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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Mesh Network Architecture for Enabling Inter-Spacecraft Communication

To enable communication between spacecraft operating in a formation or small constellation, a mesh network architecture was developed and tested using a time division multiple access (TDMA) communication scheme. The network is designed to allow for the exchange of telemetry and other data between spacecraft to enable collaboration between small spacecraft. The system uses a peer-to-peer topology with no central router, so that it does not have a single point of failure. The mesh network is dynamically configurable to allow for addition and subtraction of new spacecraft into the communication network. Flight testing was performed using an unmanned aerial system (UAS) formation acting as a spacecraft analogue and providing a stressing environment to prove mesh network performance. The mesh network was primarily devised to provide low latency, high frequency communication but is flexible and can also be configured to provide higher bandwidth for applications desiring high data throughput. The network includes a relay functionality that extends the maximum range between spacecraft in the network by relaying data from node to node. The mesh network control is implemented completely in software making it hardware agnostic, thereby allowing it to function with a wide variety of existing radios and computing platforms..

Becker, Christopher↗
NASA NTRS1987

The performance of multicomputer interconnection networks

The interdependency of nodes and multicomputer interconnection networks is examined using simple calculations based on the asymptotic properties of queueing networks. Methods are described for choosing interconnection networks that fit individual classes of applications. It is also shown how analytic models can be extended to benchmark existing interconnection networks.

Reed, Daniel A.↗
NASA NTRS1992

Efficient hierarchical interconnection for multiprocessor systems

The authors present a novel approach to the design of a class of hierarchical interconnection networks for multiprocessor systems. This approach, based on an architecture providing separate networks for each level, gives a general and flexible way to construct efficient hierarchical networks. The performance and cost-effectiveness of the resulting networks are analyzed and compared in detail, using both unbuffered and buffered network models. It is shown that, if the design parameters are determined based on the degree of locality, the cost-effectiveness of a hierarchical network can be significantly improved. In addition, the authors investigate how to construct a cost-effectiveness hierarchical network by determining appropriate design parameters. Two associated algorithms are developed for this purpose.

Wei, Sizheng↗
NASA NTRS1995

Positron annihilation spectroscopic study of high performance semi-interpenetrating network polyimids

Semi-interpenetrating (S-IPN) network polyimids were made from different proportions of LaRC RP46 (a thermosetpolyimid) and LaRC BDTA-ODA (a thermoplastic polyimid). The ultimate goal of this networking is to improve the mechanical properties of the thermoset polyimid. Positron lifetime study was made to calculate lifetime based on second component of the life time spectra and the free volume & microvoid size. All these properties tend to decrease steadily with increasing thermoset content except at the 50 percent thermoset level where these properties show sudden drop. This result contradicts with the initial expectation that the blend properties should change gradually if it were a solid solution of thermoset (TSP) and thermoplastic (TPP) components. Thermal analyses (TMA, DSC, DMA & TGA) were run to complement the positron life time studies. The TMA and DSC studies confirm the contradiction mentioned above. Further experimentation with S-IPN polymers made at TSP/TTP content around 50/50 level are being conducted to explain this anomaly. Scanning electron microscope study of the S-IPN polyimid samples is under way in order to detect morphological differences which might help explain the phenomenon mentioned above.

Ray, Asit K.↗
NASA NTRS2012

Application of Multihop Relay for Performance Enhancement of AeroMACS Networks

A new transmission technology, based on IEEE 802.16-2009 (WiMAX), is currently being developed for airport surface communications. A C-band spectrum allocation at 5091 to 5150 MHz has been created by International Telecommunications Union (ITU) to carry this application. The proposed technology, known as AeroMACS, will be used to support fixed and mobile ground to ground applications and services. This article proposes and demonstrates that IEEE 802.16j-amendment-based WiMAX is most feasible for AeroMACS applications. This amendment introduces multihop relay as an optional deployment that may be used to provide additional coverage and/or enhance the capacity of the network. Particular airport surface radio coverage situations for which IEEE 802.16-2009-WiMAX provides resolutions that are inefficient, costly, or excessively power consuming are discussed. In all these cases, it is argued that 16j technology offers a much better alternative. A major concern about deployment of AeroMACS is interference to co-allocated applications such as the Mobile Satellite Service (MSS) feeder link. Our initial simulation results suggest that no additional interference to MSS feeder link is caused by deployment of IEEE 802.16j-based AeroMACS.

Kamali, Behnam↗
NASA NTRS2012

Application of Multihop Relay for Performance Enhancement of AeroMACS Networks

A new transmission technology, based on IEEE 802.16-2009 (WiMAX), is currently being developed for airport surface communications. A C-band spectrum allocation at 5091-5150 MHz has been created by ITU to carry this application. The proposed technology, known as AeroMACS, will be used to support fixed and mobile ground to ground applications and services. This article proposes and demonstrates that IEEE 802.16j-amendment-based WiMAX is most feasible for AeroMACS applications. This amendment introduces multihop relay as an optional deployment that may be used to provide additional coverage and/or enhance the capacity of the network. Particular airport surface radio coverage situations for which IEEE 802.16-2009-WiMAX provides resolutions that are inefficient, costly, or excessively power consuming are discussed. In all these cases, it is argued that 16j technology offers a much better alternative. A major concern about deployment of AeroMACS is interference to co-allocated applications such as the Mobile Satellite Service (MSS) feeder link. Our initial simulation results suggest that no additional interference to MSS feeder link is caused by deployment of IEEE 802.16j-based AeroMACS.

Kamali, Behnam↗
NASA NTRS2015

Converter Compressor Building, SWMU 089, Hot Spot Areas 1, 2, and 5 Operations, Maintenance, and Monitoring Report, Kennedy Space Center, Florida

This Operations, Maintenance, and Monitoring Report (OMMR) presents the findings, observations, and results from operation of the air sparging (AS) interim measure (IM) for Hot Spot (HS) Areas 1, 2, and 5 at the Converter Compressor Building (CCB) located at Kennedy Space Center (KSC), Florida. The objective of the IM at CCB HS Areas 1, 2, and 5 is to decrease concentrations of volatile organic compounds (VOCs) in groundwater in the treatment zones via AS to levels that will enable a transition to a monitored natural attenuation (MNA) phase. This OMMR presents system operations and maintenance (O&M) information and performance monitoring results since full-scale O&M began in June 2014 (2 months after initial system startup in April 2014), including quarterly performance monitoring events in July and October 2014 and January and May 2015. Based on the results to date, the AS system is operating as designed and is meeting the performance criteria and IM objective. The performance monitoring network is adequately constructed for assessment of IM performance at CCB HS Areas 1, 2, and 5. At the March 2014 KSC Remediation Team (KSCRT) Meeting, team consensus was reached for the design prepared for expansion of the system to treat the HS 4 area, and at the November 2014 KSCRT Meeting, team consensus was reached that HS 3 was adequately delineated horizontally and vertically and for selection of AS for the remedial approach for HS 3. At the July 2015 KSCRT meeting, team consensus was reached to continue IM operations in all zones until HSs 3 and 4 is operational, once HS 3 and 4 zones are operational discontinue operations in HS 1, 2, and 5 zones where concentrations are less than GCTLs to observe whether rebounding conditions occur. Team consensus was also reached to continue quarterly performance monitoring to determine whether operational zones achieve GCTLs and to continue annual IGWM of CCB-MW0012, CCBMW0013, and CCB-MW0056, located south of the treatment area. The next performance monitoring event is scheduled for July 2015.

Converter Compressor Building↗
NASA NTRS2012

Micro/Nanosatellite Mars Network for Global Lower Atmosphere Characterization

To address multiple key challenge areas for robotic exploration of Mars, to achieve scientific goals and reduce risk for future human missions, a micro/nanosatellite constellation for lower atmosphere characterization is proposed. A microsatellite design is discussed that can operate (1) in tandem with another microsat or (2) as a "mother-ship" to deploy a network of nanosatellites (CubeSats). Either configuration of the network would perform radio occultation-based atmospheric measurements. Advantages of the proposed network are low development cost based on an existing microsatellite bus, and proven performance of the bus to date. Continued efforts in miniaturization of instruments are needed to fully enable the mother-ship/nanosat version of the proposed network.

Tinker, Mike L.↗
NASA NTRS2020

Improving Trust in Deep Neural Networks with Nearest Neighbors

Deep neural networks are used increasingly for perception and decision-making in UAVs. For example, they can be used to recognize objects from images and decide what actions the vehicle should take. While deep neural networks can perform very well at complex tasks, their decisions may be unintuitive to a human operator. When a human disagrees with a neural network prediction, due to the black box nature of deep neural networks, it can be unclear whether the system knows something the human does not or whether the system is malfunctioning. This uncertainty is problematic when it comes to ensuring safety. As a result, it is important to develop technologies for explaining neural network decisions for trust and safety. This paper explores a modification to the deep neural network classification layer to produce both a predicted label and an explanation to support its prediction. Specifically, at test time, we replace the final output layer of the neural network classifier by a k-nearest neighbor classifier. The nearest neighbor classifier produces 1) a predicted label through voting and 2) the nearest neighbors involved in the prediction, which represent the most similar examples from the training dataset. Because prediction and explanation are derived from the same underlying process, this approach guarantees that the explanations are always relevant to the predictions. We demonstrate the approach on a convolutional neural network for a UAV image classification task. We perform experiments using a forest trail image dataset and show empirically that the hybrid classifier can produce intuitive explanations without loss of predictive performance compared to the original neural network. We also show how the approach can be used to help identify potential issues in the network and training process.

Lee, Ritchie↗
NASA NTRS1968

GERT simulation program for GERT network analysis

GERT Simulation Program simulates GERT networks to obtain statistics on specified nodes of the network. It performs sampling experiments to determine which branches of the network are taken and how long it takes to traverse a branch of the network.

Alan, A.↗
NASA NTRS2000

Modeling and Performance Simulation of the Mass Storage Network Environment

This paper describes the application of modeling and simulation in evaluating and predicting the performance of the mass storage network environment. Network traffic is generated to mimic the realistic pattern of file transfer, electronic mail, and web browsing. The behavior and performance of the mass storage network and a typical client-server Local Area Network (LAN) are investigated by modeling and simulation. Performance characteristics in throughput and delay demonstrate the important role of modeling and simulation in network engineering and capacity planning.

Kim, Chan M.↗
NASA NTRS1978

Deep Space Network to Viking Orbiter telecommunications performance during the Viking extended mission, November 1976 - February 1978

The telecommunications performance during the Viking extended mission, starting with the completion of the first superior conjunction in November 1976 and ending with the jettison of the VO-2 aft bioshield early in March 1978 is discussed. Viking Orbiter activities and problems, the ground system activities and problems, radio science activities, and communication link performance are included. The substantial involvement of the Deep Space Network and the coordination of their telecommunication planners with Viking Project telecommunications analysts in the planning and execution of complex Viking Orbiter sequences are discussed.

Taylor, F. H. J.↗
NASA NTRS1993

Detection of bearing failure in mechanical devices using neural networks

We present a novel time-domain method for the detection of faulty bearings that has direct applicability to monitoring the health of the turbo pumps on the Space Shuttle Main Engine. A feed-forward neural network was trained to detect modelled roller bearing faults on the basis of the periodicity of impact pulse trains. The network's performance was dependent upon the number of pulses in the network's input window and the signal-to-noise ratio of the input signal. To test the model's validity, we fit the model's parameters to an actual vibration signal generated by a faulty roller element bearing and applied the network trained on this model to detect faults in actual vibration data. When this network was tested on the actual vibration data, it correctly identified the vibration signal as a fault condition 76 percent of the time.

Burne, Richard A.↗
NASA NTRS2005

Hot Chips and Hot Interconnects for High End Computing Systems

I will discuss several processors: 1. The Cray proprietary processor used in the Cray X1; 2. The IBM Power 3 and Power 4 used in an IBM SP 3 and IBM SP 4 systems; 3. The Intel Itanium and Xeon, used in the SGI Altix systems and clusters respectively; 4. IBM System-on-a-Chip used in IBM BlueGene/L; 5. HP Alpha EV68 processor used in DOE ASCI Q cluster; 6. SPARC64 V processor, which is used in the Fujitsu PRIMEPOWER HPC2500; 7. An NEC proprietary processor, which is used in NEC SX-6/7; 8. Power 4+ processor, which is used in Hitachi SR11000; 9. NEC proprietary processor, which is used in Earth Simulator. The IBM POWER5 and Red Storm Computing Systems will also be discussed. The architectures of these processors will first be presented, followed by interconnection networks and a description of high-end computer systems based on these processors and networks. The performance of various hardware/programming model combinations will then be compared, based on latest NAS Parallel Benchmark results (MPI, OpenMP/HPF and hybrid (MPI + OpenMP). The tutorial will conclude with a discussion of general trends in the field of high performance computing, (quantum computing, DNA computing, cellular engineering, and neural networks).

Saini, Subhash↗
NASA NTRS2014

Network Monitor and Control of Disruption-Tolerant Networks

For nearly a decade, NASA and many researchers in the international community have been developing Internet-like protocols that allow for automated network operations in networks where the individual links between nodes are only sporadically connected. A family of Disruption-Tolerant Networking (DTN) protocols has been developed, and many are reaching CCSDS Blue Book status. A NASA version of DTN known as the Interplanetary Overlay Network (ION) has been flight-tested on the EPOXI spacecraft and ION is currently being tested on the International Space Station. Experience has shown that in order for a DTN service-provider to set up a large scale multi-node network, a number of network monitor and control technologies need to be fielded as well as the basic DTN protocols. The NASA DTN program is developing a standardized means of querying a DTN node to ascertain its operational status, known as the DTN Management Protocol (DTNMP), and the program has developed some prototypes of DTNMP software. While DTNMP is a necessary component, it is not sufficient to accomplish Network Monitor and Control of a DTN network. JPL is developing a suite of tools that provide for network visualization, performance monitoring and ION node control software. This suite of network monitor and control tools complements the GSFC and APL-developed DTN MP software, and the combined package can form the basis for flight operations using DTN.

network monitor↗
NASA NTRS1993

Neural networks for atmospheric retrievals

We use neural networks to perform retrievals of temperature and water fractions from simulated clear air radiances for the Atmospheric Infrared Sounder (AIRS). Neural networks allow us to make effective use of the large AIRS channel set, and give good performance with noisy input. We retrieve surface temperature, air temperature at 64 distinct pressure levels, and water fractions at 50 distinct pressure levels. Using 728 temperature and surface sensitive channels, the RMS error for temperature retrievals with 0.2K input noise is 1.2K. Using 586 water and temperature sensitive channels, the mean error with 0.2K input noise is 16 percent. Our implementation of backpropagation training for neural networks on the 16,000-processor MasPar MP-1 runs at a rate of 90 million weight updates per second, and allows us to train large networks in a reasonable amount of time. Once trained, the network can be used to perform retrievals quickly on a workstation of moderate power.

Motteler, Howard E.↗
NASA NTRS1988

Performance evaluation of NASA/KSC CAD/CAE graphics local area network

This study had as an objective the performance evaluation of the existing CAD/CAE graphics network at NASA/KSC. This evaluation will also aid in projecting planned expansions, such as the Space Station project on the existing CAD/CAE network. The objectives were achieved by collecting packet traffic on the various integrated sub-networks. This included items, such as total number of packets on the various subnetworks, source/destination of packets, percent utilization of network capacity, peak traffic rates, and packet size distribution. The NASA/KSC LAN was stressed to determine the useable bandwidth of the Ethernet network and an average design station workload was used to project the increased traffic on the existing network and the planned T1 link. This performance evaluation of the network will aid the NASA/KSC network managers in planning for the integration of future workload requirements into the existing network.

Zobrist, George↗