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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

An experiment to verify that the weak interactions satisfy the strong equivalence principle

The construction of a clock based on the beta decay process is proposed to test for any violations by the weak interaction of the strong equivalence principle bu determining whether the weak interaction coupling constant beta is spatially constant or whether it is a function of gravitational potential (U). The clock can be constructed by simply counting the beta disintegrations of some suitable source. The total number of counts are to be taken a measure of elapsed time. The accuracy of the clock is limited by the statistical fluctuations in the number of counts, N, which is equal to the square root of N. Increasing N gives a corresponding increase in accuracy. A source based on the electron capture process can be used so as to avoid low energy electron discrimination problems. Solid state and gaseous detectors are being considered. While the accuracy of this type of beta decay clock is much less than clocks based on the electromagnetic interaction, there is a corresponding lack of knowledge of the behavior of beta as a function of gravitational potential. No predictions from nonmetric theories as to variations in beta are available as yet, but they may occur at the U/sg C level.

Eby, P. B.↗
NASA NTRS1992

Types and Characteristics of Data for Geomagnetic Field Modeling

Given here is material submitted at a symposium convened on Friday, August 23, 1991, at the General Assembly of the International Union of Geodesy and Geophysics (IUGG) held in Vienna, Austria. Models of the geomagnetic field are only as good as the data upon which they are based, and depend upon correct understanding of data characteristics such as accuracy, correlations, systematic errors, and general statistical properties. This symposium was intended to expose and illuminate these data characteristics.

R A Langel↗
NASA NTRS1993

Sensitivity of trajectory calculations to the temporal frequency of wind data

A mesoscale primitive equation model is used to create a 36-h simulation of the three-dimensional wind field of an intense maritime extratropical cyclone. The control experiment uses the simulated wind field every 15 min in a trajectory model to calculate back trajectories from various horizontal and vertical positions of interest relative to synoptic features of the storm. The latter trajectories are compared to trajectories that were calculated with the simulated wind data degraded in time to 30 min, 1 h, 3 h, 6h, and 12 h. Various error statistics reveal significant deterioration in trajectory accuracy between trajectories calculated with 1- and 3-h data frequencies. Trajectories calculated with 15-min, 30-min, and 1-h data frequencies yielded similar results, while trajectories calculated with data time frequencies 3 h and greater yielded results with unacceptably large errors.

Doty, Kevin G.↗
NASA NTRS1991

Land cover stratification using Landsat Thematic Mapper data in Sahelian and Sudanian woodland and wooded grassland

A standard methodology for thematic mapping of natural vegetation using remotely sensed imagery and digital image processing was modified to account for the spatial and spectral properties of semi-arid landscapes, and tested in study areas in the Sahelian and Sudanian zones, Mali. A principal components transformation of registered wet and dry season Landsat TM images produced a set of synthetic spectral channels differentiating vegetation cover between seasons, and allowed areas with annual grass growth to be distinguished from areas with woody cover. The transformed data were statistically clustered and clusters were assigned to vegetation type and density categories. In a separate step, the images were manually interpreted to differentiate broad soil classes. Four statistics were compared to evaluate the accuracy of the maps based on sample points from air photos. For the relatively detailed categories initially defined, map accuracies were substandard; however, when vegetation density classes were aggregated, overall accuracy was around 90 percent, and class accuracy was greater than 80 percent for most classes. This method is suitable for stratification and inventory of woody biomass at a regional scale in semi-arid woodland and wooded grassland.

Franklin, J.↗
NASA NTRS2001

Tropospheric Ozone Near-Nadir-Viewing IR Spectral Sensitivity and Ozone Measurements from NAST-I

Infrared ozone spectra from near nadir observations have provided atmospheric ozone information from the sensor to the Earth's surface. Simulations of the NPOESS Airborne Sounder Testbed-Interferometer (NAST-I) from the NASA ER-2 aircraft (approximately 20 km altitude) with a spectral resolution of 0.25/cm were used for sensitivity analysis. The spectral sensitivity of ozone retrievals to uncertainties in atmospheric temperature and water vapor is assessed in order to understand the relationship between the IR emissions and the atmospheric state. In addition, ozone spectral radiance sensitivity to its ozone layer densities and radiance weighting functions reveals the limit of the ozone profile retrieval accuracy from NAST-I measurements. Statistical retrievals of ozone with temperature and moisture retrievals from NAST-I spectra have been investigated and the preliminary results from NAST-I field campaigns are presented.

Zhou, Daniel K.↗
NASA NTRS2022

Deep Interacting Multiple Model Filtering

In this paper, a deep learning-based multiple model estimation framework is presented for the state estimation of hybrid dynamical systems from high dimensional observations such as camera images. A low dimensional vector which represents the measurement of the latent dynamical system and its corresponding variance are learned using a deep encoder neural network. An Interacting Multiple Model (IMM) filter is used to generate the latent state estimates and covariances using multiple dynamical models, which can be learned using backpropagation through time. The state estimates of the dynamical system and the corresponding covariance matrix are generated from the latent state estimates and covariance using a deep decoder neural network. The whole network is trained in an end-to-end manner using a loss function which minimizes the negative log-likelihood of the neural network parameters. Simulation results are presented using a 2D bouncing ball example and estimation error statistics are computed which demonstrates the accuracy and consistency of the estimation.

Ghananeel Rotithor↗
NASA NTRS2010

Methods and Results for a Global Precipitation Measurement (GPM) Validation Network Prototype

As one component of a ground validation system to meet requirements for the upcoming Global Precipitation Measurement (GPM) mission, a quasi-operational prototype a system to compare satellite- and ground-based radar measurements has been developed. This prototype, the GPM Validation Network (VN), acquires data from the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite and from ground radar (GR) networks in the continental U.S. and participating international sites. PR data serve as a surrogate for similar observations from the Dual-frequency Precipitation Radar (DPR) to be present on GPM. Primary goals of the VN prototype are to understand and characterize the variability and bias of precipitation retrievals between the PR and GR in various precipitation regimes at large scales, and to improve precipitation retrieval algorithms for the GPM instruments. The current VN capabilities concentrate on comparisons of the base reflectivity observations between the PR and GR, and include support for rain rate comparisons. The VN algorithm resamples PR and GR reflectivity and other 2-D and 3-D data fields to irregular common volumes defined by the geometric intersection of the instrument observations, and performs statistical comparisons of PR and GR reflectivity and estimated rain rates. Algorithmic biases and uncertainties introduced by traditional data analysis techniques are minimized by not performing interpolation or extrapolation of data to a fixed grid. The core VN dataset consists of WSR-88D GR data and matching PR orbit subset data covering 21 sites in the southeastern U. S., from August, 2006 to the present. On average, about 3.5 overpass events per month for these WSR-88D sites meet VN criteria for significant precipitation, and have matching PR and GR data available. This large statistical sample has allowed the relative calibration accuracy and stability of the individual ground radars, and the quality of the PR reflectivity attenuation correction in convective and stratiform precipitation to be evaluated. We will present results of PR-GR reflectivity and rain rate bias comparisons for each OR site, and for different rain types, for the full data set and as time series. The capabilities of the statistical analysis and vertical cross section tools for display and analysis of individual site overpass event data will be described, and examples of the tools' outputs will be shown.

Morris, Kenneth R.↗
NASA NTRS2002

Investigation of Error Patterns in Geographical Databases

The objective of the research conducted in this project is to develop a methodology to investigate the accuracy of Airport Safety Modeling Data (ASMD) using statistical, visualization, and Artificial Neural Network (ANN) techniques. Such a methodology can contribute to answering the following research questions: Over a representative sampling of ASMD databases, can statistical error analysis techniques be accurately learned and replicated by ANN modeling techniques? This representative ASMD sample should include numerous airports and a variety of terrain characterizations. Is it possible to identify and automate the recognition of patterns of error related to geographical features? Do such patterns of error relate to specific geographical features, such as elevation or terrain slope? Is it possible to combine the errors in small regions into an error prediction for a larger region? What are the data density reduction implications of this work? ASMD may be used as the source of terrain data for a synthetic visual system to be used in the cockpit of aircraft when visual reference to ground features is not possible during conditions of marginal weather or reduced visibility. In this research, United States Geologic Survey (USGS) digital elevation model (DEM) data has been selected as the benchmark. Artificial Neural Networks (ANNS) have been used and tested as alternate methods in place of the statistical methods in similar problems. They often perform better in pattern recognition, prediction and classification and categorization problems. Many studies show that when the data is complex and noisy, the accuracy of ANN models is generally higher than those of comparable traditional methods.

Dryer, David↗
NASA NTRS2002

Thermocouple Calibration and Accuracy in a Materials Testing Laboratory

A consolidation of information has been provided that can be used to define procedures for enhancing and maintaining accuracy in temperature measurements in materials testing laboratories. These studies were restricted to type R and K thermocouples (TCs) tested in air. Thermocouple accuracies, as influenced by calibration methods, thermocouple stability, and manufacturer's tolerances were all quantified in terms of statistical confidence intervals. By calibrating specific TCs the benefits in accuracy can be as great as 6 C or 5X better compared to relying on manufacturer's tolerances. The results emphasize strict reliance on the defined testing protocol and on the need to establish recalibration frequencies in order to maintain these levels of accuracy.

Lerch, B. A.↗
NASA NTRS1993

Detecting the diurnal cycle of rainfall using satellite observations

The diurnal cycle in rainfall varies considerably from region to region in the tropics. Determining this variability is important both for comparing predictions of atmospheric models to real atmospheric behavior and for making sure that estimates of total rainfall from low-altitude satellites are not biased because of their infrequent observations of a given region of the earth. Although there are no data from the proposed Tropical Rainfall Measuring Mission (TRMM) satellite to work with yet, we can ask how well the diurnal cycle in rainfall will be detected when the satellite is eventually collecting data, given the satellite's proposed sampling characteristics. Data analyses for the diurnal cycle are discussed, taking into account the fact that the satellite visits will be irregularly spaced in time. The amplitudes of the first few harmonics will be determined by least-squares fits to the satellite observations, and the tests needed to establish the statistical significance of the fitted amplitudes are discussed. The accuracy with which the first few harmonics of the diurnal cycle can be detected is estimated from several months of satellite data using rainfall statistics observed during the GARP (Global Atmospheric Research Program) Atlantic Tropical Experiment (GATE).

Bell, Thomas L.↗
NASA NTRS1982

Characterization and measurement of phase-locked loop performance

A set of performance measures and tests are presented which can be implemented at the 'black box' level for the characterization of such statistical aspects of phase-locked loop behavior as the acquisition and tracking threshold, phase error jitter, Doppler accuracy, etc. Also presented is an automatic measurement system, designated the Statistical Loop Analyzer, which has been developed in order to undertake these phase-locked device performance measurements.

Lindsey, W. C.↗
NASA NTRS2015

Estimation of Aerosol Optical Depth at Different Wavelengths by Multiple Regression Method

This study aims to investigate and establish a suitable model that can help to estimate aerosol optical depth (AOD) in order to monitor aerosol variations especially during non-retrieval time. The relationship between actual ground measurements (such as air pollution index, visibility, relative humidity, temperature, and pressure) and AOD obtained with a CIMEL sun photometer was determined through a series of statistical procedures to produce an AOD prediction model with reasonable accuracy. The AOD prediction model calibrated for each wavelength has a set of coefficients. The model was validated using a set of statistical tests. The validated model was then employed to calculate AOD at different wavelengths. The results show that the proposed model successfully predicted AOD at each studied wavelength ranging from 340 nm to 1020 nm. To illustrate the application of the model, the aerosol size determined using measure AOD data for Penang was compared with that determined using the model. This was done by examining the curvature in the ln [AOD]-ln [wavelength] plot. Consistency was obtained when it was concluded that Penang was dominated by fine mode aerosol in 2012 and 2013 using both measured and predicted AOD data. These results indicate that the proposed AOD prediction model using routine measurements as input is a promising tool for the regular monitoring of aerosol variation during non-retrieval time.

Tan, Fuyi↗
NASA NTRS1977

JAN transistor and diode characterization test program: JANTX diode 1N759A

The necessary data to create a new class of specifications was the objective of this characterization program. Sample selection was made according to the following criteria: (1) manufacturer or qualified distributor; (2) two vendors; and (3) two date codes. The general guidelines for procurement were two QPL vendors, JAN or JANTX, and two manufacturing lots, 27 from each lot. All data were acquired with three digit accuracy. The data processing and calculation of statistical parameters were performed by the Tektronix computer system using 4 digit display.

Takeda, H.↗
NASA NTRS1979

Short-term solar activity forecasting

A method of forecasting the level of activity of every active region on the surface of the Sun within one to three days is proposed in order to estimate the possibility of the occurrence of ionospheric disturbances and proton events. The forecasting method is a probability process based on statistics. In many of the cases, the accuracy in predicting the short term solar activity was in the range of 70%, although there were many false alarms.

Xie-Zhen, C.↗
NASA NTRS1982

The intercrater plains of Mercury and the Moon: Their nature, origin and role in terrestrial planet evolution. Areal measurement of Mercury's first quadrant

Various linear and areal measurements of Mercury's first quadrant which were used in geological map preparation, map analysis, and statistical surveys of crater densities are discussed. Accuracy of each method rests on the determination of the scale of the photograph, i.e., the conversion factor between distances on the planet (in km) and distances on the photograph (in cm). Measurement errors arise due to uncertainty in Mercury's radius, poor resolution, poor coverage, high Sun angle illumination in the limb regions, planetary curvature, limited precision in measuring instruments, and inaccuracies in the printed map scales. Estimates are given for these errors.

Leake, M. A.↗
NASA NTRS1982

Natural hydrocarbon emission estimates based on Landsat data as an input to a regional ozone photochemical model

Landsat-derived forest cover data were employed with non-methane hydrocarbon (NMHC) emission rates in a model to quantify summer forest ozone production for the Tidewater Region of Virginia. The areal extent of the three major forest types - coniferous, deciduous, and mixed - were determined from Landsat data on two adjacent scenes, using an unsupervised approach to spectral signature development. The forest type results from both data sets were verified in an extensive accuracy assessment and merged to provide regional statistics for total acreages, percent forest, and error rates. The Landsat statistics were incorporated into forest type emission factor equations to produce an estimated emission rate for natural hydrocarbons from forests. This estimate, along with measured rates for nitrogen oxides and NMHC from anthropogenic sources, was provided as input to computer simulations of atmospheric ozone generation for the Tidewater Region using a photochemical oxident model.

Middleton, E. M.↗