Generation of high fidelity covariance data sets for the natural molybdenum isotopes including a series of molybdenum sensitive critical experiment designs
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Quantification of uncertainty in computational models of nuclear systems is required for assessing margins of safety for both design and operation of those systems. The largest source of uncertainty in computational models of nuclear systems derives from the nuclear cross section data used for modeling. There are two parts to cross section uncertainty data: the relative uncertainty in the cross section at a particular energy, and how that uncertainty is correlated with the uncertainty at all other energies. This cross section uncertainty and uncertainty correlation is compiled as covariance data. High fidelity covariance data exists for a few key isotopes, however the covariance data available for many structural materials is considered low fidelity, and is derived primarily from integral measurements with little meaningful correlation between energy regions. Low fidelity covariance data is acceptable for materials to which the operating characteristics of the modeled nuclear system are insensitive. However, in some cases, nuclear systems can be sensitive to isotopes with only low fidelity covariance data. Such is the case for the new U(19.5%)-10Moly foil fuel form to be produced at the Y-12 National Security Complex for use in research and test reactors. This fuel is ten weight percent molybdenum, the isotopes of which have only low fidelity covariance data. Improvements to the molybdenum isotope covariance data would benefit the modeling of systems using the new fuel form. This dissertation provides a framework for deriving high fidelity molybdenum isotope covariance data from a set of elemental molybdenum experimental cross section results. Additionally, a series of critical experiments featuring the new Y-12 fuel form was designed to address deficiencies in the critical experiment library with respect to molybdenum isotopes. Along with existing molybdenum sensitive critical experiments, these proposed experiments were used as a basis to compare the performance of the new high fidelity molybdenum covariance data set with the existing low fidelity covariance data set using the nuclear modeling code SCALE. The use of the high fidelity covariance data was found to result in reduced overall bias, reduced bias due to the molybdenum isotopes, and improved goodness-of-fit of computational results to experimental results.