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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

New Features of the NEQAIR Radiation Code

The longest-lived code for predicting shock layer radiation, NEQAIR, is now in its 5th decade of service. Substantial changes to the code have been made over the previous decade, the most recent report of which was at the 5th Workshop on Radiation in High Temperature Gases in 2014, for the version referred to as NEQAIR14. This paper will review some of the improvements made to the NEQAIR code since then, which is now at v15.2. Some of these features are discussed briefly below. NEQAIR15 and subsequent versions have enabled parallel evaluation of multiple lines of sight. This is accomplished by utilizing the HDF5 file format and placing multiple lines into a single file, LOS.h5, which is used for both input and output. This approach enables straightforward parallel execution both over the number of lines of sight and the number of points per line. For large problems, runtime reduces linearly with the number of nodes deployed since each line is processed independently by a subset of MPI ranks. Three applications of the multi-line solver are discussed. The first has to do with performing loosely coupled radiation-flowfield solutions. In this case the computed absorption and emission coefficients are used to evaluate the total energy absorbed or emitted at each point, allowing evaluation of the volumetric source term in the flowfield. The second computation is for obtaining heat flux from nonuniform flows, which require integration over spherical co-ordinates. These are of particular interest for evaluating radiation on the vehicle backshell. This 3D option improves the angular integration scheme and allows adaptive line selection that together reduce the number of lines required by about an order of magnitude. The final application is for remote observation, which is essentially the 3D integration problem over a small solid angle. For all three of these computations, data can be stored in the HDF5 file which allows a NEQAIR run to be restarted when it times out, or to add atmospheric absorption or instrument scan functions. An additional level of parallelism is enabled in NEQAIR15.2 using GPU routines. The GPU parallelism has realized up to 8x speed-up when running on a single core but diminishes as CPU parallelism is increased. For running multi-line simulations, it may be easier to reserve a large number of CPU nodes than to obtain the number of GPU nodes required for similar performance. A GUI, known as NEQTPY, allows for reading and creating input files, running NEQAIR, and displaying results. A significant feature of NEQTPY is the ability to perform spectral fits to data. The fits can operate on a single line spectrum (radiance vs. wavelength) or a 3D input file with multiple columns of data. Other new features include improved constants, additional species, more detailed non-Boltzmann modelling, advanced user controls, the ability to read and calculate spectra from HITRAN datafiles, photodissociation and photoionization cross-sections. A “fast” automatic grid option may reduce the size and time of spectral calculations while still maintaining good accuracy for total heat flux.

Brett A Cruden↗
NASA NTRS2023

Parameterization of Features on Spherical Surfaces

NASA’s Planetary Systems Laboratory (PSL) at the Goddard Spaceflight Center in Greenbelt, Maryland is tasked with the study of solar system objects. This work is frequently based on analysis of imagery from visiting spacecraft, orbiting telescopes, and ground-based sensors. A consequence of this mission is the need to characterize features on the spherical surface of planets and moons, such characterization including the overall area of the feature, its center, its moments of inertia, its perimeter, its compactness, its major axis, its bounding box, its aspect ratio and its North-South orientation. Accurate assessment of these measures from a “flat” two-dimensional image is a challenge, since the scale of distance observed at the center of a spherical object distorts in any direction towards the horizon. PSL has developed a technique to guarantee accurate and automated measurement at any point on the visible surface, by overlaying an imaginary grid of equal-area cells onto the two-dimensional image of the sphere. The technique is named Grid-Oriented Normalization for Analysis of Spherical Areas (GONASA). This paper discusses the construction of the normalization grid and describes specific algorithms for feature parameterization. The algorithms are implemented in an accompanying Excel spreadsheet, both for clarity and ease of adoption, and to emphasize their aptness for automation. Finally, a concrete use case is offered where the GONASA grid and algorithms are used to characterize methane clouds on the Saturnian moon Titan.

Planetary science↗
NASA NTRSDate not supplied

The Multiplatform Precipitation Feature (MPF) Database: Synthesizing Satellite and Ground-Based Precipitation and Lightning Datasets for Convective Studies

NASA’s Lightning Imaging Sensor (LIS) and the Global Precipitation Measurement (GPM) mission have contributed a wealth of data toward global lightning and precipitation studies, respectively. Combining lightning and precipitation datasets leverages their unique insights into deep convective processes that inform about characteristics of convection and its intensity. Recent efforts to synthesize the LIS and GPM datasets prepare the opportunity for unprecedented large-scale, value-added multiplatform analyses of convection. This data synthesis proof-of-concept study elaborates on the creation of a database of reflectivity-based multiplatform precipitation features (MPFs) that capture a combination of information extracted from spatiotemporally coincident lightning and precipitation data within individual storm features. The space-based GPM Dual-frequency Precipitation Radar (DPR) provides a record of precipitation data, while the GPM Validation Network (VN) additionally incorporates ground-based polarimetric Doppler radar data to provide microphysical and kinematic context to DPR data. The LIS instrument onboard the International Space Station has contributed lightning observations since 2017. MPFs encapsulating information from these datasets are created from isolated regions of filtered, smoothed DPR reflectivity data to which ellipses are fit. Each MPF includes feature location, size, and eccentricity information as well as summary reflectivity characteristics. They also include summaries of precipitation microphysics and derived three-dimensional wind available from ground-based radar data. LIS data provides standard lightning characteristics such as flash count and density to each MPF as well as other informative metrics such as flash area and radiance. Each MPF file includes information about the original data from which the MPF and its characteristics were determined, allowing end-user reconstruction of the ellipse and deeper “level I” analysis of captured data. This database of VN-LIS MPFs enables broad statistical analysis of the relationships between the microphysical, kinematic, and electrical properties of convection. Preliminary results from a demonstration of the database will be described as well as ongoing efforts and avenues for future work.

Lightning↗
NASA NTRSDate not supplied

Critical Progressive Damage Analysis Model Features for Low-Velocity Impact on Thermoset and Thermoplastic Panels

A previous verification and validation framework evaluated the ability of various progressive damage analysis (PDA) tools to predict the mechanical response and damage state in post-buckled stiffened aerospace structures composed of fiber-reinforced thermoset composite materials. Herein, the ability of PDA tools to predict damage in thermoplastic composite materials subject to low-velocity impact (LVI) loading has been assessed. LVI tests and analyses have been conducted for similar panels, comprising thermoset or thermoplastic composite materials. Preliminary test/analysis correlations revealed that using the same combination of PDA model features and finite element model-building guidelines for the thermoset and thermoplastic LVI specimens resulted in underprediction of matrix crack lengths and delaminated area in the thermoplastic analyses despite yielding good correlations for the thermoset specimens. In this paper, the quality of the test/analysis correlations for analyses of thermoplastic LVI specimens performed with different combinations of PDA model features using the NASA CompDam material model are presented. Model features that were assessed in terms of effect on the quality of the test/analysis correlation include the representation of damageable interfaces, residual thermal stresses, and fiber damage.

Frank Leone↗
NASA NTRSDate not supplied

Critical Progressive Damage Analysis Model Features for Low-Velocity Impact on Thermoset and Thermoplastic Panels

A previous verification and validation framework evaluated the ability of various progressive damage analysis (PDA) tools to predict the mechanical response and damage state in post-buckled stiffened aerospace structures composed of fiber-reinforced thermoset composite materials. Herein, the ability of PDA tools to predict damage in thermoplastic composite materials subject to low-velocity impact (LVI) loading has been assessed. LVI tests and analyses have been conducted for similar panels, comprising thermoset or thermoplastic composite materials. Preliminary test/analysis correlations revealed that using the same combination of PDA model features and finite element model-building guidelines for the thermoset and thermoplastic LVI specimens resulted in underprediction of matrix crack lengths and delaminated area in the thermoplastic analyses despite yielding good correlations for the thermoset specimens. In this paper, the quality of the test/analysis correlations for analyses of thermoplastic LVI specimens performed with different combinations of PDA model features using the NASA CompDam material model are presented. Model features that were assessed in terms of effect on the quality of the test/analysis correlation include the representation of damageable interfaces, residual thermal stresses, and fiber damage.

Frank Leone↗
NASA NTRSDate not supplied

Features for a Modern Strain-Gage Balance Data Analysis Software Tool

Required, recommended, and optional features are discussed that benefit preparation and evaluation of the load prediction equations in a strain-gage balance data analysis tool. First, milestones in the evolution of load prediction methods are reviewed so that suggested features can be put into a historical context. Afterwards, independent and dependent variable choices for the balance data analysis are discussed. Then, it is illustrated how three different metrics may be used for the identification of the root cause of an unwanted divergence of the load iterations that may be observed during an iterative load prediction. Finally, a list of features is provided to guide software development efforts.

wind tunnel test↗
NASA NTRSDate not supplied

Understanding the Impact of Unobservable Variables on the Performance of Predictive Models: The Need for Feature Space Partitioning and Fusion

When developing predictive models over a dataset, the model is globally optimized across the entire feature space to learn a decision boundary. However, when unobservable variables—which cannot be measured or estimated—interact with the observable variables, this can negatively impact the optimization applied to the decision boundary since the data samples introduced by unobservable variables may have little to no association with the applied global optimization. This, consequently, penalizes the entire decision boundary and model performance. This paper examines some of the detrimental effects of unobservable variables, particularly their role in creating new modes in the distribution of observable variables and reducing the separability of class distributions. Such challenges result in skewed or warped decision boundaries and decreased accuracy of model predictions, particularly for interpretable models like logistic regression and decision trees. Through two illustrative case examples, we highlight the need to address the challenges imposed by unobservable variables. We propose a strategy to mitigate these challenges by creating local regions within the feature space through partitioning. This enables the optimization of local models within the regions to overcome the impact of unobservability in different feature space localities. Research into a more sophisticated partitioning strategy and where the partition should be relative to the sample of interest is left as future work. Through the analysis of the impact of unobservability and the development of a partitioning method, we demonstrate the clear need for a partitioning strategy that integrates knowledge from multiple local models to estimate risk factors using information fusion. Thus, we establish the foundation and motivation for using partitioning and information fusion to overcome the effects of unobservability in predictive models. Formal fusion methods, such as Dempster-Shafer theory, can better leverage the information from local regions to improve the performance of interpretable predictive models in the presence of unobservable variables.

Time Series Data↗
NASA NTRS1995

An Example of Unsupervised Networks Kohonen's Self-Organizing Feature Map

Kohonen's self-organizing feature map belongs to a class of unsupervised artificial neural network commonly referred to as topographic maps. It serves two purposes, the quantization and dimensionality reduction of date. A short description of its history and its biological context is given. We show that the inherent classification properties of the feature map make it a suitable candidate for solving the classification task in power system areas like load forecasting, fault diagnosis and security assessment.

Kohonen Feature Map↗
NASA NTRSDate not supplied

Feature-Guided Analysis of Neural Networks

Applying standard software engineering practices to neural networks is challenging due to the lack of high-level abstractions describing a neural network’s behavior. To address this challenge, we propose to extract high-level task-specific features from the neural network internal representation, based on monitoring the neural network activations.The extracted feature representations can serve as a link to high-level requirements and can be leveraged to enable fundamental software engineering activities, such as automated testing, debugging, requirements analysis, and formal verification, leading to better engineering of neural networks. Using two case studies, we present initial empirical evidence demonstrating the feasibility of our ideas.

Features↗
NASA NTRS1972

Selected volcanic features, part L

Volcanic features obtained from a preliminary examination of Apollo 15 orbital photographs are described. Of particular interest are the features photographed in the vicinity of the far-side crater basin Tsiolkovsky. The photographs indicate that smooth, plains-forming material is present in parts of the ejecta blanket southeast of the basin rim. A debris flow on the northwestern part of the rim is also depicted. The usefulness of near-terminator photography is evidenced by the fact that numerous flow fronts not seen in photographs taken at higher angles of illumination are clearly visible. It is concluded that the presence of so many fronts confirms the belief that multiple flows are responsible for the filling of lunar mare basins.

West, M. N.↗
NASA NTRS1972

An unusual mare feature, part N

During rapid scanning of the Apollo 15 panoramic camera photography, a peculiar feature was noted in a small patch of mare material lying between the Haemus and the Apennine Mountains. The patch is abnormal in that it is an unbordered plateau with the surface appearing to lie several hundred meters above adjacent mare patches. Significant characteristics of the feature are discussed and two panoramic camera photographs are illustrated.

Whitaker, E. A.↗
NASA NTRS1971

Geological features in Wyoming from Nimbus 1

The identification of ground features in Nimbus photography by comparisons with geology, soils, and vegetation maps is discussed for the Wyoming-Colorado area. It is concluded that in a semiarid region, high topographic relief shows good coassociation with exposed geology and with vegetation and, to a lesser degree, with soils types. In lower, flatter basins, most tonal patterns are related to subtle variations in soil color and vegetation cover. It is thought that maps based on spectral parameters as the proper descriptor of surface features may be required.

Short, N. M.↗
NASA NTRS1971

Calculated and observed features of stable auroral red arcs during three geomagnetic storms.

Satellite electron temperature and density data are used to calculate the structure of several stable auroral red arcs (SAR arcs) according to the thermal conduction model of the arc. The calculated lambda 6300 emission rates are compared with ground-based photometric observations taken at the same time and in the vicinity of the satellite crossings of the arcs. The SAR arcs analyzed include a range of lambda 6300 intensities, geographical locations, and times during the associated geomagnetic storm. In addition, satellite data were obtained at different altitudes over and within the SAR-arc region. Enhanced electron temperatures within or on the equatorward edge of an electron-density depression are common features of all the SAR arcs examined. There is general agreement between the calculated and observed lambda 6300 emission features for SAR arcs observed during the geomagnetic storm periods of Oct. 29 to Nov. 2, 1968, May 14-15, 1969, and Mar. 8-9, 1970. For these SAR arcs, thermal conduction from the magnetosphere alone is sufficient to excite the lambda 6300 emission to its observed intensity.

Roble, R. G.↗
NASA NTRS1971

A search for spectral features in the submillimeter background radiation.

Mountaintop observations were made at 1 per cent spectral resolution of atmospheric and sky emission in an attempt to determine the spectral features of submillimeter background radiation. No emission features were found that could be related to the diffuse isotropic flux reported from rocket and balloon experiments.

Mather, J. C.↗
NASA NTRS1971

Dissociative excitation of vacuum-ultraviolet emission features by electron impact on molecular gases. II.

Atomic-nitrogen multiplets have been excited. The excitation cross sections have been measured over the energy range from threshold to 350 eV. The transition arrays, mean wavelengths, and cross sections for dissociative excitation of the multiplets at 100 eV are presented. The experiment featured a monoenergetic electron beam which was incident on a quasi-static gas target. Vacuum-ultraviolet emission features were isolated by a normal-incidence monochromator, and multiscaling pulse-counting techniques were used.

Mumma, M. J.↗
NASA NTRS1972

Chemical features of the Luna 16 regolith sample.

The Luna 16 regolith sample differs from Apollo 11, 12 and 14 regolith and basalt samples by having smaller negative Eu and Sr anomalies and nearly chondritic Eu/Sm and Eu/Sr ratios although the overall REE, Ba, Sr and U concentrations are 25 to 45 times chondrites. Major element data, in particular FeO vs Al2O3, show that the Luna 16 regolith sample is composed of materials that follow a quantitatively different Fe/Al variation than do Apollo 11, 12, 14 and 15 samples. The small Eu and Sr anomalies and the displaced Fe/Al variation are two chemical features unique to the Luna 16 regolith sample. The Luna 16 regolith sample can contain little if any of the rock types abundant at Apollo sites, thus indicating that the unique chemical features are typical of local or nearby materials and indicate a separate petrogenetic province for major component rock types of the Luna 16 regolith.

Hubbard, N. J.↗