Investigation of a fast partial defect detection method for safeguarding PWR spent fuel assemblies

Identification of Diversions in Spent Pwr Fuel Assemblies by Pdet Signatures Using Artificial Neural Networks (Anns)

“…This task is crucial before the assemblies are transferred to dry cask storage or encapsulated for permanent repository disposal (Vaccaro et al, 2018), where further inspections become more challenging or impossible. In the safeguards community, the search for missing/replaced fuel pins in SNF assemblies is known as detection of partial defects (IAEA, 2022; Lee and Yim, 2020). Spent nuclear fuel is particularly sensitive from a safeguards perspective because of its residual fissile material such as 235 U and 239 Pu.…”