Mean Field Limit of Interacting Filaments and Vector Valued Non-linear PDEs

Families of N interacting curves are considered, with long range, mean field type, interaction. They generalize models based on classical interacting point particles to models based on curves. In this new set-up, a mean field result is proven, as \(N\rightarrow \infty \). The limit PDE is vector valued and, in the limit, each curve interacts with a mean field solution of the PDE. This target is reached by a careful formulation of curves and weak solutions of the PDE which makes use of 1-currents and their topologies. The main results are based on the analysis of a nonlinear Lagrangian-type flow equation. Most of the results are deterministic; as a by-product, when the initial conditions are given by families of independent random curves, we prove a propagation of chaos result. The results are local in time for general interaction kernel, global in time under some additional restriction. Our main motivation is the approximation of 3D-inviscid flow dynamics by the interacting dynamics of a large number of vortex filaments, as observed in certain turbulent fluids; in this respect, the present paper is restricted to smoothed interaction kernels, instead of the true Biot–Savart kernel.     

Stochastic Attractors for Shell Phenomenological Models of Turbulence

Recently, it has been proposed that the Navier–Stokes equations and a relevant linear advection model have the same long-time statistical properties, in particular, they have the same scaling exponents of their structure functions. This assertion has been investigate rigorously in the context of certain nonlinear deterministic phenomenological shell model, the Sabra shell model, of turbulence and its corresponding linear advection counterpart model. This relationship has been established through a “homotopy-like” coefficient λ which bridges continuously between the two systems. That is, for λ=1 one obtains the full nonlinear model, and the corresponding linear advection model is achieved for λ=0. In this paper, we investigate the validity of this assertion for certain stochastic phenomenological shell models of turbulence driven by an additive noise. We prove the continuous dependence of the solutions with respect to the parameter λ. Moreover, we show the existence of a finite-dimensional random attractor for each value of λ and establish the upper semicontinuity property of this random attractors, with respect to the parameter λ. This property is proved by a pathwise argument. Our study aims toward the development of basic results and techniques that may contribute to the understanding of the relation between the long-time statistical properties of the nonlinear and linear models.     

Martingale solutions for stochastic Euler equations

We prove existence of martingale solutions for the Euler equations in the 2-Dimensional space. The result is obtained by a compactness method     

Criterion on stability for Markov processes applied to a model with jumps

We formulate and prove a new criterion for stability of e-processes. In particular we show that any e-process which is averagely bounded and concentrating is asymptotically stable. This general result is applied to a stochastic process with jumps that is a continuous counterpart of the chain considered in Szarek (Ann. Probab. 34:1849–1863, 2006).     

Some Rigorous Results on a Stochastic GOY Model

A stochastic infinite dimensional version of the GOY model is rigorously investigated. Well posedness of strong solutions, existence and p-integrability of invariant measures is proved. Existence of solutions to the zero viscosity equation is also proved. With these preliminary results, the asymptotic exponents ζ_p of the structure function are investigated. Necessary and sufficient conditions for ζ₂≥ 2/3 and ζ₂=2/3 are given and discussed on the basis of numerical simulations.     

Invariant Measures of Gaussian Type for 2D Turbulence

Gaussian measures ?? ^??,?? are associated to some stochastic 2D models of turbulence. They are Gibbs measures constructed by means of an invariant quantity of the system depending on some parameter ?? (related to the 2D nature of the fluid) and the viscosity???. We prove the existence and the uniqueness of the global flow for the stochastic viscous system; moreover the measure ?? ^??,?? is invariant for this flow and is the unique invariant measure. Finally, we prove that the deterministic inviscid equation has a ?? ^??,?? -stationary solution (for any ??>0).     

On the stability of the solutions to the compressible Navier-Stokes equations when the Mach number goes to zero

In this paper an asymptotic stability result is estabilished for the compressible navier-Stokes equations. Since the Mach number tends to zero, the incompressible limit solution of compressible Navier-Stokes equations is proved to be stable exponentially. Some results of Stokes' problem are used.