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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Coronal fine structure as seen in the Skylab white light coronagraph

The white light coronograph (WLC) on Skylab provided an opportunity to study the corona at high spatial and temporal resolution. The spatial resolution of the instrument was approximately 25 cm with images taken approximately one per min. One set of images taken over a 10 min period was digitized, providing ten high spatial resolution images for analysis. The progress in data processing techniques available at the time was not sufficient to permit a reliable study of the fine structure in these images. Using current techniques an investigation of the sizes and lifetimes of the smallest scale features in the data was carried out. A preliminary analysis of an area between 2 and 3 Ro was completed. The results show that very narrow rays extend from at least 2 to 3 Ro. The narrowest of these rays has a thickness of approximately 75 cm. The contrast is so low that they are very close to the noise limit of the data. Most of the rays observed become unrecognizable after 10 min, although some remain visible over the entire time. Some notion seems to be detectable in the fine structure rays, but analysis of more frames will be needed to quantify these results.

Poland, Arthur I.↗
DOE OSTI2020

STEM Characterization of Dislocation Loops in Irradiated FCC Alloys

In this study, we demonstrate the methodology systematically developed for dislocation loop (perfect and faulted loops) imaging and analysis in irradiated face-centered-cubic (FCC) alloys using scanning transmission electron microscopy (STEM). On-zone [001] STEM imaging was identified as the preferred choice for its accuracy and effectiveness based on the comparison with other dislocation loop imaging techniques including: (i) on-zone STEM imaging using other major low-index zone axes, (ii) kinematic two-beam conditions bright field imaging near the [001] zone axis in conventional TEM (CTEM) mode, and (iii) Rel-Rod CTEM dark-field (DF) imaging near the [011] zone axis. The effect of STEM collection angle on the contrast formation of dislocation loops was also investigated. The developed method was confirmed by imaging all populations of perfect and faulted loops of types a/2$\langle$110$\rangle${110} and a/3$\langle$111$\rangle${111} found in an ion irradiated Ni40Fe40Cr20 alloy. The proposed STEM-based technique can easily identify said loops with a size greater than 10 nm without any assumptions such as those commonly made using the conventional Rel-Rod CTEM-DF technique. The recommended methodology in this study is developed as a quick and convenient tool that can be generally applied to irradiated FCC-based materials due to their common crystallography.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Segmentation of tomography datasets using 3D convolutional neural networks

Dendritic microstructures are ubiquitous in nature and are the primary solidification morphologies in metallic materials. Techniques such as X-ray computed tomography (XCT) have provided new insights into dendritic phase transformation phenomena. However, manual identification of dendritic morphologies in microscopy data can be both labor intensive and potentially ambiguous. The analysis of 3D datasets is particularly challenging due to their large sizes (terabytes) and the presence of artifacts scattered within the imaged volumes. Here, in this study, we trained 3D convolutional neural networks (CNNs) to segment 3D datasets. Three CNN architectures were investigated, including a new version of FCDenseNet which we extended to 3D. We show that using hyperparameter optimization (HPO) and fine-tuning techniques, both 2D and 3D CNN architectures outperform the previous state of the art. The 3D U-Net architecture trained in this study produced the best segmentations according to quantitative metrics (intersection-over-union of 95.56% and a boundary displacement error of 0.58 pixels), while 3D FCDense produced the smoothest boundaries and best segmentations according to visual inspection. The trained 3D CNNs are able to segment entire 852 × 852 × 250 voxel 3D volumes in only ~60 s, thus hastening the progress towards a deeper understanding of phase transformation phenomena such as dendritic solidification.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Information-Theoretic Exploration of Multivariate Time-Varying Image Databases

Modern scientific simulations produce very large datasets, making interactive exploration of such data computationally prohibitive. An increasingly common data reduction technique is to store visualizations and other data extracts in a database. The Cinema project is one such approach, storing visualizations in an image database for post hoc exploration and interactive image-based analysis. This work focuses on developing efficient algorithms that can quantify various types of multivariate dependencies existing within multi-variable datasets. It applies specific mutual information measures for the quantification of salient regions from multivariate image data. Here, using such information measures, the opacity of the images is modulated so that the salient regions are automatically highlighted and the domain scientists can interactively explore the most relevant regions for scientific discovery.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Quantification of morphological change in materials based on image data utilizing machine learning techniques

Computed tomography (CT) resolution has become high enough to monitor morphological changes due to aging in materials in long-term applications. We explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images visually reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect. Both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Utilization of the Critic Subnetwork of a Generative Adversarial Network as Detector of Morphological Material Change in Image Data

The resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long-term applications. For this work, we explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The performance of additively manufactured Haynes 282 in supercritical CO 2

The use of supercritical carbon dioxide (sCO 2 ) as a working fluid is garnering interest in next generation power production systems due to the possibility of increased operational efficiencies and lower associated costs. Its implementation requires alloys with excellent high temperature strength and corrosion resistance, which makes Haynes 282® (H282) a suitable candidate. With increasing adoption of additive manufacturing (AM) in the energy industry, there is a need to investigate long-term sCO2 exposure on AM produced materials. Additively manufactured H282 (AM-H282) samples built using laser powder bed fusion in two different orientations were analyzed through imaging, gravimetric analysis, and room-temperature tensile testing before and after 1000-h exposure to CO 2 at 750 °C and 20 MPa. Performed imaging included observation of the sample surfaces and of the material bulk (cross sections) through means of Scanning Electron Microscopy (SEM) and optical microscopy. In comparison to wrought H282, it was found that the exposed material exhibited a similar Cr 2 O 3 oxide protective layer about 2 μm in thickness with additional top-surface TiO 2 oxide and carbon-rich precipitates. It was also similarly observed that internal oxidation was present but limited to a depth of 20 μm, and a 1–3 μm γ’ denuded region appeared to surround all internal and surface oxidation. Thermal aging effects were noted with the precipitation of needle-like structures in the γ/γ’ matrix and a coarsening of the γ’ precipitates from 28 nm to 73 nm. Mass measurements analyzing oxide precipitation revealed a larger increase compared to wrought, representing an approximate 20% difference. Tensile testing results showed similar behavior to wrought with a slight increase in yield strength and a large reduction in elongation in the exposed samples.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Measurement of Transport Properties of Woody Biomass Feedstock Particles Before and After Pyrolysis by Numerical Analysis of X-Ray Tomographic Reconstructions

Lignocellulosic biomass has a complex, species-specific microstructure that governs heat and mass transport during conversion processes. A quantitative understanding of the evolution of pore size and structure is critical to optimize conversion processes for biofuel and bio-based chemical production. Further, improving our understanding of the microstructure of biochar coproduct will accelerate development of its myriad applications. This work quantitatively compares the microstructural features and the anisotropic permeabilities of two woody feedstocks, red oak and Douglas fir, using X-ray computed tomography (XCT) before and after the feedstocks are subjected to pyrolysis. Quantitative analysis of the three-dimensional (3D) reconstructions allows for direct calculations of void fractions, pore size distributions and tortuosity factors. Next, 3D images are imported into an immersed boundary based finite volume solver to simulate gas flow through the porous structure and to directly calculate the principal permeabilities along longitudinal, radial, and tangential directions. The permeabilities of native biomass are seen to differ by three to four orders of magnitude in the different principal directions, but we find that this anisotropy is substantially reduced in the biochar formed during pyrolysis. The quantitative transport properties reported here enhance the ability of pyrolysis simulations to account for feedstock-specific effects and thereby provide a useful touchstone for the biorefining community.

09 BIOMASS FUELS↗
NASA NTRS1975

Software techniques for image processing

The present paper describes several software techniques that can be used to get the 'most' out of an image without destroying or adding any information. A simple overview is given of a general image-processing system, a number of systems in current use are listed, and three types of processing tasks are delineated: image diagnostics, subjective enhancement, and quantitative restoration. Examples of each of these types are discussed in some detail, including histogram, differences, and Fourier analysis for image diagnostics; contrast stretching, edge enhancement, and pseudocolor displays for subjective enhancement; and photometric correction, contouring, and geometric correction for quantitative restoration.

Klinglesmith, D. A.↗
NASA NTRS2007

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

This report details one of three experiments performed during FY 2007 for the NASA RPC (Rapid Prototyping Capability) at Stennis Space Center. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria dispar). The intent of the RPC experiment was to assess the degree to which VIIRS data can provide forest disturbance monitoring information as an input to a forest threat EWS (Early Warning System) as compared to the level of information that can be obtained from MODIS data. The USDA Forest Service (USFS) plans to use MODIS products for generating broad-scaled, regional monitoring products as input to an EWS for forest health threat assessment. NASA SSC is helping the USFS to evaluate and integrate currently available satellite remote sensing technologies and data products for the EWS, including the use of MODIS products for regional monitoring of forest disturbance. Gypsy moth defoliation of the mid-Appalachian highland region was selected as a case study. Gypsy moth is one of eight major forest insect threats listed in the Healthy Forest Restoration Act (HFRA) of 2003; the gypsy moth threatens eastern U.S. hardwood forests, which are also a concern highlighted in the HFRA of 2003. This region was selected for the project because extensive gypsy moth defoliation occurred there over multiple years during the MODIS operational period. This RPC experiment is relevant to several nationally important mapping applications, including agricultural efficiency, coastal management, ecological forecasting, disaster management, and carbon management. In this experiment, MODIS data and VIIRS data simulated from MODIS were assessed for their ability to contribute broad, regional geospatial information on gypsy moth defoliation. Landsat and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data were used to assess the quality of gypsy moth defoliation mapping products derived from MODIS data and from simulated VIIRS data. The project focused on use of data from MODIS Terra as opposed to MODIS Aqua mainly because only MODIS Terra data was collected during 2000 and 2001-years with comparatively high amounts of gypsy moth defoliation within the study area. The project assessed the quality of VIIRS data simulation products. Hyperion data was employed to assess the quality of MODIS-based VIIRS simulation datasets using image correlation analysis techniques. The ART (Application Research Toolbox) software was used for data simulation. Correlation analysis between MODIS-simulated VIIRS data and Hyperion-simulated VIIRS data for red, NIR (near-infrared), and NDVI (Normalized Difference Vegetation Index) image data products collectively indicate that useful, effective VIIRS simulations can be produced using Hyperion and MODIS data sources. The r(exp 2) for red, NIR, and NDVI products were 0.56, 0.63, and 0.62, respectively, indicating a moderately high correlation between the 2 data sources. Temporal decorrelation from different data acquisition times and image misregistration may have lowered correlation results. The RPC experiment also generated MODIS-based time series data products using the TSPT (Time Series Product Tool) software. Time series of simulated VIIRS NDVI products were produced at approximately 400-meter resolution GSD (Ground Sampling Distance) at nadir for comparison to MODIS NDVI products at either 250- or 500-meter GSD. The project also computed MODIS (MOD02) NDMI (Normalized Difference Moisture Index) products at 500-meter GSD for comparison to NDVI-based products. For each year during 2000-2006, MODIS and VIIRS (simulated from MOD02) time series were computed during the peak gypsy moth defoliation time frame in the study area (approximately June 10 through July 27). Gypsy moth defoliation mapping products from simated VIIRS and MOD02 time series were produced using multiple methods, including image classification and change detection via image differencing. The latter enabled an automated defoliation detection product computed using percent change in maximum NDVI for a peak defoliation period during 2001 compared to maximum NDVI across the entire 2000-2006 time frame. Final gypsy moth defoliation mapping products were assessed for accuracy using randomly sampled locations found on available geospatial reference data (Landsat and ASTER data in conjunction with defoliation map data from the USFS). Extensive gypsy moth defoliation patches were evident on screen displays of multitemporal color composites derived from MODIS data and from simulated VIIRS vegetation index data. Such defoliation was particularly evident for 2001, although widespread denuded forests were also seen for 2000 and 2003. These visualizations were validated using aforementioned reference data. Defoliation patches were visible on displays of MODIS-based NDVI and NDMI data. The viewing of apparent defoliation patches on all of these products necessitated adoption of a specialized temporal data processing method (e.g., maximum NDVI during the peak defoliation time frame). The frequency of cloud cover necessitated this approach. Multitemporal simulated VIIRS and MODIS Terra data both produced effective general classifications of defoliated forest versus other land cover. For 2001, the MOD02-simulated VIIRS 400-meter NDVI classification produced a similar yet slightly lower overall accuracy (87.28 percent with 0.72 Kappa) than the MOD02 250-meter NDVI classification (88.44 percent with 0.75 Kappa). The MOD13 250-meter NDVI classification had a lower overall accuracy (79.13 percent) and a much lower Kappa (0.46). The report discusses accuracy assessment results in much more detail, comparing overall classification and individual class accuracy statistics for simulated VIIRS 400-meter NDVI, MOD02 250-meter NDVI, MOD02-500 meter NDVI, MOD13 250-meter NDVI, and MOD02 500-meter NDMI classifications. Automated defoliation detection products from simulated VIIRS and MOD02 data for 2001 also yielded similar, relatively high overall classification accuracy (85.55 percent for the VIIRS 400-meter NDVI versus 87.28 percent for the MOD02 250-meter NDVI). In contrast, the USFS aerial sketch map of gypsy moth defoliation showed a lower overall classification accuracy at 73.64 percent. The overall classification Kappa values were also similar for the VIIRS (approximately 0.67 Kappa) versus the MOD02 (approximately 0.72 Kappa) automated defoliation detection product, which were much higher than the values exhibited by the USFS sketch map product (overall Kappa of approximately 0.47). The report provides additional details on the accuracy of automated gypsy moth defoliation detection products compared with USFS sketch maps. The results suggest that VIIRS data can be effectively simulated from MODIS data and that VIIRS data will produce gypsy moth defoliation mapping products that are similar to MODIS-based products. The results of the RPC experiment indicate that VIIRS and MODIS data products have good potential for integration into the forest threat EWS. The accuracy assessment was performed only for 2001 because of time constraints and a relative scarcity of cloud-free Landsat and ASTER data for the peak defoliation period of the other years in the 2000-2006 time series. Additional work should be performed to assess the accuracy of gypsy moth defoliation detection products for additional years.The study area (mid-Appalachian highlands) and application (gypsy moth forest defoliation) are not necessarily representative of all forested regions and of all forest threat disturbance agents. Additional work should be performed on other inland and coastal regions as well as for other major forest threats.

Spruce, Joseph P.↗
NASA NTRS1974

Analysis research for earth resource information systems - Where do we stand

Discussion of the state of the technology of earth resources information systems relative to future operational implementation. The importance of recognizing the difference between systems with image orientation and systems with numerical orientation is illustrated in an example concerning the effect of noise on multiband multispectral data obtained in an agricultural experiment. It is suggested that the data system hardware portion of the total earth resources information system be designed in terms of a numerical orientation; it is argued, however, that this choise is entirely compatible with image-oriented analysis tasks. Some aspects of interfacing such an advanced technology with an operational user community in such a way as to accommodate the user's need for flexibility and yet provide the services needed on a cost-effective basis are discussed.

Landgrebe, D. A.↗
NASA NTRS1987

A study of the Io-associated plasma and neutral sodium cloud

Narrow-band interference filter images were obtained for the Io torus at the S II wavelengths of 6716, 6731 and at the wavelenght of the S III, 9532 spectrum. The purpose of these observations is to study the short term temporal behavior of the torus and to gain a better understanding of the systematic morphology of the torus. From these images, estimates were obtained for the electron and ion densities and ion temperatures as a function of longitude, latitude, radius from Jupiter, and time. From the analysis of images taken in 1983 and 1984, extremely sharp longitudinal variations in plasma density were detected, subcorotational velocities were measures in the torus plasma, the presence of an optical east-west brightness asymmetry was confirmed in the ion emissions, and longitudinal variations were detected in torus ion temperatures.

Pilcher, Carl B.↗
NASA NTRS2000

Scanning Electron Microscopy Investigation of a Sample Depth Profile Through the Martian Meteorite Nakhla

The ongoing scientific debate as to whether or not the Martian meteorite ALH84001 contained evidence of possible biogenic activities showed the need to establish consistent methods to ascertain the origin of such evidence. To distinguish between terrestrial organic material/microbial contaminants and possible indigenous microbiota within meteorites is therefore crucial. With this in mind a depth profile consisting of four samples from a new sample allocation of Martian meteorite Nakhla was investigated using scanning electron microscopy (SEM) and energy dispersive X-ray analysis. SEM imaging of freshly broken fractured chips revealed structures strongly recent terrestrial microorganisms, in some cases showing evidence of active growth. This conclusion was supported by EDX analysis, which showed the presence of carbon associated with these structures, we concluded that these structures represent recent terrestrial contaminants rather than structures indigenous to the meteorite. Page

Toporski, Jan↗
DOE OSTI2020

Differential electron yield imaging with STXM

In this report total electron yield (TEY) imaging is an established scanning transmission X-ray microscopy (STXM) technique that gives varying contrast based on a sample's geometry, elemental composition, and electrical conductivity. However, the TEY-STXM signal is determined solely by the electrons that the beam ejects from the sample. A related technique, X-ray beam-induced current (XBIC) imaging, is sensitive to electrons and holes independently, but requires electric fields in the sample. Here we report that multi-electrode devices can be wired to produce differential electron yield (DEY) contrast, which is also independently sensitive to electrons and holes, but does not require an electric field. Depending on whether the region illuminated by the focused STXM beam is better connected to one electrode or another, the DEY-TXM contrast changes sign. DEY-STXM images thus provide a vivid map of a device's connectivity landscape, which can be key to understanding device function and failure. To demonstrate an application in the area of failure analysis, we image a 100 nm, lithographically-defined aluminum nanowire that has failed after being stressed with a large current density.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

XRIPL

XRIPL is a library of tools for processing x-ray radiographs and extracting contours of interest within the image using computer vision techniques. Features include spatial calibration, denoising, background and attenuation correction through pseudo-flatfielding, watershed segmentation, contour processing, and visualization. The details of the XRIPL analysis pipeline are published in the Proceedings of the 23rd Topical Conference on High-Temperature Plasma Diagnostics Proceedings (LA-UR-20-30133) [1]. [1] P. M. Kozlowski, Y. Kim, B. M. Haines, H. F. Robey, T. J. Murphy, H. M. Johns, and T. S. Perry. Use of Computer Vision for analysis of image data sets from high temperature plasma experiments. Review of Scientific Instruments 92, 033532 (2021) https://doi.org/10.1063/5.0040285

Kozlowski, Pawel↗
NASA NTRS1984

Analysis of the quality of image data acquired by the LANDSAT-4 Thematic Mapper and Multispectral Scanners

The geometric quality of TM film and digital products is evaluated by making selective photomeasurements and by measuring the coordinates of known features on both the TM products and map products. These paired observations are related using a standard linear least squares regression approach. Using regression equations and coefficients developed from 225 (TM film product) and 20 (TM digital product) control points, map coordinates of test points are predicted. The residual error vectors and analysis of variance (ANOVA) were performed on the east and north residual using nine image segments (blocks) as treatments. Based on the root mean square error of the 223 (TM film product) and 22 (TM digital product) test points, users of TM data expect the planimetric accuracy of mapped points to be within 91 meters and within 117 meters for the film products, and to be within 12 meters and within 14 meters for the digital products.

Colwell, R. N.↗
DOE OSTI2023

A synthetic Roman Space Telescope High-Latitude Time-Domain Survey: supernovae in the deep field

ABSTRACT NASA will launch the Nancy Grace Roman Space Telescope (hereafter Roman) in the second half of this decade, which will allow for a generation-defining measurement of dark energy through multiple probes, including Type Ia supernovae (SNe Ia). To improve decisions on survey strategy, we have created the first simulations of realistic Roman images that include artificial SNe Ia injected as point sources in the images. Our analysis combines work done on Roman simulations for weak gravitational lensing studies as well as catalogue-level simulations of SN Ia samples. We have created a time series of images over 2 yr containing ∼1050 SNe Ia, covering a 1 deg2 subarea of a planned 5 deg2 deep survey. We have released these images publicly for community use along with input catalogues of all injected sources. We create secondary products from these images by generating coadded images and demonstrating recovery of transient sources using image subtraction. We perform first-use analyses on these images in order to measure galaxy detection efficiency, point source detection efficiency, and host-galaxy association biases. The simulated images can be found here at https://roman.ipac.caltech.edu/sims/SN_Survey_Image_sim.html.

Astronomy & Astrophysics↗
DOE OSTI2022

Multi-frame, ultrafast, x-ray microscope for imaging shockwave dynamics

Inertial confinement fusion (ICF) holds increasing promise as a potential source of abundant, clean energy, but has been impeded by defects such as micro-voids in the ablator layer of the fuel capsules. It is critical to understand how these micro-voids interact with the laser-driven shock waves that compress the fuel pellet. At the Matter in Extreme Conditions (MEC) instrument at the Linac Coherent Light Source (LCLS), we utilized an x-ray pulse train with ns separation, an x-ray microscope, and an ultrafast x-ray imaging (UXI) detector to image shock wave interactions with micro-voids. To minimize the high- and low-frequency variations of the captured images, we incorporated principal component analysis (PCA) and image alignment for flat-field correction. After applying these techniques we generated phase and attenuation maps from a 2D hydrodynamic radiation code (xRAGE), which were used to simulate XPCI images that we qualitatively compare with experimental images, providing a one-to-one comparison for benchmarking material performance. Moreover, we implement a transport-of-intensity (TIE) based method to obtain the average projected mass density (areal density) of our experimental images, yielding insight into how defect-bearing ablator materials alter microstructural feature evolution, material compression, and shock wave propagation on ICF-relevant time scales.

47 OTHER INSTRUMENTATION↗