G2Aero Database of Airfoils - Curated Airfoils

Doronina, Olga; Glaws, Andrew; Grey, Zachary; Lee, Bumseok

doi:10.25984/2448331

Title: G2Aero Database of Airfoils - Curated Airfoils

Dataset
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Abstract

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 thinnedmore »« less

Authors:

; Glaws, Andrew; Grey, Zachary; Lee, Bumseok

National Renewable Energy Lab - NREL

Publication Date:: Tue Sep 24 00:00:00 EDT 2024

Other Number(s):: 6198

Research Org.:: DOE Open Energy Data Initiative (OEDI); National Renewable Energy Lab - NREL

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)

Collaborations:: National Renewable Energy Lab - NREL

Subject:: Array; BigFoil; G2Aero; PGA; airfoils; curated; data; database; dataset; energy; machine learning; parameter space; shapes; wind energy

OSTI Identifier:: 2448331

DOI:: https://doi.org/10.25984/2448331

Citation Formats


                    Doronina, Olga, Glaws, Andrew, Grey, Zachary, and Lee, Bumseok. G2Aero Database of Airfoils - Curated Airfoils.  United States: N. p., 2024. 
        Web.  doi:10.25984/2448331.

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                    Doronina, Olga, Glaws, Andrew, Grey, Zachary, & Lee, Bumseok. G2Aero Database of Airfoils - Curated Airfoils.  United States.  doi:https://doi.org/10.25984/2448331

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                    Doronina, Olga, Glaws, Andrew, Grey, Zachary, and Lee, Bumseok. 2024.  
"G2Aero Database of Airfoils - Curated Airfoils".  United States.  doi:https://doi.org/10.25984/2448331.  https://www.osti.gov/servlets/purl/2448331. Pub date:Tue Sep 24 00:00:00 EDT 2024

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@article{osti_2448331,

  title        = {G2Aero Database of Airfoils - Curated Airfoils},

  author       = {Doronina, Olga and Glaws, Andrew and Grey, Zachary and Lee, Bumseok},

  abstractNote = {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.},

  doi          = {10.25984/2448331},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Sep 24 00:00:00 EDT 2024},

  month        = {Tue Sep 24 00:00:00 EDT 2024}

}

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DOI: https://doi.org/10.25984/2448331

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