Particles In Gas-solid Flow Research Articles

Neural-network-based drag force model for polydisperse assemblies of irregular-shaped particles

In this study, a drag force model of irregular-shaped particles in gas-solid flows is investigated using neural network approaches. Pre-developed variational autoencoder, multi-layer perceptron model, and transpose convolutional neural-network model are utilized to obtain intermediate parameters of a pair-wise interaction point-particle (PIEP) model. These parameters are utilized to predict individual drag force coefficients of polydisperse, particulate flows. To apply the PIEP-based model to medium-concentration flows, the average drag force coefficients are obtained through an in-house particle-resolved direct numerical simulation, and a regressed model is developed to predict solid volume fraction factors. With the regression model, the PIEP-based model using the neural-network approaches shows good prediction in particulate systems from low to intermediate concentrations. This study provides computationally efficient models of practical, realistic particulate systems for large scale fluid dynamics simulation, in that it allows predicting the drag forces of polydisperse particles with a small amount of data.

Secondary Motion of Non-Spherical Particles in Gas Solid Flows

Objective of this study is to investigate the effect of secondary motion of particles in multiphase gas-solid flows parametrically and test the relative impacts of particle shape and orientation information on particle distribution. For that purpose, predictive accuracies of simplified drag coefficient models are assessed for the conditions relevant to a wood recovery plant operating at dilute flow regime. After demonstrating the strong impact of the shape and orientation information on the force balance for single particles, we compared the steady state Eulerian-Lagrangian simulation results for particle volume fractions, residence times and particle diameter distributions within the chamber for different (i) superficial gas velocities (5 m/s, 7.5 m/s), (ii) orientation tendencies and (iii) particle shapes. Transient simulations are performed until the system reaches steady state conditions by monitoring the mass flow rates of the particulate phases leaving the chamber. The secondary motion of non-spherical particles is represented by stochastic sampling from the available experimental data. Analysis of the force balance on single particles revealed log-scale variations if the orientation of the particles with respect to flow fluctuates. Variations in the single particle force balances are found to be still visible in the CFD analysis, where the secondary motion of particles drastically changed the particle distribution in the chamber. The native non-spherical model which only accounts for the shape correction was found to over-predict the entrainment, leading to a significantly different particle volume fraction and diameter distributions. Spherical particle assumption also caused significant errors in the particle distribution, which increases as aspect ratio of the cylindrical particle diverges from one. Results show that particle orientation statistics are extremely important to capture the particle mixing and segregation patterns at dilute regime, which cannot be captured with such simplifying assumptions.

Heat Transfer Studies of Arrays of Prolate Particles in Gas-Solid Flows

Numerical study of forced convection heat transfer from arrays of prolate particles is performed using the second-order Immersed Boundary-Lattice Boltzmann Method (IB-LBM). Prolate particle is studied with aspect ratio of 2.5 with solid volume fraction variation from 0.1 to 0.3. For each solid volume fraction, arrays of prolate particles are generated and simulations have been performed to calculate Nusselt number for four different Hermans orientation factors and various Reynolds numbers. From the simulation results, it has been observed that, for any specific value of Hermans orientation factor, Nusselt number increases with the increase of the Reynolds number and solid volume fraction. More importantly, it is found that the effect of orientations on Nusselt number is significant. Nusselt number correlation is developed for ellipsoidal particles as function of Reynolds number, Prandtl number, solid volume fraction, and orientation factors. This correlation is valid for 0.1 ≤ c ≤ 0.3 and 0 < Re ≤ 100 .

Local solid particle velocity measurement based on spatial filter effect of differential capacitance sensor array

This study proposes a novel velocity measurement method based on a differential capacitance sensor array (DCSA) for the solid particles in gas-solid flow. Firstly, the DCSA is modelled by the finite-element software ANSOFT, and its sensitivity characteristic is acquired. Additionally, the spatial filtering effect of DCSA is theoretically investigated, which validates the feasibility of particle velocity measurement based on DCSA. By measuring the frequency bandwidth (cut-off frequency) of the DCSA's output capacitance signal, the velocity of the local particles in the pipeline can be calculated. Further through the form of differential detection, the cut-off frequency can be accurately converged. Finally, a novel solid particle velocimeter based on DCSA is developed and tested on a gravity-delivery particle experimental device. The results indicate that the method has the feasibility for the velocity measurement and its repeatability is within 11% over the velocity range of 1–3 m/s.

Continuum prediction of entrainment rates and agglomeration of gas-fluidized, lightly-cohesive particles

In this work, a continuum theory for cohesive particles developed recently (Kellogg et al., 2017) is applied to lightly-cohesive particles in an unbounded, gas-solid riser. The novelty of this recent theory is its fundamental incorporation of the effects of the granular temperature (i.e., continuum measure of impact velocity) and the material and cohesion properties on the rates of aggregation and breakage of agglomerates. Here, we extend this theory to multiphase systems and place particular emphasis on its ability to predict entrainment rate, as past empirical correlations vary by orders of magnitude when applied to the same system (Chew et al., 2015). Specifically, continuum predictions of entrainment rates and agglomerate fraction are compared with Discrete Element Method (DEM) simulations of lightly-cohesive particles in a gas-solid flow. The agreement obtained for these quantities provides preliminary validation for the use of the continuum theory for cohesive particles in gas-solid flows.

Experimental and Eulerian-Lagrangian-Lagrangian study of binary gas-solid flow containing particles of significantly different sizes

The coexistence of large particles (such as biomass or coal particles) and fine particles in gas-solid flow is common. In this study, an Eulerian-Lagrangian-Lagrangian method (EMMS-DPM-DEM) was developed to simulate the binary gas-solid flow containing particles of significantly different sizes, where fine particles were simulated using coarse grained discrete element method and the motion of large particles was captured using discrete element method. Experiments on density segregation of large particles were also carried out to validate the developed simulation method. It was shown that EMMS-DPM-DEM can predict the density segregation process of large particles reasonably well. Furthermore, the density segregation mechanism of large particles in a dense fluidized bed was explained at different scales, i.e., the Archimedes principle at macroscale, the entrainment and the global circulation pattern due to bubble motions at mesoscale and the particle-particle and gas-particle interactions at microscale. The method proposed here can be directly used to study the hydrodynamics of biomass thermochemical conversion in fluidized beds, although it was validated using segregation experiments of coal particles.

Effect of particle clusters on mass transfer between gas and particles in gas-solid flows

Gas–solid riser flows tend to be characterized by particle clusters that significantly affect the flow, the mass/heat transfer, and the reaction behavior. To account for the effect of such particle clustering on the mass transfer between gas and particles, we use a lattice Boltzmann model with coupled mass transfer to conduct fully resolved simulations for flow past arrays of particles with both homogeneous and heterogeneous structures. We find that the distributions of velocity and concentration among the particle arrays are both affected significantly by particle clustering, and that the computed Sherwood number for either the homogeneous or heterogeneous particle structure increases exponentially with Reynolds number. However, the Sherwood number for homogeneously distributed particles is 3–5 times greater than that for heterogeneously distributed particles. This further supports the case for particle clustering having a serious effect on the mass-transfer efficiency between gas and solid in processes that involve flow past arrays of particles. Finally, the feasibility of using the lattice Boltzmann method with our mass-transfer model to describe the mass transfer in a heterogeneous two-phase gas–solid flow is also discussed.

2512 固気二相流中において粒子群が形成する空間構造(OS25.粒・粉・滴のパターン形成(2),ポスターセッションP-1)

2512 固気二相流中において粒子群が形成する空間構造(OS25.粒・粉・滴のパターン形成(2),ポスターセッションP-1)