Simulation of Pellet Ablation for Tokamak Fuelling
Abstract.
A magnetohydrodynamic numerical model and parallel software for the
ablation of cryogenic deuterium pellets in the process of tokamak
fuelling has been developed based on the method of front tracking of
ITAPS Center. The main features of the model are the explicit tracking
of material interfaces, a surface ablation model, a kinetic model for
the electron heat flux, a cloud charging and rotation model, and an
equation of state accounting for atomic processes in the ablation
cloud. The software was used for the first systematic studies of
the pellet ablation rate and properties of the ablation channel in
magnetic fields. Simulations revealed new features of the pellet
ablation such as strong dependence of the radius of the ablation
channel and ablation rate on the ``warm-up'' time and supersonic
spinning of the ablation channel.
Introduction.
The injection of small frozen deuterium-tritium pellets is an
experimentally proven method of refuelling tokamaks [1]. Pellet
injection is currently seen as the most likely refuelling technique for
the International Thermonuclear Experimental Reactor (ITER). In order
to evaluate the efficiency of this fuelling method, it is necessary to
determine the pellet ablation rate.
The ablation of tokamak pellets and its influence on the tokamak plasma
has been studied using several analytical and numerical approaches (see
[2] and references therein). The inherent limitation of the previous
ablation models has been the the absence of a rigorous inclusion of
important details of physics processes in the vicinity of the pellet
and in the ablation channel, and insufficient accuracy of numerical
models due to extreme change of thermodynamics states on short length
scales. The motivation of the present work is to improve both the
accuracy of computational models by using the front tracking technology
of the Interoperable Technologies for Advanced Petascale Simulations
(ITAPS) Center [3], and physics modeling of the interaction of the
pellet ablation channel with the tokamak magnetic field. The present
work is a continuation of [5] which introduced sharp interface
numerical MHD model for the pellet ablation, but omitted effects of
charging and rotation of the pellet ablation channel. Both sharp
interface numerical techniques and the resolution of complex physics
processes in the pellet ablation channel are important not only for the
calculation of pellet ablation rates and the fuelling efficiency, but
also for the understanding of striation instabilities in tokamaks [6].
Main physics processes
In this section, we briefly summarize the main physics processes
associated with the ablation of a cryogenic deuterium pellet in a
tokamak magnetic field (Figure 1). Hot electrons travelling along the
magnetic field lines hit the pellet surface causing a rapid ablation. A
cold, dense, and neutral gas cloud forms around the pellet and shields
it from the incoming hot electrons. After the initial stage of
ablation, the most important processes determining the ablation
rate occur in the cloud. The cloud away from the pellet heats-up
above the dissociation and then the ionization levels, and partially
ionized plasma channels along the magnetic field lines. As it was shown
in [5], this process can be described by the system of MHD
equations in the low magnetic Reynolds number approximation. The plasma
cloud stops the incident plasma ions at the cloud / plasma interface,
while the faster incident electrons penetrate the cloud where their
flux is partially attenuated depending on the cloud opacity. We employ
the kinetic model for the hot electron - plasma interaction
proposed in [9]. The tendency of the background plasma to remain
neutral confines the main potential drop to a thin sheath adjacent to
both end-faces of the cloud. Inside the cloud, the potential slowly
changes along each field line. Since the cloud density and opacity vary
radially, the potential inside the cloud varies from field line to
field line causing E x B cloud rotation about the symmetry axis. The
potential can be explicitly found using kinetic models for hot currents
inside the cloud [6]. The fast cloud rotation widens the ablation
channel, redistributes the ablated gas, and changes the ablation rate.
We believe that it also causes striation instabilities observed
in pellet injection experiments [6].
Numerical method
In this section, we will describe numerical ideas implemented in the
FronTier-MHD code. In general, the system of MHD equations in the low
magnetic Reynolds number
approximation is a coupled hyperbolic - elliptic system in a
geometrically complex moving domain. We have developed numerical
algorithms and parallel software for 3D simulations of such a system
\cite{SamDu07} based on the ITAPS front tracking technology
\cite{FT_lite}.
The numerical method uses the operator splitting method. We decouple
the hyperbolic and elliptic parts of the MHD system for every time
step. The mass, momentum, and energy conservation equations are solved
first without the electromagnetic terms
(Lorentz force). We use the front tracking hydro code FronTier
with free interface support
for solving the hyperbolic subsystem. The electromagnetic terms are
then found, in the general case,
from the solution of the Poisson equation for the electric potential in
the conducting medium using
the embedded boundary method, as described in \cite{SamDu07}.
%In the current 2.5D axisymmetric model
%for the pellet ablation, the elliptic step is eliminated as the
current
%density in each point of the ablation cloud is a function of the
hydrodynamic state and some integrated
%quantities along the corresponding magnetic field line. In our current
work in progress on 3D pellet
%ablation, solving of a modified 3D Poisson problem is required.
At the end of the time step, the fluid states are integrated along
every grid line in the longitudinal
direction in order to obtain the electron heat deposition and internal
hot currents.
The heat deposition changes the internal energy and temperature of
fluid states, and therefore
the electrical conductivity. The Lorentz force and the centrifugal
force are then added to the momentum equation.
FronTier represents interfaces as lower dimensional meshes moving
through a volume filling grid (\Fig{FT_structures}).
The traditional volume filling finite difference grid supports smooth
solutions located
in the region between interfaces. The location of the discontinuity and
the jump in the solution
variables are defined on the interface. A computational stencil is
constructed at every interface
point in the normal and tangential direction, and stencil states are
obtained through interpolation.
Then Euler equations, projected on the normal and tangential
directions, are solved. The normal
propagation of an interface point employs a predictor - corrector
technique. We solve the Riemann problem for
left and right interface states to predict the location and states of
the interface at the next time step.
Then a corrector technique is employed which accounts for fluid
gradients on both sides of the interface.
Namely, we trace back characteristics from the predicted new interface
location and solve Euler
equations along characteristics. After the propagation of the
interface points, the new interface is checked for consistency of
intersections. The untangling of the
interface at this stage consists in removing unphysical intersections,
and rebuilding a topologically
correct interface. The update of interior states using a second order
conservative scheme is performed
in the next step. The tracked interface allows us to avoid the
integration across large discontinuities
of fluid states, and thus eliminate the numerical diffusion. The
FronTier code has been used for
large scale simulations on various platforms including the
IBM BlueGene supercomputer New York Blue located at Brookhaven National
Laboratory.
References
\bibitem{Baylor00}
[1] L. Baylor et al., Improved core fueling with high field pellet
injection in the DIII-D tokamak, Phys. Plasmas, {\bf 7} (2000),
1878-1885.
\bibitem{Pegourie}
[2] Pegourie B Review: Pellet injection experiments and modelling,
Plasma Phys. Control. Fusion 49 (2007) R87- R160.
\bibitem{ITAPS}
[3] http://www.tstt-scidac.org/
\bibitem{SamDu07}
[4] R. Samulyak, J. Du, J. Glimm, Z. Xu, A numerical algorithm for MHD
of free surface flows at low magnetic Reynolds numbers, J. Comp. Phys.,
226 (2007), 1532 - 1549.
\bibitem{SamLuParks07}
[5] R. Samulyak, T. Lu, P. Parks, A magnetohydrodynamic simulation of
pellet ablation in the electrostatic approximation, Nuclear Fusion, 47
(2007), 103-118.
\bibitem{Parks96}
[6] P. Parks, Theory of pellet cloud oscillation striations, Plasma.
Phys. Control. Fusion, 38 (1996) 571 - 591.
\bibitem{FT_lite}
[7] J. Du, B. Fix, J. Glimm, X. Li, Y. Li, L. Wu, A Simple Package for
Front Tracking, J. Comp. Phys., 213, 613–628, 2006.
\bibitem{NGS}
[8] P. Parks, R. Turnbull, Effect of transonic flow in the
ablation cloud on the lifetime of a solid hydrogen pellet in
plasma, Phys. Fluids, 21 (1978), 1735 - 1741.
\bibitem{Ishizaki}
[9] R. Ishizaki, P. Parks, N. Nakajima, M. Okamoto, Two-dimensional
simulation of pellet ablation with atomic processes, Phys. Plasmas, 11
(2004), 4064 - 4080.