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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 37 records · Page 2

Physically-based parameterization of spatially variable soil and vegetation using satellite multispectral data

A stochastic-geometric landsurface reflectance model is formulated and tested for the parameterization of spatially variable vegetation and soil at subpixel scales using satellite multispectral images without ground truth. Landscapes are conceptualized as 3-D Lambertian reflecting surfaces consisting of plant canopies, represented by solid geometric figures, superposed on a flat soil background. A computer simulation program is developed to investigate image characteristics at various spatial aggregations representative of satellite observational scales, or pixels. The evolution of the shape and structure of the red-infrared space, or scattergram, of typical semivegetated scenes is investigated by sequentially introducing model variables into the simulation. The analytical moments of the total pixel reflectance, including the mean, variance, spatial covariance, and cross-spectral covariance, are derived in terms of the moments of the individual fractional cover and reflectance components. The moments are applied to the solution of the inverse problem: The estimation of subpixel landscape properties on a pixel-by-pixel basis, given only one multispectral image and limited assumptions on the structure of the landscape. The landsurface reflectance model and inversion technique are tested using actual aerial radiometric data collected over regularly spaced pecan trees, and using both aerial and LANDSAT Thematic Mapper data obtained over discontinuous, randomly spaced conifer canopies in a natural forested watershed. Different amounts of solar backscattered diffuse radiation are assumed and the sensitivity of the estimated landsurface parameters to those amounts is examined.

Jasinski, Michael F.↗

Optical and radio variability in blazars

An analysis is presented of the optical (0.44 micron) and radio flux density variations (4.8, 8.0, and 14.5 GHz) of the five best observed variable AGN, of which three are BL Lac objects and two are optically violent variable (OVV) quasars. For each object the nature of the variability at individual wavelengths is determined by using a structure function analysis and the autocorrelation function as calculated from the discrete correlation technique. Both techniques yield similar results, showing that the optical variations are similar for all objects and are a combination of flicker and shot noise. The radio variability is distinct, being described by shot noise (less variation at short times), with the two OVVs exhibiting the most extreme behavior. The time lag between the variations at the three radio frequencies and the optical flux is studied with the discrete cross-correlation function and the mean variance methods. It is concluded that the optical and radio emitting regions are physically related, exist on distinct time scales, and excite their synchrotron emitting plasmas differently.

Hufnagel, Beth R.↗

Estimates of tropical analysis differences in daily values produced by two operational centers

To assess the uncertainty of daily synoptic analyses for the atmospheric state, the intercomparison of three First GARP Global Experiment level IIIb datasets is performed. Daily values of divergence, vorticity, temperature, static stability, vertical motion, mixing ratio, and diagnosed diabatic heating rate are compared for the period of 26 January-11 February 1979. The spatial variance and mean, temporal mean and variance, 2D wavenumber power spectrum, anomaly correlation, and normalized square difference are employed for comparison.

Kasahara, Akira↗

An investigation of error correcting techniques for OMV and AXAF

The original objectives of this project were to build a test system for the NASA 255/223 Reed/Solomon encoding/decoding chip set and circuit board. This test system was then to be interfaced with a convolutional system at MSFC to examine the performance of the concantinated codes. After considerable work, it was discovered that the convolutional system could not function as needed. This report documents the design, construction, and testing of the test apparatus for the R/S chip set. The approach taken was to verify the error correcting behavior of the chip set by injecting known error patterns onto data and observing the results. Error sequences were generated using pseudo-random number generator programs, with Poisson time distribution between errors and Gaussian burst lengths. Sample means, variances, and number of un-correctable errors were calculated for each data set before testing.

Ingels, Frank↗

Probabilistic finite elements for fatigue and fracture analysis

Attenuation is focused on the development of Probabilistic Finite Element Method (PFEM), which combines the finite element method with statistics and reliability methods, and its application to linear, nonlinear structural mechanics problems and fracture mechanics problems. The computational tool based on the Stochastic Boundary Element Method is also given for the reliability analysis of a curvilinear fatigue crack growth. The existing PFEM's have been applied to solve for two types of problems: (1) determination of the response uncertainty in terms of the means, variance and correlation coefficients; and (2) determination the probability of failure associated with prescribed limit states.

Belytschko, Ted↗

Truncated Gaussians as tolerance sets

This work focuses on the use of truncated Gaussian distributions as models for bounded data measurements that are constrained to appear between fixed limits. The authors prove that the truncated Gaussian can be viewed as a maximum entropy distribution for truncated bounded data, when mean and covariance are given. The characteristic function for the truncated Gaussian is presented; from this, algorithms are derived for calculation of mean, variance, summation, application of Bayes rule and filtering with truncated Gaussians. As an example of the power of their methods, a derivation of the disparity constraint (used in computer vision) from their models is described. The authors' approach complements results in Statistics, but their proposal is not only to use the truncated Gaussian as a model for selected data; they propose to model measurements as fundamentally in terms of truncated Gaussians.

Cozman, Fabio↗

Integral-moment analysis of the BATSE gamma-ray burst intensity distribution

We have applied the technique of integral-moment analysis to the intensity distribution of the first 260 gamma-ray bursts observed by the Burst and Transient Source Experiment (BATSE) on the Compton Gamma Ray Observatory. This technique provides direct measurement of properties such as the mean, variance, and skewness of the convolved luminosity-number density distribution, as well as associated uncertainties. Using this method, one obtains insight into the nature of the source distributions unavailable through computation of traditional single parameters such as V/V(sub max)). If the luminosity function of the gamma-ray bursts is strongly peaked, giving bursts only a narrow range of luminosities, these results are then direct probes of the radial distribution of sources, regardless of whether the bursts are a local phenomenon, are distributed in a galactic halo, or are at cosmological distances. Accordingly, an integral-moment analysis of the intensity distribution of the gamma-ray bursts provides for the most complete analytic description of the source distribution available from the data, and offers the most comprehensive test of the compatibility of a given hypothesized distribution with observation.

Horack, John M.↗

Correlated noise in the COBE DMR sky maps

The Cosmic Background Explorer Satellite Differential Radiometer (COBE DMR) sky maps contain low-level correlated noise. We obtain estimates of the amplitude and pattern of the correlated noise from three techniques: angular averages of the covariance matrix, Monte Carlo simulations of two-point correlation functions and direct analysis of the DMR maps. The results from the three methods are mutually consistent. The noise covariance matrix of a DMR sky maps is diagonal to an accuracy of better than 1%. For a given sky pixel, the dominant noise covariance occure with the ring of pixels at an angular separation of 60 deg due to the 60 deg separation of the DMR horns. The mean covariance at 60 deg is 0.45%((sup +0.18)(sub -0.14)) of the mean variance. Additionally, the variance in a given pixel is 0.7% greater than would be expected from a single beam experiment with the same noise properties. Autocorrelation functions suffer from a approximately 1.5 sigma positive bias at 60 deg while cross-correlations have no bias. Published COBE DMR results are not significantly affected by correlated noise.

Lineweaver, C. H.↗

Viking Lander image analysis of Martian atmospheric dust

We have reanalyzed three sets of Viking Lander 1 and 2 (VL1 and VL2) images of the Martian atmosphere to better evaluate the radiative properties of the atmospheric dust particles. The properties of interest are the first two moments of the size distribution, the single-scattering albedo, the dust single-scattering phase function, and the imaginary index of refraction. These properties provide a good definition of the influence that the atmospheric dust has on heating of the atmosphere. Our analysis represents a significant improvement over past analyses (Pollack et al. 1977, 1979) by deriving more accurate brightness closer to the sun, by carrying out more precise analyses of the data to acquire the quantities of interest, and by using a better representation of scattering by nonspherical particles. The improvements allow us to better define the diffraction peak and hence the size distribution of the particles. For a lognormal particle size distribution, the first two moments of the size distribution, weighted by the geometric cross section, are found. The geometric cross-section weighted mean radius r(sub eff) is found to be 1.85 +/- 0.3 micrometers at VL2 during northern summer when dust loading was low and 1.52 +/- 0.3 micrometers at VL1 during the first dust storm. In both cases the best cross-section weighted mean variance nu(sub eff) of the size distribution is equal to 0.5 +/- 0.2 micrometers. The changes in size distribution, and thus radiative properties, do not represent a substantial change in solar energy deposition in the atmosphere over the Pollak et al. (1977, 1979) estimates.

Pollack, James B.↗

Distributions of the interplanetary magnetic field revisited

The adequacy of the power spectrum to characterize the variations of a parameter depends on whether or not the parameter has a Gaussian distribution. We here perform very simple tests of Gaussianity on the distribution. We here perform very simple tests of Gaussianity on the distributions of the magnitudes of the interplanetary magnetic field, and on the distributions of the components; that is, we find the first four cumulants of the distributions (mean, variance, skewness, and kurtosis) and their solar cycle variations. We find, consistent with other recent analyses, that the traditional distributions of the 1-hour averaged magnitude are not distributed normally or lognomally as has often been assumed and the 1-hour averaged z component is found to have a nonzero kurtosis. Thus the power spectrum is insufficient to completely characterize these variations and polyspectra are needed. We have isolated variations in the 1/f frequency region of the spectrum and show that the distributions of the magnitudes have nonzero skewness and kurtosis, the magnitudes are not distributed lognormally, and the distributions of the components have nonzero kurtosis. Thus higher-order spectra are again needed for a full characterization.

Feynman, Joan↗

Inverse sequential procedures for the monitoring of time series

When one or more new values are added to a developing time series, they change its descriptive parameters (mean, variance, trend, coherence). A 'change index (CI)' is developed as a quantitative indicator that the changed parameters remain compatible with the existing 'base' data. CI formulate are derived, in terms of normalized likelihood ratios, for small samples from Poisson, Gaussian, and Chi-Square distributions, and for regression coefficients measuring linear or exponential trends. A substantial parameter change creates a rapid or abrupt CI decrease which persists when the length of the bases is changed. Except for a special Gaussian case, the CI has no simple explicit regions for tests of hypotheses. However, its design ensures that the series sampled need not conform strictly to the distribution form assumed for the parameter estimates. The use of the CI is illustrated with both constructed and observed data samples, processed with a Fortran code 'Sequitor'.

Radok, Uwe↗

Viking Lander image analysis of Martian atmospheric dust

We have reanalyzed three sets of Viking Lander 1 and 2 (VL1 and VL2) images of the Martian atmosphere to better evaluate the radiative properties of the atmospheric dust particles. The properties of interest are the first two moments of the size distribution, the single-scattering albedo, the dust single-scattering phase function, and the imaginary index of refraction. These properties provide a good definition of the influence that the atmospheric dust has on heating of the atmosphere. Our analysis represents a significant improvement over past analyses (Pollack et al. 1977,1979) by deriving more accurate brightnesses closer to the sun, by carrying out more precise analyses of the data to acquire the quantities of interest, and by using a better representation of scattering by nonspherical particles. The improvements allow us to better define the diffraction peak and hence the size distribution of the particles. For a lognormal particle size distribution, the first two moments of the size distribution, weighted by the geometric cross section, are found. The geometric cross-section weighted mean radius (r(sub eff)) is found to be 1.85 +/- 0.3 microns at VL2 during northern summer when dust loading was low and 1.52 +/- 0.3 microns at VL1 during the first dust storm. In both cases the best cross-section weighted mean variance (nu(eff)) of the size distribution is equal to 0.5 +/- 0.2 microns. The changes in size distribution, and thus radiative properties, do not represent a substantial change in solar energy deposition in the atmosphere over the Pollack et al. (1977,1979) estimates.

Pollack, James B.↗

Analysis of Darwin Rainfall Data: Implications on Sampling Strategy

Rainfall data collected by radar in the vicinity of Darwin, Australia, have been analyzed in terms of their mean, variance, autocorrelation of area-averaged rain rate, and diurnal variation. It is found that, when compared with the well-studied GATE (Global Atmospheric Research Program Atlantic Tropical Experiment) data, Darwin rainfall has larger coefficient of variation (CV), faster reduction of CV with increasing area size, weaker temporal correlation, and a strong diurnal cycle and intermittence. The coefficient of variation for Darwin rainfall has larger magnitude and exhibits larger spatial variability over the sea portion than over the land portion within the area of radar coverage. Stationary, and nonstationary models have been used to study the sampling errors associated with space-based rainfall measurement. The nonstationary model shows that the sampling error is sensitive to the starting sampling time for some sampling frequencies, due to the diurnal cycle of rain, but not for others. Sampling experiments using data also show such sensitivity. When the errors are averaged over starting time, the results of the experiments and the stationary and nonstationary models match each other very closely. In the small areas for which data are available for I>oth Darwin and GATE, the sampling error is expected to be larger for Darwin due to its larger CV.

Rafael, Qihang Li↗

Experiences with Probabilistic Analysis Applied to Controlled Systems

This paper presents a semi-analytic method for computing frequency dependent means, variances, and failure probabilities for arbitrarily large-order closed-loop dynamical systems possessing a single uncertain parameter or with multiple highly correlated uncertain parameters. The approach will be shown to not suffer from the same computational challenges associated with computing failure probabilities using conventional FORM/SORM techniques. The approach is demonstrated by computing the probabilistic frequency domain performance of an optimal feed-forward disturbance rejection scheme.

Kenny, Sean P.↗

A Method for Retrieving Ground Flash Fraction from Satellite Lightning Imager Data

A general theory for retrieving the fraction of ground flashes in N lightning observed by a satellite-based lightning imager is provided. An "exponential model" is applied as a physically reasonable constraint to describe the measured optical parameter distributions, and population statistics (i.e., mean, variance) are invoked to add additional constraints to the retrieval process. The retrieval itself is expressed in terms of a Bayesian inference, and the Maximum A Posteriori (MAP) solution is obtained. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The ability to retrieve ground flash fraction has important benefits to the atmospheric chemistry community. For example, using the method to partition the existing satellite global lightning climatology into separate ground and cloud flash climatologies will improve estimates of lightning nitrogen oxides (NOx) production; this in turn will improve both regional air quality and global chemistry/climate model predictions.

Koshak, William J.↗

Second Cancers After Fractionated Radiotherapy: Stochastic Population Dynamics Effects

When ionizing radiation is used in cancer therapy it can induce second cancers in nearby organs. Mainly due to longer patient survival times, these second cancers have become of increasing concern. Estimating the risk of solid second cancers involves modeling: because of long latency times, available data is usually for older, obsolescent treatment regimens. Moreover, modeling second cancers gives unique insights into human carcinogenesis, since the therapy involves administering well characterized doses of a well studied carcinogen, followed by long-term monitoring. In addition to putative radiation initiation that produces pre-malignant cells, inactivation (i.e. cell killing), and subsequent cell repopulation by proliferation can be important at the doses relevant to second cancer situations. A recent initiation/inactivation/proliferation (IIP) model characterized quantitatively the observed occurrence of second breast and lung cancers, using a deterministic cell population dynamics approach. To analyze ifradiation-initiated pre-malignant clones become extinct before full repopulation can occur, we here give a stochastic version of this I I model. Combining Monte Carlo simulations with standard solutions for time-inhomogeneous birth-death equations, we show that repeated cycles of inactivation and repopulation, as occur during fractionated radiation therapy, can lead to distributions of pre-malignant cells per patient with variance >> mean, even when pre-malignant clones are Poisson-distributed. Thus fewer patients would be affected, but with a higher probability, than a deterministic model, tracking average pre-malignant cell numbers, would predict. Our results are applied to data on breast cancers after radiotherapy for Hodgkin disease. The stochastic IIP analysis, unlike the deterministic one, indicates: a) initiated, pre-malignant cells can have a growth advantage during repopulation, not just during the longer tumor latency period that follows; b) weekend treatment gaps during radiotherapy, apart from decreasing the probability of eradicating the primary cancer, substantially increase the risk of later second cancers.

Sachs, Rainer K.↗

Dual-Frequency Observations of 140 Compact, Flat-Spectrum Active Galactic Nuclei for Scintillation-Induced Variability

The 4.9 GHz Micro-Arcsecond Scintillation-Induced Variability (MASIV) Survey detected a drop in Interstellar Scintillation (ISS) for sources at red shifts z > or approx. 2, indicating an apparent increase in angular diameter or a decrease in flux density of the most compact components of these sources, relative to their extended emission. This can result from intrinsic source size effects or scatter broadening in the Intergalactic Medium (IGM) , in excess of the expected (1+z)1/2 angular diameter scaling of brightness temperature limited sources resulting from cosmological expansion. We report here 4.9 GHz and 8.4 GHz observations and data analysis for a sample of 140 compact, fiat-spectrum sources which may allow us to determine the origin of this angular diameter-redshift relation by exploiting their different wavelength dependences. In addition to using ISS as a cosmological probe, the observations provide additional insight into source morphologies and the characteristics of ISS. As in the MASIV Survey, the variability of the sources is found to be significantly correlated with line-of-sight H(alpha) intensities, confirming its link with ISS. For 25 sources, time delays of about 0.15 to 3 days are observed between the scintillation patterns at both frequencies, interpreted as being caused by a shift in core positions when probed at different optical depths. Significant correlation is found between ISS amplitudes and source spectral index; in particular, a large drop in ISS amplitudes is observed at alpha < -0.4 confirming that steep spectrum sources scintillate less. We detect a weakened redshift dependence of ISS at 8.4 GHz over that at 4.9 GHz, with the mean variance at 4-day timescales reduced by a factor of 1.8 in the z > 2 sources relative to the z < 2 sources, as opposed to the factor of 3 decrease observed at 4.9 GHz. This suggests scatter broadening in the IGM, but the interpretation is complicated by subtle selection effects that will be explored further in a follow-up paper.

Koay, J. Y.↗

A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications

Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort.

Grauer, Jared A.↗