Multi-stage Design Approach for High Fidelity Aerodynamic Optimization of Multi-body Geometries by Kriging Based Models and Adjoint Variable Method

An efficient and high-fidelity design approach for wing-body configuration is presented. Depending on the size of design space and the number of design of variable, aerodynamic shape optimization is carried out via selective optimization strategy at each design stage. In the first stage, global optimization techniques are applied to planform design with a few geometric design variables. In the second stage, local optimization techniques are employed for wing surface design with a lot of design variables which can maintain a sufficient design space with a high DOF (Degree of Freedom) geometric change. For global optimization, Kriging method in conjunction with GA (Genetic Algorithm) is used. A searching algorithm of EI (Expected Improvement) points is introduced to enhance the quality of global optimization for the wing-planform design. For local optimization, a discrete adjoint method is adopted, and adjoint numerical dissipation is introduced to improve convergence behavior of the adjoint solver. By the successive combination of global and local optimization techniques, drag minimization is performed for a multi-body aircraft configuration in inviscid and viscous flow conditions while maintaining the baseline lift and the wing weight. Through the design process, performances of the test models are remarkably improved in comparison with the single stage design approach. The performance of the proposed design framework including wing planform design variables can be efficiently evaluated by the drag decomposition method, which can examine the improvement of various drag components, such as induced drag, wave drag and viscous drag.