Organisation profile
Organisation profile
Our ambition is both to reduce the time required for and increase the value of physical testing of wind turbine structural components by using high-performance virtual testing and cutting-edge digital technologies.
The section’s expertise lies in multi-scale progressive failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics, which are utilized for efficient, non-destructive inspection, damage characterization, damage evaluation, and health monitoring of wind turbine structural elements and components.
We develop tools and software to increase both the accuracy and efficiency of structural digital representation as virtual digital twins, providing high-quality value-added services to the industry.
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Collaborations and top research areas from the last five years
Profiles
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AQUADA-UNI: A super-efficient unified cascade multimodal model for thermographic wind turbine blade segmentation and damage detection
Jia, X. & Chen, X., 2026, In: Advanced Engineering Informatics. 71, Part C, 12 p., 104387.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile40 Downloads (Orbit) -
Design and testing of an element test specimen for fatigue delamination crack growth initiating at a ply drop
Miao, X.-Y., Johansen, N.F.-J., Bangaru, A. K., McGugan, M., Erives, R. I. & Sørensen, B. F., 2026, In: Composites Part B: Engineering. 308, 19 p., 112977.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile40 Downloads (Orbit) -
The path to virtual testing for certification of large composite wind turbine blades: Challenges, progress and insights
Schøn, R. K., Branner, A. & Chen, X., 2026, In: Composites Part C: Open Access. 19, 12 p., 100706.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile4 Downloads (Orbit)