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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 NTRS1995

DREAMS and IMAGE: A Model and Computer Implementation for Concurrent, Life-Cycle Design of Complex Systems

Computing architectures are being assembled that extend concurrent engineering practices by providing more efficient execution and collaboration on distributed, heterogeneous computing networks. Built on the successes of initial architectures, requirements for a next-generation design computing infrastructure can be developed. These requirements concentrate on those needed by a designer in decision-making processes from product conception to recycling and can be categorized in two areas: design process and design information management. A designer both designs and executes design processes throughout design time to achieve better product and process capabilities while expanding fewer resources. In order to accomplish this, information, or more appropriately design knowledge, needs to be adequately managed during product and process decomposition as well as recomposition. A foundation has been laid that captures these requirements in a design architecture called DREAMS (Developing Robust Engineering Analysis Models and Specifications). In addition, a computing infrastructure, called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment), is being developed that satisfies design requirements defined in DREAMS and incorporates enabling computational technologies.

Hale, Mark A.↗
NASA NTRS2001

Use of Spacecraft Data to Drive Regions on Mars where Liquid Water would be Stable

Combining Viking pressure and temperature data with Mars Orbital Laser Altimeter (MOLA) topography data we have computed the fraction of the martian year during which pressure and temperature allow for liquid water to be stable on the martian surface. We find that liquid water would be stable within the Hellas and Argyre basin and over the northern lowlands equatorward of about 40 degrees. The location with the maximum period of stable conditions for liquid water is in the southeastern portion of Utopia Planitia where 34% of the year liquid water would be stable if it was present. Locations of stability appear to correlate with the distribution of valley networks.

Lobitz, Brad↗
NASA NTRS2005

Numerical Modeling of Flow Distribution in Micro-Fluidics Systems

This paper describes an application of a general purpose computer program, GFSSP (Generalized Fluid System Simulation Program) for calculating flow distribution in a network of micro-channels. GFSSP employs a finite volume formulation of mass and momentum conservation equations in a network consisting of nodes and branches. Mass conservation equation is solved for pressures at the nodes while the momentum conservation equation is solved at the branches to calculate flowrate. The system of equations describing the fluid network is solved by a numerical method that is a combination of the Newton-Raphson and successive substitution methods. The numerical results have been compared with test data and detailed CFD (computational Fluid Dynamics) calculations. The agreement between test data and predictions is satisfactory. The discrepancies between the predictions and test data can be attributed to the frictional correlation which does not include the effect of surface tension or electro-kinetic effect.

Majumdar, Alok↗
NASA NTRS2011

The Modeling and Simulation Catalog for Discovery, Knowledge and Reuse

The DoD M&S Steering Committee has noted that the current DoD and Service's modeling and simulation resource repository (MSRR) services are not up-to-date limiting their value to the using communities. However, M&S leaders and managers also determined that the Department needs a functional M&S registry card catalog to facilitate M&S tool and data visibility to support M&S activities across the DoD. The M&S Catalog will discover and access M&S metadata maintained at nodes distributed across DoD networks in a centrally managed, decentralized process that employs metadata collection and management. The intent is to link information stores, precluding redundant location updating. The M&S Catalog uses a standard metadata schemas based on the DoD's Net-Centric Data Strategy Community of Interest metadata specification. The Air Force, Navy and OSD (CAPE) have provided initial information to participating DoD nodes, but plans on the horizon are being made to bring in hundreds of source providers.

Stone, George F. III↗
NASA NTRS2011

Using Ensemble Decisions and Active Selection to Improve Low-Cost Labeling for Multi-View Data

This paper seeks to improve low-cost labeling in terms of training set reliability (the fraction of correctly labeled training items) and test set performance for multi-view learning methods. Co-training is a popular multiview learning method that combines high-confidence example selection with low-cost (self) labeling. However, co-training with certain base learning algorithms significantly reduces training set reliability, causing an associated drop in prediction accuracy. We propose the use of ensemble labeling to improve reliability in such cases. We also discuss and show promising results on combining low-cost ensemble labeling with active (low-confidence) example selection. We unify these example selection and labeling strategies under collaborative learning, a family of techniques for multi-view learning that we are developing for distributed, sensor-network environments.

machine learning↗
NASA NTRS2013

Service Oriented Robotic Architecture for Space Robotics: Design, Testing, and Lessons Learned

This paper presents the lessons learned from six years of experiments with planetary rover prototypes running the Service Oriented Robotic Architecture (SORA) developed by the Intelligent Robotics Group (IRG) at the NASA Ames Research Center. SORA relies on proven software engineering methods and technologies applied to space robotics. Based on a Service Oriented Architecture and robust middleware, SORA encompasses on-board robot control and a full suite of software tools necessary for remotely operated exploration missions. SORA has been eld tested in numerous scenarios of robotic lunar and planetary exploration. The experiments conducted by IRG with SORA exercise a large set of the constraints encountered in space applications: remote robotic assets, ight relevant science instruments, distributed operations, high network latencies and unreliable or intermittent communication links. In this paper, we present the results of these eld tests in regard to the developed architecture, and discuss its bene ts and limitations.

service oriented architecture↗
NASA NTRS2015

Zero Boil-Off System Testing

Cryogenic propellants such as liquid hydrogen (LH2) and liquid oxygen (LO2) are a part of NASA's future space exploration plans due to their high specific impulse for rocket motors of upper stages. However, the low storage temperatures of LH2 and LO2 cause substantial boil-off losses for long duration missions. These losses can be eliminated by incorporating high performance cryocooler technology to intercept heat load to the propellant tanks and modulating the cryocooler temperature to control tank pressure. The technology being developed by NASA is the reverse turbo-Brayton cycle cryocooler and its integration to the propellant tank through a distributed cooling tubing network coupled to the tank wall. This configuration was recently tested at NASA Glenn Research Center in a vacuum chamber and cryoshroud that simulated the essential thermal aspects of low Earth orbit, its vacuum and temperature. This test series established that the active cooling system integrated with the propellant tank eliminated boil-off and robustly controlled tank pressure.

Reverse turbo-Brayton cycle↗
NASA NTRS2015

Zero Boil-Off System Testing

Cryogenic propellants such as liquid hydrogen (LH2) and liquid oxygen (LO2) are a part of NASA's future space exploration due to their high specific impulse for rocket motors of upper stages suitable for transporting 10s to 100s of metric tons of payload mass to destinations outside of low earth orbit and for their return. However, the low storage temperatures of LH2 and LO2 cause substantial boil-off losses for missions with durations greater than several months. These losses can be eliminated by incorporating high performance cryocooler technology to intercept heat load to the propellant tanks and modulating the cryocooler to control tank pressure. The active thermal control technology being developed by NASA is the reverse turbo-Brayton cycle cryocooler and its integration to the propellant tank through a distributed cooling tubing network coupled to the tank wall. This configuration was recently tested at NASA Glenn Research Center, in a vacuum chamber and cryoshroud that simulated the essential thermal aspects of low Earth orbit, its vacuum and temperature. Testing consisted of three passive tests with the active cryocooler system off, and 7 active tests, with the cryocooler powered up. The test matrix included zero boil-off tests performed at 90 full and 25 full, and several demonstrations at excess cooling capacity and reduced cooling capacity. From this, the tank pressure response with varied cryocooler power inputs was determined. This test series established that the active cooling system integrated with the propellant tank eliminated boil-off and robustly controlled tank pressure.

Plachta, David W.↗
NASA NTRS2017

Liquid Nitrogen Zero Boiloff Testing

Cryogenic propellants such as liquid hydrogen (LH2) and liquid oxygen (LO2) are a part of NASAs future space exploration due to their high specific impulse for rocket motors of upper stages suitable for transporting 10s to 100s of metric tons of payload mass to destinations outside of low earth orbit and for their return. However, the low storage temperatures of LH2 and LO2 cause substantial boil-off losses for missions with durations greater than several months. These losses can be eliminated by incorporating high performance cryocooler technology to intercept heat load to the propellant tanks and modulating the cryocooler to control tank pressure. The active thermal control technology being developed by NASA is the reverse turbo-Brayton cycle cryocooler and its integration to the propellant tank through a distributed cooling tubing network coupled to the tank wall. This configuration was recently tested at NASA Glenn Research Center, in a vacuum chamber and cryo-shroud that simulated the essential thermal aspects of low Earth orbit, its vacuum and temperature. Testing consisted of three passive tests with the active cryo-cooler system off, and 7 active tests, with the cryocooler powered up. The test matrix included zero boil-off tests performed at 90 full and 25 full, and several demonstrations at excess cooling capacity and reduced cooling capacity. From this, the tank pressure response with varied cryocooler power inputs was determined. This test series established that the active cooling system integrated with the propellant tank eliminated boil-off and robustly controlled tank pressure.

Cryogenic fluid management↗
NASA NTRS2019

Radar Cross Section of Orbital Debris Objects

This discussion is concerned with the radar-data analysis and usage involved in the building of model orbital debris (OD) populations in the near-Earth environment, focusing on radar cross section (RCS). While varying with radar wavelength, physical dimension, material composition, overall shape and structure, the RCS of an irregular object is also strongly dependent on its spatial orientation. The historical records of observed RCSs for cataloged OD objects in the Space Surveillance Network are usually distributed over an RCS range, forming respective characteristic patterns. The National Aeronautics and Space Administration (NASA) Size Estimation Model provides an empirical probability-density function of RCS as a function of “effective diameter” (or “characteristic length”), which makes it feasible to predict possible RCS distributions for a given model OD population and to link data with model from a statistical perspective. The discussion also includes application of the widely used method of moments (MoM) and the Generalized Multi-particle Mie-solution (GMM) in the prediction of the RCS of arbitrarily shaped objects. Theoretical calculation results for an aluminum cube are compared with corresponding experimental measurements.

Xu, Yu-Lin↗
DOE OSTI2023

Residual loss due to magnetic flux trapping in niobium superconducting microwave cavities

One of the significant source of radio frequency loss in superconducting microwave cavities is the trapped residual magnetic field during the cooldown due to the incomplete Messier effect. The sensitivity of flux trapping depends on the distribution of impurities, network of dislocations and defects which pin vortices. Recent advancement in cavity processing techniques resulted in very high quality factors with impurity doping, however the rf loss related to the flux trapping increases. High quality factor in SRF cavities is not only limited to particle accelerators but also emerging as an application to quantum computing and quantum information science. In this presentation, we present the results of measurements of flux trapping sensitivity on several 1.3 GHz elliptical accelerating cavities with different grain size, impurity content and surface preparations.

Dhakal, P.↗
NASA NTRS1994

Fractal characteristics of ozonometric network

The fractal (correlation) dimensions are calculated which characterize the distribution of stations in the ground-based total ozone measuring network and the distribution of nodes in a latitude-longitude grid. The dimension of the ground-based ozonometric network equals 1.67 +/- 0.1 with an appropriate scaling in the 60 to 400 km range. For the latitude-longitude grid two scaling regimes are revealed. One regime, with the dimension somewhat greater than one, is peculiar to smaller scales and limited from a larger scale by the latitudinal resolution of the grid. Another scaling regime, with the dimension equal 1.84, ranges up to 15,000 km scale. The fact that the dimension of a measuring network is less than two possesses problems in observing sparse phenomena. This has to have important consequences for ozone statistics.

Gruzdev, Alexander N.↗
DOE OSTI2022

Communication systems and methods

A communication system is provided that includes a first quantum key distribution device and a communication device. The first quantum key distribution device is configured to be coupled to a second quantum key distribution device over a quantum channel and to generate a quantum key based on a quantum state transmitted along the quantum channel. The communication device is communicatively connected to the first quantum key distribution device within a network. The communication device is configured to receive the quantum key from the first quantum key distribution device and transmit the quantum key to an end device in the network via a classical link to enable the end device to use the quantum key for encrypting and/or decrypting messages communicated through the network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Detecting Rain–Snow-Transition Elevations in Mountain Basins Using Wireless Sensor Networks

Here, to provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature T wet and the other based on snow-depth measurements of accumulation and ablation. With data from 17 spatially distributed clusters (178 nodes) from two networks, in the American and Feather River basins of California’s Sierra Nevada, we analyzed transition elevation during 76 storm events in 2014–18. A T wet threshold of 0.5°C best matched the transition elevation defined by snow depth. Transition elevations using T wet in upper elevations of the basins generally agreed with atmospheric snow level from radars located at lower elevations, while radar snow level was ~100 m higher due to snow-level lowering on windward mountainsides during orographic lifting. Diurnal patterns of the difference between transition elevation and radar snow level were observed in the American basin, related to diurnal ground-temperature variations. However, these patterns were not found in the Feather basin due to complex terrain and higher uncertainties in transition-elevation estimates. The American basin tends to exhibit 100-m-higher transition elevations than does the Feather basin, consistent with the Feather basin being about 1° latitude farther north. Transition elevation averaged 155 m higher in intense atmospheric river events than in other events; meanwhile, snow-level lowering was enhanced with a 90-m-larger difference between radar snow level and transition elevation. On-the-ground continuous observations from distributed sensor networks can complement radar data and provide important ground truth and spatially resolved information on transition elevations in mountain basins.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Parallel physics-informed neural networks via domain decomposition

Here we develop a distributed framework for the physics-informed neural networks (PINNs) based on two recent extensions, namely conservative PINNs (cPINNs) and extended PINNs (XPINNs), which employ domain decomposition in space and in time-space, respectively. This domain decomposition endows cPINNs and XPINNs with several advantages over the vanilla PINNs, such as parallelization capacity, large representation capacity, efficient hyperparameter tuning, and is particularly effective for multi-scale and multi-physics problems. Here, we present a parallel algorithm for cPINNs and XPINNs constructed with a hybrid programming model described by MPI + X, where X ∈ {CPUs, GPUs}. The main advantage of cPINN and XPINN over the more classical data and model parallel approaches is the flexibility of optimizing all hyperparameters of each neural network separately in each subdomain. We compare the performance of distributed cPINNs and XPINNs for various forward problems, using both weak and strong scalings. Our results indicate that for space domain decomposition, cPINNs are more efficient in terms of communication cost but XPINNs provide greater flexibility as they can also handle time-domain decomposition for any differential equations, and can deal with any arbitrarily shaped complex subdomains. To this end, we also present an application of the parallel XPINN method for solving an inverse diffusion problem with variable conductivity on the United States map, using ten regions as subdomains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A Framework to Demonstrate a DNP3 Interface With a CIM-Based Data Integration Platform: Preprint

The contemporary electrical grid is characterized by its complexity and abundance of data. A control-rich environment supported by information and communication technologies within an Advanced Distribution Management System (ADMS) presents a viable and cost-effective option for utility companies aiming to implement advanced real-time analytical schemes for monitoring and remotely controlling distribution feeders. Modular platform-based approaches to distribution operations require a structured framework for acquiring field device measurements, performing analytics, converting the setpoint to the correct protocol, and sending it on the appropriate communications network to the field devices. We present the development and deployment of an application service to integrate an open-source standardsbased platform with an ADMS test bed with field devices using the Distributed Network Protocol (DNP3) for data exchange. The step-by-step procedure for establishing the DNP3-Master service on an open-source distribution platform is outlined, comprehensively explaining the Master setup process. Moreover, sample use case results highlight the capabilities of the DNP3- Master service setup. Results demonstrate the scalability and configurability of the DNP3-Master service, making it adaptable for integration with other relevant applications, thus providing potential opportunities for real-world field trials and real-time assessments.

ADMS↗
DOE OSTI2022

Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks

This work proposes and develops an implementation of a fault location method to provide a fast and resilient protection scheme for power distribution systems. The method analyzes the transient dynamics of traveling waves (TWs) to generate features using the discrete wavelet transform (DWT), which are then used to train several graph convolutional network (GCN) models. Faults are simulated in the IEEE 34-node system, which is divided into three protection zones (PZs). The goal is to identify the PZ in which the fault occurs. The GCN models create a distributed protection scheme, as all nodes are able to retrieve a prediction. Given that message-passing between nodes occurs both during training and in the execution of the model, the resiliency of such schemes to communication losses was analyzed and demonstrated. One of the models, which only uses voltage measurements, was implemented on a Texas Instruments F28379D development board. The execution times were monitored to assess the speed of the protection scheme. It is shown that the proposed method can be executed in approximately a millisecond, which is comparable to existing TW protection in the transmission system. For experimental purposes, a DWT-based detection method is employed. A design of a setup to playback TWs using two development boards is also addressed.

Jiménez-Aparicio, Miguel (ORCID:000000016864461X)↗