The Advancement of a Technique Using Principal Component Analysis for the Non-Intrusive Depth Profiling of Radioactive Contamination

Adams, Jamie and Joyce, Malcolm and Mellor, M. (2012) The Advancement of a Technique Using Principal Component Analysis for the Non-Intrusive Depth Profiling of Radioactive Contamination. IEEE Transactions on Nuclear Science, 59 (4). pp. 1448-1452. ISSN 0018-9499

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Abstract

A significant development of the principal component analysis technique, to non-intrusively infer the depth of the fission fragment cesium-137, when it is buried under silica sand has been described. In this paper we describe the advancement of the technique by further validating it using blind tests for applications outside of the laboratory, where not only the depth (z) but also the surface (x,y) location of gamma-ray emitting contamination is often poorly characterized. Also uncertainty analysis has been conducted to test the robustness of the technique. At present the technique has been tested at the point of maximum activity above the entrained -ray emitting source (where the optimal , location is known). This is not usually practical in poorly characterized environments where the detector cannot be conveniently placed at such an optimal location to begin with and scanning at multiple points around the region of interest is often required. Using a uniform scanning time, the point of maximum intensity can be located by sampling in terms of total count rate, and converging on this optimal point of maximum intensity

Item Type:
Journal Article
Journal or Publication Title:
IEEE Transactions on Nuclear Science
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/3100/3106
Subjects:
?? DEPTH PROFILINGGAMMA-RAYSGAMMA SPECTROSCOPYPRINCIPAL COMPONENT ANALYSISRADIOACTIVE CONTAMINATIONSHIELDINGNUCLEAR ENERGY AND ENGINEERINGELECTRICAL AND ELECTRONIC ENGINEERINGNUCLEAR AND HIGH ENERGY PHYSICS ??
ID Code:
60021
Deposited By:
Deposited On:
16 Nov 2012 11:15
Refereed?:
Yes
Published?:
Published
Last Modified:
21 Sep 2023 01:26