Large-scale 3D Lagrangian particle tracking using soap bubbles

Field measurements of atmospheric turbulence are challenging to conduct, not only because flow conditions are constantly changing in space and time, but also because of the high Reynolds numbers and thus the large range of scales present in the turbulence. Among the most challenging techniques is Lagrangian particle tracking, which is used to investigate turbulent mixing and dispersion behaviour. The ability to conduct highly-resolved Lagrangian measurements in the atmosphere is of interest to a wide range of applications including wind turbine flows, the spreading of pollutants and urban fluid dynamics.

This study is motivated by the desire to investigate coherent structures in the wakes of wind turbines. These flow structures are too small to be adequately captured by large-scale measurement techniques like LIDAR and remote sensing. However, they require fields of view significantly larger than those achieved in laboratory-scale experiments. Here, we explore soap bubbles as atmospheric tracer particles. We use Phantom high-speed cameras for data acquisition and a shake-the-box code for reconstructing the particle tracks. The long-term goal of this work is to image the largest possible field of view in order to study the flow behind wind turbines and other large-scale structures.