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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Registration of a synthetic aperture radar image to Thematic Mapper imagery for remote sensing applications

Multiple Thematic Mapper multitemporal acquisitions from Landsat and one synthetic-aperture radar acquisition from Seasat have been precisely registered using Johnson Space Center registration processors. The registered images have been output in the Universal Transverse Mercator projection. The procedure to accomplish such disparate data processing tasks and the registration accuracy evaluation are discussed.

Yao, S. S.↗
NASA NTRS1998

Neutral Networks for Subpixel Classification of Multispectral Images

In this work, the implementation and use of AVHRR (Advanced Very High Resolution Radiometer) images for subpixel analysis is studied. The work consists of two parts, the first is making training data, the second is using the training data to design a neural net subpixel analyzer. Most work on subpixel analysis has been done with images with more spectral bands. AVHRR images were chosen because of their easy acquisition, and because the five spectral bands allow investigation into the development of training data. The first step in subpixel analysis is the development of training data. This consists of image to be classified, and the classification of each pixel. In order to do the classification, a high spatial resolution image is typically needed in order to manually create a classified image. It is difficult to have both the image of interest, and a high spatial resolution image of the same area taken at the same time. Thus it was studied whether a subsampled image taken from the image of interest could serve as the training data. Statistical work has been done showing the unusefulness of this approach. In the second part of the analysis, a feedforward neural net was trained and used to classify the AVHRR images. Results of these tests, comparing the neural net with typical statistical based schemes are shown.

Figueroa, Ricardo R.↗
DOE OSTI2021

Striving to translate shale physics across ten orders of magnitude: What have we learned?

Shales will play an important role in the successful transition of energy from fossil-based resources to renewables in the coming decades. Aside from being a significant source of low-carbon intensity fuels, like natural gas, they also serve as geologic seals of subsurface formations that may be used to isolate nuclear waste, sequester CO 2 , or store intermittent energy (e.g., solar hydrogen). Despite their importance, shales pose significant engineering and environmental challenges due to their nanoporous structure and extreme heterogeneity that spans at least ~10 orders of magnitude in spatial scale. Two challenges inhibit a system-level understanding: (1) the physics of fluid flow and phase behavior in shales are poorly understood due to the dominant molecular interactions between minerals and fluids under confinement, and (2) the apparent lack of scale separation that prevents a reliable (closed) description of the physics at any single scale of observation. In this review, we focus on the latter issue and discuss scale translation, which in its broadest sense is transforming data or simulations from one spatiotemporal scale to another. While effective scale translation is not exclusive to shales, but all geologic porous media, the need for it is especially acute in shales given their high degree of heterogeneity. Classical theories like homogenization, while indispensable, fail when scales are not separated. Other methods, like numerical upscaling, scale-translate in only one direction: small to large, but not the reverse, called downscaling. However, the confluence of advances in three areas are bringing challenging problems such as shales within reach: increased computational power and scalable algorithms; high-resolution imaging and multi-modal data acquisition; and machine learning to process massive amounts of data. While these advances equip geoscientists with a wide array of experimental and computational tools, no individual tool can probe the entire gamut of heterogeneity in shales. Their effective use, therefore, requires an ability to bridge between various data types obtained at different scales. The aim of this review is to present a coherent account of computational and experimental methods that may be used to achieve just that, i.e., to perform scale translation. We provide a broader definition of scale translation, one that transcends classical homogenization and upscaling methods, but is consistent with them and accommodates notions like downscaling and data translation. After a brief introduction to homogenization, we review hybrid methods, numerical upscaling and its recent extensions, multiscale computing, high-resolution imaging, and machine learning. We place particular emphasis on multiscale computing and propose an algorithmic framework to bridge between the pore (micro) and Darcy (macro) scales. Throughout the paper, we draw comparisons between the various methods and highlight their (often hidden) similarities, differences, benefits, and pitfalls. We finally conclude with two case studies on shales that exemplify some of the methods presented.

58 GEOSCIENCES↗
DOE OSTI2024

Deep learning-driven super-resolution in Raman hyperspectral imaging: Efficient high-resolution reconstruction from low-resolution data

Deep learning (DL) has become an indispensable tool in hyperspectral data analysis, automatically extracting valuable features from complex, high-dimensional datasets. Super-resolution reconstruction, an essential aspect of hyperspectral data, involves enhancing spatial resolution, particularly relevant to low-resolution hyperspectral data. Yet, the pursuit of super-resolution in hyperspectral analysis is fraught with challenges, including acquiring ground truth high-resolution data for training, generalization, and scalability. The pressing issue of extended spectral acquisition times, notably for high-resolution scans, is a significant roadblock in hyperspectral imaging. Super-resolution methods offer a promising solution by providing higher spatial resolution data to expedite data collection and yield more efficient outcomes. This paper delves into a practical application of these concepts using Raman imaging, where spectral acquisition times can be prohibitively long. In this context, DL-based super-resolution models demonstrate their efficacy by predicting and reconstructing high-resolution Raman data from low-resolution input, eliminating the need for resource-intensive high-resolution scans. While previous work often relied on substantial high-resolution datasets, this study showcases the ability to achieve similar outcomes even with limited data, presenting a more practical and cost-effective approach. In conclusion, the results offer a glimpse into the transformative potential of this technology to streamline hyperspectral imaging applications by saving valuable time and resources through the successful generation of high-resolution data from low-resolution inputs.

42 ENGINEERING↗
DOE OSTI2021

Five-second STEM dislocation tomography for 300 nm thick specimen assisted by deep-learning-based noise filtering

Scanning transmission electron microscopy (STEM) is suitable for visualizing the inside of a relatively thick specimen than the conventional transmission electron microscopy, whose resolution is limited by the chromatic aberration of image forming lenses, and thus, the STEM mode has been employed frequently for computed electron tomography based three-dimensional (3D) structural characterization and combined with analytical methods such as annular dark field imaging or spectroscopies. However, the image quality of STEM is severely suffered by noise or artifacts especially when rapid imaging, in the order of millisecond per frame or faster, is pursued. Here we demonstrate a deep-learning-assisted rapid STEM tomography, which visualizes 3D dislocation arrangement only within five-second acquisition of all the tilt-series images even in a 300 nm thick steel specimen. The developed method offers a new platform for various in situ or operando 3D microanalyses in which dealing with relatively thick specimens or covering media like liquid cells are required.

47 OTHER INSTRUMENTATION↗
NASA NTRS2003

Cellular Oxygen and Nutrient Sensing in Microgravity Using Time-Resolved Fluorescence Microscopy

Oxygen and nutrient sensing is fundamental to the understanding of cell growth and metabolism. This requires identification of optical probes and suitable detection technology without complex calibration procedures. Under this project Microcosm developed an experimental technique that allows for simultaneous imaging of intra- and inter-cellular events. The technique consists of frequency-domain Fluorescence Lifetime Imaging Microscopy (FLIM), a set of identified oxygen and pH probes, and methods for fabrication of microsensors. Specifications for electronic and optical components of FLIM instrumentation are provided. Hardware and software were developed for data acquisition and analysis. Principles, procedures, and representative images are demonstrated. Suitable lifetime sensitive oxygen, pH, and glucose probes for intra- and extra-cellular measurements of analyte concentrations have been identified and tested. Lifetime sensing and imaging have been performed using PBS buffer, culture media, and yeast cells as a model systems. Spectral specifications, calibration curves, and probes availability are also provided in the report.

Szmacinski, Henryk↗
NASA NTRS1978

Analysis of the classification of US and Canadian intensive test sites using the Image 100 hybrid classification system

The author has identified the following significant results. Labeling of wheat rather than total grains, particularly with only one acquisition, led to significant overestimates in some segments. The Image-100 software and procedures were written to facilitate classification of the LACIE segments but were not designed to record data for later accuracy assessment. A much better evaluation would have been possible if accuracy assessment data had been collected following each satisfactory classification.

Hocutt, W. T.↗
NASA NTRS1984

Investigation of TM Band-to-band Registration Using the JSC Registration Processor

The JSC registration processor performs scene-to-scene (or band-to-band) correlation based on edge images. The edge images are derived from a percentage of the edge pixels calculated from the raw scene data, excluding clouds and other extraneous data in the scene. Correlations are performed on patches (blocks) of the edge images, and the correlation peak location in each patch is estimated iteratively to fractional pixel location accuracy. Peak offset locations from all patches over the scene are then considered together, and a variety of tests are made to weed out outliers and other inconsistencies before a distortion model is assumed. Thus, the correlation peak offset locations in each patch indicate quantitatively how well the two TM bands register to each other over that patch of scene data. The average of these offsets indicate the overall accuracies of the band-to-band registration. The registration processor was also used to register one acquisition to another acquisition of multitemporal TM data acquired over the same ground track. Band 4 images from both acquisitions were correlated and an rms error of a fraction of a pixel was routinely obtained.

Yao, S. S.↗
DOE OSTI2022

Simple through-plane spatial filter for 2D MRI projections

A simple spatial filter for 2D projection MR imaging is introduced. It works in the third (unresolved) direction to eliminate uniform or slowly varying interfering background signals. A constant amplitude gradient pulse in the unresolved direction is applied at the same time as the usual phase encode gradient during 2D acquisition. The filter is demonstrated for root imaging in soil, where background soil water signals can be troublesome. The filter suppresses the soil water signal while preserving the desired signal of plant roots. Fundamental to the operation of the filter is that the roots are sparse in the image domain, meaning there are relatively few pixels with multiple roots present. Here, the performance of the through-plane filter is demonstrated and compares favorably to more conventional in-plane spatial filtering.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Megahertz-rate shock-wave distortion cancellation via phase conjugate digital in-line holography

Abstract Holography is a powerful tool for three-dimensional imaging. However, in explosive, supersonic, hypersonic, cavitating, or ionizing environments, shock-waves and density gradients impart phase distortions that obscure objects in the field-of-view. Capturing time-resolved information in these environments also requires ultra-high-speed acquisition. To reduce phase distortions and increase imaging rates, we introduce an ultra-high-speed phase conjugate digital in-line holography (PCDIH) technique. In this concept, a coherent beam passes through the shock-wave distortion, reflects off a phase conjugate mirror, and propagates back through the shock-wave, thereby minimizing imaging distortions from phase delays. By implementing the method using a pulse-burst laser setup at up to 5 million-frames-per-second, time-resolved holograms of ultra-fast events are now possible. This technique is applied for holographic imaging through laser-spark plasma-generated shock-waves and to enable three-dimensional tracking of explosively generated hypersonic fragments. Simulations further advance our understanding of physical processes and experiments demonstrate ultra-high-speed PCDIH techniques for capturing dynamics.

Science & Technology - Other Topics↗
DOE OSTI2025

The LSST Camera (LSSTCam)

The LSST Camera is the sole instrument for the NSF-DOE Vera C. Rubin Observatory and consists of a 3.2 gigapixel focal plane mosaic with in-vacuum controllers, dedicated guider and wavefront CCDs, a three-element corrector whose largest lens is 1.55m in diameter, six optical interference filters covering a 320-1050nm band pass with an out-of-plane filter exchange mechanism, and camera slow control and data acquisition systems capable of digitizing each image in 2 seconds.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1971

The automation of the stellar proper motion survey

A microdensitometer, scanning pairs of star plates of identical areas of the sky taken a decade apart, is coupled to a magnetic tape unit through a data acquisition system. This system performs an image density threshold level selection for each plate and a buffer memory system to smooth the data flow as well as analog and digital display controls. The data from the tape are processed later by a large scale high speed computer which reconstructs the scanned images, discovers, measures, and documents stellar proper motions by precise comparison of corresponding areas of the two star plates to detect those images which have moved at least 0.10 seconds annually in the time interval between the exposures.

Newcomb, J. S.↗
NASA NTRS1979

Geologic application of thermal inertia imaging using HCMM data

The author has identified the following significant results. The day infrared and visible HCMM satellite data for Death Valley taken on 31 May 1978 were compared with aircraft data of the same area taken in March of the same year. In the visible image, it is possible to note the drying of the valley floor during the two month period between acquisition of the two data sets. On the IR image however, the valley floor remains cool, probably indicating that while the standing water has disappeared, the floor is still moist.

Paley, H. N.↗
NASA NTRS1981

STARPROBE: A design study for an X-ray imaging instrument

The primary objective of the X-ray imaging telescope on STARPROBE is the acquisition of very high spacial resolution observations during the spacecraft's perihelion passage. Design parameters, telescope prefilters, and structural and thermal analyses of the equipment are described and discussed. It is believed that the spatial resolution of the information recorded by the baseline design would be at least a factor of 10 better than can be reasonably expected from Earth orbit. Thermal models used in the study are also discussed.

Source record↗
NASA NTRS1982

Neotectonics of the San Andreas Fault system, basin and range province juncture

The development, active processes, and tectonic interplay of the southern San Andreas fault system and the basin and range province were studied. The study consist of data acquisition and evaluation, technique development, and image interpretation and mapping. Potentially significant geologic findings are discussed.

Estes, J. E.↗
NASA NTRS1986

Calibration and analysis for a 0.53 micron incoherent Doppler lidar

A ground based, prototype Doppler lidar is being developed to demonstrate the feasibility of an incoherent detection technique to remotely measure winds in the atmosphere. This prototype system consists of a narrow band, single frequency laser transmitter, a high resolution, Fabry-Perot Interferometer utilizing a multichannel image plane detector and a data acquisition system. A description of the prototype Doppler lidar hardware is given in Rosenberg and Sroga, 1985. The calibration and analysis procedures for this system is described. Preliminary results from data obtained with the system pointed vertically is presented.

Sroga, J.↗
NASA NTRS1987

1986 Nuclear Science Symposium, 33rd, and 1986 Symposium on Nuclear Power Systems, 18th, Washington, DC, Oct. 29-31, 1986, Proceedings

Papers are presented on space, low-energy physics, and general nuclear science instrumentations. Topics discussed include data acquisition systems and circuits, nuclear medicine imaging and tomography, and nuclear radiation detectors. Consideration is given to high-energy physics instrumentation, reactor systems and safeguards, health physics instrumentation, and nuclear power systems.

Stubblefield, F. W.↗