Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Non-Intrusive Uncertainty Quantification of CFD Based on Adaptive Stochastic Kriging


    Beteiligte:
    Wang, Bo (Autor:in) / Zhang, Yudong (Autor:in) / Gong, Jian (Autor:in) / Zhang, Weimin (Autor:in) / Zhang, Kun (Autor:in)

    Kongress:

    AIAA Modeling and Simulation Technologies Conference



    Erscheinungsdatum :

    2016-01-01



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Multifidelity Uncertainty Quantification Using Non-Intrusive Polynomial Chaos and Stochastic Collocation

    Ng, L.W.-T. / Eldred, M. / American Institute of Aeronautics and Astronautics | British Library Conference Proceedings | 2012



    Efficient Uncertainty Quantification Using Gradient-Enhanced Kriging

    Dwight, R. / Han, Z. | British Library Conference Proceedings | 2009


    Dynamic Adaptive Sampling Based on Kriging Surrogate Models for Efficient Uncertainty Quantification

    Shimoyama, K. / Kawai, S. / Alonso, J.J. et al. | British Library Conference Proceedings | 2013


    Efficient Uncertainty Quantification Using Gradient-Enhanced Kriging

    Dwight, Richard / Han, Zhong-Hua | AIAA | 2009