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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Interannual and Decadal Variability of Ocean Surface Latent Heat Flux as Seen from Passive Microwave Satellite Algorithms

Ocean surface turbulent fluxes are critical links in the climate system since they mediate energy exchange between the two fluid systems (ocean and atmosphere) whose combined heat transport determines the basic character of Earth's climate. Deriving physically-based latent and sensible heat fluxes from satellite is dependent on inferences of near surface moisture and temperature from coarser layer retrievals or satellite radiances. Uncertainties in these "retrievals" propagate through bulk aerodynamic algorithms, interacting as well with error properties of surface wind speed, also provided by satellite. By systematically evaluating an array of passive microwave satellite algorithms, the SEAFLUX project is providing improved understanding of these errors and finding pathways for reducing or eliminating them. In this study we focus on evaluating the interannual variability of several passive microwave-based estimates of latent heat flux starting from monthly mean gridded data. The algorithms considered range from those based essentially on SSM/I (e.g. HOAPS) to newer approaches that consider additional moisture information from SSM/T-2 or AMSU-B and lower tropospheric temperature data from AMSU-A. On interannual scales, variability arising from ENSO events and time-lagged responses of ocean turbulent and radiative fluxes in other ocean basins (as well as the extratropical Pacific) is widely recognized, but still not well quantified. Locally, these flux anomalies are of order 10-20 W/sq m and present a relevant "target" with which to verify algorithm performance in a climate context. On decadal time scales there is some evidence from reanalyses and remotely-sensed fluxes alike that tropical ocean-averaged latent heat fluxes have increased 5-10 W/sq m since the early 1990s. However, significant uncertainty surrounds this estimate. Our work addresses the origin of these uncertainties and provides statistics on time series of tropical ocean averages, regional space / time correlation analysis, and separation of contributions by variations in wind and near surface humidity deficit. Comparison to variations in reanalysis data sets is also provided for reference.

Robertson, Franklin R.↗
NASA NTRS1992

Loss of 'complexity' and aging. Potential applications of fractals and chaos theory to senescence

The concept of "complexity," derived from the field of nonlinear dynamics, can be adapted to measure the output of physiologic processes that generate highly variable fluctuations resembling "chaos." We review data suggesting that physiologic aging is associated with a generalized loss of such complexity in the dynamics of healthy organ system function and hypothesize that such loss of complexity leads to an impaired ability to adapt to physiologic stress. This hypothesis is supported by observations showing an age-related loss of complex variability in multiple physiologic processes including cardiovascular control, pulsatile hormone release, and electroencephalographic potentials. If further research supports this hypothesis, measures of complexity based on chaos theory and the related geometric concept of fractals may provide new ways to monitor senescence and test the efficacy of specific interventions to modify the age-related decline in adaptive capacity.

Non-NASA Center↗
NASA NTRS1997

Issues on Internet-Based Teleoperation

This paper describes experiments of Internet modeling and of Internet-based teleoperation aimed at developing suitable control laws to overcome the variable time-delay and the data losses typical of Internet communication. The effects of packet delay jitter and losses on teleoperation performance are demonstrated using a 2-dof force feedback master.

Internet real-time communication↗
NASA NTRS1985

Radar and the Detection of Liquid Water on Mars

Detection of the seasonally variable radar reflectivity in the Goldstone Mars data (the Solis Lacus radar anomaly and the proposed interpretation in terms of the near-surface presence of liquid water created a controversy in the planetary science community. Over the past year, skepticism was voiced about the reality of the phenomenon of a seasonally variable radar reflectivity anywhere on Mars. The necessary background information and the pertinent data are reviewed in a format perhaps more convincing than that employed in the original presentation of the discovery. A summary of the results and recommendations for future work are included.

Roth, L. E.↗
NASA NTRS1979

Conditional replenishment using motion prediction

Conditional replenishment is an interframe video compression method that uses correlation in time to reduce video transmission rates. This method works by detecting and sending only the changing portions of the image and by having the receiver use the video data from the previous frame for the non-changing portion. The amount of compression that can be achieved through this technique depends to a large extent on the rate of change within the image, and can vary from 10 to 1 to less than 2 to 1. An additional 3 to 1 reduction in rate is obtained by the intraframe coding of data blocks using a 2-dimensional variable rate Hadamard transform coder. A further additional 2 to 1 rate reduction is achieved by using motion prediction. Motion prediction works by measuring the relative displacements of a subpicture from one frame to the next. The subpicture can then be transmitted by sending only the value of the 2-dimensional displacement. Computer simulations have demonstrated that data rates of 2 to 4 Mega-bits/second can be achieved while still retaining good fidelity in the image.

Hein, D. N.↗
NASA NTRS2006

Formaldehyde Distribution over North America: Implications for Satellite Retrievals of Formaldehyde Columns and Isoprene Emission

Formaldehyde (HCHO) columns measured from space provide constraints on emissions of volatile organic compounds (VOCs). Quantitative interpretation requires characterization of errors in HCHO column retrievals and relating these columns to VOC emissions. Retrieval error is mainly in the air mass factor (AMF) which relates fitted backscattered radiances to vertical columns and requires external information on HCHO, aerosols, and clouds. Here we use aircraft data collected over North America and the Atlantic to determine the local relationships between HCHO columns and VOC emissions, calculate AMFs for HCHO retrievals, assess the errors in deriving AMFs with a chemical transport model (GEOS-Chem), and draw conclusions regarding space-based mapping of VOC emissions. We show that isoprene drives observed HCHO column variability over North America; HCHO column data from space can thus be used effectively as a proxy for isoprene emission. From observed HCHO and isoprene profiles we find an HCHO molar yield from isoprene oxidation of 1.6 +/- 0.5, consistent with current chemical mechanisms. Clouds are the primary error source in the AMF calculation; errors in the HCHO vertical profile and aerosols have comparatively little effect. The mean bias and 1Q uncertainty in the GEOS-Chem AMF calculation increase from <1% and 15% for clear skies to 17% and 24% for half-cloudy scenes. With fitting errors, this gives an overall 1 Q error in HCHO satellite measurements of 25-31%. Retrieval errors, combined with uncertainties in the HCHO yield from isoprene oxidation, result in a 40% (1sigma) error in inferring isoprene emissions from HCHO satellite measurements.

Millet, Dylan B.↗
NASA NTRS2009

Space Technology 5 Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

Space Technology 5 (ST5) is a constellation mission consisting of three microsatellites. It provides the first multipoint magnetic field measurements in low Earth orbit, which enables us to separate spatial and temporal variations. In this paper, we present a study of the temporal variability of field-aligned currents using the ST5 data. We examine the field-aligned current observations during and after a geomagnetic storm and compare the magnetic field profiles at the three spacecraft. The multipoint data demonstrate that mesoscale current structures, commonly embedded within large-scale current sheets, are very dynamic with highly variable current density and/or polarity in approx.10 min time scales. On the other hand, the data also show that the time scales for the currents to be relatively stable are approx.1 min for mesoscale currents and approx.10 min for large-scale currents. These temporal features are very likely associated with dynamic variations of their charge carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of mesoscale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Le, G.↗
NASA NTRS1976

An Empirical Model for the Mixing of a Row of Dilution Jets with a Confined Crossflow

An empirical model was developed for predicting the temperature distribution downstream from a row of cool jets injected normally into a hot confined crossflow. The model is based on the assumption that all properly non-dimensionalized vertical temperature profiles can be expressed in a self-similar form. The scaling parameters in this form were correlated in terms of the independent flow and geometric variables. The effect of parametric variation of each of the independent variables on the experimental and predicted profiles are examined. The predicted distributions show excellent agreement with the data over a wide range of the independent variables.

Holdeman, J. D.↗
NASA NTRS1976

An empirical model for the mixing of a row of dilution jets with a confined crossflow

An empirical model has been developed for predicting the temperature distribution downstream of a row of cool jets injected normal to a hot confined crossflow. The model is based on the assumption that all properly non-dimensionalized vertical temperature profiles can be expressed in a self-similar form. The scaling parameters in this form have been correlated in terms of the independent flow and geometric variables. The effect of parametric variation of each of the independent variables on the experimental and predicted profiles are examined. The predicted distributions show excellent agreement with the data over a wide range of the independent variables.

Holdeman, J. D.↗
NASA NTRS1988

In situ measurements of thermospheric composition, temperature, and winds by mass spectrometry

Mass spectrometry, in which a beam of electrons ionizes a sample of atmospheric gas and then analyses the ions thus produced to determine the concentration of each species in the sample, is presently evaluated as a basis for the study of earth atmosphere and other planetary atmospheres' properties. Recent applications of in situ mass spectrometry have measured thermospheric neutral gas composition, temperatures, and winds, with a spatial resolution sufficiently high to reveal previously unsuspected atmospheric variability. It is expected that analyses of these data will lead to a more detailed understanding of the deposition processes governing the thermosphere's highly variable structure.

Spencer, N. W.↗
NASA NTRS1993

Sea surface height variability during 1986-1988 in the tropical Pacific Ocean

A description of the sea surface height variabilities during 1986-1988 in the tropical Pacific Ocean is presented on the basis of Geosat altimeter data and a tropical Pacific Ocean GCM (OGCM) forced with observed winds from Florida State University. Both data sets are validated against in situ sea-level measurements at 12 selected sea-level stations in the equatorial Pacific and were found to be in good agreement with these measurements with correlation coefficients of 0.69 for Geosat and 0.71 for OGCM. The Geosat altimeter data are capable of describing sea surface height variabilities during 1986-1988 in the tropical Pacific, in particular, the seasonal cycle, the 1987 El Nino and 1988 La Nina episodes, and the December 1986 equatorial Kelvin wave event. The OGCM-simulated surface dynamic height is found to be sensitive to different surface wind products.

Chao, YI↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), has typically limited machine learning (ML) in space studies and further study of radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNAseq) data from 6 mouse liver GeneLab datasets (GLDS) with a total of 113 spaceflight and ground-control samples to determine top features relevant to spaceflight including the effect of radiation exposure. Data was normalized within each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. The top MRMR features were used to predict spaceflight vs. ground-control samples using a Random Forest (RF) classifier with 5-fold cross validation (CV). The ML-based gene sets were further compared against differential gene expression results from individual GLDS. CV training using the top 100 MRMR genes show averages of 86% accuracy and 0.95 AUC value on the validation set over 5 folds (Figure 1A). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 811 or 68 DEGs overlapping between at least 2 or 3 studies, respectively (Figure 1B). Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism. Set analysis between the MRMR features and the DEGs showed 60 or 8 genes overlapping with at least 1 or 2 studies, respectively. MRMR feature selection and ensemble ML methods (e.g. RF) improve performance relative to a Naïve Bayes classifier when NGS data sets are analyzed. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise ratio. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from RNASeq analysis. Non-intersecting sets introduce opportunity to explore spaceflight relevant genes and implementing ML methods across existing NGS datasets may overcome sample size limitations. ML coupled with existing analytical methods enhances understanding of disease by revealing common underlying pathways across datasets.

Machine Learning↗
NASA NTRS1957

Exploratory Investigation of Boundary-Layer Transition on a Hollow Cylinder at a Mach Number of 6.9

The Reynolds number for transition on the outside of a hollow cylinder with heat transfer from the boundary layer to the wall has been investigated at a Mach number of 6.9 in the Langley 11-inch hypersonic tunnel. The type of boundary layer was determined from impact-pressure surveys and optical viewing. From a correlation of results obtained from various sources at lower Mach numbers (in the range 2.0 to 4.5) and data from the present tests with variable Reynolds number per inch, leading-edge thickness and free-stream Reynolds number per inch appear to be important considerations in flat-plate transition results. At a given Mach number, it appears that the Reynolds number based on leading-edge thickness is an important parameter that must be considered in comparisons of flat-plate transition data from various installations.

Bertram, Mitchel H↗
NASA NTRS2011

Combining Satellite and in Situ Data with Models to Support Climate Data Records in Ocean Biology

The satellite ocean color data record spans multiple decades and, like most long-term satellite observations of the Earth, comes from many sensors. Unfortunately, global and regional chlorophyll estimates from the overlapping missions show substantial biases, limiting their use in combination to construct consistent data records. SeaWiFS and MODIS-Aqua differed by 13% globally in overlapping time segments, 2003-2007. For perspective, the maximum change in annual means over the entire Sea WiFS mission era was about 3%, and this included an El NinoLa Nina transition. These discrepancies lead to different estimates of trends depending upon whether one uses SeaWiFS alone for the 1998-2007 (no significant change), or whether MODIS is substituted for the 2003-2007 period (18% decline, P less than 0.05). Understanding the effects of climate change on the global oceans is difficult if different satellite data sets cannot be brought into conformity. The differences arise from two causes: 1) different sensors see chlorophyll differently, and 2) different sensors see different chlorophyll. In the first case, differences in sensor band locations, bandwidths, sensitivity, and time of observation lead to different estimates of chlorophyll even from the same location and day. In the second, differences in orbit and sensitivities to aerosols lead to sampling differences. A new approach to ocean color using in situ data from the public archives forces different satellite data to agree to within interannual variability. The global difference between Sea WiFS and MODIS is 0.6% for 2003-2007 using this approach. It also produces a trend using the combination of SeaWiFS and MODIS that agrees with SeaWiFS alone for 1998-2007. This is a major step to reducing errors produced by the first cause, sensor-related discrepancies. For differences that arise from sampling, data assimilation is applied. The underlying geographically complete fields derived from a free-running model is unaffected by solar zenith angle requirements and obscuration from clouds and aerosols. Combined with in situ dataenhanced satellite data, the model is forced into consistency using data assimilation. This approach eliminates sampling discrepancies from satellites. Combining the reduced differences of satellite data sets using in situ data, and the removal of sampling biases using data assimilation, we generate consistent data records of ocean color. These data records can support investigations of long-term effects of climate change on ocean biology over multiple satellites, and can improve the consistency of future satellite data sets.

Gregg, Watson↗
NASA NTRS2004

Ionospheric Variability and Storms on Mars

The goal of this grant was to conduct the first-ever study of ionospheric variability on Mars. To do so, we used data from the Radio Science (RS) experiment onboard the Mars Global Surveyor (MGS) satellite. Dr. David Hinson of the RS team at Stanford University was a most helpful and valuable colleague throughout the studies we conducted. For the initial RS datasets available from the MGS mission, there were no severe storms caused by solar wind activity, so we concentrated on day-to-day effects. This turned out to be a wise approach since understanding "normal variability" had to be done before any claim could be made about "space weather" effects. Our approach was three-fold: (1) select a good dataset for characterization of ionosphere variability at Mars, one for which excellent terrestrial data were also available. This turned out to be the period 9-27 March 1999; (2) once the variability at Mars was described, develop and use a new photochemical model of the martian ionosphere to find the extent to which solar variability on those days caused or contributed to the observed patterns; (3) use the results from the above, together with additional datasets from the MGS/RS experiment, to describe some practical consequences that the martian ionosphere would have upon NASA s proposed navigation and communications systems for Mars. The results of these studies showed that: (a) solar variability is the dominant source of ionospheric variability at Mars (during periods of quiet solar wind), (b) that current models do a good job in portraying such effects at the height of the ionospheric peak electron density, and (c) that ionospheric structure on Mars can affect attempts at precise position-fixing at Mars should relatively high (GPS-like) frequencies not be used in a Mars communications and navigation system.

Mendillo, Michael↗
NASA NTRS1974

The application of ERTS-1 data to the land use planning process

Land resource data has been extracted on a percent of cell basis from ERTS imagery, RB-57 color infrared imagery and best available conventional sources for a 10,000 square kilometer test area in eastern Wisconsin. First, the data from the three sources is compared on a spatial basis for a 300 square kilometer portion of the test area. For those land resource variables associated with cover, ERTS derived resource data compared favorably with both the RB-57 and conventional data. Second, the effect of the data source on land use decisions is examined. Three interstate highway corridors are located through the same region based upon data extracted from each of the three sources. A policy of preserving natural environmental systems was used as a basis for the corridors selection in each case. The resulting three corridors compare favorably.

Clapp, J. L.↗
NASA NTRS1975

Remote sensing and urban public health

The applicability of remote sensing in the form of aerial photography to urban public health problems is examined. Environmental characteristics are analyzed to determine if health differences among areas could be predicted from the visual expression of remote sensing data. The analysis is carried out on a socioeconomic cross-sectional sample of census block groups. Six morbidity and mortality rates are the independent variables while environmental measures from aerial photographs and from the census constitute the two independent variable sets. It is found that environmental data collected by remote sensing are as good as census data in evaluating rates of health outcomes.

Rush, M.↗
NASA NTRS2003

Atmospheric Soundings from AIRS/AMSU/HSB

AIRS was launched on EOS Aqua on May 5, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an RMS error of 1K, and 1 km layer precipitable water with an rms error of 1K, and 1 km layer precipitable water with an rms error of 20 percent, in cases with up to 80 percent cloud cover. The AIRS data products are significant for studying climate variability and change, as well as for use in initialization of General Circulation Models with the objective of improving analysis fields and subsequent forecast skill. Data assimilation experiments to evaluate the impact of AIRS retrievals on analysis and forecast skill are being conducted. Sample fields of parameters retrieved from AIRS/AMSU/HSB data will be presented and validated as a function of retrieved fractional cloud cover. Select fields will also be compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, on both an instantaneous and monthly mean basis, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis.

Susskind, Joel↗