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On the multifractal properties of the energy dissipation derived from turbulence data

Published online by Cambridge University Press:  26 April 2006

E. Aurell
Affiliation:
Department of Mathematics, KTH, 10044 Stockholm, Sweden CNRS, Observatoire de Nice, B.P. 229, 06304 Nice Cedex 4, France
U. Frisch
Affiliation:
CNRS, Observatoire de Nice, B.P. 229, 06304 Nice Cedex 4, France
J. Lutsko
Affiliation:
Physique Non-Linéaire et Mécanique Statistique, Univ. Libre de Bruxelles, C.P. 231, 1050 Brussels, Belgium
M. Vergassola
Affiliation:
CNRS, Observatoire de Nice, B.P. 229, 06304 Nice Cedex 4, France Dipartimento di Fisica, Università di Roma ‘La Sapienza’, P.le A. Moro 2, I-00185 Rome, Italy

Abstract

Various difficulties can be expected in trying to extract from experimental data the distribution of singularities, the f(α) function, of the energy dissipation. One reason is that the multifractal model of turbulence implies a dependence of the viscous cutoff on the singularity exponent. It is an open question if current hot-wire probes can resolve the scales implied by exponents a significantly less than 1.

Two exactly soluble models are used to show how spurious scaling can occur, due to finite Reynolds number effects. In the Gaussian model the true velocity signal is replaced by independent Gaussian random variables. The dissipation, defined as the square of the difference of successive variables, has trivial scaling in so far as all the moments of spatial averages of the dissipation behave asymptotically as a uniform dissipation. Still, contamination by subdominant terms requires that scaling exponents for high-order moments be identified over an increasingly large range of scales. If the available range is limited by the Reynolds number, scaling exponents for high orders will be systematically underestimated and spurious intermittency will be inferred. Burgers’ model is used to highlight further problems. At finite Reynolds numbers, regions with no small-scale activity (away from shocks) have a residual dissipation which contributes a spurious point (α = 1,f(α) = 1). In addition, when the f(α) function is obtained by Legendre transform techniques, convex hull effects generate an entire spurious segment.

Finally, Burgers’ model also indicates that the relation between exponents of structure functions and exponents of local dissipation moments, which goes back to Kolmogorov's (1962) work, leads to an inconsistency for structure functions of low positive order.

Type
Research Article
Copyright
© 1992 Cambridge University Press

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References

Abramowitz, M. & Stegun, I. A. 1965 Handbook of Mathematical Functions. Dover.
Anselmet, A., Gagne, Y., Hopfinger, E. J. & Antonia, R. A. 1984 High-order velocity structure functions in turbulent shear flows. J. Fluid Mech. 140, 63.Google Scholar
Argoul, F., Arnéodo, A., Grasseau, G., Gagne, Y., Hopfinger, E. J. & Frisch, U. 1989 Wavelet analysis of turbulence reveals the multifractal nature of the Richardson cascade. Nature 338, 51.Google Scholar
Artuso, R., Aurell, E. & Cvitanović, P. 1990a Recycling of strange sets: I. Cycle expansions. Nonlinearity 3, 325.Google Scholar
Artuso, R., Aurell, E. & Cvitanović, P. 1990b Recycling of strange sets: II. Applications. Nonlinearity 3, 361.Google Scholar
Bacry, E., Arnéodo, A., Frisch, U., Gagne, Y. & Hopfinger, E. J. 1990 Wavelet analysis of fully developed turbulence data and measurement of scaling exponents. In Turbulence and Coherent Structures (ed. O. Métais & M. Lesieur), pp. 203215. Kluwer.
Bensimon, D., Jensen, M. H. & Kadanoff, L. P. 1986 Renormalization-group analysis of the global structure of the period-doubling attractor. Phys. Rev. A 33, 3622.Google Scholar
Benzi, R., Paladin, G., Parisi, G. & Vulpiani, A. 1984 On the multifractal nature of fully developed turbulence and chaotic systems. J. Phys. Paris A 17, 3521.Google Scholar
Bracket, M. E. 1990 Géométrie des structures à petite échelle dans le vortex de Taylor—Green. C. R. Acad. Sci. Paris 311, 775.Google Scholar
Burgers, J. M. 1974 The Nonlinear Diffusion Equation. D. Reidel.
Castaing, B., Gagne, Y. & Hopfinger, E. J. 1990 Velocity probability density functions of high Reynolds number turbulence. Physica D 46, 177.Google Scholar
Cole, J. D. 1951 On a quasi-linear parabolic equation occurring in aerodynamics. Q. Appl. Maths 9, 225.Google Scholar
Douady, S., Couder, Y. & Brachet, M. E. 1991 Direct observation of the intermittency of intense vorticity filaments in turbulence. Phys. Rev. Lett. 67, 983.Google Scholar
Fournier, J. D. & Frisch, U. 1983 L'équation de Burgers déterministe et statistique. J. Méc. Théor. Appl. 2, 699.Google Scholar
Frisch, U. 1991 From global scaling, à la Kolmogorov, to local multifractal scaling in developed turbulence. Proc. R. Soc. Lond. A 434, 89.Google Scholar
Frisch, U. & Vergassola, M. 1991 A prediction of the multifractal model: the intermediate dissipation range. Europhys. Lett. 14, 439.Google Scholar
Gagne, Y. & Castaing, B. 1991 Une représentation universelle sans invariance globale d'échelle des spectres d'énergie en turbulence développée. C. R. Acad. Sci. Paris 312, 414.Google Scholar
Glazier, J. A., Jensen, M. H., Libchaber, A. & Stavans, J. 1986 Structure of Arnold tongues and the f(α) spectrum for period-doubling: experimental results. Phys. Rev. A 34, 1621.Google Scholar
Gradshteyn, I. S. & Ryzhik, I. M. 1965 Table of Integrals, Series and Products. Academic.
Grassberger, P., Badii, R. & Politi, A. 1988 Scaling laws for invariant measures on hyperbolic and nonhyperbolic attractors. J. Stat. Phys. 51, 135.Google Scholar
Halsey, T. C., Jensen, M. H., Kadanoff, L. P., Procaccia, I. & Shraiman, B. I. 1986 Fractal measures and their singularities: the characterization of strange sets. Phys. Rev. A 33, 1141.Google Scholar
Hopf, E. 1950 The partial differential equation ut + uux = ux. Commun. Pure Appl. Maths 3, 201.Google Scholar
Kida, S. 1979 Asymptotic properties of Burgers turbulence. J. Fluid Mech. 93, 337.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.Google Scholar
Kolmogorov, A. N. 1941b Dissipation of energy under locally isotropic turbulence. Dokl. Akad. Nauk SSSR 32, 16.Google Scholar
Kolmogorov, A. N. 1962 A refinement of previously hypotheses concerning the local structure of turbulence in a viscous incompressible fluid at high Reynolds number. J. Fluid Mech. 13, 82.Google Scholar
Mandelbrot, B. 1974 Intermittent turbulence in self-similar cascades: divergence of high moments and dimension of the carrier. J. Fluid Mech. 62, 331.Google Scholar
Mandelbrot, B. 1991 Random multifractals: negative dimensions and the resulting limitations of the thermodynamic formalism. Proc. R. Soc. Lond. A 434, 79.Google Scholar
Meneveau, C. M. & Nelkin, M. 1989 Attractor size in intermittent turbulence. Phys. Rev. A 39, 3732.Google Scholar
Meneveau, C. M. & Sreenivasan, K. R. 1987 The multifractal spectrum of the dissipation field in turbulent flows. Nucl. Phys. B Proc. Suppl. 2, 49.Google Scholar
Meneveau, C. M. & Sreenivasan, K. R. 1989 Measurement of f(α) from scaling of hystograms and applications to dynamical systems and turbulence. Phys. Lett. A 137, 103112.Google Scholar
Meneveau, C. M. & Sreenivasan, K. R. 1991 The multifractal nature of turbulent energy dissipation. J. Fluid Mech. 224, 429.Google Scholar
Miles, R. B., Connors, J. J., Markovitz, E. C., Howard, P. J. & Roth, G. J. 1989 Instantaneous profiles and turbulence statistics of supersonic free shear layers by Raman excitation plus laser-induced electronic fluorescence (Relief) velocity tagging of oxygen. Expts Fluids 8, 17.Google Scholar
Miller, P. & Dimotakis, P. 1991 Stochastic geometric properties of scalar interfaces in turbulent jets. Phys. Fluids A 3, 168.Google Scholar
Monin, A. S. & Yaglom, A. M. 1975 Statistical Fluid Mechanics, vol. 2 (Ed. J. Lumley). MIT Press.
Oboukhov, A. M. 1962 Some specific features of atmospheric turbulence. J. Fluid Mech. 13, 77.Google Scholar
Paladin, G. & Vulpiani, A. 1987 Degrees of freedom of turbulence. Phys. Rev. A 35, 1971.Google Scholar
Parisi, G. & Frisch, U. 1985 On the singularity spectrum of fully developed turbulence. In Turbulence and Predictability in Geophysical Fluid Dynamics, Proc. Intl School of Physics ‘E. Fermi’, 1983, Varenna, Italy (ed. M. Ghil, R. Benzi & G. Parisi), p. 84. North-Holland.
Politi, A., Badii, R. & Grassberger, P. 1988 On the geometric structure of non-hyperbolic attractors. J. Phys. A: Math. Gen. 21, 763.Google Scholar
Prasad, R. R., Meneveau, C. & Sreenivasan, K. R. 1989 The multifractal nature of the dissipation field of passive scalars in fully turbulent flows. Phys. Rev. Lett. 61, 74.Google Scholar
She, Z. S., Frisch, U. & Aurell, E. 1992 The inviscid Burgers equation with initial data of Brownian type. Commun. Math. Phys. (submitted).Google Scholar
She, Z. S., Jackson, E. & Orszag, S. A. 1990 Intermittent vortex structures in homogeneous isotropic turbulence. Nature 344, 226.Google Scholar
Sinai, Y. 1992 Statistics of shock waves in solutions of the inviscid Burgers equation. Commun. Math. Phys. (submitted).Google Scholar
Vergassola, M., Benzi, R., Biferale, L. & Pisarenko, D. 1991 Wavelet analysis of a Gaussian Kolmogorov signal. Wavelets and Turbulence, Proc. USA-French Workshop, 1991, Princeton University, USA (submitted).Google Scholar
Vincent, A. & Meneguzzi, M. 1991 The spatial structure and statistical properties of homogeneous turbulence. J. Fluid Mech. 225, 1.Google Scholar
Van de Water, W., Van der Vorst, B. & Van de Wetering, E. 1991 Multiscaling of turbulent structure functions. Europhys. Lett. 16, 443.Google Scholar
Wu, X. Z., Kadanoff, L., Libchaber, A. & Sano, M. 1990 Frequency power spectrum of temperature fluctuations in free convection. Phys. Rev. Lett. 64, 2140.Google Scholar