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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Segmentation Of Multifrequency, Multilook SAR Data

Segmentation of multifrequency, multilook synthetic-aperture radar (SAR) image intensity data into regions, within each of which backscattering characteristics of target scene considered homogeneous, enhanced by use of two statistical models. One represents statistics of multifrequency, multilook speckled intensities of SAR picture elements; other represents statistics of labels applied to regions into which picture elements grouped. Each region represents different type of terrain, terrain cover, or other surface; e.g., forest, agricultural land, sea ice, or water. Segmentation of image into regions of neighboring picture elements accomplished by method similar to that described in "Algorithms For Segmentation Of Complex-Amplitude SAR Data" (NPO-18524).

Rignot, Eric J.↗
NASA NTRS1986

Statistics of the geomagnetic secular variation for the past 5Ma

A new statistical model is proposed for the geomagnetic secular variation over the past 5Ma. Unlike previous models, the model makes use of statistical characteristics of the present day geomagnetic field. The spatial power spectrum of the non-dipole field is consistent with a white source near the core-mantle boundary with Gaussian distribution. After a suitable scaling, the spherical harmonic coefficients may be regarded as statistical samples from a single giant Gaussian process; this is the model of the non-dipole field. The model can be combined with an arbitrary statistical description of the dipole and probability density functions and cumulative distribution functions can be computed for declination and inclination that would be observed at any site on Earth's surface. Global paleomagnetic data spanning the past 5Ma are used to constrain the statistics of the dipole part of the field. A simple model is found to be consistent with the available data. An advantage of specifying the model in terms of the spherical harmonic coefficients is that it is a complete statistical description of the geomagnetic field, enabling us to test specific properties for a general description. Both intensity and directional data distributions may be tested to see if they satisfy the expected model distributions.

Constable, C. G.↗
NASA NTRS1988

Statistics of the geomagnetic secular variation for the past 5 m.y

A new statistical model is proposed for the geomagnetic secular variation over the past 5Ma. Unlike previous models, the model makes use of statistical characteristics of the present day geomagnetic field. The spatial power spectrum of the non-dipole field is consistent with a white source near the core-mantle boundary with Gaussian distribution. After a suitable scaling, the spherical harmonic coefficients may be regarded as statistical samples from a single giant Gaussian process; this is the model of the non-dipole field. The model can be combined with an arbitrary statistical description of the dipole and probability density functions and cumulative distribution functions can be computed for declination and inclination that would be observed at any site on Earth's surface. Global paleomagnetic data spanning the past 5Ma are used to constrain the statistics of the dipole part of the field. A simple model is found to be consistent with the available data. An advantage of specifying the model in terms of the spherical harmonic coefficients is that it is a complete statistical description of the geomagnetic field, enabling us to test specific properties for a general description. Both intensity and directional data distributions may be tested to see if they satisfy the expected model distributions.

Constable, C. G.↗
DOE OSTI2025

Misclassification in Workers’ Telecommuting Frequency Choices Using a Generalized Extreme Value Model

Telecommuting frequency is a response variable collected in travel surveys and is, therefore, prone to errors leading to mismeasurements or misclassification. Misclassification of explanatory variables is a common risk when using statistical modeling techniques. We define “misclassification” as a response reported or recorded in the wrong category; for example, a variable is recorded as a 1 when it should be 0. Here, in this context, this study aims to develop a statistical model to analyze telecommuting data which accounts for potential misclassification errors by building on existing literature in econometrics. The empirical analysis was undertaken using the 2017 National Household Travel Survey (NHTS) and the general extreme value (GEV) models available in the literature. Specifically, the frequency of telecommuting days was analyzed using the negative binomial (NB) model recast as the multinomial logit (MNL) model. By nature—and consistent with other studies—NHTS data are prone to errors that can be classified as intentional or unintentional misinformation provided by the person being interviewed. Ignoring these errors while modeling telecommuting frequencies using standard discrete count models can result in biased parameter estimates. The misclassification parameter was calculated for both over-reporting and under-reporting scenarios. The misclassification errors can be as high as 14% over-reported and 10% under-reported, particularly for the neighboring values. Statistical fit comparison between the models shows that models that ignore misclassification have worse data fit and biased parameter estimates with significant policy implications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1990

The beam filling error in the Nimbus 5 electronically scanning microwave radiometer observations of Global Atlantic Tropical Experiment rainfall

A comparison of rain rates retrieved from the Nimbus 5 electronically scanning microwave radiometer brightness temperatures and observed from shipboard radars during the Global Atlantic Tropical Experiment (GATE) phase I shows that the beam filling error is the major source of discrepancy between the two. When averaged over a large scene (the GATE radar array, 400 km in diameter), the beam filling error is quite stable, being 50 percent of the observed rain rate. This suggests the simple procedure of multiplying retrieved rain rates by 2 (correction factor). A statistical model of the beam filling error is developed by envisioning an idealized instrument field-of-view that encompasses an entire gamma distribution of rain rates. A modeled correction factor near 2 is found for rain rate and temperature characteristics consistent with GATE conditions. The statistical model also suggests that the correction factor varies from 1.5 to 2.5 for suppressed to enhanced tropical convective regimes, and decreases to 1.5 as the freezing level and average depth of the rain column decreases to 2.5 km.

Short, David A.↗
NASA NTRS1986

The effect of the dynamic wet troposphere on VLBI measurements

Calculations using a statistical model of water vapor fluctuations yield the effect of the dynamic wet troposphere on Very Long Baseline Interferometry (VLBI) measurements. The statistical model arises from two primary assumptions: (1) the spatial structure of refractivity fluctuations can be closely approximated by elementary (Kolmogorov) turbulence theory, and (2) temporal fluctuations are caused by spatial patterns which are moved over a site by the wind. The consequences of these assumptions are outlined for the VLBI delay and delay rate observables. For example, wet troposphere induced rms delays for Deep Space Network (DSN) VLBI at 20-deg elevation are about 3 cm of delay per observation, which is smaller, on the average, than other known error sources in the current DSN VLBI data set. At 20-deg elevation for 200-s time intervals, water vapor induces approximately 1.5 x 10 to the minus 13th power s/s in the Allan standard deviation of interferometric delay, which is a measure of the delay rate observable error. In contrast to the delay error, the delay rate measurement error is dominated by water vapor fluctuations. Water vapor induced VLBI parameter errors and correlations are calculated. For the DSN, baseline length parameter errors due to water vapor fluctuations are in the range of 3 to 5 cm. The above physical assumptions also lead to a method for including the water vapor fluctuations in the parameter estimation procedure, which is used to extract baseline and source information from the VLBI observables.

Treuhaft, R. N.↗
NASA NTRS1983

Effects of preprocessing Landsat MSS data on derived features

Important to the use of multitemporal Landsat MSS data for earth resources monitoring, such as agricultural inventories, is the ability to minimize the effects of varying atmospheric and satellite viewing conditions, while extracting physically meaningful features from the data. In general, the approaches to the preprocessing problem have been derived from either physical or statistical models. This paper compares three proposed algorithms; XSTAR haze correction, Color Normalization, and Multiple Acquisition Mean Level Adjustment. These techniques represent physical, statistical, and hybrid physical-statistical models, respectively. The comparisons are made in the context of three feature extraction techniques; the Tasseled Cap, the Cate Color Cube. and Normalized Difference.

Parris, T. M.↗
NASA NTRS1991

The Marshall Engineering Thermosphere model atmosphere Statistical Analysis Mode (MET-SAM)

The minimum, mean, and maximum exospheric temperature on the globe were calculated for every three hour period from 1947 through 1989 using the algorithms in the Marshall Engineering Thermosphere (MET) model and the appropriate solar activity input parameters. Cumulative percent frequency (CPF) distributions were then calculated for each of these temperatures at five levels of solar activity as defined by the 13-month smoothed values of the 10.7-cm solar radio noise flux. Next, the 50, 95, 97.7, and 100 percentile temperature values in each of these five levels of solar activity were curve fit as a function of the 13-month smoothed 10.7-cm flux. The resulting algorithms are used to compute the exospheric temperature in the MET model instead of the technique developed by Jacchia in his 1970 model. These temperatures are then used to enter tables to determine the total mass density and/or the atomic oxygen number density for application to engineering problems. Users can specify the risk level they are willing to accept in the results of analyses that require neutral atmosphere parameters inputs. The model eliminates the guess work in how to combine the solar activity input parameters to insure that the results provide answers at the proper risk levels.

Smith, Robert E.↗
NASA NTRS1994

Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover, soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations.

Zhang, Taiping↗
NASA NTRS2015

Turbulent Concentration of mm-Size Particles in the Protoplanetary Nebula: Scale-Dependent Cascades

The initial accretion of primitive bodies (here, asteroids in particular) from freely-floating nebula particles remains problematic. Traditional growth-by-sticking models encounter a formidable "meter-size barrier" (or even a mm-to-cm-size barrier) in turbulent nebulae, making the preconditions for so-called "streaming instabilities" difficult to achieve even for so-called "lucky" particles. Even if growth by sticking could somehow breach the meter size barrier, turbulent nebulae present further obstacles through the 1-10km size range. On the other hand, nonturbulent nebulae form large asteroids too quickly to explain long spreads in formation times, or the dearth of melted asteroids. Theoretical understanding of nebula turbulence is itself in flux; recent models of MRI (magnetically-driven) turbulence favor low-or- no-turbulence environments, but purely hydrodynamic turbulence is making a comeback, with two recently discovered mechanisms generating robust turbulence which do not rely on magnetic fields at all. An important clue regarding planetesimal formation is an apparent 100km diameter peak in the pre-depletion, pre-erosion mass distribution of asteroids; scenarios leading directly from independent nebula particulates to large objects of this size, which avoid the problematic m-km size range, could be called "leapfrog" scenarios. The leapfrog scenario we have studied in detail involves formation of dense clumps of aerodynamically selected, typically mm-size particles in turbulence, which can under certain conditions shrink inexorably on 100-1000 orbit timescales and form 10-100km diameter sandpile planetesimals. There is evidence that at least the ordinary chondrite parent bodies were initially composed entirely of a homogeneous mix of such particles. Thus, while they are arcane, turbulent concentration models acting directly on chondrule size particles are worthy of deeper study. The typical sizes of planetesimals and the rate of their formation can be estimated using a statistical model with properties inferred from large numerical simulations of turbulence. Nebula turbulence is described by its Reynolds number Re = (L/eta)(exp 4/3), where L = H alpha(exp 1/2) is the largest eddy scale, H is the nebula gas vertical scale height, alpha the turbulent viscosity parameter, and eta is the Kolmogorov or smallest scale in turbulence (typically about 1km), with eddy turnover time t(sub eta). In the nebula, Re is far larger than any numerical simulation can handle, so some physical arguments are needed to extend the results of numerical simulations to nebula conditions. In this paper, we report new physics to be incorporated into our statistical models.

mm-size particles↗
NASA NTRS2019

On the Maximum Expected Electric Field in Electrically Small, Undermoded Enclosures

This paper reports the experimental validation of an improved statistical model for the prediction of maximum expected electric field in electrically small and under-moded enclosures. The aerospace community is interested in application of Hill's statistical models to design of avionics boxes for shielding effectiveness and for tailoring EMC test requirements for critical applications. However, it is observed that the probability distribution for mean-squared electric field in an electrically small enclosure differs from the exponential distribution which is widely used in reverberation chamber testing. It is postulated here that the difference is attributable to the under-moded character of the small enclosure.

Bremner, Paul↗
NASA NTRS2019

On the Maximum Expected Electric Field in Electrically Small, Undermoded Enclosures

This paper reports the experimental validation of an improved statistical model for the prediction of maximum expected electric field in electrically small and under-moded enclosures. The aerospace community is interested in application of Hill’s statistical models to design of avionics boxes for shielding effectiveness and for tailoring EMC test requirements for critical applications. However, it is observed that the probability distribution for mean-squared electric field (|E(sub x)|(exp 2)) in an electrically small enclosure differs from the exponential distribution which is widely used in reverberation chamber testing. It is postulated here that the difference is attributable to the under-moded character of the small enclosure. We will define “under-moded” as the condition where a single excitation frequency does not excite enough closely spaced resonant modes to achieve Hill’s assumption of an isotropic (or fully diffuse) plane wave field in the enclosure.

Bremner, P. G.↗
NASA NTRS2015

Online Dectection and Modeling of Safety Boundaries for Aerospace Application Using Bayesian Statistics

The behavior of complex aerospace systems is governed by numerous parameters. For safety analysis it is important to understand how the system behaves with respect to these parameter values. In particular, understanding the boundaries between safe and unsafe regions is of major importance. In this paper, we describe a hierarchical Bayesian statistical modeling approach for the online detection and characterization of such boundaries. Our method for classification with active learning uses a particle filter-based model and a boundary-aware metric for best performance. From a library of candidate shapes incorporated with domain expert knowledge, the location and parameters of the boundaries are estimated using advanced Bayesian modeling techniques. The results of our boundary analysis are then provided in a form understandable by the domain expert. We illustrate our approach using a simulation model of a NASA neuro-adaptive flight control system, as well as a system for the detection of separation violations in the terminal airspace.

Statistics↗
NASA NTRS2004

Novel Image Processing Interface to Relate DSB Spatial Distribution from Immunofluorescence Foci Experiments to the State-of-the-Art Models of DNA Breakage

A recently developed software (NASARadiationTrackImage) allows a quick and automatic segmentation of foci that indicate spatial localization of specific proteins that are visualized by immunofluorescence. Of interest are the spatial and temporal distribution of foci such as gammaH2AX, a signal of the phosphorylation of a variant of the histone H2A that has been shown to correspond to DSBs, or proteins involved in DSB processing, such as ATM, Rad51, and p53, following exposures of human cells to high charge and energy (HZE) ion irradiation. Experimental data are recorded as sets of two-dimensional images in color with cells and foci of gammaH2AX, ATM, Rad51 or others shown. Different cells, levels of radiation and timing after radiation were recorded. The software allows us to calculate the number of foci per cell, overall intensity of light in foci and their spatial organization. A simple statistical model allows for testing of foci overlap (eclipse). A more complex statistical model previously known as DNAbreak simulates track structure and random chromosome geometry. It has one adjustable parameter corresponding to an average intensity of DSB creation in cubic micrometers of DNA volume per particle track or unit dose. Its limitation is the low-resolution limit both in physical space and DSB's along DNA. It works adequately on the scale of a cell and provides further insights on how the geometry of tracks and DNA affects genomic damage of the cell and subsequent repair. Future developments of the model for the description of the time evolution of DNA damage response proteins, and more robust track structure models will be discussed.

Ponomarev, A. L.↗
NASA NTRS1995

Compilation and Analysis of 20- and 30-GHz Rain Fade Events at the ACTS NASA Ground Station: Statistics and Model Assessment

Since the beginning of the operational phase of the NASA Research Center's Advanced Communication Technology Satellite (ACTS), signal-fade measurements have been recorded at the NASA Ground Station located in Cleveland, Ohio, with the use of the 20- and 30-GHz beacon signals. Compilations of the daily data have been statistically analyzed on a monthly and yearly basis. Such analyses have yielded relevant parameters as (1) cumulative monthly and yearly probability distributions of signal attenuation by rain, (2) attenuation duration versus attenuation threshold probabilities, and (3) rate-of-fade probabilities. Not only are such data needed for a realistic data base to support the design and performance analysis of future satellite systems, but they are necessary to assess predictions made with the ACTS Rain Attenuation Prediction Model.

Manning, Robert M.↗
DOE OSTI2025

First Measurement of 87 Rb( α , xn ) Cross Sections at Weak r -process Energies in Supernova ν -driven Ejecta to Investigate Elemental Abundances in Low-metallicity Stars

Observed abundances of Z ∼ 40 elements in metal-poor stars vary from star to star, indicating that the rapid and slow neutron capture processes may not contribute alone to the synthesis of elements beyond iron. The weak r-process was proposed to produce Z ∼ 40 elements in a subset of old stars. Thought to occur in the ν-driven ejecta of a core-collapse supernova, ( α, xn ) reactions would drive the nuclear flow toward heavier masses at T = 2−5 GK. However, current comparisons between modeled and observed yields do not bring satisfactory insights into the stellar environment, mainly due to the uncertainties of the nuclear physics inputs where the dispersion in a given reaction rate often exceeds 1 order of magnitude. Involved rates are calculated with the statistical model where the choice of an α -optical-model potential ( α OMP) leads to such a poor precision. The first experiment on 87 Rb( α, xn ) reactions at weak r -process energies is reported here. Total inclusive cross sections were assessed at E c.m. = 8.1−13 MeV (3.7−7.6 GK) with the active target MUlti-Sampling Ionization Chamber. With an N = 50 seed nucleus, the measured values agree with statistical model estimates using the α OMP Atomki-V2. A reevaluated reaction rate was incorporated into new nucleosynthesis calculations, focusing on ν-driven ejecta conditions known to be sensitive to this specific rate. These conditions were found to fail to reproduce the lighter heavy element abundances in metal-poor stars.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2004

The Application of Probabilistic Methods to the Mistuning Problem

FMM is a reduced order model for efficiently calculating the forced response of a mistuned bladed disk. FMM ID is a companion program which determines the mistuning in a particular rotor. Together, these methods provide a way to acquire data on the mistuning in a population of bladed disks, and then simulate the forced response of the fleet. This process is tested experimentally, and the simulated results are compared with laboratory measurements of a fleet of test rotors. The method is shown to work quite well. It is found that accuracy of the results depends on two factors: the quality of the statistical model used to characterize mistuning, and how sensitive the system is to errors in the statistical modeling.

Griffin, J. H.↗
NASA NTRS1991

Total ozone trends deduced from Nimbus 7 TOMS data

The Total Ozone Mapping Spectrometer (TOMS) on the Nimbus 7 satellite has been measuring the total column amount of ozone over the globe for more than 11 years. Recent improvements in the data analysis have led to a technique for determining and removing drift in the calibration such that the data at the end of the record are precise to + or - 1.3 percent (2-sigma) relative to the data at the beginning of the record. A statistical model, including terms for seasonal variation, linear trend, quasi-biennial oscillation, solar cycle and second-order autoregressive noise has been fit to the TOMS time series of total ozone data. The linear trend obtained when this statistical model is fit to the TOMS data averaged between 65 N and 65 S latitudes is -0.26 + or - 0.14 percent/year or -3 percent over the 11.6 year time period from November 1978 to May 1990. The trend is near zero (0.0002 + or - 0.2 percent/year) at the equator and increases toward both poles.

Stolarski, Richard S.↗