HEAT TRANSFER AND FRICTION FACTOR OF FLAT PLATE SOLAR COLLECTOR WITH Al2O3 -CuO/WATER HYBRID NANOFLUIDS: EXPERIMENTAL AND ANN PREDICTIONS

The Nusselt number, heat transfer, and friction factor of flat plate collector working with Al2O3-CuO/water hybrid nanofluids were estimated experimentally, and the obtained data is used for the artificial neural network- Support Vector Regression method. Experiments were conducted from 09:00 to 16:30 hr, with volume loadings of 0.048%, 0.096%, 0.144%, 0.192% and 0.24%, respectively. The entire region is divided into time zone 1 (09:00 hr to 13:00 hr) and time zone 2 (13:00 hr to 16:30 hr). Results show the time zone-1, at 13:00 hrs, at 0.24% vol. and a Reynolds number of 364.66, the Nusselt number is enhanced by 20.43%, and at time zone-2, at 16:30 hrs, at 0.24% vol., and at Reynolds number of 211.23, the Nusselt number is enhanced by 14.08%, respectively, over the base fluid. Similarly, for time zone-1 and time zone-2, at 13:00 hrs and 16:30 hrs, at 0.24% vol. and at Reynolds number 364.66 and 211.23, the friction factor is enhanced by 15.34% and 11.50%, respectively, over the base fluid. The employed support vector regression algorithm accurately predicts the values with experimental data. The correlation coefficients found for the Nusselt number, heat transfer, and friction factor are 0.99497, 0.9947, and 0.99955, respectively.