Compressible Turbulent Mixing


A fundamental understanding of compressible turbulent mixing is critical to advancing technologies in aeronautical, automotive, clean energy and acoustics. This project aims to develop state-of-the-art methods and further push forward our understanding of the role of turbulence.


Dr Ben Thornber

Research Location

Aerospace, Mechanical and Mechatronic Engineering

Program Type



Compressible turbulent mixing is responsible for the growth of boundary layers around wings thus dictating drag, for the mixing of fuel and air in a combustor thus dictating reaction rates, and in producing noise in aircraft and helicopters. These flows are incredibly complex, consisting of a wide range of vortex sizes, where often the largest vortices are more than a million times larger than the smallest vortices. In addition, where two or more species are present, the mixing of these two species occurs due to diffusion, which acts at a very small length scale, yet can impact the evolution of the whole mixing layer (particularly in reacting flows). When turbulence interacts with solid surfaces, or with other fluids (when jets meet for example) then the deformation of structures within the turbulent flow field can cause noise. All of the above mechanisms are made more complex by the underlying compressibility of the fluid. So why not just undertake computations of these flows to give the needed insight? The reason is that these computations are extremely challenging, needing to resolve the aforementioned large range of vortex sizes, plus multiple species, and in some cases shock waves. Due to these reasons, it is not yet possible to undertake the `perfect computation’, and will not be for some time.  This project aims to shed light into compressible turbulent mixing problems with a particular focus on the development of algorithms capable of significantly improving on the current state-of-the-art, then applying these algorithms to understand outstanding fundamental problems in turbulence including self-similarity, influence of initial conditions, mixing in reacting flows and noise production.

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compressible, turbulent, mixing, aeronautical, automotive, clean energy, acoustics, aircraft, helicopters, CFD, Computational Fluid Dynamics

Opportunity ID

The opportunity ID for this research opportunity is: 2276

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