Pyroprocessing is an electrochemical method for recovering actinides from used nuclear fuel and recycling them into fresh nuclear fuel. It is posited herein that proposed safeguards approaches on pyroprocessing for nuclear material control and accountability face several challenges due to the unproven plutonium-curium inseparability argument and the limitations of neutron counters. Thus, the Hybrid K-Edge Densitometer is currently being investigated as an assay tool for the measurement of pyroprocessing materials in order to perform effective safeguards. This work details the development of a computational model created using the Monte Carlo N-Particle code to reproduce HKED assay of samples expected from the pyroprocesses. The model incorporates detailed geometrical dimensions of the Oak Ridge National Laboratory HKED system, realistic detector pulse height spectral responses, optimum computational efficiency, and optimization capabilities. The model has been validated on experimental data representative of samples from traditional reprocessing solutions and then extended to the sample matrices and actinide concentrations of pyroprocessing. Data analysis algorithms were created in order to account for unsimulated spectral characteristics and correct inaccuracies in the simulated results. The realistic assay results obtained with the model have provided insight into the extension of the HKED technique to pyroprocessing safeguards and reduced the calibration and validation efforts in support of that design study. Application of the model has allowed for a detailed determination of the volume of the sample being actively irradiated as well as provided a basis for determining the matrix effects from the pyroprocessing salts on the HKED assay spectra.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/54358 |
Date | 07 January 2016 |
Creators | Mickum, George S. |
Contributors | Hertel, Nolan E. |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Language | en_US |
Detected Language | English |
Type | Dissertation |
Format | application/pdf |
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