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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Federated Giovanni: A Distributed Web Service for Analysis and Visualization of Remote Sensing Data

The Geospatial Interactive Online Visualization and Analysis Interface (Giovanni) is a popular tool for users of the Goddard Earth Sciences Data and Information Services Center (GES DISC) and has been in use for over a decade. It provides a wide variety of algorithms and visualizations to explore large remote sensing datasets without having to download the data and without having to write readers and visualizers for it. Giovanni is now being extended to enable its capabilities at other data centers within the Earth Observing System Data and Information System (EOSDIS). This Federated Giovanni will allow four other data centers to add and maintain their data within Giovanni on behalf of their user community. Those data centers are the Physical Oceanography Distributed Active Archive Center (PO.DAAC), MODIS Adaptive Processing System (MODAPS), Ocean Biology Processing Group (OBPG), and Land Processes Distributed Active Archive Center (LP DAAC). Three tiers are supported: Tier 1 (GES DISC-hosted) gives the remote data center a data management interface to add and maintain data, which are provided through the Giovanni instance at the GES DISC. Tier 2 packages Giovanni up as a virtual machine for distribution to and deployment by the other data centers. Data variables are shared among data centers by sharing documents from the Solr database that underpins Giovanni's data management capabilities. However, each data center maintains their own instance of Giovanni, exposing the variables of most interest to their user community. Tier 3 is a Shared Source model, in which the data centers cooperate to extend the infrastructure by contributing source code.

Giovanni↗
NASA NTRS1977

Instrumentation complex for Langley Research Center's National Transonic Facility

The instrumentation discussed in the present paper was developed to ensure reliable operation for a 2.5-meter cryogenic high-Reynolds-number fan-driven transonic wind tunnel. It will incorporate four CPU's and associated analog and digital input/output equipment, necessary for acquiring research data, controlling the tunnel parameters, and monitoring the process conditions. Connected in a multipoint distributed network, the CPU's will support data base management and processing; research measurement data acquisition and display; process monitoring; and communication control. The design will allow essential processes to continue, in the case of major hardware failures, by switching input/output equipment to alternate CPU's and by eliminating nonessential functions. It will also permit software modularization by CPU activity and thereby reduce complexity and development time.

Russell, C. H.↗
NASA NTRS1993

Space Station Freedom ground data system: Design and operations

Over the previous year the Space Station Freedom (SSF) Program (SSFP) ground data distribution system has become independent of a number of data systems that were to have been provided by other National Aeronautics and Space Administration (NASA) programs. Consequently, the SSFP has outlined the basic architecture of a new data system dedicated to supporting SSF requirements. This has been accomplished through a complete redesign of the ground network and a reallocation of selected functions. There are a number of aspects of the new ground data distribution system that are unique among NASA programs. These considerations make SSF ground data distribution one of the most extensive and complex data management challenges encountered in the arena of Space Operations. A description of this system comprises the main focus of the paper.

Dunning, Richard A., Jr.↗
NASA NTRS1993

Data management system performance modeling

This paper discusses analytical techniques that have been used to gain a better understanding of the Space Station Freedom's (SSF's) Data Management System (DMS). The DMS is a complex, distributed, real-time computer system that has been redesigned numerous times. The implications of these redesigns have not been fully analyzed. This paper discusses the advantages and disadvantages for static analytical techniques such as Rate Monotonic Analysis (RMA) and also provides a rationale for dynamic modeling. Factors such as system architecture, processor utilization, bus architecture, queuing, etc. are well suited for analysis with a dynamic model. The significance of performance measures for a real-time system are discussed.

Kiser, Larry M.↗
NASA NTRS2004

New Earth Science Data and Access Methods

NASA's Earth Science Enterprise, working with its domestic and international partners, provides scientific data and analysis to improve life here on Earth. NASA provides science data products that cover a wide range of physical, geophysical, biochemical and other parameters, as well as services for interdisciplinary Earth science studies. Management and distribution of these products is administered through the Earth Observing System Data and Information System (EOSDIS) Distributed Active Archive Centers (DAACs), which all hold data within a different Earth science discipline. This paper will highlight selected EOS datasets and will focus on how these observations contribute to the improvement of essential services such as weather forecasting, climate prediction, air quality, and agricultural efficiency. Emphasis will be placed on new data products derived from instruments on board Terra, Aqua and ICESat as well as new regional data products and field campaigns. A variety of data tools and services are available to the user community. This paper will introduce primary and specialized DAAC-specific methods for finding, ordering and using these data products. Special sections will focus on orienting users unfamiliar with DAAC resources, HDF-EOS formatted data and the use of desktop research and application tools.

Moses, John F.↗
NASA NTRS2019

New Era, New Opportunity, Is GES DISC Ready for Big Data Challenge?

The new era of Big Data has opened doors for many new opportunities, as well as new challenges, for both Earth science research/application and data communities. As one of the twelve NASA data centers - Goddard Earth Sciences Data and Information Services Center (GES DISC), one of our great challenges has been how to help research/application community efficiently (quickly and properly) accessing, visualizing and analyzing the massive and diverse data in natural hazard research, management, or even prediction. GES DISC has archived over 2000 TB data on premises and distributed over 23,000 TB of data since 2010. Our data has been widely used in every phase of natural hazard management and research, i.e. long term risk assessment and reduction, forecasting and predicting, monitoring and detection, early warning, damage assessment and response. The big data challenge is not just about data storage, but also about data discoverability and accessibility, and even more, about data migration/mirroring in the cloud. This paper is going to demonstrate GES DISC’s efforts and approaches of evolving our overall Web services and powerful Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) tool into further improving data discoverability and accessibility. Prototype works will also be presented.

Li, A.↗
NASA NTRS1986

Notes on a storage manager for the Clouds kernel

The Clouds project is research directed towards producing a reliable distributed computing system. The initial goal is to produce a kernel which provides a reliable environment with which a distributed operating system can be built. The Clouds kernal consists of a set of replicated subkernels, each of which runs on a machine in the Clouds system. Each subkernel is responsible for the management of resources on its machine; the subkernal components communicate to provide the cooperation necessary to meld the various machines into one kernel. The implementation of a kernel-level storage manager that supports reliability is documented. The storage manager is a part of each subkernel and maintains the secondary storage residing at each machine in the distributed system. In addition to providing the usual data transfer services, the storage manager ensures that data being stored survives machine and system crashes, and that the secondary storage of a failed machine is recovered (made consistent) automatically when the machine is restarted. Since the storage manager is part of the Clouds kernel, efficiency of operation is also a concern.

Pitts, David V.↗
NASA NTRS1989

Exploiting replication in distributed systems

Techniques are examined for replicating data and execution in directly distributed systems: systems in which multiple processes interact directly with one another while continuously respecting constraints on their joint behavior. Directly distributed systems are often required to solve difficult problems, ranging from management of replicated data to dynamic reconfiguration in response to failures. It is shown that these problems reduce to more primitive, order-based consistency problems, which can be solved using primitives such as the reliable broadcast protocols. Moreover, given a system that implements reliable broadcast primitives, a flexible set of high-level tools can be provided for building a wide variety of directly distributed application programs.

Birman, Kenneth P.↗
NASA NTRS1993

AVIRIS and TIMS data processing and distribution at the land processes distributed active archive center

The U.S. Government has initiated the Global Change Research program, a systematic study of the Earth as a complete system. NASA's contribution of the Global Change Research Program is the Earth Observing System (EOS), a series of orbital sensor platforms and an associated data processing and distribution system. The EOS Data and Information System (EOSDIS) is the archiving, production, and distribution system for data collected by the EOS space segment and uses a multilayer architecture for processing, archiving, and distributing EOS data. The first layer consists of the spacecraft ground stations and processing facilities that receive the raw data from the orbiting platforms and then separate the data by individual sensors. The second layer consists of Distributed Active Archive Centers (DAAC) that process, distribute, and archive the sensor data. The third layer consists of a user science processing network. The EOSDIS is being developed in a phased implementation. The initial phase, Version 0, is a prototype of the operational system. Version 0 activities are based upon existing systems and are designed to provide an EOSDIS-like capability for information management and distribution. An important science support task is the creation of simulated data sets for EOS instruments from precursor aircraft or satellite data. The Land Processes DAAC, at the EROS Data Center (EDC), is responsible for archiving and processing EOS precursor data from airborne instruments such as the Thermal Infrared Multispectral Scanner (TIMS), the Thematic Mapper Simulator (TMS), and Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). AVIRIS, TIMS, and TMS are flown by the NASA-Ames Research Center ARC) on an ER-2. The ER-2 flies at 65000 feet and can carry up to three sensors simultaneously. Most jointly collected data sets are somewhat boresighted and roughly registered. The instrument data are being used to construct data sets that simulate the spectral and spatial characteristics of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument scheduled to be flown on the first EOS-AM spacecraft. The ASTER is designed to acquire 14 channels of land science data in the visible and near-IR (VNIR), shortwave-IR (SWIR), and thermal-IR (TIR) regions from 0.52 micron to 11.65 micron at high spatial resolutions of 15 m to 90 m. Stereo data will also be acquired in the VNIR region in a single band. The AVIRIS and TMS cover the ASTER VNIR and SWIR bands, and the TIMS covers the TIR bands. Simulated ASTER data sets have been generated over Death Valley, California, Cuprite, Nevada, and the Drum Mountains, Utah using a combination of AVIRIS, TIMS, amd TMS data, and existing digital elevation models (DEM) for the topographic information.

Mah, G. R.↗
NASA NTRS2004

New Generation Power System for Space Applications

The Deep Space Avionics (DSA) Project is developing a new generation of power system building blocks. Using application specific integrated circuits (ASICs) and power switching modules a scalable power system can be constructed for use on multiple deep space missions including future missions to Mars, comets, Jupiter and its moons. The key developments of the DSA power system effort are five power ASICs and a mod ule for power switching. These components enable a modular and scalab le design approach, which can result in a wide variety of power syste m architectures to meet diverse mission requirements and environments . Each component is radiation hardened to one megarad) total dose. The power switching module can be used for power distribution to regular spacecraft loads, to propulsion valves and actuation of pyrotechnic devices. The number of switching elements per load, pyrotechnic firin gs and valve drivers can be scaled depending on mission needs. Teleme try data is available from the switch module via an I2C data bus. The DSA power system components enable power management and distribution for a variety of power buses and power system architectures employing different types of energy storage and power sources. This paper will describe each power ASIC#s key performance characteristics as well a s recent prototype test results. The power switching module test results will be discussed and will demonstrate its versatility as a multip urpose switch. Finally, the combination of these components will illu strate some of the possible power system architectures achievable fro m small single string systems to large fully redundant systems.

power switching↗
NASA NTRSDate not supplied

Stochastic Verification by Analysis for Autonomous Systems Management Architecture (ASMA)

The Gateway Vehicle Systems Manager (VSM) is the top-level of a distributed, hierarchical software control system. VSM is data-driven and will make decisions related to mission, fault, resource management and vehicle control. These attributes combined with a high degree of autonomy make it susceptible to emergent behavior. In order to achieve the high level of confidence needed in this critical system, the VSM team has developed a multifaceted verification strategy employing traditional verification techniques, simulation, model checking, and runtime verification. Individual algorithms are verified using conventional testing and model checking using assume-guarantee contracts. A discrete event-based simulation approach is being developed to verify timelines. This presentation describes an enhancement to the verification approach using analysis to enhance system robustness by detecting and resolving the potential for emergent behavior. The verification by analysis employs a Software in the Loop (SITL) environment with real flight software executing on emulated processors, simulations of vehicle subsystems, flight dynamics, and human inputs. Since the possible input space and configuration data set are too large for exhaustive testing, a Monte Carlo approach is used to cover feasible scenarios, augmented with corner cases and known higher-risk scenarios. A key problem in using Monte Carlo-based system verification is evaluating test results to ensure that system behavior is correct. The presentation describes the approach the VSM team uses to monitor behavior for compliance with predetermined boundaries and to identify anomalous behavior for further analysis. This presentation describes the multi-level systems approach to verification, and the simulation-based layer that covers the feasible state space: 1. Overview of the Gateway VSM 2. Special challenges due to heterogeneous, hierarchical architecture 3. Modeling and simulation environment using flight software and system simulations 4. Developing input sets to ensure state-space coverage 5. Developing model and data configuration sets to ensure model coverage 6. Interpreting results without predetermined outcomes 7. Lessons learned and future work

Verification and Validation↗
NASA NTRS2016

Integrating Satellite and Surface Sensor Networks for Irrigation Management Applications in California

Satellite mapping of evapotranspiration (ET) from irrigated agricultural lands can provide agricultural producers and water managers with information that can be used to optimize agricultural water use, especially in regions with limited water supplies. The timely delivery of information on agricultural crop water requirements has the potential to make irrigation scheduling more practical, convenient, and accurate. We present a system for irrigation scheduling and management support in California and describe lessons learned from the development and implementation of the system. The Satellite Irrigation Management Support (SIMS) framework integrates satellite data with information from agricultural weather networks to map crop canopy development, basal crop coefficients (Kcb), and basal crop evapotranspiration (ETcb) at the scale of individual fields. Information is distributed to agricultural producers and water managers via a web-based irrigation management decision support system and web data services. SIMS also provides an application programming interface (API) that facilitates integration with other irrigation decision support tools, estimation of total crop evapotranspiration (ETc) and calculation of on-farm water use efficiency metrics. Accuracy assessments conducted in commercial fields for more than a dozen crop types to date have shown that SIMS seasonal ETcb estimates are within 10 mean absolute error (MAE) for well-watered crops and within 15 across all crop types studied, and closely track daily ETc and running totals of ETc measured in each field. Use of a soil water balance model to correct for soil evaporation and crop water stress reduces this error to less than 8 MAE across all crop types studied to date relative to field measurements of ETc. Results from irrigation trials conducted by the project for four vegetable crops have also demonstrated the potential for use of ET-based irrigation management strategies to reduce total applied water by 20-40 relative to grower standard practices while maintaining crop yields and quality.

Nemani, Ramakrishna R.↗
NASA NTRS2001

Flight Demonstration of X-33 Vehicle Health Management System Components on the F/A-18 Systems Research Aircraft

The X-33 reusable launch vehicle demonstrator has identified the need to implement a vehicle health monitoring system that can acquire data that monitors system health and performance. Sanders, a Lockheed Martin Company, has designed and developed a COTS-based open architecture system that implements a number of technologies that have not been previously used in a flight environment. NASA Dryden Flight Research Center and Sanders teamed to demonstrate that the distributed remote health nodes, fiber optic distributed strain sensor, and fiber distributed data interface communications components of the X-33 vehicle health management (VHM) system could be successfully integrated and flown on a NASA F-18 aircraft. This paper briefly describes components of X-33 VHM architecture flown at Dryden and summarizes the integration and flight demonstration of these X-33 VHM components. Finally, it presents early results from the integration and flight efforts.

Schweikhard, Keith A.↗
NASA NTRS2004

Telescience Resource Kit Software Capabilities and Future Enhancements

The Telescience Resource Kit (TReK) is a suite of PC-based software applications that can be used to monitor and control a payload on board the International Space Station (ISS). This software provides a way for payload users to operate their payloads from their home sites. It can be used by an individual or a team of people. TReK provides both local ground support system services and an interface to utilize remote services provided by the Payload Operations Integration Center (POIC). by the POIC and to perform local data functions such as processing the data, storing it in local files, and forwarding it to other computer systems. TReK can also be used to build, send, and track payload commands. In addition to these features, work is in progress to add a new command management capability. This capability will provide a way to manage a multi- platform command environment that can include geographically distributed computers. This is intended to help those teams that need to manage a shared on-board resource such as a facility class payload. The environment can be configured such that one individual can manage all the command activities associated with that payload. This paper will provide a summary of existing TReK capabilities and a description of the new command management capability. For example, 7'ReK can be used to receive payload data distributed

Schneider, Michelle↗
NASA NTRS1998

Flight Demonstration of X-33 Vehicle Health Management System Components on the F/A-18 Systems Research Aircraft

The X-33 reusable launch vehicle demonstrator has identified the need to implement a vehicle health monitoring system that can acquire data that monitors system health and performance. Sanders, a Lockheed Martin Company, has designed and developed a commercial off-the-shelf (COTS)-based open architecture system that implements a number of technologies that have not been previously used in a flight environment. NASA Dryden Flight Research Center and Sanders teamed to demonstrate that the distributed remote health nodes, fiber optic distributed strain sensor, and fiber distributed data interface communications components of the X-33 vehicle health management (VHM) system could be successfully integrated and flown on a NASA F-18 aircraft. This paper briefly describes components of X-33 VHM architecture flown at Dryden and summarizes the integration and flight demonstration of these X-33 VHM components. Finally, it presents early results from the integration and flight efforts.

Schweikhard, Keith A.↗
NASA NTRS1977

Instrumentation and data acquisition systems

A comprehensive and integrated measurement system was identified and a design and development effort initiated to meet the criteria imposed by the National Transonic Facility operating environment. Specific measurement areas receiving concentrated attention include: data acquisition, force measurement, pressure instrumentation, flow visualization techniques, model attitude and model deformation measurement, and temperature measurement. The NTF instrument complex will be centered around four 32-bit, 1-microsecond-cycle-time central processing units connected in a multipoint-distributed network configuration. The principal activities to be supported by these computers are: (1) data base management and processing; (2) research measurement data acquisition and display; (3) tunnel and model control; and (4) process monitoring and communication control. The distributed network approach was chosen to modularize the functional software into definable and implementable parts by the various groups involved in the design and to permit use of similar hardware configurations to improve reliability and maintainability.

Guarino, J. F.↗
DOE OSTI2024

Integrating the PanDA Workload Management System with the Vera C. Rubin Observatory

The Vera C. Rubin Observatory will produce an unprecedented astronomical data set for studies of the deep and dynamic universe. Its Legacy Survey of Space and Time (LSST) will image the entire southern sky every three to four days and produce tens of petabytes of raw image data and associated calibration data over the course of the experiment’s run. More than 20 terabytes of data must be stored every night, and annual campaigns to reprocess the entire dataset since the beginning of the survey will be conducted over ten years. The Production and Distributed Analysis (PanDA) system was evaluated by the Rubin Observatory Data Management team and selected to serve the Observatory’s needs due to its demonstrated scalability and flexibility over the years, for its Directed Acyclic Graph (DAG) support, its support for multi-site processing, and its highly scalable complex workflows via the intelligent Data Delivery Service (iDDS). PanDA is also being evaluated for prompt processing where data must be processed within 60 seconds after image capture. This paper will briefly describe the Rubin Data Management system and its Data Facilities (DFs). Finally, it will describe in depth the work performed in order to integrate the PanDA system with the Rubin Observatory to be able to run the Rubin Science Pipelines using PanDA.

79 ASTRONOMY AND ASTROPHYSICS↗