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Flapping Airfoil Aerodynamics using Recurrent Neural Network

2024-01-04Conference object Embargoed access
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dc.contributor.authorPereira, João A.
dc.contributor.authorCamacho, Emanuel A. R.
dc.contributor.authorMarques, Flávio D.
dc.contributor.authorSilva, André
dc.date.accessioned2025-01-06T11:16:39Z
dc.date.embargo2060-01-04
dc.date.issued2024-01-04
dc.description.abstractThe recent increase in interest in artificial intelligence and neural networks has stirred up various industries. Inevitably, its application will trickle down to the most fundamental studies, for instance, unsteady aerodynamics. The present paper serves the purpose of exploring the ability of a recurrent neural network to predict flapping airfoil aerodynamics, in particular the lift coefficient of a plunging NACA0012 airfoil. Thus, a neural network is designed and trained using motion parameters, such as motion frequency and effective angle of attack, to output the instantaneous lift coefficient over a plunging period. Training data is generated using a panel code (HSPM) for fast generation and early testing. Results show that the neural network can adequately predict the lift coefficient for various conditions, including plunging kinematics that are far from the training domain. Future work will build on this framework and extend it to other aerodynamic coefficients using CFD results and experiments, which should enhance the value of the estimates.pt_PT
dc.description.sponsorshipFundação para a Ciência e a Tecnologia (FCT) e Brazilian National Council for Scientific and Technological Development – CNPq (grant #306824/2019-1)pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationJoão A. Pereira, Emanuel A. Camacho, Flavio D. Marques and Andre R. Silva, "Flapping Airfoil Aerodynamics using Recurrent Neural Network", 2024 AIAA SciTech Forum and Exposition, Orlando (FL), USA , 8-12 January 2024pt_PT
dc.identifier.doi10.2514/6.2024-1982pt_PT
dc.identifier.isbn978-162410711-5
dc.identifier.urihttp://hdl.handle.net/10400.6/14964
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherAmerican Institute of Aeronautics and Astronautics, Incpt_PT
dc.relationAssociate Laboratory of Energy, Transports and Aeronautics
dc.relationAssociate Laboratory of Energy, Transports and Aeronautics
dc.relationAssociate Laboratory of Energy, Transports and Aerospace.
dc.relationBoundary Layer Control in Plunging and Pitching Airfoils
dc.relation.publisherversionhttps://arc.aiaa.org/doi/abs/10.2514/6.2024-1982pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectAerodynamic Coefficientspt_PT
dc.subjectFlapping Airfoilpt_PT
dc.subjectRecurrent Neural Networkpt_PT
dc.subjectAerodynamic Performancept_PT
dc.subjectComputational Fluid Dynamicspt_PT
dc.subjectArtificial Intelligencept_PT
dc.subjectUnsteady Aerodynamicspt_PT
dc.subjectReduced Order Modellingpt_PT
dc.subjectHelicopter Bladept_PT
dc.subjectFlow Conditionspt_PT
dc.titleFlapping Airfoil Aerodynamics using Recurrent Neural Networkpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleAssociate Laboratory of Energy, Transports and Aeronautics
oaire.awardTitleAssociate Laboratory of Energy, Transports and Aeronautics
oaire.awardTitleAssociate Laboratory of Energy, Transports and Aerospace.
oaire.awardTitleBoundary Layer Control in Plunging and Pitching Airfoils
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50022%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F50022%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0079%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/POR_CENTRO/2020.04648.BD/PT
oaire.citation.conferencePlaceOrlando (FL), Estados Unidos da Américapt_PT
oaire.citation.title2024 AIAA SciTech Forum and Expositionpt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamPOR_CENTRO
person.familyNameRodrigues Camacho
person.familyNameMarques
person.familyNameResende Rodrigues da Silva
person.givenNameEmanuel António
person.givenNameFlávio D.
person.givenNameAndré
person.identifier1584962
person.identifierJ-4185-2012
person.identifier.ciencia-id4416-08D8-F83D
person.identifier.ciencia-id8316-99B9-CBB4
person.identifier.ciencia-id8219-4B2B-E1C7
person.identifier.orcid0000-0002-1648-8368
person.identifier.orcid0000-0003-1451-3424
person.identifier.orcid0000-0002-4901-7140
person.identifier.ridF-4698-2012
person.identifier.scopus-author-id7102759984
person.identifier.scopus-author-id11440407500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.embargofctOs direitos do artigo foram concedidos à American Institute of Aeronautics and Astronautics, Inc.pt_PT
rcaap.rightsembargoedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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