Stably stratified shear flows are ubiquitous in the environment and industrial systems. In the atmosphere such flows are associated with clear air turbulence. In lakes, convective circulation give rise to thermally-driven exchange flows. In subsea umbilical cables, the sequential injection of fluids may give rise to stratified pipe flows. The accurate prediction of transverse mixing and turbulence intensity and structure in such flows is essential for optimizing the injection schemes in subsea umbilicals and predicting contaminant transport in the atmosphere and in aquatic systems.
Despite their ubiquity, many fundamental questions remain. The aim of this project is to improve our understanding of the impact of incline, transverse confinement, density contrast, fluid rheology, and boundary roughness on stratified shear flows. You will generate these flows in a newly built Aberdeen Tilting Lock-Exchange Facility (ATLEF) in the School’s Fluids Mechanics Research Laboratory, and measure the turbulent velocity field and density distribution using particle image velocimetry and laser-induced fluorescence, respectively. Using your data as a guide, you will develop predictive models for the propagation speed, interface profile, and flow regimes as a function of the experimental variables of your choice.
The successful candidate will interact with members of two Research Groups within the School: (a) Mechanics of Fluids, Soils and Structures Research Group and (b) the Petroleum & Natural Gas Engineering Research Group. Members of these Groups use different combinations of laboratory experiments, field measurements, numerical simulations, and theoretical analysis to study physical processes associated with a wide range of applications, including enhanced oil recovery, flow through aquatic vegetation, wind turbines, and coastal erosion.
Candidates should have (or expect to achieve) a UK honours degree at 2.1 or above (or equivalent) in relevant engineering or physical science discipline.
Essential background: Fluid mechanics
Previous laboratory experience and familiarity with MATLAB are essential. Experience in programming, data processing, and image analysis will be an advantage. Good written and spoken communication skills are essential.
• Apply for Degree of Doctor of Philosophy in Engineering
• State name of the lead supervisor as the Name of Proposed Supervisor
• State ‘Self-funded’ as Intended Source of Funding
• State the exact project title on the application form
When applying please ensure all required documents are attached:
• All degree certificates and transcripts (Undergraduate AND Postgraduate MSc-officially translated into English where necessary)
• Detailed CV
Informal inquiries can be made to Dr Y Tanino ([email protected]
) with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Postgraduate Research School ([email protected]