Aeroelastic global structural optimization using an efficient CFD-based reduced order model

In aeroelastic structure optimization, the structural model needs to be modified repeatedly to meet all targets. Although computational fluid dynamics (CFD) based reduced order models (ROMs) have been successfully applied to transonic aeroelastic analysis, the existing CFD-based ROMs are at a fixed flight condition for a frozen aeroelastic model configuration. The aerodynamic and structural model have to be reconstructed to ensure accuracy, when a structural modification was made. These reconstructions take a considerable time and the computational costs become prohibitive. To overcome the realistic challenge, we have developed an efficient CFD-based ROM, which is robust to aeroelastic system. This paper presents a new optimization process using the efficient method for aeroelastic global structural optimization. The optimization process employs Genetic Algorithms (GAs) as optimization tool. In order to assess the performance of presented optimization process, the AGARD 445.6 wing model is taken as numerical example. The results show that the most feasible and optimal solutions are effectively obtained by the presented optimization process