Abstract Evolutionary Algorithms (EAs) based on structured coding have been proposed for aerodynamic optimization of wing design. Fractional factorial design is used to investigate interactions of the design variables to determine the appropriate coding structure for EAs in advance. The present EAs is applied to wing design problems where the wing shape is modeled using the parameter set for th...

In the present talk, the strategies to apply the sensitivity analysis method to aerodynamic shape optimization problems of complex geometries are intensively discussed. To resolve the design of complicated aircraft geometries such as high-lift devices, wing/body configurations, overset mesh techniques are adopted. In addition, a noticeable sensitivity analysis method, adjoint approach, which sh...

This paper focuses on the demonstration of an integrated aerostructural method for the design of aerospace vehicles. Both aerodynamics and structures are represented using high-fidelity models such as the Euler equations for the aerodynamics and a detailed finite element model for the primary structure. The aerodynamic outer-mold line and a structure of fixed topology are parameterized using a ...

Optimizing the NACA0015 airfoil which is widely applied in small-scale vertical axis wind turbine to make it has a better aerodynamic performance. In the optimization process, using CST parameterization method to perturb the airfoil geometry, the thickness and camber of the airfoil are selected as the constraint, and the value of the maximum tangential force coefficient is chosen as the objecti...

A two-dimensional Newton–Krylov aerodynamic shape optimization algorithm is applied to several optimization problems in which the location of laminar-turbulent transition is free. The coupled Euler and boundary-layer solver MSES is used to obtain transition locations through the e method, which are then used in Optima2D, a Newton–Krylov discrete-adjoint optimization algorithm based on the compr...

The solution of a multiobjective multidisciplinary design optimization (MDO) using a genetic algorithm (GA) is considered. The objective functions in the optimization problem measure the aerodynamic feasibility based on the drag and lift coefficients and the electromagnetic feasibility based on the backscatter of the two-dimensional airfoil designs. The flow and backscatter are modeled by the t...