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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Voyager 1 assessment of Jupiter's planetary magnetic field

An estimate of Jupiter's planetary magnetic field is obtained from the Voyager 1 observations of the Jovian magnetosphere. An explicit model for the magnetodisc current system is combined with a spherical harmonic model of the planetary field with both sets of parameters determined simultaneously using a nonlinear generalized inverse methodology. The resulting model fits the observations extremely well throughout the analysis interval (r 20 Jovian radii). The Jovian internal field model obtained from the Voyager 1 data is very similar to the octopole Pioneer 11 models. The best fitting magnetodisc lies in the centrifugal equator, 2/3 of the way between the rotational and magnetic equators, as appropriate for centrifugal loading of the magnetosphere by a cold plasma.

Connerney, J. E. P.↗
NASA NTRS1984

Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain

Microwave modeling of vegetated terrain was investigated. The purpose was to: (1) use discrete scatter theory to model vegetation (crops and forested regions) in microwave region; (2) develop models for scatterers and ground; (3) multiple scattering analysis relate model parameters to average scattered power; and (4) develop inversion techniques to remotely determine model parameters.

Lang, R. H.↗
NASA NTRS2011

Use of Inverse Reinforcement Learning for Identity Prediction

We adopt Markov Decision Processes (MDP) to model sequential decision problems, which have the characteristic that the current decision made by a human decision maker has an uncertain impact on future opportunity. We hypothesize that the individuality of decision makers can be modeled as differences in the reward function under a common MDP model. A machine learning technique, Inverse Reinforcement Learning (IRL), was used to learn an individual's reward function based on limited observation of his or her decision choices. This work serves as an initial investigation for using IRL to analyze decision making, conducted through a human experiment in a cyber shopping environment. Specifically, the ability to determine the demographic identity of users is conducted through prediction analysis and supervised learning. The results show that IRL can be used to correctly identify participants, at a rate of 68% for gender and 66% for one of three college major categories.

Hayes, Roy↗
NASA NTRS1997

Multi-Wavelength Observations of 3C 273 in 1993-1995

We present the results of the multi-wavelength campaigns on 3C 273 in 1993-1995. During the observations in late 1993 this quasar showed an increase of its flux for energies >= 100 MeV from about 2.1 x 10(exp -7) photons/sq cm.s to approximately 5.6 x 10(exp -7) photons/sq cm.s during a radio outburst at 14.5, 22 and 37 GHz. However, no one-to-one correlation of the gamma-ray radiation with any frequency could be found. The photon spectral index of the high energy spectrum changed from GAMMA(sub gamma) = (3.20 +/- 0.54) to GAMMA(sub gamma) = (2.20 +/- 0.22) in the sense that the spectrum flattened when the gamma-ray flux increased. Fits of the three most prominent models (synchrotron self-Comptonization, external inverse Comptonization and the proton initiated cascade model) for the explanation of the high gamma-ray emission of active galactic nuclei were performed to the multi-wavelength spectrum of 3C 273 . All three models are able to represent the basic features of the multi-wavelength spectrum. Although there are some differences the data are still not decisive enough to discriminate between the models.

vonMontigny, C.↗
NASA NTRS2018

A New Model of Jupiter's Magnetic Field From Juno's First Nine Orbits

A spherical harmonic model of the magnetic field of Jupiter is obtained from vector magnetic field observations acquired by the Juno spacecraft during its first nine polar orbits about the planet. Observations acquired during eight of these orbits provide the first truly global coverage of Jupiter's magnetic field with a coarse longitudinal separation of ~45 deg between perijoves. The magnetic field is represented with a degree 20 spherical harmonic model for the planetary ("internal") field, combined with a simple model of the magnetodisc for the field ("external") due to distributed magnetospheric currents. Partial solution of the underdetermined inverse problem using generalized inverse techniques yields a model ("Juno Reference Model through Perijove 9") of the planetary magnetic field with spherical harmonic coefficients well determined through degree and order 10, providing the first detailed view of a planetary dynamo beyond Earth.

Connerney, J. E. P.↗
NASA NTRS1999

Main Geomagnetic Field Models from Oersted and Magsat Data Via a Rigorous General Inverse Theory with Error Bounds

The purpose of the grant was to study how prior information about the geomagnetic field can be used to interpret surface and satellite magnetic measurements, to generate quantitative descriptions of prior information that might be so used, and to use this prior information to obtain from satellite data a model of the core field with statistically justifiable error estimates. The need for prior information in geophysical inversion has long been recognized. Data sets are finite, and faithful descriptions of aspects of the earth almost always require infinite-dimensional model spaces. By themselves, the data can confine the correct earth model only to an infinite-dimensional subset of the model space. Earth properties other than direct functions of the observed data cannot be estimated from those data without prior information about the earth. Prior information is based on what the observer already knows before the data become available. Such information can be "hard" or "soft". Hard information is a belief that the real earth must lie in some known region of model space. For example, the total ohmic dissipation in the core is probably less that the total observed geothermal heat flow out of the earth's surface. (In principle, ohmic heat in the core can be recaptured to help drive the dynamo, but this effect is probably small.) "Soft" information is a probability distribution on the model space, a distribution that the observer accepts as a quantitative description of her/his beliefs about the earth. The probability distribution can be a subjective prior in the sense of Bayes or the objective result of a statistical study of previous data or relevant theories.

Backus, George E.↗
NASA NTRS2006

Computing Fault Displacements from Surface Deformations

Simplex is a computer program that calculates locations and displacements of subterranean faults from data on Earth-surface deformations. The calculation involves inversion of a forward model (given a point source representing a fault, a forward model calculates the surface deformations) for displacements, and strains caused by a fault located in isotropic, elastic half-space. The inversion involves the use of nonlinear, multiparameter estimation techniques. The input surface-deformation data can be in multiple formats, with absolute or differential positioning. The input data can be derived from multiple sources, including interferometric synthetic-aperture radar, the Global Positioning System, and strain meters. Parameters can be constrained or free. Estimates can be calculated for single or multiple faults. Estimates of parameters are accompanied by reports of their covariances and uncertainties. Simplex has been tested extensively against forward models and against other means of inverting geodetic data and seismic observations. This work

Lyzenga, Gregory↗
NASA NTRS2002

Plasmasphere Empirical Modeling with the IMAGE Mission

Empirical models of plasmaspheric properties date from the pioneering work of Storey where he developed the analysis of ground whistler observations that lead to his estimate for the equatorial plasma density at L=3. The most recent in situ satellite study takes us to 1000 CRRES satellite passes and a statistical analysis of the plasmapause location at all local times and for varying geomagnetic conditions by Moldwin et al. These and many other studies over the intervening 49 years have given us a strong familiarity with the distribution of cold plasmaspheric ions throughout the magnetosphere. The major components of inner plasmasphere, nightside bulge, sunward convection tail, and plasmapause are all well established. Storm-time erosion and the resulting ionospheric refilling has been encompassed, even if not completely understood. Small-scale density variations near the plasmapause and extending at least to geosynchronous orbit have been characterized in a variety of ways, even though we do not yet understand their origin. This paper will present early empirical modeling results from the inversion of IMAGE/EW global intensity images to density distributions. Densities are obtained in this initial study through use of forward image modeling with a simple 3-parameter plasmaspheric and plasmapause mathematical model. Individual interior plasmaspheric density profiles and plasmapause locations are obtained every 10 degrees in magnetic local time for each E W image analyzed. Derived profile parameters are statistically characterized in the context of storm magnitude and evolution. Identified patterns in the appearance of plasmaspheric structures, plasmapause erosion, and refilling will be presented. Comparisons to existing empirical plasmaspheric models and the implications for new modeling will be presented. Additional information is included in the original extended abstract.

Gallagher, D. L.↗
NASA NTRS2003

Reliability of CHAMP Anomaly Continuations

CHAMP is recording state-of-the-art magnetic and gravity field observations at altitudes ranging over roughly 300 - 550 km. However, anomaly continuation is severely limited by the non-uniqueness of the process and satellite anomaly errors. Indeed, our numerical anomaly simulations from satellite to airborne altitudes show that effective downward continuations of the CHAMP data are restricted to within approximately 50 km of the observation altitudes while upward continuations can be effective over a somewhat larger altitude range. The great unreliability of downward continuation requires that the satellite geopotential observations must be analyzed at satellite altitudes if the anomaly details are to be exploited most fully. Given current anomaly error levels, joint inversion of satellite and near- surface anomalies is the best approach for implementing satellite geopotential observations for subsurface studies. We demonstrate the power of this approach using a crustal model constrained by joint inversions of near-surface and satellite magnetic and gravity observations for Maude Rise, Antarctica, in the southwestern Indian Ocean. Our modeling suggests that the dominant satellite altitude magnetic anomalies are produced by crustal thickness variations and remanent magnetization of the normal polarity Cretaceous Quiet Zone.

vonFrese, Ralph R. B.↗
NASA NTRS1971

Photovoltage inversion effect and its application to semiconductor surface studies: CdS.

Experimental results on the surface states of the basal plane of CdS are presented and discussed in the light of a model of the photovoltage inversion effect. It is found that the surface states associated with this effect are in poor communication with the bulk and under normal conditions may require long periods of time to reach equilibrium. A combination of photovoltage inversion, photovoltage quenching, and photovoltage spectroscopy is believed to constitute a very effective tool for the study of surfaces of wide energy gap semiconductors.

Lagowski, J.↗
NASA NTRS1992

Inversion of snow parameters by neural network with iterative inversion

The inversion of snow parameters from passive microwave remote sensing measurements is performed with a neural network trained with a dense media multiple scattering model. A constrained iterative inversion scheme is used. Inversion of four parameters is performed from five brightness temperatures. The four parameters are: mean grain size of ice particles in snow, snow density, snow temperature, and snow depth. The five brightness temperatures are that of 19-GHz vertical polarization, 19-GHz horizontal polarization, 22-GHz vertical polarization, 37-GHz vertical polarization, and 37-GHz horizontal polarization. Based on the neural network constrained iterative inversion algorithm, synthetic mapping of the terrain is performed. The retrieval of synthetic mapping has been achieved. The incorporation of ground truth information is considered.

Chen, Zhengxiao↗
NASA NTRS1985

Penecontemporaneous metamorphism, fragmentation, and reassembly of ordinary chondrite parent bodies

The thermal histories of ordinary chondrites and the canonical internal heating or onion shell models, which predict an inverse relation between the petrologic type of chondrites and the metallographic cooling rate, are reviewed. The thermal and accretional requirements of the 'metamorphosed planetesimal' model proposed by Scott and Rajan (1981) are analyzed, and an alternative model consistent with the metallographic cooling rate constraints is suggested in which ordinary chondrite parent bodies are collisionally fragmented and then rapidly reassembled before metamorphic heat has been dissipated.

Grimm, R. E.↗
NASA NTRSDate not supplied

Impact Of Rotation on the Sun’s Subsurface Structure

It is well known that the dynamical evolution of subsurface flows of the Sun and magnetic fields is strongly linked to rotation. Observational investigation of sub surface structuring and dynamics can be performed only with relatively low resolution using helioseismic inversion techniques. To confidently model the coupling of turbulent convection, magnetic fields, and rotation in the solar interior, we perform advanced radiative hydrodynamic and MHD modeling of local scales. To explore the coupling effects in the upper layers of the convection zone, we present results of analysis from a series of hydrodynamic simulations performed for a 25-Mm-deep computational domain at different latitudes obtained for 1) the Carrington rotation rate at all latitudes and 2) the realistic rotation rate from the global helioseismic inversions during the solar minimum. Using additional 3D radiative hydrodynamic models, we reveal how physical properties of the solar convection are affected by rotation.

Heliophysics↗
NASA NTRS2016

Combing Visible and Infrared Spectral Tests for Dust Identification

The MODIS Dark Target aerosol algorithm over Ocean (DT-O) uses spectral reflectance in the visible, near-IR and SWIR wavelengths to determine aerosol optical depth (AOD) and Angstrom Exponent (AE). Even though DT-O does have "dust-like" models to choose from, dust is not identified a priori before inversion. The "dust-like" models are not true "dust models" as they are spherical and do not have enough absorption at short wavelengths, so retrieved AOD and AE for dusty regions tends to be biased. The inference of "dust" is based on postprocessing criteria for AOD and AE by users. Dust aerosol has known spectral signatures in the near-UV (Deep blue), visible, and thermal infrared (TIR) wavelength regions. Multiple dust detection algorithms have been developed over the years with varying detection capabilities. Here, we test a few of these dust detection algorithms, to determine whether they can be useful to help inform the choices made by the DT-O algorithm. We evaluate the following methods: The multichannel imager (MCI) algorithm uses spectral threshold tests in (0.47, 0.64, 0.86, 1.38, 2.26, 3.9, 11.0, 12.0 micrometer) channels and spatial uniformity test [Zhao et al., 2010]. The NOAA dust aerosol index (DAI) uses spectral contrast in the blue channels (412nm and 440nm) [Ciren and Kundragunta, 2014]. The MCI is already included as tests within the "Wisconsin" (MOD35) Cloud mask algorithm.

aerosol optical depth↗
NASA NTRS2014

Ground Delay Program Analytics with Behavioral Cloning and Inverse Reinforcement Learning

We used historical data to build two types of model that predict Ground Delay Program implementation decisions and also produce insights into how and why those decisions are made. More specifically, we built behavioral cloning and inverse reinforcement learning models that predict hourly Ground Delay Program implementation at Newark Liberty International and San Francisco International airports. Data available to the models include actual and scheduled air traffic metrics and observed and forecasted weather conditions. We found that the random forest behavioral cloning models we developed are substantially better at predicting hourly Ground Delay Program implementation for these airports than the inverse reinforcement learning models we developed. However, all of the models struggle to predict the initialization and cancellation of Ground Delay Programs. We also investigated the structure of the models in order to gain insights into Ground Delay Program implementation decision making. Notably, characteristics of both types of model suggest that GDP implementation decisions are more tactical than strategic: they are made primarily based on conditions now or conditions anticipated in only the next couple of hours.

Bloem, Michael↗
NASA NTRS1975

Comparison of some biased estimation methods (including ordinary subset regression) in the linear model

Ridge, Marquardt's generalized inverse, shrunken, and principal components estimators are discussed in terms of the objectives of point estimation of parameters, estimation of the predictive regression function, and hypothesis testing. It is found that as the normal equations approach singularity, more consideration must be given to estimable functions of the parameters as opposed to estimation of the full parameter vector; that biased estimators all introduce constraints on the parameter space; that adoption of mean squared error as a criterion of goodness should be independent of the degree of singularity; and that ordinary least-squares subset regression is the best overall method.

Sidik, S. M.↗
NASA NTRS2013

GRAIL Refinements to Lunar Seismic Structure

Joint interpretation of disparate geophysical datasets helps reduce drawbacks that can result from analyzing them individually. The Apollo seismic network was situated on the lunar nearside surface in a roughly equilateral triangle having sides approximately 1000 km long, with stations 12/14 nearly co-located at one corner. Due to this limited geographical extent, near-surface ray coverage from moonquakes is low, but increase with depth. In comparison, gravity surveys and their resulting gravity anomaly maps have traditionally offered optimal resolution at crustal depths. Gravimetric maps and seismic data sets are therefor well suited to joint inversion, since the complementary information reduces inherent model ambiguity. We will perform a joint inversion of Apollo seismic delay times and gravity data collected by GRAIL lunar gravity mission, in order to recover seismic velocity and density as a function of latitude, longitude and depth within the Moon. We will relate density (rho) to seismic velocity (v) using a linear relationship that is allowed to be depth-dependent. The corresponding coefficient (B) can reflect a variety of material properties that vary with depth, including temperature and composition. The inversion seeks to recover the set of rho, v, and B perturbations that minimize (in a least-squares sense) the difference between the observed and calculated data.

Weber, Renee C.↗
NASA NTRS2014

Grail Refinements to Lunar Seismic Structure

To probe a planet's interior, seismology provides the most direct constraints on the variables that govern the dynamic properties of the body. However, the GRAIL (Gravity Recovery and Interior Laboratory) mission's high-resolution measurements of the lunar gravity field provide constraints on crustal thickness, mantle structure, core radius and stratification, and core state (solid vs. molten). These data complement seismic investigations, and joint interpretation permits improved constraints on the Moon's internal structure. Joint interpretation of disparate geophysical datasets helps reduce drawbacks that can result from analyzing them individually. The Apollo seismic network was situated on the lunar nearside surface in a roughly equilateral triangle having sides approximately 1000 km long, with stations 12/14 nearly co-located at one corner. Due to this limited geographical extent, near-surface ray coverage from moonquakes is low, but increase with depth. In comparison, gravity surveys and their resulting gravity anomaly maps have traditionally offered optimal resolution at crustal depths. Gravimetric maps and seismic data sets are therefor well suited to joint inversion, since the complementary information reduces inherent model ambiguity. We will perform a joint inversion of Apollo seismic delay times and gravity data collected by GRAIL lunar gravity mission, in order to recover seismic velocity and density as a function of latitude, longitude and depth within the Moon. We will relate density (rho) to seismic velocity (v) using a linear relationship that is allowed to be depth-dependent. The corresponding coefficient (B) can reflect a variety of material properties that vary with depth, including temperature and composition. The inversion seeks to recover the set of rho, v, and B perturbations that minimize (in a least-squares sense) the difference between the observed and calculated data.

Weber, Renee C.↗