Application of unsteady aerodynamic reduced-order modeling techniques to a complex configuration

In the present work, different nonlinear reduced-order modeling (ROM) approaches are employed to assess their performance and efficiency for unsteady aerodynamic computations. The ROM techniques are applied to a complex aircraft model in order to indicate their potential for industrial applications. On the one hand, a neurofuzzy-model-based ROM is employed to compute the aerodynamic response due to small-amplitude motions across variable angles of attack. On the other hand, the unsteady surface pressure distribution is predicted by combining system identification methods with the proper orthogonal decomposition (POD). For demonstrations purposes, NASA’s common research model (CRM) configuration is investigated at transonic flow conditions, while forced-motion computational fluid dynamics (CFD) simulations are carried out to obtain the aerodynamic responses induced by structural mode-shape-based deflections. It is shown that the presented methods can be applied to speed-up multidisciplinary analyses with respect to industry-relevant configurations.