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http://hdl.handle.net/11375/26906
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DC Field | Value | Language |
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dc.contributor.advisor | Novog, David | - |
dc.contributor.author | MacConnachie, Elizabeth | - |
dc.date.accessioned | 2021-09-27T14:47:45Z | - |
dc.date.available | 2021-09-27T14:47:45Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://hdl.handle.net/11375/26906 | - |
dc.description.abstract | Nuclear research reactors offer a unique opportunity to the scientific community to investigate phenomena that are significant to both the renewable energy sector and the radiopharmaceutical industry. As the neutron flux dictates in-core processes that are crucial both to reactor operations and isotope production, highly precise measurements of this value are generally required to optimize and validate reactor physics analyses and day-to-day operations. Although neutron flux measurements in research reactors are well-documented, a detailed investigation of their uncertainties, and a methodology to quantify and combine them, has not yet been undertaken. These uncertainties are required to perform direct validation studies between experimental data and simulation models, to perform high-fidelity sensitivity and uncertainty quantification analyses, and to provide a basis for optimizing experimental activation processes in research reactor facilities. Several experimental campaigns in the McMaster Nuclear Reactor (MNR) were designed to quantify the effects of various reactor parameters on neutron flux measurements. It was determined that the indicated reactor power and the sample positioning in the irradiation site are the most significant contributors to the final reported neutron flux uncertainty. By combining an experimental campaign with historical core data and Monte-Carlo models of MNR, it was determined that the effects of fuel management were generally insignificant and do not contribute significantly to the reported neutron flux uncertainty. A Bayesian-based, Markov-Chain Monte-Carlo (MCMC) model was developed to accept fully covariant sets of nuclear data as inputs, such that their uncertainties could be included in a spectrum unfolding analysis. While nuclear data uncertainties are generally insignificant compared to other sources of uncertainty, the choice of flux spectrum parameterization may account for the trends in the final flux uncertainty across the energy spectrum. | en_US |
dc.language.iso | en | en_US |
dc.title | NEUTRON FLUX MEASUREMENTS FOR UNCERTAINTY QUANTIFICATION AT THE MCMASTER NUCLEAR REACTOR | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Engineering Physics | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Doctor of Philosophy (PhD) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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MacConnachie_Elizabeth_L_202109_PhD.pdf | 2.95 MB | Adobe PDF | View/Open |
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