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Compressed frictional granular matter cannot flow without dilation. Upon forced shearing to generate flow, the amount of dilation may depend on the initial preparation and a host of material variables. On the basis of both experiments and numerical simulations we show that as a result of training by repeated compression-decompression cycles the amount of dilation induced by shearing the system depends only on the shear rate and on the (pre-shearing) packing fraction. Relating the rheological response to structural properties allows us to derive a scaling law for the amount of dilation after $n$ cycles of compression-decompression. The resulting scaling law has a universal exponent that for trained systems is independent of the inter-granules force laws, friction parameters and strain rate. The amplitude of the scaling law is analytically computable, and it depends only on the shear rate and the asymptotic packing fraction., Comment: 8 pages, 10 figures, Published Version

Particles floating on the surface of a turbulent incompressible fluid accumulate along string-like structures, while leaving large regions of the flow domain empty. This is reflected experimentally by a very peaked probability distribution function of $c_r$, the coarse-grained particle concentration at scale $r$, around $c_r = 0$, with a power-law decay over two decades of $c_r$, $\Pi (c_r) \propto c_r^{-\beta_r}$. The positive exponent $\beta_r$ decreases with scale in the inertial range, and stays approximately constant in the dissipative range, thus indicating a qualitative difference between the dissipative and the inertial ranges of scales, also visible in the first moment of $c_r$., Comment: 5 pages, 3 figures and 1 table

We study local power fluctuations in numerical simulations of stationary, homogeneous, isotropic turbulence in two and three dimensions with Gaussian forcing. Due to the near-Gaussianity of the one-point velocity distribution, the probability distribution function (pdf) of the local power is well modelled by the pdf of the product of two joint normally distributed variables. In appropriate units, this distribution is parameterised only by the mean dissipation rate, $\epsilon$. The large deviation function for this distribution is calculated exactly and shown to satisfy a Fluctuation Relation (FR) with a coefficient which depends on $\epsilon$. This FR is entirely statistical in origin. The deviation from the model pdf are most pronounced for positive fluctuations of the power and can be traced to a slightly faster than Gaussian decay of the tails of the one-point velocity pdf. The resulting deviations from the FR are consistent with several recent experimental studies., Comment: 5 Pages, 5 Figures

The statistics of power fluctuations are studied in simulations of two-dimensional turbulence in both inverse (energy) and direct (enstrophy) cascade regimes from both Lagrangian and Eulerian perspectives. The probability density function (PDF) of the appropriately defined dimensionless power is strongly non-gaussian with asymmetric exponential tails. This distribution can be modeled by the distribution of the product of correlated normal variables allowing a derivation of the asymptotics of the tails. The PDF of the dimensionless power is shown to exhibit an empirical Fluctuation Relation. An expression for the entropy production rate is deduced from the asymptotic form of the power PDF and is found to agree very well with the measured entropy rate., Comment: 5 Pages and 3 figures. Revised version contains additional results for Eulerian power fluctuations, better presentation of the data to facilitate easy comparison between different regimes and an explanation for the value of the entropy rate in the empirical Fluctuation Relation

We examine the probability distribution function (pdf) of energy injection rate (power) in numerical simulations of stationary two--dimensional (2D) turbulence in the Lagrangian frame. The simulation is designed to mimic an electromagnetically driven fluid layer, a well-documented system for generating two--dimensional turbulence in the laboratory. In our simulations, the forcing and velocity fields are close to Gaussian. On the other hand, the measured PDF of injected power is very sharply peaked at zero, suggestive of a singularity there, with tails which are exponential but asymmetric. Large positive fluctuations are more probable than large negative fluctuations. It is this asymmetry of the tails, which leads to a net positive mean value for the energy input despite the most probable value being zero. The main features of the power distribution are well described by Craig's XY distribution for the PDF of the product of two correlated normal variables. We show that the power distribution should exhibit a logarithmic singularity at zero and decay exponentially for large absolute values of the power. We calculate the asymptotic behavior and express the asymmetry of the tails in terms of the correlation coefficient of the force and velocity. We compare the measured pdfs with the theoretical calculations and briefly discuss how the power pdf might change with other forcing mechanisms., Comment: 9 pages, 10 figures. Revised version includes additional results from higher resolution simulations, better representation of the data for easier comparison of different regimes and additional references