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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 307 records · Page 17

All sources NASA NTRS DOE OSTI

NASA NTRS1992

Photonics and other approaches to high speed communications

Our research group of 4 faculty and about 10-15 graduate students was actively involved (as a group) in the development of computer communication networks for the last five years. Many of its individuals have been involved in related research for a much longer period. The overall research goal is to extend network performance to higher data rates, to improve protocol performance at most ISO layers and to improve network operational performance. We briefly state our research goals, then discuss the research accomplishments and direct your attention to attached and/or published papers which cover the following topics: scalable parallel communications; high performance interconnection between high data rate networks; and a simple, effective media access protocol system for integrated, high data rate networks.

Maly, Kurt↗

NASA NTRS1984

Considerations on command and response language features for a network of heterogeneous autonomous computers

The design of a uniform command language to be used in a local area network of heterogeneous, autonomous nodes is considered. After examining the major characteristics of such a network, and after considering the profile of a scientist using the computers on the net as an investigative aid, a set of reasonable requirements for the command language are derived. Taking into account the possible inefficiencies in implementing a guest-layered network operating system and command language on a heterogeneous net, the authors examine command language naming, process/procedure invocation, parameter acquisition, help and response facilities, and other features found in single-node command languages, and conclude that some features may extend simply to the network case, others extend after some restrictions are imposed, and still others require modifications. In addition, it is noted that some requirements considered reasonable (user accounting reports, for example) demand further study before they can be efficiently implemented on a network of the sort described.

Engelberg, N.↗

DOE OSTI2020

Toward lower-diameter large-scale HPC and data center networks with co-packaged optics

We investigate the advantages of using co-packaged optics for building low-diameter, large-scale high-performance computing (HPC) and data center networks. The increased escape bandwidth offered by co-packaged optics can enable high-radix switch implementations of more than 150 switch ports, which can be combined with data rates of up to 400 Gb/s per port. From the network architecture perspective, the key benefits of using co-packaged optics in future fat-tree networks include (a) the ability to implement large-scale topologies of > <#comment/> 11 , 000 end points by eliminating the need for a third switching layer and (b) the ability to provide up to 4 × <#comment/> higher bisection bandwidth compared to existing solutions, reducing at the same time the number of required switch application-specific integrated circuits by > <#comment/> 80 % <#comment/> . From the network operation perspective, both reduced energy consumption and lower packet delays can be achieved since fewer hops are required; i.e., packets need to traverse fewer serializer/deserializer lanes and fewer switch buffers, which reduces the probability of contending with other packets and improves the tolerance of network congestion. The performance of the proposed architecture is evaluated via discrete-event simulations for a wide range of representative HPC synthetic-traffic cases that include both hotspot and non-hotspot scenarios. The simulation results suggest that co-packaged optics form a promising solution to keep up with bandwidth scaling in future networks, while the reduced number of switching layers can lead to significant mean packet delay improvements that start from 30% and reach up to 74% for high-load conditions.

Maniotis, Pavlos (ORCID:0000000244905253)↗

DOE OSTI2022

Resolving extreme jet substructure

We study the effectiveness of theoretically-motivated high-level jet observables in the extreme context of jets with a large number of hard sub-jets (up to N = 8). Previous studies indicate that high-level observables are powerful, interpretable tools to probe jet substructure for N ≤ 3 hard sub-jets, but that deep neural networks trained on low-level jet constituents match or slightly exceed their performance. We extend this work for up to N = 8 hard sub-jets, using deep particle-flow networks (PFNs) and Transformer based networks to estimate a loose upper bound on the classification performance. A fully-connected neural network operating on a standard set of high-level jet observables, 135 N-subjetiness observables and jet mass, reach classification accuracy of 86.90%, but fall short of the PFN and Transformer models, which reach classification accuracies of 89.19% and 91.27% respectively, suggesting that the constituent networks utilize information not captured by the set of high-level observables. We then identify additional high-level observables which are able to narrow this gap, and utilize LASSO regularization for feature selection to identify and rank the most relevant observables and provide further insights into the learning strategies used by the constituent-based neural networks. The final model contains only 31 high-level observables and is able to match the performance of the PFN and approximate the performance of the Transformer model to within 2%.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Synergistic learning with multi-task DeepONet for efficient PDE problem solving

Multi-task learning (MTL) is an inductive transfer mechanism designed to leverage useful information from multiple tasks to improve generalization performance compared to single-task learning. It has been extensively explored in traditional machine learning to address issues such as data sparsity and overfitting in neural networks. In this work, we apply MTL to problems in science and engineering governed by partial differential equations (PDEs). However, implementing MTL in this context is complex, as it requires task-specific modifications to accommodate various scenarios representing different physical processes. To this end, we present a multi-task deep operator network (MT-DeepONet) to learn solutions across various functional forms of source terms in a PDE and multiple geometries in a single concurrent training session. We introduce modifications in the branch network of the vanilla DeepONet to account for various functional forms of a parameterized coefficient in a PDE. Additionally, we handle parameterized geometries by introducing a binary mask in the branch network and incorporating it into the loss term to improve convergence and generalization to new geometry tasks. Our approach is demonstrated on three benchmark problems: (1) learning different functional forms of the source term in the Fisher equation; (2) learning multiple geometries in a 2D Darcy Flow problem and showcasing better transfer learning capabilities to new geometries; and (3) learning 3D parameterized geometries for a heat transfer problem and demonstrate the ability to predict on new but similar geometries. Finally, our MT-DeepONet framework offers a novel approach to solving PDE problems in engineering and science under a unified umbrella based on synergistic learning that reduces the overall training cost for neural operators.

42 ENGINEERING↗

NASA NTRS2006

CCSDS SLE Service Management: Real-World Use Cases

The purpose of this paper is to illustrate how the standard SLE-SM services can be applied to the operations of current TT&C providers. It begins with a brief overview of the scope and operating environment of the SLE-SM services, then describes several use cases in which SLE-SM services can be applied to existing operational situations. The paper also addresses how SLE-SM services can be adopted in an evolutionary fashion. The paper concludes with a brief identification of additions to SLE-SM that are under consideration to make SLE-SM applicable to an even broader range of network operations concepts, policies, and procedures.

Consultative Committee for Space Data Systems (CCS↗

NASA NTRS2007

The Earth Based Ground Stations Element of the Lunar Program

The Lunar Architecture Team (LAT) is responsible for developing a concept for building and supporting a lunar outpost with several exploration capabilities such as rovers, colonization, and observatories. The lunar outpost is planned to be located at the Moon's South Pole. The LAT Communications and Navigation Team (C&N) is responsible for defining the network infrastructure to support the lunar outpost. The following elements are needed to support lunar outpost activities: A Lunar surface network based on industry standard wireless 802.xx protocols, relay satellites positioned 180 degrees apart to provide South Pole coverage for the half of the lunar 28-day orbit that is obscured from Earth view, earth-based ground stations deployed at geographical locations 120 degrees apart. This paper will focus on the Earth ground stations of the lunar architecture. Two types of ground station networks are discussed. One provides Direct to Earth (DTE) support to lunar users using Kaband 23/26Giga-Hertz (GHz) communication frequencies. The second supports the Lunar Relay Satellite (LRS) that will be using Ka-band 40/37GHz (Q-band). This paper will discuss strategies to provide a robust operational network in support of various lunar missions and trades of building new antennas at non-NASA facilities, to improve coverage and provide site diversification for handling rain attenuation.

Gal-Edd, Jonathan↗

NASA NTRS2011

Camp Blanding Lightning Mapping Array

A seven station, short base-line Lightning Mapping Array was installed at the Camp Blanding International Center for Lightning Research and Testing (ICLRT) during April 2011. This network will support science investigations of Terrestrial Gamma-Ray Flashes (TGFs) and lightning initiation using rocket triggered lightning at the ICLRT. The network operations and data processing will be carried out through a close collaboration between several organizations, including the NASA Marshall Space Flight Center, University of Alabama in Huntsville, University of Florida, and New Mexico Tech. The deployment was sponsored by the Defense Advanced Research Projects Agency (DARPA). The network does not have real-time data dissemination. Description, status and plans will be discussed.

Blakeslee,Richard↗

NASA NTRS1988

Terminal attractors for addressable memory in neural networks

A new type of attractors - terminal attractors - for an addressable memory in neural networks operating in continuous time is introduced. These attractors represent singular solutions of the dynamical system. They intersect (or envelope) the families of regular solutions while each regular solution approaches the terminal attractor in a finite time period. It is shown that terminal attractors can be incorporated into neural networks such that any desired set of these attractors with prescribed basins is provided by an appropriate selection of the weight matrix.

Zak, Michail↗

NASA NTRS1994

Using the Global GPS Network and Other Satellite Data to Monitor Ionospheric Total Electron Content

A globally distributed network of dual-frequency global positioning system (GPS) receivers is the primary source of data used to measure ionospheric total electron content (TEC) on global scales. Maps of TEC useful for calibrating propagation delays, or monitoring the solar-terrestrial environment, can be produced using this continuously operating network. The maps can also form the basis of a TEC calibration service for users around the world. Potential users may include single-frequency satellite altimetry missions, satellite tracking stations, and astronomical observatories.

satellite altimetry↗

DOE OSTI2024

RandONets: Shallow networks with random projections for learning linear and nonlinear operators

Deep neural networks have been extensively used for the solution of both the forward and the inverse problem for dynamical systems. However, their implementation necessitates optimizing a high-dimensional space of parameters and hyperparameters. This fact, along with the requirement of substantial computational resources, pose a barrier to achieving high numerical accuracy, but also interpretability. Here, to address the above challenges, we present Random Projection-based Operator Networks (RandONets): shallow networks with random projections and tailor-made numerical analysis methods that learn accurately and fast linear and nonlinear operators. Building on previous works, we prove that RandOnets are universal approximators of linear and nonlinear operators. Due to their simplicity, RandONets provide a one-step transformation of the input space, facilitating interpretability. For the evaluation of their performance, we focus on operators of PDEs. We show, that RandONets outperform by several orders of magnitude, both in terms of numerical approximation accuracy and computational cost, the “vanilla” DeepONets. Hence, we believe that our method will trigger further developments in the field of scientific machine learning, for the development of new ‘’light”schemes that will provide high accuracy while reducing dramatically the computational cost. A MATLAB toolbox for RandONets, including demos, is available on GitHub at https://github.com/GianlucaFabiani/RandONets.

Interpretable machine learning↗

NASA NTRS1989

JPL reuse program

The goal of the JPL reuse activity is to develop a quantitative understanding of the factors which encourage or inhibit software reuse, and of productivity improvements achievable through reuse. The primary activity is the measurement of parameters relevant to reuse in the environment of actual projects. The program has three objectives: (1) to develop a model to allow assessment of competing reuse techniques, (2) to extend reuse from the unit to the sub-system level, and (3) to expand from specific applications to a broader application domain. Application domains, which apply to all interplanetary projects, include Mission Operations, Science Information Systems, Flight Software, and Simulations. The program is targeting all phases and activities of the life cycle and a full range of software products. The approach will be both experimental (observe, hypothesize and evaluate) and constructive (introduce new tools and techniques). The primary target projects are Deep Space Network activities - the Ground Facilities facility upgrade, the Network Operations Control Center upgrade, and the Signal Processing Center. This is the first group of closely related projects being done in Ada at JPL. A reuse base will be developed initially by classifying potentially reusable components from one project; it will be used and expanded with additional projects.

Brown, James W.↗

NASA NTRS1973

Satellite-tracking and earth-dynamics research programs

The following activities in Smithsonian Astrophysical Observatory's (SAO) earth-dynamics programs are covered: (1) satellite-tracking network operations; (2) satellite geodesy and geophysics programs; (3) atmospheric research. Approximately 46,000 successful range measurements were acquired by the SAO laser stations in Peru, South Africa, Brazil, and Arizona. The Peole satellite-tracking campaign conducted in conjunction with the Centre National d'Etudes Spatiales was completed in August 1973. The SAO network obtained 4482 validated returns of 310 arcs of Peole. These data are of particular value for obtaining more accurate gravity-field and zonal-harmonics coefficients.

Weiffenbach, G. C.↗

NASA NTRS1993

Power attenuation characteristics as switch-over criterion in personal satellite mobile communications

A third generation mobile system intends to support communications in all environments (i.e., outdoors, indoors at home or office and when moving). This system will integrate services that are now available in architectures such as cellular, cordless, mobile data networks, paging, including satellite services to rural areas. One way through which service integration will be made possible is by supporting a hierarchical cellular structure based on umbrella cells, macro cells, micro and pico cells. In this type of structure, satellites are part of the giant umbrella cells allowing continuous global coverage, the other cells belong to cities, neighborhoods, and buildings respectively. This does not necessarily imply that network operation of terrestrial and satellite segments interconnect to enable roaming and spectrum sharing. However, the cell concept does imply hand-off between different cell types, which may involve change of frequency. Within this propsective, the present work uses power attenuation characteristics to determine a dynamic criterion that allows smooth transition from space to terrestrial networks. The analysis includes a hybrid channel that combines Rician, Raleigh and Log Normal fading characteristics.

Castro, Jonathan P.↗

DOE OSTI2024

First-generation college student forges ahead, now key to Lab's mission

Fatima Woody was just 17 and a student at Pojoaque Valley High School when she first started her career as a Los Alamos Neutron Science Center receptionist. Now she's in a crucial role that keeps plutonium pit production and other mission processes operating with as little interruption as possible. Over nearly four decades, Fatima has gradually advanced from her initial positions as a receptionist and administrative secretary to become a computer technician, then a computer system professional who specializes in project management. Today, she coordinates the workflow for nearly two dozen deployed information technology technicians who keep the computer systems and networks operating at the high-tech complex that houses the Lab's Plutonium Facility.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1989

Terminal attractors in neural networks

A new type of attractor (terminal attractors) for content-addressable memory, associative memory, and pattern recognition in artificial neural networks operating in continuous time is introduced. The idea of a terminal attractor is based upon a violation of the Lipschitz condition at a fixed point. As a result, the fixed point becomes a singular solution which envelopes the family of regular solutions, while each regular solution approaches such an attractor in finite time. It will be shown that terminal attractors can be incorporated into neural networks such that any desired set of these attractors with prescribed basins is provided by an appropriate selection of the synaptic weights. The applications of terminal attractors for content-addressable and associative memories, pattern recognition, self-organization, and for dynamical training are illustrated.

Zak, Michail↗

NASA NTRSDate not supplied

Optimizing Altitude Sampling and Sensitivity with the Goldstone Orbital Debris Radar

The NASA Orbital Debris Program Office (ODPO) has used the Goldstone Orbital Debris Radar (Goldstone) since 1993 to characterize orbital debris (OD) in low Earth orbit too small to be tracked by the U.S. Space Surveillance Network. Operated by NASA’s Jet Propulsion Laboratory, Goldstone can measure OD as small as 3 mm at 1000 km altitude and lower. Goldstone is a bistatic radar that for 25 years used Deep Space Station (DSS)-14 as a transmitter and DSS-15 as a receiver. In early 2018, DSS-15 was decommissioned and replaced with DSS-25 (and occasionally DSS-26) of the Deep Space Network Apollo Cluster. The increased baseline between DSS-14 and DSS-25 significantly reduced the instantaneous altitude coverage of the bistatic beam overlap. Initial measurements in 2018 were focused around 800 km, which has approximately the highest flux of sub-centimeter debris. In 2019, DSS-14 was offline for maintenance, and the ODPO designed an annual survey observation plan to efficiently sample altitudes from 700 km to 1000 km, since many NASA satellites fly in this range. This paper discusses the observation plan, including the development of the pointings, a refinement of the altitudes of interest, and an analysis of the effects of random pointing errors on beam overlap. Additionally, results from measurements taken in 2020 and 2021 are presented, showing that not only is the observation plan effective at sampling 700 km to 1000 km altitude, but it is also producing the most sensitive terrestrial radar measurements at these altitudes to date.

James Murray↗

NASA NTRS2023

Optimizing Altitude Sampling and Sensitivity with the Goldstone Orbital Debris Radar

James Murray↗