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Open AccessArticle
Experimental and Dynamic Modeling of a Variable-Pitch VAWT Using a Neural Network and the DMST Model
by
Luz M. Sanchez-Rivera
Luz M. Sanchez-Rivera *
,
Jorge Díaz-Salgado
Jorge Díaz-Salgado
,
Oliver M. Huerta-Chávez
Oliver M. Huerta-Chávez and
Jesús García-Barrera
Jesús García-Barrera
División de Ingeniería Mecánica, Mecatrónica e Industrial, Posgrado de Ingeniería Mecatrónica, Tecnológico Nacional de México (TecNM), Campus Ecatepec–Tecnológico de Estudios Superiores de Ecatepec (TESE), Ecatepec de Morelos 55210, Estado de México, Mexico
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(20), 10989; https://doi.org/10.3390/app152010989 (registering DOI)
Submission received: 6 September 2025
/
Revised: 28 September 2025
/
Accepted: 8 October 2025
/
Published: 13 October 2025
Abstract
The mathematical modeling and experimental validation of a non-conventional vertical-axis wind turbine (VAWT) with a variable-pitch angle are presented, employing the Double-Multiple Streamtube (DMST) method to simulate aerodynamic performance. The aerodynamic coefficients required by the model are obtained through a data-driven approach using a multi-input, two-output multilayer perceptron artificial neural network (MLP–ANN). The model is validated through numerical simulations under two distinct wind input profiles. An experimental evaluation with a prototype replicates the step input. It shows strong agreement with the simulations, particularly in the angular velocity response, which fluctuates between 35 and 55 RPM, with an average value in the range of 40–45 RPM. This hybrid methodology enhances the modeling fidelity of VAWTs and provides a scalable framework for real-time aerodynamic analysis and control.
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MDPI and ACS Style
Sanchez-Rivera, L.M.; Díaz-Salgado, J.; Huerta-Chávez, O.M.; García-Barrera, J.
Experimental and Dynamic Modeling of a Variable-Pitch VAWT Using a Neural Network and the DMST Model. Appl. Sci. 2025, 15, 10989.
https://doi.org/10.3390/app152010989
AMA Style
Sanchez-Rivera LM, Díaz-Salgado J, Huerta-Chávez OM, García-Barrera J.
Experimental and Dynamic Modeling of a Variable-Pitch VAWT Using a Neural Network and the DMST Model. Applied Sciences. 2025; 15(20):10989.
https://doi.org/10.3390/app152010989
Chicago/Turabian Style
Sanchez-Rivera, Luz M., Jorge Díaz-Salgado, Oliver M. Huerta-Chávez, and Jesús García-Barrera.
2025. "Experimental and Dynamic Modeling of a Variable-Pitch VAWT Using a Neural Network and the DMST Model" Applied Sciences 15, no. 20: 10989.
https://doi.org/10.3390/app152010989
APA Style
Sanchez-Rivera, L. M., Díaz-Salgado, J., Huerta-Chávez, O. M., & García-Barrera, J.
(2025). Experimental and Dynamic Modeling of a Variable-Pitch VAWT Using a Neural Network and the DMST Model. Applied Sciences, 15(20), 10989.
https://doi.org/10.3390/app152010989
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