AG Turbo TurboHyTec AP 4.3 – Probabilistic Design of Turbines
Project director: Prof. Dr.-Ing. habil. Ronald Mailach
Research Associate: Elmira Emmrich, M. Sc.
Scientific collaboration: AG TURBO TurboHyTec
Funding: BMWi, Rolls-Royce Deutschland, MTU Aero Engines AG
Schedule: 12/2023 - 11/2026
Description:
To ensure safe and efficient operation of current and future power engineering systems under changing requirements, it is necessary to accurately assess their service life. Probabilistic methods allow for the direct incorporation of uncertainties into lifetime calculations. This project focuses on adapting and applying probabilistic methods to engineering problems. It includes a feasibility study for the automatic parameterization of turbine geometry and the further development and extension of the Chair's internal graphical user interface for the surrogate model with new functions. Machine learning methods are being utilized. Additionally, new probabilistic methods are being developed, including investigations aimed at reducing the probabilistic parameters of the system under investigation while minimizing the loss of information.
The project results provide a foundation for improved ecological and economic resource utilization. The findings enable faster and more efficient development analyses, resulting in more robust products. This contributes significantly to the improvement of the development and design process for future highly efficient turbine components.
