PNNL

Abstract

As nuclear warhead stockpiles are reduced under current and future arms treaties, accuracy in accountancy of material stockpiles becomes increasingly important. Image-based active interrogation offers advantages to spectroscopic detection in its ability to measure the location and extent of a material, or materials, of interest from a declaration. However, the detail that imaging provides is often viewed as too intrusive due to its potential to disseminate sensitive information. In this work, we present a method for reducing multi-energy, x-ray radiography data to a few important attributes, based on declarations from behind an information barrier, which can then be used to confirm or deny a declaration. We build on previous work by improving the physics modeling; considering currently attainable, multiple-endpoint x-ray systems; and posing the problem as a nonlinear, inverse problem. Regularization is added to the problem, which smooths the solution and stabilizes an otherwise unstable solution. Here we show the ability to discriminate high-atomic–number materials from others with simulated single-view multiple-endpoint radiography data and present results from initial bench-top measurements.