Intermittency in Turbulence: Multiplicative random process in space and time

We present a simple stochastic algorithm for generating multiplicative processes with multiscaling both in space and in time. With this algorithm we are able to reproduce a synthetic signal with the same space and time correlation as the one coming from shell models for turbulence and the one coming from a turbulent velocity field in a quasi-Lagrangian reference frame.Comment: 23 pages, 12 figure

The statistical properties of turbulence in the presence of a smart small-scale control

By means of high-resolution numerical simulations, we compare the statistical properties of homogeneous and isotropic turbulence to those of the Navier-Stokes equation where small-scale vortex filaments are strongly depleted, thanks to a non-linear extra viscosity acting preferentially on high vorticity regions. We show that the presence of such smart small-scale drag can strongly reduce intermittency and non-Gaussian fluctuations. Our results pave the way towards a deeper understanding on the fundamental role of degrees of freedom in turbulence as well as on the impact of (pseudo)coherent structures on the statistical small-scale properties. Our work can be seen as a first attempt to develop smart-Lagrangian forcing/drag mechanisms to control turbulence.Comment: 5 pages, 5 figure

How to detect illegal waste shipments? The case of the international trade in polyethylene waste

The purpose of this research is to provide a methodological framework that is able to enhance our capability to detect illegal waste shipment with particular reference to waste plastics. Based on a very large cross-sectional dataset covering 187 countries over the period 2002-2012, our study aims to do this by using both the mirror statistics method and the network analysis. Specifically, by using mirror statistics, we identify the existence of a set of “suspicious” trade relations between pairs of countries. Then, we employ social network analysis in order to define the position of each country in this illegal trade structure, and to have a clear exposition of the connections between them. Our main findings reveal the central positions of the USA, Germany and the UK as sources and China and Malaysia as outlets of illegal shipments of waste plastics. Moreover, our methodology allows us to highlight the presence of other countries, which carry out an intermediary role within the global trade network, and to detect the changes in traditional illegal shipment routes. Therefore, this paper shows how social network analysis provides a useful instrument by means of which crime analysts and police detectives can develop effective strategies to interdict criminal activities

Statistics of small scale vortex filaments in turbulence

We study the statistical properties of coherent, small-scales, filamentary-like structures in Turbulence. In order to follow in time such complex spatial structures, we integrate Lagrangian and Eulerian measurements by seeding the flow with light particles. We show that light particles preferentially concentrate in small filamentary regions of high persistent vorticity (vortex filaments). We measure the fractal dimension of the attracting set and the probability that two particles do not separate for long time lapses. We fortify the signal-to-noise ratio by exploiting multi-particles correlations on the dynamics of bunches of particles. In doing that, we are able to give a first quantitative estimation of the vortex-filaments life-times, showing the presence of events as long as the integral correlation time. The same technique introduced here could be used in experiments as long as one is capable to track clouds of bubbles in turbulence for a relatively long period of time, at high Reynolds numbers; shading light on the dynamics of small-scale vorticity in realistic turbulent flows.Comment: 5 pages, 5 figure

Droplet breakup in homogeneous and isotropic turbulence

This fluid dynamics video shows the breakup of a droplet in a stationary homogeneous and isotropic turbulent flow. We consider droplets with the same density of the transporting fluid. The droplets and the fluid are numerically modelled by means of a multicompo- nent Lattice-Boltzmann method. The turbulent fluid is maintained through a large scale stirring force and the radius of stable droplets, for the parameters in our simulation, is larger than the Kolmogorov scale. Events of droplet deformation, break-up and aggregation are clearly visible from the movie. With the present database droplet evo- lution can be studied from both an Eulerian and Lagrangian point of view. The Kolmogorov-Hinze criteria for droplets break-up can be tested also by means of simulations with different viscosity contrast between the two components.Comment: 4 pages, 4 figures, 1 tabl

Multiscale anisotropic fluctuations in sheared turbulence with multiple states

We use high resolution direct numerical simulations to study the anisotropic contents of a turbulent, statistically homogeneous flow with random transitions among multiple energy containing states. We decompose the velocity correlation functions on different sectors of the three dimensional group of rotations, SO(3), using a high-precision quadrature. Scaling properties of anisotropic components of longitudinal and transverse velocity fluctuations are accurately measured at changing Reynolds numbers. We show that independently of the anisotropic content of the energy containing eddies, small-scale turbulent fluctuations recover isotropy and universality faster than previously reported in experimental and numerical studies. The discrepancies are ascribed to the presence of highly anisotropic contributions that have either been neglected or measured with less accuracy in the foregoing works. Furthermore, the anomalous anisotropic scaling exponents are devoid of any sign of saturation with increasing order. Our study paves the way to systematically assess persistence of anisotropy in high Reynolds number flows.Comment: 6 pages, 5 figure

Probing structures in channel flow through SO(3) and SO(2) decomposition

SO(3) and SO(2) decompositions of numerical channel flow turbulence are performed. The decompositions are used to probe, characterize, and quantify anisotropic structures in the flow. Close to the wall the anisotropic modes are dominant and reveal the flow structures. The SO(3) decomposition does not converge for large scales as expected. However, in the shear buffer layer it also does not converge for small scales, reflecting the lack of small scales isotropization in that part of the channel flow.Comment: 25 pages, 22 figure

Lattice Boltzmann Methods for thermal flows: continuum limit and applications to compressible Rayleigh-Taylor systems

We compute the continuum thermo-hydrodynamical limit of a new formulation of lattice kinetic equations for thermal compressible flows, recently proposed in [Sbragaglia et al., J. Fluid Mech. 628 299 (2009)]. We show that the hydrodynamical manifold is given by the correct compressible Fourier- Navier-Stokes equations for a perfect fluid. We validate the numerical algorithm by means of exact results for transition to convection in Rayleigh-B\'enard compressible systems and against direct comparison with finite-difference schemes. The method is stable and reliable up to temperature jumps between top and bottom walls of the order of 50% the averaged bulk temperature. We use this method to study Rayleigh-Taylor instability for compressible stratified flows and we determine the growth of the mixing layer at changing Atwood numbers up to At ~ 0.4. We highlight the role played by the adiabatic gradient in stopping the mixing layer growth in presence of high stratification and we quantify the asymmetric growth rate for spikes and bubbles for two dimensional Rayleigh- Taylor systems with resolution up to Lx \times Lz = 1664 \times 4400 and with Rayleigh numbers up to Ra ~ 2 \times 10^10.Comment: 26 pages, 13 figure

Lagrangian single particle turbulent statistics through the Hilbert-Huang Transform

The Hilbert-Huang transform is applied to analyze single particle Lagrangian velocity data from numerical simulations of hydrodynamic turbulence. The velocity trajectory is described in terms of a set of intrinsic mode functions, C_{i}(t), and of their instantaneous frequency, \omega_{i}(t). On the basis of this decomposition we define the \omega-conditioned statistical moments of the C_{i} modes, named q-order Hilbert Spectra (HS). We show that such new quantities have enhanced scaling properties as compared to traditional Fourier transform- or correlation-based (Structure Functions) statistical indicators, thus providing better insights into the turbulent energy transfer process. We present a clear empirical evidence that the energy-like quantity, i.e. the second-order HS, displays a linear scaling in time in the inertial range, as expected from dimensional analysis and never observed before. We also measure high order moment scaling exponents in a direct way, without resorting the Extended Self Similarity (ESS) procedure. This leads to a new estimate of the Lagrangian structure functions exponents which are consistent with the multifractal prediction in the Lagrangian frame as proposed in [Biferale et al., Phys. Rev. Lett. vol. 93, 064502 (2004)].Comment: 5 pages, 5 figure