Year
2011
Abstract
Waste materials from nuclear processes are often highly heterogeneous and distributed within poorly-characterized matrices. Neutron measurements are well suited for assaying heterogeneous mixtures because the high penetrability of neutrons allows a representative result to be obtained; however, they may require a correction for the effects of the matrix. The Add-a-Source technique has been used for many years for matrix corrections on waste drums and crates. For smaller containers, we have developed a new approach to matrix corrections called the Neutron Energy Leverage (NEL) technique. NEL is based on the efficiency curve of the neutron detector as a function of the hydrogen content of the measured item. The efficiency is a function of the hydrogen content in both the item and the detector. There is an under-moderated portion of the curve where the lower energy incident neutrons dominate the response, a peak at the optimal hydrogen content where the maximum count rate is achieved, and an over-moderated portion of the curve where the moderator begins to function as a shield. NEL requires a detector system with three rows of 3 He tubes: (1) a front row that sits on the under-moderated portion of the curve for a typical waste container, (2) a middle row that sits on the peak for optimal count rate, and (3) a back row that is significantly over-moderated. The waste assay uses the sum of the responses from all of the detectors for the passive doubles and multiplicity signals; whereas, the hydrogenous matrix correction uses the front-to-back ratio of the singles. An item with high hydrogen content will increase the efficiency of the front detectors while simultaneously reducing the back row efficiency. Thus, the front-to-back ratio provides a signature for the amount of hydrogen in the item and a correction function can be generated using MCNPX simulations. For small waste containers, NEL offers a convenient alternative to the Add-a-Source technique. In this paper, we explain the NEL technique in more detail, present proof-of-principle measurements, and discuss the results of a MCNPX modeling study