A compressible Reynolds-averaged mixing model considering turbulent entropy and heat flux
Hansong Xie, Tengfei Luo, Yaomin Zhao, Yousheng Zhang, Jianchun Wang

TL;DR
This paper introduces a new compressible RANS mixing model that incorporates turbulent entropy and heat flux to improve prediction accuracy of compressible mixing flows, especially in high-fidelity scenarios.
Contribution
The study develops a novel compressible RANS mixing model with physical corrections, extending previous incompressible models to better predict compressible flow mixing.
Findings
Model accurately predicts compressible mixing flows.
Incorporating turbulent entropy and heat flux improves model performance.
Validations confirm the model's effectiveness in complex scenarios.
Abstract
In typical nature and engineering scenarios, such as supernova explosion and inertial confinement fusion, mixing flows induced by hydrodynamics interfacial instabilities are essentially compressible. Despite their significance, accurate predictive tools for these compressible flows remain scarce. For engineering applications, the Reynolds-averaged Navier-Stokes (RANS) simulation stands out as the most practical approach due to its outstanding computational efficiency. However, the majority of RANS mixing studies reported have concentrated on incompressible scenarios, with quite limited attention given to compressible cases. Moreover, most of the existing RANS mixing models demonstrate significantly inaccurate predictions for compressible mixing flow. This study develops a novel compressible RANS mixing model by incorporating physical compressibility corrections into the incompressible…
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Taxonomy
TopicsLaser-Plasma Interactions and Diagnostics · Combustion and flame dynamics · Computational Fluid Dynamics and Aerodynamics
