Systems and methods that include and/or leverage a neural network to approximate the steady-state performance of a turbine engine are provided. In one exemplary aspect, the neural network is trained to model a physics-based, steady-state cycle deck. When properly trained, novel input data can be input into the neural network, and as an output of the network, one or more performance indicators indicative of the steady-state performance of the turbine engine can be received. In another aspect, systems and methods for approximating the steady-state performance of a “virtual” or target turbine engine based at least in part on a reference neural network configured to approximate the steady-state performance of a “fielded” or reference turbine engine are provided.


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    Titel :

    Neural Network for Steady-State Performance Approximation


    Beteiligte:

    Erscheinungsdatum :

    2018-09-20


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B64D Ausrüstung für Flugzeuge , EQUIPMENT FOR FITTING IN OR TO AIRCRAFT / F01D Strömungsmaschinen [Kraft- und Arbeitsmaschinen oder Kraftmaschinen], z.B. Dampfturbinen , NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, e.g. STEAM TURBINES / G07C TIME OR ATTENDANCE REGISTERS , Zeit- oder Anwesenheitskontrollgeräte