A parametric study of the heat flux partitioning model for nucleate boiling of nanofluids

Li, X, Yuan, Y and Tu, J 2015, 'A parametric study of the heat flux partitioning model for nucleate boiling of nanofluids', International Journal of Thermal Sciences, vol. 98, pp. 42-50.

Document type: Journal Article
Collection: Journal Articles

Title A parametric study of the heat flux partitioning model for nucleate boiling of nanofluids
Author(s) Li, X
Yuan, Y
Tu, J
Year 2015
Journal name International Journal of Thermal Sciences
Volume number 98
Start page 42
End page 50
Total pages 9
Publisher Elsevier Masson
Abstract The dramatic boiling heat transfer performances of nanofluids have been widely attributed to the nanoparticle deposition during the boiling process. The deposited nanoparticles significantly change the microstructures and properties of the heater surface, and hence alter the characteristics of bubble nucleation and departure. Therefore, it is crucial to take into account the effects of nanoparticle deposition when modeling nucleate boiling of nanofluids using the heat flux partitioning (HFP) model (Kurul N., Podowski M.Z., 1990) [1]. In this study, new closure correlations were incorporated for the nucleate boiling parameters including the active site density, the bubble departure diameter and frequency. Parametric studies were performed through 2-D computations to analyze the effects of surface wettability enhancement, the nanoparticle material and size, respectively. The results demonstrated that through appropriate considering the modifications induced by nanoparticle deposition, the HFP model achieved a satisfactory agreement with the experimental data available in the literature, and provided a more feasible and mechanistic approach than the classic Rohsenow correlation for predicting nucleate pool boiling of nanofluids.
Subject Applied Mathematics not elsewhere classified
Keyword(s) Heat flux partitioning
Nanoparticle deposition
Nucleate boiling
Surface modifications
DOI - identifier 10.1016/j.ijthermalsci.2015.06.020
Copyright notice © 2015 Elsevier Masson SAS.
ISSN 1290-0729
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Citation counts: TR Web of Science Citation Count  Cited 11 times in Thomson Reuters Web of Science Article | Citations
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