English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Caustics in the dynamics of heavy particles in turbulence accelerate particlecollisions. The rate $\mathscr{J}$ at which these singularities form dependssensitively on the Stokes number St, the non-dimensional inertia parameter.Exact results for this sensitive dependence have been obtained using Gaussianstatistical models for turbulent aerosols. However, direct numericalsimulations of heavy particles in turbulence yield much largercaustic-formation rates than predicted by the Gaussian theory. In order tounderstand possible mechanisms explaining this difference, we analyse anon-Gaussian statistical model for caustic formation in the limit of small St.We show that at small St, $\mathscr{J}$ depends sensitively on the tails of thedistribution of Lagrangian fluid-velocity gradients. This explains whydifferent authors obtained different St-dependencies of $\mathscr{J}$ innumerical-simulation studies. The most-likely gradient fluctuation that inducescaustics at small St, by contrast, is the same in the non-Gaussian and Gaussianmodels. Direct-numerical simulation results for particles in turbulence showthat the optimal fluctuation is similar, but not identical, to that obtained bythe model calculations.

Caustic formation in a non-Gaussian model for turbulent aerosols