We investigate the preferential concentration of particles which are neutrally buoyant but with a diameter significantly larger than the dissipation scale of the carrier flow. Such particles are known not to behave as flow tracers (Qureshi et al., Ph
ys. Re. Lett. 2007) but whether they do cluster or not remains an open question. For this purpose, we take advantage of a new turbulence generating apparatus, the Lagrangian Exploration Module which produces homogeneous and isotropic turbulence in a closed water flow. The flow is seeded with neutrally buoyant particles with diameter 700mum, corresponding to 4.4 to 17 times the turbulent dissipation scale when the rotation frequency of the impellers driving the flow goes from 2 Hz to 12 Hz, and spanning a range of Stokes numbers from 1.6 to 24.2. The spatial structuration of these inclusions is then investigated by a Voronoi tesselation analysis, as recently proposed by Monchaux et al. (Phys. Fluids 2010), from images of particle concentration field taken in a laser sheet at the center of the flow. No matter the rotating frequency and subsequently the Reynolds and Stokes numbers, the particles are found not to cluster. The Stokes number by itself is therefore shown to be an insufficient indicator of the clustering trend in particles laden flows.
We discuss the effect of stochastic resonance in a simple model of magnetic reversals. The model exhibits statistically stationary solutions and bimodal distribution of the large scale magnetic field. We observe a non trivial amplification of stochas
tic resonance induced by turbulent fluctuations, i.e. the amplitude of the external periodic perturbation needed for stochastic resonance to occur is much smaller than the one estimated by the equilibrium probability distribution of the unperturbed system. We argue that similar amplifications can be observed in many physical systems where turbulent fluctuations are needed to maintain large scale equilibria.
Using exact relations between velocity structure functions (Hill, Hill and Boratav, and Yakhot) and neglecting pressure contributions in a first approximation, we obtain a closed system and derive simple order-dependent rescaling relationships betwee
n longitudinal and transverse structure functions. By means of numerical data with turbulent Reynolds numbers ranging from $Re_lambda=320$ to $Re_lambda=730$, we establish a clear correspondence between their respective scaling range, while confirming that their scaling exponents do differ. This difference does not seem to depend on Reynolds number. Making use of the Mellin transform, we further map longitudinal to (rescaled) transverse probability density functions.
We study a simple magnetohydrodynamical approach in which hydrodynamics and MHD turbulence are coupled in a shell model, with given dynamo constrains in the large scales. We consider the case of a low Prandtl number fluid for which the inertial range
of the velocity field is much wider than that of the magnetic field. Random reversals of the magnetic field are observed and it shown that the magnetic field has a non trivial evolution linked to the nature of the hydrodynamics turbulence.
