A quick global transition to a full energy generation from renewable sources is essential to mitigate the impact of climate change and ensure the long-term sustainability of our society. UK’s decarbonisation target is to achieve net-zero greenhouse gas emissions by 2050 and, to this end, Offshore Renewable Energy (ORE) is key to achieve this ambitious but necessary goal. The UK is world leader in ORE with the world’s largest offshore wind energy capacity installed and a projected five-fold increase by 2050. As turbines to be installed in forthcoming Offshore Wind Farms (OWFs) will have diameters larger than 220m with hub heights of 150-200m and thus top tip heights exceeding 300m, there will be new challenges that need to be analysed in order to understand the environmental implications of large-scale OWFs, such as changes in the local meteorology, or quantify the interaction between distant OWFs.
This PhD project aims at building a state-of-the-art Computational Fluid Dynamics (CFD) model that is capable of representing with high spatial and temporal precision future operating OWFs. This novel computational framework will enable the analysis of the induced impacts of OWFs in the local and regional meteorology.
The student will be responsible for the coupling between a mesoscale atmospheric model (WRF – Weather Research Forecasting) and a microscale model (DOFAS – Digital Offshore FArms Simulator) in which the wind farms will be embedded. This high-fidelity model will resolve the relevant turbulent flow scales involved and thus provide accurate results to assess industry and policymakers about the future environmental changes OWFs might generate.
During the PhD, the student is expected to interact with academics across different departments from the University of Manchester, e.g. offshore renewable energy, atmospheric sciences, aerodynamics, or modelling and simulation, as well as external institutions and organisations, such as the Offshore Renewable Energy Catapult or Met Office.
Candidates must have a 1st or high 2i in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science, or Atmospheric Sciences. Knowledge in fluid mechanics, numerical methods and computational modelling would be advantageous. The ideal candidate is expected to have a strong interest in renewable energy, be enthusiastic about computational modelling, be able to have a proactive attitude towards problem solving independently, and ability to work in multidisciplinary teams. The student is expected that she/he has prior experience writing code on Fortran, C/C++, or similar, and on Linux systems.
For further information about the project or any informal enquiries, please contact Dr Pablo Ouro, email@example.com.
Interested applicants should send to Dr Pablo Ouro:
• Up to date CV,
• One or two letters of recommendation,
• 1-page personal statement including prior experience, motivation to learn and future research goals.
Suitable candidates will be asked to complete the electronic application form at The University of Manchester.
As an equal opportunities employer, we welcome applications from all suitably qualified persons. As the School is committed to the principles of the Race Equality Charter Mark and Athena SWAN, we would particularly welcome applications from women and the black and minority ethnic (BME) community, who are both currently under-represented at this grade. All appointments will be made on merit.
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