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14 april 2019 13:04:15

 
Energies, Vol. 12, Pages 1434: Combined Effect of Rotational Augmentation and Dynamic Stall on a Horizontal Axis Wind Turbine (Energies)
 


Rotational augmentation and dynamic stall have been extensively investigated on horizontal axis wind turbines (HAWTs), but usually as separate topics. Although these two aerodynamic phenomena mainly determine the unsteady loads and rotor performance, the combined effect of rotational augmentation and dynamic stall is still poorly understood and is challenging to model. We perform a comprehensive comparative analysis between the two-dimensional (2D) airfoil flow and three-dimensional (3D) blade flow to provide a deep understanding of the combined effect under yawed inflow conditions. The associated 2D aerodynamic characteristics are examined by the unsteady Reynolds-averaged Navier-Stokes Simulations, and are compared with the experimental data of NREL Phase VI rotor in three aspects: aerodynamic hysteresis, flow field development, and dynamic stall regimes. We find that the combined effect can dramatically reduce the sectional lift and drag hysteresis by almost 60% and 80% from the supposed definitions of hysteresis intensity, and further delay the onset of stall compared with either of rotational augmentation and dynamic stall. The flow field development analysis indicates that the 3D separated flow is greatly suppressed in the manner of changing the massive trailing-edge separation into the moderate leading-edge separation. Furthermore, the 3D dynamic stall regime indicates a different stall type and an opposite trend of the separated zone development, compared with the 2D dynamic stall regime. These findings suggest that the modelling of 3D unsteady aerodynamics should be based on the deep understanding of 3D unsteady blade flow rather than correcting the existing 2D dynamic stall models. This work is helpful to develop analytical models for unsteady load predictions of HAWTs.


 
109 viewsCategory: Biophysics, Biotechnology, Physics
 
Energies, Vol. 12, Pages 1435: Fractional Order Fuzzy PID Control of Automotive PEM Fuel Cell Air Feed System Using Neural Network Optimization Algorithm (Energies)
Energies, Vol. 12, Pages 1433: Analysis of Different Neural Networks and a New Architecture for Short-Term Load Forecasting (Energies)
 
 
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