The dynamics of particles in flows ("flowing matter") is fundamental to understanding chemical and kinetic processes in the Natural Sciences. Often the fluid flow is turbulent ("turbulent aerosols"). It is at present very difficult to perform direct numerical simulations of such systems, because of the large range of time and length scales involved. We have therefore pursued an alternative approach: we analyse statistical models of turbulent aerosols. The resulting equations parallelise in an ideal way: different statistical realisations are farmed out on independent processors. This approach has allowed us to identify and characterise important fundamental mechanisms determining the dynamics of particles in flows [Gustavsson & Mehlig, Adv. Phys. (2016)].
1.) Statistical models for the angular dynamics of small ice crystals settling in turbulen clouds (Kristian Gustavsson)
2.) Statistical models for collisions between non-spherical particles in turbulence (Kristian Gustavsson).
3.) Effects of fluid inertia on the rate of caustic formation for inertial particles in linear steady flows (collaboration with Tomas Rosen, Stony Brook).
4. Statistical-model simulations of evaporation and condensation of cloud droplets in the turbulent air at the edge of a cumulus cloud (Johan Fries)