Computational framework for thermal transportation in radiative bio-convective micropolar nanomaterial flow over stretched sheet with entropy optimization

Abstract

Entropy generation (EG) in bioconvective nanofluid flows is a phenomenon that occurs due to the presence of nanoparticles and microorganisms within fluid flows. EG leads to an increase in thermodynamic irreversibility within the system. Understanding and quantifying EG in nanofluid flows is essential to optimize heat transfer processes and design efficient systems. Current investigation aims to analyze the irreversibility of the magnetized bioconvective flow of non-Newtonian micropolar type nanofluid. Flow features are modeled considering flow by a Darcy Forchheimer permeable surface of a stretched sheet. Phenomenon of bioconvection in a micropolar fluid is considered to regulate the solid tiny particles. Magnetic field and permeability effects are accounted in momentum relation. Energy relation is constructed in the presence of Joule heating, internal fluid friction, and thermal radiation. Mass concentration equation is formulated by accounting Arrhenius kinetics and binary chemical reaction. Furthermore, the buoyancy effects of solid tiny particles are considered in thermal and concentration relations. Total entropy of the considered flow is modeled using the second thermodynamics law. System of dimensional equations representing the flow is obtained with the implementation of boundary layer approximations. The acquired system is altered into an ordinary one through transformations and then tackled by numerical scheme Runge-Kutta-Fehlberg method (RKF-45) in the Mathematica package. Behavior of velocity, thermal field, entropy production, mass concentration, motile density, and Bejan number versus sundry variables is investigated through plots. Skin friction, local heat, mass, and density rates are numerically examined. Thermal field upsurges and velocity field decays versus higher Hartmann number. Entropy generation improved versus higher Brinkman number, microorganisms diffusion variable, and temperature difference ratio variable.