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1 - Small-Scale Statistics and Structure of Turbulence – in the Light of High Resolution Direct Numerical Simulation

Published online by Cambridge University Press:  05 February 2013

Yukio Kaneda
Affiliation:
Center for General Education Aichi Institute of Technology
Koji Morishita
Affiliation:
Kobe University
Peter A. Davidson
Affiliation:
University of Cambridge
Yukio Kaneda
Affiliation:
Aichi Institute of Technology, Japan
Katepalli R. Sreenivasan
Affiliation:
New York University
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Summary

Introduction

Fully developed turbulence is a phenomenon involving huge numbers of degrees of dynamical freedom. The motions of a turbulent fluid are sensitive to small differences in flow conditions, so though the latter are seemingly identical they may give rise to large differences in the motions.1 It is difficult to predict them in full detail.

This difficulty is similar, in a sense, to the one we face in treating systems consisting of an Avogadro number of molecules, in which it is impossible to predict the motions of them all. It is known, however, that certain relations, such as the ideal gas laws, between a few number of variables such as pressure, volume, and temperature are insensitive to differences in the motions, shapes, collision processes, etc. of the molecules.

Given this, it is natural to ask whether there is any such relation in turbulence. In this regard, we recall that fluid motion is determined by flow conditions, such as boundary conditions and forcing. It is unlikely that the motion would be insensitive to the difference in these conditions, especially at large scales. It is also tempting, however, to assume that, in the statistics at sufficiently small scales in fully developed turbulence at sufficiently high Reynolds number, and away from the flow boundaries, there exist certain kinds of relation which are universal in the sense that they are insensitive to the detail of large-scale flow conditions. In fact, this idea underlies Kolmogorov's theory (Kolmogorov, 1941a, hereafter referred as K41), and has been at the heart of many modern studies of turbulence. Hereafter, universality in this sense is referred to as universality in the sense of K41

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Publisher: Cambridge University Press
Print publication year: 2012

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References

Antonia, R. A., Chambers, A. J. and Satyaprakash, B. R. 1981. Reynolds number dependence of high-order moments of the streamwise turbulent velocity derivative. Boundary-Layer Met., 21, 159–171.Google Scholar
Antonia, R. A. and Burattini, P. 2006. Approach to the 4/5 law in homogeneousisotropic turbulence. J. Fluid Mech., 550, 175–184.Google Scholar
Aoyama, T., Ishihara, T., Kaneda, Y., Yokokawa, M., Itakura, K. and Uno, A. 2005. Statistics of energy transfer in high-resolution direct numerical simulation of turbulence in a periodic box. J. Phys. Soc. Jpn., 74, 3202–3212.Google Scholar
Betchov, R. 1956. An inequality concerning the production of vorticity in isotropic turbulence. J. Fluid Mech., 1, 497–504.Google Scholar
Biferale, L. and Procaccia, I. 2005. Anisotropy in turbulent flows and in turbulent transport. Physics Reports, 414, 43–164.Google Scholar
Burgers, J. M. 1948. A mathematical model illustrating the theory of turbulence. Adv. in Appl. Mech., 1, 171–199.Google Scholar
Bustamante, M. D. and Kerr, R. M. 2008. 3D Euler about a 2D symmetry plane. PhysicaD, 237, 1912–1920.Google Scholar
Cerutti, S. and Meneveau, C. 1998. Intermittency and relative scaling of subgrid-scale energy dissipation in isotropic turbulence. Phys. Fluids, 10, 928–937.Google Scholar
Chhabra, A. B. and Sreenivasan, K. R. 1992. Scale-invariant multiplier distributions in turbulence. Phys. Rev. Lett., 68, 2762–2765.Google Scholar
Champagne, F. H. 1978. The fine-scale structure of the turbulent velocity field. J. Fluid Mech., 86, 67–108.Google Scholar
Chen, S., Doolen, G., Herring, J. R., Kraichnan, R. H., Orszag, S. A. and She, Z. -S. 1993. Far-dissipation range of turbulence. Phys. Rev. Lett., 70, 3051–3054.Google Scholar
Danaila, L., Anselmet, F. and Antonia, R. A. 2002. An overview of the effect of large-scale inhomogeneities on small-scale turbulence. Phys. Fluids, 14, 2475–2484.Google Scholar
Davidson, P. A. 2004. Turbulence: An Introduction for Scientists and Engineers. Oxford University Press.
Davidson, P. A., Morishita, K. and Kaneda, Y. 2008. On the generation and flux of enstrophy in isotropic turbulence. J. Turbulence, 9, 42.Google Scholar
Doering, C. R. and Foias, C. 2002. Energy dissipation in body-forced turbulence. J. Fluid Mech., 467, 289–306.Google Scholar
Doering, C. R. 2009. The 3D Navier–Stokes problem. Ann. Rev. Fluid. Mech., 41, 109–128.Google Scholar
Domaradzki, J. A. 1992. Nonlocal triad interactions and the dissipation range of isotropic turbulence. Phys. FluidsA, 4, 2037–2045.Google Scholar
Donnelly, R. J. and Sreenivasan, K. R. 1998. Flow at Ultra-High Reynolds and Rayleigh Numbers: A Status Report. Springer-Verlag.
Donzis, D. A., Sreenivasan, K. R. and Yeung, P. K. 2005. Scalar dissipation rate and dissipative anomaly in isotropic turbulence. J. Fluid Mech., 532, 199–216.Google Scholar
Donzis, D. A., Yeung, P. K. and Sreenivasan, K. R. 2008. Dissipation and enstropy in isotropic turbulence: Resolution effects and scaling in direct numerical simulations. Phys. Fluids, 20, 045108.Google Scholar
Donzis, D. A. and Sreenivasan, K. R. 2010. The bottleneck effect and the Kolmogorov constant in isotropic turbulence. J. Fluid Mech., 657, 171–188.Google Scholar
Donzis, D. A., Sreenivasan, K. R. and Yeung, P. K. 2010. The Batchelor spectrum for mixing of passive scalars in isotropic turbulence. Flow Turbulence Combust, 85, 549–566.Google Scholar
Duchon, J. and Robert, R. 2000. Inertial energy dissipation for weak solutions of incompressible Euler and Navier–Stokes equations. Nonlinearity, 13, 249–255.Google Scholar
Eyink, G. L. 2003. Local 4/5–law and energy dissipation anomaly in turbulence. Nonlinearity, 16, 137–145.Google Scholar
Frisch, U. 1995. Turbulence: the Legacy of A. N. Kolmogorov. Cambridge University Press.
Foias, C., Manley, O. and Sirovich, L. 1990. Empirical and Stokes eigenfunctions and the far-dissipative turbulent spectrum. Phys. FluidsA, 2, 464–467.Google Scholar
Gotoh, T., Kaneda, Y. and Bekki, N. 1988. Numerical-integration of the Lagrangian renormalized approximation. J. Phys. Soc. Jpn., 57, 866–880.Google Scholar
Gotoh, T., Fukayama, D. and Nakano, T. 2002. Velocity field statistics in homogeneous steady turbulence obtained using a high-resolution direct numerical simulation. Phys. Fluids, 14, 1065–1081.Google Scholar
Grant, H. L., Stewart, R. W. and Moilliet, A. 1962. Turbulence spectra in a tidal channel. J. Fluid Mech., 12, 241–268.Google Scholar
Gurvich, A. S. and Yaglom, A. M. 1967. Breakdown of eddies and probability distributions for small-scale turbulence. Phys. Fluids, 10, S59–S65.Google Scholar
Gylfason, A., Ayyalasomayajula, S. and Warhaft, Z. 2004. Intermittency, pressure and acceleration statistics from hot-wire measurements in wind-tunnel turbulence. J. Fluid Mech., 501, 213–229.Google Scholar
Herring, J. R. and Kraichnan, R. H. 1979. A numerical comparison of velocity-based and strain-based Lagrangian-history turbulence approximations. J. Fluid Mech., 91, 581–597.Google Scholar
Hill, R. J. 2002. Possible alternative to R-lambda-scaling of small-scale turbulence statistics. J. Fluid Mech., 463, 403–412.Google Scholar
Hierro, J. and Dopazo, C. 2003. Fourth-order statistical moments of the velocity gradient tensor in homogeneous, isotropic turbulence. Phys. Fluids, 15, 3434–3442.Google Scholar
Hosokawa, I., and Yamamoto, K. 1989. Fine structure of a directly simulated isotropic turbulence. J. Phys. Soc. Jpn., 58, 20–23.Google Scholar
Ishida, T. and Kaneda, Y. 2007. Small-scale anisotropy in magnetohydrodynamic turbulence under a strong uniform magnetic field. Phys. Fluids, 19, 075104.Google Scholar
Ishihara, T. and Kaneda, Y. 1998. Fine-scale structure of thin vortical layers. J. Fluid Mech., 364, 297–318.Google Scholar
Ishihara, T., Yoshida, K. and Kaneda, Y. 2002. Anisotropic velocity correlation spectrum at small scales in a homogeneous turbulent shear flow. Phys. Rev. Lett., 88, 154501.Google Scholar
Ishihara, T., Kaneda, Y., Yokokawa, M., Itakura, K. and Uno, A. 2005. Energy spectrum in the near dissipation range of high resolution direct numerical simulation of turbulence. J. Phys. Soc. Jpn., 74, 1464–1471.Google Scholar
Ishihara, T., Kaneda, Y., Yokokawa, M., Itakura, K. and Uno, A. 2007. Small-scale statistics in high-resolution direct numerical simulation of turbulence: Reynolds number dependence of one-point velocity gradient statistics. J. Fluid Mech., 592, 335–366.Google Scholar
Ishihara, T., Gotoh, T. and Kaneda, Y. 2009. Study of high-Reynolds number isotropic turbulence by direct numerical simulation. Ann. Rev. Fluid Mech., 41, 165–180.Google Scholar
Jiménez, J. 2000. Intermittency and cascades. J. Fluid Mech., 409, 99–120.Google Scholar
Jiménez, J. 2001. Self-similarity and coherence in turbulent cascade. In IUTAM Symposium on Geometry and Statistics of Turbulence, T., Kambe, T., Nakano and T., Miyauchi (eds.), 57–66. Kluwer Academic Publishers.
Jiménez, J., Wray, A. A., Saffman, P. G. and Rogallo, R. S. 1993. The structure of intense vorticity in isotropic turbulence. J. Fluid Mech., 255, 65–90.Google Scholar
Jiménez, J., Moisy, F., Tabeling, P. and Willaime, H. 2001. Scaling and structure in isotropic turbulence. In Intermittency in Turbulent Flows, J. C., Vassilicos (ed.), Cambridge University Press.
Kármán, T. and Howarth, L. 1938. On the statistical theory of isotropic turbulence. Proc. R. Soc. Lond, Ser. A, 164, 192–215.Google Scholar
Kaneda, Y. 1981. Renormalized expansions in the theory of turbulence with the use of the Lagrangian position function. J. Fluid Mech., 107, 131–145.Google Scholar
Kaneda, Y. 1993. Lagrangian and Eulerian time correlations in turbulence. Phys. FluidsA, 5, 2835–2845.Google Scholar
Kaneda, Y. and Ishihara, T. 2006. High-resolution direct numerical simulation of turbulence. J. Turbulence, 7, 20.Google Scholar
Kaneda, Y. and Ishihara, T. 2007. Attempts at a computational science of turbulence. Nagare, 26, 375–383. (in Japanese)Google Scholar
Kaneda, Y. and Morishita, K. 2007. Intermittency of energy dissipation in high-resolution direct numerical simulation of turbulence. J. Phys. Soc. Jpn., 76, 073401.Google Scholar
Kaneda, Y. and Yoshida, K. 2004. Small-scale anisotropy in stably stratified turbulence. New Journal of Physics, 6, 34.Google Scholar
Kaneda, Y., Ishihara, T., Yokokawa, M., Itakura, K. and Uno, A. 2003. Energy dissipation rate and energy spectrum in high resolution direct numerical simulations of turbulence in a periodic box. Phys. Fluids, 15, L21–L24.Google Scholar
Kaneda, Y., Yoshino, J. and Ishihara, T. 2008. Examination of Kolmogorov's 4/5 law by high-resolution direct numerical simulation data of turbulence. J. Phys. Soc. Jpn., 77, 064401.Google Scholar
Kerr, R. M. 1985. Higher-order derivative correlations and the alignment of small-scale structures in isotropic numerical turbulence. J. Fluid Mech., 153, 31–58.Google Scholar
Kholmyansky, M. and Tsinober, A. 2009. On an alternative explanation of anomalous scaling and how well-defined is the concept of inertial range. Physics Lett.A, 373, 2364–2367.Google Scholar
Kida, S. 1993. Tube-like structures in Turbulence. Lecture Notes in Numerical Applied Analysis, 12, 137–159.Google Scholar
Kida, S. and Murakami, Y. 1987. Kolmogorov similarity in freely decaying turbulence. Phys. Fluids, 30, 2030–2039.Google Scholar
Kida, S., Kraichnan, R. H., Rogallo, R. S., Waleffe, F. and Zhou, Y. 1992. Triad Interactions in the Dissipation Range. Proc. CTR Summer Program 1992, 83–99.Google Scholar
Kolmogorov, A. N. 1941a. The local structure of turbulence in incompressible viscous fluid for very large Reynolds numbers. Dokl. Akad. Nauk SSSR, 30, 301–305.Google Scholar
Kolmogorov, A. N. 1941b. On degeneration of isotropic turbulence in an incompressible viscous liquid. Dokl. Akad. Nauk SSSR, 31, 538–540.Google Scholar
Kolmogorov, A. N. 1941c. Dissipation of energy in the locally isotropic turbulence. Dokl. Akad. Nauk SSSR, 32, 16–18.Google Scholar
Kolmogorov, A. N. 1962. A refinement of previous hypotheses concerning the local structure of turbulence in a viscous incompressible fluid at high Reynolds number. J. Fluid Mech., 13, 82–85.CrossRefGoogle Scholar
Kraichnan, R. H. 1959. The structure of isotropic turbulence at very high Reynolds numbers. J. Fluid Mech., 5, 497–543.Google Scholar
Kraichnan, R. H. 1965. Lagrangian-history closure approximation for turbulence. Phys. Fluids, 8, 575–598.Google Scholar
Kraichnan, R. H. 1966. Isotropic turbulence and inertial-range structure. Phys. Fluids, 9, 1728–1752.Google Scholar
Kraichnan, R. H. 1974. On Kolmogorov's inertial-range theories. J. Fluid Mech., 62, 305–330.Google Scholar
Kraichnan, R. H. 1978. A strain-based Lagrangian-history turbulence theory. J. Fluid Mech., 88, 355–367.Google Scholar
Kubo, R. 1966. The fluctuation–dissipation theorem. Rep. Progr. Phys., 29, 255–284.Google Scholar
Küchemann, D. 1965. Reports on IUTAM Symposium on concentrated vortex motions in fluids. J. Fluid Mech., 21, 1–20.Google Scholar
Kurien, S. and Sreenivasan, K. R. 2000. Anisotropic scaling contributions to high-order structure functions in high-Reynolds-number turbulence. Phys. Rev.E, 62, 2206–2212.Google Scholar
Landau, L. D. and Lifshitz, E. M. 1987. Fluid Mechanics, 2nd ed., Pergamon Press.
Leslie, D. C. 1973. Developments in the Theory of Turbulence. Clarendon Press.
Lindborg, E. 1999. Correction to the four-fifths law due to variations of the dissipation. Phys. Fluids, 11, 510–512.Google Scholar
Lohse, D. 1994. Crossover from high to low Reynolds number turbulence. Phys. Rev. Lett., 73, 3223–3226.Google Scholar
Lumley, J. L. 1967. Similarity and the turbulent energy spectrum. Phys. Fluids, 10, 855–858.Google Scholar
Lundgren, T. S. 1982. Strained spiral vortex model for turbulent fine structure. Phys. Fluids, 25, 2193–2203.Google Scholar
Lundgren, T. S. 2003. Linearly forced isotropic turbulence. CTR Annual Research Briefs 2003, 461–473.Google Scholar
Mandelbrot, B. B. 1974. Intermittent turbulence in self-similar cascades: divergence of high moments and dimension of the carrier. J. Fluid Mech., 62, 331–358.Google Scholar
Martínez, D. O., Chen, S., Doolen, G. D., Kraichnan, R. H., Wang, L.-P. and Zhou, Y. 1997. Energy spectrum in the dissipation range of fluid turbulence.J. Plasma Phys., 57, 195–201.Google Scholar
Meneveau, C. and Sreenivasan, K. R. 1991. The multifractal nature of turbulent energy dissipation. J. Fluid Mech., 224, 429–484.Google Scholar
Miyauchi, T. and Tanahashi, M. 2001. Coherent fine scale structure in turbulence. In IUTAM Symp. Geometry and Statistics of Turbulence, T., Kambe, T., Nakano and T., Miyauchi (eds.), 67–76, Kluwer Academoic Publishers.
Moisy, F., Tabeling, P. andWillaime, H. 1999. Kolmogorov equation in a fully developed turbulence experiment. Phys. Rev. Lett., 82, 3993–3997.Google Scholar
Moffatt, H. K., Kida, S. and Ohkitani, K. 1994. Stretched vortices - the sinews of turbulence; large-Reynolds-number asymptotics. J. Fluid Mech., 259, 241–264.Google Scholar
Monin, A. S. and Yaglom, A. M. 1975. Statistical Fluid Mechanics: Mechanics of Turbulence, 2, MIT Press.
Nelkin, M. 1994. Universality and scaling in fully developed turbulence. Adv. Physics, 43, 143–181.Google Scholar
Novikov, E. A. 1971. Intermittency and scale similarity of the structure of turbulent flow. Prikl. Math. Mekh., 35, 266–277.Google Scholar
Obukhov, A. M. 1949. Local structure of atmospheric turbulence. Dokl. Acad. Nauk SSSR, 67, 643–646.Google Scholar
Obukhov, A. M. 1962. Some specific features of atmospheric turbulence. J. Fluid Mech., 13, 77–81.Google Scholar
Naert, A., Friedrich, R. and Peinke, J. 1997. Fokker–Planck equation for the energy cascade in turbulencePhys. Rev.E, 56, 6719–6722.Google Scholar
Nie, Q. and Tanveer, S. 1999. A note on third-order structure functions in turbulence. Proc. R. Soc. Lond.A, 455, 1615–1635.Google Scholar
Onsager, L. 1931. Reciprocal relations in irreversible processes. I. Phys. Rev., 37, 405–426.Google Scholar
Orszag, S. A. 1977. Lectures on the statistical theory of turbulence. In Fluid Dynamics, Balian, R. and Peube, J.-L. (eds.), 235–374. Gordon and Breach Science Publishers.
Pedrizzetti, G., Novikov, E. A. and Praskovsky, A. A. 1996. Self-similarity and probability distributions of turbulent intermittency. Phys. Rev.E, 53, 475–484.Google Scholar
Qian, J. 1997. Inertial range and the finite Reynolds number effect of turbulence. Phys. Rev.E, 55, 337–342.Google Scholar
Qian, J. 1998. Normal and anomalous scaling of turbulence. Phys. Rev.E, 58, 7325–7329.Google Scholar
Qian, J. 1999. Slow decay of the finite Reynolds number effect of turbulence. Phys. Rev.E, 60, 3409–3412.Google Scholar
Piomelli, U., Cabot, W. H., Moin, P. and Lee, S. 1991. Subgrid-scale backscatter in turbulent and transitional flows. Phys. FluidsA, 3, 1766–1771.Google Scholar
Saddougghi, S. G. and Veeravalli, S. V. 1994. Local isotropy in turbulent boundary layers at high Reynolds number. J. Fluid Mech., 268, 333–372.Google Scholar
Saffman, P. G. and Baker, G. R. 1979. Vortex interactions. Ann. Rev. Fluid Mech., 11, 95–122.Google Scholar
Sanada, T. 1992. Comment on the dissipation-range spectrum in turbulent flows. Phys. FluidsA, 4, 1086–1087.Google Scholar
Schumacher, J. 2007. Sub-Kolmogorov-scale fluctuations in fluid turbulence. EPL, 80, 54001.Google Scholar
Schumacher, J., Sreenivasan, K. R. and Yakhot, V. 2007. Asymptotic exponents from low-Reynolds-number flows. New Journal of Physics, 9, 89.Google Scholar
She, Z.-S. and Jackson, E. 1993. On the universal form of energy spectra in fully developed turbulence. Phys. Fluids A, 5, 1526–1528.Google Scholar
She, Z.-S. and Leveque, E. 1994. Universal scaling laws in fully developed turbulence. Phys. Rev. Lett., 72, 336–339.Google Scholar
She, Z.-S., Jackson, E. and Orszag, S. A. 1990. Intermittent vortex structures in homogeneous isotropic turbulence. Nature, 344, 226–228.Google Scholar
Siggia, E. D. 1981. Numerical study of small-scale intermittency in three-dimensional turbulence. J. Fluid Mech., 107, 375–406.Google Scholar
Sreenivasan, K. R. 1984. On the scaling of the turbulence energy dissipation rate. Phys. Fluids, 27, 1048–1951.Google Scholar
Sreenivasan, K. R. 1985. On the fine-scale intermittency of turbulence. J. Fluid Mech., 151, 81–103.Google Scholar
Sreenivasan, K. R. 1995. On the universality of Kolmogorov constant. Phys. Fluids, 7, 2778–2784.Google Scholar
Sreenivasan, K. R. 1998. An update on the energy dissipation rate in isotropic turbulence. Phys. Fluids, 10, 528–529.Google Scholar
Sreenivasan, K. R. and Antonia, R. A. 1997. The phenomenology of small-scale turbulence. Ann. Rev. Fluid Mech., 29, 435–472.Google Scholar
Sreenivasan, K. R. and Bershadskii, A. 2006. Finite-Reynolds-number effects in turbulence using logarithmic expansions. J. Fluid Mech., 554, 477–498.Google Scholar
Sreenivasan, K. R. and Dhruva, B. 1998. Is there scaling in high-Reynolds-number turbulence?Prog. Theor. Phys. Supplement, 130, 103–120.Google Scholar
Sreenivasan, K. R. and Stolovitzky, G. 1995. Turbulent cascades. J. Stat. Phys., 78, 311–333.Google Scholar
Tabeling, P., Zocchi, G, Belin, F., Maurer, J. and Willaime, H. 1996. Probability density functions, skewness, and flatness in large Reynolds number turbulence. Phys. Rev.E, 53, 1613–1621.Google Scholar
Tatsumi, T. 1980. Theory of homogeneous turbulence. Adv. Appl. Mech., 20, 39–133.Google Scholar
Taylor, M. A., Kurien, S. and Eyink, G. L. 2003. Recovering isotropic statistics in turbulence simulations: the Kolmogorov 4/5th law. Phys. Rev.E, 68, 026310.Google Scholar
Townsend, A. A. 1951. On the Fine-Scale Structure of Turbulence. Proc. R. Soc. Lond.A, 208, 534–542.Google Scholar
Tsinober, A. 2009. An Informal Conceptual Introduction to Turbulence, 2nd ed. Springer.
Tsuji, Y. 2009. High-Reynolds-number experiments: the challenge of understanding universality in turbulence. Fluid Dyn. Res., 41, 064003.Google Scholar
Van Atta, C. W. and Yeh, T. T. 1975. Evidence for scale similarity of internal intermittency in turbulent flows at large Reynolds numbers. J. Fluid Mech., 71, 417–440.Google Scholar
Vincent, A. and Meneguzzi, M. 1991. The spatial structure and statistical properties of homogeneous turbulence. J. Fluid Mech., 225, 1–20.Google Scholar
von Neumann, J. 1949. In Collected Works, Vol.6: Theories of Games, Astrophysics, Hydrodynamics and Meteorology, A. H., Taub (ed.), 437–472 (1963). Pergamon Press.
Wang, L. -P., Chen, S., Brasseur, J. G. and Wyngaard, J. C. 1996. Examination of hypotheses in the Kolmogorov refined turbulence theory through high-resolution simulations. Part 1. Velocity field. J. Fluid Mech., 309, 113–156.Google Scholar
Watanabe, T. and Gotoh, T. 2004. Statistics of a passive scalar in homogeneous turbulence. New Journal of Physics, 6, 40.Google Scholar
Yamamoto, K. and Hosokawa, I. 1988. A decaying isotropic turbulence pursued by spectral method. J. Phys. Soc. Jpn., 57, 1532–1535.Google Scholar
Yakhot, V. and Sreenivasan, K. R. 2004. Towards a dynamical theory of multifractals in turbulence. PhysicaA, 343, 147–155.Google Scholar
Yakhot, V. 2006. Probability densities in strong turbulence. PhysicaD, 215, 166–174.Google Scholar
Yeung, P. K., Pope, S. B., Lamorgese, A. G. and Donzis, D. A. 2006. Acceleration and dissipation statitics of numerically simulated isotropic turbulence. Phys. Fluids, 18, 065103.Google Scholar
Yokokawa, M., Itakura, K., Uno, A., Ishihara, T. and Kaneda, Y. 2002. 16.4-Tflops direct numerical simulation of turbulence by a Fourier spectral method on the Earth Simulator. Proc. IEEE/ACM SC2002 Conf., Baltimore, 2002, http://www.sc-2002.org/paperPDFs/pap.pap273.PDF.Google Scholar
Yoshida, K., Ishihara, T. and Kaneda, Y. 2003. Anisotropic spectrum of homogeneous turbulent shear flow in a Lagrangian renormalized approximation. Phys. Fluids, 15, 2385–2397.Google Scholar
Yoshizawa, A. 1998. Hydrodynamic and Magnetohydrodynamic Turbulent Flow. Kluwer Academic Publishers.
Zhou, T. and Antonia, R. A. 2000. Reynolds number dependence of the small-scale structure of grid turbulence. J. Fluid Mech., 406, 81–107.Google Scholar

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