Enhancing Multiplicity Analysis with a Position-Corrected Efficiency Algorithm through ListMode data acquisition

Year
2023
Author(s)
Cole J. Thompson - Los Alamos National Laboratory
Robert K. Weinmann-Smith - Los Alamos National Laboratory
Brian Weaver - Los Alamos National Laboratory
Nik Economy - Los Alamos National Laboratory
Martyn Swinhoe - Los Alamos National Laboratory
Vlad Henzl - Los Alamos National Laboratory
Marc Ruch - Los Alamos National Laboratory
Audrey Roman - Los Alamos National Laboratory
Duc Vo - Los Alamos National Laboratory
Rollin Lakis - Los Alamos National Laboratory
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Abstract
Neutron nondestructive assay (NDA) is often used for assay of waste materials at nuclear facilities to characterize the amount of nuclear material contained within an item or matrix. Specifically, multiplicity counting can be applied to waste assay and is a mathematical model that uses three measured quantities, singles rate, doubles rate, and triples rate to determine three unknown quantities of interest: alpha, multiplication, and effective 240Pu mass. The advent of multi-channel list-mode data acquisition for neutron NDA allows for greater spatial resolution of data than ever before because the signal from each 3He tube can be recorded individually. These data can then be used in novel, complex analysis, for example to solve for other variables in the multiplicity equations. Efficiency is one variable in the multiplicity counting equations and can be one the largest drivers of an instrument’s total measurement uncertainty. This is because of the spatial variation of efficiency within the instrument well that is historically not captured by using a single, error-free, efficiency term, which leads to large deviations in the assayed effective 240Pu mass. This work presents an algorithm that uses multi-channel data readout from 3He tubes to identify the effective radial and axial position of material being assayed to update the efficiency value used in the neutron multiplicity counting equations. MCNP simulations of a small plutonium source in the High-Level Neutron Counter (HLNC) with many different matrix fill materials, similar to those encountered in waste assay, were performed. Results from these simulations show that using the position-corrected efficiency algorithm with multiplicity counting decreases the worst-case percent difference of assayed effective 240Pu mass to declared effective 240Pu mass by up to 70% compared to the assayed effective 240Pu mass using multiplicity with a single efficiency value.