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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

NASA's Earth Observing Data and Information System - Near-Term Challenges

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of the NASA Earth observation program since the 1990's. EOSDIS manages data covering a wide range of Earth science disciplines including cryosphere, land cover change, polar processes, field campaigns, ocean surface, digital elevation, atmosphere dynamics and composition, and inter-disciplinary research, and many others. One of the key components of EOSDIS is a set of twelve discipline-based Distributed Active Archive Centers (DAACs) distributed across the United States. Managed by NASA's Earth Science Data and Information System (ESDIS) Project at Goddard Space Flight Center, these DAACs serve over 3 million users globally. The ESDIS Project provides the infrastructure support for EOSDIS, which includes other components such as the Science Investigator-led Processing systems (SIPS), common metadata and metrics management systems, specialized network systems, standards management, and centralized support for use of commercial cloud capabilities. Given the long-term requirements, and the rapid pace of information technology and changing expectations of the user community, EOSDIS has evolved continually over the past three decades. However, many challenges remain. Challenges addressed in this paper include: growing volume and variety, achieving consistency across a diverse set of data producers, managing information about a large number of datasets, migration to a cloud computing environment, optimizing data discovery and access, incorporating user feedback from a diverse community, keeping metadata updated as data collections grow and age, and ensuring that all the content needed for understanding datasets by future users is identified and preserved.

Remote Sensing↗
NASA NTRS2010

Digital Video Over Space Systems and Networks

This slide presentation reviews the use of digital video with space systems and networks. The earliest use of video was the use of film precluding live viewing, which gave way to live television from space. This has given way to digital video using internet protocol for transmission. This has provided for many improvements with new challenges. Some of these ehallenges are reviewed. The change to digital video transmitted over space systems can provide incredible imagery, however the process must be viewed as an entire system, rather than piece-meal.

Grubbs, Rodney↗
DOE OSTI2021

Efficient Contingency Analysis in Power Systems via Network Trigger Nodes

Modeling failure dynamics within a power system is a complex and challenging process due to multiple inter-dependencies and convoluted inter-domain relationships. Subject matter experts (SMEs) are interested in understanding these failure dynamics for reducing the impact from future disasters (i.e., losses or failures of power system components, such as transmission lines). Contingency analysis (CA) tools enable such ’what-if’ scenario analyses to evaluate the impacts on the power system. Analyzing all possible contingencies among N system components can be computationally expensive. An important step for performing CA is identifying a set of k ‘trigger’ components, which when failed initially can significantly impact the overall system by causing multiple failures. Currently SMEs focus on identifying these trigger components by running expensive simulations on all possible subsets, which quickly becomes infeasible. Hence finding a relevant set of trigger components (contingencies) rapidly to enable efficient and useful CA is crucial.In a collaboration between computer scientists and power system experts, we propose an efficient method for performing CA by exploiting network inter-dependencies in power system components. First, we construct a network with multiple electric grid infrastructure components and dependencies as connections among them. We reformulate the problem of finding a set of trigger components as a problem of identifying critical nodes in the network, which can cascade power failures through connected nodes and cause significant damage to the network. To guide the practical CA tools, we develop a network-based model with a probabilistic edge-weights setup using intricate domain rules. Then we conduct an empirical study on real power system data in the US for both regional and national levels. Firstly, we use power system datasets for the US to create a national-scale domain-driven model. Secondly, we demonstrate that network-based model outperforms the outputs from a real CA tool and show on average 25 × improved selection of contingencies, thereby showcasing practical benefits to the power experts.

Tabassum, Anika↗
NASA NTRS1985

State of the art survey of network operating systems development

The results of the State-of-the-Art Survey of Network Operating Systems (NOS) performed for Goddard Space Flight Center are presented. NOS functional characteristics are presented in terms of user communication data migration, job migration, network control, and common functional categories. Products (current or future) as well as research and prototyping efforts are summarized. The NOS products which are revelant to the space station and its activities are evaluated.

Source record↗
DOE OSTI2017

ESnet Network Operating System (ENOS)

ENOS is a prototype next-generation ESnet architecture for handling data-intensive science workflows. The concept of a 'network operating system', a software layer that enables applications to get information about the network and to program it to meet its needs, has been around in academic papers for a while but appears to be feasible now due to the wide adoption of the Software-Defined Networking (SDN) paradigm. The SDN paradigm constitutes a network architecture that separates the control plane from the distributed data plane and provides logical centralization of the network control and state. These logical central control plane capabilities can be evolved to become the operating system through which the network policies are implemented across the entire network and applications can program network behavior.

ESnet↗
NASA NTRS1984

Spacelab data analysis using the space plasma computer analysis network (SCAN) system

The Space-plasma Computer Analysis Network (SCAN) currently connects a large number of U.S. Spacelab investigators into a common computer network. Used primarily by plasma physics researchers at present, SCAN provides access to Spacelab investigators in other areas of space science, to Spacelab and non-Spacelab correlative data bases, and to large Class VI computational facilities for modeling. SCAN links computers together at remote institutions used by space researchers, utilizing commercially available software for computer-to-computer communications. Started by the NASA's Office of Space Science in mid 1980, SCAN presently contains ten system nodes located at major universities and space research laboratories, with fourteen new nodes projected for the near future. The Stanford University computer gateways allow SCAN users to connect onto the ARPANET and TELENET overseas networks.

Green, J. L.↗
DOE OSTI2026

Mapping Critical Vulnerabilities in Natural Gas Pipeline Systems through Network Centrality and GIS Analytics

Natural gas plays a central role in the US energy landscape, providing 43% of electricity generation in 2023. Its exclusive recovery ability on pipelines for transmission underscores the importance of understanding the disruption recovery ability of this infrastructure. This study employs a network-based analytical framework integrating geographic information systems (GIS) with multiple centrality measures—betweenness, closeness, degree, and eigenvector—to pinpoint key segments and evaluate the structural robustness of the national pipeline network. Pipelines are grouped by System ID and Operator ID to capture variations across organizational and physical structures. The analysis reveals uneven patterns of network influence, where certain pipelines function as critical connectors or dominant hubs. Spatial mapping highlights geographic dependencies and potential chokepoints, offering a clear view of where targeted risk prevention measures would be most effective. The findings provide practical guidance for prioritizing maintenance, enhancing system robustness, and mitigating risks to ensure a stable and secure energy supply. Future research will expand the framework to incorporate dynamic operational data and real-time network behavior.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗
DOE OSTI2021

PSSE Network Reduction

This code can reduce power system network models in PSSE. The user selects single-port or two-port subnetworks for reduction, and the software reduces the subnetwork as described in the paper "Power System Network Reduction for Power Hardware-in-the-Loop Simulation" (submitted).

Wang, Bin↗
DOE OSTI2015

Decentralized Energy Management System for Networked Microgrids in Grid-connected and Islanded Modes

This paper proposes a decentralized energy management system (EMS) for the coordinated operation of networked Microgirds (MGs) in a distribution system. In the grid-connected mode, the distribution network operator (DNO) and each MG are considered as distinct entities with individual objectives to minimize their own operation costs. It is assumed that both dispatchable and renewable energy source (RES)-based distributed generators (DGs) exist in the distribution network and the networked MGs. In order to coordinate the operation of all entities, we apply a decentralized bi-level algorithm to solve the problem with the first level to conduct negotiations among all entities and the second level to update the non-converging penalties. In the islanded mode, the objective of each MG is to maintain a reliable power supply to its customers. In order to take into account the uncertainties of DG outputs and load consumption, we formulate the problems as two-stage stochastic programs. The first stage is to determine base generation setpoints based on the forecasts and the second stage is to adjust the generation outputs based on the realized scenarios. Case studies of a distribution system with networked MGs demonstrate the effectiveness of the proposed methodology in both grid-connected and islanded modes.

Distributed Generator (DG)↗
DOE OSTI2017

Computer network defense system

A method and apparatus for protecting virtual machines. A computer system creates a copy of a group of the virtual machines in an operating network in a deception network to form a group of cloned virtual machines in the deception network when the group of the virtual machines is accessed by an adversary. The computer system creates an emulation of components from the operating network in the deception network. The components are accessible by the group of the cloned virtual machines as if the group of the cloned virtual machines was in the operating network. The computer system moves network connections for the group of the virtual machines in the operating network used by the adversary from the group of the virtual machines in the operating network to the group of the cloned virtual machines, enabling protecting the group of the virtual machines from actions performed by the adversary.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Adaptive neural network management system

A method and computer system for managing a neural network. Data is sent into an input layer in a portion of layers of nodes in the neural network. The data moves on an encode path through the portion such that an output layer in the portion outputs encoded data. The encoded data is sent into the output layer on a decode path through the portion back to the input layer to obtain a reconstruction of the data by the input layer. A determination is made as to whether an undesired amount of error has occurred in the output layer based on the data sent into the input layer and the reconstruction of the data. A number of new nodes is added to the output layer when a determination is present that the undesired amount of the error occurred, enabling reducing the error using the number of the new nodes.

Draelos, Timothy J.↗
DOE OSTI2022

Resilient Hierarchical Networked Control Systems: Secure Controls for Critical Locations and at Edge

Integration of information and communication technology (ICT) offers new opportunities in improving the management and operation of critical infrastructures such as power systems as it allows connection of different sensors and control components via a communication network, leading to the so-called networked control systems (NCS). However, the use of open and pervasive ICT such as the Internet or wireless communication technologies comes at a price of making NCS vulnerable to cyber intrusions/attacks which may cause physical damage. Here, this chapter presents control algorithms to ensure resilient and safe operation of NCS under unknown cyberattacks. Specifically, a variant of dynamic watermarking strategies is presented by embedding encoding/decoding components of chaotic signals into the NCS for secure control for critical locations where the measurement/control signals are transmitted to/from the control center via a communication network. In addition, resilient cooperative control algorithms are discussed to ensure safe operation at edge of the NCS which consists of a large number of distributed controllable devices. Several numerical examples are provided to illustrate the proposed control strategies.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1992

The Deep Space Network information system in the year 2000

The Deep Space Network (DSN), the largest, most sensitive scientific communications and radio navigation network in the world, is considered. Focus is made on the telemetry processing, monitor and control, and ground data transport architectures of the DSN ground information system envisioned for the year 2000. The telemetry architecture will be unified from the front-end area to the end user. It will provide highly automated monitor and control of the DSN, automated configuration of support activities, and a vastly improved human interface. Automated decision support systems will be in place for DSN resource management, performance analysis, fault diagnosis, and contingency management.

Markley, R. W.↗
NASA NTRS1993

Network command processing system overview

The Network Command Processing System (NCPS) developed for the National Aeronautics and Space Administration (NASA) Ground Network (GN) stations is a spacecraft command system utilizing a MULTIBUS I/68030 microprocessor. This system was developed and implemented at ground stations worldwide to provide a Project Operations Control Center (POCC) with command capability for support of spacecraft operations such as the LANDSAT, Shuttle, Tracking and Data Relay Satellite, and Nimbus-7. The NCPS consolidates multiple modulation schemes for supporting various manned/unmanned orbital platforms. The NCPS interacts with the POCC and a local operator to process configuration requests, generate modulated uplink sequences, and inform users of the ground command link status. This paper presents the system functional description, hardware description, and the software design.

Nam, Yon-Woo↗
NASA NTRS1988

Network Queueing System

Program directs traffic in UNIX-based network. NQS provides facilities for remote queueing, request routing, remote status, queue-access controls, batch-request resource-quota limits, and remote output return. Written in C.

Kingsbury, Brent↗