Vortical flow fields are complex in nature and are prevalent in aircraft aerodynamics. Reynolds Averaged Navier Stokes simulation methodology along with eddy viscosity based Menter—Shear Stress Transport model is widely used in the research community for practical applications. Extensions to Menter—SST turbulence model based on flow physics are explored in the present work to improve the prediction capability for separated and vortical flow fields. A data driven calibration approach is employed based on Bayesian modeling to determine the coefficients of the extended turbulence model. Performance of the extended model is studied with complex delta wings under subsonic flow conditions.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Bayesian Calibration of Extended Menter-SST Turbulence Model for Vortical Flows


    Weitere Titelangaben:

    Notes Numerical Fluid Mech.


    Beteiligte:
    Heinrich, Ralf (Herausgeber:in) / Subbian, Gokul (Autor:in) / Moshagen, Thilo (Autor:in) / Friedman, Noemi (Autor:in) / Zander, Elmar (Autor:in) / Radespiel, Rolf (Autor:in)


    Erscheinungsdatum :

    18.10.2024


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch