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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

The International Space Station: A Unique Platform for Remote Sensing of Natural Disasters

Assembly of the International Space Station (ISS) was completed in 2012, and the station is now fully operational as a platform for remote sensing instruments tasked with collecting scientific data about the Earth system. Remote sensing systems are mounted inside the ISS, primarily in the U.S. Destiny Module's Window Observational Research Facility (WORF), or are located on the outside of the ISS on any of several attachment points. While NASA and other space agencies have had remote sensing systems orbiting Earth and collecting publicly available data since the early 1970s, these sensors are carried onboard free-flying, unmanned satellites. These satellites are traditionally placed into Sun-synchronous polar orbits that allow imaging of the entire surface of the Earth to be repeated with approximately the same Sun illumination (typically local solar noon) over specific areas, with set revisit times that allow uniform data to be taken over long time periods and enable straightforward analysis of change over time. In contrast, the ISS has an inclined, Sun-asynchronous orbit (the solar illumination for data collections over any location changes as the orbit precesses) that carries it over locations on the Earth between approximately 52degnorth and 52deg south latitudes (figure 1). The ISS is also unique among NASA orbital platforms in that it has a human crew. The presence of a crew provides options not available to robotic sensors and platforms, such as the ability to collect unscheduled data of an unfolding event using handheld digital cameras as part of the Crew Earth Observations (CEO) facility and on-the-fly assessment of environmental conditions, such as cloud cover, to determine whether conditions are favorable for data collection. The crew can also swap out internal sensor systems installed in the WORF as needed. The ISS orbit covers more than 90 percent of the inhabited surface of the Earth, allowing the ISS to pass over the same ground locations at different times of the day and night. This is important for two reasons: 1) certain surface processes (i.e., development of coastal fog banks) occur at times other than local solar noon, making it difficult to collect relevant data from traditional satellite platforms, and 2) it provides opportunities for the ISS to collect data for short-duration events, such as natural disasters, that polar-orbiting satellites may miss due to their orbital dynamics - in essence, the ISS can be "in the right place at the right time" to collect data. An immediate application of ISS remote sensing data collection is that the data can be used to provide information for humanitarian aid after a natural disaster. This activity contributes directly to the station's Benefits to Humanity mission. The International Charter, Space and Major Disasters (also known as the International Disaster Charter, or IDC) is an agreement between agencies of several countries to provide - on a best-effort basis - remotely sensed data related to natural disasters to requesting countries in support of disaster response. In the United States, the lead agency for interaction with the IDC is the United States Geological Survey (USGS); when an IDC request, or activation, is received, the USGS notifies the science teams for NASA instruments with targeting information for data collection. In the case of the ISS, Earth scientists in the JSC ARES Directorate, in association with the ISS Program Science Office, coordinate targeting and data collection with the USGS. If data is collected, it is passed back to the USGS for posting on its Hazards Data Distribution System and made available for download. The ISS was added to the USGS's list of NASA remote sensing assets that could respond to IDC activations in May 2012. Initially, the NASA ISS sensor systems available to respond to IDC activations included the ISS Agricultural Camera (ISSAC), an internal multispectral visible-near infrared wavelength system mounted in the WORF; CEO, a project that collects imagery through the ISS windows using off-the-shelf handheld digital visible-wavelength cameras; and the Hyperspectral Imager for the Coastal Oceans (HICO), a visible to near-infrared system mounted externally on the Japanese Experiment Module - Exposed Facility. Since May 2012, there have been 37 IDC activations; ISS sensor systems have collected data for 10 of these events.

Stefanov, William L.↗
NASA NTRS1975

Requirements and Capabilities for Planetary Missions: Mariner Encke Ballistic Flyby 1980

This mission will provide a broad-based fast reconnaissance of comet Encke, building a data base for subsequent more detailed comet investigations, including rendezvous. After a 3 month flight, the spacecraft will encounter the comet at a nominal range of about 500 km. Flyby velocity will be 7 to 28 km/sec depending on choice of arrival data (0 to 35 days before Encke perihelion) and launch vehicle. The spacecraft will be similar to the MVM 73 spacecraft, with scan platform and 117 kbps encounter data rate, and designed to survive the thermal environment of 0.34 to 0.8 AU.

Ball, G. G.↗
NASA NTRS2025

NAIRAS Version 3 Atmospheric Ionizing Radiation Validation: Comparisons to RaD-X Measurements

The Nowcast of Aerospace Ionizing RAdiation System (NAIRAS) model predicts dosimetric and radiative flux quantities for assessing human radiation exposure levels and radiation effects on flight electronic systems from the surface of the Earth to deep space. NAIRAS version 3 includes many updates and improvements to the model. In this paper, NAIRAS version 3 dosimetric quantities are compared to observations of the atmospheric radiation environment taken during the Radiation Dosimetry Experiment (RaD-X) flight campaign. The RaD-X campaign consisted of a high-altitude balloon flight, with altitudes up to 40 km, and four coordinated aircraft flights covering an altitude range from 6-20 km. The RaD-X measurement data from the different flight platforms were acquired in September 2015 and at nearly the same vertical cutoff rigidity (3-4 GV). High quality, flight-averaged measurement data were provided at seven altitudes, which correspond to regions of fundamentally different radiation transport and collisional interaction physics. The NAIRAS model agrees with the RaD-X measurements to within 30% over the entire altitude domain of the flight campaign (0-40 km), which is within the measurement uncertainty.

Christopher J Mertens↗
NASA NTRS1994

Simulated ASTER data for Geologic Studies

The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) is a high spatial resolution imaging instrument, due to be launched on NASA's Earth Observing System AM-1 satellite platform in 1998. ASTER acquires data in 14 bands, spanning the wavelength region from the visible, near infrared, short wavelength infrared, and thermal infrared, with spatial resolution varying from 15 m to 90 m, depending on wavelength region. In order to evaluate our ability to use ASTER data for geological mapping, we used aircraft data over Cuprite, Nevada to create a simulated 14-band ASTER data set. The study site has sparse vegetation, and exposes a wide range of unaltered and hydrothermally altered volcanic rocks. The wide range of wavelengths covered by ASTER allowed us to recognize or separate iron oxide minerals, clay-bearing minerals, sulfate minerals, ammonia minerals, siliceous rocks, and carbonates. Combined with laboratory spectral measurements, we were able to identify these constituents. Based on both sets of information, we produced an alteration map showing the distribution of argillized rocks, opalized rocks with alunite, silicified rocks, and areas dominated by kaolinite and buddingtonite. The map was as accurate as published maps made by traditional field methods. ASTER promises to be a major improvement over existing satellite systems for geologic mapping.

Advanced↗
NASA NTRSDate not supplied

The Environmental Data Application for Analysis of Space Telemetry Data

Sensors on the International Space Station (ISS) and multiple spacecraft elsewhere in Earth orbit and in deep space continuously monitor and collect environmental data, transmitting this information back to Earth. These data include ionizing radiation and, on the ISS and spacecrafts, CO2, relative humidity levels, and temperature, and are of great importance to space biology research. Looking ahead to future long duration crewed missions beyond low Earth orbit, the ability to study how factors including CO2 levels, light cycle, temperature modulate the response to ionizing radiation and microgravity is essential. To date, access to these data has been fragmented across space agencies, spacecraft, and databases. To address this issue, NASA’s Open Science Data Repository (OSDR) has developed a user interface for interrogation of telemetry data: the Environmental Data Application (EDA). The EDA provides the capability to visualize telemetry and radiation data collected on the International Space Station and corresponding ground platforms during the Rodent Research missions. Telemetry data includes temperature, relative humidity, and CO2 levels. Radiation data includes galactic cosmic rays, the contribution of the South Atlantic Anomaly, total radiation dose rate, and accumulated radiation dose. The application allows users to view single missions, compare multiple missions, and view and download summary or full data tables. In summary, the EDA provides GUIs for data visualization and exploration, as well as means for data export, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.

telemetry↗
NASA NTRS1987

Trace gas measurements from tethered balloon platforms

Instrumentation and chemical sampling and analysis procedures are described for making measurements of atmospheric carbon disulfide in the concentration range 1-1000 pptv from tethered balloon platforms. Results of a study on the CS2 composition of air downward of a saltwater marsh are reported. A method for obtaining the necessary data for solving the budget equations for surface fluxes, chemical formation rates and chemical destruction rates using data acquired from tethered balloon platforms is presented.

Bandy, Alan R.↗
NASA NTRSDate not supplied

Radiation-Hard Parallel Readout Circuit for Low-Frequency Voltage Signal Measurements

NASA Goddard Space Flight Center (GSFC) has successfully developed and tested a custom-designed low-noise multi-channel digitizer (MCD) application specific integrated circuit (ASIC) for operation in harsh radiation environments. The MCD-ASIC is optimized for low-frequency and low-voltage signal measurements from sensors and transducers. It has 20 input channels where each channel is comprised of auto-zeroed chopper variable-gain amplifier, post amplifier, and a second order ∑∆ modulator. ∑∆ analog-to-digital converter (ADC) relies on oversampling and noise shaping to achieve high-resolution conversion. However, the MCD-ASIC requires digital filtering and decimation to convert the output single bit streams from the ADC to useful data words. A parallel digital platform such as a field-programmable-gate-array (FPGA) is highly suitable to fully leverage the capabilities of the MCD-ASIC. The FPGA controls the MCD-ASIC via serial peripheral interface (SPI) protocol and acquires data from it. A Python-script communicates with the FPGA board through a USB interface on a cross operating platform. Using this architecture, the system is capable of monitoring up to 20 voltage readout channels simultaneously in a real-time manner. Each channel’s parameters can be programmed independently allowing maximum user versatility. In this paper, we present analysis of the analog front-end, the implementation of the digital processing unit on the FPGA, and provide noise performance results from the MCD-ASIC readout.

ASIC↗
NASA NTRSDate not supplied

Recap of DIP Workshop Series: #1 DIP Architecture and Data Integrations Services

This workshop will cover DIP architecture and data integration services to obtain feedback from America for Airlines (A4A) Air Traffic Management Council (ATMC). Participants will get a look at how the DIP architecture is set-up as well as how data integration services are planned to be hosted on the platform. The DIP architecture review is intended to cover how DIP was envisioned and how DIP is being developed to address data needs across the industry. Participants will have a chance to provide feedback on the DIP architecture and gain insight into how one might interface with the DIP to send or receive data. The data integration services portion is intended to cover DIP’s technical approach to data integration. As an example implementation, there will be a first look at possible data fusion on the platform, including utilizing NASA’s Fuser, and tailoring for industry data consumers. Descriptions, at a high-level, of input to and output of the Fuser will also be discussed.

ATM-X↗
NASA NTRS2018

Generalizing a Data Analysis Pipeline in the Cloud to Handle Diverse Use Cases in NASA's EOSDIS

NASA's Earth Observing System Data and Information System (EOSDIS) is tasked with archiving and distributing Earth Observation data across a range of disciplines, including atmospheric science, oceanography, land processes, natural hazards, solar radiance and even socioeconomic aspects relating to the environment. Driven by rapidly rising data volumes, EOSDIS is migrating to a cloud computing based archive over the next few years. Although this simplifies data management somewhat, the main aim is to provide the data in an environment where end users can bring their analysis to the data rather than attempting to download and manage ever-increasing volumes. To that end, a cloud-based analysis platform is being constructed to enable data transformations, analyses and visualization without egressing the data from the cloud. In this endeavor, we expect a wide variety of users, algorithms and use cases. Consequently, the architecture of this cloud analytics platform is expressly designed to be based on open services, thus fostering an ecosystem that enables the efficient combination of common components with data-specific or analysis-specific components. Reviewed and approved by Andrew Mitchell, ESDIS project manager.

Cloud computing↗
NASA NTRSDate not supplied

DIP Architecture and Data Integration Services

This workshop will cover DIP architecture and data integration services. Participants will get a look at how the DIP architecture is set-up as well as how data integration services are planned to be hosted on the platform. The DIP architecture review is intended to cover how DIP was envisioned and how DIP is being developed to address data needs across the industry. Participants will have a chance to provide feedback on the DIP architecture and gain insight into how one might interface with the DIP to send or receive data. The data integration services portion is intended to cover DIP’s technical approach to data integration. As an example implementation, there will be a first look at possible data fusion on the platform, including utilizing NASA’s Fuser, and tailoring for industry data consumers. Descriptions, at a high-level, of input to and output of the Fuser will also be discussed.

ATM-X↗
NASA NTRS2011

Experiment in Onboard Synthetic Aperture Radar Data Processing

Single event upsets (SEUs) are a threat to any computing system running on hardware that has not been physically radiation hardened. In addition to mandating the use of performance-limited, hardened heritage equipment, prior techniques for dealing with the SEU problem often involved hardware-based error detection and correction (EDAC). With limited computing resources, software- based EDAC, or any more elaborate recovery methods, were often not feasible. Synthetic aperture radars (SARs), when operated in the space environment, are interesting due to their relevance to NASAs objectives, but problematic in the sense of producing prodigious amounts of raw data. Prior implementations of the SAR data processing algorithm have been too slow, too computationally intensive, and require too much application memory for onboard execution to be a realistic option when using the type of heritage processing technology described above. This standard C-language implementation of SAR data processing is distributed over many cores of a Tilera Multicore Processor, and employs novel Radiation Hardening by Software (RHBS) techniques designed to protect the component processes (one per core) and their shared application memory from the sort of SEUs expected in the space environment. The source code includes calls to Tilera APIs, and a specialized Tilera compiler is required to produce a Tilera executable. The compiled application reads input data describing the position and orientation of a radar platform, as well as its radar-burst data, over time and writes out processed data in a form that is useful for analysis of the radar observations.

Holland, Matthew↗
NASA NTRS2018

PYSAT: Python Satellite Data Analysis Toolkit

A common problem in space science data analysis is combining complementary data sources that are provided and analyzed in different formats and programming languages. The Python Satellite Data Analysis Toolkit (pysat) addresses this issue by providing an open source toolkit that implements the general process of space science data analysis, from beginning to end, in an instrumentindependent manner. This toolkit uses an Instrument object that enables systematic analysis of science data from a variety of platforms within a single interface. Basic functions such as downloading, loading, and cleaning are included for all supported instruments. Common analysis routines are also included, which are instrument and data source independent. A nanokernel is used to provide instrument independence, it is attached to the Instrument object and mediates the systematic and arbitrary modification of loaded data. Pysat uses the nanokernel to improve the rigor of time series analysis, support onthefly orbit determination, and cleanly span file breaks. Pysat's functions and higherlevel scientific analysis features are validated through the use of unit testing. Further adoption by the community provides a set of scientific results produced by a common core, constituting a distributed heritage that supports the validity of the underlying processing and scientific output. These features are used to demonstrate consistency between derived electron density profiles and measured ion drifts, particularly downward ion drifts in the afternoon hours during extreme solar minimum. Pysat builds upon open source Python software that is freely available and encourages communitydriven development.

Stoneback, R.A.↗
NASA NTRS2019

Assessing Vegetation Function with Imaging Spectroscopy

Healthy vegetation function supports diverse biological communities and ecosystem processes, and provides crops, forest products, forage, and countless other benefits. Vegetation function can be assessed by examining dynamic processes and by evaluating plant traits, which themselves are dynamic. Using both trait-based and process-based approaches, spectroscopy can assess vegetation function at multiple scales using a variety of sensors and platforms ranging from proximal to airborne and satellite measurements. Since spectroscopic data are defined by the instruments and platforms available, along with their corresponding spatial, temporal and spectral scales, and since these scales may not always match those of the function of interest, consideration of scale is a necessary focus. For a full understanding of vegetation processes, combined (multi-scale) sampling methodsusing empirical and theoretical approaches are required, along with improved informatics.

Gamon, J. A.↗
NASA NTRS1991

Improved geometric calibration of the SIR-C data

Errors in the determination of the platform state vector (position and velocity) limit the accuracy with which individual pixels in a SAR (synthetic aperture radar) image can be located. A method of updating the state vector based on the SAR data is described. The algorithm combines reference targets at known locations with the estimates available from the mission control center, utilizing a maximum likelihood estimator. The targets can be located at calibration sites or be easily recognizable targets of opportunity. The accuracy of the update depends on the number of targets, their geometry, and the accuracy of their position determination. The algorithm is tested using Seasat SAR data. High-accuracy state vectors were perturbed by Gaussian distributed errors with standard deviations and cross-correlations based on worst-case expectations for SIR-C (Shuttle Imaging Radar). Tests using ground targets located in topographic maps (1:24,000) showed that state vector position errors on the order of 300-400 m and velocity accuracies of 2-3 m/s are readily achievable.

Madsen, S. N.↗
NASA NTRS1979

Swath width study. A simulation assessment of costs and benefits of a sensor system for agricultural application

Satellites provide an excellent platform from which to observe crops on the scale and frequency required to provide accurate crop production estimates on a worldwide basis. Multispectral imaging sensors aboard these platforms are capable of providing data from which to derive acreage and production estimates. The issue of sensor swath width was examined. The quantitative trade trade necessary to resolve the combined issue of sensor swath width, number of platforms, and their orbits was generated and are included. Problems with different swath width sensors were analyzed and an assessment of system trade-offs of swath width versus number of satellites was made for achieving Global Crop Production Forecasting.

Source record↗
NASA NTRS2000

Radiation Hardened, Modulator ASIC for High Data Rate Communications

Satellite-based telecommunication services are challenged by the need to generate down-link power levels adequate to support high quality (BER approx. equals 10(exp 12)) links required for modem broadband data services. Bandwidth-efficient Nyquist signaling, using low values of excess bandwidth (alpha), can exhibit large peak-to-average-power ratio (PAPR) values. High PAPR values necessitate high-power amplifier (HPA) backoff greater than the PAPR, resulting in unacceptably low HPA efficiency. Given the high cost of on-board prime power, this inefficiency represents both an economical burden, and a constraint on the rates and quality of data services supportable from satellite platforms. Constant-envelope signals offer improved power-efficiency, but only by imposing a severe bandwidth-efficiency penalty. This paper describes a radiation- hardened modulator which can improve satellite-based broadband data services by combining the bandwidth-efficiency of low-alpha Nyquist signals with high power-efficiency (negligible HPA backoff).

McCallister, Ron↗
NASA NTRS1988

Geological and vegetational applications of Shuttle Imaging Radar-B, Mineral County, Nevada

Multiple-incidence angle and multi-azimuth radar data were acquired from a Shuttle platform over test sites in Nevada in October 1984. An attempt was made to correlate these data with ground features for the purpose of evaluating the use of such data for geological and vegetational assessment. Standard ecological parameters with respect to the flora (community composition, dominance, and relative cover) were recorded in the field at the time of overflight. Although a total of 33 species representing 11 plant families were recognized, and plant cover ranged from 13 to 26 percent, radar data could not be used to separate plant communities. The signal return is more a function of abiotic conditions than vegetative characteristics. Illumination geometry plays an important role in the ability to detect strike-slip and dip-slip faults. Local incidence angle is the most important parameter, and SIR-B data takes with small incidence angles are superior for identifying certain styles of faulting. Look direction is critical for detecting faults with a dip-slip component. New structural features were not observed. Problems with radar antenna power and recording significantly affected data quality.

Borengasser, M. X.↗