Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Label Space”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Living with a Star (LWS) Space Environment Testbeds (SET), Mission Carrier Overview and Capabilities

NASA has initiated the Living With a Star (LWS) Program to develop the scientific understanding to address the aspects of the Connected Sun-Earth system that affect life and society. A goal of the program is to bridge the gap between science, engineering, and user application communities. This will enable future science, operational, and commercial objectives in space and atmospheric environments by improving engineering approaches to the accommodation and/or mitigation of the effects of solar variability on technological systems. The three program elements of the LWS Program are Science Missions; Targeted Research and Technology; and Space Environment Testbeds (SETS). SET is an ideal platform for small experiments performing research on space environment effects on technologies and on the mitigation of space weather effects. A short description of the LWS Program will be given, and the SET will be described in detail, giving the mission objectives, available carrier services, and upcoming flight opportunities.

Patschke, Robert↗
NASA NTRS2007

High Performance Processors for Space Environments: A Subproject of the NASA Exploration Missions Systems Directorate "Radiation Hardened Electronics for Space Environments" Technology Development Program

Implementation of challenging Exploration Systems Missions Directorate objectives and strategies can be constrained by onboard computing capabilities and power efficiencies. The Radiation Hardened Electronics for Space Environments (RHESE) High Performance Processors for Space Environments project will address this challenge by significantly advancing the sustained throughput and processing efficiency of high-per$ormance radiation-hardened processors, targeting delivery of products by the end of FY12.

Johnson, M.↗
NASA NTRS2009

Panel Discussion: Life in the Cosmos

Water appears to be essential to all life on Earth. For this reason, "Follow the Water" has been adopted as a mantra for the search for Life in the Cosmos. Expeditions have helped to establish the limits and biodiversity of life in the most extreme environments on Earth. Microbial extremophiles inhabit acidic streams; hypersaline and hyperalkaline lakes and pools; the cold deep sea floor, permafrost, rocks, glaciers, and perennially ice-covered lakes of the polar environments; geysers, volcanic fumaroles, hydrothermal vents and hot rocks deep within the Earth's crust. The ESA Venus Express Spacecraft entered Venusian Orbit in 2006 and continues to produce exciting results. The Visible and Infrared Thermal Imaging Spectrometer (VIRTIS) instrument made the first detection of hydroxyl in the atmosphere of Venus, indicating it is much more similar to Earth and Mars than previously thought. Huge hurricane-like vortices have been found above the poles of the planet and as yet unidentified UV absorbers that form mysterious dark bands in the upper atmosphere. At 70 km and below, water vapor and sulfur dioxide combine to form sulfuric acid droplets that create a haze above the cloud tops. Thermophilic acidophiles, such as have recently been discovered on Earth, could possibly survive in the hot sulfuric acid droplets that exist in the upper atmosphere of Venus. In order to understand how to search for life elsewhere in the Solar System, over 40 VIRTIS images of Earth from Venus have been obtained to search for evidence of life on Earth. The signatures of water and molecular Oxygen were detected in the Earth s atmosphere, but the atmosphere of Venus also exhibits these signatures. The water and water ice are far more abundant on comet, the polar caps and permafrost of Mars and the icy moons of Jupiter and Saturn. These "frozen worlds" of our Solar System, are much more promising regimes where extant or extinct microbial life may exist. The ESA Mars Advanced Radar for Subsurface and Ionospheric Sounding (MARSIS) probe has found that both the North and South Polar Caps of Mars are approximately 3.5 km thick and are composed almost entirely of water ice. In winter, a thin dry ice layer covers the caps, but it sublimates directly to CO2 in the spring. The ESA Mars Express Orbiter images reveal Rupes Tenuis to be a vast snow-laden region on the southern edge of the Martian North Polar Cap. The Mars Exploration Rover Spirit found alkaline volcanic rocks in the Gusev Crater and the Phoenix Mars Lander has shown that the soil of Mars is much more alkaline than previously expected. The Phoenix Mars Lander has also made direct observations of frozen and liquid water on Mars. It is known that microorganisms from Alaska, Siberia and Antarctica can remain alive frozen in permafrost or ice for long periods of time. These discoveries increase the possibility that the Labeled Release Experiment may have discovered life on Mars during the Viking Mission and provide strong impetus for the return of life detection experiments to Mars. Changes in the spin rate of Saturn's moon Titan indicate that it may also harbor a 300 km thick liquid water ocean beneath its icy crust. The NASA/ESA/Italian Space Agency Cassini Spacecraft has imaged geysers containing water vapor, methane, carbon dioxide and organics erupting from the "tiger stripe" regions near the South Pole of Saturn's moon Enceladus. The high temperatures observed, the water vapor and large number of ice particles expelled suggest that a liquid water lake may exist beneath the "tiger stripe" ice cracks of Enceladus. The NASA Deep Impact probe found the surface temperature of comet 9P/Temple 1 at 1.5 AY was slightly above the ice/water phase change temperature (273 K). This suggests melting of water ice near the comet surface. A spectrometer the spacecraft detected a mixture of clay and carbonate minerals (that form in the presence of liquid water) streaming off the comet after the collision with the pactor. The study of chemical and mineral biomarkers, chiral amino acids and possible indigenous microfossils in SNC and carbonaceous meteorites continues. These results suggest that comets should be considered prime targets in the search for Life in the Cosmos. The ESA Rosetta mission is on track to rendezvous with comet 67P/Churyumov-Gerasimenko. The recent space observations combined with new information about the ability of microbial extremophiles to thrive in polar environments suggest that life may be far more widely distributed in the Cosmos than previously thought possible. The Panelists will review recent discoveries and provide their own insights about Life in the Cosmos -- followed by a question and answer session with the audience.

Hoover, Richard B.↗
NASA NTRSDate not supplied

LLMs and GenAI Tools to Depict Contributions of Human Systems to Spaceflight Tasks Execution

Recent advancements in Artificial Intelligence and Machine Learning (AI/ML) technologies, particularly Large Language Models (LLMs) capable of sophisticated syntax analysis, offer substantial potential in automating complex processes, thereby saving time and human resources. This study explores the development of an LLM-driven model designed to analyze and categorize a diverse set of Mars mission tasks into 18 predefined Human System Task Categories (HSTCs) based on their textual descriptions. As part of developing the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA projects Performance Risk Model (PRisM) proof-of-concept, we established a framework to project performance scores from small-scale tests onto a preliminary list of Mars tasks. The foundation of our model was a comprehensive spreadsheet populated by NASA experts and clinicians, which detailed each Mars task alongside binary indicators of HSTC involvement. This dataset enabled the initial application of supervised ML, training and testing on existing HSTC labels. The HSTCs were originally defined from a medical system perspective, focusing on task impairments due to deteriorated human health. To expand our model's scope to include categories impacting performance, we face the challenge of generating binary labels (0 or 1) for new categories without pre-existing data. We address this by employing Generative AI (GenAI) software to determine whether a given task involved a new category by asking, "Does task A involve using category B?" We validate our approach by comparing the GenAI's binary classifications with the expert-provided labels for existing HSTCs. Notably, we utilize Ollama [4], a locally hosted GenAI tool that does not require cloud access, thus safeguarding NASA's proprietary data from unauthorized exposure. This study demonstrates the feasibility of leveraging cutting-edge AI tools to advance research, paving the way for automation and rapid decision-making in space exploration.

Mona Matar↗
NASA NTRS2003

Single-Event Effects Ground Testing and On-Orbit Rate Prediction Methods: The Past, Present and Future

Over the past 27 years, or so, increased concern over single event effects in spacecraft systems has resulted in research, development and engineering activities centered around a better understanding of the space radiation environment, single event effects predictive methods, ground test protocols, and test facility developments. This research has led to fairly well developed methods for assessing the impact of the space radiation environment on systems that contain SEE sensitive devices and the development of mitigation strategies either at the system or device level.

Reed, Robert A.↗
NASA NTRS2018

Earth Science Deep Learning: Applications and Lessons Learned

Deep Learning: A subfield of machine learning; Algorithms inspired by function of the brain; Scales with amount of training data; Powerful tool without the need for feature engineering; Suitable for Earth Science applications. Deep Learning for Earth science at MSFC (Marshall Space Flight Center): Phenomena identification; Hurricane intensity (wind speed) estimation; Severe storm (hailstorm) detection; Transverse bands detection; Entity extraction for knowledge graph creation; Ephemeral water detection.

Labeled Data↗
NASA NTRS1977

Status of the DOE /STOR/-sponsored national program on hydrogen production from water via thermochemical cycles

A pure thermochemical cycle is a system of linked regenerative chemical reactions which accepts only water and heat and produces hydrogen. Thermochemical cycles are potentially a more efficient and cheaper means of producing hydrogen from water than is the generation of electricity followed by electrolysis. The Energy Storage Systems Division of the Department of Energy is currently funding a national program on thermochemical hydrogen production. The National Aeronautics and Space Administration is responsible for the technical management of this program. The goal is to develop a cycle which can potentially operate with an efficiency greater than 40% using a heat source providing a maximum available temperature of 1150 K. A closed bench-scale demonstration of such a cycle would follow. This cycle would be labeled a 'reference cycle' and would serve as a baseline against which future cycles would be compared.

Baker, C. E.↗
NASA NTRS1984

Use of satellite data in agricultural surveys

The state-of-the-art of crop surveying by satellite is reviewed with an emphasis on the signature extension problem. Registration and preprocessing procedures are discussed with refereence to: normalization of the radiometric values of each scene for scene-to-scene differences; registration techniques, implemented at the NASA Johnson Space Center, capable of 0.5 pixel root-mean-square error; and current research in this direction. Data transformation and modeling techniques applied to the Landsat MSS images and a solution for the field-to-field variations of the greenness and brightness temporal trajectories are included. Finally, a review of the mixture decomposition method of labeling and estimating the areal proportions is given.

Hall, F. G.↗
NASA NTRS1993

Optical effects of space weathering on lunar soils and the role of the finest fraction

Lunar soils represent a cumulative product of space weathering and as such they exhibit distinct optical alteration. In comparison to the optical properties of similar rock powders, lunar soils are darker, have weaker diagnostic absorption bands, and exhibit a characteristic red continuum slope between 0.3 and 4.5 microns. Well-developed (mature) lunar soils have a mean grain size of about 60 microns and may contain more than 50 percent agglutinates (complex, glass-welded aggregates) which were previously believed to be the principal carriers of optical alteration resulting from space weathering. A detailed analysis of the spectral reflectance properties of the bulk soil, size separates, and agglutinate separates of several Apollo and Luna soils has been undertaken to evaluate the validity of the agglutinate paradigm for optical effects of space weathering. The data and results are summarized here which indicate that the finest fraction of natural lunar soils, rather than larger complex agglutinates, carries the principal effects of optical alteration. Bidirectional reflectance spectra were obtained using the small sample configuration of the RELAB facility, which accommodates 5-30 mg of material. Spectra are displayed with the labels for individual samples listed in order of brightness.

Pieters, C. M.↗
NASA NTRS2004

The Near-Earth Space Radiation for Electronics Environment

The earth's space radiation environment is described in terms of: a) charged particles as relevant to effects on spacecraft electronics, b) the nature and distribution of trapped and transiting radiation, and c) their effect on electronic components.

Stassinopoulos, E. G.↗
NASA NTRS2021

Exploring Sentinel-1 and Sentinel-2 diversity for Flood inundation mapping using deep learning

Identification of flood water extent from satellite images has historically relied on either synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to cloud free conditions, whereas SAR imagery is plagued by noise-like speckle. Prior studies that use combinations of MS and SAR data to overcome individual limitations of these sensors have not fully examined sensitivity of flood mapping performance to different combinations of SAR and MS derived spectral indices or band transformations in color space. This study explores the use of diverse bands of Sentinel 2 (S2) through well-established water indices and Sentinel 1 (S1) derived SAR imagery along with their combinations to assess their capability for generating accurate flood inundation maps. The robustness in performance of S-1 and S-2 band combinations was evaluated using 446 hand labeled flood inundation images spanning across 11 flood events from Sen1Floods11 dataset which are highly diverse in terms of land cover as well as location. A modified K-fold cross validation approach is used to evaluate the performance of 32 combinations of S1 and S2 bands using a fully connected deep convolutional neural network known as U-Net. Our results indicated that usage of elevation information has improved the capability of S1 imagery to produce more accurate flood inundation maps. Compared to a median F1 score of 0.62 when using only S1 bands, the combined use of S1 and elevation information led to an improved median F1 score of 0.73. Water extraction indices based on S2 bands have a statistically significant superior performance in comparison to S1. Among all the band combinations, HSV (Hue, Saturation, Value) transformation of S2 bands provides a median F1 score of 0.9, outperforming the commonly used water spectral indices owing to HSV’s transformation’s superior contrast distinguishing abilities. Additionally, U-Net algorithm was able to learn the relationship between raw S2 based water extraction indices and their corresponding raw S2 bands, but not of HSV owing to relatively complex computation involved in the latter. Results of the paper establishes important benchmarks for the extension of S1 and S2 data-based flood inundation mapping efforts over large spatial extents.

Goutam Konapala↗
NASA NTRS2023

A Global Land Cover Training Dataset From 1984 to 2020

State-of-the-art cloud computing platforms such as Google Earth Engine (GEE) enable regional-to-global land cover and land cover change mapping with machine learning algorithms. However, collection of high-quality training data, which is necessary for accurate land cover mapping, remains costly and labor-intensive. To address this need, we created a global database of nearly 2 million training units spanning the period from 1984 to 2020 for seven primary and nine secondary land cover classes. Our training data collection approach leveraged GEE and machine learning algorithms to ensure data quality and biogeographic representation. We sampled the spectral-temporal feature space from Landsat imagery to efficiently allocate training data across global ecoregions and incorporated publicly available and collaborator-provided datasets to our database. To reflect the underlying regional class distribution and post-disturbance landscapes, we strategically augmented the database. We used a machine learning-based cross-validation procedure to remove potentially mis-labeled training units. Our training database is relevant for a wide array of studies such as land cover change, agriculture, forestry, hydrology, urban development, among many others.

Radost Stanimirova↗
NASA NTRS2004

Space Communications Emulation Facility

Establishing space communication between ground facilities and other satellites is a painstaking task that requires many precise calculations dealing with relay time, atmospheric conditions, and satellite positions, to name a few. The Space Communications Emulation Facility (SCEF) team here at NASA is developing a facility that will approximately emulate the conditions in space that impact space communication. The emulation facility is comprised of a 32 node distributed cluster of computers; each node representing a satellite or ground station. The objective of the satellites is to observe the topography of the Earth (water, vegetation, land, and ice) and relay this information back to the ground stations. Software originally designed by the University of Kansas, labeled the Emulation Manager, controls the interaction of the satellites and ground stations, as well as handling the recording of data. The Emulation Manager is installed on a Linux Operating System, employing both Java and C++ programming codes. The emulation scenarios are written in extensible Markup Language, XML. XML documents are designed to store, carry, and exchange data. With XML documents data can be exchanged between incompatible systems, which makes it ideal for this project because Linux, MAC and Windows Operating Systems are all used. Unfortunately, XML documents cannot display data like HTML documents. Therefore, the SCEF team uses XML Schema Definition (XSD) or just schema to describe the structure of an XML document. Schemas are very important because they have the capability to validate the correctness of data, define restrictions on data, define data formats, and convert data between different data types, among other things. At this time, in order for the Emulation Manager to open and run an XML emulation scenario file, the user must first establish a link between the schema file and the directory under which the XML scenario files are saved. This procedure takes place on the command line on the Linux Operating System. Once this link has been established the Emulation manager validates all the XML files in that directory against the schema file, before the actual scenario is run. Using some very sophisticated commercial software called the Satellite Tool Kit (STK) installed on the Linux box, the Emulation Manager is able to display the data and graphics generated by the execution of a XML emulation scenario file. The Emulation Manager software is written in JAVA programming code. Since the SCEF project is in the developmental stage, the source code for this type of software is being modified to better fit the requirements of the SCEF project. Some parameters for the emulation are hard coded, set at fixed values. Members of the SCEF team are altering the code to allow the user to choose the values of these hard coded parameters by inserting a toolbar onto the preexisting GUI.

Hill, Chante A.↗
NASA NTRS2003

In-Flight Observations of Long-Term Single Event Effect(SEE)Performance on Orbview-2 and Xray Timing Explorer(XTE)Solid State Recorders (SSR)

This paper presents Single Event Effect (SEE) in-flight data on Solid State Recorders (SSR) that have been collected over a long period of time for two NASA spacecraft: Orbview-2 and XTE. SEE flight data on solid-state memories give an opportunity to study the behavior in space of SEE sensitive commercial devices. The actual Single Event Upset (SEU) rates can be compared with the calculated rates based on environment models and ground test data. The SEE mitigation schemes can also be evaluated in actual implementation. A significant amount of data has already been published concerning observed SEE effects on memories in space. However, most of the data presented cover either a short period of time or a small number of devices. The data presented here has been collected on a large number of devices during several years. This allows statistically significant information about the effect of space weather fluctuations on SEU rates, and the effectiveness of SEE countermeasures used to be analyzed. Only Orbview-2 data is presented in this summary. XTE data will be included in the final paper.

Poivey, Christian↗
NASA NTRS1999

Did Viking discover life on Mars?

A major argument in the claim that life had been discovered during the Viking mission to Mars is that the results obtained in the Labeled Release (LR) experiment are analogous to those observed with terrestrial microorganisms. This assertion is critically examined and found to be implausible.

Non-NASA Center↗
NASA NTRSDate not supplied

In Situ Water Quality Data for the Chesapeake Bay

This paper examines in situ water quality datameasured during2020-2021in the Chesapeake Bay for comparison with optical satellite data. Thiscollection was performed as part of a NASA project aiming to develop new methods for water quality monitoring from satellite remote sensingusing artificial intelligence. Our objective is to use insitu data as ground-truth to provide water quality classifications, or labels,to their overlapping (in time and location)satellite imagery. Having such labeled data, can help us achieve our project’s longer-termgoal:to train artificial intelligencemodelsto recognize features in spectral informationfor monitoringwater qualityfrom satellites. Because routine monitoring by state agencies is conducted at discrete locations, we obtained a flow-through system operated from small boats to measure waterquality parameters along transects for comparison with two-dimensional maps collected from space, with an initial focus on low oxygenevents, due to their large spatial extent and regular occurrence each summer.We also evaluated similar in situ data collected during 1984-2021by the Chesapeake Program.

Nargess Memarsadeghi↗