Turbulence Gallery

Clustering of Inertial Cloud Droplets in Isotropic Turbulence

Inertial particles (i.e., particles with densities greater than that of the carrier fluid) are centrifuged out of vortex cores in a turbulent flow and accumulate in low vorticity regions.  Such accumulation, referred to as "clustering" or "preferential concentration," has been linked to the acceleration of precipitation in cumulus clouds by increasing the collision frequency and the coalescence rate of the cloud droplets.  

The videos show inertial droplets clustering in a direct numerical simulation of a turbulent flow performed on over 8 billion grid points, using 16,384 processors on the Yellowstone supercomputer at NCAR. The cloud droplets are visualized in white, and high vorticity regions of the flow are shown in yellow.

The left image shows intermediate-sized droplets (75 microns with a Kolmogorov-scale Stokes number of 1) and the right image shows rain-size drops (400 microns with a Stokes number of 30). The former are very responsive to the underlying flow and form small, dense clusters, whereas the latter have a damped response to the flow and form larger, much less dense clusters.  The radial distribution function (RDF) is a statistical measure of clustering. As you can see from the RDF plots included in the video, the degree of clustering for the smaller droplets is much higher than for the larger droplets. Indeed, clustering peaks near a Stokes number of unity.

Influence of a densely built-up artificial island on the turbulent flow in the city of Macau (2014)

This animation of a large-eddy simulation displays the development of turbulence structures induced by a densely built-up artificial island off the coast of Macau. The turbulence is generated by a significant increase in surface roughness and additional wind shear at the walls of the high-rises. It forms a so called internal boundary layer, which grows in downstream direction. Animation data were derived using the parallelized large-eddy simulation model PALM (http://palm.muk.uni-hannover.de/), simulating a neutrally stratified flow over Macau, with a mean flow from the southeast to the northwest and a 10-m wind of approximately 1m/s. Turbulence structures and intensities are visualized by the rotation of the velocity vector (absolute values), with highest values in red and lowest values in white. Buildings are displayed in blue. The animation spans over 1 hour with a time-lapse factor of 43, and was rendered with VAPOR. The total PALM model domain had a size of 768 x 256 x 96 grid points in streamwise, spanwise and vertical direction, with a uniform grid spacing of 8m in each direction. Above 400m the vertical grid spacing is successively stretched up to a maximum vertical grid spacing of 40m. Non-cyclic boundary conditions are used in streamwise direction and a turbulence recycling method is applied, in order to guarantee a fully turbulent inflow. In total, the simulation required 1 hour of CPU time using 128 cores on the Cray-XC30 of the North-German Supercomputing Alliance (https://www.hlrn.de/). Further descriptions will be displayed during the animation. Responsible authors are Helge Knoop, Marius Keck and Siegfried Raasch. The visualization is published with DOI http://dx.doi.org/10.5446/14368 and licensed under Creative Commons Attribution NonCommercial - NoDerivs 3.0 Germany.

Small scale vorticity in fully developed turbulence

Turbulent mixing in a cylinder