Exploration of Nuclear Material Discrimination Modeling and Boron Composition Effects

Abstract

The accuracy in the ability to discriminate nuclear materials is an essential aspect for nuclear security and material control purposes. The challenge in achieving competent levels of high fidelity and accuracy in this aspect are due to the complex radiation interactions that vary with enrichments levels and compositions of nuclear fuel materials. A solution would be a system whose ability is not only competent in the task of nuclear material discrimination, but one that could be performed successfully without the requirement of large time allocations for the purpose of practicality. This study is a supplementary addition to a previous study that explored the aforementioned accuracy of nuclear material discrimination with detection systems such as the EJ-309 liquid scintillator, CLYC crystal scintillator and EJ-276 plastic scintillator. The previous utilized these systems as well as machine learning refine a model had an accuracy greater than 96%. This study aims to explore the effects of boron content in discrimination accuracy and fidelity. In addition, this study’s purpose is to explore alterations to the previous model’s calculations that could refine model for increased discrimination capabilities with nuclear materials that are held in the contents of or have a composition of boron.