Gradient‐Based Optimization Modeling of Total Entropy and Heat Transfer in Exothermic Blood Analog Gold Nanoparticle Suspension

Abstract

ABSTRACT The Casson‐micropolar fluid model herein represents the microstructure (yield stress) and micro‐rotational dynamics of engineered nanoparticles in blood‐analog suspensions. We present the mathematical model for a Casson (blood)‐gold nanoparticle suspension and perform gradient‐based objective optimization to (i) maximize the convective heat‐transfer coefficient and (ii) minimize total entropy generation. The computational framework of non‐Newtonian exothermic Casson‐micropolar fluid with variable viscosity and thermal conductivity is implemented via the spectral method, while the optimization scheme employs the multi‐start Nelder–Mead methodology to simulate the decision variables by random restarts with local convergence and a derivative‐free simplex method. Fluid velocity decreases with higher nanoparticle volume fractions but increases with the Frank‐Kamenetskii parameter, particularly near the convective slippery wall, and the thermodynamic irreversibility escalates with the Frank‐Kamenetskii parameter near the thermally insulated wall, whereas increasing the nanoparticle volume fraction and thermal conductivity effectively minimizes entropy generation. The least contribution of the variable viscosity, maximum values of thermal conductivity, Kamenetskii parameter, higher convective heating, continuous injection of nanoparticle volume fraction, and the avoidance of thermal radiation have the greatest impact on minimizing the disorderliness in the considered geometry. Maximizing the system heat transfer, the dominant contribution of nanoparticle fraction, thermal radiation, convective heat transfer, and variability of the thermal conductivity is required.