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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Variable beamwidth monopulse feed for Tracking and Data Relay Satellite (TDRS)

The Tracking and Data Relay Satellite with a set of circularly-polarized, amplitude-sensing monopulse patterns suitable for acquiring and tracking user spacecraft at Ku-band (15.0 GHz) is discussed. The possibility of increasing the less than 0.4-degree half-power beamwidth of the data beam to almost 1.0 degree during the acquisition phase is predicated on the use of feeds situated in the first bright-ring of the Airy diffraction structure. A complex-vector simulation equivalent to the Kirchhoff-Kottler or Franz formulations is used to compute transmitted and received field information for a dual-reflector (Cassegrain) antenna configuration in a three-dimensional space.

Schmidt, R. F.↗
NASA NTRS1975

Vapor-modulated heat pipe report. Flight data analysis and further development of variable-conductance heat pipes

The design and testing of a heat pipe for spacecraft application is presented. The application in mind calls for heat loads up to 20 watts, a set-point temperature of 294K, and a sink that varies from -220K to nearly as high as the set-point. The overall heat pipe length is 137 cm. Two basically different mechanisms of achieving variable conductance in the pipe by vapor-flow throttling were studied. In one, the thermal resistance between the heat source and sink is due to a saturation-temperature drop corresponding to the vapor-pressure drop developed across the valve. In the other, the pressure difference across the valve induces capillary groove and wick dry out in an evaporation region, and thus results in an increased thermal resistance. This mechanism was selected for fabrication and testing. The pipe is a stainless-steel/methanol two-heat-pipe system. Results are presented and discussed. Engineering drawings and specifications of the pipe are shown.

Eninger, J. E.↗
NASA NTRS1976

Flight data analysis and further development of variable-conductance heat pipes

Continuing efforts in large gains in heat-pipe performance are reported. It was found that gas-controlled variable-conductance heat pipes can perform reliably for long periods in space and effectively provide temperature stabilization for spacecraft electronics. A solution was formulated that allows the control gas to vent through arterial heat-pipe walls, thus eliminating the problem of arterial failure under load, due to trace impurities of noncondensable gas trapped in an arterial bubble during priming. This solution functions well in zero gravity. Another solution was found that allows priming at a much lower fluid charge. A heat pipe with high capacity, with close temperature control of the heat source and independent of large variations in sink temperature was fabricated.

Enginer, J. E.↗
NASA NTRS1976

Flight data analysis and further development of variable-conductance heat pipes

The work focuses on the mathematical modeling of three critical mechanisms of heat-pipe operation: (1) the effect that excess liquid has on heat-pipe performance; (2) the calculation of the dryout limit of circumferential grooves; (3) an efficient mathematical model for the calculation of the viscous-inertial interaction in the vapor flow. These mathematical models are incorporated in the computer program GRADE II, which is described.

Eninger, J. E.↗
NASA NTRS1983

Experimental test of the variability of G using Viking lander ranging data

Results are presented from the analysis of solar-system astrometric data, notably the range data to the Viking landers on Mars. A least-squares fit of the parameters of the solar system model to these data limits a simple time variation in the effective Newtonian gravitational constant to (2 + or - 4) x 10 to the -12th/yr and a rate of drift of atomic clocks relative to the implicit clock of relativistic dynamics to (1 + or - 8) x 10 to the -12th/yr. The error limits quoted are the result of uncertainties in the masses of the asteroids.

Hellings, R. W.↗
NASA NTRS1984

Inversion of vegetation canopy reflectance models for estimating agronomic variables. III - Estimation using only canopy reflectance data as illustrated by the suits model. IV - Total inversion of the SAIL model

The possibility of estimating agronomic and spectral parameters for a vegetation canopy from the canopy reflectance (CR) data in the infrared region is investigated for a set of solar/view directions. It is shown that such an estimation is possible, in principle, for the Suits (1972) model for a homogeneous canopy. The technique is then applied to a more complex model, the SAIL (scattering by arbitrarily inclined leaves) model which explicitly includes the leaf angle distribution in the computation of the canopy reflectance. It is concluded that, given the expected accuracy of CR measurements and the accuracy of the SAIL model in representing CR in the infrared region, the agronomic parameters, leaf area index, and leaf angle distribution can be estimated fairly accurately using ancillary data on spectral parameters.

Goel, N. S.↗
NASA NTRS1986

Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth

Terrestrial climatic effects associated with solar variability have been proposed for at least a century, but could not be assessed quantitatively owing to observational uncertainities in solar flux variations. Measurements from 1980 to 1984 by the Active Cavity Radiometer Irradiance Monitor (ACRIM), capable of resolving fluctuations above the sensible atmosphere less than 0.1% of the solar constant, permit direct albeit preliminary assessments of solar forcing effects on global temperatures during this period. The global temperature response to ACRIM-measured fluctuations was computed from 1980 to 1985 using the NYU transient climate model including thermal inertia effects of the world ocean; and compared the results with observations of recent temperature trends. Monthly mean ACRIM-driven global surface temperature fluctuations computed with the climate model are an order of magnitude smaller, of order 0.01 C. In constrast, global mean surface temperature observations indicate an approx. 0.1 C increase during this period. Solar variability is therefore likely to have been a minor factor in global climate change during this period compared with variations in atmospheric albedo, greenhouse gases and internal self-inducedoscillations. It was not possible to extend the applicability of the measured flux variations to longer periods since a possible correlation of luminosity with solar annual activity is not supported by statistical analysis. The continuous monitoring of solar flux by satellite-based instruments over timescales of 20 years or more comparable to timescales for thermal relaxation of the oceans and of the solar cycle itself is needed to resolve the question of long-term solar variation effects on climate.

Hoffert, M. I.↗
NASA NTRS1988

Analysis of IUE data on V426 Ophiuchi - Outburst and orbital variability

Time-resolved IUE spectra throughout two orbits of the dwarf nova V426 Oph during quiescence are presented. It is found that the visual and C IV fluxes remain relatively constant during both orbits, whereas the UV coninua and Mg II lines vary by 20-30 percent. The time scales of this variability are discussed. Analysis of other spectra at brighter optical magnitudes shows that the UV lags the optical during a probable rise to outburst, similar to the behavior of SS Cyg. The reddening of V426 Oph is determined to be E(B-V) = 0.1. The contribution of the white dwarf to the UV flux at quiescence is estimated to be 25 percent, based on the system parameters of Hessman (1988) and the period-temperature relation of Sion (1987).

Szkody, Paula↗
NASA NTRS1990

Dependence of the microwave radar cross section on ocean surface variables - Comparison of measurements and theory using data from the Frontal Air-Sea Interaction Experiment

The purpose of this investigation was to study the ability of theoretical radar cross section (RCS) models to predict the absolute magnitude of the ocean radar cross section under a wide variety of sea and atmospheric conditions. The dependence of the RCS on wind stress (as opposed to wind speed) was also studied. An extensive amount of experimental data was acquired during the Frontal Air-Sea Interaction Experiment. Measurements across an ocean front demonstrated that the vertical polarization and horizontal polarization radar cross section were more strongly dependent on wind stress than on wind magnitude. Current theoretical models for the RCS, based on stress, were tested with this data. In situations where the Bragg scattering theory does not agree with the measured radar cross section (magnitude and angle dependence), revisions are hypothesized and evaluated.

Weissman, David E.↗
NASA NTRS1990

A satellite retrieval of the shortwave heating of the atmosphere and the surface - Relationship to the general circulation, interannual climate variability, and the cryosphere

Data from several Nimbus-7 instruments and monthly averaged, multilayer delta-Eddington radiative transfer calculations are used to estimate the full vertical profile of the SW heating in the surface and the atmosphere. The noontime physical profile of clouds, water vapor, and surface albedo is used to compute a daily, monthly averaged top-of-atmosphere albedo (TOA), which was produced with noontime Nimbus-7 data, and a profile of SW heating for the atmosphere and surface. The daily, monthly averaged TOA albedo for July 1983 is compared with the ERBE daily, monthly averaged TOA albedo for July 1985. The sensitivity of the vertical SW heating profiles to the retrieval input assumptions is shown.

Charlock, Thomas P.↗
NASA NTRS2007

On the Use of Ocean Color Remote Sensing to Measure the Transport of Dissolved Organic Carbon by the Mississippi River Plume

We investigated the use of ocean color remote sensing to measure transport of dissolved organic carbon (DOC) by the Mississippi River to the Gulf of Mexico. From 2000 to 2005 we recorded surface measurements of DOC, colored dissolved organic matter (CDOM), salinity, and water-leaving radiances during five cruises to the Mississippi River Plume. These measurements were used to develop empirical relationships to derive CDOM, DOC, and salinity from monthly composites of SeaWiFS imagery collected from 1998 through 2005. We used river flow data and a two-end-member mixing model to derive DOC concentrations in the river end-member, river flow, and DOC transport using remote sensing data. We compared our remote sensing estimates of river flow and DOC transport with data collected by the United States Geological Survey (USGS) from 1998 through 2005. Our remote sensing estimates of river flow and DOC transport correlated well (r2 ~ 0.70) with the USGS data. Our remote sensing estimates and USGS field data showed low variability in DOC concentrations in the river end-member (7-11%), and high seasonal variability in river flow (~50%). Therefore, changes in river flow control the variability in DOC transport, indicating that the remote sensing estimate of river flow is the most critical element of our DOC transport measurement. We concluded that it is possible to use this method to estimate DOC transport by other large rivers if there are data on the relationship between CDOM, DOC, and salinity in the river plume.

DelCastillo, Carlos E.↗
NASA NTRS2016

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

Safe and efficient surface operations↗
NASA NTRS2021

Assessing Cyanobacterial Frequency and Abundance at Surface Waters Near Drinking Water Intakes Across the United States

This study presents the first large-scale assessment of cyanobacterial frequency and abundance of surface water near drinking water intakes across the United States. Public water systems serve drinking water to nearly 90% of the United States population. Cyanobacteria and their toxins may degrade the quality of finished drinking water and can lead to negative health consequences. Satellite imagery can serve as a cost-effective and consistent monitoring technique for surface cyanobacterial blooms in source waters and can provide drinking water treatment operators information for managing their systems. This study uses satellite imagery from the European Space Agency’s Ocean and Land Colour Instrument (OLCI) spanning June 2016 through April 2020. At 300-m spatial resolution, OLCI imagery can be used to monitor cyanobacteria in 685 drinking water sources across 285 lakes in 44 states, referred to here as resolvable drinking water sources. First, a subset of satellite data was compared to a subset of responses (n = 84) submitted as part of the U.S. Environmental Protection Agency’s fourth Unregulated Contaminant Monitoring Rule (UCMR 4). These UCMR 4 qualitative responses included visual observations of algal bloom presence and absence near drinking water intakes from March 2018 through November 2019. Overall agreement between satellite imagery and UCMR 4 qualitative responses was 94% with a Kappa coefficient of 0.70. Next, temporal frequency of cyanobacterial blooms at all resolvable drinking water sources was assessed. In 2019, bloom frequency averaged 2% and peaked at 100%, where 100% indicated a bloom was always present at the source waters when satellite imagery was available. Monthly cyanobacterial abundances were used to assess short-term trends across all resolvable drinking water sources and effect size was computed to provide insight on the number of years of data that must be obtained to increase confidence in an observed change. Generally, 2016-2020 was an insufficient time period for confidently observing changes at these source waters; on average, a decade of satellite imagery would be required for observed environmental trends to outweigh variability in the data. However, five source waters did demonstrate a sustained short-term trend, with one increasing in cyanobacterial abundance from June 2016 to April 2020 and four decreasing.

remote sensing↗
NASA NTRS1992

Observations of stationary radio sources: Coronal polar plumes?

Observations and preliminary results of polar radio sources which are often brighter than streamers are presented. The results are preliminary and an analysis is needed using a larger data set to firmly establish the properties such as time variability of these sources. Data which are not corrected for ionospheric refraction are used, thus the determination of rotational characteristics is not accurate. Thermal and/or weak nonthermal emission from polar plumes may be responsible for the polar radio sources. However, nonthermal process may be necessary to explain time variability.

Gopalswamy, Natchimuthkonar↗
DOE OSTI2025

Machine Learning Prediction of Tritium‐Helium Groundwater Ages in the Central Valley, California, USA

Abstract Groundwater ages provides insight into recharge rates, flow velocities, and vulnerability to contaminants. The ability to predict groundwater ages based on more accessible parameters via Machine Learning (ML) would advance our ability to guide sustainable management of groundwater resources. In this study, ML models were trained and tested on a large data set of tritium concentrations and tritium‐helium groundwater ages from the California Central Valley, a large groundwater basin with complex land use, irrigation, and water management practices. The ML models were trained on 63 features, including location, well construction information, landscape characteristics, and climate variables, water chemistry, and stable isotopes. The Bagging regressor method can accurately classify (F1‐score = 0.91) groundwater samples as either modern or pre‐modern whereas the accuracy of the ML prediction of continuous tritium‐helium groundwater ages is limited and explains only of the variability in this data set. In general, ML groundwater age prediction relies mostly on features related to (a) the source of groundwater recharge, (b) contaminant history, (c) aquifer materials, (d) well construction, and (e) geochemical reactions along flow paths.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Trophic classification of Tennessee Valley area reservoirs derived from LANDSAT multispectral scanner data

LANDSAT MSS data from four different dates were extracted from computer tapes using a semiautomated digital data handling and analysis system. Reservoirs were extracted from the surrounding land matrix by using a Band 7 density level slice of 3; and descriptive statistics to include mean, variance, and ratio between bands for each of the four bands were calculated. Significant correlations ( 0.80) were identified between the MSS statistics and many trophic indicators from ground truth water quality data collected at 35 reservoirs in the greater Tennessee Valley region. Regression models were developed which gave significant estimates of each reservoir's trophic state as defined by its trophic state index and explained in all four LANDSAT frames at least 85 percent of the variability in the data. To illustrate the spatial variations within reservoirs as well as the relative variations between reservoirs, a table look up elliptical classification was used in conjunction with each reservoir's trophic state index to classify each reservoir on a pixel by pixel basis and produce color coded thematic representations.

Meinert, D. L.↗
NASA NTRS1983

A sampling system for estimating the cultivation of wheat (Triticum aestivum L) from LANDSAT data

Using digitally processed MSS/LANDSAT data as auxiliary variable, a methodology to estimate wheat (Triticum aestivum L) area by means of sampling techniques was developed. To perform this research, aerial photographs covering 720 sq km in Cruz Alta test site at the NW of Rio Grande do Sul State, were visually analyzed. LANDSAT digital data were analyzed using non-supervised and supervised classification algorithms; as post-processing the classification was submitted to spatial filtering. To estimate wheat area, the regression estimation method was applied and different sample sizes and various sampling units (10, 20, 30, 40 and 60 sq km) were tested. Based on the four decision criteria established for this research, it was concluded that: (1) as the size of sampling units decreased the percentage of sampled area required to obtain similar estimation performance also decreased; (2) the lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation was 90% using 10 sq km s the sampling unit; and (3) wheat area estimation by direct expansion (using only aerial photographs) was less precise and accurate when compared to those obtained by means of regression estimation.

Parada, N. D. J.↗