A new scientific paper has been published by AIRE’s partner DTU. The objective of this paper is to demonstrate the impact of the variable characteristics of raindrops on the development of rain erosion damage.
The basics
Blade erosion is a challenge to the durability and performance of wind turbines. Modelling of rain erosion damage whilst considering atmospheric conditions improves our understanding of the progression of leading-edge erosion on wind turbine blades.
Why is that a Problem?
Wind turbines are designed to operate for decades. However, continuous exposure to varying environmental conditions can accelerate the fatigue process, leading to premature failures. This not only results in high maintenance and repair costs but also affects the reliability of energy supply. Identifying and mitigating the effects of fatigue is crucial to ensure the sustainability and economic viability of wind energy.
Paper details
This paper, published in the Journal of Physics, aims to analyse the mechanisms of fatigue in the materials used in wind turbines and propose methods to improve post processing of disdrometer data. The methodological approach includes measurements, data analysis and computational simulations to evaluate the behaviour of materials under different rain conditions.
Process
By analysing 2.5 years of data from a disdrometer at the Risø campus, which measures the size and velocity of falling rain droplets, four post-processing methods were used to estimate representative droplet diameters and fall velocities for each rain event. Measured droplet fall velocities are compared with theoretical terminal velocities, revealing a necessity for revising theoretical approaches to raindrop fall velocity for erosion damage modelling.
Main results

Figure 1. Droplet fall velocity versus droplet diameter.
As shown in the graph, larger drops generally have a higher fall velocity. However, the actual measured droplets fall slower and have a wider range of speeds compared to the theoretical speeds predicted by the Best theoretical droplet size distribution. When estimating droplet sizes, the median diameter estimates (orange dots) fit better within the size categories defined by the disdrometer. The arithmetic mean (green dots) provided the smallest diameters and the mass-weighted mean (blue dots) the biggest diameters.
Using these estimates for damage prediction, the median volume method showed the lowest bias at -2% compared to the bin-wise summation. The other three approaches result in higher deviations, with the arithmetic mean method and the theoretical median derived from Best’s approach resulting in the largest bias at ~20% positive and negative respectively.
Theoretical and measured fall velocities of the droplets were compared, revealing discrepancies that underscore the need for an updated theoretical approach to raindrop fall velocity, especially for sites equipped solely with rain gauges. Therefore, the study has highlighted the significant impact of different liquid water content estimation methods on erosion damage predictions. The findings reveal that, for a given amount of rainfall, smaller droplets induce more damage than larger droplets. This counterintuitive observation is particularly relevant for modern wind turbines operating at rated wind speeds, where the blade tip velocity, rather than the droplet fall velocity, governs the damage prediction.
For the full publication go to: Journal of Physics: Conference Series.
Author: Oria Pardo
Editor: Lucia Salinas
January, 2025