Computational Fluid Dynamics Simulations of Gas-Phase Radial Dispersion in Fixed Beds with Wall Effects

The effective medium approach to radial fixed bed dispersion models, in which radial dispersion of mass is superimposed on axial plug flow, is based on a constant effective dispersion coefficient, DT. For packed beds of a small tube-to-particle diameter ratio (N), the experimentally-observed decreas...

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Main Authors: Anthony G. Dixon, Nicholas J. Medeiros
Format: Article
Language:English
Published: MDPI AG 2017-10-01
Series:Fluids
Subjects:
Online Access:https://www.mdpi.com/2311-5521/2/4/56
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spelling doaj-388ebe6102e440c283bd06dddc06e6c72020-11-25T01:49:57ZengMDPI AGFluids2311-55212017-10-01245610.3390/fluids2040056fluids2040056Computational Fluid Dynamics Simulations of Gas-Phase Radial Dispersion in Fixed Beds with Wall EffectsAnthony G. Dixon0Nicholas J. Medeiros1Department of Chemical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USADepartment of Chemical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USAThe effective medium approach to radial fixed bed dispersion models, in which radial dispersion of mass is superimposed on axial plug flow, is based on a constant effective dispersion coefficient, DT. For packed beds of a small tube-to-particle diameter ratio (N), the experimentally-observed decrease in this parameter near the tube wall is accounted for by a lumped resistance located at the tube wall, the wall mass transfer coefficient km. This work presents validated computational fluid dynamics (CFD) simulations to obtain detailed radial velocity and concentration profiles for eight different computer-generated packed tubes of spheres in the range 5.04 ≤ N ≤ 9.3 and over a range of flow rates 87 ≤ Re ≤ 870 where Re is based on superficial velocity and the particle diameter dp. Initial runs with pure air gave axial velocity profiles vz(r) averaged over the length of the packing. Then, simulations with the tube wall coated with methane yielded radial concentration profiles. A model with only DT could not describe the radial concentration profiles. The two-parameter model with DT and km agreed better with the bed-center concentration profiles, but not with the sharp decreases in concentration close to the tube wall. A three-parameter model based on classical two-layer mixing length theory, with a wall-function for the decrease in transverse radial convective transport in the near-wall region, showed greatly improved ability to reproduce the near-wall concentration profiles.https://www.mdpi.com/2311-5521/2/4/56computational fluid dynamicsfixed bedmass transfertransverse dispersion
collection DOAJ
language English
format Article
sources DOAJ
author Anthony G. Dixon
Nicholas J. Medeiros
spellingShingle Anthony G. Dixon
Nicholas J. Medeiros
Computational Fluid Dynamics Simulations of Gas-Phase Radial Dispersion in Fixed Beds with Wall Effects
Fluids
computational fluid dynamics
fixed bed
mass transfer
transverse dispersion
author_facet Anthony G. Dixon
Nicholas J. Medeiros
author_sort Anthony G. Dixon
title Computational Fluid Dynamics Simulations of Gas-Phase Radial Dispersion in Fixed Beds with Wall Effects
title_short Computational Fluid Dynamics Simulations of Gas-Phase Radial Dispersion in Fixed Beds with Wall Effects
title_full Computational Fluid Dynamics Simulations of Gas-Phase Radial Dispersion in Fixed Beds with Wall Effects
title_fullStr Computational Fluid Dynamics Simulations of Gas-Phase Radial Dispersion in Fixed Beds with Wall Effects
title_full_unstemmed Computational Fluid Dynamics Simulations of Gas-Phase Radial Dispersion in Fixed Beds with Wall Effects
title_sort computational fluid dynamics simulations of gas-phase radial dispersion in fixed beds with wall effects
publisher MDPI AG
series Fluids
issn 2311-5521
publishDate 2017-10-01
description The effective medium approach to radial fixed bed dispersion models, in which radial dispersion of mass is superimposed on axial plug flow, is based on a constant effective dispersion coefficient, DT. For packed beds of a small tube-to-particle diameter ratio (N), the experimentally-observed decrease in this parameter near the tube wall is accounted for by a lumped resistance located at the tube wall, the wall mass transfer coefficient km. This work presents validated computational fluid dynamics (CFD) simulations to obtain detailed radial velocity and concentration profiles for eight different computer-generated packed tubes of spheres in the range 5.04 ≤ N ≤ 9.3 and over a range of flow rates 87 ≤ Re ≤ 870 where Re is based on superficial velocity and the particle diameter dp. Initial runs with pure air gave axial velocity profiles vz(r) averaged over the length of the packing. Then, simulations with the tube wall coated with methane yielded radial concentration profiles. A model with only DT could not describe the radial concentration profiles. The two-parameter model with DT and km agreed better with the bed-center concentration profiles, but not with the sharp decreases in concentration close to the tube wall. A three-parameter model based on classical two-layer mixing length theory, with a wall-function for the decrease in transverse radial convective transport in the near-wall region, showed greatly improved ability to reproduce the near-wall concentration profiles.
topic computational fluid dynamics
fixed bed
mass transfer
transverse dispersion
url https://www.mdpi.com/2311-5521/2/4/56
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AT nicholasjmedeiros computationalfluiddynamicssimulationsofgasphaseradialdispersioninfixedbedswithwalleffects
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