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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Analysis of ISS Plasma Interaction

To date, the International Space Station (ISS) has been one of the largest objects flown in lower earth orbit (LEO). The ISS utilizes high voltage solar arrays (160V) that are negatively grounded leading to pressurized elements that can float negatively with respect to the plasma. Because laboratory measurements indicate a dielectric breakdown potential difference of 80V, arcing could occur on the ISS structure. To overcome the possibility of arcing and clamp the potential of the structure, two Plasma Contactor Units (PCUs) were designed, built, and flown. Also a limited amount of measurements of the floating potential for the present ISS configuration were made by a Floating Potential Probe (FPP), indicating a minimum potential of 24 Volts at the measurement location. A predictive tool, the ISS Plasma Interaction Model (PIM) has been developed accounting for the solar array electron collection, solar array mast wire and effective conductive area on the structure. The model has been used for predictions of the present ISS configuration. The conductive area has been inferred based on available floating potential measurements. Analysis of FPP and PCU data indicated distribution of the conductive area along the Russian segment of the ISS structure. A significant input to PIM is the plasma environment. The International Reference Ionosphere (IRI 2001) was initially used to obtain plasma temperature and density values. However, IRI provides mean parameters, leading to difficulties in interpretation of on-orbit data, especially at eclipse exit where maximum charging can occur. This limits our predicative capability. Satellite and Incoherent Scatter Radar (ISR) data of plasma parameters have also been collected. Approximately 130,000 electron temperature (Te) and density (Ne) pairs for typical ISS eclipse exit conditions have been extracted from the reduced Langmuir probe data flown aboard the NASA DE-2 satellite. Additionally, another 18,000 Te and Ne pairs of ISR data from several radar locations around the globe were used to assure consistency of the satellite data. PIM predictions for ISS charging made with this data correlated very well with FPP data, indicating that the general physics of spacecraft charging with high voltage solar arrays have been captured. The predictions also provided the probabilities of occurrences for ISS charging. These probabilities give a numerical measure of the number of times when the ISS will approach or exceed the vehicle plasma hazard conditions for each configuration. In this paper we shall present the interaction mechanisms between the ISS and the surrounding plasma and give an overview of the PIM components. PIM predictions are compared with available data followed by a discussion of the variability of plasma parameters and the conductive area on the ISS. The ISS PIM will be further tested and verified as data from the Floating Potential Measurement Unit become available, and construction of the ISS continues.

Reddell, Brandon↗
NASA NTRS1993

Properties and decay of stratospheric aerosols in the Arctic following the 1991 eruptions of Mount Pinatubo

Sunphotometer observations made from an aircraft several months after the June 1991 eruptions of Mount Pinatubo are used to quantify the spectral opacity of the Arctic stratosphere. Ancillary surface-based measurements are presented in support of the aircraft data that show large increases in stratospheric optical depth attributed to the presence of volcanic aerosols. Visible optical depths greater than 0.2 were observed during flight segments flown above the tropopause. An inversion algorithm and the optical depth data are used to infer effective aerosol size distributions. The distributions tend to be bimodal, having a large-partical mode radius of about 0.50 micron and a small-particle mode of higher concentration with radii less than 0.18 micron. Surface measurements made during spring 1992 and 1993 are also used to estimate a time constant (e-folding time) of about 13.5 months assuming that the Arctic stratosphere's opacity decays exponentially; this estimate is larger than decay times observed following other major volcanic eruptions. Our results suggest that any climate perturbations in the Arctic caused by eruptions of Pinatubo may be significant and will very likely persist longer than any volcanically-induced changes observed there during the past century.

Stone, Robert S.↗
NASA NTRS1977

Chemical stratigraphy of the Apollo 17 deep drill cores 70009-70007

A description is presented of an analysis of a total of 26 samples from three core segments (70009, 70008, 70007) of the Apollo 17 deep drill string. The deep drill string was taken about 700 m east of the Camelot Crater in the Taurus-Littrow region of the moon. Three core segments have been chemically characterized from the mainly coarse-grained upper portion of the deep drill string. The chemical data suggest that the entire 70007-70009 portion of the deep drill string examined was not deposited as a single unit, but was formed by several events sampling slightly different source materials which may have occurred over a relatively short period of time. According to the data from drill stem 70007, there were at least two phases of deposition. Core segment 70009 is probably derived from somewhat different source material than 70008. It seems to be a very well mixed material.

Ehmann, W. D.↗
NASA NTRS1990

Primary and diagenetic controls of isotopic compositions of iron-formation carbonates

Results are presented on parallel analyses of carbonate and chert microbands in segments from the early Proterozoic Dales Gorge Member of the Brockman Iron Formation (western Australia), including data on isotopic, chemical, and mineralogic variations in microbanded carbonates, cherts, and coexisting minerals in four core segments from Paraburdoo and one from Wittenoom. It is shown that patterns of variation observed in isotopic abundance and mineral composition can be consistently explained in terms of diagenetic replacement of fine-grained primary precipitates by secondary ones, rather than by mineral-dependent fractionations, metamorphism, or the influence of large volumes of water in an open system.

Kaufman, Alan J.↗
DOE OSTI2024

CryoSegNet: accurate cryo-EM protein particle picking by integrating the foundational AI image segmentation model and attention-gated U-Net

Picking protein particles in cryo-electron microscopy (cryo-EM) micrographs is a crucial step in the cryo-EM-based structure determination. However, existing methods trained on a limited amount of cryo-EM data still cannot accurately pick protein particles from noisy cryo-EM images. The general foundational artificial intelligence–based image segmentation model such as Meta’s Segment Anything Model (SAM) cannot segment protein particles well because their training data do not include cryo-EM images. Here, we present a novel approach (CryoSegNet) of integrating an attention-gated U-shape network (U-Net) specially designed and trained for cryo-EM particle picking and the SAM. The U-Net is first trained on a large cryo-EM image dataset and then used to generate input from original cryo-EM images for SAM to make particle pickings. CryoSegNet shows both high precision and recall in segmenting protein particles from cryo-EM micrographs, irrespective of protein type, shape and size. On several independent datasets of various protein types, CryoSegNet outperforms two top machine learning particle pickers crYOLO and Topaz as well as SAM itself. The average resolution of density maps reconstructed from the particles picked by CryoSegNet is 3.33 Å, 7% better than 3.58 Å of Topaz and 14% better than 3.87 Å of crYOLO. It is publicly available at https://github.com/jianlin-cheng/CryoSegNet

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

Reduction of structural loads using maneuver load control on the Advanced Fighter Technology Integration (AFTI)/F-111 mission adaptive wing

A transonic fighter-bomber aircraft, having a swept supercritical wing with smooth variable-camber flaps was fitted with a maneuver load control (MLC) system that implements a technique to reduce the inboard bending moments in the wing by shifting the spanwise load distribution inboard as load factor increases. The technique modifies the spanwise camber distribution by automatically commanding flap position as a function of flap position, true airspeed, Mach number, dynamic pressure, normal acceleration, and wing sweep position. Flight test structural loads data were obtained for loads in both the wing box and the wing root. Data from uniformly deflected flaps were compared with data from flaps in the MLC configuration where the outboard segment of three flap segments was deflected downward less than the two inboard segments. The changes in the shear loads in the forward wing spar and at the roots of the stabilators also are presented. The camber control system automatically reconfigures the flaps through varied flight conditions. Configurations having both moderate and full trailing-edge flap deflection were tested. Flight test data were collected at Mach numbers of 0.6, 0.7, 0.8, and 0.9 and dynamic pressures of 300, 450, 600, and 800 lb/sq ft. The Reynolds numbers for these flight conditions ranged from 26 x 10(exp 6) to 54 x 10(exp 6) at the mean aerodynamic chord. Load factor increases of up to 1.0 g achieved with no increase in wing root bending moment with the MLC flap configuration.

Thornton, Stephen V.↗
NASA NTRS1991

Integration of visible-through microwave-range multispectral image data sets for geologic mapping

Multispectral remote sensing data sets collected during the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 in the southwestern U.S. were used to produce thematic image maps showing details of the surface geology. LANDSAT TM (Thematic Mapper) images were used to map the distribution of clays, carbonates, and iron oxides. AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data were used to identify and map calcite, dolomite, sericite, hematite, and geothite, including mixtures. TIMS (Thermal Infrared Multispectral Scanner) data were used to map the distribution of igneous rock phases and carbonates based on their silica contents. AIRSAR (Airborne Synthetic Aperture Radar) data were used to map surface textures related to the scale of surface roughness. The AIRSAR also allowed identification of previously unmapped fault segments and structural control of lithology and minerology. Because all of the above data sets were geographically referenced, combination of different data types and direct comparison of the results with conventional field and laboratory data sets allowed improved geologic mapping of the test site.

Kruse, Fred A.↗
NASA NTRS2009

Ares I-X: On the Threshold of Exploration

Ares I-X, the first flight of the Ares I crew launch vehicle, is less than a year from launch. Ares I-X will test the flight characteristics of Ares I from liftoff to first stage separation and recovery. The flight also will demonstrate the computer hardware and software (avionics) needed to control the vehicle; deploy the parachutes that allow the first stage booster to land in the ocean safely; measure and control how much the rocket rolls during flight; test and measure the effects of first stage separation; and develop and try out new ground handling and rocket stacking procedures in the Vehicle Assembly Building (VAB) and first stage recovery procedures at Kennedy Space Center (KSC) in Florida. All Ares I-X major elements have completed their critical design reviews, and are nearing final fabrication. The first stage--four-segment solid rocket booster from the Space Shuttle inventory--incorporates new simulated forward structures to match the Ares I five-segment booster. The upper stage, Orion crew module, and launch abort system will comprise simulator hardware that incorporates developmental flight instrumentation for essential data collection during the mission. The upper stage simulator consists of smaller cylindrical segments, which were transported to KSC in fall 2008. The crew module and launch abort system simulator were shipped in December 2008. The first stage hardware, active roll control system (RoCS), and avionics components will be delivered to KSC in 2009. This paper will provide detailed statuses of the Ares I-X hardware elements as NASA's Constellation Program prepares for this first flight of a new exploration era in the summer of 2009.

Davis, Stephan R.↗
DOE OSTI2021

2021 Smoky Mountains Conference Data Challenge Synthetic-to-Real Domain Adaptation for Autonomous Driving Dataset

The dataset is comprised of both real and synthetic images from a vehicle's forward-facing camera. Each camera image is accompanied by a corresponding pixel-level semantic segmentation image (all files are .png files). In total, the dataset contains 5600 images in the training/validation set and 1400 images in the testing set. The training dataset contains mostly synthetic RGB images collected with a wide range of weather and lighting conditions using the CARLA simulator [1]. In addition, the training data also includes a small pre-selected subset of data from the Cityscapes training dataset – which is comprised of RGB-segmentation image pairs from driving scenarios in various European cities [2]. The testing data is split into three sets. The first set contains synthetic CARLA images with weather/lighting conditions that were not present in the training set. The second set is a subset of the Cityscapes testing dataset. Finally, the third set is an unknown testing set which will not be revealed to the participants until after the submission deadline. [1] Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., and Koltun, V. (2017, October). CARLA: An open urban driving simulator. In Conference on robot learning (pp. 1-16). PMLR. [2] Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., ... and Schiele, B. (2016). The cityscapes dataset for semantic urban scene understanding. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3213-3223).

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2014

Field Results from Three Campaigns to Validate the Performance of the Miniaturized Laser Heterodyne Radiometer (Mini‐LHR) for Measuring Carbon Dioxide and Methane in the Atmospheric Column

In a collaboration between NASA GSFC and GWU, a low-cost, surface instrument is being developed that can continuously monitor key carbon cycle gases in the atmospheric column: carbon dioxide (CO2) and methane (CH4). The instrument is based on a miniaturized, laser heterodyne radiometer (LHR) using near infrared (NIR) telecom lasers. Despite relatively weak absorption line strengths in this spectral region, spectrallyresolved atmospheric column absorptions for these two molecules fall in the range of 60-80% and thus sensitive and precise measurements of column concentrations are possible. In the last year, the instrument was deployed for field measurements at Park Falls, Wisconsin; Castle Airport near Atwater, California; and at the NOAA Mauna Loa Observatory in Hawaii. For each subsequent campaign, improvement in the figures of merit for the instrument has been observed. In the latest work the absorbance noise is approaching 0.002 optical density (OD) noise on a 1.8 OD signal. An overview of the measurement campaigns and the data retrieval algorithm for the calculation of column concentrations will be presented. For light transmission through the atmosphere, it is necessary to account for variation of pressure, temperature, composition, and refractive index through the atmosphere that are all functions of latitude, longitude, time of day, altitude, etc. For temperature, pressure, and humidity profiles with altitude we use the Modern-Era Retrospective Analysis for Research and Applications (MERRA) data. Spectral simulation is accomplished by integrating short-path segments along the trajectory using the SpecSyn spectral simulation suite developed at GW. Column concentrations are extracted by minimizing residuals between observed and modeled spectrum using the Nelder-Mead simplex algorithm. We will also present an assessment of uncertainty in the reported concentrations from assumptions made in the meteorological data, LHR instrument and tracker noise, and radio frequency bandwidth and describe additional future goals in instrument development and deployment target

meteorological data↗
NASA NTRS1976

Experimental-analytical correlation of optimum duct acoustic liner performance

Mode matching and segmented duct analytical models have been developed to take advantage of relative placement of liner segments in the design of optimal duct acoustic liners of one, two, and three segments. This paper presents experimental results which were obtained for liners installed in a rectangular duct for the case with no mean airflow through the duct. Excellent correlation is shown between the analytical and experimental data, thus verifying the analytical procedures used to design the optimum segmented lining configurations.

Patterson, J. D.↗
NASA NTRS1979

Large Area Crop Inventory Experiment (LACIE). Phase 3 direct wheat study of North Dakota

The author has identified the following significant results. The green number and brightness scatter plots, channel plots of radiance values, and visual study of the imagery indicate separability between barley and spring wheat/oats during the wheat mid-heading to mid-ripe stages. In the LACIE Phase 3 North Dakota data set, the separation time is more specifically the wheat soft dough stage. At this time, the barley is ripening, and is therefore, less green and brighter than the wheat. Only 4 of the 18 segments studied indicate separation of barley/other spring small grain, even though 11 of the segments have acquisitions covering the wheat soft dough stage. The remaining seven segments had less than 5 percent barley based on ground truth data.

Kinsler, M. C.↗
NASA NTRS1979

Estimating crop proportions from remotely sensed data

The classification/pixel-count method for estimating the proportion of wheat in each segment is theoretically biased even if all distributional assumptions are met. Alternative ways to estimate crop proportions are examined and their performance testing is considered. Topics covered include general linear functional estimates, the method of moments, and maximum likelihood estimators.

Feiveson, A. H.↗
DOE OSTI2020

Machine learning-based multidomain processing for texture-based image segmentation and analysis

Atomic and molecular resolved atomic force microscopy (AFM) images offer unique insights into materials' properties such as local ordering, molecular orientation, and topological defects, which can be used to pinpoint physical and chemical interactions occurring at the surface. Utilizing machine learning for extracting underlying physical parameters increases the throughput of AFM data processing and eliminates inconsistencies intrinsic to manual image analysis, thus enabling the creation of reliable frameworks for qualitative and quantitative evaluation of experimental data. Here, we present a robust and scalable approach to the segmentation of AFM images based on flexible pre-selected classification criteria. The usage of supervised learning and feature extraction allows us to retain the consideration of specific problem-dependent features (such as types of periodical structures observed in the images and the associated numerical parameters: spacing, orientation, etc.). We highlight the applicability of this approach for the segmentation of molecular resolved AFM images based on the crystal orientation of the observed domains, automated selection of boundaries, and collection of relevant statistics. Finally, we outline a general strategy for machine learning-enabled analysis of nanoscale systems exhibiting periodic order that could be applied to any analytical imaging technique

36 MATERIALS SCIENCE↗
NASA NTRS2023

Neural-Based Compression Scheme for Solar Image Data

Studying the solar system and especially the Sun relies on the data gathered daily from space missions. These missions are data-intensive and compressing this data to make them efficiently transferable to the ground station is a twofold decision to make. Stronger compression methods, by distorting the data, can increase data throughput at the cost of accuracy which could affect scientific analysis of the data. On the other hand, preserving subtle details in the compressed data requires a high amount of data to be transferred, reducing the desired gains from compression. In this work, we propose a neural network-based lossy compression method to be used in NASA’s data-intensive imagery missions. We chose NASA’s Solar Dynamics Observatory (SDO) mission which transmits 1.4 terabytes of data each day as a proof of concept for the proposed algorithm. In this work, we propose an adversarially trained neural network, equipped with local and non-local attention modules to capture both the local and global structure of the image resulting in a better trade-off in rate-distortion (RD) compared to conventional hand-engineered codecs. The RD variational autoencoder used in this work is jointly trained with a channel-dependent entropy model as a shared prior between the analysis and synthesis transforms to make the entropy coding of the latent code more effective. We also studied how optimizing perceptual losses could help our neural compressor to preserve high-frequency details of the data in the reconstructed compressed image. Our neural image compression algorithm outperforms currently-in-use and state-of-the-art codecs such as JPEG and JPEG-2000 in terms of the RD performance when compressing extreme-ultraviolet (EUV) data. As a proof of concept for use of this algorithm in SDO data analysis, we have performed coronal hole (CH) detection using our compressed images, and generated consistent segmentations, even at a compression rate of ∼ 0.1 bits per pixel (compared to 8 bits per pixel on the original data) using EUV data from SDO.

Image coding↗
NASA NTRS2014

High-Speed On-Board Data Processing for Science Instruments

A new development of on-board data processing platform has been in progress at NASA Langley Research Center since April, 2012, and the overall review of such work is presented in this paper. The project is called High-Speed On-Board Data Processing for Science Instruments (HOPS) and focuses on a high-speed scalable data processing platform for three particular National Research Council's Decadal Survey missions such as Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS), Aerosol-Cloud-Ecosystems (ACE), and Doppler Aerosol Wind Lidar (DAWN) 3-D Winds. HOPS utilizes advanced general purpose computing with Field Programmable Gate Array (FPGA) based algorithm implementation techniques. The significance of HOPS is to enable high speed on-board data processing for current and future science missions with its reconfigurable and scalable data processing platform. A single HOPS processing board is expected to provide approximately 66 times faster data processing speed for ASCENDS, more than 70% reduction in both power and weight, and about two orders of cost reduction compared to the state-of-the-art (SOA) on-board data processing system. Such benchmark predictions are based on the data when HOPS was originally proposed in August, 2011. The details of these improvement measures are also presented. The two facets of HOPS development are identifying the most computationally intensive algorithm segments of each mission and implementing them in a FPGA-based data processing board. A general introduction of such facets is also the purpose of this paper.

Beyon, Jeffrey Y.↗
NASA NTRS1973

Wheat classification exercise, using 11 June 1973, ERTS MSS data for Fayette County, Illinois (for CITARS task)

The prime emphasis was on classification of pixels in field centers, away from boundary effects. Results were encouraging in both training and test field centers for wheat and other major types of vegetation present. However, the location of fields was found to be a serious problem and it was even more difficult to select field-center pixels for fields of sizes less than 20 acres (or even larger, depending upon field shape) for use in the field-center analysis. The majority of fields in the segment are less than 20 acres in size. ERTS-1 data were received on 12 September 1973. Ground truth information and aerial photography were received on 9 and 15 September. The data were analyzed and processed digitally using the ERIM multispectral software system.

Malila, W. A.↗
DOE OSTI2026

Correlating and Simulating Socio-Demographically Driven Residential End-Use Activity Schedules

Incorporating socio-demographic and behavioral considerations into decision-support tools is crucial for identifying gaps and addressing consumer needs to ensure reliable and affordable energy solutions. In energy simulation models, the correlation between socio-demographics and time-use behavior is not well-captured. Thus, we developed a large-scale simulation workflow to generate schedules for 10 residential activities across 24 population segments defined by age, income, and employment status. Using pre-pandemic 2015-2019 American Time Use Survey (ATUS) data, we used ANOVA to confirm the correlation between demographic factors and time use. We explored three k-modes clustering methods-backward, forward, and a new hybrid approach-to delineate the occupancy patterns based on demographics. Using the probability of cluster membership for each population segment and a time inhomogeneous Markov chain to generate activity transition probabilities for each cluster, we simulated 50,000 schedules per segment and validated them against the ATUS data. The hybrid method produced the most socio-demographically differentiated clusters while demonstrating comparable performance to other approaches, with an overall root mean square error of 0.12 for both weekday and weekend schedules. Thus, the hybrid method, where each cluster is dominated by certain demographic segments and occupancy patterns, offers more modeling versatility in terms of scenario analysis. The new workflow improves the socio demographic differentiation of energy consumption by considering differences in time use. This approach enables future research on demographically segmented time of use (TOU) energy consumption, including impacts of TOU utility bills and rate analysis, long-run marginal emissions, and energy retrofits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗