Inverse Method for Noninvasive Material Discrimination with Multienergy X-Ray Radiography

Andrew J. Gilbert, Benjamin S. McDonald, and Mark R. Deinert
Phys. Rev. Applied 18, 054043 – Published 15 November 2022
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Abstract

Active x-ray inspections have great potential for noninvasive detection of illicit materials. Dual-energy x-ray radiography, in particular, has been used to determine material composition by utilizing the energy-dependence of the x-ray attenuation coefficients. However, current implementations of this method are limited in their ability to determine the material composition of composite objects. Here we present an inverse algorithm that uses multienergy x-ray radiography data to noninvasively reconstruct the contents of a container. A critical feature of the current contribution is that material identification can be performed using conventional detectors and x-ray spectra with different endpoint energies produced by varying nothing more than the tube voltage. Adaptive regularization is used to increase the accuracy of material estimations from multienergy data sets. The utility of these methods is demonstrated with experimentally acquired radiographs obtained using a tunable x-ray source that produces spectra with endpoint energies of 100–450 keV. The object inspected is a scale model of a nuclear materials storage container composed of three-dimensional printed plastic and stainless-steel spheres inside a thin-walled steel container. Reconstructions of the steel sphere thicknesses are within a root-mean-square error of 0.37 cm.

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  • Received 4 June 2022
  • Accepted 15 August 2022

DOI:https://doi.org/10.1103/PhysRevApplied.18.054043

© 2022 American Physical Society

Physics Subject Headings (PhySH)

Nuclear PhysicsCondensed Matter, Materials & Applied PhysicsAtomic, Molecular & Optical

Authors & Affiliations

Andrew J. Gilbert1, Benjamin S. McDonald1, and Mark R. Deinert2,*

  • 1Pacific Northwest National Laboratory, Richland, Washington 99354, USA
  • 2Colorado School of Mines, Golden, Colorado 80401, USA

  • *mdeinert@mines.edu

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Vol. 18, Iss. 5 — November 2022

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