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Aero-engine manufacturers need to eliminate high cycle fatigue failures to improve aircraft safety, engine reliability and cost of ownership. Additionally there is a strong need to be able to predict vibration levels in order to reduce lead times and to expand the freedom of the turbine blade designer to explore more optimal designs.
The objectives of this project are to provide good quality data with which to validate current and future prediction software, and to compare a variety of approaches to give an exchange rate between cost and accuracy.
To achieve these objectives, two experimental campaigns were devised. The first rig at EPFL was used to verify the superposition principle for forced response, since many prediction methods already assume that the aerodynamic force and the aerodynamic damping can be calculated independently. The second rig at DLR provided aerodynamic and vibration response validation data for a realistic turbine stage. The measurement programme was designed to allow validation at all stages throughout the prediction process so that errors can be accurately pinpointed.
The project has fulfilled its objectives. A database of the results was established and populated during the project, enabling an accessible record of all the results and also easy comparison of data from any source. The results show that many aspects of the prediction process are well modelled, but the prediction of unsteady aerodynamics remains the largest contributor to error.
Additionally the DLR rig showed a significant low engine order response and this will provide a useful head start for the follow on project: ADTurB II.
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