Towards turbine blade production with zero waste
TURBO public presentation
A short public overview presentation has been prepared by the consortium to provide an introduction …
Deadline date for 43rd Risø Symposium!
TURBO Coordinator DTU will host the 43rd Risø International Symposium on Materials Science: Composit…
TURBO joins 4ZDM Cluster
TURBO has joined the 4ZDM Cluster! The 4ZDM cluster is composed of completed and running projects at…
TURBO at WTB Manufacture in Dusseldorf
TURBO had a booth at the Wind Turbine Blade Manufacture exhibition in Duesseldorf (13-15 Dec-2022) a…
TURBO visit to Siemens Gamesa Aalborg factory
On 22-23 Nov-2022 the TURBO team visited the huge Siemens Gamesa Renewable Energy wind turbine blade…
Wind turbines are already part of everyday European life and are an essential element of the strategy to meet the Green Deal targets. Wind turbine blade (WTB) size is steadily increasing with the largest new offshore blades >100 m in length. Composite blades are manufactured using resin infusion and coating processes. Even using modern manufacturing methods, these are subject to defects which result in re-work, scrap and repair.
TURBO will reduce defect formation through better process simulation, monitoring and control, improve defect identification with new methods of non-destructive testing (NDT) and introduce novel repair strategies in composites and coatings.
- Simulation: The project will develop simulations of the production process to minimise defect formation by combining the latest multi-physics process modelling with reduced order models to improve understanding of the composite manufacturing process.
- NDT: TURBO will investigate both in-line NDT to monitor WTB composite infusion and post-manufacture sub-surface WTB coating inspection, combining ultrasound and mid-infrared optical coherence tomography.
- Process control: The production equipment, monitoring sensor and in-line NDT data will be combined to establish a digital twin for real-time analysis and production control including the application of machine learning.
The project will demonstrate its results in the fabrication of full size WTB sections at the Siemens Gamesa Renewable Energy factory in Aalborg, Denmark. The workplan also includes full lifecycle analysis, environmental assessments and production efficiency analysis to quantify the project benefits.
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