PNNL

Abstract

A Monte Carlo study of the neutron slowing-down spectrometry technique for measuring fissile isotopic content in irradiated fuel has been completed. The neutron spectrometer system is characterized in terms of design, slowing-down time relation, isotopic response functions, and assay signals. The nonlinear effect of interrogating neutron self-shielding for a high fissile content fuel is compared to the same parameter for a low fissile content fuel. Simulated assays of 23 different fuel assemblies with a broad range of total fissile mass content (1.3 to 8.3 wt%) and fissile isotopic ratios are performed and analyzed using two different methods: a linear system model using a least-squares regression analysis and a radial basis neural network. Mean errors using the linear system model for the 23 different fuel types were approximatley 20% for 233U and 43% for total plutonium. The radial basis neural network assay signal soltions showed promising results, considerably better than the linear model: 4.9% for 233U, 5.4% for total plutonium, and 0.5% for total fissile content.