Droplet impact on solid surfaces and material damage: applications to wind turbines
File(s)
Author(s)
Hao, Hao
Type
Thesis
Abstract
The thesis investigates droplet impact erosion, with a focus on rain-induced damage on the leading edges of wind turbine blades. Two distinct scales are addressed: (1) the micro-scale, involving single-droplet impacts and fluid-structure interactions; and (2) the macro-scale, focusing on in-field erosion assessment and material lifetime prediction.
At the micro-scale, an analytical framework based on potential flow theory was developed to describe the impact loadings as functions of time and space on a solid surface. These analytical solutions, presented in explicit closed form, were validated against both literature data and a numerical finite-volume (FV) simulation developed in this study. The derived loadings were coupled with a finite-element (FE) model to evaluate material response, forming a novel fluid-structure interaction (FSI) framework. This approach eliminates the need to numerically simulate the liquid phase, reducing computational cost to just 2.8%of that required by conventional methods while maintaining high accuracy. Additionally, a compressible multiphase flow model was used to investigate cavitation within impacting droplets. Homogenous and heterogeneous cavitation phenomena were predicted at impact velocities as low as 50 m/s. The resulting cavity collapse loadings were comparable to initial water-hammer (WH) peaks, implying a potentially halved material fatigue life.
At the macro-scale, a new lifetime prediction model, BEETool, was developed for leading-edge erosion (LEE) assessment in wind turbines. Unlike conventional approaches—such as the Springer fatigue model or those based on Rain Erosion Tester (RET) data—BEETool can be applied directly to erosion inspection data without requiring prior knowledge of material properties or laboratory testing. This makes it particularly useful for ageing turbines or those with repaired coatings.
Overall, this work advances understanding of droplet impact physics and associated material degradation, while translating these insights into a practical computational tool for wind turbine blade lifetime assessment.
At the micro-scale, an analytical framework based on potential flow theory was developed to describe the impact loadings as functions of time and space on a solid surface. These analytical solutions, presented in explicit closed form, were validated against both literature data and a numerical finite-volume (FV) simulation developed in this study. The derived loadings were coupled with a finite-element (FE) model to evaluate material response, forming a novel fluid-structure interaction (FSI) framework. This approach eliminates the need to numerically simulate the liquid phase, reducing computational cost to just 2.8%of that required by conventional methods while maintaining high accuracy. Additionally, a compressible multiphase flow model was used to investigate cavitation within impacting droplets. Homogenous and heterogeneous cavitation phenomena were predicted at impact velocities as low as 50 m/s. The resulting cavity collapse loadings were comparable to initial water-hammer (WH) peaks, implying a potentially halved material fatigue life.
At the macro-scale, a new lifetime prediction model, BEETool, was developed for leading-edge erosion (LEE) assessment in wind turbines. Unlike conventional approaches—such as the Springer fatigue model or those based on Rain Erosion Tester (RET) data—BEETool can be applied directly to erosion inspection data without requiring prior knowledge of material properties or laboratory testing. This makes it particularly useful for ageing turbines or those with repaired coatings.
Overall, this work advances understanding of droplet impact physics and associated material degradation, while translating these insights into a practical computational tool for wind turbine blade lifetime assessment.
Version
Open Access
Date Issued
2026-03-11
Date Awarded
2026-05-01
Copyright Statement
Attribution-NonCommercial 4.0 International Licence (CC BY-NC)
License URL
Advisor
Hardalupas, Yannis
Taylor, Alex
Charalambides, Maria
Sergis, Antonis
Sponsor
Imperial College London
Publisher Department
Department of Mechanical Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)