Computational fluid dynamics analysis and optimisation of polymerase chain reaction thermal flow systems
Hamad, Hazim S. and Kapur, Nik and Khatir, Zinedine and Querin, O.M. and Thompson, Harvey M. and Wang, Yongxing and Wilson, Mark (2020) Computational fluid dynamics analysis and optimisation of polymerase chain reaction thermal flow systems. Applied Thermal Engineering, 183 (116122). ISSN 1359-4311
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Computational Fluid Dynamics Analysis and Optimisation of Polymerase Chain Reaction Thermal Flow Systems-ATE_2020_accepted.pdf - Accepted Version Download (6MB) |
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.
Item Type: | Article |
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Identification Number: | 10.1016/j.applthermaleng.2020.116122 |
Dates: | Date Event 26 September 2020 Accepted 11 October 2020 Published Online |
Uncontrolled Keywords: | PCR, Computational fluid dynamics, Machine learning, Multi-objective optimisation |
Subjects: | CAH02 - subjects allied to medicine > CAH02-05 - medical sciences > CAH02-05-01 - medical technology CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-01 - engineering (non-specific) CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-02 - mechanical engineering CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-09 - chemical, process and energy engineering |
Divisions: | Architecture, Built Environment, Computing and Engineering > Engineering |
Depositing User: | Zinedine Khatir |
Date Deposited: | 29 Oct 2020 11:54 |
Last Modified: | 20 Jun 2024 11:50 |
URI: | https://www.open-access.bcu.ac.uk/id/eprint/10173 |
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