Probabilistic Property Prediction of Aero-Engine Components for Fatigue

Abstract

Service lives for critical rotating parts in aero engine gas turbines are declared using deterministic lifing calculations based on fixed point values of key mechanical properties and factors to allow for the scatter. However, novel probabilistic lifing algorithms have been developed, which are able to take into account the degree of scatter in the material properties throughout the component. Process simulation software has been developed to predict the material flow, residual stresses, microstructure and properties in components during the disc forging operations to ensure robust manufacturing routes. This allows the changes in the materials microstructure, and the mechanical property variation throughout the component, to be predicted as the crack initiation and propagation properties are significantly dependent on the grain structure. These two strains of research have been combined in an attempt to increase the reliability of service life predictions through modelling the scatter in the mechanical properties resulting from manufacturing variation. Results will be presented which indicate that significant life benefits can be obtained by adopting a location specific lifing method based on this approach.