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Abstract Filtered two-fluid model (fTFM) for gas-particle flows require closures for the sub-filter scale corrections to interphase drag force and stresses, the former being more significant. In this study, we have formulated a neural-network-based model to predict the sub-grid drift velocity, which is then used to estimate the drag correction. As a part of the neural network model development effort, we derived a transport equation for drift velocity and then performed a budget analysis to conclude that an algebraic model for drift velocity in terms of the filtered variables that are resolved in a fTFM simulation is adequate, and the model should include the filtered gas-phase pressure gradient as a marker in addition to the filtered particle volume fraction and the filtered gas-solid slip velocity. Both a priori and a posteriori analyses reveal that the present model for drift velocity when used in a fTFM simulation is able to capture the fine-grid simulation results quite well. Graphical abstract Unlabelled Image [ABSTRACT FROM AUTHOR]

Polyethylene particles were tribocharged in a glass container subjected to vertical vibration and the resulting charge per unit mass was measured. The experimental data in conjunction with discrete element method simulations coupled with a tribocharging model were used to deduce effective work function differences between the particles and the glass container at different humidity levels. In addition, we investigated the effect of different mass loadings on the particle charge, and found that the charge increased non-linearly when the mass loading was decreased. The proposed phenomenological model was found to capture this effect. Based on the estimated effective work function difference, it was predicted that a glass-walled fluidized bed of these particles would manifest vastly different hydrodynamics at 20 % and 60 % relative humidity levels. These predictions were confirmed experimentally. [ABSTRACT FROM AUTHOR]

To investigate the interplay between particle charging and hydrodynamics in fluidized beds, models for triboelectric charging and electrostatic forces were built into a computational fluid dynamics-discrete element method model. Charge transfer was governed by the difference in effective work function between contacting materials as well as the electric field at the point of contact. Monodisperse particles were fluidized with an effective work function difference between the particles and the conducting walls. For smaller work function differences, hydrodynamics were not changed significantly as compared with an uncharged case. In these simulations, the average charge saturated at a value much lower than the value anticipated based on the work function difference, and a unimodal distribution of charges was observed. For larger work function differences, particles stuck to walls and bed height oscillations due to slugging were less pronounced. For these cases, a bimodal distribution of charges emerged due to effects from strong electric fields. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1872-1891, 2017 [ABSTRACT FROM AUTHOR]

In particulate flow devices particles acquire electric charge through triboelectric charging, and resulting electrostatic forces can alter hydrodynamics. To capture this effect, the electrostatic force acting on individual particles in the device should be computed accurately. Electrostatic force is calculated using a hybrid approach consisting of: (1) long-range contributions from an Eulerian electric field solved using the Poisson equation (2) short-range contributions calculated using a truncated pairwise sum and (3) a correction to avoid double counting. Euler-Lagrange simulation of flows incorporating this hybrid approach reveals that bed height oscillations in small fluidized beds of particles with monopolar charge decreases with increasing charge level, which is related to lateral segregation of particles. A ring-like layer of particles, reported in experimental studies, forms at modestly high charge levels. Beds with equal amounts of positively and negatively charged particles are fluidized in a manner similar to uncharged particles. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2282-2295, 2016 [ABSTRACT FROM AUTHOR]

In a fluidized bed, air flow is used to fluidize solid material inside the container. Transient computations on fluidized beds are quite time consuming, and current models may fail in certain cases. One way to speed up the computations is to use steady simulations, but they require closure models, which need experimental parameters. On the other hand, particle image velocimetry (PIV) and volume fraction (VOF) measurements on industrial fluidized beds are very difficult to execute. In this study, a novel VOF computation method and a mass conservation-based least square method are proposed in order to decrease errors in the measurement. The methods performance was tested in various simulations, and experimentally in a case of a small-scale fluidized bed. The method was found to decrease error caused by noise and outliers, while the required time was of the same order as the time used in PIV computations. Our experiments on a small-scale cold model bed suggest that the proposed methods have better accuracy than the logarithmic model often used in the literature. [ABSTRACT FROM AUTHOR]