Particle Numerical Simulations Research Articles

Optimized structure design for binary particle mixing in rotating drums using a combined DEM and gaussian process-based model

Particle mixing is a crucial operation in various industrial production processes. However, phenomena like segregation or local accumulation can arise, especially when particles differ in properties like radius and density. Numerical simulation of particles using Discrete Element Method (DEM) allows for the manipulation of control variables in batches, generating a large amount of data and facilitating quantitative research. In this study, the mixing behaviors of binary particles in rotating drums are systematically investigated. The DEM model is first validated with experimental data and then rotating drums with varying obstacles, rotation speeds, particle radii, and densities are simulated. Moreover, a Gaussian process-based optimization is conducted by correlating Lacey mixing index (MI) and parameterized shape of obstacle to find the optimized mixing condition. Experimental validations are further performed on the optimized condition to verify the design. It is shown that this integrated approach holds significant potential for enhancing the efficiency, effectiveness of industrial mixing processes and the consideration of energy consumption when balancing the mixing efficiency and optimal rotating speed.

Discovering dynamic laws from observations: The case of self-propelled, interacting colloids.

Active matter spans a wide range of time and length scales, from groups of cells and synthetic self-propelled colloids to schools of fish and flocks of birds. The theoretical framework describing these systems has shown tremendous success in finding universal phenomenology. However, further progress is often burdened by the difficulty of determining forces controlling the dynamics of individual elements within each system. Accessing this local information is pivotal for the understanding of the physics governing an ensemble of active particles and for the creation of numerical models capable of explaining the observed collective phenomena. In this work, we present ActiveNet, a machine-learning tool consisting of a graph neural network that uses the collective motion of particles to learn active and two-body forces controlling their individual dynamics. We verify our approach using numerical simulations of active Brownian particles, active particles undergoing underdamped Langevin dynamics, and chiral active Brownian particles considering different interaction potentials and values of activity. Interestingly, ActiveNet can equally learn conservative or nonconservative forces as well as torques. Moreover, ActiveNet has proven to be a useful tool to learn the stochastic contribution to the forces, enabling the estimation of the diffusion coefficients. Therefore, all coefficients of the equationof motion of Active Brownian Particles are captured. Finally, we apply ActiveNet to experiments of electrophoretic Janus particles, extracting the active and two-body forces controlling colloids' dynamics. On the one side, we have learned that the active force depends on the electric field and area fraction. On the other side, we have also discovered a dependence of the two-body interaction with the electric field that leads us to propose that the dominant force between active colloids is a screened electrostatic interaction with a constant length scale. We believe that the proposed methodological tool, ActiveNet, might open a new avenue for the study and modeling of experimental suspensions of active particles.

Caustic formation in a non-Gaussian model for turbulent aerosols

Caustics in the dynamics of heavy particles in turbulence accelerate particle collisions. The rate J at which these singularities form depends sensitively on the Stokes number St, the nondimensional inertia parameter. Exact results for this sensitive dependence have been obtained using Gaussian statistical models for turbulent aerosols. However, direct numerical simulations of heavy particles in turbulence yield much larger caustic-formation rates than predicted by the Gaussian theory. To understand the possible mechanisms explaining this difference, we analyze a non-Gaussian statistical model for caustic formation in the limit of small St. We show that at small St, J depends sensitively on the tails of the distribution of Lagrangian fluid-velocity gradients. This explains why different authors obtained different St-dependencies of J in numerical-simulation studies. The most likely gradient fluctuation that induces caustics at small St, by contrast, is the same in the non-Gaussian and Gaussian models. Direct numerical simulation results for particles in turbulence show that the optimal fluctuation is similar, but not identical, to that obtained by the model calculations. Published by the American Physical Society 2024

Comparative analysis of internal flow characteristics and particle trajectories of centrifugal pumps with different impeller structures under solid-liquid two-phase flow conditions

The disc pump is a non-conventional centrifugal pump that utilizes centrifugal force and boundary layer effects to transport fluids. This pump is widely used in industries such as petrochemicals. However, due to the presence of particles in the solid-liquid two-phase flow, it causes wear and performance degradation of the pump’s flow components. However, due to the presence of particles in the solid-liquid two-phase flow, it can cause wear and performance degradation of the pump components. To study the internal flow characteristics of solid-liquid flow and the particle trajectory in a bladed disc pump, numerical simulation method was adopted to perform steady-state numerical simulation of spherical particles with different diameters (0.1 mm, 0.25 mm, 0.4 mm) in the bladed disc pump. The results indicate that compared to conventional centrifugal pumps, the performance of the bladed disc pump is lower. The variation in particle diameter has a minor influence on the intensity of the internal flow field in the bladed disc pump. The particle trajectories inside the impeller of the bladed disc pump are more chaotic, with larger diameter particles exhibiting a wider range of trajectory variations, while smaller diameter particles maintain relatively stable motion trajectories.

Numerical simulation of particles beneath a towed circular cylinder

This study investigates particle dynamics around a towed circular cylinder near a wall. The flow field obtained from a numerical model based on the Reynolds-Average Navier–Stokes equations is utilized to estimate the particle trajectories computed using a Lagrangian approach. The simulated flow resembles a towed fishing gear and the particles which represent sea stars, muscles, and sediments are seeded at the seabed. The ejection of particles from the seabed is related to the upward flow induced by lee-wake vortex shedding. The effect of the gap between the cylinder and the seabed is investigated, where an increased distance leads to fewer ejected particles and distinct trajectories. Furthermore, for the same relative distance to the seabed, a larger diameter cylinder, and hence a different relative initial position and Reynolds number, leads to fewer ejected particles. The optimal position of the fishing net of a towed fishing gear relative to the cylinder is investigated based on the trajectories.

Modeling Linear Polarization of the Didymos–Dimorphos System before and after the DART Impact

We analyze the polarization observations of the Didymos–Dimorphos system before and after the impact by the NASA Double Asteroid Redirection Test spacecraft on Dimorphos. We fit empirical polarization phase curve models and statistically confirm the discovery by Gray et al. about the degree of linear polarization of the system decreasing on the impact and remaining altered for at least 30 days post-impact. With numerical simulations of particles in the geometric optics domain, we estimate the dominant size of the particles either in the regolith of Didymos and Dimorphos or in the impact-driven ejecta cloud to be several hundred micrometers. The observed change between the pre-impact and post-impact systems indicates either a decrease in average particle size of some tens of micrometers or a decreased level of space weathering.

Avalanche properties at the yielding transition: from externally deformed glasses to active systems.

We investigated the yielding phenomenon in the quasistatic limit using numerical simulations of soft particles. Two different deformation scenarios, simple shear (passive) and self-random force (active), and two interaction potentials were used. Our approach reveals that the exponents describing the avalanche distribution are universal within the margin of error, showing consistency between the passive and active systems. This indicates that any differences observed in the flow curves may have resulted from a dynamic effect on the avalanche propagation mechanism. The evolution time required to reach a steady state differs significantly between active and passive scenarios under similar conditions. However, we demonstrated that plastic avalanches under athermal quasistatic simulation dynamics display a similar scaling relationship between avalanche size and relaxation time, which cannot explain the different flow curves.

Numerical investigation of multi‐particle interactions using the discrete element method

AbstractThe numerical simulation of particles that can be used as crash absorbers, for example, in ship collisions, is of high interest, as experimental investigation is often associated with high costs. After extensive studies on the breakage of single‐particles, the focus is now on the investigation of multi‐particle simulation. Although many parameter studies have been carried out for single‐particle compression tests, their results cannot be transferred to multi‐particle compression tests. The influence of various simulation parameters differs greatly between single and multiple particles due to the interaction between individual granules. Therefore, it is necessary to repeat the parameter studies with respect to these interactions in order to gain a better insight into the bulk behaviour of granular materials, which can then be used for the simulation of particle‐enhanced collisions.

Numerical simulation of particle and bubble detachment process in turbulent flow environment using CFD-DEM

Three-dimensional discrete element method (DEM) models were developed to simulate particle-bubble interactions by utilizing the API function within the EDEM software platform. Geometric grids were constructed using FLUENT software to induce isotropic turbulence, and this turbulence environment was incorporated into the CFD-DEM framework. The simulations focused on the detachment of particles and bubbles, with particle sizes ranging from 0.10 to 0.30 mm, particle densities ranging from 1500 to 2500 kg/m³, and fixed bubble sizes of 1.00, 1.20, 1.60, and 2.00 mm. The detachment processes occurred within a turbulent flow field at distances of 1, 1.5, 2, and 3 mm from the grid. It is found that the particle-bubble bond required more capillary force to maintain attachment equilibrium as the particle density and size, bubble size, and flow field turbulence environment increased, the smaller the initial flow velocity to bring the bubble and particle to a critical desorption state, indicating the increase in all these factors were not conducive to attachment stability.

Particle-resolved direct numerical simulation of particle-laden turbulence modulation with high Stokes number monodisperse spheres

Graphic processing units (GPU)-accelerated direct numerical simulations of particle–fluid systems based on lattice Boltzmann method combined with discrete element method are successfully performed. This method is validated to be accurate and efficient in the four-way coupling simulation of particle–fluid systems. Particle-laden homogeneous isotropic turbulence under particle size dp=30.1η (the Kolmogorov length scale), a wide range of solid volume fraction ϕV=2%−20% and particle Stokes number St=503.87−50 387 are systematically studied. The additional energy dissipation rate εaddi induced by particles is quantitatively calculated. One criterion for turbulence enhancement or attenuation based on energy balance is proposed and successfully used in different particle-laden turbulence. The relative magnitude of two-way coupling rate ψ and particle-induced dissipation εaddi is the direct factor determining the modulation effect on turbulence. Turbulence laden with high Stokes number particles is enhanced. Turbulence laden with high volume fraction particles transited rapidly from enhancement to attenuation, which is attributed to the more rapid decay of ψ relative to εaddi in the freely decaying turbulence.

Predictive modeling of mixing time for super-ellipsoid particles in a four-bladed mixer: A DEM-based approach

Numerical simulations of super-ellipsoid particles in a four-bladed mixer using the discrete element method is presented. The effect of number of particles, blade rake angle and impeller rotation speed, on the performance of the mixer was examined. Mixing mechanism and flow pattern of particles were studied through velocity profiles, particle trajectories and granular temperature. It was found that the spherical particles mix faster than the prolate and the oblate particles. In case of using acute blade rake angles, the mixing is slower than obtuse angle. It was found that the granular temperature is higher in the vicinity of the wall for all particle shapes. The spherical particles have the highest granular temperature than the prolate and the oblate particles, which have same granular temperatures. To predict the mixing time, regression models were employed. The voting regressor model was shown to be successful at predicting the mixing time.

Thermodynamics of fermions at any temperature based on parametrized partition function.

In this work, we study the recently developed parametrized partition function formulation and show how we can infer the thermodynamic properties of fermions based on numerical simulation of bosons and distinguishable particles at various temperatures. In particular, we show that in the three-dimensional space defined by energy, temperature, and the parameter characterizing parametrized partition function, we can map the energies of bosons and distinguishable particles to fermionic energies through constant-energy contours. We apply this idea to both noninteracting and interacting Fermi systems and show it is possible to infer the fermionic energies at all temperatures, thus providing a practical and efficient approach to obtain thermodynamic properties of Fermi systems with numerical simulation. As an example, we present energies and heat capacities for 10 noninteracting fermions and 10 interacting fermions and show good agreement with the analytical result for the noninteracting case.

On the clustering of low-aspect-ratio oblate spheroids settling in ambient fluid

We have performed particle-resolved direct numerical simulations of many heavy non-spherical particles settling under gravity in the dilute regime. The particles are oblate spheroids of aspect ratio $1.5$ and density ratio $1.5$ . Two Galileo numbers are considered, namely $111$ and $152$ , for which a single oblate spheroid follows a steady vertical and a steady oblique path, respectively. In both cases, a strongly inhomogeneous spatial distribution of the disperse phase in the form of columnar clusters is observed, with a significantly enhanced average settling velocity as a consequence. Thus, in contrast to previous results for spheres, the qualitative difference in the single-particle regime does not result in a qualitatively different behaviour of the many-particle cases. In addition, we have carried out an analysis of pairwise interactions of particles in the well-known drafting–kissing–tumbling set-up, for oblate spheroids of aspect ratio $1.5$ and for spheres. We have varied systematically the relative initial position between the particle pair and we have considered free-to-rotate particles and rotationally locked ones. We have found that the region of attraction for both particle shapes, with and without rotation, is very similar. However, significant differences occur during the drafting and tumbling phases. In particular, free-to-rotate spheres present longer drafting phases and separate quickly after the collision. Spheroids remain close to each other for longer times after the collision, and free-to-rotate ones experience two or more collision events. Therefore, we have observed a shape-induced increase in the interaction time which might explain the increased tendency to cluster of the many-particle cases.

Research on particle swarm screening mechanism and performance optimization based on simulated lunar microgravity

The research on particle size classification in lunar microgravity has gradually attracted the attention of scholars. Based on the discrete element method (DEM), this work proposes a double-layer auxiliary screening vibrating screen in the form of intermediate feeding, and takes the screening efficiency and screening time as the evaluation indicators. Firstly, the Helmholtz-Maxwell coil is used to simulate the force of particles under lunar microgravity, which verifies the reliability of the numerical simulation of particles under lunar microgravity based on the discrete element method. Then, the influence of the parameters of each screen on the comprehensive performance of screening was analyzed by a single-factor experiment. Finally, based on the BP (Back Propagation) neural network optimized by genetic algorithm, the evaluation model of screen parameters and screen performance is established, and the multi-objective genetic algorithm is used to optimize the screen parameters combination scheme with excellent performance. An efficient comprehensive model of screening is provided to improve the screening performance and the design of the screen machine under lunar microgravity.

Simulation and Validation of Discrete Element Parameter Calibration for Fine-Grained Iron Tailings

In order to improve the calculation efficiency of a discrete element EDEM (Discrete Element Method) numerical simulation software for micron particles, the particle model is linearly enlarged. At the same time, the parameters of the amplified particles were calibrated according to the Hertz-Mindlin with JKR (Johnson-Kendall-Roberts) contact model to make the amplified particles have the same particle flow characteristics as the actual particles. Actual tests were utilized to gather the angle of repose of the microfine iron tailings, which was then used as a reference value for response surface studies based on the JKR contact model from six factors connected to the fine iron tailings particles. The Plackett-Burman test was used to identify three parameters that had a significant effect on the rest angle: static friction factor; rolling friction factor; and JKR surface energy. The Box-Behnken experiment was used to establish a second-order regression model of the rest angle, and the significant parameters and the optimized parameters were: surface energy JKR coefficient 0.459; particle-particle static friction coefficient 0.393; and particle-particle dynamic friction coefficient 0.393, with a dynamic friction coefficient between particles of 0.106. By entering the parameters into the discrete element program, the angle of repose generated from the simulations was compared with the real test values, and the error was 1.56%. The contact parameters obtained can be used in the discrete element simulation of the amplified particles of fine-grained iron tailings, providing an EDEM model reference for the numerical simulation of fine-grained iron tailings particles. There is no discernible difference between the actual and simulated angles.

Scanning Horn Simulation Code for Electron Beam Machine Based on Boris Algorithm

A numerical particle simulation code package to estimate the irradiation distribution of an electron beam machine is presented. Particle-to-particle interactions are calculated using particle-in-cell method, while the equation of motion is solved using Boris algorithm. The amplitude of oscillating magnetic field distribution from the scanning horn is obtained using CST magnetic field solver. The code was run using Intel’s i7-10700 processor without multithreading. For cases where particle-to-particle interactions are negligible, the simulation requires about 10 000 seconds to finish. The results show that different shapes of signals will result in different irradiation distributions. For a relatively low magnetic oscillation frequency, it is shown that a triangular signal will result in a more evenly distributed irradiation compared to a sinusoidal signal. Normal 0 false false false EN-ID JA AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman",serif; mso-fareast-language:EN-US;}

Lagrangian Numerical Simulation of Proppant Transport in Channel Fracturing

This paper focuses on the numerical simulation of particle (“proppant”) transport in channel fracturing, in which fiber-proppant fluid is pumped intermittently into hydraulic fractures, alternated with clean fluid pulses. The pulsed pumping protocol leads to heterogeneous/channelized proppant distribution in fractures, generating open flow channels with high conductivity. To understand the evolution of the channelized proppant distribution, we develop an efficient pseudo-3D multiphase particle-in-cell (P3D MP-PIC) method to simulate the proppant transport during the pumping process. Compared with the Eulerian-Eulerian (EE) models, the MP-PIC approach has higher accuracy in modeling particle-fluid and particle-particle interactions by tracing the particles in a Lagrangian fashion. Compared with the computational fluid dynamics-discrete element method (CFD-DEM), the MP-PIC method is more computationally efficient due to a parcel feature and the fast calculation of particle forces. Reduced from the 3D MP-PIC method, the P3D MP-PIC method has better computational efficiency and flexibility to couple with other subsurface processes (e.g., fracture propagation and fluid leakoff) while also achieving sufficient accuracy for engineering purposes. Due to the Eulerian-Lagrangian (EL) nature, the P3D MP-PIC method can track the trajectories of the fiber-proppant clusters whose effective viscosity and the settling velocity are determined based on the laboratory results. With an accurate description of fluid and particle dynamics, this work reveals the critical physical mechanisms of the proppant transport in channel fracturing: stable displacement and Saffman-Taylor (ST) instability. The alternate occurrence of these two mechanisms gives rise to the channelized proppant distribution. To investigate the influential factors of the channel patterns, we conduct parametric studies on the operational parameters, including injection rate, fiber concentration, and pulsing mode. The effect of fracture propagation and gravitational settling is also discussed in detail.

Neutral Beams for Neutron Generation in Fusion Neutron Sources

Neutral beam injection is supposed to be the main source of high-energy particles, driving non-inductive current and generating primary neutrons in fusion neutron sources design based on tokamaks. Numerical simulation of high-energy particles’ thermalization in plasma and fusion neutron emission is calculated by novel dedicated software (NESTOR code). The neutral beam is reproduced statistically by up to 109 injected particles. The beam efficiency and contribution to primary neutron generation is shown to be dependent on the injection energy, input current, and plasma temperature profile. A beam-driven plasma operation scenario, specific for FNS design, enables the fusion rate and neutron generation in plasma volume to be controlled by the beam parameters; the resultant primary neutron yield can be efficiently boosted in plasma maintained at a relatively low temperature when compared to ‘pure’ fusion reactors. NESTOR results are applicable to high-precision nuclear and power balance estimations, neutron power loads distribution among tokamak components, tritium generation in hybrid reactors, and for many other tasks critical for FNS design.

Particle‐resolved simulations of four‐way coupled, polydispersed, particle‐laden flows

AbstractWe present a collocated‐grid framework for direct numerical simulations of polydisperse particles submerged in a viscous fluid. The fluid‐particle forces are coupled with the immersed boundary method (IBM) while the particle‐particle forces are modeled with a combination of contact and lubrication models, adapted for collocated grids. Our method is modified from the staggered‐grid IBM of previous authors to a collocated‐grid IBM by adapting the fluid and particle solvers. The method scales well on high‐performance parallel computing platforms. It has been validated against various cases and is able to reproduce experimental results. Tuning parameters have been thoroughly calibrated to ensure the accuracy of the method. Finally, we demonstrate the capability of the method to simulate both monodispersed and bidispersed fluidized beds and reproduce the power law relationship between the inflow velocity and the porosity.

Numerical simulations of polygonal particles settling within non-Newtonian fluids

The settling of circular and polygonal particles within non-Newtonian fluids is investigated by combining the lattice Boltzmann method (LBM) and the discrete element method (DEM). The immersed moving boundary (IMB) scheme with good numerical stability is adopted to couple LBM and DEM. To efficiently calculate the solid coverage ratio in IMB, a novel method is developed, which simply involves judging whether the square is fully occupied by the particle and subdividing the square crossed by the fluid–solid boundary. After validations, the drafting–kissing–tumbling dynamics of two particles settling in the Newtonian and power-law fluids are studied first. It shows that the shear-thickening fluid has a longer kissing duration than the Newtonian and shear-thinning fluids. The kissing duration of squared particles (0.29–0.41 s) is shorter than triangular particles (0.32–0.84 s) and much shorter than circular particles (0.61–0.98 s). Then, the settling of multiple and multi-shape particles in a closed cavity is analyzed. The disturbed area of kinematic viscosity induced by particle motion in the shear-thinning fluid is 21.0–22.5 cm2, significantly larger than in the shear-thickening fluid (10.1–10.8 cm2). Circular particles have a larger disturbed area than the polygonal particles due to the larger settling velocity. Moreover, compared with the Newtonian and shear-thinning fluids, the shear-thickening fluid has a smaller vertical length of particle cluster, meaning a positive influence on the agglomeration of particles.