Validation of a Robust Flutter Prediction by Optimization
ChanHoon Chung* and SangJoon Shin**
International Journal of Aeronautical and Space Sicences, vol. 13, no. 1, pp.70-84, 2012
Abstract : In a modern aircraft, there are many variations in its mass, stiffness, and aerodynamic characteristics. Recently, an analytical
approach was proposed, and this approach uses the idea of uncertainty to find out the most critical flight flutter boundary due
to the variations in such aerodynamic characteristics. An analytical method that has been suggested to predict robust stability
is the mu method. We previously analyzed the robust flutter boundary by using the mu method, and in that study, aerodynamic
variations in the Mach number, atmospheric density, and flight speed were taken into consideration. The authors¡¯ previous
attempt and the results are currently quoted as varying Mach number mu analysis. In the author¡¯s previous method, when the
initial flight conditions were located far from the nominal flutter boundary, conservative predictions were obtained. However,
relationships among those aerodynamic parameters were not applied. Thus, the varying Mach number mu analysis results
required validation. Using an optimization approach, the varying Mach number mu analysis was found out to be capable of
capturing a reasonable robust flutter boundary, i.e., with a low percentage difference from boundaries that were obtained by
optimization. Regarding the optimization approach, a discrete nominal flutter boundary is to be obtained in advance, and based
on that boundary, an interpolated function was established. Thus, the optimization approach required more computational
effort for a larger number of uncertainty variables. And, this produced results similar to those from the mu method which had
lower computational complexity. Thus, during the estimation of robust aeroelastic stability, the mu method was regarded as more
efficient than the optimization method was. The mu method predicts reasonable results when an initial condition is located near
the nominal flutter boundary, but it does not consider the relationships that are among the aerodynamic parameters, and its
predictions are not very accurate when the initial condition is located far from the nominal flutter boundary. In order to provide
predictions that are more accurate, the relationships among the uncertainties should also be included in the mu method.
Keyword : Robust aeroelasticity, Worst case flutter boundary, Uncertainty, Unsteady aerodynamics, Optimization, |