부산대학교 도서관

In this study, experiments were conducted for the flow of R-134a condensing in an enhanced inclined tube at a saturation condensing temperature of 40 °C. The enhanced tube had a helix angle of 14° with a mean internal diameter of 8.71 mm. The mass velocities were varied from 200 to 600 kg m−2 s−1, while the inclination angles were varied from − 90° to + 90°. It was found that the inclination angle had a considerable effect on the flow patterns and the thermal performance. It was also found that the maximum heat transfer coefficients were obtained at tube inclinations of between − 15° and − 5° (downward flows). By using the experimental data and artificial neural networks (ANN), a model was proposed to predict the heat transfer coefficients during condensation inside the enhanced inclined tube. By using four statistical criteria, the performance of the proposed model was examined against experimental data, and it was found that ANN was a useful tool for the prediction of the heat transfer coefficients based on the effective parameters of vapour quality, mass velocity and inclination angle. [ABSTRACT FROM AUTHOR]