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Refining our Understanding of Small-scale Turbulence Dynamics

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

About This PhD Project

Project Description

Improved modelling methods for fluid flows require a better understanding of how turbulent, Newtonian fluids such as water or air dissipate energy. This project focuses on the topologies associated with these dissipative events. In terms of the velocity gradient tensor, it can be readily shown that relevant complexities result from the nonlocality intrinsic to the Navier-Stokes equations. We have recently proposed a new way forward in this respect, with new terms derived for the dynamics represented by these nonlocal processes (Keylock, 2018). The aim of this project is to continue this analysis using both mathematical and numerical methods in order to propose new ways forward for model closure schemes. Placing confidence on the results using statistical methods (Keylock, 2017) may also form a significant component of the project.

Entry Requirements

Applicants should have, or expect to achieve, a First Class Honours degree (or equivalent) in mathematics, physics, aeronautics or a related field.

A relevant Master's degree and / or experience in one or more of the following will be an advantage:
Computer programming;
Computational Fluid Dynamics;
Linear Algebra;
Time-series analysis (wavelets and Fourier methods)


Keylock, C.J. 2017. Synthetic velocity gradient tensors and the identification of significant aspects of the structure of turbulence, Physical Review Fluids 2, 8, 084607.

Keylock, C.J. 2018. The Schur decomposition of the velocity gradient tensor for turbulent flows, Journal of Fluid Mechanics 848, 876-904, 10.1017/jfm.2018.344.

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