Date of Award
Master of Science
Guillermo Maldonado, Ondrej Chvala
A significant portion of nuclear related research and application is dependent on the ability to utilize and improve nuclear data libraries. This has led to a tremendous amount of effort to be put in to develop and fill in the gaps in knowledge in these libraries. This analysis works to address this by categorizing and re-analyzing historical experimental data from High Flux Isotope Reactor (HFIR) in order to accurately characterize the HFIR neutron flux profile to improve precision for new experiments. If this historical data can be utilized in characterizing the neutron flux profile in HFIR to a reliable level, then it would allow for HFIR to perform high-precision new measurements. A methodology was developed for experiment information indexing by categorizing the flux into different regions, sample materials, and axial locations to create a detailed summary of important information of the experiments, which allows for more accurate comparison between samples. This re-analysis uses current nuclear data libraries to perform neutron spectral adjustment on material samples using the STAYSL PNNL suite. This analysis focuses on three distinct regions of the HFIR core: The Flux Trap, Peripheral Target Position, and Removable Beryllium regions. For each region, the chi-squared values for the fitted flux shapes remain low, implying STAYSL was able to find a neutron spectrum that fit well for each sample across all three major regions. Overall, between samples, there are low levels of variability in neutron flux, and a noticeable trend in variability decreasing for the neutron flux as the samples gets radially and axially closer to the center of the core. This holds true for each region across the entire energy spectrum. In addition, there is a clear delineation in the flux spectrum between samples from the 85 MW and the 100 MW cores in HFIR, implying distinct irradiation environments.
Stanford, Austin, "Flux Spectrum Adjustment in High Flux Isotope Reactor (HFIR). " Master's Thesis, University of Tennessee, 2020.