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

Reduced-Order Modeling for Aerodynamic Applications and MDO

Görtz, Stefan (2020) Reduced-Order Modeling for Aerodynamic Applications and MDO. VKI Lecture Series on Machine Learning for Fluid Mechanics: Analysis, Modeling, Control and Closures, Brüssel, Belgien.

Full text not available from this repository.

Abstract

Parametric reduced order models (ROMs) for both steady and unsteady aerodynamic applications are presented. The focus is on compressible, turbulent flows with shocks. We consider ROMs combining proper orthogonal decomposition (POD), Isomap, which is a manifold learning method, and autoencoder networks with interpolation methods as well as physics-based ROMs, where an approximate solution is found in the POD-subspace by minimizing the corresponding steady or unsteady flow-solver residual. The ROMs are used to predict unsteady gusts loads for rigid aircraft as well as static aeroelastic loads in the context of multidisciplinary design optimization (MDO) where the structural model is to be sized for the (aerodynamic) loads. They are also used in a process where an a priori identification of the critical load cases is of interest and the sheer number of load cases to be considered does not lend itself to high-fidelity CFD. The different ROM methods are applied to 2D and 3D test cases at transonic flow conditions where shock waves occur and in particular to a commercial full aircraft configuration.

Item URL in elib:https://elib.dlr.de/134318/
Document Type:Conference or Workshop Item (Lecture)
Title:Reduced-Order Modeling for Aerodynamic Applications and MDO
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Görtz, StefanStefan.Goertz (at) dlr.deUNSPECIFIED
Date:28 February 2020
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:reduced order modeling, aerodynamics, CFD, multidisciplinary design optimization, POD, isomap, autoencoder, loads
Event Title:VKI Lecture Series on Machine Learning for Fluid Mechanics: Analysis, Modeling, Control and Closures
Event Location:Brüssel, Belgien
Event Type:Other
Organizer:von Karman Institute for Fluid Dynamics
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, L - VicToria
Location: Braunschweig , Dresden
Institutes and Institutions:Institute for Aerodynamics and Flow Technology > CASE, BS
Institute of Software Methods for Product Virtualization
Deposited By: Görtz, Stefan
Deposited On:09 Mar 2020 13:18
Last Modified:09 Mar 2020 13:18

Repository Staff Only: item control page

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