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

Journal of Psychology and Neuroscience 2025 1 citation ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Yulin Sun, Leon Mishnaevsky, Katharina Koschek, Florian Sayer

Summary

Researchers developed a multiphysics finite element model to evaluate a self-healing polyurethane-urea coating for wind turbine blades, showing the coating can autonomously repair erosion damage by coupling temperature, moisture, and mechanical stress responses under real environmental conditions.

Polymers
Body Systems

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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