Efficient Aircraft Flutter Analysis Using Model Order Reduction with Error Estimation

Speaker: Brandon Lowe, University of Toronto
February 22, 2022

Presentation

Abstract

Flutter safety is an important consideration in the design and development of aircraft. However, fast and accurate flutter analysis in the transonic regime remains an open problem due to the high computational cost associated with accurately modeling transient aerodynamic forces. Model order reduction techniques can be applied to reduce computational expenses while retaining the accuracy of high-fidelity models. However, the ad hoc nature of model order reduction makes it nearly impossible to develop best practice training methods which consistently produce accurate reduced-order models (ROMs) for flutter analysis while minimizing computational expenses. To address this challenge, a model order reduction approach for flutter prediction with error estimation is presented. A projection-based model order reduction approach is used to create an aerodynamic ROM which is coupled to a structural model to create a primal aeroelastic ROM. Flutter analysis is conducted by analyzing the eigenvalues of the aeroelastic ROM. A dual-weighted residual-based error estimator is presented which approximates the error in the eigenvalues obtained from the reduced eigenproblem relative to the eigenvalues from the high-dimensional aeroelastic model. Solutions of the dual problem are shown to be the left eigenpair and are efficiently computed using a dual aeroelastic ROM. Additionally, an extension to the eigenvalue error estimator for approximations of the error in the predicted flutter point is also presented. With the application of error estimation, the primal and dual aeroelastic ROMs are iteratively constructed to ensure eigenvalue and flutter point prediction accuracy. The new ROM-based flutter analysis method provides the user with approximate aeroelastic eigenvalues, an approximate flutter point, and an estimate of the error in both these quantities. This methodology is shown to be computationally efficient, minimize the requirement for user knowledge, and provide user-prescribed accuracy for flutter prediction relative to the high-dimensional aeroelastic model.

Biography

Brandon Lowe is a Ph.D. candidate at the University of Toronto Institute for Aerospace Studies in the Computational Aerodynamics Group under the supervision of Professor David W. Zingg. His research focuses on the development and application of projection-based model order reduction with error estimation for aircraft flutter prediction. Prior to his doctoral studies, Brandon received a B.A.Sc. in Mechanical Engineering in 2016 from the University of Ottawa.

Seminar Participation

Attending In Person

For select seminars, you may wish to attend in-person if you are in the vicinity of NASA Ames Research Center. These AMS seminars are held in Building N258 in Room 127, just off the front lobby. Sessions available to attend in-person will be indicated in the announcement information. In-person participants without NASA badges will need a valid visitor badge (US citizenship or permanent residency is required) to enter the facility.

Join Us Online

To attend an AMS seminar, click on the Microsoft Teams link in the seminar description. You can connect through the desktop Teams App if you have it, or you can select "Watch on the Web Instead" to enter the meeting as a guest. Please ensure that you've muted your microphone in Teams before you select "Join Now" to enter the meeting lobby.