This paper summarizes the status of ongoing NASA research supported over the past eight years to advance computational capabilities for modeling civil aircraft loss of control due to airframe damage or wing stall. The research is motivated by a desire to exploit the capabilities of computational methods to create augmented flight simulation models that improve pilot training for such loss-of-control scenarios. Flight of aircraft with either airframe damage or operating near and beyond the stall boundary encounters additional nonlinear aerodynamic influences on stability and control from dynamic motions that, if not included in flight simulation models, may lead to incorrect pilot responses. In the present work, both low- and high-fidelity computational methods are explored for analyzing such nonlinearities. The challenge of creating nonlinear reduced-order models from high-fidelity computational data is also addressed. At the beginning, few guidelines were available for computing or modeling the dynamic stability characteristics of civil aircraft in nonlinear stalled flight regimes. To accelerate progress, additional resources were leveraged through participation in two NATO task groups consisting of a diverse international body of computational aerodynamicists and flight simulation experts. As a result, a large body of knowledge has been generated, documenting the state of the art for computing and modeling the highly nonlinear stability characteristics of an unmanned air combat vehicle. This knowledge was infused directly into the NASA loss-of-control work through parallel application studies with the NASA Generic Transport Model. From this, it is concluded that the Reynolds-averaged Navier–Stokes formulation should suffice for capturing the representative behavior of civil aircraft stall for training purposes. Furthermore, promising approaches have been identified for creating nonlinear reduced-order models from computational data that can potentially augment flight simulation models for loss-of-control scenarios.


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    Title :

    Computational Aerodynamic Modeling Tools for Aircraft Loss of Control



    Published in:

    Publication date :

    2016-05-23


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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