The Settling Rates of Particles in Rayleigh–Bénard Turbulence

It is widely recognized that better understanding the interaction between clouds and aerosols is among the most pressing and essential endeavors in climate and atmospheric sciences. One particular process of interest is the settling rate of heavy particles and how this controls changes in rain formation and droplet size distribution. While much work has been done understanding particle settling rates in homogeneous isotropic turbulence and the potential for particles to settle significantly faster than their predicted Stokes settling velocity, more work needs to be done in other environments. Towards this aim, a set of experiments were conducted utilizing the Pi Chamber experimental facility at Michigan Technological University to investigate the physics dictating particle settling time in Rayleigh-Bénard turbulence; knowledge of droplet settling and lifetime is vital for characterizing how long droplets are exposed to a modeled turbulent environment.

The Pi Chamber is a rectangular chamber with an inner working volume of 3.14 m³ built for generating clouds. Among other features, it can maintain a statistically steady, turbulent Rayleigh-Bénard flow at a Rayleigh number of approximately 10⁹. In this set of experiments, solid, non-evaporating spheres (namely oil, glass, and hollow glass) of varying sizes were added to the chamber. After the initial injection, the decreasing concentration of particles over time was measured, and from this, a decay rate was calculated. An ideal Stokes settling velocity would predict that these decay rates vary as the square of the particle diameter, and a primary goal of this work is to quantify any deviation from this theoretical behavior. In this talk, we will show the results across a broad range of particle sizes (and thus Stokes and settling numbers), highlighting the multiple physical mechanisms dictating settling rate across particle size and density. In future work, this knowledge will be combined with condensational growth and decay in a cloudy environment to improve our understanding of cloud droplet growth and size distribution evolution.