253 research outputs found
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
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