Neutron Rodeo Phase II Final Report

Fulvio, Angela Di; Shin, Tony H.; Clarke, Shaun D.; Pozzi, Sara A.; Sanders, J.E.; Chichester, David L.; Lee, Dongwon; Feng, Patrick L.; Root, Margaret A.; Geist, W. H.; Menlove, H.O.; Prasad, M. K.; Verbeke, Jérome; Gariazzo, Claudio Andres

doi:10.2172/1504942

Cited by 2 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Cases 2 and 3, we mimicked the scenario where fuel pins were missing. In Cases 4 and 5, we used depleted uranium to replace cobalt because it resulted in the highest attenuation among different potential replacement materials 10 , which would allow us to examine the algorithm's capability of distinguishing replaced pins. In Case 6, we wanted to explore whether the algorithm is able to render an accurate image of a space-dependent activity distribution.…”

Section: Resultsmentioning

confidence: 99%

Quantitative imaging and automated fuel pin identification for passive gamma emission tomography

Fang

Altmann

Latta

et al. 2021

Sci Rep

Self Cite

View full text Add to dashboard Cite

Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography (PGET) system is a novel instrument developed within the framework of the International Atomic Energy Agency (IAEA) project JNT 1510, which included the European Commission, Finland, Hungary and Sweden. The PGET is used for the verification of spent nuclear fuel stored in water pools. Advanced image reconstruction techniques are crucial for obtaining high-quality cross-sectional images of the spent-fuel bundle to allow inspectors of the IAEA to monitor nuclear material and promptly identify its diversion. In this work, we have developed a software suite to accurately reconstruct the spent-fuel cross sectional image, automatically identify present fuel rods, and estimate their activity. Unique image reconstruction challenges are posed by the measurement of spent fuel, due to its high activity and the self-attenuation. While the former is mitigated by detector physical collimation, we implemented a linear forward model to model the detector responses to the fuel rods inside the PGET, to account for the latter. The image reconstruction is performed by solving a regularized linear inverse problem using the fast-iterative shrinkage-thresholding algorithm. We have also implemented the traditional filtered back projection (FBP) method based on the inverse Radon transform for comparison and applied both methods to reconstruct images of simulated mockup fuel assemblies. Higher image resolution and fewer reconstruction artifacts were obtained with the inverse-problem approach, with the mean-square-error reduced by 50%, and the structural-similarity improved by 200%. We then used a convolutional neural network (CNN) to automatically identify the bundle type and extract the pin locations from the images; the estimated activity levels finally being compared with the ground truth. The proposed computational methods accurately estimated the activity levels of the present pins, with an associated uncertainty of approximately 5%.

show abstract

Section: Resultsmentioning

confidence: 99%

Quantitative imaging and automated fuel pin identification for passive gamma emission tomography

Fang

Altmann

Latta

et al. 2021

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

Neutron Detectors

Henzlova,

Baker,

Bartlett

et al. 2024

Nondestructive Assay of Nuclear Materials for Safeguards and Security

View full text Add to dashboard Cite

This chapter describes the principles of operation of the main types of neutron detector that are used in nondestructive assay. One section is devoted to gas detectors (3He and BF3) as well as boron-lined detectors, proton recoil detectors and fission chambers. A second section describes scintillation detectors. The description includes a discussion of light collection and signal acquisition. The measurement of neutron energy spectra is also described.

show abstract

Neutron Rodeo Phase II Final Report

Cited by 2 publications

References 8 publications

Quantitative imaging and automated fuel pin identification for passive gamma emission tomography

Quantitative imaging and automated fuel pin identification for passive gamma emission tomography

Neutron Detectors

Contact Info

Product

Resources

About