| Περίληψη: | A probabilistic methodology for the reliability analysis of composite rotor blades at the ply level was developed. The proposed methodology involves (i) the quantification of the uncertainties (physical, statistical and model) related to the material properties and the extreme aero-elastic loads based on experimental data as well as on 10 min load simulations respectively, (ii) the identification of the critical failure modes of the composite structure in terms of limit state functions and (iii) the selection of an appropriate reliability method to perform the analysis. It is pointed out that the reliability method should be able to handle the considerably large number of limit state function introduced by the ply level reliability approach and estimate the failure probability of the structure. To efficiently deal with the problem, an appropriate implementation of the Response Surface Method combined with crude Monte Carlo simulation was proposed.
The methodology was implemented for two real rotor blade designs, namely a 30m Glass/Polyester and the 65m UPWIND reference rotor baled. Initially, calculations were performed for the first case study using a 3D shell FE formulation in a commercial probabilistic code. An efficient procedure was introduced to define the stochastic character of the concentrated loads acting on the 3D FE model starting from load time series of sectional stress resultants from aero-elastic beam simulations. For the first time such a detailed model was analyzed and assessed in a probabilistic base. Nevertheless, a considerable CPU time was in need for the performance of such a reliability analysis. The development of an efficient probabilistic tool capable to perform consecutive reliability analyses at the ply level of the composite rotor blade structure and prove valuable for the probabilistic design was carried out. To demonstrate the efficiency of the developed tool, the impact of various probabilistic modelling assumptions directly on the β-index value of a rotor blade design was studied.
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