Evolution of passive scalar mixing layers in stratified and unstratified homogeneous turbulence

TL;DR

This study uses high-resolution simulations to analyze passive scalar mixing in stratified and unstratified turbulence, revealing differences in mixing behavior and modeling approaches.

Contribution

It provides new insights into the evolution and modeling of passive scalar mixing layers in stratified turbulence, including effective models for scalar flux.

Findings

Transverse scalar spreading is slightly faster in stratified turbulence.

Stratification suppresses vertical mixing, leading to minimal vertical scalar spreading.

A one-constant model effectively predicts scalar flux when the mean profile is known.

Abstract

High-resolution large-eddy simulations of decaying stratified and unstratified homogeneous turbulence are used to understand the mixing of passive scalars in stably stratified flows. Two passive scalar mixing layers, one in the vertical direction and the other in the transverse direction, are a model for a plume that is very large relative to the length scale of the velocity. In the transverse direction, the evolution of the passive scalar is broadly similar in the stratified and unstratified cases, although it does spread slightly faster when stratified. Also, the intensity of the scalar fluctuations is higher in the stratified case, and the turbulent/non-turbulent interface is more intermittent. In the vertical direction, though, the stratified case has almost no mixing because the stratification prevents large-scale stirring. Initially, the stratified passive layer grows until its width is proportional to the vertical integral length of the horizontal velocity, which is itself constrained to maintain the vertical Froude number order one. After this early growth, there is little additional spreading of the passive scalar. Modelling of the stratified scalar flux in the transverse direction is done effectively with a one-constant model if the mean profile is known, and a two-constant model if the profile shape must be assumed. In the latter case, the model is good only if the scalar is in quasi-equilibrium with the velocity field such that the length scale of the scalar can be scaled from the kinetic energy. In this study, the Prandtl number of the active and passive scalars is 0.7. It is anticipated that the reverse buoyancy flux resulting from higher Prandtl numbers will affect the passive scalar mixing.