Abstract

Abstract

Highlights

  • A wide range of applications include the fundamental phenomenon of turbulence sustained by shear between streams of fluids

  • Since these simulations have reached self-similar growth at sufficient Reynolds numbers to be past the mixing transition, they form a comprehensive data set for evaluating the variable density effects on late-time turbulence dynamics

  • The results demonstrate that, as Atwood number is increased while keeping the average density of the two free streams constant, the most intense turbulence is sustained in lighter-than-average fluid during self-similar growth

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Summary

Introduction

A wide range of applications include the fundamental phenomenon of turbulence sustained by shear between streams of fluids. Brown (1974) studied the thickness growth rate of variable-density spatially developing fully turbulent mixing layers He assumed that the temporal growth rate (i.e. from a frame of reference moving with the mixing layer convection velocity) is independent of the density difference between the streams, which is contrary to the reductions observed by Pantano & Sarkar (2002) and Almagro et al (2017). Olson et al (2011) simulated mixing layers with mixed RT (buoyant) and KH (shear) instability and Atwood numbers ranging up to 0.71 using the same governing equations as for our present study They focused on early times when complicated interactions between the instabilities produce complex effects on the growth rate. This is followed by appendices addressing (a) the relationship between density profiles and mean cross-stream velocity and (b) contrasts between the present variable-composition flow and variable-thermodynamic-property flow

Simulation approach
Governing equations
Notations
Numerical approach
Domain size
Initial conditions
Mean velocity and density profiles
Initial disturbance
Viscosity and diffusivity
Basic definitions and theoretical flow properties
Conservation properties
Self-similarity
Thickness definitions
Time evolution of mean profiles and thickness growth
Determining the time interval of self-similar growth
Time-averaged self-similar statistical profiles
Velocity fluctuation intensity profiles
Analysis of thickness growth rate during self-similar growth
Profiles involving density fluctuations
Conditional statistics
Findings
Conclusions
Full Text
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