Grey-box models for life-time assessment of composite wind turbine components

Research proposals

Project Description:

Where structures operate in complex dynamic environments (e.g. offshore), current technology is unable to sufficiently quantify or predict their behaviours to provide an accurate estimate of remaining useful life. This project will develop a transformative approach for response prediction and fatigue usage quantification for wind turbine components that takes advantage of the strengths of established knowledge and physics-based models in combination with the flexibility and power of machine learning (the combination of which is termed grey-box modelling). The ability to accurately predict current condition and remaining life of our high value assets is crucial to guarantee safety, maximise use and minimise maintenance costs.

Methodology

The project will develop grey-box models that can characterise and predict the dynamic behaviour of composite wind turbine components, taking into account monitoring data and any known structural behaviour. The researcher will use sophisticated machine learning technology in combination with structural dynamics analyses adapted for use on composite materials. The researcher will draw on facilities at the Laboratory for Verification and Validation (see lvv.ac.uk) and the Composites Centre at the Advanced Manufacturing Research Centre.

 

For an informal discussion, call +44 (0) 1482 463331
or contact auracdt@hull.ac.uk