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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. the proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photofractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feedforward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

Liu, Hua-Kuang↗
NASA NTRS2010

LDCM Ground System. Network Lesson Learned

This slide presentation reviews the Landsat Data Continuity Mission (LDCM) and the lessons learned in implementing the network that was assembled to allow for the acquisition, archiving and distribution of the data from the Landsat mission. The objective of the LDCM is to continue the acquisition, archiving, and distribution of moderate-resolution multispectral imagery affording global, synoptic, and repetitive coverage of the earth's land surface at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. It includes a review of the ground network, including a block diagram of the ground network elements (GNE) and a review of the RF design and testing. Also included is a listing of the lessons learned.

Gal-Edd, Jonathan↗
NASA NTRS2017

Gaining the most utility from our geospace observational system: Network analysis of total electron content as a means to understand space weather to the point of prediction

We present the first network analysis of interplanetary magnetic field (IMF) clock angle dependent, high-latitude, hemispheric-specific total electron content (TEC) data. We examine network parameters to describe spatio-temporal correlations in the TEC data for January 2016. We find that significant network structure exists distinguishing the dayside and nightside ionosphere, and specific features in the high-latitudes (cusp/ionospheric footpoints of magnetospheric boundary layers, polar cap, and auroral zone), and that these features vary with IMF clock angle. In this brief summary paper, we provide proof of concept results and identify important areas of future research, providing a basis for the discussion of network analysis and machine learning approaches for space weather applications.

Malik, Nishant↗
NASA NTRS1993

NASDA satellite mission operation system and operations

NASDA has recently developed a new tracking and control system as a basis for future satellite mission operation. It is named type-I Space Operations and Data Systems (type-I SODS). The software of this system is separated into three parts: operation and control system, network system, and support and information system. The operation control system treats telemetry and command operations. The network system controls the communication line and ground station equipments to connect the satellite and the operation control system. The support and information system provides to other systems necessary information. JERS-1 which was launched in February of this year is the first satellite operated by type-l SODS. We explain the architecture and operation methods of this system using JERS-1 mission operations.

Yamaya, Kousaku↗
NASA NTRS1998

Scalable Hierarchical Network Management System for Displaying Network Information in Three Dimensions

A network management system has SNMP agents distributed at one or more sites, an input output module at each site, and a server module located at a selected site for communicating with input output modules, each of which is configured for both SNMP and HNMP communications. The server module is configured exclusively for HNMP communications, and it communicates with each input output module according to the HNMP. Non-iconified, informationally complete views are provided of network elements to aid in network management.

George, Jude↗
NASA NTRS1993

A programming environment for distributed complex computing. An overview of the Framework for Interdisciplinary Design Optimization (FIDO) project. NASA Langley TOPS exhibit H120b

The Framework for Interdisciplinary Design Optimization (FIDO) is a general programming environment for automating the distribution of complex computing tasks over a networked system of heterogeneous computers. For example, instead of manually passing a complex design problem between its diverse specialty disciplines, the FIDO system provides for automatic interactions between the discipline tasks and facilitates their communications. The FIDO system networks all the computers involved into a distributed heterogeneous computing system, so they have access to centralized data and can work on their parts of the total computation simultaneously in parallel whenever possible. Thus, each computational task can be done by the most appropriate computer. Results can be viewed as they are produced and variables changed manually for steering the process. The software is modular in order to ease migration to new problems: different codes can be substituted for each of the current code modules with little or no effect on the others. The potential for commercial use of FIDO rests in the capability it provides for automatically coordinating diverse computations on a networked system of workstations and computers. For example, FIDO could provide the coordination required for the design of vehicles or electronics or for modeling complex systems.

Townsend, James C.↗
NASA NTRS1990

Research summary, January 1989 - June 1990

The Research Institute for Advanced Computer Science (RIACS) was established at NASA ARC in June of 1983. RIACS is privately operated by the Universities Space Research Association (USRA), a consortium of 62 universities with graduate programs in the aerospace sciences, under a Cooperative Agreement with NASA. RIACS serves as the representative of the USRA universities at ARC. This document reports our activities and accomplishments for the period 1 Jan. 1989 - 30 Jun. 1990. The following topics are covered: learning systems, networked systems, and parallel systems.

Source record↗
NASA NTRS1966

Apollo systems

Network data systems to support Apollo project

Data control system↗
NASA NTRS2013

Applying Model Based Systems Engineering to NASA's Space Communications Networks

System engineering practices for complex systems and networks now require that requirement, architecture, and concept of operations product development teams, simultaneously harmonize their activities to provide timely, useful and cost-effective products. When dealing with complex systems of systems, traditional systems engineering methodology quickly falls short of achieving project objectives. This approach is encumbered by the use of a number of disparate hardware and software tools, spreadsheets and documents to grasp the concept of the network design and operation. In case of NASA's space communication networks, since the networks are geographically distributed, and so are its subject matter experts, the team is challenged to create a common language and tools to produce its products. Using Model Based Systems Engineering methods and tools allows for a unified representation of the system in a model that enables a highly related level of detail. To date, Program System Engineering (PSE) team has been able to model each network from their top-level operational activities and system functions down to the atomic level through relational modeling decomposition. These models allow for a better understanding of the relationships between NASA's stakeholders, internal organizations, and impacts to all related entities due to integration and sustainment of existing systems. Understanding the existing systems is essential to accurate and detailed study of integration options being considered. In this paper, we identify the challenges the PSE team faced in its quest to unify complex legacy space communications networks and their operational processes. We describe the initial approaches undertaken and the evolution toward model based system engineering applied to produce Space Communication and Navigation (SCaN) PSE products. We will demonstrate the practice of Model Based System Engineering applied to integrating space communication networks and the summary of its results and impact. We will highlight the insights gained by applying the Model Based System Engineering and provide recommendations for its applications and improvements.

Bhasin, Kul↗
NASA NTRS1985

Network operating system focus technology

An activity structured to provide specific design requirements and specifications for the Space Station Data Management System (DMS) Network Operating System (NOS) is outlined. Examples are given of the types of supporting studies and implementation tasks presently underway to realize a DMS test bed capability to develop hands-on understanding of NOS requirements as driven by actual subsystem test beds participating in the overall Johnson Space Center test bed program. Classical operating system elements and principal NOS functions are listed.

Source record↗
NASA NTRS1993

NASDA knowledge-based network planning system

One of the SODS (space operation and data system) sub-systems, NP (network planning) was the first expert system used by NASDA (national space development agency of Japan) for tracking and control of satellite. The major responsibilities of the NP system are: first, the allocation of network and satellite control resources and, second, the generation of the network operation plan data (NOP) used in automated control of the stations and control center facilities. Up to now, the first task of network resource scheduling was done by network operators. NP system automatically generates schedules using its knowledge base, which contains information on satellite orbits, station availability, which computer is dedicated to which satellite, and how many stations must be available for a particular satellite pass or a certain time period. The NP system is introduced.

Yamaya, K.↗
NASA NTRS1995

Performance Modeling of Network-Attached Storage Device Based Hierarchical Mass Storage Systems

Network attached storage devices improve I/O performance by separating control and data paths and eliminating host intervention during the data transfer phase. Devices are attached to both a high speed network for data transfer and to a slower network for control messages. Hierarchical mass storage systems use disks to cache the most recently used files and a combination of robotic and manually mounted tapes to store the bulk of the files in the file system. This paper shows how queuing network models can be used to assess the performance of hierarchical mass storage systems that use network attached storage devices as opposed to host attached storage devices. Simulation was used to validate the model. The analytic model presented here can be used, among other things, to evaluate the protocols involved in 1/0 over network attached devices.

Menasce, Daniel A.↗
NASA NTRS1993

Network Queuing System, Version 2.0

Network Queuing System (NQS) computer program is versatile batch- and device-queuing facility for single UNIX computer or group of computers in network. User invokes NQS collection of user-space programs to move batch and device jobs freely among different computers in network. Provides facilities for remote queuing, request routing, remote status, queue-status controls, batch-request resource quota limits, and remote output return. Revision of NQS provides for creation, deletion, addition, and setting of complexes aiding in limiting number of requests handled at one time. Also has improved device-oriented queues along with some revision of displays. Written in C language.

Walter, Howard↗
NASA NTRS2018

Spreading Sequence System for Full Connectivity Relay Network

Fully connected uplink and downlink fully connected relay network systems using pseudo-noise spreading and despreading sequences subjected to maximizing the signal-to-interference-plus-noise ratio. The relay network systems comprise one or more transmitting units, relays, and receiving units connected via a communication network. The transmitting units, relays, and receiving units each may include a computer for performing the methods and steps described herein and transceivers for transmitting and/or receiving signals. The computer encodes and/or decodes communication signals via optimum adaptive PN sequences found by employing Cholesky decompositions and singular value decompositions (SVD). The PN sequences employ channel state information (CSI) to more effectively and more securely computing the optimal sequences.

Kwon, Hyuck M.↗