Double layered combined convective heated flow of Eyring-Powell fluid across an elevated stretched cylinder using intelligent computing approach

This study investigates the possessions of a dual stratified common on the diverse convection barrier layer discharge of an Eyring-Powell fluid (CBLFEPL) induced by an prone extensive barrel. The temperature and concentration at the exterior of the barrel are assumed to be larger than the moving fluid. To solve the resulting flow equations, an brilliant numerical established aggregating solver is employed using the Levenberg-Marquardt neural network scheme (LMNNS). The governing equations of partial differential are converted into interconnected nonlinear ordinary differential equations using appropriate transformations. First, a dataset is generated for two distinct cases, one with a zero curvature parameter (plate) and the other with a non-zero curvature parameter (cylinder). The behaviors of skin-friction coefficient, Sherwood number and Nusselt number are presented over chart obtained using the BVP4C technique. Subsequently, an intelligent computing algorithm nftool, is utilized for training, validation, and testing steps to approximate solutions for various cases. The designed solver, LMNNS, is applied to solve the CBLFEPL problem through regression, mean squared error (MSE), histogram studies, and gradient analysis. The study of double-layered combined convection flow of Eyring-Powell fluid around an elevated stretched cylinder provides insights into heat and mass transfer characteristics, crucial for applications in engineering and fluid dynamics. This study aims to contribute insights that can be applied to engineering and fluid dynamics, aiding in the optimization of relevant processes and applications. The research methodology involves employing numerical technique, three-stage Lobatto IIIa formula, to solve the governing equations of the double-layered combined convection flow of Eyring-Powell fluid around an elevated stretched cylinder, while systematically varying key parameters to analyze their impact on heat and mass transfer phenomena. The speed of the fluid experiences a notable rise with higher values of curvature parameter K, fluid parameter M, mixed convection parameter lambda m, and the ratio of buoyancy forces N. Conversely, the velocity profile exhibits a contrasting behavior concerning the thermal stratification parameter epsilon 1, solutal stratification parameter epsilon 2, and an inclination angle alpha.