By using direct numerical simulations (DNS) at unprecedented resolution, we study turbulence under rotation in the presence of simultaneous direct and inverse cascades. The accumulation of energy at large scale leads to the formation of vertical coherent regions with high vorticity oriented along the rotation axis. By seeding the flowwithmillions ofinertialparticles,wequantify -- forthefirsttime -- theeffects ofthose coherent vertical structures on the preferential concentration of light and heavy particles. Furthermore, we quantitatively show that extreme fluctuations, leading to deviations from a normal-distributed statistics, result from the entangled interaction of the vertical structures with the turbulent background. Finally, we present the first-ever measurement of the relative importance between Stokes drag, Coriolis force, and centripetal force along the trajectories of inertial particles. We discover that vortical coherent structures lead to unexpected diffusion properties for heavy and light particles in the directions parallel and perpendicular to the rotation axis.

Breakup of small aggregates in fully developed turbulence is studied by means of direct numerical simulations in a series of typical bounded and unbounded flow configurations, such as a turbulent channel flow, a developing boundary layer and homogeneous isotropic turbulence. The simplest criterion for breakup is adopted, whereby aggregate breakup occurs when the local hydrodynamic stress "1=2, with " being the energy dissipation at the position of the aggregate, overcomes a given threshold cr, which is characteristic for a given type of aggregate. Results show that the breakup rate decreases with increasing threshold. For small thresholds, it develops a scaling behaviour among the different flows. For high thresholds, the breakup rates show strong differences between the different flow configurations, highlighting the importance of non-universal mean-flow properties. To further assess the effects of flow inhomogeneity and turbulent fluctuations, the results are compared with those obtained in a smooth stochastic flow. Furthermore, we discuss the limitations and applicability of a set of independent proxies.

Breakup of small tracer-like aggregates is studied by means f numerical simulations in four different flows, namely homogeneous isotropic turbulence, smooth stochastic flow, turbulent channel flow, and developing boundary layer flow.

Spatial and velocity statistics of heavy point-like particles in incompressible, homogeneous, and isotropic three-dimensional turbulence is studied by means of direct numerical simulations at two values of the Taylor-scale Reynolds number Re-lambda similar to 200 and Re-lambda similar to 400, corresponding to resolutions of 512(3) and 2048(3) grid points, respectively. Particles Stokes number values range from St approximate to 0.2 to 70. Stationary small-scale particle distribution is shown to display a singular -multifractal- measure, characterized by a set of generalized fractal dimensions with a strong sensitivity on the Stokes number and a possible, small Reynolds number dependency. Velocity increments between two inertial particles depend on the relative weight between smooth events - where particle velocity is approximately the same of the fluid velocity-, and caustic contributions - when two close particles have very different velocities. The latter events lead to a non-differentiable small-scale behaviour for the relative velocity. The relative weight of these two contributions changes at varying the importance of inertia. We show that moments of the velocity difference display a quasi bi-fractal-behavior and that the scaling properties of velocity increments for not too small Stokes number are in good agreement with a recent theoretical prediction made by K. Gustavsson and B. Mehlig arXiv:1012.1789v1 [physics.fludyn], connecting the saturation of velocity scaling exponents with the fractal dimension of particle clustering.

Coalescence growth of droplets is a fundamental process for liquid cloud evolution. The initiation of collisions and coalescence occurs when a few droplets become large enough to fall. Gravitational collisions represent the most efficient mechanism for multi-disperse solutions, when droplets span a large variety of sizes. However, turbulence provides another mechanism for droplets coalescence, taking place also in the case of uniform condensational growth leading to narrow droplet-size spectra. We consider the problem of estimating the rate of collisions of small droplets dispersed in a highly turbulent medium. The problem is investigated by means of high-resolution direct numerical simulations of a three-dimensional turbulent flow, seeded with inertial particles, up to resolutions of 2048^3 grid points. Rate of collision is estimated in terms of the probability to find particles at close positions, and of the statistics of particles velocity. In particular, we show that the statistics of velocity differences between inertial particles suspended in an incompressible turbulent flow is extremely intermittent. When particles are separated by distances of the order of their diameter, the competition between quiet regular regions and multivalued caustics leads to a quasi bi-fractal behavior of the particle velocity statistics, with high-order moments bringing the signature of caustics. This results in large probabilities that close particles have important velocity differences. Together with preferential concentration of particles in low-vorticity regions, caustics contribute to speed-up collisions between inertial particles. Implications for the early stage of rain droplets formation are discussed.

The statistics of velocity differences between pairs of heavy inertial point particles suspended in an incompressible turbulent flow is studied and found to be extremely intermittent. The problem is particularly relevant to the estimation of the efficiency of collisions among heavy particles in turbulence. We found that when particles are separated by distances within the dissipative subrange, the competition between regions with quiet regular velocity distributions and regions where very close particles have very different velocities (caustics) leads to a quasi bi-fractal behaviour of the particle velocity structure functions. Contrastingly, we show that for particles separated by inertial-range distances, the velocity-difference statistics can be characterized in terms of a local roughness exponent, which is a function of the scale-dependent particle Stokes number only. Results are obtained from high-resolution direct numerical simulations up to 2048 3 collocation points and with millions of particles for each Stokes number.

Relative dispersion of tracers - i.e. very small, neutrally buoyant particles-, is particularly efficient in incompressible turbulent flows. Due to the non smooth behaviour of velocity differences in the inertial range, the separation distance between two trajectories, R(t)=X1(t)-X2(t) , grows as a power of time superdiffusively, R2(t)t3 , as first observed by L.F. Richardson [1]. This now well established result has no counterpart in the theory of heavy particle suspensions, namely finite-size particles with a mass density much larger that of the carrier fluid. The complete knowledge of particle properties of mixing in turbulent flows -yet an open problem-, is of great importance in cloud physics, or in estimating pollutant dispersion for hazardous safety purposes.

We present results from recent direct numerical simulations of heavy particle transport in homogeneous, isotropic, fully developed turbulence, with grid resolution up to 5123 and R? ? 185. By following the trajectories of millions of particles with different Stokes numbers, St ? [0.16 : 3.5], we are able to characterize in full detail the statistics of particle acceleration. We focus on the probability density function of the normalised acceleration a/arms and on the behaviour of their rootmean-squared acceleration arms as a function of both St and R?. We explain our findings in terms of two concurrent mechanisms: particle clustering, very effective for small St, and filtering induced by finite particle response time, taking over at larger St.

We present a collection of eight data sets from state-of-the-art experiments and numerical simulations on turbulent velocity statistics along particle trajectories obtained in different flows with Reynolds numbers in the range Rlambda[is-an-element-of][120:740]. Lagrangian structure functions from all data sets are found to collapse onto each other on a wide range of time lags, pointing towards the existence of a universal behavior, within present statistical convergence, and calling for a unified theoretical description. Parisi-Frisch multifractal theory, suitably extended to the dissipative scales and to the Lagrangian domain, is found to capture the intermittency of velocity statistics over the whole three decades of temporal scales investigated here.

A detailed comparison between data from experimental measurements and numerical simulations of Lagrangian velocity structure functions in turbulence is presented. Experimental data, at Reynolds number ranging from R? = 350 to R? = 815, are obtained in a swirling water flow between counter-rotating baffled disks. Direct numerical simulations (DNS) data, up to R? = 284, are obtained from a statistically homogeneous and isotropic turbulent flow. By integrating information from experiments and numerics, a quantitative understanding of the velocity scaling properties over a wide range of time scales and Reynolds numbers is achieved. To this purpose, we discuss in detail the importance of statistical errors, anisotropy effects, and finite volume and filter effects, finite trajectory lengths. The local scaling properties of the Lagrangian velocity increments in the two data sets are in good quantitative agreement for all time lags, showing a degree of intermittency that changes if measured close to the Kolmogorov time scales or at larger time lags. This systematic study resolves apparent disagreement between observed experimental and numerical scaling properties.

Distributions of heavy particles suspended in incompressible turbulent flows are investigated by means of high-resolution direct numerical simulations. It is shown that particles form fractal clusters in the dissipative range, with properties independent of the Reynolds number. Conversely, in the inertial range, the particle distribution is not scale-invariant. It is however shown that deviations from uniformity depends only on a rescaled contraction rate, and not on the local Stokes number given by dimensional analysis. Particle distribution is characterized by voids spanning all scales of the turbulent flow; their signature on the coarse-grained mass probability distribution is an algebraic behavior at small densities.

Spatial distributions of heavy particles suspended in an incompressible isotropic and homogeneous turbulent flow are investigated by means of high resolution direct numerical simulations. In the dissipative range, it is shown that particles form fractal clusters with properties independent of the Reynolds number. Clustering is there optimal when the particle response time is of the order of the Kolmogorov time scale tau(eta). In the inertial range, the particle distribution is no longer scale invariant. It is, however, shown that deviations from uniformity depend on a rescaled contraction rate, which is different from the local Stokes number given by dimensional analysis. Particle distribution is characterized by voids spanning all scales of the turbulent flow; their signature in the coarse-grained mass probability distribution is an algebraic behavior at small densities.

The Lagrangian statistics of heavy particles and of fluid tracers transported by a fully developed turbulent flow are investigated by means of high resolution direct numerical simulations. The Lagrangian velocity structure functions are measured in a time range spanning about three decades, from a tenth of the Kolmogorov time scale, tau(eta), up to a few large-scale eddy turnover times. Strong evidence is obtained that fluid tracer statistics are contaminated in the time range tau is an element of[1:10]tau(eta) by a bottleneck effect due to vortex filament. This effect is found to be significantly reduced for heavy particles which are expelled from vortices by inertia. These findings help in clarifying the results of a recent study by H. Xu [Phys. Rev. Lett. 96, 024503 (2006)], where differences between experimental and numerical results on scaling properties of fluid tracers were reported. (c) 2006 American Institute of Physics.

We present the results of direct numerical simulations of heavy particle transport in homogeneous, isotropic, fully developed turbulence, up to resolution 512(3) (R-lambda approximate to 185). Following the trajectories of up to 120 million particles with Stokes numbers, St, in the range from 0.16 to 3.5 we are able to characterize in full detail the statistics of particle acceleration. We show that: (i) the root-mean-squared acceleration arms sharply falls off from the fluid tracer value at quite small Stokes numbers; (ii) at a given St the normalized acceleration a(rms)/(is an element of(3)/nu)(1/4) increases with R-lambda consistently with the trend observed for fluid tracers; (iii) the tails of the probability density function of the normalized acceleration a/a(rms) decrease with St. Two concurrent mechanisms lead to the above results: preferential concentration of particles, very effective at small St. and filtering induced by the particle response time, that takes over at larger St.

We present the results of direct numerical simulations (DNS) of turbulent flows seeded with millions of passive inertial particles. The maximum Reynolds number is Re-lambda similar to 200. We consider particles much heavier than the carrier flow in the limit when the Stokes drag force dominates their dynamical evolution. We discuss both the transient and the stationary regimes. In the transient regime, we study the growth of inhomogeneities in the particle spatial distribution driven by the preferential concentration out of intense vortex filaments. In the stationary regime, we study the acceleration fluctuations as a function of the Stokes number in the range St is an element of [0.16 : 3.3]. We also compare our results with those of pure fluid tracers ( St = 0) and we find a critical behavior of inertia for small Stokes values. Starting from the pure monodisperse statistics we also characterize polydisperse suspensions with a given mean Stokes, (St) over bar.