Automating CFD using knowledge-based systems
Applications are invited for our EPSRC funded Doctoral Training Partnership (DTP) PhD studentship for the project titled “Automating CFD using knowledge-based systems” starting 1st October 2021. The successful applicant will receive an annual stipend (bursary) of £17,609, including inner London weighting, plus payment of their full-time home tuition fees for a period of 36 months (3 years). You must be eligible for home tuition fees either through nationality, residency or other connection to the UK.
This funded project will involve the generation of modules to automate mesh generation, run steady and unsteady simulations, extract and visualise data, perform AI/machine learning and link these within a knowledge-based system. This will allow LES to be consistently deployed with minimal intervention. The project builds upon recent LES of turbine zones. The candidate will use EPSRC HPC resources and should have good knowledge of turbulent flows and their modelling. Working within a vibrant, multi-disciplinary team in the Department of Mechanical and Aerospace Engineering there will also be opportunities to engage with internationally leading academics and industries.
The accuracy of predicted turbine flowfields using typical steady CFD is strongly dependent on the turbulence model chosen and flow characteristics. Large Eddy Simulation produces accurate flow data consistently for a wide variety of complex flows. Although LES requires careful case setup, the accuracy, data detail and cost make its use attractive for many applications. Modern CFD solvers utilise High-Performance Computing (HPC) to reduce simulation turnaround time. However, pre-processing (mesh generation) and post-processing (data extraction + visualisation) are now bottlenecks, requiring significant manual intervention and time. Modelling of flow features such as separation in gas-turbine internal cooling ducts lends themselves towards automation.
Please email Dr James Tyacke at email@example.com to ask questions about the project or to arrange an informal discussion about the project or studentship.
You will have or achieve an undergraduate (first) degree classified at 2:1 or above in Engineering, Mathematics, Physics or a similar discipline. A Postgraduate Masters degree is not required but may be an advantage. You should be highly motivated, able to work independently as well as in a team, collaborate with others and have good communication skills.
You should be familiar with fundamental CFD processes, specific physical requirements of the problem, transforming knowledge into useful guidelines and sustainable code development. Experience in fluid dynamics, CFD, HPC, Fortran/C++/Python/Matlab is an advantage.
How to apply
Please submit your application documents (see list below) by 12:00 Noon on Friday 9 April 2021 to firstname.lastname@example.org Interviews will take place in April/May 2021.
- Your up-to-date CV;
- Your personal statement (300 to 500 words) summarising your background, skills and experience;
- Your Undergraduate/Postgraduate Masters degree certificate(s) and transcript(s);
- Evidence of your English language skills to IELTS 6.5 (or equivalent, 6.0 in all sections), if appropriate;
- Contact details for TWO referees, one of which can be an academic member of staff in the College.
Please state the title of the project at the top of your personal statement.