Our world is facing unprecedented environmental challenges. Keeping the global temperature rise below 1.5°C implies a mandatory drop in CO2 emissions. Against this backdrop, the EC has issued the European Green Deal: an ambitious plan towards a fully sustainable economy, including aviation. With one million species endangered, biodiversity restoration is another key issue. Once aviation has recovered from the COVID pandemic effects, global air traffic as a major enabler of connectivity and economic growth will resume and keep increasing. This emphasizes the challenge of reducing the environmental impact of the air transportation sector as a whole. OLGA partners (airports, airline, handler, industry, research, SMEs) unite a wealth of expertise to contribute to solving this complex challenge: efficient and carbon neutral airport and airline operations, sustainable logistics, smart energy & mobility, intermodality for passengers and freight, emission/air quality assessments, green construction and circular end-of-life solutions. Sustainable Aviation Fuels supply chains will be integrated in conventional jet fuel infrastructure. Complementary types of low-emission mobilities, electric ground support equipment, hydrogen infrastructure and reduced carbon airside operations will be demonstrated. OLGA will achieve significant quantified advances already within the first three years, ready for exploitation by partners. This will lead to proven CO2 reduction, air quality improvement and biodiversity preservation with involvement of the entire sector's value chain. Sustainable impacts will be realised on societal, environmental and economic levels at local, national and EU scale. OLGA will have a duration of 60 months, requesting a 25 MEuros grant. OLGA's airports are uniquely positioned to showcase the environmental innovations, while the airports of Zagreb and Cluj will prove scalability and EU-wide applicability.

PERF-AI will apply Machine Learning techniques on flight data (parametric & non-parametric approaches) to accurately measure actual aircraft performance throughout its lifecycle. Within current airline operations, both at flight preparation (on-ground) & at flight management (in-air) levels, the trajectory is first planned, then managed by the Flight Management System (FMS) using a single manufacturer’s performance model that is the same for every aircraft of the same type, & also on weather forecast that is computed long before the flight. It induces a lack of accuracy during the planning phase with a flight route pre-established at specific altitudes & speeds to optimize fuel burn, from take-off to landing using aircraft performances that are not those of the real aircraft. Also, the actual flight will usually shift from the original plan because of Air Traffic Control (ATC) constraints, adverse weather, wind changes & tactical re-routing, without possibility for the flight crew, either using the FMS or through connected services to tactically recompute the trajectory in order to continuously optimize the flight path. This is in particular due to the limitations of the performance databases that the current systems are using. Hence, PERF-AI is focusing on identifying adequate machine learning algorithms, testing their accuracy & capability to perform flight data statistical analysis & developing mathematical models to optimize real flight trajectories with respect to the actual aircraft performance, thus, minimizing fuel consumption throughout the flight. The consortium consists of Safety-Line (FR) & INRIA (FR), having full expertise at Aircraft Performance & Data Science, hence, able to fully propose, test & validate different statistical models that will allow to accurately solve some optimization challenges & implement them in an operational environment. PERF-AI total grant request to the CSJU is 568 550€ with total project duration of 24 months.