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Data-Driven Aerodynamic Modeling Using the DLR SMARTy Toolbox

Bekemeyer, Philipp and Bertram, Anna and Hines Chaves, Derrick Armando and Dias Ribeiro, Mateus and Garbo, Andrea and Kiener, Anna and Sabater Campomanes, Christian and Stradtner, Mario and Widhalm, Markus and Görtz, Stefan and Jäckel, Florian and Hoppe, Robert and Hoffmann, Nils (2022) Data-Driven Aerodynamic Modeling Using the DLR SMARTy Toolbox. In: AIAA Aviation 2022 Forum, pp. 1-19. American Institute of Aeronautics and Astronautics, Inc.. AIAA Aviation 2022 Forum, 2022-06-27 - 2022-07-01, Chicago, USA. doi: 10.2514/6.2022-3899.

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Official URL: https://arc.aiaa.org/doi/10.2514/6.2022-3899

Abstract

From aircraft design to certification a huge amount of aerodynamic data is needed for the entire flight envelope including pressure and shear stress distributions, global coefficients as well as derivatives. The goal of data-driven methods is to provide aerodynamic data based on various data-sources but with lower evaluation time and storage than the original models. These data-sources might include flight tests, wind tunnel experiments or numerical simulations, and they are often available at various levels of fidelity, ranging from simple hand book methods over high-fidelity numerical simulations to in-flight measurements. Within the past few years, the demand for efficient exploitation and exploration of these data sets became evident to further enhance existing designs and approaches, evaluate new technical capabilities and foster the availability of high-fidelity aerodynamic data in closely related disciplines. The German Aerospace Center is continuously developing the Surrogate Modeling for Aero-Data Toolbox in python (SMARTy) with the aim of providing state-of-the-art data-driven techniques for both, developers and practical engineers. SMARTy is designed following an Application Programming Interface approach that enables easy combination of different modules into larger, complex applications. Moreover, integration into multi-disciplinary analysis and optimization workflows is possible relying on the FlowSimulator. The SMARTy capabilities are highlighted herein by means of several application cases. This includes surrogate modeling, multi-fidelity modeling, data fusion, reduced order modeling, deep learning as well as highly integrated tasks such as surrogate-based robust design, intrusive reduced order modeling for unsteady responses or data-driven turbulence modeling.

Item URL in elib:https://elib.dlr.de/191797/
Document Type:Conference or Workshop Item (Speech)
Additional Information:View Video Presentation: https://doi.org/10.2514/6.2022-3899.vid
Title:Data-Driven Aerodynamic Modeling Using the DLR SMARTy Toolbox
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Bekemeyer, PhilippUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Bertram, AnnaUNSPECIFIEDhttps://orcid.org/0000-0002-2757-670XUNSPECIFIED
Hines Chaves, Derrick ArmandoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Dias Ribeiro, MateusUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Garbo, AndreaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kiener, AnnaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Sabater Campomanes, ChristianUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Stradtner, MarioUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Widhalm, MarkusUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Görtz, StefanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Jäckel, FlorianUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Hoppe, RobertUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Hoffmann, NilsUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:June 2022
Journal or Publication Title:AIAA Aviation 2022 Forum
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI:10.2514/6.2022-3899
Page Range:pp. 1-19
Editors:
EditorsEmailEditor's ORCID iDORCID Put Code
UNSPECIFIEDAIAAUNSPECIFIEDUNSPECIFIED
Publisher:American Institute of Aeronautics and Astronautics, Inc.
Status:Published
Keywords:Data-driven Modeling, ROMs, Aerodynamics, Software
Event Title:AIAA Aviation 2022 Forum
Event Location:Chicago, USA
Event Type:international Conference
Event Start Date:27 June 2022
Event End Date:1 July 2022
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Efficient Vehicle
DLR - Research area:Aeronautics
DLR - Program:L EV - Efficient Vehicle
DLR - Research theme (Project):L - Digital Technologies
Location: Braunschweig
Institutes and Institutions:Institute for Aerodynamics and Flow Technology > CASE, BS
Institute of Software Methods for Product Virtualization > Enabling Software Technologies
Deposited By: Bekemeyer, Philipp
Deposited On:16 Dec 2022 09:27
Last Modified:24 Apr 2024 20:53

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