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An immersed boundary-based large-eddy simulation approach to predict the performance of vertical axis tidal turbines

Ouro, Pablo and Stoesser, Thorsten 2017. An immersed boundary-based large-eddy simulation approach to predict the performance of vertical axis tidal turbines. Computers & Fluids 152 , pp. 74-87. 10.1016/j.compfluid.2017.04.003

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Abstract

Vertical axis tidal turbines (VATTs) are perceived to be an attractive alternative to their horizontal axis counterparts in tidal streams due to their omni-directionality. The accurate prediction of VATTs demands a turbulence simulation approach that is able to predict accurately flow separation and vortex shed- ding and a numerical method that can cope with moving boundaries. Thus, in this study an immersed boundary-based large-eddy simulation (LES-IB) method is refined to allow accurate simulation of the blade vortex interaction of VATTs. The method is first introduced and validated for a VATT subjected to laminar flow. Comparisons with highly-accurate body-fitted numerical models results demonstrate the method’s ability of reproducing accurately the performance and fluid mechanics of the chosen VATT. Then, the simulation of a VATT under turbulent flow is performed and comparisons with data from exper- iments and results from RANS-based models demonstrate the accuracy of the method. The vortex-blade interaction is visualised for various tip speed ratios and together with velocity spectra detailed insights into the fluid mechanics of VATTs are provided.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Advanced Research Computing @ Cardiff (ARCCA)
Engineering
Water Research Institute (WATER)
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TC Hydraulic engineering. Ocean engineering
Uncontrolled Keywords: Vertical axis turbines; Immersed boundary method; Large-eddy simulation; Direct forcing; Tidal turbines; Vortex-blade interaction
Publisher: Elsevier
ISSN: 0045-7930
Funders: EPSRC
Date of First Compliant Deposit: 29 June 2017
Date of Acceptance: 6 April 2017
Last Modified: 28 Jun 2019 14:32
URI: http://orca.cf.ac.uk/id/eprint/100022

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