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Surrogate Model-Based Approaches to UQ and Their Range of Applicability

Maruyama, Daigo and Liu, Dishi and Görtz, Stefan (2019) Surrogate Model-Based Approaches to UQ and Their Range of Applicability. In: Uncertainty Management for Robust Industrial Design in Aeronautics Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 140. Springer International Publishing AG. pp. 703-714. ISBN 978-3-319-77766-5. ISSN 1612-2909

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

Abstract

Efficient surrogate modeling approaches are presented in the context of robust design. The type of surrogate model and the number and distribution of the sample points are discussed. The test case is the UMRIDA BC-02 airfoil with two uncertain operational and 10 uncertain geometrical parameters. Statistics of the quantity of interest (QoI) are evaluated based on surrogate models of the QoI. Here the QoI is lift coefficient or drag coefficient. Both Kriging and gradient-enhanced Kriging (GEK) surrogate models are considered. The surrogate models are generated based on scattered samples of QoI. A Sobol-sequence is used to generate samples with a low-discrepancy distribution, for which the QoI and its gradients with respect to the uncertain parameters are evaluated with a Computational Fluid Dynamics (CFD) solver and its adjoint counterpart. The mean and standard deviation of the QoI are efficiently evaluated by using GEK with more than 12 samples for large numbers of uncertainty parameters more than 10. The accuracy of the surrogate models is also investigated in terms of the derived robust design solutions. The error dispersion of the stochastic objective function due to the sample distribution affects the optimal solution. 30 sample points are necessary to reduce the error dispersion to within one drag count, which is considered to be on the same order of magnitude as the epistemic uncertainty due to CFD errors.

Item URL in elib:https://elib.dlr.de/125237/
Document Type:Contribution to a Collection
Title:Surrogate Model-Based Approaches to UQ and Their Range of Applicability
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Maruyama, Daigodaigo.maruyama (at) dlr.deUNSPECIFIED
Liu, Dishidishi.liu (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. 703-714
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:Surrogate, Uncertainty Quantification, Design of Experiments, Adaptive Sampling, Aerodynamic Data
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 13:10
Last Modified:03 Jan 2019 13:10

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