Abstract
The present work investigates the performance of a mesoscopic LaGrangian approach for the prediction of gas–particle flows under the influence of different physical and numerical parameters. To this end, Geldart D particles with 1 mm diameter and density of 2500 kg/m 3 are simulated in a pseudo-2D fluidized bed using a Discrete Element Method (DEM)/Large-Eddy Simulation (LES) solver called YALES2. Time-averaged quantities are computed and compared with experimental results reported in the literature. A mesh sensitivity analysis showed that better predictions regarding the particulate phase are achieved when the mesh is finer. This is due to a better description of the local and instantaneous gas–particle interactions, leading to an accurate prediction of the particle dynamics. Slip and no-slip wall conditions regarding the gas phase were tested and their effect was found negligible for the simulated regimes. Additional simulations showed that increasing either the particle–particle or the particle–wall friction coefficients tends to reduce bed expansion and to initiate bubble formation. A set of friction coefficients was retained for which the predictions were in good agreement with the experiments. Simulations for other Reynolds number and bed weight conditions are then carried out and satisfactory results were obtained.
Highlights
Based on their effectiveness regarding gas-solid heat and mass transfers, fluidized beds are among the best options for developing economically and environmentally viable techniques for fossil-fuel-based energy generation
The velocities are divided by the inlet gas velocity (U f ) and the mass flowrates by the inlet gas mass flowrate
This slight improvement is attributed to a better prediction of the gas-particle interactions through the drag and the pressure gradient forces
Summary
Based on their effectiveness regarding gas-solid heat and mass transfers, fluidized beds are among the best options for developing economically and environmentally viable techniques for fossil-fuel-based energy generation. The accurate prediction of the underlying physics makes possible to improve existing processes and to design more efficient new facilities In this context, the development of reliable numerical approaches is an essential prerequisite. Discrete Element Method (DEM) is among the most appropriate meso-scale approaches to simulate small scale fluidized beds, with O(106 ) particles [2]. In this technique the particle motion is given by the Newtonian equations. Detailed models, based on averaged Navier-Stokes equations for the gas phase, DEM technique for the particles and coupling procedure between the phases are provided in Sections 2.1–2.3, respectively.
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