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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 NTRS1983

Selection of optimum frequencies for atmospheric electric path length measurement by satellite-borne microwave radiometers

Numerical experiments using regressions by leaps and bounds have been performed to determine the optimum frequencies for satellite-borne microwave radiometers to estimate atmospheric electrical path length over the sea. The frequency range 5-40 GHz was searched. The effect of surface wind speed, sea surface temperature, and clouds was considered in the optimum frequency selection. The analysis indicates that approximately 0.6-cm rms accuracy is possible for one-way path length measurement using a proper pair of frequencies. The best two-channel subset selected by the leaps and bounds techniques is (16.0, 21.0) GHz.

Pandey, P. C.↗

DOE OSTI2025

Constrained or unconstrained? Neural-network-based equation discovery from data

Throughout many fields, practitioners often rely on differential equations to model systems. Yet, for many applications, the theoretical derivation of such equations and/or the accurate resolution of their solutions may be intractable. Instead, recently developed methods, including those based on parameter estimation, operator subset selection, and neural networks, allow for the data-driven discovery of both ordinary and partial differential equations (PDEs), on a spectrum of interpretability. The success of these strategies is often contingent upon the correct identification of representative equations from noisy observations of state variables and, as importantly and intertwined with that, the mathematical strategies utilized to enforce those equations. Specifically, the latter has been commonly addressed via unconstrained optimization strategies. Representing the PDE as a neural network, we propose to discover the PDE (or the associated operator) by solving a constrained optimization problem and using an intermediate state representation similar to a physics-informed neural network (PINN). The objective function of this constrained optimization problem promotes matching the data, while the constraints require that the discovered PDE is satisfied at a number of spatial collocation points. We present a penalty method and a widely used trust-region barrier method to solve this constrained optimization problem, and we compare these methods on numerical examples. Our results on several example problems demonstrate that the latter constrained method outperforms the penalty method, particularly for higher noise levels or fewer collocation points. This work motivates further exploration into using sophisticated constrained optimization methods in scientific machine learning, as opposed to their commonly used, penalty-method or unconstrained counterparts. For both of these methods, we solve these discovered neural network PDEs with classical methods, such as finite difference methods, as opposed to PINNs-type methods relying on automatic differentiation. Here, we briefly highlight how simultaneously fitting the data while discovering the PDE improves the robustness to noise and other small, yet crucial, implementation details.

Data-driven discovery↗

DOE OSTI2025

Influence of counterion substitution on the properties of imidazolium-based ionic liquid clusters

Due to their unique physiochemical properties that may be tailored for specific purposes, ionic liquids (ILs) have been investigated for various applications, including chemical separations, catalysis, energy storage, and space propulsion. The different cations and anions comprising ILs may be selected to optimize a range of desired properties, such as thermal stability, ionic conductivity, and volatility, leading to the designation of certain ILs as designer “green” solvents. The effect of counterions on the properties of ILs is of both fundamental scientific interest and technological importance. Herein, we report a systematic experimental and theoretical investigation of the size, charge, stability toward dissociation, and geometric/electronic structure of 1-ethyl-3-methyl imidazolium (EMIM)-based IL clusters containing two different atomic counterions (i.e., bromide [Br − ] and iodide [I − ]). This work extends our studies of EMIM + cations with atomic chloride (Cl − ) and molecular tetrafluoroborate (BF 4 − ) anions reported previously by Baxter et al. [Chem. Mater. 34, 2612 (2022)] and Zhang et al . [J. Phys. Chem. Lett. 11, 6844 (2020)], respectively. Distributions of anionic IL clusters were generated in the gas phase using electrospray ionization and characterized by high mass resolution mass spectrometry, energy-resolved collision-induced dissociation, and negative ion photoelectron spectroscopy experiments. The experimental results reveal anion-dependent trends in the size distribution, relative abundance, ionic charge state, stability toward dissociation, and electron binding energies of the IL clusters. Complementary global optimization theory provides molecular-level insights into the bonding and electronic structure of a selected subset of clusters, including their low energy structures and electrostatic potential maps, and how these fundamental characteristics are influenced by anion substitution. Collectively, our findings demonstrate how the fundamental properties of ILs, which determine their suitability for many applications, may be tuned by substituting counterions. These observations are critical in the sub-nanometer cluster size regime where phenomena do not scale predictably to the bulk phase, and each atom counts toward determining behavior.

cluster↗

DOE OSTI2024

AGS-GNN: Attribute-guided Sampling for Graph Neural Networks

We propose AGS-GNN, a novel attribute-guided sampling algorithm for Graph Neural Networks (GNNs) that exploits node features and connectivity structure of a graph while simultaneously adapting for both homophily and heterophily in graphs. (In homophilic graphs vertices of the same class are more likely to be connected, and vertices of different classes tend to be linked in heterophilic graphs.) While GNNs have been successfully applied to homophilic graphs, their application to heterophilic graphs remains challenging. The best-performing GNNs for heterophilic graphs do not fit the sampling paradigm, suffer high computational costs, and are not inductive. We employ samplers based on feature-similarity and feature-diversity to select subsets of neighbors for a node, and adaptively capture information from homophilic and heterophilic neighborhoods using dual channels. Currently, AGS-GNN is the only algorithm that we know of that explicitly controls homophily in the sampled subgraph through similar and diverse neighborhood samples. For diverse neighborhood sampling, we employ submodularity, which was not used in this context prior to our work. The sampling distribution is pre-computed and highly parallel, achieving the desired scalability. Using an extensive dataset consisting of 35 small (<=100K nodes) and large (>100K nodes) homophilic and heterophilic graphs, we demonstrate the superiority of AGS-GNN compare to the current approaches in the literature. AGS-GNN achieves comparable test accuracy to the best-performing heterophilic GNNs, even outperforming methods using the entire graph for node classification. AGS-GNN also converges faster compared to methods that sample neighborhoods randomly, and can be incorporated into existing GNN models that employ node or graph sampling.

artificial intelligence↗

NASA NTRS1973

Discrimination techniques employing both reflective and thermal multispectral signals

Recent improvements in remote sensor technology carry implications for data processing. Multispectral line scanners now exist that can collect data simultaneously and in registration in multiple channels at both reflective and thermal (emissive) wavelengths. Progress in dealing with two resultant recognition processing problems is discussed: (1) More channels mean higher processing costs; to combat these costs, a new and faster procedure for selecting subsets of channels has been developed. (2) Differences between thermal and reflective characteristics influence recognition processing; to illustrate the magnitude of these differences, some explanatory calculations are presented. Also introduced, is a different way to process multispectral scanner data, namely, radiation balance mapping and related procedures. Techniques and potentials are discussed and examples presented.

Malila, W. A.↗

NASA NTRS1975

Minimization search method for data inversion

Technique has been developed for determining values of selected subsets of independent variables in mathematical formulations. Required computation time increases with first power of the number of variables. This is in contrast with classical minimization methods for which computational time increases with third power of the number of variables.

Fymat, A. L.↗

NASA NTRS1975

A cloud physics investigation utilizing Skylab data

The author has identified the following significant results. The Lowtran 2 program, S191 spectral response, and solar spectrum were used to compute the expected absorption by 2.0 micron band for a variety of cloud pressure levels and solar zenith angles. Analysis of the three long wavelength data channels continued in which it was found necessary to impose a minimum radiance criterion. It was also found necessary to modify the computer program to permit the computation of mean values and standard deviations for selected subsets of data on a given tape. A technique for computing the integrated absorption in the A band was devised. The technique normalizes the relative maximum at approximately .78 micron to the solar irradiance curve and then adjusts the relative maximum at approximately .74 micron to fit the solar curve.

Alishouse, J.↗

NASA NTRS1977

Numerical image manipulation and display in solar astronomy

The paper describes the system configuration and data manipulation capabilities of a solar image display system which allows interactive analysis of visual images and on-line manipulation of digital data. Image processing features include smoothing or filtering of images stored in the display, contrast enhancement, and blinking or flickering images. A computer with a core memory of 28,672 words provides the capacity to perform complex calculations based on stored images, including computing histograms, selecting subsets of images for further analysis, combining portions of images to produce images with physical meaning, and constructing mathematical models of features in an image. Some of the processing modes are illustrated by some image sequences from solar observations.

Levine, R. H.↗

NASA NTRS1977

Quantitative comparison of combined gas chromatographic/mass spectrometric profiles of complex mixtures

The paper describes a method called HISLIB for automatic quantitative comparison of gas chromatographic/mass spectrometric (GC/MS) results obtained on complex mixtures of organic compounds. The method is based on comparing new mixtures to 'historical' libraries of previous results. Co-occurrence of components is determined by matching relative retention indices (RRIs) and mass spectra after background removal and resolution of overlapping GC components. Internal standards are used to quantify the relative concentrations of components. Applications of HISLIB include validation of analytical procedures to isolate complex mixtures; development of historical libraries which might include complete summaries of all past observations, compilations of controls, or any other selected subset of results; improvement of the quality of existing libraries of mass spectral data; and detection of differences in kind and/or amounts of individual components. Limitations of the method are mentioned along with causes of their occurrence.

Smith, D. H.↗

NASA NTRS1982

The use of Landsat-3 thermal data to help differentiate land covers

Landsat-3 Multispectral Scanner Subsystem (MSS) digital data of the Baltimore, Maryland area gathered on May 24, 1978, are examined to show the usefulness of thermal data in providing better discrimination between agricultural and residential areas, certain types of urban/industrial areas and water, cloud shadows and water, and bare-extractive areas and bright urban cover types. High altitude aircraft imagery taken on May 3, 1978, provides ground truth and training site verification. Two classifications are made for each training site: the initial one using bands 4, 5, and 7 and a second in which the thermal data are included with the visible and near infrared data. This permits a direct comparison of areas spectrally similar with and without the inclusion of the thermal data. Commission errors determined from selected subsets of the data show reductions of 95% for the urban/industrial versus water themes, 84% for the residential versus agriculture themes, 64.0% for the bare-extractive versus bright urban themes, and 24% for the cloud shadow versus water themes when the thermal data are included in the signature.

Ormsby, J. P.↗

NASA NTRS1982

The volcanic explosivity index /VEI/ - An estimate of explosive magnitude for historical volcanism

A composite estimate of the magnitude of past explosive eruptions, referred to as the Volcanic Explosivity Index (VEI), is proposed as a semiquantitative compromise between poor data and the need in various disciplines to evaluate the record of past volcanism. The VEI is assigned to more than 8000 historic and prehistoric eruptions. It is shown that the VEI can help detect incompleteness and reporting biases and can help in selecting subsets of the historical record suitable for each study. The VEI is a composite estimate of Walkers (1980) magnitude and/or intensity and/or destructiveness and/or (less frequently) dispersive power, violence, and energy release rate, depending on the data that are available.

Newhall, C. G.↗

NASA NTRS1983

Plasma properties of driver gas following interplanetary shocks observed by ISEE-3

Plasma fluid parameters calculated from solar wind and magnetic field data to determine the characteristic properties of driver gas following a select subset of interplanetary shocks were studied. Of 54 shocks observed from August 1978 to February 1980, 9 contained a well defined driver gas that was clearly identifiable by a discontinuous decrease in the average proton temperature. While helium enhancements were present downstream of the shock in all 9 of these events, only about half of them contained simultaneous changes in the two quantities. Simultaneous with the drop in proton temperature the helium and electron temperature decreased abruptly. In some cases the proton temperature depression was accompanied by a moderate increase in magnetic field magnitude with an unusually low variance, by a small decrease in the variance of the bulk velocity, and by an increase in the ratio of parallel to perpendicular temperature. The cold driver gas usually displayed a bidirectional flow of suprathermal solar wind electrons at higher energies.

Zwickl, R. D.↗

NASA NTRS1985

A preliminary harmonic spline model from Magsat data

A preliminary main field model for 1980 derived from a carefully selected subset of Magsat vector measurements, using the method of harmonic splines, is presented. This model (PHS /80/) for preliminary harmonic splines is the smoothest model (in the sense that the rms radial field at the core surface is minimum) consistent with the measurements (with an rms misfit of 10 nT to account for crustal and external fields as well as noise in the measurement procedure). Therefore PHS (80) is more suitable for studies of the core than models derived with the traditional least squares approach (e.g., GSFC /9/80/). A comparison is conducted of the characteristics of the harmonic spline spectrum, topology of the core field and especially the null-flux curves (loci where the radial field is zero) and the flux through patches bounded by such curves. PHS (80) is less complex than GSFC (9/80) and is therefore more representative of that part of the core field that the data constrain.

Shure, L.↗

NASA NTRS1991

An analysis of the least-squares problem for the DSN systematic pointing error model

A systematic pointing error model is used to calibrate antennas in the Deep Space Network. The least squares problem is described and analyzed along with the solution methods used to determine the model's parameters. Specifically studied are the rank degeneracy problems resulting from beam pointing error measurement sets that incorporate inadequate sky coverage. A least squares parameter subset selection method is described and its applicability to the systematic error modeling process is demonstrated on Voyager 2 measurement distribution.

Alvarez, L. S.↗

NASA NTRS1991

Condition of chromic acid anodized aluminum clamps flown

A survey of the condition of the chromic acid anodized (CAA) coating on selected LDEF tray clamps was carried out. Measurements of solar absorptance and thermal emittance were carried out at multiple locations on both the space exposed and spacecraft facing sides of the clamps. Multiple clamps from each available angle relative to the ram direction were examined. The diffuse component of the reflectance spectrum was measured for a selected subset of the clamps. The thickness of the CAA was determined for a small set of clamps. Examples of variation in integrity of the coatings from leading to trailing edge will be shown.

Plagemann, W. L.↗

NASA NTRS1994

TOAD Gateway

TOAD Gateway is interactive software tool for converting data files to and from variety of file formats. Currently reads and writes following file formats: TOAD; Standard Interface File (SIF); Program to Optimize Simulated Trajectories (POST) input; Comma Separated Value and Tab Separated Value, common in PC and Macintosh spreadsheet and database packages; and general free format. Additional modules for accommodating other formats easily developed and installed. Companion program, TOAD Editor (LAR-14423), manipulates contents of TOAD files and extracts selected subsets of data. TOAD Gateway written in FORTRAN 77.

Bingel, Bradford D.↗

NASA NTRS1992

The NSO FTS database program and archive (FTSDBM)

Data from the NSO Fourier transform spectrometer is being re-archived from half inch tape onto write-once compact disk. In the process, information about each spectrum and a low resolution copy of each spectrum is being saved into an on-line database. FTSDBM is a simple database management program in the NSO external package for IRAF. A command language allows the FTSDBM user to add entries to the database, delete entries, select subsets from the database based on keyword values including ranges of values, create new database files based on these subsets, make keyword lists, examine low resolution spectra graphically, and make disk number/file number lists. Once the archive is complete, FTSDBM will allow the database to be efficiently searched for data of interest to the user and the compact disk format will allow random access to that data.

Lytle, D. M.↗

NASA NTRS1991

Transferable Output ASCII Data (TOAD) editor version 1.0 user's guide

The Transferable Output ASCII Data (TOAD) editor is an interactive software tool for manipulating the contents of TOAD files. The TOAD editor is specifically designed to work with tabular data. Selected subsets of data may be displayed to the user's screen, sorted, exchanged, duplicated, removed, replaced, inserted, or transferred to and from external files. It also offers a number of useful features including on-line help, macros, a command history, an 'undo' option, variables, and a full compliment of mathematical functions and conversion factors. Written in ANSI FORTRAN 77 and completely self-contained, the TOAD editor is very portable and has already been installed on SUN, SGI/IRIS, and CONVEX hosts.

Bingel, Bradford D.↗