Abstract
Thrust, power and intermediate wake predictions obtained using resolved rotating blade with sliding mesh simulations for a hydrokinetic turbine (HKT) are assessed using the open-source flow solver OpenFOAM. Single- and two-phase URANS and DES computations are performed for three-blade, 0.5m diameter (D) turbine mounted on a stanchion that intersects the free surface with a tip-speed ratio λ = 6.15. The thrust and power predictions compare within 5% of the experimental data. Results show that the thrust predictions are dominated by the pressure distribution on the blades, whereas the shear stress plays a significant role in the power predictions. The turbine performance showed unsteadiness with amplitudes around 3% of the mean, due to the disruption of the flow each time a blade passed in front of the stanchion. The wake recovery is primarily due to the growth of shear layers (originating from the blade tips) towards the turbine axis, which are primarily caused by the cross-plane turbulent velocity. The shear layer growth is enhanced by the turbulence produced by the stanchion. Predictions of the mean wake profile compared within 10% of the experimental data, which is significant improvement over previous Fluent predictions that showed large errors of 22%. The improved predictions in OpenFOAM is attributed to better turbulence predictions. Two-phase results show that the interaction between the wake and free-surface is initiated by the interaction of stanchion with the free-surface. The free-surface creates a blockage effect that accelerates the flow in the upper bypass region and enhances the wake recovery.
Highlights
HYDROELECTRIC power represents a clean and renewable source of energy that accounts for 16% of all electricity generated in the world [1] and is predominately produced by the impoundment of rivers
The results demonstrated that traditional Reynolds Averaged Navier Stokes (RANS) models predict faster wake recovery than experiments and over predict turbulent kinetic energy (TKE)
The results showed a strong interaction between the wake defict region and 1 √kk is plotted in the figure, as it provides a measure of the turbulent velocity
Summary
HYDROELECTRIC power represents a clean and renewable source of energy that accounts for 16% of all electricity generated in the world [1] and is predominately produced by the impoundment of rivers. Hydrokinetic power, produced by naturally flowing water without impoundment such as river currents, ocean currents, and tidal streams, represents a largely untapped renewable energy source. Computational fluid dynamics (CFD) has the ability to assist in design of hydrokinetic turbine farms through assessment of device performance under complex flow conditions [3]. On power production and loading on turbines; and prediction of turbine wake recovery for a single turbine [8] or those in an array [9,10] to estimate appropriate array design [11].
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