The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.
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Analysis Methods for Airborne Radioactivity
Jarmo J. Ala-Heikkilä
Dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Faculty of Information and Natural Sciences for public examination and debate in Auditorium K216 at Helsinki University of Technology (Espoo, Finland) on the 20th of August, 2008, at 12 noon.
Dissertation in PDF format (ISBN 978-951-22-9440-4) [2131 KB]
Dissertation is also available in print (ISBN 978-951-22-9439-8)
Abstract
High-resolution gamma-ray spectrometry is an analysis method well suitable for monitoring airborne radioactivity. Many of the natural radionuclides and a majority of anthropogenic nuclides are prominent gamma-ray emitters. With gamma-ray spectrometry different radionuclides are readily observed at minute concentrations that are far from health hazards. The gamma-ray spectrometric analyses applied in air monitoring programmes can be divided into particulate measurements and gas measurements. In this work, methods applicable for particulate sample analysis have been presented, implemented in analysis software, and evaluated with a wide variety of cases. Our goal has been to develop a collection of tools that enables a complete quantitative explanation of all components of a measured gamma-ray spectrum with a minimum of user intervention.
In a high-resolution spectrum, all essential information is contained in the peaks. Most of them are full-energy peaks that can be explained with gamma-ray lines in a reference library. Among the full-energy peaks, however, there are annihilation escape peaks, X-ray escape peaks, coincidence sum peaks, and random sum peaks that are not tabulated. Calculation methods for these special peaks are presented, implemented in SHAMAN, and evaluated in this work.
Expert system SHAMAN combines a comprehensive ENSDF-based reference library with an inference engine that applies pruning rules to select the acceptable candidate nuclides, utilizing a collection of calculational methods. Its performance with air filter spectra is evaluated in this work with four different spectrum sets. The performance of SHAMAN is also benchmarked against another identification software in completely automated analysis.
In summary, expert system SHAMAN is well applicable at any organization where environmental radioactivity is monitored. The system can also be utilized in other applications, but the current rule base has been tailored most comprehensively for air filter spectra. The analysis capabilities of the system can be improved in other applications of gamma-ray spectrometry by tuning the analysis parameters of the system. Naturally, there is still room for improvement in the methodology of SHAMAN, but already with the currently implemented features it is a reliable expert system for nuclide identification.
Keywords: gamma-ray spectrometry, airborne radioactivity, radionuclide identification
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© 2008 Helsinki University of Technology
Last update 2011-05-26