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Title: | A modelling workflow for quantification of photobioreactor performance |
Authors: | Gu, W Theau, E Anderson, AW Fletcher, DF Kavanagh, JM McClure, DD |
Keywords: | photobioreactor;scale-up;CFD;microalgae;Particle tracking |
Issue Date: | 31-Oct-2023 |
Publisher: | Elsevier |
Citation: | Gu, W. et al. (2023) 'A modelling workflow for quantification of photobioreactor performance', Chemical Engineering Journal, 0 (in press, pre-proof), 147032, pp. 1 - 35. doi: 10.1016/j.cej.2023.147032. |
Abstract: | Copyright © 2023 The Authors. In this work we have developed a comprehensive modelling workflow for the quantification of photobioreactor performance. Computational Fluid Dynamics (CFD) modelling combined with Lagrangian particle tracking was used to characterise the flow field inside the reactor; this information was combined with a Monte-Carlo model of light attenuation and a kinetic growth model to predict the performance of the system over the duration of the entire batch. The CFD model was validated against measurements of the overall hold-up, local hold-up and mixing time for superficial velocities between 0.6 and 6 cm s−1 in a pilot-scale bubble column photobioreactor, with the CFD predictions agreeing with the experimental data. Comparison was also made between the predicted biomass concentration and experimental measurements using the diatom Phaeodactylum tricornutum, with the model predictions being in good agreement with the experimental results. The model was used to investigate a range of operating conditions and reactor designs, with the most promising predicted to give a 40 % increase in the biomass productivity. Results from this work can be used for the in-silico design and optimisation of photobioreactor systems, thereby enabling their wider use as a sustainable production technology. |
Description: | Data availability: Data has been uploaded to the Brunel figshare repository: https://doi.org/10.17633/rd.brunel.23905842 Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S1385894723057637?via%3Dihub#s0065 . |
URI: | https://bura.brunel.ac.uk/handle/2438/27510 |
DOI: | https://doi.org/10.1016/j.cej.2023.147032 |
ISSN: | 1385-8947 |
Other Identifiers: | ORCID iD: Dale D. McClure https://orcid.org/0000-0001-6790-5179 147032 |
Appears in Collections: | Dept of Chemical Engineering Research Papers |
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File | Description | Size | Format | |
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FullText.pdf | Copyright © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/). | 3.97 MB | Adobe PDF | View/Open |
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