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Response Surface Methods for Efficient Aerodynamic Surrogate Models

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Computational Flight Testing

Part of the book series: Notes on Numerical Fluid Mechanics and Multidisciplinary Design ((NNFM,volume 123))

Abstract

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.

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Authors and Affiliations

  1. Abteilung Mathematik, Universität Trier, D-54286, Trier, Germany

    Benjamin Rosenbaum & Volker Schulz

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  1. Benjamin Rosenbaum
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  2. Volker Schulz
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Editors and Affiliations

  1. , Institute of Aerodynamics and, German Aerospace Center (DLR), Lilienthalplatz 7, Braunschweig, 38108, Germany

    Norbert Kroll

  2. Institute of Fluid Mechanics, Technische Universität Braunschweig, Hermann-Blenk-Str. 37, Braunschweig, 38108, Germany

    Rolf Radespiel

  3. Airbus Operations Gmbh, Airbus-Allee 1, Bremen, 28199, Germany

    Jan Willem Burg

  4. Aerodynamics & Methods, Cassidian, Rechliner Strasse, Manching, 85077, Germany

    Kaare Sørensen

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Rosenbaum, B., Schulz, V. (2013). Response Surface Methods for Efficient Aerodynamic Surrogate Models. In: Kroll, N., Radespiel, R., Burg, J., Sørensen, K. (eds) Computational Flight Testing. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38877-4_9

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  • DOI: https://doi.org/10.1007/978-3-642-38877-4_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38876-7

  • Online ISBN: 978-3-642-38877-4

  • eBook Packages: EngineeringEngineering (R0)

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