects 22 sands with a wide range of particle sphericity, roundness, gradations, and mean particle sizes. A total of 207 direct shear tests are prepared at various relative densities and normal stresses to establish the database. This database is further augmented by experimental data of another 97 sands from published geotechnical engineering sources. Influences of image-based sphericity, roundness, and gradation on the frictional and dilational components of soil strength are analyzed, leading to observations that angular, elongated, and well-graded sands exhibit larger values of critical strength, dilatancy, and peak strength. A material parameter is proposed by integrating roundness and gradation that captures the joint effects of intrinsic properties. The material parameter is used to develop predictive models for critical friction angles, dilation angles, and peak friction angles. The effectiveness and accuracy of the predicted models are validated by various published geotechnical experimental data. The material parameter and predictive models provide insights into relationships between micro particle level properties and macro mechanical behavior of sands and enable researchers and practitioners to rapidly estimate the strength and dilatancy of sands without performing laboratory tests.

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An innovative methodology for predicting gradation stability using integrated machine learning technologies is introduced. Current geometric criteria for suffusion assessment rely on a limited set of characteristic particle sizes, which results in a loss of detailed gradation information embedded in grading curves. This study proposes a new framework for evaluating the suffusion sensitivity through predicting the gradation stability of granular soil with a specified grading curve. Two distinct integrated machine learning models are developed to quantitatively assess soil internal stability. The predicted results and performance analysis demonstrate that the PCA-SVM model achieves superior classification accuracy for internal stability, while the PCA-ANN exhibits enhanced predictive capability in estimating the probability of internal stability within the given dataset. The proposed methodology provides a novel application for investigating the relationship between gradation characteristics and stability. This study will facilitate further research on establishing the accurate gradation stability criteria and predicting the soil suffusion sensitivity.

Graphical Abstract