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A decoupled mechanism of interface growth in single-mode hydrodynamic instabilities

Published online by Cambridge University Press:  02 June 2023

Changwen Liu
Affiliation:
HEDPS, Center for Applied Physics and Technology, College of Engineering, Peking University,Beijing 100871, PR ChinaState Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University, Beijing 100871, PR China
Hongzhi Wu-Wang
Affiliation:
State Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University, Beijing 100871, PR China
Yousheng Zhang*
Affiliation:
HEDPS, Center for Applied Physics and Technology, College of Engineering, Peking University,Beijing 100871, PR ChinaInstitute of Applied Physics and Computational Mathematics, Beijing 100094, PR China
Zuoli Xiao*
Affiliation:
HEDPS, Center for Applied Physics and Technology, College of Engineering, Peking University,Beijing 100871, PR ChinaState Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University, Beijing 100871, PR ChinaNanchang Innovation Institute, Peking University, Nanchang 330008, PR China
*
†Email addresses for correspondence: zhang_yousheng@iapcm.ac.cn, z.xiao@pku.edu.cn
†Email addresses for correspondence: zhang_yousheng@iapcm.ac.cn, z.xiao@pku.edu.cn

Abstract

One of the most significant issues in hydrodynamic interfacial instabilities is the growth rate of the interfacial perturbations, which plays an important role in both scientific research (e.g. supernova explosion) and engineering applications (e.g. inertial confinement fusion). Yet the underlying mechanisms of such flow phenomena remain unclear or controversial. In this paper the decoupled mechanisms of two effects are found to dominate the interface growth of the single-mode Rayleigh–Taylor instability (RTI) and Richtmyer–Meshkov instability (RMI) via Layzer's potential-flow model. One is the inertial effect induced by the interfacial density gradient and the acceleration, and the other is the frontal distortion effect stemming from interface shape evolution. The former determines the dominant features of interface evolution, while the latter influences the local concavity and convexity of growth rate such as the overshoot phenomenon. These two effects can be approximated as a linearly decoupled analytical solution if their nonlinear interaction term is neglected. With the decoupled solution, the theoretical growth rates agree well with high-fidelity numerical simulation results. The present result indicates that the long-time evolution of fluid interface in both RTI and RMI at all density ratios can be accurately predicted if both inertia and frontal distortion effects are taken into account. Furthermore, the strong dependence of instability evolution on initial amplitude is quantified based on the effects of decoupling, which sheds light on the physical origin of the overshoot phenomenon.

Information

Type
JFM Papers
Copyright
© The Author(s), 2023. Published by Cambridge University Press
Figure 0

Figure 1.Schematic of different development stages of RTI based on the numerical result from Wei & Livescu (2012) and sketch map from Zhang & Guo (2016).

Figure 1

Figure 2.The budget of (2.11) for (a) ${A=0.3}$ and (b) ${A=0.7}$. All terms are normalized by the maximum absolute value of gravitational acceleration term ${F_5 g}$.

Figure 2

Figure 3.Evolutions of the RTI bubble growth rate (a,c,e) and spike growth rate (b,d,f) at $A=0.05$, $0.3$ and $0.7$, which are described by the inertial effect (black solid lines), frontal distortion effect (pink dash-dotted lines) and the total growth rate with combined effects (blue dashed lines), respectively. The results from the DS model (Liu et al.2023) (red dotted lines) and numerical simulation (Sohn 2004) (red circles) are included for comparison. Results are shown for (a) $A=0.05$ (bubble), (b) $A=-0.05$ (spike), (c) $A=0.3$ (bubble),(d) $A=-0.3$ (spike), (e) $A=0.7$ (bubble), (f) $A=-0.7$ (spike).

Figure 3

Figure 4.Evolution of the RMI bubble growth rate (a,c,e) and spike growth rate (b,d,f) with $A=0.3$, $0.7$ and $0.88$, which are described by inertial effect (black solid lines), frontal distortion effect (pink dash-dotted lines) and the total growth rate with combined effects (blue dashed lines), respectively. The results from the DS model (Liu et al.2023) (red dotted lines), numerical simulation (Sohn 2004) (red circles) and numerical results (FLASH) from Dimonte & Ramaprabhu (2010) (‘+’ and ‘$\times$’ signs) are included for comparison. Results are shown for (a) $A=0.3$ (bubble), (b) $A=-0.3$ (spike), (c) $A=0.7$ (bubble), (d) $A=-0.7$ (spike), (e) $A=0.88$ (bubble), (f) $A=-0.88$ (spike).

Figure 4

Figure 5.Evolutions of the RTI bubble growth rate predicted by (a) the DS model (Liu et al.2023) and (b) the decoupled model (3.3) at $A=0.3$. Evolutions of (c) the bubble curvature from the DS model and (d) the frontal distortion effect from the decoupled model are plotted for discussion. The results for different initial curvatures are marked as $\xi ^0=-0.15$ (black dashed lines), $-0.25$ (red solid lines) and $-0.35$ (blue dash-dotted lines). The numerical simulation results from Sohn (2004) at $\xi ^0= -0.25$ (red circles) are also included for comparison. (a) Growth rate (DS model), (b) growth rate (decoupled), (c) curvature, (d) frontal distortion effect.

Figure 5

Figure 6.Evolutions of the RMI bubble growth rate predicted by (a) the DS model (Liu et al.2023) and (b) the decoupled model (3.4) at $A=0.3$. Evolutions of (c) the bubble curvature from the DS model and (d) the frontal distortion effect from the decoupled model are plotted for discussion. The results for different initial curvatures are marked as $\xi ^0=-0.15$ (black dashed lines), $-0.25$ (red solid lines) and $-0.35$ (blue dash-dotted lines). The numerical simulation results from Sohn (2004) at $\xi ^0= -0.25$ (red circles) are also included for comparison. (a) Growth rate (DS model), (b) growth rate (decoupled), (c) curvature, (d) frontal distortion effect.