Response surface methods for the approximation of outputs of computer experiments such as the Kriging method often suffer from a lack of accuracy or efficiency. Many computationally expensive samples are needed for the globally correct reproduction of an unknown response. We investigate adaptive sampling strategies, which can automatically identify critical regions of an input-parameter domain and require less samples than traditional one-stage approaches like Latin hypercube designs. Furthermore, we propose a new method which makes use of the assumption that the aerodynamic responses are not of arbitrary structure, but rather related to other instances of a mutual problem class. Both approaches are validated with numerical test cases, showing that they produce more accurate surrogate models using less samples than traditional approaches.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Response Surface Methods for Efficient Aerodynamic Surrogate Models


    Additional title:

    Notes Numerical Fluid Mech.


    Contributors:


    Publication date :

    2013-01-01


    Size :

    17 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Response Surface Methods for Efficient Aerodynamic Surrogate Models

    Rosenbaum, B. / Schulz, V. | British Library Conference Proceedings | 2013



    Comparison of Adaptive Sampling Methods for Generation of Surrogate Aerodynamic Models

    Mackman, T. J. / Allen, C. B. / Ghoreyshi, M. et al. | AIAA | 2013



    Comparison of Adaptive Sampling Methods for Generation of Surrogate Aerodynamic Models

    Mackman, Thomas / Allen, Christian / Ghoreyshi, Mehdi et al. | AIAA | 2011