CFD Simulation of a 3-Bladed Horizontal Axis Tidal Stream Turbine using RANS and LES

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CFD Simulation of a 3-Bladed Horizontal Axis

Tidal Stream Turbine using RANS and LES

J. McNaughton, I. Afgan, D.D. Apsley, S. Rolfo, T. Stallard and P.K. Stansby

Modelling and Simulation Centre, School of MACE, The University of Manchester

Oxford Tidal Energy Workshop Oxford, UK.

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Overview

1 Introduction

2 Methodology

3 RANS Results

4 RANS and LES comparison

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Introduction

ReDAPT (Reliable Data Acquisition Platform for Tidal): Project designed to accelerate the tidal energy industry. Aim to inspire market confidence in tidal stream turbines (TST).

Deployment of a full scale 1MW turbine at EMEC in the Orkneys.

This work:

UsingCode Saturne to accurately predict loading on tidal turbines.

Assess the influence of turbulence and waves on TSTs. Current results compare Reynolds Averaged Navier Stokes (RANS) model and Large Eddy Simulation (LES) against those for a laboratory scale turbine.

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Introduction

Case overview

CFD modelling of experimental study of Bahaj et al. (2005). 0.4 m radius,R, turbine pulled through a towing tank.

Parametric study of force coefficients against tip-speed-ratio (TSR).

Photo reproduced from Bahaj et al. (2005).

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Methodology

CFD Solver

EDF’s open-source CFD code,Code Saturne (Archambeau

et al., 2004), is used to simulate turbulent flow past a TST. A sliding mesh method is developed inCode Saturne to allow for the TST rotation.

Second order in space (central differencing).

First-order in time with ∆t ≈1.5◦ of rotation per time-step. Thek−ω SST RANS turbulence model is used to simulate the flow.

Results are also compared against an LES that is also been performed as part of this project.

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Methodology

Sliding-mesh method

Start in cell centre,I, with face-centre,F.

I is projected throughF to give a halo point,H.

Search for, J, the nearest cell-centre to the halo-point.

The face-centre value is given a Dirichlet condition with the value:

φF = 1 2(φI+φH), Where: φH =φJ + ∂φ ∂x J (JH). Interface I H J F

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Methodology

Meshing strategy

Geometry built in two parts, inner turbine and outer domain.

Block-structured approach with hanging nodes to control cell-count.

≈2 million cells with 15<y+<200 at the walls. LES mesh is wall refined with≈

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RANS Results

Flow-field

Pressure iso-surfaces coloured by velocity are shown for the instantaneous flow-field for TSR = 6.

Tip effects are clearly visible in the near wake whilst the mast creates main structures further down-stream.

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RANS Results

Flow-field

Instantaneous velocity on centre-plane shows tip-effects and influence of mast on flow.

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RANS Results

Force coefficients

Effect of blades passing the mast is clear from instantaneous force coefficients.

Power Spectral Density (PSD) analysis of theCPshows

peaks at 3 and 6 times the blade rotation frequency (f).

0.739 0.74 0.741 0.742

0.743 Force coefficients over one full rotation for TSR=6

7.68 7.82 7.96 Time (s) 0.404 0.405 0.406 0.407 0.408 CT CP

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RANS Results

Force coefficients

k−ω SST predicts force curve against TSR although under predicted by approximately 10%.

LES shows gain in precision matching experiments within 3% except for the lower values of TSR.

4 5 6 7 8 9 TSR 0.4 0.6 0.8 1 1.2 C_T Bahaj et al 2005 k-ω - Present work k-ω - McSherry et al 2011 LES 4 5 6 7 8 9 TSR 0 0.1 0.2 0.3 0.4 0.5 C_P

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RANS and LES comparison

Flow structures

Iso-Q 0.5 (ΩijΩij−SijSij) surfaces coloured by vorticity are

shown for RANS and LES.

LES maintains the tip vortices and captures structures in the wake better than RANS.

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RANS and LES comparison

Pressure coefficients on the blades

Mean pressure coefficients are shown on the blades at quarter length locations.

Both RANS and LES predict similar behaviour although LES captures larger forces on pressure and suction surfaces.

0 0.2 0.4 0.6 0.8 1 x / c -2 -1 0 1 2 -CP r/R = 0.25 r/R = 0.50 r/R = 0.75 k−ω SST 0 0.2 0.4 0.6 0.8 1 x / c -2 -1 0 1 2 -CP r/R = 0.25 r/R = 0.50 r/R = 0.75 LES

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Conclusions & Further work

Conclusions:

Sliding-mesh method successfully implemented in

Code Saturne to simulate a rotating TST.

Flow features are captured well by RANS and LES.

RANS under predicts the force coefficients whilst LES is far more accurate.

Difference in calculations is near wall modelling and higher order time-scheme used byCode Saturne for LES.

Further work:

Wall refined RANS simulation to compare with experiments. Assess influence of waves on full scale MCT comparing with data from EMEC.

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Acknowledgements

This research was performed as part of the Reliable Data Acquisition Platform for Tidal (ReDAPT) project commissioned and funded by the Energy Technologies Institute (ETI). The authors are highly grateful to EDF for additional funding and access to its High Performance Computing (HPC) facilities.

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References

Archambeau, F., Mechitoua, N., and Sakiz, M. (2004). Code Saturne: a finite volume code for the computation of turbulent incompressible flows-industrial applications.International Journal on Finite Volumes, 1(1):1–62. Bahaj, A. S., Batten, W. M. J., Molland, A. F., and Chaplin, J. R. (2005). Experimental investigation into the

effect of rotor blade sweep on the performance of the Marine Current Turbines.Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 215(5):611–622.

Mcsherry, R., Grimwade, J., Jones, I., Mathias, S., Wells, A., Mateus, A., and House, E. F. (2011). 3D CFD modelling of tidal turbine performance with validation against laboratory experiments.

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Sliding-mesh method

Implementation:Code Saturne Subroutines

Black - Unchanged.

Red- Modified.

Blue- New.

findha - Search for closest cell-centre to halo-point. upcoef - Updates Dirichlet values on interface. caltri inivar usiniv tridim usclim findha navsto preduv codits upcoef resolp upcoef upcoef

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Sliding-mesh method

Implementation: Pressure-Velocity Loop

Code Saturne’s existing pressure-velocity loop is enabled by setting NTERUP>1. Loop used to ensure continuity over the interface.

Modification to include the RANS subroutines. tridim phyvar usclim navsto turb** phyvar P-V Loop

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RANS and LES comparison

Comparison of numerical set-up

RANS (k−ω SST) LES

Time-scheme 1st order 2nd order

Rotation per time-step 1.5◦ 0.05◦

Space discretization Centred Centred

Wall modelling Wall-functions Wall refined