Progress on Associate-Particle Imaging Algorithms, 2020

Hausladen, Paul; Blackston, M. A.; Mattingly, John; Gregor, Jens; Gilbert, Andrew

doi:10.2172/1764473

Cited by 3 publications

(1 citation statement)

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“…𝑥 * = argmin ψ(𝑥) such that TV(𝑥) < 𝜀 Matrix 𝐴 models the system geometry and physics associated with the induced gamma reactions; matrix 𝑊 implements statistical weighting; and vectors 𝑥 and 𝑦 represent the image being reconstructed and the acquired projection data, respectively, as reported previously [1,2]. Each equation in the linear system represents what happens to neutrons as they travel in the direction of an alpha ray from the D-T source toward the detector array.…”

Section: High-level Summary Of Fy 2020-2021 Effortsmentioning

confidence: 99%

Progress on Associated-Particle Imaging Algorithms, 2022

Hausladen,

Heath,

Newby

et al. 2022

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The present work describes progress on developing imaging algorithms that use fast neutron signatures acquired using the associated-particle imaging (API) method. The present work complements ongoing work to develop neutron source and detector hardware to enable field inspection by investigating algorithms that can discriminate among critical materials or extract 3D geometrical information from single-sided or transmission measurements. The present work has three focus areas:1. Iterative reconstruction of inelastic gamma-ray emissions to perform 3D time-of-flight (TOF) imaging in a single view in either transmission or backscatter configurations. Iterative reconstruction enables better image resolution than the inherent TOF resolution.2. Decomposition of registered neutron and x-ray radiographs into an assumed material list for each pixel in the image.3. Material identification using full spectral analysis that includes the emergent neutron and gamma-ray energies, times, and angles.Progress for each approach is summarized for FY 2022.

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Section: High-level Summary Of Fy 2020-2021 Effortsmentioning

confidence: 99%