journal article Open Access Nov 01, 2014

A systematic study of pool boiling heat transfer on structured porous surfaces: From nanoscale through microscale to macroscale

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Abstract
An experimental study has been conducted to examine the effects of macroscale, microscale, and nanoscale surface modifications in water pool boiling heat transfer and to determine the different heat transfer enhancing mechanisms at different scales. Nanostructured surfaces are created by acid etching, while microscale and macroscale structured surfaces are synthesized through a sintering process. Six structures are studied as individual and collectively integrated surfaces from nanoscale through microscale to macroscale: polished plain, flat nanostructured, flat porous, modulated porous, nanostructured flat porous, and nanostructured modulated porous. Boiling performance is measured in terms of critical heat flux (CHF) and heat transfer coefficient (HTC). Both HTC and CHF have been greatly improved on all modified surfaces compared to the polished baseline. Hierarchical multiscale surfaces of integrated nanoscale, microscale, and macroscale structures have been proven to have the most significant improvements on HTC and CHF. The CHF and HTC of the hierarchical multiscale modulated porous surface have achieved the most significant improvements of 350% and 200% over the polished plain surface, respectively. Experimental results are compared to the predictions of a variety of theoretical models with an attempt to reveal the different heat transfer enhancing mechanisms at different scales. It is concluded that models for the structured surfaces at all scales need to be further developed to be able to have good quantitative predictions of CHFs on structured surfaces.
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References
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Published
Nov 01, 2014
Vol/Issue
4(11)
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Funding
Villanova University Startup Funding
Cite This Article
Russell P. Rioux, Eric C. Nolan, Calvin H. Li (2014). A systematic study of pool boiling heat transfer on structured porous surfaces: From nanoscale through microscale to macroscale. AIP Advances, 4(11). https://doi.org/10.1063/1.4902343