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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Spaceflight tracking and data network support in the space tug era

This paper describes the Spaceflight Tracking and Data Network (STDN) which will be used to provide command, telemetry and tracking support to the Space Tug in the 1980's. A description of the mission support capabilities of the two major elements of the STDN - the ground based sites (GSTDN) and the Tracking and Data Relay Satellite System (TDRSS) - is provided. This paper also contains a summary description of the mission/STDN RF and Data Handling interface.

Stelter, L. R.↗
NASA NTRS1987

Verification of mesoscale objective analyses of VAS and rawinsonde data using the March 1982 AVE/VAS special network data

Various combinations of VAS (Visible and Infrared Spin Scan Radiometer Atmospheric Sounder) data, conventional rawinsonde data, and gridded data from the National Weather Service's (NWS) global analysis, were used in successive-correction and variational objective-analysis procedures. Analyses are produced for 0000 GMT 7 March 1982, when the VAS sounding distribution was not greatly limited by the existence of cloud cover. The successive-correction (SC) procedure was used with VAS data alone, rawinsonde data alone, and both VAS and rawinsonde data. Variational techniques were applied in three ways. Each of these techniques was discussed.

Doyle, James D.↗
NASA NTRS1988

Verification of mesoscale objective analyses of VAS and rawinsode data using the March 1982 AVE/VAS special network data

Various combinations of VAS (Visible and Infrared Spin Scan Radiometer Atmospheric Sounder) data, conventional rawinsonde data, and gridded data from the National Weather Service's (NWS) global analysis, were used in successive-correction and variational objective-analysis procedures. Analyses are produced for 0000 GMT 7 March 1982, when the VAS sounding distribution was not greatly limited by the existence of cloud cover. The successive-correction (SC) Procedure was used with VAS data alone, rawinsonde data alone, and both VAS and rawinsonde data. Variational techniques were applied in three ways. Each of these techniques was discussed.

Doyle, James D.↗
NASA NTRS2001

QoS for Real Time Applications over Next Generation Data Networks

Viewgraphs on Qualtity of Service (QOS) for real time applications over next generation data networks are presented. The progress to date include: Task 1: QoS in Integrated Services over DiffServ networks (UD); Task 2: Interconnecting ATN with the next generation Internet (UD); Task 3: QoS in DiffServ over ATM (UD); Task 4: Improving Explicit Congestion Notification with the Mark-Front Strategy (OSU); Task 5: Multiplexing VBR over VBR (OSU); and Task 6: Achieving QoS for TCP traffic in Satellite Networks with Differentiated Services (OSU).

Ivancic, William↗
DOE OSTI2025

NCAR-RAL Surface Hydrometeorological Observation Network Data for LASSO-CACTI Overview Paper

This data set contains the 15 minute resolution surface meteorology and soils data from the 15 NCAR/RAL weather stations that were operated around central Argentina during the RELAMPAGO (Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations) Extended Observing Period (EOP). Data providence, citation, and acknowledgement This ARM data set is a copy of v1.0 of the NCAR data set obtained in June 2024 from https://doi.org/10.26023/KW8Z-F2WX-H0Y. The citation for the original data source is: Gochis, D., et al. 2019. NCAR-RAL Surface Hydrometeorological Observation Network Data. Version 1.0. UCAR/NCAR - Earth Observing Laboratory. https://doi.org/10.26023/KW8Z-F2WX-H0Y Accessed June 2024. In addition to the citation reference and any other acknowledgements, please acknowledge NCAR/EOL in your publications with text such as: “Data provided by NCAR/EOL under the sponsorship of the National Science Foundation. https://data.eol.ucar.edu/”

air temperature↗
NASA NTRS1981

The evolution of the spaceflight tracking and data network

The evolution of the Minitrack Network, the first worldwide satellite tracking capability (1957-1962), into the Satellite Tracking and Data Acquisition Network (1960-1966) is described. Attention is also given to the Mercury Network, which became operational in 1961, was the foundation for the Manned Space Flight Network, and supported the Gemini and Apollo missions. The development of the NASA Communications Network, which began to take shape in the early 1960s, is described. An account is also given of the way in which all these functions began playing together (1965) and were consolidated in the early 1970s as the Space Tracking and Data Network.

Hocking, W. M.↗
DOE OSTI2021

Improved lithospheric attenuation structure of the Arabian Peninsula through the use of national network data

We characterize the attenuation structure of the Arabian Peninsula through the measurement of regional phase amplitudes. High-resolution is achieved by combining stations from global networks with national network data through the cooperative effort of several countries in the region, including Saudi Arabia, Oman, Iraq, and Kuwait. The result is an improved attenuation model of the crust and upper mantle for a broad frequency band that extends from 0.5 to 10 Hz. The observed attenuation is in accordance with various elements of earth structure, including plate boundary type, style of tectonism, thermo-tectonic age, and temperature. Emerging features from the model include details in the structure along the Red Sea, and improved imaging of the southern Arabian Peninsula extending north from the Gulf of Aden. Finally, the resulting attenuation model can be employed for better magnitude estimates, in isolating tectonic and structural features, and in characterizing strong ground motion in the Arabian Peninsula.

58 GEOSCIENCES↗
DOE OSTI2025

A product data network to enable faster, easier, and better planning of building envelopes

The building envelopes contributes significantly to the energy-efficiency of the building. Building performance simulation has made it possible to compare façade technologies regarding energy demand, daylighting, thermal and visual comfort in detail. Planners, such as architects and engineers, need experience to find product data with the right quality and level of detail, and to process the data to fit the calculation and the application. In the available time, planners can compare only a limited number of products, which means that better solutions could go unnoticed. This paper presents a new concept for making product data easily accessible for building façade planning. The concept consists of a network of databases for the efficient exchange and use of optical and calorimetric data of glazing units, shading devices, and combinations of both. The paper presents the research questions, an analysis of the current challenges, six design goals for the product data network and its implementation together with a discussion. Many product data sources can be connected to many planning software applications via the specified application programming interface. When planning software connects to the product data network, the planning of building envelopes can be much faster because planners do not need to spend so much time to search and process product data manually. The planning of building envelopes can also become much easier, especially for planners with limited experience. They do not need to understand all the details about which data fits which calculation if the software company implements this. The planning of building envelopes can become much more reliable when software companies validate their use of the product data network, because the current manual process is prone to errors. The planning of building envelopes can also improve because more products can be compared in the available time, allowing better solutions to be found.

Maurer, Christoph↗
NASA NTRS1974

Spaceflight tracking and data network operational reliability assessment for Skylab

Data on the spaceflight communications equipment status during the Skylab mission were subjected to an operational reliability assessment. Reliability models were revised to reflect pertinent equipment changes accomplished prior to the beginning of the Skylab missions. Appropriate adjustments were made to fit the data to the models. The availabilities are based on the failure events resulting in the stations inability to support a function of functions and the MTBF's are based on all events including 'can support' and 'cannot support'. Data were received from eleven land-based stations and one ship.

Seneca, V. I.↗
DOE OSTI2026

Data for The Stem Cell-Type Transcriptome of Bioenergy Sorghum Reveals the Spatial Regulation of Secondary Cell Wall Networks

Bioenergy sorghum is a low-input, drought-resilient, deep-rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum’s 4-5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about stem cell-type gene expression and regulation was available to enable engineering. To obtain this information, Laser Capture Microdissection (LCM) was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell-type specific gene regulatory networks (GRNs) revealed that unique TF families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell-specific transcriptome data was combined with a stem developmental transcriptome dataset to identify the GRN that differentially activates the secondary cell wall (SCW) formation in stem xylem sclerenchyma and epidermal cells. The cell-type transcriptomic dataset provides a valuable source of information about the function of sorghum stem cell types and GRNs that will enable the engineering of bioenergy sorghum stems.

Software↗
NASA NTRS2022

An Examination of the Recent Stability of Ozonesonde Global Network Data

The recent Assessment of Standard Operating Procedures for OzoneSondes (ASOPOS 2.0; WMO/GAW Report #268) addressed questions of homogeneity and long-term stability in global electrochemical concentration cell (ECC) ozone sounding network time series. Among its recommendations was adoption of a standard for evaluating data quality in ozonesonde time series. Total column ozone (TCO) derived from the sondes compared to TCO from Aura’s Ozone Monitoring Instrument (OMI) is a primary quality indicator. Comparisons of sonde ozone with Aura’s Microwave Limb Sounder (MLS) are used to assess the stability of stratospheric ozone. This paper provides a comprehensive examination of global ozonesonde network data stability and accuracy since 2004 in light of the sudden post-2013 TCO “dropoff” of ~3-4% that was reported previously at select stations (Stauffer et al., 2020). Comparisons with Aura OMI TCO averaged across the network of 60 stations are stable within about ±2% over the past 18 years. Sonde TCO has similar stability compared to three other TCO satellite instruments, and the stratospheric ozone measurements average to within ±5% of MLS from 50 to 10 hPa. Thus, sonde data are reliable for trends, but with a caveat applied for a subset of dropoff stations in the tropics and subtropics. The dropoff is associated with only one of two major ECC instrument types. A detailed examination of ECC serial numbers pinpoints the timing of the dropoff. However, we find that overall, ozonesonde data are stable and accurate compared to independent measurements over the past two decades.

Ryan M. Stauffer↗
NASA NTRS2000

BOREAS AFM-5 Level-1 Upper Air Network Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-5 team collected and processed data from the numerous radiosonde flights during the project. The goals of the AFM-05 team were to provide large-scale definition of the atmosphere by supplementing the existing Atmospheric Environment Service (AES) aerological network, both temporally and spatially. This data set includes basic upper-air parameters collected from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region. The data are contained in tabular ASCII files. The level-1 upper-air network data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files also are available on a CD-ROM (see document number 20010000884).

Barr, Alan↗
DOE OSTI2021

Utilizing the Dynamic Networks Data Processing and Analysis Experiment (DNE18) to Establish Methodologies for the Comparison of Automatic Infrasonic Signal Detectors

The Dynamic Networks Experiment 2018 (DNE18) was a collaborative effort between Los Alamos National Laboratory (LANL), Sandia National Laboratories (SNL), Lawrence Livermore National Laboratory (LLNL) and Pacific Northwest National Laboratory (PNNL) designed to evaluate methodologies for multi-modal data ingestion and processing. One component of this virtual experiment was a quantitative assessment of current capabilities for infrasound data processing, beginning with the establishment of a baseline for infrasound signal detection. To produce such baselines, SNL and LANL exploited a common dataset of infrasound data recorded across a regional network in Utah from December 2010 through February 2011. We utilize two automated signal detectors, the Adaptive F-Detector (AFD) and the Multivariate Adaptive Learning Detector (MALD) to produce automated signal detection catalogs and an analyst-produced catalog. Comparisons indicate that automatic detectors may be able to identify small amplitude, low SNR events that cannot be identified by analyst review. We document detector performance in terms of precision and recall, demonstrating that the AFD is more precise, but the MALD has higher recall. We use a synthetic dataset of signals embedded in pink noise in order to highlight shortcomings in assessing detection algorithms for low signal to noise ratio signals which are commonly of interest to the nuclear monitoring community. For comparisons utilizing the synthetic dataset, the AFD has higher recall while precision is equal for both detectors. These results indicate that both detectors perform well across a variety of background noise environments; however, both detectors fail to identify repetitive, short duration signals arriving from similar backazimuths. These failures represent specific scenarios that could be targeted for further detector development.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A guide to the BRAIN Initiative Cell Census Network data ecosystem

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

59 BASIC BIOLOGICAL SCIENCES↗