Performance Optimization of Airfoil Designs for Enhanced Lift-to-Drag Ratios in Subsonic Flow Conditions

Yangqing Ming

doi:10.62051/ijmee.v8n5.05

Authors

Yangqing Ming Faculty of Natural, Mathematical & Engineering Sciences, King's College London, London WC2R 2LS, United Kingdom

DOI:

https://doi.org/10.62051/ijmee.v8n5.05

Keywords:

Airfoil Optimization, Lift-to-drag Ratio, Genetic Algorithm, Computational Fluid Dynamics

Abstract

The paper explores the use of a combined approach of computational fluid dynamics and genetic algorithm in improving the performance of airfoils in subsonic sub-flows to achieve high lift and low-drag ratios. Airfoil shapes are modeled with the use of PARSEC geometric parameterization with eleven design variables, which allows exploring the design space systematically and with physical realizations. Simulations of Reynolds-Averaged Navier-Stokes with Spalart-Allmaras turbulence models offer aerodynamic performance analysis at Reynolds number at Re = 3×10⁶ over angles of attack between -4° to 16°. The genetic algorithm optimization model, which uses tournament selection, simulated binary crossover, and polynomial mutation operators, used populations of 50 individuals which evolved over 100 generations to maximize the lift-to-drag ratio at cruise conditions (α = 4°). The findings show that peak L/D = 98.5, which is equivalent to an increase of 26.5% over NACA 2412 base level and 38.7% over NACA 0012. The streamlined design has lift coefficient Cₗ = 0.52 and drag coefficient Cⴅ = 0.00528 by optimized pressure distribution with increased suction peak and better aft pressure recovery. The results of the computational predictions are in great agreement with the experimental validation data with mean absolute error of 2.8% and 4.2% mean error of lift coefficient and drag coefficient respectively, as well as correlation coefficients higher than R² = 0.99. The study lays down systematic optimization procedures that can be used in the design of unmanned aerial vehicles, general aviation purposes, and wind turbine blades to give the aerospace engineers a solid computational foundation of aerodynamic performance improvements

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