In this third lecture the ideal and extended magnetohydrodynamics (MHD) fluid moment descriptions of magnetized plasmas are discussed first. The ideal MHD equilibrium in a toroidally axisymmetric tokamak plasma is discussed next. Then, the collisional viscous force closure moments and their effects on the parallel Ohm's law and poloidal flows in the extended MHD model of tokamak plasmas are discussed. Finally, the species fluid moment equations are transformed to magnetic flux coordinates, averaged over a flux surface and used to obtain the tokamak plasma transport equations. These equations describe the transport of the plasma electron density, plasma toroidal angular momentum and pressure of the electron and ion species "radially" across the nested tokamak toroidal magnetic flux surfaces.[-]

In this final, fourth lecture the many effects on radial tokamak plasma transport caused by various physical processes are noted first: transients, collision- and microturbulence-induced transport, sources and sinks, and small three-dimensional (3-D) magnetic field perturbations. The main focus of this lecture is on the various effects of small 3-D fields on plasma transport which is a subject that has come of age over the past decade. Finally, the major themes of these CEMRACS 2014 lectures are summarized and a general framework for combining extended MHD, hybrid kinetic/fluid and transport models of tokamak plasma behavior into unified descriptions and numerical simulations that may be able to provide a "predictive capability" for ITER plasmas is presented.[-]

This series of 4 lectures discusses the key physical processes in fusion-relevant plasmas, the equations used to describe them, and the interrelationships between them. The focus is on developing comprehensive equations and models for magnetically-confined fusion plasmas on a hierarchy of time scales. The relevant plasma equations for inertial fusion are also briefly mentioned. The pedagogical development begins with the very short time scale microscopic charged-particle-based Coulomb collision processes in a plasma. This microscopic description is then used to develop a comprehensive plasma kinetic equation, fluid moment, magnetohydrodynamic (MHD) and hybrid kinetic/fluid moment plasma descriptions, and finally the long time scale equations for plasma transport across the confining magnetic field. The present grand challenge in magnetic fusion is to develop a "predictive capability" for deuteron-triton (D-T) burning plasmas in ITER (http://www.iter.org). Individual .pdf files of the final, corrected sets of viewgraphs are available via http://homepages.cae.wisc.edu/~callen/plasmas.

This initial lecture first discusses the wide range of characteristic length and time scales involved in modeling fusion plasmas. Next, the Coulomb scattering of a charged test particle's velocity and the differences between the ensemble-averaged electron and ion collisional scattering and relaxation rates are discussed. Then, the mathematical properties of these collisional scattering processes are used to develop a Fokker-Planck collision operator. Finally, a general plasma kinetic equation (PKE) is developed and its general properties discussed.[-]

In this second lecture a Green function solution of the perturbed plasma kinetic equation (PKE) that determines the effects of Coulomb collisional scattering on linear Landau damping is presented first. This is followed by the development of the fluid moment equations obtained from the PKE. An extended Chapman-Enskog-type approach is used to determine the needed collisional and fluid moment closures for this comprehensive, hybrid kinetic/fluid model. Finally, closures for collision-dominated unmagnetized and magnetized plasmas are presented and their limitations discussed.[-]

The aim of this two-hour lecture is to present the mathematical underpinnings of some common numerical approaches to compute average properties as predicted by statistical physics. The first part provides an overview of the most important concepts of statistical physics (in particular thermodynamic ensembles). The aim of the second part is to provide an introduction to the practical computation of averages with respect to the Boltzmann-Gibbs measure using appropriate stochastic dynamics of Langevin type. Rigorous ergodicity results as well as elements on the estimation of numerical errors are provided. The last part is devoted to the computation of transport coefficients such as the mobility or autodiffusion in fluids, relying either on integrated equilibrium correlations à la Green-Kubo, or on the linear response of nonequilibrium dynamics in their steady-states.[-]

We consider a general network of harmonic oscillators driven out of thermal equilibrium by coupling to several heat reservoirs at different temperatures. The action of the reservoirs is implemented by Langevin forces. Assuming the existence and uniqueness of the steady state of the resulting process, we construct a canonical entropy production functional $S(t)$ which satisfies the Gallavotti-Cohen fluctuation theorem. More precisely, we prove that cumulant generating function of $S(t)$ has a large-time limit $e(a)$ which is finite on a closed interval centered at $a=1/2$, infinite on its complement and satisfies the Gallavotti-Cohen symmetry $e(1-a)=e(a)$ for all $a$. It follows from well known results that $S(t)$ satisfies a global large deviation principle with a rate function $I(s)$ obeying the Gallavotti-Cohen fluctuation relation $I(-s)-I(s)=s$ for all $s$. We also consider perturbations of $S(t)$ by quadratic boundary terms and prove that they satisfy extended fluctuation relations, i.e., a global large deviation principle with a rate function that typically differs from $I(s)$ outside a finite interval. This applies to various physically relevant functionals and, in particular, to the heat dissipation rate of the network. Our approach relies on the properties of the maximal solution of a one-parameter family of algebraic matrix Ricatti equations. It turns out that the limiting cumulant generating functions of $S(t)$ and its perturbations can be computed in terms of spectral data of a Hamiltonian matrix depending on the harmonic potential of the network and the parameters of the Langevin reservoirs. This makes our approach well adapted to both analytical and numerical investigations. This is joint work with Vojkan Jaksic and Armen Shirikyan.[-]

(Work in collaboration with C. Bardos and I. Moyano). Consider the linear Boltzmann equation of radiative transfer in a half-space, with constant scattering coefficient $\sigma$. Assume that, on the boundary of the half-space, the radiation intensity satisfies the Lambert (i.e. diffuse) reflection law with albedo coefficient $\alpha$. Moreover, assume that there is a temperature gradient on the boundary of the half-space, which radiates energy in the half-space according to the Stefan-Boltzmann law. In the asymptotic regime where $\sigma \to +\infty$ and $1 − \alpha ∼ C/\sigma$, we prove that the radiation pressure exerted on the boundary of the half-space is governed by a fractional diffusion equation. This result provides an example of fractional diffusion asymptotic limit of
a kinetic model which is based on the harmonic extension definition of $\sqrt{−\Delta}$. This fractional diffusion limit therefore differs from most of other such limits for kinetic models reported in the literature, which are based on specific properties of the equilibrium distributions (“heavy tails”) or of the scattering coefficient as in [U. Frisch-H. Frisch: Mon. Not. R. Astr. Not. 181 (1977), 273–280].[-]

This talk is devoted to the quasi linear approximation for solutions of the Vlasov equation a very popular tool in Plasma Physic cf. [4] which proposes, for the quantity:
(1)
$$
q(t,\ v)=\int_{\mathbb{R}_{v}^{d}}f(x,\ v,\ t)dx)\ ,
$$
the solution of a parabolic, linear or non linear evolution equation
(2)
$$
\partial_{t}q(t,\ v)-\nabla_{v}(D(q,\ t;v)\nabla_{v}q)=0
$$
Since the Vlasov equation is an hamiltonian reversible dynamic while (2) is not reversible whenever $D(q,\ t,\ v)\# 0$ the problem is subtle. Hence I did the following things :

1. Give some sufficient conditions, in particular in relation with the Landau damping that would imply $D(q,\ t,\ v)\simeq 0$. a situation where the equation (2) with $D(q,\ t;v)=0$ does not provides a meaning full approximation.

2. Building on contributions of [7] and coworkers show the validity of the approximation (2) for large time and for a family of convenient randomized solutions. This is justified by the fact that the assumed randomness law is in agreement which what is observed by numerical or experimental observations (cf. [1]).

3. In the spirit of a Chapman Enskog approximation formalize the very classical physicist approach (cf. [6] pages 514-532) one can show [3] that under analyticity assumptions this approximation is valid for short time. As in [6] one of the main ingredient of this construction is based on the spectral analysis of the linearized equation and as such it makes a link with a classical analysis of instabilities in plasma physic.

Remarks

In some sense the two approaches are complementary The short time is purely deterministic and the stochastic is based on the intuition that over longer time the randomness will take over of course the transition remains from the first regime to the second remains a challenging open problem. The similarity with the transition to turbulence in fluid mechanic is striking It is underlined by the fact that the tensor
$$
\lim_{\epsilon\rightarrow 0}\mathbb{D}^{\epsilon}(t,\ v)=\lim_{\epsilon\rightarrow 0}\int dx\int_{0}^{\frac{t}{\epsilon^{2}}}d\sigma E^{\epsilon}(t,\ x+\sigma v)\otimes E^{\epsilon}(t-\epsilon^{2}\sigma,\ x)
$$
which involves the electric fields here plays the role of the Reynolds stress tensor.

2 Obtaining, for some macroscopic description, a space homogenous equation for the velocity distribution is a very natural goal. Here the Vlasov equation is used as an intermediate step in the derivation. And more generally it appears as an example of weak turbulence. In particular defining what would be the physical natural probability seems related to the derivation of $\mathrm{e}$ of the Lenard-Balescu equation as done in [5].[-]