Self-similar scaling of variable-density Rayleigh-Taylor turbulence
Abstract
The dynamics of self-similar Rayleigh-Taylor (RT) mixing layers are investigated across a broad range of Atwood and Reynolds numbers using the statistically stationary Rayleigh-Taylor (SRT) flow configuration - a computational framework that enables simulation of self-similar RT flows at reduced cost compared to conventional temporally growing mixing layers. Normalizations are developed for all dominant non-transport terms in the continuity, mixed mass, and turbulent kinetic energy budgets in terms of the input parameters: the mixing layer height , gravitational acceleration , and fluid densities and . Most normalized quantities collapse well across the parameter space. In some cases, variations in the Atwood number (or equivalently, the density ratio ) lead to consistent integral magnitudes but spatially shifted profiles. These shifts are primarily related to a division by density and are similarly observed in the analytical solution of the one-dimensional variable-density diffusion problem. The analysis introduces a reference density for the mixed mass, examines trends in Favre-averaged statistics, and derives a scaling law for the growth rate of the mixing layer. For height definitions encompassing the full extent of the layer, the conventional growth parameter, , varies with Atwood number. Our analysis leads to an alternative formulation using an effective Atwood number, , that is consistent with the scaling proposed by Belen'kii & Fradkin (Trudy FIAN, vol. 29, 1965, pp. 207-238). The corresponding growth parameter, , remains nearly constant across all Atwood numbers considered, offering a unified scaling for variable-density RT flows.
Keywords
Cite
@article{arxiv.2511.10512,
title = {Self-similar scaling of variable-density Rayleigh-Taylor turbulence},
author = {Chian Yeh Goh and Daniel Brito Matehuala and Guillaume Blanquart},
journal= {arXiv preprint arXiv:2511.10512},
year = {2026}
}
Comments
36 pages, 17 figures (52 subfigures in total)