Investigating the Thermal Efficiency of Al2O3–Cu–CuO–Cobalt with Engine Oil Tetra-Hybrid Nanofluid with Motile Gyrotactic Microorganisms Under Suction and Injection Scenarios: Response Surface Optimization

Abstract

Nanofluids, due to their complex behavior and enhanced thermal properties, are utilized across chemical, biotechnology and thermal engineering disciplines. They are particularly integral to heat transfer processes in heavy machinery and vehicles. This study introduces a novel method for analyzing heat transfer within a tetra nanofluid system through a hybrid analytical and numerical approach. Our research primarily examines the dynamics of a magneto Williamson hybrid tetra nanofluid embedded with motile gyrotactic microorganisms. The study is designed around two scenarios: one investigates the behavior of an Al2O3–Cu–CuO–Cobalt/Engine oil nanofluid under suction conditions, and the other under injection conditions. By employing similarity variables, we transform the original fluid flow equations into nonlinear differential equations to further explore the influence of various physical parameters on the fluid’s flow. Such parameters include the nanofluid temperature and velocity as well as the concentration of nanoparticles, and the volume fraction of motile gyrotactic microorganisms. The optimization of the numerical results for skin friction, Nusselt number, Sherwood number and microorganisms concentration is validated through response surface optimization techniques. Additionally, the study utilizes Matlab‘s bvp4c function to examine the thermal efficiency and characteristics of fluid flow across a spectrum of parameter values.