Research Associate: High Fidelity CFD of ORE Farm Wake Interaction

Overall, Purpose of the Job

The main tasks are to advance the use of high-fidelity modelling to improve understanding of the characteristics of the turbulent wakes that develop downstream of large offshore wind farms or tidal stream arrays. Such wakes are important to understand and predict because of their potential to impact the energy supply from such renewable energy projects. Analysis will be conducted using high-fidelity CFD model such as Large-Eddy Simulation (LES). The work will include simulation of shallow boundary layer flows such as atmospheric flows with differing thermal stability and of depth constrained coastal flows with differing bed conditions representative of deployment sites. Interaction of the flow with horizontal axis turbines will be simulated using actuator methods leading to wake development. Boundary conditions to the CFD model will be further developed to analyse the impact of meso-scale variation of the flow occurring over much larger spatial scales than the turbine array. Flow conditions and turbine operating conditions studied will be representative of the sites at which offshore energy projects are being developed. Analysis of model outputs will be conducted to improve understanding of the processes that affect the extent of the farm wake and to quantify the impact on nearby offshore renewable energy projects. This work will include further development and use of an in-house CFD code (DOFAS) as well as drawing on other datasets such as from wider-area resource modelling and physical measurements. These activities will inform further development of the computationally efficient models that are employed for engineering design of wind- and tidal-stream farms and will inform design of physical measurement campaigns to enable further model validation.

Tasks will include

• Development and validation of CFD methods including Large-Eddy Simulation (LES) to resolve turbulent boundary layer flows representative of flows at offshore energy farms.
• Use of CFD methods including LES to analyse performance, loading and wakes of arrays of turbines in representative flow conditions.
• Analysis of CFD model outputs to inform reduced order model development, and to inform design of experimental and measurement campaigns.
• Set-up, conduct and analyse simulations on High Performance Computing platforms, e.g. the Manchester’s Computational Shared Facility (CSF) or ARCHER2, as appropriate.

Other benefits from employment at The University of Manchester

• Fantastic market leading Pension scheme
• Excellent employee health and wellbeing services including an Employee Assistance Programme
• Exceptional starting annual leave entitlement, plus bank holidays
• Additional paid closure over the Christmas period
• Local and national discounts at a range of major retailers

As an equal opportunity employer, we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

Our university is positive about flexible working – you can find out more here

Hybrid working arrangements may be considered.

Please be aware that due to the number of applications we are unfortunately not able to provide individual feedback on your application.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Any recruitment enquiries from recruitment agencies should be directed to People.Recruitment@manchester.ac.uk.

Any CV’s submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Professor Tim Stallard

Email: tim.stallard@manchester.ac.uk

General enquiries:

Email: People.recruitment@manchester.ac.uk

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.