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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 433 records · Page 24

Physics-informed machine learning exploration of Na storage mechanisms in disordered carbon

Sodium-ion batteries are a cost-effective, sustainable alternative to lithium-ion systems for large-scale energy storage. However, optimizing sodium storage in carbon-based anodes with microstructural complexity and atomic disorder remains a major challenge. The intrinsic inhomogeneity of these materials produces diverse local environments, making it difficult for conventional methods to predict and control ion dynamics. Hard carbon (HC) anodes, composed of ranges of ordered-to-disordered graphitic and amorphous nanodomains, offer tunable ion storage and rate capacity, yet rationale design remains a challenge due to poorly understood correlation between local atomic feature and ion transport mechanism. Here, to address this challenge, we introduce a data-driven framework that integrates validated machine-learned interatomic potentials, large-scale molecular dynamics simulations, and machine learning to elucidate sodium transport mechanisms as a function of carbon and sodium loading densities. By computing per-ion structural descriptors and applying unsupervised learning, we identify distinct diffusion modes governed by microscopic features. Supervised analysis and correlation mapping then establish quantitative links between these transport regimes and processing variables such as bulk carbon density and sodium content. This physics-informed approach establishes quantitative structure–transport relationships and offers actionable design principles for engineering high-performance HC anodes.

Data-driven framework↗

Sculpting 2D Crystals via Membrane Contractions before and during Solidification

When phospholipids crystallize within the otherwise fluid membranes of giant unilamellar vesicles, the resulting molecularly thin “2D” solids exhibit great variety in their morphology evolution. For example, within membranes containing moderate amounts of the crystallizing component, crystals grow with a fixed morphology depending on vesicle size. Conversely for membranes containing large amounts of the crystallizing species, we find small compact crystals on vesicles of all sizes. However, on large vesicles, growing crystals sprout flower petals that lengthen progressively. These behaviors result from two combined mechanisms: first, like other 2D solids, the shear rigidity of phospholipid crystals renders them intolerant to morphologies with nonzero Gaussian curvature. As a result and especially at elevated membrane tension, the cost of bending elasticity is reduced at the expense of line energy by the formation of flowers as opposed to compact crystals. Second, the composition-dependent tension rise during cooling relaxes via water permeation of the membrane with a time constant scaling as R2. The amount of crystal formed for a small decrease in temperature determines this composition-dependent increase in stress from thermal contractions versus solidification. Surface Evolver computations were motivated using the predicted tension evolution to develop a processing space that maps to experimental observations for initial and growing crystal morphology. Important variable groups are identified, including a scaled ratio of bending to line energy, a vesicle-size-independent group for membrane contractions, and a time constant for stress relaxation. Though processing stresses ultimately relax, the crystal morphology persists well beyond the processing window.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bounded state variables and the calculus of variations

An optimal control problem with bounded state variables is transformed into a Lagrange problem by means of differentiable mappings which take some Euclidean space onto the control and state regions. Whereas all such mappings lead to a Lagrange problem, it is shown that only those which are defined as acceptable pairs of transformations are suitable in the sense that solutions to the transformed Lagrange problem will lead to solutions to the original bounded state problem and vice versa. In particular, an acceptable pair of transformations is exhibited for the case when the control and state regions are right parallelepipeds. Finally, a description of the necessary conditions for the bounded state problem which were obtained by this method is given.

Hanafy, L. M.↗

Roughness of the marine geoid from Seasat altimetry

The geographical variability of short wavelength geoid power spectra (geoid roughness) has been mapped for the world's oceans between latitudes 72 deg N and 72 deg S. A spectral analysis of Seasat altimeter data, reduced to sea surface heights, has been performed at 2-min intervals for 15 consecutive days of the 3-day repeat orbit. The geoid roughness represented by these spectra for wavelengths shorter than about 220 km is separated from the total sea height variance and is displayed in the form of a global contour map. The global average geoid roughness is 32 cm RMS, varying from a high in excess of 2 m RMS near deep ocean trenches to a low of 2 cm RMS in the southeast Pacific near the east Pacific rise. This average value agrees well with previous estimates based on gravimetry and GEOS 3 altimetry. In general, the smoothest areas in the marine geoid overlie relatively young sea floor adjacent mid-ocean spreading centers, where even short wavelength topographic variations tend to be isostatically compensated.

Brown, R. D.↗

On the geographical correlation of orbit error

The orbit accuracies needed to support the global crustal dynamics project and recent satellite altimeter missions have placed unique demands on the data analysis and orbit analysis systems. These demands include accurate and well distributed observations, improved computational techniques and substantial enhancements in the force models which represent the satellite's motion. For example, the satellite altimeter mission (TOPEX), whose objectives will be: (1) to measure the time variable ocean surface topography, and (2) to demonstrate the ability to map the general ocean circulation, requires that the radial component of the satellite's orbit be known with an rms accuracy of 13 cm for the three year mission lifetime. The primary force model uncertainty which limits the contemporary orbit computation accuracy is the inaccuracy in the values assigned to the spherical harmonic coefficients used to model the Earth's gravity field.

Tapley, B. D.↗

NASA applications project in Miami County, Indiana

The study site selection is intended to serve all of the different research areas within the project, i.e., soil conditions, soil management, etc. There are seven major soil associations or soils formed on similar landscapes in the Miami Co., and over 38 soil series that were mapped. Soil sampling was conducted in some sites because of its variability in soils and cover types, variable topography, and presence of erosion problems. Results from analysis of these soil data is presented.

Fernandez, R. Norberto↗

Object-Oriented Control System Design Using On-Line Training of Artificial Neural Networks

This report deals with the object-oriented model development of a neuro-controller design for permanent magnet (PM) dc motor drives. The system under study is described as a collection of interacting objects. Each object module describes the object behaviors, called methods. The characteristics of the object are included in its variables. The knowledge of the object exists within its variables, and the performance is determined by its methods. This structure maps well to the real world objects that comprise the system being modeled. A dynamic learning architecture that possesses the capabilities of simultaneous on-line identification and control is incorporated to enforce constraints on connections and control the dynamics of the motor. The control action is implemented "on-line", in "real time" in such a way that the predicted trajectory follows a specified reference model. A design example of controlling a PM dc motor drive on-line shows the effectiveness of the design tool. This will therefore be very useful in aerospace applications. It is expected to provide an innovative and noval software model for the rocket engine numerical simulator executive.

Rubaai, Ahmed↗

Remote Sensing of Tropospheric Pollution from Space

We review the progress of tropospheric trace gas observations and address the need for additional measurement capabilities as recommended by the National Academy of Science (NAS, 2007). Tropospheric measurements from current and earlier instruments show pollution in the Northern Hemisphere as a result of fossil fuel burning and a strong seasonal dependence with the largest amounts of photochemically-generated ozone in summer. At low latitudes, where photon flux is stronger throughout the year, trace gas concentrations are driven by the abundance of the emissions, where the largest source, biomass burning, is readily seen in carbon monoxide measurements, but lightning and biogenic trace gases may also contribute to trace gas variability. Although substantive progress has been achieved in seasonal and global mapping of a few tropospheric trace gases, satellite trace-gas observations with considerably better temporal and spatial resolution are essential to forecasting air quality at scales required by policy-makers. The concurrent use of atmospheric composition measurements for both scientific and operational purposes is a new paradigm for the atmospheric chemistry community. The examples presented illustrate both the promise and challenge of merging satellite information with in situ observations in state-of-the-art data assimilation models.

Fishman, Jack↗

Conceptual Design of a Two Spool Compressor for the NASA Large Civil Tilt Rotor Engine

This paper focuses on the conceptual design of a two spool compressor for the NASA Large Civil Tilt Rotor engine, which has a design-point pressure ratio goal of 30:1 and an inlet weight flow of 30.0 lbm/sec. The compressor notional design requirements of pressure ratio and low-pressure compressor (LPC) and high pressure ratio compressor (HPC) work split were based on a previous engine system study to meet the mission requirements of the NASA Subsonic Rotary Wing Projects Large Civil Tilt Rotor vehicle concept. Three mean line compressor design and flow analysis codes were utilized for the conceptual design of a two-spool compressor configuration. This study assesses the technical challenges of design for various compressor configuration options to meet the given engine cycle results. In the process of sizing, the technical challenges of the compressor became apparent as the aerodynamics were taken into consideration. Mechanical constraints were considered in the study such as maximum rotor tip speeds and conceptual sizing of rotor disks and shafts. The rotor clearance-to-span ratio in the last stage of the LPC is 1.5% and in the last stage of the HPC is 2.8%. Four different configurations to meet the HPC requirements were studied, ranging from a single stage centrifugal, two axi-centrifugals, and all axial stages. Challenges of the HPC design include the high temperature (1,560deg R) at the exit which could limit the maximum allowable peripheral tip speed for centrifugals, and is dependent on material selection. The mean line design also resulted in the definition of the flow path geometry of the axial and centrifugal compressor stages, rotor and stator vane angles, velocity components, and flow conditions at the leading and trailing edges of each blade row at the hub, mean and tip. A mean line compressor analysis code was used to estimate the compressor performance maps at off-design speeds and to determine the required variable geometry reset schedules of the inlet guide vane and variable stators that would result in the transonic stages being aerodynamically matched with high efficiency and acceptable stall margins based on user specified maximum levels of rotor diffusion factor and relative velocity ratio.

Veres, Joseph P.↗

Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

remote sensing↗

Remote sensing of land use and water quality relationships - Wisconsin shore, Lake Michigan

This investigation assessed the utility of remote sensing techniques in the study of land use-water quality relationships in an east central Wisconsin test area. The following types of aerial imagery were evaluated: high altitude (60,000 ft) color, color infrared, multispectral black and white, and thermal; low altitude (less than 5000 ft) color infrared, multispectral black and white, thermal, and passive microwave. A non-imaging hand-held four-band radiometer was evaluated for utility in providing data on suspended sediment concentrations. Land use analysis includes the development of mapping and quantification methods to obtain baseline data for comparison to water quality variables. Suspended sediment loads in streams, determined from water samples, were related to land use differences and soil types in three major watersheds. A multiple correlation coefficient R of 0.85 was obtained for the relationship between the 0.6-0.7 micrometer incident and reflected radiation data from the hand-held radiometer and concurrent ground measurements of suspended solids in streams. Applications of the methods and baseline data developed in this investigation include: mapping and quantification of land use; input to watershed runoff models; estimation of effects of land use changes on stream sedimentation; and remote sensing of suspended sediment content of streams. High altitude color infrared imagery was found to be the most acceptable remote sensing technique for the mapping and measurement of land use types.

Haugen, R. K.↗

Interannual and Seasonal Variability of Biomass Burning Emissions Constrained by Satellite Observations

We present a methodology for estimating the seasonal and interannual variation of biomass burning designed for use in global chemical transport models. The average seasonal variation is estimated from 4 years of fire-count data from the Along Track Scanning Radiometer (ATSR) and 1-2 years of similar data from the Advanced Very High Resolution Radiometer (AVHRR) World Fire Atlases. We use the Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) data product as a surrogate to estimate interannual variability in biomass burning for six regions: Southeast Asia, Indonesia and Malaysia, Brazil, Central America and Mexico, Canada and Alaska, and Asiatic Russia. The AI data set is available from 1979 to the present with an interruption in satellite observations from mid-1993 to mid-1996; this data gap is filled where possible with estimates of area burned from the literature for different regions. Between August 1996 and July 2000, the ATSR fire-counts are used to provide specific locations of emissions and a record of interannual variability throughout the world. We use our methodology to estimate mean seasonal and interannual variations for emissions of carbon monoxide from biomass burning, and we find that no trend is apparent in these emissions over the last two decades, but that there is significant interannual variability.

Duncan, Bryan N.↗

Formation, distribution and variability in snow cover on the Asian territory of the USSR

A description is given of maps compiled for annual and average multiple-year water reserves. The annual and average multiple-year maximum snow cover height for winter, extreme values of maximum snow reserves, and the average height and snow reserves at the end of each decade are shown. These maps were made for the entire Asian territory of the USSR, excluding Central Asia, Kamchatka Peninsula, and the Sakhalin Islands.

Pupkov, V. N.↗

Space Telescope and Optical Reverberation Mapping Project. VI. Reverberating Disk Models for NGS 5548

We conduct a multi-wavelength continuum variability study of the Seyfert 1 galaxy NGC 5548 to investigate the temperature structure of its accretion disk. The 19 overlapping continuum light curves (1158 Angstrom to 9157 Angstrom) combine simultaneous Hubble Space Telescope, Swift, and ground-based observations over a 180 day period from 2014 January to July. Light-curve variability is interpreted as the reverberation response of the accretion disk to irradiation by a central time-varying point source. Our model yields the disk inclination i = 36deg +/- 10deg, temperature T(sub 1) = (44+/-6) times 10 (exp 3)K at 1 light day from the black hole, and a temperature radius slope (T proportional to r (exp -alpha)) of alpha = 0.99 +/- 0.03. We also infer the driving light curve and find that it correlates poorly with both the hard and soft X-ray light curves, suggesting that the X-rays alone may not drive the ultraviolet and optical variability over the observing period. We also decompose the light curves into bright, faint, and mean accretion-disk spectra. These spectra lie below that expected for a standard blackbody accretion disk accreting at L/L(sub Edd) = 0.1.

accretion↗

The Soil Moisture Active and Passive Mission (SMAP): Science and Applications

The Soil Moisture Active and Passive mission (SMAP) will provide global maps of soil moisture content and surface freeze/thaw state. Global measurements of these variables are critical for terrestrial water and carbon cycle applications. The SMAP observatory consists of two multipolarization L-band sensors, a radar and radiometer, that share a deployable-mesh reflector antenna. The combined observations from the two sensors will allow accurate estimation of soil moisture at hydrometeorological (10 km) and hydroclimatological (40 km) spatial scales. The rotating antenna configuration provides conical scans of the Earth surface at a constant look angle. The wide-swath (1000 km) measurements will allow global mapping of soil moisture and its freeze/thaw state with 2-3 days revisit. Freeze/thaw in boreal latitudes will be mapped using the radar at 3 km resolution with 1-2 days revisit. The synergy of active and passive observations enables measurements of soil moisture and freeze/thaw state with unprecedented resolution, sensitivity, area coverage and revisit.

radiometry↗

Interannual variability study of the earth radiation budget from Nimbus 7 monthly data

The broadband data set on the earth radiation budget recorded by Nimbus-7 instrumentation from 1978-84 is summarized, along with the results of several statistical evaluations. The emitted longwave radiation (W/sq m), albedo and net radiation (W/sq m) are tabulated in terms of yearly means and summer and winter departures from those means. Global maps are also provided for 6-yr averaged values of the same parameters. The largest variabilities were observed over the equatorial Pacific Ocean, the Indian Ocean, and Indonesia, indicating the extent of annual variations of the size of the Intertropical Convergence Zone.

Smith, L. D.↗

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

How Snow Aggregate Ellipsoid Shape and Orientation Variability Affects Fall Speed and Self-Aggregation Rates

Snow aggregate shapes and orientations have long been known to exhibit substantial variability. Despite this observed variability, most weather and climate prediction models use fixed power-law functions that deterministically map particle size to mass and fall speed. As such, integrated quantities like precipitation and self-aggregation rates currently ignore nonlinear effects resulting from variation in shape and orientation for aggregates of the same size. This study therefore develops an analytic framework that couples an empirically based bivariate distribution of ellipsoid shapes to classical hydrodynamic theory so as to capture an appropriate dispersion of masses, projected areas, and fall speeds for an assumed size distribution. For a fixed aggregate size, shape variations produce approximately ±0.13 m s -1 standard deviation of fall speed which increases the mass flux fall speed dispersion by more than 100% over traditional microphysics models. This increased fall speed dispersion results predominantly from shape-induced mass dispersion whereas orientation and drag dispersion play a lesser role. Shape variations can increase mass- and reflectivity-weighted fall speeds by up to 60% of traditional models whereas self-aggregation rates can increase by a factor of 100 for very small slope parameters. This implies that aggregate shape variations effectively forestall the theorized onset of fall speed distribution narrowing and subsequent quenching of the aggregation process. As a result, it is likely that secondary ice formation is necessary to prevent an ever decreasing slope parameter. The mathematical theory presented in this study is used to develop simple correction factors for snow forecast and climate models.

54 ENVIRONMENTAL SCIENCES↗