Abstract
Hypersonic aircraft have been rapidly developed in recent years both theoretically and experimentally. Aerothermoelastic simulation is very challenging due to its inherent complexity, but physical tests are a workable approach. Flutter tests with variable speed are a popular alternative to hypersonic tests which provide nonstationary structural response data. This paper proposes a nonstationarity assessment method based on energy distribution in the time-frequency domain. The proposed method reveals the nonstationarity level corresponding to the appropriate modal identification algorithm or flutter boundary prediction (FBP) method. Several classic flutter criteria are utilized to build a hypersonic aircraft FBP framework. Numerical simulation and experimental applications demonstrate the effectiveness and feasibility of the proposed method, which facilitates accurate flutter predictions for the subcritical turbulence response during hypersonic flutter flight.
Highlights
Flutter quality is a significant issue in the development of hypersonic aircraft
This paper proposes a nonstationarity assessment method based on energy distribution in the time-frequency domain
The selected test data came from a specific type of aircraft transonic flutter flight test which includes both subsonic and transonic periods
Summary
Flutter quality is a significant issue in the development of hypersonic aircraft. Problematic aspects of hypersonic flight include extreme aerodynamic heating and complex hypersonic flow field effects [1,2,3]. Existing test and data processing methods are a workable foundation for further theoretical development hypersonic aircraft simulation techniques. Structural response signal analysis can help to further improve both simulation techniques as well as innovative structure designs. There is, to this effect, urgent demand for effective hypersonic flutter flight test data processing methods. Several algorithms for modal parameter identification or flutter boundary prediction (FBP) have been established based on the stationary stochastic process theory; they include fast Fourier transform (FFT) [17, 18], random decrement technique (RDT) [19], natural excitation technique combined. A data processing framework for structural response was designed and numerical simulations and experiments validate the proposed method and framework
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