5 datasets found
  1. O

    G2Aero Database of Airfoils - Curated Airfoils

    • data.openei.org
    • osti.gov
    • +1more
    code
    Updated Sep 24, 2024
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    Olga Doronina; Andrew Glaws; Zachary Grey; Bumseok Lee; Olga Doronina; Andrew Glaws; Zachary Grey; Bumseok Lee (2024). G2Aero Database of Airfoils - Curated Airfoils [Dataset]. http://doi.org/10.25984/2448331
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    codeAvailable download formats
    Dataset updated
    Sep 24, 2024
    Dataset provided by
    Open Energy Data Initiative (OEDI)
    USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)
    National Renewable Energy Lab - NREL
    Authors
    Olga Doronina; Andrew Glaws; Zachary Grey; Bumseok Lee; Olga Doronina; Andrew Glaws; Zachary Grey; Bumseok Lee
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains a curated set of 19,164 airfoil shapes from various applications and the data-driven design space of separable shape tensors (PGA space), which can be used as a parameter space for machine-learning applications focused on airfoil shapes.

    We constructed the airfoil dataset in two main stages. First, we identified 13 baseline airfoils from the NREL 5MW and IEA 15MW reference wind turbines. We reparameterized these shapes using least-squares fits of 8-order CST parametrizations, which involve 18 coefficients. By uniformly perturbing all 18 CST coefficients by +/-20% around each baseline airfoil, we generated 1,000 unique airfoils. Each airfoil was sampled with 1,001 shape landmarks whose x-coordinates followed a cosine distribution along the chord. This process resulted in a total of 13,000 airfoil shapes, each with 1,001 landmarks.

    In the second phase, we gathered additional airfoils from the extensive BigFoil database, which consolidates data from sources such as the University of Illinois Urbana-Champaign (UIUC) airfoil database, the JavaFoil database, the NACA-TR-824 database, and others. We undertook a thorough pre-processing step to filter out shapes with sparse, noisy, or incomplete data. We also removed airfoils with sharp leading edge and those exceeding our threshold for trailing edge thickness. Additionally, we thinned out the collection of NACA airfoils-- parametric sweeps of NACA airfoils with increasing thickness and camber present in BigFoil database-- by selecting every fourth step in the parameter sweeps. Finally, we regularized the airfoils by reparametrizing them with an 8-order CST parametrization (with 1,001 shape landmarks with x coordinated following cosine distribution along the chord) and removing airfoils with high reconstruction errors. This data pre-processing resulted in a set of 6,164 airfoils. In total, our curated airfoil dataset comprises 19,164 airfoils, each with 1,001 landmarks, and is stored in the curated_airfoils.npz file.

    Using this curated airfoil dataset, we utilized the separable shape tensors framework to develop a data-driven parameterization of airfoils based on principal geodesic analysis (PGA) of separable shape tensors. This PGA space is provided in PGAspace.npz file.

  2. A database of CFD-computed flow fields around airfoils for machine-learning...

    • zenodo.org
    • data.niaid.nih.gov
    xz
    Updated Mar 26, 2021
    + more versions
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    Andrea Schillaci; Andrea Schillaci; Maurizio Quadrio; Maurizio Quadrio; Giacomo Boracchi; Giacomo Boracchi (2021). A database of CFD-computed flow fields around airfoils for machine-learning applications (part 2) [Dataset]. http://doi.org/10.5281/zenodo.4638071
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    xzAvailable download formats
    Dataset updated
    Mar 26, 2021
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Andrea Schillaci; Andrea Schillaci; Maurizio Quadrio; Maurizio Quadrio; Giacomo Boracchi; Giacomo Boracchi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset is designed to test Machine-Learning techniques on Computational Fluid Dynamics (CFD) data.

    It contains two-dimensional RANS simulations of the turbulent flow around NACA 4-digits airfoils, at fixed angle of attack (10 degrees) and at a fixed Reynolds number (3x10^6). The whole NACA family is spawned.

    The present dataset contains 425 geometries, 2600 further geometries are published in accompanying repository (10.5281/zenodo.4106752).

    For further information refer to: Schillaci, A., Quadrio, M., Pipolo, C., Restelli, M., Boracchi, G. "Inferring Functional Properties from Fluid Dynamics Features" 2020 25th International Conference on Pattern Recognition (ICPR) Milan, Italy, Jan 10-15, 2021

  3. PIBE project- Experimental characterization of stall noise in static and...

    • zenodo.org
    bin, pdf, zip
    Updated Jun 14, 2024
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    Benjamin Cotté; Benjamin Cotté; David Raus; Lisa Sicard; Monchaux Romain; Monchaux Romain; Emmanuel Jondeau; Pascal Souchotte; Michel Roger; David Raus; Lisa Sicard; Emmanuel Jondeau; Pascal Souchotte; Michel Roger (2024). PIBE project- Experimental characterization of stall noise in static and dynamic regimes using a NACA 63(3)418 airfoil [Dataset]. http://doi.org/10.5281/zenodo.10638882
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    zip, bin, pdfAvailable download formats
    Dataset updated
    Jun 14, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Benjamin Cotté; Benjamin Cotté; David Raus; Lisa Sicard; Monchaux Romain; Monchaux Romain; Emmanuel Jondeau; Pascal Souchotte; Michel Roger; David Raus; Lisa Sicard; Emmanuel Jondeau; Pascal Souchotte; Michel Roger
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Dynamic stall noise is one of the potential sources of amplitude modulations associated with wind turbine noise. This phenomenon is related to the periodic separation and reattachment of the boundary layer on the wind turbine blade suction side during its rotation. Within the framework of the PIBE project (Predicting the Impact of Wind Turbine Noise - https://www.anr-pibe.com/en), experiments were conducted in the anechoic wind tunnel of the École Centrale de Lyon in order to characterize stall noise on a pitching airfoil in both static and dynamic conditions.

    In version 1.0.0 of the database, data from the second campaign using an instrumented NACA63(3)418 airfoil in static and dynamic conditions are provided. The static data can be found in the file static_data_NACA63418.h5 that contains:

    1. static wall pressure data : lift and pressure coefficients;
    2. dynamic wall pressure data : Power Spectral Density (PSD) of fluctuating wall pressure;
    3. far-field acoustic data : Power Spectral Density (PSD) of acoustic pressure.

    The structure of the file is described in Tree_structure_static_data.pdf. To read the HDF5 file, the Matlab scripts given in read_HDF5_NACA63418_static_Matlab.zip can be used.

    The dynamic data can be found in the file dynamic_data_NACA63418.h5 that contains:

    1. static wall pressure data : phase-averaged lift coefficients;
    2. dynamic wall pressure data : phase-averaged spectrograms of fluctuating wall pressure;
    3. far-field acoustic data : phase-averaged spectrograms of acoustic pressure.

    The structure of the file is described in Tree_structure_dynamic_data.pdf. To read the HDF5 file, the Matlab scripts given in read_HDF5_NACA63418_dynamic_Matlab.zip can be used. Only the results for a mean angle of attack of 15° and an amplitude of 15° are provided in this file.

  4. f

    Data from: Numerical Simulation of the Boundary Layer Control on the NACA...

    • scielo.figshare.com
    jpeg
    Updated Jun 2, 2023
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    Douglas da Silva; Vinicius Malatesta (2023). Numerical Simulation of the Boundary Layer Control on the NACA 0015 Airfoil Through Vortex Generators [Dataset]. http://doi.org/10.6084/m9.figshare.14328945.v1
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    jpegAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    SciELO journals
    Authors
    Douglas da Silva; Vinicius Malatesta
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    ABSTRACT: This paper studies the influence caused by a vortex generator (VG) on a wing section with NACA 0015 airfoil when this generator is located before and after a recirculation bubble caused by the boundary layer detachment. The study was numerically carried out and concentrated under conditions of flow with Rec = 2.38 × 105 and angles of attack AoA = 3 and 6, characterized by the fact that they undergo detachment of the boundary layer before and after the location of the VG, respectively. The use of the generator in AoA = 3 strongly influenced the reduction of the recirculation bubble, leading to a drag reduction of 1.43%. In AoA = 6 with a bubble recirculation, the effect was much lower, with no well-defined formation of longitudinal vortices, resulting in increased drag and lift at 0.33 and 0.35%, respectively.

  5. d

    Data from: Lift Equivalence and Cancellation for Airfoil Surge-Pitch-Plunge...

    • catalog.data.gov
    • mhkdr.openei.org
    • +2more
    Updated Jan 11, 2025
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    North Carolina State University (2025). Lift Equivalence and Cancellation for Airfoil Surge-Pitch-Plunge Oscillations [Dataset]. https://catalog.data.gov/dataset/lift-equivalence-and-cancellation-for-airfoil-surge-pitch-plunge-oscillations-28eba
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    Dataset updated
    Jan 11, 2025
    Dataset provided by
    North Carolina State University
    Description

    A NACA 0018 airfoil in freestream velocity is oscillated in longitudinal, transverse, and angle-of-attack directions with respect to the freestream velocity, known as surge, plunge, and pitch. The lift-based equivalence method introduces phase shifts between these three motions to construct in-phase sinusoidal components for maximum lift, waveform construction. Lift cancellation is also determined with the exact negative pitch and plunge motion amplitudes found from the equivalence method to achieve out-of-phase wave destruction. Lift cancellation occurs when a combination of these motions is sought to obtain a constant lift magnitude throughout the oscillation cycle. To achieve both equivalence and cancellation of lift, a prescribed pure pitch amplitude through the Theodorsen theory equates the corresponding equivalent plunge amplitude and pitch-plunge phase shift. These Theodorsen, linear superposition findings of pitch-plunge are leveraged toward the Greenberg theory to determine a closed-form, surge-pitch-plunge solution through the addition of a surge-plunge phase shift and optimal surge amplitude for lift cancellation. The lift cancellation surge-pitch-plunge amplitudes define the equivalence amplitude investigated here and theoretically limit the experiment to combinations of the first lift harmonic of the Greenberg theory. The analytical results are then compared with experimental lift force measurements and dye visualization. The normalized lift differences due to unsteady wake and boundary-layer behavior are examined to explore the extents of the Greenberg theory for these cases of lift-based equivalence and cancellation.

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Olga Doronina; Andrew Glaws; Zachary Grey; Bumseok Lee; Olga Doronina; Andrew Glaws; Zachary Grey; Bumseok Lee (2024). G2Aero Database of Airfoils - Curated Airfoils [Dataset]. http://doi.org/10.25984/2448331

G2Aero Database of Airfoils - Curated Airfoils

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
codeAvailable download formats
Dataset updated
Sep 24, 2024
Dataset provided by
Open Energy Data Initiative (OEDI)
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)
National Renewable Energy Lab - NREL
Authors
Olga Doronina; Andrew Glaws; Zachary Grey; Bumseok Lee; Olga Doronina; Andrew Glaws; Zachary Grey; Bumseok Lee
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This dataset contains a curated set of 19,164 airfoil shapes from various applications and the data-driven design space of separable shape tensors (PGA space), which can be used as a parameter space for machine-learning applications focused on airfoil shapes.

We constructed the airfoil dataset in two main stages. First, we identified 13 baseline airfoils from the NREL 5MW and IEA 15MW reference wind turbines. We reparameterized these shapes using least-squares fits of 8-order CST parametrizations, which involve 18 coefficients. By uniformly perturbing all 18 CST coefficients by +/-20% around each baseline airfoil, we generated 1,000 unique airfoils. Each airfoil was sampled with 1,001 shape landmarks whose x-coordinates followed a cosine distribution along the chord. This process resulted in a total of 13,000 airfoil shapes, each with 1,001 landmarks.

In the second phase, we gathered additional airfoils from the extensive BigFoil database, which consolidates data from sources such as the University of Illinois Urbana-Champaign (UIUC) airfoil database, the JavaFoil database, the NACA-TR-824 database, and others. We undertook a thorough pre-processing step to filter out shapes with sparse, noisy, or incomplete data. We also removed airfoils with sharp leading edge and those exceeding our threshold for trailing edge thickness. Additionally, we thinned out the collection of NACA airfoils-- parametric sweeps of NACA airfoils with increasing thickness and camber present in BigFoil database-- by selecting every fourth step in the parameter sweeps. Finally, we regularized the airfoils by reparametrizing them with an 8-order CST parametrization (with 1,001 shape landmarks with x coordinated following cosine distribution along the chord) and removing airfoils with high reconstruction errors. This data pre-processing resulted in a set of 6,164 airfoils. In total, our curated airfoil dataset comprises 19,164 airfoils, each with 1,001 landmarks, and is stored in the curated_airfoils.npz file.

Using this curated airfoil dataset, we utilized the separable shape tensors framework to develop a data-driven parameterization of airfoils based on principal geodesic analysis (PGA) of separable shape tensors. This PGA space is provided in PGAspace.npz file.

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