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Research Studentship in multi-scale aerodynamic modelling of wind farms and complex terrain


Project Description

Research Studentship in multi-scale aerodynamic modelling of wind farms and complex terrain

4-year DPhil studentship, available from October 2020

This studentship is being offered jointly by the University of Oxford and the UK Met Office under the NERC CASE studentship scheme. The successful applicant will join the NERC-Oxford Doctoral Training Programme (DTP) in Environmental Research https://www.environmental-research.ox.ac.uk

Research Area
Prediction of wind resource available for large-scale wind power generation requires a good understanding of atmospheric interaction with wind turbine arrays. This problem shares much common ground with the modelling of atmospheric flow over complex terrain. In both cases the key question is how large-scale atmospheric flow is modulated by an exchange of momentum with small-scale features near the earth’s surface.

This DPhil project will build on an ongoing collaboration between the University of Oxford and the UK Met Office in the area of multi-scale modelling of large wind farms. Our recent study has demonstrated that a relatively simple theoretical model, derived from the law of momentum conservation in a two-scale coupled manner, can predict the key effect of atmospheric interaction with wind turbines satisfactorily under a variety of realistic atmospheric stability conditions (or wind profiles). This motivates an extension of the two-scale coupled flow modelling to more complex problems, including those of flow over complex terrain. Further details can be found at the following website:
https://www.environmental-research.ox.ac.uk/case-studentships/industrial-case-projects-available-for-2019-entry/a-unified-approach-to-multi-scale-modelling-of-wind-farms-and-complex-terrain

The student will be based with the DTP to undergo a training programme during the first two terms, and then transferred to the Department of Engineering Science to conduct a research project supervised jointly by Dr Takafumi Nishino (Civil Engineering Research Group, University of Oxford) and Dr Thomas Dunstan (Atmospheric Processes and Parameterizations Group, UK Met Office). The student will also have opportunities to work together with scientists at the Met Office during a placement (for approximately 6 months).

Eligibility
This studentship is available to UK students (fees plus stipend) and EU students (fees only). Please see the DTP website (https://www.environmental-research.ox.ac.uk/how-to-apply/) for full details.

Candidate Requirements
Prospective candidates will be judged according to how well they meet the following criteria:

• A first-class or high upper-second-class honours degree in Engineering, Physics or Applied Mathematics
• Experience in academic research in a field related to fluid dynamics
• Excellent written and spoken communication skills in English

The following skills are desirable but not essential:

• Experience with computational fluid dynamics (CFD)
• Knowledge of wind power generation
• Knowledge of the atmospheric boundary layer
• Ability to program in Fortran and Python

Application Procedure
Informal enquiries are encouraged and should be addressed to Dr Takafumi Nishino () before making an application. Please note that applications sent directly to this email address will not be accepted.
All applications must be submitted in accordance with the instructions provided on the DTP website (https://www.environmental-research.ox.ac.uk/how-to-apply/). Please make sure to state the title of the CASE project “A unified approach to multi-scale modelling of wind farms and complex terrain”, in your application, and please quote 20ENGCI_TN in all correspondence and in your graduate application.

Application deadline 12 noon (GMT) on Friday 24th January 2020
Start date October 2020

Funding Notes

Award Value
The studentship covers the full course fees at the level set for UK/EU students (£7,970 in 2020-21 academic year) plus a stipend (for UK students only, £15,009 in 2019-20).

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