Self-Repairing Polyurethane–Urea Coating for Wind Turbine Blades: Modeling and Analysis

This study investigates a UDETA-modified polyurethane–urea (PUU) self-healing coating for wind turbine blades, focusing on its ability to autonomously repair surface erosion damage under realistic environmental conditions. A multiphysics finite element model was developed to couple temperature, moisture, and stress effects on crack healing, and a Gaussian process regression (GPR) model was trained on 35 experimental data points to predict the mobile fraction and healing thresholds with high accuracy (R2 = 0.79, MAE = 0.059). The diffusion coefficient of water in the PUU matrix was determined as 11.03 × 10−7 mm2/s, and stress-driven moisture accumulation at crack tips was shown to accelerate crack healing. Erichsen cupping test simulations were conducted to reproduce experimental crack patterns, demonstrating brittle behavior in dehydrated coatings with a Young’s modulus of 50 MPa and critical principal strains of 0.48. An exponential healing function was incorporated into the computational model and validated against experiments, predicting significant crack healing within 24 h of humidity exposure. These findings provide quantitative design criteria for self-healing coatings, enabling the selection of UDETA content, thickness, and curing strategies to extend wind turbine blade service life while reducing maintenance costs.

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Publication Details

Journal
Coatings
Published
2025-09-10
DOI
https://doi.org/10.3390/coatings15091059
Citations
1
Primary Topic
Polymer composites and self-healing
Type
article
Field-Weighted Citation Impact
0.61

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article

Self-Repairing Polyurethane–Urea Coating for Wind Turbine Blades: Modeling and Analysis

Florian Sayer, Katharina Koschek, Leon Mishnaevsky, Yulin Sun
1 citations
Coatings
Polymer composites and self-healing
0.61
article

Self-Repairing Polyurethane–Urea Coating for Wind Turbine Blades: Modeling and Analysis

Florian Sayer, Katharina Koschek, Leon Mishnaevsky, Yulin Sun
article en
1 citations

Abstract

This study investigates a UDETA-modified polyurethane–urea (PUU) self-healing coating for wind turbine blades, focusing on its ability to autonomously repair surface erosion damage under realistic environmental conditions. A multiphysics finite element model was developed to couple temperature, moisture, and stress effects on crack healing, and a Gaussian process regression (GPR) model was trained on 35 experimental data points to predict the mobile fraction and healing thresholds with high accuracy (R2 = 0.79, MAE = 0.059). The diffusion coefficient of water in the PUU matrix was determined as 11.03 × 10−7 mm2/s, and stress-driven moisture accumulation at crack tips was shown to accelerate crack healing. Erichsen cupping test simulations were conducted to reproduce experimental crack patterns, demonstrating brittle behavior in dehydrated coatings with a Young’s modulus of 50 MPa and critical principal strains of 0.48. An exponential healing function was incorporated into the computational model and validated against experiments, predicting significant crack healing within 24 h of humidity exposure. These findings provide quantitative design criteria for self-healing coatings, enabling the selection of UDETA content, thickness, and curing strategies to extend wind turbine blade service life while reducing maintenance costs.

CoatingsVol. 15(9)
Fraunhofer Institute for Manufacturing Technology and Advanced Materials (DE), Technical University of Denmark (DK)
European Commission
Openalex Percentile: Top 31%
Polymer composites and self-healing
0.61
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