Fluid Simulation and Modeling

The efficient mixing of fluids is key in many applications, such as chemical reactions and nanoparticle
precipitation. Detailed experimental measurements of the mixing dynamics are however difficult to
obtain, and so predictive numerical tools are helpful in designing and optimizing many processes. Turbulent mixing at small scales is poorly understood, which adds to the intrinsic difficulties of modeling turbulence. 

During the operation under the harsh conditions of the atmospheric boundary layer, the rotor blades of wind turbines are directly exposed to mechanical influences such as raindrops, sand grains or insects. As a result, the leading edge of the rotor blades suffers from erosion damages and contamination, which lead to aerodynamic performance losses of up to 25 % and premature fatigue failures. For this reason, a condition monitoring of rotor blades with an early detection and characterisation of initial surface defects on wind turbines in operation is needed.

From aircraft moving through the air to fluids being pumped through pipes and even forecasting the weather, turbulence plays a crucial role in many technical and natural flow systems. Despite this, fundamental aspects about it are still poorly understood, which means that it is often also the barrier to more accurate predictions in these systems. In this project, we study the mechanisms through which turbulence is sustained in simple shear flows, in particular channel flow. We make use of recent progress in computing hardware, especially GPUs, to study such systems with methods whose application would not have been computationally feasible just a few years ago.