How to extract the angle attack on airfoils in cycloidal motion from a flow field solved with computational fluid dynamics? Development and verification of a robust computational procedure

One of the key problems faced by researchers dealing with Computational Fluid Dynamics simulations and rotating machines is represented by how to extract the angle attack from a numerically computed flow field. If this issue has been addressed successfully for some applications, in case of airfoils moving in cycloidal motion (i.e. having a rotational motion within a rectilinear flow field, like in Darrieus Vertical-Axis Wind Turbines) some proposals do exist, but always affected by some arbitrary choices on the velocity probing that are not supported by a proper verification. The aim of the present study is to try finding a robust computational procedure tailored for the scope. To this end, three different post-processing methods - detailed in the study – were considered and applied to the flow fields of 2-blade H-Darrieus rotor, coming from a high-fidelity unsteady model based on Computational Fluid Dynamics; the resulting blade angle of attack trends over one rotor revolution were then combined with available blade forces data to assess the corresponding lift and drag coefficients. In order to assess the actual accuracy of these approaches for a stable tip-speed ratio, the post-processed force coefficients were compared to the ones computed via a numerical pitching airfoil model, which received the sampled angle of attack trends as input; eventually, the pitched lift and drag values have been used to reconstruct the blade forces over one rotor revolution and compare them with the ones coming from full turbine simulations. Results show large scattering of obtained data, remarking the importance of the proper selection of the angle of attack sampling strategy for the analysis of turbine performance. Overall, the “LineAverage” approach, i.e. the use of multiple sampling points around the airfoil for velocity probing, has proved to be the most accurate method.