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Characterizing Material Scalability for Ultralight Lattice Design

Stiff yet ultra-light lattice structures constructed using digital materials have many practical applications as the building block for aircraft and other structures. By furthering our understanding of how material configuration affects the structural properties of an ultralight lattice, we can intelligently design these structures based on their intended function. Here we compare the behavior of ultralight lattice structures when fabricated by different materials. The individual unit cells of the lattice structures are referred to as voxels. The stiffness, elastic modulus, and yield strength of the specimens in compression and tension are determined through mechanical testing. Specimens are tested both as single voxel as well as 4x4x4 voxel constructions on an Instron 5982 Universal Testing System until failure. Each voxel is manufactured in bulk through injection molding, with a unit cell pitch of 76.2 mm. Individual voxels are fastened with machine screws and nuts to create assemblies. Four separate materials are used as voxel compositions in this experiment. These include a homogeneous polymer referred to as Ultem 1000, a glass-fiber reinforced polymer referred to as Ultem 2200, a polymer with chopped carbon fibers as 30% of its fill, and homogenous polypropylene. This work compares mechanical behavior, as well as the convergence behavior of the lattice as the size of the lattice assembly increases for various materials. The goal of this study is to characterize the behavior of homogenous lattices such that heterogenous lattices can be designed with different material voxels to achieve target material properties for ultralight space applications.

Sajjadi, Afsheen↗

Three-dimensional estimation of deciduous forest canopy structure and leaf area using multi-directional, leaf-on and leaf-off airborne lidar data

Airborne laser scanning (ALS) has been widely used to map gap probability and leaf area index (LAI) distribution at plot and landscape scales. As an indirect measurement, most ALS methods to estimate LAI combine waveform or point density information with supporting field measurements such as the leaf angle distribution, gap probability, or direct LAI measures. The development of a more independent estimation approach would facilitate more widespread use of existing ALS data to investigate patterns of forest structure and build realistic 3-D vegetation scenes to simulate remote sensing imagery and energy balance. Here, we develop a data processing workflow (named PVlad) using ALS point cloud apparent reflectance to estimate LAI and voxel-based leaf area density (LAD), aiming to reduce the need for associated field measurements such as the gap probability. The adaptation of the path volume (PV) concept derived from apparent reflectance integrates information from multi-directional ALS pulses, and quantifies the percentage exploration of each voxel for classification and occlusion correction, such that rigorous volumetric sampling approaches can be developed to derive LAI and LAD. The PVlad workflow was applied to discrete-return lidar data (Riegl VQ480i) acquired by NASA Goddard's LiDAR, Hyperspectral and Thermal Imager (G-LiHT) Airborne Imager during leaf-on (summer) and leaf-off (spring) conditions at the Smithsonian Environmental Research Center (SERC). The estimates of LAI and LAD captured structural differences between mature, logged, and intermediate-aged stands over eight deciduous forest plots. The derived LAI values were compared to field litter collection measurements, and the derived LAD vertical distribution was compared to the output of the VoxLAD model using terrestrial laser scan (TLS) field survey data. Using voxel sizes ranging from 0.5 m to 5 m, overall LAI estimation showed linear fitting coefficient bias and for 1 and 2 m voxel sizes, and vertical LAD distribution showed strong correlation with and for 0.5 and 1m voxel sizes. For every forest stand, upper-canopy LAD had a low variance for voxel sizes of ≤ . Application of PVlad to the G-LiHT and other similar ALS data archives enables the development of fine-resolution LAI map products, including voxelization of LAD for ecosystem science and radiative transfer simulations of remote sensing imagery or surface energy balance.

Tiangang Yin↗

Predicting Missing Regions in Charged Particle Tracks Using a Sparse 3D Convolutional Neural Network

The 2x2 Demonstrator is a prototype detector for the Deep Underground Neutrino Experiment (DUNE)'s Near Detector. Both the 2x2 Demonstrator and the Near Detector itself will have inactive regions wherein there is no sensitivity to charge deposition and light signals that arise from charged particle interactions with liquid argon. In the 2x2, these inactive regions are positioned in-between the active detector modules, which introduces the challenge of inferring what charge signals ought to look like in these regions. This study explores the use of a Sparse 3D Convolutional Neural Network (ConvNet) to infer missing regions in charged particle tracks. Hits corresponding to energy depositions are voxelized into a three-dimensional (3D) grid for each track. Inactive regions within the tracks are replaced with a dense, rectangular 3D grid of voxels, ensuring consistent step sizes in X, Y, and Z directions. Voxels in these dense regions are initialized with an energy value of -1, indicating nonphysical energy or charge. The model is trained to predict which voxels should activate as part of the track and which should not, with the goal of eventually inferring the missing charge or energy values in these voxels. Results indicate that the model accurately predicts track voxels within 1 unit in X, Y, or Z directions and effectively identifies non-track voxels, despite some overprediction. The approach shows promise in prediction of missing track regions with some accuracy.

Utaegbulam, Hilary↗

Tomo2Mesh: Fast Reconstruction and Visualization of Tomography Data in Mesh Format

Tomo2Mesh is an open-source project targeted towards real-time reconstruction, segmentation, and visualization of computed tomography (CT) data in mesh format. The CT reconstruction scheme is based on filtered back-projection of voxel subsets. The segmentation scheme uses a 3D convolutional neural network. To allow for fast, real-time reconstruction, voxel subsets are first identified by coarse reconstruction. The detail in specific regions of interest is improved through full reconstruction of voxel subsets in that region. Data structures are implemented to store and process voxel subsets. Finally, voxel data is labeled using connected components to detect disconnected regions such as voids whose morphological attributes (e.g., Feret diameter, principal axis orientation, local number density, size, etc.) can be measured also in real-time. Finally, a fast marching cubes implementation processes labeled voxel data into a triangular face mesh (vertices and faces) in .ply format for visualization in Paraview or other mesh visualization tools. The code provides a simple programming interface for detecting, classifying, and visualizing regions of interest based on morphology. For example, detected voids can be classified as round pores or extended cracks. Highly porous neighborhoods can be identified based on local number density. The mesh texture (or color) is assigned based these morphological attributes to allow smart visualization scenarios in real-time (e.g., show only long cracks). At the time of first release (July 2022), extraction of face mesh for visualization for raw CT data from a 2 megapixel camera would take between 1-5 minutes for most scenarios.

TEKAWADE, ANIKET↗

Exercise Effects on the Brain and Sensorimotor Function in Bed Rest

Long duration spaceflight microgravity results in cephalad fluid shifts and deficits in posture control and locomotion. Effects of microgravity on sensorimotor function have been investigated on Earth using head down tilt bed rest (HDBR). HDBR serves as a spaceflight analogue because it mimics microgravity in body unloading and bodily fluid shifts. Preliminary results from our prior 70 days HDBR studies showed that HDBR is associated with focal gray matter (GM) changes and gait and balance deficits, as well as changes in brain functional connectivity. In consideration of the health and performance of crewmembers we investigated whether exercise reduces the effects of HDBR on GM, functional connectivity, and motor performance. Numerous studies have shown beneficial effects of exercise on brain health. We therefore hypothesized that an exercise intervention during HDBR could potentially mitigate the effects of HDBR on the central nervous system. Eighteen subjects were assessed before (12 and 7 days), during (7, 30, and ~70 days) and after (8 and 12 days) 70 days of 6-degrees HDBR at the NASA HDBR facility in UTMB, Galveston, TX, US. Each subject was randomly assigned to a control group or one of two exercise groups. Exercise consisted of daily supine exercise which started 20 days before the start of HDBR. The exercise subjects participated either in regular aerobic and resistance exercise (e.g. squat, heel raise, leg press, cycling and treadmill running), or aerobic and resistance exercise using a flywheel apparatus (rowing). Aerobic and resistance exercise intensity in both groups was similar, which is why we collapsed the two exercise groups for the current experiment. During each time point T1-weighted MRI scans and resting state functional connectivity scans were obtained using a 3T Siemens scanner. Focal changes over time in GM density were assessed using voxel based morphometry (VBM8) under SPM. Changes in resting state functional connectivity was assessed using both a region of interest (ROI, or seed-to-voxel) approach as well as a whole brain intrinsic connectivity (i.e., voxel-to-voxel) analysis. For the ROI analysis we selected 11 ROIs of brain regions that are involved in sensorimotor function (i.e., L. Insular C., L. Putamen, R. Premotor C., L.+R. Primary Motor C., R. Vestibular C., L. Posterior Cingulate G., R. Cerebellum Lobule V + VIIIb + Crus I, and the R. Superior Parietal G.) and correlated their time course of brain activation during rest with all other voxels in the brain. The whole brain connectivity analysis tests changes in the strength of the global connectivity pattern between each voxel and the rest of the brain. Functional mobility was assessed using an obstacle course. Vestibular contribution to balance was measured using Neurocom Sensory Organization Test 5. Behavioral measures were assessed pre-HDBR, and 0, 8 and 12 days post-HDBR. Linear mixed models were used to test for effects of time, group, and group-by-time interactions. Family-wise error corrected VBM revealed significantly larger increases in GM volume in the right primary motor cortex in bed rest control subjects than in bed rest exercise subjects. No other significant group by time interactions in gray matter changes with bed rest were observed. Functional connectivity MRI revealed that the increase in connectivity during bed rest of the left putamen with the bilateral midsagittal precunes and the right cingulate gyrus was larger in bed rest control subjects than in bed rest exercise subjects. Furthermore, the increase in functional connectivity with bed rest of the right premotor cortex with the right inferior frontal gyrus and the right primary motor cortex with the bilateral premotor cortex was smaller in bed rest control subjects than in bed rest exercise subjects. Functional mobility performance was less affected by HDBR in exercise subjects than in control subjects and post HDBR exercise subjects recovered faster than control subjects. The group performance differences and GM changes were not related. Exercise in HDBR partially mitigates the adverse effect of HDBR on functional mobility, particularly during the post-bed rest recovery phase. In addition, exercise appears to result in differential brain structural and functional changes in motor regions such as the primary motor cortex, the premotor cortex and the putamen. Whether these central nervous system changes are related to motor behavioral changes including gait and balance warrants further research.

Koppelmans, V.↗

System and method for identifying objects of interest in images based on likelihood map decluttering

An automatic threat recognition system and method is disclosed for scanning the x-ray CT image of an article to identify the objects of interest (OOIs) contained within the article, which are otherwise not always quickly apparent or discernable to an individual. The system uses a computer to receive information from two-dimensional (2D) image slices from a reconstructed computed tomography (CT) scan image and to produce a plurality of voxels for each slice of the 2D image. The computer analyzes the voxels to create a likelihood map (LM) representing likelihoods that voxels making up the CT image are associated with a material of interest (MOI). The computer further analyzes the LM to construct neighborhoods of voxels within the LM, and classifies each voxel neighborhood based on its features, thereby decluttering the LM to facilitate the process of connecting voxels of a like MOI together to form segments. The computer classifies each candidate segment based on its features, thereby identifying those segments that correspond to objects of interest.

Paglieroni, David W.↗

Monte-Carlo Simulation of Radiation Track Structure and Calculation of Dose Deposition in Nanovolumes

INTRODUCTION: The radiation track structure is of crucial importance to understand radiation damage to molecules and subsequent biological effects. Of a particular importance in radiobiology is the induction of double-strand breaks (DSBs) by ionizing radiation, which are caused by clusters of lesions in DNA, and oxidative damage to cellular constituents leading to aberrant signaling cascades. DSB can be visualized within cell nuclei with gamma-H2AX experiments. MATERIAL AND METHODS: In DSB induction models, the DSB probability is usually calculated by the local dose obtained from a radial dose profile of HZE tracks. In this work, the local dose imparted by HZE ions is calculated directly from the 3D Monte-Carlo simulation code RITRACKS. A cubic volume of 5 micron edge (Figure 1) is irradiated by a (Fe26+)-56 ion of 1 GeV/amu (LET approx.150 keV/micron) and by a fluence of 450 H+ ions, 300 MeV/amu (LET approx. 0.3 keV/micron). In both cases, the dose deposited in the volume is approx.1 Gy. The dose is then calculated into each 3D pixels (voxels) of 20 nm edge and visualized in 3D. RESULTS AND DISCUSSION: The dose is deposited uniformly in the volume by the H+ ions. The voxels which receive a high dose (orange) corresponds to electron track ends. The dose is deposited differently by the 56Fe26+ ion. Very high dose (red) is deposited in voxels with direct ion traversal. Voxels with electron track ends (orange) are also found distributed around the path of the track. In both cases, the appearance of the dose distribution looks very similar to DSBs seen in gammaH2AX experiments, particularly when the visualization threshold is applied. CONCLUSION: The refinement of the dose calculation to the nanometer scale has revealed important differences in the energy deposition between high- and low-LET ions. Voxels of very high dose are only found in the path of high-LET ions. Interestingly, experiments have shown that DSB induced by high-LET radiation are more difficult to repair. Therefore, this new approach may be useful to understand the nature of DSB and oxidative damage induced by ionizing radiation.

Plante, I.↗

X-Ray Computed Tomography During Preliminary Examination of Apollo Drive Tube 73001

Introduction: Starting in 2019, the Apollo Next Generation Sample Analysis (ANGSA) Program has enabled consortium studies of specially curated Apollo samples that were previously unstudied (or under studied). This began with unsealed core tube 73002 [1,2] that is the upper part of a station 3 double drive tube. More recently the pro-gram extended to the study of a variety of frozen Apollo 17 samples [3], as well as the gas extraction [4] and dis-section [5] of 73001, the lower half of the station 3 double drive tube, that was sealed under vacuum on the Moon. In this abstract we will examine the role of X-ray Computed Tomography (XCT) during the preliminary examination process for sealed core 73001, including: (1) engineering scans to aid in understanding the gas extraction process, whole-core scanning prior to opening to inform extrusion and dissection work, and (3) individual particle scanning to characterize rock fragment lithologies for follow on studies. Methodology: Sample 73001 is a 33 cm long, 4 cm diameter regolith sample collected inside a drive tube (~1 mm aluminum walls). That drive tube was sealed inside a 0.5 mm thick stainless steel (SS) Core Sample Vacuum Container (CSVC). XCT scans for engineering purposes were done on the Nikon XTH 320 system at Johnson Space Center using the 225 kV multi-metal reflection source at 215 kV, 179 A, and a 38.49 m voxel size. Individual >4 mm particles separated from the core during processing (then triply sealed in Teflon bags) were also scanned at JSC using the 180 kV source at 90 kV, 33 A, and a 2.98 – 10.65 m voxel size. Whole-core scans were done at the University of Texas High-Resolution X-ray Computed Tomography Facility (UTCT) on the 225 kV reflection source on the North Star Imaging cabinet XCT system. These scans included: (1) a series of 9 overlapping super-resolution scans each covering a ~4 cm length of the tube at 190 kV, 180 µA, and a 12.9 µm voxel size and (2) a lower resolution continuous helical scan of the entire core at 190 kV, 180 µA, and a 51.8 µm voxel size. Progress and Results: Before piercing and extracting the gas from sample 73001, an XCT scan of the bottom portion of the CSVC was used to confirm the location of the Teflon cap on the inner drive tube, to ensure it was not accidentally pierced during gas extraction. Similarly, after piercing, the bottom and top portions of the CSVC were scanned in order to capture engineering knowledge about the results of the piercing process, as well as the metal knife edge vacuum seal (SS into In-Ag alloy). Both scans will provide constraints on future work of this type, particularly for samples collected during the Artemis mission. Another finding from these "engineering" scans was that the device in the drive tube that immobilizes the regolith (the keeper) was not seated in the tube properly. This meant that (1) the drive tube could not be removed from the CSVC for the trip to UTCT, and (2) the procedure for opening and extruding the drive tube had to be modified. Had either of these things not been known prior to opening the CSVC, it could have led to an inability to XCT scan the whole core at high resolution and/or potential disruption of the core stratigraphy during extrusion. At UTCT, the entire length of the core was scanned at high resolution (12.9 microns per voxel). This scan serves multiple purposes: (1) A lower resolution (and uncorrected) version of these scans stitched together was used to help inform the processors of potential pitfalls during extrusion and dissection; and (2) the full resolution corrected data will serve as the permanent in situ record of the stratigraphy of the sample and will enable future researchers to perform a variety of analyses. So far, 92 of the 121 >4 mm particles separated during dissection pass 1 of sample 73001 have been individually scanned. These scans clearly show the lithology of each particle while keeping the particles in pristine condition. Because of the dust adhering to particle exteriors it would otherwise be impossible to determine lithologies in a non-contaminating way. Thus far the types of lithologies seen in sample 73001 (e.g., regolith breccias, impact-melt breccias, agglutinates, and basalts) are similar to those previously identified in sample 73002 [2]. By the time of the meeting, all particles from all 3 dissection passes will have been scanned and statistics on the different lithologies in 73001 compiled. References: [1] Shearer et al. (2020) 51st LPSC, abstract 1181. [2] Zeigler et al. (2020) 51st LPSC, abstract 3023. [3] Kent et al. (2022) This Volume. [4] McDonald et al. (2022) European Lunar Symposium. [5] Gross et al (2022) This volume.

Moon↗

X-Ray Computed Tomography of Apollo Drive Tube 73001 as Part of the Apollo Next Generation Sample Analysis Program

Introduction: Starting in 2019, the Apollo Next Generation Sample Analysis (ANGSA) Program has enabled consortium studies of specially curated Apollo samples that were previously unstudied (or under studied). This program was intended as a participating scientist program for these Apollo samples, as well as a preparation for upcoming lunar sample return missions (e.g., Artemis). The work began with studies of unsealed core tube 73002 [1,2] that is the upper ~35 cm of an Apollo 17 double drive tube (~70 cm total depth) collected on the landslide deposit near Lara Crater at Station 3 in the Taurus Littrow Valley. More recently the program extended to the study of a variety of frozen Apollo 17 samples [3], as well as the gas extraction [4] and dissection [5] of 73001, the lower half of the station 3 double drive tube. Sample 73001 was sealed under vacuum on the Moon in a Core Sample Vacuum Container (CSVC). In this abstract we will examine the role of X-ray Computed Tomography (XCT) during the preliminary examination process for sealed core 73001, including: (1) engineering scans to aid in understanding the gas extraction process, (2) whole-core scanning prior to opening to inform extrusion and dissection work, and (3) individual particle scanning to characterize rock fragment lithologies for follow on studies. Methodology: Sample 73001 is a 33 cm long, 4 cm diameter regolith sample collected inside a lunar drive tube (~1 mm aluminum walls). That drive tube was sealed inside a 0.5 mm thick stainless steel (SS) CSVC. XCT scans for engineering purposes were done on the Nikon XTH 320 system at Johnson Space Center using the 225 kV multi-metal reflection source at 215 kV, 179 A, and a 38.49 m voxel size. Individual >4 mm particles separated from the core during processing (then triply sealed in Teflon bags) were also scanned at JSC using the 180 kV source at 90 kV, 33 A, and a 2.98 – 10.65 m voxel size. Whole-core scans were done at the University of Texas High-Resolution X-ray Computed Tomography Facility (UTCT) on the 225 kV reflection source on the North Star Imaging cabinet XCT system. These scans included: (1) a series of 9 overlapping super-resolution scans each covering a ~4 cm length of the tube at 190 kV, 180 µA, and a 12.9 µm voxel size and (2) a lower resolution continuous helical scan of the entire core at 190 kV, 180 µA, and a 51.8 µm voxel size. Progress and Results: Before piercing and extracting the gas from sample 73001, an XCT scan of the bottom portion of the CSVC was used to confirm the location of the Teflon cap on the inner drive tube and whether there was an “air” gap between the Teflon cap and the CSVC. This was to ensure the Teflon cap (which immobilized the soil inside the drive tube) was not accidentally pierced during gas extraction. Similarly, after piercing, the bottom and top portions of the CSVC were scanned in order to capture engineering knowledge about the results of the piercing process, as well as the metal knife edge vacuum seal (SS into an In-Ag alloy). Both scans will provide constraints on future work of this type, both for the design of tools used on the lunar surface during Artemis, as well as how we open future samples of this type. An unexpected finding from these engineering scans was that the device in the drive tube that immobilizes the regolith (the keeper) was not seated in the tube properly. This meant that (1) the drive tube could not be removed from the CSVC for the trip to UTCT, and (2) the procedure for opening and extruding the drive tube had to be modified. Had either of these things not been known prior to opening the CSVC, it could have led to an inability to XCT scan the whole core at high resolution and/or potential disruption of the core stratigraphy during extrusion. At UTCT, the entire length of the core was scanned at high resolution (12.9 microns per voxel). This scan serves multiple purposes: (1) A lower resolution (and uncorrected) version of these scans stitched together was used to help inform the processors of potential pitfalls during extrusion and dissection (voids, angular fragments at the edges of the sample, etc.); and (2) the full resolution corrected data will serve as the permanent in situ record of the stratigraphy of the sample and will enable future researchers to perform a variety of analyses. All 121 >4 mm particles separated during dissection pass 1 of sample 73001 have been individually scanned. These scans clearly show the lithology of each particle while keeping the particles in pristine condition (they are individually triply bagged in Teflon within our N2 purged processing cabinets). Because of the dust adhering to particle exteriors, it would otherwise be impossible to determine lithologies in a non-contaminating way. Thus far the types of lithologies seen in sample 73001 (e.g., regolith breccias, impact-melt breccias, agglutinates, and bas-alts) are similar to those previously identified in sample 73002 [2]. By the time of the meeting, all particles from all 3 dissection passes will have been scanned and statistics on the different lithologies in 73001 compiled. References: [1] Shearer et al. (2020) 51st LPSC, abstract 1181. [2] Zeigler et al. (2020) 51st LPSC, abstract 3023. [3] Kent et al. (2022) This Volume. [4] McDonald et al. (2022) European Lunar Symposium. [5] Gross et al (2022) This volume.

Moon↗

Spherical time-encoded radiation imaging simulations

Radiation source localization is important for nuclear nonproliferation and can be obtained using time-encoded imaging systems with unsegmented detectors. A scintillation crystal can be used with a moving coded-aperture mask to vary the detected count rate produced from radiation sources in the far field. The modulation of observed counts over time can be used to reconstruct an image with the known coded-aperture mask pattern. Current time-encoded imaging systems incorporate cylindrical coded-aperture masks and have limits to their fully coded imaging field-of-view. This work focuses on expanding the field-of-view to 4π by using a novel spherical coded-aperture mask. A regular icosahedron is used to approximate a spherical mask. This icosahedron consists of 20 equilateral triangles; the faces of which are each subdivided into four equilateral triangle-shaped voxels which are then projected onto a spherical surface, creating an 80-voxel coded-aperture mask. Furthermore, these polygonal voxels can be made from high-Z materials for gamma-ray modulation and/or low-Z materials for neutron modulation. In this work, we present Monte Carlo N-Particle (MCNP) simulations and simple models programmed in Mathematica to explore image reconstruction capabilities of this 80-voxel coded-aperture mask.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Tailoring thermal insulation architectures from additive manufacturing

Abstract Tailoring thermal transport by structural parameters could result in mechanically fragile and brittle networks. An indispensable goal is to design hierarchical architecture materials that combine thermal and mechanical properties in a continuous and cohesive network. A promising strategy to create such a hierarchical network targets additive manufacturing of hybrid porous voxels at nanoscale. Here we describe the convergence of agile additive manufacturing of porous hybrid voxels to tailor hierarchically and mechanically tunable objects. In one strategy, the uniformly distributed porous silica voxels, which form the basis for the control of thermal transport, are non-covalently interfaced with polymeric networks, yielding hierarchic super-elastic architectures with thermal insulation properties. Another additive strategy for achieving mechanical strength involves the versatile orthogonal surface hybridization of porous silica voxels retains its low thermal conductivity of 19.1 mW m −1 K −1 , flexible compressive recovery strain (85%), and tailored mechanical strength from 71.6 kPa to 1.5 MPa. The printed lightweight high-fidelity objects promise thermal aging mitigation for lithium-ion batteries, providing a thermal management pathway using 3D printed silica objects.

36 MATERIALS SCIENCE↗

Feasibility of a multigroup Boltzmann–Fokker–Planck solution for electron beam dose calculations

Legacy nuclear-reactor Boltzmann solvers start clinical deployment as an alternative to Monte Carlo (MC) codes and Fermi–Eyges semiemprical models in radiation oncology treatment planning. Today’s certified clinical solvers are limited to photon beams. In this paper, ELECTR, a state-of-the-art multigroup electron cross sections generation module in NJOY is presented and validated against Lockwood’s calorimetric measurements, EGS-nrc and GEANT-4 for 1–20 MeV unidirectional electron beams. The nuclear-reactor DRAGON-5 solver is upgraded to access the library and solve the Boltzmann–Fokker–Planck (BFP) equation. A variety of heterogeneous radiotherapy and radiosurgery phantom configurations were used for validation purpose. Case studies include a thorax benchmark, that of a typical breast Intra-Operative Radiotherapy and a high-heterogeneity patient-like benchmark. For all beams, 100% of the water voxels satisfied the American Association of Physicists in Medicine accuracy criterion for a BFP-MC dose error below 2%. At least, 97.0% of adipose, muscle, bone, lung, tumor and breast voxels satisfied the 2% criterion. The average BFP-MC relative error was about 0.56% for all voxels, beams and materials combined. By irradiating homogeneous slabs from Z = 1 (hydrogen) to Z = 99 (einsteinium), we reported performance and defects of the CEPXS mode [US. Sandia National Lab., SAND-89-1685] in ELECTR for the entire periodic table. For all Lockwood’s benchmarks, NJOY-DRAGON dose predictions are within the experimental data precision for 98% of voxels.

42 ENGINEERING↗

X-ray Computed Tomography Data of Dense Metallic Components

The data shared in here are X-ray computed tomography (XCT) scans of a hexagonal fuel nozzle in 3 sections with the Metrotom 800 system at the Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory. The data are used in the paper "Tomographic Sparse View Selection using the View Covariance Loss, by Lin et al. (doi:10.1109/TPAMI.2025.36000720), accepted to the international conference on computational imaging (ICCP 2025). Figures 4-7 in the paper describe the part/XCT scan. File name Descriptions: Bottom section: TCR- Single Channeled SRC L 2019-3-18 12-26-41.hdf5 Medium section: TCR- Single Channeled SRC M 2019-3-18 13-8-9.hdf5 Top section: TCR- Single Channeled SRC T 2019-3-18 13-45-39.hdf5 Each hdf5 file contains projection data, and all the relevant X-ray CT scan setting. The full list of included attributes: distance_unit: Units of all distances specified angle_unit : Units of the angles angles: Array of all angles used voxel_size_xy: Baseline recon (if any) has this voxel size in the in-plane direction voxel_size_z: Baseline recon (if any) has this voxel size in the cross-plane direction det_pixel_size_col: Size of the detector pixels in the column dimension det_pixel_size_row: Size of the detector pixels in the row dimension src_iso_dist: Source to iso-center distance iso_det_dist: Iso-center to detector distance det_angle: If the detector is rotated/tilted, this angle corresponds to that value det_row_offset: Center of rotation offset in the vertical direction det_col_offset: Center of rotation offset in the horizontal direction reconstruction: A baseline reconstruction stored as 3D array BHC params: Beam-hardening parameters - Van De Casteel Model - if it has been used to pre-process the projections We also provided a python script (hdf_io.py) that allows the user to read the relevant data from each hdf5 file.

Ziabari, Amir [Oak Ridge National Laboratory]↗

Advanced Three-Dimensional Display System

A desktop-scale, computer-controlled display system, initially developed for NASA and now known as the VolumeViewer(TradeMark), generates three-dimensional (3D) images of 3D objects in a display volume. This system differs fundamentally from stereoscopic and holographic display systems: The images generated by this system are truly 3D in that they can be viewed from almost any angle, without the aid of special eyeglasses. It is possible to walk around the system while gazing at its display volume to see a displayed object from a changing perspective, and multiple observers standing at different positions around the display can view the object simultaneously from their individual perspectives, as though the displayed object were a real 3D object. At the time of writing this article, only partial information on the design and principle of operation of the system was available. It is known that the system includes a high-speed, silicon-backplane, ferroelectric-liquid-crystal spatial light modulator (SLM), multiple high-power lasers for projecting images in multiple colors, a rotating helix that serves as a moving screen for displaying voxels [volume cells or volume elements, in analogy to pixels (picture cells or picture elements) in two-dimensional (2D) images], and a host computer. The rotating helix and its motor drive are the only moving parts. Under control by the host computer, a stream of 2D image patterns is generated on the SLM and projected through optics onto the surface of the rotating helix. The system utilizes a parallel pixel/voxel-addressing scheme: All the pixels of the 2D pattern on the SLM are addressed simultaneously by laser beams. This parallel addressing scheme overcomes the difficulty of achieving both high resolution and a high frame rate in a raster scanning or serial addressing scheme. It has been reported that the structure of the system is simple and easy to build, that the optical design and alignment are not difficult, and that the system can be built by use of commercial off-the-shelf products. A prototype of the system displays an image of 1,024 by 768 by 170 (=133,693,440) voxels. In future designs, the resolution could be increased. The maximum number of voxels that can be generated depends upon the spatial resolution of SLM and the speed of rotation of the helix. For example, one could use an available SLM that has 1,024 by 1,024 pixels. Incidentally, this SLM is capable of operation at a switching speed of 300,000 frames per second. Implementation of full-color displays in future versions of the system would be straightforward: One could use three SLMs for red, green, and blue, respectively, and the colors of the voxels could be automatically controlled. An optically simpler alternative would be to use a single red/green/ blue light projector and synchronize the projection of each color with the generation of patterns for that color on a single SLM.

Geng, Jason↗

Predicting Missing Regions in Charged Particle Tracks Using a Sparse 3D Convolutional Neural Network

The 2x2 Demonstrator is a prototype of ND-LAr, the liquid argon time-projection chamber of the Deep Underground Neutrino Experiment’s Near Detector complex. Both the 2x2 Demonstrator and ND-LAr are modular detectors that will have pixelated charge readouts and inactive regions wherein there is no sensitivity to charge deposition and light signals that arise from charged particle interactions with liquid argon. In the 2x2, these inactive regions are located in between the active detector modules, which introduces the challenge of inferring what charge signals ought to look like in these regions. This study explores the use of a Sparse 3D Convolutional Neural Network (ConvNet) to infer missing regions in charged particle tracks. Hits corresponding to energy depositions are voxelized into a three-dimensional grid for each track. Voxels that fall into predefined inactive regions are removed to simulate the lack of detector output. The model is trained to infer the topology of the missing track voxels, with the ultimate goal of inferring the missing charge or energy values in these voxels as well. Results indicate that this approach shows promise in prediction of missing track regions with some accuracy.

Utaegbulam, Hilary↗

An extrapolation method to remove spurious stress concentration in micromechanical analyses of composites using pixel-based meshes

It is easier to generate a finite element mesh of complicated geometries with voxel-based meshes compared to conformal meshes. However, the local stresses in voxel-based meshes are higher owing to artificial stress concentration caused due to jagged lines that approximate a curve. Here, we propose a method that accounts for this anomaly which would lead to accurate prediction of maximum von Mises stress in voxel-based meshes. The method is based on the variation of reciprocal of stresses and associated numerical gradient. The prediction of the proposed method is compared against the results of a conformal mesh by considering four two-dimensional example problems. The accuracy of the proposed method is verified using different mesh densities, material properties, and integration schemes. The proposed method was also implemented on a conformal mesh to verify that it filters out just the spurious stress concentration and not the realistic stress concentration.

36 MATERIALS SCIENCE↗

Machine learning-assisted upscaling analysis of reservoir rock core properties based on micro-computed tomography imagery

Optimum solutions for geologic modeling and reservoir simulation in industries such as oil and gas recovery and carbon capture and storage require accurate characterization of reservoir properties, which are often heterogeneous. In this study, high-quality micro-computed tomography (CT) images (1.475-μm/pixel resolution) of a sandstone core acquired from the Bell Creek oil field, USA, were used to provide nondestructive analysis of pore- and core-scale heterogeneity across measurement scales of 94–566 μm. In addition to characterizing the as-received sample, the core sample was flooded with brine to evaluate the capacity of the core sample to receive injected fluids. The micro-CT images were systematically segmented into pore spaces and grains via machine learning (ML) steps including image preprocessing, label creation using a traditional ML method based on limited manual image annotation, and finally U-Net segmentation. The segmented image stacks were reconstructed into digital cubes of various scales of voxel lengths. The 3D porosity values were calculated for all the digital cubes, and the fractal dimensions of the cubes were estimated using a box-counting method. The results showed that smaller cubes had greater heterogeneity and that the porosity values could be accurately estimated by fractal dimension and voxel lengths using ML models. For the core sample with brine flooding, the ratio of pores filled by brine to the total pore space was related to the porosity and could also be accurately estimated by porosity, fractal dimension, and voxel lengths using ML models. In conclusion, the results of this study demonstrate that the concept of fractal dimension can be a useful vector to perform upscaling analysis of sandstone rock heterogeneity from the pore to core scale and that fractal dimensions can be used to estimate porosity values and pore space-filling capacity across those scales.

58 GEOSCIENCES↗

Statistical White-Line Analysis in High-Throughput TXM-XANES for Chemical State Quantification

The transmission X-ray microscopy (TXM) based X-ray absorption near-edge structure (XANES) technique provides three-dimensional mapping of element-specific chemical states at nanometer-scale spatial resolution and micrometer-scale fields of view. However, compared to conventional volume-averaged XANES (VA-XANES) measurements, the inherently small voxel size in TXM-XANES leads to a lower signal-to-noise ratio, making full-spectrum analysis computationally demanding and less robust. Here, we present the structural and compositional conditions for a statistical white-line analysis framework under which chemical state information can be directly extracted from the white-line peak position in voxel spectra without the need for voxel-wise background subtraction or normalization, under well-defined structural and compositional conditions. The method is validated on layered oxide cathode materials, where low-order polynomial fitting accurately reproduces white-line features, and the extracted energy distributions correlate strongly with VA-XANES results. This statistical approach enables high-throughput, dose-efficient, and noise-robust chemical state quantification in TXM-XANES, offering broad applicability to functional materials requiring nanoscale oxidation-state mapping.

TXM↗