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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Astrometric Reduction of Phoebe Using a Digital Shape Model

The Cassini Imaging Science Subsystem (ISS) has provided the most spectacular images of the Saturnian system [1] and these observations constitute a fundamental dataset of high accuracy and exceptionally long-time span for the purpose of astrometry [2]. Several elaborate astrometric efforts using Cassini ISS data have demonstrated their use for the development and maintenance of the Saturnian satellite ephemerides and have been critical in improving our understanding of their secular orbital evolution and interior properties[3].Astrometric efforts using images with well-resolved bodies often employ limb-based methods for center finding; this is proven to be robust for satellites with a uniform ellipsoidal shape. However, systematic biases are of concern for bodies that deviate considerably from tri-axial ellipsoids(e.g., moons with irregular shapes and/or extensive features such as craters, ridges, slumps and grooves). To help understand such biases, we used the Goddard Image Analysis and Navigation Tool (GIANT) [4,5]to improve the astrometric reduction of these moons. Here we apply the method to Phoebe (Saturn IX).

V Viswanathan↗
NASA NTRS2021

High Energy Particle Excitations as a Measure of Electronic Crosstalk in MODIS and VIIRS VIS/NIR Bands

The MODIS instruments aboard the Terra and Aqua satellites and the VIIRS instruments aboard the SNPP and NOAA-20 satellites each contain several arrays of Si detectors that measure Earth-reflected radiance in the visible and near-infrared spectral range. Even in the absence of incident light, the Si detectors are occasionally excited by high energy charged particles that pass through the spacecraft. These particle radiation events are, fortunately, infrequent enough that they do not lead to significant degradation of the detectors and they do not have a significant impact on the Earth scene radiance images. On the other hand, they are frequent enough that the cumulative data from many years on orbit may provide valuable diagnostic information about the sensors. In this paper, we provide some basic statistics on the frequency and magnitude of the particle excitation events for MODIS and VIIRS and explore the usefulness of this data as a measure of electronic crosstalk. Large amounts of crosstalk can degrade the quality of the Earth images, so it is crucial to have methods to characterize and correct for it on-orbit, which has previously been done for MODIS using lunar image analysis. The particle excitations can manifest as single-pixel spikes in the otherwise dark space view background, which may be an ideal source for evaluating crosstalk. We derive crosstalk coefficients between the NIR band detectors of Terra MODIS, and compare them to coefficients previously derived from lunar observations. The same approach is applied to SNPP VIIRS, which does not show any significant electronic crosstalk. While the HgCdTe detectors used in the MODIS and VIIRS infrared bands can also be excited by particle radiation, the magnitudes of the excitations are much smaller compared to the Si detectors and in general are not large enough to be useful for examining crosstalk.

MODIS↗
NASA NTRSDate not supplied

A Comparison of Bearing Measurements to Surface Features Generated Using Stereophotoclinometry and Surface Feature Navigation Techniques

The Origins Spectral Interpretation Resource Identification Security Regolith Explorer (OSIRIS-REx) mission to the asteroid Bennu completed successful two-and-a-half year proximity operations in May 2021. The mission comprehensively mapped Bennu at unprecedented detail and collected a sample of Bennu’s surface to return to Earth. Throughout proximity operations, the OSIRIS-REx navigation team used the maps made of Bennu’s surface to navigate in the Bennu environment with high accuracy through the use of precise and accurate optical navigation data, radiometric data, and force modelling. The primary type of optical navigation measurements extracted from the images captured by OSIRIS-REx (particularly after first entering orbit around Bennu) were observations of known features on Bennu’s surface. Two related but different techniques/tools were used to extract these observations from the images: the Goddard Image Analysis and Navigation Tool Surface Feature Navigation (GIANT SFN) and Stereophotoclinometry (SPC) Autoregister. In this paper we compare the differences between the observables extracted using GIANT SFN and SPC Autoregister, explain the differences, and discuss where each technique is best suited.

Andrew Liounis↗
NASA NTRS2021

Search for Lensing Signatures in the Gravitational-Wave Observations from the First Half of LIGO–Virgo's Third Observing Run

We search for signatures of gravitational lensing in the gravitational-wave signals from compact binary coalescences detected by Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) and Advanced Virgo during O3a, the first half of their third observing run. We study: (1) the expected rate of lensing at current detector sensitivity and the implications of a non-observation of strong lensing or a stochastic gravitational-wave background on the merger-rate density at high redshift; (2) how the interpretation of individual high-mass events would change if they were found to be lensed; (3) the possibility of multiple images due to strong lensing by galaxies or galaxy clusters; and (4) possible wave-optics effects due to point-mass microlenses. Several pairs of signals in the multiple-image analysis show similar parameters and, in this sense, are nominally consistent with the strong lensing hypothesis. However, taking into account population priors, selection effects, and the prior odds against lensing, these events do not provide sufficient evidence for lensing. Overall, we find no compelling evidence for lensing in the observed gravitational-wave signals from any of these analyses.

R. Abbott↗
NASA NTRS2022

Radiation Tolerance and Mitigation for Neuromorphic Processors

Neuromorphic processors are designed to execute Deep Neural Networks (DNNs) at very high speed using only a fraction of the electrical power needed to run a DNN on a traditional CPU or GPU. This unique capability makes Neuromorphic processors a prime candidate for space systems, where advanced computational tasks like image analysis, depth map reconstruction, or rover control need to be executed in a power-starved environment. In contrast to the growing number of applications of Neuromorphic processors in smart phones, the automotive and robotics domain, the space environment is unforgiving because of extreme temperatures and high levels of radiation. Any space system, operating beyond LEO requires computing hardware that is resilient against radiation effects. However, Neuromorphic processors have not yet been designed or tested for their radiation tolerance. In this report, we consider traditional methods of detection of radiation events and mitigation via redundancy and gauge their effectiveness on DNNs. In contrast to traditional flight software, however, neural networks represent a statistical algorithm, which might affect its resilience against radiation events. We will focus on the analysis of the tolerance of DNNs with respect to radiation events and discuss techniques to detect radiation hits using on-chip triple modular redundancy (TMR) on an Intel Loihi neuromorphic processor and to mitigate radiation damage. We describe an architecture for on-chip TMR for the Intel Loihi and present results of initial experiments.

Neural Networks↗
NASA NTRSDate not supplied

New Optical Navigation Results Using Historical MESSENGER Data

This paper describes new optical navigation (OpNav) results obtained by processing previously collected measurements from the MESSENGER mission to Mercury. This project also serves to mature the tools and capabilities of NASA Goddard Space Flight Center (GSFC) in OpNav, using the open source Goddard Image Analysis and Navigation Tool (GIANT). New navigation measurements are obtained during the Mercury flyby and orbital phases, using OpNav measurements generated by GIANT, and these measurements are compared to predictions. The results obtained provide a set of improvements to be made in navigation tools and will pave the way for future missions to navigate near terrestrial bodies using optical measurements.

Optical Navigation↗
NASA NTRSDate not supplied

Restoring the Dunes: Using Satellite Imagery to Help Restore Turtle Nesting Grounds In Puerto Rico After Hurricane Maria

The North coast of Puerto Rico sustained heavy damage from Hurricane Maria and other subsequent tropical storms. This damage included erosion of beaches and foredunes. The foredunes are a delicate ecological environment, which provides important nesting grounds for endangered turtles. Local ecologists have been working to restore these dunes with mixed results. Presented here is an evaluation of dune restoration sites, and strategies to improve the success of subsequent restoration efforts. This involves both historical satellite image analysis and field work to evaluate sediment migration pathways. Local ecologists use a technique called Biomimicry to restore dunes. This involves inserting sticks or plants into the ground, simulating the effects of natural vegetation to slow wind speeds and deposit wind-blown sand. Manually planted vegetation can follow to stabilize the trapped sand. While often successful, this technique occasionally fails to accumulate significant amounts of sand. Satellite imagery shows that one of the controlling factors is the orientation of the dune and beach to the prevailing wind. Dunes that are oriented parallel to the prevailing wind are relatively slower-growing due to sediment bypass. Satellite imagery also indicates that the fastest growing dunes are in close proximity to major sediment sources. This is complicated by large dams, which limit the amount of sediment delivered to the coast. Field observation shows that biomimicry matrices are occasionally located too close to the swash zone, where storms over-top the dunes, poisoning stabilizing vegetation with salt water. Another common observation was that many dunes were starting to form behind fallen trees, suggesting that a different type of biomimicry might be successful. Satellite and field observation suggest that strategies to protect nearshore environments and improve dune restoration biomimicry efforts include: 1) orient biomimicry matrices at a higher angle to prevailing winds. 2) Prioritize sites near river mouths, particularly those without upstream dams. 3) Test other orientations of biomimicry, such as horizontal boards to mimic fallen trees. 4) Improve sediment supply by preventing further dam development, and releasing trapped sediment.

Paul Bremner↗
NASA NTRS2023

The Life and Death of A Subglacial Lake in West Antarctica

Over the past 50 years, the discovery and initial investigation of subglacial lakes in Antarctica have highlighted the paleoglaciological information that may be recorded in sediments at their beds. In December 2018, we accessed Mercer Subglacial Lake, West Antarctica, and recovered the first in situ subglacial lake-sediment record—120 mm of finely laminated mud. We combined geophysical observations, image analysis, and quantitative stratigraphy techniques to estimate long-term mean lake sedimentation rates (SRs) between 0.49 ± 0.12 mm a –1 and 2.3 ± 0.2 mm a –1 , with a most likely SR of 0.68 ± 0.08 mm a –1 . These estimates suggest that this lake formed between 53 and 260 a before core recovery (BCR), with a most likely age of 180 ± 20 a BCR—coincident with the stagnation of the nearby Kamb Ice Stream. Our work demonstrates that interconnected subglacial lake systems are fundamentally linked to larger-scale ice dynamics and highlights that subglacial sediment archives contain powerful, century-scale records of ice history and provide a modern process-based analogue for interpreting paleo–subglacial lake facies.

subglacial lakes↗
NASA NTRS2024

Soil Salinity Level Assessment and Prediction Integrating UAV-borne Hyperspectral Imaging and Machine Learning Algorithms to Combat Desertification

In response to the ongoing global food crisis, the United Nations has identified “Zero Hunger” as one of its Sustainable Development Goals. A central contributor to the crisis is the process in which agricultural lands go through desertification. Research has shown a direct correlation between soil salinity and desertification - increased salinity levels indicate a higher risk for desertification. Furthermore, researchers have explored various techniques to map soil salinity, but these methods are oftentimes inefficient and don’t address future salinity predictions. To improve desertification monitoring, soil salinity can be observed via hyperspectral imaging on unmanned aerial vehicles (UAVs) to predict the risk of agricultural desertification using artificial intelligence (AI) and machine learning (ML) techniques. A significant gap exists in past research that applies ML and imaging techniques to soil salinity: convolutional neural networks (CNNs) and regression models are rarely leveraged together, despite the efficiency and accuracy of these models. To compensate for this gap, the proposed system leverages the use of these AI and ML models to improve soil assessment and prediction techniques. This approach involves three steps - data collection, image analysis, and future prediction. Using hyperspectral cameras on UAVs to collect the data from the region, a trained CNN model will output estimated soil salinity levels at a specific time. The estimations will then be analyzed by a regression model to assess the accuracy of future soil salinity predictions. The proposed system will identify regions at risk of desertification to help farmers mitigate agricultural loss, in turn helping alleviate the food crisis.

UAV systems↗
DOE OSTI2021

AXEAP (ARGONNE X-RAY EMISSION PACKAGE)

Argonne X-ray Emission Package (AXEAP), a singular purpose software package for processing X-ray emission (XES) images collected with a 2-dimensional position sensitive pixel array detector, has been developed. AXEAP can rapidly convert XES image files into a spectral form by applying parallel computation and unsupervised machine learning to compute vast amount of image data. Special focus has been placed on designing user-friendly-interface for processing multiple edges, non-resonant and resonant x-ray emission image analysis, in order to make data processing quick and easy. AXEAP is free software and is written in MATLAB, armed with powerful libraries and toolboxes. The software runs on all common operating systems such as Linux, Window, and Mac.

SUN, CHENGJUN↗
DOE OSTI2022

Synthetic Data Generation Using Machine Learning

Robust machine learning techniques for image analysis require a substantial amount of data to yield confident results. In the nuclear domain, data scarcity is a substantial challenge because there are so few facilities worldwide. This research focuses on being able alleviate the data scarcity problem by generating synthetic data to bridge the gap between large and small datasets. This work achieves that goal using a Generative Adversarial Network (GAN) architectural approach, by training a model on real-world data and expands that small dataset through synthetic data amendments. Model performance is impacted by the size of the real-world dataset and the number of training epochs utilized. This means that 1) It is important to develop your GAN to be optimized with the specific data type, and 2) approaches taken when training the GAN should be specialized to encompass important aspects of the dataset that it is generating. By taking a step to improve dataset sizes in this way, the gap between models trained by parties with significant amount of data and those without access to large data, closes, allowing for robust analyses of satellite imagery for nuclear domain applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

n-Propylbenzene Droplet Combustion: Experiments and Numerical Modeling

n-Propylbenzene (PB, C9H12, 432K boiling point) is important as a constituent in surrogates for some transportation fuels but little is understood about its droplet burning characteristics. We present an experimental and numerical study of a fuel droplet burning under conditions where the sole means of gas transport is fuel evaporation at the droplet surface thereby creating a one-dimensional gas transport that is amenable to detailed numerical modeling. The one-dimensional gas transport that results is amenable to detailed numerical modeling. Initial droplet diameters (Do) ranged from 0.3 mm to about 5 mm to better understand the mechanisms that control burning over such a wide range of Do. For Do < 1 mm droplets were burned while anchored to 14 m SiC fibers within a sealed container in free-fall during which time the droplets were ignited by spark discharge and the burning process recorded by video cameras. Larger and free-floating droplets were studied in the spaced-based platform of the orbiting International Space Station for Do > 1.0 mm which provided unlimited times for experimental observation. Measurements of droplet, flame and soot shell diameters were made and are discussed in the presentation. The experimental results showed formation of optically thick soot clouds developing during burning that required a robust image analysis algorithm to enable measurement of droplet diameter. The measured droplet diameters were well predicted by a numerical model that included soot formation, a PB kinetic mechanism comprising 576 species and 27369 reactions, unsteady gas and liquid transport, variable properties and radiative transport. Flame diameters showed more variability compared to the simulations, depending on how the flame was defined (peak gas temperature and OH concentration). Droplets burned slower as Do was increased and the PB sooting propensity increased with Do. Flame extinction was observed for Do > 3.3 mm indicating a strong effect of radiation as Do was increased compared to the smaller droplet diameters examined where extinction was not experimentally observed. For the largest droplets examined the possibility that the observed extinction is indicative of a transition to cool flame burning is still under investigation.

Guo, Songtao↗
DOE OSTI2020

Optical Investigation of Catalyst Heating Operation in a Light-Duty Compression-Ignition Engine

It is well known that cold start engine operation contributes a majority of tail-pipe emissions during a vehicle drive cycle. Aftertreatment catalysts have poor conversion efficiency during this period due to low conversion efficiency at temperatures less than their light-off temperature. A late post injection strategy, with a delayed injection to increase exhaust enthalpy, can help decrease the time required to heat-up the catalyst. However, late injections into conditions with decreasing temperature and density can result in high emissions and combustion instability. In this study a three-injection strategy with a late-post injection was investigated in an optically-accessible engine. For the first two injections (pilot and main) timing and duration were held constant as the post injection timing was swept and duration varied to hold load constant, at a relevant light-load catalyst heating operating condition. Simultaneous double-pass schlieren and OH chemiluminescence data were acquired in an optically-accessible 0.4 L single-cylinder engine to understand spray characteristics and combustion behavior for #2 diesel fuel. Optical images analysis revealed higher liquid penetration and lower vaporization of the liquid fuel jet as post injection is retarded. It is also observed that retarding post injection timing to +25 CAD resulted in lower observed soot concentration in the piston bowl.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Examining Constituent Redistribution in U-19Pu-10Zr Fuel as it Evolves with Local Burnup

While constituent redistribution is a known irradiation behavior in U-Pu-Zr fuel, new data have shown it is more complex than our current understanding and predictive capabilities. The size and composition of redistributed rings evolve as a function of pin composition, burnup, geometry, and irradiation temperature. In this work, we extract microstructural information from optical microscopy conducted on U-19Pu-10Zr pins (irradiated between 1.9 at. % and 11.6 at. % peak burnup). Both manual image analysis techniques and machine learning-assisted segmentation are used to quantify the thicknesses of the cladding, fuel-cladding interaction layers, and rings of fuel constituent redistribution in addition to pore distribution. These microstructural features and individual redistributed regions affect local thermomechanical properties, and identifying the relationship between burnup and constituent redistribution will improve accurate prediction of advanced reactor fuel performance.

Constituent Redistribution↗
NASA NTRS1992

Analysis of CCD images of the coma of comet P/Halley

The modeling analysis objective of this project is to make use of the skill acquired in the development of Monte Carlo particle trajectory models for the distributions of gas species in cometary comae as a basis for a new dust coma model. This model will include a self-consistent picture of the time-dependent dusty-gas dynamics of the inner coma and the three-dimensional time-dependent trajectories of the dust particles under the influence of solar gravity and solar radiation pressure in the outer coma. Our purpose is to use this model as a tool to analyze selected images from two sets of data of the comet P/Halley with the hope that we can help to understand the effects of a number of important processes on the spatial morphology of the observed dust coma. The study will proceed much in the same way as our study of the spatially extended hydrogen coma where we were able to understand the spatial morphology of the Lyman-alpha coma in terms of the partial thermalization of the hot H atoms produced by the photodissociation of cometary H2O and OH. The processes of importance to the observed dust coma include: (1) the dust particle size distribution function; (2) the terminal velocities of various sized dust particles in the inner coma; (3) the radiation scattering properties of dust particles, which are important both in terms of the observed scattered radiation and the radiation pressure acceleration on dust particles; (4) the fragmentation and/or vaporization of dust particles; (5) the relative importance of CHON and silicate dust particles as they contribute both to the dusty-gas dynamics in the inner coma (that produce the dust particle terminal velocities) and to the observed spatial morphology of the outer dust coma; and (6) the time and direction dependence of the source of dust.

Combi, Michael R.↗
NASA NTRS1989

Integrating NASA's Land Analysis System (LAS) image processing software with an appropriate Geographic Information System (GIS): A review of candidates in the public domain

A user requirements analysis (URA) was undertaken to determine and appropriate public domain Geographic Information System (GIS) software package for potential integration with NASA's LAS (Land Analysis System) 5.0 image processing system. The necessity for a public domain system was underscored due to the perceived need for source code access and flexibility in tailoring the GIS system to the needs of a heterogenous group of end-users, and to specific constraints imposed by LAS and its user interface, Transportable Applications Executive (TAE). Subsequently, a review was conducted of a variety of public domain GIS candidates, including GRASS 3.0, MOSS, IEMIS, and two university-based packages, IDRISI and KBGIS. The review method was a modified version of the GIS evaluation process, development by the Federal Interagency Coordinating Committee on Digital Cartography. One IEMIS-derivative product, the ALBE (AirLand Battlefield Environment) GIS, emerged as the most promising candidate for integration with LAS. IEMIS (Integrated Emergency Management Information System) was developed by the Federal Emergency Management Agency (FEMA). ALBE GIS is currently under development at the Pacific Northwest Laboratory under contract with the U.S. Army Corps of Engineers' Engineering Topographic Laboratory (ETL). Accordingly, recommendations are offered with respect to a potential LAS/ALBE GIS linkage and with respect to further system enhancements, including coordination with the development of the Spatial Analysis and Modeling System (SAMS) GIS in Goddard's IDM (Intelligent Data Management) developments in Goddard's National Space Science Data Center.

Rochon, Gilbert L.↗
NASA NTRS2012

Improved Hierarchical Optimization-Based Classification of Hyperspectral Images Using Shape Analysis

A new spectral-spatial method for classification of hyperspectral images is proposed. The HSegClas method is based on the integration of probabilistic classification and shape analysis within the hierarchical step-wise optimization algorithm. First, probabilistic support vector machines classification is applied. Then, at each iteration two neighboring regions with the smallest Dissimilarity Criterion (DC) are merged, and classification probabilities are recomputed. The important contribution of this work consists in estimating a DC between regions as a function of statistical, classification and geometrical (area and rectangularity) features. Experimental results are presented on a 102-band ROSIS image of the Center of Pavia, Italy. The developed approach yields more accurate classification results when compared to previously proposed methods.

Classification↗
NASA NTRS1987

A preliminary computer pattern analysis of satellite images of mature extratropical cyclones

This study has applied computerized pattern analysis techniques to the location and classification of features of several mature extratropical cyclones that were depicted in GOES satellite images. These features include the location of the center of the cyclone vortex core and the location of the associated occluded front. The cyclone type was classified in accord with the scheme of Troup and Streten. The present analysis was implemented on a personal computer; results were obtained within approximately one or two minutes without the intervention of an analyst.

Burfeind, Craig R.↗