Award details

Towards High-Fidelity Computational Fluid Dynamics Simulations of Moving Parts - Engineering - EPSRC DTP funded PhD Studentship Ref: 2960

About the award

This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding.

The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students.

Please note that of the total number of projects within the competition, up to 15 studentships will be filled.

Supervisors
Dr David Moxey

Location 
Streatham Campus, Exeter

Project Description
This funded PhD position will develop novel, high-fidelity methods for computational fluid dynamics problems in aeronautics that require the simulation of rotating parts, with a particular emphasis on the investigation of turbomachinery applications.

The use of computational fluid dynamics (CFD) within the engineering and aeronautics communities has increased dramatically over the last decade, with the use of CFD becoming common practice in the advanced engineering design of modern cars, aircraft and renewable energy devices such as wind turbines. At Exeter, the PI of this project is developing highly accurate time-dependent fluid dynamics solvers for CFD simulations using novel numerical methods. This provides much greater fidelity than current industry-standard tools by leveraging modern computing hardware, including large supercomputers comprising of hundreds of thousands of processors. In particular the use of this numerical method gives us the opportunity to investigate complex fluid dynamics problems at a level of unprecedented detail.

A common feature in all of the aforementioned research areas is the necessity to model moving features, such as the blades of a wind turbine or the interior rotor of a jet engine. The successful candidate under this funded PhD studentship will extend existing work to accurately model rotating features using sliding mesh technology, and investigate how these can be applied efficiently in the context of extremely large, parallel simulations. These developments will be performed inside the open-source Nektar++ spectral element framework (www.nektar.info), and then applied to engineering practice in problems of interest to academically relevant flow problems including various industrial partners, with a particular emphasis on turbomachinery applications.

Entry Requirements
You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in an area related to scientific computing and/or aeronautics (e.g. engineering, applied mathematics or physics). Experience in computational fluid dynamics, finite element methods or high-performance computing is desirable.

Previous programming knowledge and/or experience with high-performance computing is essential, particularly in languages involving object-orientated programming such as C++.

If English is not your first language you will need to meet the English language requirements and provide proof of proficiency. Click here for more information and a list of acceptable alternative tests.

The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes.  If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU.  For information on EPSRC residency criteria click here.

Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database for alternative options.

Summary

Application deadline:10th January 2018
Value:3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year.
Duration of award:per year
Contact: Doctoral Collegepgrenquiries@exeter.ac.uk

How to apply

You will be required to upload the following documents:
•       CV
•       Letter of application outlining your academic interests, prior research experience and reasons for wishing to
        undertake the project.
•       Transcript(s) giving full details of subjects studied and grades/marks obtained.  This should be an interim
        transcript if you are still studying.
•       If you are not a national of a majority English-speaking country you will need to submit evidence of your current
        proficiency in English.  For further details of the University’s English language requirements please see
        http://www.exeter.ac.uk/postgraduate/apply/english/.

The closing date for applications is midnight (GMT) on Wednesday 10 January 2018.  Interviews will be held at the University of Exeter in late February 2018.

If you have any general enquiries about the application process please email: pgrenquiries@exeter.ac.uk.
Project-specific queries should be directed to the supervisor.

During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates.  These are not limited to, but may include disclosures to:

• the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs;
• administrative staff at one or more other HEIs participating in the relevant programme.

Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent.