Feasibility of fuel cycle characterization using multiple nuclide signatures

The feasibility of identifying spent nuclear fuel arising from an unknown fuel cycle in terms of reactor type and burnup using a database of nuclide composition vectors generated for combinations of these two variables is examined. The database and test cases were generated using ORIGEN-ARP, and the concentrations of 200 nuclides were analyzed for each sample. Nearest neighbors and ridge regression techniques were used to make predictions of the reactor type and burnup of test cases. Various truncated nuclide lists were also tested. An initial examination of the techniques’ sensitivity to measurement error was made by perturbing the unknowns’ composition vector and examining the effect on each of the technique’s predictions. We demonstrate through the results of these experiments that investigation and development of multivariate data analysis methodologies for nuclear forensics applications is warranted.