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Emulating natural mechanisms in technology has become a very efficienttechnique to optimize and improve the current machinery. Riblets are such kindsof bio-inspired surface patterns which are seen on Sharks. Their geometricproperties induce secondary flows resulting in lower drag, allowing Sharks toachieve such high speeds. Secondary flows are broadly subcategorized intoPrandtls first and second kind; the secondary flows induced by riblets belongprimarily to Prandtls second kind. These secondary flows have been proven todelay the boundary layer separation by reducing momentum losses. This paperaims to optimize the use of these bio-inspired patterns on an airfoil. Byapplying the ribletted surface on an airfoil, the boundary layer separation canbe delayed, thus leading to a reduction in drag and increasing the criticalangle of attack. Specific geometric properties such as the height and thewavelength of the riblets are varied to find the most optimal design. Thedesign framework couples the optimization algorithm, computational fluiddynamics, and post-processing analysis. An Invasive Weed Model is implementedfor optimization due to its commendable performance in converging close toglobal optima. The optimization process is initialized by generating apopulation of riblet profiles with randomly distributed geometry parameters.These profiles are then evolved over generations with the objective to minimizethe drag, which is computed through Computational Fluid Dynamics simulationsconducted on OpenFOAM. The optimized geometries show a significant reduction indrag as compared to bare airfoils. Lastly, a flow field analysis of theoptimized geometry established using the genetic algorithm is done tounderstand the riblets-induced enhancement in the aerodynamic efficiency of theairfoil.

Metaheuristic Optimization Framework for Drag Reduction Using Bioinspired Surface Riblets