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Numerical study of the effect of tip-speed ratio on hydrokinetic turbine wake recovery

El Fajri, Oumnia, Bowman, Joshua, Bhushan, Shanti, Thompson, David and O'Doherty, Tim 2022. Numerical study of the effect of tip-speed ratio on hydrokinetic turbine wake recovery. Renewable Energy 182 , pp. 725-750. 10.1016/j.renene.2021.10.030

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Abstract

The predictive capabilities of blade-resolved unsteady Reynolds averaged Navier-Stokes (URANS) and detached eddy simulation (DES), the most commonly used hybrid RANS/large eddy simulation (LES) model, are assessed for hydrokinetic turbine performance and mean and turbulent flows in the intermediate-wake region, and results for a range of tip-speed ratio encompassing design and off-design conditions are analyzed to understand the wake recovery mechanism. The performance predictions compared within 5% of the experimental data. Both URANS and DES models performed reasonably well for the near wake predictions, where the errors were <15%. DES outperformed URANS for both mean wake deficit and turbulence predictions in the intermediate-wake region and both quantities compared within 10% of the experiments. The improved prediction by DES is because of its ability to predict the tip vortex breakdown, which plays a critical role in the wake recovery, especially for higher tip speed ratios (λ). However, DES significantly underpredicted the turbulence predictions in the near-wake region, which could be partly due to the negligence of free-surface effects and partly due to modeling issues, namely modeled stress depletion. The study reveals that the tip vortex breakdown mechanism depends on λ. For lower values of λ, instabilities generated in the root vortex core are identified to be the cause of breakdown. For higher values, the breakdown occurred because of the instabilities generated during the vortex filament entanglement. Future work should focus on investigation of other hybrid RANS/LES models to address the limitations of the DES models, and extension of the study to include free-surface effects.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 0960-1481
Date of Acceptance: 8 October 2021
Last Modified: 29 Nov 2021 17:00
URI: https://orca.cardiff.ac.uk/id/eprint/145668

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