An experimental approach into the degradation of wind turbine blade coating systems due to rain and weathering

  • Grant Leishman

Student thesis: Doctoral Thesis

Abstract

Leading edge erosion of wind turbine blades is an issue which is increasing in prevalence due to the ever-growing installed capacity of wind turbines globally. Leading edge erosion causes a reduction in the aerodynamic efficiency of a wind turbine blade, in turn reducing the turbine’s energy yield and therefore also the annual energy production. Furthermore, leading edge erosion can lead to structural degradation, resulting in premature failure of the blade.This thesis looks to define a quantitative experimental methodology to assess and characterise erosion on wind turbine blades. Furthermore, this thesis goes on to include weathering as a factor in wind turbine blade coating system assessment. Accelerated test were used to mimic the effects of years of in-situ rain erosion and weathering on test specimens. A suite of analytical laboratory tools was used to measure the effects of rain erosion and weathering, both individually and as a combined study on, industrially relevant and operationally used, wind turbine blade coating systems.It was found that coating systems from different manufacturers were unique in their response and degradation behaviour. A novel methodology, using surface gloss, was used to quantify erosion and then categorise the specimen into one of the developed erosion stages. Additionally, this approach provides a greater accuracy in erosion quantification than the current method of mass loss measurement and the gloss methodology can be used in situ, whereas mass loss cannot. Another key finding from this thesis is that weathering has a measurable effect on erosion, increasing mass loss by 1.5% and gloss loss by up to 15% for one of the coating systems tested.
Date of Award2 Jun 2023
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SponsorsEPSRC (Engineering and Physical Sciences Research Council)
SupervisorDavid Nash (Supervisor) & Liu Yang (Supervisor)

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