A method for identifying global aerodynamic models from flight data in an efficient manner is explained and demonstrated. A novel experiment design technique was used to obtain dynamic flight data over a range of flight conditions with a single flight maneuver. Multivariate polynomials and polynomial splines were used with orthogonalization techniques and statistical modeling metrics to synthesize global nonlinear aerodynamic models directly and completely from flight data alone. Simulation data and flight data from a subscale twin-engine jet transport aircraft were used to demonstrate the techniques. Results showed that global multivariate nonlinear aerodynamic dependencies could be accurately identified using flight data from a single maneuver. Flight-derived global aerodynamic model structures, model parameter estimates, and associated uncertainties were provided for all six nondimensional force and moment coefficients for the test aircraft. These models were combined with a propulsion model identified from engine ground test data to produce a high-fidelity nonlinear flight simulation very efficiently. Prediction testing using a multi-axis maneuver showed that the identified global model accurately predicted aircraft responses.


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    Title :

    Efficient Global Aerodynamic Modeling from Flight Data


    Contributors:

    Conference:

    50th AIAA Aerospace Sciences Meeting and Exhibit ; 2012 ; Nashville, TN, United States


    Publication date :

    2012-01-09


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English




    Efficient Global Aerodynamic Modeling from Flight Data

    Morelli, E. / American Institute of Aeronautics and Astronautics | British Library Conference Proceedings | 2012





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