2025-08-11
Applying Machine Learning Algorithms to Classify Digitized Special Nuclear Material Obtained from Scintillation Detectors
2025-08-11 • Sai Kiran Kokkiligadda, Cathleen Barker, E. Gunger, Joseph E. Johnson, Bradley M. Turner, Andreas Enqvist
The capability to discriminate among nuclear fuel properties is essential for a successful nuclear safeguard and security program. Accurate nuclear material identification is hindered due to challenges such as differing levels of enrichments, weak radiation signals in the case of fresh nuclear fuel, and complex self-shielding effects. This study explores the application of supervised machine learning algorithms to digitized radiation detector data for classifying signatures of special nuclear materials. Three scin…