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Uncertainty Quantification and Management in the Context of Loads and Aerodynamic Design

Maruyama, Daigo und Görtz, Stefan und Coggon, Simon und Engelbrecht, Thomas und Sharma S, Sanjiv (2017) Uncertainty Quantification and Management in the Context of Loads and Aerodynamic Design. DiPaRT 2017 Flight Physics Symposium, 20-22 Nov 2017, Bristol, United Kingdom.

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Kurzfassung

In this talk we present a robust design optimization framework for aircraft design and show results for robust aerodynamic design. As a first step, we focus on quantifying uncertainties in the drag coefficient and formulate and investigate two measures of robustness, a worst-case scenario and a formulation based on expectation measure and mean-risk. To reduce the computational effort required to compute the output uncertainties we make use of a Sobol sequence-based quasi Monte Carlo method (QMC) and a gradient-enhanced Kriging (GEK) surrogate model. A small number of samples is computed with the full-order CFD code TAU and its adjoint version to construct the GEK model. The statistics are computed by interrogating the surrogate model with a QMC method using a sufficiently large number of samples. In terms of the input uncertainties, we are interested both in operational and geometrical uncertainties. Our strategy to model the inherently large number of geometrical uncertainties is by using a truncated Karhunen-Loève expansion (tKLE), which introduces some elements of model uncertainty. The test case used here to demonstrate the framework is a transonic RAE2822 airfoil. We confirm that the robust design measures are accurately evaluated to within one drag count and that adaptive sampling techniques are required especially in the worst case scenario. Then, a Subplex algorithm is used to optimize the robustness measure. The robustly optimized airfoil features the best stochastic values in terms of the robustness measure compared with the initial airfoil and a deterministically optimized airfoil. Current work is aiming to extend our framework for uncertainty quantification and management (UQ&M) based on high-fidelity CFD to the loads process, especially at extremes of the flight envelope. There are two issues arising that we are concerned with: One is about efficient nonintrusive UQ&M methods for high-dimensional output uncertainties, in particular reduced order models (ROMs) for loads are sought after. Also, methods for identifying dominant (input) uncertainties and dimension reduction, in particular management and reduction of the critical design load cases are required. The other one is model uncertainty. Model uncertainties arising as part the CFD computations, which are reducible, can have a larger influence on the accuracy of the output uncertainties than the realistic (irreducible) ones, for instance, at high Mach numbers and high angles of attack. Efficient non-intrusive UQ&M methods considering the above two issues are then to be incorporated in the context of multidisciplinary design optimization (MDO) in the future.

elib-URL des Eintrags:https://elib.dlr.de/116264/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Uncertainty Quantification and Management in the Context of Loads and Aerodynamic Design
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Maruyama, Daigodaigo.maruyama (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Görtz, Stefanstefan.goertz (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Coggon, SimonNICHT SPEZIFIZIERTNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Engelbrecht, ThomasNICHT SPEZIFIZIERTNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Sharma S, SanjivNICHT SPEZIFIZIERTNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:November 2017
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Status:veröffentlicht
Stichwörter:Uncertainty Quantification, Robust Design, Aerodynamics, Surrogate Models, Reduced Order Models
Veranstaltungstitel:DiPaRT 2017 Flight Physics Symposium
Veranstaltungsort:Bristol, United Kingdom
Veranstaltungsart:nationale Konferenz
Veranstaltungsdatum:20-22 Nov 2017
Veranstalter :Airbus
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Luftfahrt
HGF - Programmthema:Flugzeuge
DLR - Schwerpunkt:Luftfahrt
DLR - Forschungsgebiet:L AR - Aircraft Research
DLR - Teilgebiet (Projekt, Vorhaben):L - Flugphysik (alt), L - Simulation und Validierung (alt)
Standort: Braunschweig
Institute & Einrichtungen:Institut für Aerodynamik und Strömungstechnik > CASE, BS
Hinterlegt von: Maruyama, Daigo
Hinterlegt am:21 Dez 2017 09:44
Letzte Änderung:21 Dez 2017 09:44

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