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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Implementing Distributed Operations: A Comparison of Two Deep Space Missions

Two very different deep space exploration missions--Mars Exploration Rover and Cassini--have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a mission of more than ten years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process. Additionally, MER has benefited from the initial co-location of its entire operations team, and from having a single Principal Investigator, while Cassini operations have had to reconcile multiple science teams distributed from before launch. Cassini has faced greater challenges in implementing effective distributed operations. Because extensive early planning is required to capture science opportunities on its tour and because sequence development takes significantly longer than sequence execution, multiple teams are contributing to multiple sequences concurrently. The complexity of integrating inputs from multiple teams is exacerbated by spacecraft operability issues and resource contention among the teams, each of which has their own Principal Investigator. Finally, much of the technology that MER has exploited to facilitate distributed operations was not available when the Cassini ground system was designed, although later adoption of web-based and telecommunication tools has been critical to the success of Cassini operations.

Cassini Mission↗
NASA NTRS2010

An Overview of the Landsat Data Continuity Mission

The advent of the Landsat Data Continuity Mission (LDCM), currently with a launch readiness date of December, 2012, will see evolutionary changes in the Landsat data products available from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The USGS initiated a revolution in 2009 when EROS began distributing Landsat data products at no cost to requestors in contrast to the past practice of charging the cost of fulfilling a request; that is, charging $600 per Landsat scene. To implement this drastic change, EROS terminated data processing options for requestors and began to produce all data products using a consistent processing recipe. EROS plans to continue this practice for the LDCM and will required new algorithms to process data from the LDCM sensors. All previous Landsat satellites flew multispectral scanners to collect image data of the global land surface. Additionally, Landsats 4, 5, and 7 flew sensors that acquired imagery for both reflective spectral bands and a single thermal band. In contrast, the LDCM will carry two pushbroom sensors; the Operational Land Imager (OLI) for reflective spectral bands and the Thermal InfraRed Sensor (TIRS) for two thermal bands. EROS is developing the ground data processing system that will both calibrate and correct the data from the thousands of detectors employed by the pushbroom sensors and that will also combine the data from the two sensors to create a single data product with registered data for all of the OLI and TIRS bands.

Irons, James R.↗
NASA NTRS1977

Application of LANDSAT to the management of Delaware's marine and wetland resources

The author has identified the following significant results. LANDSAT data were found to be the best source of synoptic information on the distribution of horizontal water mass discontinuities (fronts) at different portions of the tidal cycle. Distributions observed were used to improve an oil slick movement prediction model for the Delaware Bay. LANDSAT data were used to monitor the movement and dispersion of industrial acid waste material dumped over the continental shelf. A technique for assessing aqueous sediment concentration with limited ground truth was proposed.

Klemas, V.↗
NASA NTRS1992

Methodologies for building robust schedules

COMPASS is the name of a Computer Aided Scheduling System designed and built for NASA. COMPASS can be used to develop schedule of activities based upon the temporal relationships of the activities and their resource requirements. COMPASS uses this information, and guided by the user, develops precise start and stop times for the activities. In actual practice however, it is impossible to know with complete certainty what the actual durations of the scheduled activities will really be. The best that one can hope for is knowledge of the probability distribution for the durations. This paper investigates methodologies for using a scheduling tool like COMPASS that is based upon definite values for the resource requirements, while building schedules that remain valid in the face of the schedule execution perturbations. Representations for the schedules developed by these methodologies are presented, along with a discussion of the algorithm that could be used by a computer onboard a spacecraft to efficiently monitor and execute these schedules.

Dean, John H.↗
NASA NTRS2007

AIRSAR Web-Based Data Processing

The AIRSAR automated, Web-based data processing and distribution system is an integrated, end-to-end synthetic aperture radar (SAR) processing system. Designed to function under limited resources and rigorous demands, AIRSAR eliminates operational errors and provides for paperless archiving. Also, it provides a yearly tune-up of the processor on flight missions, as well as quality assurance with new radar modes and anomalous data compensation. The software fully integrates a Web-based SAR data-user request subsystem, a data processing system to automatically generate co-registered multi-frequency images from both polarimetric and interferometric data collection modes in 80/40/20 MHz bandwidth, an automated verification quality assurance subsystem, and an automatic data distribution system for use in the remote-sensor community. Features include Survey Automation Processing in which the software can automatically generate a quick-look image from an entire 90-GB SAR raw data 32-MB/s tape overnight without operator intervention. Also, the software allows product ordering and distribution via a Web-based user request system. To make AIRSAR more user friendly, it has been designed to let users search by entering the desired mission flight line (Missions Searching), or to search for any mission flight line by entering the desired latitude and longitude (Map Searching). For precision image automation processing, the software generates the products according to each data processing request stored in the database via a Queue management system. Users are able to have automatic generation of coregistered multi-frequency images as the software generates polarimetric and/or interferometric SAR data processing in ground and/or slant projection according to user processing requests for one of the 12 radar modes.

Chu, Anhua↗
NASA NTRS2013

Distributed Prognostics and Health Management with a Wireless Network Architecture

A heterogeneous set of system components monitored by a varied suite of sensors and a particle-filtering (PF) framework, with the power and the flexibility to adapt to the different diagnostic and prognostic needs, has been developed. Both the diagnostic and prognostic tasks are formulated as a particle-filtering problem in order to explicitly represent and manage uncertainties in state estimation and remaining life estimation. Current state-of-the-art prognostic health management (PHM) systems are mostly centralized in nature, where all the processing is reliant on a single processor. This can lead to a loss in functionality in case of a crash of the central processor or monitor. Furthermore, with increases in the volume of sensor data as well as the complexity of algorithms, traditional centralized systems become for a number of reasons somewhat ungainly for successful deployment, and efficient distributed architectures can be more beneficial. The distributed health management architecture is comprised of a network of smart sensor devices. These devices monitor the health of various subsystems or modules. They perform diagnostics operations and trigger prognostics operations based on user-defined thresholds and rules. The sensor devices, called computing elements (CEs), consist of a sensor, or set of sensors, and a communication device (i.e., a wireless transceiver beside an embedded processing element). The CE runs in either a diagnostic or prognostic operating mode. The diagnostic mode is the default mode where a CE monitors a given subsystem or component through a low-weight diagnostic algorithm. If a CE detects a critical condition during monitoring, it raises a flag. Depending on availability of resources, a networked local cluster of CEs is formed that then carries out prognostics and fault mitigation by efficient distribution of the tasks. It should be noted that the CEs are expected not to suspend their previous tasks in the prognostic mode. When the prognostics task is over, and after appropriate actions have been taken, all CEs return to their original default configuration. Wireless technology-based implementation would ensure more flexibility in terms of sensor placement. It would also allow more sensors to be deployed because the overhead related to weights of wired systems is not present. Distributed architectures are furthermore generally robust with regard to recovery from node failures.

Goebel, Kai↗
NASA NTRSDate not supplied

NASA's Earthdata Forum: Bringing the Science Community Together

The Earthdata Forum is an actively maintained and operational user forum for all participating NASA EOSDIS Distributed Active Archive Centers (DAACs) and GCMD. The Forum serves as a cross-DAAC platform from which user communities can obtain authoritative information relating to NASA Earth Science. The Atmospheric Science Data Center (ASDC) DAAC takes on the role of both Project Manager and Hosting Organization. As Project Manager, the ASDC leads and facilitates the project's efforts. The Forum launched February 2020 with five participating DAACs: Atmospheric Science Data Center (ASDC), Crustal Dynamics Data Information System (CDDIS), Goddard Earth Science Data and Information Services Center (GES DISC), Global Hydrology Resource Center (GHRC), and Land Processes DAAC (LP DAAC). Since February 2020, the of Level 1 and Atmosphere Archive and Distribution System DAAC (LAADS), the Ocean Biology DAAC (OBDAAC) and Global Change Master Directory (GCMD) have also joined the Forum. The Forum assumes both a proactive and reactive approach to NASA products scientific queries, allowing the scientific community to ask questions about NASA's products, tools, and services and receive announcements and news regarding products, new data releases, and such. In this presentation, we will describe the Earthdata Forum approach to support the scientific community in detail and discuss the successes and challenges of this approach.

Ingrid Garcia-Solera↗
NASA NTRS2022

The VIPER Mission, a Resource-Mapping Mission on Another Celestial Body

The Volatiles Investigation Polar Exploration Rover (VIPER) mission is a lunar polar volatiles prospecting mission developed through NASA’s Science Mission Directorate (SMD) Planetary Science Division with launch in late 2023. VIPER’s mission goals are to (1) characterize the distribution and physical state of lunar polar water and other volatiles in lunar cold traps and regolith and (2)provide the data necessary for NASA to evaluate potential return of In-Situ Resource Utilization (ISRU) from lunar polar regions. VIPER will be optimized for lunar regions that receive prolonged periods of sunlight (short lunar nights). The mission duration will be more than 90 Earth days and result in a traverse distance of up to 20 km. The mission includes a rover-borne payload that can locate surface and near-subsurface volatiles, excavate, and analyze samples of the volatile-bearing regolith, and demonstrate the form, extractability, and usefulness of the materials.

The Volatiles Investigation Polar Exploration Rove↗
NASA NTRSDate not supplied

The Future of Oaks in the Santa Monica Mountains: A Case Study in Using Remote Sensing Data for Species Distributions Models

The Woolsey Fire began on November 8, 2018, and lasted for almost two weeks, during which it burned almost 100,000 acres of valuable landscape and habitat, including a vast area of woodland. The persistence of key woodland species provides aesthetic, monetary, and ecological value to the landscape through carbon sequestration, air temperature moderation, and erosion mitigation, among other ecosystem services. This study investigated the impact of the Woolsey Fire on native woodland species distributions and identified areas suitable for restoration within the Santa Monica Mountains National Recreation Area. The team partnered with the Resource Conservation District of the Santa Monica Mountains; National Park Service, Santa Monica Mountains National Recreation Area; California Department of Parks and Recreation, Los Angeles County Division; County of Los Angeles Fire Department, Prevention Services Bureau, Forestry Division; County of Los Angeles Department of Regional Planning; and the University of Montana. The Earth observations used include data from Landsat 8 Operational Land Imager, NASA ER-2 Jet Airborne Visible InfraRed Imaging Spectrometer, Shuttle Radar Topography Mission, and RapidEye. The team produced maps of burn severity from the Woolsey Fire, its impact on plant species distributions, and habitat suitability projections for 2050 and 2099 to assist partners in prioritizing areas for restoration. A plant community classification was successfully created using Multiple Endmember Spectral Mixture Analysis (MESMA). Overall accuracy was assessed at 90.54% by comparing the classification to validation pixels derived from ground truth information provided by our partners.

Roger Ly↗
NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗
NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗
NASA NTRS2022

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

Kanefsky, Bob↗
NASA NTRS1977

Lunar resources and their utilization

The paper reviews the physical and chemical characteristics of lunar surface materials noting the thickness of the regolith, grain size distribution, regolith petrography, and the chemical composition of the regolith. A comprehensive design of a processing system for the production of structural metals, oxygen, silicon, glass, and ceramic materials is presented. Specifications regarding the location of the processing plant, and its mass, volume, and power requirements are reviewed.

Phinney, W. C.↗
NASA NTRSDate not supplied

LIRA: Probing the Lunar Surface for Resources.

The thermal, compositional and electrical properties of the lunar regolith, such as the triboelectric properties of lunar dust, the volatile content and the thermophysical properties of the polar regolith are essential to understand from a scientific perspective as well as for resource extraction and hazard mitigation. Understanding these properties specifically requires in situ measurement, as these properties are inherent in the ambient environment. With the Lunar In situ Regolith Analyzer (LIRA) we will combine mature surface sensor technologies from previous spacecraft missions (TECP) with new sensors (ClO4- ) and battery capability to achieve a compact in situ analysis package. The surface instrument suite is adapted for lunar conditions from a sensor developed as part of the Microscopy, Electrochemistry, and Conductivity Analyzer (MECA) instrument on the 2007 Mars Phoenix mission, as well as supplemental sensors. • The Thermal and Electrical Conductivity Probe (TECP), flown on MECA/Phoenix, which measures heat capacity, thermal conductivity, electrical resistance, and electrical permittivity between needles inserted into the soil. The TECP also measured atmospheric humidity, a capability that will be retained to search for subsurface H2O ice. The Mars TECP weighed 100-gram and by definition was at TRL 9. The lunar version (LIRA) is TRL 4. • The Perchlorate (ClO4) sensor is based on the fluorescence property of perchlorate (Mg, Fe, Na). We added a light source to excite the perchlorate (ClO4) and a photo diode to collect the emission wavelength. A sun-shade over the photo diode blocks out the ambient light during day light hours. The unifying goal of LIRA is to deliver a complete, integrated experiment suite that investigates properties that must be measured in situ, and provides the capability to power the suite at night or in PSRs, as well as a means to simulate aspects of the diurnal transition by delivering an optical pulse to the surface with intensity comparable to sunlight. We describe the scientific context of LIRA, touching on the electrical state of the near-surface environment, the thermal properties of the undisturbed regolith, and the distribution, geochemistry, and mobility of water. We also address the exploration implications of the work, examining hazards and resources in the context of strategic knowledge gaps (SKGs).

Heather Smith↗
NASA NTRS1974

A reconnaissance space sensing investigation of crustal structure for a strip from the eastern Sierra Nevada to the Colorado Plateau

The author has identified the following significant results. Studies were conducted in key field areas in the Sierra Nevada, the Basin Range Province and the Colorado Plateau to evaluate the origins and significance of geologic and structural anomalies expressed in the ERTS-1 data. The investigation included development of image enhancement and analysis techniques and comparison of remote sensing data available over the test site. The ERTS-1 MSS imagery has proven to be an effective tool for studying the interrelationsships between Cenozoic tectonic patterns and the distributions of Cenozoic plutonism and volcanism, seismic activity, geologic hazards, and known mineral, geothermal and ground water resources. Recommendations are made for applications of ERTS-1 data to natural and resource exploration and management.

Liggett, M. A.↗
NASA NTRS1986

Exobiology experiment concepts for space station

The exobiology discipline uses ground based and space flight resources to conduct a multidiscipline research effort dedicated to understanding fundamental questions about the origin, evolution, and distribution of life and life related molecules throughout the universe. Achievement of this understanding requires a methodical research strategy which traces the history of the biogenic elements from their origins in stellar formation processes through the chemical evolution of molecules essential for life to the origin and evolution of primitive and, ultimately, complex living species. Implementation of this strategy requires the collection and integration of data from solar system exploration spacecraft and ground based and orbiting observatories and laboratories. The Science Lab Module (SLM) of the Space Station orbiting complex may provide an ideal setting in which to perform certain classes of experiments which form the cornerstone of exobiology research. These experiments could demonstrate the pathways and processes by which biomolecules are synthesized under conditions that simulate the primitive Earth, planetary atmospheres, cometary ices, and interstellar dust grains. Exobiology experiments proposed for the Space Station generally fall into four classes: interactions among gases and grains (nucleation, accretion, gas-grain reactions), high energy chemistry for the production of biomolecules, physical and chemical processes occurring on an artificial comet, and tests of the theory of panspermia.

Griffiths, L. D.↗
NASA NTRS1987

Exobiology experiment concepts for Space Station

The exobiology discipline uses ground based and space flight resources to conduct a multidiscipline research effort dedicated to understanding fundamental questions about the origin, evolution, and distribution of life and life related molecules throughout the universe. Achievement of this understanding requires a methodical research strategy which traces the history of the biogenic elements from their origins in stellar formation processes through the chemical evolution of molecules essential for life to the origin and evolution of primitive and, ultimately, complex living species. Implementation of this strategy requires the collection and integration of data from solar system exploration spacecraft and ground based and orbiting observatories and laboratories. The Science Lab Module (SLM) of the Space Station orbiting complex may provide an ideal setting in which to perform certain classes of experiments which form the cornerstone of exobiology research. These experiments could demonstrate the pathways and processes by which biomolecules are synthesized under conditions that stimulate the primitive earth, planetary atmospheres, cometary ices, and interstellar dust grains. Exobiology experiments proposed for the Space Station generally fall into four classes: interactions among gases and grains (nucleation, accretion, gas-grain reactions), high energy chemistry for the production of biomolecules, physical and chemical processes occurring on an artificial comet, and tests of the theory of panspermia.

Griffiths, Lynn D.↗