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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Characterization of fluidized bed chemical vapor deposition ZrC coatings on PyC/YSZ kernels deposited under differing conditions

In this study, coated fuel particle architectures with ZrC coatings are candidate fuels for advanced power reactors and space nuclear propulsion (SNP) concepts. Owing to its relevance to SNP, the composition, microstructure, and mechanical properties of eight ZrC coatings prepared by fluidized bed chemical vapor deposition were evaluated. Evaluation by SEM and EBSD showed that all grains were columnar. Across the various examined samples, minor axis diameters varied between 0.3 and 1.1 μm, and major axis diameters varied between 0.4 and 2.3 μm. Major and minor diameters increased with thickness particularly at higher deposition temperatures in which the major grain axis (from an ellipse fit to the grain shape) increased by 2.5 μm over the entire coating. Coatings with higher reactive gas flows and Zr/C concentrations closer to 1 were observed to contain nanocrystalline graphite deposits. Reactive gas flow doubling led to increases in coating thickness from around 10–15 μm to around 22–27 μm.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

X-ray morphology of cluster-mass haloes in self-interacting dark matter

ABSTRACT We perform cosmological zoom-in simulations of 19 relaxed cluster-mass haloes with the inclusion of adiabatic gas in the cold dark matter (CDM) and self-interacting dark matter (SIDM) models. These clusters are selected as dynamically relaxed clusters from a parent simulation with $M_{\rm 200} \simeq (1\!-\!3)\times 10^{15}{\, \rm M_\odot }$. Both the dark matter and the intracluster gas distributions in SIDM appear more spherical than their CDM counterparts. Mock X-ray images are generated based on the simulations and are compared to the real X-ray images of 84 relaxed clusters selected from the Chandra and ROSAT archives. We perform ellipse fitting for the isophotes of mock and real X-ray images and obtain the ellipticities at cluster-centric radii of $r\simeq 0.1\!-\!0.2R_{\rm 200}$. The X-ray isophotes in SIDM models with increasing cross-sections are rounder than their CDM counterparts, which manifests as a systematic shift in the distribution function of ellipticities. Unexpectedly, the X-ray morphology of the observed non-cool-core clusters agrees better with SIDM models with cross-section $(\sigma /m)= 0.5\!-\!1\, {\rm cm}^2\, {\rm g}^{-1}$ than CDM and SIDM with $(\sigma /m)=0.1\, {\rm cm}^2\, {\rm g}^{-1}$. Our statistical analysis indicates that the latter two models are disfavoured at the $68{{\ \rm per\ cent}}$ confidence level (as conservative estimates). This conclusion is not altered by shifting the radial range of measurements or applying a temperature selection criterion. However, the primary uncertainty originates from the lack of baryonic physics in the adiabatic model, such as cooling, star formation and feedback effects, which still have the potential to reconcile CDM simulations with observations.

Shen, Xuejian (ORCID:000000026196823X)↗
DOE OSTI2022

Analysis of Defects in Metal Additive Manufacturing with Augmented Data Generation

Laser powder bed fusion (LPBF) is a method of additive manufacturing (AM) that selectively melts and fuses together microscopic metallic powder. LPBF offers the benefit of producing custom structures out of high strength metals that can be difficult to fabricate with conventional methods. The challenge of LPBF is that 3D printed structures often have internal pores due to process flaws. Pulsed thermal tomography (PTT) is a method for reconstructing the depth profile of materials, allowing the visualization internal voids in solids. In prior work, we developed a convolutional neural network (CNN) which, having been trained on simulated 2D PTT images of subsurface elliptical defects, was able to classify the semi-major radii, semi-minor radii, and angular orientation of the best-fit ellipses in previously unseen PTT images. The unseen PTT images contained subsurface irregular defect shapes imported from scanning electron microscopy (SEM) images of metallic LPBF-printed specimens. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Improved Subseasonal Forecasting of Extreme Polar Vortices Using Machine Learning

Our research was focused on forecasting the position and shape of the winter stratospheric polar vortex at a subseasonal timescale of 15 days in advance. To achieve this, we employed both statistical and neural network machine learning techniques. The analysis was performed on 42 winter seasons of reanalysis data provided by NASA giving us a total of 6,342 days of data. The state of the polar vortex for determined by using geometric moments to calculate the centroid latitude and the aspect ratio of an ellipse fit onto the vortex. Timeseries for thirty additional precursors were calculated to help improve the predictive capabilities of the algorithm. Feature importance of these precursors was performed using random forest to measure the predictive importance and the ideal number of precursors. Then, using the precursors identified as important, various statistical methods were tested for predictive accuracy with random forest and nearest neighbor performing the best. An echo state network, a type of recurrent neural network that features sparsely connected hidden layer and a reduced number of trainable parameters that allows for rapid training and testing, was also implemented for the forecasting problem. Hyperparameter tuning was performed for each methods using a subset of the training data. The algorithms were trained and tuned on the first 41 years of data, then tested for accuracy on the final year. In general, the centroid latitude of the polar vortex proved easier to predict than the aspect ratio across all algorithms. Random forest outperformed other statistical forecasting algorithms overall but struggled to predict extreme values. Forecasting from echo state network suggested a strong predictive capability past 15 days, but further work is required to fully realize the potential of recurrent neural network approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Pulsed Infrared Thermography Nondestructive Imaging of SiC-SiC f Composite Cladding Architectures; Understanding the Performance of SiC-SiC f Composite Cladding Architectures with Cr Coating in Normal Operating and Accident Conditions in LWRs and Advanced Reactors

SiC-SiC f composites, consisting of silicon carbide fibers embedded in a silicon carbide matrix, are advanced materials with high thermal conductivity, temperature stability, and resistance to radiation damage. Traditional methods for quality control of fabricated SiC-SiC f composites involve nondestructive evaluation (NDE) with X-ray computed tomography (XCT). However, XCT imaging of typical SiC-SiC f structures for cladding applications can involve several hours. In this project, we investigate an alternative approach to NDE of SiC-SiC f composites that involves rapid (on the order of seconds) imaging with Pulsed infrared thermography (PIT). PIT images of a planar SiC-SiC f specimen show the structure of the surface monolith layer and internal SiC f structures. The capability of PIT imaging in visualizing SiC f structures is qualitatively confirmed by observing similarity in the PIT and X-ray transmission images of the same specimen. Computer vision analysis of defects in the PIT image of the monolith was performed with thresholding followed by topological structural analysis that computed geometric descriptors, including major/minor axes of fitted ellipses, area, perimeter, Feret diameter, circularity, roundness, and solidity.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1987

Shapes of small satellites

The accurate measurement of limb coordinates on small satellite is the major technique for evaluating their sizes and shapes in the absence of good stereoscopic image coverage. The shapes of satellites may be clues to their internal structure if they are relaxed into ellipsoids. The distinction between irregular and ellipsoidal satellites can now be made quantitatively with the availability of many accurate limb profiles of satellites. The residuals from these fit ellipses provide a convenient and quantitative measure of the topography on the satellites. Departures from gravitational (and tidal) equipotentials would be greater, but on the average this is a good measure of the relaxed or nonrelaxed nature of the shape of the objects. The limb topography is also related to specific forms on the objects, and a systematic survey of these forms on small and larger objects is underway.

Thomas, P.↗
NASA NTRS1991

The galaxy activity-interaction connection. I - Optical observations

As part of an investigation into the triggering of nuclear radio emission in interacting galaxies, new multicolor, broadband data are presented from a subset of Arp-Madore Catalog galaxies selected on the basis of their optical morphology - systems with loops and/or tails. The CTIO 4 m is used to obtain images in B, V, R, and I for the purpose of performing synthetic aperture photometry. Isophotal ellipse fitting to the more regular objects in the sample is also performed to quantify their isophotal deviation from purely elliptical morphologies. Color index maps for the galaxies are constructed, and the optical morphologies, broadband colors, and detailed photometric properties as well as the IRAS fluxes for the galaxies are discussed. These data are used to obtain a rough measure of the level of activity present in these systems.

Smith, Eric P.↗
NASA NTRS1993

NGC 4314. II - Hubble Space Telescope I-band surface photometry of the nuclear region

We present an HST I-band Planetary Camera image of the nuclear region of NGC 4314, an anemic barred galaxy with recent star formation confined to a nuclear ring. These data resolve the nuclear ring into multiple sites of new star formation and resolve associated dust lanes into discrete clouds. Deconvolution results in at least 0.13 arcsec resolution, as demonstrated by the de Vaucouleurs r exp 1/4 law. Contrasted with similar studies of M87 and NGC 7457, we find no photometric evidence for an extreme concentration of stars in the center of NGC 4314. We identify an oval distortion of length 8 arcsec in the nuclear region, using ellipse-fitting routines and the unsharp masked frame. This nuclear bar has newer stars near its ends. We catalog 14 star clusters associated with H II regions in the nuclear ring. As an additional demonstration of the resolution achieved, the integral size distribution of these clusters is described by an exponential relationship which prevails down to 0.14 arcsec.

Benedict, G. F.↗
NASA NTRS2010

Landmark Detection in Orbital Images Using Salience Histograms

NASA's planetary missions have collected, and continue to collect, massive volumes of orbital imagery. The volume is such that it is difficult to manually review all of the data and determine its significance. As a result, images are indexed and searchable by location and date but generally not by their content. A new automated method analyzes images and identifies "landmarks," or visually salient features such as gullies, craters, dust devil tracks, and the like. This technique uses a statistical measure of salience derived from information theory, so it is not associated with any specific landmark type. It identifies regions that are unusual or that stand out from their surroundings, so the resulting landmarks are context-sensitive areas that can be used to recognize the same area when it is encountered again. A machine learning classifier is used to identify the type of each discovered landmark. Using a specified window size, an intensity histogram is computed for each such window within the larger image (sliding the window across the image). Next, a salience map is computed that specifies, for each pixel, the salience of the window centered at that pixel. The salience map is thresholded to identify landmark contours (polygons) using the upper quartile of salience values. Descriptive attributes are extracted for each landmark polygon: size, perimeter, mean intensity, standard deviation of intensity, and shape features derived from an ellipse fit.

Wagstaff, Kiri L.↗
NASA NTRS2010

Three-Dimensional Morphology of a Coronal Prominence Cavity

We present a three-dimensional density model of coronal prominence cavities, and a morphological fit that has been tightly constrained by a uniquely well-observed cavity. Observations were obtained as part of an International Heliophysical Year campaign by instruments from a variety of space- and ground-based observatories, spanning wavelengths from radio to soft-X-ray to integrated white light. From these data it is clear that the prominence cavity is the limb manifestation of a longitudinally-extended polar-crown filament channel, and that the cavity is a region of low density relative to the surrounding corona. As a first step towards quantifying density and temperature from campaign spectroscopic data, we establish the three-dimensional morphology of the cavity. This is critical for taking line-of-sight projection effects into account, since cavities are not localized in the plane of the sky and the corona is optically thin. We have augmented a global coronal streamer model to include a tunnel-like cavity with elliptical cross-section and a Gaussian variation of height along the tunnel length. We have developed a semi-automated routine that fits ellipses to cross-sections of the cavity as it rotates past the solar limb, and have applied it to Extreme Ultraviolet Imager (EUVI) observations from the two Solar Terrestrial Relations Observatory (STEREO) spacecraft. This defines the morphological parameters of our model, from which we reproduce forward-modeled cavity observables. We find that cavity morphology and orientation, in combination with the viewpoints of the observing spacecraft, explains the observed variation in cavity visibility for the east vs. west limbs

Gibson, S. E.↗
NASA NTRS2012

Hubble Space Telescope Observations of the HD 202628 Debris Disk

A ring-shaped debris disk around the G2V star HD 202628 (d = 24.4 pc) was imaged in scattered light at visible wavelengths using the coronagraphic mode of the Space Telescope Imaging Spectrograph on the Hubble Space Telescope. The ring is inclined by approx.64deg from face-on, based on the apparent major/minor axis ratio, with the major axis aligned along PA = 130deg. It has inner and outer radii (> 50% maximum surface brightness) of 139 AU and 193 AU in the northwest ansae and 161 AU and 223 AU in the southeast ((Delta)r/r approx. = 0.4). The maximum visible radial extent is approx. 254 AU. With a mean surface brightnesses of V approx. = 24 mag arcsec.(sup -2), this is the faintest debris disk observed to date in reflected light. The center of the ring appears offset from the star by approx.28 AU (deprojected). An ellipse fit to the inner edge has an eccentricity of 0.18 and a = 158 AU. This offset, along with the relatively sharp inner edge of the ring, suggests the influence of a planetary-mass companion. There is a strong similarity with the debris ring around Fomalhaut, though HD 202628 is a more mature star with an estimated age of about 2 Gyr. We also provide surface brightness limits for nine other stars in our study with strong Spitzer excesses around which no debris disks were detected in scattered light (HD 377, HD 7590, HD 38858, HD 45184, HD 73350, HD 135599, HD 145229, HD 187897, and HD 201219).

Krist, John E.↗
NASA NTRS2017

Examination of Multiple Lithologies Within the Primitive Ordinary Chondrite NWA 5717

Northwest Africa 5717 is a primitive (subtype 3.05) ungrouped ordinary chondrite which contains two apparently distinct lithologies. In large cut meteorite slabs, the darker of these, lithology A, looks to host the second, much lighter in color, lithology B (upper left, Fig. 1). The nature of the boundary between the two is uncertain, ranging from abrupt to gradational and not always following particle boundaries. The distinction between the lithologies, beyond the obvious color differences, has been supported by a discrepancy in oxygen isotopes and an incongruity in the magnesium contents of chondrule olivine. Here, quantitative textural analysis and mineralogical methods have been used to investigate the two apparent lithologies within NWA 5717. Olivine grains contained in a thin section from NWA 7402, thought to be paired to 5717, were also measured to re-examine the distinct compositional range among the light and dark areas. Procedure: Particles from a high-resolution mosaic image of a roughly 13x15cm slice of NWA 5717 were traced in Adobe Photoshop. Due to the large size of the sample, visually representative regions of each lithology were chosen to be analyzed. The resulting layers of digitized particles were imported into ImageJ, which was used to measure their area, along with the axes, the angle from horizontal, and the centroid coordinates of ellipses fitted to each particle following the approach. Resulting 2D pixel areas were converted to spherical diameters employing the unfolding algorithm, which outputs a 3D particle size distribution based on digitized 2D size frequency data. Spatstat was used to create kernel density plots of the centroid coordinates for each region. X-ray compositional maps, microprobe analyses, and Mossbauer spectroscopy was conducted on a thin section of NWA 7402, tentatively paired to NWA 5717.

Cato, M. J.↗
NASA NTRS2018

Orion Optical Navigation Progress Toward Exploration: Mission 1

Optical navigation of human spacecraft was proposed on Gemini and implemented successfully on Apollo as a means of autonomously operating the vehicle in the event of lost communication with controllers on Earth. It shares a history with the "method of lunar distances" that was used in the 18th century and gained some notoriety after its use by Captain James Cook during his 1768 Pacific voyage of the HMS Endeavor. The Orion emergency return system utilizing optical navigation has matured in design over the last several years, and is currently undergoing the final implementation and test phase in preparation for Exploration Mission 1 (EM-1) in 2019. The software development is being worked as a Government Furnished Equipment (GFE) project delivered as an application within the Core Flight Software of the Orion camera controller module. The mathematical formulation behind the initial ellipse fit in the image processing is detailed in Christian. The non-linear least squares refinement then follows the technique of Mortari as an estimation process of the planetary limb using the sigmoid function. The Orion optical navigation system uses a body fixed camera, a decision that was driven by mass and mechanism constraints. The general concept of operations involves a 2-hour pass once every 24 hours, with passes specifically placed before all maneuvers to supply accurate navigation information to guidance and targeting. The pass lengths are limited by thermal constraints on the vehicle since the OpNav attitude generally deviates from the thermally stable tail-to-sun attitude maintained during the rest of the orbit coast phase. Calibration is scheduled prior to every pass due to the unknown nature of thermal effects on the lens distortion and the mounting platform deformations between the camera and star trackers. The calibration technique is described in detail by Christian, et al. and simultaneously estimates the Brown-Conrady coefficients and the Star Tracker/Camera interlock angles. Accurate attitude information is provided by the star trackers during each pass. Figure 1 shows the various phases of lunar return navigation when the vehicle is in autonomous operation with lost ground communication. The midcourse maneuvers are placed to control the entry interface conditions to the desired corridor for safe landing. The general form of optical navigation on Orion is where still images of the Moon or Earth are processed to find the apparent angular diameter and centroid in the camera focal plane. This raw data is transformed into range and bearing angle measurements using planetary data and precise star tracker inertial attitude. The measurements are then sent to the main flight computer's Kalman filter to update the onboard state vector. The images are, of course, collected over an arc to converge the state and estimate velocity. The same basic technique was used by Apollo to satisfy loss-of-comm, but Apollo used manual crew sightings with a vehicle-integral sextant instead of autonomously processing optical imagery. The software development is past its Critical Design Review, and is progressing through test and certification for human rating. In support of this, a hardware-in-the-loop test rig was developed in the Johnson Space Center Electro-Optics Lab to exercise the OpNav system prior to integrated testing on the Orion vehicle. Figure 2 shows the rig, which the test team has dubbed OCILOT (Orion Camera In the Loop Optical Testbed). Analysis performed to date shows a delivery that satisfies an allowable entry corridor as shown in Figure 3.

Holt, Greg N.↗
NASA NTRS2022

X-Ray Morphology of Cluster-Mass Haloes in Self-Interacting Dark Matter

We perform cosmological zoom-in simulations of 19 relaxed cluster-mass haloes with the inclusion of adiabatic gas in the cold dark matter (CDM) and self-interacting dark matter (SIDM) models. These clusters are selected as dynamically relaxed clusters from a parent simulation with M200(1-3) × 10 15 M. Both the dark matter and the intracluster gas distributions in SIDM appear more spherical than their CDM counterparts. Mock X-ray images are generated based on the simulations and are compared to the real X-ray images of 84 relaxed clusters selected from the Chandra and ROSAT archives. We perform ellipse fitting for the isophotes of mock and real X-ray images and obtain the ellipticities at cluster-centric radii of r0.1–0.2R 200 .The X-ray isophotes in SIDM models with increasing cross-sections are rounder than their CDM counterparts, which manifests as asystematic shift in the distribution function of ellipticities. Unexpectedly, the X-ray morphology of the observed non-cool-coreclusters agrees better with SIDM model swith cross-section (σ/m)=0.5–1cm2g−1 than CDM and SIDM with (σ/m)=0.1cm2g−1. Our statistical analysis indicates that the latter two models are disfavoured at the 68 percent confidence level (as conservative estimates). This conclusion is not altered by shifting the radial range of measurements or applying a temperature selection criterion. However, the primary uncertainty originates from the lack of baryonic physics in the adiabatic model, such as cooling, star formation and feedback effects, which still have the potential to reconcile CDM simulations with observations.

dark matter – cosmology↗
NASA NTRS2009

Processing Images of Craters for Spacecraft Navigation

A crater-detection algorithm has been conceived to enable automation of what, heretofore, have been manual processes for utilizing images of craters on a celestial body as landmarks for navigating a spacecraft flying near or landing on that body. The images are acquired by an electronic camera aboard the spacecraft, then digitized, then processed by the algorithm, which consists mainly of the following steps: 1. Edges in an image detected and placed in a database. 2. Crater rim edges are selected from the edge database. 3. Edges that belong to the same crater are grouped together. 4. An ellipse is fitted to each group of crater edges. 5. Ellipses are refined directly in the image domain to reduce errors introduced in the detection of edges and fitting of ellipses. 6. The quality of each detected crater is evaluated. It is planned to utilize this algorithm as the basis of a computer program for automated, real-time, onboard processing of crater-image data. Experimental studies have led to the conclusion that this algorithm is capable of a detection rate >93 percent, a false-alarm rate <5 percent, a geometric error <0.5 pixel, and a position error <0.3 pixel.

Cheng, Yang↗
NASA NTRS1992

The IRAF Fabry-Perot analysis package: Ring fitting

As introduced at ADASSI, a Fabry-Perot analysis package for IRAF is currently under development as a joint effort of ourselves and Frank Valdes of the IRAF group. Although additional portions of the package were also implemented, we report primarily on the development of a robust ring fitting task, useful for fitting the calibration rings obtained in Fabry-Perot observations. The general equation of an ellipse is fit to the shape of the rings, providing information on ring center, ellipticity, and position angle. Such parameters provide valuable information on the wavelength response of the etalon and the geometric stability of the system. Appropriate statistical weighting is applied to the pixels to account for increasing numbers with radius, the Lorentzian cross-section, and uneven illumination. The major problems of incomplete, non-uniform, and multiple rings are addressed with the final task capable of fitting rings regardless of center, cross-section, or completion. The task requires only minimal user intervention, allowing large numbers of rings to be fit in an extremely automated manner.

Shopbell, P. L.↗
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 NTRS1988

The shape and internal structure of Mimas

The present effort to determine the shape of Mimas proceeds on the basis of limb profiles from six Voyager images; the fitting of ellipses to the limbs indicates that the shape is a triaxial ellipsoid. The satellite mass determined by Kozai (1957), in conjunction with a second-order theory for the ellipsoidal figure of equilibrium, leads to a satellite mean radius determination of 198.8 + or - 0.6 km, and a mean density of 1.137 + or - 0.018 g/cu cm. It is suggested that Mimas is probably differentiated, with a rocky core and a water-ice crust; alternatively, Mimas has a cosmic composition of ice and rock and is undifferentiated.

Dermott, Stanley F.↗