Magneto-nanofluid flow with heat transfer past a stretching surface for the new heat flux model using numerical approach

Sheet processing of magnetic nanomaterials is emerging as a new branch of smart materials manufacturing. The efficient production of such materials combines many physical phenomena including magnetohydrodynamics (MHD), nanoscale, thermal and mass diffusion effects. To improve understanding of complex inter-disciplinary transport phenomena in such systems, mathematical models provide a robust approach. Motivated by this, herein we develop a mathematical model for steady, laminar, magnetohydrodynamic, incompressible nanofluid flow, heat and mass transfer from a stretching sheet. A uniform constant strength magnetic field is applied transverse to the plane of the stretching flow. The Buonjiornio nanofluid model is employed to represent thermophoretic and Brownian motion effects. A non-Fourier (Cattaneo-Christov) model is deployed to simulate thermal conduction effects of which the Fourier model is a special case when thermal relaxation effects are neglected. The governing conservation equations are rendered dimensionless with suitable scaling transformations. The emerging nonlinear boundary value problem is solved with a fourth order Runge-Kutta algorithm and also shooting quadrature. Validation is achieved with earlier non-magnetic and forced convection flow studies. The influence of key thermophysical parameters e.g. Hartmann magnetic number, thermal Grashof number, thermal relaxation time parameter, Schmidt number, thermophoresis parameter, Prandtl number and Brownian motion number on velocity, skin friction, temperature, Nusselt number, Sherwood number and nano-particle concentration distributions is investigated. A strong elevation in temperature accompanies an increase in Brownian motion parameter whereas increasing magnetic parameter is found to reduce heat transfer rate at the wall (Nusselt number). Nano-particle volume fraction is observed to be strongly suppressed with greater thermal Grashof number, Schmidt number and thermophoresis parameter whereas it is elevated significantly with greater Brownian motion parameter. Higher temperatures are achieved with greater thermal relaxation time values i.e. the non-Fourier model predicts greater values for temperature than the classical Fourier model