Enhanced heat transfer rate on the flow of hybrid nanofluid through a rotating vertical cone: a statistical analysis

Abstract

The recent study needs the optimal conditions for maximizing heat transfer rate with minimizing energy consumption. This is a basic objective of several industries in their production processes along with in improving the efficiency in electronic gadgets. Therefore, hybrid nanofluid plays an important role in enhancing heat transport phenomena. The current study investigates the improved heat transfer properties of a water-based hybrid nanofluid containing Al2O3 and Cu nanoparticles flowing through a rotating vertical cone embedded in a porous medium. The convective flow is enhanced by a magnetic field and thermal radiation, contributing to the complexity of the flow dynamics. However, the dimensional physical quantities are transformed to non-dimensional parameters by the implementation of suitable similarity rules. Furthermore, the transformed equations are numerically solved using a fourth-order Runge-Kutta shooting method. Henceforth, to get the optimal heat transfer rate, a robust statistical technique called response surface methodology (RSM) and for the validation a hypothetical test is organized by using analysis of variance. The parametric behavior is conducted via graphs and the physical description is presented briefly. Further, the major outcomes of the study are: both the particle concentrations attenuate the axial velocity whereas the fluid temperature enhances significantly. Increasing radiative heat augments the heat transport phenomena and the observation reveals that the case of hybrid nanofluids overrides the case of nanofluids.