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Full-Text Articles in Engineering
An Assessment Of The Spatial Variation Of Isotopic Ratios In A Candu-6 Reactor For Nuclear Treaty Monitoring, Aaron W. Burkhardt
An Assessment Of The Spatial Variation Of Isotopic Ratios In A Candu-6 Reactor For Nuclear Treaty Monitoring, Aaron W. Burkhardt
Theses and Dissertations
The Preparatory Commission for the Comprehensive Nuclear Test Ban Treaty Organization developed the International Monitoring System for monitoring for nuclear explosive testing and compliance with nuclear treaties. Many of the International Monitoring System stations are capable of detecting radionuclides that can be used to determine their origin and creation environment. However, there is not a single unique signature associated with each creation environment. Nuclear reactors, for example, can have a wide range of isotopic concentrations caused by spatial variations in neutron flux intensity and energy. As a single sample only provides a single isotopic measurement, this can make disambiguation difficult …
Analysis Of The Correlation Between Re Filament Surface Features And Tims Performance, Christopher J. Mihal
Analysis Of The Correlation Between Re Filament Surface Features And Tims Performance, Christopher J. Mihal
Theses and Dissertations
Thermal Ionization Mass Spectrometry (TIMS) is an invaluable tool in nuclear forensics as it enables isotopic assays of actinides to be measured, permitting analysis to include special nuclear material isotopic assays, nuclear reactor monitoring, and treaty verification. In one method of measurement for the TIMS system, samples are deposited in solution form on high-purity rhenium filaments. The filaments are heated to evaporate the solvent, and then further heated to cause sample ionization, permitting the sample to be transmitted through a magnetic field which separates ions based on mass to charge ratio into detectors for counting. Heavier ions will be deflected …
A Machine Learning Approach To Characterizing Particle Morphology In Nuclear Forensics, Daniel A. Gum
A Machine Learning Approach To Characterizing Particle Morphology In Nuclear Forensics, Daniel A. Gum
Theses and Dissertations
A machine learning approach is taken to characterizing a group of synthetic uranium bearing particles. SEM images of these lab-created particles were converted into a binary representation that captured morphological features in accordance with a guide established by Los Alamos National Laboratory. Each particle in the dataset contains an association with chemical creation conditions: processing method, precipitation temperature and pH, calcination temperature are most closely tied to particle morphology. Additionally, trained classifiers are able to relate final products between particles, implying that morphological features are shared between particles with similar composition.