Modeling of Rayleigh-Taylor mixing using single-fluid models

Area of Science:

• Fluid Dynamics
• Computational Physics

Background:

• Rayleigh-Taylor (RT) instability drives mixing in various astrophysical and inertial confinement fusion scenarios.
• Accurate modeling of turbulence mixing is crucial for predicting RT flow evolution.

Purpose of the Study:

• To evaluate and compare turbulence mixing models of varying complexity for Rayleigh-Taylor flows.
• To assess the trade-off between model accuracy and computational complexity.
• To provide guidance on selecting appropriate turbulence models for RT simulations.

Main Methods:

• Implementation of four turbulence models (K-L, K-L-a, K-L-a-b, BHR-2) within a consistent numerical framework.
• High-resolution implicit large eddy simulations (ILES) were employed.
• Validation against canonical one-dimensional (1D) RT mixing and a 2D tilted-rig experiment.

Main Results:

• Different model complexities yield varying predictions for Rayleigh-Taylor mixing.
• The Besnard-Harlow-Rauenzahn (BHR-2) model and the four-equation K-L-a-b model show improved accuracy in complex scenarios.
• Simpler models (K-L, K-L-a) may suffice for less demanding applications, but with reduced fidelity.

Conclusions:

• Model selection for Rayleigh-Taylor flows should balance desired accuracy with computational resources.
• The study offers a framework for understanding the performance of different turbulence mixing models.
• Guidance is provided for researchers to choose the most suitable turbulence model based on specific simulation requirements.