Gradient-Enhanced Hierarchical Kriging Model for Aerodynamic Design Optimization
Publication: Journal of Aerospace Engineering
Volume 30, Issue 6
Abstract
A cokriging model incorporating gradient information and the function value of sample points can reduce the computational cost with a given level of accuracy. In this paper, the hierarchical kriging, a recently proposed cokriging method is employed, and a new method called gradient-enhanced hierarchical kriging (GEHK) is developed. First of all, a low-fidelity kriging model is built using derived samples, which are obtained by Taylor approximation using gradients and selected step sizes. Then a high-fidelity model is built by adjusting the low-fidelity kriging model with initial sample points. The GEHK model is more efficient than the traditional gradient-based cokriging model in the aerodynamic optimization, and could get a better optimum value. Taking the advantage of the modeling strategy, the global accuracy of the GEHK is not sensitive to step sizes, and the accuracy of prediction is enhanced evidently. The GEHK method is able to overcome limitations of traditional gradient-based cokriging models, and the prediction accuracy of the model is improved globally.
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Acknowledgments
This research was sponsored by the National Natural Science Foundation of China (NSFC) under Grant No. 11272263.
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Published In
Journal of Aerospace Engineering
Volume 30 • Issue 6 • November 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Aug 3, 2016
Accepted: Mar 29, 2017
Published online: Aug 28, 2017
Published in print: Nov 1, 2017
Discussion open until: Jan 28, 2018
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