Granular Matter最新文献

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.

Graphic abstract

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.

Graphical Abstract

Thermal energy storage (TES) systems have been proven in their capacity as a crucial component of energy grids relying on renewable sources. An established sensible heat storage technology is a packed-bed TES, employing a granular filling material as a heat storage medium, which is subjected to repeated heating-cooling cycles. As a result of the recurring particle expansion and contraction, excessive stresses and strains can develop and cause material damage. This leads to the increasing need for reliable numerical tools in order to improve the TES design and increase their durability. For this purpose, we propose a continuous thermo-mechanical approach, within the framework of the theory of hypoplasticity, that can accurately predict the single as well as cyclic loading behavior of the filling material. This work focuses on the stress–strain relations and compaction mechanisms of the granular bed in contact with a storage wall with variable inclination and friction coefficient. Furthermore, the important aspect of the wall expansion under the temperature change is also taken into account as well as the specific case when the wall expands more than the granular material. By conducting comprehensive simulations, we demonstrate that our novel numerical model adheres to existing experimental investigations and mitigates shortcomings in the predictive capabilities of previous continuous approaches.

Graphic abstract

Existing empirical relations used to predict the porosity of gravel beds are mainly derived from laboratory-generated sediment beds with random grain packing. However, such relations could not adequately describe beds with non-random grain arrangements that occur widely in fluvial deposits. In this work, the effect of grain imbrication on gravel-bed porosity has been quantified using beds with variable strengths of imbrication generated by flume experiments. Mono-sized ellipsoids with specific shapes were used in experiments to remove particle size and sorting effects on porosity. Random bed packings were generated by settling of ellipsoids in still water whilst imbricated beds generated under flowing water. Beds were frozen using liquid nitrogen before extraction. A new relatively simple and time-saving workflow was developed to measure the orientation of particles and quantify the degree of grain imbrication in frozen beds from X-ray Computed Tomography images. Beds with the strongest grain fabric display a ca. 0.03 absolute reduction of porosity value on average (8–10% relative reduction) compared to that of random packing for undisturbed beds. Further, results were obtained for beds deposited under still-water conditions subject to disturbance by shaking, to mimic the potential effect of vibrations from currents, waves or other sources in the environment. A reduction in bed porosity of ca. 0.014–0.018 (ca. 5% relative reduction) is observed between beds with the strongest grain fabric and those with random packing that had undergone shaking after deposition. Hence, a significant proportion (> 50%) of the porosity loss observed for imbricated beds may be attributable to tighter packing due to turbulence-related vibrations from the flow. The small decrease in porosity value despite the formation of strong imbrication is considered to be due to the limited improvement in grain organization, as the results show that the flat shape of the ellipsoids and the uniformity of their size promote the formation of a stacking structure under gravity, leading to a similarly highly ordered grain organization in random packings compared to the imbricated packings.

Graphical abstract

The effects of the stress loading rate and maximum servo wall speed on the instability characteristics of granular materials were investigated using stress-controlled biaxial compression simulation. The results indicate that: (1) the stress loading rate affects the destabilization process of the specimen, with a higher stress loading rate making it easier for the sample to destabilize in a shorter time. (2) The maximum servo wall speed impacts the shear behavior of the specimen and can even lead to simulation test failure. It is therefore strongly recommended that this parameter be listed as a key parameter in future studies. (3) Based on the above analysis, a new conceptual framework was proposed to characterise the different cases of stress-controlled tests, which can guide the rational selection of rates.

Electron beam melting is a powder bed fusion process capable of manufacturing parts from a variety of high-temperature alloys. Given that the process relies on feedstock recycling for process economics, understanding process-part quality relationships is critical. This work investigates process-part quality relationships in terms of the internal and external defects and component microstructure relative to a feedstock subjected to 33 build cycles without replacement. To accomplish this, a volume of fluid mesoscale model consisting of three different powder distributions were considered: (1) Monomodal; (2) As-measured; and (3) Irregular. Particle morphology was characterized using shape factors examined via optical microscopy. To approximate the particle shapes in three-dimensions, a method is presented that utilizes a binarized domain to define low frequency, macroscale particle “base” shapes implicitly and is thus not restricted to starlike particles. The discrete element method was also used to investigate velocity distributions and packing densities of the as-measured and irregular particles with respect to deviations in the nominal layer thickness of 50 μm. In general, beam power and scan speed were found to have an appreciable effect on microstructure formation and surface roughness. Finally, correlations were found between specific classifications of irregular particles and lack of fusion defect formation.

Graphical abstract

Overview of the discrete element method simulation domain for the electron beam melting powder bed fusion process