This work proposes a new method for using reduced-order models in lieu of high-fidelity analysis during the sensitivity analysis step. Reduced-order models are developed using a combination of proper orthogonal decomposition and radial basis functions. Interpolation using reduced-order models based on proper orthogonal decomposition is compared against normal optimization on a general airfoil shape optimization problem. The interpolation procedure does not require additional high-fidelity evaluations to construct new reduced-order models. The errors associated with the reduced-order models themselves as well as the gradients calculated from them are compared. The effects of each approach on the overall optimization paths, times, and function counts are also examined.


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    Titel :

    Reduced-Order Techniques for Sensitivity Analysis and Design Optimization of Aerospace Systems


    Beteiligte:
    Parrish, J. (Autor:in) / Rais-Rohani, M. (Autor:in) / Janus, M. (Autor:in)

    Erschienen in:

    AIAA Journal ; 53 , 12 ; 3567-3576


    Erscheinungsdatum :

    01.12.2015




    Medientyp :

    Aufsatz (Konferenz) , Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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