Lamelar Ichthyosis

Pramudita, Adelia Wuri; Mawardi, Prasetyadi

doi:10.46889/jcmr.2021.2302

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2024

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“…The comparison between the original and the derived airfoils showed only a minimal error margin. This approach was developed utilizing MATLAB ® building on the work of Pramudita Satria Palar [13].…”

Section: Key Observationsmentioning

confidence: 99%

A Comprehensive Dataset of the Aerodynamic and Geometric Coefficients of Airfoils in the Public Domain

Agarwal,

Vijaykrishnan,

Mohanty

et al. 2024

Preprint

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This study presents an extensive collection of data on the aerodynamic behavior at a low Reynolds number and geometric coefficients for 2900 airfoils obtained through the class shape transformation (CST) method. By employing a verified OpenFOAM-based CFD simulation framework, lift and drag coefficients were determined at a Reynolds number of 10^5. Considering the limited availability of data on low Reynolds number airfoils, this dataset is invaluable for a wide range of applications, including unmanned aerial vehicles (UAVs) and wind turbines. Additionally, the study offers a method for automating CFD simulations that could be applied to obtain aerodynamic coefficients at higher Reynolds numbers. The breadth of this dataset also supports the enhancement and creation of machine learning (ML) models, further advancing research into the aerodynamics of airfoils and lifting surfaces.

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Section: Key Observationsmentioning

confidence: 99%