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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 NTRS2018

Leverage Points for System Health Management of Autonomous Systems

Systems Health Management (SHM) is one of three basic functionalities that constitute an autonomous capability of a system. The other two functionalities are Planning & Scheduling, and Task Execution. In an autonomous system, variable autonomy is often distinct from variable authority to sense, decide, and act. There are quantifiable Levels of Autonomy that can be achieved by tuning different portions of the Observe-Orient-Decide-Act loop to provide flexibility and control. This approach is tabulated for multiple domains such as spacecraft and aerial vehicles. Examining SHM through a Systems Thinking lens helps us understand its stocks and flows, loops, and delays. Systems thinking, and modeling, is a useful way to understand change and complexity of systems of many types. There are certain archetypes that underlie well-known autonomy architectures. And there often are leverage points - best places to intervene in a system - that can resolve or mitigate some fundamental challenges in the design and deployment of autonomous systems. I identify these levers and present the ones that have been successfully used in NASA missions.

Systems Thinking↗
NASA NTRS2018

NASA GIBS and Worldview: Leveraging Visualizations to Improve Data Discovery

NASA's Global Imagery Browse Services (GIBS) leverages scientific and community best practices and standards to provide a scalable, compliant, and authoritative source for NASA Earth Observing System (EOS) Earth science data visualizations. Since 2013, its goal has been to "transform how end users interact and discover [EOS] data through visualizations." Imagery layers within GIBS allow end users to easily and quickly interact with full resolution, pre-generated visualizations of scientific parameters. This interactive discovery approach relies on visual observation and identification of phenomena that are not as simply identified otherwise.

Global Imagery Browse Services↗
NASA NTRS2018

Magnetospheric Constellation: Leveraging Space 2.0 for Big Science

Earth's magnetosphere is a large magnetic cavity formed through the interaction of the solar wind and Earth's intrinsic magnetic field. Solar wind energy enters this cavity through a boundary - the magnetopause - separating Earth's field from the solar wind. This energy leads to many forms of "space weather", including the aurora, geomagnetic storms, and energization of the Van Allen radiation belts. Despite decades of research, we still do not understand the extent of dayside reconnection sites, nor do we have a quantifiable understanding of how much energy enters the magnetosphere during different solar wind conditions - necessary for space weather prediction. On the nightside, impulsive flows at various spatial and temporal scales occur frequently during storms and substorms, and couple to the ionosphere through still unresolved physical mechanisms. Because the magnetosphere is so large, it has been understood since the dawn of the space age that a full understanding of this complex region could only be achieved with a large fleet of in situ spacecraft. NASA has studied one such constellation, the socalled "Magnetospheric Constellation" (MagCon), since the1990's, but it is deemed too expensive to implement using traditional approaches. The CubeSat/ SmallSat revolution represents a fundamental disruption to traditional mission architectures, and in this paper I will discuss how, by leveraging innovation in spacecraft subystems, advanced manufacturing, and access to space, we can finally realize this long-term vision of exploration and discovery. The proposed modular approach, utilizing rideshare and propulsive ESPAs, would also enable worldwide participation in the mission, and is applicable to any constellation mission, including Earth Science missions.

Kepko, Emil Larry↗
NASA NTRS2019

Leveraging the Power of SAR Observations for Forest Monitoring Systems

Earth observations from Synthetic Aperture Radar (SAR) can provide unique information related to forest structure and condition. Despite the many advantages of SAR, particularly where clouds impede optical observations, a knowledge gap has prevented the applied remote sensing community from harnessing its full potential. Here, we discuss the results of a collaboration between SERVIR, a joint program between NASA and the U.S. Agency for International Development (USAID), and SilvaCarbon, the United States’ contribution to the Global Forest Observation Initiative, to build global capacity in using SAR for forest monitoring and biomass estimation. This includes primarily the creation of 1) The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation, 2) a series of international hands-on trainings and training materials, 3) quick-reference guides illustrating SAR concepts, and 4) animated videos explaining how SAR works. The SERVIR-Global community joined efforts to develop a hands-on guide to support decision-makers in the forestry community to leverage the power of SAR technology to better protect and manage forest resources. We worked with world-renowned SAR experts to provide targeted trainings and develop the SAR Handbook. This handbook consists of approachable theoretical background and applied content that contributes to filling the knowledge gap in the applied use of SAR technology for forestry applications. We hope that forest managers and remote sensing specialists will use these materials to benefit from currently available SAR datasets, as well as prepare for future SAR missions, such as NISAR and BIOMASS. Since its release on April 11, 2019, the SAR Handbook has been accessed more than 100,000 times in less than a month, demonstrating the remote sensing community’s urgent need and interest to learn and use SAR.

Herndon, Kelsey E.↗
NASA NTRS2017

Leveraging Heritage on the Mars 2020 Project

NASA’s Mars 2020 mission is charged with responding to the highest priority objectives of the 2011 planetary sciences decadal survey, conducting extensive in-situ science on the surface of the Red Planet, and carrying important cross-agency human precursor technologies. The mission concept was predicated on and enabled by leveraging the Curiosity rover engineering design, successful Sky Crane landing systems, and other elements from the Mars Science Laboratory project into a new mission with new payload elements. High-heritage paradigms are unusual for flagship science missions and can be difficult to execute as the realities of spacecraft development intervene. However the project has had good success to-date from concept through formulation and into early implementation. This paper will describe the general approaches developed and used by the Mars 2020 Project team at NASA’s Jet Propulsion Laboratory (JPL).

Wallace, Matthew↗
NASA NTRS2019

Leveraging the Cloud for HDF1 Software Testing

In this talk we will discuss how we leverage the Cloud for HDF software daily regression testing including testing of the HDF5 parallel library on the Cloud cluster using Orange FS.

CI testing↗
NASA NTRS2019

NASA GIBS and Worldview: Leveraging FOSS for NASA Earth Science Data Visualizations

The NASA Global Imagery Browse Services (GIBS) and Worldview interactive mapping site leverage scientific and community best practices, open source software, and public standards to provide a scalable, compliant, and authoritative source for NASA Earth Observing System (EOS) Earth science data visualizations. GIBS and Worldview allow end users to easily and quickly interact with more than 800 full resolution pre-generated raster- and vector-based visualizations. This interactive discovery approach relies on visual observation and identification of phenomena that are not as simply identified otherwise. This eLightning presentation will exhibit the broad set of capabilities and visualization layers made possible through the GIBS and Worldview open source software. Specific dependencies on, and contributions to, open source software will be highlighted. Additionally, opportunities for future improvements for better interoperability and reuse through open source software will be discussed.

NASA Global Imagery Browse Services (GIBS)↗
NASA NTRS2019

Leveraging the Power of SAR Observations for Forest Monitoring Systems

Earth observations from Synthetic Aperture Radar (SAR) can provide unique information related to forest structure and condition. Despite the many advantages of SAR, particularly where clouds impede optical observations, a knowledge gap has prevented the applied remote sensing community from harnessing its full potential. Here, we discuss the results of a collaboration between SERVIR, a joint program between NASA and the U.S. Agency for International Development (USAID), and SilvaCarbon, the United States' contribution to the Global Forest Observation Initiative, to build global capacity in using SAR for forest monitoring and biomass estimation. This includes primarily the creation of 1) The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation, 2) a series of international hands-on trainings and training materials, 3) quick-reference guides illustrating SAR concepts, and 4) animated videos explaining how SAR works. The SERVIR-Global community joined efforts to develop a hands-on guide to support decision-makers in the forestry community to leverage the power of SAR technology to better protect and manage forest resources. We worked with world-renowned SAR experts to provide targeted trainings and develop the SAR Handbook. This handbook consists of approachable theoretical background and applied content that contributes to filling the knowledge gap in the applied use of SAR technology for forestry applications. We hope that forest managers and remote sensing specialists will use these materials to benefit from currently available SAR datasets, as well as prepare for future SAR missions, such as NISAR and BIOMASS. Since its release on April 11, 2019, the SAR Handbook has been accessed more than 100,000 times in less than a month, demonstrating the remote sensing community's urgent need and interest to learn and use SAR.

Herndon, Kelsey E.↗
NASA NTRS2020

Leveraging ASTM Industry Standard F3269-17 for Providing Safe Operations of a Highly Autonomous Aircraft

This paper expands upon the ASTM industry standard F3269-17 to outline a run-time assurance (RTA) network architecture for use in ensuring safe flight operations of a highly autonomous aircraft. An RTA network architecture is proposed and critical features discussed to implement functions where automation is primarily responsible for the safety of the aircraft instead of a pilot. This shift in responsibility, made possible by the proposed architecture, is key to highly resilient automation and is a core enabler for future “pilotless” transportation concepts. The findings in this paper stem from the researcher’s experiences with ASTM in the generation of the standard and some seven years of RTA system development on various flight programs leveraging the RTA concepts outlined in the ASTM standard.

autonomous systems↗
NASA NTRS2020

Leveraging Google Earth Engine User Interface for Semiautomated Wetland Classification in the Great Lakes Basin at 10 m With Optical and Radar Geospatial Datasets

As one of the world’s largest freshwater ecosystems,the Great Lakes Basin houses hundreds of thousands of acres of wetlands that support a variety of crucial ecological and environmental functions at the local, regional, and global levels.Monitoring these wetlands is critical to conservation and restoration efforts, however current methods that rely on field monitoring are labor-intensive, costly, and often outdated. In this study, we present a graphical user interface constructed in Google Earth Engine called the Wetland Extent Tool (WET),which allows semi-automatic wetland classification according to a user-input area of interest and date range. WET composites datasets and conducts multi source, moderate resolution processing utilizing Landsat 8 OLI, Sentinel-2 MSI, Sentinel-1 C-SAR, and Shuttle Radar Topography Mission (SRTM) datasets to classify wetlands in the entire Great Lakes Basin. We evaluated classification results of wetlands, uplands, and open water from May-September 2019, and tested whether SRTM elevation, slope,or the Dynamic Surface Water Extent produced the most accurate results in each Great Lake Basin in conjunction with optical indices and radar composites. We found that elevation produced the most accurate classification in Lake Erie, Michigan,and Ontario, while slope performed best in Lake Huron and Superior. Lake Erie, Michigan, Ontario, and Huron achieved high overall accuracy and identification of wetlands. WET leverages cloud-computing for multi source processing of moderate resolution remote sensing data, and employs a user interface in Google Earth Engine that wetland managers and conservationists can use to monitor wetland extent in the Great Lakes Basin in near real-time.

Vanessa L Valenti↗
NASA NTRS2001

Leveraging middleware-based infrastructure for remote exploration

This paper describes middleware systems developed at JPL, shows how leveraging middleware implementation strategies can facilitate building a mission operations system for managing multiple interacting missions on Mars, and proposes an approach to implementing demonstrations as part of a roadmap providing progressively more intelligent remote exploration.

middleware↗
NASA NTRS2018

Leveraging Commercial Software Defined Radio for Low Cost Deep Space Testing

In a typical space mission development life cycle, there is a stage where the spacecraft needs to test against the ground station for interface compatibility to ensure that the spacecraft will be properly tracked after launch. This testing normally requires the spacecraft team to bring their flight equipment to the ground station facility. While recognizing that testing with actual flight or engineering module is the most preferred option because of maximum fidelity, there are occasion when the use of actual flight hardware is a logistically challenge because of spacecraft development. Having another test tool that can emulate the spacecraft signal – by recording the signal transmitted by the spacecraft and regenerate an RF signal for ground system testing - would be very useful. It is even more an attractive option if such spacecraft emulator is inexpensive and highly portable. In this paper, we describe a low-cost, light-weight recorder/playback assembly (RPA) that supports deep space missions testing. The equipment leverages on commercially available software defined radios (SDR) and public-domain software. The RPA has been used to support two missions. One effort is to validate that the Uchinoura 34-m tracking station of the Japanese Aerospace Exploration Agency (JAXA) would be able to track the upcoming NASA Exploration Mission 1 (EM-1) spacecraft, scheduled for launch in 2019. The second effort is to help with the testing and certification of the 21-m antenna ground station at the Morehead State University (MSU) in Kentucky, United States, prior to the time when the Lunar IceCube spacecraft is ready for actual compatibility testing. The RPA also enables students/staff training of the new ground station, using the RPA signal as test input into the system. This low-cost test signal allows the MSU team to save money on not having to develop a full-scale self-generated telemetry test signal source.

White, Leslie↗
NASA NTRS2018

Low-Thrust Trajectory Design via Direct Transcription Leveraging Structure from the Low-Thrust Restricted Problem

A primary challenge of low-thrust mission design is the development of an initial guess for the state and control history of a trajectory. To address this challenge, one technique assembles dynamical structures, such as periodic orbits and their associated manifolds, into discontinuous chains that are corrected to locally optimal transfer solutions via direct transcription. In this investigation, dynamical structures that leverage low-thrust in a multi-body regime are incorporated into the orbit chain approach to expand the options available for construction of an initial guess and to guide the direct transcription algorithm toward different categories of locally optimal solutions. The properties and structures of the low-thrust model which facilitate orbit chain construction are demonstrated in representative transfer scenarios. Direct transcription is applied to converge upon locally optimal transfer trajectories in both simplified and ephemeris models. Results indicate that low-thrust dynamical structures offer a promising new catalog of options for use in the orbit chain approach to designing optimal low-thrust trajectories.

Grebow, Daniel↗
NASA NTRS2019

Leveraging STARE for Co-aligned Data Locality with netCDF and Python MPI

We have leveraged STARE indexing to package partitioned data chunks from diverse datasets into netCDF files, distributed them on a cluster of 16 lightweight nodes with their placements spatiotemporally co-aligned, and demonstrated a few integrative analyses using netCDF parallel I/O and Python MPI, with single-user performance and scalability comparable to, or even better than, that of a parallel array database management system (ADBMS) such as SciDB. However, records of the node location and STARE index ranges for each data chunk, similar to the chunk maps of SciDB, must be maintained and consulted by the I/O and analysis code for coordinating the analytic operations in parallel, in order to achieve the good performance and scalability.

Kwo-Sen Kuo↗
NASA NTRS2021

NASA Leveraging Commercial Communication Ground Stations for Small Satellites

The Space Communications and Navigation (SCaN) program at NASA has reorganized its operations portfolio into two networks: the Deep Space Network and the new Near Space Network (NSN). With this reorganization, NASA can begin transforming to 100% direct-to-Earth commercial communications services for missions in the near-Earth region. NASA’s leveraging of commercial direct-to-Earth ground stations offers several benefits for the small satellite community, including lower cost, greater coverage, and increased technology infusion. In the fall of 2020, SCaN announced their intention to rely primarily on industry-provided communications services for missions close to Earth by 2030. Commercial services are one way to infuse new technology into the ground station network without requiring an investment from NASA. Digital Video Broadcast, Satellite Second Generation (DVB-S2) is one example of a current technology. When combined with variable coding and modulation (VCM), the system automatically optimizes the data rate based on signal performance, significantly increasing total downlink data volume without an increase in the spacecraft effective isotropic radiated power (EIRP). There are several commercial service providers, including Amazon Web Service (AWS) Ground Station (AGS) and the KSATLITE ground stations that support SmallSat missions using DVB-S2 waveforms for downlinks. This paper identifies some commercial off-the-shelf (COTS) CubeSat/SmallSat DVB-S2 X-band and Ka-band radios. Overall, NASA’s increased dependence on commercial direct-to-Earth ground stations is a significant benefit for the small satellite community.

Space Communications↗
NASA NTRS2022

Co-leveraging Scientific Advances in Space Biology and Astrobiology Towards Achieving NASA’s Life Science Objectives

Executive Summary: Distinct lines of scientific inquiry drives the separation of NASA’s fundamental life science research into Space Biology and Astrobiology. This division developed as a way to place life scientists alongside experts in the physical constraints that define the acclimation, adaptation and evolution of biology systems relevant to their respective subjects. For astrobiology, integration with disciplines such as geology, geochemistry, astronomy, planetary science, etc., enables a comprehensive assessment of the physical environment and its co-evolution with biological processes. Space Biology’s co-location with Physical Sciences places life science researchers adjacent to experts in the physical phenomena associated with microgravity and spaceflight, enabling an understanding of how the spaceflight environment affects biological systems. Despite this separation, aspects of both disciplines have converged on a similar, fundamental objective: to describe and understand the dynamics of complex living communities in the contexts of their physical environments. While the environmental systems and timescales are dramatically different, continuing to motivate the separation into distinct fields, similarities in the underlying objective present opportunities to find efficiencies, reduce overlap, and minimize duplication of effort. Space Biology and Astrobiology share a common need to understand microbial physiology in extreme environments – whether the ‘built’ spaceflight environment or the natural environments in which many astrobiology studies are conducted. In particular, open questions in each discipline require the development of quantitative frameworks, applicable at the ecosystem level, that support predictive capabilities for environments where observations are sparse. Additionally, both disciplines have a need to prepare, detect, and analyze the (potential) biological signal in complex samples-often in a completely autonomous fashion. The next decade will see NASA Space Biology moving to understand and describe the effects of the beyond low-earth orbit (BLEO) spaceflight environment on living systems. This new direction will dramatically reduce the opportunities for ground-based analysis of space-flown samples, driving space biology investigations towards fully autonomous experiments and missions. At the same time, astrobiology life detection missions aimed at detecting biosignatures on Mars and icy moons in the outer solar system could benefit from fully automated sample processing and analysis. There are opportunities to leverage instrument and method development between both disciplines within the context of these BLEO missions.

Astrobiology↗
NASA NTRS2020

A Regional L-band High Biomass Estimation Framework Leveraging Spaceborne Lidar and Interferometric Data to Overcome Backscatter Saturation

We propose a framework to estimate high above ground biomass (AGB) from L-band SAR imagery leveraging spaceborne lidars such as GEDI or ICESat-2 and repeat-pass coherence. Our results indicate we are able to overcome model saturation typically associated with purely backscatter methodologies. We validate our approach using lidar-derived AGB maps from the AfriSAR datasets at Mondah, Ogooue, and Lope. We apply our framework to UAVSAR and ALOS- 2 imagery to obtain 50 meter resolution biomass maps. We obtain < 60% nRMSE (in some cases much better) with negligible relative bias using a multiscale random forest model. We illustrate that the inclusion of coherence can significantly improve high AGB estimation particularly at the coastal site Mondah.

Liao, Tien-hao↗