Hostname: page-component-cb9f654ff-5kfdg Total loading time: 0 Render date: 2025-09-03T05:00:47.835Z Has data issue: false hasContentIssue false

On the evolution of the mixing layer in rotation-driven Rayleigh–Taylor turbulence

Published online by Cambridge University Press:  01 September 2025

Xin Xu
Affiliation:
Department of Modern Mechanics, University of Science and Technology of China, Hefei, Anhui 230026, PR China
Zhiye Zhao*
Affiliation:
Department of Modern Mechanics, University of Science and Technology of China, Hefei, Anhui 230026, PR China Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
Fenghui Lin
Affiliation:
Department of Modern Mechanics, University of Science and Technology of China, Hefei, Anhui 230026, PR China
Pei Wang
Affiliation:
National Key Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Beijing 100094, PR China
Nan-Sheng Liu
Affiliation:
Department of Modern Mechanics, University of Science and Technology of China, Hefei, Anhui 230026, PR China
Xi-Yun Lu
Affiliation:
Department of Modern Mechanics, University of Science and Technology of China, Hefei, Anhui 230026, PR China
*
Corresponding author: Zhiye Zhao, zzy12@ustc.edu.cn

Abstract

The evolution of the mixing layer in rotation-driven Rayleigh–Taylor (RT) turbulence is investigated theoretically and numerically. It is found that the evolution of the turbulent mixing layer in rotation-driven RT turbulence is self-similar, but the width of the mixing layer does not follow the classical quadratic growth observed in planar RT turbulence induced by constant external acceleration. Based on the approach used in cylindrical RT turbulence without rotation (Zhao et al. 2021, Phys. Rev. E, vol. 104, 055104), a theoretical model is established to predict the growth of mixing widths in rotation-driven RT turbulence, and the model’s excellent agreement with direct numerical simulations (DNS) serves to validate its reliability. The model proposes a rescaled time that allows for the unification of the evolutions of the mixing layers in rotation-driven RT turbulence with various Atwood numbers and rotation numbers. It is further identified that the growth law described by the model of rotation-driven RT turbulence can be recovered to quadratic growth when the effects of geometrical curvature, radial inhomogeneity of the centrifugal force, and Coriolis force become negligible. Moreover, based on the DNS results, we find that turbulent mixing layers in rotation-driven RT turbulence cover a wide range of length scales. The strong rotation at the same Atwood number enhances the generation of fine-scale structures but is not conducive to overall fluid mixing within the mixing layer.

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

Abarzhi, S.I. & Sreenivasan, K.R. 2022 Self-similar Rayleigh–Taylor mixing with accelerations varying in time and space. Proc. Natl Acad. Sci. USA 119 (47), e2118589119.10.1073/pnas.2118589119CrossRefGoogle ScholarPubMed
Akula, B., Suchandra, P., Mikhaeil, M. & Ranjan, D. 2017 Dynamics of unstably stratified free shear flows: an experimental investigation of coupled Kelvin–Helmholtz and Rayleigh–Taylor instability. J. Fluid Mech. 816, 619660.10.1017/jfm.2017.95CrossRefGoogle Scholar
Andrews, M.J. & Spalding, D.B. 1990 A simple experiment to investigate two-dimensional mixing by Rayleigh–Taylor instability. Phys. Fluids A 2 (6), 922927.10.1063/1.857652CrossRefGoogle Scholar
Baldwin, K.A., Scase, M.M. & Hill, R.J.A. 2015 The inhibition of the Rayleigh–Taylor instability by rotation. Sci. Rep. 5, 11706.10.1038/srep11706CrossRefGoogle ScholarPubMed
Bodner, S.E. 1974 Rayleigh–Taylor instability and laser-pellet fusion. Phys. Rev. Lett. 33, 761764.10.1103/PhysRevLett.33.761CrossRefGoogle Scholar
Boffetta, G. & Mazzino, A. 2017 Incompressible Rayleigh–Taylor turbulence. Annu. Rev. Fluid Mech. 49, 119143.10.1146/annurev-fluid-010816-060111CrossRefGoogle Scholar
Boffetta, G., Mazzino, A. & Musacchio, S. 2016 Rotating Rayleigh–Taylor turbulence. Phys. Rev. Fluids 1, 054405.10.1103/PhysRevFluids.1.054405CrossRefGoogle Scholar
Buyko, A.M., Garanin, S.F., Mokhov, V.N. & Yakubov, V.B. 1997 Possibility of low-dense magnetized DT plasma ignition threshold achievement in a MAGO system. Laser Part. Beams 15 (1), 127132.10.1017/S0263034600010818CrossRefGoogle Scholar
Cabot, W. & Zhou, Y. 2013 Statistical measurements of scaling and anisotropy of turbulent flows induced by Rayleigh–Taylor instability. Phys. Fluids 25 (1), 015107.10.1063/1.4774338CrossRefGoogle Scholar
Cabot, W.H. & Cook, A.W. 2006 Reynolds number effects on Rayleigh–Taylor instability with possible implications for type Ia supernovae. Nat. Phys. 2 (8), 562568.10.1038/nphys361CrossRefGoogle Scholar
Caproni, A., Lanfranchi, G.A., da Silva, A.L. & Falceta-Gonçalves, D. 2015 Three-dimensional hydrodynamical simulations of the supernovae-driven gas loss in the dwarf spheroidal galaxy Ursa Minor. Astrophys. J. 805, 109.10.1088/0004-637X/805/2/109CrossRefGoogle Scholar
Carnevale, G.F., Orlandi, P., Zhou, Y. & Kloosterziel, R.C. 2002 Rotational suppression of Rayleigh–Taylor instability. J. Fluid Mech. 457, 181190.10.1017/S0022112002007772CrossRefGoogle Scholar
Ceci, A. & Pirozzoli, S. 2025 Direct numerical simulation study of turbulent pipe flow with imposed radial rotation. J. Fluid Mech. 1004, A15.10.1017/jfm.2024.1172CrossRefGoogle Scholar
Cherfils, C. & Mikaelian, K.O. 1996 Simple model for the turbulent mixing width at an ablating surface. Phys. Fluids 8 (2), 522535.10.1063/1.868805CrossRefGoogle Scholar
Cook, A.W., Cabot, W. & Miller, P.L. 2004 The mixing transition in Rayleigh–Taylor instability. J. Fluid Mech. 511, 333362.10.1017/S0022112004009681CrossRefGoogle Scholar
Cook, A.W. & Dimotakis, P.E. 2001 Transition stages of Rayleigh–Taylor instability between miscible fluids. J. Fluid Mech. 443, 6999.10.1017/S0022112001005377CrossRefGoogle Scholar
Cook, A.W. & Zhou, Y. 2002 Energy transfer in Rayleigh–Taylor instability. Phys. Rev. E 66 (2), 026312.10.1103/PhysRevE.66.026312CrossRefGoogle ScholarPubMed
Cui, A.Q. & Street, R.L. 2004 Large-eddy simulation of coastal upwelling flow. Environ. Fluid Mech. 4, 197223.10.1023/B:EFMC.0000016610.05554.0fCrossRefGoogle Scholar
Dimonte, G. 2000 Spanwise homogeneous buoyancy-drag model for Rayleigh–Taylor mixing and experimental evaluation. Phys. Plasmas 7 (6), 22552269.10.1063/1.874060CrossRefGoogle Scholar
Dimotakis, P.E. 2000 The mixing transition in turbulent flows. J. Fluid Mech. 409, 6998.10.1017/S0022112099007946CrossRefGoogle Scholar
Ecke, R.E. & Shishkina, O. 2023 Turbulent rotating Rayleigh–Bénard convection. Annu. Rev. Fluid Mech. 55 (1), 603638.10.1146/annurev-fluid-120720-020446CrossRefGoogle Scholar
Fu, C.-Q., Zhao, Z., Wang, P., Liu, N.-S., Wan, Z.-H. & Lu, X.-Y. 2023 Bubble re-acceleration behaviours in compressible Rayleigh–Taylor instability with isothermal stratification. J. Fluid Mech. 954, A16.10.1017/jfm.2022.1003CrossRefGoogle Scholar
Fu, C.-Q., Zhao, Z.-Y., 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 (2), 023902.10.1103/PhysRevFluids.7.023902CrossRefGoogle 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
Ge, J., Zhang, X.-T., Li, H.-F. & Tian, B.-L. 2020 Late-time turbulent mixing induced by multimode Richtmyer–Meshkov instability in cylindrical geometry. Phys. Fluids 32 (12), 124116.10.1063/5.0035603CrossRefGoogle Scholar
Gelfand, J.D., Slane, P.O. & Zhang, W.-Q. 2009 A dynamical model for the evolution of a pulsar wind nebula inside a nonradiative supernova remnant. Astrophys. J. 703, 20512067.10.1088/0004-637X/703/2/2051CrossRefGoogle Scholar
Guo, H.-Y., Yu, X.-J., Wang, L.-F., Ye, W.-H., Wu, J.-F. & Li, Y.-J. 2014 On the second harmonic generation through bell–Plesset effects in cylindrical geometry. Chin. Phys. Lett. 31 (4), 044702.10.1088/0256-307X/31/4/044702CrossRefGoogle Scholar
Hillier, A. 2020 Self-similar solutions of asymmetric Rayleigh–Taylor mixing. Phys. Fluids 32 (1), 015103.10.1063/1.5130893CrossRefGoogle Scholar
Hinds, W.C., Ashley, A., Kennedy, N.J. & Bucknam, P. 2002 Conditions for cloud settling and Rayleigh–Taylor instability. Aerosol Sci. Technol. 36, 11281138.10.1080/02786820290108449CrossRefGoogle Scholar
Hu, R.-N., Li, X.-L. & Yu, C.-P. 2024 Effects of streamwise rotation on helicity and vortex in channel turbulence. J. Fluid Mech. 980, A50.10.1017/jfm.2024.37CrossRefGoogle Scholar
Huneault, J., Plant, D. & Higgins, A.J. 2019 Rotational stabilisation of the Rayleigh–Taylor instability at the inner surface of an imploding liquid shell. J. Fluid Mech. 873, 531567.10.1017/jfm.2019.346CrossRefGoogle Scholar
Jiang, H.-C., Wang, D.-P., Liu, S. & Sun, C. 2022 Experimental evidence for the existence of the ultimate regime in rapidly rotating turbulent thermal convection. Phys. Rev. Lett. 129 (20), 204502.10.1103/PhysRevLett.129.204502CrossRefGoogle ScholarPubMed
Jiang, H.-C., Zhu, X.-J., Wang, D.-P., Huisman, S.G. & Sun, C. 2020 Supergravitational turbulent thermal convection. Sci. Adv. 6 (40), eabb8676.10.1126/sciadv.abb8676CrossRefGoogle ScholarPubMed
Kord, A. & Capecelatro, J. 2019 Optimal perturbations for controlling the growth of a Rayleigh–Taylor instability. J. Fluid Mech. 876, 150185.10.1017/jfm.2019.532CrossRefGoogle Scholar
Lavacot, D.-L., Liu, J., Williams, H., Morgan, B.E. & Mani, A. 2024 Non-locality of mean scalar transport in two-dimensional Rayleigh–Taylor instability using the macroscopic forcing method. J. Fluid Mech. 985, A47.10.1017/jfm.2024.323CrossRefGoogle Scholar
Liu, W.-H., Yu, C.-P., Ye, W.-H. & Wang, L.-F. 2014 Nonlinear saturation amplitude of cylindrical Rayleigh–Taylor instability. Chin. Phys. B 23 (9), 094502.10.1088/1674-1056/23/9/094502CrossRefGoogle 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. Lond. A, 371(2003), 20120185.Google Scholar
Livescu, D., Wei, T. & Brady, P.T. 2021 Rayleigh–Taylor instability with gravity reversal. Physica D 417, 132832.10.1016/j.physd.2020.132832CrossRefGoogle Scholar
Luo, T.-F. & Wang, J.-C. 2021 Effects of Atwood number and stratification parameter on compressible multi-mode Rayleigh–Taylor instability. Phys. Fluids 33, 115111.10.1063/5.0071437CrossRefGoogle Scholar
Olson, D.H. & Jacobs, J.W. 2009 Experimental study of Rayleigh–Taylor instability with a complex initial perturbation. Phys. Fluids 21 (3), 034103.10.1063/1.3085811CrossRefGoogle Scholar
Rayleigh, L. 1882 Investigation of the character of the equilibrium of an incompressible heavy fluid of variable density. Proc. R. Math. Soc. s1-14, 170177.10.1112/plms/s1-14.1.170CrossRefGoogle Scholar
Read, K.I. 1984 Experimental investigation of turbulent mixing by Rayleigh–Taylor instability. Physica D 12 (1–3), 4558.10.1016/0167-2789(84)90513-XCrossRefGoogle Scholar
Reckinger, S.J., Livescu, D. & Vasilyev, O.V. 2016 Comprehensive numerical methodology for direct numerical simulations of compressible Rayleigh–Taylor instability. J. Comput. Phys. 313, 181208.10.1016/j.jcp.2015.11.002CrossRefGoogle Scholar
Ristorcelli, J.R. & Clark, T.T. 2004 Rayleigh–Taylor turbulence: self-similar analysis and direct numerical simulations. J. Fluid Mech. 507, 213253.10.1017/S0022112004008286CrossRefGoogle Scholar
Scase, M.M., Baldwin, K.A. & Hill, R.J.A. 2017 Rotating Rayleigh–Taylor instability. Fluids 2, 024801.Google Scholar
Scase, M.M., Baldwin, K.A. & Hill, R.J.A. 2020 Magnetically induced Rayleigh–Taylor instability under rotation: comparison of experimental and theoretical results. Phys. Rev. E 102, 043101.10.1103/PhysRevE.102.043101CrossRefGoogle ScholarPubMed
Scase, M.M. & Hill, R.J.A. 2018 Centrifugally forced Rayleigh–Taylor instability. J. Fluid Mech. 852, 543577.10.1017/jfm.2018.539CrossRefGoogle Scholar
Scase, M.M. & Sengupta, S. 2021 Cylindrical rotating Rayleigh–Taylor instability. J. Fluid Mech. 907, A33.10.1017/jfm.2020.842CrossRefGoogle Scholar
Schultz, D.M., et al. 2006 The mysteries of mammatus clouds: observations and formation mechanisms. J. Atmos. Sci. 63, 24092435.10.1175/JAS3758.1CrossRefGoogle Scholar
Suchandra, P. & Ranjan, D. 2023 Dynamics of multilayer Rayleigh–Taylor instability at moderately high Atwood numbers. J. Fluid Mech. 974, A35.10.1017/jfm.2023.689CrossRefGoogle Scholar
Tao, J.-J., He, X.-T., Ye, W.-H. & Busse, F.H. 2013 Nonlinear Rayleigh–Taylor instability of rotating inviscid fluids. Phys. Rev. E 87, 013001.10.1103/PhysRevE.87.013001CrossRefGoogle ScholarPubMed
Taylor, G.I. 1950 The instability of liquid surfaces when accelerated in a direction perpendicular to their planes. I. Proc. R. Soc. Lond. A 201, 192196.Google Scholar
Teng, H., Liu, N.-S., Lu, X.-Y. & Khomami, B. 2015 Direct numerical simulation of Taylor–Couette flow subjected to a radial temperature gradient. Phys. Fluids 27 (12), 125101.10.1063/1.4935700CrossRefGoogle Scholar
Tritschler, V.K., Zubel, M., Hickel, S. & Adams, N.A. 2014 Evolution of length scales and statistics of Richtmyer–Meshkov instability from direct numerical simulations. Phys. Rev. E 90 (6), 063001.10.1103/PhysRevE.90.063001CrossRefGoogle ScholarPubMed
Wang, L.-F., Wu, J.-F., Ye, W.-H., Zhang, W.-Y. & He, X.-T. 2013 Weakly nonlinear incompressible Rayleigh–Taylor instability growth at cylindrically convergent interfaces. Phys. Plasmas 20 (4), 042708.10.1063/1.4803067CrossRefGoogle Scholar
Wei, Y.-K., Li, Y.-M., Wang, Z.-D., Yang, H., Zhu, Z.-C., Qian, Y.-H. & Luo, K.-H. 2022 Small-scale fluctuation and scaling law of mixing in three-dimensional rotating turbulent Rayleigh–Taylor instability. Phys. Rev. E 105, 015103.10.1103/PhysRevE.105.015103CrossRefGoogle ScholarPubMed
Woosley, S.E., Wunsch, S. & Kuhlen, M. 2004 Carbon ignition in type Ia supernovae: an analytic model. Astrophys. J. 607 (2), 921.10.1086/383530CrossRefGoogle Scholar
Yang, Y.-L., Wang, C.-L., Guo, R. & Zhang, M.-Q. 2023 Numerical analyses of the flow past a short rotating cylinder. J. Fluid Mech. 975, A15.10.1017/jfm.2023.840CrossRefGoogle Scholar
Yao, Z.-Z., Emran, M.S., Teimurazov, A. & Shishkina, O. 2025 Direct numerical simulations of centrifugal convection: from gravitational to centrifugal buoyancy dominance. Intl J. Heat Mass Transfer 236, 126314.10.1016/j.ijheatmasstransfer.2024.126314CrossRefGoogle Scholar
Yeung, P.-K. & Pope, S.B. 1989 Lagrangian statistics from direct numerical simulations of isotropic turbulence. J. Fluid Mech. 207, 531586.10.1017/S0022112089002697CrossRefGoogle Scholar
Youngs, D.L. 1984 Numerical simulation of turbulent mixing by Rayleigh–Taylor instability. Physica D 12 (1), 3244.10.1016/0167-2789(84)90512-8CrossRefGoogle Scholar
Youngs, D.L. 2013 The density ratio dependence of self-similar Rayleigh–Taylor mixing. Phil. Trans R. Soc. Lond. A, 371(2003), 20120173.Google ScholarPubMed
Yuan, M., Zhao, Z.-Y., Liu, L.-Q., Wang, P., Liu, N.-S. & Lu, X.-Y. 2023 Instability evolution of a shock-accelerated thin heavy fluid layer in cylindrical geometry. J. Fluid Mech. 969, A6.10.1017/jfm.2023.555CrossRefGoogle Scholar
Zhang, H., Betti, R., Yan, R. & Aluie, H. 2020 Nonlinear bubble competition of the multimode ablative Rayleigh–Taylor instability and applications to inertial confinement fusion. Phys. Plasmas 27 (12), 122701.10.1063/5.0023541CrossRefGoogle Scholar
Zhang, Z.-P. & Wang, B.-C. 2024 Direct numerical simulation of turbulent flow and structures in a circular pipe subjected to axial system rotation. J. Fluid Mech. 1000, A1.10.1017/jfm.2024.649CrossRefGoogle Scholar
Zhao, D.-X., 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, Z.-Y., Liu, N.-S. & Lu, X.-Y. 2020 a Kinetic energy and enstrophy transfer in compressible Rayleigh–Taylor turbulence. J. Fluid Mech. 904, A37.10.1017/jfm.2020.700CrossRefGoogle Scholar
Zhao, Z.-Y., Wang, P., Liu, N.-S. & Lu, X.-Y. 2020 b Analytical model of nonlinear evolution of single-mode Rayleigh–Taylor instability in cylindrical geometry. J. Fluid Mech. 900, A24.10.1017/jfm.2020.526CrossRefGoogle Scholar
Zhao, Z.-Y., Wang, P., Liu, N.-S. & Lu, X.-Y. 2021 Scaling law of mixing layer in cylindrical Rayleigh–Taylor turbulence. Phys. Rev. E 104 (5), 055104.10.1103/PhysRevE.104.055104CrossRefGoogle ScholarPubMed
Zhong, J., Wang, D.-P. & Sun, C. 2023 From sheared annular centrifugal Rayleigh–Bénard convection to radially heated Taylor–Couette flow: exploring the impact of buoyancy and shear on heat transfer and flow structure. J. Fluid Mech. 972, A29.10.1017/jfm.2023.730CrossRefGoogle Scholar
Zhou, Q. 2013 Temporal evolution and scaling of mixing in two-dimensional Rayleigh–Taylor turbulence. Phys. Fluids 25 (8), 085107.10.1063/1.4818554CrossRefGoogle Scholar
Zhou, Y. 2017 a Rayleigh–Taylor and Richtmyer–Meshkov instability induced flow, turbulence, and mixing I. Phys. Rep. 720, 1136.Google Scholar
Zhou, Y. 2017 b Rayleigh–Taylor and Richtmyer–Meshkov instability induced flow, turbulence, and mixing II. Phys. Rep. 723, 1160.Google Scholar
Zhou, Y., Cabot, W.H. & Thornber, B. 2016 Asymptotic behavior of the mixed mass in Rayleigh–Taylor and Richtmyer–Meshkov instability induced flows. Phys. Plasmas 23 (5), 052712.10.1063/1.4951018CrossRefGoogle Scholar
Zhu, Y.-B., Song, J.-X., Lin, F.-H., Liu, N.-S., Lu, X.-Y. & Khomami, B. 2022 Relaminarization of spanwise-rotating viscoelastic plane Couette flow via a transition sequence from a drag-reduced inertial to a drag-enhanced elasto-inertial turbulent flow. J. Fluid Mech. 931, R7.10.1017/jfm.2021.1009CrossRefGoogle Scholar