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Peer-reviewed veterinary case report

A comprehensive approach to mechanical performance prediction of wind turbines considering key design factors via dimensional analysis and angular momentum conservation.

Year:
2025
Authors:
Eain W & Leephakpreeda T.
Affiliation:
School of Manufacturing Systems and Mechanical Engineering

Abstract

Several critical variables in experimental design- such as type, size, material, and wind speed- influence the mechanical characteristics and performance of wind turbines. The novel contribution of this study is the derivation of quantitative relationships between mechanical performance and efficiency, in relation to these design factors, through the application of both dimensional analysis and angular momentum conservation. As a result, performance predictions for various wind turbine design factors can be made without the need for CFD analysis or wind tunnel tests. This finding enables a systematic justification of optimal wind turbine design. The validation and effectiveness of the proposed methodology are confirmed through CFD analysis of a Savonius wind turbine and experimental testing of a hybrid Savonius-Darrieus wind turbine in a wind tunnel. The predictions of mechanical characteristics and power coefficient in the wind tunnel test demonstrate strong agreement with experimental data, as indicated by 95% confidence intervals with low mean absolute errors of 0.0040 Nm and 0.0014 and narrow margins of error of ± 0.0023 Nm and ± 0.0005, respectively.

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Original publication: https://europepmc.org/article/MED/41272094