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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/16704
Title: Combining a reduced polynomial chaos expansion approach with universal Kriging for uncertainty quantification
Authors: Weinmeister J.
Xie N.
Gao X.
Prasad A.K.
Roy S.
Published in: Proceedings of 8th AIAA Theoretical Fluid Mechanics Conference, 2017
Abstract: Engineering design optimization studies are computationally expensive based on the large number of computational fluid dynamics simulations necessary for uncertainty quantification. Polynomial chaos expansion methods have the potential to save computational costs by reducing the number of input design parameters. Kriging methods are able to accurately predict off-design values and give an estimate of their error. In this paper, we combine a reduced dimensional polynomial chaos approach with a universal Kriging method as a new non-intrusive metamodeling method for fast uncertainty quantification and optimization in a simplified engine nacelle inlet design. Its performance is benchmarked against the reduced dimensional polynomial chaos approach and universal Kriging. Results show the reduced-polynomial-chaos-Kriging method gives more accurate results than the reduced dimensional polynomial chaos approach for non-smooth solutions. However, the new method is highly-dependent on the experimental design used and can become discontinuous. The application of a standalone Kriging method on the reduced model produced excellent stability and indicates refinement of the method is possible. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
Citation: Proceedings of 8th AIAA Theoretical Fluid Mechanics Conference, 2017, (2017)
URI: http://repository.iitr.ac.in/handle/123456789/16704
Issue Date: 2017
Publisher: American Institute of Aeronautics and Astronautics Inc, AIAA
Keywords: Computational fluid dynamics
Fluid mechanics
Interpolation
Uncertainty analysis
Computational costs
Computational fluid dynamics simulations
Engineering design optimization
Metamodeling methods
Non-smooth solutions
Polynomial chaos expansion
Reduced-dimensional
Uncertainty quantifications
Polynomials
ISBN: 9.78E+12
Author Scopus IDs: 57194854612
57190859745
56218218900
56723412600
55364099700
Author Affiliations: Weinmeister, J., Computational Fluid Dynamics and Propulsion Laboratory, Colorado State University, Fort Collins, CO 80523, United States
Xie, N., Computational Fluid Dynamics and Propulsion Laboratory, Colorado State University, Fort Collins, CO 80523, United States
Gao, X., Computational Fluid Dynamics and Propulsion Laboratory, Colorado State University, Fort Collins, CO 80523, United States
Prasad, A.K., High Speed System Simulation Laboratory, Colorado State University, Fort Collins, CO 80523, United States
Roy, S., High Speed System Simulation Laboratory, Colorado State University, Fort Collins, CO 80523, United States
Appears in Collections:Conference Publications [ECE]

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