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    Titel :

    Aerodynamic Data Predictions for Transonic Flows via a Machine-Learning-based Surrogate Model (AIAA 2018-1905)


    Beteiligte:

    Kongress:

    AIAA/ASCE/AHS/ASC Structures, dynamics and materials (Conference)



    Erscheinungsdatum :

    01.01.2018


    Format / Umfang :

    23 pages



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch



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