Evaluation of prediction methods for heat transfer coefficient of annular flow and a novel correlation

Flow boiling heat transfer of annular flow is very important to the thermal design of evaporating heat exchanger. In this study, an experimental heat transfer coefficient database containing 2783 data points is built from 26 open literatures for annular flow. The database includes both macro-channels and mini/micro-channels data and covers wide range of working conditions. The annular flow database consists of 7 working fluids, covering hydraulic diameters of 0.5-14.0 mm, mass velocities of 50-1290 kg/m(2) s, liquid-only Reynolds numbers of 240-55,119, vapor qualities of 0.10-0.98, and reduced pressures from 0.01 to 0.77. In addition, 19 existing prediction methods for flow boiling heat transfer coefficient are summarized and evaluated by the built database. At last, a novel correlation of heat transfer coefficient for annular flow is developed. Comparing with the conventional correlations, the proposed correlation gets high prediction accuracy for different tube diameters and fluids. The overall MAE against the database is 13.7%, with 66.5% and 89.0% of the data falling within +/- 15% and +/- 30% error bands, respectively. The MAEs against macro-channels and mini/micro-channels data are 12.2% and 15.3%. And the MAEs against R134a, R22, ammonia, CO2, R236fa, R245fa, and R1234ze data are 12.6%, 18.5%, 12.9%, 23.9%, 6.5%, 12.6% and 9.4%, respectively. (C) 2016 Elsevier Ltd. All rights reserved.