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ISBN : 978-1-56700-478-6

Proceedings of the 24th National and 2nd International ISHMT-ASTFE Heat and Mass Transfer Conference (IHMTC-2017)
2017, December 27-30 , BITS Pilani, Hyderabad, India


DOI: 10.1615/IHMTC-2017.3380
pages 2417-2423


In the present study subcooled flow boiling heat transfer experiments are performed with water and ethanol/water mixtures. The flow boiling experiments are conducted with variation in the heat flux, mass flux and ethanol volume fraction. Visualization is carried out to investigate the bubble dynamics during subcooled flow boiling by a digital high speed camera. The bubble parameters like departure diameter, growth time and waiting time are measured by image processing. It is observed that the bubble parameters increase with increase in ethanol volume fraction and decrease with increase in heat flux and mass flux. But it is observed that 30% ethanol volume fraction has least values of bubble parameters. Hence the subcooled flow boiling heat transfer coefficient increases at 30% ethanol volume fraction and decreases with further addition of ethanol. Comparisons between the experimental heat transfer coefficients with that predicted from existing correlation is presented. The forced convective heat transfer coefficient of water deviated by 24.51% from Stephan equation and by 19.80% from Churchill-Ozie equation. Also, wall heat flux partitioning using existing mechanistic heat transfer model has been done. From the mechanistic model for prediction of wall heat flux and partitioning, it is found that the heat flux due to forced convection and evaporation are 39.26% and 60.65% respectively of the total heat flux and heat flux due to agitation is negligibly small in partial nucleate boiling region however in fully developed nucleate boiling region evaporation and agitation heat flux accounts for 64.11% and 27.73% respectively of the total heat flux. It is found that the model predicts the experimental values with a deviation of 22.26%. The difference between predicted and experimental data is because of the reason that the conditions for which they were developed is not duplicated.