Imagine being able to test a new airplane wing or engine on a computer so accurately that you barely need to build physical prototypes. This project uses smart AI to predict how air flows around a plane instantly, rather than waiting days for slow simulations. It's like having a digital mirror of the aircraft that predicts when parts will break before they actually do.
Aircraft manufacturers struggle to reduce CO2 emissions while maintaining growth because traditional design and testing cycles are too slow and expensive. There is a critical need to account for manufacturing uncertainties without building endless physical prototypes.
A suite of digital enablers including an open-source MDO engine (GEMSEO), AI-based flow-field predictors, and digital twin tools for heat exchangers and engine components.
If you are an aircraft manufacturer dealing with high costs of testing green technologies — this project developed digital enablers and MDO engines that reduce time and cost for entry-into-service. It allows for the design of high bypass-ratio fans with less risk.
If you are a maintenance provider dealing with unpredictable part failures — this project developed smart health assessment tools and digital twins. These tools allow for smart prototyping and upkeep based on real-world operational variability.
If you are a software company dealing with slow CFD simulation speeds — this project developed a hybrid deep learning system that predicts flow-fields instantaneously. This can be integrated into design tools to speed up the engineering cycle.
Based on available project data, no specific commercial pricing is provided, but the project utilized a EU contribution of EUR 4,720,525 to develop these capabilities.
Yes, the project validated its methodologies through 8 industrial test cases representative of aircraft and engine manufacturers.
The project mentions that the GEMSEO MDO engine is open-source, making it more accessible for industry use.
It integrates via plug-ins and new functionalities in the GEMSEO engine to ease the setup of distributed workflows and data fusion procedures.
The project runs from 2022-09-01 to 2025-12-31, suggesting that the tools are currently in the validation and demonstration phase.
The consortium is heavily weighted toward industrial application, with a 44% industry ratio (7 industrial partners, including 4 SMEs). This balance between 9 research organizations and 4 leading aeronautical industries ensures that the digital tools developed are not just theoretical but are tested against real-world aircraft and engine components.
Contact ONERA (France) for technical inquiries regarding the GEMSEO engine.
Contact us to connect with the NEXTAIR consortium for licensing or partnership opportunities.
