A modeling approach to account for unstable stratification, flow acceleration, and variable thermophysical properties for supercritical carbon dioxide

Abstract

A first of its kind reduced-order predictive heat transfer model is developed to account for the effects of unstable stratification, flow acceleration, and variable thermophysical properties for supercritical carbon dioxide. These phenomena govern thermal transport in the proximity of the pseudo-critical point when the applied heating is limited to the bottom wall of the flow channel. The reduced order model assumes two-dimensional thermal transport and involves the iterative solution of the turbulent Prandtl number. The predictions of this model were compared against experimental data. Out of a total of 16 test data sets, each comprising over 200 individual data points, the model was able to predict 14 data sets with a mean average percent error (MAPE) of less than 20%. Additionally, a heat transfer design correlation is proposed which can predict the experimental data with a MAPE of less than 22%. The modeling approaches outlined in this work provide an alternative to using CFD to model coupled and counteracting phenomena that governs thermal transport for supercritical fluids in asymmetrically bottom heated ducts.