SEARCH · Search NASA

Results for “ADVANCED NETWORKING”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

NASA NTRS2019

Search for Intermediate Mass Black Hole Binaries in the First and Second Observing Runs of the Advanced LIGO and VIRGO Network

Gravitational-wave astronomy has been firmly established with the detection of gravitational waves from the merger of ten stellar-mass binary black holes and a neutron star binary. This paper reports on the all-sky search for gravitational waves from intermediate mass black hole binaries in the first and second observing runs of the Advanced LIGO and Virgo network. The search uses three independent algorithms: two based on matched filtering of the data with waveform templates of gravitational-wave signals from compact binaries, and a third, model-independent algorithm that employs no signal model for the incoming signal. No intermediate mass black hole binary event is detected in this search. Consequently, we place upper limits on the merger rate density for a family of intermediate mass black hole binaries. In particular, we choose sources with total masses 𝑀=𝑚1+𝑚2∈[120,800] 𝑀⊙ and mass ratios 𝑞=𝑚2/𝑚1∈[0.1,1.0]. For the first time, this calculation is done using numerical relativity waveforms (which include higher modes) as models of the real emitted signal. We place a most stringent upper limit of 0.20 Gpc−3 yr−1 (in comoving units at the 90% confidence level) for equal-mass binaries with individual masses 𝑚1,2=100 𝑀⊙ and dimensionless spins 𝜒1,2=0.8 aligned with the orbital angular momentum of the binary. This improves by a factor of ∼5 that reported after Advanced LIGO’s first observing run.

B. P. Abbott↗

DOE OSTI2019

Search for intermediate mass black hole binaries in the first and second observing runs of the Advanced LIGO and Virgo network

Gravitational-wave astronomy has been firmly established with the detection of gravitational waves from the merger of ten stellar-mass binary black holes and a neutron star binary. This paper reports on the all-sky search for gravitational waves from intermediate mass black hole binaries in the first and second observing runs of the Advanced LIGO and Virgo network. The search uses three independent algorithms: two based on matched filtering of the data with waveform templates of gravitational-wave signals from compact binaries, and a third, model-independent algorithm that employs no signal model for the incoming signal. No intermediate mass black hole binary event is detected in this search. Consequently, we place upper limits on the merger rate density for a family of intermediate mass black hole binaries. In particular, we choose sources with total masses $M={m}_{1}+{m}_{2}{\in}[120,800]\text{ }\text{ }{M}_{{\bigodot}}$ and mass ratios $q={m}_{2}/{m}_{1}{\in}[0.1,1.0]$. For the first time, this calculation is done using numerical relativity waveforms (which include higher modes) as models of the real emitted signal. Here, we place a most stringent upper limit of 0.20 Gpc -3 yr -1 (in comoving units at the 90% confidence level) for equal-mass binaries with individual masses ${m}_{1,2}=100\text{ }\text{ }{M}_{{\bigodot}}$ and dimensionless spins ${{\chi}}_{1,2}=0.8$ aligned with the orbital angular momentum of the binary. This improves by a factor of ${\sim}5$ that reported after Advanced LIGO's first observing run.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data

Many distribution network monitoring and control applications - including state estimation, volt/VAR optimization, and network reconfiguration - rely on accurate network models; however, the network models maintained by utilities can become outdated because of restoration activities, network reconfiguration, and missing data. With the widespread deployment of advanced metering infrastructure (AMI), abundant measurement data from low-voltage secondary networks are available. The AMI measurement data can be used for phase identification to improve the network models. Although the existing phase identification techniques work well in passive distribution feeders that do not have photovoltaic (PV) generation, they can fail to accurately identify the phases in the presence of PV. This paper proposes a robust phase identification algorithm based on supervised machine learning that accurately identifies the AMI meter phase connectivity in the presence of significant PV generation. The proposed algorithm does not require network topology information or feeder head measurement data. The algorithm is validated using the AMI measurement data collected in the field and the field-validated phase connectivity database on two real distribution feeders from San Diego Gas & Electric Company that have significant PV generation.

advanced metering infrastructure↗

DOE OSTI2022

Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data

Many distribution network monitoring and control applications - including state estimation, Volt/VAr optimization, and network reconfiguration - rely on accurate network models; however, the network models maintained by utilities can become outdated because of restoration activities, network reconfiguration, and missing data. With the widespread deployment of advanced metering infrastructure (AMI), abundant measurement data from low-voltage secondary networks are available. The AMI measurement data can be used for phase identification to improve the network models. Although the existing phase identification techniques work well in passive distribution feeders that do not have photovoltaic (PV) generation, they can fail to accurately identify the phases in the presence of PV. This paper proposes a robust phase identification algorithm based on supervised machine learning that accurately identifies the AMI meter phase connectivity in the presence of significant PV generation. The proposed algorithm does not require network topology information or feeder-head measurement data. The algorithm is validated using the AMI measurement data collected in the field and the field-validated phase connectivity database on two real distribution feeders from San Diego Gas & Electric Company that have significant PV generation.

advanced metering infrastructure (AMI)↗

NASA NTRS1988

Advanced information processing system: Input/output network management software

The purpose of this document is to provide the software requirements and specifications for the Input/Output Network Management Services for the Advanced Information Processing System. This introduction and overview section is provided to briefly outline the overall architecture and software requirements of the AIPS system before discussing the details of the design requirements and specifications of the AIPS I/O Network Management software. A brief overview of the AIPS architecture followed by a more detailed description of the network architecture.

Nagle, Gail↗

DOE OSTI2022

Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data: Preprint

advanced metering infrastructure↗

DOE OSTI2013

Advanced Scientific Computing Research Network Requirements: ASCR Network Requirements Review Final Report

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In October 2012, ESnet and the Office of Advanced Scientific Computing Research (ASCR) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the ASCR program office. The requirements identified at the review are summarized in the Findings section, and are described in more detail in the body of the report.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Final Report on the 2023 LaserNetUS Annual Meeting

LaserNetUS is a network of advanced laser facilities created by the Department of Energy Fusion Energy Sciences to provide greatly improved access to the most powerful lasers in North America. It is dedicated to the development of the high energy density physics workforce, especially the training and advancement of early career scientists. The network is helping to build a larger, better skilled and more diverse scientific community. The result of the work of LaserNetUS towards these goals was on display at the 2023 LaserNetUS Annual Meeting, held at the University of Maryland, College Park, Maryland on June 27-29, 2023 (Figure 1). The meeting had 216 participants, the largest sponsor/exhibitor participation of any LaserNetUS annual meeting, wide ranging plenary, invited, and contributed talks, a vigorous poster session, outreach to a diverse range of students, and two awards sessions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1994

Analysis of space network loading

The NASA Space Network (SN) consists of several geosynchronous communications satellites, in addition to ground support facilities. Space Network management must predict years in advance what network resources are necessary to adequately satisfy all SN users. Similarly, users of the Space Network must know throughout all stages of mission planning and operations to what extent their communication support requirements can be met. NASA, at the Goddard Space Flight Center, performs Space Network and Mission Modeling using The Network Planning and Analysis System (NPAS), to determine the answers to these questions.

Simons, Mark↗

DOE OSTI2022

Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles

Abstract The sciences struggle to integrate across disciplines, coordinate across data generation and modeling activities, produce connected open data, and build strong networks to engage stakeholders within and beyond the scientific community. The American Geophysical Union (AGU) is divided into 25 sections intended to encompass the breadth of the geosciences. Here, we introduce a special collection of commentary articles spanning 19 AGU sections on challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross‐system transferability of science outcomes. This article (a) summarizes the ICON principles; (b) discusses the crowdsourced approach to creating the collection; (c) explores insights from across the articles; and (d) proposes steps forward. There were common themes among the commentary articles, including broad agreement that the benefits of using ICON principles outweigh the costs, but that using ICON principles has important risks that need to be understood and mitigated. It was also clear that the ICON principles are not monolithic or static, but should instead be considered a heuristic tool that can and should be modified to meet changing needs. As a whole, the collection is intended as a resource for scientists pursuing ICON science and represents an important inflection point in which the geosciences community has come together to offer insights into ICON principles as a unified approach for improving how science is done across the geosciences and beyond.

Goldman, A. E.↗

DOE OSTI2026

Science Uses Deployment Operations-Advanced Wireless: Exploring Open Radio Access Network Technologies for Energy Science

Open Radio Access Network is emerging as a solution to the increasing demand for more flexible, cost-effective, and advanced mobile network infrastructures. This evolution is driven by advancements in wireless technologies and the growing complexity of deploying and managing these networks. O-RAN represents a significant shift in wireless technology, building upon the 3rd Generation Partnership Project framework to foster openness, flexibility, and interoperability. By decoupling hardware and software components, Open Radio Access Network enables a multi-vendor ecosystem that encourages innovation and diverse solutions. Open Radio Access Network's potential extends beyond traditional wireless applications, with growing interest in its role in advancing energy systems, particularly in the context of smart grids, microgrids, and the integration of renewable energy sources. While the role of open-wireless technologies in driving energy transformation is increasingly recognized, further exploration is needed. Vendors and utilities are investigating how Open Radio Access Network technologies can optimize energy use cases and improve the performance of 5G and beyond applications. This report outlines efforts under the Science Uses Deployment Operations Advance Wireless project, a collaboration between the National Laboratory of the Rockies' Cybersecurity Research Center, Argonne National Laboratory, Lawrence Berkeley National Laboratory, and the Department of Energy's Energy Science Network research and operations staff. The focus of this project is on due diligence, through testing and evaluation, preparing for the deployment of advanced wireless infrastructure for scientific use cases, with an emphasis on Open Radio Access Network technology, its components, integrations, and its ability to support vertical stack application across the energy sector. Additionally, the report highlights the value cases for utilities, underscoring how adopting open wireless standards can accelerate the evolution of energy systems, foster innovation, and improve the integration of critical energy technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2020

The Evolution of Lidar Networks: A US Perspective

Atmospheric aerosols and clouds play an important role in climate by directly scattering and absorbing sunlight. Aerosol-cloud interactions modify the particle properties causing indirect effects, alter aerosol deposition and rainfall, and contribute substantially to the uncertainties in predicting climate effects. Aerosols also affect air quality and both constituents modulate boundary layer dynamics to a certain extent, in turn impacting aerosol transport and aerosol-cloud interactions. The spatiotemporal distribution of aerosol and cloud layers is thus important, and lidar remains the primary instrument for determining the vertical distribution of aerosols and thin clouds. Lidar still provides important information for opaque cloud layers by determining base heights. Combined lidar and radar data provide a comprehensive coverage of aerosol and cloud vertical distributions, and thus locations where and when they interact. Lidar data provide a means of constraining column aerosol loading observations (e.g. AOD) to vertical extents. In addition, lidar has proven effective at determining a proxy for boundary layer height by examining aerosol gradients and/or cloud base heights in lidar profiles. Polarized lidars provide additional information on particle shape, allowing estimates of cloud phase and separation of dust or smoke from sulfate and sea salt aerosols. Given the importance of lidar observations and a critical maturation in technology and retrieval techniques, several organizations began to build operational lidar networks around 2000. The European Aerosol Research Lidar Network (EARLINET) was started as a research focused network of advanced lidars across Europe. The Asian Dust Lidar Network (ADNET) was also developed as a regional network providing lidar profiles of dust and pollution across Eastern Asia. In the US, the NASA Micro Pulse Lidar Network (MPLNET) was created to provide global lidar profiling at key sites in the NASA Aerosol Robotic Network (AERONET). The Network for the Detection of Atmospheric Composition Change (NDACC) pre-dates these networks and many sites have lidar, but it is not strictly a lidar network and at the time focused less on the lower troposphere. Finally, there were already existing ceilometer networks operated by various meteorological agencies, but in particular here in the US the profile data has not been available. The ceilometer networks were used to provide only clouds base heights and estimates of PBL height. Thus, the distinguishing feature between lidar and ceilometer networks was historically the ability to actually provide profile information (in addition to differences in wavelength, and advanced retrievals such as the raman technique). As time progressed, each lidar network matured and developed more operational capabilities and data sets, coupled with viable data centers providing DAAC services and access to near-real-time (NRT) data. In 2008 under WMO guidance, the Global Atmospheric Watch (GAW) Aerosol Lidar Observation Network (GALION) was formed as a global network made up of the existing lidar networks. The goal was to share information, best practices, and develop frameworks and techniques for quality data. GALION grew to include several other regional lidar networks and this has led to a vast increase in quality lidar sites worldwide.

Welton, Ellsworth J.↗

DOE OSTI2021

Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles

The sciences struggle with poor integration across disciplines, the absence of coordination within and across data generation and modeling activities, scarce or disconnected open data, and weaknesses of networks to engage diverse stakeholders within and beyond the scientific community. The American Geophysical Union (AGU) is divided into 25 sections intended to encompass the breadth of the geosciences. Here, we introduce a special collection of commentary articles spanning 19 AGU sections on the challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross-system transferability of science outcomes. This article summarizes the ICON principles; discusses the crowdsourced approach to creating the collection; and explores insights from across the articles. There were multiple common themes among the commentary articles, including the broad agreement that the benefits of using ICON principles outweigh the costs, but that using ICON principles has important risks that need to be understood and mitigated. It was also clear that the ICON principles are not monolithic or static, but should instead be considered a heuristic tool that can and should be modified to meet changing needs. As a whole, the collection is intended as a resource for scientists pursuing ICON science and represents an important inflection point in which the geosciences community has come together around ICON principles as a unified approach for improving how science is done across the geosciences and beyond.

58 GEOSCIENCES↗

NASA NTRS1986

US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 1: Executive summary

Over the past two decades, fiber optics has emerged as a highly practical and cost-efficient communications technology. Its competitiveness vis-a-vis other transmission media, especially satellite, has become a critical question. This report studies the likely evolution and application of fiber optic networks in the United States to the end of the century. The outlook for the technology of fiber systems is assessed and forecast, scenarios of the evolution of fiber optic network development are constructed, and costs to provide service are determined and examined parametrically as a function of network size and traffic carried. Volume 1 consists of the Executive Summary. Volume 2 focuses on fiber optic technology and long distance fiber optic networks. Volume 3 develops a traffic and financial model of a nationwide long distance transmission network. Among the study's most important conclusions are: revenue requirements per circuit for LATA-to-LATA fiber optic links are less than one cent per call minute; multiplex equipment, which is likely to be required in any competing system, is the largest contributor to circuit costs; the potential capacity of fiber optic cable is very large and as yet undefined; and fiber optic transmission combined with other network optimization schemes can lead to even lower costs than those identified in this study.

Source record↗

DOE OSTI2022

Advances in Secure 5G Network for a Nationwide Drone Corridor

Recent research has validated the proposal to add a separate set of antennas for 5G coverage in the air, while the conventional set of antennas continues to provide coverage on the ground, for a nationwide drone corridor for 5G cellular drones. More importantly, this drone corridor can be made secure and reliable by adapting the drone trajectories to avoid interference and security attacks, and with advanced precoding and physical layer security. Energy efficiency can also be improved with low-resolution massive multiple-input multiple-output (MIMO) systems that utilize low resolution digital to analog converters. This paper describes additional research findings to further support the creation of this nationwide drone corridor. We design optimal drone trajectory within the drone corridor to improve safety for pedestrians and vehicles on the ground. We derive the optimum antenna uptilt angle to minimize outage probability for a given drone corridor. We also study the placement of intelligent reflector surfaces in an urban drone corridor in order to improve the multi-path scattering and hence the spatial multiplexing gains for serving drones. We calculate trajectories to maximize data rate in the presence of smart interference when drones are used as relays and each drone may be deployed in the paths of data flows from multiple BSs to multiple UEs. Next we demonstrate how the use of the additional set of antennas along with the 3GPP standard based subframe blanking method can minimize the interference from ground reflection of the radio frequency (RF) radiation from the downtilted antennas. The paper concludes with plans to continue with experimental studies to advance this work further.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2003

Perspectives on Advanced Learning Technologies and Learning Networks and Future Aerospace Workforce Environments

An overview of the advanced learning technologies is given in this presentation along with a brief description of their impact on future aerospace workforce development. The presentation is divided into five parts (see Figure 1). In the first part, a brief historical account of the evolution of learning technologies is given. The second part describes the current learning activities. The third part describes some of the future aerospace systems, as examples of high-tech engineering systems, and lists their enabling technologies. The fourth part focuses on future aerospace research, learning and design environments. The fifth part lists the objectives of the workshop and some of the sources of information on learning technologies and learning networks.

Noor, Ahmed K.↗

NASA NTRS1982

The telecommunications and data acquisition report

Developments in Earth-based radio technology are reported. The Deep Space Network is discussed in terms of its advanced systems, network and facility engineering and implementation, operations, and energy sources. Problems in pulse communication and radio frequency interference are addressed with emphasis on pulse position modulation and laser beam collimation.

Renzetti, N. A.↗

NASA NTRS1996

The " Swarm of Ants vs. Herd of Elephants" Debated Revisited: Performance Measurements of PVM-Overflow Across a Wide Spectrum of Architectures

The Gorden Bell Prizes given out at Supercomputing every year includes at least two catergories: performance (highest GFLOP count) and price-performance (GFLOP/million $$) for real applications. In the past five years, the winners of the price-performance categories all came from networks of work-stations. This reflects three important facts: 1. supercomputers are still too expensive for the masses; 2. achieving high performance for real applications takes real work; and, most importantly; 3. it is possible to obtain acceptable performance for certain real applications on network of work stations. With the continued advance of network technology as well as increased performance of "desktop" workstation, the "Swarm of Ants vs. Herd of Elephants" debate, which began with vector multiprocessors (VPPs) against SIMD type multiprocessors (e.g. CM2), is now recast as VPPs against Symetric Multiprocessors (SMPs, e.g. SGI PowerChallenge). This paper reports on performance studies we performed solving a large scale (2-million grid pt.s) CFD problem involving a Boeing 747 based on a parallel version of OVERFLOW that utilizes message passing on PVM. A performance monitoring tool developed under NASA HPCC, called AIMS, was used to instrument and analyze the the performance data thus obtained. We plan to compare its performance data obtained across a wide spectrum of architectures including: the Cray C90, IBM/SP2, SGI/Power Challenge Cluster, to a group of workstations connected over a simple network. The metrics of comparison includes speed-up, price-performance, throughput, and turn-around time. We also plan to present a plan of attack for various issues that will make the execution of Grand Challenge Applications across the Global Information Infrastructure a reality.

Yan, Jerry C.↗