H-1NF: Information for Prospective Students
Effect of different discharge conditions
on the surface
quality of the H-1 vacuum system:
You will use the new computer controlled
residual gas analyser to compare different regimes of glow discharge
conditioning, baking, and pulsed discharge cleaning in their efficiency
at
removing carbon and oxygen from the internal walls of the H-1 vacuum
vessel. This could be extended to
analysing the visible spectral lines of full scale H-1 plasma to relate
the
discharge conditioning to the final improvement in plasma purity.
Analysis of
Alfvén eigenmode data from H-1
plasma.
One of the major concerns in predictions
of the
plasma parameters required for next step fusion experiments (e.g.
ITER)
is the possible deleterious effect of the excitation of large amplitude
Alfvén
eigenmodes, manifesting as magnetic field fluctuations which can cause
energy
transport across the confining magnetic field. Similar fluctuations are
observed in high temperature H-1 plasmas. You would analyse some of
the
substantial data set of frequency vs. time data ("voiceprint")
looking for agreement or otherwise with a few simple theories, or for
different
characteristic phenomena. We have data viewing and data mining
software
already, which you are encouraged to use, or you could improve this, or
develop
your own approach. A PhD student near completion (David Pretty) would
be
able to help with software and analysis.
A LabView-based control system for fast acquisition of vacuum magnetic surfaces (Poincare plots) will be extended to include data acquisition and initial analysis of a 720 view x 64 channel tomographic system. This system will display data in various raw and analysed forms during acquisition to allow the quality of data to be improved, and to feed back into the experiment to allow the scan parameters to be chosen strategically. Using “Labview” and Research Systems Inc’s “IDL”, we expect that a measurement campaign of days can be performed in hours.
Data Quality Assessment
for H-1
This is a software-oriented project,
creating a set of rules and a procedure for checking the quality of the
data
and plasma parameters recorded each time we pulse H-1. Our
data are numerous and diverse, and
expensive to acquire, so if a data set is flawed, we would like to know
quickly, to save wasting resources, and avoid the need to repeat the
data
taking.
The set of rules or classifications that
define “good” data should be developed from two directions:
a/ experts write some simple rules, and then fine tune them
on old data, and new data is at arrives.
b/ experts classify good and bad data, pulse by pulse and
machine learning techniques are used to discover new rules that define
bad
data.
The most efficient way to get started
would be to use the IDL data visualization language to evaluate the
required
quantities - we have much existing code, and it allows quick debugging,
and has
great interactive graphics. This would be a learning curve for
students.
Alternatively you could use Java, which is more widespread, but
requires a bit
more development time. Also if you are
not familiar with Java, you would have to be prepared to spend a
substantial
part your time learning the language.
Finally you could try Python, which is in between (but free).
We have an extensive mysql database of shots, and David McLenaghan's Java “eScope” data viewer has simple data mining capabilities ready and working if you want a head start.
One of the following two:
Mapping of Magnetic Field Configurations
in H-1
The unique heliac plasma shape is generated
by a carefully designed, fully three dimensional magnetic field. The magnetic field lines can be directly
mapped by launching electrons, and collecting them on a 64 wire grid
array. The data is tomographically
inverted by existing algorithms. This
apparatus has been recently upgraded, and the project is to map the
magnetic
field for various configurations, looking at sensitivity to small
changes in
current, formation of magnetic islands, and the chaotic region at the
plasma
edge.
Soft XRay emissions from H-1
Use a new 16 channel absolute extreme
ultraviolet array (AXUV http://www.ird-inc.com/axuvope.html) to obtain soft xray data from the H-1 heliac
plasma. This can be used as a “radiation
bolometer” or with a thin foil, as a “soft” (200eV-1000eV) Xray
detector, and should
allow an estimate of temperature and impurity distributions in the
plasma.
Boyd.Blackwell@anu.edu.au
x 52482
wait several rings past the tone change to be forwarded to my
mobile.
