About the project
You will join a group of PhD students and post-doctoral researchers using high performance computing to advance understanding of high speed aerodynamics. Over the past decade we have developed efficient open-source software that enables us to run large numerical simulations with billions grid points on mixed computer architectures including CPU and GPU machines. A current project is preparing the code set for the next generation of exascale computing, including development of tools for analysis of large data sets
All surfaces are rough to some extent and it is necessary to predict drag accurately to be able to assess technologies leading to NetZero. In addition, local heating due to roughness can be severe in high Mach number flows. In this project we will consider roughness effects with pressure gradients, firstly during transition to turbulence, including the effects of distributed roughness on flow instability and the generation of local hot spots during the transition process, when eddies are stronger than in the resulting turbulent flow. Secondly, we will use machine learning to connect rough surface features to increased heat transfer in the fully rough regime. The methods used for the research will be direct and large-eddy numerical simulation. On the project you will gain skills in advanced computational methods, working alongside a diverse group of researchers. You will develop your writing and presentation skills and have the opportunity to present results at international conferences and interact with other groups around the world.
We are particularly looking for UK national students, either having or expecting to achieve a first class degree in aerospace or mechanical engineering. You should have studied fluid mechanics or aerodynamics to a high level, have an aptitude for computational work and have carried out successful project work. Early applications are welcome.
