Abstract

This work’s main objective is to investigate the thermal behavior of a tetra-ferrite-based nanofluid model under four physical controls. The tetra-nanofluid contains Fe3O4, CoFe2O4, NiZnFe2O4, and MnZnFe2O4 tetra-nanoparticles over a porous surface using ethylene and water (50%–50%) as the base fluid. The fundamental constitutive models are reduced nonlinear ordinary differential equations using appropriate transformative functions. The resulting set of governing equations are found using the Runge–Kutta algorithm. The impacts of critical quantities on the heat transfer, shear factor, and Nusselt number are illustrated through graphs and numerical data. It is noticed that when the concentration of nanoparticles is from 0.1% to 0.6%, the thermal conductivity varies from 102.661% to 116.706% for nanofluid (NF), 108.893% to 140.384% for hybrid nanofluid, and 117.994% to 195.794% for tetra-nanofluid (Tet.NF), which played a crucial role in the temperature performance of the fluidic system. Furthermore, the velocity depreciated against ϕ1 = 1%, 2%, 3%, 4%, 5%, 6%, and 7%. The Forchheimer effects Fr = 1.0, 2.0, 3.0, 4.0, Q = 0.1, 0.4, 0.7, 1.0, and Rd = 0.1, 0.2, 0.3, 0.4 enhanced the temperature of all types of NFs, while the stretching parameter S = 0.01, 0.08, 0.15, 0.22 reduced it. The results would benefit the researchers about the prediction of the parametric ranges and nanoparticle concentration to acquire the heat transfer results for practical applications, particularly in applied thermal engineering.