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TECHNICAL PAPERS

A Kriging Approach for CFD/Wind-Tunnel Data Comparison

[+] Author and Article Information
J.-C. Jouhaud1

 Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS), 42, Avenue Gaspard Coriolis, 31057 Toulouse Cedex, Francejjouhaud@cerfacs.fr

P. Sagaut

Laboratoire de Modélisation en Mécanique, University of Paris VI, 4, place Jussieu, 75252 Paris Cedex 05, Francesagaut@lmm.jussieu.fr

B. Labeyrie

 Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS), 42, Avenue Gaspard Coriolis, 31057 Toulouse Cedex, France

1

Corresponding author.

J. Fluids Eng 128(4), 847-855 (Nov 16, 2005) (9 pages) doi:10.1115/1.2201642 History: Received January 07, 2005; Revised November 16, 2005

A Kriging-based method for the parametrization of the response surface spanned by uncertain parameters in computational fluid dynamics is proposed. A multiresolution approach in the sampling space is used to improve the accuracy of the method. It is illustrated considering the problem of the computation of the corrections needed to recover equivalent free-flight conditions from wind-tunnel experiments. Using the surface response approach, optimal corrected values of the freestream Mach number and the angle of attack for the compressible turbulent flow around the RAE 2822 wing are computed. The use of the response surface to gain an insight into the sensitivity of the results with respect to other parameter is also assessed.

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Copyright © 2006 by American Society of Mechanical Engineers
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Figures

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Figure 1

Kriging computational suite

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Figure 2

View of the computational grid

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Figure 3

Flow around the RAE2822 wing, Mach number contours for Spalart-Allmaras and -Cp stations.

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Figure 4

Location of sampling points in the (M∞,α) plane for building of the response surface via Kriging interpolation. Black circles: first grid level; white triangle: second grid level.

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Figure 5

Surface function of the cost function in the (M∞,α) plane: coarse resolution sampling

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Figure 6

Surface function of the cost function in the (M∞,α) plane: locally refined resolution

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Figure 7

Surface function of the cost function in the (M∞,xt) plane: coarse resolution sampling

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Figure 8

Surface function of the cost function in the (M∞,xt) plane: locally refined resolution

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