University of Sheffield
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We are excited to announce a new PhD opportunity in modelling, control & optimisation of wall-bounded turbulent flows.
The successful candidate will join a vibrant team of researchers within the thermo-fluids group at Sheffield as well as benefiting from national and international (with Europe and China) collaborations. The project aims to provide PhD students with top-quality, challenging training at the forefront of research into fundamental and applied fluid mechanics.
Topic of research: Pipes and ducts are the most common means to distribute fluids throughout society, with applications ranging from the oil & gas industry to domestic settings. Most often these flows are turbulent and a lot of energy is wasted due to the large associated frictional losses. It is estimated that around 20% of the global electric power consumption is spent by pumping systems to overcome frictional drag. This figure could be drastically reduced if flows in these systems were smooth and laminar rather than turbulent, with consequent huge cuts in pumping costs and carbon emissions.
This project thus aims to investigate efficient control strategies to completely suppress turbulence in pipe flow. The problem will be tackled using advanced mathematical tools combined with state-of-the-art numerical simulations and modern data-driven/machine-learning techniques. Different relaminarisation (i.e. the process of transition from turbulent to laminar flow) scenarios will be analysed in order to gain a unified fundamental understanding of the physical mechanisms underlying this process. Such knowledge will then be exploited to develop new control techniques that are applicable in practice.
During this project, you will gain significant experience in:
– Computational fluid mechanics using in-house high-fidelity numerical software
– Analysing large data-sets and developing codes for data processing
– Turbulence theory (modelling and control), flow instabilities and transition to turbulence
– Optimisation and data-driven/machine learning techniques for fluid mechanics.
– Working in a multi-disciplinary/international environment
If you’re interested in applying and wish to discuss any details of the project informally, please contact Dr Elena Marensi at [email protected]
Requirements:
Education A very good 4-year degree or master’s degree in Mechanical, Aeronautical, Marine, Civil, Chemical Engineering, Applied Mathematics or Physics (at least a UK 2:1 honours degree, or its international equivalent)..
Knowledge, skills Strong background in fluid mechanics, good programming skills (e.g. Fortran, Python/Matlab) ; desirable: wall-bounded turbulence, dynamical system theory, numerical analysis. Any previous experience in applying machine-learning algorithms is a plus. Desirable: final-year project on a fluid mechanics problem.
Other requirements We are looking for a dedicated, dynamics and self-motivated individual with a strong passion for fluid mechanics research. Excellent communication and scientific writing skills are also required as well as a strong ability to work both individually and in a team.
To apply, please use our on-line PhD application form, including
· Personal statement
· Curriculum Vitae
· Two reference letters
· Degree Transcripts to date
If you have questions regarding the application process please contact Marina Boulis ([email protected])
Funding Notes
The funding for this post includes standard home tuition fees and a stipend of £18,622 tax-free per annum for up to 3.5 years. For international students, please contact: [email protected] for more details about overseas fees.
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