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This thesis presents a method for evaluating gamma radiation profiles using a low power gamma radiation detector system (GRDS). This method enables multiple radioactive gamma isotopes to be identified and determine the respective vector directions of those sources relative to the GRDS location. This detection method must be accurate, implemented as a handheld or fixed solution, and have a suitable battery life for a variety of industrial needs.
This paper will first explain the low power GRDS that was used for developing these detection methods. The target gamma isotopes that are used for validating these methods will be described along with explaining the different particle interactions that occur within the system. A set of mathematical models are developed to describe the theoretical outputs of the GRDS profiles given various gamma source configurations. These theoretical models are then used as a foundation to create algorithms for gamma isotope identification and source directional detection.
The algorithm architecture and the code level details to implement these functions will be explained. The algorithms are developed and validated using an independent software tool and simulated with a set of gamma source configurations before porting the functions to be run on the GRDS. The thesis will conclude by showing the results obtained by running the GRDS algorithms against a set of gamma source configurations to determine the accuracy of the system, and examine how the results map to the theoretical models.
Advisers: Sina Balkir and Michael Hoffman