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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,639 records · Page 91

Prospective Seal Unit Spatial Extent Database for U.S. Sedimentary Basins

The Prospective Seal Unit Spatial Extent Database for U.S. Sedimentary Basins contains a series of spatial datasets representing spatial extents of publicly available data for caprock and seal rock units within the Appalachian Basin, Denver-Julesburg Basin, Great Valley Basin (Sacramento and San Joaquin Basins), Illinois Basin, Michigan Basin, San Juan Basin, U.S. Gulf Coast Basin, and Williston Basin. The database is designed to support carbon storage feasibility and resources assessment for carbon transport and storage (CTS) projects while displaying the spatial extent of prospective seal units and provide a guide to the original data source. This database leverages publicly available data resources from authoritative sources (e.g. U.S. Geological Survey, State Geologic Surveys, and published reports), and aims to help guide users to understand the seal unit's spatial coverage and data gaps from the regional to sub-basin/field scale. The database is organized by seal unit/formation, including the spatial extent for data found to be available for the seal unit. The various datasets represented include spatial extents of the lithologic formation, depth to top structural contour maps, and thickness/isopach maps. Included in this submission are the following resources: 1. Geodatabase/Dataset: “prospective-seal-unit-extents-2025.gdb” 2. ReadMe: “readme-prospective-seal-unit-spatial-extent-dataset-2025.pdf” 3. Data Catalog: “prospective-seal-unit-spatial-extents-data-catalog-2025.xlsx” 4. Data Sources Key: “data-source.csv” Please see NETL disclaimers here: https://netl.doe.gov/home/disclaimer

Basin↗

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗

Improved quality metrics for association and reproducibility in chromatin accessibility data using mutual information

Correlation metrics are widely utilized in genomics analysis and often implemented with little regard to assumptions of normality, homoscedasticity, and independence of values. This is especially true when comparing values between replicated sequencing experiments that probe chromatin accessibility, such as assays for transposase-accessible chromatin via sequencing (ATAC-seq). Such data can possess several regions across the human genome with little to no sequencing depth and are thus non-normal with a large portion of zero values. Despite distributed use in the epigenomics field, few studies have evaluated and benchmarked how correlation and association statistics behave across ATAC-seq experiments with known differences or the effects of removing specific outliers from the data. Here, we developed a computational simulation of ATAC-seq data to elucidate the behavior of correlation statistics and to compare their accuracy under set conditions of reproducibility. Using these simulations, we monitored the behavior of several correlation statistics, including the Pearson’s R and Spearman’s ρ coefficients as well as Kendall’s τ and Top–Down correlation. We also test the behavior of association measures, including the coefficient of determination R 2 , Kendall’s W, and normalized mutual information. Our experiments reveal an insensitivity of most statistics, including Spear man’s ρ, Kendall’s τ, and Kendall’s W, to increasing differences between simulated ATAC-seq replicates. The removal of co-zeros (regions lacking mapped sequenced reads) between simulated experiments greatly improves the estimates of correlation and association. After removing co-zeros, the R 2 coefficient and normalized mutual information display the best performance, having a closer one-to-one relationship with the known portion of shared, enhanced loci between simulated replicates. When comparing values between experimental ATAC-seq data using a random forest model, mutual information best predicts ATAC-seq replicate relationships. Collectively, this study demonstrates how measures of correlation and association can behave in epigenomics experiments. We provide improved strategies for quantifying relationships in these increasingly prevalent and important chromatin accessibility assays.

59 BASIC BIOLOGICAL SCIENCES↗

Generative AI for Power Grid Operations

Generative artificial intelligence (AI) has captured into the mainstream, demonstrating capabilities that once belonged solely to the realm of human cognition. From defeating world champions in complex games to generating human-quality text and images, Generative AI has proven its potential to revolutionize countless industries. The electric power grid is no exception. Generative AI's ability to process vast amounts of data rapidly, assist decision support and identify patterns could significantly enhance power grid operations. For example, Generative AI could improve state estimation where measurements are not available or integrate renewable energy sources more efficiently with probabilistic forecasting. The key contributions of this whitepaper are outlined below: (1) Comprehensive overview of Generative AI's applications in power grid operations: It highlights the opportunities in areas such as forecasting, state estimation, and demonstrating the potential for enhancing efficiency, reliability, and resilience. (2) Expanding Generative AI's impact through synergies with emerging technologies: The paper introduce NREL developed eGridGPT and explores how AI orchestration, multi-agent systems, and Digital Twins can collaborate to optimize grid operations, addressing the complexities of a decarbonized and electrified future. (3) In-depth analysis of challenges in implementing Generative AI: This includes considerations like data availability and quality, model validation, certification, and ethical concerns, ensuring responsible AI deployment. (4) Emphasizing human-AI collaboration: The whitepaper underscores the importance of trustworthy, transparency, and explainability in AI systems to promote seamless interaction between human operators and AI, ultimately improving decision-making. (5) Exploring future research and development: It identifies critical areas for further advancement to fully realize Generative AI's potential in power grid operations. This whitepaper serves as a valuable resource for researchers, practitioners, and policymakers looking to harness Generative AI for a more reliable, stable, and cost-effective power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Satellite-sensed winter nocturnal temperature patterns of the Everglades Agricultural Area

Surface temperature patterns of drained organic soil farmland in the Everglades Agricultural Area south of Lake Okeechobee, Florida, were studied using GOES-1 satellite infrared digital data for the winters of 1976-77 and 1977-78. Local thermal features were explained in terms of soil types, soil depths and climate modification caused by organic soil drainage. A cold-prone area was delineated in the Everglades Agricultural Area with satellite data. The winter nighttime surface temperatures of this area were more characteristic of north central Florida, approximately 370 km further north, than of surrounding areas of mineral soil or undrained organic soil.

Chen, E.↗

Cratering flow fields - Implications for the excavation and transient expansion stages of crater formation

Theoretical depths, volumes of excavation, hinge radii, ejection angles and transient structural rim uplifts are calculated, for comparison with experimental and field data from impact and explosion craters, by means of a Maxwell Z-model cratering flow field originating at non-zero depths-of-burst. It is found that the formation of a hinge, about which the coherent ejecta flap rotates at the rim of the transient crater, divides material in the flow field into ejected and downward and outward-driven portions. Ejected material originates from an excavation cavity whose geometry is distinct from that of the transient crater. The shallow depths of excavation both observed in impact and explosion craters and predicted by the Z-model flow fields imply that thickness estimates of such lunar geologic units as the maria basalts, which are determined by assuming that excavation depths are similar to (1) final or (2) transient crater depths, must be reduced by factors of two to three respectively. It is concluded that lunar basin excavation cavities exhibit proportional growth, and have maximum depths of excavation near 0.1 the diameter of the basin transient crater.

Croft, S. K.↗

Detection of Non-Symmetrical Damage in Smart Plate-Like Structures

A two-dimensional model for in-plane vibrations of a cantilever plate with a non-symmetrical damage is used in the context of defect identification in materials with piezoelectric ceramic patches bonded to their surface. These patches can act both as actuators and sensors in a self-analyzing fashion, which is a characteristic of smart materials. A Galerkin method is used to approximate the dynamic response of these structures. The natural frequency shifts due to the damage are estimated numerically and compared to experimental data obtained from tests on cantilever aluminum plate-like structures damaged at different locations with defects of different depths. The damage location and extent are determined by an enhanced least square identification method. Efficacy of the frequency shift based algorithms is demonstrated using experimental data.

Blanks, H. T.↗

A Model-Driven Visualization Tool for Use with Model-Based Systems Engineering Projects

Model-Based Systems Engineering (MBSE) promotes increased consistency between a system's design and its design documentation through the use of an object-oriented system model. The creation of this system model facilitates data presentation by providing a mechanism from which information can be extracted by automated manipulation of model content. Existing MBSE tools enable model creation, but are often too complex for the unfamiliar model viewer to easily use. These tools do not yet provide many opportunities for easing into the development and use of a system model when system design documentation already exists. This study creates a Systems Modeling Language (SysML) Document Traceability Framework (SDTF) for integrating design documentation with a system model, and develops an Interactive Visualization Engine for SysML Tools (InVEST), that exports consistent, clear, and concise views of SysML model data. These exported views are each meaningful to a variety of project stakeholders with differing subjects of concern and depth of technical involvement. InVEST allows a model user to generate multiple views and reports from a MBSE model, including wiki pages and interactive visualizations of data. System data can also be filtered to present only the information relevant to the particular stakeholder, resulting in a view that is both consistent with the larger system model and other model views. Viewing the relationships between system artifacts and documentation, and filtering through data to see specialized views improves the value of the system as a whole, as data becomes information

relational databases↗

Use of TV in space science activities - Some considerations

Advantages in the use of TV on board satellites as the primary data-recording system in a manned space laboratory when certain types of experiments are flown are indicated. Real-time or near-real-time validation, elimination of film weight, improved depth of field and low-light sensitivity, and better adaptability to computer and electronic processing of data are spelled out as advantages of TV over photographic techniques, say, in fluid dynamics experiments, and weightlessness studies.

Bannister, T. C.↗

Seismic velocity structure of the lunar mantle

The recently completed set of seismic arrival times from the Apollo lunar seismic network are inverted to estimate the average seismic velocities in three sections of the lunar mantle: two for the upper mantle and one for the middle mantle. The method used is a variation of the linearized least squares inversion where the inversion is accomplished in steps. The estimated average velocities in the upper mantle decrease from Vp = 7.74 km/sec and Vs = 4.49 km/sec in the section above 270-km depth to Vp = 7.46 km/sec and Vs = 4.25 km/sec in the section between 270- and 500-km depth, confirming the earlier finding of negative gradients based on seismic amplitude variations. The average velocities in the middle mantle between the depths of 500 km and 1000 km of Vp = 8.26 km/sec and Vs = 4.65 km/sec are significantly higher than those in the upper mantle, contradicting earlier estimates based on more limited data. The higher velocities may suggest initial melting of the moon down to at least 1000-km depth.

Nakamura, Y.↗

Analysis of Pitting Corrosion on Wrought and Additively Manufactured 316L Stainless Steel in Atmospheric Environments

Additive manufacturing of metal components enables rapid fabrication of complex geometries. However, metal additive manufacturing also introduces new morphological and microstructural characteristics which might be detrimental to component performance. Here we report the pitting corrosion properties of wrought and additively manufactured 316L stainless steel after atmospheric exposure to coastal environments and laboratory-created environments. Qualitative visualization in combination with quantitative analysis of resulting pits provided an in-depth understanding of pitting differences between wrought and additively manufactured 316L stainless steel and between coastal and laboratory-based exposure. Optical and scanning electron microscopy were utilized for visualization, while white light interferometry measured pits across approximately 5mm x 5mm areas on each sample. Post-processing of the interferometry data enables quantification of pitting attack for each sample in terms of both pit depth and pit volume. The pitting analysis introduced herein offers a new technique to compare pitting attack between different manufacturing processes and materials.

36 MATERIALS SCIENCE↗

Strategies for Improved CALIPSO Aerosol Optical Depth Estimates

In the spring of 2010, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) project will be releasing version 3 of its level 2 data products. In this paper we describe several changes to the algorithms and code that yield substantial improvements in CALIPSO's retrieval of aerosol optical depths (AOD). Among these are a retooled cloud-clearing procedure and a new approach to determining the base altitudes of aerosol layers in the planetary boundary layer (PBL). The results derived from these modifications are illustrated using case studies prepared using a late beta version of the level 2 version 3 processing code.

Vaughan, Mark A.↗

SMASH: Survey of the MAgellanic Stellar History

The Large and Small Magellanic Clouds are unique local laboratories for studying the formation and evolution of small galaxies in exquisite detail. The Survey of the MAgellanic Stellar History (SMASH) is an NOAO community Dark Energy Camera (DECam) survey of the Clouds mapping 480 deg{sup 2} (distributed over ∼2400 square degrees at ∼20% filling factor) to ∼24th mag in ugriz . The primary goals of SMASH are to identify low surface brightness stellar populations associated with the stellar halos and tidal debris of the Clouds, and to derive spatially resolved star formation histories. Here, we present a summary of the survey, its data reduction, and a description of the first public Data Release (DR1). The SMASH DECam data have been reduced with a combination of the NOAO Community Pipeline, the PHOTRED automated point-spread-function photometry pipeline, and custom calibration software. The astrometric precision is ∼15 mas and the accuracy is ∼2 mas with respect to the Gaia reference frame. The photometric precision is ∼0.5%–0.7% in griz and ∼1% in u with a calibration accuracy of ∼1.3% in all bands. The median 5 σ point source depths in ugriz are 23.9, 24.8, 24.5, 24.2, and 23.5 mag. The SMASH data have already been used to discover the Hydra II Milky Way satellite, the SMASH 1 old globular cluster likely associated with the LMC, and extended stellar populations around the LMC out to R ∼ 18.4 kpc. SMASH DR1 contains measurements of ∼100 million objects distributed in 61 fields. A prototype version of the NOAO Data Lab provides data access and exploration tools.

79 ASTRONOMY AND ASTROPHYSICS↗

Coherent structures in wind shear induced wave–turbulence–vegetation interaction in water bodies

Flume experiments with particle imaging velocimetry (PIV) were conducted recently to study a complex flow problem where wind shear acts on the surface of a static water body in presence of flexible emergent vegetation and induces a rich dynamics of wave–turbulence–vegetation interaction inside the water body without any gravitational gradient. The experiments were aimed at mimicking realistic vegetated wetlands and the present work is targeted to improve the understanding of the coherent structures associated with this interaction by employing a combination of techniques such as quadrant analysis, proper orthogonal decomposition (POD), Shannon entropy and mutual information content (MIC). The turbulent transfer of momentum is found to be dominated by organized motions such as sweeps and ejections, while the wave component of vertical momentum transport does not show any such preference. Furthermore, by reducing the data using POD we see that wave energy for large flow depths and turbulent energy for all water depths is concentrated among the top few modes, which can allow development of simple reduced order models. Vegetation flexibility is found to induce several roll type structures, however if the vegetation density is increased, drag effects dominate over flexibility and organize the flow. The interaction between waves and turbulence is also found to be highest among flexible sparse vegetation. But, rapidly evolving parts of the flow such as the air–water interface reduces wave–turbulence interaction.

54 ENVIRONMENTAL SCIENCES↗

Characterization of a minor actinides bearing metallic fuel pin irradiated in EBR-II

The X501 transmutation experiment irradiated in Experimental Breeder Reactor II (EBR-II) was intended to evaluate the safety and performance of the addition of minor actinides (Am, Np) into the metallic nuclear fuel system. The irradiation of this experiment is also of paramount importance for comparisons between true fast spectrum irradiations (e.g. EBR-II) and shrouded irradiation capsules performed at the thermal neutron spectrum Idaho National Laboratory Advanced Test Reactor. The X501 experimental fuel pins were irradiated to a peak measured burnup of 6.2% fission per initial heavy metal atom. This paper reports and discusses Postirradiation Examination results for one of two minor actinide bearing pins from the EBR-II X-501 experiment (X501-G591) with a focus on fuel microstructure evolution. Additionally, fuel swelling, fission product distribution, cladding strain, fission gas release, fuel microstructure and fuel cladding chemical interaction were all evaluated. The fission gas release was 79.9% and the microstructure along the fuel pin presented several characteristics very similar to other EBR-II U-Pu-Zr ternary metallic fuel experience. Minor actinides seem to not dramatically affect the overall performance of this candidate transmutation fuel. Scanning Electron Microscopy was also performed and an in-depth characterization of the different regions and phases is presented. Performance data from these irradiations can be used to inform the feasibility of minor actinide transmutation in future reactor systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Indentation investigation of 304L stainless steel friction stir weld simulated crack repair

Simulated cracks were repaired in 304L stainless steel using low temperature friction stir welding. Indentation studies were carried out to understand the effect of microstructural features on the mechanical property variation across the weld and to measure the size of the weld zones with a quantitative technique. Microhardness and nanoindentation hardness profiles were constructed on a transverse section across the weld. The data obtained were correlated by extrapolating the nanoindentation hardness to greater depths which showed that the nanoindentation hardness closely reflects the microhardness values throughout the weld. Finally, grain size in the stir zone (SZ) was found to vary with the tool temperature which, in turn, alters the nanoindentation modulus variability and higher tool temperature resulted in widening of the SZ.

36 MATERIALS SCIENCE↗

Why Firn Quakes

Snow dampens sounds, but anecdotal reports concisely describe audible propagating collapse events—firnquakes—in Antarctic and Arctic snowfields. We propose combining granular and continuum mechanics to form a testable theory for conditioning, triggering, and propagation of firnquakes consistent with scarce data. A central condition for collapse events is unconsolidated firn at depth. As firn grains compact, stresses are transmitted along force chains which carry the overburden and transition into a continuous medium by pressure sintering. This granular legacy creates solid-like supports of denser layers that keep the material below unconsolidated. Dynamic amplification triggers local brittle failure of the supports, which induces a cascade of collapse propagation. Using bulk density from ice cores as proxy for stiffness, we find the flexural wave speed by collapsing supports matches the recorded firnquake velocities on the order of 100 m/s. Our theory is to be tested in firn sheets and other compacting granular materials.

Voigtländer, A. [Lawrence Berkeley National Labora↗

Time and space resolved current density mapping in three dimensions using magnetic field probe array in a high voltage coaxial gap

We present an experimental analysis of the symmetry of current density in a coaxial geometry, diagnosed using a magnetic field probe array and calculations of the Fowler-Nordheim enhancement factor. Data were collected on the coaxial gap breakdown device (240 A, 25 kV, 150 ns, ~0.1 Hz), and data from experiments using 2 different gap sizes and different penetration depths are compared over runs comprising 50 shots for each case. The magnetic field probe array quantifies the distribution of current density at three axial locations, on either sides of a vacuum breakdown, and tracks the evolution with time and space. The results show asymmetries in current density, which can be influenced by changes in the gap size and the penetration depth (of the center electrode into the outer electrode). For smaller gap sizes (400 μm), symmetric current profiles were not observed, and the change in the penetration depth changes both the symmetric behavior of the current density and the enhancement factor. For larger gaps (900 μm), current densities were typically more uniform and less influenced by the penetration depth, which is reflected in the enhancement factor values. Furthermore it is possible that the change in inductance caused by the localization of current densities plays a role in the observed behavior.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗