Expected Outcome:
Project results are expected to contribute to all of the following expected outcomes:
- AI-assisted digital aircraft design, redesign and certification – in collaboration with existing or improved digital twins and virtual products.
- AI-assisted design tools for aircraft requirement definition, validation and verification, to improve efficiency of the system design activities.
- AI-assisted digital (i) aircraft manufacturing, (ii) aircraft operation, condition monitoring and prediction, (iii) maintenance, repair and overhaul operations.
Scope:
This topic focuses on the development of robust AI-assisted capabilities that will work in tandem to digital twins. The term aircraft includes propulsion, aerostructures, systems and their integration, if not explicitly addressed.
Proposals may focus on:
- Robust, reliable, verifiable and accelerated training of AI-assisted digital capabilities;
- Efficient and high-performance AI-assisted computing, in connection to complex multi-disciplinary design and optimisation methodologies – at system and/or at integrated level;
- Protocols, standards and AI-assisted digital capabilities for the entire aircraft manufacturing and MRO supply chain;
- Accelerated experimental validation capabilities of machine learning algorithms, for selected industrial use cases, linked to novel EU research and technology infrastructures;
- Verifiable and reproduceable usage of Generative AI and Large Language Models for recommendation systems and information retrieval, especially within areas under authority regulation to maintain airworthiness and safety of airframes and their major systems (i.e. using Explainable Generative AI or surrogate models);
- AI-assisted prescriptive maintenance procedures for efficient condition-based maintenance and maximized circularity by optimizing the utilization of the globally available high-value items (components, engines, airframes);
- AI-assisted maintenance assistance systems for efficient human-in-the-loop integration.
