(70b) Detailed Numerical Simulation of a Full-Loop Circulating Fluidized Bed Under Different Operating Conditions

Detailed
numerical simulation of a full-loop circulating fluidized bed under different
operating conditions

Yupeng Xu^1,*,
Jordan Musser¹, Tingwen Li^1,2, William A. Rogers¹

1 National Energy Technology Laboratory,
Morgantown, WV 26505, USA

2 AECOM, Morgantown, WV 26505, USA

Abstract

Circulating
fluidized beds (CFB) are widely employed in industry for a wide variety of
gas-solid contacting operations. Over the past few decades, CFB hydrodynamics
have been studied using various experimental techniques and by numerical
simulations. Recently, several efforts have modeled full-loop CFBs using the
two-fluid model (TFM) whereby gas and solids are treated as interpenetrating
continua. However, this technique only resolves solid motion at the
computational cell level. With the advancement of high-performance computing,
higher fidelity models, like Computational Fluid Dynamics-Discrete Element
Method (CFD-DEM) which tracks the trajectory of individual particles, have
become increasingly popular as research tools. This is because particle-scale
information including residence time, collision forces, and dispersion
intensities are readily available for detailed analysis of complex flow
phenomena.

In
this first of its kind work, both experimental and computational studies of a
benchtop, full-loop circulating fluidized bed are conducted. Experimental data include
pressure drops across different components, solids circulation rate measured using
Particle Image Velocimetry (PIV), and standpipe inventory height. Numerical
simulations were performed with MFIX-DEM, a coupled Computational Fluid
Dynamics-Discrete Element Method (CFD-DEM) solver. Comparison of experimental
and simulation data shows good agreement with respect to system component
pressure drops and standpipe inventory height. Additionally, the effects of
drag model selection and particle representation (mono-sized particles versus a
particle size distribution) are also reported.

Figure
1. Experimental setup and operation conditions (SLPM)

Figure 2. Direct
comparison between experiments and simulations under different operating
conditions (Left: experiments, right: simulation)