The hydrodynamics within counter-current flow packed beds is of vital importance to provide insight into the design and operational parameters that may impact reactor and reaction efficiencies in processes used for post combustion CO2 capture. However, the multiphase counter-current flows in random packing used in these processes are complicated to visualize. Hence, this work aimed at developing a computational fluid dynamics (CFD) model to study more precisely the complex details of flow inside a packed bed. The simulation results clearly demonstrated the development of, and changes in, liquid distributions, wetted areas, and film thickness under various gas and liquid flow rates. An increase in values of the We number led to a more uniform liquid distribution, and the flow patterns changed from droplet flow to film flow and trickle flow as the We number was increased. In contrast, an increase in gas flow rate had no significant effect on the wetted areas and liquid holdup. It was also determined that the number of liquid inlets affected flow behavior, and the liquid surface tension had an insignificant influence on pressure drop or liquid holdup; however, lower surface tension provided a larger wetted area and a thinner film. An experimental study, performed to enable comparisons between experimentally measured pressure drops and simulation-determined pressure drops, showed close correspondence and similar trends between the experimental data and the simulation data; hence, it was concluded that the simulation model was validated and could reasonably predict flow dynamics within a counter-current flow packed bed.

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Published in Energies, v. 11, issue 6, 1441, p. 1-14.

© 2018 by the authors.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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This research was funded by the Key Laboratory of Coal-based CO2 Capture and Geological Storage, Jiangsu Province (China University of Mining and Technology) (NO: 2016B05).