DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Interpolation-based reduced-order modelling for steady transonic flows via manifold learning

Franz, Thomas and Zimmermann, R. and Görtz, S. and Karcher, N. (2014) Interpolation-based reduced-order modelling for steady transonic flows via manifold learning. International Journal of Computational Fluid Dynamics, 28 (3-4), pp. 106-121. Taylor & Francis. doi: [10.1080/10618562.2014.918695]. ISSN 1061-8562.

Full text not available from this repository.

Official URL: http://dx.doi.org/10.1080/10618562.2014.918695


This paper presents a parametric reduced-order model (ROM) based on manifold learning (ML) for use in steady transonic aerodynamic applications. The main objective of this work is to derive an efficient ROM that exploits the low-dimensional nonlinear solution manifold to ensure an improved treatment of the nonlinearities involved in varying the inflow conditions to obtain an accurate prediction of shocks. The reduced-order representation of the data is derived using the Isomap ML method, which is applied to a set of sampled computational fluid dynamics (CFD) data. In order to develop a ROM that has the ability to predict approximate CFD solutions at untried parameter combinations, Isomap is coupled with an interpolation method to capture the variations in parameters like the angle of attack or the Mach number. Furthermore, an approximate local inverse mapping from the reduced-order representation to the full CFD solution space is introduced. The proposed ROM, called Isomap+I, is applied to the two-dimensional NACA 64A010 airfoil and to the 3D LANN wing. The results are compared to those obtained by proper orthogonal decomposition plus interpolation (POD+I) and to the full-order CFD model.

Item URL in elib:https://elib.dlr.de/90980/
Document Type:Article
Title:Interpolation-based reduced-order modelling for steady transonic flows via manifold learning
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Franz, ThomasThomas.Franz (at) dlr.deUNSPECIFIED
Zimmermann, R.Ralf.Zimmermann (at) tu-braunschweig.deUNSPECIFIED
Görtz, S.Stefan.Görtz (at) dlr.deUNSPECIFIED
Karcher, N.Niklas.Karcher (at) dlr.deUNSPECIFIED
Journal or Publication Title:International Journal of Computational Fluid Dynamics
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
DOI :[10.1080/10618562.2014.918695]
Page Range:pp. 106-121
Publisher:Taylor & Francis
Keywords:dimensionality reduction; reduced-order model; Isomap; manifold learning; proper orthogonal decomposition; aerodynamics
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 (old)
Location: Braunschweig
Institutes and Institutions:Institute of Aerodynamics and Flow Technology > C²A²S²E - Center for Computer Applications in AeroSpace Science and Engineering
Deposited By: Franz, Thomas
Deposited On:15 Oct 2014 14:49
Last Modified:06 Sep 2019 15:20

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.