Inverse design optimization of transonic wings based on multi-objective genetic algorithms

Multi-objective genetic algorithms (MOGAs) have been applied to optimize an inverse design of a transonic wing shape. First, the wing planform is opti mized by solving a multidisciplinary optimization problem based on aerodyna mic, 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 p rofile drag and the induced drag is performed under constraints on lift and other design principles. Applying these two preprocessing procedures by us ing MOGAs, Pareto surfaces can be studied for tradeoffs among multiple obje ctives. Thus, a designer is able to choose a good compromise for wing planf orm and target pressures for the inverse design. Corresponding for wing sur face geometry is obtained by Takanashi's inverse method, and a sample desig n result is given.