Neural network method for quadratic radiation and quadratic convection unsteady flow of Sutterby nanofluid past a rotating sphere

Abstract In this study, the heat relocation properties of quadratic thermal radiation and convective unsteady stagnation point flow electro-magnetic Sutterby nanofluid past a spinning sphere under zero mass flux heating conditions are investigated. The governing equations developed expressed as partial differential equations, which afterwards transformed into ordinary by applying similarity conversion. investigation, JAX library in Python is employed with numerical approach to artificial neural networks. It investigated what extent physical characteristics affect primary secondary velocity, temperature, concentration fields. results demonstrate that due increasing unsteadiness, fluid, magnetic field parameters, zone accelerates (x-direction) slows down rotational (z-direction). outcome also shows an increase parameter, constraint, electric constraint induce increases temperature distribution nanofluid. study nanoparticles decreases Lewis numbers unsteadiness parameter values. Additionally, graph illustrating mean square error provided.