Investigation of the Computational Framework of Leading-Edge Erosion for Wind Turbine Blades

Non-contact acoustic detection methods for blades have gained significant attention due to their advantages such as easy installation and immunity to mechanical noise interference. Numerical simulation investigations on the aerodynamic noise mechanism of blade erosion provide a theoretical basis for acoustic detection. However, constructing a three-dimensional erosion model remains a challenge due to the uncertainty in external natural environmental factors. This study investigates a leading-edge erosion calculation model for wind turbine blades subjected to rain erosion. A rain erosion distribution model based on the Weibull distribution of raindrop size is first constructed. Then, the airfoil modification scheme combined with the erosion distribution model is presented to calculate leading-edge erosion mass. Finally, for a sample National Renewable Energy Laboratory 5 MW wind turbine, a three-dimensional erosion model is investigated by analyzing erosion mass related to the parameter of the attack angle. The results indicate that the maximum erosion amount is presented at the pressure surface near the leading edge, and the decrease in erosion on the pressure surface is more rapid than the suction side from the leading edge to the trailing edge. With an increase in the attack angle, the erosion on the pressure side is more severe. Furthermore, a separation vortex appears at the leading edge of the airfoil under computational non-uniform erosion. For aerodynamic noise, a larger sound pressure level with significant fluctuation occurs at 400–1000 Hz.

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Publication Details

Journal
Energies
Published
2025-04-22
DOI
https://doi.org/10.3390/en18092146
Citations
2
Primary Topic
Fluid Dynamics and Turbulent Flows
Type
article
Field-Weighted Citation Impact
2.67

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article

Investigation of the Computational Framework of Leading-Edge Erosion for Wind Turbine Blades

Bin Chen, Hongyu Wang
2 citations
Energies
Fluid Dynamics and Turbulent Flows
2.67
article

Investigation of the Computational Framework of Leading-Edge Erosion for Wind Turbine Blades

Bin Chen, Hongyu Wang
article en
2 citations

Abstract

Non-contact acoustic detection methods for blades have gained significant attention due to their advantages such as easy installation and immunity to mechanical noise interference. Numerical simulation investigations on the aerodynamic noise mechanism of blade erosion provide a theoretical basis for acoustic detection. However, constructing a three-dimensional erosion model remains a challenge due to the uncertainty in external natural environmental factors. This study investigates a leading-edge erosion calculation model for wind turbine blades subjected to rain erosion. A rain erosion distribution model based on the Weibull distribution of raindrop size is first constructed. Then, the airfoil modification scheme combined with the erosion distribution model is presented to calculate leading-edge erosion mass. Finally, for a sample National Renewable Energy Laboratory 5 MW wind turbine, a three-dimensional erosion model is investigated by analyzing erosion mass related to the parameter of the attack angle. The results indicate that the maximum erosion amount is presented at the pressure surface near the leading edge, and the decrease in erosion on the pressure surface is more rapid than the suction side from the leading edge to the trailing edge. With an increase in the attack angle, the erosion on the pressure side is more severe. Furthermore, a separation vortex appears at the leading edge of the airfoil under computational non-uniform erosion. For aerodynamic noise, a larger sound pressure level with significant fluctuation occurs at 400–1000 Hz.

EnergiesVol. 18(9)
Beijing University of Posts and Telecommunications (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 13%
Fluid Dynamics and Turbulent Flows
2.67
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Investigation of the Computational Framework of Leading-Edge Erosion for Wind Turbine Blades — Bin Chen, Hongyu Wang · Energies (2025) | TGRS Research Map | TGRS