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Characterization And Analysis Of Bomarc Accident Debris, Aaron J. Heffelfinger
Characterization And Analysis Of Bomarc Accident Debris, Aaron J. Heffelfinger
Theses and Dissertations
Accidents involving nuclear weapons, such as the Boeing Michigan Aeronautical Research Center (BOMARC) accident in 1960, always pose a significant risk of allowing particles composed of nuclear materials to enter the environment. These particles often differ in characteristics and can be of greatly varying sizes. Gamma ray analysis was conducted on the soil sample and radioisotopes within the sample were identified. Two non-destructive methods for locating actinide bearing particles within the sample were testing, resulting in 70 actinide bearing particles ranging from 1-34 microns being identified. These 70 particles underwent both morphological and elemental characterization, indicating uranium and other elements.
Application Of Artificial Neural Networks To Elemental Assay Data For Nuclear Forensics Analysis, Jason G. Seik
Application Of Artificial Neural Networks To Elemental Assay Data For Nuclear Forensics Analysis, Jason G. Seik
Theses and Dissertations
There is a need to quickly and accurately determine the likely physical origins of a collected sample for nuclear treaty verification purposes. The objective of this research is to prove there is a means to relate different samples (Q-values) to one another using a 'same versus not-same' artificial neural network called a Siamese network. This would provide the capability of comparing an unknown sample to a database of samples with known physical origins. Using moment transformations on current data has shown to increase the prediction capabilities of a Siamese network, and using a triplet loss function in connection with the …
Error Reduction For The Determination Of Transverse Moduli Of Single-Strand Carbon Fibers Via Atomic Force Microscopy, Joshua D. Frey
Error Reduction For The Determination Of Transverse Moduli Of Single-Strand Carbon Fibers Via Atomic Force Microscopy, Joshua D. Frey
Theses and Dissertations
The transverse modulus of single strand carbon fibers is measured using PeakForce Atomic Force Microscopy - Quantitative Nanomechanical Measurement to less than 5 percent error for 11 types of carbon fiber with longitudinal moduli between 924-231 GPA, including export-controlled fibers. Statistical methods are employed to improve the quality of data to exclude outliers within an measurement and within the sample set. A positive linear correlation between the longitudinal and transverse modulus with an R2=0.76 is found. Pitch-based fibers exhibit lower measurement error than PAN-based fibers, while PAN fibers exhibited no apparent modulus correlation when the Pitch fibers are …