CFD and ANN surrogate modelling for fixing angle optimisation of a Darrieus vertical axis wind turbine

Amir Tamaddon; Ma Mohin; Yakub Iqbal Mogul; Jaimon Dennis Quadros; Mamadou Ndiaye

doi:10.1080/19942060.2026.2654918

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CFD and ANN surrogate modelling for fixing angle optimisation of a Darrieus vertical axis wind turbine

Journal article

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CFD and ANN surrogate modelling for fixing angle optimisation of a Darrieus vertical axis wind turbine

Amir Tamaddon, Ma Mohin, Yakub Iqbal Mogul, Jaimon Dennis Quadros and Mamadou Ndiaye

Engineering applications of computational fluid mechanics, Vol.20(1), 2654918

01/12/2026

DOI: https://doi.org/10.1080/19942060.2026.2654918

Abstract

Artificial Neural Network

Darrieus Rotor

Fixing Angle

Tip-Speed Ratio

Vertical Axis Wind Turbine

Computational Fluid Dynamics

Global decarbonisation requires efficient and reliable renewable energy systems, with Vertical Axis Wind Turbines [Formula: see text] offering advantages in turbulent and urban environments. This study examines the effect of blade Fixing Angle [Formula: see text] on the aerodynamic performance of a three-bladed Darrieus [Formula: see text] using Unsteady Reynolds-Averaged Navier–Stokes[Formula: see text] based Computational Fluid Dynamics [Formula: see text] simulations coupled with an Artificial Neural Network [Formula: see text] surrogate model.A parametric analysis was carried out for seven [Formula: see text] values across a Tip-Speed Ratio [Formula: see text] range of [Formula: see text]. Results show that a small positive [Formula: see text] (toe-out) improves efficiency by delaying stall onset and extending upwind torque production. The optimum case [Formula: see text] achieved a [Formula: see text] increase in power coefficient [Formula: see text] compared to the baseline [Formula: see text]. In contrast, negative FA reduced performance due to earlier separation and greater downwind losses.The [Formula: see text] surrogate, trained on [Formula: see text] data, effectively captured the nonlinear dependence of [Formula: see text] on [Formula: see text] and [Formula: see text], achieving [Formula: see text] and a Mean Absolute Error [Formula: see text] below [Formula: see text]. Once validated, the [Formula: see text] enabled rapid optimisation of the design space, locating the global optimum with negligible computational cost.Flow-field and force-coefficient analyses further reveal that positive [Formula: see text] modifies the incidence-angle distribution, mitigates torque ripple, and suppresses dynamic stall, thereby explaining the observed performance enhancement. Overall, the integration of [Formula: see text] and [Formula: see text] provides both physical insight and computational efficiency, establishing a solid foundation for future multi-objective optimisation of [Formula: see text] considering parameters such as [Formula: see text], torque ripple, and self-starting capability.

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Published (Version of record) Open Access Open CC BY V4.0 — You are free to: Share — copy and redistribute the material in any medium or format for any purpose, even commercially. Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

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Title: CFD and ANN surrogate modelling for fixing angle optimisation of a Darrieus vertical axis wind turbine
Creators - without role: Amir Tamaddon - University of Greater Manchester
Ma Mohin - University of Greater Manchester
Yakub Iqbal Mogul - University of Greater Manchester, National Centre for Motorsport Engineering
Jaimon Dennis Quadros - University of Greater Manchester, National Centre for Motorsport Engineering
Mamadou Ndiaye - University of Greater Manchester, Mechanical Engineering
Publication Details: Engineering applications of computational fluid mechanics, Vol.20(1), 2654918
Publisher: Taylor & Francis Group
Grants: JA25/008, University of Greater Manchester (United Kingdom, Bolton)
Data Availability Statement (DAS): The datasets generated and/or analysed during this study (CFD simulation results and ANN surrogate model training data) are not publicly available due to their large size but are available from the corresponding author upon request.
Identifiers: 9972726808841; 1994-2060; 1997-003X; 1997-003X
Copyright: © 2026 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use,distribution, and reproduction in any medium, provided the original work is properly cited.
Academic Unit: National Centre for Motorsport Engineering; Mechanical Engineering
Language: English
Resource Type: Journal article
Electronic publication date: 13/04/2026
Date accepted: 28/02/2026

CFD and ANN surrogate modelling for fixing angle optimisation of a Darrieus vertical axis wind turbine

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