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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Modeling of Damage Initiation and Progression in a SiC/SiC Woven Ceramic Matrix Composite

The goal of an ongoing project at NASA Glenn is to investigate the effects of the complex microstructure of a woven ceramic matrix composite and its variability on the effective properties and the durability of the material. Detailed analysis of these complex microstructures may provide clues for the material scientists who `design the material? or to structural analysts and designers who `design with the material? regarding damage initiation and damage propagation. A model material system, specifically a five-harness satin weave architecture CVI SiC/SiC composite composed of Sylramic-iBN fibers and a SiC matrix, has been analyzed. Specimens of the material were serially sectioned and polished to capture the detailed images of fiber tows, matrix and porosity. Open source analysis tools were used to isolate various constituents and finite elements models were then generated from simplified models of those images. Detailed finite element analyses were performed that examine how the variability in the local microstructure affected the macroscopic behavior as well as the local damage initiation and progression. Results indicate that the locations where damage initiated and propagated is linked to specific microstructural features.

Mital, Subodh K.↗
NASA NTRS2013

Simulation of Detecting Damage in Composite Stiffened Panel Using Lamb Waves

Lamb wave damage detection in a composite stiffened panel is simulated by performing explicit transient dynamic finite element analyses and using signal imaging techniques. This virtual test process does not need to use real structures, actuators/sensors, or laboratory equipment. Quasi-isotropic laminates are used for the stiffened panels. Two types of damage are studied. One type is a damage in the skin bay and the other type is a debond between the stiffener flange and the skin. Innovative approaches for identifying the damage location and imaging the damage were developed. The damage location is identified by finding the intersection of the damage locus and the path of the time reversal wave packet re-emitted from the sensor nodes. The damage locus is a circle that envelops the potential damage locations. Its center is at the actuator location and its radius is computed by multiplying the group velocity by the time of flight to damage. To create a damage image for estimating the size of damage, a group of nodes in the neighborhood of the damage location is identified for applying an image condition. The image condition, computed at a finite element node, is the zero-lag cross-correlation (ZLCC) of the time-reversed incident wave signal and the time reversal wave signal from the sensor nodes. This damage imaging process is computationally efficient since only the ZLCC values of a small amount of nodes in the neighborhood of the identified damage location are computed instead of those of the full model.

Wang, John T.↗
NASA NTRS2017

Seasonal Assessment and Classification of Aerosols Transported to Lahore Using AERONET and MODIS Deep Blue Retrievals

Daily measurements of aerosol optical depth (𝜏) and Ångstrom wavelength exponent (𝛼) acquired from Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectrometer (MODIS) are analysed over Lahore - an urban city of Pakistan (period: 2010-2014) to investigate contribution of different types of aerosols originating from both local and regional source locations. The obtained annual averages (mean+/-standard deviation) for AERONET retrievals of 𝜏 (500 nm) and 𝛼 (440-870 nm) are 0.68+/-0.37 (0.08-2.91) and 0.99+/-0.33 (0-1.8), respectively. Of all the sources, 61% are found within Pakistan, 11% in India, 19% in Afghanistan, 6% in Iran and 2% in Saudi Arabia with seasonal contributions of 35, 25, 23 and 17% in pre-monsoon, monsoon, winter and post-monsoon, respectively. The bimodal distributions of 𝛼 show dominance of coarse-mode particles during pre-monsoon, fine-mode particles during post-monsoon and presence of both coarse-mode and fine-mode particles during winter and monsoon with winter showing more fine-mode particles. Two broad classes of aerosols namely desert dust (DD) and biomass burning/urban industrial (BU) are identified with criteria, e.g. 𝜏 ≥0.3 and 𝛼 ≤0.75 indicating presence of DD while 𝜏 ≥0.2 and 𝛼 ≥1.15 indicating BU. The frequency of occurrence (FOO) of DD and BU aerosols is further identified by applying classification criteria over Aqua-MODIS deep blue retrievals. The FOO identifies anthropogenic activity on-going throughout the year, disrupted with DD aerosols only during pre-monsoon and monsoon. The maximum dust activity is seen over Indo-Gangetic plains (IGP) (localized maxima: 35-45%) and the Arabian peninsula (>55%) during pre-monsoon, while maximum BU aerosols are found over IGP, central and south-eastern plains of India and the state of Gujarat (localized maxima: >70%) in winter and post-monsoon.

Zafar, Qudsia↗
NASA NTRS2020

Oxygen Isotopic Imaging of Refractory Inclusions from the Miller Range (MIL) 090019 CO3 Chondrite: A Perovskite Perspective

Calcium-Aluminum-rich Inclusions (CAIs) in primitive meteorites are the first solids to condense in the Solar System. The oxygen isotopic compositions recorded in various mineral components of CAIs provide clues about their origins and post-formation histories, recording processes such as condensation, melting, nebular alteration, and fluidrock reactions on the parent body. MIL 090019 is similar to some rare carbonaceous chondrites such as Acfer 094, DOM 08004/6 and ALH 77303 that contain high abundances of a variety of refractory inclusions. This provides an opportunity to study the oxygen isotopic record of different types of refractory inclusions within the same meteorite. We analyzed CAIs specifically targeting primary minerals that are direct nebular condensates, such as corundum and perovskite, with the goal of gaining insights into the O isotopic composition of the nebular gas(es) from which these CAIs condensed. As MIL 090019 is a classified as CO3.1, it shows some signs of thermal metamorphism, compared to the more primitive CO3 meteorites (e.g., DOM 08004/06). A second goal of this study is to search for evidence of nebular processes in phases such as perovskite and melilite that are susceptible to parent body alteration to varying degrees. We analyzed the oxygen isotopic compositions of various CAIs from the MIL 090019 CO3 carbonaceous chondrite by ion imaging using the NanoSIMS 50L (Nano Secondary Ion Mass Spectrometer) at JSC following methods described in. An advantage of ion imaging over traditional spot analyses is that it provides spatial context to the oxygen isotopic data. This work builds on previously reported oxygen isotopic composition of two other CAIs (CAI-44 and CAI-E2) from the same meteorite thin section.

Mane, P.↗
NASA NTRS1982

Analysis of a multisensor image data set of south San Rafael Swell, Utah

A Shuttle Imaging Radar (SIR-A) image of the southern portion of the San Rafael Swell in Utah has been digitized and registered to coregistered Landsat, Seasat, and HCMM thermal inertia images. The addition of the SIR-A image to the registered data set improves rock type discrimination in both qualitative and quantitative analyses. Sedimentary units can be separated in a combined SIR-A/Seasat image that cannot be seen in either image alone. Discriminant Analyses show that the classification accuracy is improved with addition of the SIR-A image to Landsat images. Classification accuracy is further improved when texture information from the Seasat and SIR-A images is included.

Evans, D. L.↗
NASA NTRS2003

Mars Exploration Rovers as Virtual Instruments for Determination of Terrain Roughness and Physical Properties

The two 2003 Mars Exploration Rovers (MERs), in combination with the Athena Payload, will be used as virtual instrument systems to infer terrain properties during traverses, in addition to using the rover wheels to excavate trenches, exposing subsurface materials for remote and in-situ observations. The MERs are being modeled using finite element-based rover system transfer functions that utilize the distribution of masses associated with the vehicle, together with suspension and wheel dynamics, to infer surface roughness and mechanical properties from traverse time series data containing vehicle yaw, pitch, roll, encoder counts, and motor currents. These analyses will be supplemented with imaging and other Athena Payload measurements. The approach is being validated using Sojourner data, the FIDO rover, and experiments with MER testbed vehicles. In addition to conducting traverse science and associated analyses, trenches will be excavated by the MERs to depths of approximately 10-20 cm by locking all but one of the front wheels and rotating that wheel backwards so that the excavated material is piled up on the side of the trench away from the vehicle. Soil cohesion and angle of internal friction will be determined from the trench telemetry data. Emission spectroscopy and in-situ observations will be made using the Athena payload before and after imaging. Trenching and observational protocols have been developed using Sojourner results; data from the FIDO rover, including trenches dug into sand, mud cracks, and weakly indurated bedrock; and experiments with MER testbed rovers. Particular attention will be focused on Mini-TES measurements designed to determine the abundance and state of subsurface water (e.g. hydrated, in zeolites, residual pore ice?) predicted to be present from Odyssey GRS/NS/HEND data.

R E Arvidson↗
NASA NTRS1992

Visual information processing; Proceedings of the Meeting, Orlando, FL, Apr. 20-22, 1992

Topics discussed in these proceedings include nonlinear processing and communications; feature extraction and recognition; image gathering, interpolation, and restoration; image coding; and wavelet transform. Papers are presented on noise reduction for signals from nonlinear systems; driving nonlinear systems with chaotic signals; edge detection and image segmentation of space scenes using fractal analyses; a vision system for telerobotic operation; a fidelity analysis of image gathering, interpolation, and restoration; restoration of images degraded by motion; and information, entropy, and fidelity in visual communication. Attention is also given to image coding methods and their assessment, hybrid JPEG/recursive block coding of images, modified wavelets that accommodate causality, modified wavelet transform for unbiased frequency representation, and continuous wavelet transform of one-dimensional signals by Fourier filtering.

Huck, Friedrich O.↗
NASA NTRS2014

Sedimentology of Martian Gravels from Mardi Twilight Imaging: Techniques

Quantitative sedimentologic analysis of gravel surfaces dominated by pebble-sized clasts has been employed in an effort to untangle aspects of the provenance of surface sediments on Mars using Curiosity's MARDI nadir-viewing camera operated at twilight Images have been systematically acquired since sol 310 providing a representative sample of gravel-covered surfaces since the rover departed the Shaler region. The MARDI Twilight imaging dataset offers approximately 1 millimeter spatial resolution (slightly out of focus) for patches beneath the rover that cover just under 1 m2 in area, under illumination that makes clast size and inter-clast spacing analysis relatively straightforward using semi- automated codes developed for use with nadir images. Twilight images are utilized for these analyses in order to reduce light scattering off dust deposited on the front MARDI lens element during the terminal stages of Curiosity's entry, descent and landing. Such scattering is worse when imaging bright, directly-illuminated surfaces; twilight imaging times yield diffusely-illuminated surfaces that improve the clarity of the resulting MARDI product. Twilight images are obtained between 10-30 minutes after local sunset, governed by the timing of the end of the no-heat window for the camera. Techniques were also utilized to examine data terrestrial locations (the Kau Desert in Hawaii and near Askja Caldera in Iceland). Methods employed include log hyperbolic size distribution (LHD) analysis and Delauney Triangulation (DT) inter-clast spacing analysis. This work extends the initial results reported in Yingst et al., that covered the initial landing zone, to the Rapid-Transit Route (RTR) towards Mount Sharp.

sedimentologic↗
NASA NTRS2006

Modeling the Self-organized Critical Behavior of Earth's Plasma Sheet Reconnection Dynamics

Analyses of Polar UVI auroral image data show that bright night-side high-latitude W emissions exhibit so many of the key properties of systems in self-organized criticality that an alternate interpretation has become virtually impossible. These analyses will be reviewed. It is now necessary to find and model the source of this behavior. We note that the most common models of self-organized criticality are numerical sandpiles. These are, at root, models that govern the transport of some quantity from a region where it is loaded to another where it is unloaded. Transport is enabled by the excitation of a local threshold instability; it is intermittent and bursty, and it exhibits a number of scale-free statistical properties. Searching for a system in the magnetosphere that is analogous and that, in addition, is known to produce auroral signatures, we focus on the reconnection dynamics of the magnetotail plasma sheet. In our previous work, a driven reconnection model has been constructed and has been under study. The transport of electromagnetic (primarily magnetic) energy carried by the Poynting flux into the reconnection region of the model has been examined. All of the analysis techniques (and more) that have been applied to the auroral image data have also been applied to this Poynting flux. New results will be presented showing that this model also exhibits so many of the key properties of systems in self-organized criticality that an alternate interpretation is implausible. A strong correlation between these key properties of the model and those of the auroral UV emissions will be demonstrated. We suggest that, in general, the driven reconnection model is an important step toward a realistic plasma physical model of self-organized criticality and we conclude, more specifically, that it is also a step in the right direction toward modeling the multiscale reconnection dynamics of the magnetotail.

Klimas, Alexander J.↗
NASA NTRS1992

Goddard high resolution spectrograph science verification and data analysis

The data analysis performed was to support the Orbital Verification (OV) and Science Verification (SV) of the GHRS was in the areas of the Digicon detector's performance and stability, wavelength calibration, and geomagnetic induced image motion. The results of the analyses are briefly described. Detailed results are given in the form of attachments. Specialized software was developed for the analyses. Calibration files were formatted according to the specifications in a Space Telescope Science report. IRAS images were restored of the Large Magellanic Cloud using a blocked iterative algorithm. The algorithm works with the raw data scans without regridding or interpolating the data on an equally spaced image grid.

Source record↗
NASA NTRS1973

Analyses of requirements for computer control and data processing experiment subsystems: Image data processing system (IDAPS) software description (7094 version), volume 2

A description of each of the software modules of the Image Data Processing System (IDAPS) is presented. The changes in the software modules are the result of additions to the application software of the system and an upgrade of the IBM 7094 Mod(1) computer to a 1301 disk storage configuration. Necessary information about IDAPS sofware is supplied to the computer programmer who desires to make changes in the software system or who desires to use portions of the software outside of the IDAPS system. Each software module is documented with: module name, purpose, usage, common block(s) description, method (algorithm of subroutine) flow diagram (if needed), subroutines called, and storage requirements.

Source record↗
NASA NTRS1998

Analysis of Mauna Kea Imaging of Comet Shoemaker-Levy 9

The aim of this proposal was to analyse a set of charge-coupled device images of the Jupiter-impacting comet D/Shoemaker-Levy 9. The images were obtained primarily using the University of Hawaii 2.2-m telescope and a standardized imaging device, providing an unusually uniform set of data. Additional data included a set of spectra taken in search of gaseous emission from SL9 using the UH 2.2-m and Keck 10-m telescopes.

Jewitt, David↗
DOE OSTI2025

Stochastic 3D reconstruction of cracked polycrystalline NMC particles using 2D SEM data

Li-ion battery performance is strongly influenced by the 3D microstructure of its cathode particles. Cracks within these particles develop during calendaring and cycling, reducing connectivity but increasing reactive surface, making their impact on battery performance complex. Understanding these contradictory effects requires a quantitative link between particle morphology and battery performance. However, informative 3D imaging techniques are time-consuming, costly and rarely available, such that analyses often have to rely on 2D image data. This paper presents a novel stereological approach for generating virtual 3D cathode particles exhibiting crack networks that are statistically equivalent to those observed in 2D sections of experimentally measured particles. Consequently, 2D image data suffices for deriving a full 3D characterization of cracked cathodes particles. Such virtually generated 3D particles could serve as geometry input for spatially resolved electro-chemo-mechanical simulations to enhance our understanding of structure-property relationships of cathodes in Li-ion batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2025

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↗
DOE OSTI2023

Data associated with “Different methods of estimating riverbed sediment grain size diverge at the basin scale ” (v2)

This data package is associated with the publication “Different methods of estimating riverbed sediment grain size diverge at the basin scale” published in Frontiers in Earth Science (Regier et al., 2025). The distribution of sediment grain size in streams and rivers is often quantified by the median grain size (d50), a key metric for understanding and predicting hydrologic and biogeochemical function of streams and rivers. Manual methods to measure d50 are time-consuming and ignore larger grains, while model-based methods to estimate d50 often over-generalize basin characteristics, and therefore cannot accurately represent site-scale heterogeneity. Here, we apply a machine learning-enabled photogrammetry methodology (You Only Look Once, or YOLO) for estimating d50 for grains > 2 mm based on images collected from streams and rivers throughout the Yakima River Basin (YRB). To understand how such methods may help bridge the gaps in resolution and accuracy between manual and catchment characteristics model-based d50 estimates, we compared YOLO d50 values to manual and model-based estimates across the YRB. We found distinct differences among methods for d50 averages and variability, and relationships between d50 estimates and basin characteristics. Source images can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052. This data package was originally published in May 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. In addition to the readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) and subfolders containing data, figures, and scripts. The data folder contains datasets used for the analyses in the manuscript in image, text-delimited or geospatially-referenced formats. The figures folder contains the figures from the manuscript in different formats. The scripts folder contains all of the scripts used to complete the analyses in the manuscript. All files are .csv, .rds, .dbf, .prj, .shp, .shx, .jpg, .png, .R, .Rproj, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Conference on Applications of Digital Image Processing to Astronomy, Pasadena, Calif., August 20-22, 1980, Proceedings

The astronomic applications of non-military digital image processing are covered in this conference volume. Systems like CCD's, interactive data analysis facilities, stellar speckle interferometry, sky flux subsystems, guide star systems and various image processing systems are described. Techniques in photometry including filtering, automatic photometry, and image restoration are examined. Digital spectral analyses of galaxies, supernova remnants, stars and other celestial bodies are discussed together with algorithms developed to calibrate, clean up, enhance, and quantitatively analyze data. The techniques of image processing permit astronomers to make much more efficient use of their data for both subjective and quantitative analyses. Future missions, such as the Space Telescope, representing a vast data base are briefly covered.

Elliott, D. A.↗
DOE OSTI2022

Convolutional neural networks for intra-hour solar forecasting based on sky image sequences

Accurate and timely solar forecasts play an increasingly critical role in power systems. Compared to longer forecasting timescales, very short-term solar forecasting has lagged behind in both research and practice. In this paper, we propose deep convolutional neural networks (CNNs) to provide operational intra-hour (10-minute-ahead to 60-minute-ahead) solar forecasts. We develop two CNN structures inspired by a widely-used CNN architecture. The CNNs are tailored to our solar forecasting regression tasks and rely solely on sky image sequences. Case studies based on six years of data (over 150,000 data points) demonstrate that the best CNN model has forecast skill scores of 20%-39% over the naive persistence of cloudiness benchmark, even at these very short timescales. The CNNs also have consistently superior performance when compared to shallow machine learning models with meteorological predictors, where the improvement averages around 7%. The sensitivity analyses show that the sky image length, resolution, and weather conditions have impacts on the deep learning model accuracy. In our intra-hour problem with specific setups, two sky images with a 10-minute 128 x 128 resolution yield the most accurate forecasts. Current limitations, future work, and deployment challenges and solutions are also discussed.

14 SOLAR ENERGY↗