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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Muon tracking in a LiquidO opaque scintillator detector

LiquidO is an innovative radiation detector concept. The core idea is to exploit stochastic light confinement in a highly scattering medium to self-segment the detector volume. In this paper, we demonstrate event-by-event muon tracking in a LiquidO opaque scintillator detector prototype. The detector consists of a 30 mm cubic scintillator volume instrumented with 64 wavelength-shifting fibres arranged in an 8 × 8 grid with a 3.2 mm pitch and read out by silicon photomultipliers. A wax-based opaque scintillator with a scattering length of approximately 0.5 mm is used. The tracking performance of this LiquidO detector is characterised with cosmic-ray muons and the position resolution is demonstrated to be 450 μm per row of fibres. These results highlight the potential of LiquidO opaque scintillator detectors to achieve fine spatial resolution, enabling precise particle tracking and imaging.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Sister Rod Destructive Examinations (FY22) Appendix B: Segmentation, Defueling, Metallographic Data and Total Cladding Hydrogen

This report documents work performed under the Spent Fuel and Waste Disposition’s Spent Fuel and Waste Science and Technology program for the US Department of Energy (DOE) Office of Nuclear Energy (NE). This work was performed to fulfill Level 2 Milestone M2SF-23OR010201024, “FY22 Report on ORNL Sibling Rod Testing Results,” within work package SF-23OR01020102 and is an update to the work reported in M2SF-22OR010201047, M2SF-21OR010201032, M2SF-19ORO010201026, and M2SF 19OR010201028. As a part of the DOE-NE High Burnup Spent Fuel Data Project, Oak Ridge National Laboratory (ORNL) is performing destructive examinations (DEs) of high burnup (HBU) (>45 GWd/MTU) spent nuclear fuel (SNF) rods from the North Anna Nuclear Power Station operated by Dominion Energy. The SNF rods, called sister rods or sibling rods are all HBU and include four different kinds of fuel rod cladding: standard Zircaloy-4 (Zirc-4), low-tin (LT) Zirc-4, ZIRLO ® , and M5 ® . Appendix B provides detailed information regarding defueling activities, metallographic imaging and measurements, and total cladding hydrogen measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Effects of Polymer Morphology on Solvent and Catalyst Accessibility during Polyethylene and Polystyrene Autoxidation

Efficient catalytic deconstruction of plastics requires facile solvent and catalyst access to polymer substrates to minimize mass transfer effects. Autoxidation using Co(II) acetate, Mn(II) acetate, and a radical carrier in acetic acid is a promising strategy to deconstruct mixed plastic waste, yet the role of polymer morphology in governing solvent and catalyst accessibility remains poorly understood. Here, in situ simultaneous small- and wide-angle X-ray scattering (SAXS/WAXS), complemented by X-ray fluorescence (XRF) imaging and high-pressure differential scanning calorimetry (DSC), were used to elucidate interactions between acetic acid, a Co/Mn catalyst solution, and semicrystalline polyethylene (PE) and amorphous polystyrene (PS) from room temperature to 160 °C. In PE, acetic acid and catalyst access were confined to amorphous regions and cryomilled particle interfaces at room temperature, while crystalline lamellae remained intact after soaking for up to 34 h. Increasing temperature enabled solvent uptake into PE, followed by solvent-assisted softening above 100 °C, and a modest melting-point depression that removed lamellar transport barriers upon melting. Conversely for PS, acetic acid penetrated the glassy polymer without inducing chain mobility until the glass transition was reached, above which the observed structural changes were consistent with enhanced segmental mobility which enabled bulk penetration. These results suggest that polymer morphology and thermally activated physical transitions arising from diffusion and polymer–solvent interactions can influence whether autoxidation of plastics is transport-limited or kinetically controlled, providing a framework for aligning reaction conditions with reaction outcomes.

09 BIOMASS FUELS↗
DOE OSTI2025

Stochastic parametric skeletal dosimetry model for humans: Pediatric and adult computational skeleton phantoms for internal bone marrow dosimetry

Currently, computational phantoms that simulate skeletal tissues are used in active red bone marrow (AM) internal dosimetry. Up-to-date reference computational phantoms recommended by the ICRP are based on the analysis of CT-images of cadavers. Such phantoms have significant disadvantages. One disadvantage is that the assessment of uncertainty due to the population variability of skeleton dimensions and microstructure results from the limited availability of autopsy material. Another disadvantage is the simplified modelling of cortical layer and bone microarchitecture. A method of stochastic parametric skeletal dosimetry modelling of the bone structures – SPSD modelling – has been developed as an alternative to the ICRP reference phantoms. In the framework of this approach, skeletal phantom parameters are evaluated based on extensively reviewed results of published measurements of real bones. The SPSD approach allows for the assessment of both population-average values and their variability. SPSD-phantoms of the skeleton are modelled in voxel representation. They consist of smaller phantoms of the bone sites – segments – described by simple geometric shapes with uniform microarchitecture parameters. Such segmentation makes it possible to account for non-homogeneous skeletal microarchitecture and to model the bone structure with the required voxel resolution to elaborate suitable skeletal phantoms. The current study presents the parameters of the SPSD skeletal phantoms for the following age-groups: newborn, 1-year-old, 5-year-old, 10-year-old, 15-year-old (male and female), and adult (male and female). This skeletal phantom can be used for dosimetry as an alternative to available reference phantoms for bone-seeking radionuclides. The above-mentioned age- and sex-specific skeletal phantoms are comprised of 289 unique segments. The characteristics of the SPSD phantoms do not contradict published data and are in good agreement with the measurement results of real bones.

Science & Technology - Other Topics↗
DOE OSTI2021

Efficient Data Compression for 3D Sparse TPC via Bicephalous Convolutional Autoencoder

Real-time data collection and analysis in large experimental facilities present a great challenge across multiple domains, including high energy physics, nuclear physics, and cosmology. To address this, machine learning (ML)-based methods for real-time data compression have drawn significant attention. However, unlike natural image data, such as CIFAR and ImageNet that are relatively small-sized and continuous, scientific data often come in as three-dimensional 3D data volumes at high rates with high sparsity (many zeros) and non-Gaussian value distribution. This makes direct application of popular ML compression methods, as well as conventional data compression methods, suboptimal. To address these obstacles, this work introduces a dual-head autoencoder to resolve sparsity and regression simultaneously, called Bicephalous Convolutional AutoEncoder (BCAE). This method shows advantages both in compression fidelity and ratio compared to traditional data compression methods, such as MGARD, SZ, and ZFP. To achieve similar fidelity, the best performer among the traditional methods can reach only half the compression ratio of BCAE. Moreover, a thorough ablation study of the BCAE method shows that a dedicated segmentation decoder improves the reconstruction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Large area position sensitive detector for thermal neutrons

Large area thermal neutron detectors are applied in many fields including industrial imaging, nuclear safeguarding, neutron scattering, and fundamental science. Historically, these detectors were based on 3 He gas proportional counters despite the limitations of 3 He detectors such as high cost, limited supply, non-uniform spatial resolution, and depth of absorption problems. Two alternatives to 3 He detectors are 6 Li-loaded glass scintillators, and powdered ZnS(Ag) scintillators mixed with 6LiF neutron converters. The 6 LiF/ZnS(Ag) scintillator has advantages over 6 Li glass as it is less expensive and can be produced in larger areas, although its self-absorption presents a problem. In this work, we developed a large area thermal neutron detector based on 6 LiF/ZnS(Ag) scintillator coupled with wavelength shifting fibers. The detector uses resistive charge divider-based position encoding. We further modified and improved the method by 2D segmentation of the detector using modular multichannel readout electronics. This segmentation approach allows for a combination of large detector area, improved spatial resolution, and increased count rate. Furthermore, spatial resolution can be variable across the detector area by adjusting the segment size.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Dimensionally Aligned Signal Projection Algorithms Library

Dimensionally aligned signal projection (DASP) algorithms are used to analyze fast Fourier transforms (FFTs) and generate visualizations that help focus on the harmonics for specific signals. At a high level, these algorithms extract the FFT segments around each harmonic frequency center, and then align them in equally sized arrays ordered by increasing distance from the base frequency. This allows for a focused view of the harmonic frequencies, which, among other use cases, can enable machine learning algorithms to more easily identify salient patterns. This work seeks to provide an effective open-source implementation of the DASP algorithms proposed by Vann et al. (2018) as well as functionality to help explore and test how these algorithms work with an interactive dashboard and signal-generation tool. The DASP library is implemented in Python and contains four types of algorithms for implementing these feature engineering techniques: fixed harmonically aligned signal projection (HASP), decimating HASP, interpolating HASP, and frequency aligned signal projection (FASP). Each algorithm returns a numerical array, which can be visualized as an image. The HASP algorithms are variations of the algorithms originally presented by Vann et al. (2018). For consistency, FASP, which is the terminology used for the short-time Fourier transform (STFT), has been implemented as part of the library to provide a similar interface to the STFT of the raw signal. Additionally, the library contains an algorithm to generate artificial signals with basic customizations such as the base frequency, sample rate, duration, number of harmonics, noise, and number of signals. Finally, the library provides multiple interactive visualizations, each of which is implemented using IPyWidgets and works in a Jupyter environment. A dashboard-style visualization is provided, which contains some common signal-processing visual components (signal, FFT, spectogram) updating in unison with the HASP functions (see Figure 1 below). Separate from the dashboard, an independent visualization is provided for each of the DASP algorithms as well as for the artifical signal generator. These visualizations are included in the library to aid in developing an intuitive understanding how the algorithms are affected by different input signals and parameter selections.

harmonics↗
DOE OSTI2026

Web-based Preprocessing and Visualization of 3D FIB Tomography Data for Nuclear Fuel Characterization

Three-dimensional (3D) focused ion beam (FIB) tomography enables reconstruction of internal nuclear fuel features that can't be fully evaluated through surface imaging alone. This capability supports characterization of fuel constituents and defects under thermal and irradiation conditions relevant to microreactor development. However, large tomography datasets can create data-handling, loading, and visualization challenges, especially when image-stack preparation and file conversion must be completed with separate tools. The Computational Ultraspatial Tomography Toolkit for High-Resolution Object Analysis Tools (CUTTRHOAT) is an open-source web application being developed to display FIB tomography datasets available through the Nuclear Research Data System (NRDS). The current alpha version requires prepared HDF5 datasets and has limited integrated data-preparation capabilities. This project improves CUTTHROAT by adding dataset-folder selection, automatic input detection, dataset scanning, missing-slice identification, blank-slice insertion, and image-stack-to-HDF5 conversion. Two applications will be compared: the baseline CUTTHROAT alpha workflow and the updated application containing the integrated data-handling and preprocessing functions. Evaluation will consider dataset detection accuracy, conversion success, loading time, rendering responsiveness, application stability, and user interaction. Preliminary results demonstrate successful loading of existing HDF5 files and converted image stacks, while testing also identified performance reductions caused by excessive blank-slice generation. The updated workflow reduces reliance on external preparation tools and supports more direct movement from image stacks to color-code 3D visualization. Future work includes refining missing-slice handling, integrating additional preprocessing functions, like a denoising feature, parsing TIFF metadata for automatic voxel scaling, and adding manual X, Y, and Z voxel-spacing inputs for PNG and JPEG.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Effectiveness of Deep Learning Trained on SynthCity Data for Urban Point-Cloud Classification

3D object recognition is one of the most popular areas of study in computer vision. Many of the more recent algorithms focus on indoor point clouds, classifying 3D geometric objects, and segmenting outdoor 3D scenes. One of the challenges of the classification pipeline is finding adequate and accurate training data. Hence, this article seeks to evaluate the accuracy of a synthetically generated data set called SynthCity, tested on two mobile laser-scan data sets. Varying levels of noise were applied to the training data to reflect varying levels of noise in different scanners. The chosen deep-learning algorithm was Kernel Point Convolution, a convolutional neural network that uses kernel points in Euclidean space for convolution weights.

Geology↗
DOE OSTI2024

Investigating the Influence of River Geomorphology on Human Presence Using Night Light Data: A Case Study in the Indus Basin

Human settlements have historically thrived near rivers due to enhanced navigation and trade, and the availability of water supply and resources. The use of night light data, representing economic activities, provides a novel approach to studying the interactions between human activity and rivers over time. Here, we use the Defense Meteorological Satellite Program (DMSP) stable night light data from 2000 to 2013 as a proxy for human presence and activities to quantify the statistical relationships between night light presence and intensity in the Indus Basin, Asia. We test how these data are affected by proximity to trunk channels and by channel type (single/multi-thread) in the study area. We find that night light presence is enhanced by 26% within a 0 to 5 km proximity range of the Indus River and its tributaries, relative to the basin as a whole. We interpret this to represent increased human presence and activity within this zone. However, the mean intensity is lower near the river and higher away from the river, signifying denser settlements, such as towns and cities, which are preferentially located away from the Indus and its tributaries. Moreover, the enhancement of lit pixels signifying human presence and activities is increased by 18% near single-thread sections of the Indus River, compared to segments of the Indus displaying multi-thread morphologies. We suggest that this is due to the enhanced stability of single-threaded channels, relative to mobile multi-threaded channel reaches. This study demonstrates how night lights are an important tool in studying the relationship between human presence and river dynamics in large catchments such as the Indus, and we suggest that these data will have an important role in assessing differential flood spatial and social vulnerability at a regional scale.

Environmental Sciences & Ecology↗
DOE OSTI2021

Semantic segmentation with a sparse convolutional neural network for event reconstruction in MicroBooNE

We present the performance of a semantic segmentation network, SparseSSNet, that provides pixel-level classification of MicroBooNE data. The MicroBooNE experiment employs a liquid argon time projection chamber for the study of neutrino properties and interactions. SparseSSNet is a submanifold sparse convolutional neural network, which provides the initial machine learning based algorithm utilized in one of MicroBooNE's ν e -appearance oscillation analyses. The network is trained to categorize pixels into five classes, which are re-classified into two classes more relevant to the current analysis. The output of SparseSSNet is a key input in further analysis steps. This technique, used for the first time in liquid argon time projection chambers data and is an improvement compared to a previously used convolutional neural network, both in accuracy and computing resource utilization. Here, the accuracy achieved on the test sample is ≥ 99%. For full neutrino interaction simulations, the time for processing one image is ≈ 0.5 sec, the memory usage is at 1 GB level, which allows utilization of most typical CPU worker machine.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Content-aware foveated camera for multi-target tracking

Modern image sensors deliver substantial space-time bandwidth, yet indiscriminate acquisition often overwhelms memory, computation, and downstream perception. We present a content-aware, multi-foveated camera that dynamically reallocates sensing and magnification to multiple regions of interest (ROIs). A phase-only spatial light modulator (SLM) serves as a solid-state, inertia-free beam-steering and lens element, enabling per-frame field-of-view (FOV) reconfiguration and content-aware target tracking. By interleaving frames across foveae, our system preserves a wide-FOV situational context while refreshing each ROI at high rates, thereby reducing data volume without degrading task performance. We constructed a prototype employing a single-SLM, single-sensor architecture and demonstrated its application in real-time multi-object tracking with dynamic ROI maintenance across multiple viewpoints. The approach offers a general pathway to integrate detection, tracking, and segmentation algorithms in the acquisition loop, shifting workload from post hoc processing to intelligent capture.

Zang, Zihan [Univ. of California, Los Angeles, CA ↗
DOE OSTI2020

Measurements of an AC-LGAD strip sensor with a 120 GeV proton beam

The development of detectors that provide high resolution in four dimensions has attracted wide-spread interest in the scientific community for several applications in high-energy physics, nuclear physics, medical imaging, mass spectroscopy as well as quantum information. In addition to high time resolution and thanks to the AC-coupling of the electrodes, LGAD silicon sensors can provide high resolution in the measurement of spatial coordinates of an incident minimum ionizing particle. Such AC-coupled LGADs, also known as AC-LGADs, are therefore considered as candidates for future detectors to provide 4-dimensional measurements in a single sensing device with 100% fill factor. This article presents the first characterization of an AC-LGAD sensor with a proton beam of 120 GeV momentum at Fermilab. The sensor consists of strips with 80 μm width, fabricated at Brookhaven National Laboratory. The signal properties, efficiency, spatial, and time resolution are presented. Overall, the experimental results show that the time resolution of such an AC-LGAD is compatible to standard LGADs with similar gain, and that AC-LGADs can be segmented with fine pitches as standard strip or pixel detectors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Measurements of an AC-LGAD strip sensor with a 120 GeV proton beam

The development of detectors that provide high resolution in four dimensions has attracted wide-spread interest in the scientific community for several applications in high-energy physics, nuclear physics, medical imaging, mass spectroscopy as well as quantum information. In addition to high time resolution and thanks to the AC-coupling of the electrodes, LGAD silicon sensors can provide high resolution in the measurement of spatial coordinates of an incident minimum ionizing particle. Such AC-coupled LGADs, also known as AC-LGADs, are therefore considered as candidates for future detectors to provide 4-dimensional measurements in a single sensing device with 100$\%$ fill factor. This article presents the first characterization of an AC-LGAD sensor with a proton beam of 120 GeV momentum at Fermilab. The sensor consists of strips with 80 $\mu$m width, fabricated at Brookhaven National Laboratory. The signal properties, efficiency, spatial, and time resolution are presented. The experimental results show that the time resolution of such an AC-LGAD is compatible to standard LGADs with similar gain, and that AC-LGADs can be segmented with fine pitches as standard strip or pixel detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

In-Cell Deployment and First Use of Digital Image Correlation for In-Situ Strain Analysis of Irradiated Nuclear Fuel Rods During LOCA Transient

Digital image correlation (DIC) is a noncontact, optical method increasingly used across industries and research environments for acquiring multidimensional strain data. At Oak Ridge National Laboratory’s (ORNL’s) Severe Accident Test Station (SATS), DIC has been extensively applied to study the thermomechanical response of nuclear fuel claddings, yielding fundamental insights into material behavior. However, these efforts have focused exclusively on unirradiated materials and relied on the SATS out-of-cell infrastructure. Efforts over the past two years have been made to extend these capabilities to ORNL’s Irradiated Fuels Examination Laboratory SATS system within the hot-cells to enable testing of irradiated fuel cladding materials. Integrating DIC into the hot-cell SATS infrastructure presents unique challenges, including enabling remote operation of optical equipment and adapting auxiliary hot-cell systems for DIC implementation. This report discusses design, stand-up testing, and application of DIC to an irradiated nuclear fuel cladding segment. A DIC testing rig was successfully built and validated out-of-cell through extensive surrogate tests and calibrations. The rig and specialized DIC furnace were installed in the hot-cell, and a DIC test was successfully conducted. Results from that test correspond to expectations for Zr-based alloys and showed similar uncertainties compared to out-of-cell tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

3D Quantification of Pore Networks and Anthropogenic Carbon Mineralization in Stacked Basalt Reservoirs

Basalt formations are promising candidates for the geologic storage of anthropogenic CO 2 due to their storage capacity, porosity, permeability, and reactive geochemical trapping ability. The Wallula Basalt Carbon Storage Pilot Project demonstrated that supercritical CO 2 injected into >800 m deep Columbia River Basalt Group stacked reservoir flow tops mineralizes to ankerite-siderite-aragonite on month-year timescales, with 60% of the 977 metric tonnes of CO 2 converted within two years. The potential impacts of mineral precipitation and consequent changes on rock porosity, pore structure, pore size, and pore size distributions have likely been underestimated hitherto. Herein, we address these knowledge gaps using X-ray Micro Computed Tomography (XMT) to evaluate the pore network architecture of sidewall cores recovered two years after CO 2 injection. In the present study, we performed a detailed quantitative analysis of the CO 2 -reacted basalt cores by XMT imaging. Reconstructed 3D images were analyzed to study the distribution and volumetric details of porosity and carbonate nodules in the cores along with the various other phases, providing insight into paragenesis and carbonate growth mechanisms, including mineralogic/chemical zonation. Finally, these findings are being used to parametrize multiphase reactive transport models to predict the fate and transport of subsurface CO 2 , enabling scale-up to commercial-scale geologic carbon storage in basalts and other reactive mafic-ultramafic formations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

(U) Endpoint Energy and Scintillator Geometry Effects on the Swank Factor, Quantum Efficiency, and DQE(0) for High-Energy Radiography

High-energy radiography is used to image imploding materials to better understand weapon design and performance. The Enhanced Capabilities for Subcritical Experiments (ECSE) is a new facility proposal that aims to collect radiographic images of nuclear material. As part of the facility design, we aim to optimize data quality and radiographic performance by investigating different detector designs. We addressed design decisions by simulating different scintillator designs using M CNP6 and calculated the quantum efficiency, Swank factor, and detective quantum efficiency at zero-frequency (DQE(O)). First, we investigated the effects of the x-ray endpoint energy on the detector response. We generated three x-ray spectra with endpoint energies of 20 MeV, 22 MeV, and 24 MeV. The three raw spectra were filtered using the Dual-Axis Radiographic Hydrodynamic Test facility (DARHT) line-of-sight materials along with 1) flat field filtration using 7 cm tungsten alloy in the bullnose and 2) an FTO with 4 plates. The scatter-to-direct radiation ratio was much larger for FTO with 4 plates (50-60%) compared to the flat field with 7 cm of bullnose material (8%). We used these filtered spectra to calculate the detector response for the original DARHT segmented scintillator design. We found that the endpoint energy and filtration had a negligible effect on the detector response. The quantum efficiency was 0.63, the Swank factor was 0.84, and the DQE(O) was 0.53 for all six spectra.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Nanopore networks in colloidal silica assemblies characterized by XCT for confined fluid flow modeling

Fluid flow through nanopore structures has exhibited different behavior than that described by Darcy's law, derived from pore networks of micrometer scale. Here, pressure assemblies of colloidal silica spheres of specified diameters from 94 to 620 nanometers were prepared as model nano-porous media. The smaller silica spheres tended to form random packing, but some substantial ordering was found in the packing of the larger silica spheres. X-ray computed tomography (XCT), with a voxel resolution of 16 nm, was used to characterize the nanopore networks. The porosity of the Nano-XCT pore network (34%) was less than the total porosity of the assemblies as determined by X-ray attenuation (52%), possibly due to the limits of voxel resolution during segmentation. Fluid flow in the nanopore networks was simulated using the single-phase Lattice Boltzmann Method, and the simulated permeability was compared with the empirical and experimental values. Based on our characterization, although a well-ordered packing of silica spheres was not achieved, it was found that the nanopore networks in the colloidal silica assemblies had pore size distributions corresponding to the particle sizes. The simulated permeability was less than the experimental measurement for water flow, but the complex packing of silica spheres and surface chemistry issues need to be considered in future research.

02 PETROLEUM↗