| description abstract | The actuator line method (ALM), combining a lumped-parameter representation of the rotating blades with the computational fluid dynamics (CFD) resolution of the turbine flow field, stands out among the modern simulation methods for wind turbines as probably the most interesting compromise between accuracy and computational cost. Being however a method relying on tabulated coefficients for modeling the blade-flow interaction, the correct implementation of the submodels to account for higher-order aerodynamic effects is pivotal. Inter alia, the introduction of a dynamic stall model is extremely challenging: first, it is important to extrapolate a correct value of the angle of attack (AoA) from the solved flow field; second, the AoA history needed to calculate the rate of dynamic variation of the angle itself is characterized by a low signal-to-noise ratio, leading to severe numerical oscillations of the solution. The study introduces a robust procedure to improve the quality of the AoA signal extracted from an ALM simulation. It combines a novel method for sampling the inflow velocity from the numerical flow field with a low-pass filtering of the corresponding AoA signal based on cubic spline smoothing (CSS). Such procedure has been implemented in the actuator line module developed by the authors for the commercial ansysfluent solver. To verify the reliability of the methodology, two-dimensional (2D) unsteady Reynolds-averaged Navier–Stokes (URANS) simulations of a test two-blade Darrieus H-rotor, for which high-fidelity experimental and numerical blade loading data were available, have been performed for a selected unstable operation point. | |
