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A computational framework for rain erosion prediction in composite wind turbine blades

We present a computational framework for rain erosion prediction in composite wind turbine blades. A stochastic rain texture model is developed to generate three-dimensional fields of raindrops using the rain intensity history at a certain location. The model uses microstructural properties of rain, i.e. the size distribution as well as relationships that relate average volume fraction of raindrops to rain intensity. An in-house GPU-accelerated computational fluid dynamics model of free-surface flow is used to simulate the impact of raindrops and to capture the impact pressure as a function of time and space. An interpolation scheme is proposed to find the impact pressure field for a given drop diameter using high fidelity simulation results for a set of rain drops significantly reducing the computational cost. Pressure fields are then fed into a 3D finite element model of the composite wind turbine blade shell to analyze the transient stresses from raindrop impact. The analysis is complemented with a fatigue stress-life estimation process that uses the Rainflow-counting algorithm and cumulative fatigue damage calculation with the goal of using fatigue life as an indication of the onset of surface coating roughening or the incubation period, after which the wind turbine blade aerodynamic performance deteriorates.

Author(s):

Behrooz Amirzadeh    
University of Massachusetts Dartmouth
United States

Mehdi Raessi    
University of Massachusetts Dartmouth
United States

Mazdak Tootkaboni    
University of Massachusetts Dartmouth
United States