The project MYTHOS proposes to develop and demonstrate an innovative and disruptive design methodology for future short/medium range civil engines. For a complete decarbonization, this class of engines should be operating using a wide range of liquid and gaseous fuels including Sustainable Air Fuels (SAFs) and, ultimately, pure hydrogen.
To achieve this goal, the MYTHOS consortium develops and adopts a multidisciplinary multi-fidelity modelling approach for the characterization of the relevant engine components, deploying the full power of the method of machine learning. The latter will lead through hidden-physics discovery to advance data-driven reduced models which will be embedded in a holistic tool for the prediction of the environmental footprint of the civil aviation of all speeds. A unique aspect of the project is the high-fidelity experimental validation of the numerical approaches. MYTHOS consortium through this approach will contribute to reduce time-to-market for engines designed and engineered to burn various types of environmentally friendly fuels, such as SAF, in the short and medium term, and hydrogen, in the long term.
To develop a demonstrated innovative and disruptive design methodology for future short/medium range civil engines capable of using a wide range of liquid and gaseous fuels including SAFs and, ultimately, pure hydrogen.