Publication: On the extension of k-ω-SST corrections to predict flow separation on thick airfoils with leading-edge roughness
| dc.contributor.author | Gutiérrez Amo, Rubén | |
| dc.contributor.author | Zamponi, Riccardo | |
| dc.contributor.author | Ragni, Daniele | |
| dc.contributor.author | Llorente, Elena | |
| dc.contributor.author | Aranguren Garacochea, Patricia | |
| dc.contributor.department | Ingeniería | es_ES |
| dc.contributor.department | Ingeniaritza | eu |
| dc.date.accessioned | 2023-08-23T06:21:38Z | |
| dc.date.available | 2023-08-23T06:21:38Z | |
| dc.date.issued | 2023 | |
| dc.date.updated | 2023-08-23T06:13:52Z | |
| dc.description.abstract | Modern wind turbines employ thick airfoils in the outer region of the blade with strong adverse pressure gradients and high sensitivity to flow separation, which can be anticipated by leading-edge roughness. However, Reynolds average Navier-Stokes simulations currently overpredict the Reynolds shear stresses near the surface, and the flow separation is not correctly predicted. Hence, these methods are not representative enough to optimize the blade design to avoid flow separation, which becomes relevant for rough blades. While several eddy-viscosity corrections in the (Formula presented.) turbulence model have been previously studied to predict flow separation over smooth airfoils, the present study aims to extend their applicability to airfoils with leading-edge roughness. Two corrections, whose effect on flow physics has not been empirically quantified, are addressed. Particle image velocimetry measurements have been performed on a 30% thick airfoil to quantify the impact of these corrections. The reduction of the eddy viscosity introduced by the corrections leads to a shift of the peak location of the Reynolds shear stresses away from the surface, which, in turn, promotes flow separation and improves the prediction of the mean velocity and the pressure-coefficient distribution. Besides, the ratio between the main turbulent shear stress and turbulent kinetic energy is demonstrated to be lower than the standard value used in the (Formula presented.) turbulence model at the boundary-layer outer edge. Adjusting this ratio for an angle of attack of 0° decreases the error on the predicted lift and drag coefficients from 75% to 3% and from 58% to 39%, respectively. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Gutierrez, R., Zamponi, R., Ragni, D., Llorente, E., & Aranguren, P. (2023). On the extension of k − ω − SST corrections to predict flow separation on thick airfoils with leading‐edge roughness. Wind Energy, 26(7), 650-667. https://doi.org/10.1002/we.2822 | en |
| dc.identifier.doi | 10.1002/we.2822 | |
| dc.identifier.issn | 1095-4244 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/46012 | |
| dc.language.iso | eng | en |
| dc.publisher | Wiley | en |
| dc.relation.ispartof | Wind Energy, 2023; 26: 650–667 | en |
| dc.relation.publisherversion | https://doi.org/10.1002/we.2822 | |
| dc.rights | © 2023 The Author. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Aerodynamics | en |
| dc.subject | Distributed roughness | en |
| dc.subject | Flow separation | en |
| dc.subject | PIV | en |
| dc.subject | Thick airfoils | en |
| dc.title | On the extension of k-ω-SST corrections to predict flow separation on thick airfoils with leading-edge roughness | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | Versión publicada / Argitaratu den bertsioa | es |
| dc.type.version | info:eu-repo/semantics/publishedVersion | en |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | b28d5c01-2691-468a-a076-5b6bb74ff88a | |
| relation.isAuthorOfPublication.latestForDiscovery | b28d5c01-2691-468a-a076-5b6bb74ff88a |