At ESI and DTU Construct, numerical simulation combined with sensor data will be used to minimise defect formation both by defining the manufacturing processes itself, as well as understanding how the process should be modified in real-time in response to in situ monitoring data.
Synthesites will develop a complete system to monitor online the location of the resin during infusion, estimate resin viscosity as well as the developing glass transition temperature and the degree of cure without interfering with the manufacturing process or deteriorating the part quality. CPI will develop embedded wireless resin arrival and temperature sensors fabricated on flexible substrate which will be placed within the whole blade structure during fabrication, sending live sensor data out of the mould.
Smartia and NCC have worked on several lab-scale projects to investigate composite production using digital twins. TURBO will extend the reach of such work by scaling up to the first ever whole blade section infusion process based on a digital twin, representing a technological leap in both complexity and size.
Improved wind turbine blade manufacturing
Hübers will work closely with Siemens Gamesa Renewable Energy to integrate all the TURBO advances into infusion and control systems which will be used to make large wind turbine blades. This will include all the items described above: better processes through simulation, improved monitoring of the infusion process and in-line control by machine learning-based analysis of the digital twin.
Non-destructive testing (NDT) of blade coatings
Norblis, DTU Electro and NCC will build the world-first industrial-scale combined ultrasound and mid-IR optical coherence tomography (OCT) scanner, which will be used to inspect wind turbine blade coatings.
This approach exploits the deep penetration of ultrasound together with the new technology of mid-IR OCT which can provide high resolution images of the critical upper layers. OCT at longer mid-IR wavelengths (e.g. 4 µm) can penetrate deeper than traditional near-IR OCT systems (typically 1.3 µm) due reduced scattering.
UPV will develop machine learning based algorithms which will analyse the OCT images to automatically identify and classify anomalies as part of the defect reduction strategy.
As an important part of TURBO, Arditec will lead a detailed sustainability assessment and develop circular pathways for production waste. Very few studies have considered the waste associated with the wind turbine blade manufacturing process and how it can be reduced and optimised. The lifecycle assessments carried out in TURBO will evaluate its impacts, identify hotspots for potential optimisation and provide fully quantified cradle-to-gate comparisons with current blade manufacturing processes from environmental and socio-economic perspectives.
A large section of a >80 m blade will be used to demonstrate the TURBO advances. This will allow analysis of large blade aspects which would not be possible with trials on a smaller scale blade. This demonstration will serve to assess how the data flows, algorithms, NDT and control loops can be integrated into a real production line and ascertain the quantified benefits in terms of improved quality and reduced scrap.