Summary
MYTHOS proposes 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, thus aiming at fulfilling the objective of decarbonize civil aviation as fore-seen by the ACARE SRIA short, mid and long-term Goals by 2050. To achieve these, the MYTHOS consor-tium 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 engi-neered to burn various types of environmentally friendly fuels, such as SAF, in the short and medium term, and hydrogen, in the long term.
The proposed work responds to the needs and objectives of the HORIZON-CL5-2022-D5-01-12: Towards a silent and ultra-low local air pollution aircrafts Call as described in detail below.
The proposed work responds to the needs and objectives of the HORIZON-CL5-2022-D5-01-12: Towards a silent and ultra-low local air pollution aircrafts Call as described in detail below.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101096286 |
| Start date: | 01-01-2023 |
| End date: | 31-12-2026 |
| Total budget - Public funding: | 3 135 145,00 Euro - 3 135 144,00 Euro |
Cordis data
Original description
MYTHOS proposes 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, thus aiming at fulfilling the objective of decarbonize civil aviation as fore-seen by the ACARE SRIA short, mid and long-term Goals by 2050. To achieve these, the MYTHOS consor-tium 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 engi-neered to burn various types of environmentally friendly fuels, such as SAF, in the short and medium term, and hydrogen, in the long term.The proposed work responds to the needs and objectives of the HORIZON-CL5-2022-D5-01-12: Towards a silent and ultra-low local air pollution aircrafts Call as described in detail below.
Status
SIGNEDCall topic
HORIZON-CL5-2022-D5-01-12Update Date
09-02-2023
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