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At least 1,171 records · Page 65

A Comparison of Phasor Communication Protocols

In this paper, we compare three approaches used for continuous transfer of real-time synchrophasor data: IEEE C37.118.2-2011, IEC TR 61850-90-5 and a new protocol being developed under the Department of Energy (DOE) project DOE-OE-859 called the Streaming Telemetry Transport Protocol (STTP). STTP is currently being advanced as a potential third standard protocol via the IEEE Power Engineering Society STTP P10 Work Group (P2664). Each of these three synchrophasor protocols is described in detail in this paper along with the basis for their operating characteristics using Internet Protocol (IP) transport. The dominant protocol for the exchange of synchrophasor data is IEEE C37.118, both in the U.S. and internationally. The most recent IEEE C37.118 standard is broken into two parts where IEEE C37.118.1-2011 (Part 1) defines the normative synchrophasor measurement requirements and IEEE C37.118.2-2011 (Part 2) defines the protocol’s data transmission format. Both the IEC TR 61850-90-5 and the emergent STTP specifications only address synchrophasor data transmission; therefore, this paper focuses on comparing the data transmission protocol elements of these standards. The primary dimensions of comparison of these three protocols explored in this paper are: structure, efficiency, susceptibility to data loss, scalability, security, and other operability functionality. Additionally, though not specifically relevant to synchrophasor data telemetry, the three protocols are evaluated with respect to flexibility for transporting non-synchrophasor precise-time data streams.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Antarctic Meteorite Location and Mapping Project (AMLAMP): Antarctic meteorite location map series explanatory text and user's guide to AMLAMP data

This technical report is an update to LPI Technical Report 89-02, which contained data and information that was current to May 1987. Since that time approximately 4000 new meteorites have been collected, mapped, and characterized, mainly from the numerous ice fields in the Allan Hills-David Glacier region, from the Pecora Escarpment and Moulton Escarpment in the Thiel Mountains-Patuxent region, the Wisconsin Range region, and from the Beardmore region. Meteorite location maps for ice fields from these regions have been produced and are available. This report includes explanatory texts for the maps of new areas and provides information on updates of maps of the areas covered in LPI Technical Report 89-02. Sketch maps and description of locales that have been searched and have yielded single or few meteorites are also included. The meteorite listings for all the ice fields have been updated to include any classification changes and new meteorites recovered from ice fields in the Allan Hills-David Glacier region since 1987. The text has been reorganized and minor errors in the original report have been corrected. Computing capabilities have improved immensely since the early days of this project. Current software and hardware allow easy access to data over computer networks. With various commercial software packages, the data can be used many different ways, including database creation, statistics, and mapping. The databases, explanatory texts, and the plotter files used to produce the meteorite location maps are available through a computer network. Information on how to access AMLAMP data, its formats, and ways it can be used are given in the User's Guide to AMLAMP Data section. Meteorite location maps and thematic maps may be ordered from the Lunar and Planetary Institute. Ordering information is given in Appendix A.

Schutt, J.↗

Bridging the Gap between NASA Hydrological Data and the Geospatial Community

There is a vast and ever increasing amount of data on the Earth interconnected energy and hydrological systems, available from NASA remote sensing and modeling systems, and yet, one challenge persists: increasing the usefulness of these data for, and thus their use by, the geospatial communities. The Hydrology Data and Information Services Center (HDISC), part of the Goddard Earth Sciences DISC, has continually worked to better understand the hydrological data needs of the geospatial end users, to thus better able to bridge the gap between NASA data and the geospatial communities. This paper will cover some of the hydrological data sets available from HDISC, and the various tools and services developed for data searching, data subletting ; format conversion. online visualization and analysis; interoperable access; etc.; to facilitate the integration of NASA hydrological data by end users. The NASA Goddard data analysis and visualization system, Giovanni, is described. Two case examples of user-customized data services are given, involving the EPA BASINS (Better Assessment Science Integrating point & Non-point Sources) project and the CUAHSI Hydrologic Information System, with the common requirement of on-the-fly retrieval of long duration time series for a geographical point

Rui, Hualan↗

Striped Data Analysis Framework

Traditionally, High Energy data analysis is based on the model where data are stored in files and analyzed by running multiple analysis processes, each reading one or more of the data files. This process involves repeated data reduction step, which produces smaller files, which is time consuming and leads to data duplication. We propose an alternative approach to data storage and analysis, based on the Big Data technologies. The idea is to store each element of data once and only once in a distributed scalable database and analyze data by reading only "interesting" pieces of data from the database. To make this approach possible, we developed columnar Striped Data Representation Format as the basis of the framework. Traditional columnar approach allows for efficient analysis of complex data structures. While keeping all the benefits of columnar data representation, striped mechanism goes further by enabling efficient parallelization of computations and flexible dist ribution of data analysis. The framework includes scalable and elastic data storage, compute and user analysis backend components. The framework uses off-the shelf web services and data caching technologies as the compute/data co-location mechanism. Flexible architecture allows the framework run in the cloud using container technologies. The framework offers Python/Jupyter as the user analysis backend platform, but can also run in command line or batch mode. In the article, we will present the results of the FNAL-LDRD-2016-032 FNAL LDRD project, the design, implementation, features and performance characteristics of the Striped Data Analysis Framework.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Graphic Three-Axes Presentation of Residual Gas Analyzer Data

Residual gas analyzers (RGA) are commonly used to measure the composition of residual gases in thermal-vacuum test chambers. Measurements from RGA's are often used to identify and quantify outgassing contaminants from a test article during thermal-vacuum testing. RGA data is typically displayed as snapshots in time, showing instantaneous concentrations of ions from ionized residual gas molecules at different atomic masses. This ion concentration information can be interpreted to be representative of the composition of the residual gas in the chamber at the instant of analysis. Typically, test personnel are most interested in tracking the time history of changes in the composition of chamber residual gas to determine the relative cleanliness and the clean-up rate of the test article under vacuum. However, displays of instantaneous RGA data cannot provide test personnel with the preferred time history information. In order to gain an understanding of gas composition trends, a series of plots of individual data snapshots must be analyzed. This analysis is cumbersome and still does not provide a very satisfactory view of residual gas composition trends. A method was devised by the authors to present RCA data in a three-axis format, plotting Atomic Mass Unit (AMU), the Ionization Signal Response (ISR) as amps/torr as a function of AMU, and Time, to provide a clear graphic visualization of trends of changes in ISR with respect to time and AMU (representative of residual gas composition). This graphic visualization method provides a valuable analytical tool to interpret test article outgassing rates during thermal vacuum tests. Raw RGA data was extracted from a series of delimited ASCII files and then converted to a data array in a spreadsheet. Consequently, using the 3-D plotting functionality provided by the spreadsheet program, 3-D plots were produced. After devising the data format conversion process, the authors began developing a program to provide real-time 3-D plotting of RGA data. The intent of this program is to automate the RGA data acquisition process and to generate up-to-the-minute time history 3-D displays of stored RGA data (development of this program was not complete at the time of this writing). This paper provides a brief description of the data format conversion process and presents results from a recent test to illustrate the usefulness of this 3-D RGA data plotting technique.

Johnson, Kenneth R.↗

History and Status of ALSEP and the Apollo Lunar Data Project

A suite of automated scientific instruments (the Apollo Lunar Surface Experiment Package, or ALSEP) was installed at each of the landing sites of Apollo 12, 14, 15, 16, and 17 from 1969 to 1972. They operated from deployment until decommissioning on 30 September 1977. These data were continuously transmitted to Earth and saved on the Range Tapes, which were recorded at the Manned Space Flight Network stations. These data were also broken out by experiment and sent to the experiment Principal Investigators on what were called the P.I. Tapes. Starting in April 1973 the Range Tape data were stored in digital format on 7-track magnetic tapes, the ARCSAV Tapes. In February 1976, the handling of the Range Tapes was transferred to UT Galveston. They produced 9-track tapes referred to as the Work Tapes. Following the Apollo program the Range and ARCSAV tapes, which were never archived, were lost. The Work Tapes were archived at the National Space Science Data Center (NSSDC). Some investigators archived their individual experiment data with NSSDC as well, but much of the data had minimal documentation, were not in digital form, or were stored in difficult to translate formats. Data from many experiments were never delivered to the NSSDC. The Lunar Data Project was started to address the problem of both missing and not readily usable data. Our effort has resulted in recovery of some of the ARCSAV tapes, recovery and digitization of a large volume of Apollo scientific and technical documentation, and restoration of many ALSEP and other Apollo data collections. Restoration involves deciphering formats, assembling necessary ancillary data (metadata), and packaging data in digital format to be archived with the Planetary Data System (PDS). Recovery of the data from the ARCSAV tapes involved having the tapes read on special equipment and extracting the individual experiment data out of the integrated data stream. We will report on the history and status of the various recovery efforts.

Work Tapes↗

Airfoil tip vortex formation noise

Spectral data are presented for the noise produced due to the turbulent three-dimensional vortex flow existing near the rounded tip of lifting airfoils. The results are obtained by the comparison of sets of two- and three-dimensional test data for different airfoil model sizes, angles of attack, and tunnel flow velocities. Microphone cross-correlation and cross-spectral methods were used to determine the radiated noise. Corrections were made for tunnel shear layer and source directivity effects. Interpretation of the results are aided by a three-dimensional flow analysis developed for this study which determines open tunnel and finite aspect ratio corrections heretofore neglected in tip vortex studies. Hot wire measurements were made in the tip vortex formation region for the specification of governing flow parameters. The spectral data is normalized in a format considered most useful for subsequent quantitative prediction of this noise mechanism for practical systems such as helicopter rotors. Comparison is made to the analysis of George and Chou. A recommended prediction method is given.

Brooks, T. F.↗

The interconnected data directory system and Catalog Interoperability

The Catalog Interoperability (CI) project, designed to enable rapid and efficient identification, location, and access to data of interest to the science community, is considered. The CI goal is to create a worldwide data information network composed of interconnected directory, guide (catalog), and inventory systems. Directories were created to aid in finding data. The directories contain brief information about the data sets, sufficient for determining whether further investigation is warranted. They also provide automated links to other information systems which give more detail on data of interest. A common format for describing data sets has been developed, called the Directory Interchange Format (DIF), which is used as the basis of information to be shared among the directories. These DIF files can be passed among the directories to keep their information up to date.

Thieman, James R.↗

Tracking and Data Relay Satellite System (TDRSS) Range and Doppler Tracking System Observation Measurement and Modeling

This document gives detailed descriptions of the tracking services, signal generation and processing, range and Doppler extraction, and the principles and procedures involved in modeling range and Doppler observations via the Tracking and Data Relay Satellite System (TDRSS). Major topics discussed include the following: TDRSS telecommunication services, functional description of the TDRSS, tracking signal generation and processing, range and Doppler observations modeling, angular observed and computed measurement algorithms, and tracking data transmission format.

Tracking and Data Relay Satellite System (TDRSS)↗

Cost effective data system design approach for EOS AM-1

The question of how to design a cost-effective data system for a space-based application with a high aggregate data rate is addressed. The steps used by the EOS AM-1 design team are defined. A summary of the design as of January 1993 is outlined. The AM-1 Science Data system is comprised of one subsystem that ingests, formats, and routes data - the Science Formatting Equipment (SFE), and another that records the data. Key interfaces are the interfaces to the high rate science instruments, the real-time transmitters, and the internal interface between the SFR and the Solid State Recorder. A cost-effective design approach for the AM-1 data system must take into account impacts on ground systems, data processing facilities, availability of data for real-time users, and future spacecraft designs.

Westmeyer, Paul A.↗

Data readiness pipeline patterns for scientific AI at scale: Insights from climate, fusion, life sciences, and materials

This article examines how data readiness for AI principles apply to large scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, life sciences, and materials—to identify common preprocessing patterns and domain‐specific constraints. We introduce a two‐dimensional readiness model that combines canonical preprocessing patterns with a five‐level operational readiness scale, both tailored to high‐performance computing (HPC) environments. This construct helps outline key challenges in transforming large‐scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross‐domain support for scalable and reproducible AI for science. Finally, we evaluate this maturity matrix in the context of case studies including ClimaX (climate), AFLOW (materials), OpenFold (proteomics), and DIII‐D fusion disruption‐prediction workflows, from which we distill lessons learned and provide recommendations to guide practitioners in developing robust AI‐readiness pipelines. Finally, we discuss remaining cross‐cutting challenges that persist across scientific domains.

97 MATHEMATICS AND COMPUTING↗

Data Readiness for Scientific AI at Scale

This paper examines how Data Readiness for AI (DRAI) principles apply to leadership-scale scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, bio/health, and materials—to identify common preprocessing patterns and domain-specific constraints. We introduce a two-dimensional readiness framework that combines canonical preprocessing patterns with a five-level operational readiness scale, both tailored to high-performance computing (HPC) environments. This framework helps outline key challenges in transforming large-scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross-domain support for scalable and reproducible AI for science.

Brewer, Wes [ORNL] (ORCID:0000000236393956)↗

HERO WEC Belt Test Data

The following submission includes raw and processed data from the 2024 Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC) belt tests conducted using NREL's Large Amplitude Motion Platform (LAMP). A description of the motion profiles run during testing can be found in the run log document. Data was collected using NREL's Modular Ocean Data AcQuisition (MODAQ) system in the form of TDMS files. Data was then processed using Python and MATLAB and converted to MATLAB workspace, parquet, and csv file formats. During Data processing, a low pass filter was applied to each array and the arrays were then resampled to common 10Hz timestamps. A MATLAB data viewer script is provided to quickly visualize these data sets. The following arrays are contained in each test data file: - Time: Unix seconds timestamp - Test_Time: Time in seconds since beginning of test - POS_OS_1001: Encoder position in degrees (the encoder is located on the secondary shaft of the spring return and is driven by the winch after a 4.5:1 gear reduction) - LC_ST_1001: Anchor load cell data in lbf - PRESS_OS_2002: Air spring pressure in psi This data set has been developed by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office.

16 TIDAL AND WAVE POWER↗

The Mariner Venus Mercury flight data subsystem.

The flight data subsystem (FDS) discussed handles both the engineering and scientific measurements performed on the MVM'73. It formats the data into serial data streams, and sends it to the modulation/demodulation subsystem for transmission to earth or to the data storage subsystem for storage on a digital tape recorder. The FDS is controlled by serial digital words, called coded commands, received from the central computer sequencer of from the ground via the modulation/demodulation subsystem. The eight major blocks of the FDS are: power converter, timing and control, engineering data, memory, memory input/output and control, nonimaging data, imaging data, and data output. The FDS incorporates some 4000 components, weighs 17 kg, and uses 35 W of power. General data on the mission and spacecraft are given.

Whitehead, P. B.↗

Flight tests of vortex-attenuating splines

Visual data on formation and motion of lift-induced wingtip vortex were obtained by stationary, airflow visualization method. Visual data indicated that vortex cannot be eliminated by merely reshaping wingtip. Configuration change will likely have only small effect on far-field flow.

Patterson, J. C., Jr.↗

Digital interpolators for polar format processing

The polar format approach to SAR image formation requires data to be interpolated from a warped grid onto a Cartesian lattice. In general, this requires that data be interpolated between varying sampling rates. In this paper, frequency-domain optimality criteria for polar format interpolators are defined and justified, and an approach to designing the corresponding digital filters is described.

Adams, John W.↗

Guide to Magellan image interpretation

An overview of Magellan Mission requirements, radar system characteristics, and methods of data collection is followed by a description of the image data, mosaic formats, areal coverage, resolution, and pixel DN-to-dB conversion. The availability and sources of image data are outlined. Applications of the altimeter data to estimate relief, Fresnel reflectivity, and surface slope, and the radiometer data to derive microwave emissivity are summarized and illustrated in conjunction with corresponding SAR image data. Same-side and opposite-side stereo images provide examples of parallax differences from which to measure relief with a lateral resolution many times greater than that of the altimeter. Basic radar interactions with geologic surfaces are discussed with respect to radar-imaging geometry, surface roughness, backscatter modeling, and dielectric constant. Techniques are described for interpreting the geomorphology and surface properties of surficial features, impact craters, tectonically deformed terrain, and volcanic landforms. The morphologic characteristics that distinguish impact craters from volcanic craters are defined. Criteria for discriminating extensional and compressional origins of tectonic features are discussed. Volcanic edifices, constructs, and lava channels are readily identified from their radar outlines in images. Geologic map units are identified on the basis of surface texture, image brightness, pattern, and morphology. Superposition, cross-cutting relations, and areal distribution of the units serve to elucidate the geologic history.

Ford, John P.↗