ROM-based uncertainties quantification of flutter speed prediction of the BSCW wing
ROM-based uncertainties quantification of flutter speed prediction of the BSCW wing
This paper deals with the implementation of a data--driven machinery to produce aerodynamic reduced order models for the rapid prediction of the flutter boundary. A thorough investigation was carried out that ranges from the dependence on model forms and the choice of training samples in the model generation, to establishing the validity range of the predictions when applying the model to other flight conditions than those used for the model generation. We propagated these sources of uncertainty on the flutter boundary using the aerodynamic reduced order models. It was found that multiple model forms contribute to having a confidence level in predictions. A disagreement in predictions from multiple model forms is an early indicator of increased complexity in the flow physics, alerting that: a) the form of reduced order models may be overly simplified; and b) the ability to resolve the correct physics may call for a higher fidelity flow solver than used for the training set. The test case is for the NASA-SC(2)0414 supercritical airfoil.
Aerospace Research Central
Righi, Marcello
07b278f4-014c-49ac-a206-8654cf405d75
Düzel, Sven
586ca941-f8e7-4b06-89bc-966ed63e1222
Anderegg, David
22e7692e-0005-49c2-8bcf-17ab9859a48c
Da Ronch, Andrea
a2f36b97-b881-44e9-8a78-dd76fdf82f1a
Massegur Sampietro, David
d5bc71e8-f1b8-4c9f-9537-7ff63ad19426
Soukhmane, Issam
8cd305ab-34bb-4e98-9bff-c47b400398c2
Righi, Marcello
07b278f4-014c-49ac-a206-8654cf405d75
Düzel, Sven
586ca941-f8e7-4b06-89bc-966ed63e1222
Anderegg, David
22e7692e-0005-49c2-8bcf-17ab9859a48c
Da Ronch, Andrea
a2f36b97-b881-44e9-8a78-dd76fdf82f1a
Massegur Sampietro, David
d5bc71e8-f1b8-4c9f-9537-7ff63ad19426
Soukhmane, Issam
8cd305ab-34bb-4e98-9bff-c47b400398c2
Righi, Marcello, Düzel, Sven, Anderegg, David, Da Ronch, Andrea, Massegur Sampietro, David and Soukhmane, Issam
(2021)
ROM-based uncertainties quantification of flutter speed prediction of the BSCW wing.
In AIAA SCITECH 2022 Forum.
Aerospace Research Central..
(doi:10.2514/6.2022-0179).
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper deals with the implementation of a data--driven machinery to produce aerodynamic reduced order models for the rapid prediction of the flutter boundary. A thorough investigation was carried out that ranges from the dependence on model forms and the choice of training samples in the model generation, to establishing the validity range of the predictions when applying the model to other flight conditions than those used for the model generation. We propagated these sources of uncertainty on the flutter boundary using the aerodynamic reduced order models. It was found that multiple model forms contribute to having a confidence level in predictions. A disagreement in predictions from multiple model forms is an early indicator of increased complexity in the flow physics, alerting that: a) the form of reduced order models may be overly simplified; and b) the ability to resolve the correct physics may call for a higher fidelity flow solver than used for the training set. The test case is for the NASA-SC(2)0414 supercritical airfoil.
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e-pub ahead of print date: 29 December 2021
Venue - Dates:
AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum 2022), , San Diego, United States, 2022-01-03 - 2022-01-07
Identifiers
Local EPrints ID: 484026
URI: http://eprints.soton.ac.uk/id/eprint/484026
PURE UUID: ed20d56a-996f-4cd6-9328-9904d3339894
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Date deposited: 09 Nov 2023 17:33
Last modified: 18 Mar 2024 03:59
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Author:
Marcello Righi
Author:
Sven Düzel
Author:
David Anderegg
Author:
David Massegur Sampietro
Author:
Issam Soukhmane
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