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At least 1,153 records · Page 64
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NASA NTRS2014

Shaping the Dust Mass-Star-Formation Rate Relation

There is a remarkably tight relation between the observationally inferred dust masses and star-formation rates (SFRs) of Sloan Digital Sky Survey galaxies, M dust ∝ SFR 1.11(exp). Here we extend the M dust-SFR relation to the high end and show that it bends over at very large SFRs (i.e., dust masses are lower than predicted for a given SFR). We identify several distinct evolutionary processes in the diagram: (1) a star-bursting phase in which dust builds up rapidly at early times. The maximum attainable dust mass in this process is the cause of the bend-over of the relation. A high dust-formation efficiency, a bottom-light initial mass function, and negligible supernova shock dust destruction are required to produce sufficiently high dust masses. (2) A quiescent star-forming phase in which the subsequent parallel decline in dust mass and SFR gives rise to the M dust-SFR relation, through astration and dust destruction. The dust-to-gas ratio is approximately constant along the relation. We show that the power-law slope of the M dust-SFR relation is inversely proportional to the global Schmidt-Kennicutt law exponent (i.e., ~0.9) in simple chemical evolution models. (3) A quenching phase which causes star formation to drop while the dust mass stays roughly constant or drops proportionally. Combined with merging, these processes, as well as the range in total baryonic mass, give rise to a complex population of the diagram which adds significant scatter to the original M dust-SFR relation. (4) At very high redshifts, a population of galaxies located significantly below the local relation is predicted.

Shaping↗
NASA NTRSDate not supplied

Document Classification Techniques for Aviation Letters of Agreement

Often when working with technical documents, it is helpful to classify them into specific categories. In this paper, we conduct a thorough review of natural language processing techniques to perform this classification task on Letters of Agreement (LOAs), technical aviation documents outlining rules for utilizing US airspace. We evaluate multiple techniques, including Transfer Learning, for representing the text in the documents as embeddings: unigram and bigram Term Frequency Inverse Document Frequency (TFIDF), Word2Vec, Doc2Vec, GloVe and RoBERTa. We investigate a wide range of classification models: K-Nearest Neighbors, Random Forest, Support Vector Machines (SVM), Logistic Regression, Naive Bayes, Feed-Forward Neural Network, Convolutional Neural Networks (CNNs) and Long-Short Term Memory (LSTM). By comparing the different methods, we found the best overall approach for our task was to use unigram TFIDF representations with SVM while also gaining insight into how the other methodologies performed on a small technical datasets.

Aayushi Batra↗
NASA NTRSDate not supplied

Document Classification Techniques for Aviation Letters of Agreement

Often when working with historic air traffic management (ATM) documents, it is helpful to classify them into specific categories. In this paper, we conduct a thorough review of natural language processing techniques to perform this classification task on Letters of Agreement (LOAs), technical aviation documents outlining rules for utilizing US airspace. We evaluate multiple techniques for representing the text in the documents as embeddings: unigram and bigram Term Frequency Inverse Document Frequency (TFIDF), Word2Vec, Doc2Vec, GloVe and RoBERTa. We investigate a wide range of classification models: K-Nearest Neighbors, Random Forest, Support Vector Machines (SVM), Logistic Regression, Naive Bayes, Feed-Forward Neural Network, Convolutional Neural Networks (CNNs) and Long-Short Term Memory (LSTM). By comparing the different methods, we found the best overall approach for our task was to use unigram TFIDF representations with SVM while also gaining insight into how the other methodologies performed on a small technical datasets.

ATM↗
NASA NTRSDate not supplied

Document Classification Techniques for Aviation Letters of Agreement

Often when working with historic air traffic management (ATM) documents, it is helpful to classify them into specific categories. In this paper, we conduct a thorough review of natural language processing techniques to perform this classification task on Letters of Agreement (LOAs), technical aviation documents outlining rules for utilizing US airspace. We evaluate multiple techniques for representing the text in the documents as embeddings: unigram and bigram Term Frequency Inverse Document Frequency (TFIDF), Word2Vec, Doc2Vec, GloVe and RoBERTa. We investigate a wide range of classification models: K-Nearest Neighbors, Random Forest, Support Vector Machines (SVM), Logistic Regression, Naive Bayes, Feed-Forward Neural Network, Convolutional Neural Networks (CNNs) and Long-Short Term Memory (LSTM). By comparing the different methods, we found the best overall approach for our task was to use unigram TFIDF representations with SVM while also gaining insight into how the other methodologies performed on a small technical datasets.

ATM↗
NASA NTRS2009

2D and 3D Numerical Simulations of Flux Cancellation

Cancellation of magnetic flux in the solar photosphere and chromosphere has been linked observationally and theoretically to a broad range of solar activity, from filament channel formation to CME initiation. Because this phenomenon is typically measured at only a single layer in the atmosphere, in the radial (line of sight) component of the magnetic field, the actual processes behind this observational signature are ambiguous. It is clear that reconnection is involved in some way, but the location of the reconnection sites and associated connectivity changes remain uncertain in most cases. We are using numerical modeling to demystify flux cancellation, beginning with the simplest possible configuration: a subphotospheric Lundquist flux tube surrounded by a potential field, immersed in a gravitationally stratified atmosphere, spanning many orders of magnitude in plasma beta. In this system, cancellation is driven slowly by a 2-cell circulation pattern imposed in the convection zone, such that the tops of the cells are located around the beta=1 level (i.e., the photosphere) and the flows converge and form a downdraft at the polarity inversion line; note however that no flow is imposed along the neutral line. We will present the results of 2D and 3D MHD-AMR simulations of flux cancellation, in which the flux at the photosphere begins in either an unsheared or sheared state. In all cases, a low-lying flux rope is formed by reconnection at the polarity inversion line within a few thousand seconds. The flux rope remains stable and does not rise, however, in contrast to models which do not include the presence of significant mass loading.

Karpen, Judith T.↗
NASA NTRS2009

20 and 3D Numerical Simulations of Flux Cancellation

Cancellation of magnetic flux in the solar photosphere and chromosphere has been linked observationally and theoretically to a broad range of solar activity, from filament channel formation to CME initiation. Because this phenomenon is typically measured at only a single layer in the atmosphere, in the radial (line of sight) component of the magnetic field, the actual processes behind this observational signature are ambiguous. It is clear that reconnection is involved in some way, but the location of the reconnection sites and associated connectivity changes remain uncertain in most cases. We are using numerical modeling to demystify flux cancellation, beginning with the simplest possible configuration: a subphotospheric Lundquist flux tube surrounded by a potential field, immersed in a gravitationally stratified atmosphere, spanning many orders of magnitude in plasma beta. In this system, cancellation is driven slowly by a 2-cell circulation pattern imposed in the convection zone, such that the tops of the cells are located around the beta= 1 level (Le., the photosphere) and the flows converge and form a downdraft at the polarity inversion line; note however that no flow is imposed along the neutral line. We will present the results of 2D and 3D MHD-AMR simulations of flux cancellation, in which the flux at the photosphere begins in either an unsheared or sheared state. In all cases, a lOW-lying flux rope is formed by reconnection at the polarity inversion line within a few thousand seconds. The flux rope remains stable and does not rise, however, in contrast to models which do not include the presence of significant mass loading.

Karpen, Judith T.↗
NASA NTRS1988

Confidence set inference with a prior quadratic bound

In the uniqueness part of a geophysical inverse problem, the observer wants to predict all likely values of P unknown numerical properties z = (z sub 1,...,z sub p) of the earth from measurement of D other numerical properties y(0)=(y sub 1(0),...,y sub D(0)) knowledge of the statistical distribution of the random errors in y(0). The data space Y containing y(0) is D-dimensional, so when the model space X is infinite-dimensional the linear uniqueness problem usually is insoluble without prior information about the correct earth model x. If that information is a quadratic bound on x (e.g., energy or dissipation rate), Bayesian inference (BI) and stochastic inversion (SI) inject spurious structure into x, implied by neither the data nor the quadratic bound. Confidence set inference (CSI) provides an alternative inversion technique free of this objection. CSI is illustrated in the problem of estimating the geomagnetic field B at the core-mantle boundary (CMB) from components of B measured on or above the earth's surface. Neither the heat flow nor the energy bound is strong enough to permit estimation of B(r) at single points on the CMB, but the heat flow bound permits estimation of uniform averages of B(r) over discs on the CMB, and both bounds permit weighted disc-averages with continous weighting kernels. Both bounds also permit estimation of low-degree Gauss coefficients at the CMB. The heat flow bound resolves them up to degree 8 if the crustal field at satellite altitudes must be treated as a systematic error, but can resolve to degree 11 under the most favorable statistical treatment of the crust. These two limits produce circles of confusion on the CMB with diameters of 25 deg and 19 deg respectively.

Backus, George E.↗
NASA NTRS2003

Improving the Accuracy of Lunar Laser Ranging Tests of Gravitational Theory: Modeling and Future Directions

Accurate analysis of precision ranges to the Moon have provided several tests of gravitational theory: the equivalence principle, geodetic precession, PPN parameters beta and gamma, and the constancy of the gravitational constant G. Other possible tests include the inverse square law at 20,000 km length scales and the PPN parameter 1. The uncertainties of these tests have decreased as data accuracies have improved and data time span has lengthened. We are exploring the modeling improvements necessary to proceed from cm to mm range accuracies. Looking to future exploration, what characteristics are desired for the next generation of ranging devices, what fundamental questions can be investigated, and what are the challenges for modeling and data analysis?

Williams, James G.↗
NASA NTRS1983

Strong turbulence and atmospheric waves in stellar occultations

General techniques for producing model lightcurves for a variety of realistic atmospheric irregularities, including turbulence and inertia-gravity waves, are presented and applied. The restrictions of weak scintillation theory are relaxed and model lightcurves are constructed using wave optics for atmospheres with strong, anisotropic turbulence. This is accomplished by numerical simulations which model the propagation of a wave through a phase-changing screen while maintaining complete amplitude and phase information from the wave. The results are compared with available weak scintillation theory and with recent occultation data. The effects of large scale atmospheric waves with realistic horizontal structure are examined, and the reliability of the numerical inversion method in retrieving the true atmospheric vertical structure under conditions of strong ray crossing and horizontal inhomogeneities is assessed. The nature of model lightcurve spikes generated using geometric optics and wave optics are compared.

French, R. G.↗
NASA NTRS1990

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

Source record↗
NASA NTRS2018

T-infinity: The Dependency Inversion Principle for Rapid and Sustainable Multidisciplinary Software Development

The CFD Vision 2030 Study recommends that, “NASA should develop and maintain an integrated simulation and software development infrastructure to enable rapid CFD technology maturation.... [S]oftware standards and interfaces must be emphasized and supported whenever possible, and open source models for noncritical technology components should be adopted.” The current paper presents an approach to an open source development architecture, named T-infinity, for accelerated research in CFD leveraging the Dependency Inversion Principle to realize plugins that communicate through collections of functions without exposing internal data structures. Steady state flow visualization, mesh adaptation, fluid-structure interaction, and overset domain capabilities are demonstrated through compositions of plugins via standardized abstract interfaces without the need for source code dependencies between disciplines. Plugins interact through abstract interfaces thereby avoiding N 2 direct code-to-code data structure coupling where N is the number of codes. This plugin architecture enhances sustainable development by controlling the interaction between components to limit software complexity growth. The use of T-infinity abstract interfaces enables multidisciplinary application developers to leverage legacy applications alongside newly-developed capabilities. While rein, a description of interface details is deferred until the are more thoroughly tested and can be closed to modification.

O'Connell, Matthew D.↗
NASA NTRS1987

Spatially random models, estimation theory, and robot arm dynamics

Spatially random models provide an alternative to the more traditional deterministic models used to describe robot arm dynamics. These alternative models can be used to establish a relationship between the methodologies of estimation theory and robot dynamics. A new class of algorithms for many of the fundamental robotics problems of inverse and forward dynamics, inverse kinematics, etc. can be developed that use computations typical in estimation theory. The algorithms make extensive use of the difference equations of Kalman filtering and Bryson-Frazier smoothing to conduct spatial recursions. The spatially random models are very easy to describe and are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. The models can also be used to generate numerically the composite multibody system inertia matrix. This is done without resorting to the more common methods of deterministic modeling involving Lagrangian dynamics, Newton-Euler equations, etc. These methods make substantial use of human knowledge in derivation and minipulation of equations of motion for complex mechanical systems.

Rodriguez, G.↗
NASA NTRS2005

Microwave Signatures of Melting/Refreezing Snow: Observations and Modeling Using Dense Medium Radiative Transfer Theory

Microwave brightness temperatures of snow covered terrains can be modeled by means of the Dense Radiative Transfer Medium Theory (DMRT). In a dense medium, such as snow, the assumption of independent scattering is no longer valid and the scattering of correlated scatterers must be considered. In the DMRT, this is done considering a pair distribution function of the particles position. In the electromagnetic model, the snowpack is simulated as a homogeneous layer having effective permittivity and albedo calculated through the DMRT. In order to account for clustering of snow crystals, a model of cohesive particles can be applied, where the cohesion between the particles is described by means of a dimensionless parameters called stickiness (z), representing a measure of the inversion of the attraction of the particles. The lower the z the higher the stickiness. In this study, microwave signatures of melting and refreezing cycles of seasonal snowpacks at high altitudes are studied by means of both experimental and modeling tools. Radiometric data were collected 24 hours per day by the University of Michigan Tower Mounted Radiometer System (TMRS). The brightness temperatures collected by means of the TMRS are simulated by means of a multi-layer electromagnetic model based on the dense medium theory with the inputs to the model derived from the data collected at the snow pits and from the meteorological station. The paper is structured as follows: in the first Section the temperature profiles recorded by the meteorological station and the snow pit data are presented and analyzed; in the second Section, the characteristics of the radiometric system used to collect the brightness temperatures are reported together with the temporal behavior of the recorded brightness temperatures; in the successive Section the multi-layer DMRT-based electromagnetic model is described; in the fourth Section the comparison between modeled and measured brightness temperatures is discussed. We dedicate the last Section to the conclusions and future works.

Tedesco, Marco↗
NASA NTRS2013

Analytical Algorithms to Quantify the Uncertainty in Remaining Useful Life Prediction

This paper investigates the use of analytical algorithms to quantify the uncertainty in the remaining useful life (RUL) estimate of components used in aerospace applications. The prediction of RUL is affected by several sources of uncertainty and it is important to systematically quantify their combined effect by computing the uncertainty in the RUL prediction in order to aid risk assessment, risk mitigation, and decisionmaking. While sampling-based algorithms have been conventionally used for quantifying the uncertainty in RUL, analytical algorithms are computationally cheaper and sometimes, are better suited for online decision-making. While exact analytical algorithms are available only for certain special cases (for e.g., linear models with Gaussian variables), effective approximations can be made using the the first-order second moment method (FOSM), the first-order reliability method (FORM), and the inverse first-order reliability method (Inverse FORM). These methods can be used not only to calculate the entire probability distribution of RUL but also to obtain probability bounds on RUL. This paper explains these three methods in detail and illustrates them using the state-space model of a lithium-ion battery.

Sankararaman, Shankar↗
NASA NTRS2016

Extracting Ocean-Generated Tidal Magnetic Signals from Swarm Data Through Satellite Gradiometry

Ocean-generated magnetic field models of the Principal Lunar, M2, and the Larger Lunar elliptic, N2, semidiurnal tidal constituents were estimated through a "Comprehensive Inversion" of the first 20.5 months of magnetic measurements from European Space Agency's (ESA) Swarm satellite constellation mission. While the constellation provides important north-south along-track gradiometry information, it is the unique low-spacecraft pair that allows for east-west cross-track gradiometry. This latter type is crucial in delivering an M2 estimate of similar quality with that derived from over 10 years of CHAMP satellite data but over a shorter interval, at higher altitude, and during more magnetically disturbed conditions. Recovered N2 contains nonoceanic signal but is highly correlated with theoretical models in regions of maximum oceanic amplitude. Thus, satellite magnetic gradiometry may eventually enable the monitoring of ocean electrodynamic properties at temporal resolutions of 1 to 2 years, which may have important implications for the inference of ocean temperature and salinity.

Magnetic↗
NASA NTRS1994

On the analysis of para-ammonia observations

The intensities and optical depths of the (1, 1), (2, 2), and (2, 1) inversion transitions of ammonia can be calculated quite accurately without solving the equations of statistical equilibrium. A two-temperature partition function suffices. The excitation of the K-ladders can be approximated by using a temperature obtained from a two-level model with the (2, 1) and (1, 1) levels. Distribution of populations between the ladders is described with the kinetic temperature. This enables one to compute the (1, 1) and (2, 1) inversion transition excitation temperatures and optical depths. To compute the (2, 2) brightness temperatures, the fractional population of the (2, 2) doublet is computed from the population of the (1, 1) doublet using the 'true rotation temperature,' which is calculated using a three-level model with the (2, 1), (2, 2), and (1, 1) levels. In spite of some iterative steps, the calculation is quite fast.

Kuiper, T. B. H.↗
NASA NTRS1995

Global precipitation estimates based on a technique for combining satellite-based estimates, rain gauge analysis, and NWP model precipitation information

The 'satellite-gauge model' (SGM) technique is described for combining precipitation estimates from microwave satellite data, infrared satellite data, rain gauge analyses, and numerical weather prediction models into improved estimates of global precipitation. Throughout, monthly estimates on a 2.5 degrees x 2.5 degrees lat-long grid are employed. First, a multisatellite product is developed using a combination of low-orbit microwave and geosynchronous-orbit infrared data in the latitude range 40 degrees N - 40 degrees S (the adjusted geosynchronous precipitation index) and low-orbit microwave data alone at higher latitudes. Then the rain gauge analysis is brougth in, weighting each field by its inverse relative error variance to produce a nearly global, observationally based precipitation estimate. To produce a complete global estimate, the numerical model results are used to fill data voids in the combined satellite-gauge estimate. Our sequential approach to combining estimates allows a user to select the multisatellite estimate, the satellite-gauge estimate, or the full SGM estimate (observationally based estimates plus the model information). The primary limitation in the method is imperfections in the estimation of relative error for the individual fields. The SGM results for one year of data (July 1987 to June 1988) show important differences from the individual estimates, including model estimates as well as climatological estimates. In general, the SGM results are drier in the subtropics than the model and climatological results, reflecting the relatively dry microwave estimates that dominate the SGM in oceanic regions.

Huffman, George J.↗
NASA NTRS1986

On compactness of admissible parameter sets: Convergence and stability in inverse problems for distributed parameter systems

A series of numerical examples is reported and several algorithms compared for estimation of coefficients in differential equation models. Unconstrained, constrained and Tikhonov regularization methods are tested for their behavior with regard to both convergence (of approximation methods for the states and parameters) and stability (continuity of the estimates with respect to perturbations in the data or observed states).

Banks, H. T.↗