MACHINE LEARNING AIDED PREDICTION OF RAIN EROSION DAMAGE ON WIND TURBINE BLADE SECTIONS

被引:0
|
作者
Castorrini, Alessio [1 ]
Venturini, Paolo [2 ]
Gerboni, Fabrizio [3 ]
Corsini, Alessandro [2 ]
Rispoli, Franco [2 ]
机构
[1] Univ Basilicata, Sch Engn, Potenza, Italy
[2] Sapienza Univ Rome, Dept Mech & Aerosp Engn, Rome, Italy
[3] Sapienza Univ Rome, Rome, Italy
关键词
COMPUTATIONAL ANALYSIS; PERFORMANCE; FRAMEWORK;
D O I
暂无
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Rain erosion of wind turbine blades represents an interesting topic of study due to its non-negligible impact on annual energy production of the wind farms installed in rainy sites. A considerable amount of recent research works has been oriented to this subject, proposing rain erosion modelling, performance losses prediction, structural issues studies, etc. This work aims to present a new method to predict the damage on a wind turbine blade. The method is applied here to study the effect of different rain conditions and blade coating materials, on the damage produced by the rain over a representative section of a reference 5MW turbine blade operating in normal turbulence wind conditions.
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页数:12
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