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DOE OSTI2021

Visual HPC Workflows for the Analysis of System Dynamics Models

Visual analytics supported by high performance computing (HPC) accelerates and enhances the discovery, exploration, and analysis of causal patterns in complex system dynamics (SD) models. We present a suite of visualization-assisted ensemble-based techniques for hypothesis generation and testing, and for sensitivity analysis. By employing HPC to provide parallel, on-demand simulation of SD models, one can “steer” an ensemble of simulated scenarios in real time as one first formulates and then informally tests those hypotheses: this provides rapid feedback for analysts to refine their understanding of the causal relationships emergent from a model. Such understandings can be followed and augmented by rigorous application of statistical methods, namely global variance-based sensitivity analysis, Monte-Carlo filtering, adaptive regional sensitivity analysis, and self-organized maps: here timely computation relies on HPC, while effective presentation emphasizes high-dimensional multivariate data visualization. Immersive visualization in virtual 3D environments provides an excellent adjunct to the traditional 2D graphics typically used for SD models, as it generates an embodied understanding of model behavior and facilitates an active, collaborative critique of model structure and output. Finally, we summarize prospects for HPC-enabled visual analytics applied to SD modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

Four-Dimensional Imaging of ZnO-Coated Alumina Aerogels by Scanning Transmission X-ray Microscopy and Ptychographic Tomography

Functional porous materials are of mounting significance in energy conversion and catalysis. Improved analysis is needed to guide optimization. Four-dimensional (4D) imaging [chemical mapping in three-dimensional (3D) by spectro-tomography] of an Al 2 O 3 aerogel coated with ZnO by atomic layer deposition was performed using soft X-ray ptychography at the Zn L-edge. A two-dimensional spatial resolution of 14(2) nm was achieved. Visualizations of the 3D chemical structure are provided. The degree of ZnO coverage of the surface of the Al 2 O 3 aerogel framework in two different samples was estimated and found to be both thicker and less homogeneous than expected. Other analyses of the 4D results, including the degree of contact between Al 2 O 3 and ZnO, were extracted from the reconstructed 3D data. This pioneering soft X-ray spectro-ptycho-tomography research will anchor further studies of functional porous materials.

36 MATERIALS SCIENCE↗

DOE OSTI2023

3D Modeling of Safety-Related Upgrade Pilot Project

Constellation Energy and the United States Department of Energy (DOE) have established a public/private partnership to implement a pilot digital upgrade to replace legacy analog, safety-related reactor protection and emergency safety feature actuation systems (RPS/ESFAS) with modern digital systems. This effort is occurring at Constellation’s Limerick Generating Station. This project is being performed in accordance with industry processes that have been adapted to better support digital upgrades. These processes include IP-ENG-001, Standard Design Process, NISP-EN-04, Standard Digital Engineering Process and Electric Power Research Institute Report 3002011816, Digital Engineering Guide. The Light Water Reactor Sustainability (LWRS) Program at the Idaho National Laboratory (INL) has been supporting this effort. Latest INL HFE efforts in support of this project have focused on definition and implementation of the Human Factors Engineering (HFE) Program in support of Constellation design and related licensing efforts. This paper will present the development of the HFE 3D modeling execution of the Main Control Room safety upgrades. New equipment and modifications are planned for upgrading the new safety systems. 3D modeling allows for visualization of the new equipment and modifications to be shared with engineering and design teams for evaluation and review. Anthropometric considerations such as sight lines and functional reach can be evaluated directly using the 3D model. This effort has helped to provide visualizations for additional review with operations personnel and project stakeholders.

3D Modeling↗

DOE OSTI2023

Electron tomography unravels new insights into fiber cell wall nanostructure; exploring 3D macromolecular biopolymeric nano-architecture of spruce fiber secondary walls

Lignocellulose biomass has a tremendous potential as renewable biomaterials for fostering the “bio-based society” and circular bioeconomy paradigm. It requires efficient use and breakdown of fiber cell walls containing mainly cellulose, hemicellulose and lignin biopolymers. Despite their great importance, there is an extensive debate on the true structure of fiber walls and knowledge on the macromolecular nano-organization is limited and remains elusive in 3D. We employed dual-axis electron tomography that allows visualization of previously unseen 3D macromolecular organization/biopolymeric nano-architecture of the secondary S2 layer of Norway spruce fiber wall. Unprecedented 3D nano-structural details with novel insights into cellulose microfibrils (~2 nm diameter), macrofibrils, nano-pore network and cell wall chemistry (volume %) across the S2 were explored and quantified including simulation of structure related permeability. Matrix polymer association with cellulose varied between microfibrils and macrofibrils with lignin directly associated with MFs. Simulated bio-nano-mechanical properties revealed stress distribution within the S2 and showed similar properties between the idealized 3D model and the native S2 (actual tomogram). Present work has great potential for significant advancements in lignocellulose research on nano-scale understanding of cell wall assembly/disassembly processes leading to more efficient industrial processes of functionalization, valorization and target modification technologies.

3-D reconstruction↗

DOE OSTI2016

Modeling fuels and fire effects in 3D: Model description and applications

Scientists and managers critically need ways to assess how fuel treatments alter fire behavior, yet few tools currently exist for this purpose. In this work, we present a spatially-explicit-fuel-modeling system, FuelManager, which models fuels, vegetation growth, fire behavior (using a physics-based model, FIRETEC), and fire effects. FuelManager's flexible approach facilitates modeling fuels across a wide range of detail. Large trees or shrubs with specific coordinates are modeled as individual “Plants”, while understory plants are modeled as collections of plants called “LayerSets”. Both Plants and LayerSets contain various fuel particles (leaves, needles, twigs) with various properties including shape, size and surface area to volume ratio. A wide range of vegetation and treatments can be modeled, analyzed quantitatively and visualized in a 3D viewer. We describe the modeling approach and demonstrate fuel modeling at different levels of detail, fuel treatment and fire effects capabilities. Lastly, detailed model equations are provided in the Appendices.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Polyhedral 3D structure of human plasma very low density lipoproteins by individual particle cryo-electron tomography

Human VLDLs assembled in the liver and secreted into the circulation supply energy to peripheral tissues. VLDL lipolysis yields atherogenic LDLs and VLDL remnants that strongly correlate with CVD. Although the composition of VLDL particles has been well-characterized, their 3D structure is elusive because of their variations in size, heterogeneity in composition, structural flexibility, and mobility in solution. Here, we employed cryo-electron microscopy and individual-particle electron tomography to study the 3D structure of individual VLDL particles (without averaging) at both below and above their lipid phase transition temperatures. The 3D reconstructions of VLDL and VLDL bound to antibodies revealed an unexpected polyhedral shape, in contrast to the generally accepted model of a spherical emulsion-like particle. The smaller curvature of surface lipids compared with HDL may also reduce surface hydrophobicity, resulting in lower binding affinity to the hydrophobic distal end of the N-terminal β-barrel domain of cholesteryl ester transfer protein (CETP) compared with HDL. The directional binding of CETP to HDL and VLDL may explain the function of CETP in transferring TGs and cholesteryl esters between these particles. This first visualization of the 3D structure of VLDL could improve our understanding of the role of VLDL in atherogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Anatomy of an agricultural antagonist: Feeding complex structure and function of three xylem sap‐feeding insects illuminated with synchrotron‐based 3D imaging

Abstract Many insects feed on xylem or phloem sap of vascular plants. Although physical damage to the plant is minimal, the process of insect feeding can transmit lethal viruses and bacterial pathogens. Disparities between insect‐mediated pathogen transmission efficiency have been identified among xylem sap‐feeding insects; however, the mechanistic drivers of these trends are unclear. Identifying and understanding the structural factors and associated integrated functional components that may ultimately determine these disparities are critical for managing plant diseases. Here, we applied synchrotron‐based X‐ray microcomputed tomography to digitally reconstruct the morphology of three xylem sap‐feeding insect vectors of plant pathogens: Graphocephala atropunctata (blue‐green sharpshooter; Hemiptera, Cicadellidae) and Homalodisca vitripennis (glassy‐winged sharpshooter; Hemiptera, Cicadellidae), and the spittlebug Philaenus spumarius (meadow spittlebug; Hemiptera, Aphrophoridae). The application of this technique revealed previously undescribed anatomical features of these organisms, such as key components of the salivary complex. The visualization of the 3D structure of the precibarial valve led to new insights into the mechanism of how this structure functions. Morphological disparities with functional implications between taxa were highlighted as well, including the morphology and volume of the cibarial dilator musculature responsible for extracting xylem sap, which has implications for force application capabilities. These morphological insights will be used to target analyses illuminating functional differences in feeding behavior.

3D imaging↗

DOE OSTI2024

All-optical image denoising using a diffractive visual processor

Abstract Image denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers, present latency due to several iterations implemented in, e.g., graphics processing units (GPUs). While deep learning-enabled methods can operate non-iteratively, they also introduce latency and impose a significant computational burden, leading to increased power consumption. Here, we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images – implemented at the speed of light propagation within a thin diffractive visual processor that axially spans <250 × λ, where λ is the wavelength of light. This all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features, causing them to miss the output image Field-of-View (FoV) while retaining the object features of interest. Our results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of ~30–40%. We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz spectrum. Owing to their speed, power-efficiency, and minimal computational overhead, all-optical diffractive denoisers can be transformative for various image display and projection systems, including, e.g., holographic displays.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Computational 3D histological phenotyping of whole zebrafish by X-ray histotomography

Organismal phenotypes frequently involve multiple organ systems. Histology is a powerful way to detect cellular and tissue phenotypes, but is largely descriptive and subjective. To determine how synchrotron-based X-ray micro-tomography (micro-CT) can yield 3-dimensional whole-organism images suitable for quantitative histological phenotyping, we scanned whole zebrafish, a small vertebrate model with diverse tissues, at ~1 micron voxel resolutions. Micro-CT optimized for cellular characterization (histotomography) allows brain nuclei to be computationally segmented and assigned to brain regions, and cell shapes and volumes to be computed for motor neurons and red blood cells. Striking individual phenotypic variation was apparent from color maps of computed densities of brain nuclei. Unlike histology, the histotomography also allows the study of 3-dimensional structures of millimeter scale that cross multiple tissue planes. We expect the computational and visual insights into 3D cell and tissue architecture provided by histotomography to be useful for reference atlases, hypothesis generation, comprehensive organismal screens, and diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Segmentation of tomography datasets using 3D convolutional neural networks

Dendritic microstructures are ubiquitous in nature and are the primary solidification morphologies in metallic materials. Techniques such as X-ray computed tomography (XCT) have provided new insights into dendritic phase transformation phenomena. However, manual identification of dendritic morphologies in microscopy data can be both labor intensive and potentially ambiguous. The analysis of 3D datasets is particularly challenging due to their large sizes (terabytes) and the presence of artifacts scattered within the imaged volumes. Here, in this study, we trained 3D convolutional neural networks (CNNs) to segment 3D datasets. Three CNN architectures were investigated, including a new version of FCDenseNet which we extended to 3D. We show that using hyperparameter optimization (HPO) and fine-tuning techniques, both 2D and 3D CNN architectures outperform the previous state of the art. The 3D U-Net architecture trained in this study produced the best segmentations according to quantitative metrics (intersection-over-union of 95.56% and a boundary displacement error of 0.58 pixels), while 3D FCDense produced the smoothest boundaries and best segmentations according to visual inspection. The trained 3D CNNs are able to segment entire 852 × 852 × 250 voxel 3D volumes in only ~60 s, thus hastening the progress towards a deeper understanding of phase transformation phenomena such as dendritic solidification.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Interactive Correlation Analysis and Visualization of Climate Data

The relationship between our ability to analyze and extract insights from visualization of climate model output and the capability of the available resources to make those visualizations has reached a crisis point. The large volume of data currently produced by climate models is overwhelming the current, decades-old visualization workflow. The traditional methods for visualizing climate output also have not kept pace with changes in the types of grids used, the number of variables involved, and the number of different simulations performed with a climate model or the feature-richness of high-resolution simulations. This project has developed new and faster methods for visualization in order to get the most knowledge out of the new generation of high-resolution climate models. While traditional climate images will continue to be useful, there is need for new approaches to visualization and analysis of climate data if we are to gain all the insights available in ultra-large data sets produced by high-resolution model output and ensemble integrations of climate models such as those produced for the Coupled Model Intercomparison Project. Towards that end, we have developed new visualization techniques for performing correlation analysis. We have also introduced highly scalable, parallel rendering methods for visualizing large-scale 3D data. This project was done jointly with climate scientists and visualization researchers at Argonne National Laboratory and NCAR.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Examining phase separation and crystallization in glasses with X-ray nano-computed tomography

X-ray nano-computed tomography (nano-CT) is a powerful technique to characterize and visualize 3 dimensional (3D) phenomena in complex glasses at the nanoscale. This technique can offer a unique opportunity to explore the intricate morphology of multicomponent glass and glass-ceramic samples, due to its low X-ray energy and high spatial resolution (down to 50 nm). In the current demonstration paper, nano-CT provided insight into crystallization and phase separation, as well as a variety of other phenomena, including corrosion, fracture, and porosity. At scales ranging from 100 to 20 μm, the microstructures of phase separation in borosilicate, complex silicate, and chalcogenide glass compositions were examined. In addition, crystallites present in simulant nuclear waste glasses, volcanic glasses, and other related samples were explored. Nano-CT analysis can add to the understanding of (1) the formation processes, (2) distributions, interactions, and compositions of phases, and (3) the mechanisms, structures, and growth of crystallization and phase separation. Nano-CT offers wide potential in the field of glass science, especially when (1) common characterization methods are insufficient, (2) simple sample preparation is required, (3) 3D rendering is needed, or (4) compelling images of small, complex features are desired.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Gradient Architecture Design in Scalable Porous Battery Electrodes

Because it has been demonstrated to be effective toward faster ion diffusion inside the pore space, low-tortuosity porous architecture has become the focus in thick electrode designs, and other possibilities are rarely investigated. Here, to advance current understanding in the structure-affected electrochemistry and to broaden horizons for thick electrode designs, we present a gradient electrode design, where porous channels are vertically aligned with smaller openings on one end and larger openings on the other. With its 3D morphology carefully visualized by Raman mapping, the electrochemical properties between opposite orientations of the gradient electrodes are compared, and faster energy storage kinetics is found in larger openings and more concentrated active material near the separator. As further verified by simulation, this study on gradient electrode design deepens the knowledge of structure-related electrochemistry and brings perspectives in high-energy battery electrode designs.

25 ENERGY STORAGE↗

DOE OSTI2015

Super-resolution reconstruction in frequency, image, and wavelet domains to reduce through-plane partial voluming in MRI

Purpose: To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging. Methods: The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) of image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities. Results: Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in resampled out-of-plane views consistently showed the superiority of SRR compared to original axial and coronal image acquisitions. Conclusions: Thick-slice 2D T2-weighted MRI scans are part of many routine clinical protocols due to their high signal-to-noise ratio, but are often severely affected by through-plane partial voluming effects. This study shows that while radiologic assessment is performed in 2D on thick-slice scans, super-resolution MRI reconstruction techniques can be used to fuse those scans to generate a high-resolution image with reduced partial voluming for improved postacquisition processing. Qualitative and quantitative evaluation showed the efficacy of all SRR techniques with the best results obtained from SRR in the image domain. The limitations of SRR techniques are uncertainties in modeling the slice profile, density compensation, quantization in resampling, and uncompensated motion between scans.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Fat Crayon Toolkit

The Fat Crayon Toolkit (FCT) provides python modules for assisting in the design and visualization of boreholes and tunnels and their relationship with natural features such as fractures. Distances of closest approach among the boreholes can be calculated, along with other key design metrics. Additionally, the shear propensity of natural fractures (either deterministic or stochastic) can be visualized in either 3D (as VTK files) or in 2D (stereonets). The example provided demonstrates a test bed developed for the Enhanced Geothermal Systems (EGS) Collab project. This material is based upon work supported by the Geothermal Office of the Department of Energy and the Sanford Underground Research Facility and was prepared by LLNL under Contract DE-AC52-07NA27344.

Morris, JosephP.↗

DOE OSTI2025

Remote sensing images, DEM, and point clouds associated with “Accuracy evaluation of cost-effective 3D reconstruction approaches for hydrobiogeochemical processes in non-perennial stream riverbeds”

This data package is associated with the publication “Accuracy evaluation of cost-effective 3D reconstruction approaches for hydrobiogeochemical processes in non-perennial stream riverbeds” published in Frontiers in Environmental Science, Environmental Informatics and Remote Sensing (Bao et al., 2026; doi: 10.3389/fenvs.2026.1725258). This data package includes the drone photos for a section of Umtanum Creek in Washington, Unted States. The photos were used to reconstruct the 3-dimensional (3D) digital elevation model (DEM) of the riverbed for the investigated stream section. The reconstruction results from four approaches are provided: (1) unoccupied aerial vehicle (UAV, colloquially known as drone) imagery-based Structure-from-Motion (SfM), (2) a machine learning-based 3D reconstruction model, Visual Geometry Grounded Deep Structure from Motion (VGGSfM), (3) Visual Geometry Grounded Transformer for long sequence of images (VGGT-Long), and (4) handheld smartphone LiDAR scanning. The ground truth measurements by tripod-mounted optical level kit and ground control points GPS locations for evaluating the accuracy of the four reconstruction approaches are also provided in this data package. A preliminary version of this data package was published in October 2025 at the time of manuscript submission. It was updated in March 2026, at the time of manuscript acceptance, to include additional metadata (this readme, data dictionary, and file level metadata). The data did not change. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) 8 folders; (2) the detailed flight configuration html files; (3) field metadata; (4) a readme; (5) a data dictionary; and (6) file-level metadata. The folders “2024_10_18_d01” and “2024_10_18_d02” contain the original drone photos for the two drone flights (d01 and d02) on October 18, 2024. The reconstruction results from each of the approaches are in the folders called “ODM_SfM”, “VGGSfM”, “VGGTLong”, and “LiDAR”. The ground truth measurements are in the folder called “optical_level_kit”. Lastly, results comparing the different approaches are in the folder called “comparisons”. All files are .csv, .html, .jpg, .obj, .txt, and .npy. For information on using the .obj and .npy files, see the readme files within the same folder as the files.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Tools to Address Glare and Avian Flux Hazards from Solar Energy Systems

This report describes software tools that can be used to evaluate and mitigate potential glare and avian-flux hazards from photovoltaic and concentrating solar power (CSP) plants. Enhancements to the Solar Glare Hazard Analysis Tool (SGHAT) include new block-space receptor models, integration of PVWatts for energy prediction, and a 3D daily glare visualization feature. Tools and methods to evaluate avian-flux hazards at CSP plants with large heliostat fields are also discussed. Alternative heliostat standby aiming strategies were investigated to reduce the avian-flux hazard and minimize impacts to operational performance. Finally, helicopter flyovers were conducted at the National Solar Thermal Test Facility and at the Ivanpah Solar Electric Generating System to evaluate the alternative heliostat aiming strategies and to provide a basis for model validation. Results showed that the models generally overpredicted the measured results, but they were able to simulate the trends in irradiance values with distance. A heliostat up-aiming strategy is recommended to alleviate both glare and avian-flux hazards, but operational schemes are required to reduce the impact on heliostat slew times and plant performance. Future studies should consider the trade-offs and collective impacts on these three factors of glare, avian-flux hazards, and plant operations and performance.

14 SOLAR ENERGY↗

DOE OSTI2025

Evaluating FRI3D for Cost Savings in Fire Hazard Analysis at DOE Sites

A fire hazard analysis, required for many U.S. Department of Energy (DOE) facilities, is a complex, cumbersome, and costly process. Fire hazard analyses may be viewed as a checkbox, but ideally and in spirit with the DOE-STD-1066, the fire hazard analysis (FHA) should be a part of the workflow and used to help in modifications, maintenance, and improving operational safety. With current FHA development processes, it is both time and cost prohibitive for true integration. A tool called Fire Risk Investigation in 3D or FRI3D was developed under the DOE Light Water Reactor Sustainability program to simplify and automate many aspects of a fire probabilistic risk analysis for existing nuclear power plants. The FRI3D tool automates fire scenarios by combining approved fire simulation codes, U.S. Nuclear Regulatory Commission fire calculations methods, 3D modeling and visualization, and probabilistic risk analysis models into a single workflow supported with a user interface. FRI3D was initially designed for used in combination with a PRA, this case study, evaluated using FRI3D for a plant modification, determined the benefits that detailed fire modeling can have for U.S. Department of Energy facilities with or without a PRA model. It also looked at what tasks from DOE requirements could be reduced using the tool and what is needed to integrate fire hazard analysis into site workflow.

97 - MATHEMATICS AND COMPUTING↗