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2026, Vol: 15, Issue: 1
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Technical Note 


A Surrogate ANN–BEM Framework for Aerodynamic Modeling of Smart Wind Turbine Blades

Naoual Afif, Yassine Lakhal, Mohammed Haiek, Fatima Zahra Baghli, Samagassi Soulaimane.


Abstract
Accurate prediction of aerodynamic coefficients is essential for the design and control of smart blades featuring morphing airfoils. This study presents a data-driven metamodel based on Artificial Neural Networks (ANNs) developed to predict the aerodynamic behavior of airfoils within the NACA series. The model accepts geometric descriptors of airfoils along with the angle of attack (AoA) as input and outputs corresponding lift (Cl) and drag (Cd) coefficients. A high-fidelity aerodynamic database was generated through systematic simulations across a wide range of AoAs and NACA profiles to train and validate the ANN. The model is trained on NACA 4-digit series profiles covering a wide range of AoA and geometric parameters. The ANN model achieved a mean squared error of 2.10805 e-3 and an R² above 0.997 on test data. The trained metamodel demonstrates excellent generalisation accuracy while drastically reducing computational requirements compared to conventional CFD or BEM-based methods. The model is particularly suited for integration into larger simulation frameworks, such as Blade Element Momentum (BEM) codes or adaptive control systems, enabling real-time performance estimation for morphing smart blades. This work contributes a scalable and efficient surrogate modelling approach for aerodynamic prediction across diverse airfoil geometries.

Key words: NACA, airfoil, artificial neural networks (ANN), morphing blade, smart blades


 
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How to Cite this Article
Pubmed Style

Afif N, Lakhal Y, Haiek M, Baghli FZ, Soulaimane S. A Surrogate ANN–BEM Framework for Aerodynamic Modeling of Smart Wind Turbine Blades. Sol. Energy Sustain. Dev.. 2025; 14(2): 364-377.

doi:10.51646/jsesd.v14i2.1215

Web Style

Afif N, Lakhal Y, Haiek M, Baghli FZ, Soulaimane S. A Surrogate ANN–BEM Framework for Aerodynamic Modeling of Smart Wind Turbine Blades. https://www.jsesd.org/?mno=302658180 [Access: November 12, 2026].

doi:10.51646/jsesd.v14i2.1215

AMA (American Medical Association) Style

Afif N, Lakhal Y, Haiek M, Baghli FZ, Soulaimane S. A Surrogate ANN–BEM Framework for Aerodynamic Modeling of Smart Wind Turbine Blades. Sol. Energy Sustain. Dev.. 2025; 14(2): 364-377.


doi:10.51646/jsesd.v14i2.1215

Vancouver/ICMJE Style

Afif N, Lakhal Y, Haiek M, Baghli FZ, Soulaimane S. A Surrogate ANN–BEM Framework for Aerodynamic Modeling of Smart Wind Turbine Blades. Sol. Energy Sustain. Dev.. (2025), [cited November 12, 2026]; 14(2): 364-377.


doi:10.51646/jsesd.v14i2.1215

Harvard Style

Afif, N., Lakhal, . Y., Haiek, . M., Baghli, . F. Z. & Soulaimane, . S. (2025) A Surrogate ANN–BEM Framework for Aerodynamic Modeling of Smart Wind Turbine Blades. Sol. Energy Sustain. Dev., 14 (2), 364-377.


doi:10.51646/jsesd.v14i2.1215

Turabian Style

Afif, Naoual, Yassine Lakhal, Mohammed Haiek, Fatima Zahra Baghli, and Samagassi Soulaimane. 2025. A Surrogate ANN–BEM Framework for Aerodynamic Modeling of Smart Wind Turbine Blades. Solar Energy and Sustainable Development, 14 (2), 364-377.


doi:10.51646/jsesd.v14i2.1215

Chicago Style

Afif, Naoual, Yassine Lakhal, Mohammed Haiek, Fatima Zahra Baghli, and Samagassi Soulaimane. "A Surrogate ANN–BEM Framework for Aerodynamic Modeling of Smart Wind Turbine Blades." Solar Energy and Sustainable Development 14 (2025), 364-377.


doi:10.51646/jsesd.v14i2.1215

MLA (The Modern Language Association) Style

Afif, Naoual, Yassine Lakhal, Mohammed Haiek, Fatima Zahra Baghli, and Samagassi Soulaimane. "A Surrogate ANN–BEM Framework for Aerodynamic Modeling of Smart Wind Turbine Blades." Solar Energy and Sustainable Development 14.2 (2025), 364-377. Print.


doi:10.51646/jsesd.v14i2.1215

APA (American Psychological Association) Style

Afif, N., Lakhal, . Y., Haiek, . M., Baghli, . F. Z. & Soulaimane, . S. (2025) A Surrogate ANN–BEM Framework for Aerodynamic Modeling of Smart Wind Turbine Blades. Solar Energy and Sustainable Development, 14 (2), 364-377.


doi:10.51646/jsesd.v14i2.1215

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