This paper summarizes recent progress in developing metamodels for efficiently predicting the aerodynamic loads acting on industrial aircraft configurations. We introduce a physics-based approach to reduced-order modeling based on proper orthogonal decomposition of snapshots of the full-order CFD model, and a mathematical approach to variable-fidelity modeling that aims at combining many low-fidelity CFD results with as few high-fidelity CFD results as possible using bridge functions and variants of Kriging and Cokriging. In both cases, the goal is to arrive at a model that can be used as an efficient surrogate to the original high-fidelity or full-order CFD model but with significantly less evaluation time and storage requirements. Both approaches are demonstrated on industrial aircraft configurations at subsonic and transonic flow conditions.


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    Titel :

    Variable-Fidelity and Reduced-Order Models for Aero Data for Loads Predictions


    Weitere Titelangaben:

    Notes Numerical Fluid Mech.


    Beteiligte:
    Kroll, Norbert (Herausgeber:in) / Radespiel, Rolf (Herausgeber:in) / Burg, Jan Willem (Herausgeber:in) / Sørensen, Kaare (Herausgeber:in) / Görtz, Stefan (Autor:in) / Zimmermann, Ralf (Autor:in) / Han, Zhong-Hua (Autor:in)


    Erscheinungsdatum :

    2013-01-01


    Format / Umfang :

    14 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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