arXiv subjects

A. Vulpiani

Publications and source records attributed to A. Vulpiani.

At least 73 records · Page 4Linked to original sources

arXiv1998

A kinetic approach to granular gases

We address the problem of the so-called ``granular gases'', i.e. gases of massive particles in rapid movement undergoing inelastic collisions. We introduce a class of models of driven granular gases for which the stationary state is the result of the balance between the dissipation and the random forces which inject energies. These models exhibit a genuine thermodynamic limit, i.e. at fixed density the mean values of kinetic energy and dissipated energy per particle are independent of the number $N$ of particles, for large values of $N$. One has two regimes: when the typical relaxation time $τ$ of the driving Brownian process is small compared with the mean collision time $τ_c$ the spatial density is nearly homogeneous and the velocity probability distribution is gaussian. In the opposite limit $τ\gg τ_c$ one has strong spatial clustering, with a fractal distribution of particles, and the velocity probability distribution strongly deviates from the gaussian one. Simulations performed in one and two dimensions under the {\it Stosszahlansatz} Boltzmann approximation confirm the scenario. Furthermore we analyze the instabilities bringing to the spatial and the velocity clusterization. Firstly, in the framework of a mean-field model, we explain how the existence of the inelasticity can bring to a spatial clusterization; on the other side we discuss, in the framework of a Langevin dynamics treating the collisions in a mean-field way, how a non-gaussian distribution of velocity can arise. The comparison between the numerical and the analytical results exhibits an excellent agreement.

cond-mat.stat-mech↗

arXiv1998

Clustering and Non-Gaussian Behavior in Granular Matter

We investigate the properties of a model of granular matter consisting of $N$ Brownian particles on a line subject to inelastic mutual collisions. This model displays a genuine thermodynamic limit for the mean values of the energy and the energy dissipation. When the typical relaxation time $τ$ associated with the Brownian process is small compared with the mean collision time $τ_c$ the spatial density is nearly homogeneous and the velocity probability distribution is gaussian. In the opposite limit $τ\gg τ_c$ one has strong spatial clustering, with a fractal distribution of particles, and the velocity probability distribution strongly deviates from the gaussian one.

cond-mat.stat-mech↗

arXiv1998

Optimal Strategies for Prudent Investors

We consider a stochastic model of investment on an asset of a stock market for a prudent investor. She decides to buy permanent goods with a fraction $\a$ of the maximum amount of money owned in her life in order that her economic level never decreases. The optimal strategy is obtained by maximizing the exponential growth rate for a fixed $\a$. We derive analytical expressions for the typical exponential growth rate of the capital and its fluctuations by solving an one-dimensional random walk with drift.

cond-mat.dis-nn↗

arXiv1998

Pair dispersion in synthetic fully developed turbulence

The Lagrangian statistics of relative dispersion in fully developed turbulence is numerically investigated. A scaling range spanning many decades is achieved by generating a synthetic velocity field with prescribed Eulerian statistical features. When the velocity field obeys Kolmogorov similarity, the Lagrangian statistics is self similar too, and in agreement with Richardson's predictions. For an intermittent velocity field the scaling laws for the Lagrangian statistics are found to depend on Eulerian intermittency in agreement with a multifractal description. As a consequence of the Kolmogorov law the Richardson law for the variance of pair separation is not affected by intermittency corrections. A new analysis method, based on fixed scale averages instead of usual fixed time statistics, is shown to give much wider scaling range and should be preferred for the analysis of experimental data.

chao-dyn↗

arXiv1998

Resonant enhanced diffusion in time dependent flow

Explicit examples of scalar enhanced diffusion due to resonances between different transport mechanisms are presented. Their signature is provided by the sharp and narrow peaks observed in the effective diffusivity coefficients and, in the absence of molecular diffusion, by anomalous transport. For the time-dependent flow considered here, resonances arise between their oscillations in time and either molecular diffusion or a mean flow. The effective diffusivities are calculated using multiscale techniques.

chao-dyn↗

arXiv1998

Relative dispersion in fully developed turbulence: from Eulerian to Lagrangian statistics in synthetic flows

The effect of Eulerian intermittency on the Lagrangian statistics of relative dispersion in fully developed turbulence is investigated. A scaling range spanning many decades is achieved by generating a multi-affine synthetic velocity field with prescribed intermittency features. The scaling laws for the Lagrangian statistics are found to depend on Eulerian intermittency in agreement with a multifractal description. As a consequence of the Kolmogorov's law, the Richardson's law for the variance of pair separation is not affected by intermittency corrections.

chao-dyn↗

arXiv1998

An extension of the Lyapunov analysis for the predictability problem

The predictability problem for systems with different characteristic time scales is investigated. It is shown that even in simple chaotic dynamical systems, the leading Lyapunov exponent is not sufficient to estimate the predictability time. This fact is due the saturation of the error on the fast components of the system which therefore do not contribute to the exponential growth of the error at large errors. It is proposed to adopt a generalization of the Lyapunov exponent which is based on the natural concept of error growing time at finite error size. The method is first illustrated on a simple numerical model obtained by coupling two Lorenz systems with different time scales. As a more realistic example, this analysis is then applied to a toy model of Atmospheric circulation recently introduced by Lorenz.

chao-dyn↗

arXiv1998

Mixing in a Meandering Jet: a Markovian Approximation

In this paper we investigate mixing and transport in correspondence of a meandering jet. The large-scale flow field is a kinematically assigned streamfunction. Two basic mixing mechanisms are considered, first separately and then combined together: deterministic chaotic advection, induced by a time dependence of the flow, and turbulent diffusion, described by means of a stochastic model for particle motion. Rather than looking at the details of particle trajectories, fluid exchange is studied in terms of markovian approximations. The two-dimensional physical space accessible to fluid particles is subdivided into regions characterized by different Lagrangian behaviours. From the observed transitions between regions it is possible to derive a number of relevant quantities characterizing transport and mixing in the studied flow regime, such as residence times, meridional mixing, correlation functions. These estimated quantities are compared with the corresponding ones resulting from the actual simulations. The outcome of the comparison suggests the possibility of describing in a satisfactory way at least some of the mixing properties ot the system through the very simplified approach of a first order markovian approximation, whereas other properties exhibit memory patterns of higher order.

chao-dyn↗

arXiv1998

Characterization of the spatial complex behavior and transition to chaos in flow systems

We introduce a ``spatial'' Lyapunov exponent to characterize the complex behavior of non chaotic but convectively unstable flow systems. This complexity is of spatial type and is due to sensitivity to the boundary conditions. We show that there exists a relation between the spatial-complexity index we define and the comoving Lyapunov exponents. In these systems the transition to chaos, i.e. the appearing of a positive Lyapunov exponent, can take place in two different ways. In the first one (from neither chaotic nor spatially complex behavior to chaos) one has the typical scenario; that is, as the system size grows up the spectrum of the Lyapunov exponents gives rise to a density. In the second one (when the chaos develops from a convectively unstable situation) one observes only a finite number of positive Lyapunov exponents.

chao-dyn↗

arXiv1997

Mimicking a turbulent signal: sequential multiaffine processes

An efficient method for the construction of a multiaffine process, with prescribed scaling exponents, is presented. At variance with the previous proposals, this method is sequential and therefore it is the natural candidate in numerical computations involving synthetic turbulence. The application to the realization of a realistic turbulent-like signal is discussed in detail. The method represents a first step towards the realization of a realistic spatio-temporal turbulent field.

chao-dyn↗

arXiv1997

Time-reversible Dynamical Systems for Turbulence

Dynamical Ensemble Equivalence between hydrodynamic dissipative equations and suitable time-reversible dynamical systems has been investigated in a class of dynamical systems for turbulence. The reversible dynamics is obtained from the original dissipative equations by imposing a global constraint. We find that, by increasing the input energy, the system changes from an equilibrium state to a non-equilibrium stationary state in which an energy cascade, with the same statistical properties of the original system, is clearly detected.

chao-dyn↗

arXiv1997

Dispersion of passive tracers in closed basins: beyond the diffusion coefficient

We investigate the spreading of passive tracers in closed basins. If the characteristic length scale of the Eulerian velocities is not very small compared with the size of the basin the usual diffusion coefficient does not give any relevant information about the mechanism of spreading. We introduce a finite size characteristic time $τ(δ)$ which describes the diffusive process at scale $δ$. When $δ$ is small compared with the typical length of the velocity field one has $τ(δ) \sim λ^{-1}$, where $λ$ is the maximum Lyapunov exponent of the Lagrangian motion. At large $δ$ the behavior of $τ(δ)$ depends on the details of the system, in particular the presence of boundaries, and in this limit we have found a universal behavior for a large class of system under rather general hypothesis. The method of working at fixed scale $δ$ makes more physical sense than the traditional way of looking at the relative diffusion at fixed delay times. This technique is displayed in a series of numerical experiments in simple flows.

chao-dyn↗

arXiv1997

Slow and fast dynamics in coupled systems: A time series analysis view

We study the dynamics of systems with different time scales, when access only to the slow variables is allowed. We use the concept of Finite Size Lyapunov Exponent (FSLE) and consider both the case when the equations of motion for the slow components are known, and the situation when a scalar time series of one of the slow variables has been measured. A discussion on the effects of parameterizing the fast dynamics is given. We show that, although the computation of the largest Lyapunov exponent can be practically infeasible in complex dynamical systems, the computation of the FSLE allows to extract information on the characteristic time and on the predictability of the large-scale, slow-time dynamics even with moderate statistics and unresolved small scales.

chao-dyn↗

arXiv1996

Predictability in the large: an extension of the concept of Lyapunov exponent

We investigate the predictability problem in dynamical systems with many degrees of freedom and a wide spectrum of temporal scales. In particular, we study the case of $3D$ turbulence at high Reynolds numbers by introducing a finite-size Lyapunov exponent which measures the growth rate of finite-size perturbations. For sufficiently small perturbations this quantity coincides with the usual Lyapunov exponent. When the perturbation is still small compared to large-scale fluctuations, but large compared to fluctuations at the smallest dynamically active scales, the finite-size Lyapunov exponent is inversely proportional to the square of the perturbation size. Our results are supported by numerical experiments on shell models. We find that intermittency corrections do not change the scaling law of predictability. We also discuss the relation between finite-size Lyapunov exponent and information entropy.

chao-dyn↗

arXiv1996

Characterization of a periodically driven chaotic dynamical system

We discuss how to characterize the behavior of a chaotic dynamical system depending on a parameter that varies periodically in time. In particular, we study the predictability time, the correlations and the mean responses, by defining a local--in--time version of these quantities. In systems where the time scale related to the time periodic variation of the parameter is much larger than the ``internal'' time scale, one has that the local quantities strongly depend on the phase of the cycle. In this case, the standard global quantities can give misleading information.

chao-dyn↗

arXiv1996

Growth of non-infinitesimal perturbations in turbulence

We discuss the effects of finite perturbations in fully developed turbulence by introducing a measure of the chaoticity degree associated to a given scale of the velocity field. This allows one to determine the predictability time for non-infinitesimal perturbations, generalizing the usual concept of maximum Lyapunov exponent. We also determine the scaling law for our indicator in the framework of the multifractal approach. We find that the scaling exponent is not sensitive to intermittency corrections, but is an invariant of the multifractal models. A numerical test of the results is performed in the shell model for the turbulent energy cascade.

chao-dyn↗

arXiv1995

Characterization of chaos in random maps

We discuss the characterization of chaotic behaviours in random maps both in terms of the Lyapunov exponent and of the spectral properties of the Perron-Frobenius operator. In particular, we study a logistic map where the control parameter is extracted at random at each time step by considering finite dimensional approximation of the Perron-Frobenius operator

chao-dyn↗

arXiv1995

Broken ergodicity and glassy behavior in a deterministic chaotic map

A network of $N$ elements is studied in terms of a deterministic globally coupled map which can be chaotic. There exists a range of values for the parameters of the map where the number of different macroscopic configurations is very large, and there is violation of selfaveraging. The time averages of functions, which depend on a single element, computed over a time $T$, have probability distributions that do not collapse to a delta function, for increasing $T$ and $N$. This happens for both chaotic and regular motion, i.e. positive or negative Lyapunov exponent.

cond-mat↗