Entropy optimization of inverse Darcy-Forchheimer model of Jeffrey fluid flow over a curved stretching surface using ANOVA-Taguchi technique

The Jeffrey fluid model, known for describing viscoelastic non-Newtonian fluids, is widely applied in polymer processing due to its significance, biological systems, and manufacturing processes. However, most existing studies focus on simplified geometries, neglecting complex interactions and advanced physical effects. Despite extensive studies on Jeffrey fluid flow, the combined effects of inverse Darcy resistance, Cattaneo-Christov double diffusion, magnetic field, Joule heating, chemical reaction, and Newtonian heating over a curved stretching sheet remain unexplored. This study aims to analyse the significance of entropy generation in such a flow system and optimize heat transfer efficiency. To achieve this, the fourth-fifth order Runge-Kutta-Fehlberg method is used for numerical solution, while ANOVA-Taguchi optimization technique is employed to determine optimal conditions for enhancing heat transfer performance. Here, the study reveals that an increase in the Deborah number enhances the velocity profile, while higher values of the inverse Darcy number and inertial co-efficient suppress it. A rise in the thermal relaxation parameter reduces the temperature profile, whereas Newtonian heating increases it. The concentration profile decreased as the concentration relaxation parameter increased, while it increased as the chemical reaction parameter increased. Furthermore, a greater inverse Darcy number and inertial co-efficient result in increased entropy generation, while the Bejan number initially rises near the boundary before gradually decreasing. The ANOVA-Taguchi analysis reveals that the Hartmann number has the least contribution to minimize entropy generation by only 1.66%, while the Eckert number has the most dominant effect at 78.92%.