Abstract: Devices and computer-implemented methods for analyzing aircraft trajectories, the method includes the steps of receiving data associated with a plurality of aircraft trajectories; breaking the trajectories down into a plurality of vectors, a vector comprising one or more sequences of enumerators; aligning multiple vectorized trajectories by shifting sequences of enumerators by one or more positions; and detecting one or more anomalies in one or more trajectories by unsupervised classification (e.g. DBSCAN). Developments describe the supervised determination of trajectory anomaly detection models, the use of density-based algorithms, the use of one or more neural networks and/or decision trees, one or more display steps, notably displaying root causes (explainable or understandable artificial intelligence), the processing of avionics data flows, etc. System (e.g. computing) and software aspects are described.

Abstract: Systems and methods for managing the flight of an aircraft, include the steps of receiving data from recordings of the flight of an aircraft; the data comprising data from sensors and/or data from the onboard avionics; determining the aircraft state at a point N on the basis of the received data; determining the state of the aircraft at the point N+1 on the basis of the state of the aircraft at point N by applying a model learnt by means of machine learning. Developments describe the use of the flight parameters SEP, FF and N1; offline and/or online unsupervised machine learning, according to a variety of algorithms and neural networks. Software aspects are described.

Abstract: Methods and systems for optimizing the flight of an aircraft are disclosed. The trajectory is divided into segments, each of the segments being governed by distinct sets of equations, depending on engine thrust mode and on vertical guidance (climb, cruise or descent). By assuming two, aerodynamic and engine-speed, models, data from flight recordings are received and a number of parameters from a parameter-optimization engine is iteratively determined by applying a least-squares calculation until a predefined minimality criterion is satisfied. The parameter optimization engine is next used to predict the trajectory point following a given point. Software aspects and system (e.g. FMS and/or EFB) aspects are described.

Abstract: Computer-implemented devices and methods for analysing navigation databases are provided, particularly including the steps of: comparing two databases and determining a list of different procedures between the databases (referred to as deviations); describing one or more of these procedures by N distinct flight scenarios, corresponding to different combinations of variations in flight parameter values (combinations of variations in performance, meteorological and/or speed parameters); in an aeronautical computer e.g. FMS, for one flight scenario, determining one or more flyable trajectories associated with one (or more or each) ?P procedure. Developments describe determining operational impacts, machine learning processes, analyses of deviation by trajectory, by procedure or by deviations between procedures. System and software aspects are described.

Abstract: The invention relates to a method for generating at least one engine-out standard instrument departure trajectory, called EOSID trajectory, for at least one take-off runway, each EOSID trajectory being associated with a respective take-off runway. The method is implemented by an electronic generating device and comprises, for each take-off runway, the following steps: acquiring a set of characteristic(s) relating to the take-off runway, the set of characteristic(s) comprising an orientation of the axis of the take-off runway with respect to North; calculating, from the acquired set of characteristic(s), at least one flight segment of a respective EOSID trajectory, the heading of each segment being defined with respect to the orientation of the take-off runway axis; and generating each EOSID trajectory from the calculated flight segment(s).

Abstract: Devices and computer-implemented methods for analyzing aircraft trajectories, the method includes the steps of receiving data associated with a plurality of aircraft trajectories; breaking the trajectories down into a plurality of vectors, a vector comprising one or more sequences of enumerators; aligning multiple vectorized trajectories by shifting sequences of enumerators by one or more positions; and detecting one or more anomalies in one or more trajectories by unsupervised classification (e.g. DBSCAN). Developments describe the supervised determination of trajectory anomaly detection models, the use of density-based algorithms, the use of one or more neural networks and/or decision trees, one or more display steps, notably displaying root causes (explainable or understandable artificial intelligence), the processing of avionics data flows, etc. System (e.g. computing) and software aspects are described.

Abstract: A method is provided for managing the revising of a flight plan of an aircraft implemented by at least two systems, one being of avionics type (qualified, certified) and the other not. From a flight plan, flight plan revisions are determined, even assessed, then one or more of these revisions are selected and/or combined. Subsequently, these combinations are processed by the avionics system and the corresponding avionics parameters are calculated. By comparing the different results of avionics quality, the impact of each revision can be quantified then rendered to the pilot to assist in his or her decision-making, in particular with regard to negotiating the revisions with air traffic control. Combinatorial optimization and learning steps are described, as are system and software aspects.

Abstract: Computer-implemented methods and systems for managing the lifecycle of aeronautical data stored in a blockchain, include steps of receiving or sending aeronautical data, and encrypting and/or decrypting these data using a smart contract. The use of a plurality of blockchains, and the facts and rules of management of the lifecycle of the data (e.g. programmed obsolescence, time-dependent quality indicator, etc.) are described. Transactional aspects; the use of oracle services; asymmetric, homomorphic and post-quantum encryption methods; the use of chameleon hash functions, so as to manipulate at least partially redactable blockchains; and machine-learning techniques, are in particular described with respect to a number of embodiments. Software and system aspects are described.

Abstract: Systems and methods for managing the flight of an aircraft, include the steps of receiving data from recordings of the flight of an aircraft; the data comprising data from sensors and/or data from the onboard avionics; determining the aircraft state at a point N on the basis of the received data; determining the state of the aircraft at the point N+1 on the basis of the state of the aircraft at point N by applying a model learnt by means of machine learning. Developments describe the use of the flight parameters SEP, FF and N1; offline and/or online unsupervised machine learning, according to a variety of algorithms and neural networks. Software aspects are described.

Abstract: Methods and systems for optimizing the flight of an aircraft are disclosed. The trajectory is divided into segments, each of the segments being governed by distinct sets of equations, depending on engine thrust mode and on vertical guidance (climb, cruise or descent). By assuming two, aerodynamic and engine-speed, models, data from flight recordings are received and a number of parameters from a parameter-optimization engine is iteratively determined by applying a least-squares calculation until a predefined minimality criterion is satisfied. The parameter optimization engine is next used to predict the trajectory point following a given point. Software aspects and system (e.g. FMS and/or EFB) aspects are described.

Abstract: The present invention relates to a method for verifying the ability of an aircraft to attain an endpoint from a starting point, comprising the steps of supplying an external evolution context of the aircraft, supplying an internal evolution context of the aircraft; calculating a trajectory of the aircraft between the starting point and the endpoint according to the external evolution context and the internal evolution context of the aircraft and according to a predetermined strategy for circumventing three-dimensional obstacles and associating an endpoint attainability state. When there is at least one trajectory between the starting point and the endpoint, the method further comprising a step of estimating a surplus of energy of the aircraft at the endpoint of the calculated trajectory.

Abstract: A method is provided for managing the revising of a flight plan of an aircraft implemented by at least two systems, one being of avionics type (qualified, certified) and the other not. From a flight plan, flight plan revisions are determined, even assessed, then one or more of these revisions are selected and/or combined. Subsequently, these combinations are processed by the avionics system and the corresponding avionics parameters are calculated. By comparing the different results of avionics quality, the impact of each revision can be quantified then rendered to the pilot to assist in his or her decision-making, in particular with regard to negotiating the revisions with air traffic control. Combinatorial optimization and learning steps are described, as are system and software aspects.