General research description

I use numerical simulations to study turbulence and turbulent phenomena in the ocean and atmosphere. For my PhD, I am using direct numerical simulation (DNS) to study the turbulent wake behind a bluff body in a stratified fluid. DNS is a computational technique which solves the governing equations in their exact form without any models and resolves all relevant length and time scales. It is computationally expensive even for problems with simple geometries and is therefore not applicable for most practical applications. However, DNS gives very detailed almost analytical quality results and has proven instrumental in developing understanding in many problems that are not tractable analytically and/or experimentally. While the turbulent wake behing a moving body is a fundamental problem in turbulence and has been studied for hundreds of years, even the wake behind relatively simple shapes such as spheres still lacks a complete description. The reason for this is that the wake is highly nonlinear which makes it difficult to make progress analytically. The presence of a density gradient significantly complicates matters as it destroys the symmetry of the problem and introduces a complex coupling between kinetic and potential energy.

Research Projects (Click on images for details)

Large Eddy Simulation of the near to intermediate wake of a heated sphere at Re = 10,000

SF2s: a computational tool for high resolution simulation of turbulent flow phenomena

Flow past sphere link Prandtl number link

Simulations of a propelled wake with moderate excess momentum in a stratified fluid

The effect of the Prandtl number on a stratified turbulent wake

Excess momentum link Prandtl number link

Near wake behind a cylinder

Stratified shear layer simulations

Cylinder near wake link Stratified shear layer link

Research Projects before UCSD (Click on images for details)

Fluid flow in gas centrifuges

Optimization of the geometry of a heat sink

Gas centrifuge link Hypersonic Heat Flux on X-43
© 2011 Matt de Stadler