Entropy analysis of Casson ternary hybrid nanofluid using convective cross diffusion model via spinning sphere based artificial neural network

The current analysis explores the Soret and Dufour effects on the stagnation point flow of the Casson ternary hybrid nanofluid around a revolving sphere in the presence of porous medium and magnetic field. The influence of heat source/sink, thermal radiation, and chemical reactions is considered when assessing the mass and heat transmission features. The governing equations of the present problem are converted into non-dimensional ordinary differential equations (ODEs) using the similarity transformations. The resultant ODEs are numerically solved utilizing the Runge Kutta Fehlberg’s fourth-fifth order (RKF-45) technique. Additionally, the artificial neural network (ANN) is utilized to evaluate the fluid flow, mass, and heat transmission attributes. A thorough description and visualization of the graphical variations of major emergent elements are offered, and the accuracy of ANN is confirmed using statistically based neural network assessment tools such as regression plots, mean square errors, error histograms, and curve fitting graphs. Additionally, the entropy generation is performed in the present analysis. The increased porous and magnetic parameters decline the velocity profile. The energy profile rises as the heat source/sink and radiation parameters grow. As the values of Biot and Dufour numbers rise, the thermal profile intensifies. The upsurge in chemical reaction parameter drops the concentration profile.