Langari, M, Yang, Z, Dunne, J F, Jafari, S, Pirault, J-P, Long, C A and Thalackottore Jose, J (2018) Conjugate heat transfer predictions for subcooled boiling flow in a horizontal channel using a volume-of-fluid framework. Journal of Heat Transfer, 140 (10). a104501 1-6. ISSN 0022-1481

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Abstract

The accuracy of computational fluid dynamic (CFD)-based heat transfer predictions have been examined of relevance to liquid cooling of IC engines at high engine loads where some nucleate boiling occurs. Predictions based on (i) the Reynolds Averaged Navier-Stokes (RANS) solution and (ii) large eddy simulation (LES) have been generated. The purpose of these simulations is to establish the role of turbulence modeling on the accuracy and efficiency of heat transfer predictions for engine-like thermal conditions where published experimental data are available. A multiphase mixture modeling approach, with a volume-of-fluid interface-capturing method, has been employed. To predict heat transfer in the boiling regime, the empirical boiling correlation of Rohsenow is used for both RANS and LES. The rate of vapor-mass generation at the wall surface is determined from the heat flux associated with the evaporation phase change. Predictions via CFD are compared with published experimental data showing that LES gives only slightly more accurate temperature predictions compared to RANS but at substantially higher computational cost.

Item Type:	Article
Keywords:	Flow boiling, IC engines, CFD, Large Eddy Simulation, Reynolds Averaged Navier-Stokes.
Schools and Departments:	School of Engineering and Informatics > Engineering and Design
Research Centres and Groups:	Dynamics, Control and Vehicle Research Group
Subjects:	Q Science > QC Physics > QC0251 Heat > QC0310.15 Thermodynamics T Technology T Technology > TA Engineering (General). Civil engineering (General) > TA0349 Mechanics of engineering. Applied mechanics > TA0357 Applied fluid mechanics T Technology > TJ Mechanical engineering and machinery > TJ0255 Heat engines
Depositing User:	Julian Dunne
Date Deposited:	19 Feb 2018 09:31
Last Modified:	06 Jan 2021 16:40
URI:	http://sro.sussex.ac.uk/id/eprint/73637

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