Zhang, G., Ma, L. orcid.org/0000-0002-3731-8464 and Pourkashanian, M. (2023) A porous medium approach to the 3D modelling of an entire rotating packed bed for post-combustion carbon capture. Chemical Engineering Science, 274. 118687. ISSN 0009-2509
Abstract
Rotating packed bed (RPB) technology shows great potential for post-combustion capture. However, the capture process inside the full RPB is difficult to simulate, due to the complexity of the process and the neglect of the CO2 capture in the outer cavity zone. In this paper, a full 3D CFD model, including the packing and the inner and outer cavity zones, has been established employing the Eulerian porous medium method coupled with various sub-models. The CO2 capture performance in the packing and outer cavity zones has been quantitatively analyzed under different operating conditions. The simulation results show good agreement with the experimental data, and the contribution of the outer cavity zone to the CO2 capture of the RPB is in the range of 28 %∼42 %. This work provides a new approach to efficiently simulate the mass transfer process in the RPB.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 Elsevier. This is an author produced version of a paper subsequently published in Chemical Engineering Science. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Rotating packed bed; Eulerian method; 3D porous media model; CO2 absorption; Outer cavity zone |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/P026214/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 12 Apr 2023 08:28 |
Last Modified: | 27 Mar 2024 01:13 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.ces.2023.118687 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:198130 |