SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Overview of the NASA Astrophysics Data Systems (ADS) is presented in the form of view graphs. The following subject areas are covered: The problem; the ADS project; architectural approach; elements of the solution; status of the effort; and the future plans.
NASA is presented with a number of opportunities and challenges in federating its Earth Science Data Systems in the burgeoning world of cloud computing. Cloud hosting of Earth Science data provides a new way of bringing data together, at least from a virtual location sense, and is one of the main motives for NASA to host data there. However, NASA is also faced with a Big Data Variety challenge, brought on by the variety of the EO datasets in its archives. This diversity requires many diverse science archives to service the different science communities. As a result, nearly every major function in the Earth Observing System Data and Information System (EOSDIS) must also be federated across its data centers. This pattern is repeated with many of the outside agencies and organizations that EOSDIS federates with, such as the Committee for Earth Observing Satellites, leading to pioneering work on "deep federation" in a joint project with the European Space Agency to develop a Multi-Mission Algorithm and Analysis Platform.
An ongoing NASA-funded Data Rods (time series) project has demonstrated the removal of a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series) for selected variables of the North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) and other NASA data sets. Data rods are pre-generated or generated on-the-fly (OTF), leveraging the NASA Simple Subset Wizard (SSW), a gateway to NASA data centers. Data rods Web services are accessible through the CUAHSI Hydrologic Information System (HIS) and the Goddard Earth Sciences Data and Information Services Center (GES DISC) but are not easily discoverable by users of other non-NASA data systems. An ongoing GEOSS Water Services project aims to develop a distributed, global registry of water data, map, and modeling services cataloged using the standards and procedures of the Open Geospatial Consortium and the World Meteorological Organization. Preliminary work has shown GEOSS can be leveraged to help provide access to data rods. A new NASA-funded project is extending this early work.
The ascent air data system of the Space Shuttle consists of a simple biconic spike probe on the nose of the external tank. Pressure measurements were calibrated in a wind tunnel to obtain vehicle attitude and speed (relative to the air) and dynamic pressure. The wind tunnel test data analysis and the calibration are discussed in terms of test problems and calibration parameter formulation. The flight pressures are traced from telemetry data to final air data products. Analysis of the flight results showed that static pressure could not be accurately determined at the higher Mach numbers (above approx. 2.0). By replacing static pressure with data from a postflight estimated trajectory the ascent air data system performance met the user requirements. Lessons learned are enumerated, the most important being the need for a thorough systems integration effort.
The Mission Design and Navigation (MDNAV) Section at the Jet Propulsion Laboratory (JPL) supports many deep space and earth orbiting missions from formulation to end of mission operations. The requirements of these missions are met with a multimission approach to MDNAV ground data system (GDS) infrastructure capable of being shared and allocated in a seamless and consistent manner across missions. The MDNAV computing infrastructure consists of compute clusters, network attached storage, mission support area facilities, and desktop hardware. The multimission architecture allows these assets, and even personnel, to be leveraged effectively across the project lifecycle and across multiple missions simultaneously. It provides a more robust and capable infrastructure to each mission than might be possible if each constructed its own. It also enables a consistent interface and environment within which teams can conduct all mission analysis and navigation functions including: trajectory design; ephemeris generation; orbit determination; maneuver design; and entry, descent, and landing analysis. The savings of these efficiencies more than offset the costs of increased complexity and other challenges that had to be addressed: configuration management, scheduling conflicts, and competition for resources. This paper examines the benefits of the multimission MDNAV ground data system infrastructure, focusing on the hardware and software architecture. The result is an efficient, robust, scalable MDNAV ground data system capable of supporting more than a dozen active missions at once.
In order to meet the increasing demand for Earth Science data, NASA has significantly improved the Earth Science Data Systems over the last two decades. This improvement is reviewed in this slide presentation. Many Earth Science disciplines have been able to access the data that is held in the Earth Observing System (EOS) Data and Information System (EOSDIS) at the Distributed Active Archive Centers (DAACs) that forms the core of the data system.
A data system, which includes parts in the orbiting Gamma-Ray Observatory and in its associated ground system, has been designed to rapidly deliver autonomous, packeted data to the science users. Data autonomy means all of the data, including auxiliary data, necessary for processing is included in the data packet that leaves the spacecraft. The data packets leaving the spacecraft remain unopened until they reach the user. Handling the data on a packet rather than a byte level allows simpler and generic software. The data goes through the system more quickly. This in turn reduces cost.
As baselined, the Cassini Ground Data System (GDS) will be composed of Project specific and multimission elements. The former will be developed by the Cassini Project and the latter by two JPL institutional organizations, the Telecommunications and Data Acquisition Office (TDA) and the Multimission Operations Systems Office (MOSO). The GDS will be developed in three principal phases: Spacecraft Test, Launch-cruise, and Science Tour, with a significant part of the development deferred until the post-launch period. New capabilities are being introduced that are key to the achievement of more cost effective operations. Successful development of the system will require careful planning and will involve participation of diverse disciplines. This paper introduces the Cassini Project from the Ground Data System perspective and discusses development approaches expected to produce systems which meet functional and performance requirements and which will be delivered on schedule and within budget.
A data management analysis methodology is being proposed. The objective of the methodology is to assist mission managers by identifying a series of ordered activities to be systematically followed in order to arrive at an effective ground system design. Existing system engineering tools and concepts have been assembled into a structured framework to facilitate the work of a mission planner. It is intended that this methodology can be gainfully applied (with probable modifications and/or changes) to the EOS payloads and their associated data systems.
Sensitivity in sampled-data handling systems
The functions that a space station could serve are outlined and details of the data systems requirements are discussed. The data system design will be guided by an overall space systems plan, and will feature distributed, layered architecture, user friendliness, hierarchical control, technology transparency, standard interfaces, and automated engineering tools. The station would begin with a limited core capability and evolve to serve functions defined thereafter. The automation of the engineering tools will be necessary to permit an optimized, minimized crew to control all functions of the space station, while at the same time freeing the crew from being actively involved in maintaining the nominal life support functions of the equipment. One major criterion is that the software must be error free, while another is adaptibility to changing space station configurations and demands.
NASA has been collecting Earth observation data from spaceborne instruments since 1960. Today, there are tens of satellites orbiting the Earth and collecting frequent global observations for the benefit of mankind. Collaboration between NASA and organizations in the US and other countries has been extremely important in maintaining the Earth observation capabilities as well as collecting, organizing and managing the data. These collaborations have occurred in the form of: 1. NASA’s developing and launching spacecraft and instruments for operation by other agencies; 2. Instruments from collaborating organizations being flown on NASA satellites; and 3. Instruments from NASA being flown on satellites from collaborating organizations. In addition, there are collaborations such as joint science teams, data exchanges, and participation in international organizations to promote interoperability of various data systems. The purpose of this paper is to describe some of the Earth science data-related collaborative efforts in which NASA participates, and highlight a few results relevant to Earth system science research obtained through such collaborations.
The SEADS pressure data obtained from the Shuttle flight 61-C are analyzed in conjunction with the preflight database. Based on wind tunnel data, the sensitivity of the Shuttle Orbiter stagnation region pressure distribution to angle of attack and Mach number is demonstrated. Comparisons are made between flight and wind tunnel SEADS orifice pressure distributions at several points throughout the re-entry. It is concluded that modified Newtonian theory provides a good tool for the design of a flush air data system, furnishing data for determining orifice locations and transducer sizing. Ground-based wind tunnel facilities are capable of providing the correction factors necessary for the derivation of accurate air data parameters from pressure data.
The Goddard Space Flight Center's new thermal vacuum data acquisition system is a networked client-sever application that enables lab operations crews to monitor all tests from a central location. The GSFC thermal vacuum lab consists of eleven chambers in Building 7 and one chamber in Building 10. The new data system was implemented for several reasons. These included the need for centralized data collection, more flexible and easier to use operator interface, greater data accessibility, a reduction in testing time and cost, and increased payload and personnel safety. Additionally, a new data system was needed for year-2000 compliance. This paper discusses the incorporation of the Thermal Vacuum Data System (TVDS) within the thermal vacuum lab at GSFC, its features and capabilities and lessons learned in its implementation. Additional topics include off-center (Internet) capability for remote monitoring and the role of TVDS in the efforts to automate thermal vacuum chamber operations.
The Goddard Space Flight Center's new thermal vacuum data acquisition system is a networked client-sever application that enables lab operations crews to monitor all tests from a central location. The GSFC thermal vacuum lab consists of eleven chambers in Building 7 and one chamber in Building 10. The new data system was implemented for several reasons. These included the need for centralized data collection, more flexible and easier to use operator interface, greater data accessibility, a reduction in testing time and cost, and increased payload and personnel safety. Additionally, a new data system was needed for year-2000 compliance. This paper discusses the incorporation of the Thermal Vacuum Data System (TVDS) within the thermal vacuum lab at GSFC, its features and capabilities and lessons learned in its implementation. Additional topics include off-center (Internet) capability for remote monitoring and the role of TVDS in the efforts to automate thermal vacuum chamber operations.
X-transform for open/closed loop sampled data system with zero-order hold device
The TOPEX Project is a proposed oceanographic mission to measure the topography of the sea surface for a period of three years. This mission is sponsored by the National Aeronautics and Space Administration and managed by the Jet Propulsion Laboratory. Measurements of topography are used to study ocean currents, tides, bathymetry and the oceanic geoid. Several of the primary goals of this mission are to process and verify the altimetric data, and distribute them within days to the science investigators. This paper describes the TOPEX end-to-end ground data system. In addition to controlling the TOPEX satellite, the ground data system has been designed to minimize the time from data acquisition to science processing and data distribution. A centralized design supports the favorable response time of the system and also allows for operational efficiencies. Networking of real time and non-real time elements of the data system provides for more effective data processing.
An optimization method for flush-orifice air data system design has been developed using the Genetic Algorithm approach. The optimization of the orifice array minimizes the effect of normally distributed random noise in the pressure readings on the calculation of air data parameters, namely, angle of attack, sideslip angle and freestream dynamic pressure. The optimization method is applied to the design of Pressure Distribution/Air Data System experiment (PD/ADS) proposed for inclusion in the Aeroassist Flight Experiment (AFE). Results obtained by the Genetic Algorithm method are compared to the results obtained by conventional gradient search method.