Methods for Predicting Transonic Flutter Using Simple Data Models

Ames Research Center, Moffett Field, CA

A 2D polynomial curve fit of model parameter, a (semimajor axis): (a) regression on a, (b) model results for a, and (c) relative error in regression. (Image: NASA)

Aircraft moving at transonic speeds (i.e., ~0.7 to 0.85 Mach - or near the speed of sound) experience transonic wing flutter. Engineers have traditionally relied on experimental or computational methods to understand wing flutter for the design process. Modeling wing flutter using the customary computational methods requires tens of hours of simulations on a supercomputer that is costly to buy or rent. Having a method to model wing flutter aerodynamics without requiring supercomputer use would (a) increase the efficiency and decrease the cost of aircraft wing design and (b) enable real-time wing-flutter modeling to aid in-flight aircraft operation and control.

NASA’s Ames Research Center has developed a novel closed-form solution to model wing flutter aerodynamics for any aircraft wing (within a certain thickness regime and without camber). This closed-form solution can be readily extended to wing sections with camber. The closed-form solution matches, in near real-time, the complex supercomputer simulations at a fraction of cost and time necessary to perform transonic flutter modeling for an airfoil.

Transonic flutter is a pacing item in transport aircraft design in that it is crucial to characterize this phenomenon for each aircraft to prevent catastrophic failure. Aerodynamic study of flows around airfoils is a canonical problem that entails both experimental and computational approaches. While the transonic flutter prediction can be more accurate with high-fidelity computational fluid dynamics (CFD) methods than with unsteady potential flow methods, the computational cost is high. Therefore, computationally efficient methods for transonic flutter prediction continue to be of high interest to the aircraft design community.

NASA’s novel method eliminates the need for expensive calculations of aerodynamics of wing flutter, which typically takes tens of hours on a supercomputer.

Such calculations are now replaced by machine-learning-based closed form solutions that provide the solution almost instantaneously. The technology presents a new approach to predict the flow around pitching NACA00 series airfoils. NACA airfoils are generally symmetric, and thus they do not possess camber. However, the invention can readily extend to wings with camber.

This novel data modeling approach is orders of magnitude faster than the traditional CFD approach of predicting aerodynamic effects of transonic pitching airfoils. The data model is based on a subset of unsteady CFD simulations that train the model. The trained model then resolves the pitching airfoil in time for any other set on the order of a second, as compared with a complete CFD simulation that typically takes 30 hours on a supercomputer. The data model is demonstrated in this invention for transonic flow corresponding to Mach number of 0.755 over pitching NACA00 series airfoils for a reduced frequency range typical of flutter, i.e., k lies in the range 0.02-0.25.

NASA is actively seeking licensees to commercialize this technology. Please contact NASA’s Licensing Concierge at This email address is being protected from spambots. You need JavaScript enabled to view it. or call at 202-358-7432 to initiate licensing discussions. For more information, visit here .