Shape-dependent heat transfer analysis of hybrid nanofluid using a modified finite propagation model for enhanced thermal management

The hybrid nanofluids (HNF) have become promising class modern fluids due to synergistic features and thermo-physical dynamic. Despite the available studies on the hybrid nanomaterials, the analysis of hybrid nanofluid with applications of shape features, nonlinear radiated effects and implementation of modified Fourier’s model remains unexplored, specially for the blood-based systems. Motivated by such research gap, this investigation explores the enhanced dynamic of heat transfer due to viscoelastic hybrid nanofluid when nonlinear radiated effects are prominent. The molybdenum disulfide (MoS 2 ) and uranium dioxide (UO 2 ) nanoparticles are uniformly decomposed in blood to analyze the HNF features. Thermal analysis formulation is based on non-Fourier’s model which accounts the finite thermal propagation applications while consideration of nonlinear radiated features elaborates the significance of high-temperature energy transport. The novel feature of current model is the systemic inspection of distinguish shape features like cylindrical, spherical, tetrahedral, hexahedral and columnar geometries. The solution methodology is based on implementation of shooting scheme. A parametric analysis is performed to elucidates the influence of modeled parameters on distribution of velocity, surface shear force, temperature field and Nusselt number. It has been observed that change in viscoelastic fluid parameter effectively grows the rate of heat transfer. The blade nanoparticles possess peak thermal rate where the diamond-shaped nanoparticles maintain lowest thermal profile. The simulations present novel insights for the optimization and design of modern energy systems including heat exchangers, energy storage units, controlled thermal devise and peak-performance thermal management techniques.