Electronic Thesis and Dissertation Repository

Degree

Master of Engineering Science

Program

Mechanical and Materials Engineering

Supervisor

Chao Zhang

2nd Supervisor

Jesse Zhu

Co-Supervisor

Abstract

The liquid-solid circulating fluidized bed (LSCFB) has many potential applications in biochemical and petroleum industries, as well as in wastewater treatments, given its higher contact efficiency and being able to accommodate two reactions under one system. With extensive experimental results becoming available, there is clearly a need for computational fluid dynamics (CFD) modeling to expand our understandings of LSCFBs and to predict the hydrodynamic behaviors of the two-phase flows within LSCFB.

In this research, the Eulerian-Eulerian two-phase model combined with the kinetic theory for the granular phase is applied to simulate the two-phase flows in LSCFBs. The key factors affecting the simulation results including the drag model, near wall treatment and boundary condition are investigated and the CFD model is validated by comparing the numerical results with the experimental data. Then, the hydrodynamics of LSCFBs under different operating conditions are investigated numerically.

Among the seven different drag models examined in this study, the adjusted Syamlal O’Brien drag model and the irregular particle drag model were found to provide the best numerical solutions for spherical and irregular particles, respectively. For the three different near wall treatments tested, the Menter-Lechner near wall treatment was found to provide the best predictions for the near wall region. It is also found that the numerical results are insensitive to the restitution and specularity coefficients, which are used in the boundary conditions for the solid phase. In addition, the proposed CFD model with the best drag model and near wall treatment is applied to simulate the two-phase flows in LSCFBs under different operating conditions, including different superficial liquid velocities, superficial solid velocities and particle densities. The numerical predictions show correct trends and good agreements with the experimental data.


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