Influence of surface roughness on multidiffusive mixed convective nanofluid flow

The main objective of this work is to investigate the mixed convective nanofluid flow along a slender cylinder with a rough surface in the presence of liquid hydrogen and ethanol diffusions. The surface roughness is represented by a deterministic model with low-amplitude high-frequency sinusoidal variations. The governing equations of the flow are expressed in the form of dimensional nonlinear partial differential equations and are solved with the help of non-similar transformations and the numerical technique of quasilinearization. The so obtained non-dimensional linear partial differential equations are discretized by implementing an implicit finite difference scheme for the computation of a numerical solution. The numerical study focuses on the analysis of rough surface effects regarding small parameter alpha and frequency parameter n along with the effects of velocity ratio parameter epsilon. The sinusoidal variations observed in the values of the gradients with their mean values are closely identified with values corresponding to a smooth surface. Also, increasing the slender cylinder's wall roughness increases the magnitude of sinusoidal variations in all the gradients. The addition of nanoparticles into the working fluid reduces the surface friction and transfer of heat, but increases the transfer of mass for both a smooth or rough surface. The presence of thermophoresis and Brownian diffusion causes an increase in the thermal boundary layer. The diffusions of liquid hydrogen and ethanol are considered, and the impact of surface roughness is significant on the mass transfer rates of these liquid gases. Also, the species concentration profiles are higher for liquid hydrogen diffusion as compared to that for ethanol. The effect of the velocity ratio parameter epsilon is to increase the magnitudes of the velocity profile as well as the heat and mass transfer rates but to decrease the species concentration profile and the skin-friction coefficient. Moreover, higher values of Lewis number reduce the nanoparticle volume fraction profile, while higher values of nanoparticle buoyancy ratio parameter increase the same.