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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Spacecraft control/flexible structures interaction study

An initial study to begin development of a flight experiment to measure spacecraft control/flexible structure interactions was completed. The approach consisted of developing the equations of motion for a vehicle possessing a flexible solar array, then linearizing about some nominal motion of the craft. A set of solutions is assumed for array deflection using a continuous normal mode method and important parameters are identified. Interrelationships between these parameters, measurement techniques, and input requirements are discussed which assure minimization of special vehicle maneuvers and optimization of data to be obtained during the normal flight sequence. Limited consideration is given to flight data retrieval and processing techniques as correlated with the requirements imposed by the measurement system. Results indicate that inflight measurement of the bending and torsional mode shapes and respective frequencies, and damping ratios, is necessary. Other parameters may be measured from design data.

Kaplan, M. H.↗
NASA NTRS2010

Enhanced Microbial Detection Capabilities by a Rapid Portable Instrument

We present data describing a progression of continuing technology development - from expanding the detection capabilities of the current PTS unit to re-outfitting the instrument with a protein microarray increasing the number of detectable compounds. To illustrate the adaptability of the cartridge format, on-orbit operations data from the ISS demonstrate the detection of the fungal cell wall compound beta-glucan using applicable LOCAD-PTS cartridges. LOCAD-PTS is a handheld device consisting of a spectrophotometer, an onboard pumping mechanism, and data storage capabilities. A suite of interchangeable cartridges lined with four distinct capillaries allow a hydrated sample to mix with necessary reagents in the channels before being pumped to the optical well for spectrophotometric analysis. The reagents housed in one type of cartridge trigger a reaction based on the Limulus Amebocyte Lysate (LAL) assay, which results in the release of paranitroaniline dye. The dye is measured using a 395 nm filter. The LAL assay detects the Gram-negative bacterial cell wall molecule, endotoxin or lipopolysaccharide (LPS). The more dye released, the greater the concentration of endotoxin in the sample. Sampling, quantitative analysis, and data retrieval require less than 20 minutes. This is significantly faster than standard culture-based methods, which require at least a 24 hour incubation period.Using modified cartridges, we demonstrate the detection of Gram negative bacteria with protein microarray technology. Additionally, we provide data from multiple field tests where both standard and advanced PTS technologies were used. These tests investigate the transfer of target microbial molecules from one surface to another. Collectively, these data demonstrate that the new cartridges expand the number of compounds detected by LOCAD-PTS, while maintaining the rapid, in situ analysis characteristic of the instrument. The unit provides relevant data for verifying sterile sample collection protocols, which are critical for conducting accurate scientific experiments during future missions to the Moon and Mars.

Morris, Heather↗
NASA NTRS2023

Easy, Scalable Subsetting of GEDI Point Clouds

The GEDI Subsetter, a Python tool developed for NASA’s Multi-mission Algorithm and Analysis Platform (MAAP), optimizes the accessibility and visualization of GEDI point clouds by enabling users to efficiently subset data in a convenient, scalable manner. Complex science data often requires users to learn new software skills and handle many large files. Handling and cleaning large data sets is tedious and error-prone. These challenges significantly impede analysis. One of the goals of NASA's MAAP is to provide a platform that lowers the barrier to conducting research and analysis at scale. When a group of MAAP users wanted to conduct above-ground biomass estimation using GEDI data, we found that their existing workflow for leveraging GEDI data suffered from the barriers mentioned above. Furthermore, their workflow did not scale easily beyond a small number of granules. We found that existing tools related to GEDI data retrieval and subsetting were too limiting, so the GEDI Subsetter was written to support MAAP users’ needs. Being able to run many subsetting jobs simultaneously in the MAAP, and parallelizing the code itself, has led to significant speed improvements in obtaining relevant data, reducing subsetting time from hours to minutes. MAAP users can now more quickly and easily obtain only the data relevant to their research, by choosing which GEDI collection they want to work with (L1A, L2A, L2B, or L4A), and how they want to subset it, by specifying an area of interest, a temporal range, and relevant attributes. This has significantly reduced the feedback loop for users, allowing them to much more quickly subset GEDI data and begin their analysis. Although the GEDI Subsetter originally targeted users of the MAAP, it is generalized such that it can also be used outside of the MAAP and includes a command-line interface for convenience. Furthermore, with minor modifications, it should be possible to use it with non-GEDI data as the general pattern should be applicable to other sparse/track-based sensors.

Charles Daniels↗
NASA NTRS2008

Interoperability of Heliophysics Virtual Observatories

If you'd like to find interrelated heliophysics (also known as space and solar physics) data for a research project that spans, for example, magnetic field data and charged particle data from multiple satellites located near a given place and at approximately the same time, how easy is this to do? There are probably hundreds of data sets scattered in archives around the world that might be relevant. Is there an optimal way to search these archives and find what you want? There are a number of virtual observatories (VOs) now in existence that maintain knowledge of the data available in subdisciplines of heliophysics. The data may be widely scattered among various data centers, but the VOs have knowledge of what is available and how to get to it. The problem is that research projects might require data from a number of subdisciplines. Is there a way to search multiple VOs at once and obtain what is needed quickly? To do this requires a common way of describing the data such that a search using a common term will find all data that relate to the common term. This common language is contained within a data model developed for all of heliophysics and known as the SPASE (Space Physics Archive Search and Extract) Data Model. NASA has funded the main part of the development of SPASE but other groups have put resources into it as well. How well is this working? We will review the use of SPASE and how well the goal of locating and retrieving data within the heliophysics community is being achieved. Can the VOs truly be made interoperable despite being developed by so many diverse groups?

Thieman, J.↗
NASA NTRS2007

Tracking-Data-Conversion Tool

Object Oriented Data Technology (OODT) is a software framework for creating a Web-based system for exchange of scientific data that are stored in diverse formats on computers at different sites under the management of scientific peers. OODT software consists of a set of cooperating, distributed peer components that provide distributed peer-topeer (P2P) services that enable one peer to search and retrieve data managed by another peer. In effect, computers running OODT software at different locations become parts of an integrated data-management system.

Flora-Adams, Dana↗
NASA NTRS2007

Software Framework for Peer Data-Management Services

Object Oriented Data Technology (OODT) is a software framework for creating a Web-based system for exchange of scientific data that are stored in diverse formats on computers at different sites under the management of scientific peers. OODT software consists of a set of cooperating, distributed peer components that provide distributed peer-to-peer (P2P) services that enable one peer to search and retrieve data managed by another peer. In effect, computers running OODT software at different locations become parts of an integrated data-management system.

Hughes, John↗
NASA NTRS1992

The emulsion chamber technology experiment

Photographic emulsion has the unique property of recording tracks of ionizing particles with a spatial precision of 1 micron, while also being capable of deployment over detector areas of square meters or 10's of square meters. Detectors are passive, their cost to fly in Space is a fraction of that of instruments of similar collecting. A major problem in their continued use has been the labor intensiveness of data retrieval by traditional microscope methods. Two factors changing the acceptability of emulsion technology in space are the astronomical costs of flying large electronic instruments such as ionization calorimeters in Space, and the power and low cost of computers, a small revolution in the laboratory microscope data-taking. Our group at UAH made measurements of the high energy composition and spectra of cosmic rays. The Marshall group has also specialized in space radiation dosimetry. Ionization calorimeters, using alternating layers of lead and photographic emulsion, to measure particle energies up to 10(exp 15) eV were developed. Ten balloon flights were performed with them. No such calorimeters have ever flown in orbit. In the ECT program, a small emulsion chamber was developed and will be flown on the Shuttle mission OAST-2 to resolve the principal technological questions concerning space exposures. These include assessments of: (1) pre-flight and orbital exposure to background radiation, including both self-shielding and secondary particle generation; the practical limit to exposure time in space can then be determined; (2) dynamics of stack to optimize design for launch and weightlessness; and (3) thermal and vacuum constraints on emulsion performance. All these effects are cumulative and affect our ability to perform scientific measurements but cannot be adequately predicted by available methods.

Gregory, John C.↗
NASA NTRSDate not supplied

Tracking the Hunga Tonga-Hunga Ha’apai Eruption Stratospheric Aerosol and Trace Gas Plumes Using Machine Learning

On January 15, 2022, the Hunga Tonga-Hunga Ha’apai (hereafter, Hunga Tonga) submarine volcano had an explosive eruption that thrusted ash, gases, and water vapor through the troposphere into the stratosphere and mesosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using data retrieved from low earth orbiting satellite instruments (e.g., OMPS, OMI, and CALIPSO), this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), with prompt engineering can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline using NASA Earthdata and Openscapes, establishes a framework for systematically and rapidly studying extreme events, including volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of remote sensing data, this work demonstrates how AI and open science can accelerate research and generate actionable results. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions (e.g., the Atmosphere Observing System (AOS)), and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters and extreme events in a changing world.

David M. Giles↗
NASA NTRS2016

The Sensitivity of SeaWiFS Ocean Color Retrievals to Aerosol Amount and Type

As atmospheric reflectance dominates top-of-the-atmosphere radiance over ocean, atmospheric correction is a critical component of ocean color retrievals. This paper explores the operational Sea-viewing Wide Field-of-View Sensor (SeaWiFS) algorithm atmospheric correction with approximately 13 000 coincident surface-based aerosol measurements. Aerosol optical depth at 440 nm (AOD(sub 440)) is overestimated for AOD below approximately 0.1-0.15 and is increasingly underestimated at higher AOD; also, single-scattering albedo (SSA) appears overestimated when the actual value less than approximately 0.96.AOD(sub 440) and its spectral slope tend to be overestimated preferentially for coarse-mode particles. Sensitivity analysis shows that changes in these factors lead to systematic differences in derived ocean water-leaving reflectance (Rrs) at 440 nm. The standard SeaWiFS algorithm compensates for AOD anomalies in the presence of nonabsorbing, medium-size-dominated aerosols. However, at low AOD and with absorbing aerosols, in situ observations and previous case studies demonstrate that retrieved Rrs is sensitive to spectral AOD and possibly also SSA anomalies. Stratifying the dataset by aerosol-type proxies shows the dependence of the AOD anomaly and resulting Rrs patterns on aerosol type, though the correlation with the SSA anomaly is too subtle to be quantified with these data. Retrieved chlorophyll-a concentrations (Chl) are affected in a complex way by Rrs differences, and these effects occur preferentially at high and low Chl values. Absorbing aerosol effects are likely to be most important over biologically productive waters near coasts and along major aerosol transport pathways. These results suggest that future ocean color spacecraft missions aiming to cover the range of naturally occurring and anthropogenic aerosols, especially at wavelengths shorter than 440 nm, will require better aerosol amount and type constraints.

single scattering albedo↗
NASA NTRS2022

A New Machine Learning Based Analysis for Improving Satellite Retrieved Atmospheric Composition Data: OMI SO2 as an Example

Despite recent progress, satellite retrievals of anthropogenic SO2 still suffer from relatively low signal-tonoise ratios. In this study, we demonstrate a new machine learning data analysis method to improve the quality of satellite SO2 products. In the absence of large ground-truth datasets for SO2, we start from SO2 slant column densities (SCDs) retrieved from the Ozone Monitoring Instrument (OMI) using a data-driven, physically based algorithm and calculate the ratio between the SCD and the root mean square (rms) of the fitting residuals for each pixel. To build the training data, we select presumably clean pixels with small SCD / rms ratios (SRRs) and set their target SCDs to zero. For polluted pixels with relatively large SRRs, we set the target to the original retrieved SCDs. We then train neural networks (NNs) to reproduce the target SCDs using predictors including SRRs for individual pixels, solar zenith, viewing zenith and phase angles, scene reflectivity, and O3 column amounts, as well as the monthly mean SRRs. For data analysis, we employ two NNs: (1) one trained daily to produce analyzed SO2 SCDs for polluted pixels each day and (2) the other trained once every month to produce analyzed SCDs for less polluted pixels for the entire month. Test results for 2005 show that our method can significantly reduce noise and artifacts over background regions. Over polluted areas, the monthly mean NN-analyzed and original SCDs generally agree to within ±15 %, indicating that our method can retain SO2 signals in the original retrievals except for large volcanic eruptions. This is further confirmed by running both the NN-analyzed and original SCDs through a topdown emission algorithm to estimate the annual SO2 emissions for ∼ 500 anthropogenic sources, with the two datasets yielding similar results. We also explore two alternative approaches to the NN-based analysis method. In one, we employ a simple linear interpolation model to analyze the original SCD retrievals. In the other, we develop a PCA–NN algorithm that uses OMI measured radiances, transformed and dimension-reduced with a principal component analysis (PCA) technique, as inputs to NNs for SO2 SCD retrievals. While the linear model and the PCA–NN algorithm can reduce retrieval noise, they both underestimate SO2 over polluted areas. Overall, the results presented here demonstrate that our new data analysis method can significantly improve the quality of existing OMI SO2 retrievals. The method can potentially be adapted for other sensors and/or species and enhance the value of satellite data in air quality research and applications.

Can Li↗
NASA NTRS2006

Controlled Vocabularies Boost International Participation and Normalization of Searches

The Global Change Master Directory's (GCMD) science staff set out to document Earth science data and provide a mechanism for it's discovery in fulfillment of a commitment to NASA's Earth Science progam and to the Committee on Earth Observation Satellites' (CEOS) International Directory Network (IDN.) At the time, whether to offer a controlled vocabulary search or a free-text search was resolved with a decision to support both. The feedback from the user community indicated that being asked to independently determine the appropriate 'English" words through a free-text search would be very difficult. The preference was to be 'prompted' for relevant keywords through the use of a hierarchy of well-designed science keywords. The controlled keywords serve to 'normalize' the search through knowledgeable input by metadata providers. Earth science keyword taxonomies were developed, rules for additions, deletions, and modifications were created. Secondary sets of controlled vocabularies for related descriptors such as projects, data centers, instruments, platforms, related data set link types, and locations, along with free-text searches assist users in further refining their search results. Through this robust 'search and refine' capability in the GCMD users are directed to the data and services they seek. The next step in guiding users more directly to the resources they desire is to build a 'reasoning' capability for search through the use of ontologies. Incorporating twelve sets of Earth science keyword taxonomies has boosted the GCMD S ability to help users define and more directly retrieve data of choice.

Olsen, Lola M.↗
NASA NTRS1976

Seasat-A oceanographic data system and users

The Seasat-A system is reviewed with emphasis on data retrieval, processing and dissemination plans. Attention is paid to the sensors of the Seasat satellite including the compressed pulse radar altimeter, the coherent synthetic aperture imaging radar, the microwave wind scatterometer, and the scanning visible/infrared radiometer. Particular emphasis is placed on a particular set of experiments: the Navy's Fleet Numerical Weather Control will receive Seasat data in real time and process the data into products that will be used in weather and sea condition forecasts.

Mccandless, S. W., Jr.↗
NASA NTRS1983

The Network Information Management System (NIMS) in the Deep Space Network

In an effort to better manage enormous amounts of administrative, engineering, and management data that is distributed worldwide, a study was conducted which identified the need for a network support system. The Network Information Management System (NIMS) will provide the Deep Space Network with the tools to provide an easily accessible source of valid information to support management activities and provide a more cost-effective method of acquiring, maintaining, and retrieval data.

Wales, K. J.↗
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 NTRS2014

Mars' Water Vapor Mapping by the SPICAM IR Spectrometer: Five Martian Years of Observations

The SPICAM IR instrument on the Mars Express mission continuously observes the water vapor in the martian atmosphere starting from 2004 in the 1.38-micrometer spectral band. The water vapor column abundance is retrieved from nadir observations to characterize its spatial, seasonal and interannual variations. A reference set of SPICAM water vapor column abundances (zonally averaged) covering the time period from 2004 to 2013 (martian years 27-31) is available for a grid of 2 deg Ls 2 latitude, along with an average reference map of water vapor abundance combining all the martian years of Mars Express observations. Compared to the previous data retrieval by Fedorova et al. (Fedorova, A., Korablev, O., Bertaux, J.L., Rodin, A., Kiselev, A., Perrier, S. [2006]. J. Geophys. Res. 111, E09S08) the new processing algorithm includes many improvements concerning the calibration and assumed parameters. A major improvement is the account for aerosol scattering based on dust and water ice cloud optical depths measured by THEMIS/Mars Odyssey (Smith, M.D. [2009]. Icarus 202, 444-452). The account for multiple scattering by aerosol particles increases the retrieved water vapor amount by approximately 10% in polar areas during summer, and up to 60-70% for large solar zenith angles. The sensitivity of the results to aerosol properties, surface albedo, solar spectrum, and water vapor vertical distribution has also been studied. The retrieved water vapor reveals nominal annual cycle with maximum abundance of about 60-70 pr. lm for the Northern summer and approximately 20 pr. lm for the Southern summer. The annual average amount of water has been estimated to be of 10-20 pr. micrometers, in agreement with other measurements. From year to year the seasonal cycle of water vapor abundance is very stable. An observed decrease during the MY 28 global dust storm cannot be fully attributed to the masking effect of dust, and indicates a real decrease of water amount near or above the surface. No evidence of diurnal variation of column water vapor amount was found, even though the 1.38-micrometer measurements are sensitive to the few lowermost kilometers above the surface.

Mars water vapor↗
NASA NTRS1989

Initial operating capability for the hypercluster parallel-processing test bed

The NASA Lewis Research Center is investigating the benefits of parallel processing to applications in computational fluid and structural mechanics. To aid this investigation, NASA Lewis is developing the Hypercluster, a multi-architecture, parallel-processing test bed. The initial operating capability (IOC) being developed for the Hypercluster is described. The IOC will provide a user with a programming/operating environment that is interactive, responsive, and easy to use. The IOC effort includes the development of the Hypercluster Operating System (HYCLOPS). HYCLOPS runs in conjunction with a vendor-supplied disk operating system on a Front-End Processor (FEP) to provide interactive, run-time operations such as program loading, execution, memory editing, and data retrieval. Run-time libraries, that augment the FEP FORTRAN libraries, are being developed to support parallel and vector processing on the Hypercluster. Special utilities are being provided to enable passage of information about application programs and their mapping to the operating system. Communications between the FEP and the Hypercluster are being handled by dedicated processors, each running a Message-Passing Kernel, (MPK). A shared-memory interface allows rapid data exchange between HYCLOPS and the communications processors. Input/output handlers are built into the HYCLOPS-MPK interface, eliminating the need for the user to supply separate I/O support programs on the FEP.

Cole, Gary L.↗
NASA NTRS1996

Data Archival and Retrieval Enhancement (DARE) Metadata Modeling and Its User Interface

The Defense Nuclear Agency (DNA) has acquired terabytes of valuable data which need to be archived and effectively distributed to the entire nuclear weapons effects community and others...This paper describes the DARE (Data Archival and Retrieval Enhancement) metadata model and explains how it is used as a source for generating HyperText Markup Language (HTML)or Standard Generalized Markup Language (SGML) documents for access through web browsers such as Netscape.

The Defense Nuclear Agency DNA DARE Data Archival ↗
NASA NTRS1993

The UoSAT-5 solar cell experiment: First year in orbit

The results for the first year in orbit of the DRA solar cell experiment flying on the Surrey University UoSAT-5 satellite are described. Several problems were identified with the measured data, which are discussed along with the techniques used to remove or minimize the effect of the problems. After 1 year in orbit the majority of the cells flying on the experiment have undergone little or no degradation. The exception to this are all the ITO/InP cells, supplied by two different manufacturers, they are showing more degradation than the GaAs cells. This result is unexpected and currently unexplainable. It will be necessary to retrieve data from the experiment for several years to obtain the best results due to the relatively benign radiation environment.

Goodbody, C.↗