Siemens Gamesa Renewable Energy: Individual Blade Digital Twins for Recording and Analysing Production Parameters

Aura CDT Industry PhD Scholarships

Siemens Gamesa Renewable Energy: Individual Blade Digital Twins for Recording and Analysing Production Parameters

In partnership with Siemens Gamesa Renewable Energy (SGRE), the Aura CDT is offering a cluster of 4-year taught and research industry-sponsored PhD scholarships. This 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.

Instructions on How to Apply

Academic Supervisors

Dr Peter Osborne, AMRC Sheffield   email:

Prof David Wagg, Sheffield   email:

Prof James Gilbert, Hull   email:



This full-time Siemens Gamesa Renewable Energy PhD Scholarship will include fees at the ‘Home/EU’ student rate and maintenance (£15,285 per annum, 2020/21 rate) for four years, depending on satisfactory progress. We are unable to accept International students on this project.


Entry requirements

If you have a First-class Honours degree or a 2:1 Honours degree and a Masters (or the international equivalents) in Mechanical or Chemical Engineering or related disciplines, we would like to hear from you. Experience of modelling mechanical systems and/or manufacturing processes would be advantageous.

If your first language is not English you will be required to provide evidence of your English language proficiency level that meets the requirements of the Aura CDT’s academic partners. This course requires academic IELTS 7.0 overall, with no less than 6.0 in each skill.

Apply here