A Statistical Model for Generating a Population of Unclassified Objects and Radiation Signatures Spanning Nuclear Threats

This report describes an approach for generating a simulated population of plausible nuclear threat radiation signatures spanning a range of variability that could be encountered by radiation detection systems. In this approach, we develop a statistical model for generating random instances of smuggled nuclear material. The model is based on physics principles and bounding cases rather than on intelligence information or actual threat device designs. For this initial stage of work, we focus on random models using fissile material and do not address scenarios using non-fissile materials. The model has several uses. It may be used as a component in a radiation detection system performance simulation to generate threat samples for injection studies. It may also be used to generate a threat population to be used for training classification algorithms. In addition, we intend to use this model to generate an unclassified 'benchmark' threat population that can be openly shared with other organizations, including vendors, for use in radiation detection systems performance studies and algorithm development and evaluation activities. We assume that a quantity of fissile material is being smuggled into the country for final assembly and that shielding may have been placed around the fissile material. In terms of radiation signature, a nuclear weapon is basically a quantity of fissile material surrounded by various layers of shielding. Thus, our model of smuggled material is expected to span the space of potential nuclear weapon signatures as well. For computational efficiency, we use a generic 1-dimensional spherical model consisting of a fissile material core surrounded by various layers of shielding. The shielding layers and their configuration are defined such that the model can represent the potential range of attenuation and scattering that might occur. The materials in each layer and the associated parameters are selected from probability distributions that span the range of possibilities. Once an object is generated, its radiation signature is calculated using a 1-dimensional deterministic transport code. Objects that do not make sense based on physics principles or other constraints are rejected. Thus, the model can be used to generate a population of spectral signatures that spans a large space, including smuggled nuclear material and nuclear weapons