Abstract

The evaluation of fissile mass inside radioactive waste drums by neutron measurements is essential for radioactive waste management, nuclear safety, and criticality issues. However, passive and active neutron measurements can be strongly impacted by the uncertainty on the neutron source position within the drum and by the matrix effects. Therefore, an imaging panel proposed by Proportional Technologies Inc., and composed of seven boron-coated straw (BCS) detectors has been tested to localize neutron interactions, in view to reduce uncertainties associated with plutonium or uranium position inside radioactive waste drums. In a previous work, a numerical model of the imaging panel has been developed and validated from a comparison with experimental profiles obtained with a <sup>252</sup>Cf source. In the first section, the feasibility of neutron emission tomography by a setup composed of five extended imaging BCS panels is demonstrated by numerical Monte Carlo simulation. The second section details the experimental validation of the neutron emission tomography. Measurements are carried out with AmBe and <sup>252</sup>Cf sources located inside an empty 118 L drum by rotating the BCS imaging panel around it. Afterward, the Richardson&#x2013;Lucy deconvolution algorithm is applied to provide 2-D neutron source images for each angle. Finally, the 3-D images are reconstructed using the reconstruction toolkit (RTK) backprojection projection routine. The results demonstrate the capability of the BCS imaging to provide the 3-D location, i.e., axial and radial positions of one and two neutron sources. Furthermore, the first tests with this passive neutron measurement system show a satisfactory 3-D reconstruction for <sup>252</sup>Cf and AmBe sources separated by 20 cm. Consequently, BCS imaging panels open interesting prospects to reduce the uncertainty associated with plutonium or uranium localization in neutron measurements. Work is undergoing to assess the capability of this system for 118 L drums filled with organic and metallic matrices. Additionally, further prospects concern the performance of other deconvolution and reconstruction algorithms.

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