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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Exploring Sentinel-1 and Sentinel-2 diversity for Flood inundation mapping using deep learning

Identification of flood water extent from satellite images has historically relied on either synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to cloud free conditions, whereas SAR imagery is plagued by noise-like speckle. Prior studies that use combinations of MS and SAR data to overcome individual limitations of these sensors have not fully examined sensitivity of flood mapping performance to different combinations of SAR and MS derived spectral indices or band transformations in color space. This study explores the use of diverse bands of Sentinel 2 (S2) through well-established water indices and Sentinel 1 (S1) derived SAR imagery along with their combinations to assess their capability for generating accurate flood inundation maps. The robustness in performance of S-1 and S-2 band combinations was evaluated using 446 hand labeled flood inundation images spanning across 11 flood events from Sen1Floods11 dataset which are highly diverse in terms of land cover as well as location. A modified K-fold cross validation approach is used to evaluate the performance of 32 combinations of S1 and S2 bands using a fully connected deep convolutional neural network known as U-Net. Our results indicated that usage of elevation information has improved the capability of S1 imagery to produce more accurate flood inundation maps. Compared to a median F1 score of 0.62 when using only S1 bands, the combined use of S1 and elevation information led to an improved median F1 score of 0.73. Water extraction indices based on S2 bands have a statistically significant superior performance in comparison to S1. Among all the band combinations, HSV (Hue, Saturation, Value) transformation of S2 bands provides a median F1 score of 0.9, outperforming the commonly used water spectral indices owing to HSV’s transformation’s superior contrast distinguishing abilities. Additionally, U-Net algorithm was able to learn the relationship between raw S2 based water extraction indices and their corresponding raw S2 bands, but not of HSV owing to relatively complex computation involved in the latter. Results of the paper establishes important benchmarks for the extension of S1 and S2 data-based flood inundation mapping efforts over large spatial extents.

Goutam Konapala↗
NASA NTRS2024

Vegetation Greening Mitigates the Impacts of Increasing Extreme Rainfall on Runoff Events

Future flood risk assessment has primarily focused on heavy rainfall as the main driver, with the assumption that projected increases in extreme rain events will lead to subsequent flooding. However, the presence of and changes in vegetation have long been known to influence the relationship between rainfall and runoff. Here, we extract historical (1850–1880) and projected (2070–2100) daily extreme rainfall events, the corresponding runoff, and antecedent conditions simulated in a prominent large Earth system model ensemble to examine the shifting extreme rainfall and runoff relationship. Even with widespread projected increases in the magnitude (78% of the land surface) and number (72%) of extreme rainfall events, we find projected declines in event-based runoff ratio (runoff/rainfall) for a majority (57%) of the Earth surface. Runoff ratio declines are linked with decreases in antecedent soil water driven by greater transpiration and canopy evaporation (both linked to vegetation greening) compared to areas with runoff ratio increases. Using a machine learning regression tree approach, we find that changes in canopy evaporation is the most important variable related to changes in antecedent soil water content in areas of decreased runoff ratios (with minimal changes in antecedent rainfall) while antecedent ground evaporation is the most important variable in areas of increased runoff ratios. Our results suggest that simulated interactions between vegetation greening, increasing evaporative demand, and antecedent soil drying are projected to diminish runoff associated with extreme rainfall events, with important implications for society.

soil moisture↗
NASA NTRS1980

Limit on rotational energy available to excite Jovian aurora

There is a fundamental relationship between the power that is extracted from Jupiter's rotation to drive magnetospheric processes and the rate at which mass is injected into the Io plasma torus. Half of this power is consumed by bulk motion of the plasma and the other half represents an upper limit on the energy from rotation available for dissipation and in particular to excite the Jovian aurora. Since the rotation of the planet is the only plausible source of energy, the power inferred from the observed auroral intensities requires a plasma injection rate of 2.6 x 10 to the 29th AMU/sec or greater. This in turn leads to a residence time of a torus particle of 48 days or less. These results raise doubts about the applicability of equilibrium thermodynamics to the determination of plasma parameters in the Io torus.

Eviatar, A.↗
NASA NTRS1988

Using AGNESS (A Generalized Network-based Expert System Shell) for matching images

The image correspondence problem is considered the most difficult step in both stereo and motion analysis. Stereo vision is useful in determining the 3-D positions of points on visible surface in a scene. Motion analysis is useful in determining the spatial and temporal relationships of objects in an environment. Besides stereo and motion analysis, there is the image correspondence problem. Most of this work is based on point or local area properties of the observed gray level values in 2-D images. A global and general approach to this problem is described by using a knowledge-based system. The knowledge it uses consists of both physical properties and spatial relationships of the edges and regions extracted from the given images. The physical component depends on features of the edge or region) in isolation. The spatial component involves the set of edges and regions adjacent to a given edge (or region) of the first image and the set of edges and regions adjacent to each potentially matching edge (or region) of the second image; thus the spatial context of each edge or region is considered. A computational network is used to represent this knowledge, it allows the computation of the likelihood of matching two edges or regions with logical and heuristic operators. An expert system shell called AGNESS (A Generalized Network-based Expert System Shell) is used to build a prototype system.

Pong, Ting-Chuen↗
NASA NTRS2016

Wavenumber-frequency deconvolution of aeroacoustic microphone phased array data of arbitrary coherence

Deconvolution of aeroacoustic data acquired with microphone phased arrays is a computationally-challenging task for distributed sources with arbitrary coherence. A new technique for performing such deconvolution is proposed. This technique relies on analysis of the array data in the wavenumber-frequency domain, allowing for fast convolution and reduced storage requirements when compared to traditional coherent deconvolution. A positive semidefinite constraint for the iterative deconvolution procedure is implemented and shows improved behavior in terms of quantifiable convergence metrics when compared to a standalone covariance inequality constraint. A series of simulations validates the method's ability to resolve coherence and phase angle relationships between partially-coherent sources, as well as determines convergence criteria for deconvolution analysis. Simulations for point sources near the microphone phased array show potential for handling such data in the wavenumber-frequency domain. In particular, a physics-based integration boundary calculation is described, and can successfully isolate sources and track the appropriate integration bounds with and without the presence of flow. Magnitude and phase relationships between multiple sources are successfully extracted. Limitations of the deconvolution technique are determined from the simulations, particularly in the context of a simulated acoustic field in a closed test section wind tunnel with strong boundary layer contamination. A final application to a trailing edge noise experiment conducted in an open-jet wind tunnel matches best estimates of acoustic levels from traditional calculation methods and qualitatively assesses the coherence characteristics of the trailing edge noise source.

phased array↗
NASA NTRS2011

Superpixel-Augmented Endmember Detection for Hyperspectral Images

Superpixels are homogeneous image regions comprised of several contiguous pixels. They are produced by shattering the image into contiguous, homogeneous regions that each cover between 20 and 100 image pixels. The segmentation aims for a many-to-one mapping from superpixels to image features; each image feature could contain several superpixels, but each superpixel occupies no more than one image feature. This conservative segmentation is relatively easy to automate in a robust fashion. Superpixel processing is related to the more general idea of improving hyperspectral analysis through spatial constraints, which can recognize subtle features at or below the level of noise by exploiting the fact that their spectral signatures are found in neighboring pixels. Recent work has explored spatial constraints for endmember extraction, showing significant advantages over techniques that ignore pixels relative positions. Methods such as AMEE (automated morphological endmember extraction) express spatial influence using fixed isometric relationships a local square window or Euclidean distance in pixel coordinates. In other words, two pixels covariances are based on their spatial proximity, but are independent of their absolute location in the scene. These isometric spatial constraints are most appropriate when spectral variation is smooth and constant over the image. Superpixels are simple to implement, efficient to compute, and are empirically effective. They can be used as a preprocessing step with any desired endmember extraction technique. Superpixels also have a solid theoretical basis in the hyperspectral linear mixing model, making them a principled approach for improving endmember extraction. Unlike existing approaches, superpixels can accommodate non-isometric covariance between image pixels (characteristic of discrete image features separated by step discontinuities). These kinds of image features are common in natural scenes. Analysts can substitute superpixels for image pixels during endmember analysis that leverages the spatial contiguity of scene features to enhance subtle spectral features. Superpixels define populations of image pixels that are independent samples from each image feature, permitting robust estimation of spectral properties, and reducing measurement noise in proportion to the area of the superpixel. This permits improved endmember extraction, and enables automated search for novel and constituent minerals in very noisy, hyperspatial images. This innovation begins with a graph-based segmentation based on the work of Felzenszwalb et al., but then expands their approach to the hyperspectral image domain with a Euclidean distance metric. Then, the mean spectrum of each segment is computed, and the resulting data cloud is used as input into sequential maximum angle convex cone (SMACC) endmember extraction.

Thompson, David R.↗
NASA NTRS1995

Penetration experiments in aluminum 1100 targets using soda-lime glass projectiles

The cratering and penetration behavior of annealed aluminum 1100 targets, with thickness varied from several centimeters to ultra-thin foils less than 1 micrometer thick, were experimentally investigated using 3.2 mm diameter spherical soda-lime glass projectiles at velocities from 1 to 7 km/s. The objective was to establish quantitative, dimensional relationships between initial impact conditions (impact velocity, projectile diameter, and target thickness) and the diameter of the resulting crater or penetration hole. Such dimensional relationships and calibration experiments are needed to extract the diameters and fluxes of hypervelocity particles from space-exposed surfaces and to predict the performance of certain collisional shields. The cratering behavior of aluminum 1100 is fairly well predicted. However, crater depth is modestly deeper for our silicate impactors than the canonical value based on aluminum projectiles and aluminum 6061-T6 targets. The ballistic-limit thickness was also different. These differences attest to the great sensitivity of detailed crater geometry and penetration behavior on the physical properties of both the target and impactor. Each penetration experiment was equipped with a witness plate to monitor the nature of the debris plume emanating from the rear of the target. This plume consists of both projectile fragments and target debris. Both penetration hole and witness-plate spray patterns systematically evolve in response to projectile diameter/target thickness. The relative dimensions of the projectile and target totally dominate the experimental products documented in this report; impact velocity is an important contributor as well to the evolution of penetration holes, but is of subordinate significance for the witness-plate spray patterns.

Horz, Friedrich↗
NASA NTRS2010

A Tool for Empirical Forecasting of Major Flares, Coronal Mass Ejections, and Solar Particle Events from a Proxy of Active-Region Free Magnetic Energy

This presentation describes a new forecasting tool developed for and is currently being tested by NASA s Space Radiation Analysis Group (SRAG) at JSC, which is responsible for the monitoring and forecasting of radiation exposure levels of astronauts. The new software tool is designed for the empirical forecasting of M and X-class flares, coronal mass ejections, as well as solar energetic particle events. Its algorithm is based on an empirical relationship between the various types of events rates and a proxy of the active region s free magnetic energy, determined from a data set of approx.40,000 active-region magnetograms from approx.1,300 active regions observed by SOHO/MDI that have known histories of flare, coronal mass ejection, and solar energetic particle event production. The new tool automatically extracts each strong-field magnetic areas from an MDI full-disk magnetogram, identifies each as an NOAA active region, and measures a proxy of the active region s free magnetic energy from the extracted magnetogram. For each active region, the empirical relationship is then used to convert the free magnetic energy proxy into an expected event rate. The expected event rate in turn can be readily converted into the probability that the active region will produce such an event in a given forward time window. Descriptions of the datasets, algorithm, and software in addition to sample applications and a validation test are presented. Further development and transition of the new tool in anticipation of SDO/HMI is briefly discussed.

Barghouty, A. F.↗
NASA NTRS1991

Software Engineering Laboratory (SEL) relationships, models, and management rules

Over 50 individual Software Engineering Laboratory (SEL) research results, extracted from a review of published SEL documentation, that can be applied directly to managing software development projects are captured. Four basic categories of results are defined and discussed - environment profiles, relationships, models, and management rules. In each category, research results are presented as a single page that summarizes the individual result, lists potential uses of the result by managers, and references the original SEL documentation where the result was found. The document serves as a concise reference summary of applicable research for SEL managers.

Decker, William↗
NASA NTRS1991

Quantitative knowledge acquisition for expert systems

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. While it is relatively easy to collect data and to log the comments of human operators engaged in experiments, generalizing such information to a set of rules has not previously been a direct task. A statistical method is presented for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development is described of a Navigation Sensor Management (NSM) Expert System from Kalman Filter convariance data. The method invokes two statistical techniques: Analysis of Variance (ANOVA) and the ID3 Algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithms identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set. Both are detailed.

Belkin, Brenda L.↗
NASA NTRS1991

Knowledge acquisition for expert systems using statistical methods

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. A statistical method for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors is presented. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development of a Navigation Sensor Management (NSM) Expert System from Kalman Filter covariance data is described. The development method invokes two statistical techniques: Analysis-of-Variance (ANOVA) and the ID3 algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithm identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set.

Belkin, Brenda L.↗
NASA NTRS2020

Application of Sparse Identification of Nonlinear Dynamics for Physics-Informed Learning

Advances in machine learning and deep neural networks has enabled complex engineering tasks like image recognition, anomaly detection, regression, and multi-objective optimization, to name but a few. The complexity of the algorithm architecture, e.g., the number of hidden layers in a deep neural network, typically grows with the complexity of the problems they are required to solve, leaving little room for interpreting (or explaining) the path that results in a specific solution. This drawback is particularly relevant for autonomous aerospace and aviation systems, where certifications require a complete understanding of the algorithm behavior in all possible scenarios. Including physics knowledge in such data-driven tools may improve the interpretability of the algorithms, thus enhancing model validation against events with low probability but relevant for system certification. Such events include, for example, spacecraft or aircraft sub-system failures, for which data may not be available in the training phase. This paper investigates a recent physics-informed learning algorithm for identification of system dynamics, and shows how the governing equations of a system can be extracted from data using sparse regression. The learned relationships can be utilized as a surrogate model which, unlike typical data-driven surrogate models, relies on the learned underlying dynamics of the system rather than large number of fitting parameters. The work shows that the algorithm can reconstruct the differential equations underlying the observed dynamics using a single trajectory when no uncertainty is involved. However, the training set size must increase when dealing with stochastic systems, e.g., nonlinear dynamics with random initial conditions.

Corbetta, Matteo↗
NASA NTRS2018

Using a Knowledge Graph to Discover Earth Science Information

Knowledge graphs link key entities within a specific domain to other entities via relationships. Researchers are able to mine these relationships from numerous sources to infer new knowledge. Text extraction from peer-reviewed papers and scientific reports are untapped resources that can be leveraged by knowledge graphs to accelerate scientific discovery.

Freitag, Brian↗
NASA NTRS1990

Relationship between the longwave cloud radiative forcing at the surface and the top of the atmosphere

In order to achieve global coverage, any surface radiation climatology has to be based on satellite observations. In the last decade several schemes have been devised to obtain the surface solar insolation from top of the atmosphere reflected solar radiation. More recently, attempts have been made to infer the components of longwave radiation at the surface from satellite sounder data using a radiative transfer model. In addition to the radiative transfer scheme, these methods require assumptions about the effective emitting temperature of cloud tops and bases. Modeling studies have shown that although there are strong correlations between the solar upwelling radiative flux and surface flux, this is not true of the longwave. However, if the clear sky component is considered separately such that the cloud longwave forcing at the top and at the surface are compared, a slightly different picture emerges. During the FIRE Cirrus IFO, surface radiation measurements were made at several sites and coincident satellite overpass data was also collected. It may be possible to extract the longwave cloud radiative forcing at the top and surface from these data. If relationships are verifiable by observations, this information can be useful for the extraction of the surface longwave radiation from satellite data. The radiative transfer schemes used to convert upwelling spectral radiances into a downwelling longwave radiation can provide the clear sky component. The cloud radiative forcing at the top of the atmosphere can then modify the surface fluxes according to relationships shown. It should be noted that this procedure may be considered only for temporal averages and not for instantaneous deductions of surface fluxes. This would be most useful in compiling monthly mean regional climatologies of the surface longwave fluxes.

HARSHVARDHAN↗
NASA NTRS1982

The lunar regolith - Chemistry, mineralogy, and petrology

The data base on the lunar regolith is surveyed to form a synthesis of the lunar regolith chemistry, mineralogy, and petrology. The data were derived from samples collected by the Apollo missions 11-17 and the Luna 16, 20, and 24 probes. The missions were sent to sample formations and areas which typified the common observed features of the lunar surface. Drive tubes were used to extract samples from beneath the surface in order to study the relationship between the regolith and the bedrock, as well as to identify the processes that formed the regolith, which is regarded as the prime source of raw materials for early lunar industrial activities. Regolith origins are now understood to be destructive processes of comminution and constructional processes of agglutinate formation. Mixing occurs on the local scale, although lateral transport is inefficient on the moon. The usual contents of the fraction of regolith less than 10 microns in diameter are Al2O3, CaO, Na2O, K2O, light REE, and Th.

Papike, J. J.↗
NASA NTRS2005

Multiscale Modeling for the Analysis for Grain-Scale Fracture Within Aluminum Microstructures

Multiscale modeling methods for the analysis of metallic microstructures are discussed. Both molecular dynamics and the finite element method are used to analyze crack propagation and stress distribution in a nanoscale aluminum bicrystal model subjected to hydrostatic loading. Quantitative similarity is observed between the results from the two very different analysis methods. A bilinear traction-displacement relationship that may be embedded into cohesive zone finite elements is extracted from the nanoscale molecular dynamics results.

Glaessgen, Edward H.↗
NASA NTRS1973

A study of morphology, provenance, and movement of desert sand seas in Africa, Asia, and Australia

The author has identified the following significant results. The most significant result to date is recongition that complexes are indeed visible on ERTS-1 images, and that the extent and nature of dune fields in many remote areas of the world can, for the first time, be observed almost simultaneously and directly compared. The primary scientific problem is to determine accurately the relationships among certain patterns, trends, and boundaries clearly revealed on ERTS-1 imagery to true surface configurations of desert landforms, and further, to relate the defined features to controlling factors such as wind direction and intensity, moisture in the air and on the ground and barriers to sand movement. It is hoped to produce, by photographic and cartographic extraction from ERTS-1 images, a set of thematic maps that will illustrate the relationships of optical appearance of various materials and effects of the color of various sand bodies upon ERTS-1 images.

Mckee, E. D.↗
NASA NTRS1982

A method for the extraction and quantitation of phycoerythrin from algae

A summary of a new technique for the extraction and quantitation of phycoerythrin (PHE) from algal samples is described. Results of analysis of four extracts representing three PHE types from algae including cryptomonad and cyanophyte types are presented. The method of extraction and an equation for quantitation are given. A graph showing the relationship of concentration and fluorescence units that may be used with samples fluorescing around 575-580 nm (probably dominated by cryptophytes in estuarine waters) and 560 nm (dominated by cyanophytes characteristics of the open ocean) is provided.

Stewart, D. E.↗