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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Compact Holographic Data Storage

NASA's future missions would require massive high-speed onboard data storage capability to Space Science missions. For Space Science, such as the Europa Lander mission, the onboard data storage requirements would be focused on maximizing the spacecraft's ability to survive fault conditions (i.e., no loss in stored science data when spacecraft enters the 'safe mode') and autonomously recover from them during NASA's long-life and deep space missions. This would require the development of non-volatile memory. In order to survive in the stringent environment during space exploration missions, onboard memory requirements would also include: (1) survive a high radiation environment (1 Mrad), (2) operate effectively and efficiently for a very long time (10 years), and (3) sustain at least a billion write cycles. Therefore, memory technologies requirements of NASA's Earth Science and Space Science missions are large capacity, non-volatility, high-transfer rate, high radiation resistance, high storage density, and high power efficiency. JPL, under current sponsorship from NASA Space Science and Earth Science Programs, is developing a high-density, nonvolatile and rad-hard Compact Holographic Data Storage (CHDS) system to enable large-capacity, high-speed, low power consumption, and read/write of data in a space environment. The entire read/write operation will be controlled with electrooptic mechanism without any moving parts. This CHDS will consist of laser diodes, photorefractive crystal, spatial light modulator, photodetector array, and I/O electronic interface. In operation, pages of information would be recorded and retrieved with random access and high-speed. The nonvolatile, rad-hard characteristics of the holographic memory will provide a revolutionary memory technology meeting the high radiation challenge facing the Europa Lander mission. Additional information is contained in the original extended abstract.

Chao, T. H.↗
NASA NTRS2018

Automated Impact Assessment: A New Approach to ISS Payload Operations Anomaly Response

The International Space Station (ISS) Payload Operations and Integration Center (POIC) is undergoing rapid growth as the space station program focuses on science and commercial activities. The ISS is expanding its onboard capabilities to support additional science activities. In parallel, the POIC is expanding the capabilities of our operations tools to support the higher pace of payload activities being executed each week. An effect of these changes is that anomaly resolution has become more challenging. In the event of a real-time system fault, operators are responsible for analyzing telemetry displays, anomaly monitoring tools, documentation, and system models in order to produce failure impacts and recovery strategies. This approach to operations relies on the operator to ingest, process, and analyze information from an array of deterministic sources to provide actionable data on impacted systems and activities. Changing the existing approach of anomaly response is necessary if the ISS community is to succeed in the age of science and commercialization of space. The creation of a tool that captures deterministic technical systems knowledge and integrates existing telemetry, documentation, and planning information will allow the burden of impact assessment to be automated, thereby allowing the operator to focus on non-deterministic tasks, such as recovering failed systems and restoring critical payload operations.

Hall, R. Mason↗
NASA NTRS2020

Operations Concept for Responding to Urgent Requests for NASA-ISRO Synthetic Aperture Radar (NISAR)

The NASA-ISRO Synthetic Aperture Radar, or NISAR, mission is an Earth-mapping radar observatory to be launched from Sriharikota (India) in 2022. This mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Indian Space Research Organization (ISRO). This spacecraft will carry two instruments that will operate at radar wavelengths (L and Sband) and will provide data for understanding changes in the Earth’s land surface. The scientific data from this mission will revolutionize our understanding of the causes and consequences of land surface changes on Earth, ranging from Solid Earth Deformation in the form of natural hazards like earthquakes, volcanic eruptions and landslides, to ecosystem disturbances, to changes in the cryosphere (measurements of polar ice caps, ice sheets and sea ice). A nominal Reference Observation Plan, that repeats roughly every 12-24 days, developed prior to launch by the NISAR Mission Planning team, in consultation with the Science Team, will form the basis of science data collection by the payload instruments onboard the NISAR observatory after launch. Scheduling of science observations for the mission requires accounting for limited spacecraft resources like onboard data storage, downlink capacity, energy/power, thermal limits and instrument duty cycles. In addition to nominal science data collection, the project has a Level 1 requirement to respond to requests for urgent data acquisition over disaster sites (natural or anthropogenic) by scheduling new acquisitions within 24 hrs of notification and delivering science data within 5 hours of data acquisition. This capability is to be exercised on a ‘best-efforts basis’. While the definition of what constitutes an ‘urgent request’, and how such requests would be submitted to the project, is within the domain of the Science Team, the Mission System team is responsible for developing the baseline operations concept and implementation approach for responding to such requests. Given the ‘best-efforts’ nature of this requirement, a few highlevel guidelines have been developed to help guide the formulation of the operations concept, and are presented in this paper. Requests for urgent response data will be accommodated following the guiding principle of minimal to no impact on nominal science and planned engineering activities. No change in satellite orbit or attitude will be made for urgent response. Restricting response approaches to only changing the downlink and/or ground processing priority for existing observations, and adding new observations only in areas where NISAR will not be nominally imaging, allows for minimal impact on the Reference science Observation Plan. No instrument mode changes will be allowed for urgent response (except for high-priority requests), and no new observations that impact either planned science or engineering activities will be scheduled. Additionally, data requests must fit within the available project resource margins (both spacecraft and ground resources are to be evaluated). Both JPL and ISRO will be involved at various steps of the implementation, irrespective of whether the urgent request is for L-SAR (NASA instrument) or S-SAR (ISRO instrument) or a joint dataset.

Sharma, Priyanka↗
NASA NTRS2011

The Quest for Organic Carbon on Mars

We are entering an era of Mars exploration in which organic carbon detection, characterization, and structural identification will be key to addressing some of the outstanding science objectives of the Mars Exploration Program. Success of these missions will depend on technical, scientific, and strategic elements--all of which are strongly determined based on terrestrial experience and knowledge of organic matter formation, concentration, and preservation. Analog studies including Precambrian sediments, modern endolithic communities, and experiments help us fine-tune these approaches, but we also need to expect the unexpected. This presentation will provide perspective on the challenges of detecting organic carbon on Mars, how we may achieve such detections with the in situ instruments, such as the SAM (Science Analysis at Mars) instrument suite onboard Curiosity, the rover for the 2011 Mars Science Laboratory mission.

Eigenbrode, Jennifer↗
NASA NTRS1999

Spacecraft Onboard Software Maintenance: An Effective Approach which Reduces Costs and Increases Science Return

Flight software (FSW) is a mission critical element of spacecraft functionality and performance. When ground operations personnel interface to a spacecraft, they are dealing almost entirely with onboard software. This software, even more than ground/flight communications systems, is expected to perform perfectly at all times during all phases of on-orbit mission life. Due to the fact that FSW can be reconfigured and reprogrammed to accommodate new spacecraft conditions, the on-orbit FSW maintenance team is usually significantly responsible for the long-term success of a science mission. Failure of FSW can result in very expensive operations work-around costs and lost science opportunities. There are three basic approaches to staffing on-orbit software maintenance, namely: (1) using the original developers, (2) using mission operations personnel, or (3) assembling a Center of Excellence for multi-spacecraft on-orbit FSW support. This paper explains a National Aeronautics and Space Administration, Goddard Space Flight Center (NASA/GSFC) experience related to the roles of on-orbit FSW maintenance personnel. It identifies the advantages and disadvantages of each of the three approaches to staffing the FSW roles, and demonstrates how a cost efficient on-orbit FSW Maintenance Center of Excellence can be established and maintained with significant return on the investment.

Shell, Elaine M.↗
NASA NTRS2022

Quasi-Periodic Whistler Mode Emission in the Plasmasphere as Observed By the DSX Spacecraft

We describe the quasi-periodic (QP) whistler-mode emissions found in the plasmasphere as detected by electric and magnetic instrumentation onboard the Demonstration and Science Experiments (DSX) spacecraft in medium Earth orbit. Over the course of the nearly 2-year mission, at least 45 episodes of whistler mode QP emissions were detected by the Broad Band Receiver (BBR) onboard DSX. Episodes of QP emissions were identified by discrete events having a clear unambiguous periodic nature as detected by both the electric antennae and search coil magnetic sensor in the BBR survey data at 30 second temporal resolution. Most of the QP episodes occurred in a frequency range between 1- 4 kHz, in a band previously identified by Van Allen Probes and Cluster investigators. However, episodes were also detected by DSX at higher frequencies - events in these episodes extending all the way to 15 kHz. We present our findings on these unusual high frequency events in the presentation herein. Specifically, these high frequency QP episodes tended to be observed near dawn/dusk when the spacecraft was at relatively high magnetic latitudes and on magnetic L-shells between 3-5. Another unusual feature of these episodes is that individual up-drifting events making up the episode were found to sometimes occur concurrently in time: The high frequency portion of one up-drifting ‘polliwog-shaped’ event overlapped in time with the low frequency portion of the subsequent event. This behavior of the QP emissions has not been previously emphasized and we consider how this temporal concurrence relates to the source processes.

Quasi-periodic↗
NASA NTRS2012

Expedition Earth and Beyond: Using Crew Earth Observation Imagery from the International Space Station to Facilitate Student-Led Authentic Research

Student-led authentic research in the classroom helps motivate students in science, technology, engineering, and mathematics (STEM) related subjects. Classrooms benefit from activities that provide rigor, relevance, and a connection to the real world. Those real world connections are enhanced when they involve meaningful connections with NASA resources and scientists. Using the unique platform of the International Space Station (ISS) and Crew Earth Observation (CEO) imagery, the Expedition Earth and Beyond (EEAB) program provides an exciting way to enable classrooms in grades 5-12 to be active participants in NASA exploration, discovery, and the process of science. EEAB was created by the Astromaterials Research and Exploration Science (ARES) Education Program, at the NASA Johnson Space Center. This Earth and planetary science education program has created a framework enabling students to conduct authentic research about Earth and/or planetary comparisons using the captivating CEO images being taken by astronauts onboard the ISS. The CEO payload has been a science payload onboard the ISS since November 2000. ISS crews are trained in scientific observation of geological, oceanographic, environmental, and meteorological phenomena. Scientists on the ground select and periodically update a series of areas to be photographed as part of the CEO science payload.

Graff, P. V.↗
NASA NTRS2014

Prototype and Metrics for Data Processing Chain Components of IPM

This presentation lays out the evolution of the Intelligent Payload Module (IPM) vision given that the HyspIRI mission has been delayed. It shows that there has been a focus on airborne vehcile and unmanned aerial systems to further develop the IPM functionality. This of course does not preclude use of the IPM for space missions but provides alternate paths to continue the concept of improved onboard processing for low latency users of science data products.

Onboard Processing↗
NASA NTRSDate not supplied

CLDP/ISS Glovebox Technical Interchange Meeting

This presentation is designed to provide a high-level overview of the Microgravity Science Glovebox (MSG) and the Life Sciences Glovebox (LSG) facilities onboard the International Space Station. In addition, it provides metrics and lessons-learned information intended for the Commercial Low-Earth Orbit Development Program (CLDP) Partners.

glovebox↗
NASA NTRSDate not supplied

Machine Learning for NASA Advanced Information Systems

NASA's Advanced Information Systems Technology (AIST) Program is one of several Technology programs managed by the Earth Science Technology Office (ESTO) in the Earth Science Division (ESD). The AIST Program focuses on advanced information systems and novel computer science technologies that will be needed by NASA Earth Science in the next 5 to 10 years. The three main thrusts of the AIST Program deal with Novel Observing Strategies (NOS), Analytic Collaborative Frameworks (ACF) and Earth System Digital Twins (ESDT). For all these thrusts, Machine Learning (ML) is increasingly being used in multiple aspects of Earth science systems, e.g., for onboard autonomy and decision making, for the analysis of massive and diverse datasets as well as more recently for developing surrogate models that will represent one of the main components of future Digital Twins of the Earth. Particularly, ESDT technologies developed by the AIST Program will allow to develop integrated Earth Science frameworks that will mirror the Earth with state-of-the-art models (Earth system models and others), timely and relevant observations, and analytic tools. These information systems will be used for supporting near- and long-term science and policy decisions. ESDT frameworks will build on previously developed AIST capabilities and technologies to integrate interconnected models with continuous streams of observations, data analytics, data assimilation, simulations, advanced visualizations and the ability to conduct "what-if" scenarios. This talk will describe the three thrusts of the AIST Program with a special focus on Machine Learning and how it is being used at all steps of the Earth Science data lifecycle.

Mathematical and Computer Sciences (General)↗
NASA NTRS2003

Machine learning challenges in Mars rover traverse science

The successful implementation of machine learning in autonomous rover traverse science requires addressing challenges that range from the analytical technical realm, to the fuzzy, philosophical domain of entrenched belief systems within scientists and mission managers.

OASIS onboard autonomous science investigation sys↗
NASA NTRS2002

The Intelligent Data Understanding Element of NASA's Intelligent Systems Program

Within the NASA Intelligent Systems Program, the Intelligent Data Understanding (IDU) element develops techniques for transforming data into scientific understanding. Automating such tools is critical for space science, space-based earth science, and planetary exploration with onboard scientific data analysis. Intelligent data understanding (IDU) is about extracting meaning from large, diverse science and engineering databases, via autonomous techniques that transform very large datasets into understanding. The earth science community in particular needs new tools for analyzing multi-formatted and geographically distributed datasets and for identifying cause-effect relationships in the complex data. Research within the IDU program element seeks to automate data analysis tasks so that humans can focus on creative hypothesis generation and knowledge synthesis. It may also enable NASA space missions in which autonomous agents must generate knowledge and take actions, and missions where limited bandwidth permits transmission of only the most interesting scientific observations, summaries, and conclusions. Twenty-seven research projects are-currently funded.

Coughlan, Joseph C.↗
NASA NTRS2017

AI and Autonomy Initiatives for NASA’s Deep Space Network (DSN)

NASA’s Deep Space Network (DSN) consists of thirteen large (34- and 70-meter) antennas that are used to communicate with approximately 40 NASA and partner spacecraft, all at great distance from the earth (generally at Lunar distances and beyond). The DSN has a long history — over 50 years — and has evolved with cutting edge, often custom, telecommunications equipment and associated software systems. In recent years, and in preparation for an increasing future demand, there has been an effort to invest in initiatives that will result in significant cost savings in the future. These efforts are building on, or augmenting, the recent deployment of “Follow-the-Sun” operations (day shift remote operational control of the entire network from each of the three antenna complexes in turn) — which is being deployed in 2017. This paper focuses on Adaptive Demand Access: in a paradigm shift from completely pre-planned operations, this concept calls for spacecraft to signal their intent (or not) for near-future contacts, in case they have science results of interest, or have experienced an anomaly. This would take advantage of a beacon tone transmission, which can be detected using smaller antennas. When a connection request is received, the DSN ground systems would adaptively accommodate the request, inserting the contact into the plan as soon as possible, subject to constraints and priorities. The demand access concept incorporates onboard data analysis and science data processing, so that beacon tones can be generated with maximum information. This area is representative of several where infusing AI technologies can lead to improved effectiveness of the DSN as the network readies for support of expanded Mars exploration efforts in the 2020’s and beyond.

Wyatt, E. Jay↗
NASA NTRS2013

Detection of Organics at Mars: How Wet Chemistry Onboard SAM Helps

For the first time in the history of space exploration, a mission of interest to astrobiology could be able to analyze refractory organic compounds in the soil of Mars. Wet chemistry experiment allow organic components to be altered in such a way that improves there detection either by releasing the compounds from sample matricies or by changing the chemical structure to be amenable to analytical conditions. The latter is particular important when polar compounds are present. Sample Analysis at Mars (SAM), on the Curiosity rover of the Mars Science Laboratory mission, has onboard two wet chemistry experiments: derivatization and thermochemolysis. Here we report on the nature of the MTBSTFA derivatization experiment on SAM, the detection of MTBSTFA in initial SAM results, and the implications of this detection.

astrobiology↗
NASA NTRS2003

Rover traverse science for increased mission science return

In this paper, we will describe out methods for the prioritization of geologic data acquired by an in-situ rover. Our techniques are applicable to a wide range of data modalites, however out initial demonstration is focused on image analysis, as images consume a large volume of the downlink bandwidth for such missions.

data prioritization↗
NASA NTRS2004

The EO-1 Autonomous Science Agent Architecture

An Autonomous Science Agent is currently flying onboard the Earth Observing One Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and run-time robust execution. Because of the deployment to a remote spacecraft, this Autonomous Science Agent has stringent constraints of autonomy, reliability, and limited computing resources. We describe these constraints and how they are reflected in our agent architecture.

Earth Observing One (EO-1)↗
NASA NTRS2004

Safe Agents in Space: Lessons from the Autonomous Sciencecraft Experiment

An Autonomous Science Agent is currently flying onboard the Earth Observing One Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and run-time robust execution. Because of the deployment to a remote spacecraft, this Autonomous Science Agent has stringent constraints of autonomy, reliability, and limited computing resources. We describe these constraints and how they are reflected in our agent architecture.

Eatth Observing One Spacecraft↗