Abstract Porous structures, as metal foams, can enhance the heat transfer performance. For a safe industrial application, a predictive model for both heat transfer coefficient and maximum heat flux is… Click to show full abstract
Abstract Porous structures, as metal foams, can enhance the heat transfer performance. For a safe industrial application, a predictive model for both heat transfer coefficient and maximum heat flux is required. But, there is no correlation for dielectric fluids on metal foams available in the literature. This work aims to develop a correlation based on dimensional analysis for metal foam surfaces in pool boiling with different dielectric fluids. The model takes into account the porous heating surface characteristics (porosity, pore diameter, and thickness), the working fluid thermophysical properties, and its interaction. The model was developed based on the experimental database obtained by the authors and validated with the open literature database. Two metal foams with different characteristics were used for carrying out the pool boiling tests with two different working fluids: HFE-7100 and ethanol. The newly developed correlation predicted well the database with an average error equal to 10.8% where 93.8% within the error range of ± 30%. To the maximum heat flux, the average error was 13.6% where 100% within the error range of ± 30%. The pore diameter and thickness play an important role in both models. The porosity and solid-phase thermal conductivity from the metal foam change the porous medium thermal conductivity, which influences the heat transfer coefficient (HTC). Finally, the properties of the working fluid also influence the predictive model, mainly the latent heat of vaporization, liquid thermal conductivity, and saturation temperature.
               
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