Abstract
Active interrogation systems for cargo inspection are designed to automatically determine the presence of special nuclear material (SNM) in transport by observing the radiation emitted by an object when exposed to an external radiation source. Active interrogation systems are contrasted with passive detection systems, such as radiation portal monitor systems, that detect the neutron and gamma radiation spontaneously emitted by SNM. Operational limitations to not interfere with commerce can restrict the use any interdiction system, including passive detection, active-interrogation and imaging systems. Because of their cost and complexity, active interrogation systems are intended for applications where SNM may be in shielded configurations that may not normally be detectable by passive systems. Active interrogation systems range from those that only indicate the presence of high-Z materials, to fissionable material detection, to those that detect specific SNM materials. The decision to deploy an AI system will depend on its ability to meet standards and specifications, its effectiveness, and its ability to fit into the operational environment. To ensure AI systems are designed and tested to a consistent level, minimum performance standards have been developed for evaluating these systems. Development of an active interrogation system that has the sensitivity to SNM that is needed while also being deployable is a challenge. It is the aim of standards to define a set of tests that can be performed on a system in an economic manner while challenging the capability of the system.
Richard Kouzes; with contributions from Edward Siciliano, Glen Warren (Pacific Northwest National Laboratory) and Peter Chiaro (Oak Ridge National Laboratory)
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Notes
- 1.
While AI systems are also used for other contraband detection, the focus here is only on standards for SNM detection.
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Kouzes, R. (2018). Active Interrogation Testing Standards. In: Jovanovic, I., Erickson, A. (eds) Active Interrogation in Nuclear Security. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-74467-4_11
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