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At least 523 records · Page 29

On-Orbit Performance of the Spitzer Space Telescope: Science Meets Engineering

The Spitzer Space Telescope operated for over 16 years in an Earth-trailing solar orbit, returning not only a wealth of scientific data but also, as a by-product, spacecraft and instrument engineering data that will be of interest to future mission planners. These data will be particularly useful because Spitzer operated in an environment essentially identical to that at the L2 LaGrange point, where many future astrophysics missions will operate. In particular, the radiative cooling demonstrated by Spitzer has been adopted by other infrared space missions, from JWST to SPHEREx. We aim to facilitate the utility of the Spitzer engineering data by collecting the more unique and potentially useful portions into a single, readily accessible publication. We avoid discussion of less unique systems, such as the telecom, flight software, and electronics systems, and do not address the innovations in mission and science operations that the Spitzer team initiated. These and other items of potential interest are addressed in references supplied in an appendix to this paper.

Spitzer↗

Historical data and analysis for the first five years of KSC STS payload processing

General and specific quantitative and qualitative results were identified from a study of actual operational experience while processing 186 science, applications, and commercial payloads for the first 5 years of Space Transportation System (STS) operations at the National Aeronautics and Space Administration's (NASA) John F. Kennedy Space Center (KSC). All non-Department of Defense payloads from STS-2 through STS-33 were part of the study. Historical data and cumulative program experiences from key personnel were used extensively. Emphasis was placed on various program planning and events that affected KSC processing, payload experiences and improvements, payload hardware condition after arrival, services to customers, and the impact of STS operations and delays. From these initial considerations, operational drivers were identified, data for selected processing parameters collected and analyzed, processing criteria and options determined, and STS payload results and conclusions reached. The study showed a significant reduction in time and effort needed by STS customers and KSC to process a wide variety of payload configurations. Also of significance is the fact that even the simplest payloads required more processing resources than were initially assumed. The success to date of payload integration, testing, and mission operations, however, indicates the soundness of the approach taken and the methods used.

Ragusa, J. M.↗

A Method for Validating Causal Diagrams of Human Health Risk in Space Flight

The complexity of cause-and-effect relationships between spaceflight hazards and resulting health conditions clouds understanding of the totality of human system risk in space. In response, NASA has introduced Directed Acyclic Graphs (causal diagrams) into the human systems risk management process. These diagrams allow for a common understanding of the mechanisms that lead from unique hazards of spaceflight to the health outcomes important to agencies and astronauts. However, the paucity of available biomedical data from spaceflight creates a need for methods of validating causal models that can accommodate data from spaceflight model analogs. Here we outline one approach utilizing open-access rodent bone datasets from the Ames Life Sciences Data Archive. The properties of directed acyclic graphs themselves can provide an epistemological and statistical framework for validation of a priori causal representations of human system risk in space flight. The assumed causal connections on the graph creates sets of logical implications: variables that – if the causal diagram is correct – should be correlated, as well as sets that should be conditionally independent. By testing these implied correlations and conditional independencies both statistically and heuristically, we can provide evidence for or against specific causal pathways on the causal diagram. In addition to validation of expert-generated causal diagrams, machine learning techniques can learn the most likely structure of a causal diagram from a given dataset. Comparison with and reconciliation between machine-learned causal diagrams and expert-generated diagrams is another technique for challenging assumptions and improving our understanding of causal mechanisms. Accurately representing complex causation is essential to systemic understanding of human health risks in space travel. Having a robust system of validating causal diagrams helps us arrive at more accurate representations of causal systems. This process will be integral to developing the countermeasures necessary for extended exploration of the moon and Mars.

Robert Reynolds↗

NASA’s Earth System Observatory Formulation Overview

NASA’s Earth System Observatory (ESO) is an array of Earth-focused, interconnected satellite missions focused on five core study areas: Surface Biology and Geology, Mass Change, Aerosols, Surface Deformation and Change, and Clouds, Convection, and Precipitation. Observatory development follows recommendations from the National Academies of Sciences, Engineering and Medicine’s 2017 Earth Science Decadal Survey. Data gathered by ESO missions will provide actionable science to inform decisions related to climate change, disaster mitigation, and wildfires, improve real-time agricultural processes, and many other applications. Targeting launch dates in the late 2020s and early 2030s, each ESO satellite will deliver valuable information, but by working together as a single observatory system, their combined data and imagery will provide the global community with a 4D, holistic view of Earth, from bedrock to atmosphere. The ESO is also building on the legacy of international collaboration in Earth science, with initial participation and collaboration on these missions across space agency partners, including the Japanese Aerospace Exploration Agency (JAXA), Centre National D'Etudes Spatiales (CNES), Canadian Space Agency (CSA), Deutsches Zentrum für Luft- und Raumfahrt (DLR), and Agenzia Spaziale Italiana (ASI). This paper provides an overview of ESO, as well as an update on ESO missions currently in formulation – the Atmosphere Observing System, Mass Change, and Surface Biology and Geology elements – including current mission architectures, international partner collaboration, science community engagement, and applications efforts, as well as how NASA and its partners will make ESO data accessible to users all over the world.

NASA Earth Science↗

Solar System Visualization: Global Science Maps

The goal of the Solar System Visualization (SSV) project is to re-explore the planets using the data from previous National Aeronautics and Space Administration (NASA) planetary missions on and public information.

planetary surfaces↗

High School Citizen Scientists Use AI/ML to Predict Intra-Ocular Pressure From Gene Expression Data for Spaceflown Mice

Artificial Intelligence (AI) and Machine Learning (ML) have increasingly become pivotal in biological and biomedical research, largely due to the culture of open data sharing and its associated benefits. The methodologies inherent in AI/ML are particularly adept at identifying and forecasting biological phenotypes from the vast amounts of data generated by next-generation sequencing technologies. These techniques offer substantial promise for advancing research in space biosciences and for the development of automated systems for monitoring space health. Nevertheless, there are crucial aspects to consider when training, validating, and testing machine learning models in both biological research and clinical contexts. It is essential that Open Science principles, including data sharing and the availability of open-source code, are complemented by high-quality, publicly accessible training resources. These resources should focus on best practices and include modules based on real-world scientific cases and data to ensure that future AI/ML practitioners gain practical experience with genuine problems. Addressing this knowledge gap, we have designed, developed, and delivered both interactive and self-paced training programs for citizen scientists worldwide, enabling them to utilize AI/ML for space biology research. This initiative was made possible through generous funding from a Transformation to Open Science Training grant. The interactive training sessions, conducted this summer, utilized AI/ML techniques to analyze data from the Open Science Data Repository, specifically targeting the effects of spaceflight on ocular structure and function. The dataset OSD-583, from the Rodent Research 9 mission, provides experimental data detailing the ocular responses of mice subjected to a 35-day spaceflight, compared with ground control counterparts. Using OSD-583 as observational data, our summer training participants applied AI/ML methods to predict intraocular pressure from RNA-seq data and identify the genes most predictive of the observed responses. Further analysis through pathway enrichment and gene set enrichment revealed that these genes are involved in molecular and cellular processes contributing to retinal degeneration.

James Casaletto↗

Data Storage and sharing for the long tail of science

Research data infrastructure such as storage must now accommodate new requirements resulting from trends in research data management that require researchers to store their data for the long term and make it available to other researchers. We propose Data Depot, a system and service that provides capabilities for shared space within a group, shared applications, flexible access patterns and ease of transfer at Purdue University. We evaluate Depot as a solution for storing and sharing multiterabytes of data produced in the long tail of science with a use case in soundscape ecology studies from the Human- Environment Modeling and Analysis Laboratory. We observe that with the capabilities enabled by Data Depot, researchers can easily deploy fine-grained data access control, manage data transfer and sharing, as well as integrate their workflows into a High Performance Computing environment.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Bandwidth-Efficient Communication through 225 MHz Ka-band Relay Satellite Channel

The communications and navigation space infrastructure of the National Aeronautics and Space Administration (NASA) consists of a constellation of relay satellites (called Tracking and Data Relay Satellites (TDRS)) and a global set of ground stations to receive and deliver data to researchers around the world from mission spacecraft throughout the solar system. Planning is underway to enhance and transform the infrastructure over the coming decade. Key to the upgrade will be the simultaneous and efficient use of relay transponders to minimize cost and operations while supporting science and exploration spacecraft. Efficient use of transponders necessitates bandwidth efficient communications to best use and maximize data throughput within the allocated spectrum. Experiments conducted with NASA's Space Communication and Navigation (SCaN) Testbed on the International Space Station provides a unique opportunity to evaluate advanced communication techniques, such as bandwidth-efficient modulations, in an operational flight system. Demonstrations of these new techniques in realistic flight conditions provides critical experience and reduces the risk of using these techniques in future missions. Efficient use of spectrum is enabled by using high-order modulations coupled with efficient forward error correction codes. This paper presents a high-rate, bandwidth-efficient waveform operating over the 225 MHz Ka-band service of the TDRS System (TDRSS). The testing explores the application of Gaussian Minimum Shift Keying (GMSK), 2/4/8-phase shift keying (PSK) and 16/32- amplitude PSK (APSK) providing over three bits-per-second-per-Hertz (3 b/s/Hz) modulation combined with various LDPC encoding rates to maximize through- put. With a symbol rate of 200 M-band, coded data rates of 1000 Mbps were tested in the laboratory and up to 800 Mbps over the TDRS 225 MHz channel. This paper will present on the high-rate waveform design, channel characteristics, performance results, compensation techniques for filtering and equalization, and architecture considerations going forward for efficient use of NASA's infrastructure.

transmitters receivers↗

Bandwidth-Efficient Communication through 225 MHz Ka-band Relay Satellite Channel

The communications and navigation space infrastructure of the National Aeronautics and Space Administration (NASA) consists of a constellation of relay satellites (called Tracking and Data Relay Satellites (TDRS)) and a global set of ground stations to receive and deliver data to researchers around the world from mission spacecraft throughout the solar system. Planning is underway to enhance and transform the infrastructure over the coming decade. Key to the upgrade will be the simultaneous and efficient use of relay transponders to minimize cost and operations while supporting science and exploration spacecraft. Efficient use of transponders necessitates bandwidth efficient communications to best use and maximize data throughput within the allocated spectrum. Experiments conducted with NASA's Space Communication and Navigation (SCaN) Testbed on the International Space Station provides a unique opportunity to evaluate advanced communication techniques, such as bandwidth-efficient modulations, in an operational flight system. Demonstrations of these new techniques in realistic flight conditions provides critical experience and reduces the risk of using these techniques in future missions. Efficient use of spectrum is enabled by using high-order modulations coupled with efficient forward error correction codes. This paper presents a high-rate, bandwidth-efficient waveform operating over the 225 MHz Ka-band service of the TDRS System (TDRSS). The testing explores the application of Gaussian Minimum Shift Keying (GMSK), 248-phase shift keying (PSK) and 1632- amplitude PSK (APSK) providing over three bits-per-second-per-Hertz (3 bsHz) modulation combined with various LDPC encoding rates to maximize throughput. With a symbol rate of 200 Mbaud, coded data rates of 1000 Mbps were tested in the laboratory and up to 800 Mbps over the TDRS 225 MHz channel. This paper will present on the high-rate waveform design, channel characteristics, performance results, compensation techniques for filtering and equalization, and architecture considerations going forward for efficient use of NASA's infrastructure.

space communications↗

Medical and surgical applications of space biosensor technology

Researchers in space life sciences are rapidly approaching a technology impasse. Many of the critical questions on the impact of spaceflight on living systems simply cannot be answered with the limited available technologies. Research subjects, particularly small animal models like the rat, must be allowed to function relatively untended and unrestrained for long periods to fully reflect the impact of microgravity and spaceflight on their behavior and physiology. These requirements preclude the use of present hard-wired instrumentation techniques and limited data acquisition systems. Implantable sensors and miniaturized biotelemetry are the only means of capturing the fundamental and critical data. This same biosensor and biotelemetry technology has direct application to Earth-based medicine and surgery. Continuous, on-line data acquisition and improved measurement capabilities combined with the ease and flexibility offered by automated, wireless, and portable instruments and data systems, should provide a boon to the health care industry. Playing a key role in this technology revolution is the Sensors 2000! (S2K!) Program at NASA Ames Research Center. S2K!, in collaboration with space life sciences researchers and managers, provides an integrated capability for sensor technology development and applications, including advanced biosensor technology development, spaceflight hardware development, and technology transfer and commercialization. S2K! is presently collaborating on several spaceflight projects with dual-use medical applications. One prime example is a collaboration with the Fetal Treatment Center (FTC) at the University of California at San Francisco. The goal is to develop and apply implantable chemical sensor and biotelemetry technology to continuously monitor fetal patients during extra-uterine surgery, replacement into the womb, through birth and beyond. Once validated for ground use, the method will be transitioned to spaceflight applications to remotely monitor key biochemical parameters in flight animals. Successful application of NASA implantable biosensor and biotelemetry technologies should accelerate the advancement of this and other modern medical procedures while furthering the exploration of life in space.

NASA Discipline General Space Life Sciences↗

The I4 Online Query Tool for Earth Observations Data

The NASA Earth Observation System Data and Information System (EOSDIS) delivers an average of 22 terabytes per day of data collected by orbital and airborne sensor systems to end users through an integrated online search environment (the Reverb/ECHO system). Earth observations data collected by sensors on the International Space Station (ISS) are not currently included in the EOSDIS system, and are only accessible through various individual online locations. This increases the effort required by end users to query multiple datasets, and limits the opportunity for data discovery and innovations in analysis. The Earth Science and Remote Sensing Unit of the Exploration Integration and Science Directorate at NASA Johnson Space Center has collaborated with the School of Earth and Space Exploration at Arizona State University (ASU) to develop the ISS Instrument Integration Implementation (I4) data query tool to provide end users a clean, simple online interface for querying both current and historical ISS Earth Observations data. The I4 interface is based on the Lunaserv and Lunaserv Global Explorer (LGE) open-source software packages developed at ASU for query of lunar datasets. In order to avoid mirroring existing databases - and the need to continually sync/update those mirrors - our design philosophy is for the I4 tool to be a pure query engine only. Once an end user identifies a specific scene or scenes of interest, I4 transparently takes the user to the appropriate online location to download the data. The tool consists of two public-facing web interfaces. The Map Tool provides a graphic geobrowser environment where the end user can navigate to an area of interest and select single or multiple datasets to query. The Map Tool displays active image footprints for the selected datasets (Figure 1). Selecting a footprint will open a pop-up window that includes a browse image and a link to available image metadata, along with a link to the online location to order or download the actual data. Search results are either delivered in the form of browse images linked to the appropriate online database, similar to the Map Tool, or they may be transferred within the I4 environment for display as footprints in the Map Tool. Datasets searchable through I4 (http://eol.jsc.nasa.gov/I4_tool) currently include: Crew Earth Observations (CEO) cataloged and uncataloged handheld astronaut photography; Sally Ride EarthKAM; Hyperspectral Imager for the Coastal Ocean (HICO); and the ISS SERVIR Environmental Research and Visualization System (ISERV). The ISS is a unique platform in that it will have multiple users over its lifetime, and that no single remote sensing system has a permanent internal or external berth. The open source I4 tool is designed to enable straightforward addition of new datasets as they become available such as ISS-RapidSCAT, Cloud Aerosol Transport System (CATS), and the High Definition Earth Viewing (HDEV) system. Data from other sensor systems, such as those operated by the ISS International Partners or under the auspices of the US National Laboratory program, can also be added to I4 provided sufficient access to enable searching of data or metadata is available. Commercial providers of remotely sensed data from the ISS may be particularly interested in I4 as an additional means of directing potential customers and clients to their products.

Stefanov, William L.↗

Cassini Titan Science Integration: Getting a 'Jumpstart' on the Process

The Cassini spacecraft has been in orbit for five years, returning a wealth of scientific data from Titan and the Saturn system. The mission is a cooperative undertaking between NASA, ESA and the Italian Space Agency and the project is currently planning for a second extension of the mission. The Cassini Solstice Mission (CSM) will extend the mission's lifetime until Saturn's northern summer solstice in 2017. The Titan Orbiter Science Team (TOST) has the task of integrating the science observations for all 126 targeted Titan flybys (44 in the Prime Mission, 26 in the first extension (Equinox Mission), and 56 in the second extension (Solstice Mission)) contained in the chosen trajectory. Cassini science instruments are body-fixed with limited ability to articulate; thus, the spacecraft pointing during the flybys must be allocated among the instruments to accomplish the mission's science goals. The science that can be accomplished on each Titan flyby also critically depends on the closest approach altitude, which is in turn determined by the attitude, but changing the altitude impacts the overall trajectory for the Solstice Mission. During the Prime and Extended missions, TOST has learned that the best way to achieve Cassini's Titan science goals is via a 'jumpstart' process prior to final delivery of the trajectory. The jumpstart is driven by the desire to balance Titan science across the entire set of flybys during the CSM, and to influence any changes (tweaks) to the flyby altitudes. By the end of the jumpstart, TOST produces Master Timelines for each flyby, identifying each flyby's prime science observations and allocating control of the spacecraft attitude to specific instrument teams. In addition, developing timelines early, while the science and operations teams are still fully funded, decreases the future workload in integration and implementation.

Steadman, Kimberly B.↗

USSR Space Life Sciences Digest, issue 1

The first issue of the bimonthly digest of USSR Space Life Sciences is presented. Abstracts are included for 49 Soviet periodical articles in 19 areas of aerospace medicine and space biology, published in Russian during the first quarter of 1985. Translated introductions and table of contents for nine Russian books on topics related to NASA's life science concerns are presented. Areas covered include: botany, cardiovascular and respiratory systems, cybernetics and biomedical data processing, endocrinology, gastrointestinal system, genetics, group dynamics, habitability and environmental effects, health and medicine, hematology, immunology, life support systems, man machine systems, metabolism, musculoskeletal system, neurophysiology, perception, personnel selection, psychology, radiobiology, reproductive system, and space biology. This issue concentrates on aerospace medicine and space biology.

Hooke, L. R.↗

AIAA/NASA International Symposium on Space Information Systems, 2nd, Pasadena, CA, Sept. 17-19, 1990, Proceedings. Vols. 1 & 2

These proceedings overview major space information system projects and lessons learned from current missions. Other topics include the science information system requirements for the 1990s, an information systems design approach for major programs, the technology needs and projections, the standards for space data information systems, the artificial intelligence technology and applications, international interoperability, and spacecraft data systems and architectures advanced communications. Other topics include the software engineering technology and applications, the multimission multidiscipline information system architectures, the distributed planning and scheduling systems and operations, and the computer and information systems architectures. Paper presented include prospects for scientific data analysis systems for solar-terrestrial physics in the 1990s, the Columbus data management system, data storage technologies for the future, the German aerospace research establishment, and launching artificial intelligence in NASA ground systems.

Tavenner, Leslie A.↗

Clouds and the Earth's Radiant Energy System (CERES): An Earth Observing System Experiment

Clouds and the Earth's Radiant Energy System (CERES) is an investigation to examine the role of cloud/radiation feedback in the Earth's climate system. The CERES broadband scanning radiometers are an improved version of the Earth Radiation Budget Experiment (ERBE) radiometers. The CERES instruments will fly on several National Aeronautics and Space Administration Earth Observing System (EOS) satellites starting in 1998 and extending over at least 15 years. The CERES science investigations will provide data to extend the ERBE climate record of top-of-atmosphere shortwave (SW) and longwave (LW) radiative fluxes CERES will also combine simultaneous cloud property data derived using EOS narrowband imagers to provide a consistent set of cloud/radiation data, including SW and LW radiative fluxes at the surface and at several selected levels within the atmosphere. CERES data are expected to provide top-of-atmosphere radiative fluxes with a factor of 2 to 3 less error than the ERBE data Estimates of radiative fluxes at the surface and especially within the atmosphere will be a much greater challenge but should also show significant improvements over current capabilities.

Wielicki, Bruce A.↗

Earth Remote Sensing: A Column Closure Approach

Entering the new millennium, there is no doubt that scientists expand greatly their scientific knowledge of the Earth system by utilizing unique capabilities from the vantage points of space. These global satellite observations include the NASA/NOAA Pathfinder and other ongoing data analysis projects, the Earth Observing System (EOS) program, the Earth System Science Pathfinders (ESSP) small research satellite missions, multi-agency planning for the National Polar-orbiting Operational Environmental Satellite (NPOESS), and other international satellite missions. However, using satellite remotely sensed data alone cannot explore fully the physical processes and energetic balance involved in our changing climate. To close the loop, the ground-based remote sensing and airborne in situ measurements are required. This talk provides an overview of the general strategy of Earth remote sensing for a column closure approach and discusses necessary instrumentation.

Tsay, Si-Chee↗