Abstract
Low-cycle fatigue is typical failure mode of aero-engine turbine disk, traditional reliability analysis method based on the binary state assumption has certain limitations for turbine disk reliability evaluation, because it doesn't consider the change of damage strength parameter caused by loading sequences and the enhanced damage by small load. On the basis of fatigue reliability analysis of the turbine disk, this paper considers the fuzzy state assumption of turbine disk, then select the membership function and indicate fuzzy failure probability of turbine disk, which can be transformed into a series of conventional failure probability by Gaussian quadrature. An active learning Kriging model is used to orderly calculate the failure probability corresponding to different limit state functions and the fuzzy failure probability of turbine disk. A global sensitivity index based on fuzzy failure probability is established to analyze the influence of input variables on the fuzzy failure probability, which is helpful to the reliability design and structural optimization of the turbine disk.
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