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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 19 records
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NASA NTRS1979

IMF orientation, solar wind velocity, and Pc 3-4 signals - A joint distribution

Separate studies using the same micropulsation data base in the period range 10-150 s have shown earlier that signal levels recorded during September, October, and November 1969 at Calgary correlated positively with both solar-wind alignment of the IMF and solar-wind speed, but each correlation contained enough scatter to allow for the influence of the other factor. In this report, joint correlations of velocity and field direction with parameters representing hourly distributions rather than minima of IMF orientation angle display the relative effect of the two agents on magnetic pulsation signal levels. The joint correlations reduce the overall scatter and show that solar-wind speeds above 200-300 km/s and angles between the IMF and the sun-earth line of less than 50-60 deg are associated with enlarged magnetic pulsation amplitudes. These threshold effects tend to support both the bow-shock origin and the Kelvin-Helmholtz amplification of daytime signal transients in the Pc 3, 4 period ranges.

Greenstadt, E. W.↗
NASA NTRS1978

Analysis of vector wind change with respect to time for Cape Kennedy, Florida

Multivariate analysis was used to determine the joint distribution of the four variables represented by the components of the wind vector at an initial time and after a specified elapsed time is hypothesized to be quadravariate normal; the fourteen statistics of this distribution, calculated from 15 years of twice-daily rawinsonde data are presented by monthly reference periods for each month from 0 to 27 km. The hypotheses that the wind component changes with respect to time is univariate normal, that the joint distribution of wind component change with respect to time is univariate normal, that the joint distribution of wind component changes is bivariate normal, and that the modulus of vector wind change is Rayleigh are tested by comparison with observed distributions. Statistics of the conditional bivariate normal distributions of vector wind at a future time given the vector wind at an initial time are derived. Wind changes over time periods from 1 to 5 hours, calculated from Jimsphere data, are presented. Extension of the theoretical prediction (based on rawinsonde data) of wind component change standard deviation to time periods of 1 to 5 hours falls (with a few exceptions) within the 95 percentile confidence band of the population estimate obtained from the Jimsphere sample data. The joint distributions of wind change components, conditional wind components, and 1 km vector wind shear change components are illustrated by probability ellipses at the 95 percentile level.

Adelfang, S. I.↗
NASA NTRS2004

Product Distribution Theory for Control of Multi-Agent Systems

Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS's). First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint stare of the agents. Accordingly we can consider a team game in which the shared utility is a performance measure of the behavior of the MAS. For such a scenario the game is at equilibrium - the Lagrangian is optimized - when the joint distribution of the agents optimizes the system's expected performance. One common way to find that equilibrium is to have each agent run a reinforcement learning algorithm. Here we investigate the alternative of exploiting PD theory to run gradient descent on the Lagrangian. We present computer experiments validating some of the predictions of PD theory for how best to do that gradient descent. We also demonstrate how PD theory can improve performance even when we are not allowed to rerun the MAS from different initial conditions, a requirement implicit in some previous work.

Lee, Chia Fan↗
NASA NTRS2001

Satellite Remote Sensing of Tropical Precipitation and Ice Clouds for GCM Verification

This project, supported by the NASA New Investigator Program, has primarily been funding a graduate student, Darren McKague. Since August 1999 Darren has been working part time at Raytheon, while continuing his PhD research. Darren is planning to finish his thesis work in May 2001, thus some of the work described here is ongoing. The proposed research was to use GOES visible and infrared imager data and SSM/I microwave data to obtain joint distributions of cirrus cloud ice mass and precipitation for a study region in the Eastern Tropical Pacific. These joint distributions of cirrus cloud and rainfall were to be compared to those from the CSU general circulation model to evaluate the cloud microphysical amd cumulus parameterizations in the GCM. Existing algorithms were to be used for the retrieval of cloud ice water path from GOES (Minnis) and rainfall from SSM/I (Wilheit). A theoretical study using radiative transfer models and realistic variations in cloud and precipitation profiles was to be used to estimate the retrieval errors. Due to the unavailability of the GOES satellite cloud retrieval algorithm from Dr. Minnis (a co-PI), there was a change in the approach and emphasis of the project. The new approach was to develop a completely new type of remote sensing algorithm - one to directly retrieve joint probability density functions (pdf's) of cloud properties from multi-dimensional histograms of satellite radiances. The usual approach is to retrieve individual pixels of variables (i.e. cloud optical depth), and then aggregate the information. Only statistical information is actually needed, however, and so a more direct method is desirable. We developed forward radiative transfer models for the SSM/I and GOES channels, originally for testing the retrieval algorithms. The visible and near infrared ice scattering information is obtained from geometric ray tracing of fractal ice crystals (Andreas Macke), while the mid-infrared and microwave scattering is computed with Mie scattering. The radiative transfer is performed with the Spherical Harmonic Discrete Ordinate Method (developed by the PI), and infrared molecular absorption is included with the correlated k-distribution method. The SHDOM radiances have been validated by comparison to version 2 of DISORT (the community "standard" discrete-ordinates radiative transfer model), however we use SHDOM since it is computationally more efficient.

Evans, K. Franklin↗
NASA NTRS1994

Comparison of TOPEX/POSEIDON sigma(sub 0) and significant wave height distributions to Geosat

Monthly Ku band sigma(sub 0) and significant wave height (SWH) histograms from the NASA altimeter on the TOPEX/POSEIDON satellite are preseneted for January through June 1993 for three latitude bands between +/- 60 degrees. The data are compared to distributions from the Geosat mission for the same months in 1987-1989. Generally, the distributions agree quite well, although there are some seasonal/hemispherical differences. The sigma(sub 0) comparison reveals an overall bias between the two altimeters with the TOPEX sigma(sub 0) higher by about 0.7 dB, which is consistent with algorithm improvements for TOPEX. The SWH distributions show strong hemispherical/seasonal changes. The seasonal/hemispherical differences between TOPEX and Geosat are consistent for SWH and sigma(sub 0). The joint distribution of sigma(sub 0) and SWH is extremely stable friom month to month. The typical SWH is independent of sigma(sub 0) for sigma(sub 0) greater than 11.3 dB. The minimum SWH grows exponentially with wind speed. This joint distribution may be useful for understanding electromagnetic bias in altimeter measurements. Finally, altimeter data are compared to buoy values from 21 overflights of the NASA verification site near Pt. Conception, California. Wave heights agree well with an root mean square (RMS) difference of only 0.2 m. Altimeter sigma(sub 0) values are compared to buoy wind speeds. The results are consistent with the -0.7 dB sigma(sub 0) offset from the histogram comparisons.

Callahan, Philip S.↗
NASA NTRS1977

Analysis of vector wind change with respect to time for Cape Kennedy, Florida: Wind aloft profile change vs. time, phase 1

Wind vector change with respect to time at Cape Kennedy, Florida, is examined according to the theory of multivariate normality. The joint distribution of the four variables represented by the components of the wind vector at an initial time and after a specified elapsed time is hypothesized to be quadravariate normal; the fourteen statistics of this distribution, calculated from fifteen years of twice daily Rawinsonde data are presented by monthly reference periods for each month from 0 to 27 km. The hypotheses that the wind component changes with respect to time is univariate normal, the joint distribution of wind component changes is bivariate normal, and the modulus of vector wind change is Rayleigh, has been tested by comparison with observed distributions. Statistics of the conditional bivariate normal distributions of vector wind at a future time given the vector wind at an initial time are derived. Wind changes over time periods from one to five hours, calculated from Jimsphere data, are presented.

Adelfang, S. I.↗
NASA NTRS1981

Computer simulation of random variables and vectors with arbitrary probability distribution laws

Assume that there is given an arbitrary n-dimensional probability distribution F. A recursive construction is found for a sequence of functions x sub 1 = f sub 1 (U sub 1, ..., U sub n), ..., x sub n = f sub n (U sub 1, ..., U sub n) such that if U sub 1, ..., U sub n are independent random variables having uniform distribution over the open interval (0,1), then the joint distribution of the variables x sub 1, ..., x sub n coincides with the distribution F. Since uniform independent random variables can be well simulated by means of a computer, this result allows one to simulate arbitrary n-random variables if their joint probability distribution is known.

Bogdan, V. M.↗
NASA NTRS1973

The asymptotic distribution of maxima in bivariate samples

The joint distribution (as n tends to infinity) of the maxima of a sample of n independent observations of a bivariate random variable (X,Y) is studied. A method is developed for deriving the asymptotic distribution of the maxima, assuming that X and Y possess asymptotic extreme-value distributions and that the probability element dF(x,y) can be expanded in a canonical series. Applied both to the bivariate normal distribution and to the bivariate gamma and compound correlated bivariate Poisson distributions, the method shows that maxima from all these distributions are asymptotically uncorrelated.

Campbell, J. W.↗
NASA NTRS1992

On probability-possibility transformations

Several probability-possibility transformations are compared in terms of the closeness of preserving second-order properties. The comparison is based on experimental results obtained by computer simulation. Two second-order properties are involved in this study: noninteraction of two distributions and projections of a joint distribution.

Klir, George J.↗
NASA NTRS1983

Radar modeling of space diversity associated with slant path rain attenuation at variable path angles, frequencies, and drop size distributions

Single and joint terminal slant path attenuation statistics at frequencies of 28.56 and 19.04 GHz were derived from radar data. Statistics were independently obtained for path angles of 20, 45, and 90 deg, in order to examine how path angle influences both single terminal and joint probability distributions. A prediction technique is demonstrated to work well for calculating both single and joint terminal distributions at other path angles. Diversity gains and autocorrelation function dependence on site spacing were determined employing the radar modeling results.

Goldhirsh, J.↗
NASA NTRS1997

Estimating the Uncertainty in Passive-Microwave Rain-Retrievals

Current passive-microwave rain-retrieval methods are largely based on databases built off-line using cloud models. The vertical distribution of hydrometeors within the cloud has a large impact on upwelling brightness temperatures ([31,[5]). Thus, a forward radiative transfer model can predict off-line the radiance associated with different rain scenarios. To estimate the rain from measured brightness temperatures, one simply looks for the rain scenario whose associated radiances are closest to the measurements. To understand the uncertainties in this process, we first study the dependence of the simulated brightness temperatures on different hydrometeor size distribution (DSD) models. We then analyze the marginal and joint distributions of the radiances observed by the Tropical Rainfall Measuring Mission satellite and of those in the databases used in the TRMM rain retrievals. We finally calculate the covariances of the rain profiles and brightness temperatures in the TRMM passive-microwave database and derive a simple parametric model for the conditional uncertainty, given measured radiances. These results are used to characterize the uncertainty inherent in the passive-microwave retrieval.

Coppens, Dorothee↗
NASA NTRS1988

Learning a Probability Distribution Efficiently and Reliably

A new algorithm, called the CDF-Inversion Algorithm, is described. Using it, one can efficiently learn a probability distribution over a finite set to a specified accuracy and confidence. The algorithm can be extended to learn joint distributions over a vector space. Some implementation results are described.

Laird, Philip↗
NASA NTRS1980

Statistical wind profile gust model

A statistical wind profile gust model for the Space Transportation Operations and Trade Studies is developed by using 1800 Jimsphere wind profile data collected at Cape Kennedy during 1965 to 1972. Wind profiles from the surface to 20 km in component form, i.e., zonal and meridional are processed through the digital filters of different wave length ranges bases on the Martin-Graham cosine rolloff model. The residuals obtained from the filtering processes for the data base for the statistical analysis. For each wind component the gust and gust length at a specified reference altitude in a residual profile are defined. A two parameter gamma probability marginal distribution seems to fit the component gust amplitude and the gust length when redefined. The problem of finding an appropriate bivariate joint distribution of the gust amplitude and length remains to be solved. The probability distribution of the modulus of the gust amplitudes was derived under the assumption that they are independently distributed as gamma variates.

Doss, D. C.↗
NASA NTRS1982

Results of the VPI&SU Comstar experiment

This paper summarizes annual and cumulative attenuation data, depolarization data, and associated local rain rate distributions obtained with the Comstar family of 19.04- and 28.56-GHz satellite beacons during the years 1977-1981. It discusses the relationships between attenuation and rain rate and between attenuation and depolarization, compares measured data on the joint distribution of attenuation and depolarization, and examines the limitations that propagation effects will impose on future 20/30-GHz satellite communications systems.

Andrews, J. H.↗
NASA NTRS1987

Probabilistic SSME blades structural response under random pulse loading

The purpose is to develop models of random impacts on a Space Shuttle Main Engine (SSME) turbopump blade and to predict the probabilistic structural response of the blade to these impacts. The random loading is caused by the impact of debris. The probabilistic structural response is characterized by distribution functions for stress and displacements as functions of the loading parameters which determine the random pulse model. These parameters include pulse arrival, amplitude, and location. The analysis can be extended to predict level crossing rates. This requires knowledge of the joint distribution of the response and its derivative. The model of random impacts chosen allows the pulse arrivals, pulse amplitudes, and pulse locations to be random. Specifically, the pulse arrivals are assumed to be governed by a Poisson process, which is characterized by a mean arrival rate. The pulse intensity is modelled as a normally distributed random variable with a zero mean chosen independently at each arrival. The standard deviation of the distribution is a measure of pulse intensity. Several different models were used for the pulse locations. For example, three points near the blade tip were chosen at which pulses were allowed to arrive with equal probability. Again, the locations were chosen independently at each arrival. The structural response was analyzed both by direct Monte Carlo simulation and by a semi-analytical method.

Shiao, Michael↗