A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Coating material loss and surface roughening due to leading edge erosion of wind turbine blades: Probabilistic analysis
This study presents a novel approach for the prediction of random erosion roughness patterns of leading edge protection coatings for wind turbine blades. The predictions can be used for determining the effect on aerodynamic performance and provide decision support for repairs. The model removes coating material fragments from the surface of the blade based on a Weibull failure probability function. Input from rain erosion tests of a coating material are used to fit the parameters of the failure probability function and the predictions are validated with data from available literature. Predictions for the time required to reach full breakthrough of the coating layer are made for tip speeds between 90–120 m/s. For tip speeds larger than 100 m/s, the examined coating is predicted to experience significant damage within a few months after installation. The sequence of rain events with different rain intensities was also found to have a significant effect on the amount of surface damage. Using droplet size distributions based on measurements was predicted to lead to different coating lifetimes than when using Best’s droplet size distribution. Measurements of erosion craters from rain erosion test samples were used to define a size distribution for failed coating fragments. A machine learning approach for automatic parameter fitting based on erosion depth data from tests is also presented.
Coating material loss and surface roughening due to leading edge erosion of wind turbine blades: Probabilistic analysis
This study presents a novel approach for the prediction of random erosion roughness patterns of leading edge protection coatings for wind turbine blades. The predictions can be used for determining the effect on aerodynamic performance and provide decision support for repairs. The model removes coating material fragments from the surface of the blade based on a Weibull failure probability function. Input from rain erosion tests of a coating material are used to fit the parameters of the failure probability function and the predictions are validated with data from available literature. Predictions for the time required to reach full breakthrough of the coating layer are made for tip speeds between 90–120 m/s. For tip speeds larger than 100 m/s, the examined coating is predicted to experience significant damage within a few months after installation. The sequence of rain events with different rain intensities was also found to have a significant effect on the amount of surface damage. Using droplet size distributions based on measurements was predicted to lead to different coating lifetimes than when using Best’s droplet size distribution. Measurements of erosion craters from rain erosion test samples were used to define a size distribution for failed coating fragments. A machine learning approach for automatic parameter fitting based on erosion depth data from tests is also presented.
Coating material loss and surface roughening due to leading edge erosion of wind turbine blades: Probabilistic analysis
Tempelis, Antonios (author) / Mishnaevsky, Leon (author)
2025-01-01
Tempelis , A & Mishnaevsky , L 2025 , ' Coating material loss and surface roughening due to leading edge erosion of wind turbine blades: Probabilistic analysis ' , Wear , vol. 566-567 , 205755 . https://doi.org/10.1016/j.wear.2025.205755
Article (Journal)
Electronic Resource
English
Wind energy , Erosion , Coatings , Surface damage , Wear
HVOF coating and surface treatment for enhancing droplet erosion resistance of steam turbine blades
| British Library Online Contents | 2003