A Similarity Solution for Mixed-Convection Boundary Layer Nanofluid Flow on an Inclined Permeable Surface

摘要

This paper concerns with calculation of heat transfer and pressure drop in a mixed-convection nanofluid flow on a permeable inclined flat plate. Solution of governing boundary layer equations is presented for some values of injection/suction parameter (f_0), surface angle (γ), Galileo number (Ga), mixed-convection parameter (λ), volume fraction (φ), and type of nanoparticles. The numerical outcomes are presented in terms of average skin friction coefficient (Cf) and Nusselt number (Nu). The results indicate that adding nanoparticles to the base fluid enhances both average friction factor and Nusselt number for a wide range of other effective parameters. We found that for a nanofluid with φ = 0.6, injection from the wall (f_0 = -0.2) offers an enhancement of 30 in C_f than the base fluid, while this growth is about 35 for the same case with wall suction (f_0 = 0.2). However, increasing the wall suction will linearly raise the heat transfer rate from the surface, similar for all range of nanoparticles volume fraction. The computations also showed that by changing the surface angle from horizontal state to 60 deg, the friction factor becomes 2.4 times by average for all φ's, while 25 increase yields in Nusselt number for the same case. For assisting flow, there is a favorable pressure gradient due to the buoyancy forces, which results in larger C_f and Nu than in opposing flows. We can also see that for all φ values, enhancing Ga/Re~2 parameter from 0 to 0.005 makes the friction factor 4.5 times, while causes 50 increase in heat transfer coefficient. Finally, we realized that among the studied nanoparticles, the maximum influence on the friction and heat transfer belongs to copper nanoparticles.