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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Enhancing the efficiency of time-dependent density functional theory calculations of dynamic response properties

X-ray Thomson scattering (XRTS) constitutes an essential technique for diagnosing material properties under extreme conditions, such as high pressures and intense laser heating. Time-dependent density functional theory (TDDFT) is one of the most accurate available ab initio methods for modeling XRTS spectra, as well as a host of other dynamic material properties. However, strong thermal excitations, along with the need to account for variations in temperature and density as well as the finite size of the detector significantly increase the computational cost of TDDFT simulations compared to ambient conditions. In this work, we present a broadly applicable method for optimizing and enhancing the efficiency of TDDFT calculations. Our approach is based on a one-to-one mapping between the dynamic structure factor and the imaginary time density–density correlation function, which naturally emerges in Feynman’s path integral formulation of quantum many-body theory. Specifically, we combine rigorous convergence tests in the imaginary time domain with a constraints-based attenuation of narrow-band fluctuations to improve the efficiency of TDDFT modeling without the introduction of any significant bias. As a result, we can report a speed-up by up to an order of magnitude, thus substantially reducing the burden of computational cost required for XRTS analysis.

Moldabekov, Zhandos A. [Helmholtz-Zentrum Dresden-↗
DOE OSTI2024

Mapping the Microstructure During the Historic U-Mo Monolithic Fuel Foil Fabrication Process

Since 2004, there has been extensive effort towards the development of a uranium molybdenum monolithic fuel system to convert high performance research and test reactors. The RERTR-6 experiment was the first to attempt a monolithic fuel instead of a dispersed fuel form. The fabrication methods evolved overtime and provided the basis for current fabrication methods. The various steps in the process inevitably tailor the fuel alloy microstructure which is known to influence irradiation behavior. This document aims to present and discuss the fabrication evolution that transpired through a recounting of historical data from the various fabrication campaigns. By overlaying this data with basic science studies on the U-Mo that explored transformation kinetics, it is possible to estimate a measure of the impact heat treatments have on the final as-fabricated microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Sedimentary Geothermal Resources in Nevada, Utah, Colorado, and Texas

The objectives of this project were to (1) perform a literature review of sedimentary geothermal resources, (2) identify data sources and develop data-collection methodologies that characterize selected resources, (3) screen sedimentary basins and formations for sedimentary geothermal potential, and (4) evaluate the technical feasibility of one or more selected locations. Numerous publications have characterized geothermal resources within sedimentary basins. A literature search reviewed publications describing resources located in Colorado, Louisiana, Nevada, Texas, Utah, and Wyoming. The most attractive resources have high temperature gradients, low drilling costs, and reservoir permeabilities greater than 10 millidarcies (mD). Prospects in Colorado, Nevada, Texas, and Utah exhibit attractive characteristics and were chosen for further analysis. Sedimentary resources in Nevada and Utah are most attractive, followed by tested resources in Texas and untested resources in Colorado. The identified resources in Wyoming and Louisiana had lower geothermal gradients and were not evaluated. Reservoir modeling and techno-economic analysis were performed at Marys River Basin–North in Nevada. Geothermal energy production at this location is expected to have a levelized cost of energy (LCOE) ranging between 10 and 20 cents/kWh. Additional work may result in lower LCOE estimates at this location and at other attractive prospects in these three regions. The Great Basin carbonate and alluvial aquifer system of eastern Nevada and western Utah includes a lower carbonate aquifer unit, which has the potential for hosting both conduction- and convection-dominated geothermal systems. Mapping has identified lateral thickness variability expressed as a roughly 120–150-km-wide central corridor, which hosts the thickest and most continuous formations and extends from near Las Vegas north to the Idaho border. Purchase and analysis of privately held legacy seismic data could potentially compensate for the lack of sufficient data documenting measured depth to the lower carbonate aquifer unit. Multiple orogenies, extension episodes, and intrusive events have deformed and displaced the target formations of the lower carbonate aquifer unit. This structural complexity and potential for dipping reservoirs emphasizes the need for detailed geological, geophysical, and reservoir modeling. Heat flow within three Colorado sedimentary basins reviewed as part of this study was calculated in targeted studies by the Colorado Geologic Survey and Colorado School of Mines. These calculations are based on bottom-hole temperature data sets with significant limitations and some variability but produce values consistently higher than the global continental average of 65 mW/m2 for all three basins. Heat flow in the Raton Basin is the highest; however, permeability measurements from specific sedimentary formations with high heat flow have not been obtained. Promising formations for sedimentary geothermal systems were found in all three regions studied—Nevada-Utah, Colorado, and Texas. The next steps for developing sedimentary geothermal resources vary due to differences in available data and resource uncertainties. Additional scopes of work are recommended for identified basins in these three regions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

PPPL Report on Reduced Modeling of Fusion Alpha Transport in ARC Burning Plasmas

We are reporting on the modeling of fusion alpha particle transport in the planned ARC fusion device being designed by the CFS (Commonwealth Fusion Systems: https://cfs.energy). The ARC tokamak is designed to operate in a burning-plasma regime characterized by a substantial population of fusion-born alpha particles. Alfvén eigenmode (AE) stability is assessed both analytically and numerically, incorporating alpha-particle drive, ion Landau, and radiative damping from thermal species and collisional damping from trapped electrons. Regions of unstable and near-threshold AE activity are mapped across ARC’s operational parameter space. Linear stability analysis with NOVA indicates multiple, often marginally unstable AEs, extending to toroidal mode numbers up to n= 30. The present report focuses on the ARC flat-top operating point prior to the sawtooth event. Alpha-particle transport on timescales exceeding the neoclassical slowing-down time is assessed using the NUBEAM module [1][2] of the TRANSP code [3], employing transport coefficients derived from the RBQ quasilinear modeling (cf. Appendix B). These global simulations identify favorable and unfavorable operating regimes with respect to alpha confinement, pressure redistribution, and overall alpha-heating efficiency. We also evaluate additional transport mechanisms—including neoclassical tearing mode (TM)–induced stochasticity, sawtooth-driven redistribution, and toroidal-field ripple using the kick model (cf. Appendix C) which makes use of the guiding-center code ORBIT, see Section 5. The kick model is integrated into TRANSP to enable self-consistent predictions of alpha-driven current formation and sustainment within the ARC scenario. Sensitivity scans are performed over the mode frequency, rational-surface alignment, island width, mode amplitude, and proximity of the limiter to the plasma. Our study provides an initial, physics-based guidance for machine design, operational planning, and equilibrium control, ensuring adequate alpha confinement and robust self-heating performance in ARC. Our simulations mostly targeted worst case scenarios, e.g. for TMs and sawteeth. Overall, we expect benign effects for the ARC scenario investigated in this work on fusion alpha confinement and losses in the presence of AEs, tearing modes and sawteeth. This report addresses three thrusts identified at the outset. The first thrust focuses on analytic estimates of the parametric dependencies of EP relaxation based on local AE stability simulations (Section 3). The second thrust involves global evaluations of AE stability using the NOVA, RBQ, and NUBEAM codes (Section 4). Finally, we investigate alpha-particle transport driven by low-frequency instabilities associated with sawteeth and tearing modes (Section 5).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

In-Situ Spatial Mapping of Hydrogen in Yttrium Hydrides at LANSCE

This report summarizes the neutron imaging techniques and experimental activities performed at the Los Alamos Neutron Science Center (LANSCE) with the main goal of measuring temperature driven hydrogen diffusion within bulk-yttrium hydride (YH x ) materials. The experimental results and technique developments reported herein support the US Department of Energy Office of Nuclear Energy’s (DOE-NE) Microreactor Program under Technology Maturation. In particular, the critical need to experimentally validate and verify hydrogen-diffusion models of metal hydrides used in hightemperature microreactor designs is addressed by means of high-spatial-resolution neutron imaging coupled with custom-built and application-specific furnaces. These capabilities were designed to apply large temperature gradients across centimeter-sized YH x pellets to simulate conditions faced in the microreactor environment. Neutron imaging, combined with in-situ sample heating, enables near real-time tracking of hydrogen diffusion in YH x on the sub-millimeter scale. In this report, an overview of neutron imaging methodology and technologies are given in the context of recent spatial measures of hydrogen concentrations in similar metals hydrides. Additionally, the commissioning and operation of a custom-built compact dual-zone furnace is given along with details on the first two in-situ heating measurements of YH x performed over the 2020 and 2021 LANSCE operation cycles. In parallel with in-situ heating measurements, neutron computed tomography scans were performed to visualize hydrogen aggregates in post-heated YH x samples. Analysis and results from these neutron imaging measurements are given along with outlooks and plans for improving future hydrogen diffusion measurements at LANSCE.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Demonstration of reconstruction-free static magnetic control of DIII-D plasma with deep reinforcement learning

This paper presents the development and experimental validation of a reinforcement learning (RL)-based magnetic controller on the DIII-D tokamak. The controller directly maps raw magnetic diagnostic signals to actuator commands, replacing the traditional isoflux control algorithm based on equilibrium reconstruction. Four RL controllers are trained using the Soft Actor–Critic algorithm with an asymmetric Actor–Critic architecture in the NSFsim simulator. All controllers are deployed in the DIII-D Plasma Control System and operated with a 4 kHz feedback loop. Two randomization strategies are evaluated during training: evolving kinetic profiles and fixed kinetic profiles within each episode. The latter approach is found to better capture experimental deviations in the current density profile and to provide overall improved control performance. Robust operation is demonstrated across heating power scans in both L- and H-mode plasmas, as well as during transient events such as L–H transitions and pellet injections. Control errors in plasma shape and radial position remained within 1.5–2.0 cm and 1 cm, respectively. A notable discrepancy was observed in the vertical X-point position, with errors of up to approximately 4 cm, attributed to the current density distribution mismatches between simulations and experiments.

DIII-D↗
DOE OSTI2020

Correlation of SWIR imaging with LPBF 304L stainless steel part properties

In the Laser Powder Bed Fusion (LPBF) process, the local thermal history can vary significantly over a part as the heat transfer characteristics and the laser scan path are geometry dependent. The variations introduce the potential for defects that lead to part failure, some of which are difficult to identify non-destructively with common ex-situ evaluation techniques. These defects include significant microstructural and mechanical property differences in the part interiors. In this paper, thermal features are extracted from in-situ Short-Wave Infrared (SWIR) imaging measurements to compile voxel based part representations and understand how the complexities in the thermal history affect part performance. The deviations in thermal features due to different laser processing parameters and complex scan pathing are explored. Empirical correlations are developed to map thermal features with the engineering properties (bulk yield strength, area percentage porosity, and local state) of 304L stainless steel parts manufactured by LPBF. Processing modes (insufficient melting and keyholing) are determined by mapping part property measurements with multiple thermal features. Generating the relationships between thermographic measurements and resulting SLM part properties lays the foundation for in-situ part qualification.

36 MATERIALS SCIENCE↗
DOE OSTI2021

HyPerPy (Hydrogen Extraction and Parabolic Trough Plant Performance Models using Python) [SWR-21-53]

The HyPerPy package consists of three scripts: 1) Model for Hydrogen Tracking in Parabolic Trough Power Plants, 2) Model for Receiver Performance, and 3) Model for Hydrogen Extraction Process. The power plant model (1) tracks hydrogen generation and transport within the circulating heat transfer fluid (HTF) of the power plant. This script is a transient, initial value simulation, in which the hydrogen concentration in the circulating HTF is 0 moles per cubic meter everywhere at time 0 seconds. Hydrogen concentration is calculated at discrete locations within the circulating HTF with 4-second time resolution. During each time step, the change in hydrogen concentration due to hydrogen generation and permeation is calculated for each location according to the local HTF temperature, vessel or piping properties, hydrogen concentration and partial pressure. This model predicts hourly hydrogen concentrations for typical operating days in the spring, summer, fall, and winter seasons. Data is used to create hourly mappings of hydrogen concentrations for a typical operating year. The receiver model (2) uses a 1-hour time step to estimate getter loading and annulus pressure. For each time step, the model uses HTF and ambient temperature data to estimate absorber tube, bellows, and getter temperatures for the time step. In addition, the model uses hourly HTF hydrogen concentrations that are generated by the power plant model (1), and annulus hydrogen pressure from the previous time step. With these data, the model calculates the moles of hydrogen permeating across the absorber tube and bellows during the time step. The net change in moles hydrogen is added or subtracted from the getter loading for the previous time step, and the hydrogen pressure is re-calculated based on getter loading and temperature. The model uses this algorithm to simulate hydrogen permeation and loading 24 hours per day, 365 days per year using seasonal temperature data. The model repeats these calculations for 25 years to create a mapping of receiver getter loading and annulus hydrogen pressure for four seasons of each year. The model for hydrogen extraction (3) estimates hydrogen extraction rates for a specific separation module configuration. The rate depends primarily on membrane area, vacuum pump performance, headspace gas flowrate to the membrane, and headspace gas hydrogen partial pressure. This model has two versions. The steady-state version predicts hydrogen extraction rates when the module is operating in separation mode. The dynamic version predicts hydrogen transfer through the membrane when the module is operating in sensor mode. The steady-state version is used with the plant model (1) to predict hydrogen partial pressures in the power plant when the extraction process is operating.

Glatzmaier, Gregory↗
DOE OSTI2025

On the Stability Analysis of Astrophysical Cooling Functions

To model the temperature evolution of optically thin astrophysical environments at MHD scales, radiative and collisional cooling rates are typically either pretabulated or fit into a functional form and then input into MHD codes as a radiative loss function. Thermal balance requires estimates of the analogous heating rates, which are harder to calculate, and due to uncertainties in the underlying dissipative heating processes these rates are often simply parameterized. The resulting net cooling function defines an equilibrium curve that varies with density and temperature. Such cooling functions can make the gas prone to thermal instability (TI), which will cause departures from equilibrium. There has been no systematic study of thermally unstable parameter space for nonequilibrium states. Motivated by our recent finding that there is a related linear instability, catastrophic cooling instability, that can dominate over TI, here we carry out such a study. We show that Balbus instability criteria for TI can be used to define a critical cooling rate, Λ c , that permits a nonequilibrium analysis of cooling functions through the mapping of TI zones. We furthermore illustrate how thermal conduction modifies the shape of TI zones. Upon applying a Λ c -based stability analysis to coronal loop simulations, we find that loops undergoing periodic episodes of coronal rain formation are linearly unstable to catastrophic cooling instability, while TI is stabilized by thermal conduction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

3D Printing of Inconel 718 with Enhanced Boron Composition as a Novel Solar Absorber Tube Material in the Concentrated Solar Power (CSP) System

The growing demands for elevated efficiency in the solar energy industry led researchers to focus on the development of functional solar absorber tube material in concentrated solar power (CSP) systems, when molten salts are adopted as the heat transfer fluid. In this study, the typical solar absorber tube material, Inconel 718, was enhanced with boron to achieve a higher solar absorptivity in the visible light spectrum. Combined with an additive manufacturing (AM) method, the boron composition exceeded the traditional manufacturing limit of 60 ppm without microstructural defects. The boron-enhanced Inconel 718 exhibited a high solar absorptivity of nearly 90 % while maintaining a high thermal cycle fatigue resistance after thermal cycling treatment between 550°C and 720°C. The boron composition was increased to the manufacturing failure point, and the effects of different boron compositions on mechanical properties, microstructure, and optical properties were studied. The provided microstructure-property map in this study delivers high potentials of functional AM-printed alloy material in CSP applications.

13 HYDRO ENERGY↗
DOE OSTI2025

Electron Energy-Loss Spectroscopy and Differential Phase Contrast Imaging with Active Decision in Multimodal Electron Microscopy: Isotopic detection at the atomic scale

Isotopic engineering provides a powerful route to control phonon behavior in crystalline solids, enabling fundamental studies of lattice dynamics and heat transport at the atomic scale. Here, we directly visualize isotope-dependent phonon propagation in epitaxial Cr 2 O 3 using aberration-corrected scanning transmission electron microscopy (STEM) combined with monochromated, high-energy-resolution electron energy-loss spectroscopy (EELS). Guided by ab initio phonon calculations, we demonstrate that optical phonon modes above 70 meV are predominantly oxygen-derived and exhibit measurable redshifts upon substitution of natural 16 O by enriched 18 O. Spatially resolved vibrational spectrum imaging reveals isotope-enriched tracer layers within Cr 2 O 3 thin films, correlating isotope concentration with phonon intensity variations and vibrational energy shifts. At the nanometer and atomic scales, vibrational EELS mapping uncovers coherent phonon propagation across isotopic interfaces, consistent with theoretical phonon density of states and dispersion relations. These results establish vibrational EELS as a quantitative probe for isotope-dependent phonon transport in materials, opening new possibilities for studying energy dissipation and lattice dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Presentation of gas-phase-reactant-accessible single-rhodium-atom catalysts for CO oxidation, via MOF confinement of an Anderson polyoxometalate

Geometric or electronic confinement of guests within nanoporous hosts holds promise for imparting catalytic functionality, including single-metal-atom catalytic functionality, to existing materials. When the nanoporous host is a metal–organic framework (MOF), single-metal-ion catalysts have typically been installed by grafting to an open site on an inorganic node, with the node effectively becoming the support for the catalyst. This approach, however, imposes compositional constraints, as the node not only needs to be receptive to grafting, but also must be capable of stabilizing the framework against solvent evacuation, chemical exposure, and heating. Here, we show that disk-like, Anderson polyoxometalate clusters (RhMo 6 O 24 n- and Mo 7 O 24 m- ; POMs) can be confined in pore-specific and orientation-specific fashion within the hierarchically porous, Zr(IV)-based MOF, NU1K. Self-limiting loading of one cluster per pore, and associated nano-confinement, serve to isolate each POM and prevent consolidation caused by sintering. Additionally, the oriented confinement serves to expose individual rhodium atoms to candidate gas-phase reactants, while enabling the rhodium atom to employ a well-defined oxy-molybdenum cluster, rather than a MOF node, as a support. Synchrotron-based difference-electron-density maps and differential pair-distribution-function analyses of scattered X-rays establish cluster siting and orientation and confirm isolation. Nanoconfined (i.e., MOF- and POM-confined) single-rhodium(III)-atoms are catalytically competent for an illustrative gas-phase reaction, CO oxidation by O 2 , with the MOF-isolated POM enormously outperforming nonporous, MOF-free, solid (NH 4 ) 3 [H 6 RhMo 6 O 24 ]·6H 2 O. This paper highlights the value of MOF-based nano-confinement and oriented isolation of planar POMs as a means of uniformly presenting and stabilizing potent single-metal-atom catalysts, in reactant-accessible form, on well-defined supports.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Hawai‘i National Marine Renewable Energy Center (HINMREC)

The Hawaii National Marine Renewable Energy Center (HINMREC) was established to facilitate the commercialization of wave energy converter (WEC) devices, and to accelerate development and testing of Ocean Thermal Energy Conversion (OTEC) technologies. Housed at the Hawaii Natural Energy Institute (HNEI) of the University of Hawaii (UH), this program started with execution of the contract between the US Department of Energy (DOE) and UH in March 2009, and activities ran through the end of the project in September 2019. The DOE tasked HINMREC with facilitating and accelerating the build-out of the Navy’s Wave Energy Test Site (WETS), the nation’s first grid-connected open water wave energy conversion test facility, located off Marine Corps Base Hawaii (MCBH) in Kaneohe, on the island of Oahu. WETS was expanded from an existing test berth at 30m water depth to include test berths at 60m and 80m water depths. In recognition of the high costs associated with at-sea testing and evaluation of WEC devices, it was deemed imperative that HINMREC seek ways to reduce costs to developers by providing key research support to these early-stage technologies. WETS and HINMREC’s support allowed development of wave energy technology by providing a testing infrastructure that allows technology developers to test, demonstrate and evaluate their WEC devices, and generate data in order to advance WEC designs toward commercial readiness. HINMREC’s roles have included support in the establishment of the full site, including of wave resource characterization and site survey, followed by the essential roles of independent WEC device power performance assessment and environmental monitoring in support of deployed pre-commercial WECs. This DOE-funded work transitioned effectively to continue Navy-funded tasks for OTEC development, and activities at WETS, now under Naval Facilities Engineering Command (NAVFAC) funding. A secondary objective in the establishment of HINMREC was to assist the private sector in moving OTEC systems beyond proof-of-concept to pre-commercialization, primarily focused on system and component engineering, and local and global investigations into the potential environmental impacts of OTEC systems. HINMREC was tasked with maintaining high-resolution models of ocean thermal resources and the potential sustainable power output of OTEC systems. Ongoing tests begun previously under Navy funding at the OTEC Heat Exchangers (HXs) Test Facility at the Natural Energy Laboratory of Hawaii Authority (NELHA), in Kona on Hawaii Island, have been continued to identify cost-effective aluminum alloys for use in OTEC systems operating in the corrosive marine environment.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

A Custom High-Throughput Optical Mapping Instrument for Accelerated Stress Testing of PV Module Materials

The performance and integrity of photovoltaic (PV) modules and materials may be assessed through optical characterizations. We have developed a custom optical mapping instrument (OMI) to improve measurement throughput time, facilitate automated measurements, allow for localized specimen examination, obtain spatial information relative to commercial benchtop spectrophotometer instruments, and provide automated data analysis. Both the key components and the methods used to improve the measurements are described. The measurement precision for the OMI is benchmarked for hemispherical transmittance relative to a previous round-robin study for commercial spectrophotometers. In addition to the unique instrument developed in this study, new insights have emerged from the examination of specimens from previous experiments, including: the depletion of the UV absorber is revealed for specimens beyond a certain size after artificial ultraviolet (UV) weathering; an optical degradation by internal haze formation is confirmed following Damp Heat (85 °C/85% relative humidity) testing; the better uniformity of the wear pattern for falling sand abrasion is used to select the DIN 52348 fixture over the ASTM D968 fixture; and the greater local (in the order of millimeters) heterogeneity of surface contamination in the soiling-prone location of Dubai relative to Kuwait. The results of the UV study have already been used to improve the standardized weathering of encapsulants. The example for Damp Heat testing is given to increase awareness of a degradation believed to be ubiquitously occurring in safety and design-type qualification testing of PV modules.

14 SOLAR ENERGY↗
DOE OSTI2024

Self-Supervised Cloud Classification

Abstract Low-level marine clouds play a pivotal role in Earth’s weather and climate through their interactions with radiation, heat and moisture transport, and the hydrological cycle. These interactions depend on a range of dynamical and microphysical processes that result in a broad diversity of cloud types and spatial structures, and a comprehensive understanding of cloud morphology is critical for continued improvement of our atmospheric modeling and prediction capabilities moving forward. Deep learning has recently accelerated our ability to study clouds using satellite remote sensing, and machine learning classifiers have enabled detailed studies of cloud morphology. A major limitation of deep learning approaches to this problem, however, is the large number of hand-labeled samples that are required for training. This work applies a recently developed self-supervised learning scheme to train a deep convolutional neural network (CNN) to map marine cloud imagery to vector embeddings that capture information about mesoscale cloud morphology and can be used for satellite image classification. The model is evaluated against existing cloud classification datasets and several use cases are demonstrated, including training cloud classifiers with very few labeled samples, interrogation of the CNN’s learned internal feature representations, cross-instrument application, and resilience against sensor calibration drift and changing scene brightness. The self-supervised approach learns meaningful internal representations of cloud structures and achieves comparable classification accuracy to supervised deep learning methods without the expense of creating large hand-annotated training datasets. Significance Statement Marine clouds heavily influence Earth’s weather and climate, and improved understanding of marine clouds is required to improve our atmospheric modeling capabilities and physical understanding of the atmosphere. Recently, deep learning has emerged as a powerful research tool that can be used to identify and study specific marine cloud types in the vast number of images collected by Earth-observing satellites. While powerful, these approaches require hand-labeling of training data, which is prohibitively time intensive. This study evaluates a recently developed self-supervised deep learning method that does not require human-labeled training data for processing images of clouds. We show that the trained algorithm performs competitively with algorithms trained on hand-labeled data for image classification tasks. We also discuss potential downstream uses and demonstrate some exciting features of the approach including application to multiple satellite instruments, resilience against changing image brightness, and its learned internal representations of cloud types. The self-supervised technique removes one of the major hurdles for applying deep learning to very large atmospheric datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Data from: "Moisture rivals temperature in limiting photosynthesis by trees establishing beyond their cold-edge range limit under ambient and warmed conditions"

This archive contains data files that were used to draw conclusions in “Moisture rivals temperature in limiting photosynthesis by trees establishing beyond their cold-edge range limit under ambient and warmed conditions”, by Moyes et al., 2015. All field research was completed in common garden plots set up as part of the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA.There are two main data file formats in this archive: comma-separated values (.csv), and Microsoft Excel (.xls and .xlsx). .xlsx files can be read using Microsoft Excel and Google Sheets, and .csv files can be read using any simple text editor program, such as TextEdit (Mac) and Notepad (Windows). This .pdf data user’s guide can be read using Adobe Acrobat Reader, or any other compatible software. Seedling photographs and their corresponding leaf area-processed images are available in .jpg/.JPG image format, and can be opened using Preview (Mac) and Photos (Windows). To provide additional spatial context, two types of geospatial files are also published in this data package: ESRI shapefiles (.shp) and .kml files. Shapefiles are compatible with any GIS software able to read the file type (such as QGIS or ESRI’s ArcGIS suite), and .kml files can be opened with Google Earth or Google Maps. Figures 3 and 4 in the publication contain data from Moyes et al. 2013. This publication is cited in the References section in this archive, and data files can be accessed via the Alpine Treeline Warming Experiment project portal on ESS-DIVE. ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Climate change is altering plant species distributions globally, and warming is expected to promote uphill shifts in mountain trees. However, at many cold-edge range limits, such as alpine treelines in the western United States, tree establishment may be colimited by low temperature and low moisture, making recruitment patterns with warming difficult to predict.- We measured response functions linking carbon (C) assimilation and temperature- and moisture-related microclimatic factors for limber pine (Pinus flexilis) seedlings growing in a heating × watering experiment within and above the alpine treeline. We then extrapolated these response functions using observed microclimate conditions to estimate the net effects of warming and associated soil drying on C assimilation across an entire growing season.- Moisture and temperature limitations were each estimated to reduce potential growing season C gain from a theoretical upper limit by 15–30% (c. 50% combined). Warming above current treeline conditions provided relatively little benefit to modeled net assimilation, whereas assimilation was sensitive to either wetter or drier conditions.- Summer precipitation may be at least as important as temperature in constraining C gain by establishing subalpine trees at and above current alpine treelines as seasonally dry subalpine and alpine ecosystems continue to warm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Global mapping of urban thermal anisotropy reveals substantial potential biases for remotely sensed urban climates

Urban thermal anisotropy (UTA) drastically biases satellite-derived urban surface temperatures and fluxes, and consequently inhibits a more comprehensive understanding of global urban climates. However, UTA patterns and associated biases in observed urban climate variables have not been investigated across an adequate number of global cities with diverse contexts; nor is it known whether there are globally measurable factors that are closely related to the UTA intensity (UTAI, quantified as the maximum difference between the nadir and off-nadir urban thermal radiation). Here we investigate the UTAI over more than 5500 cities worldwide using the moderate resolution imaging spectroradiometer (MODIS) multi-angle land surface temperature (LST) observations from 2003 to 2021. The results show that the global mean UTAI can reach 5.1, 2.7, 2.4, and 1.7 K during summer daytime, winter daytime, summer nighttime, and winter nighttime, respectively. Using nadir LST observations as a reference, our analysis reveals that UTA can lead to an underestimation of satellite-based urban surface sensible heat fluxes ( H ) by 45.4% and surface urban heat island intensity ( I s ) by 43.0% when using LST observations obtained from sensor viewing zenith angles (VZAs) of ±60°. However, practitioners can limit the biases of H and I s within ±10% by using LSTs from sensor VZAs within ±30°. We find that UTAI is closely related to urban impervious surface percentage and surface air temperature across global cities. In conclusion, these findings have implications for angular normalization of satellite-retrieved instantaneous LST observations across cities worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

In-Situ Spatial Mapping of Hydrogen in Yttrium Hydrides at LANSCE (FY23 Version, Rev. 1)

This report summarizes the development of neutron imaging capabilities and experimental activities performed at the Los Alamos Neutron Science Center (LANSCE) with the main goal of measuring temperature-driven hydrogen diffusion within bulk-yttrium hydride (YH x ) materials. Yttrium hydride is the leading candidate to serve as a solid neutron moderator in microreactor cores, owing to its high density of hydrogen atoms as well as its superior thermal stability compared to all other metal hydrides. The experimental results and technique developments reported herein support the U.S. Department of Energy Office of Nuclear Energy’s (DOE-NE) Microreactor Program under Technology Maturation. In particular, it addresses the critical need to experimentally validate and verify hydrogen-diffusion models of metal hydrides used in high-temperature microreactor designs by means of high-spatial-resolution neutron imaging. These capabilities were designed to apply large temperature gradients across centimeter-sized YH x pellets to simulate conditions faced in the microreactor environment. In principle, neutron imaging, combined with in-situ sample heating, enables near real-time tracking of hydrogen diffusion in YH x on the sub-millimeter scale. In this report, an overview of neutron imaging methodology and technologies are given in the context of recent spatial measures of hydrogen concentrations in similar metal hydrides. Additionally, the commissioning and operation of a custom-built compact dual-zone furnace is given along with details on three in-situ heating measurements of YH x performed over the 2020 to 2022 LANSCE operation cycles. The aims of these experiments ranged from furnace commissioning, determining sample quality, i.e., hydrogen uniformity via neutron computed tomography, and studying the effects of applied temperature-gradients on YH x pellets. Analyses and results from these neutron imaging measurements are given along with outlooks and guidelines for optimal future hydrogen diffusion measurements. Our conclusions are as follows. Image analyses indicate that centimeter-sized yttrium hydride cylindrical pellets exhibit uniform, whole-body hydrogen desorption and absorption without clear temperature dependence as reflected in the image attenuation at the opposing ends of each sample. This suggests that despite the large magnitude in temperature gradients applied by the furnace heating elements, the sample equilibrates to an unknown intermediate temperature. The origin of this result is likely the combination of short sample length (∼1cm) and use of a TZM can for containment where the latter created a thermal short across the sample. Nevertheless, the results from the most recent measurements indicate that neither significant concentration gradients of hydrogen were formed in centimeter-sized samples through the entire temperature range (25 °C to 950 °C) nor any formed due to temperature gradients on the order of 50 °C/cm up to 700 °C/cm. Furthermore, images from the FY2021 and FY2022 measurements indicate that samples of YH x , fabricated from either the direct hydride or powder metallurgy methods, are highly uniform in their hydrogen concentration to within the measurements’ spatial resolutions. The following questions arise from these latest results: 1) What is the intermediate temperature of the pellets in the TZM cans? 2) How quickly does the temperature equilibrate within the sample? and, 3) Do the observed changes in image attenuation follow known pressure-composition-temperature relations of yttrium hydride?

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗