Analysis of convective boiling heat transfer coefficient correlation of R290

Abstract

Currently, there exist differences between the experimental data and predicted heat transfer coefficient for small channels with continuous modifications and development to reduce them. Accurate prediction of two-phase boiling heat transfer coefficient is important to avoid under or over designing the system. This study was done to improve the two-phase flow boiling heat transfer coefficient correlation based on asymptotic approach which involves both nucleate boiling and convective heat transfer mechanisms, for refrigerant R290. This study utilized the single objective optimization in Genetic Algorithm (GA) for parameter optimization to achieve minimized mean absolute error (MAE), the absolute difference between the predicted coefficient and the experimental data. Investigations consist of different input conditions for channel inner diameter of 3 mm and saturated temperature of 10°C. The improved correlation shows a good agreement within 10% error for mass flux at 150 and 200 kg/m2s with heat flux of 15 kW/m2. It also shows a good agreement within 10% error for heat flux of 5 and 10 kW/m2 at mass flux of 100 kg/m2s. The new correlation has low MAE with expected patterns and trends when the data involves vapor quality at a range of 0 < x < 0.8. The new correlation may be used to predict the heat transfer coefficient of R290 in the analysis of heat transfer in a small channel within the operating conditions investigated.