Development of a Numerical Experiment Technique to Solve Inverse Gamma-Ray Transport Problems with Application to Nondestructive Assay of Nuclear Waste Barrels

Abstract

A numerical experimental technique is presented to find an optimum solution to an undetermined inverse gamma-ray transport problem involving the nondestructive assay of radionuclide inventory in a nuclear waste drum. The method introduced is an optimization scheme based on performing a large number of numerical simulations that account for the counting statistics, the nonuniformity of source distribution, and the heterogeneous density of the self-absorbing medium inside the waste drum. The simulation model uses forward projection and backward reconstruction algorithms. The forward projection algorithm uses randomly selected source distribution and a first-flight kernel method to calculate external detector responses. The backward reconstruction algorithm uses the conjugate gradient with nonnegative constraint or the maximum likelihood expectation maximum method to reconstruct the source distribution based on calculated detector responses. Total source activity is determined by summing the reconstructed activity of each computational grid. By conducting 10 000 numerical simulations, the error bound and the associated confidence level for the prediction of total source activity are determined.

The accuracy and reliability of the simulation model are verified by performing a series of experiments in a 208-l waste barrel. Density heterogeneity is simulated by using different materials distributed in 37 egg-crate-type compartments simulating a vertical segment of the barrel. Four orthogonal detector positions are used to measure the emerging radiation field from the distributed source. Results of the performed experiments are in full agreement with the estimated error and the confidence level, which are predicted by the simulation model.