This work examines the dynamic stall process and resulting wake features of cross-flow turbines under confined configurations using two computational modeling approaches, Reynolds-averaged Navier-Stokes (RANS) and large-eddy simulation (LES). Cross-flow turbines harvest energy from wind or water currents via rotation about an axis perpendicular to the flow and are a complementary technology to the more common axial-flow turbine. During their 360° rotation cross-flow turbine blades experience a cyclical variation in the angle of attack and velocity relative to the oncoming flow, leading to flow separation and reattachment, otherwise known as dynamic stall. The dynamic stall process causes an instantaneous loss in torque generation and unsteady force fluctuations which pose a challenge to accurate predictions of both the performance and the resulting unsteady flow field. This research compares RANS simulations to higher fidelity LES of a straight-bladed two-blade cross-flow turbine at a moderate Reynolds number (Rec = 45,000) in a confined configuration. The RANS model is shown to be very sensitive to confinement at the simulated tip speed ratio as it over-predicts power generation due to suppression of flow separation, while the flow field from LES matches well with the experimental validation. Results are compared with an unconfined configuration for which the RANS model successfully predicts a power curve; however, it displays significant differences in the evolution of flow structures such as premature shedding of the dynamic stall vortex and a lack of vortex diffusion during convection in the wake.
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