Euler multiphase‐CFD simulation on a bubble‐driven gas–liquid–solid fluidized bed

Abstract

An integrated flow model was developed to simulate the fluidization hydrodynamics in a new bubble‐driven gas–liquid–solid fluidized bed using the computational fluid dynamic (CFD) method. The results showed that axial solids holdup is affected by grid size, bubble diameter, and the interphase drag models used in the simulation. Good agreements with experimental data could be obtained by adopting the following parameters: 5 mm grid, 1.2 mm bubble diameter, the Tomiyama gas–liquid model, the Schiller–Naumann liquid–solid model, and the Gidaspow gas–solid model. At full fluidization state, an internal circulation of particles flowing upward near the wall and downward in the centre is observed, which is in the opposite direction compared with the traditional core‐annular flow structure in a gas–solid fluidized bed. The simulated results are very sensitive to bubble diameters. Using smaller bubble diameters would lead to excessive liquid bed expansions and more solid accumulated at the bottom due to a bigger gas–liquid drag force, while bigger bubble diameters would result in a higher solid bed height caused by a smaller gas–solid drag force. Considering the actual bubble distribution, population balance model (PBM) is employed to characterize the coalescence and break up of bubbles. The calculated bubble diameters grow up from 2–4 mm at the bottom to 5–10 mm at the upper section of the bed, which are comparable to those observed in experiments. The simulation results could provide valuable information for the design and optimization of this new type of fluidized system.

Three-Dimensional VOF-DEM Simulation Study of Particle Fluidization Induced by Bubbling Flow

“…Significant effort has been made to carry out CFD simulation studies of gas-liquidsolid fluidized beds. For engineering purposes, the Eulerian multi-fluid models are very popular due to the low computational effort required [6][7][8][9][10]. However, these models fall short of providing bubble-scale or particle-scale information.…”

Numerical Simulation of Liquid Flow Characteristics on a Single Spherical Particle for Trickle Bed Reactor

“…Previous studies on poor liquid distribution in the TBR have primarily relied on macroscopic indicators such as pressure drop, porosity, liquid holdup, and outlet liquid distribution. − Advances in detection technologies, such as gamma-ray tomography, electrical capacitance tomography, and magnetic resonance imaging, can make it possible to obtain detailed information on the pore structure and liquid distribution in TBR. − However, such techniques often prove costly, requiring expensive equipment and intricate experimental procedures. In recent years, computational fluid dynamics (CFD) and simulation approaches have emerged as cost-effective and convenient alternatives, gaining attraction in various fields. − Hanbin Zhong et al employed CFD to simulate the instantaneous yield of bio-oil in fluidized biomass pyrolysis, and further optimized their simulation by using long short-term memory network methods based on CFD data, thereby significantly reducing computational time . This powerful technique has also proven effective for TBR research, providing detailed information about the processes within the reactor. − Simulation approaches have been used to investigate the effects of gas and liquid feeds, particle arrangement, reactor temperature, and pressure on the liquid flow process. ,− Nonetheless, the mechanisms underlying liquid flow require further elucidation.…”

Numerical simulations and validation of gas–solid flows in a fluidized‐bed roaster based on the CFD‐DPM model

“…[23,[27][28][29][30] However, the particle continuity assumption in the method itself weakens the realism of the inhomogeneous structure of the gas-solid two-phase flow, the physical properties of the particles cannot be reflected in the calculations, and the simulation results do not reveal the complex motion processes of the particles. Previous studies have also typically focused on the application of the Euler-Euler method to air flow beds and fluidized roasting systems, [27,31] which has been successfully validated by experimental data and extended to 3D modelling. [26] In recent years, many scholars have started to experiment with the Euler-Lagrange method for particle flow solution, [22] which treats the fluid phase as a continuous phase and applies Newton's second law in the Eulerian coordinate system to track the trajectory of each discrete particle in the solved flow field to reflect the whole discrete particle field, and the continuous-phase-discretephase interaction obeys Newton's third law, with the source term added to the respective solution equation to achieve the interphase interaction coupling.…”