Sensitivity analysis of various factors on the micropolar hybrid nanofluid flow with optimized heat transfer rate using response surface methodology: A statistical approach

Abstract

The current investigation is based on the impact of the nanoparticle shape on the micropolar hybrid nanofluid flow in a vertical plate. Furthermore, the aim of this investigation is to optimize the skin friction as well as the Nusselt number using a statistical approach known as “Response Surface Methodology” (RSM). The micropolar hybrid nanofluid is considered due to its enhanced thermal properties likely the Hamilton–Crosser thermal conductivity, Gharesim model viscosity, etc. A suitable similarity rule is adopted for the transformation of the designed model into ordinary and then solved numerically utilizing the shooting-based Runge–Kutta fourth-order technique. The simulated results of diversified parameters are presented through graphs. Furthermore, RSM is employed to design and develop a mathematical model to get an optimized hear transfer rate along with the rate of shear stress. The required components are carefully selected, and the corresponding responses are recorded. The collected data is subsequently employed in constructing a response surface through regression analysis. This process allows for the determination of optimal conditions to enhance heat transfer, which is then confirmed through analysis of variance testing. However, the major outcomes of the study are; for the case of suction with increasing particle concentrations, the shear rate, hear transfer rate, and couple stress coefficients are enhanced significantly. Furthermore, the non-Newtonian parameter and the magnetic parameter also favor in enhancing the rate coefficients.