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Understanding the mechanical behavior of lunar regolith is critical for the success of future lunar excavation and construction missions. Irregular particle morphology and low geostatic stress are recognized as key factors contributing to the high internal friction angle of this unique extraterrestrial geomaterial. However, the underlying mechanisms by which low geostatic stress enhances shear strength remain unclear, and the multiscale effects of particle morphology on shear strength evolution are not yet fully elucidated. In this study, consolidated drained triaxial compression tests were performed on CUMT-1 lunar regolith simulant and Fujian standard sand to investigate their macroscopic mechanical behavior. Complementary discrete element simulations of biaxial compression were conducted to analyze mesoscopic mechanical responses of granular materials under the influence of multiscale particle morphology and confining stress. A robust macroscopic–mesoscopic strength correlation model was established, incorporating normalized mean interparticle contact force and mean coordination number to predict the normalized deviatoric stress of granular assemblies. Based on this model, the mesoscopic mechanisms through which irregular particle morphology and low geostatic stress enhance the internal friction angle were quantitatively investigated. The findings offer new insights into the shear strength characteristics of in situ lunar regolith and provide theoretical support for lunar surface construction and excavation operations.

Particle morphology is a fundamental property of granular geomaterials such as rock and soil. A reasonable characterization of irregular particle morphology is of great significance on determining materials’ physical, mechanical and hydraulic behaviors. The purpose of this study is to establish a generic theory for the morphology characterization of irregular particles. First, the Hilbert–Huang transform (HHT) of the field of nonstationary signal processing is introduced into the morphology analysis, and then the complex morphology of irregular particles is decomposed into a series of analysis objects of different scales based on HHT. Then, for the first time, according to geometric measure theory, a comprehensive descriptor system of morphology characterization with clear physical meaning is rigorously established step by step starting from basic mathematical concepts such as set and measure, in which most existing morphology descriptors can be unified, and some new valuable descriptors are extracted. The scale decomposition and descriptor system comprise the complete and generic morphology characterization of irregular particles. At the same time, a highly efficient computation program including the scale decomposition and descriptor calculation of the characterization is provided as a free download. Particle morphology analyses of lunar soil simulants and common river sand are illustrated to validate the effectiveness of the proposed characterization. Because of their generality, except for irregular particles, the characterization and corresponding program have the potential to be applied to any irregular geometry.

Particle morphology is a crucial determining factor in the physicochemical properties of geological materials. Currently, there are still substantial challenges with the characterization and reconstruction of the morphology of irregular particles. Most currently used characterization and reconstruction methods were developed separately, and lack cohesive integration of parameters between the two processes. This limitation hinders the comprehensive characterization of the multiscale geometric features and impedes a clear relation between geometrical features and reconstruction parameters. Therefore, a unified 2D and 3D morphological characterization method for irregular particles is developed in this paper, enabling a systematic morphology quantification across three relative scales. Furthermore, a geometric parameters-driven particle reconstruction approach is proposed, which is the reverse of the quantification process, achieving precise and controllable 2D and 3D irregular morphology reconstruction. The proposed methods achieve, for the first time, an integrated quantification and reconstruction framework of irregular particle morphology, as well as a unified 2D and 3D morphology characterization. Notably, the proposed approach exhibits strong robustness and computational efficiency when performing 2D and 3D particle morphology quantification and precisely controllable virtual particle reconstruction, which are the bases for accurate mechanical analyses and numerical simulations.

The discrete element method (DEM) is widely used for investigating the mechanical behaviours of rock-like materials, and the adopted particle shape considerably influences the dynamic responses of external loads. Elucidating the effect of particle shapes on mechanical properties can further clarify the macroscopic dynamic behaviours. In this study, two well-known particle shape modelling approaches were first introduced. Then, sandpile collapse simulations were conducted using the two models, and the final sandpile accumulation shapes were systematically analysed. The angle of repose increased as the rolling friction coefficient and the contents of composite irregular particles increased. However, the rolling friction model and the simple composite shape (e.g., short rod and tetrahedron) method exhibited lower resolutions than the complex composite (e.g., cuboid) method in calculating the angle of repose. Moreover, direct shear simulations were conducted to investigate the influence of particle shape on shear properties. The rolling resistance model performed better than the composite cuboid method in modelling the friction properties of materials. In conclusion, both the composite particle approach and the rolling resistance model can accurately model the friction properties of rock-like media to some extent.

Currently, fluidization techniques have been widely applied to separate and recover coarse particles (>74 μm) in mineral processing. Studies show that the main parameters affecting this regard are hydrodynamic conditions and interphase interactions. The main objective is to investigate the influences of collision coefficient and drag models on the hydrodynamic behavior of liquid-solid fluid beds. Eulerian-Eulerian method was used and spherical and irregular coarse particles were considered in calculations. In this regard, Gibilaro, Gidaspow, Huilin-Gidaspow, and Syamlal-O’ Brien equations were used to obtain the drag force. Moreover, experimental data of particle volume fraction and fluid bed expansion ratio were employed to evaluate the proposed models. The effects of three restitution coefficients (0.85, 0.90 and 0.99) and four specularity coefficients (0.01, 0.10, 0.50 and 0.99) on fluidization characteristics were studied. The results indicate that for spherical and irregular particles, Gidaspow and Hulin-Gidaspow models have good agreement with experimental data in predicting fluid bed expansion ratio and particle volume fraction. Meanwhile, high prediction accuracy can be achieved when the restitution coefficient is 0.9 and the specularity coefficient is 0.1. The results improve the understanding of coarse particle behavior in liquid-solid fluidization and provide useful information for further investigation of three-phase flotation processes.

The settlement drag coefficient of irregular particles in power-law fluids is a crucial parameter in the field of petroleum engineering. However, the irregular shape of the particle and the non-Newtonian rheological properties of the fluid make it challenging to predict the settlement drag coefficient. In this study, the spherical and irregular particle sedimentation processes in power-law fluids have been analyzed using a visual device and a high-speed camera system. A mechanical model dependent on the force balance of settlement particles was adopted to conduct a detailed statistical analysis of 114 spherical particle experimental results, and a prediction model of the drag coefficient of spherical particles in the power-law fluid was established with a mean relative error of 3.85%. On this basis, considering the influence of geometric shape on the law of particle sedimentation, a new irregular particle sedimentation resistance coefficient model in power-law fluid is established via the incorporation of the parameter circularity of 2D shape description c into the spherical particle sedimentation resistance coefficient predictive model. The parameters in the new irregular particle sedimentation resistance coefficient predictive model can be obtained via nonlinear data fitting of the 211 groups of irregular particles using experimental results in the power-law fluid. The model has high prediction accuracy for the drag coefficient of irregular particles in power-law fluid, with a mean relative error of 4.47, and expands the scope of engineering applications, which is of great significance for fracturing scheme design and wellbore cleaning.

We explore the use of graph networks to deal with irregular-geometry detectors in the context of particle reconstruction. Thanks to their representation-learning capabilities, graph networks can exploit the full detector granularity, while natively managing the event sparsity and arbitrarily complex detector geometries. We introduce two distance-weighted graph network architectures, dubbed GarNet and GravNet layers, and apply them to a typical particle reconstruction task. The performance of the new architectures is evaluated on a data set of simulated particle interactions on a toy model of a highly granular calorimeter, loosely inspired by the endcap calorimeter to be installed in the CMS detector for the High-Luminosity LHC phase. We study the clustering of energy depositions, which is the basis for calorimetric particle reconstruction, and provide a quantitative comparison to alternative approaches. The proposed algorithms provide an interesting alternative to existing methods, offering equally performing or less resource-demanding solutions with less underlying assumptions on the detector geometry and, consequently, the possibility to generalize to other detectors.

This paper presents an efficient CUDA-based implementation of a nonspherical discrete element method where irregular particles are described by using polyhedrons. Two strategies are employed to exploit the parallelism of the numerical method. One is to perform contact detection based on the contact pair level instead of the traditional particle level. The second is to reduce the computational burden of each kernel function by allocating thread blocks reasonably. Contact detection between potential contact pairs is the most complicated, time-consuming, and essential process for the polyhedral discrete element method. The linear bounding volume hierarchies are introduced to fix this issue. The hierarchies of the bounding volume tree are organized in a spatially coherent way. Such a structure can minimize branch divergence and is very suitable for parallel implementation with GPU. Two numerical examples are presented to show the performance of the code. It is found from the scenario of two sphere collision that improving the mesh resolution of polyhedral particles can reduce the computational error while slowing down the computational speed correspondingly. A trade-off must be made between accuracy and efficiency. The other example of self-gravitating aggregation demonstrates the code is convergent, stable, and highly efficient. Particularly, with a mainstream GPU, the proposed method easily performs hundreds of times faster than the serial CPU code that does the same function.

The drag coefficient CD plays an important role in studying the interaction forces between individual particles and fluid. Due to the irregular particle shape of natural sands, studying the sedimentation characteristics and drag coefficient model of irregular particles is of great significance in explaining natural phenomena, predicting the sedimentation process, and calculating the interphase forces between individual particles and fluid. In this paper, firstly, an experimental system for measuring the settling velocity was built, the settling velocity of 67 tests of spheres with different particle Reynolds number Res in the Newtonian fluid were obtained, and the CD–Res correlation of sphere settling in the Newtonian fluid was established. The proposed CD–Res correlation was in good agreement with the existing classical CD–Res correlations, which proves the reliability of the experimental system and data processing method. Existing literature shows that the previous models are only suitable for irregular-shaped particles with three-dimensional shape-described parameters. However, the three-dimensional shape information of sand particles can only be obtained through accurate laboratory measurements, and it is often impossible to calculate accurately. By introducing the two-dimensional shape-described parameter (circularity c), using image analysis technology, the two-dimensional shape information of natural sands was obtained. The settling velocity of 221 tests of natural sands in the Newtonian fluid was obtained experimentally. It is found that the sand particles’ drag force exerted by the fluid is more significant than its equivalent sphere. With the increase in the particle Reynolds number, the shape irregularity’s influence on sand particle drag coefficient is more significant, and the CD–Res correlation of natural sand was proposed by fitting. The established CD–Res correlation has good prediction accuracy and can better predict the drag coefficient and terminal settling velocity of natural sand with irregular shapes.

The behavior of microplastics (MPs) in aquatic environments can vary significantly according to their composition, shape, and physical and chemical properties. To predict the settling trajectory of MPs in aquatic environments, this study investigates the settlement law of MPs under static and dynamic conditions. Four types of materials were analyzed, namely polystyrene, polyamide, polyethylene terephthalate, and polyvinyl chloride. Approximately 1270 MP particles with irregular shapes (near-sphere, polygonal ellipsoid, and fragment) were selected for the settling experiments. The experimental results show that the main factors affecting the settling velocity of MPs were shape irregularity, density, and particle size. The settling velocity of irregular MPs was significantly lower than that of perfectly spherical MPs. We proposed a model that predicts the correlation between the settling velocity of MPs and their shape, density, particle size, and water density.