English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The detection of special nuclear materials (SNM) in commercial cargoes is a major objective in the field of nuclear security. In this work we investigate the use of two-neutron time-correlations from photo-fission using the Prompt Neutrons from Photofission (PNPF) detectors in Passport Systems Inc.’s (PSI) Shielded Nuclear Alarm Resolution (SNAR) platform for the purpose of detecting ∼5 kg quantities of fissionable materials in seconds. The goal of this effort was to extend the secondary scan mode of this system to differentiate fissile materials, such as highly enriched uranium, from fissionable materials, such as low enriched and depleted uranium (LEU and DU). Experiments were performed using a variety of material samples, and data were analyzed using the variance-over-mean technique referred to as Y2F or Feynman-α. Results were compared to computational models to improve our ability to predict system performance for distinguishing fissile materials. Simulations were then combined with empirical formulas to generate receiver operating characteristics (ROC) curves for a variety of shielding scenarios. We show that a 10 second screening with a 200 μA 9 MeV X-ray beam is sufficient to differentiate kilogram quantities of HEU from DU in various shielding scenarios in a standard cargo container.

Fissile material detection using neutron time-correlations from photofission