4.5 Article

Numerical simulation of a vertical axis wind turbine airfoil experiencing dynamic stall at high Reynolds numbers

Journal

COMPUTERS & FLUIDS
Volume 149, Issue -, Pages 12-30

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compfluid.2017.02.021

Keywords

Vertical axis wind turbine; Dynamic stall; Reynolds number; CED; Thick airfoil; Darrieus motion

Funding

  1. Cork Institute of Technology Risam PhD Scholarship Program
  2. SFI/HEA Irish Centre for High-End Computing [cieng003c]

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Multi-megawatt floating vertical axis wind turbines (VAWTs) are a promising solution to exploit offshore wind energy resources in deep water sites. At this large-scale, the VAWT's blades will operate at high Reynolds numbers and encounter dynamic stall at low tip-speed ratios. In particular, the selection of an accurate turbulence modeling approach is still a challenging undertaking in the prediction of transient blade forces during this complex unsteady event. In the present paper, the performance of Unsteady Reynolds-Averaged Navier-Stokes (U-RANS) and Detached Eddy Simulation (DES) modeling methods are compared in simulating the aerodynamics of an isolated NACA0018 airfoil experiencing Darrieus pitching motion. The U-RANS turbulence models employed were the Spalart-Allmaras (S-A) model and the k - omega SST model. Investigations were conducted to ensure satisfactory independency of the solution for both spatial and temporal discretisations, respectively. A quantitative assessment identified the S-A model as the most applicable for a VAWT design study as it showed the most desirable compromise between model fidelity and computational requirement. A qualitative analysis revealed that the thick VAWT airfoil creates a dynamic stall vortex topology highly concentrated at the trailing edge region. Finally, increasing the Reynolds number showed to be beneficial to the airfoil's aerodynamic performance as a higher maximum tangential coefficient is attained, owing to the delay in flow separation to much higher angles of attack. (C) 2017 Elsevier Ltd. All rights reserved.

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