Analysis of the multigroup model for muon tomography based threat detection

Perry, J.; Bacon, Jeffrey; Borozdin, K.; Fabritius, Joseph; Morris, C. L.

doi:10.1063/1.4865169

Cited by 10 publications

(3 citation statements)

References 20 publications

(12 reference statements)

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“…The multi-group model described in references [19,23,24] uses a multi-group model of the cosmic ray muon energy spectrum to fit the measured angular distribution. Unlike other methods, this provides a good description of the tails in the angular distribution and provides more precise thickness precision [25].…”

Section: Tomographic Algorithmmentioning

confidence: 99%

Application of muon tomography to fuel cask monitoring

Poulson

Bacon

Durham

et al. 2018

Phil. Trans. R. Soc. A.

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Section: Tomographic Algorithmmentioning

confidence: 99%

Application of muon tomography to fuel cask monitoring

Poulson

Bacon

Durham

et al. 2018

Phil. Trans. R. Soc. A.

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“…Without knowing the muon momentum, much more data will be needed to achieve the same image resolution for muon multiple scattering imaging. To counter this effect, Perry et al developed a multigroup method to improve the reconstructed image quality by fitting the muon angle distribution with a multigroup of Gaussian distributions corresponding to different momenta [16]. For muon absorption imaging, low-momentum muons can cause very large quantities of noise because their paths are no longer straight.…”

Section: Image Reconstruction Algorithmsmentioning

confidence: 99%

Novel muon imaging techniques

Yang

Clarkson

Gardner

et al. 2018

Phil. Trans. R. Soc. A.

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Owing to the high penetrating power of high-energy cosmic ray muons, muon imaging techniques can be used to image large bulky objects, especially objects with heavy shielding. Muon imaging systems work just like CT scanners in the medical imaging field—that is, they can reveal information inside of a target. There are two forms of muon imaging techniques: muon absorption imaging and muon multiple scattering imaging. The former is based on the flux attenuation of muons, and the latter is based on the multiple scattering of muons in matter. The muon absorption imaging technique is capable of imaging very large objects such as volcanoes and large buildings, and also smaller objects like spent fuel casks; the muon multiple scattering imaging technique is best suited to inspect smaller objects such as nuclear waste containers. Muon imaging techniques can be applied in a broad variety of fields, i.e. from measuring the magma thickness of volcanoes to searching for secret cavities in pyramids, and from monitoring the borders of countries checking for special nuclear materials to monitoring the spent fuel casks for nuclear safeguards applications. In this paper, the principles of muon imaging are reviewed. Image reconstruction algorithms such as Filtered Back Projection and Maximum Likelihood Expectation Maximization are discussed. The capability of muon imaging techniques is demonstrated through a Geant4 simulation study for imaging a nuclear spent fuel cask. This article is part of the Theo Murphy meeting issue ‘Cosmic-ray muography’.

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“…For example, the measured angular distribution of passing particles allows to classify the particles according their estimated energy [27]. The proposed momentum multi-group model method was experimentally tested and the reconstruction performance was quantitatively compared against the squared average, median angle squared and the average of squared angle using the receiver operating characteristic (ROC) curves [28]. The results demonstrate clear superiority for multi-group approach.…”

Section: Introductionmentioning

confidence: 99%

Atmospheric ray tomography for low-Z materials: implementing new methods on a proof-of-concept tomograph

Anbarjafari¹,

Anier²,

Avots³

et al. 2021

Preprint

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Cosmic rays interacting with the atmosphere result in a flux of secondary particles including muons and electrons. Atmospheric ray tomography (ART) uses the muons and electrons for detecting objects and their composition. This paper presents new methods and a proof-of-concept tomography system developed for the ART of low-Z materials. We introduce the Particle Track Filtering (PTF) and Multi-Modality Tomographic Reconstruction (MMTR) methods. Based on Geant4 models we optimized the tomography system, the parameters of PTF and MMTR. Based on plastic scintillating fiber arrays we achieved the spatial resolution 120 µm and 1 mrad angular resolution in the track reconstruction. We developed a novel edge detection method to separate the logical volumes of scanned object. We show its effectiveness on single (e.g. water, aluminum) and double material (e.g. explosive RDX in flesh) objects. The tabletop tomograph we built showed excellent agreement between simulations and measurements. We are able to increase the discriminating power of ART on low-Z materials significantly. This work opens up new routes for the commercialization of ART tomography.

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Analysis of the multigroup model for muon tomography based threat detection

Cited by 10 publications

References 20 publications

Application of muon tomography to fuel cask monitoring

Application of muon tomography to fuel cask monitoring

Novel muon imaging techniques

Atmospheric ray tomography for low-Z materials: implementing new methods on a proof-of-concept tomograph

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