Lampson, Alexander (2012) A Fusion Proton Diagnostic for Low Field Tokamaks. MPhil thesis, University of York.
Abstract
The use of a pinhole-type detector to image the high-energy protons produced by interactions of fast particles within the plasma of low field tokamaks such as the Mega Amp
Spherical Tokamak is explored. The minimum number of detector elements in a pinhole-type detector needed to produce accurate images of the plasma was found to be 144, giving a 5cm by 5cm resolution of the plasma in the R, Z plane. The image is recreated via a combination of singular value decomposition and maximum entropy methods. The proton
production rate is a function of the spatial distribution of fast particles, and so images of the proton production distribution can be used to directly diagnose the fast particle dis-tribution within the plasma. These fast particles are mostly produced by neutral beam injection, and so the methods presented here can be used to more accurately control the neutral beam injection energy to ensure that the heating and current drive is applied to the
desired regions of the plasma. As the orbits of the fusion born protons are influenced by the magnetic field within the
plasma, a transformation matrix is created to link the detector image with the intial proton distribution within the plasma. To do this, large numbers of test particles are needed. The calculation of the orbits of the test particles is performed using CUDA GPUs which can calculate the orbits of up to 100,000 particles per second. This takes advantage of the embarrassingly parallel nature of the problem, which is ideally suited to calculation on the GPU.
Metadata
Supervisors: | Vann, Roddy |
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Keywords: | CUDA, GPU, Proton Camera, Maximum Entropy, Fusion, MAST, tokamk |
Awarding institution: | University of York |
Academic Units: | The University of York > School of Physics, Engineering and Technology (York) |
Academic unit: | Department of Physics |
Depositing User: | The Honourable Alexander Lampson |
Date Deposited: | 24 Jun 2013 09:04 |
Last Modified: | 08 Aug 2013 08:53 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:4033 |
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