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A novel method for fast and efficient numerical simulation of microwave heating in liquids during mixing

Singh, Bhupinder, Hefford, Samuel, Sanchez-Perez, Enrique, Barter, Michael ORCID: https://orcid.org/0000-0002-4404-9397, Slocombe, Daniel R. ORCID: https://orcid.org/0000-0003-3590-6075, Cussen, Serena A. and Dimitrakis, Georgios 2025. A novel method for fast and efficient numerical simulation of microwave heating in liquids during mixing. International Journal of Heat and Mass Transfer 237 , p. 126425. 10.1016/j.ijheatmasstransfer.2024.126425

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License URL: http://creativecommons.org/licenses/by/4.0/
License Start date: 6 November 2024

Abstract

Microwave-assisted chemical reactions present potentially more sustainable routes for process intensification compared with traditional approaches, due to the reduction of reaction times, temperatures, and side reactions. Despite the common misconception that microwave heating is uniform, many processes can be expected to show temperature distributions that vary significantly over the volume, even at length scales far below the operating wavelength. Numerical methods are often employed in the design and optimization phase of a given process, however, due to the multitude of interdependent physics required; the fast and efficient modelling of microwave heating in liquids remains a significant challenge, particularly with respect to computational resources. Here, we report a new multi-physics simulation methodology that models microwave heating of liquids during agitation, requiring less computational resources and delivering temperature predictions within 2.78 % of relative root mean square error. By applying the frozen rotor approach, near-perfect temperature profiles are predicted at approximately 600 times faster convergence time compared to the conventional sliding mesh method. Our proposed model can be used to mimic real reaction systems in a fast and resource-efficient way.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Additional Information: License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by/4.0/, Start Date: 2024-11-06
Publisher: Elsevier
ISSN: 0017-9310
Date of First Compliant Deposit: 15 November 2024
Date of Acceptance: 5 November 2024
Last Modified: 04 Dec 2024 12:21
URI: https://orca.cardiff.ac.uk/id/eprint/174022

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