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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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NASA NTRS1976

Experimental investigation of the excess charge and time constant of minority carriers in the thin diffused layer of 0.1 ohm-cm silicon solar cells

An experimental method is presented that can be used to interpret the relative roles of bandgap narrowing and recombination processes in the diffused layer. This method involves measuring the device time constant by open-circuit voltage decay and the base region diffusion length by X-ray excitation. A unique illuminated diode method is used to obtain the diode saturation current. These data are interpreted using a simple model to determine individually the minority carrier lifetime and the excess charge. These parameters are then used to infer the relative importance of bandgap narrowing and recombination processes in the diffused layer.

Godlewski, M. P.↗

NASA NTRS1990

Bulk properties and velocity distributions of water group ions at Comet Halley - Giotto measurements

In the region upstream of Comet Halley, pickup heavy ions of cometary origin were directly observed by the implanted ion spectrometer on Giotto. Diffusion of this population in pitch angle and in energy, during the approach to the comet and on the outbound leg is discussed. The two data sets are compared and qualitative ideas on scattering timescales are inferred. In addition the bulk parameters of these distributions have been computed and a comparison of the observed speed in the solar wind frame and the observed density with expectations is presented. Pitch angle scattering occurs more slowly than expected with filled shells appearing at 2,500,000 km, and significant energy diffusion does not occur until the bow shock region. Also the shell distributions downstream of the shock flow at the bispherical bulk speed (related to the Alfven speed) along the magnetic field with respect to the solar wind in accordance with conservation of energy between the pickup ions and the wave turbulence.

Coates, A. J.↗

NASA NTRS1993

A statistical analysis of mesoscale rainfall as a random cascade

The paper considers the random cascade theory for spatial rainfall. Particular attention was given to the following four areas: (1) the relationship of the random cascade theory of rainfall to the simple scaling and the hierarchical cluster-point-process theories, (2) the mathematical foundations for some of the formalisms commonly applied in the develpment of statistical cascade theory, (3) the empirical evidence for a random cascade theory of rainfall, and (4) the way of using data for making estimates of parameters and for making statistical inference within this theoretical framework. An analysis of space-time rainfall data is presented. Cascade simulations are carried out to provide a comparison with methods of analysis that are applied to the rainfall data.

Gupta, Vijay K.↗

NASA NTRS2005

Current Sheet Evolution in the Aftermath of a CME Event

We report on SOHO-UVCS observations of the coronal restructuring following a Coronal Mass Ejection (CME) on November 26,2002, at the time of a SOHO-Ulysses quadrature campaign. Starting about 3 hours after a CME in the NW quadrant, UVCS began taking spectra at 1.7 solar radius, covering emission from both cool and hot plasma. Observations continued, with occasional gaps, for more than 2 days. Emission in the 974.8 Angstrom line of [Fe XVIII], indicating temperatures above 6 x 10(exp 6) K, was observed throughout the campaign in a spatially limited location. Comparison with EIT images shows the Fe XVIII emission to overlie a growing post-flare loop system formed in the aftermath of the CME. The emission most likely originates in a current sheet overlying the arcade. Analysis of the [Fe XVIII] emission allows us to infer the evolution of physical parameters in the current sheet over the entire span of our observations: in particular, we give the temperature vs. time in the current sheet and estimate the density. At the time of the quadrature, Ulysses was directly above the location of the CME and intercepted the ejecta. High ionization state Fe was detected by Ulysses-SWICS throughout the magnetic cloud associated with the CME. Both the remote and in situ observations are compared with predictions of theoretical CME models.

Bemporad, A.↗

NASA NTRS2005

Coronal Current Sheet Evolution in the Aftermath of a CME

We report on SOHO-UVCS observations of coronal restructuring following a Coronal Mass Ejection (CME) on November 26, 2002, at the time of a SOHO-Ulysses quadrature campaign. Starting about 3 hours after the CME, which was directed towards Ulysses, UVCS began taking spectra at 1.7 solar radii, covering emission from both cool and hot plasma. Observations continued, with occasional gaps, for more than 2 days. Emission in the 974.8 Angstrom line of [Fe XVIII], indicating temperatures above 6x10(6) K, was observed throughout the campaign in a spatially limited location. Comparison with EIT images shows the [Fe XVIII] emission to overlie a growing post-flare loop system formed in the aftermath of the CME. The emission most likely originates in a current sheet overlying the arcade. Analysis of the [Fe XVIII] emission allows us to infer the evolution of physical parameters in the current sheet over the entire span of our observations: in particular, we give the temperature vs. time in the current sheet and estimate the density. Ulysses was directly above the location of the CME and intercepted the ejecta. High ionization state Fe was detected by SWICS throughout the magnetic cloud associated with the CME, although the rapid temporal variation suggests bursty, rather than smooth, reconnection in the coronal current sheet. Both the remote and in situ observations are compared with predictions of theoretical CME models.

Bemporad, A.↗

NASA NTRS2006

Current Sheet Evolution In The Aftermath Of A CME Event

We report on SOHO UVCS observations of the coronal restructuring following a coronal mass ejection (CME) on 2002 November 26, at the time of a SOHO-Ulysses quadrature campaign. Starting about 1.5 hr after a CME in the northwest quadrant, UVCS began taking spectra at 1.7 R, covering emission from both cool and hot plasma. Observations continued, with occasional gaps, for more than 2 days. Emission in the 974.8 A line of [Fe XVIII], indicating temperatures above 6 x 10(exp 6) K, was observed throughout the campaign in a spatially limited location. Comparison with EIT images shows the [Fe XVIII] emission to overlie a growing post-flare loop system formed in the aftermath of the CME. The emission most likely originates in a current sheet overlying the arcade. Analysis of the [Fe XVIII] emission allows us to infer the evolution of physical parameters in the current sheet over the entire span of our observations: in particular, we give the temperature versus time in the current sheet and estimate its density. At the time of the quadrature, Ulysses was directly above the location of the CME and intercepted the ejecta. High ionization state Fe was detected by the Ulysses SWICS throughout the magnetic cloud associated with the CME, although its rapid temporal variation suggests bursty, rather than smooth, reconnection in the coronal current sheet. The SOHO-Ulysses data set provided us with the unique opportunity of analyzing a current sheet structure from its lowest coronal levels out to its in situ properties. Both the remote and in situ observations are compared with predictions of theoretical CME models.

Bemporad, A.↗

NASA NTRS2006

Lifetime Evolution of UV Jets

We report on observations acquired in May 2003 during a SOHO-Ulysses quadrature campaign. From May 25 to May 28, the SoHO LASCO Coronal Mass Ejection (CME) catalog lists a number of events which might have been observed by SOHO/UVCS, whose slit was centered along the Ulysses direction. However, because of time gaps in the observing schedule, or because of the unfavorable position of some CMEs, the most interesting events recorded by UVCS were a few short-lived ejections that represent the extension at higher altitudes of recursive EIT jets. We focus on jets occurring on May 26/27, visible also in EIT and LASCO images, which seem to propagate along the radial to Ulysses. UVCS spectra at 1.7 Rsun showed an unusually high emission in cool lines, lasting for about 10 to 25 minutes, with no evidence of hot plasma. Analysis of the cool line emission allowed us to infer the evolution of physical parameters during the jets lifetime and derive a crude estimate of the energy needed to account for their properties. We also looked for any evidence of the event in in situ data. Whether UVCS is observing jets or narrow CMEs is discussed in the contest of previous works on these classes of events and, in the last Section, we propose a scenario that accounts for our observations.

Corti, G.↗

NASA NTRS2009

Lunar Neutral Exposphere Properties from Pickup Ion Analysis

Composition and structure of neutral constituents in the lunar exosphere can be determined through measurements of phase space distributions of pickup ions borne from the exosphere [1]. An essential point made in an early study [ 1 ] and inferred by recent pickup ion measurements [2, 3] is that much lower neutral exosphere densities can be derived from ion mass spectrometer measurements of pickup ions than can be determined by conventional neutral mass spectrometers or remote sensing instruments. One approach for deriving properties of neutral exospheric source gasses is to first compare observed ion spectra with pickup ion model phase space distributions. Neutral exosphere properties are then inferred by adjusting exosphere model parameters to obtain the best fit between the resulting model pickup ion distributions and the observed ion spectra. Adopting this path, we obtain ion distributions from a new general pickup ion model, an extension of a simpler analytic description obtained from the Vlasov equation with an ion source [4]. In turn, the ion source is formed from a three-dimensional exospheric density distribution, which can range from the classical Chamberlain type distribution to one with variable exobase temperatures and nonthermal constituents as well as those empirically derived. The initial stage of this approach uses the Moon's known neutral He and Na exospheres to deriv e He+ and Na+ pickup ion exospheres, including their phase space distributions, densities and fluxes. The neutral exospheres used are those based on existing models and remote sensing studies. As mentioned, future ion measurements can be used to constrain the pickup ion model and subsequently improve the neutral exosphere descriptions. The pickup ion model is also used to estimate the exosphere sources of recently observed pickup ions on KAGUYA [3]. Future missions carrying ion spectrometers (e.g., ARTEMIS) will be able to study the lunar neutral exosphere with great sensitivity, yielding the necessary ion velocity spectra needed to further analysis of parent neutral exosphere properties.

Hartle, R. E.↗

NASA NTRS2014

Learning Extended Finite State Machines

We present an active learning algorithm for inferring extended finite state machines (EFSM)s, combining data flow and control behavior. Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses the tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.

NASA NTRS1981

Diurnal variability of regional cloud radiative parameters from geostationary satellite data

In the discussed study, Geostationary Operational Environmental Satellite visible and infrared brightness measurements are used to infer regional cloud cover and several associated radiative parameters on an hourly basis. Several techniques are utilized to derive the parameters of interest. These parameters include the areal cloud fraction, cloud-atmosphere albedo, surface-atmosphere albedo, and equivalent blackbody surface and cloud-top temperatures. Attention is given to clear radiance temperature determinations, surface temperature modeling, the infrared threshold method, narrowband-broadband correlations, and albedo determination. Monthly mean values were computed for each parameter as a function of local time. Cloud amounts and temperatures are considered along with longwave emission and shortwave albedo, and composite results.

Minnis, P.↗

NASA NTRS1984

Vertical temperature sounding of the atmosphere

Attention is given to physical principles that affect the determination of atmospheric temperature profiles from observations of outgoing IR and microwave radiation. Simultaneous analysis of IR and microwave observations enhances observations in each spectral region. While IR soundings have higher sensitivity to lower tropospheric temperatures, ground temperatures, and sea surface temperatures, microwave observations are not only more suited to stratospheric sounding but are sensitive to snow and ice cover. They significantly aid correction of IR observations for cloud effects. Because effective cloud parameters and snow and ice cover can be inferred from the observations, 'temperature sounders' also yield data for a number of important climatic parameters.

Suskind, J.↗

NASA NTRS1986

Concentrations and uncertainties of stratospheric trace species inferred from limb infrared monitor of the stratosphere data. I - Methodology and application to OH and HO2. II - Monthly averaged OH, HO2, H2O2, and HO2NO2

Difficulties arise in connection with the verification of multidimensional chemical models of the stratosphere. The present study shows that LIMS data, together with a photochemical equilibrium model, may be used to infer concentrations of a variety of zonally averaged trace Ox, OHx, and NOx species over much of the stratosphere. In the lower stratosphere, where the photochemical equilibrium assumption for HOx species breaks down, inferred concentrations should still be accurate to about a factor of 2 for OH and 2.5 for HO2. The algebraic nature of the considered model makes it possible to see easily to the first order the effect of variation of any model input parameter or its uncertainty on the inferred concontration of the HOx species and their uncertainties.

Kaye, J. A.↗

NASA NTRS2010

A Model-Based Probabilistic Inversion Framework for Wire Fault Detection Using TDR

Time-domain reflectometry (TDR) is one of the standard methods for diagnosing faults in electrical wiring and interconnect systems, with a long-standing history focused mainly on hardware development of both high-fidelity systems for laboratory use and portable hand-held devices for field deployment. While these devices can easily assess distance to hard faults such as sustained opens or shorts, their ability to assess subtle but important degradation such as chafing remains an open question. This paper presents a unified framework for TDR-based chafing fault detection in lossy coaxial cables by combining an S-parameter based forward modeling approach with a probabilistic (Bayesian) inference algorithm. Results are presented for the estimation of nominal and faulty cable parameters from laboratory data.

Schuet, Stefan R.↗

NASA NTRS2019

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗

NASA NTRS2001

Controlling Malaria and Other Diseases Using Remote Sensing

Remote sensing offers the vantage of monitoring a vast area of the Earth continuously. Once developed and launched, a satellite gives years of service in collecting data from the land, the oceans, and the atmosphere. Since the 1980s, attempts have been made to relate disease occurrence with remotely sensed environmental and geophysical parameters, using data from Landsat, SPOT, AVHRR, and other satellites. With higher spatial resolution, the recent satellite sensors provide a new outlook for disease control. At sub-meter to I 10m resolution, surface types associated with disease carriers can be identified more accurately. The Ikonos panchromatic sensor with I m resolution, and the Advanced Land Imager with 1 Om resolution on the newly launched Earth Observing-1, both have displayed remarkable mapping capabilities. In addition, an entire array of geophysical parameters can now be measured or inferred from various satellites. Airborne remote sensing, with less concerns on instrument weight, size, and power consumption, also offers a low-cost alternative for regional applications. NASA/GSFC began to collaborate with the Mahidol University on malaria and filariasis control using remote sensing in late 2000. The objectives are: (1) To map the breeding sites for the major vector species; (2) To identify the potential sites for larvicide and insecticide applications; (3) To explore the linkage of vector population and transmission intensity to environmental variables; (4) To monitor the impact of climate change and human activities on vector population and transmission; and (5) To develop a predictive model for disease distribution. Field studies are being conducted in several provinces in Thailand. Data analyses will soon begin. Malaria data in South Korea are being used as surrogates for developing classification techniques. GIS has been shown to be invaluable in making the voluminous remote sensing data more readily understandable. It will be used throughout this study to clearly demonstrate the spatial relationship between the disease intensities, geophysical variables, and socioeconomic parameters. Asides from malaria and filariasis, application of remote sensing to the control of other diseases have been vigorously pursued by NASA's Environment and Health Initiative. The current program includes projects on Rift Valley fever, St. Louis encephalitis, dengue fever, ebola, African dust and diseases, meningitis, asthma, bartonellosis, cholera, and urban health concerns. Results from these projects indicate that remote sensing will play an increasingly important role in disease control in the future.

Kiang, Richard K.↗

NASA NTRS1973

Search properties of some sequential decoding algorithms.

Sequential decoding procedures are studied in the context of selecting a path through a tree. Several algorithms are considered, and their properties are compared. It is shown that the stack algorithm introduced by Zigangirov (1966) and by Jelinek (1969) is essentially equivalent to the Fano algorithm with regard to the set of nodes examined and the path selected, although the description, implementation, and action of the two algorithms are quite different. A modified Fano algorithm is introduced, in which the quantizing parameter is eliminated. It can be inferred from limited simulation results that, at least in some applications, the new algorithm is computationally inferior to the old. However, it is of some theoretical interest since the conventional Fano algorithm may be considered to be a quantized version of it.

Geist, J. M.↗

NASA NTRS1977

Inverse solution of the pseudoscalar transfer equation through nonlinear matrix inversion

Nonlinear matrix inversion operators have been developed which, applied to observed radiances, infer maximal information regarding atmospheric scattering parameters and vertical distribution of radiant sources and sinks. The algorithm has the attractive feature of noise discrimination, attributing instrumental errors to extra-atmospheric sources.

King, J. I. F.↗

NASA NTRS1979

Applications of estimation theory to inverse problems in meteorology

The paper applies iterated and non-iterated extended Kalman filters to solve two practical meteorological inversion problems. Passive microwave satellite soundings are used to infer vertical temperature profiles and cloud parameters. In both cases it is shown that improvements can be obtained over presently used techniques. Finally, the results suggest that modern multivariate nonlinear recursive estimation techniques based in a Bayesian methodology can be a valuable tool in the area of remote sounding of atmospheric parameters.

Gustafson, D. E.↗