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Dr James Tyacke

Dr James Tyacke
Lecturer in Aerospace Engineering (Aerodynamics)

Topics

I am interested in supervising PhD projects primarily in Large Eddy Simulation (LES) of complex flows including Electronics Cooling, Aeroacoustics, Aerospace and Urban flows.  Modern High Performance Computing (HPC) architectures are being leveraged for both simulation and analysis of large data sets (Big Data), revealing unsteady flow physics.

Further interests include increasing CFD automation, including mesh generation and optimisation, solution analysis and feedback into knowledge-based systems using Machine Learning and AI.

Fully funded PhD projects may be offered to those who apply for DTP EPSRC scholarships before the deadline of Noon 29th May 2020. For eligibility and more details click here. If you are interested in this funding opportunity under my supervision, please do not hesitate to contact me via email.

I am currently looking for a student to complete a PhD under EPSRC DTP funding at Brunel University London. A range of projects are available, focusing on multi-fidelity Computational Fluid Dynamics (CFD). Potential application areas are electronics cooling, aerospace, aeroacoustics or urban flows among others. Further details can be found here: https://www.brunel.ac.uk/research/Research-degrees/PhD-Studentships/Studentship?id=a2efbe35-b0b9-46a7-b284-3fd40ff05174 .

PhD projects for research students

Multi-fidelity Modelling of Electronics Cooling

Electronics cooling is critical to the reliable performance of a vast array of todays technologies including datacentres, electric vehicles, avionics, telecommunictions to name only a few. Pertinent to this is the accurate prediction of fluid flow and heat transfer. Analyses range from below chip to data centre levels, requiring multi-fidelity Computational Fluid Dynamics (CFD) methods. Suitable methods based around Large-Eddy Simulation (LES) and immersed boundary methods (IBMs), with wide application will be developed. Suitable candidates would have a degree in Mechanical or Aerospace Engineering, or Mathematical modelling related subjects. Simulations and data analysis will utilise efficient parallel computations on CPUs and GPUs on High Performance Computing (HPC) facilities.

Multi-fidelity Modelling of Electronics Cooling

Electronics cooling is critical to the reliable performance of a vast array of today's technologies including datacentres, electric vehicles, avionics, telecommunications to name only a few. Pertinent to this is the accurate prediction of fluid flow and heat transfer. Analyses range from below chip to data centre levels, requiring multi-fidelity Computational Fluid Dynamics (CFD) methods. Suitable methods based around Large-Eddy Simulation (LES) and immersed boundary methods (IBMs), with a wide application will be developed. These will be used to assess and improve heat transfer prediction by understanding the physical mechanisms responsible and to build datasets for machine learning.

Suitable candidates would have a degree in Mechanical or Aerospace Engineering or Mathematical modelling related subjects. Simulations and data analysis will utilise efficient parallel computations on CPUs and GPUs on High Performance Computing (HPC) facilities.