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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 271 records · Page 15

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NASA NTRS2001

Composition of Hydrothermal Vent Microbial Communities as Revealed by Analyses of Signature Lipids, Stable Carbon Isotopes and Aquificales Cultures

Extremely thermophilic microbial communities associated with the siliceous vent walls and outflow channel of Octopus Spring, Yellowstone National Park, have been examined for lipid biomarkers and carbon isotopic signatures. These data were compared with that obtained from representatives of three Aquificales genera. Thermocrinis ruber. "Thermocrinis sp. HI", Hydrogenobacter thermophilus TK-6, Aquifex pyrophilus and Aquifex aeolicus all contained phospholipids composed not only of the usual ester-linked fatty acids, but also ether-linked alkyls. The fatty acids of all cultured organisms were dominated by a very distinct pattern of n-C-20:1 and cy-C-21 compounds. The alkyl glycerol ethers were present primarily as CIS() monoethers with the expection of the Aquifex spp. in which dialkyl glycerol ethers with a boarder carbon-number distribution were also present. These Aquificales biomarker lipids were the major constituents in the lipid extracts of the Octopus Spring microbial samples. Two natural samples, a microbial biofilm growing in association with deposition of amorphous silica on the vent walls at 92 C, and the well-known 'pink-streamers community' (PSC), siliceous filaments of a microbial consortia growing in the upper outflow channel at 87 C were analyzed. Both the biofilm and PSC samples contained mono and dialkyl glycerol ethers with a prevalence of C-18 and C-20 alkyls. Phospholipid fatty acids were comprised of both the characteristic Aquificales n-C-20:1 and cy-C-21, and in addition, a series of iso-branched fatty acids from i-C-15:0 to i-C-21:0, With i-C-17:0 dominant in the PSC and i-C-19:0 in the biofilm, suggesting the presence of two major bacterial groups. Bacteriohopanepolyols were absent and the minute quantities of archaeol detected showed that Archaea were only minor constituents. Carbon isotopic compositions of the PSC yielded information about community structure and likely physiology. Biomass was C-13-depleted (10.9%) relative to available CO2 from the source water inorganic carbon pool with lipids further depleted by 6.3% relative to biomass The C-20-21 Aquificales fatty acids of the PSC were somewhat heavier than the iso-branched fatty acids. The carbon isotopic signatures of lipid biomarkers were also explored using a pure culture, T ruber, previously isolated from the PSC. Cells grown on C02 with O2 and both H2 and thiosulfate as electron donors were only slightly depleted (3.3%) relative to the C-source while cells grown on formate with O2 showed a major discrimination (19.7%), possibly the result of a metabolic branch point involving the assimilation of C-formate to biomass and the dissimilation to CO2 associated with energy production. T. ruber lipids were slightly heavier than biomass (+1.3%) whether cells were grown using CO2 or formate. Fatty acids from CO2 grown T. ruber cells were a so slightly heavier (average +2.1%) than biomass. The relatively depleted PSC C-20-21 fatty acids suggest that any associated Thermocrinis biomass would also be similarly depleted and much too light to be explained by growth on CO2. The C-fractionations determined with the pure culture suggest that growth of Thermocrinis in the PSC is more likely to occur on formate, presumably generated by geothermal activity. This study points to the value of the analysis of the structural and isotopic composition of lipid blomarkers both in pure culture studies, and in establishing community structure and physiology, as a complement to genomic profiles of microbial diversity. This is especially so when the members of the microbial community are novel and difficult to cultivate in the laboratory.

Jahnke, Linda L.↗

NASA NTRS2001

Composition of Hydrothermal Vent Microbial Communities as Revealed by Analyses of Signature Lipids, Stable Carbon Isotopes and Aquificales Cultures

Jahnke, Linda L.↗

NASA NTRS2019

ATD-2 TFDM Terminal Publication Service (TTP)

Learn the many benefits of the newest SWIM feed from the surface system. This will discuss current options to onboard with this feed, allow participants to ask questions and provide some examples of how the data can be used. Service Includes Flight Data Individual flight updates containing flight identifiers, targeted times, actual times, runway, parking gate, spot, departure fix (predicted, assigned, actual as appropriate), flight states, and more. Airport Information Airport configurations, airport and runway rates, ramp closures, runway closures, taxiway closures. Traffic Management Restrictions Call for Release programs departure MIT/MINIT restrictions, departure stop/ground stop programs. Along with list of impacted flights for each. Flight Delay Airport and runway delay by arrival, departure, and total. Operational Metrics Metrics on airport throughput and individual flight metrics. Surface Metering Program SMP start / end times, metering constraint type / details, updates to existing programs, TMAT compliance window, departure queue length, and more.

Gorman, Shawn M.↗

NASA NTRSDate not supplied

Angle-of-Attack Sweep with Mesh Adaptation for High-Lift Configurations

This paper reports an angle-of-attack (alpha) sweep study with mesh adaptation for the high-lift configuration - JAXA Standard Model (JSM) from the 3rd AIAA High-Lift Prediction Workshop. The method of angle-of-attack (alpha) continuation, where the flow-field at a certain angle of attack is initialized from the solution obtained at the previous angle of attack, is applied to adapted unstructured meshes. Since the meshes are continuously adapted, flow-field initialization on a particular mesh for a certain angle is done through linear interpolation of the solution from the previous mesh. Interpolated initial conditions usually prevent massively separated solutions that may otherwise occur with impulsive initial conditions. Alpha continuations are done in both forward (increasing alpha) and reverse (decreasing alpha) directions, resulting in the formation of hysteresis loops. Skin frictions are compared with the wind-tunnel oil flow images and pressure coefficients are compared with the wind-tunnel values, at selected angles of attack. Final paper will include results also for the high-lift version of the Common Research Model (CRM-HL) from the 4th AIAA High-Lift Prediction Workshop. A thorough comparison of the results will also be made with the available wind-tunnel data.

Mesh Adaptation↗

NASA NTRS2011

The Invasive Species Forecasting System

The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these features enable a degree of decentralization and distributed ownership that have helped other types of scientific information services succeed in recent years.

Schnase, John↗

DOE OSTI2025

Educational Consortium for Energy-related Data Science & Computation in Building Engineering Programs

The project spearheaded by Pennsylvania State University aims to address the growing need for integrating energy-focused computation and data science into building engineering education. As the demand for energy-efficient building designs and operations increases, the educational sector must adapt to equip future engineers with the necessary skills. This initiative responds to this need by developing a consortium that unites multiple institutions to enhance curriculum development, dataset curation, and resource sharing, thereby ensuring students are well-prepared for the evolving energy sector. The primary goal of the project is to establish a consortium that will develop and disseminate educational materials and training programs focused on energy-related data science and computation. Key accomplishments include the creation of a beta website for resource sharing, the development of training programs and standalone modules, and the curation of datasets accessible to the public. This effort will culminate in a curriculum that incorporates advanced modeling technologies and data science skills into building engineering programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Tracking cropland transitions: A comparative analysis of U.S. land cover change data

There are a growing number of land cover data available for the conterminous United States, supporting various applications ranging from biofuel regulatory decisions to habitat conservation assessments. These datasets vary in their source information, frequency of data collection and reporting, land class definitions, categorical detail, and spatial scale and time intervals of representation. These differences limit direct comparison, contribute to disagreements among studies, confuse stakeholders, and hamper our ability to confidently report key land cover trends in the U.S. Here we assess changes in cropland derived from the Land Change Monitoring, Assessment, and Projection (LCMAP) dataset from the U.S. Geological Survey and compare them with analyses of three established land cover datasets across the coterminous U.S. from 2008-2017: (1) the National Resources Inventory (NRI), (2) a dataset Lark et al. 2020 derived from the Cropland Data Layer (CDL), and (3) a dataset from Potapov et al. 2022. LCMAP reports more stable cropland and less stable noncropland in all comparisons, likely due to its more expansive definition of cropland which includes managed grasslands (pasture and hay). Despite these differences, net cropland expansion from all four datasets was comparable (5.18-6.33 million acres), although the geographic extent and type of conversion differed. LCMAP projected the largest cropland expansion in the southern Great Plains, whereas other datasets projected the largest expansion in the northwestern and central Midwest. Most of the pixel-level disagreements (86%) between LCMAP and Lark et al. 2020 were due to definitional differences among datasets, whereas the remainder (14%) were from a variety of causes. Cropland expansion in the LCMAP likely reflects conversions of more natural areas, whereas cropland expansion in other data sources also captures conversion of managed pasture to cropland. The particular research question considered (e.g., habitat versus soil carbon) should influence which data source is more appropriate.

60 APPLIED LIFE SCIENCES↗

NASA NTRSDate not supplied

A New Statistical Estimate of the Radar Coverage of the Low Earth Orbit Debris Environment

For over three decades, the NASA Orbital Debris Program Office (ODPO) has used the Goldstone Orbital Debris Radar, Haystack Ultrawideband Satellite Imaging Radar (HUSIR), and Haystack Auxiliary (HAX) radar assets to collect data on the low Earth orbit (LEO) debris environment. Each radar, with its unique beamwidth, altitude and inclination coverage, and limiting size threshold, operates in a beam park mode to statistically sample the orbital debris population in LEO. Provided that these assets are shared with other users, the orbital debris data collection is not continuous; rather, intermittent data collects are acquired and sent to the NASA ODPO. To understand the sampling process conducted by each radar over time and any related observational biases, a Statistical Confirmation of Radar Uniformity or Bias (SCRUB) code has been implemented to model the coverage of these assets for informing future operations, as well as usage of the data collected from these ground-based sensors. For this analysis, Right Ascension of the Ascending Node (RAAN) is used as a metric to measure statistical coverage. A complete survey of the LEO environment is understood to be measurements that sufficiently sample all values of RAAN for each altitude-inclination pair visible from the radar asset. Regions of incompleteness or statistical bias can help inform future observation campaigns. The SCRUB tool evaluates the coverage of the LEO environment, not by examining individual objects that may pass through a sensor’s field of view (FOV), but by determining which orbit planes pass through the FOV. Once a pointing geometry for a radar site, observation time, and range extent are configured by the user, SCRUB computes the inclinations and altitudes that are visible by the sensor. For each inclination-altitude pair, there is a distinct pair of possible RAAN values, corresponding to the ascending and descending orbit passing through that point in the sensor cone. Repeating this process for all points in the beam, and for multiple time periods during an observation window, creates a matrix of all inclination-altitude-RAAN combinations that are visible during a sensor run. This process can then be repeated for all observations within a year (for an annual survey), propagating all the RAAN values to a common epoch, typically the start of a calendar year, and combining the observations to assemble a full estimate of the RAAN coverage of the LEO environment. This RAAN coverage can then be analyzed for uniformity of sampling, within a certain inclination-altitude pair, or between larger regions of the space environment. This paper provides a general overview of the radar assets utilized by ODPO, typical analysis data products assuming circular orbits, and a discussion of the algorithms that feed between modeling and measurement operations. Following the description of the algorithm, estimates of coverage using HUSIR radar data collected from multiple years are developed and compared.

Chris L Ostrom↗

DOE OSTI2025

LCLS Big Data Handling – How I Learned to Stop Worrying and Love the Data Deluge

Advanced data and computing systems are vital to Linac Coherent Light Source (LCLS) operations, data interpretation and overall scientific productivity. The transition to MHz-era operation marks a fundamental change in scale that requires new infrastructure and architectures to link LCLS to the required scale of computing needed for scientific interpretation. The LCLS-II Data System meets big data challenges by implementing configurable data reduction that can adapt to multiple science areas, real-time analysis frameworks to provide visualization and fast feedback, and the ability to transfer data to local and remote computational facilities for near real time analysis at the appropriate scale. Feature extracted information generated in the data analysis pipeline - at the edge, local compute, or remote High-Performance Computing (HPC) resources - can be used to steer experiments and inform user decisions during beam time. Artificial Intelligence and Machine Learning (AI/ML) techniques present new opportunities to rapidly analyse large datasets and direct experiments, but create new challenges in scaling, adaptability, complexity, and trustworthiness. We describe how the LCLS-II Data System architecture addresses its data-driven challenges in the areas of data acquisition, data processing, data management, and workflow orchestration to decrease the overall time-to-science and provide a vision for future developments.

artificial intelligence↗

NASA NTRS1992

Mapping the mineralogy and lithology of Canyonlands, Utah with imaging spectrometer data and the multiple spectral feature mapping algorithm

The sedimentary sections exposed in the Canyonlands and Arches National Parks region of Utah (generally referred to as 'Canyonlands') consist of sandstones, shales, limestones, and conglomerates. Reflectance spectra of weathered surfaces of rocks from these areas show two components: (1) variations in spectrally detectable mineralogy, and (2) variations in the relative ratios of the absorption bands between minerals. Both types of information can be used together to map each major lithology and the Clark spectral features mapping algorithm is applied to do the job.

Clark, Roger N.↗

NASA NTRS1976

Satellite cloud climatology of summertime cumulus research areas

Defense Meteorological Satellite Program data available for the summer of 1974 was used to construct a cloud climatology of areas where weather modification experiments are currently being conducted or planned; the three High Plains Experiment sites at Colby, Kansas, Big Springs, Texas, and Miles City, Montana; South Park, Colorado, where the South Park Area Cumulus Experiment is being conducted; and the National Hail Research Experiment area in northeastern Colorado. Digital data tapes were produced from the transparencies, obtained from the sun-synchronous polar-orbiting satellite passing over the study areas at about 1200 local time, and a computer analysis was carried out, producing areas and numbers of clouds for each area and day as well as providing data for cumulative averages over selected time periods for each study area.

Stodt, R. W.↗

NASA NTRS2021

Mangrove Carbon Stocks in Pongara National Park, Gabon

Mangroves are recognized for their valued ecosystem services to coastal areas, and the functional linkages between those services and ecosystem carbon stocks have been established. However, spatially explicit inventories are necessary to facilitate management and protection of mangroves, as well as providing a foundation for payment for ecosystem service programs such as REDD+. We conducted an inventory of carbon stocks in mangroves within Pongara National Park (PNP), Gabon using a stratified random sampling design based on forest canopy height derived from TanDEM-X remote sensing data. Ecosystem carbon pools, including aboveground and belowground biomass and necromass, and soil carbon to a depth of 2 m were assessed using measurements and samples from plots distributed among three canopy height classes within the park. There were two mangrove species within the inventory area in PNP, Rhizophora racemosa and R. harrisonii. R. harrisonii was predominant in the sparse, low-stature stands that dominated the west side of the park. In the east side of the park, both species occurred in tall-stature stands, with tree height often exceeding 30 m. Canopy height was an effective means to stratify the inventory area, as biomass was significantly different among the height classes. Despite those differences in aboveground biomass, the soil carbon density was not significantly different among height classes. Soils were the main component of the ecosystem carbon stock, accounting for over 84% of the total. The ecosystem carbon density ranged from 644 to 943 Mg C ha−1 among the three height classes. The ecosystem carbon stock within PNP is estimated to be 40,588 Gg C. The combination of pre-inventory information about stand conditions and their spatial distribution within the assessment area obtained from remote sensing data and a spatial decision support system were fundamental to implementing this relatively large-scale field inventory. This work exemplifies how mangrove carbon stocks can be quantified to augment national C reporting statistics, provide a baseline for projects involving monitoring, reporting and verification (i.e., MRV), and provide data on the forest composition and structure for sustainable management and conservation practices.

Carl C Trettin↗

NASA NTRS1993

Upper Atmosphere Research Satellite attitude disturbances during shadow entry and exit

The Upper Atmosphere Research Satellite (UARS), as with the Landsat-4 and Landsat-5 spacecraft, experiences large attitude disturbances when entering and exiting the Earth's shadow. Previous investigations have provided some evidence linking these disturbances to rapid bending of the solar array but have also raised questions. For example, the magnitudes of the roll attitude disturbances have shown an unmolested asymmetry, and the timing of the disturbances at sunrise appears to disagree with the modeled timing. A better understanding of this phenomenon is important in assessing the implications for UARS science gathering and for future mission design analysis. To this end, UARS attitude, sensor, and actuator data are used to evaluate the disturbances as they vary with solar beta angle and solar array drive angle. The attitude data are examined during specific periods of interest, such as the month in which the solar array was parked in its high-noon position, and are also tracked from the beginning of the mission to determine any trends that may result from changing mass properties due to cryogen boiloff and propellant usage. Attitude rate and torque profiles are derived from inertial reference until data and related to the disturbances seen in the attitude data. The timing of the disturbances with respect to spacecraft sunset and sunrise is characterized to allow event predictions. Stability during the disturbances is discussed in terms of science instrument requirements. Finally, the results are compared with the behavior predicted by models that are based on solar array bending.

Lambertson, M.↗

NASA NTRS1974

Use of ERTS-1 data: Summary report of work on ten tasks

The author has identified the following significant results. Depth mapping's for a portion of Lake Michigan and at the Little Bahama Bank test site have been verified by use of navigation charts and on-site visits. A thirteen category recognition map of Yellowstone Park has been prepared. Model calculation of atmospheric effects for various altitudes have been prepared. Radar, SLAR, and ERTS-1 data for flooded areas of Monroe County, Michigan are being studied. Water bodies can be reliably recognized and mapped using maximum likelihood processing of ERTS-1 digital data. Wetland mapping has been accomplished by slicing of single band and/or ratio processing of two bands for a single observation date. Both analog and digital processing have been used to map the Lake Ontario basin using ERTS-1 data. Operating characteristic curves were developed for the proportion estimation algorithm to determine its performance in the measurement of surface water area. The signal in band MSS-5 was related to sediment content of waters by modelling approach and by relating surface measurements of water to processed ERTS data. Radiance anomalies in ERTS-1 data could be associated with the presence of oil on water in San Francisco Bay, but the anomalies were of the same order as those caused by variations in sediment concentration and tidal flushing.

Thomson, F. J.↗

NASA NTRS1972

Unsupervised classification of remote multispectral sensing data

The new unsupervised classification technique for classifying multispectral remote sensing data which can be either from the multispectral scanner or digitized color-separation aerial photographs consists of two parts: (a) a sequential statistical clustering which is a one-pass sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. Applications of the technique using an IBM-7094 computer on multispectral data sets over Purdue's Flight Line C-1 and the Yellowstone National Park test site have been accomplished. Comparisons between the classification maps by the unsupervised technique and the supervised maximum liklihood technique indicate that the classification accuracies are in agreement.

Su, M. Y.↗

NASA NTRS1984

Classifying northern forests using Thematic Mapper Simulator data

Thematic Mapper Simulator data were collected over a 23,200 hectare forested area near Baxter State Park in north-central Maine. Photointerpreted ground reference information was used to drive a stratified random sampling procedure for waveband discriminant analyses and to generate training statistics and test pixel accuracies. Stepwise discriminant analyses indicated that the following bands best differentiated the thirteen level II - III cover types (in order of entry): near infrared (0.77 to 0.90 micron), blue (0.46 0.52 micron), first middle infrared (1.53 to 1.73 microns), second middle infrared (2.06 to 2.33 microsn), red (0.63 to 0.69 micron), thermal (10.32 to 12.33 microns). Classification accuracies peaked at 58 percent for thirteen level II-III land-cover classes and at 65 percent for ten level II classes.

Nelson, R. F.↗

NASA NTRS1984

Image variance and spatial structure in remotely sensed scenes

Digital images derived by scanning air photos and through acquiring aircraft and spcecraft scanner data were studied. Results show that spatial structure in scenes can be measured and logically related to texture and image variance. Imagery data were used of a South Dakota forest; a housing development in Canoga Park, California; an agricltural area in Mississppi, Louisiana, Kentucky, and Tennessee; the city of Washington, D.C.; and the Klamath National Forest. Local variance, measured as the average standard deviation of brightness values within a three-by-three moving window, reaches a peak at a resolution cell size about two-thirds to three-fourths the size of the objects within the scene. If objects are smaller than the resolution cell size of the image, this peak does not occur and local variance simply decreases with increasing resolution as spatial averaging occurs. Variograms can also reveal the size, shape, and density of objects in the scene.

Woodcock, C. E.↗

NASA NTRS2004

Emission From Rotation-Powered Pulsars and Magnetars

I will review the latest developments in understanding the high-energy emission of rotation-powered pulsars and magnetically-powered Anomalous X-ray Pulsars (AXPs) and Soft Gamma-Ray Repeaters (SGRs). These fields have been extremely active in the last few years, both observationally and theoretically, driven partly by new X-ray data from Chandra, XMM-Newton and RXTE. At the same time, the Parkes Multibeam Survey has discovered over 700 new radio pulsars, some of them young, coincident with EGRET sources and others having magnetar-strength magnetic fields. These new observations are raising important questions about neutron star birth and evolution, as well as the properties of their high-energy emission.

Harding, Alice K.↗