ARIADNE - Artificial Intelligence Application for the Development of New AeroEngines

Project: Research project

Project Details

Description

In order to strengthen European aviation industry for the future and to increase its competitiveness the European Commission released its vision for aviation Flightpath 2050 in 2011. Among other goals, it aims at the reduction of CO2 emissions by 75 % compared to 2000. In order to achieve this goal the efficiency of modern aero-engines has to be improved considerably, whereas artificial intelligence (AI) and digitalization will play a key role (BMK, 2020).
The Institute for Thermal Turbomachinery and Machine Dynamics at Graz University of Technology has been investigating the aerodynamics of intermediate turbine ducts, a key component of modern aero-engines, for many years. This research provides the institute with a large and well evaluated data basis. It shall be used for AI application in the project ARIADNE. Together with an informatics institute and two Austrian SMEs following goals shall be pursued to provide tools for the optimization of future intermediate turbine ducts in aero-engines:
• Setup of a data bank of the aeronautics of intermediate turbine ducts, based on measurements and simulation of different designs at various inflow conditions. The structure of the data bank shall allow a fast and efficient utilization for AI application.
• Development of methods for data reduction for efficient AI application based on POD methods and Machine Learning
• Development of a method for the fast flow prediction of new designs observing the physics of fluid mechanics
• Development of a tool for the evaluation of measurements in turbine ducts in order to find possible sensor errors
• Development of a tool for the evaluation of flow simulations of turbine ducts in order to find possible model errors or computational mesh problems
• Application of the developed tools to obtain innovative knowledge of principles in the flow of intermediate turbine ducts
• Finally, the developed tools shall be combined with an optimizer with the goal of fast and efficient design optimization, much faster than with flow simulation based optimizing methods
StatusNot started
Effective start/end date1/09/2131/08/24