Gradient-based sensitivity analysis has proven to be an enabling technology for many applications, including design of aerospace vehicles. However, conventional sensitivity analysis methods break down when applied to long-time averages of chaotic systems. This breakdown is a serious limitation because many aerospace applications involve physical phenomena that exhibit chaotic dynamics: most notably high-resolution large-eddy and direct numerical simulations of turbulent aerodynamic flows. A recently proposed methodology, called least-squares shadowing, avoids this breakdown and advances the state of the art in sensitivity analysis for chaotic flows. The first application of least-squares shadowing to a chaotic flow simulated with a large-scale computational fluid dynamics solver is presented. The least-squares shadowing sensitivity computed for this chaotic flow is verified and shown to be accurate, but the computational cost of the current least-squares shadowing implementation is high.


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    Titel :

    Least-Squares Shadowing Sensitivity Analysis of Chaotic Flow Around a Two-Dimensional Airfoil


    Beteiligte:
    Blonigan, Patrick J. (Autor:in) / Wang, Qiqi (Autor:in) / Nielsen, Eric J. (Autor:in) / Diskin, Boris (Autor:in)

    Erschienen in:

    AIAA Journal ; 56 , 2 ; 658-672


    Erscheinungsdatum :

    2017-10-24


    Format / Umfang :

    15 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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