Abstract
Predicted heat transfer coefficients (HTC) are widely used for calculations of various heat and mass transfer processes. Various empirical and semi-empirical models of non-dimensional groups are used for calculating the heat transfer coefficients. These groups depend on the fluid and flow properties. The common accuracy of the predicted heat transfer coefficient is usually about ±25%; however, the accuracy is failing by the lack of mechanistic model for convective heat transfer and by the inaccurate predictions of the fluid properties. This work is aimed to improve the heat transfer coefficient prediction by reducing the deviations which associated with the fluid properties. When the fluid is a mixture of miscible fluids the predictions of the fluid properties are very rough and therefore the prediction of the heat transfer coefficient is more complicated. In the present study the heat transfer coefficient of sub-cooled organic mixture chlorodifluoromethane (R22)–dimethylacetamide (DMAC) was measured experimentally. In order to compare the experimental value with the predicted one, thermophysical properties of the solution, such as density, viscosity, heat capacity and thermal conductivity have to be known. Since the thermal conductivity of the solution (R22–DMAC) was the only unknown property, various correlations and mixing rules were tested, and the most appropriate was chosen. Based on this method for evaluating the solution’s properties the predicted HTC obtained with an error range of 15%.
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