– This paper aims to focus on the stochastic analysis of composite rotor blades with matrix cracking in forward flight condition.
– The effect of matrix cracking and uncertainties are introduced to the aeroelastic analysis through the cross-sectional stiffness properties obtained using thin-walled beam formulation, which is based on a mixed force and a displacement method. Forward flight analysis is carried out using an aeroelastic analysis methodology developed for composite rotor blades based on the finite element method in space and time. The effects of matrix cracking are introduced through the changes in the extension, extension-bending and bending matrices of composites, whereas the effect of uncertainties are introduced through the stochastic properties obtained from previous experimental and analytical studies.
– The stochastic behavior of helicopter hub loads, blade root forces and blade tip responses are obtained for different crack densities. Further, assuming the behavior of progressive damage in same beam is measurable as compared to its undamaged state, the stochastic behaviors of delta values of various measurements are studied. From the stochastic analysis of forward flight behavior of composite rotor blades at various matrix cracking levels, it is observed that the histograms of these behaviors get mixed due to uncertainties. This analysis brings out the parameters which can be used for effective prediction of matrix cracking level under various uncertainties.
– The behavior is useful for the development of a realistic online matrix crack prediction system.
– Instead of introducing the white noise in the simulated data for testing the robustness of damage prediction algorithm, a systematic approach is developed to model uncertainties along with damage in forward flight simulation.
Aeroelastic analysis of composite blades with matrix cracking and uncertainties
Aircraft Engineering and Aerospace Technology: An International Journal ; 87 , 3 ; 189-205
2015-05-05
17 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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