Physics Department, UCC
Overview
The Plasma Data Analysis Group performs computational studies and modelling of experimental data from magnetically confined reactor-grade plasmas in the area of controlled thermonuclear fusion research. This work is heavily collaborative and there are strong links with the Max Planck Institut für Plasmaphysik, (IPP) Garching and Greifswald, and other European fusion laboratories. The present composition of the group is as follows: Patrick J. Mc Carthy (group leader), Prof. Richard J. Armstrong (visiting researcher), Brendan Cahill, Diarmuid Curran, Mike Dunne, Thomas O'Gorman, Shane O'Mahony (postgraduate researchers in the Dept. of Physics) and Kieran Beausang (Dept. of Electrical and Electronic Engineering). A brief summary of current research interests follows. A link to recent publications is on the margin to the left.
Current Research Interests
Tokamak Equilibrium Interpretation
Knowledge of the current density distribution J is crucial to understanding magnetohydrodynamic stability in
an axisymmetric tokamak plasma. J cannot be measured directly,
but must be inferred from a variety of magnetic and other diagnostic
measurements. This constitutes a complex, ill-posed inverse problem
that requires both physics insight and modelling expertise. To fully
exploit the constraints on the J profile shape that are
provided, in particular, by B-sensitive polarimetric
measurements based on the Motional Stark Effect, a major new MHD
equilibrium code has been developed and is maintained by the group. The
CLISTE code (CompLete Interpretive Suite for Tokamak Equilibria) is
used for reconstruction of the J profile on the ASDEX Upgrade
tokamak at Garching,
where it makes an essential diagnostic contribution to the ongoing
research programme,
in particular to the understanding of low-turbulence, high confinement
discharges with transport barriers.
Stellarator Equilibrium Parameterization by Database Methods
The identification of 3-D MHD equilibrium configurations in a helical stellarator plasma by a conventional equilibrium code is a computationally intensive task, requiring several hours on a workstation. The number of free parameters in a stellarator equilibrium is modest, however (of order 10), and the experimentally accessible parameter space may be adequately sampled by the order of 1000 randomly selected simulated equilibria. The inverse mapping method known as Function Parameterization (FP) entails (i) Construction of a simulated database of experimental states of a system whose parameters are to be identified from measurements of the system, (ii) A once-off offline training phase to construct simple functional relationships between measurements and system parameters and (iii) Rapid, including realtime system identification by using these numerically determined functions in predictive mode. Steps (i) and (ii) are performed rarely (on a timescale of a year or longer) but step (iii), which is computationally trivial, is used routinely. FP has been successfully applied by the group to speed up equilibrium identification on the Wendelstein 7 advanced stellarator at Garching by close on a factor of 10000, so that the equilibrium configuration is recoverable in seconds rather than hours. The method has been under further development in recent years to meet the challenges of rapid identification of equilibrium flux topology with island structures in the case of the Wendelstein 7-X (W7-X) experiment, under construction at Greifswald, Germany,
Analysis of MHD activity to improve q profile identification
In this project various methods of extracting useful information from MHD modes are considered, specifically pressure and current driven modes, to improve the reconstruction of the toroidal current profile. MHD modes, once identified and located, provide a value of q at a specific location with which the q-profile can be constrained. The study of Toroidicity-induced Alfvèn Eigenmodes (TAE modes) can be particularly beneficial, since they provide q-profile information over the whole plasma radius as opposed to individual points. This information comes from the q-dependance of the Alfvèn velocity. Thus measurement of this velocity profile taking into account the plasma rotation can be inverted to produce a q-profile independent of other sources of q-profile information.
The Influence of Fast Particles on the Beta Limit in a
Tokamak.
Fusion occurs in a deuterium-tritium fuel mixture in the
plasma state consisting of equal densities of positively and negatively
charged matter. An issue that will need to be addressed involves
determining the best way to confine plasma so that fusion can be
ignited and sustained. Confinement of the hot plasma is achieved
magnetically and an important measure of its efficiency is determined
by a parameter called the beta limit. This is the ratio of the plasma
pressure to the magnetic field pressure. It is desirable to be able to
measure and control this ratio. However there are various physical
processes that can disrupt the equilibrium that exists between these
quantities. This project is concerned with the question of how
energetic alpha particles produced by fusion reactions are confined by
the toroidally shaped magnetic field and also how they interact with
the Maxwellian background distribution of particles. The fast
population will have an effect on the beta limit in the tokamak which,
if too high, can lead to instabilities and magneto-hydrodynamic
ballooning modes which will result in a loss of confinement and energy.
MHD stability at high beta will be vital for producing a cost-effective
reactor and in determining the achievable fusion power density.