About this project
The UK is committed to the use of offshore wind energy to reach net-zero carbon emissions by 2050. The EPSRC-NERC Centre for Doctoral Training (CDT) in Offshore Wind Energy and the Environment will enable delivery of this target by developing environmental and engineering solutions to key offshore wind sector challenges; thereby supporting a sustainable energy supply. In partnership with Siemens Gamesa Renewable Energy (SGRE), a 4-year taught and research industry-sponsored Aura CDT PhD is offered. The PhD directly addresses sector needs to understand the application of digital twins to predict real world performance of turbine blades.
Wind turbine blades are some of the largest composite structures currently manufactured and they are becoming larger and more sophisticated. Blades are manufactured from composites with glass/carbon reinforcement and epoxy resin matrix. The ultimate performance of each wind turbine blade is determined by a number of variables associated with its different manufacturing steps. A digital twin is an integrated multiphysics, multiscale probabilistic simulation of an as-built component or system that uses the best available physical models and data of a system, together with its history, to mirror the state of its corresponding real-world twin at any given point in time.
In this project, a digital twin will provide a very powerful tool to analyse and control the manufacturing process of complex components such as wind turbine blades. The manufacturing digital twin will have tremendous value in modelling different scenarios to optimise production parameters of the turbine blades to increase productivity and reduce the potential for defects and resultant rework. In the longer term, robust ‘as-built’ digital twins may also provide an improved basis for lifetime management of the blades.
Working with SGRE, the largest manufacturer of offshore wind turbines, we will investigate the end-to-end production process for a wind turbine blade from materials receipt to finished blade dispatch; identifying, capturing and analysing all relevant production parameters that may impact blade quality and cause defects. The work is supported by SGRE and will involve close collaboration with SGRE colleagues in the UK and Denmark.
The project aims are
- Identifying all of the relevant parameters affecting the blade manufacturing process, e.g:
Materials batch number, storage duration
Dates, times and durations of process steps
Factory/local ambient conditions (temperature, humidity, etc)
Personnel involved in process steps
Detailed process parameters for individual steps
- Exploring how to digitalise the data collection infrastructure in a mostly analogue manufacturing process
- Creating a digital twin ecosystem and structured database for collecting process parameters
- Developing techniques to analyse data to establish any correlations between specific parameters and known defects
- Storage and future applications of blade digital twins to predict the lifespan of the components
The post is available from September 2020 as a full-time position. You will join Cohort 2 of the Aura CDT in Hull, in the heart of the UK’s Energy Estuary – the global centre for research, innovation and development for the sector. Initially, you will study for a Postgraduate Diploma in Offshore Wind Energy and the Environment, followed by a 3-year PhD in Sheffield supported by Siemens Gamesa Renewable Energy.
For more information visit www.auracdt.hull.ac.uk