AG Turbo RoboFlex project 4.4: Efficient probabilistic analysis processes under utilization of probabilistic methods for describing real geometry effects
Project leader: Prof. Dr.-Ing. habil. Ronald Mailach
Processor: Dipl.-Ing. Lukas Schlüter
Scientific collaboration: AG TURBO RoboFlex
Funding: BMWi, Rolls-Royce Deutschland
Schedule: 10/2019 - 09/2022
Summary:
Geometrical variability due to wear along with manufacturing scatter may have a great impact on the robustness of blades and vanes and thus on the Performance of gas turbines. Within the joint research program AG TURBO RoboFlex, these variations due to wear, especially in the region of the leading edge have to be parameterized and finally integrated into the in house tool Blade2Parameter (B2P). Thus an automated process chain needs to be developed in order to generate generic profiles with variable leading edge geometries. Next, probabilistic CFD-studies will be conducted for investigating the Impact of wear on the aerodynamic performance. Therein, the primary focus is on the blade’s leading edge, as it is of exceptional importance for the blade’s surrounding flow and exhibits the biggest geometric changes due to wear. Finally, by taking typical wear patterns as a function of the cycle number into account, an optimized leading edge design needs to be derived, which has a minimum of degradation in terms of efficiency and operational range. This design shall be proven by cascade measurements.
