Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “network operations”

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.

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

At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Assessing the nation's earthquakes

The basic purposes of this report are: (1) to make a convincing case for the intrinsic value of regional seismic networks; (2) to describe the seriousness of persistent problems in the current configuration and operation of these networks; (3) to outline recommendations for their modernization and future evolution, in particular, their short-term integration and long-term affiliation with the U.S. National Seismic Network. Important supplementary information is included in two appendices: a survey of regional seismic networks and implementation strategies for revitalization of regional seismic networks.

Source record↗
NASA NTRS2006

Autonomous Congestion Control in Delay-Tolerant Networks

This presentation highlights communication congestion control in delay-tolerant networks (DTNs). Large-scale future space exploration will offer complex communication challenges that may be best addressed by establishing a network infrastructure. However, current internet techniques for congestion control are not well suited for operation of a network over interplanetary distances. An alternative, delay-tolerant technique for congestion control in a delay-tolerant network is presented. A simple DTN was constructed and an experimental congestion control mechanism was applied. The mechanism appeared to be effective and each router was able to make its bundle acceptance decisions autonomously. Future research will examine more complex topologies and alternative bundle acceptance rules that might enhance performance.

congestion control↗
DOE OSTI2023

System state estimation with asynchronous measurements

The present disclosure provides techniques for estimating network states using asynchronous measurements by leveraging network inertia. For example, a device configured in accordance with the techniques of the present disclosure may receive electrical parameter values corresponding to at least one first location within a power network and determine, based on the electrical parameter values and a previous estimated state of the power network, an estimated value of unknown electrical parameters that correspond to a second location within the power network. The device may further cause at least one device within the power network to modify operation based on the estimated value of the unknown electrical parameters. The leveraging of network inertia may obviate the need for probabilistic models or pseudo-measurements.

Cavraro, Guido↗
DOE OSTI2021

Operator learning for predicting multiscale bubble growth dynamics

We report simulating and predicting multiscale problems that couple multiple physics and dynamics across many orders of spatiotemporal scales is a great challenge that has not been investigated systematically by deep neural networks (DNNs). Herein, we develop a framework based on operator regression, the so-called deep operator network (DeepONet), with the long-term objective to simplify multiscale modeling by avoiding the fragile and time-consuming “hand-shaking” interface algorithms for stitching together heterogeneous descriptions of multiscale phenomena. To this end, as a first step, we investigate if a DeepONet can learn the dynamics of different scale regimes, one at the deterministic macroscale and the other at the stochastic microscale regime with inherent thermal fluctuations. Specifically, we test the effectiveness and accuracy of the DeepONet in predicting multirate bubble growth dynamics, which is described by a Rayleigh–Plesset (R–P) equation at the macroscale and modeled as a stochastic nucleation and cavitation process at the microscale by dissipative particle dynamics (DPD). First, we generate data using the R–P equation for multirate bubble growth dynamics caused by randomly time-varying liquid pressures drawn from Gaussian random fields (GRFs). Our results show that properly trained DeepONets can accurately predict the macroscale bubble growth dynamics and can outperform long short-term memory networks. We also demonstrate that the DeepONet can extrapolate accurately outside the input distribution using only very few new measurements. Subsequently, we train the DeepONet with DPD data corresponding to stochastic bubble growth dynamics. Although the DPD data are noisy and we only collect sparse data points on the trajectories, the trained DeepONet model is able to predict accurately the mean bubble dynamics for time-varying GRF pressures. Taken together, our findings demonstrate that DeepONets can be employed to unify the macroscale and microscale models of the multirate bubble growth problem, hence providing new insight into the role of operator regression via DNNs in tackling realistic multiscale problems and in simplifying modeling with heterogeneous descriptions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

Thunderstorm currents and lightning charges at the NASA Kennedy Space Center

The NASA Kennedy Space Center, (KSC) and the U.S. Air Force are currently operating an extensive network of ground-based electric-field mills in order to detect atmospheric electrical hazards to ground operations, launches, and landings of spacecraft. Over the past 10 years, the University of Arizona has utilized data provided by this network, and other instrumentation, to investigate the electrical structure of thunderstorms and lightning in Florida. Recent analyses have included estimates of the Maxwell current density that thunderstorms produce at the ground and computations of the locations and magnitudes of lightning-caused changes in the cloud charge distribution. This work is reviewed, and an example of how thunderstorm current patterns and lightning charges develop in both space and time is presented.

Krider, E. P.↗
DOE OSTI2022

A Simple and Accurate Energy-Detector-Based Transient Waveform Detection for Smart Grids: Real-World Field Data Performance

Integration of distributed energy sources, advanced meshed operation, sensors, automation, and communication networks all contribute to autonomous operations and decision-making processes utilized in the grid. Therefore, smart grid systems require sophisticated supporting structures. Furthermore, rapid detection and identification of disturbances and transients are a necessary first step towards situationally aware smart grid systems. This way, high-level monitoring is achieved and the entire system kept operational. Even though smart grid systems are unavoidably sophisticated, low-complexity algorithms need to be developed for real-time sensing on the edge and online applications to alert stakeholders in the event of an anomaly. In this study, the simplest form of anomaly detection mechanism in the absence of any a priori knowledge, namely, the energy detector (also known as radiometer in the field of wireless communications and signal processing), is investigated as a triggering mechanism, which may include automated alerts and notifications for grid anomalies. In contrast to the mainstream literature, it does not rely on transform domain tools; therefore, utmost design and implementation simplicity are attained. Performance results of the proposed energy detector algorithm are validated by real power system data obtained from the DOE/EPRI National Database of power system events and the Grid Signature Library.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Processes and Methods used for NASA Communications Services Project Conceptualization and Formulation

The U.S. National Aeronautics and Space Administration (NASA) is partnering with the commercial SATCOM industry to demonstrate the industry’s capabilities to provide services to NASA’s near-Earth missions. Leveraging commercial capabilities will become increasingly necessary for NASA, as its incumbent Government-owned-and-operated near-Earth satellite network, the Tracking and Data Relay Satellite System (TDRSS), will approach retirement towards the end of the current decade. NASA is actively taking the first steps to making the vision of using commercial SATCOM a reality. For more than two years, NASA’s Communication Services Project (CSP) has been evaluating the feasibility of employing commercial satellite communication (SATCOM) networks for near-Earth operations. This past April, CSP awarded US$278.5 million in Funded Space Act Agreements to select commercial SATCOM providers, so they may begin developing and demonstrating their specific near-Earth space communication services that may support future agency missions. Each company will match or exceed agency contributions during the five-year development and demonstration period, totaling more than $1.5 billion of cost-share investment. The companies will complete technology development and in-space demonstrations by 2025, after which NASA intends to seek multiple long-term contracts to acquire these kinds of services. The six companies (Inmarsat Government Inc., Kuiper Government Solutions (KGS), SES Government Solutions, Space Exploration Technologies (SpaceX), Telesat U.S. Services and Viasat Inc.) will shortly begin developing and demonstrating their capabilities to provide services, ranging from launch to standard on-orbit operations. The demonstrations will be across multiple spectrum regimes from L-Band to optical, and will utilize Geostationary Orbit (GEO), Medium-Earth Orbit (MEO) and Low-Earth Orbit (LEO) constellations. This paper discusses methodologies and processes used over the past two years to reach the point of entering into these partnerships. It also includes CSP’s goals and objectives going forward, following the award of six Funded Space Act Agreements to commercial SATCOM providers to develop and demonstrate these capabilities.

Communications Services Project↗
NASA NTRSDate not supplied

Processes and Methods used for Nasa Communications Services Project Conceptualization and Formulation

The U.S. National Aeronautics and Space Administration (NASA) is partnering with the commercial SATCOM industry to demonstrate the industry’s capabilities to provide services to NASA’s near-Earth missions. Leveraging commercial capabilities will become increasingly necessary for NASA, as its incumbent Government-owned-and-operated near-Earth satellite network, the Tracking and Data Relay Satellite System (TDRSS), will approach retirement towards the end of the current decade. NASA is actively taking the first steps to making the vision of using commercial SATCOM a reality. For more than two years, NASA’s Communication Services Project (CSP) has been evaluating the feasibility of employing commercial satellite communication (SATCOM) networks for near-Earth operations. This past April, CSP awarded US$278.5 million in Funded Space Act Agreements to select commercial SATCOM providers, so they may begin developing and demonstrating their specific near-Earth space communication services that may support future agency missions. Each company will match or exceed agency contributions during the five-year development and demonstration period, totaling more than $1.5 billion of cost-share investment. The companies will complete technology development and in-space demonstrations by 2025, after which NASA intends to seek multiple long-term contracts to acquire these kinds of services. The six companies (Inmarsat Government Inc., Kuiper Government Solutions (KGS), SES Government Solutions, Space Exploration Technologies (SpaceX), Telesat U.S. Services and Viasat Inc.) will shortly begin developing and demonstrating their capabilities to provide services, ranging from launch to standard on-orbit operations. The demonstrations will be across multiple spectrum regimes from L-Band to optical, and will utilize Geostationary Orbit (GEO), Medium-Earth Orbit (MEO) and Low-Earth Orbit (LEO) constellations. This paper discusses methodologies and processes used over the past two years to reach the point of entering into these partnerships. It also includes CSP’s goals and objectives going forward, following the award of six Funded Space Act Agreements to commercial SATCOM providers to develop and demonstrate these capabilities.

Communications Services Project↗
DOE OSTI2022

Networked Microgrid Cybersecurity Architecture Design Guide: A New Jersey TRANSITGRID Use Case

Microgrids require reliable communication systems for equipment control, power delivery optimization, and operational visibility. To maintain secure communications, Microgrid Operational Technology (OT) networks must be defensible and cyber-resilient. The communication network must be carefully architected with appropriate cyber-hardening technologies to provide security defenders the data, analytics, and response capabilities to quickly mitigate malicious and accidental cyberattacks. In this work, we outline several best practices and technologies that can support microgrid operations (e.g., intrusion detection and monitoring systems, response tools, etc.). Then we apply these recommendations to the New Jersey TRANSITGRID use case to demonstrate how they would be deployed in practice.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Reliable extrapolation of deep neural operators informed by physics or sparse observations

Deep neural operators can learn nonlinear mappings between infinite-dimensional function spaces via deep neural networks. As promising surrogate solvers of partial differential equations (PDEs) for real-time prediction, deep neural operators such as deep operator networks (DeepONets) provide a new simulation paradigm in science and engineering. Pure data-driven neural operators and deep learning models, in general, are usually limited to interpolation scenarios, where new predictions utilize inputs within the support of the training set. However, in the inference stage of real-world applications, the input may lie outside the support, i.e., extrapolation is required, which may result to large errors and unavoidable failure of deep learning models. Here, we address this challenge of extrapolation for deep neural operators. First, we systematically investigate the extrapolation behavior of DeepONets by quantifying the extrapolation complexity, via the 2-Wasserstein distance between two function spaces and propose a new strategy of bias–variance trade-off for extrapolation with respect to model capacity. Subsequently, we develop a complete workflow, including extrapolation determination, and we propose five reliable learning methods that guarantee a safe prediction under extrapolation by requiring additional information—the governing PDEs of the system or sparse new observations. The proposed methods are based on either fine-tuning a pre-trained DeepONet or multifidelity learning. We demonstrate the effectiveness of the proposed framework for various types of parametric PDEs. Furthermore, our systematic comparisons provide practical guidelines for selecting a proper extrapolation method depending on the available information, desired accuracy, and required inference speed.

42 ENGINEERING↗
NASA NTRS1988

Telescience at the University of California, Berkeley

The University of California at Berkeley (UCB) is a member of a university consortium involved in telescience testbed activities under the sponsorship of NASA. The Telescience Testbed Project consists of three experiments using flight hardware being developed for the Extreme Ultraviolet Explorer project at UCB's Space Sciences Laboratory. The first one is a teleoperation experiment investigating remote instrument control using a computer network such as the Internet. The second experiment is an effort to develop a system for operation of a network of remote workstations allowing coordinated software development, evaluation, and use by widely dispersed groups. The final experiment concerns simulation as a method to facilitate the concurrent development of instrument hardware and support software. Progress in these areas is described.

Chakrabarti, S.↗
NASA NTRS1989

Telescience at the University of California, Berkeley

The University of California at Berkeley (UCB) is a member of a university consortium involved in telescience testbed activities under the sponsorship of NASA. Our Telescience Testbed Project consists of three experiments using flight hardware being developed for the Extreme Ultraviolet Explorer project at UCB's Space Sciences Laboratory. The first one is a teleoperation experiment investigating remote instrument control using a computer network such as the Internet. The second experiment is an effort to develop a system for operation of a network of remote workstations allowing coordinated software development, evaluation, and use by widely dispersed groups. The final experiment concerns simulation as a method to facilitate the concurrent development of instrument hardware and support software. We describe our progress in these areas.

Telemetry/instrumentation/methods↗
NASA NTRS2008

Read You Loud and Clear! The Story of NASA's Spaceflight Tracking and Data Network

A historical account is provided of NASA's Spaceflight Tracking and Data Network (STDN), starting with its formation in the late 1950s to what it is today in the first decade of the 21st century. It traces the roots of the tracking network from its beginnings at the White Sands Missile Range in New Mexico to the Tracking and Data Relay Satellite System space-based constellation of today. The story spans the early days of satellite tracking using the Minitrack Network, through the expansion of the Satellite Tracking and Data Acquisition Network and the Manned Space Flight Network, and finally, to the Space and Ground networks of today. These accounts tell how international goodwill and foreign cooperation were crucial to the operation of the network and why the space agency chose to build the STDN as it did.

Tsiao, Sunny↗
DOE OSTI2022

Generative Design for Resilience of Interdependent Network Systems

Abstract Interconnected complex systems usually undergo disruptions due to internal uncertainties and external negative impacts such as those caused by harsh operating environments or regional natural disaster events. To maintain the operation of interconnected network systems under both internal and external challenges, design for resilience research has been conducted from both enhancing the reliability of the system through better designs and improving the failure recovery capabilities. As for enhancing the designs, challenges have arisen for designing a robust system due to the increasing scale of modern systems and the complicated underlying physical constraints. To tackle these challenges and design a resilient system efficiently, this study presents a generative design method that utilizes graph learning algorithms. The generative design framework contains a performance estimator and a candidate design generator. The generator can intelligently mine good properties from existing systems and output new designs that meet predefined performance criteria while the estimator can efficiently predict the performance of the generated design for a fast iterative learning process. Case studies results based on synthetic supply chain networks and power systems from the IEEE dataset have illustrated the applicability of the developed method for designing resilient interdependent network systems.

Engineering↗
NASA NTRS2012

NASA Integrated Network COOP

Natural disasters, terrorist attacks, civil unrest, and other events have the potential of disrupting mission-essential operations in any space communications network. NASA's Space Communications and Navigation office (SCaN) is in the process of studying options for integrating the three existing NASA network elements, the Deep Space Network, the Near Earth Network, and the Space Network, into a single integrated network with common services and interfaces. The need to maintain Continuity of Operations (COOP) after a disastrous event has a direct impact on the future network design and operations concepts. The SCaN Integrated Network will provide support to a variety of user missions. The missions have diverse requirements and include anything from earth based platforms to planetary missions and rovers. It is presumed that an integrated network, with common interfaces and processes, provides an inherent advantage to COOP in that multiple elements and networks can provide cross-support in a seamless manner. The results of trade studies support this assumption but also show that centralization as a means of achieving integration can result in single points of failure that must be mitigated. The cost to provide this mitigation can be substantial. In support of this effort, the team evaluated the current approaches to COOP, developed multiple potential approaches to COOP in a future integrated network, evaluated the interdependencies of the various approaches to the various network control and operations options, and did a best value assessment of the options. The paper will describe the trade space, the study methods, and results of the study.

Continuity of Operations (COOP)↗
NASA NTRS2011

Observations of Leonids 2009 by the Tajikistan Fireball Network

The fireball network in Tajikistan has operated since 2009. Five stations of the network covering the territory of near eleven thousands square kilometers are equipped with all-sky cameras with the Zeiss Distagon "fish-eye" objectives and by digital SLR cameras Nikon with the Nikkor "fish-eye" objectives. Observations of the Leonid activity in 2009 were carried out during November 13-21. In this period, 16 Leonid fireballs have been photographed. As a result of astrometric and photometric reductions, the precise data including atmospheric trajectories, velocities, orbits, light curves, photometric masses and densities were determined for 10 fireballs. The radiant positions during the maximum night suggest that the majority of the fireball activity was caused by the annual stream component with only minor contribution from the 1466 trail. According to the PE criterion, the majority of Leonid fireballs belonged to the most fragile and weak fireball group IIIB. However, one detected Leonid belonged to the fireball group I. This is the first detection of an anomalously strong Leonid individual.

Borovicka, J.↗