Effect of Gamma-Ray Energy on Image Quality in Passive Gamma Emission Tomography of Spent Nuclear Fuel

Bélanger-Champagne, C.; Peura, P.; Eerola, P.; Honkamaa, Tapani; White, Timothy R.; Mayorov, Mikhail; Dendooven, P.

doi:10.1109/tns.2018.2881138

Cited by 15 publications

(9 citation statements)

References 14 publications

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“…The thresholds are typically selected to enhance the contribution of a single gamma-ray emitting isotope ( 137 Cs, 154 Eu) in each window. More detailed descriptions of the PGET instrument can be found in [4,6,10].…”

Section: Measurement With the Pget Instrumentmentioning

confidence: 99%

“…The PGET instrument is able to reliably identify single missing or replaced pins in WWER-440, BWR and PWR SFAs with burnups in the range of 5.7-57.8 GWd/tU and cooling times from 1.9-26.6 years [3][4][5]. Images reconstructed using gamma ray energies higher than those of 137 Cs (>700 keV) have better water-to-fuel contrast in fuel cooled for up to 20 years and thus have the most potential for missing fuel pin detection [6]. Following these first results, IAEA has expressed the need for new image reconstruction and processing methods for a more accurate assessment of the locations and count of missing pins and a more accurate calculation of the relative radioactivity levels of individual pins.…”

Section: Introductionmentioning

confidence: 99%

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Simultaneous reconstruction of emission and attenuation in passive gamma emission tomography of spent nuclear fuel

Backholm

Bubba

Bélanger-Champagne

et al. 2020

Inverse Problems &Amp; Imaging

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The International Atomic Energy Agency (IAEA) has recently approved passive gamma emission tomography (PGET) as a method for inspecting spent nuclear fuel assemblies (SFAs), an important aspect of international nuclear safeguards which aim at preventing the proliferation of nuclear weapons. The PGET instrument is essentially a single photon emission computed tomography (SPECT) system that allows the reconstruction of axial cross-sections of the emission map of the SFA. The fuel material heavily self-attenuates its gamma-ray emissions, so that correctly accounting for the attenuation is a critical factor in producing accurate images. Due to the nature of the inspections, it is desirable to use as little a priori information as possible about the fuel, including the attenuation map, in the reconstruction process. Current reconstruction methods either do not correct for attenuation, assume a uniform attenuation throughout the fuel assembly, or assume an attenuation map based on an initial filtered back projection (FBP) reconstruction. Here, we propose a method to simultaneously reconstruct the emission and attenuation maps by formulating the reconstruction as a constrained minimization problem with a least squares data fidelity term and regularization terms. Using simulated data, we compare the proposed method to FBP, showing that our approach produces significantly better reconstructions by various numerical metrics and a much better classification of spent, missing, and fresh fuel rods. † Currently with STUK, Finland ‡ Currently with TRIUMF, Canada

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Section: Measurement With the Pget Instrumentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simultaneous reconstruction of emission and attenuation in passive gamma emission tomography of spent nuclear fuel

Backholm

Bubba

Bélanger-Champagne

et al. 2020

Inverse Problems &Amp; Imaging

Self Cite

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“…This 2 mm stagger is devoted to obtaining 182 data collections, referred to as counts, per each view. The technical details of the PGET detector system are reported in [3,2,26].…”

Section: Introductionmentioning

confidence: 99%

Vanquishing the computational cost of passive gamma emission tomography simulations: a physics-aware reduced order modeling approach

Cavallini¹,

Ferretti²,

Boström³

et al. 2023

Preprint

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Passive Gamma Emission Tomography (PGET) has been developed by the International Atomic Energy Agency as a way to directly image the spatial distribution of individual fuel pins in a spent nuclear fuel assembly and so determine potential diversion.Constructing the analysis and interpretation of PGET measurements rely on the availability of comprehensive datasets. Experimental data are expensive, limited, and so are augmented by Monte Carlo simulations. The main issue concerning Monte Carlo simulations is the high computational cost to simulate the 360 angular views of the tomography. Similar challenges pervade numerical science.To address this challenge, we have developed a physics-aware reduced order modeling approach. It provides a framework to combine a small subset of the 360 angular views with a computationally inexpensive proxy solution, that brings the essence of the physics, to obtain a real-time high-fidelity solution at all angular views, but at a fraction of the computational cost.

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“…For any safeguards investigation of SFAs, it is important to use a minimum amount of a priori information on the SFA under study, in order to avoid biasing and potentially misleading the investigation. Eventually, IAEA approved the use of the passive gamma emission tomography (PGET) instrument [2][3][4][5][6][7] in inspections.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Activity Estimation and Uncertainty Quantification of Spent Nuclear Fuel Using Passive Gamma Emission Tomography

et al. 2021

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In this paper, we address the problem of activity estimation in passive gamma emission tomography (PGET) of spent nuclear fuel. Two different noise models are considered and compared, namely, the isotropic Gaussian and the Poisson noise models. The problem is formulated within a Bayesian framework as a linear inverse problem and prior distributions are assigned to the unknown model parameters. In particular, a Bernoulli-truncated Gaussian prior model is considered to promote sparse pin configurations. A Markov chain Monte Carlo (MCMC) method, based on a split and augmented Gibbs sampler, is then used to sample the posterior distribution of the unknown parameters. The proposed algorithm is first validated by simulations conducted using synthetic data, generated using the nominal models. We then consider more realistic data simulated using a bespoke simulator, whose forward model is non-linear and not available analytically. In that case, the linear models used are mis-specified and we analyse their robustness for activity estimation. The results demonstrate superior performance of the proposed approach in estimating the pin activities in different assembly patterns, in addition to being able to quantify their uncertainty measures, in comparison with existing methods.

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Effect of Gamma-Ray Energy on Image Quality in Passive Gamma Emission Tomography of Spent Nuclear Fuel

Cited by 15 publications

References 14 publications

Simultaneous reconstruction of emission and attenuation in passive gamma emission tomography of spent nuclear fuel

Simultaneous reconstruction of emission and attenuation in passive gamma emission tomography of spent nuclear fuel

Vanquishing the computational cost of passive gamma emission tomography simulations: a physics-aware reduced order modeling approach

Bayesian Activity Estimation and Uncertainty Quantification of Spent Nuclear Fuel Using Passive Gamma Emission Tomography

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