Unraveling the secrets of turbulence in a fluid puff

TL;DR

This paper combines theory and simulations to analyze the detailed statistical structure of turbulence in fluid puffs, advancing understanding beyond bulk properties to include space/time scaling and intermittency, with implications for virus transmission modeling.

Contribution

It introduces a novel integrated approach to predict and validate the detailed statistical behaviors of turbulence in puffs, filling a significant gap in existing research.

Findings

Excellent agreement between theory and simulations.

Predicted space/time scaling behaviors of velocity and temperature.

Implications for modeling virus-laden droplet evaporation.

Abstract

Turbulent puffs are ubiquitous in everyday life phenomena. Understanding their dynamics is important in a variety of situations ranging from industrial processes to pure and applied science. In all these fields, a deep knowledge of the statistical structure of temperature and velocity space/time fluctuations is of paramount importance to construct models of chemical reaction (in chemistry), of condensation of virus-containing droplets (in virology and/or biophysics), and optimal mixing strategies in industrial applications. As a matter of fact, results of turbulence in a puff are confined to bulk properties (i.e. average puff velocity and typical decay/growth time) and dates back to the second half of the 20th century. There is thus a huge gap to fill to pass from bulk properties to two-point statistical observables. Here we fill this gap exploiting theory and numerics in concert to predict and validate the space/time scaling behaviors of both velocity and temperature structure functions including intermittency corrections. Excellent agreement between theory and simulations is found. Our results are expected to have profound impact to develop evaporation models for virus-containing droplets carried by a turbulent puff, with benefits to the comprehension of the airborne route of virus contagion.