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Geometrical Uncertainties-Accuracy of Parametrization and Its Influence on UQ and RDO results

Liu, Dishi and Maruyama, Daigo and Görtz, Stefan (2019) Geometrical Uncertainties-Accuracy of Parametrization and Its Influence on UQ and RDO results. In: Uncertainty Management for Robust Industrial Design in Aeronautics Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 140. Springer International Publishing AG. pp. 785-798. ISBN 978-3-319-77766-5. ISSN 1612-2909

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Official URL: https://www.springer.com/gp/book/9783319777665

Abstract

A large number of geometrical uncertainties of a transonic RAE2822 airfoil is parameterized by a truncated Karhunen-Loève expansion (KLE) and the influence of the truncation on the statistics of aerodynamic quantities is investigated both in terms of efficiency and accuracy. Direct integration of a very large number of quasi Monte Carlo samples computed with CFD is used to compute the mean and standard deviation for different levels of truncation, i.e., for different numbers of uncertain parameters. We show that a parameterization based on a well-truncated KLE can efficiently reduce the number of geometrical uncertainties while maintaining accuracy. Excessive truncation will not improve the efficiency of surrogate-based statistics integration and will inevitably lead to a loss of accuracy of the estimated statistics. This is attributed to the use of a gradient-enhanced surrogate model that employs an adjoint flow solver to compute the gradient of the aerodynamic coefficients with respect to the uncertain parameters. All partial gradients can be computed at the cost of one adjoint solution, i.e., the cost of computing all partial gradients is independent of the number of uncertain parameters. It is also shown that a loss of accuracy due to an improper truncation may influence the results of robust design optimization.

Item URL in elib:https://elib.dlr.de/125241/
Document Type:Contribution to a Collection
Title:Geometrical Uncertainties-Accuracy of Parametrization and Its Influence on UQ and RDO results
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Liu, Dishidishi.liu (at) dlr.deUNSPECIFIED
Maruyama, Daigodaigo.maruyama (at) dlr.deUNSPECIFIED
Görtz, StefanStefan.Goertz (at) dlr.deUNSPECIFIED
Date:2019
Journal or Publication Title:Uncertainty Management for Robust Industrial Design in Aeronautics
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:140
DOI :10.1007/978-3-319-77767-2
Page Range:pp. 785-798
Editors:
EditorsEmail
Hirsch, CharlesNUMECA Brüssel
Wunsch, DirkNUMECA Brüssel
Szumbarski, JacekUniversity of Technology, Warschau
Laniewski-Wollk, LukaszUniversity of Technology, Warschau
Pons-Prats, JordiCIMNE Barcelona
Publisher:Springer International Publishing AG
Series Name:Notes on Numerical Fluid Mechanics and Multidisciplinary Design
ISSN:1612-2909
ISBN:978-3-319-77766-5
Status:Published
Keywords:Uncertainty Quantification, Geometrical Uncertainty, Karhunen-Loève expansion
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:fixed-wing aircraft
DLR - Research area:Aeronautics
DLR - Program:L AR - Aircraft Research
DLR - Research theme (Project):L - Simulation and Validation
Location: Braunschweig
Institutes and Institutions:Institute for Aerodynamics and Flow Technology > CASE, BS
Deposited By: Seyfried, Beate
Deposited On:03 Jan 2019 13:11
Last Modified:03 Jan 2019 13:11

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