Cluster patterns in circulating fluidized beds predicted by numerical simulation (discrete particle model versus two-fluid model)

Mathematical Modeling and Design of Parboiled Paddy-Impinging Stream Dryer Using the CFD-DEM Model

Impinging stream dryers (ISDs) are effective for removing moisture from particulate materials because of the complex multiphase transport of air particles in ISDs. Nowadays, computational techniques are powerful to simulate multiphase flows, including dilute and dense-phase gas-solid flows and hence, the use of a reliable computational model to simulate the phenomena and design a dryer has recently received more attention. In this study, computational fluid dynamics, combined with the discrete element method (CFD-DEM) and falling drying rate model, were used to predict the multiphase transport phenomena of parboiled paddy in a coaxial ISD. The design of an impinging stream pattern for improving residence time in a drying chamber of ISD was also investigated. The results showed that the CFD-DEM, in combination with the falling drying model, could be well-utilized to predict the particle motion behavior and lead to more physically realistic results. The predicted change of moisture content in parboiled paddy was in good agreement with the experimental data for 17 cycles of drying. Although the prediction of mean residence time was lower than the experimental data, the predicted mean residence time was a similar trend to the experimental data. For ISD design, the simulation revealed that the use of two stages of impinging stream region (two streams collide at the top of the drying chamber at the first stage and then the gas particles flow on the incline floor to collide with the other stream at second stage) in a drying chamber could increase the residence time approximately 75% and reduce drying cycle from 17 to 10 cycles when it was considered at the same final moisture content.

CFD-DEM Evaluation of the Clustering Behavior in a Riser-the Effect of the Drag Force Model

Riser reactors are frequently applied in catalytic processes involving rapid catalyst deactivation. Typically heterogeneous flow structures prevail because of the clustering of particles, which impacts the quality of the gas-solid contact. This phenomenon results as a competition between fluid-particle interaction (i.e., drag) and particle-particle interaction (i.e., collisions). In this study, five drag force correlations were used in a combined computational fluid dynamics-discrete element method Immersed Boundary Model to predict the clustering. The simulation results were compared with experimental data obtained from a pseudo-2D riser in the fast fluidization regime. The clusters were detected on the basis of a core-wake approach using constant thresholds. Although good predictions for the global (solids volume fraction and mass flux) variables and cluster (spatial distribution, size, and number of clusters) variables were obtained with two of the approaches in most of the simulations, all the correlations show significant deviations in the onset of a pneumatic transport regime. However, the correlations of Felice (Int. J. Multiphase Flow1994, 20, 153-159) and Tang et al. [AIChE J.2015, 61 ( (2), ), 688-698] show the closest correspondence for the time-averaged quantities and the clustering behavior in the fast fluidization regime.

Magnetic excitation of a granular gas as a bulk thermostat

A thermostat utilizing a varying magnetic field has been developed to agitate soft ferromagnetic particles in microgravity platforms for an investigation of an energy-dissipative granular gas. Although the method has experimentally realized a reasonably homogeneous spatial distribution of particles, the physics behind the magnetically excited particles has not been understood. Therefore, a numerical calculation based on the discrete element method is developed in this paper to explain the realization of homogeneously distributed particles. The calculation method allows considering inelastic and magnetic interactions between particles and tracking the motions due to those interactions during the excitation of the granular gas. The calculation results, compared with the experimental result, show that magnetic interactions between particles, a time-domain variation of magnetic-excitation directions, and random collisions of particles between each magnetic excitation contribute to distribute particles homogeneously.

Numerical simulation of particle migration from crushed sandstones during groundwater inrush

Groundwater inrush through fault fracture zones is caused by small particle migration from fractured rocks of the faults. To investigate particle migration with the water flow, a 3D model was established for the solid-water two-phase flow. First, the simulated crushed sandstone was represented by certain different-sized particles with a novel cohesive force. The discrete element method (DEM) was applied for particles considering the cohesive force, the collisions, the friction, and other conventional forces. Second, the process of particle migrating from the crushed sandstone was simulated under multiple effects accompanied by some experiments. The results indicate that the migration characteristics vary with different-sized particles, and the mass loss for different-sized particles are high at the beginning leading to stabilized conditions at different times. It can be also found that the total mass loss rate and the final mass loss all increase with the increases of initial water velocity, while the final mass loss decrease with the increases of the axial force. Moreover, selected stimulation results were compared with the experimental results and the previous simulated results, and reasonable agreements could be obtained, which would provide consults for particle migration during groundwater inrush through fault fracture zones in underground engineering.

Numerical Simulation of Particulate Matter 2.5 Distribution in a Roadway

Large amounts of dust particles pose serious hazards to the health and safety of China’s coal miners during roadway blasting processes. It is known that among these dust particles, Particulate Matter 2.5 (PM_2.5) does the greatest amount of harm. In order to study the distributions of the PM_2.5 in roadway blasting processes, a mathematical model of the gas-solid two-phase flow was established in this study, which was based on a Direct Simulation Monte Carlo Method (DSMC). Then, a multiphase flow program was developed. This study’s results indicated that following the blasting processes, fine dust particles gradually floated up and were suspended for long durations in the underground roadway space. The medium-sized dust particles slowly sink to the ground and were eventually expelled before settling to the floor of the roadway. The coarse particles were rapidly settled to the roadway floor. It was determined that the PM_2.5 particles in the front end of the dust group could not be quickly diluted, and the concentrations were high until it is expelled from the roadway, whereas the PM_2.5 dust particles in the back end of the underground roadway were found to be gradually diluted. Eventually, the PM_2.5 concentrations exhibited an alternating thin to dense phase distribution. When compared with the Particulate Matter 5 (PM₅), it was found that the PM_2.5 was more difficult to discharge, and easily formed serious PM_2.5 dust air pollution. This study’s results were determined to be conductive to the future control of PM_2.5 in the underground roadway blasting processes.

The Sustainable Characteristic of Bio-Bi-Phase Flow of Peristaltic Transport of MHD Jeffrey Fluid in the Human Body

This study deals with the peristaltic transport of non-Newtonian Jeffrey fluid with uniformly distributed identical rigid particles in a rectangular duct. The effects of a magnetohydrodynamics bio-bi-phase flow are taken into account. The governing equations for mass and momentum are simplified using the fact that wavelength is much greater than the amplitude and small Reynolds number. A closed-form solution for velocity is obtained by means of the eigenfunction expansion method whereby pressure rise is numerically calculated. The results are graphically presented to observe the effects of different physical parameters and the suitability of the method. The results for hydrodynamic, Newtonian fluid, and single-phase problems can be respectively obtained by taking the Hartmann number (M = 0), relaxation time (λ1=0), and volume fraction (C = 0) as special cases of this problem.

Modelling the Multiphase Flow in Dense Medium Cyclones

Dense medium cyclone (DMC) is widely used in mineral industry to separate solids by density. It is simple in design but the flow pattern within it is complex due to the size and density distributions of the feed and process medium solids, and the turbulent vortex formed. Recently, the so-called combined computational fluid dynamics (CFD) and discrete element method (DEM) (CFD-DEM) was extended from two-phase flow to model the flow in DMCs at the University of New South Wales (UNSW). In the CFD-DEM model, the flow of coal particles is modelled by DEM and that of medium flow by CFD, allowing consideration of medium-coal mutual interaction and particle-particle collisions. In the DEM model, Newton's laws of motion are applied to individual particles, and in the CFD model the local-averaged Navier-Stokes equations combined with the volume of fluid (VOF) and mixture multiphase flow models are solved. The application to the DMC studies requires intensive computational effort. Therefore, various simplified versions have been proposed, corresponding to the approaches such as Lagrangian particle tracking (LPT) method where dilute phase flow is assumed so that the interaction between particles can be ignored, one-way coupling where the effect of particle flow on fluid flow is ignored, and the use of the concept of parcel particles whose properties are empirically determined. In this paper, the previous works on the modelling of DMCs at UNSW are summarized and the features and applicability of the models used are discussed.