Multi-objective genetic algorithms (MOGAs) have been applied to optimize an inverse design of a transonic wing shape. First, the wing planform is optimized by solving a multidisciplinary optimization problem based on aerodynamic, structural, and fuel storing objectives and constraints. Second, three-dimensional target pressure distribution is optimized for the aerodynamic inverse design with the previously designed planform. Minimization of the profile drag and the induced drag is performed under constraints on lift and other design principles. Applying these two preprocessing procedures by using MOGAs, Pareto surfaces can be studied for tradeoffs among multiple objectives. Thus, a designer is able to choose a good compromise for wing planform and target pressures for the inverse design. Corresponding for wing surface geometry is obtained by Takanashi's inverse method, and a sample design result is given.
ASJC Scopus subject areas
- Aerospace Engineering