Data from "Wall-resolved LES modeling of a wind turbine airfoil at different angles of attack".
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Data Documentation for:"Wall-resolved LES modeling of a wind turbine airfoil at different angles of attack". Irene Solís-Gallego, Katia María Argüelles Díaz, Jesús Manuel Fernández Oro, Sandra Velarde-Suárez (*), (2020).(*) sandrav@uniovi.es. Fluid Mechanics Area, Department of Energy, University of Oviedo, C/Wifredo Ricart s/n, Gijon, Asturias, 33204, SpainPublished in Journal of Marine Science and Engineering, 8, 212, (2020).https://doi.org/10.3390/jmse8030212 General Information Name of dataset:Data from "Wall-resolved LES modeling of a wind turbine airfoil at different angles of attack". Name of data files in data set:'01_JMSE2020_lift_drag_LES.txt''02_JMSE2020_lift_drag_EXPERIMENTAL_SELIG.txt''03_JMSE2020_drag_LES_-25.txt''04_JMSE2020_drag_LES_125.txt''05_JMSE2020_drag_LES_25.txt''06_JMSE2020_drag_LES_75.txt''07_JMSE2020_lift_LES_-25.txt''08_JMSE2020_lift_LES_125.txt''09_JMSE2020_lift_LES_25.txt''10_JMSE2020_lift_LES_75.txt' Dataset language:English Date the data set was last modified:15/01/2020 Funder:This work was supported by Projects (1) “Caracterización y predicción de la generación aerodinámica de ruido en perfiles de turbinas eólicas”, DPI2011-25419, provided by the Spanish Ministry of Economy and Competitiveness; (2) “Desarrollo y construcción de turbinas eólicas de eje vertical para entornos urbanos”, ENE2017-89965-P, from the Spanish Ministry of Economy and Business, as well as by both “Severo Ochoa” predoctoral research scholarship provided by the Principality of Asturias. How to cite data:Data from [article reference] Methodology for data collection:Numerical simulations with FLUENT software was used, with a high-resolution Large Eddy Simulation (LES) model and the Smagorinsky–Lilly subgrid-scale model, to resolve the turbulent flow around the airfoil, applying velocity inlet and pressure outlet boundary conditions at a Reynolds number of 350.000. A structured C-type mesh with 19 million elements was refined in the boundary layer and trailing edge regions. Data collector(s):Katia María Argüelles DíazJesús Manuel Fernández Oro Date of data collection:01/10/2019 - 15/01/2020 Person to contact with questions:Corresponding author or first autor (see affilations and e-mail in the paper). Data entry:12/11/2025 Software (including version #) used to prepare data set:Matlab 2023bExcel 365 Data processing that was performed:The data processing involved numerical analyses. For the LES simulations, residuals of all flow variables were monitored to ensure convergence (below 10⁻⁴), and results were time-averaged after reaching a statistically steady state. Post-processing included the calculation of velocity fields, Reynolds stresses, turbulent kinetic energy (TKE), aerodynamic coefficients as well as the use of the Q-criterion to identify coherent vortex structures in the flow. Variables:flow time [s]angle [deg]lift coefficient [non-dimensional]drag coefficient [non-dimensional] File Overview:'01_JMSE2020_lift_drag_LES.txt', numerical results from the LES model, aerodynamic coefficients for each tested angle of attack (-2.5 deg, 2.5 deg, 7.5 deg and 12.5 deg). Columns: angle, lift coefficient, drag coefficient.'02_JMSE2020_lift_drag_EXPERIMENTAL_SELIG.txt', experimental results of the aerodynamic coefficients from Selig (ref. 13 of the paper). Columns: angle, lift coefficient, drag coefficient.Numerical simulation data from LES model. Temporal evolution of the drag coefficient for angles of attack: -2.5 deg, 2.5 deg, 7.5 deg and 12.5 deg. Colums: flow time, drag coefficient.'03_JMSE2020_drag_LES_-25.txt''04_JMSE2020_drag_LES_125.txt''05_JMSE2020_drag_LES_25.txt''06_JMSE2020_drag_LES_75.txt'Numerical simulation data from LES model. Temporal evolution of the lift coefficient for angles of attack: -2.5 deg, 2.5 deg, 7.5 deg and 12.5 deg. Colums: flow time, lift coefficient.'07_JMSE2020_lift_LES_-25.txt''08_JMSE2020_lift_LES_125.txt''09_JMSE2020_lift_LES_25.txt''10_JMSE2020_lift_LES_75.txt'
