Foundations for Improvements to Passive Detection Systems - Final Report

This project explores the scientific foundation and approach for improving passive detection systems for plutonium and highly enriched uranium in real applications. Sources of gamma-ray radiation of interest were chosen to represent a range of national security threats, naturally occurring radioactive materials, industrial and medical radiation sources, and natural background radiation. The gamma-ray flux emerging from these sources, which include unclassified criticality experiment configurations as surrogates for nuclear weapons, were modeled in detail. The performance of several types of gamma-ray imaging systems using Compton scattering were modeled and compared. A mechanism was created to model the combine sources and background emissions and have the simulated radiation ''scene'' impinge on a model of a detector. These modeling tools are now being used in various projects to optimize detector performance and model detector sensitivity in complex measuring environments. This study also developed several automated algorithms for isotope identification from gamma-ray spectra and compared these to each other and to algorithms already in use. Verification testing indicates that these alternative isotope identification algorithms produced less false positive and false negative results than the ''GADRAS'' algorithms currently in use. In addition to these algorithms that used binned spectra, a new approach to isotope identification using ''event mode'' analysis was developed. Finally, a technique using muons to detect nuclear material was explored.