The actual strategy in offshore wind energy development is oriented to the progressive increase of the turbine diameter as well as the per unit power. Among many pioneering technological and aerodynamic issues linked to this design trend, the wind velocity at the blade tip region reaches very high values in normal operating conditions (typically between 90 to 110 m/s). In this range of velocity, the rain erosion phenomenon can have a relevant effect on the overall turbine performance in terms of power and energy production (up to 20% loss in case of deeply eroded leading edge). Therefore, as a customary approach erosion related issues are accounted for in the scheduling of the wind turbine maintenance. When offshore, on the other hand, the criticalities inherent to the cost of maintenance and operation monitoring suggest the rain erosion concerns to be tackled at the turbine design stage. In so doing, the use of computational tools to study the erosion phenomenon of wind turbines under severe meteorological conditions could define the base-line approach in the wind turbine blades design and verification.

In this work, the authors present a report on numerical prediction of erosion on a 6 MW HAWT (horizontal axis wind turbine). Two different blade geometries of different aerodynamic loading, have been studied in a view to explore their sensitivity to rain erosion.

The fully 3D simulations are carried out using an Euler-Lagrangian approach. Flow field simulations are carried out with the open-source code OpenFOAM, based on a finite volume approach, using Multiple Reference Frame methodology. Reynolds Averaged Navier-Stokes equations for incompressible steady flow were solved with a k-ε turbulence.

An in-house code (P-Track) is used to compute the rain drops transport and dispersion, adopting the Particle Cloud Tracking approach (PCT), already validated on large industrial turbomachinery.

At the impact on blade, erosion is modelled accounting for the main quantities affecting the phenomenon, which are impact velocity and material properties of the target surface.

Results provide the regions of the two blades more sensitive to erosion, and the effect of the blade geometry on erosion attitude.

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