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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps

Abstract An accurate characterization of the water content of snowpack, or snow water equivalent (SWE), is necessary to quantify water availability and constrain hydrologic and land surface models. Recently, airborne observations (e.g., lidar) have emerged as a promising method to accurately quantify SWE at high resolutions (scales of ∼100 m and finer). However, the frequency of these observations is very low, typically once or twice per season in the Rocky Mountains of Colorado. Here, we present a machine learning framework that is based on random forests to model temporally sparse lidar-derived SWE, enabling estimation of SWE at unmapped time points. We approximated the physical processes governing snow accumulation and melt as well as snow characteristics by obtaining 15 different variables from gridded estimates of precipitation, temperature, surface reflectance, elevation, and canopy. Results showed that, in the Rocky Mountains of Colorado, our framework is capable of modeling SWE with a higher accuracy when compared with estimates generated by the Snow Data Assimilation System (SNODAS). The mean value of the coefficient of determination R 2 using our approach was 0.57, and the root-mean-square error (RMSE) was 13 cm, which was a significant improvement over SNODAS (mean R 2 = 0.13; RMSE = 20 cm). We explored the relative importance of the input variables and observed that, at the spatial resolution of 800 m, meteorological variables are more important drivers of predictive accuracy than surface variables that characterize the properties of snow on the ground. This research provides a framework to expand the applicability of lidar-derived SWE to unmapped time points. Significance Statement Snowpack is the main source of freshwater for close to 2 billion people globally and needs to be estimated accurately. Mountainous snowpack is highly variable and is challenging to quantify. Recently, lidar technology has been employed to observe snow in great detail, but it is costly and can only be used sparingly. To counter that, we use machine learning to estimate snowpack when lidar data are not available. We approximate the processes that govern snowpack by incorporating meteorological and satellite data. We found that variables associated with precipitation and temperature have more predictive power than variables that characterize snowpack properties. Our work helps to improve snowpack estimation, which is critical for sustainable management of water resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Advances in Resin Management Using 3R-Scan - 20154

The most important factor underlying optimal waste management is developing a clear picture of the radioactivity content of the waste and its impact on waste disposal cost. For over 35 years since the publishing of 10CFR61, waste characterization has relied on sampling the final waste product after formation. In the days following 10CFR61, the cost of final disposal was marginal with only a small impact on the overall costs. Constraints were added by provisions of the Low Level Waste Policy Act of 1985 leading to increasingly limited access to those disposal sites that remained available. In addition, Nuclear Regulatory Commission (NRC) pressure promoting waste volume reduction led to disposal costs inevitably rising. Despite this, characterization practices in monitoring of waste generation for activity content still center on the same dated processes. This results in a disposal classification on the basis of endpoint sampling without consideration of the homogeneity of the waste mixture. It can also disregard consideration of the representativeness of the single or small sample base. As a minimum effort, a formalized sampling program of a fixed grouping of waste streams can be implemented that could account for more than 95% of all of the activity carried in solid waste products. The sample results for each radionuclide could then be trended as time passes to develop reasonable scaling factors for difficult to measure radionuclides. This process, identified in NRC guidance, has been rigorously followed by a relatively small number of facilities. The trended scaling factors serve to improve accuracy by identifying anomalous results that could otherwise go undetected. Direct monitoring of the accumulation of activity in process streams generating solid radwaste, including demineralizers and filter streams, is a more precise approach. Nearly all of these streams are monitored by plant chemistry on a regular schedule to maintain water quality. This paper discusses viable options for developing the basis for characterization through process monitoring of the accumulation of activity at the point of generation. Special focus is on resin bed tracking and how process knowledge of these streams can be brought together to form a consistent and precise solid waste radioactivity inventory. Some of the specific points covered in this paper include the merger of the fission product release computer program, 3R-STAT, with the radwaste sample analysis computer program, SCAN4 to create 3R-SCAN, the importance of individual waste stream influences on the overall source term, and the use of historic sample data to develop scaling factors using an automated process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Exploring innovative pathway for SRF cavity fabrication

This article shows a study on an alternative pathway for the fabrication of a complete 1.3 GHz SRF cavity, aiming at improving production reliability, reducing the use of chemical polishing (EP or BCP) which is a costly and safety-critical step, and preserving surface quality after forming. Unlike the conventional pathway, the fabrication process is performed after polishing. This point is crucial as the used polishing technology could be applied only to flat geometries. The performed investigation demonstrates that damages during the fabrication process are considered minor, localized, and limited to the near-surface. Moreover, these studies confirm that the damaged layer (100-200 µm) is mainly caused by the rolling process, and not by the subsequent fabrication steps. A laser confocal microscope and SEM-EBSD technique were used to compare samples before and after forming. The preliminary results are discussed and presented in this paper.

Hryhorenko, O.↗
DOE OSTI2023

Exploring innovative pathway for SRF cavity fabrication

This article shows a study on an alternative pathway for the fabrication of a complete 1.3 GHz SRF cavity, aiming at improving production reliability, reducing the use of chemical polishing (EP or BCP) which is a costly and safety-critical step, and preserving surface quality after forming. Unlike the conventional pathway, the fabrication process is performed after polishing. This point is crucial as the used polishing technology could be applied only to flat geometries. The performed investigation demonstrates that damages during the fabrication process are considered minor, localized, and limited to the near-surface. Moreover, these studies confirm that the damaged layer (100-200 µm) is mainly caused by the rolling process, and not by the subsequent fabrication steps. A laser confocal microscope and SEM-EBSD technique were used to compare samples before and after forming. The preliminary results are discussed and presented in this paper.

Hryhorenko, O.↗
DOE OSTI2023

Applying the core-satellite species concept: Characteristics of rare and common riverine dissolved organic matter

Introduction: Dissolved organic matter (DOM) composition varies over space and time, with a multitude of factors driving the presence or absence of each compound found in the complex DOM mixture. Compounds ubiquitously present across a wide range of river systems (hereafter termed core compounds) may differ in chemical composition and reactivity from compounds present in only a few settings (hereafter termed satellite compounds). Here, we investigated the spatial patterns in DOM molecular formulae presence (occupancy) in surface water and sediments across 97 river corridors at a continental scale using the “Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems—WHONDRS” research consortium. Methods: We used a novel data-driven approach to identify core and satellite compounds and compared their molecular properties identified with Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Results: In this work, we found that core compounds clustered around intermediate hydrogen/carbon and oxygen/carbon ratios across both sediment and surface water samples, whereas the satellite compounds varied widely in their elemental composition. Within surface water samples, core compounds were dominated by lignin-like formulae, whereas protein-like formulae dominated the core pool in sediment samples. In contrast, satellite molecular formulae were more evenly distributed between compound classes in both sediment and water molecules. Core compounds found in both sediment and water exhibited lower molecular mass, lower oxidation state, and a higher degree of aromaticity, and were inferred to be more persistent than global satellite compounds. Higher putative biochemical transformations were found in core than satellite compounds, suggesting that the core pool was more processed. Discussion: The observed differences in chemical properties of core and satellite compounds point to potential differences in their sources and contribution to DOM processing in river corridors. Overall, our work points to the potential of data-driven approaches separating rare and common compounds to reduce some of the complexity inherent in studying riverine DOM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Distinct Melt Infusion Architectures of Antiperovskite Solid Electrolytes

Antiperovskite solid electrolytes are an emerging class of lithium‐ion conductors distinguished by their unusually low melting points, enabling scalable, low‐temperature processing routes not accessible to most solid electrolytes. In this work, we synthesize phase‐pure chloride (Cl), bromide (Br), and mixed halide (ClBr) variants of antiperovskites and investigate their ionic conductivities in both powder and hot‐pressed forms. Hot pressing significantly enhances conductivity across all compositions, while energy‐dispersive X‐ray spectroscopy (EDS) of the mixed halide system reveals halide surface migration during densification. We further investigate the melt‐infiltration behavior of these electrolytes into substrates relevant to solid‐state battery architectures, including Al and Cu current collectors, conventional NMC and LFP cathodes, and a foamed NMC cathode with a highly porous architecture. The foamed cathode enables deep and uniform electrolyte penetration, highlighting the role of electrode architecture in facilitating melt infiltration. Across all substrates, electrolyte halide chemistry strongly influences wetting behavior, penetration depth, and resulting microstructural morphology. Together, these results establish clear processing–structure relationships for melt‐infiltrated antiperovskite solid electrolytes and demonstrate how electrolyte chemistry and electrode architecture govern interfacial morphology during integration, providing practical guidelines for processing and structural design in solid‐state battery systems.

antiperovskite↗
DOE OSTI2021

Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems

Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems (GNSS/INS) together with cameras and/or LiDAR sensors are being widely used for topographic mapping in a variety of applications such as precision agriculture, coastal monitoring, and archaeological documentation. Integration of image-based and LiDAR point clouds can provide a comprehensive 3D model of the area of interest. For such integration, ensuring a good alignment between data from the different sources is critical. Although many works have been conducted on this topic, there is still a need for a rigorous integration approach that minimizes the discrepancy between camera and LiDAR data caused by inaccurate system calibration parameters and/or trajectory artifacts. This study proposes an automated tightly-coupled camera/LiDAR integration workflow for GNSS/INS-assisted UAV systems. The proposed strategy is conducted in three main steps. First, an image-based point cloud is generated using a LiDAR/GNSS/INS-assisted structure from motion (SfM) strategy. Then, feature correspondences between image-based and LiDAR point clouds are automatically identified. Finally, an integrated-bundle adjustment procedure including image points, LiDAR raw measurements, and GNSS/INS information is conducted to minimize the discrepancy between point clouds from different sensors while estimating system calibration parameters and refining the trajectory information. The proposed SfM strategy and integration framework are evaluated using five datasets. The SfM results show that using LiDAR data can facilitate feature matching and further increase the number of reconstructed 3D points. The experimental results also illustrate that the developed automated camera/LiDAR integration strategy is capable of accurately estimating system calibration parameters to achieve good alignment among camera/LiDAR data from single/multiple systems. Finally, an absolute accuracy in the range of 3–5 cm is achieved for the image/LiDAR point clouds after the integration process.

42 ENGINEERING↗
DOE OSTI2025

Hybrid Bismuth Halide with Rich Polymorphism and Second Harmonic Generation Response

Hybrid structures have emerged as a promising class of optical materials, due to their ability to couple the robustness of inorganic and the tunability of organic compounds. However, their application in nonlinear optics (NLO) remains limited, largely due to underexplored factors that drive the formation of noncentrosymmetric structures and NLO property characterization. In this work, we explore the formation, structural and temperature polymorphism, and optical properties of the (Et 3 NH) 3 Bi 2 Br 9 composition, which crystallizes as either noncentrosymmetric or centrosymmetric polymorph. Structural analysis showed that the alignment of [Bi 2 Br 9 ] 3– units dictates the symmetry of phases, as well as the nonlinear optical properties, with the triclinic polymorph exhibiting a second harmonic generation (SHG) response both in visible and IR regions (1.29 × KH 2 PO 4 and 0.08 × AgGaS 2 ). Thermal analysis reveals polymorphic phase transitions and low melting points, making them melt-processable and ionic liquid candidates.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Initial operation and data processing on a system for real-time evaluation of Thomson scattering signals on the Large Helical Device

A scalable system for real-time analysis of electron temperature and density based on signals from the Thomson scattering diagnostic, initially developed for and installed on the NSTX-U experiment, was recently adapted for the Large Helical Device and operated for the first time during plasma discharges. During its initial operation run, it routinely recorded and processed signals for four spatial points at the laser repetition rate of 30 Hz, well within the system’s rated capability for 60 Hz. We present examples of data collected from this initial run and describe subsequent adaptations to the analysis code to improve the fidelity of the temperature calculations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Low-temperature gas-phase formation of cyclopentadiene and its role in the formation of aromatics in the interstellar medium

The cyclopentadiene (C 5 H 6 ) molecule has emerged as a molecular building block of nonplanar polycyclic aromatic hydrocarbons (PAHs) and carbonaceous nanostructures such as corannulene (C 20 H 10 ), nanobowls (C 40 H 10 ), and fullerenes (C 60 ) in deep space. However, the underlying elementary gas-phase processes synthesizing cyclopentadiene from acyclic hydrocarbon precursors have remained elusive. Here, by merging crossed molecular beam experiments with rate coefficient calculations and comprehensive astrochemical modeling, we afford persuasive testimony on an unconventional low-temperature cyclization pathway to cyclopentadiene from acyclic precursors through the reaction of the simplest diatomic organic radical—methylidyne (CH)—with 1,3-butadiene (C 4 H 6 ) representing main route to cyclopentadiene observed in TaurusMolecular Cloud. This facile route provides potential solution for the incorporation of the cyclopentadiene moiety in complex aromatic systems via bottom–up molecular mass growth processes and offers an entry point to the low-temperature chemistry in deep space leading eventually to nonplanar PAHs in our carbonaceous Universe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Random Forest Prediction of Crystal Structure from Electron Diffraction Patterns

Transmission electron microscopy (TEM) diffraction patterns are regularly used to determine the structure of crystalline materials. Electron diffraction is the most common method to solve for unknown or partially known crystal structures, as it provides direct and interpretable feedback on the orientation of crystal grains under the beam [1]. However, it remains a challenge to determine the crystal structure of a new material or even a new phase of an existing material. Analysis of such materials commonly requires manual exploration and comparison with simulated diffraction patterns. This is often a time consuming process with no obvious start point when many similar structures are possible, and this method cannot be used to determine crystal structure or orientation from structures not included in the diffraction libraries. Therefore, we have developed a machine learning model to determine the crystal structure of a material from its electron diffraction pattern.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Abundance analysis of APOGEE spectra for 58 metal-poor stars from the bulge spheroid

The central part of the Galaxy hosts a multitude of stellar populations, including the spheroidal bulge stars, stars moved to the bulge through secular evolution of the bar, inner halo, inner thick disc, inner thin disc, as well as debris from past accretion events. We identified a sample of 58 candidate stars belonging to the stellar population of the spheroidal bulge, and analyse their abundances. The present calculations of Mg, Ca, and Si lines are in agreement with the ASPCAP abundances, whereas abundances of C, N, O, and Ce are re-examined. We find normal α-element enhancements in oxygen, similar to magnesium, Si, and Ca abundances, which are typical of other bulge stars surveyed in the optical in Baade’s Window. The enhancement of [O/Fe] in these stars suggests that they do not belong to accreted debris. No spread in N abundances is found, and none of the sample stars is N-rich, indicating that these stars are not second generation stars originated in globular clusters. Ce instead is enhanced in the sample stars, which points to an s-process origin such as due to enrichment from early generations of massive fast rotating stars, the so-called spinstars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Online learning of quadratic manifolds from streaming data for nonlinear dimensionality reduction and nonlinear model reduction

Here, this work introduces an online greedy method for constructing quadratic manifolds from streaming data, designed to enable in situ analysis of numerical simulation data on the Petabyte scale. Unlike traditional batch methods, which require all data to be available upfront and take multiple passes over the data, the proposed online greedy method incrementally updates quadratic manifolds in one pass as data points are received, eliminating the need for expensive disk input/output operations as well as storing and loading data points once they have been processed. A range of numerical examples demonstrate that the online greedy method learns accurate quadratic manifold embeddings while being capable of processing data that far exceed common disk input/output capabilities and volumes as well as main-memory sizes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Initial operation and data processing on a system for real-time evaluation of Thomson scattering signals on the Large Helical Device

A scalable system for real-time analysis of electron temperature and density based on signals from the Thomson scattering diagnostic, initially developed for and installed on the NSTX-U experiment, was recently adapted for the Large Helical Device (LHD) and operated for the first time during plasma discharges. During its initial operation run, it routinely recorded and processed signals for four spatial points at the laser repetition rate of 30 Hz, well within the system's rated capability for 60 Hz. We present examples of data collected from this initial run and describe subsequent adaptations to the analysis code to improve the fidelity of the temperature calculations.

Thomson scattering, real-time, LHD, plasma diagnos↗
DOE OSTI2020

Characterization Report for the MP-1 Experiment Fabrication Campaign

This report covers the results of MP 1 fuel characterization analysis to provide a detailed understanding of the as-fabricated fuel that would be irradiated in the MP 1 (Mini-Plate 1) experiment. The work was performed at Pacific Northwest National Laboratory (PNNL), Idaho National Laboratory (INL), and Los Alamos National Laboratory (LANL). Characterization of the as-fabricated fuel was performed in accordance with Characterization Plan for the Fabrication of U 10Mo for the MP 1 Experiment, hereinafter the MP 1 Characterization Plan (MAQP 2016). Under the MP 1 Characterization Plan, fuel foils at different points in the foil fabrication process (e.g., hot rolled annealed, cold rolled annealed) were studied to understand the effect of various thermomechanical processes on the fuel microstructure. Samples were sent to each of the three organizations so that testing and analysis could be performed independently using similar equipment and a standardized set of measurement and analysis procedures. The MP 1 experiment will provide an opportunity to understand the effects of processing conditions on the final fuel microstructure, to compare independently obtained results, and achieve a three-way validation. PNNL characterized 28 uranium–10 wt% molybdenum (U 10Mo) samples. Six pieces/specimens from each sample/foil were sectioned, in accordance with the MP 1 Characterization Plan. Similarly, INL and LANL also examined 24 and 17 U 10Mo specimens, respectively. These total 69 samples consist of six types of MP 1 characterization foils fabricated by Babcock and Wilcox Technologies (BWXT) from ingots produced by the Y-12 National Security Complex: • 0.047 in.-thick hot-rolled and annealed samples with and without Zr layers • 0.02 in.-thick cold-rolled and annealed samples with and without Zr layers • 0.01 in.-thick cold-rolled and annealed samples with and without Zr layers. Microstructure, chemical composition, carbide morphology, U 10Mo foil thickness, Zr thickness, mechanical properties (microhardness), and density were evaluated in both longitudinal and transverse directions for foils of the three different thicknesses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Size and Time-Resolved Automated Aerosol Sampling Field Campaign Report

To improve the understanding of the impacts of the vertical distribution of aerosol chemical composition on radiative forcing of aerosol, we performed a detailed physicochemical characterization of aerosol particles sampled during ARM deployment of the tethered balloon system at two ARM sites. We used multi-modal microscopy/spectroscopy techniques and advanced mass spectrometry platforms for the analysis of particles. We found variations in size-resolved aerosol composition at different altitudes. We also observed changes in aerosol composition during different seasons. Some of our observations at ARM’s Oliktok Point, Alaska site suggest cloud processing of aerosol while sampling in clouds, below clouds, and above clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Offshore Wind Energy Basics: Navigating Offshore Wind Energy Decision-Making Processes [Slides]

This webinar will provide a high-level summary of decision-making processes for siting and permitting, with a focus on the points at which local stakeholders can meaningfully engage in these processes. It will differentiate itself from other offshore wind webinars by presenting information relevant to a national audience (i.e., it will not be state specific) that helps stakeholders to "connect the dots" across agencies and processes. It will provide neutral, fact-based information from NREL staff, as well as from relevant staff at the federal, state, and local levels. This webinar will provide a helpful foundation for webinar #3 in this series, which will highlight opportunities for community engagement in the offshore wind development process more broadly, including but not limited to the regulatory processes covered in this webinar.

17 WIND ENERGY↗
DOE OSTI2023

Deciphering Fingerprints of Stellar Nucleosynthesis Through Nuclear Reaction Rate Measurements and Isotopic Analyses of Stardust

Microscopic stardust grains, found in trace amounts in primitive meteorites, afford a unique opportunity to study stellar nucleosynthesis in the laboratory by measuring their heavy element isotopic compositions. Applying LLNL’s state-of-the art material characterization capabilities to these micrometer-sized grains yields large new datasets with unprecedented precision. However, the astrophysical models necessary to interpret the isotopic record require improved nuclear physics data to constrain stellar nucleosynthesis conditions. For example, the branch point in the s-process path at 95 Zr controls the relative amounts of heavier nuclides but is poorly understood. We conducted a coordinated effort across disciplines to combine a new determination of the neutron capture cross section of 95 Zr with the laboratory analysis of hundreds of stardust grains to yield a view into stellar interiors. We developed new methods to quantify multiple isotopic systems simultaneously (e.g., Zr, Ba, and W) in stardust grains and improved the determination of the neutron capture cross section of unstable 95 Zr via the surrogate reaction method. This interdisciplinary approach is allowing us to fill gaps in our understanding of the environments in which elements are produced while enhancing LLNL’s experimental and theoretical capabilities relevant to nuclear threat reduction missions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗