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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

James Webb Space Telescope Primary and Secondary Mirror Segment Assemblies Cleaning: a Quantitative Assessment

The James Webb Space Telescope Primary Mirror Segment Assemblies (PMSAs) and Secondary Mirror Assembly (SMA) were cleaned at the Johnson Space Center (JSC) in January 2018. In order to quantify the effectiveness of the cleaning, the same cleaning process was performed on the PMSA and SMA traveling witness wafers. These wafers have accompanied their respective mirror segments from their arrival at the Goddard Space Flight Center, through transport to JSC, and ultimately their exposure in Chamber A for cryogenic testing. The traveling wafers were analyzed using an Image Analysis automated microscope both prior to and after the cleaning. The resulting data showed that the PMSA wafers' Percent Area Coverage (PAC) reduced by 83.5% on average, from 0.1524 PAC to 0.0251 PAC. The SMA wafer's PAC decreased by 97.2%, from 0.1194 PAC to 0.0034 PAC. Further analysis of the particle size bins was completed in order to calculate their particle distribution slopes. The slope of the PMSA wafers increased by 0.025 on average, and the SMA wafer slope increased by 0.066. This indicates that the ratio of large to small particles slightly increased after the cleaning across all mirror segments. Visual inspections of the wafers and the flight PMSAs and SMA showed considerable and comparable particulate coverage improvements, thus leading to the conclusion that the average PAC on the PMSAs and SMA improved by the same factor as their respective wafers.

mirror↗
DOE OSTI2017

Mechanical properties of nanoporous gold in tension

We report results of the tensile properties of nanoporous gold (NPG) as a function of the density and average ligament diameter. As-dealloyed tensile samples were thermally treated to coarsen the length scale of the NPG structure while increasing the sample density resulting from thickness reductions. The behaviors of samples with mean ligament diameters ranging from 30 to 750 nm and corresponding densities ranging from 0.30 to 0.57 that of bulk gold were examined. Digital image analysis was used to obtain ligament size histograms that were fit to the Weibull distribution. The Young's modulus was found to obey a power law, but with an exponent larger than that predicted by Gibson-Ashby scaling. The fracture behavior showed a brittle-ductile transition as a function of increasing ligament size. For samples characterized by a mean ligament diameter less than ~ 220 nm, the tensile behavior was linear elastic to sample fracture while samples with larger scale ligaments showed macroscopic yielding prior to fracture. These results are interpreted within the framework of extreme value statistics.

36 MATERIALS SCIENCE↗
NASA NTRS1999

Fidelity Analysis of Sampled Imaging Systems

Many modeling, simulation and performance analysis studies of sampled imaging systems are inherently incomplete because they are conditioned on a discrete-input, discrete-output model that only accounts for blurring during image acquisition and additive noise. For those sampled imaging systems where the effects of digital image acquisition, digital filtering and reconstruction are significant, the modeling, simulation and performance analysis should be based on a more comprehensive continuous-input, discrete-processing, continuous-output end-to-end model. This more comprehensive model should properly account for the low-pass filtering effects of image acquisition prior to sampling, the potentially important noiselike effects of the aliasing caused by sampling, additive noise due to device electronics and quantization, the generally high-boost filtering effects of digital processing, and the low-pass filtering effects of image reconstruction. This model should not, however, be so complex as to preclude significant mathematical analysis, particularly the mean-square (fidelity) type of analysis so common in linear system theory. We demonstrate that, although the mathematics of such a model is more complex, the increase in complexity is not so great as to prevent a complete fidelity-metric analysis at both the component level and at the end-to-end system level: that is, computable mean-square-based fidelity metrics are developed by which both component-level and system-level performance can be quantified. In addition, we demonstrate that system performance can be assessed qualitatively by visualizing the output image as the sum of three component images, each of which relates to a corresponding fidelity metric. The cascaded, or filtered, component accounts for the end-to-end system filtering of image acquisition, digital processing, and image reconstruction; the random noise component accounts for additive random noise, modulated by digital processing and image reconstruction filtering; and the aliased noise component accounts for the frequency folding effect of sampling, modulated by digital processing and image reconstruction filtering.

Park, Stephen K.↗
DOE OSTI2023

Mucin 4 is a cellular biomarker of necrotizing bronchiolitis in influenza A virus infection

Influenza A virus (IAV) in the human and swine host infects epithelial cells lining the respiratory tract causing a necrotizing bronchitis and bronchiolitis. These epithelial surfaces are protected by large glycoproteins called mucins. Mucin 4 (MUC4) is a transmembrane mucin that consists of an alpha subunit responsible for surface protection and intracellular beta subunit involved in signal transduction which repress apoptosis and stimulate epithelial proliferation. This study was designed to determine the expression and potential role of MUC4 during IAV infection. We used immunohistochemistry in combination with machine learning image analysis to quantify differential protein expression of MUC4 subunits in IAV-infected and uninfected lung in a porcine model. MUC4 protein basal expression in control animals varied significantly by litter. MUC4 protein expression was significantly increased in bronchioles with necrotizing bronchiolitis compared to histologically normal bronchioles, likely representing a regenerative response to restore mucosal integrity of conducting airways. Understanding the impact of differential MUC4 expression among healthy individuals and during IAV infection will facilitate control strategies by elucidating mechanisms associated with susceptibility to IAV that can be therapeutically or genetically regulated and may be extended to other respiratory diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

On the measurement of shape: With applications to lunar regolith

With the renewed commitment from NASA and other commercial entities for a presence on the Moon, the importance of understanding the characteristics of lunar regolith and how to utilize it have become the target of increasing scrutiny. Much of what is known about lunar regolith was collected during and immediately after the Apollo program, however, analytical techniques and instrumentation have advanced in leaps and bounds in the subsequent decades. Specifically, dynamic image analysis systems have advanced to the point that millions of particles can have morphological characteristics automatically determined in relatively short time frames. Particle morphological data was collected on several lunar samples and a pair of widely used regolith simulants to ascertain the accuracy of these simulants and to explore statistical analysis methods of these large datasets. It is found that these morphology datasets can vary widely depending on the particle size of the particles, and simple averaging of the data skews the results heavily towards the numerically abundant size ranges, the fines. Different reporting methods are suggested to ameliorate these problems. When applied to the lunar regolith, the particles are noted to be less morphologically complex than initially suspected. Compared to the lunar material, the simulants are found to contain some more morphological variability and angular grains. Such difference is likely due to the wildly different comminution processes that these different powder systems are subjected to.

2D shape↗
DOE OSTI2024

Characterizing the microstructures of mammalian enamel by synchrotron phase contrast microCT

The enamel of mammalian teeth is a highly mineralized tissue that must endure a lifetime of cyclic contact and is inspiring the development of next-generation engineering materials. Attempts to implement enamel-inspired structures in synthetic materials have had limited success, largely due to the absence of a detailed understanding of its microstructure. Here, the present work used synchrotron phase-contrast microCT imaging to evaluate the three-dimensional microstructure of enamel from four mammals including Lion, Gray Wolf, Snow Leopard, and Black Bear. Quantitative results of image analysis revealed that the decussation pattern of enamel consists of discrete diazone (D) and parazone (P) bands of rods organized with stacking arrangement of D+/P/D-/P in all mammals evaluated; the D+ and D- refer to distinct diazone bands with juxtaposed rod orientations from the reference plane. Furthermore, the rod orientations in the bands can be described in terms of two principal angles, defined here as the pitch and yaw. While the pitch angle increases from the outer enamel to a maximum (up to ≈ 40°) near the dentin enamel junction, minimal spatial variations are observed in yaw across the enamel thickness. There are clear differences in the decussation parameters of enamel across species that are interpreted here with respect to the structural demands placed on their teeth. The rod pitch and band width of enamel are identified as important design parameters and appear to be correlated with the bite force quotient of the four mammals evaluated.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mapping Vegetation at Species Level with High-Resolution Multispectral and Lidar Data Over a Large Spatial Area: A Case Study with Kudzu

Mapping vegetation species is critical to facilitate related quantitative assessment, and mapping invasive plants is important to enhance monitoring and management activities. Integrating high-resolution multispectral remote-sensing (RS) images and lidar (light detection and ranging) point clouds can provide robust features for vegetation mapping. However, using multiple sources of high-resolution RS data for vegetation mapping on a large spatial scale can be both computationally and sampling intensive. Here, we designed a two-step classification workflow to potentially decrease computational cost and sampling effort and to increase classification accuracy by integrating multispectral and lidar data in order to derive spectral, textural, and structural features for mapping target vegetation species. We used this workflow to classify kudzu, an aggressive invasive vine, in the entire Knox County (1362 km2) of Tennessee (U.S.). Object-based image analysis was conducted in the workflow. The first-step classification used 320 kudzu samples and extensive, coarsely labeled samples (based on national land cover) to generate an overprediction map of kudzu using random forest (RF). For the second step, 350 samples were randomly extracted from the overpredicted kudzu and labeled manually for the final prediction using RF and support vector machine (SVM). Computationally intensive features were only used for the second-step classification. SVM had constantly better accuracy than RF, and the producer’s accuracy, user’s accuracy, and Kappa for the SVM model on kudzu were 0.94, 0.96, and 0.90, respectively. SVM predicted 1010 kudzu patches covering 1.29 km2 in Knox County. We found the sample size of kudzu used for algorithm training impacted the accuracy and number of kudzu predicted. The proposed workflow could also improve sampling efficiency and specificity. Our workflow had much higher accuracy than the traditional method conducted in this research, and could be easily implemented to map kudzu in other regions as well as map other vegetation species.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1973

Analysis of ERTS imagery using special electronic viewing/measuring equipment

An electronic satellite image analysis console (ESIAC) is being employed to process imagery for use by USGS investigators in several different disciplines studying dynamic hydrologic conditions. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. Quantitative measurements of distances, areas, and brightness profiles can be extracted digitally under operator supervision. Initial results are presented for the display and measurement of snowfield extent, glacier development, sediment plumes from estuary discharge, playa inventory, phreatophyte and other vegetative changes.

Evans, W. E.↗
DOE OSTI2025

Evaluating genetic and environmental controls on silicon accumulation in Populus trichocarpa leaves

Background and aims: Silicon (Si) accumulation and formation of non-crystalline silica particles (phytoliths) inside plant cells contribute to plant function, soil carbon storage, and Si reservoirs in soils. A better understanding of how genetic and environmental factors control Si accumulation may improve understanding of Si cycling between plants and soil and its impacts on other ecosystem processes. Methods: This study examined how genetic potential for Si uptake and silicification translated to Si concentrations and phytolith formation in Populus trichocarpa leaves. Leaves were collected from four different genotypes of cultivated poplar trees that were grown in a common garden and possess established differences in leaf-level gene expression related to Si transport and silicification. Scanning electron microscopy and subsequent image analysis were used to quantify Si concentrations and phytolith abundance and features. Results: Phytoliths were identified in nearly all leaves but were often absent at very low (< 0.5 wt.%) Si concentrations at the leaf surface. The proportion of leaf area occupied by phytoliths increased as Si content increased. Silicon content and phytolith abundance at the leaf surface did not vary across genotypes, but surface Si was weakly correlated with plant available Si in soil. Conclusion: Phytoliths were prevalent in P. trichocarpa leaves; however, the genetic potential for Si uptake and silicification at the leaf-level poorly predicted foliar Si and phytolith abundance. Uniformly low expression of Si uptake genes in the roots may have reduced differences across genotypes. Consequently, Si accumulation in leaves was likely more strongly influenced by soil Si bioavailability, phenology, or additional environmental factors.

Image analysis↗
DOE OSTI2022

A New Workflow of X-ray CT Image Processing and Data Analysis of Structural Features in Rock Using Open-Source Software

X-ray computed tomography (CT) images of rock specimens often contain artifacts which must be corrected before scientific analyses are performed. Here, we present a new workflow of automated image processing to utilize poor-quality X-ray CT scan images. The workflow runs on the open-source image analysis software and efficiently separates desired features from low-contrast scanned images. The new workflow is a two-step technique using contrast enhancement and automated feature segmentation to generate noise-free binary images. The results of binary images using the proposed workflow and using a conventional thresholding technique are analyzed to show the quality of the proposed method. The paper also presents a workflow of estimating the structural geometries of features in two and three dimensions. The results of the structural feature analyses and computational time were compared between the open-source (ImageJ) and commercial image analysis software (Bruker Computed Tomography Analyzer). The commercial software was more computationally efficient, but the task-specific macros in open-source software enabled the user-desired automation in image processing and data extraction of desired structural features of comparable quality.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

A Hierarchical Feature-Based Methodology to Perform Cervical Cancer Classification

Prevention of cervical cancer could be performed using Pap smear image analysis. This test screens pre-neoplastic changes in the cervical epithelial cells; accurate screening can reduce deaths caused by the disease. Pap smear test analysis is exhaustive and repetitive work performed visually by a cytopathologist. This article proposes a workload-reducing algorithm for cervical cancer detection based on analysis of cell nuclei features within Pap smear images. We investigate eight traditional machine learning methods to perform a hierarchical classification. We propose a hierarchical classification methodology for computer-aided screening of cell lesions, which can recommend fields of view from the microscopy image based on the nuclei detection of cervical cells. We evaluate the performance of several algorithms against the Herlev and CRIC databases, using a varying number of classes during image classification. Results indicate that the hierarchical classification performed best when using Random Forest as the key classifier, particularly when compared with decision trees, k-NN, and the Ridge methods.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1977

Applications of LANDSAT data to the integrated economic development of Mindoro, Phillipines

LANDSAT data is seen as providing essential up-to-date resource information for the planning process. LANDSAT data of Mindoro Island in the Philippines was processed to provide thematic maps showing patterns of agriculture, forest cover, terrain, wetlands and water turbidity. A hybrid approach using both supervised and unsupervised classification techniques resulted in 30 different scene classes which were subsequently color-coded and mapped at a scale of 1:250,000. In addition, intensive image analysis is being carried out in evaluating the images. The images, maps, and aerial statistics are being used to provide data to seven technical departments in planning the economic development of Mindoro. Multispectral aircraft imagery was collected to compliment the application of LANDSAT data and validate the classification results.

Wagner, T. W.↗
NASA NTRS1994

Citrus Inventory

An aerial color infrared (CIR) mapping system developed by Kennedy Space Center enables Florida's Charlotte County to accurately appraise its citrus groves while reducing appraisal costs. The technology was further advanced by development of a dual video system making it possible to simultaneously view images of the same area and detect changes. An image analysis system automatically surveys and photo interprets grove images as well as automatically counts trees and reports totals. The system, which saves both time and money, has potential beyond citrus grove valuation.

Source record↗
NASA NTRSDate not supplied

Autonomous Navigation, Guidance, and Control Software in a Low SWaP Box

Onboard autonomy is a necessity for responsive space operations. Autonomous navigation, guidance, and control (NGC) enables space missions to reduce their dependence on high demand ground assets and costly ground personnel. It also allows for in-situ decision making and higher return on mission data. A flight software and hardware system providing this capability, called “autoNGC,” is currently being developed at NASA Goddard Space Flight Center for infusion into multiple future missions. The autoNGC flight software is built on the plug-and-play architecture of the core Flight System (cFS) consisting of the standard cFS apps and newly developed autoNGC interface apps and libraries. The various apps cooperate through communication over the message-based software bus. With the plug-and-play architecture of autoNGC, cFS apps can easily be added and replaced to meet the needs of different missions, even after launch. The first flight software release of autoNGC is targeted for Summer 2024 to provide autonomous navigation at the Moon and beyond. It can perform sensor fusion of multiple measurement types including pseudo-range from a Global Navigation Satellite System (GNSS) receiver (including weak signal), 1-way and 2-way range and Doppler from ground stations (i.e., direct to Earth (DTE)), bearing and range from optical camera images, and accelerometer data. Accurate onboard navigation and timing is obtained through the Goddard Enhanced Onboard Navigation System (GEONS) software library which fuses different measurement types through an extended Kalman filter (EKF) framework. Optical measurements that are ingested in GEONS are first extracted from optical images by the cFS Goddard Image Analysis and Navigation Tool (cGIANT) app. If the imaged body is far enough away that it appears as a pixel or cluster of pixels, then bearing angles to the body centroid can be provided. If the body is close enough and the shape is known coarsely, then bearing angles and range to the body centroid can be derived from the limb. Bearing angles to individual surface features can also be extracted (i.e., terrain relative navigation (TRN)). Onboard guidance and control capabilities are being developed for a future release to perform autonomous station-keeping and trajectory correction maneuvers in multiple orbital regimes. Capabilities to enable distributed systems missions and constellations, such as crosslink measurements, and onboard time management are being developed as well. The first hardware implementation of autoNGC is a minimal size, weight, and power (SWaP) design allowing for inclusion into CubeSats and SmallSat-size buses. Advancements in miniaturized space processors, such as the SpaceCube 3.0 Mini and the SpaceCube Mini-Z are utilized for low SWaP while maintaining a high level of performance. The current enclosure design is 12 cm x 17 cm x 13.5 cm. The box mass is expected to be less than 2 kg, and the nominal power is 21 W. In order to accommodate a wide range of missions, the hardware interfaces are designed for flexibility with a variety of sensor inputs. Through comprehensive testing in the software-in-the-loop, processor-in-the-loop, and hardware-in-the-loop test beds that are concurrently being developed, autoNGC is expected to achieve TRL 6 by late 2024.

Sun Hur-Diaz↗
DOE OSTI2013

HIGH-RESOLUTION IMAGING OF THE ATLBS REGIONS: THE RADIO SOURCE COUNTS

The Australia Telescope Low-brightness Survey (ATLBS) regions have been mosaic imaged at a radio frequency of 1.4 GHz with 6'' angular resolution and 72 {mu}Jy beam{sup -1} rms noise. The images (centered at R.A. 00{sup h}35{sup m}00{sup s}, decl. -67 Degree-Sign 00'00'' and R.A. 00{sup h}59{sup m}17{sup s}, decl. -67 Degree-Sign 00'00'', J2000 epoch) cover 8.42 deg{sup 2} sky area and have no artifacts or imaging errors above the image thermal noise. Multi-resolution radio and optical r-band images (made using the 4 m CTIO Blanco telescope) were used to recognize multi-component sources and prepare a source list; the detection threshold was 0.38 mJy in a low-resolution radio image made with beam FWHM of 50''. Radio source counts in the flux density range 0.4-8.7 mJy are estimated, with corrections applied for noise bias, effective area correction, and resolution bias. The resolution bias is mitigated using low-resolution radio images, while effects of source confusion are removed by using high-resolution images for identifying blended sources. Below 1 mJy the ATLBS counts are systematically lower than the previous estimates. Showing no evidence for an upturn down to 0.4 mJy, they do not require any changes in the radio source population down to the limit of the survey. The work suggests that automated image analysis for counts may be dependent on the ability of the imaging to reproduce connecting emission with low surface brightness and on the ability of the algorithm to recognize sources, which may require that source finding algorithms effectively work with multi-resolution and multi-wavelength data. The work underscores the importance of using source lists-as opposed to component lists-and correcting for the noise bias in order to precisely estimate counts close to the image noise and determine the upturn at sub-mJy flux density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Multi-View, Deep Learning, and Contextual Analysis: Promising Approaches for sUAS Land Cover Classification

Small Unmanned Aircraft System (sUAS) image collection and preprocessing to produce orthoimages, point clouds, and digital surface models have made great leaps forward in the past years. These advances and the wide spectrum of existing and emerging sUAS applications mandate parallel improvements in the algorithms used for image classification that take into consideration the specific characteristics of sUAS imagery. This chapter presents several alternative approaches to improve classification accuracy using redundant information in overlapped sUAS imagery captured in a typical sUAS mission. These include Deep Convolution Neural Network (DCNN) classification, Fully Convolutional Neural (FCN) Network, and contextual relationships under an Object-Based Image Analysis (OBIA) framework. The chapter synthesizes the results of implementing the introduced classification approaches using a case study of high-resolution sUAS images captured in a wetland area in Central Florida.

Liu, Tao↗