The objective of this research is to boost renewable energy efficiency by employing hybrid nanofluid-assisted heat transfer, utilizing experimental data related to graphene oxide/ionic nanofluids (GO/INF) with a new mathematical model.
This study aims to enhance renewable energy efficiency through hybrid nanofluid-assisted heat transfer, using experimental data on GO/INF. The Ionic liquid (IL), Water (H2O) and Graphene Oxide (GO) are used in different ratios to perform hybrid nanofluids. The simulation is carried out with a Control Volume Finite Element Method (CVFEM) that offers high precision, and analytical comprehension is obtained through the Homotopy Analysis Method (HAM). Maintaining the flow stability while moving over the inclined plane is made possible by the porous and variable nature of the flow medium.
Water, IL in the ratio 25% and 75% with GO (H2O-IL (25%–75%)-GO) hybrid nanofluid show the highest heat transfer rate, followed by H2O-IL (50%–50%)- GO and H2O-GO. The improvements in thermal performance are calculated 9.001%, 36.6%, 72.8% respectively. These results match experimental data and confirm that GO-INF hybrid nanofluids enhance energy transport, which makes them best for solar applications.
The combination of variable porous space, non-Fourier heat conduction and stagnation point flow over an inclined plane for heat transfer analysis are novel contribution.
