The University of Southampton
University of Southampton Institutional Repository

Dynamic mode decomposition-based reconstructions for fluid-structure interactions: An application to membrane wings

Dynamic mode decomposition-based reconstructions for fluid-structure interactions: An application to membrane wings
Dynamic mode decomposition-based reconstructions for fluid-structure interactions: An application to membrane wings

Four data-driven low-order modeling approaches, Dynamic mode decomposition (DMD) and three other variations (optimal mode decomposition, total-least-squares DMD and high-order DMD), are used to capture the spatio-temporal evolution of fluid–structure interactions. These methods are applied to experimental data obtained in a flow over a flexible membrane wing and its elastic deformation. Spectral coherence indicates there exists an interaction between the flow and structural deformation at a single frequency for this problem (depending on the angle of attack and/or the presence of a ground). It is therefore an ideal dataset to assess the performance of the four different methods in terms of the relevant modes/frequencies and reconstruction of flow and structural deformation. We show that the four methods detect the same dominant frequency (within Fourier resolution) and qualitatively the same associated mode. However, the modes appear to be heavily damped or amplified preventing a successful flow and structure reconstruction (except when using high-order DMD). This problem persists even if the damping coefficients are set to 0 due to imprecision in the estimation of the dominant frequency. The reconstruction is assessed by means of the average correlation between the real and reconstructed fields corresponding to 0.42 and 0.85 for the fluid and membrane deformation respectively when using high-order DMD (and virtually 0 for the other three methods). Based on the analysis, we conclude that high-order DMD, particularly for when fluid and structural data are modeled simultaneously, is the most suitable method to generate linear low-order models for fluid–structure interaction problems. Further, we show that this modeling is not dependent on the relative energies of fluid and membrane deformation.

Flow–structure interaction, Linear models, Low-order modeling, Membrane wings
0889-9746
Rodriguez-Lopez, Eduardo
8595fcd2-436b-4c93-81ca-58aab8a27bb8
Carter, Douglas
75fd127b-b918-4bd3-9ada-6e1c7e1ad69d
Ganapathisubramani, Bharathram
5e69099f-2f39-4fdd-8a85-3ac906827052
Rodriguez-Lopez, Eduardo
8595fcd2-436b-4c93-81ca-58aab8a27bb8
Carter, Douglas
75fd127b-b918-4bd3-9ada-6e1c7e1ad69d
Ganapathisubramani, Bharathram
5e69099f-2f39-4fdd-8a85-3ac906827052

Rodriguez-Lopez, Eduardo, Carter, Douglas and Ganapathisubramani, Bharathram (2021) Dynamic mode decomposition-based reconstructions for fluid-structure interactions: An application to membrane wings. Journal of Fluids and Structures, 104, [103315]. (doi:10.1016/j.jfluidstructs.2021.103315).

Record type: Article

Abstract

Four data-driven low-order modeling approaches, Dynamic mode decomposition (DMD) and three other variations (optimal mode decomposition, total-least-squares DMD and high-order DMD), are used to capture the spatio-temporal evolution of fluid–structure interactions. These methods are applied to experimental data obtained in a flow over a flexible membrane wing and its elastic deformation. Spectral coherence indicates there exists an interaction between the flow and structural deformation at a single frequency for this problem (depending on the angle of attack and/or the presence of a ground). It is therefore an ideal dataset to assess the performance of the four different methods in terms of the relevant modes/frequencies and reconstruction of flow and structural deformation. We show that the four methods detect the same dominant frequency (within Fourier resolution) and qualitatively the same associated mode. However, the modes appear to be heavily damped or amplified preventing a successful flow and structure reconstruction (except when using high-order DMD). This problem persists even if the damping coefficients are set to 0 due to imprecision in the estimation of the dominant frequency. The reconstruction is assessed by means of the average correlation between the real and reconstructed fields corresponding to 0.42 and 0.85 for the fluid and membrane deformation respectively when using high-order DMD (and virtually 0 for the other three methods). Based on the analysis, we conclude that high-order DMD, particularly for when fluid and structural data are modeled simultaneously, is the most suitable method to generate linear low-order models for fluid–structure interaction problems. Further, we show that this modeling is not dependent on the relative energies of fluid and membrane deformation.

Text
Membrane_flow_data_driven_reconstruction_revised_2 - Accepted Manuscript
Download (1MB)

More information

Accepted/In Press date: 6 May 2021
e-pub ahead of print date: 15 May 2021
Published date: July 2021
Additional Information: Publisher Copyright: © 2021 Elsevier Ltd
Keywords: Flow–structure interaction, Linear models, Low-order modeling, Membrane wings

Identifiers

Local EPrints ID: 449226
URI: http://eprints.soton.ac.uk/id/eprint/449226
ISSN: 0889-9746
PURE UUID: 6159e7cb-8c31-4123-be13-f88e77b96e4c
ORCID for Bharathram Ganapathisubramani: ORCID iD orcid.org/0000-0001-9817-0486

Catalogue record

Date deposited: 20 May 2021 16:31
Last modified: 17 Mar 2024 06:33

Export record

Altmetrics

Contributors

Author: Eduardo Rodriguez-Lopez
Author: Douglas Carter

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×