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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Optical processing for future computer networks

In the development of future data management systems, such as the NASA Space Station, a major problem represents the design and implementation of a high performance communication network which is self-correcting and repairing, flexible, and evolvable. To obtain the goal of designing such a network, it will be essential to incorporate distributed adaptive network control techniques. The present paper provides an outline of the functional and communication network requirements for the Space Station data management system. Attention is given to the mathematical representation of the operations being carried out to provide the required functionality at each layer of communication protocol on the model. The possible implementation of specific communication functions in optics is also considered.

Husain, A.↗
NASA NTRS1987

Space Station Information System integrated communications concept

This paper presents a model for integrated communications within the Space Station Information System (SSIS). The SSIS is generally defined as the integrated set of space and ground information systems and networks which will provide required data services to the Space Station flight crew, ground operations personnel, and customer communities. This model is based on the International Standards Organization (ISO) layered model for Open Systems Interconnection (OSI). The requirements used to develop the model are presented, and the various elements of the model described.

Muratore, J.↗
NASA NTRS1987

Space Station Information System requirements for integrated communications

Space Station Information System (SSIS) requirements for integrated end-to-end communications are presented. The SSIS is defined as the integrated set of space and ground data and information systems and networks which will provide required data services to the Space Station flight crew, ground operations personnel, and customer communities. This model is based on the International Standards Organization (ISO) layered model for Open System Interconnection (OSI). These SSIS requirements include grades of service, priority classifications, systems management, flow control, bandwidth allocation, and standard SSIS data services.

Marker, W.↗
NASA NTRS1992

An OSI architecture for the Deep Space Network

This article presents an Open Systems Interconnection (OSI) architecture developed for the Deep Space Network. An historical review is provided to establish the context for current United States Government policy on interprocessor communication standards. An introduction to the OSI architecture, its seven-layer approach, and an overview of application service entities are furnished as a tutorial. Finally, the results of a prototype system developed for monitor and control of a Deep Space Station are also presented.

Heuser, W. R.↗
NASA NTRS2008

OTF CCSDS SM and C Interoperability Prototype

A presentation is provided to demonstrate the interoperability between two space flight Mission Operation Centers (MOCs) and to emulate telemetry, actions, and alert flows between the two centers. One framework uses a COTS C31 system that uses CORBA to interface to the local OTF data network. The second framework relies on current Houston MCC frameworks and ad hoc clients. Messaging relies on SM and C MAL, Core and Common Service formats, while the transport layer uses AMS. A centralized SM and C Registry uses HTTP/XML for transport/encoding. The project's status and progress are reviewed.

Reynolds, Walter F.↗
NASA NTRS2010

High-Speed Ring Bus

The high-speed ring bus at the Jet Propulsion Laboratory (JPL) allows for future growth trends in spacecraft seen with future scientific missions. This innovation constitutes an enhancement of the 1393 bus as documented in the Institute of Electrical and Electronics Engineers (IEEE) 1393-1999 standard for a spaceborne fiber-optic data bus. It allows for high-bandwidth and time synchronization of all nodes on the ring. The JPL ring bus allows for interconnection of active units with autonomous operation and increased fault handling at high bandwidths. It minimizes the flight software interface with an intelligent physical layer design that has few states to manage as well as simplified testability. The design will soon be documented in the AS-1393 standard (Serial Hi-Rel Ring Network for Aerospace Applications). The framework is designed for "Class A" spacecraft operation and provides redundant data paths. It is based on "fault containment regions" and "redundant functional regions (RFR)" and has a method for allocating cables that completely supports the redundancy in spacecraft design, allowing for a complete RFR to fail. This design reduces the mass of the bus by incorporating both the Control Unit and the Data Unit in the same hardware. The standard uses ATM (asynchronous transfer mode) packets, standardized by ITU-T, ANSI, ETSI, and the ATM Forum. The IEEE-1393 standard uses the UNI form of the packet and provides no protection for the data portion of the cell. The JPL design adds optional formatting to this data portion. This design extends fault protection beyond that of the interconnect. This includes adding protection to the data portion that is contained within the Bus Interface Units (BIUs) and by adding to the signal interface between the Data Host and the JPL 1393 Ring Bus. Data transfer on the ring bus does not involve a master or initiator. Following bus protocol, any BIU may transmit data on the ring whenever it has data received from its host. There is no centralized arbitration or bus granting. The JPL design provides for autonomous synchronization of the nodes on the ring bus. An address-synchronous latency adjust buffer (LAB) has been designed that cannot get out of synchronization and needs no external input. Also, a priority-driven cable selection behavior has been programmed into each unit on the ring bus. This makes the bus able to connect itself up, according to a maximum redundancy priority system, without the need for computer intervention at startup. Switching around a failed or switched-off unit is also autonomous. The JPL bus provides a map of all the active units for the host computer to read and use for fault management. With regard to timing, this enhanced bus recognizes coordinated timing on a spacecraft as critical and addresses this with a single source of absolute and relative time, which is broadcast to all units on the bus with synchronization maintained to the tens of nanoseconds. Each BIU consists of up to five programmable triggers, which may be programmed for synchronization of events within the spacecraft of instrument. All JPL-formatted data transmitted on the ring bus are automatically time-stamped.

Wysocky, Terry↗
NASA NTRS1990

A real time neural net estimator of fatigue life

A neural network architecture is proposed to estimate, in real-time, the fatigue life of mechanical components, as part of the intelligent Control System for Reusable Rocket Engines. Arbitrary component loading values were used as input to train a two hidden-layer feedforward neural net to estimate component fatigue damage. The ability of the net to learn, based on a local strain approach, the mapping between load sequence and fatigue damage has been demonstrated for a uniaxial specimen. Because of its demonstrated performance, the neural computation may be extended to complex cases where the loads are biaxial or triaxial, and the geometry of the component is complex (e.g., turbopumps blades). The generality of the approach is such that load/damage mappings can be directly extracted from experimental data without requiring any knowledge of the stress/strain profile of the component. In addition, the parallel network architecture allows real-time life calculations even for high-frequency vibrations. Owing to its distributed nature, the neural implementation will be robust and reliable, enabling its use in hostile environments such as rocket engines.

Troudet, T.↗
NASA NTRS2002

The Micro-Pulse Lidar Network (MPL-Net)

In the early 1990s, the first small, eye-safe, and autonomous lidar system was developed, the Micro-pulse Lidar (MPL). The MPL has proven to be useful in the field because it can be automated, runs continuously (day and night), is eye-safe, can easily be transported and set up, and has a small field-of-view which limits multiple scattering concerns. The MPL acquires signal profiles of backscattered laser light from aerosols and clouds. The signals are analyzed to yield multiple layer heights, optical depths of each layer, average extinction-to-backscatter ratio of each layer, and profiles of extinction in each layer. The MPL has been used in a wide variety of field studies over the past 10 years, leading to nearly 20 papers and many conference presentations. In 2000, a new project using MPL systems was started at NASA Goddard Space Flight Center. The MPL-Net project is currently working to establish a worldwide network of MPL systems, all co-located with NASA's AERONET sunphotometers for joint measurements of optical depth and sky radiance. Automated processing algorithms have been developed to produce data products on a next day basis for all sites and some field experiments. Initial results from the first several sites are shown, along with aerosol data collected during several major field campaigns. Measurements of the aerosol extinction-to-backscatter ratio at several different geographic regions, and for various aerosol types are shown. This information is used to improve the construction of look up tables of the ratio, needed to process aerosol profiles acquired with satellite based lidars.

Welton, Ellsworth J.↗
DOE OSTI2022

$\mathrm{IH}$-$\mathrm{GAN}$: A conditional generative model for implicit surface-based inverse design of cellular structures

Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically optimized structures, particularly those represented as discrete density maps. However, the optimization of such cellular structures is challenging due to the multiscale design problem. Past work addressing this problem generally either only optimizes the volume fraction of single-type unit cells but ignoring the effects of unit cell geometry on properties, or considers the geometry–property relation but builds this relation via heuristics. In contrast, we propose a simple yet more principled way to accurately model the property to geometry mapping using a conditional deep generative model, named Inverse Homogenization Generative Adversarial Network (IH-GAN). It learns the conditional distribution of unit cell geometries given properties and can realize the one-to-many mapping from properties to geometries. Here we further reduce the complexity of IH-GAN by using the implicit function parameterization to represent unit cell geometries. Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy (R 2 -scores between target properties and properties of generated unit cells >98%) and 2) improve the optimized structural performance over the conventional variable-density single-type structure. In the minimum compliance example, our IH-GAN generated structure achieves a 79.7% reduction in concentrated stress and an extra 3.03% reduction in displacement. In the target deformation examples, our IH-GAN generated structure reduces the target matching error by 86.4% and 79.6% for two test cases, respectively. We also demonstrated that the connectivity issue for multi-type unit cells can be solved by transition layer blending.

42 ENGINEERING↗
DOE OSTI2021

Fault Detection Utilizing Convolution Neural Network on Timeseries Synchrophasor Data From Phasor Measurement Units

An end-to-end supervised learning method is proposed for fault detection in the electric grid using Big Data from multiple Phasor Measurement Units (PMUs). The approach consists of preprocessing steps aimed at reducing data noise and dimensionality, followed by utilization of six classification models considered for detecting faults. Three of the models were variants of Convolutional Neural Network (CNN) architectures that consider a single type of measurement (voltage, current or frequency) at all PMUs or all types together also at all PMUs. CNN based models were compared to traditional methods of Logistic Regression (LR), Multi-layer Perceptron (MLP) and Support Vector Machine (SVM). Evaluation was conducted on two-year data measured by PMUs at 37 locations in a large electric grid. Here, the response variable for classification were extracted from the grid-wide outage event log. Experiments show that CNN-based models outperformed traditional methods on one year out-of-sample outage detection over the entire grid.

42 ENGINEERING↗
DOE OSTI2020

Achieving Balanced Crystallization Kinetics of Donor and Acceptor by Sequential-Blade Coated Double Bulk Heterojunction Organic Solar Cells

Sequential deposition has great potential to achieve high performance in organic solar cells due to the resulting well-controlled vertical phase separation. In this work, double bulk heterojunction organic solar cells are fabricated by sequential-blade cast in ambient conditions. Probed by the in situ grazing incidence X-ray diffraction and in situ UV–vis absorption measurements, the seq-blade system exhibits a different tendency from each of the binary films during the film formation process. Due to the extensive aggregation of FOIC, the binary PBDB-T:FOIC film displays a strong and large phase separation, resulting in low current density (J sc) and unsatisfactory power conversion efficiency. In the seq-blade cast system, the bottom layer PBDB-T:IT-M produces many crystal nuclei for the top layer PBDB-T:FOIC, so the PBDB-T molecules are able to crystallize easily and quickly. Balanced crystallization kinetics between polymer and small molecule and an ideal percolation network in the film are observed. In addition, the balanced crystallization kinetics are favorable toward realizing lower recombination loss through charge transport processes.

14 SOLAR ENERGY↗
DOE OSTI2023

Revealing the aging process of solid electrolyte interphase on SiOx anode

Abstract As one of the most promising alternatives to graphite negative electrodes, silicon oxide (SiO x ) has been hindered by its fast capacity fading. Solid electrolyte interphase (SEI) aging on silicon SiO x has been recognized as the most critical yet least understood facet. Herein, leveraging 3D focused ion beam-scanning electron microscopy (FIB-SEM) tomographic imaging, we reveal an exceptionally characteristic SEI microstructure with an incompact inner region and a dense outer region, which overturns the prevailing belief that SEIs are homogeneous structure and reveals the SEI evolution process. Through combining nanoprobe and electron energy loss spectroscopy (EELS), it is also discovered that the electronic conductivity of thick SEI relies on the percolation network within composed of conductive agents (e.g., carbon black particles), which are embedded into the SEI upon its growth. Therefore, the free growth of SEI will gradually attenuate this electron percolation network, thereby causing capacity decay of SiO x . Based on these findings, a proof-of-concept strategy is adopted to mechanically restrict the SEI growth via applying a confining layer on top of the electrode. Through shedding light on the fundamental understanding of SEI aging for SiO x anodes, this work could potentially inspire viable improving strategies in the future.

25 ENERGY STORAGE↗
DOE OSTI2021

Graph convolutional networks applied to unstructured flow field data

Abstract Many scientific and engineering processes produce spatially unstructured data. However, most data-driven models require a feature matrix that enforces both a set number and order of features for each sample. They thus cannot be easily constructed for an unstructured dataset. Therefore, a graph based data-driven model to perform inference on fields defined on an unstructured mesh, using a graph convolutional neural network (GCNN) is presented. The ability of the method to predict global properties from spatially irregular measurements with high accuracy is demonstrated by predicting the drag force associated with laminar flow around airfoils from scattered velocity measurements. The network can infer from field samples at different resolutions, and is invariant to the order in which the measurements within each sample are presented. The GCNN method, using inductive convolutional layers and adaptive pooling, is able to predict this quantity with a validation R 2 above 0.98, and a Normalized Mean Squared Error below 0.01, without relying on spatial structure.

Ogoke, Francis (ORCID:0000000224327783)↗
DOE OSTI2020

A Deep Generative Model for Non-Intrusive Identification of EV Charging Profiles

The proliferation of electric vehicles (EVs) brings environmental benefits and technical challenges to power grids. An identification algorithm which can accurately extract individual EV charging profiles out of widely available smart meter measurements has attracted great interests. This paper proposes a non-intrusive identification framework for EV charging profile extraction, which is driven by deep generative models (DGM). First, the proposed DGM is designed as a representation layer embedded into the Markov process and used to model the joint probability distribution of available time-series data. A novel contribution is to approximate posterior distributions by neural networks whose parameters are obtained by variational inference and supervised learning. Second, the EV charging status is inferred from the DGM via dynamic programming. Lastly, the desired EV charging profile can be reconstructed by the rated power of EV models and inferred status. Compared with the benchmark Hidden Markov Models, the proposed framework can better handle noise in data with less computational complexity and better overall accuracy performances with smaller recall. The proposed framework is validated by numerical experiments on the Pecan Street dataset.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Hydration and reaction mechanisms on sodium silicate glass surfaces from molecular dynamics simulations with reactive force fields

Recent development of reactive force fields have enabled molecular dynamics simulations of interactions between silicate glasses and water at the atomistic scale. While multicomponent silicate glasses encompass a wide variety of compositions and properties, one common structural feature in these glasses is the combination of the network structure that is made up of silica tetrahedra linked through corner sharing interspersed with network modifiers like alkali and alkaline-earth ions that break up the Si–O–Si linkages by forming nonbridging oxygen. In reactions with water, ion exchange between alkali ions in the glass and proton or hydronium in the solution, as well as hydrolysis reaction of the Si–O–Si linkages and subsequent silanol formation, is observed and well documented. Furthermore, we have used a set of recently developed reactive force field to investigate the reactions between water and the surfaces of silica and sodium silicate glasses of different compositions for reactions up to 8 nanoseconds. Our results indicate sodium leaching into water and diffusion of water molecules up to 25 Å into the glass surface. We examined the structural and compositional changes inside the glass and around the diffused ions and use these to explain the rates of silanol formation at the surface. We also observed proton transport in the glass which has an indirect influence on the silanol formation rates. While the surface of the glass was rough to start with, it undergoes further modification into a hydrated gel-like structure in the glass for up to 5 Å in the higher alkali containing glasses. It was found that the leached sodium ions remain close to the interface and that fragments of silicate network from the surface is capable of dislodging from the bulk glass and enter the aqueous solution. These simulations thus provide insights into the formation and structure of an alteration layers commonly observed in multicomponent silicate glasses corroded in aqueous solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rheo–Electric Foundations and Engineering of Carbon Slurry Flow Electrodes

Flowable carbon slurry electrodes promise continuous, scalable electrochemical desalination and energy storage when their rheology (flow and stability) and electronic connectivity are jointly optimized. This report integrates six complementary thrusts that we executed under the Laboratory Directed Research and Development (LDRD) project: (i) a fast, ex situ, centrifuge-compatible method to quantify pellet (packed slurry) electronic conductivity, with a validated cell constant (“shape factor”) and quantitative structure–property insights for carbon mixtures; (ii) a controlled circulation study showing that peristaltic pumping can irreversibly alter particle size and morphology over laboratory-relevant durations; (iii) development of a miniature jet pump that preserves particle integrity while achieving entrainment ratios of 2–4 at practical flow rates; (iv) a comprehensive mapping of how a representative non-ionic surfactant (Tween 20) collapses the carbon gel network, separating network-percolation losses from intrinsic particle contact resistance; (v) in-situ visualization revealing how gravitational settling and flow-driven mixing compete to control charge transport, with dynamic bed layers preventing saturation while achieving 30-fold local concentration enhancement; and (vi) a simple, widely adoptable fabrication route to structured, gas-nitrided titanium nitride (TiN) titanium current collectors that dramatically lower interfacial losses and enable geometry-driven performance gains. Together, these results provide a coherent toolchain and design rules to accelerate formulation screening, de-risk device prototyping, and standardize characterization for carbon slurry electrodes in flow-electrode capacitive deionization (FCDI), electrochemical flow capacitor (EFC), and related systems.

25 ENERGY STORAGE↗
DOE OSTI2020

Robust Learning with Implicit Residual Networks

In this effort, we propose a new deep architecture utilizing residual blocks inspired by implicit discretization schemes. As opposed to the standard feed-forward networks, the outputs of the proposed implicit residual blocks are defined as the fixed points of the appropriately chosen nonlinear transformations. We show that this choice leads to the improved stability of both forward and backward propagations, has a favorable impact on the generalization power, and allows for control the robustness of the network with only a few hyperparameters. In addition, the proposed reformulation of ResNet does not introduce new parameters and can potentially lead to a reduction in the number of required layers due to improved forward stability. Finally, we derive the memory-efficient training algorithm, propose a stochastic regularization technique, and provide numerical results in support of our findings.

Reshniak, Viktor↗
NASA NTRS1993

Reconnaissance and deep-drill site selection on Taylor Dome, Antarctica

Taylor Dome is a small ice dome near the head of Taylor Valley, Southern Victoria Land. The location of the dome, just west of the Transantarctic Mountains, is expected to make the composition of the accumulating snow sensitive to changes in the extent of the Ross Ice Shelf. Thus, it is linked to the discharge of the West Antarctic Ice Sheet but protected against direct influences of glacial-interglacial sea-level rise. The record of past climatic and environmental changes in the ice provides a valuable complement to the radiocarbon-dated proxy record of climate derived from perched deltas, strandlines, and moraines that have been obtained in the nearby Dry Valleys. We carried out a reconnaissance of the Taylor Dome area over the past two field seasons to determine the most favorable location to obtain a deep core to bedrock. A stake network has been established with an 80-km line roughly along the crest of Taylor Dome, and 40-km lines parallel to it and offset by 10 km. These lines have been surveyed 1990/91, and the positions of 9 grid points have been determined with geoceivers. A higher density stake network was placed and surveyed around the most likely drill area in the second year. Ground-based radar soundings in both years provided details on bedrock topography and internal layering of the ice in the drill area. An airborne radar survey in January 1992, completed the radar coverage of the Taylor Dome field area.

Grootes, Pieter M.↗