  Emulating natural mechanisms in technology has become a very efficient
technique to optimize and improve the current machinery. Riblets are such kinds
of bio-inspired surface patterns which are seen on Sharks. Their geometric
properties induce secondary flows resulting in lower drag, allowing Sharks to
achieve such high speeds. Secondary flows are broadly subcategorized into
Prandtls first and second kind; the secondary flows induced by riblets belong
primarily to Prandtls second kind. These secondary flows have been proven to
delay the boundary layer separation by reducing momentum losses. This paper
aims to optimize the use of these bio-inspired patterns on an airfoil. By
applying the ribletted surface on an airfoil, the boundary layer separation can
be delayed, thus leading to a reduction in drag and increasing the critical
angle of attack. Specific geometric properties such as the height and the
wavelength of the riblets are varied to find the most optimal design. The
design framework couples the optimization algorithm, computational fluid
dynamics, and post-processing analysis. An Invasive Weed Model is implemented
for optimization due to its commendable performance in converging close to
global optima. The optimization process is initialized by generating a
population of riblet profiles with randomly distributed geometry parameters.
These profiles are then evolved over generations with the objective to minimize
the drag, which is computed through Computational Fluid Dynamics simulations
conducted on OpenFOAM. The optimized geometries show a significant reduction in
drag as compared to bare airfoils. Lastly, a flow field analysis of the
optimized geometry established using the genetic algorithm is done to
understand the riblets-induced enhancement in the aerodynamic efficiency of the
airfoil.
