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Passive scalar mixing and decay at finite correlation times in the Batchelor regime

Published online by Cambridge University Press:  11 July 2017

Aditya K. Aiyer*
Affiliation:
BITS-Pilani, K. K. Birla Goa campus, Zuarinagar, Goa-403726, India TIFR Centre for Interdisciplinary Sciences Narsingi, Hyderabad 500075, India Department of Mechanical Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA
Kandaswamy Subramanian
Affiliation:
IUCAA, Post Bag 4, Ganeshkhind, Pune 411007, India
Pallavi Bhat
Affiliation:
IUCAA, Post Bag 4, Ganeshkhind, Pune 411007, India Department of Astrophysical Sciences and Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543, USA Plasma Science and Fusion Center, Massachussetts Institute of Technology, Cambridge, MA 02139, USA
*
Email address for correspondence: aditya.kandaswamy@gmail.com

Abstract

An elegant model for passive scalar mixing and decay was given by Kraichnan (Phys. Fluids, vol. 11, 1968, pp. 945–953) assuming the velocity to be delta correlated in time. For realistic random flows this assumption becomes invalid. We generalize the Kraichnan model to include the effects of a finite correlation time, $\unicode[STIX]{x1D70F}$, using renewing flows. The generalized evolution equation for the three-dimensional (3-D) passive scalar spectrum $\hat{M}(k,t)$ or its correlation function $M(r,t)$, gives the Kraichnan equation when $\unicode[STIX]{x1D70F}\rightarrow 0$, and extends it to the next order in $\unicode[STIX]{x1D70F}$. It involves third- and fourth-order derivatives of $M$ or $\hat{M}$ (in the high $k$ limit). For small-$\unicode[STIX]{x1D70F}$ (or small Kubo number), it can be recast using the Landau–Lifshitz approach to one with at most second derivatives of $\hat{M}$. We present both a scaling solution to this equation neglecting diffusion and a more exact solution including diffusive effects. To leading order in $\unicode[STIX]{x1D70F}$, we first show that the steady state 1-D passive scalar spectrum, preserves the Batchelor (J. Fluid Mech., vol. 5, 1959, pp. 113–133) form, $E_{\unicode[STIX]{x1D703}}(k)\propto k^{-1}$, in the viscous–convective limit, independent of $\unicode[STIX]{x1D70F}$. This result can also be obtained in a general manner using Lagrangian methods. Interestingly, in the absence of sources, when passive scalar fluctuations decay, we show that the spectrum in the Batchelor regime at late times is of the form $E_{\unicode[STIX]{x1D703}}(k)\propto k^{1/2}$ and also independent of $\unicode[STIX]{x1D70F}$. More generally, finite $\unicode[STIX]{x1D70F}$ does not qualitatively change the shape of the spectrum during decay. The decay rate is however reduced for finite $\unicode[STIX]{x1D70F}$. We also present results from high resolution ($1024^{3}$) direct numerical simulations of passive scalar mixing and decay. We find reasonable agreement with predictions of the Batchelor spectrum during steady state. The scalar spectrum during decay is however dependent on initial conditions. It agrees qualitatively with analytic predictions when power is dominantly in wavenumbers corresponding to the Batchelor regime, but is shallower when box-scale fluctuations dominate during decay.

Type
Papers
Copyright
© 2017 Cambridge University Press 

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References

Abramowitz, M. & Stegun, I. A. 1972 Handbook of Mathematical Functions, Applied Mathematics Series, vol. 55. National Bureau of Standards.Google Scholar
Adzhemyan, L. T., Antonov, N. V. & Honkonen, J. 2002 Anomalous scaling of a passive scalar advected by the turbulent velocity field with finite correlation time: two-loop approximation. Phys. Rev. E 66 (3), 036313.Google Scholar
Balkovsky, E., Chertkov, M., Kolokolov, I. & Lebedev, V. 1995 Fourth-order correlation function of a randomly advected passive scalar. J. Expl Theor. Phys. Lett. 61, 10491054.Google Scholar
Balkovsky, E. & Fouxon, A. 1999 Universal long-time properties of Lagrangian statistics in the Batchelor regime and their application to the passive scalar problem. Phys. Rev. E 60, 41644174.Google Scholar
Batchelor, G. K. 1959 Small-scale variation of convected quantities like temperature in turbulent fluid. Part 1. General discussion and the case of small conductivity. J. Fluid Mech. 5, 113133.Google Scholar
Bhat, P. & Subramanian, K. 2014 Fluctuation dynamo at finite correlation times and the Kazantsev spectrum. Astrophys. J. 791, L34.Google Scholar
Bhat, P. & Subramanian, K. 2015 Fluctuation dynamos at finite correlation times using renewing flows. J. Plasma Phys. *81 (5). doi:10.1017/S0022377815000616.Google Scholar
Brandenburg, A. 2003 Computational aspects of astrophysical MHD and turbulence. In Advances in Nonlinear Dynamos (ed. Ferriz-Mas, A. & Núñez, M.), pp. 269344. Taylor & Francis.Google Scholar
Brandenburg, A. & Dobler, W. 2002 Hydromagnetic turbulence in computer simulations. Comput. Phys. Commun. 147, 471475.Google Scholar
Chaves, M., Eyink, G., Frisch, U. & Vergassola, M. 2001 Universal decay of scalar turbulence. Phys. Rev. Lett. 86, 23052308.Google Scholar
Chaves, M., Gawedzki, K., Horvai, P., Kupiainen, A. & Vergassola, M. 2003 Lagrangian dispersion in Gaussian self-similar velocity ensembles. J. Stat. Phys. 113 (5), 643692.Google Scholar
Chertkov, M., Falkovich, G., Kolokolov, I. & Lebedev, V. 1995 Statistics of a passive scalar advected by a large-scale two-dimensional velocity field: analytic solution. Phys. Rev. E 51, 56095627.Google Scholar
Chertkov, M., Falkovich, G. & Lebedev, V. 1996 Nonuniversality of the scaling exponents of a passive scalar convected by a random flow. Phys. Rev. Lett. 76, 37073710.Google Scholar
Chertkov, M., Kolokolov, I. & Lebedev, V. 2007 Strong effect of weak diffusion on scalar turbulence at large scales. Phys. Fluids 19 (10), 101703.Google Scholar
Chertkov, M. & Lebedev, V. 2003 Decay of scalar turbulence revisited. Phys. Rev. Lett. 90 (3), 034501.Google Scholar
Corrsin, S. 1951 On the spectrum of isotropic temperature fluctuations in an isotropic turbulence. J. Appl. Phys. 22, 469473.Google Scholar
Davidson, P. A., Kaneda, Y. & Sreenivasan, K. R. 2013 Ten Chapters in Turbulence. Cambridge University Press.Google Scholar
Dittrich, P., Molchanov, S. A., Sokolov, D. D. & Ruzmaikin, A. A. 1984 Mean magnetic field in renovating random flow. Astron. Nachr. 305, 119125.Google Scholar
DLMF 2016 NIST Digital Library of Mathematical Functions (ed. Olver, f. W. J., Olde Daalhuis, A. B., Lozier, D. W., Schneider, B. I., Boisvert, R. F., Clark, C. W., Miller, B. R. & Saunders, B. V.); http://dlmf.nist.gov/, Release 1.0.14 of 2016-12-21.Google Scholar
Donzis, D. A., Sreenivasan, K. R. & Yeung, P. K. 2010 The batchelor spectrum for mixing of passive scalars in isotropic turbulence. Flow Turbul. Combust. 85 (3–4), 549566.Google Scholar
Dunster, T. M. 1990 Bessel functions of purely imaginary order, with an application to second-order linear differential equations having a large parameter. SIAM J. Math. Anal. 21 (4), 9951018.Google Scholar
Eyink, G. L. & Xin, J. 2000 Self-similar decay in the Kraichnan model of a passive scalar. J. Stat. Phys. 100 (3), 679741.CrossRefGoogle Scholar
Falkovich, G., Gawȩdzki, K. & Vergassola, M. 2001 Particles and fields in fluid turbulence. Rev. Mod. Phys. 73, 913975.CrossRefGoogle Scholar
Fouxon, A. & Lebedev, V. 2003 Spectra of turbulence in dilute polymer solutions. Phys. Fluids 15, 20602072.Google Scholar
Gibson, C. H. 1968 Fine structure of scalar fields mixed by turbulence. II. Spectral theory. Phys. Fluids 11, 23162327.Google Scholar
Gilbert, A. D. & Bayly, B. J. 1992 Magnetic field intermittency and fast dynamo action in random helical flows. J. Fluid Mech. 241, 199214.Google Scholar
Gotoh, T., Watanabe, T. & Miura, H. 2014 Spectrum of passive scalar at very high schmidt number in turbulence. Plasma Fusion Res. 9, 3401019.Google Scholar
Gotoh, T. & Yeung, P. K. 2013 Passive scalar transport in turbulence. In Ten Chapters in Turbulence (ed. Davidson, P. A., Kaneda, Y. & Sreenivasan, K. R.). Cambridge University Press.Google Scholar
Gruzinov, A., Cowley, S. & Sudan, R. 1996 Small-scale-field dynamo. Phys. Rev. Lett. 77, 43424345.CrossRefGoogle ScholarPubMed
Haugen, N. E., Brandenburg, A. & Dobler, W. 2004 Simulations of nonhelical hydromagnetic turbulence. Phys. Rev. E 70 (1), 016308.Google Scholar
Holden, H., Karlsen, K. H., Li, K.-A. & Risebro, N. H. 2010 Splitting Methods for Partial Differential Equations with Rough Solutions: Analysis and MATLAB Programs. European Mathematical Society.Google Scholar
Kazantsev, A. P. 1967 Enhancement of a magnetic field by a conducting fluid. J. Expl Theor. Phys. 53, 18071813; (English translation: Sov. Phys. JETP 26, 1968, 1031–1034).Google Scholar
Kolekar, S., Subramanian, K. & Sridhar, S. 2012 Mean-field dynamo action in renovating shearing flows. Phys. Rev. E 86 (2), 026303.Google Scholar
Kraichnan, R. H. 1968 Small-scale structure of a scalar field convected by turbulence. Phys. Fluids 11, 945953.Google Scholar
Kraichnan, R. H. 1974 Convection of a passive scalar by a quasi-uniform random straining field. J. Fluid Mech. 64, 737762.Google Scholar
Kulsrud, R. M. & Anderson, S. W. 1992 The spectrum of random magnetic fields in the mean field dynamo theory of the Galactic magnetic field. Astrophys. J. 396, 606630.Google Scholar
Landau, L. D. & Lifshitz, E. M. 1975 The Classical Theory of Fields. Pergamon.Google Scholar
Nazarenko, S. & Laval, J.-P. 2000 Non-local two-dimensional turbulence and Batchelor’s regime for passive scalars. J. Fluid Mech. 408, 301321.Google Scholar
Obukhov, S. M. 1949 Structure of the temperature field in a turbulent flow. Izv. Akad. Nauk SSSR. Ser. Geogr. Geofiz. 13, 5869.Google Scholar
Schekochihin, A. A., Haynes, P. H. & Cowley, S. C. 2004 Diffusion of passive scalar in a finite-scale random flow. Phys. Rev. E 70 (4), 046304.Google Scholar
Shraiman, B. I. & Siggia, E. D. 2000 Scalar turbulence. Nature 405, 639646.Google Scholar
Son, D. T. 1999 Turbulent decay of a passive scalar in the Batchelor limit: exact results from a quantum-mechanical approach. Phys. Rev. E 59, R3811R3814.Google Scholar
Sreenivasan, K. R. & Schumacher, J. 2010 Lagrangian views on turbulent mixing of passive scalars. Phil. Trans. R. Soc. Lond. A 368, 15611577.Google Scholar
Szmytkowski, R. & Bielski, S. 2010 Comment on the orthogonality of the Macdonald functions of imaginary order. J. Math. Anal. Appl. 365, 195197.CrossRefGoogle Scholar
Vergeles, S. S. 2006 Spatial dependence of correlation functions in the decay problem for a passive scalar in a large-scale velocity field. J. Expl Theor. Phys. 102, 685701.Google Scholar
Warhaft, Z. 2000 Passive scalars in turbulent flows. Annu. Rev. Fluid Mech. 32, 203240.Google Scholar
Zeldovich, Ya. B., Molchanov, S. A., Ruzmaikin, A. A. & Sokoloff, D. D. 1988 Intermittency, diffusion and generation in a nonstationary random medium. Sov. Sci. Rev. C. Math. Phys. 7, 1110.Google Scholar