0
Research Papers: Techniques and Procedures

Sensitivity Analysis and Multiobjective Optimization for LES Numerical Parameters

[+] 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

Institut Jean Le Rond d’Alembert, Université Pierre et Marie Curie, 4 place Jussieu-case 162, F-75252 Paris Cedex 05, Francepierre.sagaut@upmc.fr

B. Enaux, J. Laurenceau

 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 130(2), 021401 (Jan 25, 2008) (9 pages) doi:10.1115/1.2829602 History: Received June 11, 2007; Revised August 30, 2007; Published January 25, 2008

Accuracy and reliability of large-eddy simulation data in a really complex industrial geometry are invesigated. An original methodology based on a response surface for LES data is introduced. This surrogate model for the full LES problem is built using the Kriging technique, which enables a low-cost optimal linear interpolation of a restricted set of large-eddy simulation (LES) solutions. Therefore, it can be used in most realistic industrial applications. Using this surrogate model, it is shown that (i) optimal sets of simulation parameters (subgrid model constant and artificial viscosity parameter in the present case) can be found; (ii) optimal values, as expected, depend on the cost functional to be minimized. Here, a realistic approach, which takes into account experimental data sparseness, is introduced. It is observed that minimization of the error evaluated using a too small subset of reference data may yield a global deterioration of the results.

FIGURES IN THIS ARTICLE
<>
Copyright © 2008 by American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Figure 1

Schematic illustration of the engine antiicing system

Grahic Jump Location
Figure 12

Optimized profiles in the X∕D=1 and X∕D=8 planes (L2 norm) for the cooling effectiveness

Grahic Jump Location
Figure 11

Optimized profiles in the X∕D=1 and X∕D=8 planes (L2 norm) for the velocity

Grahic Jump Location
Figure 10

Pareto front for F(2) function

Grahic Jump Location
Figure 9

Pareto front for F(1) function

Grahic Jump Location
Figure 8

Ordinary Kriging for the planes X∕D=1 and X∕D=8 (L1 norm). Cost function: (a) F(1), and (b) F(2).

Grahic Jump Location
Figure 7

Ordinary Kriging for the plane X∕D=8. Cost function: (a) F(1) and (b) F(2).

Grahic Jump Location
Figure 6

Ordinary Kriging for the plane X∕D=1. Cost function: (a) F(1) and (b) F(2).

Grahic Jump Location
Figure 5

Range of cooling effectiveness response in the damping parameter space

Grahic Jump Location
Figure 4

Range of velocity response in the damping parameter space

Grahic Jump Location
Figure 3

Fine mesh used for the LES computations

Grahic Jump Location
Figure 2

Computational domain considered for LES: (a) Top view, (b) lateral view, and (c) front view.

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In