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Details of Grant 

EPSRC Reference: GR/L35232/01
Title: INTELLIGENT PARALLEL ALGORITHMS IN APPLIED PLASMA SCIENCE
Principal Investigator: Diver, Professor DA
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: School of Physics and Astronomy
Organisation: University of Glasgow
Scheme: Standard Research (Pre-FEC)
Starts: 01 June 1997 Ends: 31 May 1999 Value (£): 89,117
EPSRC Research Topic Classifications:
Plasmas - Technological
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:  
Summary on Grant Application Form
The research programme has twin strands: the design, construction and implementation of intrinsically parallel codes for (i) automated data analysis of plasma emission spectra, and (ii) numerical simulation of dust-contaminated magnetofluid plasmas. We propose to create a new, more powerful parallel variant of our self-adapting spectral decomposition algorithms, tailored to the automated interpretation of plasma emission spectra and exploiting a novel comprehensive library of crucial spectral features which will also be constructed. The central algorithm of this code will be used in a new partial differential equation solver, with application to electrostatic field calculations. Allied to this activity will be the creation of new cellular-automata code for simulating plasma behaviour in laboratory devices, particularly finite plasmas encountering boundaries. these simulations will be used to investigate further the conditions for grain growth, enabling machine operating parameters to be investigated with regard to possible contaminant drop-out. The collective effects of dust in such environments will also be studied.The significance of this research, though motivated primarily by the challenge presented by modelling and analysing real plasmas, extends beyond the immediate applications listed here. Its true multi-disciplinary nature will pay significant scientific and commercial dividends in the near future (eg rapid identification of trace chemicals).
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Organisation Website: http://www.gla.ac.uk