Publication
Fast Flapping Aerodynamics Prediction Using a Recurrent Neural Network
| dc.contributor.author | Pereira, João A. F. | |
| dc.contributor.author | Camacho, Emanuel A. R. | |
| dc.contributor.author | Marques, Flávio D. | |
| dc.contributor.author | Silva, A. R. R. | |
| dc.date.accessioned | 2024-01-09T09:58:12Z | |
| dc.date.available | 2024-01-09T09:58:12Z | |
| dc.date.issued | 2023-11-15 | |
| dc.description.abstract | One of the major tasks of aerodynamics is the study of the flow around airfoils. While most conventional methods deal well with steady flows, unsteady airfoils, like the ones on helicopter blades, are subject to such complex dynamic flows that their study can impose substantial difficulties. However, recent applications of machine learning, in the form of neural networks, have shown very promising results when dealing with complex dynamic aerodynamic phenomena. For this reason, this paper proposes the implementation of a recurrent neural network for the time-wise prediction of the lift, momentum, and drag coefficients for an airfoil subject to plunging motion, using the 𝑅𝑒, k, h, 𝑘ℎ, and the time history of the effective angle of attack as inputs. Results from early training already suggest the network’s capability to approximate the desired outputs, even if with some limitations. However, the network configuration is flexible enough to be fed with either experimental or numerical data in the future. | pt_PT |
| dc.description.sponsorship | This research was funded by Portuguese’s Fundação para a Ciência e Tecnologia (FCT) under grant numbers UIDB/50022/2020, UIDP/50022/2020, LA/P/0079/2020, 2020.04648.BD, and by Brazil’s National Council for Scientific and Technological Development (CNPq grant #306824/2019-1). | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Pereira, J.A.F.; Camacho, E.A.R.; Marques, F.D.; Silva, A.R.R. Fast Flapping Aerodynamics Prediction Using a Recurrent Neural Network. Eng. Proc. 2023, 56, 219. https://doi.org/10.3390/ASEC2023-16272 | pt_PT |
| dc.identifier.doi | 10.3390/ASEC2023-16272 | pt_PT |
| dc.identifier.issn | 2673-4591 | |
| dc.identifier.uri | http://hdl.handle.net/10400.6/13890 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | MDPI AG | pt_PT |
| dc.relation | Associate Laboratory of Energy, Transports and Aeronautics | |
| dc.relation | Associate Laboratory of Energy, Transports and Aeronautics | |
| dc.relation | Associate Laboratory of Energy, Transports and Aerospace. | |
| dc.relation | Boundary Layer Control in Plunging and Pitching Airfoils | |
| dc.relation.publisherversion | https://www.mdpi.com/2673-4591/56/1/219 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Unsteady aerodynamics | pt_PT |
| dc.subject | Recurrent neural network | pt_PT |
| dc.subject | Potential flow | pt_PT |
| dc.title | Fast Flapping Aerodynamics Prediction Using a Recurrent Neural Network | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Associate Laboratory of Energy, Transports and Aeronautics | |
| oaire.awardTitle | Associate Laboratory of Energy, Transports and Aeronautics | |
| oaire.awardTitle | Associate Laboratory of Energy, Transports and Aerospace. | |
| oaire.awardTitle | Boundary Layer Control in Plunging and Pitching Airfoils | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50022%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F50022%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0079%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/POR_CENTRO/2020.04648.BD/PT | |
| oaire.citation.conferencePlace | Online, 27 October–10 November 2023 | pt_PT |
| oaire.citation.issue | 1 | pt_PT |
| oaire.citation.startPage | 219 | pt_PT |
| oaire.citation.title | Engineering Proceedings, 4th International Electronic Conference on Applied Sciences | pt_PT |
| oaire.citation.volume | 56 | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | POR_CENTRO | |
| person.familyName | Rodrigues Camacho | |
| person.familyName | Marques | |
| person.familyName | Resende Rodrigues da Silva | |
| person.givenName | Emanuel António | |
| person.givenName | Flávio D. | |
| person.givenName | André | |
| person.identifier | 1584962 | |
| person.identifier | J-4185-2012 | |
| person.identifier.ciencia-id | 4416-08D8-F83D | |
| person.identifier.ciencia-id | 8316-99B9-CBB4 | |
| person.identifier.ciencia-id | 8219-4B2B-E1C7 | |
| person.identifier.orcid | 0000-0002-1648-8368 | |
| person.identifier.orcid | 0000-0003-1451-3424 | |
| person.identifier.orcid | 0000-0002-4901-7140 | |
| person.identifier.rid | F-4698-2012 | |
| person.identifier.scopus-author-id | 7102759984 | |
| person.identifier.scopus-author-id | 11440407500 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
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