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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 145 records · Page 8
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NASA NTRS2017

United Kingdom Infrared Telescope's Spectrograph Observations of Human-Made Space Objects

Presented here are the results of the United Kingdom Infrared Telescope (UKIRT) spectral observations of human-made space objects taken from 2014 to 2015. The data collected using the UIST infrared spectrograph cover the wavelength range 0.7-2.5 micrometers. Overall, data were collected on 18 different orbiting objects at or near the geosynchronous (GEO) regime. Thirteen of the objects are spacecraft, one is a rocket body, and four are cataloged as debris pieces. The remotely collected data are compared to the laboratory-collected reflectance data on typical spacecraft materials; thereby general materials are identified but not specific types. These results highlight the usefulness of observations in the infrared by focusing on features from hydrocarbons and silicon. The spacecraft show distinct features due to the presence of solar panels. Signature variations between rocket bodies, due to the presence of various metals and paints on their surfaces, show a clear distinction from those objects with solar panels, demonstrating that one can distinguish most spacecraft from rocket bodies through infrared spectrum analysis. Finally, the debris pieces tend to show featureless, dark spectra. These results show that the laboratory data in its current state give excellent indications as to the nature of the surface materials on the objects. Further telescopic data collection and model updates to include more materials, noise, surface roughness, and material degradation are necessary to make better assessments of orbital object material types. A comparison conducted between objects observed previously with the NASA Infrared Telescope Facility (IRTF) shows similar materials and trends from the two telescopes and from the two distinct data sets. However, based on the current state of the model, infrared spectroscopic data are adequate to classify objects in GEO as spacecraft, rocket bodies, or debris.

Buckalew, Brent↗
NASA NTRS2024

Abort Trajectory Design Strategies for the Artemis Missions

NASA's Artemis campaign plans to send astronauts to the lunar surface for the first time since 1972. The campaign relies on the Orion crew capsule to ferry the crew from Earth to an L2 9:2 lunar synodic resonant Near-Rectlinear Halo Orbit (NRHO) before descent to the lunar surface. This investigation examines a process to construct various abort families during transit from Earth to the NRHO using the Earth-Moon Circular Restricted Three-Body Problem (CR3BP). The initial trajectories are constructed using the CR3BP and categorized in families. A process is then summarized to transcribe and converge trajectories from the CR3BP into a higher-fidelity model. Ultimately, an effective methodology to develop, classify and converge these aborts in higher-fidelity is critical to the Artemis program in the event of an anomaly during the crew transit.

Trajectory Design↗
NASA NTRS2024

Automatic Detection and Classification of Aurora in THEMIS All‐Sky Images

We report a novel machine-learning algorithm for automatically detecting and classifying aurora in all–sky images (ASI) that is largely trained without requiring ground–truth labels. By including a small number of labeled images, we are able to automatically label all of the approximately 700 million images in the Time History of Events and Macroscale Interactions during Substorms (THEMIS) ASI data set from 2008 to 2022. We use a two–stage approach. In the first stage, we adapt the Simple framework for Contrastive Learning of Representations (SimCLR) algorithm to learn latent representations of THEMIS all–sky images. We then finetune a classifier network on the latent representations our model learns of the manually labeled Oslo aurora THEMIS (OATH) data set. We demonstrate that this two–stage approach achieves excellent classification results on data for which there is no current ML classification benchmark. The outcome of this work will facilitate efficient information retrieval for researchers interested in specific categories of aurora and will enable large scale statistical studies and machine learning analyses of THEMIS all–sky images that have not previously been possible. To demonstrate possible ways to utilize this database, we performed a statistical analysis of the occurrence rates of auroral labels with respect to solar wind parameters, interplanetary magnetic field vector, and geomagnetic indices. We further investigate the occurrence rates of auroral phenomena in the annotated data set and their geoeffectiveness by utilizing the co–located THEMIS ground magnetometer data set.

Jeremiah W Johnson↗
NASA NTRS1983

Detection and recognition of simple spatial forms

A model of human visual sensitivity to spatial patterns is constructed. The model predicts the visibility and discriminability of arbitrary two-dimensional monochrome images. The image is analyzed by a large array of linear feature sensors, which differ in spatial frequency, phase, orientation, and position in the visual field. All sensors have one octave frequency bandwidths, and increase in size linearly with eccentricity. Sensor responses are processed by an ideal Bayesian classifier, subject to uncertainty. The performance of the model is compared to that of the human observer in detecting and discriminating some simple images.

Watson, A. B.↗
NASA NTRS1992

Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice

An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.

Maslanik, J. A.↗
NASA NTRSDate not supplied

Creating Regional and Seasonal Climatologies of Marine and Dusty Marine Aerosol Lidar Ratios using MODIS AOD Constrained Retrievals and GOCART Model Simulations

The CALIPSO aerosol algorithms currently assign one lidar ratio (LR) value globally for each of the seven tropospheric aerosol types. In this study, MODIS total column aerosol optical depths (AODs) are used to constrain collocated CALIOP backscatter profiles in a Fernald inversion that infers aerosol LRs for CALIOP-classified marine and dusty marine aerosols. The GOCART aerosol model is leveraged to estimate the sea salt volume fractions (SSVFs) that are collocated with the CALIOP+MODIS LR retrievals. An inverse empirical relationship is found between the SSVFs and LRs (i.e., smaller SSVFs and larger LRs near coastlines, but the opposite in the remote oceans). This SSVF/LR relationship is applied to create regional and seasonal hybrid (i.e., retrieval & model-assisted) climatological LR maps so as to develop more robust LR selections for marine and dusty marine aerosols in the CALIPSO algorithms. These analyses also provide critical LR information for the next generation of spaceborne elastic backscatter lidars.

Travis D. Toth↗
NASA NTRSDate not supplied

Creating Regional and Seasonal Climatologies of Marine and Dusty Marine Aerosol Lidar Ratios using MODIS AOD Constrained Retrievals and GOCART Model Simulations

The CALIPSO aerosol algorithms currently assign one lidar ratio (LR) value globally for each of the seven tropospheric aerosol types. In this study, MODIS total column aerosol optical depths (AODs) are used to constrain collocated CALIOP backscatter profiles in a Fernald inversion that infers aerosol LRs for CALIOP-classified marine and dusty marine aerosols. The GOCART aerosol model is leveraged to estimate the sea salt volume fractions (SSVFs) that are collocated with the CALIOP+MODIS LR retrievals. An inverse empirical relationship is found between the SSVFs and LRs (i.e., smaller SSVFs and larger LRs near coastlines, but the opposite in the remote oceans). This SSVF/LR relationship is applied to create regional and seasonal hybrid (i.e., retrieval & model-assisted) climatological LR maps so as to develop more robust LR selections for marine and dusty marine aerosols in the CALIPSO algorithms. These analyses also provide critical LR information for the next generation of spaceborne elastic backscatter lidars.

Travis D. Toth↗
NASA NTRS1997

Statistical Modeling of Landscape Pattern and the Effects of Coarse Spatial Resolution

Analysis of classified satellite imagery was conducted to characterize errors in estimates of area based on coarse resolution satellite imagery which are due to distortions in sizes of small fragments, and to explore the feasibility of correcting for these errors using a statistical modeling approach. Sizes of bodies of open water on European Remote-Sensing (ERS-1) synthetic aperture radar (SAR) and fire scars on Landsat Multispectral Scanner (MSS) imagery were measured using geographic information system (GIS) software. Statistical analysis of the smaller scars and ponds as observed with this imagery of relatively fine resolution demonstrated that the distribution of the sizes could be modeled by either of two types of statistical distributions-a power distribution related to fractal processes or a simple exponential distribution. A comparison of the size distribution of small burn scars as observed with Landsat with the distribution observed with the much coarser Advanced Very High Resolution Radiometer (AVHRR) imagery revealed effects of coarse resolution, each of which were associated with a particular size range, and whose net effect accounted for the bias in total burn area due to coarse spatial resolution. Size dependent area correction procedures are therefore feasible. A statistical modeling approach to area estimation, based models of the underlying and observed size distributions of fragments in the scene, may lead to a procedure which requires little or no ancillary data.

Hlavka, C. A.↗
NASA NTRS1990

A failure diagnosis system based on a neural network classifier for the space shuttle main engine

A conceptual design of a model based failure detection and diagnosis system is developed for the space shuttle main engine. This design relies on the accurate and reliable identification of the parameters of the highly nonlinear and very complex engine. The design approach is presented in some detail and results for a failed valve are presented. These preliminary results verify that the developed parameter identification technique together with a neural network classifier can be used for this purpose.

Duyar, Ahmet↗
NASA NTRS1990

A failure diagnosis system based on a neural network classifier for the Space Shuttle Main Engine

A conceptual design of a model based failure deeteection and diagnosis system is deeveloped for the Space Shuttle Main Engine. This design relies on the accurate and reliable identification of the parameters of the highly nonlinear and very complex engine. The design approach is presented in some detail and results for a failed valve are presented. These preliminary results verify that the developed parameter identification technique, together with a neural network classifier, can be used for this purpose.

Duyar, Ahmet↗
NASA NTRS1985

Research on the effect of noise at different times of day: Models, methods and findings

Social surveys of residents' responses to noise at different times of day are reviewed. Some of the discrepancies in published reports about the importance of noise at different times of day are reduced when the research findings are classified according to the type of time of day reaction model, the type of time of day weight calculated and the method which is used to estimate the weight. When the estimates of nighttime weights from 12 studies are normalized, it is found that they still disagree, but do not support stronger nighttime weights than those used in existing noise indices. Challenges to common assumptions in nighttime response models are evaluated. Two of these challenges receive enough support to warrant further investigation: the impact of changes in numbers of noise events may be less at night than in the day and nighttime annoyance may be affected by noise levels in other periods. All existing social survey results in which averages of nighttime responses were plotted by nighttime noise levels are reproduced.

Fields, J. M.↗
NASA NTRS1986

Geochemistry of granitoid rocks from the western Superior Province: Evidence for 2- and 3-stage crustal evolution models

The Superior Province is divisible into subprovinces that can be classified as greenstone-tonalite, paragneiss, or batholitic terranes and are distinguished by differences in lithologic proportions, metamorphic grade, and structural style. The origin and significance of contrasting geochemical characteristics of plutonic rocks from the Winnipeg River subprovince (a batholithic terrane) and the Wabigoon subprovince (a greenstone-tonalite terrane) are discussed.

Beakhouse, G. P.↗
NASA NTRS1995

Bayes classification of interferometric TOPSAR data

We report the Bayes classification of terrain types at different sites using airborne interferometric synthetic aperture radar (INSAR) data. A Gaussian maximum likelihood classifier was applied on multidimensional observations derived from the SAR intensity, the terrain elevation model, and the magnitude of the interferometric correlation. Training sets for forested, urban, agricultural, or bare areas were obtained either by selecting samples with known ground truth, or by k-means clustering of random sets of samples uniformly distributed across all sites, and subsequent assignments of these clusters using ground truth. The accuracy of the classifier was used to optimize the discriminating efficiency of the set of features that was chosen. The most important features include the SAR intensity, a canopy penetration depth model, and the terrain slope. We demonstrate the classifier's performance across sites using a unique set of training classes for the four main terrain categories. The scenes examined include San Francisco (CA) (predominantly urban and water), Mount Adams (WA) (forested with clear cuts), Pasadena (CA) (urban with mountains), and Antioch Hills (CA) (water, swamps, fields). Issues related to the effects of image calibration and the robustness of the classification to calibration errors are explored. The relative performance of single polarization Interferometric data classification is contrasted against classification schemes based on polarimetric SAR data.

Michel, T. R.↗
NASA NTRS1982

Raindrop oscillations

A model of the change in shape of a raindrop is presented. Raindrops measured by two orthogonal cameras were classified by shape and orientation to determine the nature of the oscillation. A physical model based on potential energy was then developed to study the amplitude variation of oscillating drops. The model results show that oscillations occur about the equilibrium axis ratio, but the time average axis ratio if significantly more spherical for large amplitudes because of asymmetry in the surface potential energy. A generalization of the model to oscillations produced by turbulence yields average axis ratios that are consistent with the camera measurements. The model results for average axis ratios were applied to rainfall studies with a dual polarized radar.

Beard, K. V.↗
NASA NTRS1973

Phase 1 of the earth resources data analysis program

Research completed in the Earth Resources Data Analysis Program is discussed along with recommendations for future study. Projects discussed include use of the Cholesky decomposition in feature selection and classification algorithms; optimal feature selection and extraction, probability density estimation and nonparametric classifiers; use of spatial information in classification; and model for crop row reflectance. The installation of LARSYS on the ICSA's IBM 370/155 is discussed, and a list of technical reports is included.

Source record↗
NASA NTRS1990

Gamma-Ray Observatory - The next great observatory in space

The Gamma-Ray Observatory (GRO) which is part of NASA's Great Observatories space program is presented. The GRO is equipped with the Burst and Transient Source Experiment (which detects low-energy gamma-ray photons from 20 keV to 600 keV and locates sources of gamma-ray bursts), the Oriented Scintillation Spectrometer Experiment (which detects celestial gamma rays from 100 keV to 10 MeV and identifies the elements producing these rays by measuring the ray's spectra and time variability), the Imaging Compton Telescope (which images gamma rays with energies from 1 to 30 MeV created when cosmic rays interact with interstellar matter), and the Energetic Gamma-Ray Experiment Telescope (which detects high-energy photons associated with the most energetic processes occurring in nature). After the energies of photons from each source are classified, the gamma-ray mechanisms can be modelled. Nuclei, radioactive isotopes, and nuclear reactions can be identified, and the physical conditions at the radiation's source can also be modelled. From these models, theories can be developed about the creation of elements in the explosion and collapse of giant stars, the acceleration of charged particles to velocities approaching the speed of light, and the destruction of matter and antimatter.

Neal, Valerie↗
NASA NTRS2003

Magnetogasdynamic Power Extraction and Flow Conditioning for a Gas Turbine

An extension of the Russian AJAX concept to a turbojet is being explored. This magnetohydrodynamic (MHD) energy bypass engine cycle incorporating conventional gas turbine technology has MHD flow conditioning at the inlet to electromagnetically extract part of the inlet air kinetic energy. The electrical power generated can be used for various on-board vehicle requirements including plasma flow control around the vehicle or it may be used for augmenting the expanding flow in the high speed nozzle by MHD forces to generate more thrust. In order to achieve this interaction, the air needs to be ionized by an external means even up to fairly high flight speeds, and the leading candidates may be classified as electrical discharge devices. The present kinetic modeling calculations suggest that the use of electron beams with characteristics close to the commercially available e-beam systems (electron energy approx. 60 keV, beam current approx. 0.2 mA/sq cm) to sustain ionization in intermediate pressure, low-temperature (P = 0.1 atm, T = 300 K) supersonic air flows allows considerable reduction of the flow kinetic energy (up to 10 to 20 percent in M = 3 flows). The calculations also suggest that this can be achieved at a reasonable electron beam efficiency (eta approx. 5), even if the e-beam window losses are taken into account. At these conditions, the exit NO and O atom concentrations due to e-beam initiated chemical reactions do not exceed 30 ppm. Increasing the beam current up to approx. 2 mA/sq cm, which corresponds to a maximum electrical conductivity of sigma(sub max) approx. 0.8 mho/m at the loading parameter of K = 0.5, would result in a much greater reduction of the flow kinetic energy (up to 30 to 40 percent). The MHD channel efficiency at these conditions would be greatly reduced (to eta approx. 1) due to increased electron recombination losses in the channel. At these conditions, partial energy conversion from kinetic energy to heat would result in a significant total pressure loss (P(sub 0)/P(sub 0i) approx. 0.3). The total pressure loss can be reduced operating at the loading parameter closer to unity, at the expense of the reduced electrical power output. Raising the beam current would also result in the increase of the exit O atom concentrations (up to 600 ppm) and NO (up to 150 ppm).

Adamovich, Igor V.↗
NASA NTRSDate not supplied

Investigating the Impacts of Land Use Change on Urban Heat and Vulnerability in Cali, Columbia

The urban heat island effect (UHI) is an environmental phenomenon where cities experience higher temperatures than rural areas due to increased pavement and decreased cooling from vegetation. Approximately 76% of people in Colombia live in urban areas, and the city of Santiago de Cali is facing UHI challenges exacerbated by land use change. Wetlands and forests formerly surrounded the city but were replaced by development and agriculture. The Colombian municipal government agency Departamento Administrativo de Gestión del Medio Ambiente and the community organization Fundacion Dinamizadores Ambientales partnered with NASA DEVELOP to evaluate communities in Cali most vulnerable to urban heat. This project illustrated the utility of using NASA Earth observations to evaluate the relationship between land use, temperature, and social factors in Cali, Colombia between 2013 and 2023. The team used Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), and Landsat 9 OLI-2/TIRS-2 to generate land surface temperature (LST), normalized difference vegetation index (NDVI), and albedo maps in Google Earth Engine. Heavy cloud cover limited the accuracy of the LST but incorporating up to three satellites for a median image reduced potential errors. Through further analysis in ArcGIS Pro, the team classified land use change using a deep learning model and found that LST was significantly higher in urban areas than in wetlands or forests. Using R studio, the team ran a principal component analysis to determine which social factors had the strongest correlation with LST. The team found that health care and green space access were negatively correlated, and Afro-Colombian ethnicity was positively correlated with LST. With awareness of the most impacted and vulnerable regions, the partner organizations can work to prioritize green space establishment in those areas to reduce the impacts of urban heat. Addressing the urban heat island effect will reduce environmental justice concerns within the city and improve overall health, air, and water quality for those who live there.

Brenna Bruffey↗