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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

A flight-test methodology for identification of an aerodynamic model for a V/STOL aircraft

This paper describes a flight-test methodology for developing a data base to be used to identify an aerodynamic model of a V/STOL fighter aircraft. The aircraft serves as a test bed at NASA Ames for ongoing research in advanced V/STOL control and display concepts. The flight envelope to be modeled includes hover, transition to conventional flight and back to hover, STOL operation, and normal cruise. Although the aerodynamic model is highly nonlinear, it has been formulated to be linear in the parameters to be identified. Motivation for the flight-test methodology advocated in this paper is based on the choice of a linear least-squares method for model identification. The paper covers elements of the methodology from maneuver design to the completed data base. Major emphasis is placed on the use of state estimation with tracking data to ensure consistency among maneuver variables prior to their entry into the data base. The design and processing of a typical maneuver are illustrated.

Bach, R. E., Jr.↗
NASA NTRS2017

A Network-Based Algorithm for Clustering Multivariate Repeated Measures Data

The National Aeronautics and Space Administration (NASA) Astronaut Corps is a unique occupational cohort for which vast amounts of measures data have been collected repeatedly in research or operational studies pre-, in-, and post-flight, as well as during multiple clinical care visits. In exploratory analyses aimed at generating hypotheses regarding physiological changes associated with spaceflight exposure, such as impaired vision, it is of interest to identify anomalies and trends across these expansive datasets. Multivariate clustering algorithms for repeated measures data may help parse the data to identify homogeneous groups of astronauts that have higher risks for a particular physiological change. However, available clustering methods may not be able to accommodate the complex data structures found in NASA data, since the methods often rely on strict model assumptions, require equally-spaced and balanced assessment times, cannot accommodate missing data or differing time scales across variables, and cannot process continuous and discrete data simultaneously. To fill this gap, we propose a network-based, multivariate clustering algorithm for repeated measures data that can be tailored to fit various research settings. Using simulated data, we demonstrate how our method can be used to identify patterns in complex data structures found in practice.

Koslovsky, Matthew↗
NASA NTRS1994

Evidence for X-ray flux and spectral modulation by absorption in NGC 6814. 1: The nature of the most rapid variability

The Seyfert 1 galaxy NGC 6814 was observed using the Japanese X-ray astronomy satellite Ginga in 1990 April and October. The rapid variability characteristically associated with this source was reconfirmed. Specifically, three dips were found in the April observation in which the flux dropped to nearly zero in approximately 300 s. The doubling timescale was approximately 50 s. A similar but separated drop and rise in flux was observed in the October data, different in that the flux did not decrease completely to zero. A detailed analysis of the data around the structures of most rapid variability found spectral variability and lags in flux between different energy bands. Lags were on the order of a few to tens of seconds for the April data, and on the order of tens to a couple of hundred seconds for the October data. The sense of the lags was such that during flux decreases the hard flux lagged, while during flux increases the soft flux lagged. Associated significant apparent hardening of the spectrum at low flux was observed in the April data. Apparent hardening of the spectrum also occurred in the October flux decrease, to a photon index of GAMMA = 0.85; however, the spectrum softened at lowest flux to the index of the predecrease level, GAMMA = 1.54. In the April dips, the line flux was found to decrease significantly. A marginal decrease in line flux was also observed in the October data. The variability of the line flux reconfirmed the result of Kunieda et al. (1990), who found that the line production region must be within approximately 300 light-seconds from the source. To explain the observational results, a variable-absorption model was proposed, in which the column density was assumed to vary as a function of time. Other physical processes, including intrinsic spectral changes and warm absorber models, which could account for the fastest variability, could be ruled out by the results of the data analysis. A primary constraint found for geometrical models is that the material which is doing the absorption must have relatively low ionization (xi less than 100). This result leads to severe constraints on a general orbiting cloud model, requiring high densities (n approximately 10(exp 16)/cu cm) and sheetlike geometry.

Leighly, Karen↗
NASA NTRS1984

Forest Environments

The application of remote sensing measurement techniques to scientific questions involving forests is a necessity because of the extent of forests, their variability, and the need to measure their interaction with environmental processes. The synoptic view given by remote sensing data of the extent, variability, and relation to environmental processes involving energy balances, disposition of water, and tree growth in relation to elemental storage of carbon, nitrogen and other essential elements is essential to understanding the forest in a scientific way. The ability to make comparisons in these properties at various intervals allows the determination of process functions and rates where the forest affects environmental properties. The ultimate objective in using these data is to define the extent of the forest and wildland resource, to determine the changes that are occurring in the resource due to utilization by man under conditions of changing market and population demands, and to evaluate the correlated changes occurring in various environmental properties influenced by forest vegetation on a local as well as global scale.

Zinke, P.↗
NASA NTRS1987

Long-term gamma-ray spectral variability of Cygnus X-1

Data from HEAO 3 observations of 0.05-10-MeV gamma-ray emission from Cyg X-1 during two 90-d periods (in fall 1979 and spring 1980) are compiled in tables and graphs and analyzed statistically to determine the temporal and spectral variability. It is found that a steady increase in 100-keV emission is accompanied by a decrease (and eventual disappearance) of MeV emission. The mechanisms which could theoretically be responsible for these phenomena are discussed.

Ling, J. C.↗
NASA NTRS1993

Development, refinement, and testing of a short term solar flare prediction algorithm

During the period included in this report, the expenditure of time and effort, and progress toward performance of the tasks and accomplishing the goals set forth in the two year research grant proposal, consisted primarily of calibration and analysis of selected data sets. The heliographic limits of 30 degrees from central meridian were continued. As previously reported, all analyses are interactive and are performed by the Principal Investigator. It should also be noted that the analysis time involved by the Principal Investigator during this reporting period was limited, partially due to illness and partially resulting from other uncontrollable factors. The calibration technique (as developed by MSFC solar scientists), incorporates sets of constants which vary according to the wave length of the observation data set. One input constant is then varied interactively to correct for observing conditions, etc., to result in a maximum magnetic field strength (in the calibrated data), based on a separate analysis. There is some insecurity in the methodology and the selection of variables to yield the most self-consistent results for variable maximum field strengths and for variable observing/atmospheric conditions. Several data sets were analyzed using differing constant sets, and separate analyses to differing maximum field strength - toward standardizing methodology and technique for the most self-consistent results for the large number of cases. It may be necessary to recalibrate some of the analyses, but the sc analyses are retained on the optical disks and can still be used with recalibration where necessary. Only the extracted parameters will be changed.

Smith, Jesse B., Jr.↗
NASA NTRS2000

Satellite-Derived Dynamics of Southern Ocean Sea Ice

Antarctic ERS-2, RADARSAT Synthetic Aperture Radar and ERS-1/2 Scatterometer images were analyzed with SMMI radiometer image time-series data to investigate seasonal variability in satellite-tracked sea-ice dynamics in the Southern Ocean during 1992. Supporting field data were acquired during 'in-situ' experiments including the winter 1992 Ice Station Weddell and Winter Weddell Gyre studies. A variety of surface measurements were made during these experiments including Argos-buoy deployment and GPS drift measurements. These are used in conjunction with International Program for Antarctic Buoys drift trajectories for ice-motion tracking validation. Comparisons between gridded Special Sensor Microwave Imager (SSMI) ice-motion vectors and European Center for Medium Range Weather Forecasts/National Centers for Environmental Prediction (ECMWF/NCEP) analyses indicate that large-scale drift is forced predominantly by the long-term mean, large-scale synoptic pressure field. Only sub-daily SAR sea-ice tracking can capture high-frequency fluctuations, driven by polar lows or tidal forcing. In these cases, sea-ice drift can respond rapidly to changes in forcing on semi-diurnal time scales depending on the location with respect to the coastline. Seasonality of ice drift, particularly in the Weddell and Ross Seas, is linked to ice extent and compactness, and internal ice stresses transmitted through the pack ice from the coast. Three-monthly seasonal climatologies are presented of austral winter of ice drift in the Southern Ocean. The large Weddell and Ross Sea gyres are clearly resolved along with key seasonal and spatial attributes of their cyclonic circulation. Regional time series of ice dynamics parameters are used to illustrate correlations with meteorological forcing. Persistent divergence such as that occurring in the Ronne-Filchner polynya system results in large fractions of new ice. Similarly, convergence zones produce large fractions of deformed ice and characterize the dynamics of regions where perennial ice is observed. High shear strains also help delineate the axis of the Antarctic divergence in many places in the ice cover. In these regions, the separation between the coastal 'east wind drift'and ACC-dominated drift regimes is characterized by zonally extended regions of intense shear.

Drinkwater, Mark R.↗
NASA NTRS2001

Thermal and Cycle-Life Behavior of Commercial Li-ion and Li-Polymer Cells

Accelerated and real-time LEO cycle-life test data will be presented for a range of commercial Li-ion and Li-polymer (gel type) cells indicating the ranges of performance that can be obtained, and the performance screening tests that must be done to assure long life. The data show large performance variability between cells, as well as a highly variable degradation signature during non-cycling periods within the life tests. High-resolution Dynamic Calorimetry data will be presented showing the complex series of reactions occurring within these Li cells as they are cycled. Data will also be presented for cells being tested using an Adaptive Charge Control Algorithm (ACCA) that continuously adapts itself to changes in cell performance, operation, or environment to both find and maintain the optimum recharge over life. The ACCA has been used to prevent all unneeded overcharge for Li cells, NiCd cells and NiH2 cells. While this is important for all these cell types, it is most critical for Li-ion cells, which are not designed with electrochemical tolerance for overcharge.

Zimmerman, Albert H.↗
NASA NTRS1990

Variability of photosynthetically available and total solar irradiance at the surface during FIFE - A satellite description

The satellite method of Gautier et al. (1980) is applied to GOES-6 radiometer data to determine the availability of quantitative data on the temporal variability of photosynthetically available radiation (PAR) and insolation. Comparisons with in situ measurements indicate that the modified satellite method yields insolation and PAR data with small biases and standard errors of 9 and 6.5 percent respectively. It is shown that large-scale satellite climatologies of insolation can be converted into climatologies of PAR to study photosynthetic activity on a global scale.

Frouin, Robert↗
NASA NTRS2019

Design and Construction of a NASA Airborne and Field Investigation Inventory

NASA conducts airborne and field investigations that produce a wealth of valuable research data. Unfortunately, this data is often scattered across individual scientist hard drives or NASA Distributed Active Archive Centers and it can be difficult to locate and retrieve. Although satellite data has been successfully consolidated by tools such as EarthData Search, airborne and field investigation data present unique challenges stemming from the variability of temporal, spatial, platform, and instrument metadata. To address these difficulties with data retrieval and metadata variability, the Interagency Implementation and Concepts Team established an Airborne Data Management Group to improve airborne data search, understanding, access, and use. Surveys have been conducted of end users in order to build query lists that will drive the augmentation and standardization of existing metadata. Detailed metadata was then laboriously compiled from present and historic airborne and field investigations to build a database that will enable intelligent data search and retrieval. The inventory structure and function will be described and demonstrated. The purpose of this presentation is to bring awareness to this effort, to highlight and describe the issues and complications in development, and to increase user interest prior to public release in 2020.

Davis, Carson↗
NASA NTRSDate not supplied

Understanding the Impact of Unobservable Variables on the Performance of Predictive Models: The Need for Feature Space Partitioning and Fusion

When developing predictive models over a dataset, the model is globally optimized across the entire feature space to learn a decision boundary. However, when unobservable variables—which cannot be measured or estimated—interact with the observable variables, this can negatively impact the optimization applied to the decision boundary since the data samples introduced by unobservable variables may have little to no association with the applied global optimization. This, consequently, penalizes the entire decision boundary and model performance. This paper examines some of the detrimental effects of unobservable variables, particularly their role in creating new modes in the distribution of observable variables and reducing the separability of class distributions. Such challenges result in skewed or warped decision boundaries and decreased accuracy of model predictions, particularly for interpretable models like logistic regression and decision trees. Through two illustrative case examples, we highlight the need to address the challenges imposed by unobservable variables. We propose a strategy to mitigate these challenges by creating local regions within the feature space through partitioning. This enables the optimization of local models within the regions to overcome the impact of unobservability in different feature space localities. Research into a more sophisticated partitioning strategy and where the partition should be relative to the sample of interest is left as future work. Through the analysis of the impact of unobservability and the development of a partitioning method, we demonstrate the clear need for a partitioning strategy that integrates knowledge from multiple local models to estimate risk factors using information fusion. Thus, we establish the foundation and motivation for using partitioning and information fusion to overcome the effects of unobservability in predictive models. Formal fusion methods, such as Dempster-Shafer theory, can better leverage the information from local regions to improve the performance of interpretable predictive models in the presence of unobservable variables.

Time Series Data↗
NASA NTRS2002

Variability in Ozone in the Tropical Tropopause Region from the 1998-2000 SHADOZ (Southern Hemisphere ADditional OZonesondes) Data

The first view of stratospheric and tropospheric ozone variability in the southern hemisphere tropics is provided by a 3-year, 10-site record of ozone soundings from the Southern Hemisphere ADditional OZonesondes (SHADOZ) network. Observations covering 1998-2000 were made over Ascension Island; Nairobi, Kenya; Irene, South Africa; Reunion Island; Watukosek, Java; Fiji; Tahiti; American Samoa; San Cristobal, Galapagos; Natal, Brazil. Taking the TTL (tropical tropopause layer) as the region between 12 and 17 km, we examine ozone variability in this region on a week-to-week and seasonal basis. The TTL layer is lower in September-October-November than in March-April-May, when ozone is a minimum at most SHADOZ stations. A zonal wave-one pattern is apparent in column-integrated TTL ozone because ozone mixing ratios are greater over the Atlantic and adjacent continents than over the Pacific and eastern Indian Ocean. The wave-one persists all year with varying magnitude and appears to be due to general circulation - with subsidence over the Atlantic and frequent deep convection over the Pacific and Indian Ocean. The variability of deep convection - most prominent at Java, Fiji, Samoa and Natal - is explored in time-vs-altitude ozone curtains. Stratospheric incursions into the troposphere are most prominent in soundings at Irene and Reunion Island.

Thompson, Anne M.↗
NASA NTRS2005

Variability and Extremes of Precipitation in the Global Climate as Determined by the 25-Year GEWEX/GPCP Data Set

The Global Precipitation Climatology Project (GPCP) 25-year precipitation data set is used to evaluate the variability and extremes on global and regional scales. The variability of precipitation year-to-year is evaluated in relation to the overall lack of a significant global trend and to climate events such as ENSO and volcanic eruptions. The validity of conclusions and limitations of the data set are checked by comparison with independent data sets (e.g., TRMM). The GPCP data set necessarily has a heterogeneous time series of input data sources, so part of the assessment described above is to test the initial results for potential influence by major data boundaries in the record. Regional trends, or inter-decadal changes, are also analyzed to determine validity and correlation with other long-term data sets related to the hydrological cycle (e.g., clouds and ocean surface fluxes). Statistics of extremes (both wet and dry) are analyzed at the monthly time scale for the 25 years. A preliminary result of increasing frequency of extreme monthly values will be a focus to determine validity. Daily values for an eight-year are also examined for variation in extremes and compared to the longer monthly-based study.

Adler, R. F.↗
NASA NTRS1978

A stochastic analysis of terrain evaluation variables for path selection

A stochastic analysis was performed on the variables associated with the characteristics of the terrain encountered by a roving system with an autonomous navigation system. A laser rangefinder is employed to detect terrain features at ranges up to 75 m. Analytic expressions and a numerical scheme were developed to calculate the variance of data on these four variables: (1) body clearance, (2) in-path slope, (3) tilt slope, and (4) wheel deviation. The variance is due to noise in the range data. It was found that the standard deviation of these terrain variables is large enough to warrant the use of a safety margin to aid the roving vehicle in avoiding high risk areas.

Donohue, J. G.↗
NASA NTRS2005

Diverse Applications of Occultation Data in Ozone Assimilation

Ozone profiles from solar occultation instruments provide invaluable information that can be used to evaluate the quality of assimilated ozone fields, from case studies to long-term phenomena. Occultation data can also be applied to include physical constraints while developing components of an assimilation system. Conversely, assimilation of occultation data can help in their validation, and it provides a framework for evaluation of the impact of occultation data on constraining global ozone fields within models. We illustrate these diverse applications by a series of examples using the ozone assimilation system at NASA/Goddard. In a case study, low ozone in the lower stratosphere due to transport of air from the Tropics to northern high latitudes that was captured by assimilation of Aura Microwave Limb Sounder (MLS) and Solar Backscatter Ultraviolet (SBUV) data, was found to agree with SAGE III data. For long-term monitoring, the quality of a multi-year SBUV-only assimilation was evaluated using monthly-mean time series of POAM, HALOE, and SAGE I1 data. We found realism in the representation of the annual cycle in ozone and in some aspects of interannual variability. Assimilation of POAM data was shown to improve the representation of lower stratospheric ozone, especially over Antarctica. More recently, we assimilated ILAS II ozone data in order to help in their validation. Solar occultation data are used to estimate parameters in a new model for forecast error variances that is being developed. These examples demonstrate the importance of occultation data for ozone assimilation, and potential of assimilation to increase the impact and the value of occultation data.

Markowitz, A.↗
NASA NTRS2012

NLDAS Views of North American 2011 Extreme Events

2011 was marked as one of the most extreme years in recent history. Over the course of the year, weather-related extreme events, such as floods, heat waves, blizzards, tornadoes, and wildfires, caused tremendous loss of human life and property. The North American Land Data Assimilation System (NLDAS, http://ldas.gsfc.nasa.gov/nldas/) data set, with high spatial and temporal resolutions (0.125? x 0.125?, hourly) and various water- and energy-related variables, is an excellent data source for case studies of extreme events. This presentation illustrates some extreme events from 2011 in North America, including the Groundhog Day Blizzard, the July heat wave, Hurricane Irene, and Tropical Storm Lee, all utilizing NLDAS Phase 2 (NLDAS-2) data.

Rui, Hualan↗
NASA NTRS2014

NLDAS Views of North American 2011 Extreme Events

2011 was marked as one of the most extreme years in recent history. Over the course of the year, weather-related extreme events, such as floods, heat waves, blizzards, tornadoes, and wildfires, caused tremendous loss of human life and property. The North American Land Data Assimilation System (NLDAS, http:ldas.gsfc.nasa.govnldas) data set, with high spatial and temporal resolutions (0.125 x 0.125, hourly) and various water- and energy-related variables, is an excellent data source for case studies of extreme events. This presentation illustrates some extreme events from 2011 in North America, including the Groundhog Day Blizzard, the July heat wave, Hurricane Irene, and Tropical Storm Lee, all utilizing NLDAS Phase 2 (NLDAS-2) data.

hydrology↗
NASA NTRS1994

The discrete and localized nature of the variable emission from active regions

Using data from the Extreme Ultraviolet (EUV) Spectroheliometer on Skylab, we study the empirical characteristics of the variable emission in active regions. These simultaneous multi-wavelength observations clearly confirm that active regions consist of a complex of loops at different temperatures. The variable emission from this complex has very well-defined properties that can be quantitatively summarized as follows: (1) It is localized predominantly around the footpoints where it occurs at discrete locations. (2) The strongest variability does not necessarily coincide with the most intense emission. (3) The fraction of the area of the footpoints, (delta n)/N, that exhibits variable emission, varies by +/- 15% as a function of time, at any of the wavelengths measured. It also varies very little from footpoint to footpoint. (4) This fractional variation is temperature dependent with a maximum around 10(exp 5) K. (5) The ratio of the intensity of the variable to the average background emission, (delta I)/(bar-I), also changes with temperature. In addition, we find that these distinctive characteristics persist even when flares occur within the active region.

Arndt, Martina Belz↗