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At least 703 records · Page 39

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DOE OSTI2018

Notes on the Codimension One Conjecture in the Operator Corona Theorem

Answering a question of S. R. Treil (2004), for every δ, 0 < δ < 1, we construct examples of contractions whose characteristic function F ∈ H{sup ∞}(ε →ε{sub ∗}) satisfies the conditions ‖F(z)x‖ ≥ δ‖x‖ and dim ε{sub ∗} ⊝ F(z)ε = 1 for every z ∈ 𝔻, x ∈ ε, but is not left invertible. In addition, we show that the condition where is the trace class of operators, which is sufficient for the left invertibility of an operatorvalued function F satisfying the estimate ‖F(z)x‖ ≥ δ‖x‖ for every z ∈ 𝔻, x ∈ ε, with some δ > 0 (Treil, 2004), is necessary for the left invertibility of an inner function F such that dim ε{sub ∗} ⊝ F(z)ε < ∞ for some z ∈ 𝔻.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1977

Identification of an educational production function for diverse technologies

Production function analysis used to estimate the cost effectiveness of three alternative technologies in higher education: traditional instruction, instructional television, and computer-assisted instruction is presented. Criteria and selection of a functional form are outlined and a general discussion of variable selection and measurement is presented.

Mcclung, R. L.↗

NASA NTRS1994

Size distribution and scattering phase function of aerosol particles retrieved from sky brightness measurements

Ground-based measurements of the solar transmission and sky radiance in a horizontal plane through the Sun are taken in several geographical regions and aerosol types: dust in a desert transition zone in Israel, sulfate particles in Eastern and Western Europe, tropical aerosol in Brazil, and mixed continental/maritime aerosol in California. Stratospheric aerosol was introduced after the eruption of Mount Pinatubo in June 1991. Therefore measurements taken before the eruption are used to analyze the properties of tropospheric aerosol; measurements from 1992 are also used to detect the particle size and concentration of stratospheric aerosol. The measurements are used to retrieve the size distribution and the scattering phase function at large scattering angles of the undisturbed aerosol particles. The retrieved properties represent an average on the entire atmospheric column. A comparison between the retrieved phase function for a scattering angle of 120 deg, with phase function predicted from the retrieved size distribution, is used to test the assumption of particle homogeneity and sphericity in radiative transfer models (Mie theory). The effect was found to be small (20% +/- 15%). For the stratospheric aerosol (sulfates), as expected, the phase function was very well predicted using the Mie theory. A model with a power law distribution, based on the spectral dependence of the optical thickness, alpha, cannot estimate accurately the phase function (up to 50% error for lambda = 0.87 microns). Before the Pinatubo eruption the ratio between the volumes of sulfate and coarse particles was very well correlated with alpha. The Pinatubo stratospheric aerosol destroyed this correlation. The aerosol optical properties are compared with analysis of the size, shape, and composition of the individual particles by electron microscopy of in situ samples. The measured volume size distribution before the injection of stratospheric aerosol consistently show two modes, sulfate particles with r(sub m) less than 0.2 microns and coarse paritcles with r(sub m) greater than 0.7 microns. The 'window' in the tropospheric aerosol in this radius range was used to observe a stable stratospheric aerosol in 1992, with r(sub m) approximately 0.5 microns. A combination of such optical thickness and sky measurements can be used to assess the direct forcing and the climatic impact of aerosol. Systematic inversion for the key aerosol types (sulfates, smoke, dust, and maritime aerosol) of the size distribution and phase function can give the relationship between the aerosol physical and optical properties that can be used to compute the radiative forcing. This forcing can be validated in dedicated field experiments.

Kaufman, Y. J.↗

DOE OSTI2022

Estimated timescales for wet deposition of organic compounds as a function of Henry's law constants

Atmospheric organic compounds may deposit to Earth's surfaces via dry deposition, driven by concentration gradients, and wet deposition, driven by the scavenging of compounds by precipitation. Their removal by deposition has downstream impacts on concentrations of secondary organic aerosol by removing potential aerosol precursors that would otherwise oxidize to form particulate matter. The impact of deposition processes can consequently be considered as competition between rates of oxidation and deposition, but timescales for deposition are not well constrained. While timescales for dry deposition have been estimated and experimentally validated in the past, understanding of wet deposition of organics is still very limited. In this work, we estimate the wet deposition timescale for gas-phase organic compounds in the atmosphere as a function of Henry's law constants, H, using real-world precipitation frequency and size distributions at five globally-distributed sites. The wet deposition timescale decreases significantly with the increase of H until reaching a stable minimum for compounds with H > 10 5 M per atm. We estimate that the median wet deposition timescale for highly soluble gases is approximately 5 hours during a continuous rain event for all sites. However, median estimated timescales ranged from 80 to 200 hours, depending on location. Timescales are found to depend primarily on the frequency and duration of precipitation events rather than their intensity or size characteristics. Based on these data, we demonstrate that timescales for wet deposition of gases can be estimated at any given location using only basic precipitation information, without detailed or high-precision measurements.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Metalearners for estimating heterogeneous treatment effects using machine learning

There is growing interest in estimating and analyzing heterogeneous treatment effects in experimental and observational studies. We describe a number of metaalgorithms that can take advantage of any supervised learning or regression method in machine learning and statistics to estimate the conditional average treatment effect (CATE) function. Metaalgorithms build on base algorithms—such as random forests (RFs), Bayesian additive regression trees (BARTs), or neural networks—to estimate the CATE, a function that the base algorithms are not designed to estimate directly. We introduce a metaalgorithm, the X-learner, that is provably efficient when the number of units in one treatment group is much larger than in the other and can exploit structural properties of the CATE function. For example, if the CATE function is linear and the response functions in treatment and control are Lipschitz-continuous, the X-learner can still achieve the parametric rate under regularity conditions. We then introduce versions of the X-learner that use RF and BART as base learners. In extensive simulation studies, the X-learner performs favorably, although none of the metalearners is uniformly the best. In two persuasion field experiments from political science, we demonstrate how our X-learner can be used to target treatment regimes and to shed light on underlying mechanisms. A software package is provided that implements our methods.

42 ENGINEERING↗

NASA NTRS1989

Small scale irregularities in Comet Halley's plasma mantle - An attempt at self-consistent analysis of plasma and magnetic field data

VEGA-1 measurements of the plasma density and magnetic field in the coma of Comet Halley show characteristic signatures over a significant portion of the outbound pass. It is found that the assumption that there is a balance between the thermal and magnetic pressures in these features can be used to obtain estimates of the plasma temperature as a function of distance from the nucleus. These estimates indicate that the ions cool from about 1.5 x 10 to the 6th K at 10 to the 5th km to 2 x 10 to the 5th K at 5 x 10 to the 4th km. The technique used here represents a novel approach whereby temperature measurements can be made in situations where only plasma density and magnetic field data are available.

Vaisberg, O. L.↗

NASA NTRS2013

Systems and Methods for Peak-Seeking Control

A computerized system and method for peak-seeking-control that uses a unique Kalman filter design to optimize a control loop, in real time, to either maximize or minimize a performance function of a physical object ("plant"). The system and method achieves more accurate and efficient peak-seeking-control by using a time-varying Kalman filter to estimate both the performance function gradient (slope) and Hessian (curvature) based on direct position measurements of the plant, and does not rely upon modeling the plant response to persistent excitation. The system and method can be naturally applied in various applications in which plant performance functions have multiple independent parameters, and it does not depend upon frequency separation to distinguish between system dimensions.

Ryan, John J↗

NASA NTRS1977

A new method for predicting response in complex linear systems. II

The paper describes convergence and response studies in the low frequency range of complex systems, particularly with low values of damping of different distributions, and reports on the modification of the relaxation procedure required under these conditions. A new method is presented for response estimation in complex lumped parameter linear systems under random or deterministic steady state excitation. The essence of the method is the use of relaxation procedures with a suitable error function to find the estimated response; natural frequencies and normal modes are not computed. For a 45 degree of freedom system, and two relaxation procedures, convergence studies and frequency response estimates were performed. The low frequency studies are considered in the framework of earlier studies (Kayser and Bogdanoff, 1975) involving the mid to high frequency range.

Bogdanoff, J. L.↗

NASA NTRSDate not supplied

How Much Blue Carbon do Hudson Estuary Marshes Sequester? A Full-Depth Carbon Stock Estimation of Iona Marsh, Lower Hudson, NY

Tidal marshes function as a key ecosystem, by serving as nurseries, improving water quality, protecting biodiversity, preventing erosion of coastlines, and preserving archives of paleoclimate and paleoecology. In the last few decades, researchers have come to appreciate coastal marshes’ carbon sequestration function. However, full peat depth is required for estimating the true carbon content of marshes, and very little research has been done to discover the full peat depth along coastlines. We selected Iona Marsh (73°58’44.972”W, 41°18’6.366”N), situated adjacent to Bear Mountain Park and part of the National Estuarine Research Reserve, to document the belowground storage of blue carbon. In order to calculate marsh volume, three full-depth transects were performed from 2020 to 2022, two from east to west in different regions of the marsh, and one from north to south at a minimum of 10 m intervals. We found that marsh depth ranged from 5.1 m to 13.2 m. We calculated marsh volume from the full peat depth and marsh area, obtained through the National Wetlands Inventory database, by applying the average marsh depth over its entire surface area. In order to calculate carbon content, we extracted a 9m sediment core and used loss-on-ignition (LOI) to determine organic matter, then estimate carbon content as half of the organic matter. We used 198 LOI samples to calculate the carbon, which formed at this site over 6000 years ago. We intend to apply this methodology framework to other marshes in the Hudson region. Because many previous carbon stock estimates only account for the top 1 m of peat, the role of these ecosystems in carbon sequestration is significantly underestimated. By determining the full-depth carbon stock of these marshes, we hope to emphasize the value of marshes to the community, beyond what is traditionally recognized, particularly in light of sea level rise and the vulnerability of marshes to erosion.

Tidal marshes↗

NASA NTRS1997

A Multi-Resolution Nonlinear Mapping Technique for Design and Analysis Application

This report describes a nonlinear mapping technique where the unknown static or dynamic system is approximated by a sum of dimensionally increasing functions (one-dimensional curves, two-dimensional surfaces, etc.). These lower dimensional functions are synthesized from a set of multi-resolution basis functions, where the resolutions specify the level of details at which the nonlinear system is approximated. The basis functions also cause the parameter estimation step to become linear. This feature is taken advantage of to derive a systematic procedure to determine and eliminate basis functions that are less significant for the particular system under identification. The number of unknown parameters that must be estimated is thus reduced and compact models obtained. The lower dimensional functions (identified curves and surfaces) permit a kind of "visualization" into the complexity of the nonlinearity itself.

Phan, Minh Q.↗

NASA NTRS1998

A Multi-Resolution Nonlinear Mapping Technique for Design and Analysis Applications

Phan, Minh Q.↗

DOE OSTI2022

Quasar Identification Using Multivariate Probability Density Estimated from Nonparametric Conditional Probabilities

Nonparametric estimation for a probability density function that describes multivariate data has typically been addressed by kernel density estimation (KDE). A novel density estimator recently developed by Farmer and Jacobs offers an alternative high-throughput automated approach to univariate nonparametric density estimation based on maximum entropy and order statistics, improving accuracy over univariate KDE. This article presents an extension of the single variable case to multiple variables. The univariate estimator is used to recursively calculate a product array of one-dimensional conditional probabilities. In combination with interpolation methods, a complete joint probability density estimate is generated for multiple variables. Good accuracy and speed performance in synthetic data are demonstrated by a numerical study using known distributions over a range of sample sizes from 100 to 10 6 for two to six variables. Performance in terms of speed and accuracy is compared to KDE. The multivariate density estimate developed here tends to perform better as the number of samples and/or variables increases. As an example application, measurements are analyzed over five filters of photometric data from the Sloan Digital Sky Survey Data Release 17. The multivariate estimation is used to form the basis for a binary classifier that distinguishes quasars from galaxies and stars with up to 94% accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1976

Diminiode thermionic conversion with 111-iridium electrodes

Preliminary data indicating thermionic-conversion potentialities for a 111-iridium emitter and collector spaced 0.2 mm apart are presented. These results comprise output densities of current and of power as functions of voltage for three sets of emitter, collector, and reservoir temperatures: 1553, 944, 561 K; 1605, 898, 533 K; and 1656, 1028, 586 K. For the 1605 K evaluation, estimates produced work-function values of 2.22 eV for the emitter and 1.63 eV for the collector with a 2.0-eV barrier index (collector work function plus interelectrode voltage drop) corresponding to the maximum output of 5.5 W/sq cm at 0.24 volt. The current, voltage curve for the 1656 K 111-iridium diminiode yields a 6.2 W/sq cm maximum at 0.25 volt and is comparable with the 1700 K envelope for a diode with an etched-rhenium emitter and a 0.025-mm electrode gap made by TECO and evaluated by NASA.

Koeger, E. W.↗

NASA NTRS2008

Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI)

The National Research Council Earth Science Decadal Survey, Earth Science Applications from Space, recommends that DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice), an integrated L-band InSAR and multibeam Lidar mission, launch in the 2010- 2013 timeframe. The mission will measure surface deformation for solid Earth and cryosphere objectives and vegetation structure for understanding the carbon cycle. InSAR has been used to study surface deformation of the solid Earth and cryosphere and more recently vegetation structure for estimates of biomass and ecosystem function. Lidar directly measures topography and vegetation structure and is used to estimate biomass and detect changes in surface elevation. The goal of DESDynI is to take advantage of the spatial continuity of InSAR and the precision and directness of Lidar. There are several issues related to the design of the DESDynI mission, including combining the two instruments into a single platform, optimizing the coverage and orbit for the two techniques, and carrying out the science modeling to define and maximize the scientific output of the mission.

Donnellan, Andrea↗

DOE OSTI2022

Qualitative trend analysis based on a mixed-integer representation

Shape constrained spline fitting is a useful method to impose prior knowledge onto flexible semi-parametric models during parameter estimation. Most typically, the function shape is imposed through order restrictions on the regression coefficients. The intended shape is considered known or selected based on heuristic rules. In this study, we present a method to estimate the optimal set of order restrictions to segment a univariate data series into episodes with distinct shapes. This is also known as the qualitative trend analysis (QTA) problem. The obtained solution uses a trade-off between lack-of-fit and model complexity. Further, our practical implementation takes inspiration from the generalized order restricted information criterion (GORIC) for inequality-constrained model selection. From this, one learns (a) that QTA can be formulated as a mixed-integer quadratic program (MIQP) and (b) that the newly proposed mixed order restricted information criterion (MORIC) enables optimal segmentation. This is illustrated through didactic case studies.

42 ENGINEERING↗

DOE OSTI2025

On the Stability Analysis of Astrophysical Cooling Functions

To model the temperature evolution of optically thin astrophysical environments at MHD scales, radiative and collisional cooling rates are typically either pretabulated or fit into a functional form and then input into MHD codes as a radiative loss function. Thermal balance requires estimates of the analogous heating rates, which are harder to calculate, and due to uncertainties in the underlying dissipative heating processes these rates are often simply parameterized. The resulting net cooling function defines an equilibrium curve that varies with density and temperature. Such cooling functions can make the gas prone to thermal instability (TI), which will cause departures from equilibrium. There has been no systematic study of thermally unstable parameter space for nonequilibrium states. Motivated by our recent finding that there is a related linear instability, catastrophic cooling instability, that can dominate over TI, here we carry out such a study. We show that Balbus instability criteria for TI can be used to define a critical cooling rate, Λ c , that permits a nonequilibrium analysis of cooling functions through the mapping of TI zones. We furthermore illustrate how thermal conduction modifies the shape of TI zones. Upon applying a Λ c -based stability analysis to coronal loop simulations, we find that loops undergoing periodic episodes of coronal rain formation are linearly unstable to catastrophic cooling instability, while TI is stabilized by thermal conduction.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1987

A catalog of galaxies in Hercules from the Palomar Sky Survey and the Minnesota Automated Plate Scanner

The development of galaxies catalogs from the Palomar Sky Survey using the Minnesota Automated Plate Scanner (APS) is examined. The design and operation of APS are described. The algorithm used to distinguish stars from galaxies is discussed, and the completeness and confusion of the algorithm as a function of magnitude are estimated. The quality of the photometric calibration for galaxy magnitudes and surface-brightness thresholds is evaluated. The relation between the distribution of colors and morphological types is studied. The luminosity functions for Hercules galaxies are calculated and presented. The catalog generated using the APS is 80 percent complete; photometry good to 0.23 mag rms is possible; and J-F colors are good to 0.17 mag rms.

Dickey, John M.↗

NASA NTRS2025

On the Stability Analysis of Astrophysical Cooling Functions

To model the temperature evolution of optically thin astrophysical environments at MHD scales, radiative and collisional cooling rates are typically either pretabulated or fit into a functional form and then input into MHD codes as a radiative loss function. Thermal balance requires estimates of the analogous heating rates, which are harder to calculate, and due to uncertainties in the underlying dissipative heating processes these rates are often simply parameterized. The resulting net cooling function defines an equilibrium curve that varies with density and temperature. Such cooling functions can make the gas prone to thermal instability (TI), which will cause departures from equilibrium. There has been no systematic study of thermally unstable parameter space for nonequilibrium states. Motivated by our recent finding that there is a related linear instability, catastrophic cooling instability, that can dominate over TI, here we carry out such a study. We show that Balbus instability criteria for TI can be used to define a critical cooling rate, Λc, that permits a nonequilibrium analysis of cooling functions through the mapping of TI zones. We furthermore illustrate how thermal conduction modifies the shape of TI zones. Upon applying a Λc-based stability analysis to coronal loop simulations, we find that loops undergoing periodic episodes of coronal rain formation are linearly unstable to catastrophic cooling instability, while TI is stabilized by thermal conduction.

Amanda Stricklan↗