Standardization of 106 Ru/Rh by live-timed anticoincidence counting and gamma emission determination

2019 ◽

Vol 7 (2A) ◽

Author(s):

Guilherme Soares Zahn ◽

Regina Beck Ticianelli ◽

Mitiko Saiki ◽

Frederico Antonio Genezini

Keyword(s):

Stainless Steel ◽

Neutron Activation Analysis ◽

Neutron Activation ◽

Gamma Rays ◽

Experimental Error ◽

Steel Sample ◽

Low Energy ◽

Stainless Steel Sample ◽

Gamma Emission ◽

Energy Gamma

In IPEN’s Neutron Activation Laboratory (LAN/IPEN), thin stainless steel sample holders are used for gamma spectrometry in NAA measurements. This material is very practical, but its chemical composition may be troublesome, as it presents large amounts of elements with intermediate atomic number, with attenuation factors for low-energy gamma-rays that must not be neglected. In this study, count rates obtained using different sample holders were compared. To accomplish that, an Am-241 source, with 59-keV gamma emission, was used so that low-energy gamma attenuation differences can be determined. Moreover, in order to study the energy dependence of these differences, a Ho-166m source was also used. From these results, it was possible to analyze the experimental error associated to the variations between sample holders, with the aim of introducing an addictive term to the uncertainty analysis of comparative Neutron Activation Analysis results.

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Channeling, Volume Reflection and Gamma Emission Using 14GeV Electrons in Bent Silicon Crystals - General Abstract

10.2172/1213168 ◽

2015 ◽

Author(s):

Brandon Benson

Keyword(s):

Gamma Emission ◽

Silicon Crystals ◽

Volume Reflection ◽

General Abstract

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

Scientific Reports ◽

10.1038/s41598-021-82031-8 ◽

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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Standardization of 223Ra by live-time anticoincidence counting and gamma-ray emission determination

Applied Radiation and Isotopes ◽

10.1016/j.apradiso.2020.109559 ◽

2021 ◽

pp. 109559

Author(s):

R.F.P. Simões ◽

C.J. da Silva ◽

R.L. da Silva ◽

L.V. de Sá ◽

R. Poledna ◽

...

Keyword(s):

Gamma Ray ◽

Gamma Ray Emission ◽

Anticoincidence Counting

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Rapid imaging of special nuclear materials for nuclear nonproliferation and terrorism prevention

Science Advances ◽

10.1126/sciadv.abg3032 ◽

2021 ◽

Vol 7 (21) ◽

pp. eabg3032

Author(s):

Jana Petrović ◽

Alf Göök ◽

Bo Cederwall

Keyword(s):

Nuclear Physics ◽

Imaging Modality ◽

Three Dimensional ◽

Nuclear Fission ◽

Machine Learning Techniques ◽

Nuclear Materials ◽

Prototype System ◽

Fast Time ◽

Gamma Emission ◽

Special Nuclear Materials

We introduce a neutron-gamma emission tomography (NGET) technique for rapid detection, three-dimensional imaging, and characterization of special nuclear materials like weapons-grade plutonium and uranium. The technique is adapted from fundamental nuclear physics research and represents a previously unexplored approach to the detection and imaging of small quantities of these materials. The method is demonstrated on a radiation portal monitor prototype system based on fast organic scintillators, measuring the characteristic fast time and energy correlations between particles emitted in nuclear fission processes. The use of these correlations in real time in conjunction with modern machine learning techniques provides unprecedented imaging efficiency and high spatial resolution. This imaging modality addresses global security threats from terrorism and the proliferation of nuclear weapons. It also provides enhanced capabilities for addressing different nuclear accident scenarios and for environmental radiological surveying.

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