Abstract
The thermal performance of a flat plate solar collector operating under thermosyphon conditions using MWCNT + Fe3O4/Water hybrid nanofluids was investigated in this study. Field testing was carried out at various nanoparticle concentrations at varying Reynold's numbers. At Reynold's number of 1413 and 0.3 vol%, the peak thermal efficiency of 63.84 % was attained. There was a large improvement in heat transfer coefficient (26.3 %) with a slight penalty through friction factor (18.9 %). When operated with hybrid nanofluids with 0.3 %, 0.2 %, 0.1 %, and 0.05 % vol. fractions and Re values of 1413, 1674, 1774, and 1892, the collector's exergy efficiency was increased by 40.51 %, 36.86 %, 33.21 %, and 29.56 %, respectively. Extensive testing yielded experimental data that was used to create new parametric correlation functions for heat transfer coefficient, friction factor, Nusselt's number, and collector thermal efficiency, and to create a novel prognostic model using the Ensemble Boosted Regression Tree Optimized using Bayesian Approach (BOBRT). The R, R-2, MSE, and MAPD values for the BOBRT-based output models were 0.9803-0.9999, 0.961-0.9998, 0.00003-9.326, and 0.0025-0.0662, respectively. Theil's U2 had been used to evaluate the uncertainties in the prognostic paradigm, which was found to be in range of 0.0099 to 0.1544, for BOBRT.