Computational Particle Mechanics最新文献

Since the conveyed sewage of sewage pumps contained a large amount of flexible cloth-like materials, which could easily lead to the clogging of sewage pumps. In this paper, the CFD-DEM method and high-speed photography were used to clarify the clogging mechanism of the sewage pump. Firstly, the Hertz-Mindlin nonslip model was improved based on the linear cohesion model, and the textile model was established by using the CFD-DEM method. Then, the numerical model was applied to the sewage pump and compared with visualization experiments. The reliability of the model was verified by comparing the different rotational speeds and the size of textiles. Finally, the relationship between the speed, the size of textiles, and the number of textiles on the clogging mechanism and flow field characteristics of the sewage pump was explored. The study provides theoretical support for the development of sewage pumps resistant to flexible cloth-like materials. Future work could extend this framework to investigate multi-scale textile mixtures (e.g., combined fibers and large rags) and long-term wear effects caused by textile accumulation, which are critical for industrial applications requiring durability and adaptability to heterogeneous sewage compositions.

Dry granular flow, a unique sediment gravity flow with plastic rheological properties and laminar flow state, is common in mountainous areas and causes significant damage. Retaining walls are crucial for mitigating debris flow damage, but accurately determining their impact on morphological characteristics is challenging. This paper establishes a numerical simulation model using the discrete element method (DEM) to study the influence of retaining walls on debris flow deposition morphology. Model parameters are calibrated against physical model tests to ensure similarity. This paper will introduce the grain size distribution parameters μ and Dc to represent the content of fine particles and coarse particles, respectively, in order to characterize the granular composition of dry granular flow. Research results show that Dc is closely related to deposition morphology parameters, with longitudinal deposition length and width increasing and maximum deposition thickness decreasing with larger D_c. Retaining wall position significantly affects deposition morphology, with longer and wider deposition as distance increases but thinner deposition. Based on these findings, this paper proposes calculation methods for characteristic parameters under natural conditions and restrained by retaining walls. It reveals the influence mechanism of retaining wall position on deposition morphology and finds that the number of contacts and contact forces between particles and between particles and the deposition plate change dynamically. As the value of sample Dc increases, the reduction rate of the number of force chains, which is influenced by the distance of the retaining wall, also rises. This paper also explores a three-dimensional deposition morphology prediction model, with research results expected to provide theoretical reference for studying movement laws of dry granular flow in mountainous areas and disaster prevention and mitigation.

The discrete element method has become an essential technique for examining the interaction between maize seeds and related mechanical components. Among these, precise selection of discrete element parameters is essential for accurately forecasting the motion of maize seed particles and the interaction processes between particles and mechanical components. Due to the irregular shape of maize seeds, it is difficult to directly measure particle parameters of maize seed such as coefficient of static friction between seed particles (μ_spp), coefficient of rolling friction between seed particles (μ_rpp), and coefficient of rolling friction between seed particles and working components (μ_rpw). As a result, these parameters necessitate calibration methods for accurate determination. Nonetheless, the presence of over two calibrated parameters can potentially result in challenges concerning ambiguous combinations of parameters. In this paper, three main plant maize varieties are utilized as research subjects. This paper investigates the necessity for accurate calibration of μ_spp, μ_rpp, and μ_rpw by the bulk density and “self-flow screening” tests. In addition, the sensitivity relationship between macroscopic physical phenomena and particle parameters is analyzed. The results indicate a substantial decrease in bulk density with the increase of μ_spp and μ_rpp, coupled with a significant reduction in the percentage passing of maize seeds as μ_rpw rises, emphasizing the critical need for the accurate calibration of these three parameters. Additionally, a network of sensitive relationships between macroscopic physical phenomena and three parameters is elucidated: the unloading time is sensitive only to μ_rpp, the dynamic angle of repose is influenced by both μ_spp and μ_rpp, and the percentage passing is impacted by all three parameters. Utilizing the network of sensitive relationships, a targeted calibration method is obtained for maize seed parameters. Initially, μ_rpp undergoes calibration using the unloading time test, enabling subsequent calibration of μ_spp through the dynamic angle of repose test. Subsequently, μ_rpw is calibrated via the screening rate test. Thus, the problem of ambiguous parameter combinations for parameter calibration is solved. The calibrated parameters undergo validation via lifting cylinder and shear angle tests. By comparing experimental results with simulation data, the effectiveness and accuracy of the parameters are confirmed, illustrating the viability and dependability of the calibration approach.

Graphical abstract

Aggregate strength plays a crucial role in determining the fracture behavior of concrete, particularly under dynamic loading conditions. Herein, a three-dimensional discrete element method (DEM) framework was proposed to analyze the effect of aggregate strength on dynamic splitting tensile fracture behavior of concrete. Firstly, a three-phase mesoscale model including mortar, crushable aggregates with realistic morphology, and interfacial transition zone (ITZ). And then, the conventional flat-joint model was enhanced by accounting for strain rate effects, providing precise simulations of the relationship between aggregate strength and dynamic splitting tensile behavior. On this basis, numerical simulation of splitting tensile tests was carried out on concrete with varying ratios of aggregate-to-mortar strength (({sigma }_{text{agg}}/{sigma }_{text{mor}})=0.7, 1.0, 1.5, 2.0, and 2.5) under different strain rates (10^–5/s ~ 100/s). The results revealed that post-peak behavior exhibits brittle failure characteristics at 10^–5/s and 10^–1/s, transitioning to ductile failure at 10/s and 100/s. A significant inverse relationship was observed between strain rate and the influence of aggregate strength on splitting tensile strength––this impact diminishes progressively with both increasing strain rate and higher aggregate strength at constant strain rates. Microstructural analysis revealed that enhanced aggregate strength correlates with reduced microcrack formation in aggregates, whereas microcrack density in both ITZ and mortar phases exhibits an increasing trend. These comprehensive simulation results facilitated the development of a modified dynamic increasing factor model for splitting tensile strength, which systematically incorporates both strain rate effects and aggregate strength parameters.

Granite, a commonly used construction material in engineering, is primarily composed of minerals like quartz, mica, and feldspar, characterized by its heterogeneity and brittleness. The mesostructure and mechanical properties of these mineral particles critically affect the macroscopic mechanical behavior of granite. Creating numerical models of rock materials’ mineral structures through computational reconstruction is an essential method for advancing rock mechanics studies. This paper introduces an anisotropic weighting function to the traditional equal-weight Voronoi method, presenting a novel algorithm for generating the mineral particle mesostructure in rock materials based on an elliptical control domain. The innovation of this algorithm lies in optimizing Voronoi diagram control by adjusting anisotropic weighting coefficients, which enables precise regulation of particle gradation and aspect ratio, accurately reconstructing high-volume fraction mineral particle mesostructures. This approach is particularly suited for describing the mesostructural characteristics of heterogeneous, multi-mineral rock materials, such as granite. In this study, the mineral composition and geometric parameters of specific granite particles serve as a model. Using statistical analysis results of these parameters, the algorithm reconstructs a mesostructural geometric model for granite. Additionally, a numerical analysis model for the Brazilian test of granite is developed for application with the finite discrete element method (FDEM). Through a series of continuous–discontinuous FDEM simulations, the mechanical response and crack propagation patterns in the samples are examined, and the influence of key interface mechanical parameters is comprehensively analyzed. This study demonstrates the practicality of the anisotropic weighted Voronoi-based high-volume fraction particle mesostructure generation method for simulating granite’s mechanical properties, offering vital technical support for accurately modeling and predicting the mechanical behavior of complex rock materials like granite.

Traditional methodologies primarily depend on macroscopic observations and post-experimental fracture surface analysis to identify transversely isotropic rock’s failure modes and mechanisms. This study employed discrete element method (DEM) simulations to analyze Brazilian splitting and uniaxial compression tests on transversely isotropic rocks. By applying moment tensor inversion, seismic information was extracted from acoustic emission (AE) events. The key findings are as follows: (1) The failure modes of the specimens can be categorized into three types: failure that cuts through the bedding planes, failure along the bedding planes, and composite failure, where fractures penetrate the bedding planes while partially following them. (2) In uniaxial compression tests, the sample with a bedding angle of 30(^circ ) exhibits frequent small-scale AE activity along the slip zone, resulting in progressive shear slip failure. In contrast, those at 45(^circ ) and 60(^circ ) angles show more high-magnitude events along the slip zone, with a shorter time from crack initiation to final failure, indicating catastrophic shear slip failure. (3) In the Brazilian splitting tests, specimens with a bedding angle of 60(^circ ) experienced progressive shear sliding failure, while those with a bedding angle of 75(^circ ) experienced catastrophic shear sliding failure. These findings refine the failure mode classification of transversely isotropic rocks across different bedding angles, enhancing understanding of their mechanical behavior.

Construction materials used for masonry units and mortar are typically quasi-brittle. The current research presents a computational framework to simulate fracture in these materials using the discrete element method. In this framework, the surface geometry is first discretized into a fine unstructured triangular tessellation, which is then extruded to form triangular blocks that constitute the 3D volume. The fine discretization enables modelling of the initiation, propagation and coalescence of cracking within the simulated materials. The ability of the proposed modelling approach to reproduce realistic fracture patterns is first evaluated using experimental results from the literature. The comparisons demonstrate that the proposed framework can be used to simulate Mode-I fractures in direct tension as well as mixed mode fractures under compression. The influence of block size on the crack pattern and global load–displacement predictions is systematically explored. The framework is then utilized to investigate the influence of pre-existing morphological irregularities on the fracture response. For this purpose, a custom algorithm is developed to introduce joined element clusters (to simulate stiff inclusions within the material) and voids (to simulate defects within the material) within the geometry. Results show that defects within the material, particularly in masonry mortar joints, act as crack initiators and significantly reduce load-carrying capacity, underscoring the importance of mortar integrity in structural performance. The examples highlight the framework’s potential to enhance the performance evaluation of masonry materials and structures.

When a centrifugal pump transports solid–liquid two-phase flow, its performance decreases, and the two-phase flow characteristics within the pump is directly related to the blade’s geometry. Therefore, in this study, the coupled computational fluid dynamics discrete element method (CFD-DEM) was used to analyze a prototype impeller with a wrap angle of 94°. The inverse design method was then used to develop impeller designs with different wrap angles (99°, 104°, and 109°). It was found that as the blade wrap angle increased, particle accumulation in the blade inlet region was alleviated, and the severe wear region moved toward the impeller outlet. These effects were related to the decreased energy losses of the moving particles at the inlet and increased at the outlet. Overall, there was a decreasing trend in the energy gained by the particles on the pressure surface.

With the significant advancements in parallel computing techniques, the particle-particle (PP) model has been effectively utilized in various plasma-related applications. However, PP has been limited for solving only electrostatic problems under Coulomb’s law, by analogy to the particle-in-cell (PIC) model solving Poisson’s equation. While electromagnetic PIC is common with coupled solutions of Maxwell’s equations, we propose an electromagnetic (EM) PP model taking advantage of Liénard-Wiechert potentials for point charge in this paper. In addition, this EM-PP model can contribute to simulate relativistic binary collisions with high accuracy; thus, its results are used as a baseline to compare with the classical Frankel’s relativistic scattering angle, and the accuracy and applicable scope of Frankel’s formula are discussed.

In this paper, we propose a numerical procedure for the quantification of uncertainties in wave–structure interaction. We utilize the smoothed particle hydrodynamics (SPH) scheme for modeling the wave mechanics, coupled one-way with a finite element method (FEM) for the structural response. Physical wave flumes are extensively used in the study of hydrodynamics especially in wave–structure interaction (WSI) and prediction of forces to near-shore structures in disaster mitigation and offshore structures in the oil and gas, and more recently renewable energy sector. Over the years, numerical wave flumes have been developed extensively to enable the modeling of complex wave–structure interaction. However, most of these studies are deterministic and limited to using either simple flexible beams or rigid monolithic structures to model the structural part in the WSI. Additionally, uncertainties are commonly observed in both wave and structural parameters and need to be accounted for. This work presents a numerical framework to enable uncertainty quantification for wave–structure interaction problems in terms of the forces experienced by the structure. A one-way coupling between SPH with the FEM and uncertainty quantification is proposed. We employ the so-called Tokyo wave flume geometry, which has potential for future surrogate modeling in WSI. The developed model is validated using numerical and experimental results from the literature and is used to demonstrate the prediction of probabilistic responses of structures under breaking and non-breaking wave scenarios.