Abstract

Nature has adapted throughout its existence, from humans to fishes, and amongst these adaptations, several nature-driven optimizations have made species better suited to the current environment. These optimizations can be found in Mako Sharks, which have developed geometric surface patterns that allow them to move faster. These patterns have been named riblets, and it is observed that they induce skew-induced secondary flows, which improve the overall flow behavior around the sharks. Secondary flows create a pocket of low-velocity air in the ridges, resulting in the high-speed flow being concentrated on the tips of the riblets, further resulting in reduced shear stress. Moreover, the vortical motion of the secondary flows allows a more significant transfer of energy in the boundary layer, which aids in delaying the boundary layer separation. Most of the numerical studies regarding various shapes of riblets have been carried out on flat plates using a Reynolds Averaged Navier-Stokes (RANS) approach. This study focuses on four profiles of riblets: sawtooth, scalloped, blade, and inverted U-shape, attached to the airfoil, and develops a Large Eddy Simulation (LES) framework to simulate the flow. LES resolves eddies of larger scales while modeling the smaller eddies. This allows the simulation to capture the secondary flow over the airfoil with much greater detail and accuracy when compared to RANS, which averages the fluid flow over time. The drag coefficient at various angles of attack was compared against the drag coefficient values of the bare airfoil. The scalloped riblets showed the maximum reduction in drag coefficient (8 % lesser than the bare airfoil), followed by sawtooth, inverted U-shape, and blade-shape. The LES produced accurate contours of velocity, which conform to existing research. The wall shear stress was also post-processed to find similarities between existing research and the proposed LES framework. It was observed that the wall shear stress was concentrated on the riblet-tips instead of the whole upper surface of the airfoil. Another focus of this research was to reduce the simulation's computational load, which is done by using the Spalart-Allmaras DDES solver and reducing mesh time while maintaining the accuracy of the simulation framework.

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