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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Case Study: Analysis of Autonomous Center line Tracking Neural Networks

Deep neural networks have gained widespread usage in a number of applications. However, limitations such as lack of explainability and robustness inhibit building trust in their behavior, which is crucial in safety critical applications such as autonomous driving. Therefore, techniques which aid in understanding and providing guarantees for neural network behavior are the need of the hour. In this paper, we present a case study applying a recently proposed technique, Prophecy, to analyze the behavior of a neural network model, provided by our industry partner and used for autonomous guiding of airplanes on taxi runways. This regression model takes as input an image of the runway and produces two outputs, cross-track error and heading error, which represent the position of the plane relative to the center line. We use the Prophecy tool to extract neuron activation patterns for the correctness and safety properties of the model. We show the use of these patterns to identify features of the input that explain correct and incorrect behavior. We also use the patterns to provide guarantees of consistent behavior. We explore a novel idea of using sequences of images (instead of single images) to obtain good explanations and identify regions of consistent behavior.

Deep Neural Networks↗
DOE OSTI2021

An end-to-end trainable hybrid classical-quantum classifier

Abstract We introduce a hybrid model combining a quantum-inspired tensor network and a variational quantum circuit to perform supervised learning tasks. This architecture allows for the classical and quantum parts of the model to be trained simultaneously, providing an end-to-end training framework. We show that compared to the principal component analysis, a tensor network based on the matrix product state with low bond dimensions performs better as a feature extractor for the input data of the variational quantum circuit in the binary and ternary classification of MNIST and Fashion-MNIST datasets. The architecture is highly adaptable and the classical-quantum boundary can be adjusted according to the availability of the quantum resource by exploiting the correspondence between tensor networks and quantum circuits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Identifying Vulnerabilities and Hardening Attack Graphs for Networked Systems

We investigate efficient security control methods for protecting against vulnerabilities in networked systems. A large number of interdependent vulnerabilities typically exist in the computing nodes of a cyber-system; as vulnerabilities get exploited, starting from low level ones, they open up the doors to more critical vulnerabilities. These cannot be understood just by a topological analysis of the network, and we use the attack graph abstraction of Dewri et al. to study these problems. In contrast to earlier approaches based on heuristics and evolutionary algorithms, we study rigorous methods for quantifying the inherent vulnerability and hardening cost for the system. We develop algorithms with provable approximation guarantees, and evaluate them for real and synthetic attack graphs.

attack graphs↗
DOE OSTI2012

AmeriFlux Measurement Network: Science Team Research

Research involves analysis and field direction of AmeriFlux operations, and the PI provides scientific leadership of the AmeriFlux network. Activities include the coordination and quality assurance of measurements across AmeriFlux network sites, synthesis of results across the network, organizing and supporting the annual Science Team Meeting, and communicating AmeriFlux results to the scientific community and other users. Objectives of measurement research include (i) coordination of flux and biometric measurement protocols (ii) timely data delivery to the Carbon Dioxide Information and Analysis Center (CDIAC); and (iii) assurance of data quality of flux and ecosystem measurements contributed by AmeriFlux sites. Objectives of integration and synthesis activities include (i) integration of site data into network-wide synthesis products; and (ii) participation in the analysis, modeling and interpretation of network data products. Communications objectives include (i) organizing an annual meeting of AmeriFlux investigators for reporting annual flux measurements and exchanging scientific information on ecosystem carbon budgets; (ii) developing focused topics for analysis and publication; and (iii) developing data reporting protocols in support of AmeriFlux network goals.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Dilution of precision-based lunar navigation assessment for dynamic position fixing

The NASA vision of exploration is focused on the return of astronauts to the Moon [1]. While navigation systems have already been proven in the Apollo missions to the moon, the current exploration campaign will involve more extensive and extended missions requiring new concepts for lunar navigation. In contrast to Apollo missions, which were limited to the near-side equatorial region of the moon, missions under the Exploration Systems Initiative will require navigation on the moon’s limb and far-side. As these regions have poor Earth visibility, a navigation system comprised solely of Earth-based tracking stations will not provide adequate navigation solutions in these areas. In this paper, a Dilution of Precision (DoP) based analysis of the performance of a network of Moon orbiting satellites is provided. The analysis extends previous analysis of a Lunar Network (LN) of navigation satellites by providing an assessment of the capability associated with a variety of assumptions regarding the navigation receiver and satellite visibility. The assessment is accomplished by making appropriately formed estimates of DoP, with different adaptations of DoP (i.e. GDoP, PDoP, etc.) being associated with a different set of assumptions regarding augmentations to the navigation receiver or transceiver A significant innovation described in this paper is the “Generalized” Dilution of Precision. In the same sense that the various versions of DoP can be represented as a functional of the observability grammian, Generalized DoP is defined as a functional of the sum of observability grammians associated with a batch of radiometric measurements. Generalized DoP extends the DoP concept to cases in which radiometric range and range-rate measurements are integrated over time to develop an estimate of user position (referred to here as a ‘dynamic’ solution.) Generalized DoP allows for the inclusion of cases in which the receiver location is underdetermined when assessed in the usual ‘kinematic’ sense. The Generalized DoP concept is thereby a method to assess the navigation capability associated with constellations with sparse coverage without the burden of performing a full “covariance analysis” for each point on the surface of the Moon.

Berry, Kevin↗
NASA NTRS2006

Dilution of Precision-Based Lunar Navigation Assessment for Dynamic Position Fixing

The NASA Vision for Space Exploration is focused on the return of astronauts to the Moon. While navigation systems have already been proven in the Apollo missions to the moon, the current exploration campaign will involve more extensive and extended missions requiring new concepts for lunar navigation. In contrast to Apollo missions, which were limited to the near-side equatorial region of the moon, missions under the Exploration Systems Initiative will require navigation on the moon's limb and far-side. As these regions have poor Earth visibility, a navigation system comprised solely of Earth-based tracking stations will not provide adequate navigation solutions in these areas. In this paper, a Dilution of Precision (DoP) based analysis of the performance of a network of Moon orbiting satellites is provided. The analysis extends previous analysis of a Lunar Network (LN) of navigation satellites by providing an assessment of the capability associated with a variety of assumptions. These assumptions are with regard to the navigation receiver and satellite visibility. The assessment is accomplished by making appropriately formed estimates of DoP. Different adaptations of DoP (i.e. GDoP, PDoP, etc.) are associated with a different set of assumptions regarding augmentations to the navigation receiver or transceiver. A significant innovation described in this paper is the "Generalized" Dilution of Precision. In the same sense that the various versions of DoP can be represented as a functional of the observability grammian, Generalized DoP is defined as a functional of the sum of observability grammians associated with a batch of radiometric measurements. Generalized DoP extends the DoP concept to cases in which radiometric range and range-rate measurements are integrated over time to develop an estimate of user position (referred to here as a 'dynamic' solution.) Generalized DoP allows for the inclusion of cases in which the receiver location is underdetermined when assessed in the usual 'kinematic' sense. The Generalized DoP concept is thereby a method to assess the navigation capability associated with constellations with sparse coverage. This alleviates the burden of performing a full "covariance analysis" for each point on the surface of the Moon.

Sands, Obed S.↗
DOE OSTI2016

High Fidelity Simulations of Large-Scale Wireless Networks (Part I)

Wireless systems and networks have experienced rapid growth over the last decade with the advent of smart devices for everyday use. These systems, which include smartphones, vehicular gadgets, and internet-of-things devices, are becoming ubiquitous and ever-more important. They pose interesting research challenges for design and analysis of new network protocols due to their large scale and complexity. In this work, we focus on the challenging aspect of simulating the inter-connectivity of many of these devices in wireless networks. The quantitative study of large scale wireless networks, with counts of wireless devices in the thousands, is a very difficult problem with no known acceptable solution. By necessity, simulations of this scale have to approximate reality, but the algorithms employed in most modern-day network simulators can be improved for wireless network simulations. In this report, we present advances that we have made and propositions for continuation of progress towards a framework for high fidelity simulations of wireless networks. This work is not complete in that a final simulation framework tool is yet to be produced. However, we highlight the major bottlenecks and address them individually with initial results showing enough promise.

42 ENGINEERING↗
DOE OSTI2017

Fast automated analysis of strong gravitational lenses with convolutional neural networks

Quantifying image distortions caused by strong gravitational lensing—the formation of multiple images of distant sources due to the deflection of their light by the gravity of intervening structures—and estimating the corresponding matter distribution of these structures (the ‘gravitational lens’) has primarily been performed using maximum likelihood modelling of observations. Our procedure is typically time- and resource-consuming, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers. Accurate analysis of a single gravitational lens can take up to a few weeks and requires expert knowledge of the physical processes and methods involved. Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys. We report the use of deep convolutional neural networks to estimate lensing parameters in an extremely fast and automated way, circumventing the difficulties that are faced by maximum likelihood methods. We also show that the removal of lens light can be made fast and automated using independent component analysis of multi-filter imaging data. Our networks can recover the parameters of the ‘singular isothermal ellipsoid’ density profile, which is commonly used to model strong lensing systems, with an accuracy comparable to the uncertainties of sophisticated models but about ten million times faster: 100 systems in approximately one second on a single graphics processing unit. These networks can provide a way for non-experts to obtain estimates of lensing parameters for large samples of data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2006

Dilution of Precision-Based Lunar Navigation Assessment for Dynamic Position Fixing

The NASA Vision for Space Exploration is focused on the return of astronauts to the Moon. While navigation systems have already been proven in the Apollo missions to the moon, the current exploration campaign will involve more extensive and extended missions requiring new concepts for lunar navigation. In contrast to Apollo missions, which were limited to the near-side equatorial region of the moon, missions under the Exploration Systems Initiative will require navigation on the moon's limb and far-side. As these regions have poor Earth visibility, a navigation system comprised solely of Earth-based tracking stations will not provide adequate navigation solutions in these areas. In this paper, a Dilution of Precision (DoP) based analysis of the performance of a network of Moon orbiting satellites is provided. The analysis extends previous analysis of a Lunar Network (LN) of navigation satellites by providing an assessment of the capability associated with a variety of assumptions. These assumptions are with regard to the navigation receiver and satellite visibility. The assessment is accomplished by making appropriately formed estimates of DoP. Different adaptations of DoP (i.e., GDoP, PDoP, etc.) are associated with a different set of assumptions regarding augmentations to the navigation receiver or transceiver.

Sands, Obed S.↗
NASA NTRS2007

Dilution-of-Precision-Based Lunar Surface Navigation System Analysis Utilizing Lunar Orbiters

The NASA Vision for Space Exploration is focused on the return of astronauts to the Moon. Although navigation systems have already been proven in the Apollo missions to the Moon, the current exploration campaign will involve more extensive and extended missions requiring new concepts for lunar navigation. In contrast to Apollo missions, which were limited to the near-side equatorial region of the Moon, those under the Exploration Systems Initiative will require navigation on the Moon's limb and far side. Since these regions have poor Earth visibility, a navigation system comprised solely of Earth-based tracking stations will not provide adequate navigation solutions in these areas. In this report, a dilution-of-precision (DoP)-based analysis of the performance of a network of Moon orbiting satellites is provided. This analysis extends a previous analysis of a lunar network (LN) of navigation satellites by providing an assessment of the capability associated with a variety of assumptions. These assumptions pertain to the minimum surface user elevation angle and a total single satellite failure in the lunar network. The assessment is accomplished by making appropriately formed estimates of DoP. Different adaptations of DoP, such as geometric DoP and positional DoP (GDoP and PDoP), are associated with a different set of assumptions regarding augmentations to the navigation receiver or transceiver.

Welch, Bryan W.↗
NASA NTRS1994

High-performance parallel analysis of coupled problems for aircraft propulsion

This research program deals with the application of high-performance computing methods for the analysis of complete jet engines. We have entitled this program by applying the two dimensional parallel aeroelastic codes to the interior gas flow problem of a bypass jet engine. The fluid mesh generation, domain decomposition, and solution capabilities were successfully tested. We then focused attention on methodology for the partitioned analysis of the interaction of the gas flow with a flexible structure and with the fluid mesh motion that results from these structural displacements. This is treated by a new arbitrary Lagrangian-Eulerian (ALE) technique that models the fluid mesh motion as that of a fictitious mass-spring network. New partitioned analysis procedures to treat this coupled three-component problem are developed. These procedures involved delayed corrections and subcycling. Preliminary results on the stability, accuracy, and MPP computational efficiency are reported.

Felippa, C. A.↗
DOE OSTI2016

Correlation analysis on real-time tab-delimited network monitoring data

End-End performance monitoring in the Internet, also called PingER is a part of SLAC National Accelerator Laboratory’s research project. It was created to answer the growing need to monitor network both to analyze current performance and to designate resources to optimize execution between research centers, and the universities and institutes co-operating on present and future operations. The monitoring support reflects the broad geographical area of the collaborations and requires a comprehensive number of research and financial channels. The data architecture retrieval and methodology of the interpretation have emerged over numerous years. Analyzing this data is the main challenge due to its high volume. Finally, by using correlation analysis, we can make crucial conclusions about how the network data affects the performance of the hosts and how it depends from countries to countries.

97 MATHEMATICS AND COMPUTING↗