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Areas of life science are being studied to obtain baseline data, strategies, and technology to permit life research in the space environment. The reactions of the cardiovascular system to prolonged weightlessness are also being investigated. Particle deposition in the human lung, independent respiratory support system, food technology, and remotely controlled manipulators are mentioned briefly.
The spacecraft design and operations and mission results of the Voyager Project are reviewed with particular emphasis on the results of the Saturn encounters. The mission was undertaken by two spacecraft: Voyager 2, launched first on August 20, 1977 on a lower energy trajectory to Jupiter, Saturn, Uranus and Neptune; and Voyager 1, launched on September 5, 1977 on a higher energy trajectory to closer flybys of Jupiter and Saturn. The Voyager spacecraft make use of earlier Mariner and Viking Orbiter design concepts, with additional capabilities for solar independent power, long-range communications and autonomy as well as equipment for the 11 science investigations. The Voyager operations system consists of a ground data system, missions operations system, and support by the Mission Control and Computer Center and Deep Space Network. Among the results of the Jupiter encounter are data concerning the magnetospheric structure and atmospheric dynamics of the planet and the surface features of the Galilean satellites. The encounters with Saturn produced scientific data concerning wind speeds, auroral emissions, and radio emissions from the planet, the fine structure of the previously known and newly discovered rings, the surface features of the satellites and the atmospheric composition and conditions of Titan. Voyager 1 is presently making field and particle measurements on its flight into interstellar space, while Voyager 2 is headed for an encounter with Uranus in January 1986 and Neptune in August 1989.
Space Telescope can generate multidimensional image data, very similar in nature to data produced with microdensitometers. An overview is presented of the ST science ground system between carrying out the observations and the interactive analysis of preprocessed data. The ground system elements used in data archival and retrieval are described and operational procedures are discussed. Emphasis is given to aspects of the ground system that are relevant to the science user and to general principles of system software development in a production environment. While the system being developed uses relatively conservative concepts for the launch baseline, concepts were developed to enhance the ground system. This includes networking, remote access, and the utilization of alternate data storage technologies.
A compilation is given of selected bibliographic data specifically relating to recent publications submitted by principle investigators and their associates, supported through NASA's Office of Space Science and Applications, Solar System Exploration Division, Planetary Geology and Geophysics Program. Topics include the solar system, asteroids, volcanoes, stratigraphy, remote sensing, and planetary craters.
The Deep Space Network (DSN) is responsible for the acquisition of in-situ science and engineering measurements and navigation data from spacecraft exploring the Solar System. Key characteristics of the DSN design approach, the costs to upgrade performance over the past several decades, and some fundamental constraints on performance are discussed. The specific 70-meter upgrade task and the resulting overall benefits to Voyager-Neptune and the mission set are addressed.
This is a compilation of selected bibliographic data specifically relating to recent publications submitted by principle investigators and their associates, supported through the NASA Office of Space Science and Applications, Solar System Exploration Division, Planetary Geology and Geophysics Program.
A compilation of selected bibliographic data specifically relating to recent publications submitted by principal investigators and their associates, supported through the NASA Office of Space Science and Applications, Solar System Exploration Division, Planetary Geology and Geophysics Program is presented.
The heart rate Spectral Analysis System (SAS) acquires and analyzes, in real-time, the Space Shuttle onboard electrocardiograph (EKG) experiment signals, calculates the heartrate, and applies a Fast Fourier Transformation (FFT) to the heart rate. The system also calculates other statistical parameters such as the 'mean heart rate' over specific time period and heart rate histogram. This SAS is used by NASA Principal Investigators as a research tool to determine the effects of weightlessness on the human cardiovascular system. This is also used to determine if Lower Body Negative Pressure (LBNP) is an effective countermeasure to the orthostatic intolerance experienced by astronauts upon return to normal gravity. In microgravity, astronauts perform the LBNP experiment in the mid deck of the Space Shuttle. The experiment data are downlinked by the orbiter telemetry system, then processed and analyzed in real-time by the integrated Life Sciences Data Acquisition (LSDS) - Spectral Analysis System. The data system is integrated within the framework of two different computer systems, VAX and Macintosh (Mac), using the networking infrastructure to assist the investigators in further understanding the most complex machine on Earth--the human body.
The Vehicle Processing Operations Data base (VPOD) has been designed and constructed to enable the collection and preliminary analysis of data relative to the processing of planetary exploration vehicles in low Earth orbit. VPOD has the capability to hierarchically store the events, assemblies, and equipment data needed for performing vehicle processing analysis, to whatever level of detail available. This permits some analysis to be performed even during the very early phases of vehicle and mission design. As more data about the events, assemblies, or equipment become available, the analysis can then be refined using the increased level of detail. VPOD output is based on a mission defined by selecting from the VPOD Events data base the events that are required to perform the desired tasks. The outputs available include total crew time, crew skill requirements, equipment needed, assemblies worked per event, to any available level of detail. The VPOD design is structured to interface with an operations simulation capability which is currently in the requirements definition phase. The simulator will use information from the VPOD to perform operations analysis for missions being conducted in low Earth orbit. VPOD information, along with information from the science missions operations data base and a Space Station configuration data base, will be used by the simulator to provide a capability to study total system operations and resources requirements.
This paper makes three contributions to the area of modern science data processing systems. First, the paper describes the science data processing pipeline, developed at the Multi-mission Image Processing Lab of JPL, for transforming raw space data into high quality image data and automating the distribution of data using a high-performance file transaction service. File Exchange Interface is the file transaction service developed MIPL. Second, it presents the FEI component architecture in the are of file transaction management, security,a nd file integrity verfication. Finally, the paper presents the federated model for the FEI service to demonstrate how to create a pool of file trasaction services to support load balancing and service fallover, and simplify service management.
A SmallSat using a small Radioisotope Power System for deep space destinations could potentially fit into a Discovery class mission cost cap and perform significant science with a timely return of data. Only applicable when the Discovery 12 guidelines were applied. Commonality of hardware and science instruments among identical spacecraft enabled to meet the Discovery Class mission cost cap. Multiple spacecraft shared the costs of the Launch Approval Engineering Process. Assumed a secondary science instrument was contributed. Small RPS could provide small spacecraft with a relatively high power (approx. 60 We) option for missions to deep space destinations (> 10 AU) with multiple science instruments. Study of Centaur mission demonstrated the ability to achieve New Frontiers level science. Multiple spacecraft possible with small RPS, allowing for multiple targets, science from multiple platforms, and/or redundancy.
The integration of payload instruments into the Command and Data Management Subsystem (CDMS) of the Space Shuttle Spacelab is discussed. Specific emphasis is on the distributed (self-contained processor) vs centralized (Spacelab Computer) approach to science payload utilization of these control and data handling capabilities. An overview of the Spacelab CDMS is first given. A synopsis of the integration process for Spacelab Missions 1, 2, and 3 is discussed. Three different hardware approaches to payload command and data handling are then categorized from which Spacelab implementations to date are derived. The different types of Spacelab Mission 3 payload CDMS hardware and software being used are discussed, including examples of microprocessors and data acquisition systems. Preliminary costs for Spacelab application software vs other flight software approaches are compared. A standard RAU interface that would permit a range of ECOS services to be provided, yet be implemented as a mass-produceable unit for incorporation into payloads, is proposed, in keeping with the trend toward simplifying the integration effort, standardizing CDMS interfaces, and ultimately lowering cost.
The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may soon enable unique insight into which measured phenomena correlate to biological mechanisms that are truly affected by spaceflight conditions; which are most likely to be confounded by other variables; and which are insufficiently characterized, significantly increasing existing and future science return from ISS and spaceflight missions.
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.
Observations and measurements of the Earth’s environment have been collected from space since the 1960’s. Flight Projects, airborne and field campaigns have developed and operated multi-year missions with global observing instruments, and Principle Investigator Science Teams have developed algorithms, calibrated, and derived a wide variety of Earth system environmental parameters. These data are archived and distributed for research purposes by NASA’s ESDIS Project and Distributed Active Archive Centers (DAACs). They are expected to be an important basis for Earth science and climate change research extending well beyond their observation times, the Principle Investigators/Science Teams research projects and life of the Flight Projects.
Formation flying is quickly revolutionizing the way the space community conducts autonomous science missions around the Earth and in space. This technological revolution will provide new, innovative ways for this community to gather scientific information, share this information between space vehicles and the ground, and expedite the human exploration of space. Once fully matured, this technology will result in swarms of space vehicles flying as a virtual platform and gathering significantly more and better science data than is possible today. Formation flying will be enabled through the development and deployment of spaceborne differential Global Positioning System (GPS) technology and through innovative spacecraft autonomy techniques, This paper provides an overview of the current status of NASA/DoD/Industry/University partnership to bring formation flying technology to the forefront as quickly as possible, the hurdles that need to be overcome to achieve the formation flying vision, and the team's approach to transfer this technology to space. It will also describe some of the formation flying testbeds, such as Orion, that are being developed to demonstrate and validate these innovative GPS sensing and formation control technologies.
The Pilot Land Data System (PLDS) is a data and information system serving NASA-supported investigators in the land science community. The three nodes of the PLDS, one each at the Ames Research Center (ARC), the Goddard Space Flight Center (GSFC) and the Jet Propulsion Laboratory (JPL), cooperate in providing consistent information describing the various data holding in the hardware and software (accessible via network and modem) that provide information about and access to PLDS-held data, which is available for distribution. A major new activity of the PLDS node at the Ames Research Center involves the interaction of the PLDS with an active NASA ecosystem science project, the Oregon Transect Ecosystems Research involves the management of, access to, and distribution of the large volume of widely-varying aircraft data collected by OTTER. The OTTER project, is managed by researchers at the Ames Research Center and Oregon State University. Its principal objective is to estimate major fluxes of carbon, nitrogen, and water of forest ecosystems using an ecosystem process model driven by remote sensing data. Ten researchers at NASA centers and universities are analyzing data for six sites along a temperature-moisture gradient across the western half of central Oregon (called the Oregon Transect). Sensors mounted on six different aircraft have acquired data over the Oregon Transect in support of the OTTER project.
Science Operations Services Grid is focusing on building a prototype grid-based environment that incorporates existing and new spaceflight services to enable current and future NASA programs with cost savings and new and evolvable methods to conduct science in a distributed environment. The Science Operations Services Grid (SOSG) will provide a distributed environment for widely disparate organizations to conduct their systems and processes in a more efficient and cost effective manner. These organizations include those that: 1) engage in space-based science and operations, 2) develop space-based systems and processes, and 3) conduct scientific research, bringing together disparate scientific disciplines like geology and oceanography to create new information. In addition educational outreach will be significantly enhanced by providing to schools the same tools used by NASA with the ability of the schools to actively participate on many levels in the science generated by NASA from space and on the ground. The services range from voice, video and telemetry processing and display to data mining, high level processing and visualization tools all accessible from a single portal. In this environment, users would not require high end systems or processes at their home locations to use these services. Also, the user would need to know minimal details about the applications in order to utilize the services. In addition, security at all levels is an underlying goal of the project. The Science Operations Services Grid will focus on four tools that are currently used by the ISS Payload community along with nine more that are new to the community. Under the prototype four Grid virtual organizations PO) will be developed to represent four types of users. They are a Payload (experimenters) VO, a Flight Controllers VO, an Engineering and Science Collaborators VO and an Education and Public Outreach VO. The User-based services will be implemented to replicate the operational voice, video, telemetry and commanding systems. Once the User-based services are in place, they will be analyzed to establish feasibility for Grid enabling. If feasible then each User-based service will be Grid enabled. The remaining non-Grid services if not already Web enabled will be so enabled. In the end, four portals will be developed one for each VO. Each portal will contain the appropriate User-based services required for that VO to operate.