This thesis presents the methods and results different position analysis techniques provide for Compton image reconstruction. The AGATA A006 detector a highly segmented large volume detector has been utilised for the analysis of data presented in this thesis. This data contained within the thesis was part of the GammaKEV project, which aimed to develop a portable gamma-ray spectrometer for use on a nuclear submarine, with this work focusing on how the improvement of position determination can improve the reconstructed image FWHM. The AGATA A006 detector is a 80x80x90 mm3 HPGe, 36 segment and one core, coaxial detector. The average energy resolution over all the segments and core was found to be 2.7 ke V. This work shows the improvement that parametric pulse shape analysis can make in large detector segments to Compton image reconstruction. Two 1332 keV 60CO sources have been placed in front of the AGATA A006 detector at 100 mm and have been imaged using a simple back projection Compton image reconstruction code developed at the University of Liverpool. A method has been developed to apply parametric PSA to improve the precision of locating the position of interaction within the segments. A GEANT4 simulation has been adapted to replicate the experimental setup utilising a Gaussian smearing function applied to the simulated x, y and z position and energy data to assess the improvement that parametric PSA provides to the discrimination of position within the detector segments. The simulated energy and position smeared data reconstructed image resolution has been compared to the experimental data reconstructed image resolution. It has been found that the parametric PSA method developed in this thesis, will give a position resolution of 3 ± 0.5 mm within the segments of the crystal when compared to a 15 ± 0.5 mm position resolution for data reconstructed without utilising parametric PSA.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:632553 |
| Date | January 2015 |
| Creators | Slee, Michael John |
| Publisher | University of Liverpool |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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