Hostname: page-component-54dcc4c588-xh45t Total loading time: 0 Render date: 2025-10-02T06:23:41.928Z Has data issue: false hasContentIssue false

A compressible Reynolds-averaged mixing model considering turbulent composition and heat fluxes

Published online by Cambridge University Press:  23 September 2025

Hansong Xie
Affiliation:
HEDPS, Center for Applied Physics and Technology and School of Mechanics and Engineering Science, Peking University, Beijing 100871, PR China
Tengfei Luo
Affiliation:
Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China Center for Ocean Research in Hong Kong and Macau and Division of Environment and Sustainability, Hong Kong University of Science and Technology, Hong Kong, PR China
Yaomin Zhao*
Affiliation:
HEDPS, Center for Applied Physics and Technology and School of Mechanics and Engineering Science, Peking University, Beijing 100871, PR China
Yousheng Zhang*
Affiliation:
HEDPS, Center for Applied Physics and Technology and School of Mechanics and Engineering Science, Peking University, Beijing 100871, PR China Institute of Applied Physics and Computational Mathematics, Beijing 100094, PR China National Key Laboratory of Computational Physics, Beijing 100088, PR China
Jianchun Wang
Affiliation:
Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China
*
Corresponding authors: Yaomin Zhao, yaomin.zhao@pku.edu.cn; Yousheng Zhang, zhang_yousheng@iapcm.ac.cn
Corresponding authors: Yaomin Zhao, yaomin.zhao@pku.edu.cn; Yousheng Zhang, zhang_yousheng@iapcm.ac.cn

Abstract

In typical nature and engineering scenarios, such as supernova explosion and inertial confinement fusion, mixing flows induced by hydrodynamic 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, existing RANS studies focus primarily on cases where the compressible effect plays an insignificant role in mixing development, with quite limited attention given to scenarios with significant compressibility influence. Moreover, most of the existing RANS mixing models demonstrate significantly inaccurate predictions for the latter. This study develops a novel compressible RANS mixing model by incorporating physical compressibility corrections into the $K$$L$$\gamma$ mixing transition model recently proposed by Xie et al. (J. Fluid Mech. 1002, 2025, A31). Specifically, taking the density-stratified Rayleigh–Taylor mixing flows as representative compressible cases, we first analyse the limitations of the existing model for compressible flows, based on high-fidelity data and local instability criteria. Subsequently, the equation of state for a perfect gas is employed to derive comprehensive compressibility corrections. The crucial turbulent composition and heat fluxes are integrated into the closure of the key turbulent mass flux term of the turbulent kinetic energy equation. These corrections enable the model to accurately depict compressible mixing flows. Systematic validations confirm the efficacy of the proposed modelling scheme. This study offers a promising strategy for modelling compressible mixing flows, paving the way for more accurate predictions in complex scenarios.

Information

Type
JFM Papers
Copyright
© The Author(s), 2025. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Chandrasekhar, S. 1961 Hydrodynamic and Hydromagnetic Stability. Oxford-Clarendon Press and New York-Oxford University Press.Google Scholar
Chassaing, P., Antonia, R., Anselmet, F., Joly, L. & Sarkar, S. 2002 Variable Density Fluid Turbulence. Imprint: Springer.10.1007/978-94-017-0075-7CrossRefGoogle Scholar
Cloutman, L.D. 1987 A new estimate of the mixing length and convective overshooting in massive stars. Astrophys. J. 313, 699710.10.1086/165008CrossRefGoogle Scholar
Cloutman, L.D. 2003 Compressibility corrections to closure approximations for turbulent flow simulations. Tech. Rep., Lawrence Livermore National Lab. (LLNL).10.2172/15004305CrossRefGoogle Scholar
Craxton, R.S. et al. 2015 Direct-drive inertial confinement fusion: a review. Phys. Plasmas 22 (11), 110501.10.1063/1.4934714CrossRefGoogle Scholar
Denissen, N., Rollin, B., Reisner, J. & Andrews, M. 2014 The tilted rocket rig: a Rayleigh–Taylor test case for RANS models. J. Fluids Engng 136, 091301.10.1115/1.4027776CrossRefGoogle Scholar
Dimonte, G. & Tipton, R. 2006 K–l turbulence model for the self-similar growth of the Rayleigh–Taylor and Richtmyer–Meshkov instabilities. Phys. Fluids 18 (8), 85101.10.1063/1.2219768CrossRefGoogle Scholar
Fu, C.-Q., Zhao, Z., Xu, X., Wang, P., Liu, N.-S., Wan, Z.-H. & Lu, X.-Y. 2022 Nonlinear saturation of bubble evolution in a two-dimensional single-mode stratified compressible Rayleigh–Taylor instability. Phys. Rev. Fluids 7, 023902.CrossRefGoogle Scholar
Gamalii, E.G., Rozanov, V.B., Samarskii, A.A., Tishkin, V.F., Tyurina, N.N. & Favorskii, A.P. 1980 Hydrodynamic stability of compression of spherical laser targets. Sov. Phys. JETP 52, 230237.Google Scholar
Gauthier, S. 2013 Compressibility effects in Rayleigh–Taylor flows: influence of the stratification. Phys. Scr. 2013(T155), 014012.10.1088/0031-8949/2013/T155/014012CrossRefGoogle Scholar
Gauthier, S. 2017 Compressible Rayleigh–Taylor turbulent mixing layer between Newtonian miscible fluids. J. Fluid Mech. 830, 211256.10.1017/jfm.2017.565CrossRefGoogle Scholar
Gauthier, S. & Le Creurer, B. 2010 Compressibility effects in Rayleigh–Taylor instability-induced flows. Phil. Trans. R. Soc. A 368 (1916), 16811704,CrossRefGoogle ScholarPubMed
George, E. & Glimm, J. 2005 Self-similarity of Rayleigh–Taylor mixing rates. Phys. Fluids 17 (5), 054101.CrossRefGoogle Scholar
Helmholtz, V. 1868 On discontinuous movements of fluids. Lond. Edinburgh Dublin Phil. Mag. J. Sci. 36 (244), 337346.10.1080/14786446808640073CrossRefGoogle Scholar
Jin, H., Liu, X.F., Lu, T., Cheng, B., Glimm, J. & Sharp, D.H. 2005 Rayleigh–Taylor mixing rates for compressible flow. Phys. Fluids 17 (2), 024104.CrossRefGoogle Scholar
Kelvin, L. 1871 Hydrokinetic solutions and observations. Lond. Edinburgh Dublin Phil. Mag. J. Sci. 42 (281), 362377.Google Scholar
Kokkinakis, I.W., Drikakis, D. & Youngs, D.L. 2019 Modeling of Rayleigh–Taylor mixing using single-fluid models. Phys. Rev. E 99, 013104.CrossRefGoogle ScholarPubMed
Kokkinakis, I.W., Drikakis, D. & Youngs, D.L. 2020 Two-equation and multi-fluid turbulence models for Richtmyer–Meshkov mixing. Phys. Fluids 32 (7), 074102.CrossRefGoogle Scholar
Kokkinakis, I.W., Drikakis, D., Youngs, D.L. & Williams, R.J.R. 2015 Two-equation and multi-fluid turbulence models for Rayleigh–Taylor mixing. Intl J. Heat Fluid Flow 56, 233250.10.1016/j.ijheatfluidflow.2015.07.017CrossRefGoogle Scholar
Li, H., He, Z., Zhang, Y. & Tian, B. 2019 On the role of rarefaction/compression waves in Richtmyer–Meshkov instability with reshock. Phys. Fluids 31 (5), 054102.CrossRefGoogle Scholar
Livescu, D. 2004 Compressibility effects on the Rayleigh–Taylor instability growth between immiscible fluids. Phys. Fluids 16 (1), 118127.10.1063/1.1630800CrossRefGoogle Scholar
Livescu, D. 2013 Numerical simulations of two-fluid turbulent mixing at large density ratios and applications to the Rayleigh–Taylor instability. Phil. Trans. R. Soc. A 371 (2003), 20120185.CrossRefGoogle Scholar
Luo, T., Li, Z., Yuan, Z., Peng, W., Liu, T., Wang, L. & Wang, J. 2024, Fourier neural operator for large eddy simulation of compressible Rayleigh–Taylor turbulence. Phys. Fluids 36 (7), 075165.CrossRefGoogle Scholar
Luo, T. & Wang, J. 2022 Mixing and energy transfer in compressible Rayleigh–Taylor turbulence for initial isothermal stratification. Phys. Rev. Fluids 7, 104608.CrossRefGoogle Scholar
Mellado, J.P., Sarkar, S. & Zhou, Y. 2005 Large-eddy simulation of Rayleigh–Taylor turbulence with compressible miscible fluids. Phys. Fluids 17 (7), 076101.CrossRefGoogle Scholar
Meshkov, E.E. 1969 Instability of the interface of two gases accelerated by a shock wave. Fluid Dyn. 4 (5), 101104.10.1007/BF01015969CrossRefGoogle Scholar
Morán-López, J. & Schilling, O. 2013 Multicomponent Reynolds-averaged Navier–Stokes simulations of reshocked Richtmyer–Meshkov instability-induced mixing. High Energy Density Phys. 9, 112121.CrossRefGoogle Scholar
Morgan, B. & Greenough, J. 2016 Large-eddy and unsteady RANS simulations of a shock-accelerated heavy gas cylinder. Shock Waves 26, 355383.10.1007/s00193-015-0566-3CrossRefGoogle Scholar
Qi, H., He, Z.-W., Xu, A.,-G. & Zhang, Y.-S. 2024 The vortex structure and enstrophy of the mixing transition induced by Rayleigh–Taylor instability. Phys. Fluids 36 (11), 114107.CrossRefGoogle Scholar
Rayleigh, L. 1883 Investigation of the character of the equilibrium of an incompressible heavy fluid of variable density. Proc. R. Soc. Lond. Math. Soc. 201 (1), 170177.Google Scholar
Richtmyer, R.D. 1960 Taylor instability in shock acceleration of compressible fluids. Commun. Pure Appl. Maths 13 (2), 297319.10.1002/cpa.3160130207CrossRefGoogle Scholar
Taylor, G. 1950 The instability of liquid surfaces when accelerated in a direction perpendicular to their planes. I. Proc. R. Soc. Lond. A 201, 1065,–192.Google Scholar
Thornber, B., Drikakis, D., Williams, R.J.R. & Youngs, D. 2008a On entropy generation and dissipation of kinetic energy in high-resolution shock-capturing schemes. J. Comput. Phys. 227 (10), 48534872.CrossRefGoogle Scholar
Thornber, B., Mosedale, A., Drikakis, D., Youngs, D. & Williams, R.J.R. 2008b An improved reconstruction method for compressible flows with low Mach number features. J. Comput. Phys. 227 (10), 48734894.CrossRefGoogle Scholar
Toro, E.F., Spruce, M. & Speares, W. 1994 Restoration of the contact surface in the HLL-riemann solver. Shock Waves 4, 2534.10.1007/BF01414629CrossRefGoogle Scholar
Xiao, M., Hu, Z., Dai, Z. & Zhang, Y. 2022 Experimentally consistent large-eddy simulation of re-shocked Richtmyer–Meshkov turbulent mixing. Phys. Fluids 34 (12), 125125.10.1063/5.0129595CrossRefGoogle Scholar
Xiao, M.-J., Qi, H. & Zhang, Y.-S. 2025 Local transition indicator and modelling of turbulent mixing based on the mixing state. J. Fluid Mech. 1002, A4.10.1017/jfm.2024.1135CrossRefGoogle Scholar
Xiao, M., Zhang, Y. & Tian, B. 2020 Modeling of turbulent mixing with an improved K–l model. Phys. Fluids 32 (9), 092104.10.1063/5.0019363CrossRefGoogle Scholar
Xie, H., Qi, H., Xiao, M., Zhang, Y. & Zhao, Y. 2025 An intermittency based Reynolds-averaged transition model for mixing flows induced by interfacial instabilities. J. Fluid Mech. 1002, A31.10.1017/jfm.2024.1160CrossRefGoogle Scholar
Xie, H., Zhao, Y. & Zhang, Y. 2023 Data-driven nonlinear K–l turbulent mixing model via gene expression programming method. Acta Mechanica Sin. 39 (2), 322315.CrossRefGoogle Scholar
Xie, H.-S., Xiao, M.-J. & Zhang, Y.-S. 2021 a Predicting different turbulent mixing problems with the same k– $\epsilon$ model and model coefficients. AIP Adv. 11 (7), 075213.10.1063/5.0055290CrossRefGoogle Scholar
Xie, H.-S., Xiao, M.-J. & Zhang, Y.-S. 2021 b Unified prediction of turbulent mixing induced by interfacial instabilities via Besnard–Harlow–Rauenzahn-2 model. Phys. Fluids 33 (10), 105123.10.1063/5.0069657CrossRefGoogle Scholar
Xue, C. & Ye, W. 2010 Destabilizing effect of compressibility on Rayleigh–Taylor instability for fluids with fixed density profile. Phys. Plasmas 17 (4), 042705.CrossRefGoogle Scholar
Zhang, Y., He, Z., Xie, H., Xiao, M. & Tian, B. 2020 Methodology for determining coefficients of turbulent mixing model. J. Fluid Mech. 905, A26.10.1017/jfm.2020.726CrossRefGoogle Scholar
Zhao, D., Betti, R. & Aluie, H. 2022 Scale interactions and anisotropy in Rayleigh–Taylor turbulence. J. Fluid Mech. 930, A29.10.1017/jfm.2021.902CrossRefGoogle Scholar
Zhao, R.-H., Xie, H.-S., Xiao, M.-J., Wang, Y.-H. & Zhang, Y.-S. 2025 Four-equation model for unified prediction of turbulent mixing induced by interfacial instabilities. Physica D 480, 134724.10.1016/j.physd.2025.134724CrossRefGoogle Scholar
Zhao, Z., Liu, N.-S. & Lu, X.-Y. 2020 Kinetic energy and enstrophy transfer in compressible Rayleigh–Taylor turbulence. J. Fluid Mech. 904, A37.10.1017/jfm.2020.700CrossRefGoogle Scholar
Zhou, Y. 2017a Rayleigh–Taylor and Richtmyer–Meshkov instability induced flow, turbulence, and mixing. I. Phys. Rep. 720–722, 1136.Google Scholar
Zhou, Y. 2017b Rayleigh–Taylor and Richtmyer–Meshkov instability induced flow, turbulence, and mixing. II. Phys. Rep. 723–725, 1160.Google Scholar