Shape Optimization of Airfoils in Transonic Flow Using a Multi-Objective Genetic Algorithm

2013 ◽  
Author(s):  
Xiaomin Chen ◽  
Ramesh K. Agarwal
Keyword(s):  
Genetic Algorithm ◽  
Shape Optimization ◽  
Transonic Flow ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

Leading Edge Shape Optimization of Whitcomb IL Airfoil in Transonic Flow Using a Multi-Objective Genetic Algorithm (MOGA)

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
R. Jiniraj ◽  
T. Logesh ◽  
D. Rajapatel
Keyword(s):  
Genetic Algorithm ◽  
Shape Optimization ◽  
Stokes Equations ◽  
Leading Edge ◽  
Navier Stokes ◽  
Airfoil Surface ◽  
Navier Stokes Equations ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Icem Cfd

Leading edge shape optimization of transonic airfoils requires creating an airfoil surface that reduces the drag divergence due to transonic shocks by either delaying them or reducing their strength at a given transonic cruise speed while maintaining the lift. Aircrafts like Boeing 757, Airbus A300, Boeing 777 and McDonnell Douglas AV-8B Harrier II use Whitcomb IL supercritical airfoil for efficient aerodynamic performance in transonic conditions. This study employs a multi-objective genetic algorithm for shape optimization of leading edge of the Whitcomb IL airfoil to achieve three objectives, namely dilation of shock, reduction in leading edge radius and increment of lift at a given transonic Mach number and at the given AoA. The commercially available software ICEM CFD and Fluent are employed for calculation of the flow field using the RANS (Reynolds-averaged Navier-Stokes equations) in conjunction with a two equation turbulence model. It is shown that the (MOGA) Multi-objective genetic algorithm can generate superior airfoil compared with Whitcomb IL airfoil by achieving three objectives. The optimized airfoil configuration is validated by wind tunnel testing facility.

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