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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Panel-Segmentation [SWR-21-18]

Panel-Segmentation contains the scripts for automated metadata extraction of solar PV installations, using satellite imagery coupled with computer vision techniques. In this package, the user can perform the following actions: *Automatically generate a satellite image using a set of lat-long coordinates, and a Google Maps API key. Users would need to set up a Google Cloud account and get a Maps Static API key. Please refer to Setting Up Google Maps Static API Key section for this process. *Perform image segmentation on the satellite image, to locate the solar array(s) in the image on a pixel-by-pixel basis, using an image segmentation model (panel_detection_model.pth). Get classification of the installation (rooftop, ground mounted fixed-tilt or tracking, carport, etc). *Perform azimuth estimation on each solar array cluster in the masked image. *Detect solar panels and get its latitude, longitude, and address within a geographic bounding box through the SOL-Searcher Pipeline. *Detect and calculate hurricane damage on solar installations given pre-hurricane and post-hurricane satellite imagery through the Hurricane Detection Pipeline. *Detect and calculate hail damage on solar installations given satellite imagery through the Hail Detection pipeline. *Convert NOAA MESH (Maximum Estimated Size of Hail) grib2 files into kml or geojson files. *Estimate tilt and azimuth of a solar array by processing USGS LiDAR data for the array’s location.

Edun, Ayobami↗
DOE OSTI2022

Accelerating shared file checkpoint with local burst buffers

A data management system and method for accelerating shared file checkpointing. Written application data is aggregated in an application data file created in a local burst buffer memory at a compute node, and an associated data mapping built index to maintain information related to the offsets into a shared file at which segments of the application data is to be stored in a parallel file system, and where in the buffer those segments are located. The node asynchronously transfers a data file containing the application data and the associated data mapping index to a file server for shared file storage. The data management system and method further accelerates shared file checkpointing in which a shared file, together with a map file that specifies how the shared file is to be distributed, is asynchronously transferred to local burst buffer memories at the nodes to accelerate reading of the shared file.

Gooding, Thomas↗
NASA NTRS1990

Eastern Aphrodite Terra on Venus - Characteristics, structure, and mode of origin

Altimetric and radar-image cross-strike discontinuities (CSDs) are found to cut across the nearly east-west strike of Eastern Aphrodite (EA) Terra, dividing or segmenting it into offset domains. Each of these domains is characterized by a discontinuous central chasma or trough. These features have been mapped in the altimetric and radar image data of EA on the basis of abrupt termination of riftlike central chasma, offset, and segmentation of the center highlands, and radar image discontinuities previously mapped in Western Aphrodite in terms of length, orientation, and influence on the central highlands and adjacent lowlands. It is concluded that EA displays a variety of geological and geophysical characteristics similar to those occuring at divergent boundaries. The surface map characteristics are the result of a great horizontal motion of the crust diverging from a well-defined linear region, a process that can occur whether the surface is part of a thick and strong plate detached from mantle convection or part of a thin and weak layer attached to a deep convective limb.

Crumpler, L. S.↗
NASA NTRS2004

Incoming Metrology of Segmented X-Ray Mandrels at MSFC

The Constellation-X Spectroscopy X-ray telescope (SXT) is designed to be built from X-ray optic segments. The X-ray segments will be fabricated from the segmented mandrels using a replication process. The purpose of the incoming metrology is to map the surface of the mandrels, so the performance of the X-ray optics produced can be predicted. Three Constellation-X segmented mandrels have been delivered to MSFC for incoming metrology. The segmented mandrels are 30-degree sections of a cylindrical surface and have diameters of 1.0 m, 1.2 m and 1.6 m. The maximum dimensions of the optical surface are 1.0 m axial length and 0.5 m azimuthal segment length. The metrology of the mandrels consists of the measurement of their slope differences, roundness, absolute radius, axial profile and microroughness. Accuracy goals for each type of measurement and the accuracy of the instruments used for the measurements will be discussed. The results of the mandrel metrology together with the performance predictions will be presented.

Gubarev, Mikhail↗
NASA NTRS1991

A tool for interactive exploration of a hierarchical segmentation

Hierarchical segmentation is discussed as a form of region growing in which the sequence of merges is controlled by a 'best merge first' principle, and a record of the region merging sequence is often retained for later analysis. In the author's massively parallel implementation of hierarchical segmentation, which he calls iterative parallel region growing (IPRG), a set of directional edge maps are used to store the region merging sequence information. An iteractive tool is described that allows an analyst to fully explore a hierarchical segmentation, potentially producing an image segmentation that is a combination of segmentations produced at several different iterations of the IPRG algorithm. A potential method for automatically producing such segmentations is also discussed.

Tilton, James C.↗
NASA NTRS1991

Caldera-structure relationships in Kenya - Observations from satellite data

Maps were constructed showing lineaments displayed on four Landsat MSS images, to study volcanic-tectonic relationships in the Kenya segment of the Gregory or eastern sector of the East African rift system. Many of the mapped lineaments correlated well with fractures shown on geological maps. Selected lineaments, transverse to the rift trend, could be extrapolated to intersect rift faults at locations correlative with the locations of Kenya's seven volcanic calderas. The volcano-genetic difference between these intersections vs. similar intersections having no obvious relationship to any type of volcanic vent is not yet understood.

Blodget, Herbert W.↗
DOE OSTI2019

Pore system characterization of organic-rich shales using nanoscale-resolution 3D imaging

The Vaca Muerta Shale in Argentina is the first signifcant commercial shale oil/gas play outside of North America. High-resolution 2D/3D imaging of shale rocks for the purpose of establishing their mineralogy, total, and connected porosities has become more and more sophisticated. In this paper, nanoscale-resolution focused ion beam (FIB)-scanning electron microscopy (SEM) nano-tomography was used to obtain images of pore structures within two organic-rich regions of interest (ROIs), selected based on correlative SEM and automated mineralogy maps. Advanced machine learning classification tools were used to segment the images and assign porosities and other components. Pore size distribution and pore connectivity analyzes revealed that about 95% of all the pores, present within the two ROIs, had a diameter of less than approximately 75 nm, and that most of these pores were poorly connected. In a similar fashion, the flow rate distribution analysis showed that pores with diameters of about 150-330 nm contributed to over 50% of the flow capacity of the connected pore systems. These results suggest that although most of the pores typically found in shales have pore diameter smaller than about 100 nm, most of the hydrocarbon production may be carried by a relatively small number of larger connected pores with pore diameter greater than about 150 nm. This research implies that a large portion of the organic-hosted pores (with diameter typically smaller than about 100 nm) may not provide permeable flow pathways for the oil and/or gas migration, and hence may have very little contribution to the hydrocarbon production.

58 GEOSCIENCES↗
DOE OSTI2023

Genome analyses reveal population structure and a purple stigma color gene candidate in finger millet

Finger millet is a key food security crop widely grown in eastern Africa, India and Nepal. Long considered a ‘poor man’s crop’, finger millet has regained attention over the past decade for its climate resilience and the nutritional qualities of its grain. To bring finger millet breeding into the 21 st century, here we present the assembly and annotation of a chromosome-scale reference genome. We show that this ~1.3 million years old allotetraploid has a high level of homoeologous gene retention and lacks subgenome dominance. Population structure is mainly driven by the differential presence of large wild segments in the pericentromeric regions of several chromosomes. Trait mapping, followed by variant analysis of gene candidates, reveals that loss of purple coloration of anthers and stigma is associated with loss-of-function mutations in the finger millet orthologs of the maize R1/B1 and Arabidopsis GL3/EGL3 anthocyanin regulatory genes. Proanthocyanidin production in seed is not affected by these gene knockouts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Graph-learning approach to combine multiresolution seismic velocity models

SUMMARY The resolution of velocity models obtained by tomography varies due to multiple factors and variables, such as the inversion approach, ray coverage, data quality, etc. Combining velocity models with different resolutions can enable more accurate ground motion simulations. Toward this goal, we present a novel methodology to fuse multiresolution seismic velocity maps with probabilistic graphical models (PGMs). The PGMs provide segmentation results, corresponding to various velocity intervals, in seismic velocity models with different resolutions. Further, by considering physical information (such as ray path density), we introduce physics-informed probabilistic graphical models (PIPGMs). These models provide data-driven relations between subdomains with low (LR) and high (HR) resolutions. Transferring (segmented) distribution information from the HR regions enhances the details in the LR regions by solving a maximum likelihood problem with prior knowledge from HR models. When updating areas bordering HR and LR regions, a patch-scanning policy is adopted to consider local patterns and avoid sharp boundaries. To evaluate the efficacy of the proposed PGM fusion method, we tested the fusion approach on both a synthetic checkerboard model and a fault zone structure imaged from the 2019 Ridgecrest, CA, earthquake sequence. The Ridgecrest fault zone image consists of a shallow (top 1 km) high-resolution shear-wave velocity model obtained from ambient noise tomography, which is embedded into the coarser Statewide California Earthquake Center Community Velocity Model version S4.26-M01. The model efficacy is underscored by the deviation between observed and calculated traveltimes along the boundaries between HR and LR regions, 38 per cent less than obtained by conventional Gaussian interpolation. The proposed PGM fusion method can merge any gridded multiresolution velocity model, a valuable tool for computational seismology and ground motion estimation.

Geochemistry & Geophysics↗
NASA NTRS1986

Collector-Output Analysis Program

Collector-Output Analysis Program (COAP) programmer's aid for analyzing output produced by UNIVAC collector (MAP processor). COAP developed to aid in design of segmentation structures for programs with large memory requirements and numerous elements but of value in understanding relationships among components of any program. Crossreference indexes and supplemental information produced. COAP written in FORTRAN 77.

Glandorf, D. R.↗
NASA NTRS2004

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include real-time, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identity other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

egomotion↗
NASA NTRS2004

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include realtime, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify & other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

egomotion↗
NASA NTRS2004

Real-time Detection of Moving Objects from Moving Vehicles Using Dense Stereo and Optical Flow

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time. dense stereo system to include realtime. dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop. computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

moving object detection↗
DOE OSTI2024

Datasets and U-Net Model for "A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma"

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

Artificial Intelligence↗
DOE OSTI2024

Integrable symplectic maps with a polygon tessellation

Identifying integrable dynamics remains a formidable challenge, and despite centuries of research, only a handful of examples are known to date. In this article, we explore a distinct form of area-preserving (symplectic) mappings derived from the stroboscopic Poincaré cross section of a kicked rotator—an oscillator subjected to an external force periodically switched on in short pulses. The significance of this class of problems extends to various applications in physics and mathematics, including particle accelerators, crystallography, and studies of chaos. Notably, Suris's theorem constrains the integrability within this category of mappings, outlining potential scenarios with analytic invariants of motion. In this paper, we challenge the assumption of the analyticity of the invariant by exploring piecewise linear transformations on a torus ( T 2 ) and associated systems on the plane ( R 2 ), incorporating arithmetic quasiperiodicity and discontinuities. Introducing a new automated technique, we discovered previously unknown scenarios featuring polygonal invariants that form perfect tessellations and, moreover, fibrations of the plane or torus. This work reveals a novel category of planar tilings characterized by discrete symmetries that emerge from the invertibility of transformations and are intrinsically linked to the presence of integrability. Our algorithm relies on the analysis of the Poincaré rotation number and its piecewise monotonic nature for integrable cases, contrasting with the noisy behavior in the case of chaos, thereby allowing for clear separation. Some of the newly discovered systems exhibit the peculiar behavior of “integrable diffusion,” characterized by infinite and quasirandom hopping between tiles while being confined to a set of invariant segments. Finally, through the implementation of a smoothening procedure, all mappings can be generalized to quasi-integrable scenarios with suppressed volume occupied by chaotic trajectories, thereby opening doors to potential practical applications. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Unsupervised Segmentation and Clustering Workflow for Efficient Processing of 4D-STEM and 5D-STEM Data

Four-dimensional scanning transmission electron microscopy (4D-STEM) enables mapping of diffraction information with nanometer-scale spatial resolution, offering detailed insight into local structure, orientation, and strain. However, as data dimensionality and sampling density increase, particularly for in situ scanning diffraction experiments (5D-STEM), robust segmentation of structurally consistent behavior across sequential measurements becomes essential for efficient and physically meaningful analysis. Here, we introduce a clustering framework that identifies crystallographically distinct domains from 4D-STEM datasets. By using local diffraction-pattern similarity as a metric, the method extracts closed contours delineating spatially contiguous regions. This approach produces cluster-averaged diffraction patterns that improve signal quality while reducing data volume by orders of magnitude, enabling rapid and accurate orientation, phase, and strain mapping. We demonstrate the applicability of this approach to in situ liquid-cell 4D-STEM data of gold nanoparticle growth. Our method provides a scalable and generalizable route for spatially coherent segmentation, data compression, and quantitative structure–strain mapping across diverse 4D-STEM modalities. The full analysis code and example workflows are publicly available to support reproducibility and reuse.

4D-STEM↗
NASA NTRS2010

Analysis of Ancient Fluvial Patterns on the Surface of Mars

This project involves the study of ancient fluvial patterns on the surface of Mars, including raised curvilinear features (RCFs) and negative relief channels. It requires the use of geological images provided by the Mars Reconnaissance Orbiter to determine how water shaped the surface of Mars in the form of rivers, lakes and/or oceans approximately 3.5 billion years ago, during the Noachian period. The role of the intern is to examine the images and record the corresponding measurements of ancient river systems in an Excel spreadsheet to assist in determining the Noachian water cycle on Mars. Resources used to make these measurements include the Arena software, hand-drawn sketch maps, Microsoft Word, Microsoft Excel and the images provided by the Mars Reconnaissance Orbiter. The Context Imager (CTX) returns black and white images at a resolution of six meters per pixel. The camera can take images with a width of 30 km and a length of 160 km. Seventeen images were observed in total. Images are analyzed and notes are taken concerning their terminal deposits, stream ordering and drainage pattern. The Arena software is utilized to make the images more visible by allowing control of contrast and magnification. Once the image is adjusted, measurements: length, average width, drainage basin area, sinuous ridge area are recorded, at a magnification of one, through using the line segment and polygon tools. After an image has been analyzed and measured, a sketch map is drawn in order to clearly identify the various segments, basins and terminal deposits the intern observed. Observations are used to further classify the fluvial patterns; their drainage pattern is defined as dendritic, parallel, trellis, rectangular, radial, centripetal, deranged or discordant. Once observational notes are completed, mathematical relations are used to determine drainage density, stream frequency, theoretic basin area and sinuosity index. These data will be added to a larger data set that will yield a comprehensive view of early Mars drainage systems. The data obtained from the work conducted will be used to characterize the nature and behavior of water on the surface of Mars. Thorough understanding of the Martian water cycle will serve as biologically significant information. Through working on this project, I acquired insight into the study of planet Mars, and skills in the Arena software as well as the organization of a vast amount of data.

Jethani, Henna↗
DOE OSTI2023

Transforming microseismic clouds into near real-time visualization of the growing hydraulic fracture

SUMMARY Microseismic observations during unconventional reservoir stimulation are typically seen as a proxy for clusters of hydraulic fractures and the extent of the stimulated reservoir. Such straightforward interpretation is often misleading and fails to provide a physically reasonable image of the fracturing process. This paper demonstrates the application of a physics-based machine learning algorithm which enables a rapid and accurate fracture mapping from the microseismic data. Our training and validation data set relies on a history-matched geomechanical modelling workflow implemented in GEOS software for the Hydraulic Fracturing Test Site 1 (HFTS-1) project. For this study we augmented the simulated fracture growth through geostatistical modelling of induced seismicity, so that the synthetic microseismic catalogue matches the main statistical properties of the field observations. We formulated the problem of mapping the actual fracture in the clutter of events to parallel common video segmentation workflows: several past video frames (microseismic density snapshots) are passed through a deep convolutional network to classify whether a given voxel is associated with a fracture or intact rock. We found that for accurate fracture mapping, the network’s input and architecture must be augmented to incorporate the fluid injection parameters (pressure, rate, concentration of proppant, and location of the perforation within the cluster). The error rate for the network reached as little as 10 per cent of the fracture area, while a conventional microseismic interpretation approach yielded ∼300 per cent. Our approach also yields must faster predictions than conventional methods (minutes instead of weeks), and could enable engineers to make rapid decisions regarding engineering parameters (pumping rate, viscosity) in real time during stimulation.

58 GEOSCIENCES↗