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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
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.↗
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↗
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.↗
DOE OSTI2019

Effect of low tube voltage and low iodine concentration abdominal CT on image quality and radiation dose in children: preliminary study

Purpose: To evaluate the image quality of a double-low protocol (low tube voltage and low iodine concentration) for abdominal CT in children. Materials and methods: The double-low protocol was compared to the conventional protocol in pediatric patients weighing less than 40 kg from May 2016 to December 2016. Double-low protocol (Group A, n = 18): tube voltage, 70 kVp; and iodine concentration,: 250 mgI/mL versus Conventional protocol (Group B, n = 13): tube voltage, 80–100 kVp; and iodine concentration, 350 mgI/mL. Mean attenuation, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between the two groups. Image contrast, noise, beam-hardening artifacts, and overall image quality were subjectively scored. Reader performance for correctly differentiating two groups by visual assessment was evaluated. Radiation dose and total iodine load were recorded. Results: The mean attenuations of the portal vein and liver and the mean image noise in Group A were higher than in Group B (p = 0.04, 0.03, 0.004, respectively). The mean SNR and CNR of the main portal vein and liver were lower in Group A without any statistically significant difference. There were no statistically significant differences between the two groups in qualitative analysis (image contrast, image noise, and overall image quality) with substantial agreement between the reviewers (weighted kappa values; 0.59–0.76). Significantly diminished radiation dose and iodine load were observed in Group A compared with Group B (25.0%, 36.8% reduction; p = 0.007, 0.006, respectively). Conclusion: The double-low protocol was feasible for pediatric abdominal CT and reduced both radiation dose and iodine load, while maintaining image quality.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1994

Optical Implementation of Matching Pursuit for Image Representation

We have developed a technique for image analysis, representation, and decomposition. This technique was motivated by Stephane Mallat's matching-pursuit algorithm. We've altered and simplified the mechanics of his algorithm to enable an extremely fast implementation via optical processing. Initial computer simulations show that our algorithm is capable of decomposing and representing a 2-D image as a linear combination of basis images with both high speed and high fidelity.

matching pursuit adaptive wavelet transform image ↗
DOE OSTI2017

Estimating the Temperature Experienced by Biomass Particles during Fast Pyrolysis Using Microscopic Analysis of Biochars

Here, biomass particles can experience variable thermal conditions during fast pyrolysis due to differences in their size and morphology, and from local temperature variations within a reactor. These differences lead to increased heterogeneity of the chemical products obtained in the pyrolysis vapors and bio-oil. Here we present a simple, high-throughput method to investigate the thermal history experienced by large ensembles of particles during fast pyrolysis by imaging and quantitative image analysis. We present a correlation between the surface luminance (darkness) of the biochar particle and the highest temperature that it experienced during pyrolysis. Next, we apply this correlation to large, heterogeneous ensembles of char particles produced in a laminar entrained flow reactor (LEFR). The results are used to interpret the actual temperature distributions delivered by the reactor over a range of operating conditions.

09 BIOMASS FUELS↗
DOE OSTI2019

Pore-Scale Analysis of Calcium Carbonate Precipitation and Dissolution Kinetics in a Microfluidic Device

In this work, we have characterized the calcium carbonate (CaCO 3 ) precipitates over time caused by reaction-driven precipitation and dissolution in a micromodel. Reactive solutions were continuously injected through two separate inlets, resulting in transverse-mixing induced precipitation during the precipitation phase. Subsequently, a dissolution phase was conducted by injecting clean water (pH = 4). The evolution of precipitates was imaged in two and three dimensions (2-, 3-D) at selected times using optical and confocal microscopy. With estimated reactive surface area, effective precipitation and dissolution rates can be quantitatively compared to results in the previous works. Our comparison indicates that we can evaluate the spatial and temporal variations of effective reactive areas more mechanistically in the microfluidic system only with the knowledge of local hydrodynamics, polymorphs, and comprehensive image analysis. Here, our analysis clearly highlights the feedback mechanisms between reactions and hydrodynamics. Pore-scale modeling results during the dissolution phase were used to account for experimental observations of dissolved CaCO 3 plumes with dissolution of the unstable phase of CaCO 3 . Mineral precipitation and dissolution induce complex dynamic pore structures, thereby impacting pore-scale fluid dynamics. Pore-scale analysis of the evolution of precipitates can reveal the significance of chemical and pore structural controls on reaction and fluid migration.

58 GEOSCIENCES↗
DOE OSTI2023

Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium

Left–right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case–control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case–control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case–control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case–control status. Subtle case–control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Using Ultrasound Image Augmentation and Ensemble Predictions to Prevent Machine-Learning Model Overfitting

Deep learning predictive models have the potential to simplify and automate medical imaging diagnostics by lowering the skill threshold for image interpretation. However, this requires predictive models that are generalized to handle subject variability as seen clinically. Here, we highlight methods to improve test accuracy of an image classifier model for shrapnel identification using tissue phantom image sets. Using a previously developed image classifier neural network—termed ShrapML—blind test accuracy was less than 70% and was variable depending on the training/test data setup, as determined by a leave one subject out (LOSO) holdout methodology. Introduction of affine transformations for image augmentation or MixUp methodologies to generate additional training sets improved model performance and overall accuracy improved to 75%. Further improvements were made by aggregating predictions across five LOSO holdouts. This was done by bagging confidences or predictions from all LOSOs or the top-3 LOSO confidence models for each image prediction. Top-3 LOSO confidence bagging performed best, with test accuracy improved to greater than 85% accuracy for two different blind tissue phantoms. This was confirmed by gradient-weighted class activation mapping to highlight that the image classifier was tracking shrapnel in the image sets. Overall, data augmentation and ensemble prediction approaches were suitable for creating more generalized predictive models for ultrasound image analysis, a critical step for real-time diagnostic deployment.

60 APPLIED LIFE SCIENCES↗