A Stochastic Reliability Model for Application in a Multidisciplinary Optimization of a Low Pressure Turbine Blade Made of Titanium Aluminide

Currently, there are a lot of research activities dealing with gamma titanium aluminide (γ-TiAl) alloys as new materials for low pressure turbine (LPT) blades. Even though the scatter in mechanical properties of such intermetallic alloys is more distinctive as in conventional metallic alloys, stochastic investigations on γ -TiAl alloys are very rare. For this reason, we analyzed the scatter in static and dynamic mechanical properties of the cast alloy Ti-48Al-2Cr-2Nb. It was found that this alloy shows a size effect in strength which is less pronounced than the size effect of brittle materials. A weakest-link approach is enhanced for describing a scalable size effect under multiaxial stress states and implemented in a post processing tool for reliability analysis of real components. The presented approach is a first applicable reliability model for semi-brittle materials. The developed reliability tool was integrated into a multidisciplinary optimization of the geometry of a LPT blade. Some processes of the optimization were distributed in a wide area network, so that specialized tools for each discipline could be employed. The optimization results show that it is possible to increase the aerodynamic efficiency and the structural mechanics reliability at the same time, while ensuring the blade can be manufactured in an investment casting process