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Transonic velocity fluctuations simulated using extremum diminishing uncertainty quantification based on inverse distance weighting

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Abstract

For reliable computational predictions of transonic flows, it is important to resolve the significant effects of physical variations on the shock wave locations. The resulting discontinuities in probability space require extremum diminishing uncertainty quantification to avoid overshoots and undershoots in the response surface approximation. In this paper, the extremum diminishing concept in probability space is extended to infinite parameter domains using inverse distance weighting interpolation of deterministic samples. Based on results for three analytical test functions, the combination of Halton sampling and power parameter limit value c → ∞ is selected. The approach is employed to model spatial-free-stream velocity fluctuations in the highly sensitive transonic AGARD 445.6 wing test case in an up to ten-dimensional probability space. The 0.5% input variations are amplified to a coefficient of variation for the wave drag of cvD = 9.58% in combination with an increase of the mean drag by 1.75% compared to the deterministic value.

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Authors and Affiliations

  1. Center for Turbulence Research, Stanford University, Building 500, Stanford, CA, 94305–3035, USA

    Jeroen A. S. Witteveen

  2. Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629 HS, Delft, The Netherlands

    Hester Bijl

Authors
  1. Jeroen A. S. Witteveen
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  2. Hester Bijl
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Correspondence to Jeroen A. S. Witteveen.

Additional information

Communicated by Zang.

The presented work is supported by the NODESIM–CFD project (Non-Deterministic Simulation for CFD based design methodologies); a collaborative project funded by the European Commission, Research Directorate–General in the 6th Framework Programme, under contract AST5–CT–2006–030959.

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Witteveen, J.A.S., Bijl, H. Transonic velocity fluctuations simulated using extremum diminishing uncertainty quantification based on inverse distance weighting. Theor. Comput. Fluid Dyn. 26, 459–479 (2012). https://doi.org/10.1007/s00162-011-0233-y

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  • DOI: https://doi.org/10.1007/s00162-011-0233-y

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