Large Deformation Prediction of Wing Model and Geometric Nonlinear Aeroelastic Analysis

Large flexible aircraft like High-altitude Long-endurance (HALE) airplane and large transport airplane possess large structural deformation with aerodynamic loads, which makes the dynamic characteristics changing obviously. Structural deformation predictions are vital to large flexible aircraft design and aeroelastic simulations. Deformation calculation considering geometric nonlinearities with full order models lack of practicality due to low simulation efficiency. Traditional reduced-order model (ROM) based on least square approach obtains high simulation efficiency but require large amounts of sample data participating model building. This study investigates support vector regression (SVR) algorithm to build prediction model to calculate the static deformation of flexible structure considering geometric nonlinearities. Performance of the prediction models are compared under evaluation with root mean square error (RMSE). Moreover, the prediction model can be coupled with aerodynamics models based on interpolation approach for static aeroelastic analysis. The non-planar vortex lattice method (VLM) is proposed here with appropriate accuracy and efficiency. Finally, a flexible wing model with single beam is adopted and the static aeroelastic response is compared between prediction model and wind tunnel test. The results demonstrate that the prediction model proposed has good performance and great practical application value.