Uncertainties in blade flutter damage prediction under random gust
Artikel i vetenskaplig tidskrift, 2014

In the design of highly flexible engineering structures such as rotors of wind turbines, aeroelastic stability is an important issue. A bending-torsion oscillation problem of a model blade section with structural nonlinearity has been considered in the present study. The system is subjected to a horizontal random gust modeled as a stationary process. Uncertainty quantification in highlighting the relative importance of different sources of uncertainty on aeroelastic stability, and consequently the fatigue and failure is an important step of aeroelastic design, which is addressed here. The effect of different sources of uncertainty on the fatigue damage estimate of the structure is highlighted here. Specifically, the effect of the structural parameter, the choice of aeroelastic model (modeling error) and also the stress selection criterion for the damage estimate on the fatigue damage estimate is reported in this work. The structural parameter randomness is modeled through polynomial chaos expansion in analyzing its effect on the damage estimate. The unsteady inviscid flow-field in the aeroelastic model is resolved analytically and also using a higher fidelity vortex lattice algorithm and the relative effect on damage is seen. Finally, the effect of fatigue damage criterion selection is also observed. The damage calculation is done for torsion only, bending only and for multiaxial cases. Multiaxial stresses are converted to an 'equivalent' one using a signed von Mises criterion. A linear damage accumulation rule has been used to estimate the risk for fatigue damage.

Polynomial chaos expansion

Uncertainty quantification

Fatigue damage

Bending-torsion flutter


S. Venkatesh

Indian Institute of Technology, Madras

S. Sarkar

Indian Institute of Technology, Madras

Igor Rychlik

Chalmers, Matematiska vetenskaper, matematisk statistik

Göteborgs universitet

Probabilistic Engineering Mechanics

0266-8920 (ISSN)

Vol. 36 45-55


Sannolikhetsteori och statistik