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NASA NTRS1995

Modeling the light-travel-time effect on the far-infrared size of IRC +10216

Models of the far-infrared emission from the large circumstellar dust envelope surrounding the carbon star IRC +10216 are used to assess the importance of the light-travel-time effect (LTTE) on the observed size of the source. The central star is a long-period variable with an average period of 644 +/- 17 days and a peak-to-peak amplitude of two magnituds, so a large light-travel-time effect is seen at 1 min radius. An attempt is made to use the LTTE to reconcile the discrepancy between the observations of Fazio et al. and Lester et al. regarding the far-infrared source size. This discrepancy is reviewed in light of recent, high-spatial-resolution observations at 11 microns by Danchi et al. We conclude that IRC +10216 has been resolved on the arcminute scale by Fazio et al. Convolution of the model intensity profile at 61 microns with the 60 sec x 90 sec Gaussian beam of Fazio et al. yields an observed source size full width at half maximum (FWHM) that ranges from approximately 67 sec to 75 sec depending on the phase of the star and the assumed distance to the source. Using a simple r(exp -2) dust distribution and the 106 deg phase of the Fazio et al. observations, the LTTE model reaches a peak size of 74.3 sec at a distance of 300 pc. This agrees favorably with the 78 sec x 6 sec size measured by Fazio et al. Finally, a method is outlined for using the LTTE as a distance indicator to IRC +10216 and other stars with extended mass outflows.

Wright, Edward L.↗

NASA NTRS1986

Unified control/structure design and modeling research

To demonstrate the applicability of the control theory for distributed systems to large flexible space structures, research was focused on a model of a space antenna which consists of a rigid hub, flexible ribs, and a mesh reflecting surface. The space antenna model used is discussed along with the finite element approximation of the distributed model. The basic control problem is to design an optimal or near-optimal compensator to suppress the linear vibrations and rigid-body displacements of the structure. The application of an infinite dimensional Linear Quadratic Gaussian (LQG) control theory to flexible structure is discussed. Two basic approaches for robustness enhancement were investigated: loop transfer recovery and sensitivity optimization. A third approach synthesized from elements of these two basic approaches is currently under development. The control driven finite element approximation of flexible structures is discussed. Three sets of finite element basic vectors for computing functional control gains are compared. The possibility of constructing a finite element scheme to approximate the infinite dimensional Hamiltonian system directly, instead of indirectly is discussed.

Mingori, D. L.↗

NASA NTRS1998

Comparison of Response Surface and Kriging Models for Multidisciplinary Design Optimization

In this paper, we compare and contrast the use of second-order response surface models and kriging models for approximating non-random, deterministic computer analyses. After reviewing the response surface method for constructing polynomial approximations, kriging is presented as an alternative approximation method for the design and analysis of computer experiments. Both methods are applied to the multidisciplinary design of an aerospike nozzle which consists of a computational fluid dynamics model and a finite-element model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations, and four optimization problems m formulated and solved using both sets of approximation models. The second-order response surface models and kriging models-using a constant underlying global model and a Gaussian correlation function-yield comparable results.

Simpson, Timothy W.↗

NASA NTRS2001

Variable Iron K(alpha) Lines in Seyfert 1 Galaxies

We find that variability of the iron K alpha line is common in Seyfert 1 galaxies. Using data from the ASCA archive for objects that have been observed more than once during the mission, we study the time-averaged spectra from individual observations, thereby probing variability on timescales that range from days to years. Since the statistics of the data do not warrant searches for line variability in terms of a complex physical model, we use a simple Gaussian to model the gross shape of the line and then use the centroid energy, intensity, and equivalent width as robust indicators of changes in the line profile. We find that approximately 70% of Seyfert 1 galaxies (10 out of 15) show variability in at least one of these parameters: the centroid energy, intensity, and equivalent width vary in six, four, and eight sources, respectively. Because of the low signal-to-noise ratio, limited sampling, and time averaging, we consider these results to represent lower limits to the rate of incidence of variability. In most cases changes in the line do not appear to track changes in the continuum. In particular, we find no evidence for variability of the line intensity in NGC 4151, suggesting an origin in a region larger than the putative accretion disk, where most of the iron line has been thought to originate. Mrk 279 is investigated on short timescales. The time-averaged effective line energy (as measured by the Gaussian center energy, which is weighted by emission in the entire line profile) is 6.5 keV in the galaxy rest frame. As the continuum flux increases by 20% in a few hours, the Fe K line responds within approximately 10,000 seconds with the effective line energy increasing by 0.22 keV (approximately 10,500 kilometers per second). We also examine the ROSAT PSPC spectrum of Mrk 279 but find inconsistencies with ASCA. Problems with the ASCA and ROSAT calibration that affect simultaneous spectral fits at low energies are discussed in an appendix.

Weaver, K. A.↗

NASA NTRS1975

Adaptive Bayes classifiers for remotely sensed data

An algorithm is developed for a learning, adaptive, statistical pattern classifier for remotely sensed data. The estimation procedure consists of two steps: (1) an optimal stochastic approximation of the parameters of interest, and (2) a projection of the parameters in time and space. The results reported are for Gaussian data in which the mean vector of each class may vary with time or position after the classifier is trained.

Raulston, H. S.↗

NASA NTRS1976

Velocity dispersions in galaxies. V - The nuclei of M31 and M32

Stigmatic spectra between 4160 and 4385 A of the central regions of M31 and M32 as well as the K0 III star 51 Ori are presented which were obtained using a SEC-vidicon integrating television tube and the coude spectrograph of the Hale telescope. Line-of-sight velocity dispersions of approximately 130 and 55 km/s are determined for the nuclei of M31 and M32, respectively, by directly comparing their spectra with Gaussian-broadened spectra of 51 Ori. The analytical techniques are outlined, and alternative methods for estimating velocity dispersions are evaluated, including least-squares fitting of intensities and division of Fourier transforms. It is noted that the broadened spectrum of 51 Ori fits the nucleus of M32 and the bulge of M31 much better than the nucleus of M31 in the region between 4180 and 4370 A.

Morton, D. C.↗

NASA NTRS1985

Integral functions of electron lateral distribution and their fluctuations in electron-photon cascades

Monte Carlo simulated lateral distribution functions for electrons of EPC developing in lead, at superhigh energies (.1-1 PeV) for depths t or = 60 c.u. delta t=1t. c.u. are presented. The higher moment characteristics, i.e., variation, asymmetry, excess, are presented along with analytical solutions for the same characteristics at fixed observation level calculated to theory approximations A and B by using numerical inversion of the Laplace transformation. The conclusion is made of a complex, usually non-Gaussian shape of the function of the particle number distribution within a circle of given radius at fixed depth.

Ivanenko, I. P.↗

NASA NTRS1994

VLA stereoscopy of solar active regions. 1: Method and tests

We develop a new technique for extracting three-dimensional information from multiday solar Very Large Array (VLA) observations. While standard stereoscopic methods provide a three-dimensional view of an object by combining simultaneous observations from two different aspect angles, we relax the condition of simultaneity and exploit solar rotation to vary the aspect angle. The solar radio images are decomposed into Gaussian source components, which are then cross-correlated in maps from preceding and following days. This provides measurements of the three-dimensional position of correlated source centroids. In this first paper, we describe the stereoscopic method and perform tests with simulated and real radio maps (from the VLA at 20 cm), in order to study the accuracy of altitude measurements, and the limitations introduced by (i) source confusion, (ii) source motion, and (iii) the assumed differential rotation rate. The tests demonstrate that (i) the information content of a VLA map relevant for stereoscopic correlation can be conveniently represented in terms of a small number of Gaussian components; (ii) the fitting of the three-dimensional source position is stable within a numerical accuracy of less than or approximately equal to 0.02 map pixels, (iii) the relative accuracy of the altitude determination is uniform over the solar disk, and (iv) source confusion does not affect the accuracy of stereoscopic position measurements for sources with a signal-to-noise ratio of greater than or approximately equal to 36.

Aschwanden, Markus J.↗

NASA NTRS1988

Convolution-controlled rotation and scale invariance in optical correlation

A method is presented for evoking a controlled, continuously-variable degree of rotation- and scale-invariance in optical correlation; the method is suitable for off-line computation of filters, though not for real-time computation. While a closed-form solution for the blur kernels has thus far evaded solution, a digital approximation method has been presented. A simulated correlation run with real, frame-grabbed imagery has indicated the method's desired performance. These Gaussian blur kernels can be replaced with box-car kernels or other blur kernels suitable for the given correlation-task.

Juday, Richard D.↗

NASA NTRS1989

A forward error correction technique using a high-speed, high-rate single chip codec

The authors describe an error-correction coding approach that allows operation in either burst or continuous modes at data rates of multiple hundreds of megabits per second. Bandspreading is low since the code rate is 7/8 or greater, which is consistent with high-rate link operation. The encoder, along with a hard-decision decoder, fits on a single application-specific integrated circuit (ASIC) chip. Soft-decision decoding is possible utilizing applique hardware in conjunction with the hard-decision decoder. Expected coding gain is a function of the application and is approximately 2.5 dB for hard-decision decoding at 10-5 bit-error rate with phase-shift-keying modulation and additive Gaussian white noise interference. The principal use envisioned for this technique is to achieve a modest amount of coding gain on high-data-rate, bandwidth-constrained channels. Data rates of up to 300 Mb/s can be accommodated by the codec chip. The major objective is burst-mode communications, where code words are composed of 32 n data bits followed by 32 overhead bits.

Boyd, R. W.↗

NASA NTRS1992

Bispectral analysis of equatorial spread F density irregularities

Bispectral analysis has been applied to density irregularities at frequencies 5-30 Hz observed with a sounding rocket launched from Peru in March 1983. Unlike the power spectrum, the bispectrum contains statistical information about the phase relations between the Fourier components which make up the waveform. In the case of spread F data from 475 km the 5-30 Hz portion of the spectrum displays overall enhanced bicoherence relative to that of the background instrumental noise and to that expected due to statistical considerations, implying that the observed f exp -2.5 power law spectrum has a significant non-Gaussian component. This is consistent with previous qualitative analyses. The bicoherence has also been calculated for simulated equatorial spread F density irregularities in approximately the same wavelength regime, and the resulting bispectrum has some features in common with that of the rocket data. The implications of this analysis for equatorial spread F are discussed, and some future investigations are suggested.

Labelle, J.↗

NASA NTRS1993

Polarimetric backscattering from sea ice

Polarimetric backscattering from sea ice is presented. Theoretical models for backscattering are first presented for various ice types. Then, theoretical results are compared with experimental data for new thin ice, first-year ice, and multi-year ice. Sea ice is modeled as a layer medium containing random scatterers and rough interfaces. For multi-year sea ice with snow cover, the sea ice layer is modeled as an ice background with embedded spheroidal air bubbles and the snow layer as air with ice grains. The hummocky topography on multi-year ice is characterized by a Gaussian distribution which has an averaging effect on backscattering coefficients. First-year sea ice is described by an ice medium hosting ellipsoidal brine inclusions. These inclusions are oriented preferentially in the vertical direction due to the columnar structure of first-year sea ice. Azimuthally, the orientation of the brine pockets are random corresponding to the random c-axes in sea ice, unless the axes are oriented by sea currents. For thin ice in newly opened leads, it has been observed that there exists a thin brine layer with very high salinity on the top surface of the new ice. This brine layer is depicted as a medium with high permittivity which can significantly affect electromagnetic scattering signatures from the lower thin ice layer, with a higher fractional volume of brine inclusions due to higher salinity as compared to thick first-year sea ice. The rough medium interfaces are described as Gaussian rough surfaces characterized by root-mean-square heights and surface correlation lengths. The contribution from rough surface, calculated under the Kirchhoff approximation or small perturbation method, is assumed to be independent from volume scattering. The total loss including absorption and scattering losses in the scattering media is represented by the imaginary part of effective permittivity obtained from the strong fluctuation theory. The polarimetric scattering coefficients for different ice types are then derived under the distorted Born approximation.

Nghiem, S. V.↗

NASA NTRS1998

Comparison of Response Surface and Kriging Models in the Multidisciplinary Design of an Aerospike Nozzle

The use of response surface models and kriging models are compared for approximating non-random, deterministic computer analyses. After discussing the traditional response surface approach for constructing polynomial models for approximation, kriging is presented as an alternative statistical-based approximation method for the design and analysis of computer experiments. Both approximation methods are applied to the multidisciplinary design and analysis of an aerospike nozzle which consists of a computational fluid dynamics model and a finite element analysis model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations. Four optimization problems are formulated and solved using both approximation models. While neither approximation technique consistently outperforms the other in this example, the kriging models using only a constant for the underlying global model and a Gaussian correlation function perform as well as the second order polynomial response surface models.

Simpson, Timothy W.↗

NASA NTRSDate not supplied

MISR Level 1B2 Ellipsoid Data (MI1B2E_V1)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The Ellipsoid product is referenced to the World Geodetic System 1984 (WGS84) ellipsoid, which approximates the Earth's shape at sea level. In this product, the radiances and associated altitudes are projected to the ellipsoid, so that higher elevation data appear displaced from their true location for non-nadir camera views, much as they are seen by the instrument. (A cloud at location F, or a mountain top at location T in the image below appears as if it is at location E.) The more oblique the camera view, or the higher in altitude the feature, the more displaced the elevated data will appear. This displacement is used to advantage in MISR stereo retrievals, and this product is the primary input to Level 2 top-of-atmosphere/cloud processing. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=563.2 km (cross-track); Longitude_Resolution=140.8 km (along-track); Horizontal_Resolution_Range=250 meters - < 500 meters; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

EOSDIS↗

NASA NTRSDate not supplied

MISR Level 1B2 Ellipsoid Data (MI1B2E_V2)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The Ellipsoid product is referenced to the World Geodetic System 1984 (WGS84) ellipsoid, which approximates the Earth's shape at sea level. In this product, the radiances and associated altitudes are projected to the ellipsoid, so that higher elevation data appear displaced from their true location for non-nadir camera views, much as they are seen by the instrument. (A cloud at location F, or a mountain top at location T in the image below appears as if it is at location E.) The more oblique the camera view, or the higher in altitude the feature, the more displaced the elevated data will appear. This displacement is used to advantage in MISR stereo retrievals, and this product is the primary input to Level 2 top-of-atmosphere/cloud processing. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=563.2 km (cross-track); Longitude_Resolution=140.8 km (along-track); Horizontal_Resolution_Range=500 meters - < 1 km; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

EOSDIS↗

NASA NTRSDate not supplied

MISR Level 1B2 Ellipsoid Data (MI1B2E_V3)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The Ellipsoid product is referenced to the World Geodetic System 1984 (WGS84) ellipsoid, which approximates the Earth's shape at sea level. In this product, the radiances and associated altitudes are projected to the ellipsoid, so that higher elevation data appear displaced from their true location for non-nadir camera views, much as they are seen by the instrument. (A cloud at location F, or a mountain top at location T in the image below appears as if it is at location E.) The more oblique the camera view, or the higher in altitude the feature, the more displaced the elevated data will appear. This displacement is used to advantage in MISR stereo retrievals, and this product is the primary input to Level 2 top-of-atmosphere/cloud processing. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=563.2 km (cross-track); Longitude_Resolution=140.8 km (along-track); Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

TOA↗

NASA NTRS1998

The Radio luminosity Function of Radio-Loud Quasars from the 7C Redshift Survey

We present a complete sample of 24 radio-loud quasars (RLQs) from the new 7C Redshift Survey. Every quasar with a low-frequency (151 MHz) radio flux-density S(sub 151) > 0.5 Jy in two regions of the sky covering 0.013 sr is included; 23 of these have sufficient extended flux to meet the selection criteria, 18 of these have steep radio spectra (hereafter denoted as SSQs). The key advantage of this sample over most samples of RLQs is the lack of an optical magnitude limit. By combining the 7C and 3CRR samples, we have investigated the properties of RLQs as a function of redshift z and radio luminosity L(sub 151). We derive the radio luminosity function (RLF) of RLQs and find that the data are well fitted by a single power-law with slope alpha(sub 1) = 1.9 +/- 0.1 (for H(sub 0) = 50 km/s.Mpc, OMEGA(sub M) = 1, OMEGA(sub DELTA) = 0). We find that there must be a break in the RLQ RLF at log(sub 10)(L(sub 151)/W Hz.sr) approximately < or = 27, in order for the models to be consistent with the 7C and 6C source counts. The z-dependence of the RLF follows a one-tailed gaussian which peaks at z = 1.7 +/- 0.2. We find no evidence for a decline in the co-moving space density of RLQs at higher redshifts. A positive correlation between the radio and optical luminosities of SSQs is observed, confirming a result of Serjeant. We are able to rule out this correlation being due to selection effects or biases in our combined sample. The radio-optical correlation and best-fit model RLF enable us to estimate the distribution of optical magnitudes of quasars in samples selected at low radio frequencies, We con- clude that for samples with S(sub 151) approximately < or = 1 Jy one must use optical data significantly deeper than the POSS-I limit (R approximately equal 20), in order to avoid severe incompleteness.

Willott, Chris J.↗

NASA NTRS1988

The topology of large-scale structure. II - Nonlinear evolution of Gaussian models

The evolution of non-Gaussian behavior in the large-scale universe from Gaussian initial conditions is studied. Topology measures developed in previous papers are applied to the smoothed initial, final, and biased matter distributions of cold dark matter, white noise, and massive neutrino simulations. When the smoothing length is approximately twice the mass correlation length or larger, the evolved models look like the initial conditions, suggesting that random phase hypotheses in cosmology can be tested with adequate data sets. When a smaller smoothing length is used, nonlinear effects are recovered, so nonlinear effects on topology can be detected in redshift surveys after smoothing at the mean intergalaxy separation. Hot dark matter models develop manifestly non-Gaussian behavior attributable to phase correlations, with a topology reminiscent of bubble or sheet distributions. Cold dark matter models remain Gaussian, and biasing does not disguise this.

Melott, Adrian L.↗