Sensitivity analysis and optimization of MHD forced convection of a Cu-water nanofluid flow past a wedge

.The effect of a wedge angle on the MHD laminar momentum and thermal boundary layer decelerating forced flow of a water-Cu nanofluid flow over a constant temperature wedge is investigated numerically for different nanoparticle volume fractions. The thermal conductivity and viscosity of the nanofluid are computed by considering the Brownian motion of the particles. The momentum and energy equations are solved by the Keller-Box method. The averaged friction coefficient and the Nusselt number are analyzed to explore boundary layer and heat transfer behaviours. Two regression models are obtained by using the response surface methodology for various magnetic parameters (0.5M2.5), wedge angles (90 degrees 180 degrees) and nanoparticle volume fractions (0.01 phi 0.07). Then, a sensitivity analysis is carried out to gain further insight into the impact of the factors on the problem. Finally, an optimization process is conducted in order to determine the maximum heat transfer rate and the minimum surface friction. The obtained results show that both the magnetic parameter and the wedge angle decrease the thicknesses of the hydrodynamic and thermal boundary layers, so that the averaged surface friction and the Nusselt number reduce. Surprisingly, adding nanoparticles is found to have a decreasing impact on the averaged Nusselt number by enlarging the thermal boundary layer thickness at high magnetic strength. The sensitivity analysis outcomes reveal that M, , and phi have increasing effects on the surface friction. Also, the sensitivity of to the wedge angle is found to be independent of the magnetic parameter. The optimum condition occurs when M = 0.62, =166.71 degrees, and phi = 0.052, wherein = 1.176 and (C) over bar (f) = 3.2601, with a maximum error of 0.33%.