On the Probabilistic Endurance Prediction Approach for Turbomachinery Blades and Vanes

Abstract

The design and aeromechanical assessments of turbomachinery blades and vanes comprise a wide range of complex processes that tend to be based on conventional deterministic methods. These processes often provide a “snapshot” evaluation of the new component designs at the nominal operating conditions. While the deterministic methods can predict the high cycle fatigue (HCF) endurance with reasonable accuracy, they assume that the conservative safety factors applied to cover for the parametric variations, uncertainties, and unknowns will not change during the product life cycle. This approach is intended to be conservative and in some cases may overlook the lack of robustness. The present paper proposes a robust design analysis approach based on probabilistic methodology for the aeromechanical assessment of rotor blades and stator vanes of turbomachinery. The robust design approach can account explicitly for the effects of design and manufacturing variability. This methodology can reduce the levels of conservatism in the deterministic approach and can provide a more thorough risk assessment. This paper offers a generalized aeromechanical analysis formulation based on probabilistic methods to evaluate the HCF capability of turbomachinery components. Herein, this methodology is demonstrated using a typical stator vane of an aero engine compressor and it is based on Monte-Carlo and design of experiment (DOE) simulations. The methodology consists of parametric sensitivity studies and identification of the most influential parameters that control the HCF endurance. Future ideas and roadmap of the aeromechanical probabilistic analysis capability development are also discussed.