Development of a List-Mode Collar for Fresh Fuel Pattern Recognition

Problem Statement

The uranium neutron coincidence collar (UNCL) comprised of 18 thermal neutron detector ³He tubes, AmLi(α,n) neutron source, and moderating material is currently deployed to actively interrogate fresh fuel assemblies and verify ²³⁵U linear mass density. No existing detection capability to verify loading patterns and partial defects in fresh fuel assemblies. Developing list mode data collection and analysis capabilities will advance the state of the art.

Technical Approach

Custom data collection electronics are designed, fabricated, and retrofit to the UNCL to demonstrate new list mode data collection capabilities. Radiation transport models are used to generate synthetic measurement data for a range of possible scenarios, and novel multivariate statistical learning (data analytics) methods are used to analyze data.

Benefit

Expand the capabilities of the neutron collar in terms of observable information, measurement accuracy and sensitivity, and/or measurement time. Help inspectors to draw stronger conclusions about nuclear material diversion and partial defect scenarios by extracting new signatures from a neutron assay of fresh fuel, including spatial information. Cost-effective way to improve existing neutron collar detectors in the field.