DOE OSTI · 3017021
Quantifying uncertainty in uranium concentration measurements via K-edge densitometry
Abstract
This study quantifies the uncertainty in uranium concentration predictions of fluoride and chloride-based salts within a steel pipe using K-edge densitometry. Modeling and simulation was conducted with the Monte Carlo N-Particle Transport (MCNP) code. The quality of of this technique’s prediction in a pipe requires proper characterization of the pipe’s thickness, which is dependent on the source size and axial offset from the pipe centerline. The thickness was determined as either the center-line thickness seen by the X-ray source or an average value determined through random sampling. Generally, the predicted concentrations were slightly better at lower offset with the random sampling thickness and using the center-line thickness for the highest offsets. For a line-beam source and varying axial offsets, the relative error of concentration was within 1% of the true value but uncertainty increased by 2 orders of magnitude. Similarly, for no axial offset, the relative error was significantly less than 1% while no trend for uncertainty was found. However, at the largest possible offset for a given source size, the concentrations become erroneous and greater than the allowable 1% relative error. Furthermore, high offsets tended to increase the variance of the transmission spectra by 3 orders of magnitude.
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Henning, Aarin [Georgia Institute of Technology, Atlanta, GA (United States)] (ORCID:0009000081346422), Swinney, Mathew [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000181430157), Chirayath, Sunil [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000173896846), Hogue, Karen [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000159261510), Biegalski, Steve [Georgia Institute of Technology, Atlanta, GA (United States)]. 2025-10-24. Quantifying uncertainty in uranium concentration measurements via K-edge densitometry. https://doi.org/10.1007/s10967-025-10433-3
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