Machine Learning Approach to Aerodynamic Analysis of NACA0005 Airfoil: ANN and CFD Integration

Machine Learning Approach to Aerodynamic Analysis of NACA0005 Airfoil: ANN and CFD Integration

This study presents a machine learning approach to predict the unsteady aerodynamic performance of a NACA0005 airfoil. Data generated by computational fluid dynamics (CFD) is used to train the model for Reynolds numbers <inline-formula> <tex-math notation="LaTeX">$Re \in [{1000...

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Bibliographic Details
Main Authors: Taiba Kouser, Dilek Funda Kurtulus, Srikanth Goli, Abdulrahman Aliyu, Imil Hamda Imran, Luai M. Alhems, Azhar M. Memon
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
NACA0005
aerodynamic coefficients
Reynolds number
angle of attack
artificial neural network (ANN)
Online Access:https://ieeexplore.ieee.org/document/11095683/
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