Hybrid Gas Path Analysis Using Physical and Probabilistic Models for Considering Aerosols (T21#)

• Subject Area: Hydraulic and Turbo Engines and Piston Engines
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 119193472

The aim of the transfer project is to combine classical non-linear gas path analysis (GPA) methods with approaches from the field of artificial intelligence (AI) for data-driven time series modelling of engine component deterioration. This allows for the first time a consideration of the time-resolved aerosol loading from operation in the data-driven and engine-specific GPA. Together with the application partner LHT, the algorithm is trained, validated and applied engine-specifically with verified historical and current data.

• DFG Programme: Collaborative Research Centres (Transfer Project)
• Subproject of: SFB 871: Regeneration of Complex Capital Goods
• Applicant Institution: Gottfried Wilhelm Leibniz Universität Hannover
• Business and Industry: Lufthansa Technik AG, Engine Services,; HAM /TES-Z
• Project Head: Professor Dr.-Ing. Jens Friedrichs