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At least 1,279 records · Page 71

An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel

Abstract Gaseous fission products from nuclear fission reactions tend to form fission gas bubbles of various shapes and sizes inside nuclear fuel. The behavior of fission gas bubbles dictates nuclear fuel performances, such as fission gas release, grain growth, swelling, and fuel cladding mechanical interaction. Although mechanical understanding of the overall evolution behavior of fission gas bubbles is well known, lacking the quantitative data and high-level correlation between burnup/temperature and microstructure evolution blocks the development of predictive models and reduces the possibility of accelerating the qualification for new fuel forms. Historical characterization of fission gas bubbles in irradiated nuclear fuel relied on a simple threshold method working on low-resolution optical microscopy images. Advanced characterization of fission gas bubbles using scanning electron microscopic images reveals unprecedented details and extensive morphological data, which strains the effectiveness of conventional methods. This paper proposes a hybrid framework, based on digital image processing and deep learning models, to efficiently detect and classify fission gas bubbles from scanning electron microscopic images. The developed bubble annotation tool used a multitask deep learning network that integrates U-Net and ResNet to accomplish instance-level bubble segmentation. With limited annotated data, the model achieves a recall ratio of more than 90%, a leap forward compared to the threshold method. The model has the capability to identify fission gas bubbles with and without lanthanides to better understand the movement of lanthanide fission products and fuel cladding chemical interaction. Lastly, the deep learning model is versatile and applicable to the micro-structure segmentation of similar materials.

36 MATERIALS SCIENCE↗

Impact of remote sensing upon the planning, management, and development of water resources

Principal water resources users were surveyed to determine the impact of remote data streams on hydrologic computer models. Analysis of responses demonstrated that: most water resources effort suitable to remote sensing inputs is conducted through federal agencies or through federally stimulated research; and, most hydrologic models suitable to remote sensing data are federally developed. Computer usage by major water resources users was analyzed to determine the trends of usage and costs for the principal hydrologic users/models. The laws and empirical relationships governing the growth of the data processing loads were described and applied to project the future data loads. Data loads for ERTS CCT image processing were computed and projected through the 1985 era.

Castruccio, P. A.↗

SEASAT views oceans and sea ice with synthetic aperture radar

Fifty-one SEASAT synthetic aperture radar (SAR) images of the oceans and sea ice are presented. Surface and internal waves, the Gulf Stream system and its rings and eddies, the eastern North Pacific, coastal phenomena, bathymetric features, atmospheric phenomena, and ship wakes are represented. Images of arctic pack and shore-fast ice are presented. The characteristics of the SEASAT SAR system and its image are described. Maps showing the area covered, and tables of key orbital information, and listing digitally processed images are provided.

Fu, L. L.↗

Rock type discrimination techniques using Landsat and Seasat image data

Results of a sedimentary rock type discrimination project using Seasat radar and Landsat multispectral image data of the San Rafael Swell, in eastern Utah, are presented, which has the goal of determining the potential contribution of radar image data to Landsat image data for rock type discrimination, particularly when the images are coregistered. The procedure employs several images processing techniques using the Landsat and Seasat data independently, and then both data sets are coregistered. The images are evaluated according to the ease with which contacts can be located and rock units (not just stratigraphically adjacent ones) separated. Results show that of the Landsat images evaluated, the image using a supervised classification scheme is the best for sedimentary rock type discrimination. Of less value, in decreasing order, are color ratio composites, principal components, and the standard color composite. In addition, for rock type discrimination, the black and white Seasat image is less useful than any of the Landsat color images by itself. However, it is found that the incorporation of the surface textural measures made from the Seasat image provides a considerable and worthwhile improvement in rock type discrimination.

Blom, R.↗

An iterative approach to region growing using associative memories

Region growing, often given as a classical example of the recursive control structures used in image processing which are often awkward to implement in hardware where the intent is the segmentation of an image at raster scan rates, is addressed in light of the postulate that any computation which can be performed recursively can be performed easily and efficiently by iteration coupled with association. Attention is given to an algorithm and hardware structure able to perform region labeling iteratively at scan rates. Every pixel is individually labeled with an identifier which signifies the region to which it belongs. Difficulties otherwise requiring recursion are handled by maintaining an equivalence table in hardware transparent to the computer, which reads the labeled pixels. A simulation of the associative memory has demonstrated its effectiveness.

Snyder, W. E.↗

High spectral resolution remote sensing of the land

Spectral remote sensing has been practiced on a large scale since the launch of Landsat 1 in 1972. The limited information contained in this spectrally undersampled data set has led to the development of sophisticated statistical-inferential methods for data analysis. The results are usually limited by the availability of ground truth information. Recent technological developments have made it feasible to create narrow-band, contiguous, spectral image data sets that make possible the identification of surface cover materials based on the complete reflectance spectrum for each picture element. This capability will revolutionize the use of remote sensing data and require new deterministic image processing techniques to extract the full information content from the data. Sensors, based on the concept of imaging spectrometry and the new technology of area array infrared detectors, have been constructed and are candidates for Shuttle and space platform flights.

Goetz, A. F. H.↗

NAECON 87; Proceedings of the IEEE National Aerospace and Electronics Conference, Dayton, OH, May 18-22, 1987. Volumes 1, 2, 3, & 4

The present conference discusses topics in VLSI components and their packaging, signal processing, uses of cartographic data, data transmission, advanced avionics architectures, fiber-optics, information control and display, image processing, airborne radar and fire control, navigation, air data, Kalman filtering, power generation and control, spacecraft power structures, aircraft flying qualities, flight management, fault-tolerant computer architectures, actuation technologies, self-repairing flight control system technology, multivariable control, stability and control methods, and AFTI/F-16 flight test reports. Also discussed are the ADA/JOVIAL language and its applications, software acquisition and testing, advanced software concepts, software management, computer graphics and visual systems softwear, ADA in embedded avionics, 16- and 32-bit architectures, voice interaction applications, human/machine systems analysis, human factors and AI, mental workloads and displays, pilot acceleration protection research, communications system technology, space communications, reliability and maintainability, managerial techniques, engineering management, EM compatibility and nuclear hardening, expert systems, AI language/knowledge representation, expert system implementation, machine vision/optical processing, and advanced AI concepts and architectures.

Avionics↗

Multicomponent Convection Induced by Fronts in the Chlorate-Sulfite Reaction

An application of a new method is presented for the measurement of the temperature profiles of chemical waves propagating through a solution. Using solutions of thermocolor materials, the temperature distribution caused by the heat released in the propagating chlorate oxidation of sulfite was visualized and recorded using digital image processing methods. After calibration, the temperature gradient was calculated from the gray scale value in a digitized image. Extensive multicomponent convection ('fingering') was induced by descending fronts. Only ascending fingers were observed because of the large thermal gradient that suppressed descending ones. The characteristics of the temperature profile were determined as a function of initial sulfite and chlorate concentration, and tube diameter. Unusual behavior was observed when the fronts propagated under conditions of continuously changing diameter in a conical vessel. Fingering occurred periodically in a front descending in a flask with an increasing diameter. However, when a front propagated down in flask whose diameter decreased, no multicomponent convection was observed.

Nagy, Istvan P.↗

New Observations of Subarcsecond Photospheric Bright Points

We have used an interference filter centered at 4305 A within the bandhead of the CH radical (the 'G band') and real-time image selection at the Swedish Vacuum Solar Telescope on La Palma to produce very high contrast images of subarcsecond photospheric bright points at all locations on the solar disk. During the 6 day period of 1993 September 15-20 we observed active region NOAA 7581 from its appearance on the East limb to a near-disk-center position on September 20. A total of 1804 bright points were selected for analysis from the disk center image using feature extraction image processing techniques. The measured Full Width at Half Maximum (FWHM) distribution of the bright points in the image is lognormal with a modal value of 220 km (0 sec .30) and an average value of 250 km (0 sec .35). The smallest measured bright point diameter is 120 km (0 sec .17) and the largest is 600 km (O sec .69). Approximately 60% of the measured bright points are circular (eccentricity approx. 1.0), the average eccentricity is 1.5, and the maximum eccentricity corresponding to filigree in the image is 6.5. The peak contrast of the measured bright points is normally distributed. The contrast distribution variance is much greater than the measurement accuracy, indicating a large spread in intrinsic bright-point contrast. When referenced to an averaged 'quiet-Sun' area in the image, the modal contrast is 29% and the maximum value is 75%; when referenced to an average intergranular lane brightness in the image, the distribution has a modal value of 61% and a maximum of 119%. The bin-averaged contrast of G-band bright points is constant across the entire measured size range. The measured area of the bright points, corrected for pixelation and selection effects, covers about 1.8% of the total image area. Large pores and micropores occupy an additional 2% of the image area, implying a total area fraction of magnetic proxy features in the image of 3.8%. We discuss the implications of this area fraction measurement in the context of previously published measurements which show that typical active region plage has a magnetic filling factor on the order of 10% or greater. The results suggest that in the active region analyzed here, less than 50% of the small-scale magnetic flux tubes are demarcated by visible proxies such as bright points or pores.

Berger, T. E.↗

Science Application Teams

This paper discusses the science application team activities. Science Application team are: (1) Represent the diversity of NASA onboard computing of the future. (2) Drive architecture and system software requirements. (3) Demonstrate the benefit of highly capable computing onboard. (4) Study the birth of the first galaxies. (5) Study formation of stars. (6) Discusses the next generation space telescope hardware/software requirement: image processing and on-board optical calibration. Also discusses gamma ray large area space telescope; orbital thermal imaging spectrometer; solar terrestrial probe program; autonomous Mars rover;fault tolerance and errors.

Source record↗

Document Monitor

The charters of Freedom Monitoring System will periodically assess the physical condition of the U.S. Constitution, Declaration of Independence and Bill of Rights. Although protected in helium filled glass cases, the documents are subject to damage from light vibration and humidity. The photometer is a CCD detector used as the electronic film for the camera system's scanning camera which mechanically scans the document line by line and acquires a series of images, each representing a one square inch portion of the document. Perkin-Elmer Corporation's photometer is capable of detecting changes in contrast, shape or other indicators of degradation with 5 to 10 times the sensitivity of the human eye. A Vicom image processing computer receives the data from the photometer stores it and manipulates it, allowing comparison of electronic images over time to detect changes.

Source record↗

NASA Tech Briefs, December 2009

Topics include: A Deep Space Network Portable Radio Science Receiver; Detecting Phase Boundaries in Hard-Sphere Suspensions; Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery; Very-Long-Distance Remote Hearing and Vibrometry; Using GPS to Detect Imminent Tsunamis; Stream Flow Prediction by Remote Sensing and Genetic Programming; Pilotless Frame Synchronization Using LDPC Code Constraints; Radiometer on a Chip; Measuring Luminescence Lifetime With Help of a DSP; Modulation Based on Probability Density Functions; Ku Telemetry Modulator for Suborbital Vehicles; Photonic Links for High-Performance Arraying of Antennas; Reconfigurable, Bi-Directional Flexfet Level Shifter for Low-Power, Rad-Hard Integration; Hardware-Efficient Monitoring of I/O Signals; Video System for Viewing From a Remote or Windowless Cockpit; Spacesuit Data Display and Management System; IEEE 1394 Hub With Fault Containment; Compact, Miniature MMIC Receiver Modules for an MMIC Array Spectrograph; Waveguide Transition for Submillimeter-Wave MMICs; Magnetic-Field-Tunable Superconducting Rectifier; Bonded Invar Clip Removal Using Foil Heaters; Fabricating Radial Groove Gratings Using Projection Photolithography; Gratings Fabricated on Flat Surfaces and Reproduced on Non-Flat Substrates; Method for Measuring the Volume-Scattering Function of Water; Method of Heating a Foam-Based Catalyst Bed; Small Deflection Energy Analyzer for Energy and Angular Distributions; Polymeric Bladder for Storing Liquid Oxygen; Pyrotechnic Simulator/Stray-Voltage Detector; Inventions Utilizing Microfluidics and Colloidal Particles; RuO2 Thermometer for Ultra-Low Temperatures; Ultra-Compact, High-Resolution LADAR System for 3D Imaging; Dual-Channel Multi-Purpose Telescope; Objective Lens Optimized for Wavefront Delivery, Pupil Imaging, and Pupil Ghosting; CMOS Camera Array With Onboard Memory; Quickly Approximating the Distance Between Two Objects; Processing Images of Craters for Spacecraft Navigation; Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System; Rover Slip Validation and Prediction Algorithm; Safety and Quality Training Simulator; Supply-Chain Optimization Template; Algorithm for Computing Particle/Surface Interactions; Cryogenic Pupil Alignment Test Architecture for Aberrated Pupil Images; and Thermal Transport Model for Heat Sink Design.

Source record↗

In Situ Surface Characterization

Operation of in situ space assets, such as rovers and landers, requires operators to acquire a thorough understanding of the environment surrounding the spacecraft. The following programs help with that understanding by providing higher-level information characterizing the surface, which is not immediately obvious by just looking at the XYZ terrain data. This software suite covers three primary programs: marsuvw, marsrough, and marsslope, and two secondary programs, which together use XYZ data derived from in situ stereo imagery to characterize the surface by determining surface normal, surface roughness, and various aspects of local slope, respectively. These programs all use the Planetary Image Geometry (PIG) library to read mission-specific data files. The programs themselves are completely multimission; all mission dependencies are handled by PIG. The input data consists of images containing XYZ locations as derived by, e.g., marsxyz. The marsuvw program determines surface normals from XYZ data by gathering XYZ points from an area around each pixel and fitting a plane to those points. Outliers are rejected, and various consistency checks are applied. The result shows the orientation of the local surface at each point as a unit vector. The program can be run in two modes: standard, which is typically used for in situ arm work, and slope, which is typically used for rover mobility. The difference is primarily due to optimizations necessary for the larger patch sizes in the slope case. The marsrough program determines surface roughness in a small area around each pixel, which is defined as the maximum peak-to-peak deviation from the plane perpendicular to the surface normal at that pixel. The marsslope program takes a surface normal file as input and derives one of several slope-like outputs from it. The outputs include slope, slope rover direction (a measure of slope radially away from the rover), slope heading, slope magnitude, northerly tilt, and solar energy (compares the slope with the Sun s location at local noon). The marsuvwproj program projects a surface normal onto an arbitrary plane in space, resulting in a normalized 3D vector, which is constrained to lie in the plane. The marsuvwrot program rotates the vectors in a surface normal file, generating a new surface normal file. It also can change coordinate systems for an existing surface normal file. While the algorithms behind this suite are not particularly unique, what makes the programs useful is their integration into the larger in situ image processing system via the PIG library. They work directly with space in situ data, understanding the appropriate image metadata fields and updating them properly. The secondary programs (marsuvwproj, marsuvwrot) were originally developed to deal with anomalous situations on Opportunity and Spirit, respectively, but may have more general applicability.

Deen, Robert G.↗

Advanced Characterization of Rare Earth Elements in Coal Utilization Byproducts

Rare earth elements (REE) in various forms (e.g., crystalline mineral phases; adsorbed/absorbed state on and into organic macerals, neoformed glass from flyash or bottom ash) from domestic feedstocks such as coal deposits to coal utilization byproducts (CUB) have the potential to reduce foreign REE dependence and increase domestic resource security. Characterization is critical for understanding environmental risks related to their fate and transport as well as determining the most practical and economical techniques for concentrating the REE and converting them into chemical stocks for manufacturing. Several complementary electron microscopy (SEM-EDS, EPMA-WDS, FIB-SEM, cathodoluminescence, and XRD) and post image processing techniques were used to understand REE transition from coal to CUB. Sites of interest were identified and imaged and respective elemental x-ray maps acquired and montaged. Pixel classification of SEM imagers was completed using image analysis techniques to quantify the distribution of REE associated features. Quantitative elemental analysis of phases were completed using EMPA-WDS followed by FIB-SEM. The FIB-SEM results were reconstructed into 3D volumes and features of interest (e.g. monazite) were analyzed to determine the structure and volumetric estimation of REEs and thus predict detrital REE phases to ICP-MS results. Trace minerals were identified as pyrite, zircon, REE-phosphates' (monazite, xenotime), and barite within the coal tailings. In CUB, amorphous aluminosilicates, iron oxide cenospheres, and calcium oxides were present; monazite appear to be unaltered and unaffected by the combustion process in these samples. Thermal decomposition may have occurred due to presence of detrital zircon and xenotime and subsequent thin Ca-oxide coating enriched in trace REEs.

Verba, Circe↗

Characterization of Rare Earth Element Minerals in Coal Utilization Byproducts

The United States currently produces over 100 million tons of coal utilization byproducts (CUB) per year in the form of fly ash, bottom ash, slag, and flue gas (American Coal Ash Association (ACCA), 2015). But this “waste material” also contains potentially useful levels of rare earth elements (REE). Rare earth elements are crucial for many existing and emerging technologies, but the U.S. lacks a domestic, sustainable REE source. Our project explored the possibility of developing a supply of REEs for U.S. technologies by extracting REEs from CUBs. This work offers the potential to reduce our dependence on other countries for supply of these critical elements (NETL, REE 2016 Project Portfolio). Geologic and diagenetic history, industrial preparation methods, and the specific combustion process all play major roles in the composition of CUB. During combustion, inorganic mineral phases of coal particles are fluidized at temperatures higher than 1400oC, so inorganic mineral materials are oxidized, fused, disintegrated, or agglomerated into larger spherical and amorphous (non-crystalline) particles. The original mineralogy of the coal-containing rock and heating/cooling of the material significantly affects the composition and morphology of the particles in the combustion byproduct (Kutchko and Kim, 2006). Thus, different types of coal/refuse/ash must be characterized to better understand mineral evolution during the combustion process. Our research focused on developing a working model to address how REE minerals behave during the combustion process: this research should help determine the most effective engineering methods for extracting REEs from CUBs. We used multimodal imaging and image processing techniques to characterize six rock and ash samples from different coal power plants with respect to morphology, grain size, presence of mineral phases, and elemental composition. The results of these characterization activities provided thresholds for realizing the occurrence of REE mineral phases in CUB and allowed us to calculate structural and volumetric estimates of REE. Collectively, the rock and coal ash samples contained minerals such as quartz, kaolinite, muscovite/illite, iron oxide (as hematite or magnetite), mullite, and clinochlore. Trace minerals included pyrite, zircon, siderite, rutile, diopside, foresterite, gypsum, and barite. We identified REE phosphate minerals monazite (Ce,La,Nd,Th)(PO 4 ,SiO 4 ), xenotime (YPO 4 ,SiO 4 ), and apatite (Ca 5 (PO 4 ) 3 (F,Cl,OH) via SEM and electron microprobe analysis: these materials generally occurred as 1-10 μm-long crystals in the rock and ash samples. As has been shown in other studies, amorphous material-aluminosilicate glass or iron oxyhydroxide-are the major components of coal fly and bottom ash. Trace amounts of amorphous calcium oxide and mixed element (e.g., Al-Si-Ca-Fe) slag are also present. Quartz, mullite, hematite, and magnetite are the crystalline phases present. We found that REEs are present as monomineralic grains dispersed within the ash, as well as fused to or encapsulated by amorphous aluminosilicate glass particles. Monazite and xenotime have relatively high melting points (>1800 °C) compared to typical combustion temperatures; our observations indicate that the REE-phosphates, which presumably contribute a large percentage of REE to the bulk ash REE pool, as measured by mass spectroscopy, are largely unaltered by the combustion. Our study shows that conventional coal combustion processes sequester REE minerals into aluminosilicate glass phases, which presents a new engineering challenge for extracting REE from coal ash. The characterization work summarized in this report provides a semi-quantitative assessments of REE in coal-containing rock and CUB. The data we obtained from 2- and 3-D imaging, elemental mapping, volumetric estimates, and advanced high-resolution pixel classification successfully identified the different mineral phases present in CUB. Further, our characterization results can guide techniques for extracting REEs from CUB, or other geologic and engineered materials. Whilst, interpretations will inform future REE separation and extraction techniques and technologies practical for commercial utilization of combustion byproducts generated by power plants.

01 COAL, LIGNITE, AND PEAT↗

A sampling procedure to guide the collection of narrow-band, high-resolution spatially and spectrally representative reflectance data

A multistage sampling procedure using image processing, geographical information systems, and analytical photogrammetry is presented which can be used to guide the collection of representative, high-resolution spectra and discrete reflectance targets for future satellite sensors. The procedure is general and can be adapted to characterize areas as small as minor watersheds and as large as multistate regions. Beginning with a user-determined study area, successive reductions in size and spectral variation are performed using image analysis techniques on data from the Multispectral Scanner, orbital and simulated Thematic Mapper, low altitude photography synchronized with the simulator, and associated digital data. An integrated image-based geographical information system supports processing requirements.

Brand, R. R.↗

Highly sensitive 2D X-ray absorption spectroscopy via physics informed machine learning

Abstract Improving the spatial and spectral resolution of 2D X-ray near-edge absorption structure (XANES) has been a decade-long pursuit to probe local chemical reactions at the nanoscale. However, the poor signal-to-noise ratio in the measured images poses significant challenges in quantitative analysis, especially when the element of interest is at a low concentration. In this work, we developed a post-imaging processing method using deep neural network to reliably improve the signal-to-noise ratio in the XANES images. The proposed neural network model could be trained to adapt to new datasets by incorporating the physical features inherent in the latent space of the XANES images and self-supervised to detect new features in the images and achieve self-consistency. Two examples are presented in this work to illustrate the model’s robustness in determining the valence states of Ni and Co in the LiNi x Mn y Co 1-x-y O 2 systems with high confidence.

36 MATERIALS SCIENCE↗

Image registration for accurate electrode deformation analysis in operando microscopy of battery materials

Operando imaging techniques have become increasingly valuable in both battery research and manufacturing. However, the reliability of these methods can be compromised by instabilities in the imaging setup and operando cells, particularly when utilizing high-resolution imaging systems. The acquired imaging data often include features arising from both undesirable system vibrations and drift, as well as the scientifically relevant deformations occurring in the battery sample during cell operation. For meaningful analysis, it is crucial to distinguish and separately evaluate these two factors. To address these challenges, we employ a suite of advanced image-processing techniques. These include fast Fourier transform analysis in the frequency domain, power spectrum-based assessments for image quality, as well as rigid and non-rigid image-registration methods. These techniques allow us to identify and exclude blurred images, correct for displacements caused by motor vibrations and sample holder drift and, thus, prevent unwanted image artifacts from affecting subsequent analyses and interpretations. Additionally, we apply optical flow analysis to track the dynamic deformation of battery electrode materials during electrochemical cycling. This enables us to observe and quantify the evolving mechanical responses of the electrodes, offering deeper insights into battery degradation. Together, these methods ensure more accurate image analysis and enhance our understanding of the chemomechanical interplay in battery performance and longevity.

Sun, Tianxiao↗