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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Land Water Storage within the Congo Basin Inferred from GRACE Satellite Gravity Data

GRACE satellite gravity data is used to estimate terrestrial (surface plus ground) water storage within the Congo Basin in Africa for the period of April, 2002 - May, 2006. These estimates exhibit significant seasonal (30 +/- 6 mm of equivalent water thickness) and long-term trends, the latter yielding a total loss of approximately 280 km(exp 3) of water over the 50-month span of data. We also combine GRACE and precipitation data set (CMAP, TRMM) to explore the relative contributions of the source term to the seasonal hydrological balance within the Congo Basin. We find that the seasonal water storage tends to saturate for anomalies greater than 30-44 mm of equivalent water thickness. Furthermore, precipitation contributed roughly three times the peak water storage after anomalously rainy seasons, in early 2003 and 2005, implying an approximately 60-70% loss from runoff and evapotranspiration. Finally, a comparison of residual land water storage (monthly estimates minus best-fitting trends) in the Congo and Amazon Basins shows an anticorrelation, in agreement with the 'see-saw' variability inferred by others from runoff data.

Crowley, John W.↗
DOE OSTI2021

A Privacy-Preserving Distributed Control of Optimal Power Flow

Here, we consider a distributed optimal power flow formulated as an optimization problem that maximizes a nondifferentiable concave function. Solving such a problem by the existing distributed algorithms can lead to data privacy issues because the solution information exchanged within the algorithms can be utilized by an adversary to infer the data. To preserve data privacy, in this paper we propose a differentially private projected subgradient (DP-PS) algorithm that includes a solution encryption step. We show that a sequence generated by DP-PS converges in expectation, in probability, and with probability 1. Moreover, we show that the rate of convergence in expectation is affected by a target privacy level of DP-PS chosen by the user. We conduct numerical experiments that demonstrate the convergence and data privacy preservation of DP-PS.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1990

Hydrogen constituents of the mesosphere inferred from positive ions - H2O, CH4, H2CO, H2O2, and HCN

The concentrations in the mesosphere of H2O, CH4, H2CO, H2O2, and HCN were inferred from data on positive ion compositions, obtained from one mid-latitude and four high-latitude rocket flights. The inferred concentrations were found to agree only partially with the ground-based microwave measurements and/or model prediction by Garcia and Solomon (1985). The CH4 concentration was found to vary between 70 and 4 ppb in daytime and 900 and 100 ppbv at night, respectively. Unexpectedly high H2CO concentrations were obtained, with H2CO/H2O ratios between 0.0006 and 0.1, and a mean HCN volume mixing ratio of 6 x 10 to the -10th was inferred.

Kopp, E.↗
NASA NTRS1993

Nitrogen isotopic compositions of iron meteorites

Iron meteorites analyzed in this study have nitrogen concentrations 70 microg/g or less and delta N-15 from -90 to +150 percent. Although the iron meteorites have a large range of delta N-15, most have values more negative than -50 percent. The nitrogen isotopic compositions were established by cosmochemical processes and were little modified by fractional crystallization or other chemical processes within the parent bodies. The data do not suggest the existence of a well-mixed solar nebular reservoir for nitrogen, as was already inferred from data from stony meteorites. The range of greater than 1100 percent observed for delta N-15 in bulk meteorites is probably too large to be accounted for by physical and chemical mass-dependent fractionation processes in the solar nebula, and thus reflects nebular inhomogeneities of nucleosynthetic origin.

Prombo, Carol A.↗
NASA NTRS2011

Use of Remote Sensing/Geographical Information Systems (RS/GIS) to Identify the Distributional Limits of Soil-Transmitted Helminths (STHs) and Their Association to Prevalence of Intestinal Infection in School-Age Children in Four Rural Communities in Boaco, Nicaragua

STHs can infect all members of a population but school-age children living in poverty are at greater risk. Infection can be controlled with drug treatment, health education and sanitation. Helminth control programs often lack resources and reliable information to identify areas of highest risk to guide interventions and to monitor progress. Objectives: To use RS/GIS to identify the environmental variables that correlate with the ecology of STHs and with the prevalence of STH infections. Methods: Geo-referenced in situ prevalence data will be overlaid over an ecological map derived from the RS environmental data using ESRI s ArcGIS 9.3. Prevalence data and RS environmental data matching at the same geographical location will be analyzed for correlation and those RS environmental variables that better correlate with prevalence data will be included in a multivariate regression model. Temperature, vegetation, and distance to bodies of water will be inferred using data from the Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, and Thematic Mapper (TM) and Enhance Thematic Mapper Plus (ETM+) satellite sensors onboard Landsat 5 and Landsat 7 respectively. Elevation will be estimated with data from The Shuttle Radar Topography Mission (SRTM). Prevalence and intensity of infections will be determined by parasitological survey (Kato Katz) of children enrolled in rural schools in Boaco, Nicaragua, in the communities of El Roblar, Cumaica Norte, Malacatoya 1, and Malacatoya 2). Expected Results: Associations between RS environmental data and prevalence in situ data will be determined and their applications to public health will be discussed. Discussion/Conclusions: The use of RS/GIS data to predict the prevalence of STH infections could be useful for helminth control programs, providing improved geographical guidance of interventions while increasing cost-effectiveness. Learning Objectives: (1) To identify the RS environmental variables that can help predict the prevalence of STH infections. (2) To understand potential applications of RS/GIS to national helminth control programs. (3) To asses the applicability of RS/GIS to control STH infections.

Moreno, Max J.↗
NASA NTRS1990

Quasi-coherent structures in the turbulent boundary layer. I - Status report on a community-wide summary of the data

A review is presented of the approach, motivation and early results of a reevaluation of the knowledge collected by the research community during thirty years of research on the structure of turbulent boundary layers. Four distinctions or criteria concerning the need to improve the practices in this field are discussed: data versus inferences, possible versus actual versus significant events, one structure versus many, and one or two flows versus the totality of data. Attention given to the known quasi-coherent structures show that three factors significantly reduce the information available from laboratory data as a basis for forming a complete model of the quasi-coherent structure in the turbulent boundary layer: (1) the necessity to ensemble average probe output with resulting loss of phase information, (2) the inability to see more than one or two of the various types of structures simultaneously, and (3) the inability to see the spatial relations between the various quasi-coherent structures resulting from (1) and (2).

Kline, S. J.↗
NASA NTRSDate not supplied

Application of Satellite Gravimetry for Water Resources Monitoring

Satellite gravimetry is unique in its ability to measure, from space, mass changes in the atmosphere and on and below Earth’s surface. After accounting for atmosphere and ocean mass circulations, scientists use these measurements to estimate changes in terrestrial water storage (TWS), which comprises groundwater, soil moisture, surface waters, snow, and ice. Monthly TWS data from the GRACE and GRACE-FO missions have been available since 2002. This presentation will discuss the application of these data for inferring and attributing regional trends in TWS around the world. It will also describe how the assimilation of GRACE and GRACEFO data into a land surface model enables monitoring and forecasting droughts and flood vulnerability.

Matthew Rodell↗
DOE OSTI2026

AIF for Vis (Active Inference for simulating human interpretation of data visualization) [SWR-26-084]

AIF for Vis contains the Active Inference models and analysis scripts used to study a simple visualization-interpretation task: estimating the average value of two bars in a bar chart. The work is a proof of concept for translating hypothesized cognitive strategies into executable, inspectable process models. We implement two idealized strategies inspired by dual-process accounts of visualization-aided decision making: *Fast model: a compressed, heuristic strategy that estimates the visual midpoint of the two bars and maintains a single belief over their average. *Slow model: a sequential, analytic strategy that estimates the two bar heights separately and maintains them in working memory before computing an average. Both models use a common Active-Inference-inspired framework for sequential perception, belief updating, action selection, and reporting. Their different internal representations produce distinct predicted vulnerabilities: *the Fast model is more susceptible to tick-salience bias; *the Slow model is more susceptible to working-memory decay. The repository includes the model implementations, scripts used for the experiments reported in the paper, precomputed trial-level results, and plotting scripts.

Goldwyn, Harrison [National Laboratory of the Rock↗
DOE OSTI2021

Scalable statistical inference of photometric redshift via data subsampling

Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models are often preferred over their statistical counterparts for bigger problems. But full probabilistic statistical models often outperform other models in quantifying uncertainties associated with model predictions. We develop a data-driven statistical modeling framework that combines the uncertainties from an ensemble of statistical models learned on smaller subsets of data carefully chosen to account for imbalances in the input space. We demonstrate this method on a photometric redshift estimation problem in cosmology, which seeks to infer a distribution of the redshift—the stretching effect in observing the light of far-away galaxies—given multivariate color information observed for an object in the sky. Our proposed method performs balanced partitioning, graph-based data subsampling across the partitions, and training of an ensemble of Gaussian process models.

data subsampling↗
NASA NTRS2011

Analysis of Association Between Remotely Sensed (RS) Data and Soil Transmitted Helminthes Infection Using Geographical Information Systems (GIS): Boaco, Nicaragua

Soil-transmitted helminths are intestinal nematodes that can infect all members of a population but specially school-age children living in poverty. Infection can be significantly reversed with anthelmintic drug treatments and sanitation improvement. Implementation of effective public health programs requires reliable and updated information to identify areas at higher risk and to calculate amount of drug required. Geo-referenced in situ prevalence data will be overlaid over an ecological map derived from RS data using ARC Map 9.3 (ESRI). Prevalence data and RS data matching at the same geographical location will be analyzed for correlation and those variables from RS data that better correlate with prevalence will be included in a multivariate regression model. Temperature, vegetation, and distance to bodies of water will be inferred using data from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat TM and ETM+. Elevation will be estimated with data from The Shuttle Radar Topography Mission (SRTM). Prevalence and intensity of infections are determined by parasitological survey (Kato Katz) of children enrolled in rural schools in Boaco, Nicaragua, in the communities of El Roblar, Cumaica Norte, Malacatoya 1, and Malacatoya 2). This study will demonstrate the importance of an integrated GIS/RS approach to define sampling clusters without the need for any ground-based survey. Such information is invaluable to identify areas of high risk and to geographically target control programs that maximize cost-effectiveness and sanitation efforts.

MorenoMadrinan, Max J.↗
NASA NTRS1980

Inversion of multiwavelength radiometer measurements by three-dimensional filtering

Remote sensing data from satellites typically have three dimensions: scan position, spacecraft position, and wavelength. Inversion of the radiometric data to infer geophysical parameters is a filtering problem in which the dimension of wavelength (or channel number) is transformed into a dimension of geophysical parameters, and the most general solution is a three-dimensional filter. Linear filters have the advantages of computational speed and easily described transfer functions; but often the measurements are nonlinear functions of the parameters to be inferred. To the extent that the nonlinear inversion problem is overdetermined, it can be modeled by a critically determined linear problem. As an example, inversion of Scanning Multichannel Microwave Radiometer (SMMR) data by means of a three-dimensional Wiener Filter is described. Atmospheric water vapor content, rain liquid water content, surface wind speed and surface temperature are the parameters inferred from the measurements. Nonprecipitating liquid water and water vapor scale height are also modeled but not retrieved. The a priori statistics on which the filter is trained have the effect of governing the selection of a trade-off point of noise as a function of resolution (in all three retrieval dimensions).

Rosenkranz, P. W.↗
NASA NTRS2008

Statistical Estimation of Orbital Debris Populations with a Spectrum of Object Size

Orbital debris is a real concern for the safe operations of satellites. In general, the hazard of debris impact is a function of the size and spatial distributions of the debris populations. To describe and characterize the debris environment as reliably as possible, the current NASA Orbital Debris Engineering Model (ORDEM2000) is being upgraded to a new version based on new and better quality data. The data-driven ORDEM model covers a wide range of object sizes from 10 microns to greater than 1 meter. This paper reviews the statistical process for the estimation of the debris populations in the new ORDEM upgrade, and discusses the representation of large-size (greater than or equal to 1 m and greater than or equal to 10 cm) populations by SSN catalog objects and the validation of the statistical approach. Also, it presents results for the populations with sizes of greater than or equal to 3.3 cm, greater than or equal to 1 cm, greater than or equal to 100 micrometers, and greater than or equal to 10 micrometers. The orbital debris populations used in the new version of ORDEM are inferred from data based upon appropriate reference (or benchmark) populations instead of the binning of the multi-dimensional orbital-element space. This paper describes all of the major steps used in the population-inference procedure for each size-range. Detailed discussions on data analysis, parameter definition, the correlation between parameters and data, and uncertainty assessment are included.

Xu, Y. -l↗
NASA NTRS2008

Combined Impedance Probe and Langmuir Probe Studies of the Low-Latitude E Region

The EQUIS-2 sounding rocket and radar campaign, launched from Kwajalein Atoll in 2004, included a mission to study low-latitude irregularities and electrodynamics, led by NASA GSFC. This mission included two instrumented rockets launched into the nighttime E region (apogee near 120 km), which included comprehensive electrodynamics and neutral density instrumentation. These rockets carried the first of a new generation of impedance probes, that utilize a wide-band drive signal to simultaneously measure the impedance of an antenna in a plasma as a function of frequency from 7 kEIz to 4 MHz. at a rapid cadence. This technique promises to permit true plasma spectroscopy, and resulted in the identification of multiple plasma resonances and accurate measurements of the plasma density, even in the low density nighttime E region. We present analyses of the technique and resulting spectra, and show how these data may be combined with fixed-bias Langmuir Probe data to infer the temperature structure of the E region as well as providing accurate absolute calibrations for the very high time resolution fixed-bias probe data. The data is shown to agree well with data from ionosonde, the ALTAIR radar, and the Peruvian beacon experiment.

Rowland, D. E.↗
DOE OSTI2020

Towards the spatial resolution of metalloprotein charge states by detailed modeling of XFEL crystallographic diffraction

Oxidation states of individual metal atoms within a metalloprotein can be assigned by examining X-ray absorption edges, which shift to higher energy for progressively more positive valence numbers. Indeed, X-ray crystallography is well suited for such a measurement, owing to its ability to spatially resolve the scattering contributions of individual metal atoms that have distinct electronic environments contributing to protein function. However, as the magnitude of the shift is quite small, about +2 eV per valence state for iron, it has only been possible to measure the effect when performed with monochromated X-ray sources at synchrotron facilities with energy resolutions in the range 2–3 × 10 −4 (Δ E / E ). This paper tests whether X-ray free-electron laser (XFEL) pulses, which have a broader bandpass (Δ E / E = 3 × 10 −3 ) when used without a monochromator, might also be useful for such studies. The program nanoBragg is used to simulate serial femtosecond crystallography (SFX) diffraction images with sufficient granularity to model the XFEL spectrum, the crystal mosaicity and the wavelength-dependent anomalous scattering factors contributed by two differently charged iron centers in the 110-amino-acid protein, ferredoxin. Bayesian methods are then used to deduce, from the simulated data, the most likely X-ray absorption curves for each metal atom in the protein, which agree well with the curves chosen for the simulation. The data analysis relies critically on the ability to measure the incident spectrum for each pulse, and also on the nanoBragg simulator to predict the size, shape and intensity profile of Bragg spots based on an underlying physical model that includes the absorption curves, which are then modified to produce the best agreement with the simulated data. This inference methodology potentially enables the use of SFX diffraction for the study of metalloenzyme mechanisms and, in general, offers a more detailed approach to Bragg spot data reduction.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1976

DABI: A data base for image analysis with nondeterministic inference capability

A description is given of the data base used in the perception subsystem of the Mars robot vehicle prototype being implemented at the Jet Propulsion Laboratory. This data base contains two types of information. The first is generic (uninstantiated, abstract) information that specifies the general rules of perception of objects in the expected environments. The second kind of information is a specific (instantiated) description of a structure, i.e., the properties and relations of objects in the specific case being analyzed. The generic knowledge can be used by the approximate reasoning subsystem to obtain information on the specific structures which is not directly measurable by the sensory instruments. Raw measurements are input either from the sensory instruments or a human operator using a CRT or a TTY.

Yakimovsky, Y.↗
DOE OSTI2022

A Review of Bayesian Networks for Spatial Data

We report Bayesian networks are a popular class of multivariate probabilistic models as they allow for the translation of prior beliefs about conditional dependencies between variables to be easily encoded into their model structure. Due to their widespread usage, they are often applied to spatial data for inferring properties of the systems under study and also generating predictions for how these systems may behave in the future. We review published research on methodologies for representing spatial data with Bayesian networks and also summarize the application areas for which Bayesian networks are employed in the modeling of spatial data. We find that a wide variety of perspectives are taken, including a GIS-centric focus on efficiently generating geospatial predictions, a statistical focus on rigorously constructing graphical models controlling for spatial correlation, as well as a range of problem-specific heuristics for mitigating the effects of spatial correlation and dependency arising in spatial data analysis. Special attention is also paid to potential future directions for integration of Bayesian networks with spatial processes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

Block rotation by strike-slip faulting - Structural and paleomagnetic evidence

The magnitude and sense of block rotations depicted from such structural data as fault spacing and slip are noted to agree with values obtained from independent paleomagnetic determinations. The agreement between paleomagnetic rotation data and those inferred from offset and spacing data in northern Israel is excellent, suggesting that the faults and intervening blocks were rotated with progressive deformation along the levant transform. It is suggested that the rotation of blocks and the strike-slip displacement are two qualitative and quantitative contemporaneous aspects of a single deformation process.

Ron, H.↗
NASA NTRS1992

Moessbauer Spectroscopy for Lunar Resource Assessment: Measurement of Mineralogy and Soil Maturity

First-order assessment of lunar soil as a resource includes measurement of its mineralogy and maturity. Soils in which the mineral ilmenite is present in high concentrations are desirable feedstock for the production of oxygen at a lunar base. The maturity of lunar soils is a measure of their relative residence time in the upper 1 mm of the lunar surface. Increasing maturity implies increasing load of solar wind species (e.g., N, H, and He-3), decreasing mean grain size, and increasing glass content. All these physicochemical properties that vary in a regular way with maturity are important parameters for assessing lunar soil as a resource. For example, He-3 can be extracted and potentially used for nuclear fusion. A commonly used index for lunar soil maturity is I(sub s)/FeO, which is the concentration of fine-grained metal determined by ferromagnetic resonance (I(sub s)) normalized to the total iron content (as FeO). I(sub s)/FeO has been measured for virtually every soil returned by the Apollo and Luna missions to the Moon. Because the technique is sensitive to both oxidation state and mineralogy, iron Moessbauer spectroscopy (FeMS) is a viable technique for in situ lunar resource assessment. Its utility for mineralogy is apparent from examination of published FeMS data for lunar samples. From the data published, it can be inferred that FeMS data can also be used to determine soil maturity. The use of FeMS to determine mineralogy and maturity and progress on development of a FeMS instrument for lunar surface use are discussed.

Morris, R. V.↗