Hamad, HS, Kapur, N, Khatir, Z et al. (4 more authors) (2021) Computational fluid dynamics analysis and optimisation of polymerase chain reaction thermal flow systems. Applied Thermal Engineering, 183 (1). 116122. ISSN 1359-4311
Abstract
A novel Computational Fluid Dynamics-enabled multi-objective optimisation methodology for Polymerase Chain Reaction flow systems is proposed and used to explore the effect of geometry, material and flow variables on the temperature uniformity, pressure drop and heating power requirements, in a prototype three-zone thermal flow system. A conjugate heat transfer model for the three-dimensional flow and heat transfer is developed and solved numerically using COMSOL Multiphysics® and the solutions obtained demonstrate how the design variables affect each of the three performance parameters. These show that choosing a substrate with high conductivity and small thickness, together with a small channel area, generally improves the temperature uniformity in each zone, while channel area and substrate conductivity have the key influences on pressure drop and heating power respectively. The multi-objective optimisation methodology employs accurate surrogate modelling facilitated by Machine Learning via fully-connected Neural Networks to create Pareto curves which demonstrate clearly the compromises that can be struck between temperature uniformity throughout the three zones and the pressure drop and heating power required.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020, Elsevier Ltd. All rights reserved. This is an author produced version of an article published in Applied Thermal Engineering. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | PCR; Computational fluid dynamics; Machine learning; Multi-objective optimisation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | 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: | 27 Oct 2020 15:20 |
Last Modified: | 11 Oct 2021 00:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.applthermaleng.2020.116122 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:167213 |