AIP Advances (Jul 2024)
Computational analysis of entropy generation optimization for Cu–Al2O3 water-based chemically reactive magnetized radiative hybrid nanofluid flow
Abstract
This study aims to analyze the mass transfer and entropy generation in the flow system of chemically reactive, thermal radiative hybrid nanofluids (Al2O3/Cu with H2O as base fluid) flow across flat stretching porous surfaces in the presence of viscous dissipation and transverse magnetic field. The governing partial differential equations are converted into a set of ordinary differential equations by applying a group of self-similarity transformations. The resulting differential equations are solved using the Bvp4c technique in MATLAB. The impact of several physical parameters has been examined the velocity, heat, and mass transfer components of the fluid. To optimize the complete heat transfer process, the consequences of all physical parameters are discussed on entropy generation and Bejan number and presented graphically. It is observed that velocity increases with the increase in magnetic parameter M because pressure force dominates over Lorentz force, temperature increases with the rise of Ec, concertation reduces with the enhancement of chemical reaction parameter delta, and the Bejan number decreases with the increase in Br; however, reverse phenomena are observed with increasing the value of the magnetic number and entropy increases with the rise of magnetic parameter M. Due to the increase in magnetic parameter M, drag force is accelerated, which leads to increase in entropy, With an increment in Pr and Ec, the heat exchange rate declines although the skin friction coefficient and mass transfer remain constant. There are several significant applications of the study of thermal analysis of hybrid nanofluid flows in numerous mechanical processes, such as extrusion or metal manufacturing processes, heat transportation in biological tissues, cooling of electric devices, high-size refrigeration, hydroelectric dams, and fuel systems.