scholarly journals Nuclear Safeguards and Nondestructive Assay

2021 ◽  
Author(s):  
Alexis Trahan
Keyword(s):  
Nuclear Safeguards ◽  
Nondestructive Assay

scholarly journals Nondestructive Assay for Nuclear Safeguards

2021 ◽  
Author(s):  
Alexis Trahan
Keyword(s):  
Nuclear Safeguards ◽  
Nondestructive Assay

scholarly journals Nondestructive Assay of Fissile Material Samples in Support of Nuclear Safeguards

1974 ◽  
Vol 21 (1) ◽  
pp. 628-632 ◽  
Author(s):  
Albert E. Evans
Keyword(s):  
Nuclear Safeguards ◽  
Fissile Material ◽  
Nondestructive Assay

scholarly journals Nuclear Safeguards and Nondestructive Assay

2020 ◽  
Author(s):  
Alexis Chanel Trahan
Keyword(s):  
Nuclear Safeguards ◽  
Nondestructive Assay

scholarly journals OR14-V-Uncertainty-PD2La Uncertainty Quantification for Nuclear Safeguards and Nondestructive Assay Final Report

2017 ◽  
Author(s):  
Andrew D. Nicholson ◽  
Stephen Croft ◽  
Robert Dennis McElroy
Keyword(s):  
Uncertainty Quantification ◽  
Nuclear Safeguards ◽  
Final Report ◽  
Nondestructive Assay

scholarly journals Nondestructive Assay for Nuclear Safeguards

2020 ◽  
Author(s):  
Alexis Chanel Trahan
Keyword(s):  
Nuclear Safeguards ◽  
Nondestructive Assay

scholarly journals Nondestructive Assay for Nuclear Safeguards

2020 ◽  
Author(s):  
Alexis Trahan
Keyword(s):  
Nuclear Safeguards ◽  
Nondestructive Assay

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

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ming Fang ◽  
Yoann Altmann ◽  
Daniele Della Latta ◽  
Massimiliano Salvatori ◽  
Angela Di Fulvio
Keyword(s):  
Inverse Problem ◽  
Image Reconstruction ◽  
Image Resolution ◽  
Emission Tomography ◽  
Nuclear Safeguards ◽  
Activity Levels ◽  
Spent Fuel ◽  
Gamma Emission ◽  
Cross Sectional ◽  
Fuel Rods

AbstractCompliance 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%.

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