Thermal transport and irreversibility analysis for radially magnetized Carreau–Yasuda nanofluids flow over polished surfaces

A major challenge in modern industry is the need for efficient heat transfer fluids, as conventional fluids often do not provide the necessary efficiency for heating and cooling processes. Nanofluids, seen as the future of heat transfer fluids, are developed by dispersing nanoparticles into base fluids. Owing to their unique and dynamic thermophysical properties, these innovative nanofluids have a broad spectrum of applications in nanotechnology and advanced heat transfer systems. Based on the applications of nanofluids, the flow of nanofluids composed of graphene nanoparticles suspended in lubricant oil with heat transfer is studied here. Flow is induced by a curved stretching sheet. The surface of the sheet is considered to be polished uniformly, which hence facilitates velocity slip. The novelty of this study lies in utilizing the rheological properties of graphene nanoparticles dispersed in a lubricant oil-based fluid, as empirically investigated by Bakak et al. (2021). Their findings suggest that this nanofluid exhibits non-Newtonian behavior, with experimental data closely aligning with the Carreau–Yasuda model. A radially varying magnetic field influences the flow by generating Lorentz force and Ohmic heating. In view of the experimentally reported results, the rheological properties of nanofluid are depicted using the Carreau–Yasuda model. Furthermore, flow configuration is influenced by thermal radiation, heat source, viscous dissipation, and convective heat transfer at the boundary. Irreversibility analysis is carried out to propose ways of energy optimization. Boundary layer approximations are utilized to model the partial differential equations (PDEs) governing the system. By applying a non-similarity transformation, the original PDEs are converted into dimensionless nonlinear PDEs. By applying the local non-similarity approach, the dimensionless equations are truncated to the second order, reducing them to ordinary differential equations (ODEs) that can be more easily solved. The resulting system is tackled through the BVP4c algorithm in MATLAB. Influences of pertinent flow parameters on velocity profile, drag force, isotherms, nanofluid’s temperature, streamlines, entropy generation number, thermal transfer rates, and Bejan number are analyzed through graphs and tables. Findings indicate that temperature distribution improves for higher values of Biot number, Weissenberg number, thermal radiation, and magnetic number. Additionally, the velocity of nanofluid decreases for increasing values of magnetic number. Also, it is noted that stretching a sheet with a polished surface decreases the nanofluid’s velocity. The entropy generation number demonstrates a direct relationship with the temperature profile. Furthermore, the magnitude of the drag coefficient decreases for the curvature parameter and the volume fraction of nanoparticles. Heat transfer rises with elevated values of curvature parameter, Eckert number, heat source parameter, and thermal radiation parameter, but decreases with an increase in magnetic number.