The unsteady flow conditions experienced by wind turbine blades lead to fatigue loads due to gusts, that increase the cost of energy. The decrease of the impact of these unsteady loads will most certainly lead to a decrease of the cost of energy. In order to alleviate unsteady loads the Smart Rotor Blade approach [2] applies spanwise-distributed smart load control devices, which sense the flow and consequently react on the flow. The smart load control devices are applied to avoid the fluctuating unsteady aerodynamic loads. In the context of alleviating these loads, the unsteady behaviour of the flow over a 2D airfoil due to the actuation of a 0.2 c flap is investigated. By building a database of unsteady flow experiments, reference material is created for the validation of computational fluid dynamics models simulating unsteady conditions. Eventually, the knowledge of unsteadiness of the flow acquired can be applied in projects like the Smart Rotor Blade with the purpose to reduce fluctuating blade loads. An airfoil model of the type DU96W180, with a span of 1.8 meter and a chord of 0.5 meter is tested. Using Particle Image Velocimetry (PIV), the flow is visualized as a function of flap position under unsteady conditions. The unsteadiness addressed is expressed in reduced frequency k, simulating a steady case at k =0 and unsteady flows at k =0 .1 and k =0 .2. With the integration technique derived by F. Noca [1], the unsteady forces are calculated on the blade, using velocity fields obtained from PIV measurements around the model. Multiple PIV images are stitched together and interpolated on a general grid in order to obtain a velocity vector field of the flow around the model. Having the velocity vector fields at different time steps within one cycle of the flap motion, allows for the determination of a time dependent set of unsteady forces.
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