Advection versus diffusion in Richtmyer-Meshkov mixing

Doss, F. W.

doi:10.1016/j.physleta.2022.127976

Cited by 1 publication

(3 citation statements)

References 59 publications

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“…For the flux difference splitting technique, the Harten-Lax-van Leer-Contact (HLLC) approximate Riemann solver is employed to calculate the flux at the midpoint, which is based on the three-wave assumption and suitable for multi-component compressible flows (Toro 2019). The wave speeds estimation method of Einfeldt et al (1991) and the pressure-control technique of Xie et al (2019) are used for the HLLC. The spatial derivatives of fluxes are calculated by the robust sixth-order midpoint-and-node-to-node difference scheme of Deng et al (2015).…”

Section: Methodsmentioning

confidence: 99%

“…By applying mathematical analysis of partial differential equations, Doss (2022) examined the mass transport within a decaying turbulence field, which is a specific critical class balanced between wave-like convection and heat-like diffusion. The author then extended this theory to the RM turbulence, obtaining a relationship between the molecular mixing fraction and the diffusion parameter : where is the Monin constant (Pope 1994) and .…”

Section: Characteristics Of the Mixing Layermentioning

confidence: 99%

“…The author then extended this theory to the RM turbulence, obtaining a relationship between the molecular mixing fraction and the diffusion parameter : where is the Monin constant (Pope 1994) and . Although models (3.14) and (3.15) are developed with two different methods and assumptions, they can match if the free parameters of one model are adjusted to the conventions of the other (Doss 2022). The connection between and for the three cases at the plateau stage is given in figure 10, where the prediction curves of models (3.14) and (3.15) are also provided.…”

Section: Characteristics Of the Mixing Layermentioning

confidence: 99%

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Mixing and inter-scale energy transfer in Richtmyer–Meshkov turbulence

Zhou,

Ding,

Cheng

2024

J. Fluid Mech.

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This work investigates the compressible turbulence induced by Richtmyer–Meshkov (RM) instability using high-resolution Navier–Stokes simulations. Special attention is paid to the characteristics of RM turbulence including the mixing width growth, the turbulent kinetic energy (TKE) decay, the mixing degree, inhomogeneity and anisotropy. Three distinct initial perturbation spectra are designed at the interface to reveal the initial condition imprint on the RM turbulence. Results show that cases with initial large-scale perturbations present a stronger imprint on statistical characteristics and also a quicker growth of mixing width, whereas cases with small-scale perturbations present a faster TKE decay, greater mixing level, higher isotropy and homogeneity. A thorough analysis on the inter-scale energy transfer in RM turbulence is also presented with the coarse-graining approach that exposes the two subfilter-scale (SFS) energy fluxes (i.e. deformation work and baropycnal work). A strong correlation between the nonlinear model of baropycnal work (Fluids, 4(2), 2019) and the simulation results is confirmed for the first time, demonstrating its potential in modelling the RM turbulence. Two primary mechanisms of baropycnal work (the straining and baroclinic generation processes) are explored with this nonlinear model. The evolutions of two SFS energy fluxes exhibit distinct behaviours at various filter scales, in different flow regions and under various flow motions (strain and rotation). It is found that all three cases share the common inter-scale energy transfer dynamics, which is important for modelling the RM turbulence.

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