Neural network approach to explore thermal dynamics of hydromagnetic radiative Casson fluid flow on porous exponential stretching sheet subject to thermophoretic particle deposition and variable temperature effects

Abstract This work Investigates two‐dimensional hydro‐magnetic Casson nanofluid flow on a porous exponentially stretching sheet. Magnetic effects have been applied in normal direction to motion of fluid which is subjected to the impacts of dissipative heat effects, heat source, thermal radiations and chemical reactivity. The flow of fluid is also influenced by bio‐convection and thermophoretic particle deposition. The leading equations have converted to dimensionless form by set of suitable variables and subsequently solved by using neural network approach. It has concluded in this work that, velocity profiles have declined with surge in magnetic factor and porosity parameter while thermal distribution has augmented in both these scenarios. Surge in Eckert number, radiation factor, and thermal sink/source parameter enhance thermal distribution, creating a favourable condition for effectively targeting cancerous tissues while reducing destruction to neighbouring healthy tissues and improving treatment precision. Upsurge in Peclet number and Prandtl number is responsible for decline in concentration distribution. Microorganism panels have deteriorated with progression in thermophoretic deposition particles factor, and Peclet number while amplified with intensification in chemically reactive factor. For all the six scenarios the gradient values fall at 7.732 10 −8 , 7.842 10 −8 , 7.482 10 −8 , 7.902 10 −8 , 7.231 10 −8 and 7.974 10 −8 with corresponding epochs 825, 1000, 356, 1000, 1000 and 902.