Thesis

Raindrop erosion of wind turbine blades in various environments

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Creator
Rights statement
Awarding institution
  • University of Strathclyde
Date of award
  • 2023
Thesis identifier
  • T16624
Person Identifier (Local)
  • 201856442
Qualification Level
Qualification Name
Department, School or Faculty
Abstract
  • Renewable energy is the solution to a greener, more sustainable future and wind energyis a massive contributor, especially in Scotland. One of the limiting factors to windturbines is the leading-edge erosion of the blades. This is a developing and growing issue in large multi mega-watt wind turbines within the wind industry as it affects bladeperformance and thus generating efficiency. The research presented aims to contributeto the scientific community investigating this topic by developing a fuller picture ofthe problem encountered in laboratory testing, analysing data and utilising the resultsin predictive models. This research work builds upon previous investigations into theerosion of wind turbine blades by determining the effect that stress has on the erosionrate and therefore the efficiency of the turbine this is particularly applicable with thenew larger turbine blades. To achieve this objective a custom rain erosion test facilityand stressed sample holder were designed, manufactured and commissioned as partof this research to fully understand the problem. The results demonstrated that theapplied bending stress increases the erosion rate and the trend does not follow the general accepted trends seen within the literature. This research therefore investigates thedevelopment of an alternative erosion-based model centred around the theta projectionmethod which followed the trends observed in the experimental results more closely.Theta projection model and geographical rain data were utilised to develop site specificerosion predictions for the individual blade size and geometry which determines the impact velocity of the droplet and the stress within the material. Future developments areaimed at further expanding the research and providing knowledge to optimise turbineblade maintenance and thus efficiency.
Advisor / supervisor
  • Stack, M. M. (Margaret M.)
Resource Type
DOI
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