arXiv subjects

Zhengzhi Liu

Publications and source records attributed to Zhengzhi Liu.

5 recordsLinked to original sources

arXiv2026

Machine learning methods for subpixel trajectory reconstruction in discretized position detectors

In this study, we demonstrate that compared with traditional centroid-based methods, machine learning methods (particularly transformer-based architectures) achieve superior subpixel position and therefore angular resolution in discretized particle detectors. Using Geant4 Monte Carlo simulated cosmic ray muon data from an 8x8 segmented scintillator detector array, we compare four reconstruction approaches: transformer neural networks, convolutional neural networks, linear regression, and energy-weighted centroids. The transformer architecture achieves the best angular reconstruction with a root mean square error of 1.14° and a position mean absolute error of 0.24 cm, representing improvements of 2.22x and 6.33x, respectively, over the centroid method. These results enable precise particle trajectory reconstruction for applications in muon tomography and cosmic ray detection.

physics.ins-det↗

arXiv2018

Methodologies for imaging a used nuclear fuel dry storage cask with cosmic ray muon computed tomography

Muons interact with matter via two major interaction mechanisms: ionization and radioactive process, and multiple Coulomb scattering leading to energy loss and trajectory deflection, respectively. For a monoenergetic muon beam crossing an object, the scattering angle follows a Gaussian distribution with a zero mean value and a variance that depends on the atomic number of the material object it traversed. Thus, the measured scattering angle may be used to reconstruct the geometrical and material information of the contents inside the dry storage cask. In traditional X-ray computed tomography, the projection information used to reconstruct the attenuation map of the imaged objects is the negative natural logarithm of the transmission rate of the X-rays, which is equal to the linear summation of the X-ray attenuation coefficients along the incident path. Similarly, the variance of the muon scattering angle is also the linear integral of the scattering density of the objects crossed by the muons. Thus, a muon CT image can be built by equating scattering density with attenuation coefficient. However, muon CT faces some unique challenges including: 1) long measurement times due to low cosmic muon flux, 2) insufficiently accurate muon path models, and 3) the inability to precisely measuring muon momentum. In this work, three different muon path models, two different projection methods, and two different reconstruction methods were investigated for use in muon CT of dry storage casks. The investigation was conducted in a validated Geant4 workspace, both in an ideal case and with relevant engineering restrictions considered. The results of these investigations and the expected benefits for fuel cask monitoring are reported herein.

physics.ins-det↗

arXiv2018

Muon Tracing and Image Reconstruction Algorithms for Cosmic Ray Muon Computed Tomography

Cosmic ray muon computed tomography (μCT) is a new imaging modality with unique characteristics that could be particularly important for diverse applications including nuclear nonproliferation, spent nuclear fuel monitoring, cargo scanning, and volcano imaging. The strong scattering dependence of muons on atomic number Z in combination with high penetration range could offer a significant advantage over existing techniques when dense, shielded containers must be imaged. However, μCT reconstruction using conventional filtered back-projection is limited due to the overly simple assumptions that do not take into account the effects of multiple Coulomb scattering prompting the need for more sophisticated approaches to be developed. In this paper, we argue that the use of improved muon tracing and scattering angle projection algorithms as well as use of an algebraic reconstruction technique should produce muon tomographic images with improved quality or require fewer muons to produce the same image quality compared to the case where conventional methods are used. We report on the development and assessment of three novel muon tracing methods and two new scattering angle projection methods for μCT. Simulated dry storage casks with single and partial missing fuel assemblies were used as numerical examples to assess and compare the proposed methods. The simulated images showed an expected improvement in image quality when compared with more conventional techniques, even without muon momentum information, which should lead to improved detection capability, even for partial defects.

physics.ins-det↗

arXiv2018

A Generalized Muon Trajectory Estimation Algorithm with Energy Loss for Application to Muon Tomography

This work presents a generalized muon trajectory estimation (GMTE) algorithm to estimate the path of a muon in either uniform or nonuniform media. The use of cosmic ray muons in nuclear nonproliferation and safeguards verification applications has recently gained attention due to the nonintrusive and passive nature of the inspection, penetrating capabilities, as well as recent advances in detectors that measure position and direction of the individual muons before and after traversing the imaged object. However, muon image reconstruction techniques are limited in resolution due to low muon flux and the effects of multiple Coulomb scattering (MCS). Current reconstruction algorithms rely on overly simple assumptions for muon path estimation through the imaged object. For robust muon tomography, efficient and flexible physics based algorithms are needed to model the MCS process and accurately estimate the most probable trajectory of a muon as it traverses an object. In the present work, the use of a Bayesian framework and a Gaussian approximation of MCS are explored for estimation of the most likely path of a cosmic ray muon traversing uniform or nonuniform media and undergoing MCS. The algorithm's precision is compared to Monte Carlo simulated muon trajectories. It was found that the algorithm is expected to be able to predict muon tracks to less than 1.5 mm RMS for 0.5 GeV muons and 0.25 mm RMS for 3 GeV muons, a 50 percent improvement compared to SLP and 15 percent improvement when compared to PoCA. Further, a 30 percent increase in useful muon flux was observed relative to PoCA. Muon track prediction improved for higher muon energies or smaller penetration depth where energy loss is not significant. The effect of energy loss due to ionization is investigated, and a linear energy loss relation that is easy to use is proposed.

physics.comp-ph↗

arXiv2017

Detection of Missing Assemblies and Estimation of the Scattering Densities in a VSC-24 Dry Storage Cask with Cosmic-Ray-Muon-Based Computed Tomography

Highly energetic, cosmic-ray muons can easily penetrate a dry storage cask and yield information about the material inside it by making use of the physics of multiple Coulomb scattering. Work by others has shown this information may be used for verification of dry storage cask contents after continuity of knowledge has been lost. In our modeling and simulation approach, we use ideal planar radiation detectors to record the trajectories and momentum of both incident and exiting cosmic ray muons; this choice allows us to demonstrate the fundamental limit of the technology for a particular measurement and reconstruction method. In a method analogous to computed tomography with attenuation coefficient replaced by scattering density is we apply a filtered back projection algorithm in order to reconstruct both the geometry and material information in modeled scenarios for concrete-walled cask VSC-24. A scenario where one of the middle four spent nuclear fuel assemblies is missing undetectable with a simple PoCA-based approach is expected to be readily detectable with CT-based approach. Moreover, a trickier scenario where the one or more assemblies is replaced by dummy assembly is put forward. In this case, we expect that this dry storage cask should be found to be not as declared based on our simulation and reconstruction results. Furthermore, we show that the material composition can be estimated if the momentum of individual muons can be precisely measured.

physics.ins-det↗