arXiv subjects

Angela Di Fulvio

Publications and source records attributed to Angela Di Fulvio.

17 recordsLinked to original sources

arXiv2026

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for scientific discovery demands real-time inference and decision-making, intelligent data reduction, and efficient processing architectures beyond current capabilities. Crucial to the success of this experimental paradigm are several emerging technologies, such as artificial intelligence and machine learning (AI/ML), silicon microelectronics, and the advent of quantum algorithms and processing. Their intersection includes areas of research such as low-power and low-latency devices for edge computing, heterogeneous accelerator systems, reconfigurable hardware, novel codesign and synthesis strategies, readout for cryogenic or high-radiation environments, and analog computing. This white paper presents a community-driven vision to identify and prioritize research and development opportunities in hardware-based ML systems and corresponding physics applications, contributing towards a successful transition to the new data frontier of fundamental science.

physics.ins-det↗

arXiv2024

Ortho-positronium Lifetime For Soft-tissue Classification

The objective of this work is to showcase the ortho-positronium lifetime as a probe for soft-tissue characterization. We employed positron annihilation lifetime spectroscopy to experimentally measure the three components of the positron annihilation lifetime para-positronium (p-Ps), positron, and ortho-positronium (o-Ps) for three types of porcine, non-fixated soft tissues ex vivo: adipose, hepatic, and muscle.Then, we benchmarked our measurements with X-ray phase-contrast imaging, which is the current state-of-the-art for soft-tissue analysis. We found that the o-Ps lifetime in adipose tissues (2.54+/-0.12) ns was approximately 20\% longer than in hepatic (2.04+/-0.09 ns) and muscle (2.03+/-0.12 ns) tissues .In addition, the separation between the measurements for adipose tissue and the other tissues was better from o-Ps lifetime measurement than from X-ray phase-contrast imaging. This experimental study proved that the o-Ps lifetime is a viable non-invasive probe for characterizing and classifying the different soft tissues. Specifically, o-Ps lifetime as a soft-tissue characterization probe had a strong sensitivity to the lipid content that can be potentially implemented in commercial positron emission tomography scanners that feature list-mode data acquisition.

physics.ins-det↗

arXiv2024

Deep-learning Segmentation of Small Volumes in CT images for Radiotherapy Treatment Planning

Our understanding of organs at risk is progressing to include physical small tissues such as coronary arteries and the radiosensitivities of many small organs and tissues are high. Therefore, the accurate segmentation of small volumes in external radiotherapy is crucial to protect them from over-irradiation. Moreover, with the development of the particle therapy and on-board imaging, the treatment becomes more accurate and precise. The purpose of this work is to optimize organ segmentation algorithms for small organs. We used 50 three-dimensional (3-D) computed tomography (CT) head and neck images from StructSeg2019 challenge to develop a general-purpose V-Net model to segment 20 organs in the head and neck region. We applied specific strategies to improve the segmentation accuracy of the small volumes in this anatomical region, i.e., the lens of the eye. Then, we used 17 additional head images from OSF healthcare to validate the robustness of the V Net model optimized for small-volume segmentation. With the study of the StructSeg2019 images, we found that the optimization of the image normalization range and classification threshold yielded a segmentation improvement of the lens of the eye of approximately 50%, compared to the use of the V-Net not optimized for small volumes. We used the optimized model to segment 17 images acquired using heterogeneous protocols. We obtained comparable Dice coefficient values for the clinical and StructSeg2019 images (0.61 plus/minus 0.07 and 0.58 plus/minus 0.10 for the left and right lens of the eye, respectively)

eess.IV↗

arXiv2024

Enabling pulse shape discrimination with commercial ASICs

Fast electronic readout for high-channel density scintillator-based systems is needed for radiation tracking and imaging in a wide range of applications, including nuclear physics, nuclear security and nonproliferation. Programmable electronics, like FPGAs and ASICs, provide a fast way of conditioning and processing the signal in real time. In this paper, we present a pulse shape discrimination (PSD) method based on the shaping circuit of a commercially available ASIC, the Citiroc1A by CAEN Technologies. We used two different shaping times per detector channel to calculate a shaping parameter that enables PSD. Using our new method, neutron and gamma-ray pulses detected by a d$_{12}$-stilbene scintillator can be effectively discriminated at light output values greater than 0.15 MeVee. While not achieving the PSD performance of traditional offline charge integration, our method does not require the transfer of data to a separate system for further processing and enables the direct deployment of high-channel density multi-particle detection systems. Moreover, the availability of a wider range of shaping times than those on the Citiroc1A can potentially further improve the PSD performance.

physics.ins-det↗

arXiv2024

Statistical modelling and Bayesian inversion for a Compton imaging system: application to radioactive source localisation

This paper presents a statistical forward model for a Compton imaging system, called Compton imager. This system, under development at the University of Illinois Urbana Champaign, is a variant of Compton cameras with a single type of sensors which can simultaneously act as scatterers and absorbers. This imager is convenient for imaging situations requiring a wide field of view. The proposed statistical forward model is then used to solve the inverse problem of estimating the location and energy of point-like sources from observed data. This inverse problem is formulated and solved in a Bayesian framework by using a Metropolis within Gibbs algorithm for the estimation of the location, and an expectation-maximization algorithm for the estimation of the energy. This approach leads to more accurate estimation when compared with the deterministic standard back-projection approach, with the additional benefit of uncertainty quantification in the low photon imaging setting.

stat.AP↗

arXiv2023

Rotation-Invariant Rapid TRISO-Fueled Pebble Identification Based on Feature Matching and Point Cloud Registration

Pebble bed reactor (PBR) relying on TRISO-fueled pebbles is one of the most promising Gen-IV reactor designs because of intrinsic safety and thermal efficiency. Fuel pebbles flow through PBR's core and the identification of individual pebbles exiting the core will be beneficial to improve safeguards and fuel management. We propose a pebble identification method that is fast, accurate, robust, and applicable to PBRs containing hundreds of thousands of pebbles. The identification relies on the internal distribution of TRISO fuel particles, which is a unique feature of each pebble. We experimentally demonstrated that X-ray CT can extract the particle distribution with high accuracy. We then applied the algorithm to identify a single pebble in a data set of 100,000 pebbles achieving 100% identification accuracy in 90,000 tests with the presence of arbitrary rotations and measurement noises. The average time to identify one pebble is below 50 s, compatible with PBR operation.

physics.data-an↗

arXiv2023

Simulation of Charge Collection in a Boron-coated Straw Detector for Emerging Fuel Cycles

Tristructural-isotropic (TRISO) fuel is currently one of the most mature fuel types for candidate advanced reactor types, namely pebble bed reactors (PBRs). In PBRs, TRISO-fueled pebbles can be re-introduced into the core several times before reaching their target burnup. Non-destructive techniques capable of assaying ${}^{235}$U mass in the pebble are therefore needed for nuclear material control and accountability during fuel recirculation. In this work, we have developed a new boron-coated straw (BCS) based neutron multiplicity counter (NMC) to estimate ${}^{235}$U mass in each pebble. BCS detectors are chosen for their inherent high insensitivity to gamma rays that will enable their use to assay also irradiated pebbles and high neutron detection efficiency, comparable to ${}^{3}$He detectors. The BCS-based NMC that we have designed was built by Proportional Technologies, Inc. (PTI) Houston, TX. In this work, we report the system-level simulation of the BCS-based NMC and the straw-level charge collection simulation coupled with a custom software to tally the detected pulse integral from the list mode energy deposited. We have developed a high-fidelity model of the NMC to simulate the response of a single straw detector to a ${}^{252}$Cf source. The simulated die-away time, single neutron count rate, and double neutron count rate agree well with measured values, with a relative difference within $\pm$0.4\%. The simulated charge spectrum agrees well with the measured one in the case of a round straw. We plan to use the NMC to perform active and passive interrogation of fresh and spent fuel pebbles.

physics.ins-det↗

arXiv2023

Feasibility of Neutron Coincidence Counting for Spent Fuel

High-temperature gas reactors rely on TRIstructural-ISOtropic (TRISO) fuel for enhanced fission product retention. Accurate fuel characterization would improve monitoring of efficient fuel usage and accountability. We developed a new neutron multiplicity counter (NMC) based on boron coated straw (BCS) detectors and used it in coincidence mode for 235U assay in TRISO fuel. In this work, we demonstrate that a high-efficiency version of the NMC encompassing 396 straws is able to estimate the 235U in used TRISO-fueled pebbles or compacts with a relative uncertainty below 2.5% in 100 s. We performed neutronics and fuel depletion calculation of the HTR-10 pebble bed reactor to estimate the neutron and gamma-ray source strengths of used TRISO-fueled pebbles with burnup between 9 and 90 GWd/t. Then, we measured a gamma-ray intrinsic efficiency of 10^-12 at an exposure rate of 340.87 R/h. The low gamma-ray sensitivity and high neutron detection efficiency enable the inspection of used fuel.

physics.ins-det↗

arXiv2023

Generalized Method for the Optimization of Pulse Shape Discrimination Parameters

Organic scintillators exhibit fast timing, high detection efficiency for fast neutrons and pulse shape discrimination (PSD) capability. PSD is essential in mixed radiation fields, where different types of radiation need to be detected and discriminated. In neutron measurements for nuclear security and non proliferation effective PSD is crucial, because a weak neutron signature needs to be detected in the presence of a strong gamma-ray background. The most commonly used deterministic PSD technique is charge integration (CI). This method requires the optimization of specific parameters to obtain the best gamma-neutron separation. These parameters depend on the scintillating material and light readout device and typically require a lengthy optimization process and a calibration reference measurement with a mixed source. In this paper, we propose a new method based on the scintillation fluorescence physics that enables to find the optimum PSD integration gates using only a gamma-ray emitter. We demonstrate our method using three organic scintillation detectors: deuterated trans-stilbene, small-molecule organic glass, and EJ-309. In all the investigated cases, our method allowed finding the optimum PSD CI parameters without the need of iterative optimization.

physics.ins-det↗

arXiv2023

Boron Coated Straw-based Neutron Multiplicity Counter for Neutron Interrogation of TRISO Fueled Pebbles

Pebble bed reactors (PBRs) can improve the safety and economics of the nuclear energy production. PBRs rely on TRIstructural-ISOtropic (TRISO) fuel pebbles for enhanced fission product retention. Accurate characterization of individual fuel pebbles would enable the validation of computational models, efficient use of TRISO fuel, and improve fuel accountability. We have developed and tested a new neutron multiplicity counter (NMC) based on 192 boron coated straw (BCS) detectors optimized for ${}^{235}$U assay in TRISO fuel. The new design yielded a singles and doubles neutron detection efficiency of 4.71% and 0.174%, respectively, and a die-away time of 16.7 $\mathrmμ$s. The NMC has a low intrinsic gamma-ray detection efficiency of $8.71\times10^{-8}$ at an exposure rate of 80.3 mR/h. In simulation, a high-efficiency version of the NMC encompassing 396 straws was able to estimate the ${}^{235}$U in a pebble with a relative uncertainty and error both below 2% in 100 s.

physics.ins-det↗

arXiv2022

Nonproliferation and fusion power plants

This is an abridged abstract; please see the full paper. This paper evaluates whether the nuclear nonproliferation regime applies to fusion power plants and finds that, legally, the regime does not apply. The paper then examines whether the nonproliferation regime should apply to fusion based on a technical evaluation. The paper concludes that fusion should continue to fall outside the nonproliferation regime and that the global, dual-use export control regime, including potentially developing a "controls by design" usage-based control regime, is better suited for commercial fusion energy.

physics.soc-ph↗

arXiv2022

Enabling PSD-capability for a High-density Channel Imager

Pulse shape discrimination (PSD) is crucial for non-proliferation and security applications, where fast neutrons need to be identified and measured in the presence of a strong gamma-ray background. The traditional charge-integration-based PSD method requires the storage and processing of hundreds of samples for every single pulse, which is time- and memory-consuming for high-density channel applications. In this work, we explored the possibility of implementing PSD using a commercial ASIC that allows the user to adjust the pulse shaping time. We demonstrated that PSD can be achieved by maximizing the difference between the pulse shaping circuit's responses to neutron and gamma-ray pulses.

physics.ins-det↗

arXiv2022

Algorithms for TRISO Fuel Identification Based on X-ray CT Validated on Tungsten-Carbide Compacts

Tristructural-isotropic (TRISO) fuel is one of the most mature fuel types for candidate advanced reactor types under development. TRISO-fuel pebbles flow continuously through the reactor core and can be reinserted into the reactor several times until a target burnup is reached. The capability of identifying individual fuel pebbles would allow us to calculate the fuel residence time in the core and validate pebble flow computational models, prevent excessive burnup accumulation or premature fuel discharge, and maintain accountability of special nuclear materials during fuel circulation. In this work, we have developed a 3D image reconstruction and segmentation algorithm to accurately segment TRISO particles and extract the unique 3D distribution. We have developed a rotation-invariant and noise-robust identification algorithm that allows us to identify the pebble and retrieve the pebble ID in the presence of rotations and noises. We also report the results of 200kV X-ray CT image reconstruction of a mock-up fuel sample consisting of tungsten-carbide (WC) kernels in a lucite matrix. The 3D distribution of TRISO particles along with other signatures such as $^{235}$U enrichment and burnup level extracted through neutron multiplicity counting, would enable accurate fuel identification in a reasonable amount of time.

physics.ins-det↗

arXiv2021

Neutron Tomography of Spent Fuel Casks

Dry casks for spent nuclear fuel (SNF) ensure the safe storage of SNF and provide radiation shielding. However, the presence of the thick casks encompassing several layers of steel and concrete makes inspection of the SNF a challenging task. Fast neutron interrogation is a viable method for the nondestructive assay of dry storage casks. In this study, we performed a Monte Carlo simulation-based study associated with a machine-learning-based image reconstruction method to verify the content of SNF dry storage casks. We studied the use of neutron transmission and back-scattered measurements to assess the potential damage to fuel assemblies or fuel pin diversion during transportation of dry casks. We used Geant4 to model a realistic HI-STAR 100 cask, MPC-68 canister and basket, and GE-14 fuel assembly irradiated by a D-T neutron generator. Several bundle diversion scenarios were simulated. The angular distribution of the neutrons scattered by the cask was used to identify the diversions inside the fuel cask. A fuel bundle with at least 75% of its pins removed can be identified with a drop in the back-scattered signature larger than 2σ compared with a fully loaded scenario. We combined an iterative reconstruction algorithm with a convolutional neural network (CNN) to obtain a cross-sectional image of the fuel inside the cask. The proposed imaging approach allows locating the position of a missing fuel bundle with at least 75% of the pins removed when performing tomographic imaging of a canister with an overall scan time of less than two hours, when using a commercial neutron generator with a source strength of 10^10 n/s in the 4π solid angle.

physics.ins-det↗

arXiv2021

Effect of natural gamma background radiation on portal monitor radioisotope unmixing

National security relies on several layers of protection. One of the most important is the traffic control at borders and ports that exploits Radiation Portal Monitors (RPMs) to detect and deter potential smuggling attempts. Most portal monitors rely on plastic scintillators to detect gamma rays. Despite their poor energy resolution, their cost effectiveness and the possibility of growing them in large sizes makes them the gamma-ray detector of choice in RPMs. Unmixing algorithms applied to organic scintillator spectra can be used to reliably identify the bare and unshielded radionuclides that triggered an alarm, even with fewer than 1,000 detected counts and in the presence of two or three nuclides at the same time. In this work, we experimentally studied the robustness of a state-of-the-art unmixing algorithm to different radiation background spectra, due to varying atmospheric conditions, in the 16 $^\circ$C to 28 $^\circ$C temperature range. In the presence of background, the algorithm is able to identify the nuclides present in unknown radionuclide mixtures of three nuclides, when at least 1,000 counts from the sources are detected. With fewer counts available, we found larger differences of approximately 35.9$\%$ between estimated nuclide fractions and actual ones. In these low count rate regimes, the uncertainty associated by our algorithm with the identified fractions could be an additional valuable tool to determine whether the identification is reliable or a longer measurement to increase the signal-to-noise ratio is needed. Moreover, the algorithm identification performances are consistent throughout different data sets, with negligible differences in the presence of background types of different intensity and spectral shape.

physics.ins-det↗

arXiv2020

Quantitative Imaging and Automated Fuel Pin Identification for Passive Gamma Emission Tomography

Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography system is a novel instrument developed by the International Atomic Energy Agency (IAEA) 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. We implemented a linear forward model to model the detector responses to the fuel rods inside the PGET. 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 method 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 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%.

physics.ins-det↗

arXiv2019

Positron Annihilation Lifetime Spectroscopy Using Fast Scintillators and Digital Electronics

Positron Annihilation Lifetime Spectroscopy (PALS) is a non-destructive radiological technique widely used in material science studies. PALS typically relies on an analog coincidence measurement setup and allows the estimate of the positron lifetime in a material sample under investigation. The positronium trapping at vacancies in the material results in an increased lifetime. In this work, we have developed and optimized a PALS experimental setup using organic scintillators, fast digitizers, and advanced pulse processing algorithms. We tested three pairs of different organic scintillation detectors: EJ-309 liquid, EJ-276 newly developed plastic, and BC-418 plastic, and optimized the data processing parameters for each pair separately. Our high-throughput data analysis method is based on single-pulse interpolation and a constant fraction discrimination (CFD) algorithm. The setup based on the BC-418 detector achieved the best time resolution of 198.3 +- 0.8 ps. We used such optimized setup to analyze two single-crystal quartz samples and found lifetimes of 156 +- 9 ps and 366 +- 22 ps, in good agreement with the characteristic time constants of this material. The proposed experimental set up achieve an excellent time resolution, which makes it possible to accurately characterize material vacancies by discriminating between the lifetimes of either the spin singlet or triplet states of positronium. The optimized data processing algorithms are relevant to all the applications where fast timing is important, such as nuclear medicine and radiation imaging.

physics.ins-det↗