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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Airborne Measurements of Scale‐Dependent Latent Heat Flux Impacted by Water Vapor and Vertical Velocity Over Heterogeneous Land Surfaces During the CHEESEHEAD19 Campaign

Abstract The water vapor transport associated with latent heat flux (LE) in the planetary boundary layer (PBL) is critical for the atmospheric hydrological cycle, radiation balance, and cloud formation. The spatiotemporal variability of LE and water vapor mixing ratio ( r v ) are poorly understood due to the scale‐dependent and nonlinear atmospheric transport responses to land surface heterogeneity. Here, airborne in situ measurements with the wavelet technique are utilized to investigate scale‐dependent relationships among LE, vertical velocity ( w ) variance (), and r v variance () over a heterogeneous surface during the Chequamegon Heterogeneous Ecosystem Energy‐balance Study Enabled by a High‐density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign. Our findings reveal distinct scale distributions of LE, , and at 100 m height, with a majority scale range of 120 m–4 km in LE, 32 m–2 km in , and 200 m–8 km in . The scales are classified into three scale ranges, the turbulent scale (8–200 m), large‐eddy scale (200 m–2 km), and mesoscale (2–8 km) to evaluate scale‐resolved LE contributed by and . The large‐eddy scale in PBL contributes over 70% of the monthly mean total LE with equal parts (50%) of contributions from and . The monthly temporal variations mainly come from the first two major contributing classified scales in LE, , and . These results confirm the dominant role of the large‐eddy scale in the PBL in the vertical moisture transport from the surface to the PBL, while the mesoscale is shown to contribute an additional ∼20%. This analysis complements published scale‐dependent LE variations, which lack detailed scale‐dependent vertical velocity and moisture information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Environmental drivers of spatial variation in tropical forest canopy height: Insights from NASA’s GEDI spaceborne LiDAR

Forest canopy height is a fundamental ecosystem property—influencing patterns of forest carbon storage and forest ecosystem responses to climate variability and change. Previous studies have analyzed environmental drivers influencing spatial variation in canopy height at landscape-to-regional scales; however, far less is known about the environmental determinants underlying regional and global scale variation in forest canopy height. Using the canopy height metrics products from Global Ecosystem Dynamics Investigation (GEDI), a space-borne Light Detection and Ranging (LiDAR) instrument specifically designed to characterize forest structure, we analyze the environmental correlates of spatial variation of global tropical forest canopy height. Our study demonstrates that climate, topography, and soil properties account for 75% of the variation in tropical forest canopy height. Elevation, dry season length, and solar radiation are the most important drivers in determining canopy height both locally and regionally. These results emphasize the vulnerability of tropical forest structure to ongoing changes in the earth’s climate and provide a valuable empirical baseline for tropical forest management.

Science & Technology - Other Topics↗
DOE OSTI2020

A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra

Changes in vegetation distribution, structure, and function can modify the canopy properties of terrestrial ecosystems, with potential consequences for regional and global climate feedbacks. In the Arctic, climate is warming twice as fast as compared to the global average (known as ‘Arctic amplification’), likely having stronger impacts on arctic tundra vegetation. In order to quantify these changes and assess their impacts on ecosystem structure and function, methods are needed to accurately characterize the canopy properties of tundra vegetation types. However, commonly used ground-based measurements are limited in spatial and temporal coverage, and differentiating low-lying tundra plant species is challenging with coarse-resolution satellite remote sensing. The collection and processing of multi-sensor data from unoccupied aerial systems (UASs) has the potential to fill the gap between ground-based and satellite observations. To address the critical need for such data in the Arctic, we developed a cost-effective multi-sensor UAS (the ‘Osprey’) using off-the-shelf instrumentation. The Osprey simultaneously produces high-resolution optical, thermal, and structural images, as well as collecting point-based hyperspectral measurements, over vegetation canopies. In this paper, we describe the setup and deployment of the Osprey system in the Arctic to a tundra study site located in the Seward Peninsula, Alaska. We present a case study demonstrating the processing and application of Osprey data products for characterizing the key biophysical properties of tundra vegetation canopies. In this study, plant functional types (PFTs) representative of arctic tundra ecosystems were mapped with an overall accuracy of 87.4%. The Osprey image products identified significant differences in canopy-scale greenness, canopy height, and surface temperature among PFTs, with deciduous low to tall shrubs having the lowest canopy temperatures while non-vascular lichens had the warmest. The analysis of our hyperspectral data showed that variation in the fractional cover of deciduous low to tall shrubs was effectively characterized by Osprey reflectance measurements across the range of visible to near-infrared wavelengths. Therefore, the development and deployment of the Osprey UAS, as a state-of-the-art methodology, has the potential to be widely used for characterizing tundra vegetation composition and canopy properties to improve our understanding of ecosystem dynamics in the Arctic, and to address scale issues between ground-based and airborne/satellite observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Self‐Assembled NiO Nanocrystal Arrays as Memristive Elements

Abstract Memristive switching, a nonlinear current–voltage ( I – V ) characteristic, has seen a tremendous surge in interest as an approach to achieve implementation of synaptic functions. The memristive switching behavior of self‐assembled NiO nanocrystals is investigated via scanning probe microscopy, based on first‐order reversal curve current–voltage spectroscopy. Synaptic switching is clearly observed as a direct consequence of filament growth (i.e., gradually increased conductance) in the nanocrystals. A spatial dependency of the conduction in the nanocrystals suggests that there is a localization of the switching filament. The current understanding of this localization ignores features related to local lateral variation current, which can generate an excessive local heat and temperature such as electrical dissipation. The observation of low electrical dissipation at the edge of the nanocrystals shows that less energy is wasted as heat such that the bias applied can be utilized more efficiently to assist the nucleation of the filament and thus reduces the power consumption. Electrical power dissipation is also found to scale with nanocrystal height and has spatial dependence within the nanocrystals. The combination of synaptic switching and high density of the nanocrystals demonstrate that it is feasible to exploit them to create a basic architecture for neuromorphic memory devices.

Kurnia, Fran↗
DOE OSTI2025

Characterizing falling particle curtain receivers at commercially relevant scales: Research Performance Progress Report (RPPR-1)

Sandia will construct a cold flow receiver test platform in order to characterize falling particle curtain receivers at commercially relevant scales. While Sandia has extensive experience in R&D of falling particle curtain receivers, most have been at pilot scale and smaller - on the order of 1 MW th with characteristic dimensions of nominally 1-2 m to adequately collect solar energy from the heliostat field at the National Solar Thermal Test Facility (NSTTF). However, scaling up receivers to commercially relevant scales (25 MW th and above) will require a thorough understanding of particle curtain dynamics at larger scales, especially longer drop heights, for design certainty. The goal of this project will be to construct a cold falling particle curtain test rig capable of simulating particle characteristics that are expected in a commercial scale CSP plant, namely the drop height, curtain thickness, and particle mass flow rate (normalized by length of curtain). This will enable data collection on curtain opacity and spread, both of which are correlated to receiver efficiency and reliable construction, for commercially relevant scales. It will also permit validation of numerical models that will enable detailed receiver characterization and design past currently validated scales.

14 SOLAR ENERGY↗
DOE OSTI2025

Characterizing falling particle curtain receivers at commercially relevant scales: Research Performance Progress Report (RPPR-1)

Sandia will construct a cold flow receiver test platform in order to characterize falling particle curtain receivers at commercially relevant scales. While Sandia has extensive experience in R&D of falling particle curtain receivers, most have been at pilot scale and smaller - on the order of 1 MWth with characteristic dimensions of nominally 1-2 m to adequately collect solar energy from the heliostat field at the National Solar Thermal Test Facility (NSTTF). However, scaling up receivers to commercially relevant scales (25 MWth and above) will require a thorough understanding of particle curtain dynamics at larger scales, especially longer drop heights, for design certainty. The goal of this project will be to construct a cold falling particle curtain test rig capable of simulating particle characteristics that are expected in a commercial scale CSP plant, namely the drop height, curtain thickness, and particle mass flow rate (normalized by length of curtain). This will enable data collection on curtain opacity and spread, both of which are correlated to receiver efficiency and reliable construction, for commercially relevant scales. It will also permit validation of numerical models that will enable detailed receiver characterization and design past currently validated scales.

14 SOLAR ENERGY↗
DOE OSTI2025

Leveraging Open-Source Satellite-Derived Building Footprints for Height Inference

At a global scale, cities are growing and characterizing the built environment is essential for deeper understanding of human population patterns, urban development, energy usage, climate change impacts, among others. Buildings are a key component of the built environment and significant progress has been made in recent years to scale building footprint extractions from satellite datum and other remotely sensed products. Billions of building footprints have recently been released by companies such as Microsoft and Google at a global scale. However, research has shown that depending on the methods leveraged to produce a footprint dataset, discrepancies can arise in both the number and shape of footprints produced. Therefore, each footprint dataset should be examined and used on a case-by-case study. In this work, we find through two experiments on Oak Ridge National Laboratory and Microsoft footprints within the same geographic extent that our approach of inferring height from footprint morphology features is source agnostic. Regardless of the differences associated with the methods used to produce a building footprint dataset, our approach of inferring height was able to overcome these discrepancies between the products and generalize, as evidenced by 98% of our results being within 3m of the ground-truthed height. This signifies that our approach can be applied to the billions of open-source footprints which are freely available to infer height, a key building metric. This work impacts the broader domain of urban science in which building height is a key, and limiting factor.

Stipek, Clinton [ORNL] (ORCID:0000000280501096)↗
DOE OSTI2026

Imaging surface topography with coherent x-ray reflectivity: Theory, kinematics, and simulations

A theoretical formalism is described for understanding coherent x-ray reflectivity (CXR) from the surface of a semi-infinite crystal having a variable surface topography, described by the height profile ℎ(𝑥,𝑦). The surface topography is imaged as a complex “effective density,” obtained from the phasing and inversion of the coherent x-ray reflectivity data, measured through a rocking scan centered at a vertical momentum transfer 𝑄$^{0}_{𝑧}$ and a vertical range Δ⁢𝑄 𝑧 . The formalism predicts that the effective density has an amplitude with a maximum located at the surface height for each position within the surface plane. The phase of the effective density has a lateral variation that is controlled by the surface height and a vertical variation that reflects a combination of the interfacial structure and specific choice of measurement conditions. This understanding enables direct observation of nanometer-scale interfacial topography, i.e., ℎ⁡(𝑥,𝑦)⁢𝑐 𝑠 (where 𝑐 𝑠 is the vertical substrate lattice parameter) with Å-scale sensitivity to surface height. Numerical simulations illustrate and confirm the theoretical results. These results show how the interpretation of the interfacial density phase obtained by CXR data inversion (i.e., surface topography with respect to a flat surface) is conceptually similar to that previously known for Bragg coherent diffraction imaging (BCDI) measurements of isolated nanoparticles (i.e., lattice displacements with respect to an ideal crystal lattice). This suggests that CXR can be thought of as a form of dark field imaging with respect to the bright field BCDI approach. An implication of these results is that interfacial imaging may bypass some of the significant challenges associated with BCDI imaging of multiple particles having different orientations.

X-ray imaging↗
DOE OSTI2025

Linking large-scale weather patterns to observed and modeled turbine hub-height winds offshore of the US West Coast

The US West Coast holds great potential for wind power generation, although its potential varies due to the complex coastal climate. Characterizing and modeling turbine hub-height winds under different weather conditions are vital for wind resource assessment and management. This study uses a two-stage machine learning algorithm to identify five large-scale meteorological patterns (LSMPs): post-trough, post-ridge, pre-ridge, pre-trough, and California high. The LSMPs are linked to offshore wind patterns, specifically at lidar buoy locations within lease areas for future wind farm development off Humboldt and Morro Bay. While each LSMP is associated with characteristic large-scale atmospheric conditions and corresponding differences in wind direction, diurnal variation, and jet features at the two lidar sites, substantial variability in wind speeds can still occur within each LSMP. Wind speeds at Humboldt increase during the post-trough, pre-ridge, and California-high LSMPs and decrease during the remaining LSMPs. Morro Bay has smaller responses in mean speeds, showing increased wind speed during the post-trough and California-high LSMPs. Besides the LSMPs, local factors, including the land–sea thermal contrast and topography, also modify mean winds and diurnal variation. The High-Resolution Rapid Refresh model analysis does a good job of capturing the mean and variation at Humboldt but produces large biases at Morro Bay, particularly during the pre-ridge and California-high LSMPs. The findings are anticipated to guide the selection of cases for studying the influence of specific large-scale and local factors on California offshore winds and to contribute to refining numerical weather prediction models, thereby enhancing the efficiency and reliability of offshore wind energy production.

17 WIND ENERGY↗
DOE OSTI2021

Nondimensional convection numbers modeling thermally stratified storage tanks: Richardson's number and hot-water tanks

Thermally stratified storage tank studies have spanned over 50 years to increase the thermal storage efficiency and accurate prediction of the outlet temperature particularly for solar applications. The studies have reviewed and modeled the jet and plume flow phenomena inside the tank due to the inlet mixing and stratification level. Kelvin–Helmholtz and Rayleigh–Taylor instabilities are the major drivers of the mixing in these tanks. Momentum jets deflecting off walls at the bottom of the tank also create significant mixing. Reviewing Richardson models shows that the categorization was based on the range of Reynolds numbers at the inlet. Unfortunately, the use of superficial velocity in calculating the Richardson number results in critical values in the literature ranging from below 0.25 to 100. The most used length scale associated with these flows is an inertial scale based on the tank height or diameter although the mixing can occur at a relatively smaller scale. The various inlet devices and a large span of flow rates experienced in thermally stratified storage tanks requisite the use of the Reynolds number in combination with a convection number for accurate one dimensional models that predict performance over the long-term. The evaluation of peak shifting of electric loads leveraging renewable sources for applications, including residential hot-water tanks, commercial water tanks, and large-scale chilled water storage tanks, require these models. Finally, this paper is focused on establishing the significance of the convection numbers in conjunction with the Reynolds number for modeling the thermal stratification in storage tanks.

14 SOLAR ENERGY↗
DOE OSTI2022

Probing eddy size and its effective mixing length in stably stratified roughness sublayer flows

Stably stratified roughness sublayer flows are ubiquitous yet remain difficult to represent in models and to interpret using field experiments. Here, continuous high-frequency potential temperature profiles from the forest floor up to 6.5 times the canopy height observed with distributed temperature sensing (DTS) are used to link eddy topology to roughness sublayer stability correction functions and coupling between air layers within and above the canopy. The experiments are conducted at two forest stands classified as hydrodynamically sparse and dense. Near-continuous profiles of eddy sizes (length scales) and effective mixing lengths for heat are derived from the observed profiles using a novel conditional sampling approach. The approach utilizes potential temperature isoline fluctuations from a statically stable background state. The transport of potential temperature by an observed eddy is assumed to be conserved (adiabatic movement) and we assume that irreversible heat exchange between the eddy and the surrounding background occurs along the (vertical) periphery of the eddy. This assumption is analogous to Prandtl's mixing-length concept, where momentum is transported rapidly vertically and then equilibrated with the local mean velocity gradient. A distinct dependence of the derived length scales on background stratification, height above ground, and canopy characteristics emerges from the observed profiles. Implications of these findings for (1) the failure of Monin–Obukhov similarity in the roughness sublayer and (2) above-canopy flow coupling to the forest floor are examined. The findings have practical applications in terms of analysing similar DTS data sets with the proposed approach, modelling roughness sublayer flows, and interpreting nocturnal eddy covariance measurements above tall forested canopies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Scaling of Turbulence and Microphysics in a Convection–Cloud Chamber of Varying Height

Abstract The convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady‐state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights of H = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale as H 1/3 , consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales as H 2/3 . Temperature and other scalar fluctuations scale as H −3/7 . Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross‐sectional area (i.e., as H 2 for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed‐layers in the atmosphere, such as fog layers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Nonlinear ablative Rayleigh-Taylor instability: Increased growth due to self-generated magnetic fields

The growth rate of the nonlinear ablative Rayleigh-Taylor (RT) instability is enhanced by magnetic fields self-generated by the Biermann battery mechanism; a scaling for this effect with perturbation height and wavelength is proposed and validated with extended-magnetohydrodynamic simulations. The magnetic flux generation rate around a single RT spike is found to scale with the spike height. The Hall parameter, which quantifies electron magnetization, is found to be strongly enhanced for short-wavelength spikes due to Nernst compression of the magnetic field at the spike tip. Furthermore, the impact of the magnetic field on spike growth is through both the suppressed thermal conduction into the unstable spike and the Righi-Leduc heat flow deflecting heat from the spike tip to the base. Righi-Leduc is found to be the dominant effect for small Hall parameters, while suppressed thermal conduction dominates for large Hall parameters. These results demonstrate the importance of considering magnetic fields in all perturbed inertial confinement fusion hot spots.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Quasi-stationary Planetary Scale Waves in Modern Climate Models

We evaluate climate model simulations of geopotential height at the largest space-time scales, considering the first Fourier components (in longitude) of long-term climatological means. Quasi-stationary planetary scale waves emerge from this analysis. Variations of these waves are important components of climate change, for example associated with regional drought. Systematic examination of their long-term climatology provides context for understanding their evolution in time. We compare four reanalysis datasets with “historical runs” from the latest version of the Coupled Model Intercomparison Project (CMIP) and find general agreement, but we also identify model errors outside the range of both observational uncertainty and the uncertainty implied by interannual variability. Errors in wave phase have possible implications for climate model projections of regional climate and of shifting weather patterns. One model in the set we examine, originally created nearly 20 years before the others, exhibits noticeably greater errors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Thermoelectric coolers for high-power-density 3D electronics heat management

Future advancements in three-dimensional (3D) electronics require robust thermal management methodology. Thermoelectric coolers (TECs) are reliable and solid-state heat pumping devices with high cooling capacity that can meet the requirements of emerging 3D microelectronic devices. In this work, we first provide the design of TECs for electronics cooling using a computational model and then experimentally validate the main predictions. Key device parameters such as device thickness, leg density, and contact resistance were studied to understand their influence on the performance of TECs. Our results show that it is possible to achieve high cooling power density through optimization of TE leg height and packing density. Scaling of TECs is shown to provide ultra-high cooling power density.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Development of a military-specific mesh-type computational phantom library and its application to internal dosimetry and in-field radiological triage screening

Estimates of organ-absorbed and committed doses to individuals exposed to radioactive materials via acute inhalation often rely on internal dose coefficients and detector responses from reference human computational models. To achieve more accurate dose assessments to United States Armed Forces service members exposed in-field, computational models with varying morphometric parameters representative of this population are necessary. The International Commission on Radiological Protection (ICRP) Publication 145 provides detailed mesh reference computational phantoms (MRCPs) for adult males and females, with morphometric parameters matched to the 50th percentile. Previously, these phantoms were 2D and 3D scaled to match desired height, mass, and secondary anthropomorphic parameters in the creation of the University of Florida / Memorial Sloan Kettering (UF/MSK) computational phantom library. To achieve body fat percentage targets required for accession into the US Armed Forces, muscle and fat volumes were adjusted accordingly, thus, creating the UF/Department of Defence computational phantom library presented in this study. A comprehensive library of mesh-type computational human phantoms was created, including 57 adult males and 49 adult females with morphometric parameters aligned with United States Armed Forces service members. Phantoms were restricted to a body mass index between 19 and 27.5, with body fat percentages below 26% for males and 36% for females. Specific absorbed fractions were computed for selected source and target combinations, demonstrating how variations in height and body mass influence energy absorption in target regions relative to the ICRP MRCPs. Radiation detector responses were also computed, revealing that higher body masses resulted in decreased registered counts in the detection volume. These findings highlight the importance of incorporating morphometric variability in computational phantoms to achieve more accurate dose assessments and radiation detection responses for United States Armed Forces service members who inhale radioactive materials in-field.

computational phantoms↗
DOE OSTI2024

Resource Assessment for Distributed Wind Energy: An Evaluation of Best-Practice Methods in the Continental US

Current wind resources within the United States (US) indicate a potential to profitably install nearly 1,400 gigawatts of distributed wind (DW) capacity. This amount is equivalent to over half of the United States’ current energy demand from electricity, making it enough to power millions of homes and businesses and replace countless fossil fuel-based generating plants. Despite the potential growth of DW in the US, deployments are presently hindered by a lack of confidence in resource estimation methods. One potential challenge is that smaller-scale turbines, with hub heights of 40 meters or less, are disproportionately impacted by obstacles such as buildings and vegetation. These obstacles may produce complex wake effects, best modeled with high-fidelity complex fluid dynamics (CFD) models that are too computationally expensive to use for routine siting and resource assessment. Thus, installers today make use of heuristics and simple equations to approximate the impact of obstacles while also leveraging long-term resource data from commercial or publicly available atmospheric models. This study evaluates these historical and commonly used methods alongside new lower-order obstacle models produced from CFD simulations and measurement-based bias correction. The preliminary results from this study show the importance of taking care in the choice and application of mesoscale atmospheric models and the significant value of bias correction using measurements from nearby meteorological towers. Detailed obstacle modeling provides only modest additional gains in performance and, in some cases, can add error, especially at sites where turbines have already been located to avoid obvious impact from upwind obstacles. These findings reinforce the importance of collecting in situ measurements and suggest that obstacle models may be better applied in practice to automated or computer-aided siting, rather than in economic wind resource assessments.

17 WIND ENERGY↗
DOE OSTI2023

Subsetted model output for static variables from a LASSO-CACTI WRF simulation

Static model output from a Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m through the use of four nested domains, labeled d1 through d4. The simulations are of convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. This version of the output is a collection of variables subsetted from the raw WRF output to reduce the file overhead for users not needing the full raw dataset. The subset files are in netCDF format with the height-based variables on the raw, model eta and soil levels. The variables in this file are ones that do not change during a simulation, such as the terrain height and map-scale factors.

54 ENVIRONMENTAL SCIENCES↗