Robust Aerodynamic Design Optimization via Variable Fidelity Surrogate Model

Author:

YAMAZAKI Wataru

Publisher

Japan Society for Aeronautical and Space Sciences

Subject

Space and Planetary Science,Aerospace Engineering

Reference41 articles.

1. 1) Ghate, D. and Giles, M. B.: Inexpensive Monte Carlo Uncertainty Analysis, Recent Trends in Aerospace Design and Optimization, Tata McGraw-Hill, New Delhi, 2006, pp. 203–210.

2. 2) Rumpfkeil, M. P., Yamazaki, W. and Mavriplis, D. J.: Uncertainty Analysis Utilizing Gradient and Hessian Information, 6th International Conference on Computational Fluid Dynamics, ICCFD6, 2010.

3. 3) Gumbert, C. R., Newman, P. A. and Hou, G. J.: Effect of Random Geometric Uncertainty on the Computational Design of 3-D Flexible Wing, AIAA Paper 2002-2806, 2002.

4. 4) Luckring, J. M., Hemsch, M. J. and Morrison, J. H.: Uncertainty in Computational Aerodynamics, AIAA Paper 2003-0409, 2003.

5. 5) Hosder, S., Walters, R. W. and Balch, M.: Efficient Sampling for Non-Intrusive Polynomial Chaos Applications with Multiple Uncertain Input Variables, AIAA Paper 2007-1939, 2007.

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1. Robust optimization of the aerodynamic design of a helicopter rotor blade based on multi-fidelity meta-models;Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering;2022-07-12

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