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dc.contributor.authorLiu, Dishi
dc.contributor.authorLitvinenko, Alexander
dc.contributor.authorSchillings, Claudia
dc.contributor.authorSchulz, Volker
dc.date.accessioned2017-05-23T07:35:09Z
dc.date.available2017-05-23T07:35:09Z
dc.date.issued2015-04-14
dc.date.issued2017-03-30
dc.identifier.citationLiu D, Litvinenko A, Schillings C, Schulz V (2017) Quantification of Airfoil Geometry-Induced Aerodynamic Uncertainties---Comparison of Approaches. SIAM/ASA Journal on Uncertainty Quantification 5: 334–352. Available: http://dx.doi.org/10.1137/15M1050239.
dc.identifier.issn2166-2525
dc.identifier.doi10.1137/15M1050239
dc.identifier.urihttp://hdl.handle.net/10754/623697
dc.description.abstractUncertainty quantification in aerodynamic simulations calls for efficient numerical methods to reduce computational cost, especially for uncertainties caused by random geometry variations which involve a large number of variables. This paper compares five methods, including quasi-Monte Carlo quadrature, polynomial chaos with coefficients determined by sparse quadrature and by point collocation, radial basis function and a gradient-enhanced version of kriging, and examines their efficiency in estimating statistics of aerodynamic performance upon random perturbation to the airfoil geometry which is parameterized by independent Gaussian variables. The results show that gradient-enhanced surrogate methods achieve better accuracy than direct integration methods with the same computational cost.
dc.description.sponsorshipThis work was supported by the project MUNA under the framework of the German Luftfahrtforschungsprogramm funded by the Ministry of Economics (BMWi). A part of this work was done by A. Litvinenko during his stay at King Abdullah University of Science and Technology. We are grateful to the anonymous reviewers for their diligence and insights which have greatly helped to improve this paper. Special gratitude is extended to Dr. Stefan Gortz at Institute of Aerodynamics and Flow Technology of the German Aerospace Center (DLR) for his invaluable advice during the modifi cation. The authors also thank Bernhard Eisfeld and Normann Krimmelbein at DLR for their kind help on the CFD test case.
dc.publisherSociety for Industrial & Applied Mathematics (SIAM)
dc.relation.urlhttps://arxiv.org/abs/1505.05731
dc.relation.urlhttp://epubs.siam.org/doi/10.1137/15M1050239
dc.rightsArchived with thanks to SIAM/ASA Journal on Uncertainty Quantification
dc.subjectaerodynamic simulation
dc.subjectairfoil geometric uncertainty
dc.subjectsurrogate modeling
dc.subjectgradient-enhanced kriging
dc.subjectnumerical integration
dc.titleQuantification of Airfoil Geometry-Induced Aerodynamic Uncertainties---Comparison of Approaches
dc.typeArticle
dc.contributor.departmentCenter for Uncertainty Quantification in Computational Science and Engineering (SRI-UQ)
dc.identifier.journalSIAM/ASA Journal on Uncertainty Quantification
dc.eprint.versionPost-print
dc.contributor.institutionGerman Aerospace Center (DLR), Institute of Aerodynamics and Flow Technology, Lilienthalplatz 7, 38108 Braunschweig, Germany
dc.contributor.institutionSeminar for Applied Mathematics, ETH, 8092 Zurich, Switzerland
dc.contributor.institutionDepartment of Mathematics, Universit at Trier Universit atsring 15, 54296 Trier, Germany
dc.identifier.arxividarXiv:1505.05731
kaust.personLitvinenko, Alexander
refterms.dateFOA2018-06-13T16:52:05Z


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