Turbulence refers a state of fluid where its motion is characterized by chaotic behavior. It is one of the well-known, unresolved problems in physics and has been impacting on our daily lives from a cup of hot coffee, aerodynamics of aircraft to cosmological supernova. There is a famous quote from a physicist Werner Heisenberg that, “When I meet God, I’m going to ask him two questions: why relativity? And why turbulence? I really believe he’ll have an answer for the first,” which indicates the complexities of problems we’re facing to understand the turbulence.
Although challenging to unravel the turbulence, a large number of engineering systems operate under turbulent flows, and even many systems exploit characteristics of turbulence. Any systems associated with large sizes or high speeds, they inherently deal with turbulent flows: some examples are automobiles, aircraft, wind turbines, or any combustion engines.
Especially, combustion engines intentionally provoke the turbulence as it vastly enhances mixing between fuel and oxidizer, which leads to high performances. However, the complexity increases to another level as the fluids contains hundreds of chemical species that are produced/destroyed while producing heat.
So far, most of current simulation approach for reacting flow simulations is to include all the relevant chemical species to predict the flow field. However, it is extremely expensive and time consuming to include all the chemical species. Recent researches indicate that a single passive scalar, fluid residence time, is a promising marker to simplify the complex chemical reactions. As most chemical reactions are time-dependent process, major chemical reactions can be mapped with fluid residence time.
In the proposed PhD project, the candidate characterized the stochastic properties of fluid residence time in complex turbulent flows, such as turbulent jet, wake, and swirling flows. The developed properties will be interlaced with chemical reactions to further develop reduced-order combustion/reactor models. The project may involve conducting high fidelity flow simulation to generate new data set and conduct analytic analysis to develop model for combustion/reactor models.
This project will be conducted in collaboration with University of Southampton, and possibly with Sandia National Laboratory, USA.
Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. A good fluid dynamic background is required and experience in programing language (C/C++ or Fortran) is desirable. Further information on English language requirements for EU/Overseas applicants.
Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere