González Niño, C, Kapur, N orcid.org/0000-0003-1041-8390, King, M-F orcid.org/0000-0001-7010-476X et al. (4 more authors) (2019) Computational fluid dynamic enabled design optimisation of miniaturised continuous oscillatory baffled reactors in chemical processing. International Journal of Computational Fluid Dynamics, 33 (6-7). pp. 317-331. ISSN 1061-8562
Abstract
The first CFD-enabled multi-objective design optimisation methodology for continuous oscillatory baffled reactors (COBRs), used for flow chemistry-based process development, is described, where performance is quantified in terms of two metrics: a mixing efficiency index and the variance of the residence time distribution. The effect of cross-validation approaches on the surrogate modelling of these performance metrics is examined in detail and the resultant surrogate models used to demonstrate the influence of key design variables. Pareto fronts of non-dominated solutions are presented to illustrate the available design compromises for COBR performance and it is shown that these can give a narrow Residence Time Distribution and good mixing within the final design. The novel feature of offset baffles within a channel, explored here for the first time, is identified as a key parameter in improving the performance of COBRs.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Informa UK Limited, trading as Taylor & Francis Group. This is an author produced version of an article published in International Journal of Computational Fluid Dynamics . Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Continuous oscillatory baffled reactor; surrogate modelling; multi-objective optimisation; machine learning |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemistry (Leeds) > Organic Chemistry (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Thermofluids, Surfaces & Interfaces (iETSI) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Oct 2019 14:49 |
Last Modified: | 30 Oct 2020 01:39 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/10618562.2019.1683169 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:152860 |