Optimizations Under Uncertainty Using Gradients, Hessians, and Surrogate Models-Reference-Cited by-同舟云学术

Optimizations Under Uncertainty Using Gradients, Hessians, and Surrogate Models

Published:2013-02 Issue:2 Volume:51 Page:444-451
ISSN:0001-1452
Container-title:AIAA Journal
language:en
Short-container-title:AIAA Journal

Author:

Rumpfkeil Markus P.¹

Affiliation:

1. Department of Mechanical and Aerospace Engineering, University of Dayton, Ohio 45469-0238

Publisher

American Institute of Aeronautics and Astronautics (AIAA)

Subject

Aerospace Engineering

Link

http://arc.aiaa.org/doi/pdf/10.2514/1.J051847

Reference54 articles.

1. Uncertainty in Computational Aerodynamics

2. GumbertC. R.NewmanP. A.HouG. J. “Effect of Random Geometric Uncertainty on the Computational Design of 3-D Wing,” AIAA Paper 2002-2806, June 2002.

3. Foreword: special issue on robust optimization

4. PilchM.TrucanoT. G.HeltonJ. C. “Ideas Underlying Quantification of Margins and Uncertainties (QMU): A White Paper,” Sandia National Lab. TR SAND2006-5001, 2006.

5. Measures of agreement between computation and experiment: Validation metrics

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