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

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At least 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Diurnal Variability of Vertical Structure from a TRMM Passive Microwave "Virtual Radar" Retrieval

Robust description of the diurnal cycle from TRMM observations is complicated by the limitations of Low Earth Orbit (LEO) sampling; from a 'climatological' perspective, sufficient sampling must exist to control for both spatial and seasonal variability, before tackling an additional diurnal component (e.g., with 8 additional 3-hourly or 24 1-hourly bins). For documentation of vertical structure, the narrow sample swath of the TRMM Precipitation Radar limits the resolution of any of these components. A neural-network based 'virtual radar" retrieval has been trained and internally validated, using multifrequency / multipolarization passive microwave(TM1) brightness temperatures and textures parameters and lightning (LIS) observations, as inputs, and PR volumetric reflectivity as targets (outputs). By training the algorithms (essentially highly multivariate, nonlinear regressions) on a very large sample of high-quality co-located data from the center of the TRMM swath, 3D radar reflectivity and derived parameters (VIL, IWC, Echo Tops, etc.) can be retrieved across the entire TMI swath, good to 8-9% over the dynamic range of parameters. As a step in the retrieval (and as an output of the process), each TMI multifrequency pixel (at 85 GHz resolution) is classified into one of the 25 archetypal radar profile vertical structure "types", previously identified using cluster analysis. The dynamic range of retrieved vertical structure appears to have higher fidelity than the current (Version 6) experimental GPROF hydrometeor vertical structure retrievals. This is attributable to correct representation of the prior probabilities of vertical structure variability in the neural network training data, unlike the GPROF cloud-resolving model training dataset used in the V6 algorithms. The LIS lightning inputs are supplementary inputs, and a separate offline neural network has been trained to impute (predict) LIS lightning from passive-microwave-only data. The virtual radar retrieval is thus, in principle, extensible to Aqua/AMSR-E and NPOESS/CMIS passive microwave instruments. The virtual radar approach yields a threefold increase in effective sampling from the mission, albeit of lower-quality "retrieved" data, reducing the variance of local estimates by one third (or the standard deviation by-0.57). In this talk, the variance reduction is leveraged to more finely resolve global diurnal variability in both space and time (local hour).

Boccippio, Dennis J.↗
NASA NTRSDate not supplied

Aeroelastic Trim Drag Optimization of Mach 0.745 Transonic Truss-Braced Wing Aircraft with Variable-Camber Continuous Trailing-Edge Flap

This paper presents an aeroelastic trim drag optimization study of the Mach 0.745 Transonic Truss-Braced Wing (TTBW) aircraft with the Variable-Camber Continuous Trailing-Edge Flap (VCCTEF). An aero-structural analysis solver VSPAERO with transonic small disturbance, integral boundary-layer, and wing-strut interference corrections coupled to finite-element code BEAM3D is developed to provide a rapid aircraft aeroelastic performance evaluation. The VSPAERO model has been validated against wind tunnel test data. Aeroelastic trim drag optimization studies are conducted for a VCCTEF configuration with 6-spanwise sections. Three different flight conditions corresponding to Mach 0.745 are selected for the TTBW aircraft aeroelastic trim drag optimization at the design and off-design cruise lift coefficients. The preliminary optimization results show that the TTBW aircraft with the optimized VCCTEF deflection achieves a drag reduction of about 9.1 counts, 5.9 counts, and 11.8 counts corresponding to the lift coefficients 0.68, 0.73, and 0.78, respectively. A high-fidelity CFD solver FUN3D is used to validate the aeroelastic trim drag optimization.

Aeroelastic trim drag↗
DOE OSTI2018

Regional Manufacturing Cost Structures and Supply Chain Considerations for Medium Voltage Silicon Carbide Power Applications

Bottoms-up cost analysis has been a mainstay of commoditized industry and manufacturing processes for years, however a holistic objective supply chain analysis to inform research and investment in the development of early stage technologies has not. The potential for rapid adoption of wide bandgap (WBG) semiconductors, specifically silicon carbide (SiC), highlights a need to understand the drivers of location-specific manufacturing cost, global supply chains, and plant location decisions. Further, ongoing research and investment, necessitates analytical analysis to help inform the roadmap of SiC technologies. In collaboration with PowerAmerica the project explores the bottoms-up cost analysis of wafers, devices, modules, and motor drives at the anticipated manufacturing levels. Leveraging these models, it outlines how the cost reduction potential of proposed research advances can be quantified.

42 ENGINEERING↗
DOE OSTI2025

The Technical, Economic, Risk, and Adoption Assessment for Evaluating Work Reduction Opportunities in the Nuclear Industry

Automation and cost-saving initiatives, such as process automation with advances in artificial intelligence, are gaining traction in modernization efforts across the nuclear industry. As these innovations are increasingly adopted, it becomes crucial to evaluate their impacts comprehensively. Various technical and economic attributes, along with risk and human readiness factors, must be achieved to ensure that innovative projects enabling automation and modernization are successful. However, no systematic or integrated framework exists that allows plants to evaluate these innovative projects. To address this gap, the Technical, Economic, Risk, and Adoption (TERA) assessment offers a structured method to evaluate innovative technologies, ensuring solutions meet both operational and safety standards. The TERA framework integrates the disparate perspectives to assess modernization opportunities in nuclear operations. It combines qualitative and quantitative models to evaluate the relationship between performance and business impacts, while also enabling continuous re-evaluation during project development. This approach helps plant owners identify high-priority opportunities, optimize cost savings, and minimize risks, ensuring projects remain on track to achieve desired returns. By providing a comprehensive, systematic methodology, TERA enables informed, data-driven decisions that support successful modernization efforts, enhancing efficiency, safety, and cost savings across nuclear operations. This paper explains the TERA framework and its benefits for the nuclear industry.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

A Rutile Chevron Modulation in Delafossite-Like Ga 3– x In 3 Ti x O 9+ x /2

The structure solution of the modulated, delafossite-related, orthorhombic Ga 3–x In 3 Ti x O 9+x/2 for x = 1.5 is reported here in conjunction with a model describing the modulation as a function of x for the entire system. Previously reported structures in the related A 3–x In 3 Ti x O 9+x/2 (A = Al, Cr, or Fe) systems use X-ray diffraction to determine that the anion lattice is the source of modulation. Neutron diffraction, with its enhanced sensitivity to light atoms, offers a route to solving the modulation and is used here, in combination with precession electron diffraction tomography (PEDT), to solve the structure of Ga 1.5 In 3 Ti 1.5 O 9.75 . We construct a model that describes the anion modulation through the formation of rutile chevrons as a function of x. This model accommodates the orthorhombic phase (1.5 ≤ x ≤ 2.1) in the Ga 3-x In 3 Ti x O 9+x/2 system, which transitions to a biphasic mixture (2.2 ≤ x ≤ 2.3) with a monoclinic, delafossite-related phase (2.4 ≤ x ≤ 2.5). The optical band gaps of this system are determined, and are stable at ~3.4 eV before a ~0.4 eV decrease between x = 1.9 and 2.0. After this decrease, stability resumes at ~3.0 eV. Resistance to oxidation and reduction is also presented.

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

Modulating CO 2 Electrocatalytic Conversion to the Organics Pathway by the Catalytic Site Dimension

Electrochemical reduction of carbon dioxide to organic chemicals provides a value-added route for mitigating greenhouse gas emissions. Here, we report a family of carbon-supported Sn electrocatalysts with the tin size varying from single atom, ultrasmall clusters to nanocrystallites. High single-product Faradaic efficiency (FE) and low onset potential of CO 2 conversion to acetate (FE = 90% @ –0.6 V), ethanol (FE = 92% @ –0.4 V), and formate (FE = 91% @ –0.6 V) were achieved over the catalysts of different active site dimensions. The CO 2 conversion mechanism behind these highly selective, size-modulated p-block element catalysts was elucidated by structural characterization and computational modeling, together with kinetic isotope effect investigation.

10 SYNTHETIC FUELS↗
DOE OSTI2020

Tracking Seasonal and Interannual Variability in Photosynthetic Downregulation in Response to Water Stress at a Temperate Deciduous Forest

Abstract The understanding and modeling of photosynthetic dynamics affected by climate variability can be highly uncertain. In this paper, we examined a well‐characterized eddy covariance site in a drought‐prone temperate deciduous broadleaf forest combining tower measurements and satellite observations. We find that an increase in spring temperature usually leads to enhanced spring gross primary production (GPP), but a GPP reduction in late growing season due to water limitation. We evaluated how well a coupled fluorescence‐photosynthesis model (SCOPE) and satellite data sets track the interannual and seasonal variations of tower GPP from 2007 to 2016. In SCOPE, a simple stress factor scaling of Vcmax as a linear function of observed predawn leaf water potential ( ψ pd ) shows a good agreement between modeled and measured interannual variations in both GPP and solar‐induced chlorophyll fluorescence (SIF) from the Global Ozone Monitoring Experiment‐2 (GOME‐2). The modeled and satellite‐observed changes in SIF yield are ~30% smaller than corresponding changes in light use efficiency (LUE) under severe stress, for which a common linear SIF to GPP scaling would underestimate the stress reduction in GPP. Overall, GOME‐2 SIF tracks interannual tower GPP variations better than satellite vegetations indices (VIs) representing canopy “greenness.” However, it is still challenging to attribute observed SIF variations unequivocally to greenness or physiological changes due to large GOME‐2 footprint. Higher‐resolution SIF data sets (e.g., TROPOMI) already show the potential to well capture the downregulation of late‐season GPP and could pave the way to better disentangle canopy structural and physiological changes in the future.

He, Liyin↗
DOE OSTI2026

Emergent quasi-one-dimensional antiferromagnetism in the distorted kagome magnet CePtPb

CePtPb hosts a distorted kagome lattice of Ce 3+ ions, providing a clean platform to investigate how reduced local symmetry and strong spin-orbit coupling reshape frustrated magnetism. Magnetization, specific heat, and magnetocaloric effect measurements, combined with a symmetry analysis of the single-ion anisotropy, demonstrate that the local 𝑚⁢2⁢𝑚 site symmetry selects a nearly Ising-like Kramers doublet with easy axes lying within the 𝑎⁢𝑏 plane. This results in three distinct in-plane Ising directions and an overall easy-plane anisotropy. The low-energy magnetic response is well captured by a three-sublattice Ising model, which quantitatively reproduces the saturation magnetization for arbitrary in-plane field orientations, including $[110]$ and $[1\bar{⁢1}⁢0]$, as well as the ratio of the field-induced critical fields. For 𝐵∥$[110]$, the phase diagram exhibits two quantum critical points at 𝐵 c⁢1 = 0.25T and 𝐵 c⁢2 = 0.55T, arising from the sequential polarization of the three Ising sublattices. In conclusion, these results reveal that the system develops quasi-one-dimensional spin chains along the 𝑐 axis, emerging from the nominally three-dimensional crystal structure composed of stacked kagome layers, and illustrate how reduced local symmetry can drive effective dimensional reduction in rare-earth Ising magnets.

Li, Fangli [Southern University of Science and Tec↗
DOE OSTI2018

Attenuating Sulfidogenesis in a Soured Continuous Flow Column System With Perchlorate Treatment

Hydrogen sulfide production by sulfate reducing bacteria (SRB) is the primary cause of oil reservoir souring. Amending environments with chlorate or perchlorate [collectively denoted (per)chlorate] represents an emerging technology to prevent the onset of souring. Recent studies with perchlorate reducing bacteria (PRB) monocultures demonstrated that they have the innate capability to enzymatically oxidize sulfide, thus PRB may offer an effective means of reversing souring. (Per)chlorate may be effective by (i) direct toxicity to SRB; (ii) competitive exclusion of SRB by PRB; or (iii) reversal of souring through re-oxidation of sulfide by PRB. To determine if (per)chlorate could sweeten a soured column system and assign a quantitative value to each of the mechanisms we treated columns flooded with San Francisco bay water with temporally decreasing amounts (50, 25, and 12.5 mM) of (per)chlorate. Geochemistry and the microbial community structure were monitored and a reactive transport model was developed, Results were compared to columns treated with nitrate or untreated. Souring was reversed by all treatments at 50 mM but nitrate-treated columns began to re-sour when treatment concentrations decreased (25 mM). Re-souring was only observed in (per)chlorate-treated columns when concentrations were decreased to 12.5 mM and the extent of re-souring was less than the control columns. Microbial community analyses indicated treatment-specific community shifts. Nitrate treatment resulted in a distinct community enriched in genera known to perform sulfur cycling metabolisms and genera capable of nitrate reduction. (Per)chlorate treatment enriched for (per)chlorate reducing bacteria. (Per)chlorate treatments only enriched for sulfate reducing organisms when treatment levels were decreased. A reactive transport model of perchlorate treatment was developed and a baseline case simulation demonstrated that the model provided a good fit to the effluent geochemical data. Subsequent simulations teased out the relative role that each of the three perchlorate inhibition mechanisms played during different phases of the experiment. These results indicate that perchlorate addition is an effective strategy for both souring prevention and souring reversal. It provides insight into which organisms are involved, and illuminates the interactive effects of the inhibition mechanisms, further highlighting the versatility of perchlorate as a sweetening agent.

02 PETROLEUM↗
NASA NTRS1994

Investigation of the stability and 1.0 MeV proton radiation resistance of commercially produced hydrogenated amorphous silicon alloy solar cells

The radiation resistance of commercial solar cells fabricated from hydrogenated amorphous silicon alloys is reported. A number of different device structures were irradiated with 1.0 MeV protons. The cells were annealing at 200 C. The annealing time was dependent on proton fluence. Annealing devices for one hour restores cell parameters or fluences below 1(exp 14) cm(exp -2); fluences above 1(exp 14) cm(exp -2) require longer annealing times. A parametric fitting model was used to characterize current mechanisms observed in dark I-V measurements. The current mechanisms were explored with irradiation fluence, and voltage and light soaking times. The thermal generation current density and quality factor increased with proton fluence. Device simulation shows the degradation in cell characteristics may be explained by the reduction of the electric field in the intrinsic layer.

Lord, Kenneth R., II↗
NASA NTRS2003

Effects of Convective Asymmetries on Hurricane Intensity: A Numerical Study

The influence of the uniform large-scale flow, beta effect, and vertical shear of the environmental flow on hurricane intensity is investigated in the context of the induced convective or potential vorticity asymmetries with a hydrostatic primitive equation hurricane model. In agreement with the previous studies, imposing of one of these environmental effects can substantially weaken the simulated tropical cyclones. In response t o the environmental influence, significant asymmetries develop with a structure similar to the spiral bands in real hurricanes, which are dominated by wavenumber-one components. The tendencies of the mean radial, azimuthal winds and temperature associated with the environment-induced convective asymmetries are evaluated respectively. The resulting asymmetries can effectively reduce hurricane intensity by directly producing the negative tendency of the mean tangential wind in the vicinity of the radius of maximum wind, and by weakening the mean radial circulation. The reduction effects are closely associated with the spiral structure of the induced asymmetries. The time lag observed between the imposition of the environmental influence and the resulting rise in the minimum central pressure is the time required for developing the spiral structure. This study also confirms the axisymmetrization process associated with the induced wavenumber-one components of potential vorticity asymmetries, but it exists only within the radius of maximum wind.

Wu, Liguang↗
NASA NTRSDate not supplied

Overview of Aeroacoustic Testing of the High-Lift Common Research Model

This paper presents an overview of the experimental data obtained in a 2020/2021 aeroacoustic test of the high-lift variant of the common research model. The breadth of the aerodynamic and acoustic measurements is highlighted along with some key results. Aerodynamic data were observed to be consistent with previous observations, and the acoustic measurements were repeatable once some background noise and shear layer issues were resolved. The primary purpose of the test was to evaluate the noise reduction potential of slat noise reduction devices, and a slat-gap filler was found to produce substantial noise reduction over a broad frequency range. The gap filler was designed to meet practical implementation considerations at full scale and constructed out of shape-memory alloys that would allow the slat to be articulated. However, additional structural testing will be required to demonstrate the performance of the gap filler during slat deployment and retraction. Over 3,500 test points were collected during the test, and only a small fraction of the experimental data has been processed in a preliminary manner. Nonetheless, the results presented demonstrate the quality of the dataset and reveal some insights about slat noise.

Aeroacoustics↗
NASA NTRS2019

Modelling above-ground biomass stock over Norway using national forest inventory data with ArcticDEM and Sentinel-2 data

Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the boreal domain. ArcticDEM is a collection of high-resolution (2 m) space-borne stereogrammetric digital surface models (DSM) covering the entire land area north of 60° of latitude. The free-availability of ArcticDEM data offers new possibilities for aboveground biomass mapping (AGB) across boreal forests, and thus it is necessary to evaluate the potential for these data to map AGB over alternative open-data sources (i.e., Sentinel-2). This study was performed over the entire land area of Norway north of 60° of latitude, and the Norwegian national forest inventory (NFI) was used as a source of field data composed of accurately geolocated field plots (n=7710) systematically distributed across the study area. Separate random forest models were fitted using NFI data, and corresponding remotely sensed data consisting of either: i) a canopy height model (ArcticCHM) obtained by subtracting a high-quality digital terrain model (DTM) from the ArcticDEM DSM height values, ii) Sentinel-2 (S2), or iii) a combination of the two (ArcticCHM+S2). Furthermore, we assessed the effect of the forest- and terrain-specific factors on the models’ predictive accuracy. The best model (,i.e., ArcticCHM+S2) explained nearly 60% of the variance of the training set, which translated in the largest accuracy in terms of root mean square error (RMSE=41.4 t/ha). This result highlights the synergy between 3D and multispectral data in AGB modelling. Furthermore, this study showed that despite the importance of ArcticCHM variables, the S2 model performed slightly better than ArcticCHM model. This finding highlights some of the limitations of ArcticDEM, which, despite the unprecedented spatial resolution, is highly heterogeneous due to the blending of multiple acquisitions across different years and seasons. We found that both forest- and terrain-specific characteristics affected the uncertainty of the ArcticCHM+S2 model and concluded that the combined use of ArcticCHM and Sentinel-2 represents a viable solution for AGB mapping across boreal forests. The synergy between the two data sources allowed for a reduction of the saturation effects typical of multispectral data while ensuring the spatial consistency in the output predictions due to the removal of artifacts and data voids present in ArcticCHM data. While the main contribution of this study is to provide the first evidence of the best-case-scenario (i.e., availability of accurate terrain models) that ArcticDEM data can provide for large-scale AGB modelling, it remains critically important for other studies to investigate how ArcticDEM may be used in areas where no DTMs are available as is the case for large portions of the boreal zone.

space-borne imagery↗
DOE OSTI2018

Random Alloyed versus Intermetallic Nanoparticles: A Comparison of Electrocatalytic Performance

As synthetic methods advance for metal nanoparticles, more rigorous studies of structure–function relationships can be made. Many electrocatalytic processes depend on the size, shape, and composition of the nanocatalysts. Here, the properties and electrocatalytic behavior of random alloyed and intermetallic nanoparticles are compared. Beginning with an introduction of metallic nanoparticles for catalysis and the unique features of bimetallic compositions, the discussion transitions to case studies of nanoscale electrocatalysts where direct comparisons of alloy and intermetallic compositions are undertaken for methanol electrooxidation, formic acid electrooxidation, the oxygen reduction reaction, and the electroreduction of carbon dioxide (CO2). Design and synthesis strategies for random alloyed and intermetallic nanoparticles are discussed, with an emphasis on Pt–M and Cu–M compositions as model systems. The differences in catalytic performance between alloys and intermetallic nanoparticles are highlighted in order to provide an outlook for future electrocatalyst design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidation of Ce/Zr ratio effects on the physical properties and catalytic performance of CuO x /Ce y Zr 1− y O 2 catalysts

Although cerium oxide (CeO 2 ) is widely used as a catalyst support, its limited defect sites and surface oxygen vacancy/mobility should be improved. The incorporation of zirconium (Zr) in the cerium (Ce) lattice is shown to increase the number of oxygen vacancies and improve catalytic activity. Using a fixed surface density (SD) of copper (∼2.3 Cu atoms per nm 2 ) as a surface species, the role of the support (Ce y Zr 1−y O 2 (y = 1.0, 0.9, 0.6, 0.5, and 0.0)) and defect site effects in the CO oxidation reaction was investigated. Spectroscopic (e.g., Raman, XRD, XPS) and microscopic (e.g., SEM-EDX, HR-TEM) characterization techniques were applied to evaluate the defect sites, crystallite size, lattice parameters, chemical composition, oxidation states of elements and microstructure of the catalysts. Here, the CO oxidation reaction with varied CO : O 2 ratios (1 : 5, 1 : 1, and 1 : 0.5 (stoichiometric)) was used as a model reaction to describe the relationship between the structure and the catalytic performance of each catalyst. Based on the characterization results of Ce y Zr 1−y O 2 materials, the addition of Zr causes physical and chemical changes to the overall material. The inclusion of Zr into the structure of CeO 2 decreased the overall lattice parameter of the catalyst and increased the number of defect sites. The prepared catalysts were able to reach complete CO conversion (∼100%) at low temperature conditions (<200 °C), each showing varied reaction activity. The difference in CO oxidation activity was then analyzed and related to the structure, wherein Cu loading, surface oxygen vacancies, reduction–oxidation ability, CuO x –support interaction and oxygen mobility in the catalyst were the crucial descriptors.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Theory of activated glassy dynamics in randomly pinned fluids

We generalize the force-level, microscopic, Nonlinear Langevin Equation (NLE) theory and its elastically collective generalization [elastically collective nonlinear Langevin equation (ECNLE) theory] of activated dynamics in bulk spherical particle liquids to address the influence of random particle pinning on structural relaxation. The simplest neutral confinement model is analyzed for hard spheres where there is no change of the equilibrium pair structure upon particle pinning. As the pinned fraction grows, cage scale dynamical constraints are intensified in a manner that increases with density. This results in the mobile particles becoming more transiently localized, with increases of the jump distance, cage scale barrier, and NLE theory mean hopping time; subtle changes of the dynamic shear modulus are predicted. The results are contrasted with recent simulations. Similarities in relaxation behavior are identified in the dynamic precursor regime, including a roughly exponential, or weakly supra-exponential, growth of the alpha time with pinning fraction and a reduction of dynamic fragility. However, the increase of the alpha time with pinning predicted by the local NLE theory is too small and severely so at very high volume fractions. The strong deviations are argued to be due to the longer range collective elasticity aspect of the problem which is expected to be modified by random pinning in a complex manner. A qualitative physical scenario is offered for how the three distinct aspects that quantify the elastic barrier may change with pinning. ECNLE theory calculations of the alpha time are then presented based on the simplest effective-medium-like treatment for how random pinning modifies the elastic barrier. The results appear to be consistent with most, but not all, trends seen in recent simulations. Key open problems are discussed with regard to both theory and simulation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multitask methods for predicting molecular properties from heterogeneous data

Data generation remains a bottleneck in training surrogate models to predict molecular properties. We demonstrate that multitask Gaussian process regression overcomes this limitation by leveraging both expensive and cheap data sources. In particular, we consider training sets constructed from coupled-cluster (CC) and density functional theory (DFT) data. We report that multitask surrogates can predict at CC-level accuracy with a reduction in data generation cost by over an order of magnitude. Of note, our approach allows the training set to include DFT data generated by a heterogeneous mix of exchange–correlation functionals without imposing any artificial hierarchy on functional accuracy. More generally, the multitask framework can accommodate a wider range of training set structures—including the full disparity between the different levels of fidelity—than existing kernel approaches based on Δ-learning although we show that the accuracy of the two approaches can be similar. Consequently, multitask regression can be a tool for reducing data generation costs even further by opportunistically exploiting existing data sources.

Chemistry↗