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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Auto-adaptive Harris corner detection algorithm based on entropy-improved block processing

Extracting well distributed control points (CPs) is a very challenging task for remote sensing image registration, particularly for large high-resolution images over heterogeneous landscape. Based on image analysis such as edge detection, corner detection, and information theory, a new CP detection approach is proposed to select high- quality, evenly distributed CPs. The Entropy-Block-Based variant of the Harris Corner Detector (EBB-HCD) is achieved by dividing the image into blocks and by allocating the number of CP's based upon the entropy of each block. While the block-based strategy improves the CP balance problem, a factor calculated from entropy avoids overdetection. We conducted a comparison study utilizing the well-known Harris Corner Detector (HCD) and an implementation of the Block-Based Harris Corner Detector (BB-HCD). Experimental results indicate that using EBB-HCD to find the CPs improves the overall alignment accuracy during registration compared with HCD or BB-HCD.

Sun, Yihang↗
DOE OSTI2019

Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study

The presence and configurations of defects are primary components determining materials functionality. Their population and distribution are often nonergodic and dependent on synthesis history, and therefore rarely amenable to direct theoretical prediction. Here, dynamic electron beam–induced transformations in Si deposited on a graphene monolayer are used to create libraries of possible Si and carbon vacancy defects. Deep learning networks are developed for automated image analysis and recognition of the defects, creating a library of (meta) stable defect configurations. Density functional theory is used to estimate atomically resolved scanning tunneling microscopy (STM) signatures of the classified defects from the created library, allowing identification of several defect types across imaging platforms. This approach allows automatic creation of defect libraries in solids, exploring the metastable configurations always present in real materials, and correlative studies with other atomically resolved techniques, providing comprehensive insight into defect functionalities.

36 MATERIALS SCIENCE↗
NASA NTRS2000

Highly ordered vertical structure of Synechococcus populations within the one-millimeter-thick photic zone of a hot spring cyanobacterial mat

A variety of contemporary techniques were used to investigate the vertical distribution of thermophilic unicellular cyanobacteria, Synechococcus spp., and their activity within the upper 1-mm-thick photic zone of the mat community found in an alkaline siliceous hot spring in Yellowstone National Park in Wyoming. Detailed measurements were made over a diel cycle at a 61 degrees C site. Net oxygenic photosynthesis measured with oxygen microelectrodes was highest within the uppermost 100- to 200-microm-thick layer until midmorning, but as the day progressed, the peak of net activity shifted to deeper layers, stabilizing at a depth of 300 microm from midday throughout the afternoon. Examination of vertical thin sections by bright-field and autofluorescence microscopy revealed the existence of different populations of Synechococcus which form discrete bands at different vertical positions. Denaturing gradient gel electrophoresis analysis of PCR-amplified 16S rRNA gene segments from horizontal cryosections obtained at 100-microm-thick vertical intervals also suggested vertical stratification of cyanobacterial, green sulfur bacterium-like, and green nonsulfur bacterium-like populations. There was no evidence of diel migration. However, image analysis of vertical thin sections revealed the presence of a narrow band of rod-shaped Synechococcus cells in which the cells assumed an upright position. These upright cells, located 400 to 800 microm below the surface, were observed only in mat samples obtained around noon. In mat samples obtained at other time points, the cells were randomly oriented throughout the mat. These combined observations reveal the existence of a highly ordered structure within the very thin photic zone of this hot spring microbial mat, consisting of morphologically similar Synechococcus populations that are likely to be differentially adapted, some co-occurring with green sulfur bacterium-like populations, and all overlying green nonsulfur bacterium-like populations.

Non-NASA Center↗
DOE OSTI2022

Methods—Kintsugi Imaging of Battery Electrodes: Distinguishing Pores from the Carbon Binder Domain using Pt Deposition

The mesostructure of porous electrodes used in lithium-ion batteries strongly influences cell performance. Accurate imaging of the distribution of phases in these electrodes would allow this relationship to be better understood through simulation. However, imaging the nanoscale features in these components is challenging. While scanning electron microscopy is able to achieve the required resolution, it has well established difficulties imaging porous media. This is because the flat imaging planes prepared using focused ion beam milling will intersect with the pores, which makes the images hard to interpret as the inside walls of the pores are observed. It is common to infiltrate porous media with resin prior to imaging to help resolve this issue, but both the nanoscale porosity and the chemical similarity of the resins to the battery materials undermine the utility of this approach for most electrodes. In this study, a technique is demonstrated which uses in situ infiltration of platinum to fill the pores and thus enhance their contrast during imaging. Reminiscent of the Japanese art of repairing cracked ceramics with precious metals, this technique is referred to as the kintsugi method. The images resulting from applying this technique to a conventional porous cathode are presented and then segmented using a multi-channel convolutional method. We show that while some cracks in active material particles were empty, others appear to be filled (perhaps with the carbon binder phase), which will have implications for the rate performance of the cell. Energy dispersive X-ray spectroscopy was used to validate the distribution of phases resulting from image analysis, which also suggested a graded distribution of the binder relative to the carbon additive. The equipment required to use the kintsugi method is commonly available in major research facilities and so we hope that this method will be rapidly adopted to improve the imaging of electrode materials and porous media in general.

25 ENERGY STORAGE↗
NASA NTRS1984

Geobotanical discrimination of ultramafic parent materials An evaluation of remote sensing techniques

Color and color infrared aerial photography and imagery acquired from a Daedalus DEI-1260 multispectral airborne scanner were employed in an investigation to discriminate ultramafic rock types in a test site in southwest Oregon. An analysis of the relationships between vegetation characteristics and parent materials was performed using a vegetation classification and map developed for the project, lithologic information derived from published geologic maps of the region, and terrain information gathered in the field. Several analytical methods, including visual image analysis, band ratioing, principal components analysis, and contrast enhancement and subsequent color composite generation were used in the investigation. There was a close correspondence between vegetation types and major rock types. These were readily discriminated by the remote sensing techniques. It was found that ultramafic rock types were separable from non-ultramafic rock types and serpentine was distinguishable from non-serpentinized peridotite. Further investigations involving spectroradiometric and digital classification techniques are being performed to further identify rock types and to discriminate chromium and nickel-bearing rock types.

Mouat, D. A.↗
NASA NTRS1996

Determination of Shed Ice Particle Size Using High Speed Digital Imaging

A full scale model of an aircraft engine inlet was tested at NASA Lewis Research Center's Icing Research Tunnel. Simulated natural ice sheds from the engine inlet lip were studied using high speed digital image acquisition and image analysis. Strategic camera placement integrated at the model design phase allowed the study of ice accretion on the inlet lip and the resulting shed ice particles at the aerodynamic interface plane at the rear of the inlet prior to engine ingestion. The resulting digital images were analyzed using commercial and proprietary software to determine the size of the ice particles that could potentially be ingested by the engine during a natural shedding event. A methodology was developed to calibrate the imaging system and insure consistent and accurate measurements of the ice particles for a wide range of icing conditions.

Broughton, Howard↗
NASA NTRS2007

Palomar and Table Mountain Observations of 9P/Tempel 1 during the Deep Impact Encounter: First Results

We present the first results of the Palomar Adaptive Optics observations taken during the Deep Impact encounter with 9P/Tempel 1 in July 2005. We have combined the Palomar near-IR imaging data with our visual wavelength images obtained simultaneously at JPL's Table Mountain Observatory to cover the total wavelength range from 0.4 to 2.3 micrometers in the B, V, R, I, J, H, and K filter bands, spanning the dates from 2005 July 03-07.We also include in our overall analysis images taken on the pre-encounter dates of June 1 and June 15, 2005. The broad wavelength range of our observations, along with high temporal resolution, near-IR sensitivity, and spatial resolution of our imaging, have enabled us to place constraints on the temperature of the impact flash and incandescent plume of greater than 700 K, and to provide mean dust velocities of order 197 +/- 16 m/s approximately 1.25 h after impact derived from our 1.64 micro observations. Our ejected dust mass estimates, as derived from our near-IR observations, are an order of magnitude less than those previously reported for visual wavelength observations.

Comet Tempel-1↗
DOE OSTI2018

Characterization of Cement-Geomaterial Interfaces for Subsurface Applications

Subsurface seals and wellbores are central to oil and gas production, as well as the containment of subsurface fluids (e.g. methane or CO 2 storage). Studying the evolution of cement-geomaterial interfaces of such systems is important to further our understanding of the fundamental physics and chemistry that underpins catastrophic wellbore seal failure. The objective of this study is to characterize cementitious and geomaterials through pore structure analysis and geochemical modeling. A variety of methods exist to characterize the pore structures and mineralogy of porous systems like cements and subsurface host rocks. This study will utilize traditional porosimetry techniques such as BET and IP, as well as more advanced methods using electron image analysis, to gain a more accurate understanding of pore geometries. The results of this study can help further the understanding of how cementitious materials will evolve, and can be used as inputs to field scale models used to predict wellbore behavior over time.

36 MATERIALS SCIENCE↗
NASA NTRS1979

LANDSAT digital analysis of the initial recovery of the Kokolik River tundra fire area, Alaska

The author has identified the following significant results. Considerable regrowth of vegetation was observed between August 1977 and August 1978, both in the field and through analysis of LANDSAT near infrared digital data. The spectral reflectances in the burned areas were found to increase with the age of the burn in a one year period due to vegetation regrowth. Regrowth was particularly evident in the lightly burned portions of the burned area. Image analysis techniques using the AOIPS system permitted delineation of burn severity categories. The conditions and type of ground cover prior to the fire influenced the severity of burning, as did the direction of the winds while the burning was in progress as determined from field and LANDSAT observations. More severe burning was induced by winds blowing in the northeastern and southeastern portions of the burned area.

Hall, D. K.↗
NASA NTRSDate not supplied

In-Situ Ice Adhesion Testing using the Deformed Skin Adhesion Test

There exists a plethora of ice adhesion testing methods such as centrifuge-based methods, push/pull methods, and lap joint shear tests. However, these methods often cannot be done in-situ during an icing spray and require researcher handling/preparation prior to testing. Additionally, many of these methods test ice accretions that are not representative of the ice shapes that grow on airframes which can have unintended consequences such as edge or corner stress concentrations. In order to mitigate the issues present with other ice adhesion tests a novel, hands-free, in-situ test method imbedded into the leading edge of the airfoil has been developed and tested in the NASA Glenn Research Center Icing Research Tunnel. The mechanics of the new test method are discussed with finite element simulations being used to highlight the fundamental mechanics of this test method. The testing procedures used during the experimental test campaign are discussed along with the icing cloud test matrix. Analysis of the force-displacement results highlights the repeatability of the test method with regards to both sample behavior across several days of testing and different ice shapes. The results from first run of the day showed a significant discrepancy from subsequent runs and differential image analysis was used to determine differences in the interfacial bonding states between runs.

Ice Adhesion↗
NASA NTRSDate not supplied

In-Situ Ice Adhesion Testing using the Deformed Skin Adhesion Test

There exists a plethora of ice adhesion testing methods such as centrifuge-based methods, push/pull methods, and lap joint shear tests. However, these methods often cannot be done in-situ during an icing spray and require researcher handling/preparation prior to testing. Additionally, many of these methods test ice accretions that are not representative of the ice shapes that grow on airframes which can have unintended consequences such as edge or corner stress concentrations. In order to mitigate the issues present with other ice adhesion tests a novel, hands-free, in-situ test method imbedded into the leading edge of the airfoil has been developed and tested in the NASA Glenn Research Center Icing Research Tunnel. The mechanics of the new test method are discussed with finite element simulations being used to highlight the fundamental mechanics of this test method. The testing procedures used during the experimental test campaign are discussed along with the icing cloud test matrix. Analysis of the force-displacement results highlights the repeatability of the test method with regards to both sample behavior across several days of testing and different ice shapes. The results from first run of the day showed a significant discrepancy from subsequent runs and differential image analysis was used to determine differences in the interfacial bonding states between runs.

Ice Adhesion↗
NASA NTRS2012

Two-Dimensional Nonlinear Finite Element Analysis of CMC Microstructures

A research program has been developed to quantify the effects of the microstructure of a woven ceramic matrix composite and its variability on the effective properties and response of the material. In order to characterize and quantify the variations in the microstructure of a five harness satin weave, chemical vapor infiltrated (CVI) SiC/SiC composite material, specimens were serially sectioned and polished to capture images that detailed the fiber tows, matrix, and porosity. Open source quantitative image analysis tools were then used to isolate the constituents, from which two dimensional finite element models were generated which approximated the actual specimen section geometry. A simplified elastic-plastic model, wherein all stress above yield is redistributed to lower stress regions, is used to approximate the progressive damage behavior for each of the composite constituents. Finite element analyses under in-plane tensile loading were performed to examine how the variability in the local microstructure affected the macroscopic stress-strain response of the material as well as the local initiation and progression of damage. The macroscopic stress-strain response appeared to be minimally affected by the variation in local microstructure, but the locations where damage initiated and propagated appeared to be linked to specific aspects of the local microstructure.

Mital, Subodh K.↗
DOE OSTI2014

Computerized detection of noncalcified plaques in coronary CT angiography: Evaluation of topological soft gradient prescreening method and luminal analysis

Purpose: The buildup of noncalcified plaques (NCPs) that are vulnerable to rupture in coronary arteries is a risk for myocardial infarction. Interpretation of coronary CT angiography (cCTA) to search for NCP is a challenging task for radiologists due to the low CT number of NCP, the large number of coronary arteries, and multiple phase CT acquisition. The authors conducted a preliminary study to develop machine learning method for automated detection of NCPs in cCTA. Methods: With IRB approval, a data set of 83 ECG-gated contrast enhanced cCTA scans with 120 NCPs was collected retrospectively from patient files. A multiscale coronary artery response and rolling balloon region growing (MSCAR-RBG) method was applied to each cCTA volume to extract the coronary arterial trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline. A topological soft-gradient (TSG) detection method was developed to prescreen for NCP candidates by analyzing the 2D topological features of the radial gradient field surface along the vessel wall. The NCP candidates were then characterized by a luminal analysis that used 3D geometric features to quantify the shape information and gray-level features to evaluate the density of the NCP candidates. With machine learning techniques, useful features were identified and combined into an NCP score to differentiate true NCPs from false positives (FPs). To evaluate the effectiveness of the image analysis methods, the authors performed tenfold cross-validation with the available data set. Receiver operating characteristic (ROC) analysis was used to assess the classification performance of individual features and the NCP score. The overall detection performance was estimated by free response ROC (FROC) analysis. Results: With our TSG prescreening method, a prescreening sensitivity of 92.5% (111/120) was achieved with a total of 1181 FPs (14.2 FPs/scan). On average, six features were selected during the tenfold cross-validation training. The average area under the ROC curve (AUC) value for training was 0.87 ± 0.01 and the AUC value for validation was 0.85 ± 0.01. Using the NCP score, FROC analysis of the validation set showed that the FP rates were reduced to 3.16, 1.90, and 1.39 FPs/scan at sensitivities of 90%, 80%, and 70%, respectively. Conclusions: The topological soft-gradient prescreening method in combination with the luminal analysis for FP reduction was effective for detection of NCPs in cCTA, including NCPs causing positive or negative vessel remodeling. The accuracy of vessel segmentation, tracking, and centerline identification has a strong impact on NCP detection. Studies are underway to further improve these techniques and reduce the FPs of the CADe system.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1983

Mapping project on land use changes in the carboniferous region of Santa Catarina

The utilization of remote sensing data for monitoring land use changes by means of digital image analysis is described. The following data were utilized: LANDSAT data from September 4, 1975, April 24, 1978, and September 8, 1981; LANDSAT paper photography data; area IV color photographs; IBGE topography maps, and auxiliary data about the Brazilian state of Santa Catarina. Three kinds of analyses of digital images were carried out. The project identified and mapped major classes of land use areas including urban areas, coal deposits, agricultural areas, forests, lakes, and flood plains. Five areas directly affected by coal exploration southeast of Santa Catarina are identified and described. In addition, the classification system used for organizing data about land cover in a hierarchical arrangement is presented. The project made use of two remote sensing data sources: data of MSS spectral (Mulitspectral Scanner System)/LANDSAT on a scale of 1:100,000 with approximately 80 m resolution, and infrared color aerial photographs on a scale of 1:45,000 with approximately 5 m resolution. Therefore, the classification system included three levels, two selected to be compatible with aerial photography data and the third to conform to the resolution of MSS/LANDSAT.

Valeriano, D. D.↗
NASA NTRS2005

Single-Command Approach and Instrument Placement by a Robot on a Target

AUTOAPPROACH is a computer program that enables a mobile robot to approach a target autonomously, starting from a distance of as much as 10 m, in response to a single command. AUTOAPPROACH is used in conjunction with (1) software that analyzes images acquired by stereoscopic cameras aboard the robot and (2) navigation and path-planning software that utilizes odometer readings along with the output of the image-analysis software. Intended originally for application to an instrumented, wheeled robot (rover) in scientific exploration of Mars, AUTOAPPROACH could be adapted to terrestrial applications, notably including the robotic removal of land mines and other unexploded ordnance. A human operator generates the approach command by selecting the target in images acquired by the robot cameras. The approach path consists of multiple legs. Feature points are derived from images that contain the target and are thereafter tracked to correct odometric errors and iteratively refine estimates of the position and orientation of the robot relative to the target on successive legs. The approach is terminated when the robot attains the position and orientation required for placing a scientific instrument at the target. The workspace of the robot arm is then autonomously checked for self/terrain collisions prior to the deployment of the scientific instrument onto the target.

Huntsberger, Terrance↗
DOE OSTI2013

Imaging Wellbore Cement Degradation by Carbon Dioxide under Geologic Sequestration Conditions Using X-ray Computed Microtomography

ABSTRACT: X-ray microtomography (XMT), a nondestructive three-dimensional imaging technique, was applied to demonstrate its capability to visualize the mineralogical alteration and microstructure changes in hydrated Portland cement exposed to carbon dioxide under geologic sequestration conditions. Steel coupons and basalt fragments were added to the cement paste in order to simulate cement-steel and cement-rock interfaces. XMT image analysis showed the changes of material density and porosity in the degradation front (density: 1.98 g/cm3, porosity: 40%) and the carbonated zone (density: 2.27 g/cm3, porosity: 23%) after reaction with CO2- saturated water for 5 months compared to unaltered cement (density: 2.15 g/cm3, porosity: 30%). Three-dimensional XMT imaging was capable of displaying spatially heterogeneous alteration in cement pores, calcium carbonate precipitation in cement cracks, and preferential cement alteration along the cement-steel and cement-rock interfaces. This result also indicates that the interface between cement and host rock or steel casing is likely more vulnerable to a CO2 attack than the cement matrix in a wellbore environment. It is shown here that XMT imaging can potentially provide a new insight into the physical and chemical degradation of wellbore cement by CO2 leakage.

Imaging Wellbore Cement Degradation by Carbon Diox↗
NASA NTRS1992

Computer vision in microstructural analysis

The following is a laboratory experiment designed to be performed by advanced-high school and beginning-college students. It is hoped that this experiment will create an interest in and further understanding of materials science. The objective of this experiment is to demonstrate that the microstructure of engineered materials is affected by the processing conditions in manufacture, and that it is possible to characterize the microstructure using image analysis with a computer. The principle of computer vision will first be introduced followed by the description of the system developed at Texas A&M University. This in turn will be followed by the description of the experiment to obtain differences in microstructure and the characterization of the microstructure using computer vision.

Srinivasan, Malur N.↗