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Fluctuating loads on a tidal turbine due to velocity shear and turbulence: comparison of CFD with field data

Lookup NU author(s): Dr Umair AhmedORCiD



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Fluctuating loads on tidal turbines are important for fatigue analysis and there is limited information or simulation available for full-scale conditions. Here, CFD simulations have been performed for a geometry-resolved full-scale tidal-stream turbine and compared with experimental data from a 1 MW machine deployed at the EMEC test site. Initially, Reynolds-averaged Navier-Stokes (RANS) and large- eddy simulations (LES) were performed using an inflow mean velocity profile representative of the site but low inflow turbulence. Mean blade pressures were similar for the two types of turbulence closure and yielded mean power coefficients comparable with measurements. Then, to simulate the effect of turbulence on loads, LES with synthetic turbulence prescribed at inlet was employed. For these simulations, inflow profiles of mean velocity, Reynolds stresses and length scales were determined from a precursor channel-flow simulation, with additional factoring of stresses and length scales to match hub-height conditions measured on site. Fluctuations in thrust, power and blade bending moment arise cyclically from onset mean velocity shear and the blocking effect of the support tower and over continuous spectral ranges from blade-generated turbulence, approach-flow turbulence and waves. LES simulations with realistic inflow turbulence satisfactorily reproduced the relative spectral distribution of blade bending moments in low-wave conditions.

Publication metadata

Author(s): Ahmed U, Apsley D, Afgan I, Stallard T, Stansby P

Publication type: Article

Publication status: Published

Journal: Renewable Energy

Year: 2017

Volume: 112

Pages: 235-246

Print publication date: 01/11/2017

Online publication date: 16/05/2017

Acceptance date: 14/05/2017

Date deposited: 05/08/2018

ISSN (print): 0960-1481

ISSN (electronic): 0960-1481

Publisher: Elsevier


DOI: 10.1016/j.renene.2017.05.048


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