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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Transient mixing behavior of a supercritical fluid injected into supercritical and subcritical environments

Transient, near-field mixing of a supercritical fluid injected into supercritical and subcritical environments is investigated experimentally. Fuel (propane) from a 100 μm diameter Bosch diesel injector is injected into a high-pressure test rig with a steady flow of heated, low-velocity nitrogen to control the ambient pressure and temperature. The fuel supply pressure is approximately 190 bar, allowing short injections lasting 3–4 ms to be performed in quick succession to acquire statistically significant datasets to represent the unsteady fuel–air mixing. Two test cases with the same ambient density and injector inlet pressure and temperature were chosen in an attempt to isolate effects of mixture phase behavior. Microscopic rainbow Schlieren deflectometry (RSD) is used for visualization and quantitative data acquisition. In the case of the supercritical ambient, the injector inlet and exit and ambient conditions are all supercritical. The RSD analysis reveals a mixing process similar to the single phase fluid mixing, though condensation is also observed locally, and can be explained by the adiabatic mixing theory presented in the paper. For the subcritical ambient case, the injector inlet is supercritical, but the injector exit and ambient conditions are both subcritical. The results show a rapid expansion in the near-field promoting mixing between propane and nitrogen. At downstream locations, significant condensation is also observed as predicted by the adiabatic mixing theory. As a result, the supercritical ambient case exhibited longer and narrower jet penetration compared to the subcritical ambient case.

02 PETROLEUM↗
DOE OSTI2021

Anatomy of Continuous Mars SEIS and Pressure Data from Unsupervised Learning

The seismic noise recorded by the Interior Exploration using Seismic Investigations, Geodesy, and Heat Transport (InSight) seismometer (Seismic Experiment for Interior Structure [SEIS]) has a strong daily quasi-periodicity and numerous transient microevents, associated mostly with an active Martian environment with wind bursts, pressure drops, in addition to thermally induced lander and instrument cracks. That noise is far from the Earth’s microseismic noise. Quantifying the importance of nonstochasticity and identifying these microevents is mandatory for improving continuous data quality and noise analysis techniques, including autocorrelation. Cataloging these events has so far been made with specific algorithms and operator’s visual inspection. We investigate here the continuous data with an unsupervised deep-learning approach built on a deep scattering network. This leads to the successful detection and clustering of these microevents as well as better determination of daily cycles associated with changes in the intensity and color of the background noise. We first provide a description of our approach, and then present the learned clusters followed by a study of their origin and associated physical phenomena. We show that the clustering is robust over several Martian days, showing distinct types of glitches that repeat at a rate of several tens per sol with stable time differences. We show that the clustering and detection efficiency for pressure drops and glitches is comparable to or better than manual or targeted detection techniques proposed to date, noticeably with an unsupervised approach. Finally, here we discuss the origin of other clusters found, especially glitch sequences with stable time offsets that might generate artifacts in autocorrelation analyses. We conclude with presenting the potential of unsupervised learning for long-term space mission operations, in particular, for geophysical and environmental observatories.

58 GEOSCIENCES↗
DOE OSTI2024

The Zwicky Transient Facility Bright Transient Survey. III. BTSbot: Automated Identification and Follow-up of Bright Transients with Deep Learning

Abstract The Bright Transient Survey (BTS) aims to obtain a classification spectrum for all bright ( m peak ≤ 18.5 mag) extragalactic transients found in the Zwicky Transient Facility (ZTF) public survey. BTS critically relies on visual inspection (“scanning”) to select targets for spectroscopic follow-up, which, while effective, has required a significant time investment over the past ∼5 yr of ZTF operations. We present BTSbot , a multimodal convolutional neural network, which provides a bright transient score to individual ZTF detections using their image data and 25 extracted features. BTSbot is able to eliminate the need for daily human scanning by automatically identifying and requesting spectroscopic follow-up observations of new bright transient candidates. BTSbot recovers all bright transients in our test split and performs on par with scanners in terms of identification speed (on average, ∼1 hr quicker than scanners). We also find that BTSbot is not significantly impacted by any data shift by comparing performance across a concealed test split and a sample of very recent BTS candidates. BTSbot has been integrated into Fritz and Kowalski , ZTF’s first-party marshal and alert broker, and now sends automatic spectroscopic follow-up requests for the new transients it identifies. Between 2023 December and 2024 May, BTSbot selected 609 sources in real time, 96% of which were real extragalactic transients. With BTSbot and other automation tools, the BTS workflow has produced the first fully automatic end-to-end discovery and classification of a transient, representing a significant reduction in the human time needed to scan.

Rehemtulla, Nabeel (ORCID:0000000256832389)↗
DOE OSTI2023

Pool boiling on metal-foam enhanced tube bundle: heat transfer characteristics and flow visualization

A flooded evaporator configuration is common in large central air conditioning or process cooling systems. It is basically a shell and tube heat exchanger, in which a secondary fluid (brine or water) circulates inside the tube bundle and is cooled by the vaporization of the refrigerant on the outside surface of the tubes. The enhanced pool boiling process enables the compact design of flooded evaporators, which substantially reduces the refrigerant charge. High-porosity metal foam, with a large surface-area-to-volume ratio, could provide an extended heat transfer area and a high-density of nucleation sites. This study experimentally investigated the pool boiling heat transfer and flow characteristics on metal-foam enhanced tube bundles. The enhanced bundle consists of four aluminum tubes with aluminum foam brazed around the outer surface, which are horizontally mounted in a staggered arrangement. The results showed that the metal-foam enhanced tube bundles improved the heat transfer coefficient by 100-160% with a lower wall temperature difference of 1-10°C, compared to the baseline. In addition, the tube pitch played a significant role in determining the pool boiling behavior of the tube bundles.

Yang, Cheng-Min↗
DOE OSTI2016

Noise suppressed partial volume correction for cardiac SPECT/CT

Purpose: Partial volume correction (PVC) methods typically improve quantification at the expense of increased image noise and reduced reproducibility. In this study, the authors developed a novel voxel-based PVC method that incorporates anatomical knowledge to improve quantification while suppressing noise for cardiac SPECT/CT imaging. Methods: In the proposed method, the SPECT images were first reconstructed using anatomical-based maximum a posteriori (AMAP) with Bowsher’s prior to penalize noise while preserving boundaries. A sequential voxel-by-voxel PVC approach (Yang’s method) was then applied on the AMAP reconstruction using a template response. This template response was obtained by forward projecting a template derived from a contrast-enhanced CT image, and then reconstructed using AMAP to model the partial volume effects (PVEs) introduced by both the system resolution and the smoothing applied during reconstruction. To evaluate the proposed noise suppressed PVC (NS-PVC), the authors first simulated two types of cardiac SPECT studies: a {sup 99m}Tc-tetrofosmin myocardial perfusion scan and a {sup 99m}Tc-labeled red blood cell (RBC) scan on a dedicated cardiac multiple pinhole SPECT/CT at both high and low count levels. The authors then applied the proposed method on a canine equilibrium blood pool study following injection with {sup 99m}Tc-RBCs at different count levels by rebinning the list-mode data into shorter acquisitions. The proposed method was compared to MLEM reconstruction without PVC, two conventional PVC methods, including Yang’s method and multitarget correction (MTC) applied on the MLEM reconstruction, and AMAP reconstruction without PVC. Results: The results showed that the Yang’s method improved quantification, however, yielded increased noise and reduced reproducibility in the regions with higher activity. MTC corrected for PVE on high count data with amplified noise, although yielded the worst performance among all the methods tested on low-count data. AMAP effectively suppressed noise and reduced the spill-in effect in the low activity regions. However it was unable to reduce the spill-out effect in high activity regions. NS-PVC yielded superior performance in terms of both quantitative assessment and visual image quality while improving reproducibility. Conclusions: The results suggest that NS-PVC may be a promising PVC algorithm for application in low-dose protocols, and in gated and dynamic cardiac studies with low counts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Simulation of Wind Turbine Performance and Loading Patterns using a Coupled Meso-scale/Micro-scale Flow Analysis Model

HELIOS simulations were conducted for the WPS-30 turbine from the Sexbierum experimental site. The MMCI module was used to include the effects of the atmospheric boundary layer using the strategy described in the methodology section. In Figure 1 , the thrust and power variation for the WRF/Helios (Meso-scale/micro-scale simulation) is compared with measured power and stand-alone Helios computations (uniform inflow). The unsteady variations in power and thrust caused by the turbulent inflow conditions is clearly evident from these figures. Note that the mean hub height velocity could not be exactly matched to the uniform inflow values of 8 m/s because of constraints in adjusting the geostrophic wind and roughness length in Meso-scale WRF simulations. The offset in mean power and thrust notable in the figures are because of the small difference in the mean wind speed. Nonetheless, these results provide proof-of-concept of the integrated Meso-scale/Micro-scale simulation capability developed as part of this work. To further substantiate the effects of turbulent inflow, flow visualizations (iso-surfaces of vorticity overlaid on contours of velocity magnitude) are shown in Figure 2 . Meandering of the vortex wake and eventual breakdown are observed in the flow visualizations. Vortex breakdown is observed to occur between 1.5 and 2.5 diameter distance from the turbine. In uniform inflow (not shown here), the vortex wake persists to much longer distance of about 5 diameters before beginning to breakdown. It is expected that the vortex breakdown will be strongly correlated with the turbulence intensity of the inflow. The capability developed herein provides enabling technology for analyzing and characterizing such effects.

17 WIND ENERGY↗
DOE OSTI2021

Curvature-mediated spin textures in magnetic multi-layered nanotubes

The scientific and technological exploration of artificially designed three-dimensional magnetic nanostructures opens the path to exciting novel physical phenomena, originating from the increased complexity in spin textures, topology, and frustration in three dimensions. Theory predicts that the equilibrium magnetic ground state of two-dimensional systems which reflects the competition between symmetric (Heisenberg) and antisymmetric (Dzyaloshinskii-Moriya interaction (DMI)) exchange interaction is significantly modified on curved surfaces when the radius of local curvature becomes comparable to fundamental magnetic length scales. Here, we present an experimental study of the spin texture in an 8 nm thin magnetic multilayer with growth-induced in-plane anisotropy and DMI deposited onto the curved surface of a 1.8 {\mu}m long non-magnetic carbon nanowire with a 67 nm radius. Using magnetic soft x-ray tomography the three-dimensional spin configuration in this nanotube was retrieved with about 30nm spatial resolution. The transition between two vortex configurations on the two ends of the nanotube with opposite circulation occurs through a domain wall that is aligned at an inclined angle relative to the wire axis. Three-dimensional micromagnetic simulations support the experimental observations and represent a visualization of the curvature-mediated DMI. They also allow a quantitative estimate of the DMI value for the magnetic multilayered nanotube.

Josten, Elisabeth↗
DOE OSTI2012

Metal artifact reduction strategies for improved attenuation correction in hybrid PET/CT imaging

Metallic implants are known to generate bright and dark streaking artifacts in x-ray computed tomography (CT) images, which in turn propagate to corresponding functional positron emission tomography (PET) images during the CT-based attenuation correction procedure commonly used on hybrid clinical PET/CT scanners. Therefore, visual artifacts and overestimation and/or underestimation of the tracer uptake in regions adjacent to metallic implants are likely to occur and as such, inaccurate quantification of the tracer uptake and potential erroneous clinical interpretation of PET images is expected. Accurate quantification of PET data requires metal artifact reduction (MAR) of the CT images prior to the application of the CT-based attenuation correction procedure. In this review, the origins of metallic artifacts and their impact on clinical PET/CT imaging are discussed. Moreover, a brief overview of proposed MAR methods and their advantages and drawbacks is presented. Although most of the presented MAR methods are mainly developed for diagnostic CT imaging, their potential application in PET/CT imaging is highlighted. The challenges associated with comparative evaluation of these methods in a clinical environment in the absence of a gold standard are also discussed.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2013

Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors: Automated measurement development for full field digital mammography

Purpose: The Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors are used for standardized mammographic reporting and are assessed visually. This reporting is clinically relevant because breast composition can impact mammographic sensitivity and is a breast cancer risk factor. New techniques are presented and evaluated for generating automated BI-RADS breast composition descriptors using both raw and calibrated full field digital mammography (FFDM) image data.Methods: A matched case-control dataset with FFDM images was used to develop three automated measures for the BI-RADS breast composition descriptors. Histograms of each calibrated mammogram in the percent glandular (pg) representation were processed to create the new BR{sub pg} measure. Two previously validated measures of breast density derived from calibrated and raw mammograms were converted to the new BR{sub vc} and BR{sub vr} measures, respectively. These three measures were compared with the radiologist-reported BI-RADS compositions assessments from the patient records. The authors used two optimization strategies with differential evolution to create these measures: method-1 used breast cancer status; and method-2 matched the reported BI-RADS descriptors. Weighted kappa (κ) analysis was used to assess the agreement between the new measures and the reported measures. Each measure's association with breast cancer was evaluated with odds ratios (ORs) adjusted for body mass index, breast area, and menopausal status. ORs were estimated as per unit increase with 95% confidence intervals.Results: The three BI-RADS measures generated by method-1 had κ between 0.25–0.34. These measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.87 (1.34, 2.59) for BR{sub pg}; (b) OR = 1.93 (1.36, 2.74) for BR{sub vc}; and (c) OR = 1.37 (1.05, 1.80) for BR{sub vr}. The measures generated by method-2 had κ between 0.42–0.45. Two of these measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.95 (1.24, 3.09) for BR{sub pg}; (b) OR = 1.42 (0.87, 2.32) for BR{sub vc}; and (c) OR = 2.13 (1.22, 3.72) for BR{sub vr}. The radiologist-reported measures from the patient records showed a similar association, OR = 1.49 (0.99, 2.24), although only borderline statistically significant.Conclusions: A general framework was developed and validated for converting calibrated mammograms and continuous measures of breast density to fully automated approximations for the BI-RADS breast composition descriptors. The techniques are general and suitable for a broad range of clinical and research applications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-T-154: Establishment and Implement of 3D Image Guided Brachytherapy Planning System

Purpose: Cannot observe the dose intuitionally is a limitation of the existing 2D pre-implantation dose planning. Meanwhile, a navigation module is essential to improve the accuracy and efficiency of the implantation. Hence a 3D Image Guided Brachytherapy Planning System conducting dose planning and intra-operative navigation based on 3D multi-organs reconstruction is developed. Methods: Multi-organs including the tumor are reconstructed in one sweep of all the segmented images using the multiorgans reconstruction method. The reconstructed organs group establishs a three-dimensional visualized operative environment. The 3D dose maps of the three-dimentional conformal localized dose planning are calculated with Monte Carlo method while the corresponding isodose lines and isodose surfaces are displayed in a stereo view. The real-time intra-operative navigation is based on an electromagnetic tracking system (ETS) and the fusion between MRI and ultrasound images. Applying Least Square Method, the coordinate registration between 3D models and patient is realized by the ETS which is calibrated by a laser tracker. The system is validated by working on eight patients with prostate cancer. The navigation has passed the precision measurement in the laboratory. Results: The traditional marching cubes (MC) method reconstructs one organ at one time and assembles them together. Compared to MC, presented multi-organs reconstruction method has superiorities in reserving the integrality and connectivity of reconstructed organs. The 3D conformal localized dose planning, realizing the 'exfoliation display' of different isodose surfaces, helps make sure the dose distribution has encompassed the nidus and avoid the injury of healthy tissues. During the navigation, surgeons could observe the coordinate of instruments real-timely employing the ETS. After the calibration, accuracy error of the needle position is less than 2.5mm according to the experiments. Conclusion: The speed and quality of 3D reconstruction, the efficiency in dose planning and accuracy in navigation all can be improved simultaneously.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Integration of transcriptomic and proteomic data identifies biological functions in cell populations from human infant lung

Systems biology uses computational approaches to integrate diverse data types to understand cell and organ behavior. Data derived from complementary technologies, for example transcriptomic and proteomic analyses, are providing new insights into development and disease. We compared mRNA and protein profiles from purified endothelial, epithelial, immune, and mesenchymal cells from normal human lung tissue. Signatures for each cell type were identified and compared at both mRNA and protein levels. Cell specific biological processes and pathways were predicted by analysis of concordant and discordant RNA-protein pairs. Cell clustering and gene set enrichment comparisons identified shared versus unique processes associated with transcriptomic and/or proteomic data. Clear cell-cell correlations between mRNA and protein data were obtained from each cell type. Approximately 40% of RNA-protein pairs were coherently expressed. While the correlation between RNA and their protein products was relatively low (approximately 0.4), cell specific signature genes involved in functional processes characteristic of each cell type, were more highly correlated with their protein products. Consistency of cell specific RNA-protein signatures indicated an essential framework for the function of each cell type. Visualization and reutilization of the protein and RNA profiles are supported by a new web application, "LungProteomics," which is incorporated into the LGEA web portal and freely accessible at (https://research.cchmc.org/pbge/lunggens/lungProteomics/human_sorted_profiles.html).

human lung, sorted cells, integrated omics, Transc↗
DOE OSTI2012

Alternative Fuel for Portland Cement Processing

The production of cement involves a combination of numerous raw materials, strictly monitored system processes, and temperatures on the order of 1500 °C. Immense quantities of fuel are required for the production of cement. Traditionally, energy from fossil fuels was solely relied upon for the production of cement. The overarching project objective is to evaluate the use of alternative fuels to lessen the dependence on non-renewable resources to produce portland cement. The key objective of using alternative fuels is to continue to produce high-quality cement while decreasing the use of non-renewable fuels and minimizing the impact on the environment. Burn characteristics and thermodynamic parameters were evaluated with a laboratory burn simulator under conditions that mimic those in the preheater where the fuels are brought into a cement plant. A drop-tube furnace and visualization method were developed that show potential for evaluating time- and space-resolved temperature distributions for fuel solid particles and liquid droplets undergoing combustion in various combustion atmospheres. Downdraft gasification has been explored as a means to extract chemical energy from poultry litter while limiting the throughput of potentially deleterious components with regards to use in firing a cement kiln. Results have shown that the clinkering is temperature independent, at least within the controllable temperature range. Limestone also had only a slight effect on the fusion when used to coat the pellets. However, limestone addition did display some promise in regards to chlorine capture, as ash analyses showed chlorine concentrations of more than four times greater in the limestone infused ash as compared to raw poultry litter. A reliable and convenient sampling procedure was developed to estimate the combustion quality of broiler litter that is the best compromise between convenience and reliability by means of statistical analysis. Multi-day trial burns were conducted at a full-scale cement plant with alternative fuels to examine their compatibility with the cement production process. Construction and demolition waste, woodchips, and soybean seeds were used as alternative fuels at a full-scale cement production facility. These fuels were co-fired with coal and waste plastics. The alternative fuels used in this trial accounted for 5 to 16 % of the total energy consumed during these burns. The overall performance of the portland cement produced during the various trial burns performed for practical purposes very similar to the cement produced during the control burn. The cement plant was successful in implementing alternative fuels to produce a consistent, high-quality product that increased cement performance while reducing the environmental footprint of the plant. The utilization of construction and demolition waste, woodchips and soybean seeds proved to be viable replacements for traditional fuels. The future use of these fuels depends on local availability, associated costs, and compatibility with a facility's production process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

In-Situ Visualization of a Growing Brittle Crack in Aluminum Oxynitride Using Synchrotron X-Rays and the Double-Cleavage Drilled Compression Geometry

Brittle fracture is difficult to study in situ due to the speed of a growing crack and the often-catastrophic nature of failure in brittle materials. As a result, the influence of microstructural considerations, such as orientation, grain boundary locations, and strain field, on the crack path remains poorly understood. Presented in this study is a method addressing this knowledge gap, which utilizes the double-cleavage drilled compression geometry to achieve quasi-stable fracture in aluminum oxynitride (AlON). Synchrotron X-ray micro-computed tomography is used to characterize the crack shape and length, while high-energy diffraction microscopy provides information on the strains, orientations, and shapes of grains in the microstructure surrounding the crack tip. During testing, the crack grew in discrete and irregular jumps while the fracture toughness falls within reported ranges. The crack in AlON is found to have no greater tendency to crack intergranularly as compared to transgranularly, and grains which are cracked transgranularly do not display a trend in orientation or stress when compared to those around which the crack followed a grain boundary. The high resolution of the crack path and microstructural data provides a path forward for modeling and understanding 3D brittle fracture.

Gorske, Sara F.↗
DOE OSTI2018

A Novel CT to Cone-Beam CT Registration Method Enables Immediate Real-Time Intraprocedural Three-Dimensional Assessment of Ablative Treatments of Liver Malignancies

AimTo evaluate a novel contrast-enhanced cone-beam computed tomography (CE-CBCT) registration method for accurate immediate assessment of ablation outcomes.Materials and MethodsContrast-enhanced computed tomography (CECT) was registered with CE-CBCT by applying semiautomatic landmark registration followed by automatic affine and non-rigid registration to correct for respiratory phase differences and liver deformation. This scheme was retrospectively applied to 30 patients who underwent 38 percutaneous microwave liver ablations. Three datasets were obtained for each case: (1) conventional CECT scans 24 h before ablation, (2) intraprocedural CE-CBCT scans, and (3) CECT scans 24 h post-ablation. Using a five-point scale, two experienced radiologists qualitatively assessed registration quality, equivalence of CE-CBCT assessment of ablation outcome to 24 h post-ablation CECT, and perceived increase of confidence using the fusion method to CBCT alone. Additionally, residual post-ablation tumor volumes were measured at both CE-CBCT and 24 h CECT and compared to the pre-CECT.ResultsRegistration quality was high for both radiologists (R1: 4.3 ± 0.6, R2: 4.4 ± 0.5; p = 0.87). Comparisons between the registration of pre-ablation CECT with CE-CBCT versus post-ablation CECT regarding the position of the ablated area to the treated target (R1: 4.4 ± 0.6, R2: 4.6 ± 0.4) and treatment outcome (R1: 4.5 ± 0.5, R2: 4.6 ± 0.4) were equivalent (p > 0.35). Increased confidence was noted when using fusion (R1: 4.6 ± 0.4, R2: 4.6 ± 0.4; p = 0.84). Moreover, in 6 ablations (15.8%) the intraprocedural registered CBCT showed residual tumor precisely where identified on the 24 h post-ablation CECT.ConclusionsCombined CE-CBCT holds the potential to change the current workflow of mini-invasive cancer local treatments. Given earlier visual identification of residual tumor post-ablation, this includes potentially eliminating the need for some additional treatments.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Incremental k-core decomposition: Algorithms and evaluation

A k-core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. k-core decomposition is often used in large-scale network analysis, such as community detection, protein function prediction, visualization, and solving NP-hard problems on real networks efficiently, like maximal clique finding. In many real-world applications, networks change over time. As a result, it is essential to develop efficient incremental algorithms for dynamic graph data. In this paper, we propose a suite of incremental k-core decomposition algorithms for dynamic graph data. These algorithms locate a small subgraph that is guaranteed to contain the list of vertices whose maximum k-core values have changed and efficiently process this subgraph to update the k-core decomposition. We present incremental algorithms for both insertion and deletion operations, and propose auxiliary vertex state maintenance techniques that can further accelerate these operations. Our results show a significant reduction in runtime compared to non-incremental alternatives. We illustrate the efficiency of our algorithms on different types of real and synthetic graphs, at varying scales. Furthermore, for a graph of 16 million vertices, we observe relative throughputs reaching a million times, relative to the non-incremental algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-R-18: Updates to the Computational Environment for Radiological Research for Image Analysis

Purpose: To present new tools in CERR for Texture Analysis and Visualization. Method: (1) Quantitative Image Analysis: We added the ability to compute Haralick texture features based on local neighbourhood. The Texture features depend on many parameters used in their derivation. For example: (a) directionality, (b) quantization of image, (c) patch-size for the neighborhood, (d) handling of the edge voxels within the region of interest, (e) Averaging co-occurance matrix vs texture features for different directions etc. A graphical user interface was built to set these parameters and then visualize their impact on the resulting texture maps. The entire functionality was written in Matlab. Array indexing was used to speed up the texture calculation. The computation speed is very competitive with the ITK library. Moreover, our implementation works with multiple CPUs and the computation time can be further reduced by using multiple processor threads. In order to reduce the Haralick texture maps into scalar features, we propose the use of Texture Volume Histograms. This lets users make use of the entire distribution of texture values within the region of interest rather than using just the mean and the standard deviations. (2) Qualitative/Visualization tools: The derived texture maps are stored as a new scan (derived) within CERR’s planC data structure. A display that compares various scans was built to show the raw image and the derived texture maps side-by-side. These images are positionally linked and can be navigated together. CERR’s graphics handling was updated and sped-up to be compatible with the newer Matlab versions. As a result, the users can use (a) different window levels and colormaps for different viewports, (b) click-and-drag or use mouse scroll-wheel to navigate slices. Results: The new features and updates are available via https://www.github.com/adityaapte/cerr . Conclusion: Features added to CERR increase its utility in Radiomics and Outcomes modeling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Turbulent Processes that Influence Boundary-Layer Cloud Structure (Final Technical Report)

Many models of the atmosphere simulate vertical profiles of observable fields, such as temperature, moisture, and vertical velocity. To assess the realism of such model output, it is important to evaluate the modeled profiles against observations. However, many extant evaluations consist of comparing time averaged profiles from the model and the observations. Such time averages can smooth out unrealistic features that appear in instantaneous profiles. In this way, the time averages may obscure certain model errors from detection. For instance, many models misrepresent turbulent processes, leading to profiles that are too smoothed out or too noisy. E.g., if a model has coarse vertical resolution and overly strong diffusion, then the model may be unable to produce observed sharp peaks. On the other hand, a model may have artificial approximations that produce spurious jumps in the vertical. Much can be learned by browsing through instantaneous snapshots of model output. But the volume of output produced by a global model is far too great to rely purely on visual inspection. In addition, we need a way to statistically characterize the profiles, so that anomalies can be detected more conveniently.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures

Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.

Generative Adversarial Networks↗