Efficient Flutter Prediction Using Reduced-Order Modeling

Abstract

Typical aerodynamic shape optimization and multidisciplinary optimization algorithms omit high-fidelity flutter predictions due to the associated computational costs. This paper presents a model order reduction framework as a step toward flutter-constrained aircraft optimization. The Euler equations linearized about a steady-state solution of the nonlinear Euler equations are used as the governing unsteady flow equations. Using a proper orthogonal decomposition approach, a reduced basis is constructed onto which the governing equations are projected. The result is a linear reduced-order model (ROM) with significantly fewer degrees of freedom capable of rapidly approximating aerodynamic forces. This ROM is coupled to a linear structural model to create a single monolithic aeroelastic system. The eigenvalues of the resulting system are analyzed for various flow conditions to determine the onset of flutter in the system. To ensure the stability of the ROM, the use of a stabilizing inner product is demonstrated. The flutter boundaries obtained for both a two-degree-of-freedom airfoil structure and the AGARD 445.6 wing model show good agreement with the full-order model and with the literature.