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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 73 records · Page 4

STS-40 orbital acceleration research experiment flight results during a typical sleep period

The Orbital Acceleration Research Experiment (OARE), an electrostatic accelerometer package with complete on-orbit calibration capabilities, was flown for the first time aboard the Space Shuttle on STS-40. This is also the first time an accelerometer package with nano-g sensitivity and a calibration facility has flown aboard the Space Shuttle. The instrument is designed to measure and record the Space Shuttle aerodynamic acceleration environment from the free molecule flow regime through the rarified flow transition into the hypersonic continuum regime. Because of its sensitivity, the OARE instrument defects aerodynamic behavior of the Space Shuttle while in low-earth orbit. A 2-hour orbital time period on day seven of the mission, when the crew was asleep and other spacecraft activities were at a minimum, was examined. During the flight, a 'trimmed-mean' filter was used to produce high quality, low frequency data which was successfully stored aboard the Space Shuttle in the OARE data storage system. Initial review of the data indicated that, although the expected precision was achieved, some equipment problems occurred resulting in uncertain accuracy. An acceleration model which includes aerodynamic, gravity-gradient, and rotational effects was constructed and compared with flight data. Examination of the model with the flight data shows the instrument to be sensitive to all major expected low frequency acceleration phenomena; however, some erratic instrument bias behavior persists in two axes. In these axes, the OARE data can be made to match a comprehensive atmospheric-aerodynamic model by making bias adjustments and slight linear corrections for drift. The other axis does not exhibit these difficulties and gives good agreement with the acceleration model.

Blanchard, R. C.↗

The Design of a Distributed Key-Value Store for Petascale Hot Storage in Data Acquisition Systems

Data acquisition systems for high energy physics experiments readout terabytes of data per second from a large number of electronic components. They are thus inherently distributed systems and require fast online data selection, otherwise requirements for permanent storage would be enormous. Still, incoming data need to be buffered while waiting for this selection to happen. Each minute of an experiment can produce hundreds of terabytes that cannot be lost before a selection decision is made. In this context, we present the design of DAQDB (Data Acquisition Database) - a distributed key-value store for high-bandwidth, generic data storage in event-driven systems. DAQDB offers not only high-capacity and low-latency buffer for fast data selection, but also opens a new approach in high-bandwidth data acquisition by decoupling the lifetime of the data analysis processes from the changing event rate due to the duty cycle of the data source. This is achievable by the option to extend its capacity even up to hundreds of petabytes to store hours of an experiment’s data. Our initial performance evaluation shows that DAQDB is a promising alternative to generic database solutions for the high luminosity upgrades of the LHC at CERN.

97 MATHEMATICS AND COMPUTING↗

DSN Beowulf Cluster-Based VLBI Correlator

The NASA Deep Space Network (DSN) requires a broadband VLBI (very long baseline interferometry) correlator to process data routinely taken as part of the VLBI source Catalogue Maintenance and Enhancement task (CAT M&E) and the Time and Earth Motion Precision Observations task (TEMPO). The data provided by these measurements are a crucial ingredient in the formation of precision deep-space navigation models. In addition, a VLBI correlator is needed to provide support for other VLBI related activities for both internal and external customers. The JPL VLBI Correlator (JVC) was designed, developed, and delivered to the DSN as a successor to the legacy Block II Correlator. The JVC is a full-capability VLBI correlator that uses software processes running on multiple computers to cross-correlate two-antenna broadband noise data. Components of this new system (see Figure 1) consist of Linux PCs integrated into a Beowulf Cluster, an existing Mark5 data storage system, a RAID array, an existing software correlator package (SoftC) originally developed for Delta DOR Navigation processing, and various custom- developed software processes and scripts. Parallel processing on the JVC is achieved by assigning slave nodes of the Beowulf cluster to process separate scans in parallel until all scans have been processed. Due to the single stream sequential playback of the Mark5 data, some ramp-up time is required before all nodes can have access to required scan data. Core functions of each processing step are accomplished using optimized C programs. The coordination and execution of these programs across the cluster is accomplished using Pearl scripts, PostgreSQL commands, and a handful of miscellaneous system utilities. Mark5 data modules are loaded on Mark5 Data systems playback units, one per station. Data processing is started when the operator scans the Mark5 systems and runs a script that reads various configuration files and then creates an experiment-dependent status database used to delegate parallel tasks between nodes and storage areas (see Figure 2). This script forks into three processes: extract, translate, and correlate. Each of these processes iterates on available scan data and updates the status database as the work for each scan is completed. The extract process coordinates and monitors the transfer of data from each of the Mark5s to the Beowulf RAID storage systems. The translate process monitors and executes the data conversion processes on available scan files, and writes the translated files to the slave nodes. The correlate process monitors the execution of SoftC correlation processes on the slave nodes for scans that have completed translation. A comparison of the JVC and the legacy Block II correlator outputs reveals they are well within a formal error, and that the data are comparable with respect to their use in flight navigation. The processing speed of the JVC is improved over the Block II correlator by a factor of 4, largely due to the elimination of the reel-to-reel tape drives used in the Block II correlator.

Rogstad, Stephen P.↗

Using GTO-Velo to Facilitate Communication and Sharing of Simulation Results in Support of the Geothermal Technologies Office Code Comparison Study

The Geothermal Technologies Office Code Comparison Study (GTO-CCS) aims to support the DOE Geothermal Technologies Office in organizing and executing a model comparison activity. This project is directed at testing, diagnosing differences, and demonstrating modeling capabilities of a worldwide collection of numerical simulators for evaluating geothermal technologies. Teams of researchers are collaborating in this code comparison effort, and it is important to be able to share results in a forum where technical discussions can easily take place without requiring teams to travel to a common location. Pacific Northwest National Laboratory has developed an open-source, flexible framework called Velo that provides a knowledge management infrastructure and tools to support modeling and simulation for a variety of types of projects in a number of scientific domains. GTO-Velo is a customized version of the Velo Framework that is being used as the collaborative tool in support of the GTO-CCS project. Velo is designed around a novel integration of a collaborative Web-based environment and a scalable enterprise Content Management System (CMS). The underlying framework provides a flexible and unstructured data storage system that allows for easy upload of files that can be in any format. Data files are organized in hierarchical folders and each folder and each file has a corresponding wiki page for metadata. The user interacts with Velo through a web browser based wiki technology, providing the benefit of familiarity and ease of use. High-level folders have been defined in GTO-Velo for the benchmark problem descriptions, descriptions of simulator/code capabilities, a project notebook, and folders for participating teams. Each team has a subfolder with write access limited only to the team members, where they can upload their simulation results. The GTO-CCS participants are charged with defining the benchmark problems for the study, and as each GTO-CCS Benchmark problem is defined, the problem creator can provide a description using a template on the metadata page corresponding to the benchmark problem folder. Project documents, references and videos of the weekly online meetings are shared via GTO-Velo. A results comparison tool allows users to plot their uploaded simulation results on the fly, along with those of other teams, to facilitate weekly discussions of the benchmark problem results being generated by the teams. GTO-Velo is an invaluable tool providing the project coordinators and team members with a framework for collaboration among geographically dispersed organizations.

Collaborative Tools↗

Problems in the long-term storage of data obtained from scientific space experiments

It is shown that long-term data storage systems can be achieved when the system which organizes and conducts the scientific space experiments is equipped with a specialized subsystem: the information filing system. Its main functions are described along with the necessity of stage-by-stage development and compatibility with the data processing systems. The requirements for long-term data storage media are discussed.

Zlotin, G. N.↗

High volume data storage architecture analysis

A High Volume Data Storage Architecture Analysis was conducted. The results, presented in this report, will be applied to problems of high volume data requirements such as those anticipated for the Space Station Control Center. High volume data storage systems at several different sites were analyzed for archive capacity, storage hierarchy and migration philosophy, and retrieval capabilities. Proposed architectures were solicited from the sites selected for in-depth analysis. Model architectures for a hypothetical data archiving system, for a high speed file server, and for high volume data storage are attached.

Malik, James M.↗

CESDIS

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

Source record↗

Earth observation data systems in the 1980's

The requirements for future data systems for earth resource observation data are examined. Estimates are made for both expected data volumes and data delivery requirements. Research and development activities presently underway are described, including (1) high-speed processors such as the massively parallel processor; (2) data storage systems, including optical disk configurations and (3) distributed data systems such as high-speed local networks and the applications data service system.

Bracken, P. A.↗

Adding Data Management Services to Parallel File Systems

The objective of this project, called DAMASC for “Data Management in Scientific Computing”, is to coalesce data management with parallel file system management to present a declarative interface to scientists for managing, querying, and analyzing extremely large data sets efficiently and predictably. Managing extremely large data sets is a key challenge of exascale computing. The overhead, energy, and cost of moving massive volumes of data demand designs where computation is close to storage. In current architectures, compute/analysis clusters access data in a physically separate parallel file system and largely leave it scientist to reduce data movement. Over the past decades the high-end computing community has adopted middleware with multiple layers of abstractions and specialized file formats such as NetCDF-4 and HDF5. These abstractions provide a limited set of high-level data processing functions, but have inherent functionality and performance limitations: middleware that provides access to the highly structured contents of scientific data files stored in the (unstructured) file systems can only optimize to the extent that file system interfaces permit; the highly structured formats of these files often impedes native file system performance optimizations. We are developing Damasc, an enhanced high-performance file system with native rich data management services. Damasc will enable efficient queries and updates over files stored in their native byte-stream format while retaining the inherent performance of file system data storage via declarative queries and updates over views of underlying files. Damasc has four key benefits for the development of data-intensive scientific code: (1) applications can use important data-management services, such as declarative queries, views, and provenance tracking, that are currently available only within database systems; (2) the use of these services becomes easier, as they are provided within a familiar file-based ecosystem; (3) common optimizations, e.g., indexing and caching, are readily supported across several file formats, avoiding effort duplication; and (4) performance improves significantly, as data processing is integrated more tightly with data storage. Our key contributions are: SciHadoop which explores changes to MapReduce assumption by taking advantage of semantics of structured data while preserving MapReduce’s failure and resource management; DataMods which extends common abstractions of parallel file systems so they become programmable such that they can be extended to natively support a variety of data models and can be hooked into emerging distributed runtimes such as Stanford’s Legion; and Miso which combines Hadoop and relational data warehousing to minimize time to insight, taking into account the overhead of ingesting data into data warehousing.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Systems and methods for rapid processing and storage of data

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

97 MATHEMATICS AND COMPUTING↗

Systems and methods for rapid processing and storage of data

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

Stalzer, Mark A.↗

Systems and methods for rapid processing and storage of data

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

Stalzer, Mark A.↗

Small Engine Technology (SET) - Task 14 Axisymmetric Engine Simulation Environment

As part of the NPSS (Numerical Propulsion Simulation System) project, NASA Lewis has a goal of developing an U.S. industry standard for an axisymmetric engine simulation environment. In this program, AlliedSignal Engines (AE) contributed to this goal by evaluating the ENG20 software and developing support tools. ENG20 is a NASA developed axisymmetric engine simulation tool. The project was divided into six subtasks which are summarized below: Evaluate the capabilities of the ENG20 code using an existing test case to see how this procedure can capture the component interactions for a full engine. Link AE's compressor and turbine axisymmetric streamline curvature codes (UD0300M and TAPS) with ENG20, which will provide the necessary boundary conditions for an ENG20 engine simulation. Evaluate GE's Global Data System (GDS), attempt to use GDS to do the linking of codes described in Subtask 2 above. Use a turbofan engine test case to evaluate various aspects of the system, including the linkage of UD0300M and TAPS with ENG20 and the GE data storage system. Also, compare the solution results with cycle deck results, axisymmetric solutions (UD0300M and TAPS), and test data to determine the accuracy of the solution. Evaluate the order of accuracy and the convergence time for the solution. Provide a monthly status report and a final formal report documenting AE's evaluation of ENG20. Provide the developed interfaces that link UD0300M and TAPS with ENG20, to NASA. The interface that links UD0300M with ENG20 will be compatible with the industr,, version of UD0300M.

Miller, Max J.↗

Balloon-borne video cassette recorders for digital data storage

A high speed, high capacity digital data storage system was developed for a new balloon-borne gamma-ray telescope. The system incorporates economical consumer products: the portable video cassette recorder (VCR) and a relatively newer item - the digital audio processor. The in-flight recording system employs eight VCRs and will provide a continuous data storage rate of 1.4 megabits/sec throughout a 40 hour balloon flight. Data storage capacity is 25 gigabytes and power consumption is only 10 watts.

Althouse, W. E.↗

Balloon-borne video cassette recorders for digital data storage

A high-speed, high-capacity digital data storage system has been developed for a new balloon-borne gamma-ray telescope. The system incorporates sophisticated, yet easy to use and economical consumer products: the portable video cassette recorder (VCR) and a relatively newer item - the digital audio processor. The in-flight recording system employs eight VCRs and will provide a continuous data storage rate of 1.4 megabits/sec throughout a 40 hour balloon flight. Data storage capacity is 25 gigabytes and power consumption is only 10 watts.

Althouse, W. E.↗

Data storage, image tube type

Method and apparatus for the storage of digital or analog electrical signals are provided by a memory storage system employing a conventional vidicon tube. At the beginning of an operating cycle, the vidicon is conditioned to accept electrical data input by exposing its photosensitive target to a short, high intensity light flash. A first electron beam scan of the photosensitive surface then sets up a charge pattern on the photosensitive target. A second electron beam scan of the photosensitive surface by an unmodulated electron beam then develops an output signal across an output resistor by using capacitive currents. The conditioning and scanning steps are operated repetitively at high speed using conventional television camera scan, sync, and power supply circuitry to provide a low cost data storage system.

Lipoma, P. C.↗

Data Placement Optimization for ATLAS in a Multi-Tiered Storage System within a Data Center

Scientific experiments and computations, especially in High Energy Physics, are generating and accumulating data at an unprecedented rate. Effectively managing this vast volume of data while ensuring efficient data analysis poses a significant challenge for data centers, which must integrate various storage technologies. This paper proposes addressing this challenge by designing and developing a precise data popularity prediction model utilizing state-of-theart AI/ML techniques. This model is crafted from the analysis of ATLAS data and access patterns. It enables us to migrate infrequently accessed data to more economical storage media, such as tape drives, while storing frequently accessed data on faster yet costlier storage media like HDD or SSD. This strategic approach ensures data is placed optimally into the appropriate storage classes, thereby maximizing storage capacity while minimizing data access latency for end-users. Furthermore, the paper includes a performance evaluation of the prediction model using various key metrics such as F1 score, accuracy, precision and recall. Finally, we present a prototype use case, leveraging real-world file access data to assess the model’s impact on performance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗