Computational fluid dynamic enabled design optimisation of miniaturised continuous oscillatory baffled reactors in chemical processing

González Niño, C, Kapur, N orcid.org/0000-0003-1041-8390, King, M-F 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. pp. 1-15. ISSN 1061-8562

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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:
  • Accepted: 22 September 2019
  • Published (online): 30 October 2019
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Chemical & Process Engineering (Leeds)
The University of Leeds > Faculty of Engineering (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: 14 Nov 2019 16:58
Status: Published online
Publisher: Taylor & Francis
Identification Number: https://doi.org/10.1080/10618562.2019.1683169

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