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Turbulent wake flows behind helical- and straight-bladed vertical axis wind turbines (VAWTs) in boundary layer turbulence are numerically studied using the large-eddy simulation (LES) method combined with the actuator line model. Based on the LES data, systematic statistical analyses are performed to explore the effects of blade geometry on the characteristics of the turbine wake. The time-averaged velocity fields show that the helical-bladed VAWT generates a mean vertical velocity along the center of the turbine wake, which causes a vertical inclination of the turbine wake and alters the vertical gradient of the mean streamwise velocity. Consequently, the intensities of the turbulent fluctuations and Reynolds shear stresses are also affected by the helical-shaped blades when compared with those in the straight-bladed VAWT case. The LES results also show that reversing the twist direction of the helical-bladed VAWT causes the spatial patterns of the turbulent wake flow statistics to be reversed in the vertical direction. Moreover, the mass and kinetic energy transports in the turbine wakes are directly visualized using the transport tube method, and the comparison between the helical- and straight-bladed VAWT cases show significant differences in the downstream evolution of the transport tubes.
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CFD ANALYSIS OF STALL IN A WELLS TURBINE
The Wells turbine is a self-rectifying device that employs a symmetrical blade profile, and is often used in conjunction with an oscillating water column to extract energy from ocean waves. The effects of solidity, angle of attack, blade shape and many other parameters have been widely studied both numerically and experimentally. To date, several 3-D numerical simulations have been performed using commercial software, mostly with steady flow conditions and employing various two-equation turbulence models. In this paper, the open source code Open- FOAM is used to numerically study the performance characteristics of a Wells turbine using a two-equation turbulence model, namely the Menter SST model, in conjunction with a transient fluid solver.
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- Award ID(s):
- 1659710
- PAR ID:
- 10088712
- Date Published:
- Journal Name:
- ASME 2018 Power Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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