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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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Report presents some recent developments in theory of binary neural networks. Subject matter relevant to associate (content-addressable) memories and to recognition of patterns - both of considerable importance in advancement of robotics and artificial intelligence. When probed by any pattern, network converges to one of stored patterns.
The Internet is a network of networks. It was originally funded by the Defense Advanced Research Projects Agency or DOD/DARPA and evolved in part from the connection of supercomputer sites across the United States. The National Science Foundation (NSF) made the most of their supercomputers by connecting the sites to each other. This made the supercomputers more efficient and now allows scientists, engineers and researchers to access the supercomputers from their own labs and offices. The high speed networks that connect the NSF supercomputers form the backbone of the Internet. The World Wide Web (WWW) is a menu system. It gathers Internet resources from all over the world into a series of screens that appear on your computer. The WWW is also a distributed. The distributed system stores data information on many computers (servers). These servers can go out and get data when you ask for it. Hypermedia is the base of the WWW. One can 'click' on a section and visit other hypermedia (pages). Our approach to demonstrating the importance of aviation research through the Internet began with learning how to put pages on the Internet (on-line) ourselves. We were assigned two aviation companies; Vision Micro Systems Inc. and Innovative Aerodynamic Technologies (IAT). We developed home pages for these SBIR companies. The equipment used to create the pages were the UNIX and Macintosh machines. HTML Supertext software was used to write the pages and the Sharp JX600S scanner to scan the images. As a result, with the use of the UNIX, Macintosh, Sun, PC, and AXIL machines, we were able to present our home pages to over 800,000 visitors.
In the ALE/GAGE/AGAGE global network program, continuous high frequency gas chromatographic measurements of four biogenic/anthropogenic gases (methane, CH4; nitrous oxide, N2O; hydrogen, H2; and carbon monoxide, CO) and several anthropogenic gases that contribute to stratospheric ozone destruction and/or to the greenhouse effect have been carried out at five globally distributed sites for several years. The program, which began in 1978, is divided into three parts associated with three changes in instrumentation: the Atmospheric Lifetime Experiment (ALE), which used Hewlett Packard HP5840 gas chromatographs; the Global Atmospheric Gases Experiment (GAGE), which used HP5880 gas chromatographs; and the present Advanced GAGE (AGAGE). AGAGE uses two types of instruments: a gas chromatograph with multiple detectors (GC-MD), and a gas chromatograph with mass spectrometric analysis (GC-MS). Beginning in January 2004, an improved cryogenic preconcentration system (Medusa) replaced the absorption-desorption module in the GC-MS systems at Mace Head and Cape Grim; this provided improved capability to measure a broader range of volatile perfluorocarbons with high global warming potentials. The Medusa GC-MS systems were subsequently used at other AGAGE stations (Trinidad Head, Barbados, American Samoa, Zeppelin, Jungfraujoch, and Goan) after the initial setup at Mace Head and Cape Grim. More information may be found at the AGAGE home page: https://agage.mit.edu/instruments.Compared to the previous version (https://data.ess-dive.lbl.gov/datasets/doi: doi:10.15485/1781803), the latest update (Agage_gcmd_gcms.data.2022_01_03.tar.gz) includes 6 months of new data through the end of September 2020. For a complete list of released compounds and used standard scales, please see “AGAGE_scale_2021_v1.pdf” file. Additional information can also be found on the AGAGE website (https://agage.mit.edu).
The theme to the 1995 International Mobile Satellite Conference was 'Mobile Satcom Comes of Age'. The sessions included Modulation, Coding, and Multiple Access; Hybrid Networks - 1; Spacecraft Technology; propagation; Applications and Experiments - 1; Advanced System Concepts and Analysis; Aeronautical Mobile Satellite Communications; Mobile Terminal Antennas; Mobile Terminal Technology; Current and Planned Systems; Direct Broadcast Satellite; The Use of CDMA for LEO and ICO Mobile Satellite Systems; Hybrid Networks - 2; and Applications and Experiments - 2.
In network systems, a local perturbation can amplify as it propagates, potentially leading to a large-scale cascading failure. We derive a continuous model to advance our understanding of cascading failures in power-grid networks. The model accounts for both the failure of transmission lines and the desynchronization of power generators and incorporates the transient dynamics between successive steps of the cascade. In this framework, we show that a cascade event is a phase-space transition from an equilibrium state with high energy to an equilibrium state with lower energy, which can be suitably described in a closed form using a global Hamiltonian-like function. From this function, we show that a perturbed system cannot always reach the equilibrium state predicted by quasi-steady-state cascade models, which would correspond to a reduced number of failures, and may instead undergo a larger cascade. We also show that, in the presence of two or more perturbations, the outcome depends strongly on the order and timing of the individual perturbations. These results offer new insights into the current understanding of cascading dynamics, with potential implications for control interventions.
We have developed an artificial neural network model to characterize the photosynthesis process of soybean crops under various environmental conditions.
This study develops a future scenario that enables convenient point-to-point commercial air travel via a large network of community airports and a new class of small airliners. A network demand and capacity study identifies current and future air travel demands and the capacity of this new network to satisfy these demands. A current technology small commercial airliner is defined to meet the needs of the new network, as a baseline for evaluating the improvement brought about by advanced technologies. Impact of this new mode of travel on the infrastructure and surrounding communities of the small airports in this new N+3 network are also evaluated. Year 2030-2035 small commercial airliner technologies are identified and a trade study conducted to evaluate and select those with the greatest potential for enhancing future air travel and the study metrics. The selected advanced air vehicle concept is assessed against the baseline aircraft, and an advanced, but conventional aircraft, and the study metrics. The key technologies of the selected advanced air vehicle are identified, their impact quantified, and risk assessments and roadmaps defined.
Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.
Task A, also known as HGFrac, examines the fracturing processes that may occur in the Callovo-Oxfordian claystone (COx) in the context of the high-level (HLW) and intermediate-level long-lived (ILW-LL) radioactive waste repository in France. Understanding these processes and improving numerical models to reproduce them will aid in the design, optimization, and safety of the repository. Heat and gas fracturing are studied in two independent subtasks following a stepwise approach: laboratory tests/benchmark exercises, in-situ experiment, and finally, an application case. The in-situ heater experiment aimed to thermally induce a hydraulic fracture; temperature and pore pressure were monitored to detect any evidence of fracturing. The in-situ gas injection experiment aimed to study the effect of the stress orientation and gas injection kinetics on the gas fracturing process. The occurrence of fracturing was monitored by gas pressure measured in the injection interval. In both experiments, the excavation-induced fracture network around the heater/injection boreholes played an important role in the reduction of the compressive stress state, leading to both a tensile and shear failure response of the COx. During the first two years of the project, the research teams working on each task developed and/or proposed numerical approaches for reproducing the occurrence of fracturing in the in-situ experiments. The failure criteria were defined by reproducing the measurements from laboratory extension tests for the heat fracturing subtask. In the gas fracturing subtask, their approaches were used for simulating several benchmark exercises, and an inter-comparison between models was carried out. In both tasks, the developed approaches were compared with a simplified approach considering poro-elasticity for the mechanical behaviour of the COx. Most of the developed approaches are based on a continuous medium that takes into account variations in hydraulic properties due to mechanical degradation, such as plastic deformation or damage. Other approaches implicitly modelled weak planes or embedded discontinuities to reproduce fracture propagation. The potential for fracture initiation was also studied through of a discrete approach. In the second half of the project, the research teams mainly focused on interpretative modelling of two in-situ experiments and a blind prediction exercise to test their respective approaches. The models developed by the research teams were also applied at the repository scale to evaluate fracture initiation in a case study under vi unfavourable conditions, particularly in terms of spacing between High-Level Waste cells. The results showed that the poro-elasticity approach could be an efficient tool for understanding the main processes occurring in the COx. One example is the explicit representation of the excavation-induced fracture network around the boreholes, which yielded acceptable results compared to the measurement data. However, advanced approaches were needed to evaluate the potential increase of the excavation-induced fracture network extend and better understand fracture initiation. The stress analyses carried out by the teams revealed that hydraulic boundary conditions had a strong impact on fracture initiation in the heater experiment. Furthermore, in most cases, the results required higher pore pressure increments to reach fracturing than those measured in the experiment. This implies that the measurements may have been biased by the packer’s capacity to fully isolate the piezometric chambers, leading to lower pressures. On the contrary, there was no agreement on the fracturing mode, as some reported either shear or tensile fracturing, while others reported a combination of the two modes. In the case of gas fracturing, the research teams were limited to the comparison of a single point, which complicated their task. Nonetheless, the numerical results were able to reproduce the measurements and capture processes such as longitudinal gas flow through the excavation-induced fracture network, as suggested by some evidence in the observation piezometric chambers. The numerical models also agreed with the measurements in the sense of higher probability of developing along the injection borehole than radially towards the sound rock. The approaches developed by the research teams showed that they are capable of analysing and reproducing fracture initiation in the COx. However, areas of future work should focus on the fracture propagation and fracture aperture, which were out of the scope of this task. To this end, additional data must be gathered for the parameter characterisation and validation of the numerical models. Nonetheless, various approaches showed promising results as they were able to reproduce fracture development under certain conditions.
Rapid advances in embedded system complexity and capability provides exciting opportunities for transportation security deployment. Manufacturers and developers of these embedded systems continue to provide lower cost and more powerful solutions that can be leveraged by researchers and engineers. Furthermore, deploying these devices at the “edge” of the Internet-of-Things (IoT) infrastructure provides opportunities for highly capable applications in transport security. In an edge computation architecture, the device is co-located at the source of the data in the larger IoT structure – this provides computational capability at the location directly where the data is collected. For shipment transport security, this provides a direct compute node for digestion of data and mitigation actions in real-time. In our application, the vehicle provides a significant amount of this data that can be processed in real-time via the Controller Area Network Transport Security Tracking and Reporting (C-STAR) edge device. Utilization of a computational node located on the vehicle, such as the C-STAR, capitalizes on previously discussed opportunities of edge architectures. In this paper, we will discuss this security solution’s usability, current deployments, and scalability to further applications in transport security. First, we will cover the supported vehicle platforms that can leverage the C-STAR technology. This will be particularly relevant to medium- and heavy-duty vehicles transporting high-risk shipments. Second, we will speak to current deployments of the C-STAR that are ongoing. Finally, we will discuss additional areas for expansion such as maturing the onboard algorithms through continuing collaborations.
We discuss cryptographic data protection network schemes combining the approaches of quantum cryptography with advanced computer information processing methods. The use of the latter is due to the presence of a number of unsolved problems in the existing quantum key distribution systems and is also associated with projects for the development of network-centric quantum communications and photonic networks, which involves the employment of multi-agent control models. Developments based on the Y-00 protocol with data encoding by the quantum noise of a transmitting laser are considered, and achievements in the field of quantum-optical random number generators are presented. The latter can be also used to design secure multi-valued logic encoding schemes that are promising for increasing the dimension of the key space in the ‘one-time pad’ method, for solving the tasks of position-dependent cryptography and for implementing multi-agent models.
We present the first application of deep learning forecasting for binary neutron stars, neutron star–black hole systems, and binary black hole mergers that span an eccentricity range e ≤ 0.9. In this work, we train neural networks that describe these astrophysical populations, and then test their performance by injecting simulated eccentric signals in advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) noise available at the Gravitational Wave Open Science Center to (1) quantify how fast neural networks identify these signals before the binary components merge; (2) quantify how accurately neural networks estimate the time to merger once gravitational waves are identified; and (3) estimate the time-dependent sky localization of these events from early detection to merger. Our findings show that deep learning can identify eccentric signals from a few seconds (for binary black holes) up to tens of seconds (for binary neutron stars) prior to merger. A quantized version of our neural networks achieves 4× reduction in model size, and up to 2.5× inference speedup. These novel algorithms may be used to facilitate time-sensitive multimessenger astrophysics observations of compact binaries in dense stellar environments.
Abstract— Microgrid installations have regained significant interest, driven by the increasing adoption of distributed energy resources, decentralized controls, and ongoing technological advancements. While the number of microgrids increases, there are opportunities to coordinate networks of microgrids. In this study, Irving’s algorithm is applied to a framework for the coordinated self-assembly of networked microgrids. Compared with the authors’ previous work, this new study relaxes the constraint on participated microgrids to have a single global objective. Thus, each microgrid can rank others according to its local preference. This reduces the amount of shared information, improves the privacy, and enhances the flexibility. The adaptability to that proposed framework is also maintained. Examples are presented to illustrate the networking processes and self-assembly operations.
Two trends of NASA missions are the use of multiple small spacecraft and the development of an integrated space network. To achieve these goals, a robust and agile communications system is needed. Advancements in field programmable gate array (FPGA) technology have made it possible to incorporate major communication and network functionalities in FPGA chips; thus this technology has great potential as the basis for a reconfigurable communications system. This report discusses the requirements of future space communications, reviews relevant issues, and proposes a methodology to design and construct a reconfigurable communications system for small scientific spacecraft.
As an initial step in exploring the opportunities afforded by the merger of satellite-based and land-based networks, Bellcore and JPL conducted several experiments utilizing NASA's Advanced Communications Technology Satellite (ACTS) and JPL's ACTS Mobile Terminal (AMT). Experimental goals fell into three categories: a) demonstrate personal communication applications, b) demonstrate interoperability among multiple wireless networks and the Public Switched Telecommunications Network (PSTN), and c) evaluate new protocol mechanisms for data communications using wireless links. We describe the performance of Point-of-Sale, e-mail, FAX, and call control applications, where the communication path passed through up to four networks: a wireless packet data network, the Satellite network, the PSTN, and a wireless cellular network. One important element of satellite-terrestrial interoperability is the efficiency of data communications protocols. Most protocols in use today (e.g., TCP/IP) have been optimized for wireline channels; their use over wireless networks presents significant new challenges. The characteristics of wireless channels -- increased error, longer packet delay, and limited bandwidth -- affect the design of the protocol. We describe experimental results for differing protocol mechanisms and parameters, such as acknowledgment schemes and packet sizes, that demonstrate the types of protocol needed for efficient use of wireless satellite-terrestrial networks.
Air pollution is a serious environmental health concern in the Hindu Kush Himalayan (HKH) region of south-central Asia, as rapid industrialization and population growth have led to increased anthropogenic emissions from transportation, residential, industrial, energy, and biomass burning sources. Natural emissions from dust and forest fires are additional sources of air pollutants that can exacerbate air quality in the region. The combination of the complex pollutant mixtures and atmospherically stable weather conditions during the winter monsoon can visibility reductions and hazardous air quality from persistent haze episodes. The Kathmandu Valley is especially vulnerable to extreme haze issues due to the surrounding mountains that restrict air movement and retains pollutants in the atmosphere. This study uses state-of-the-art satellite observations and modeling capabilities in conjunction with ground-based networks to provide a comprehensive data toolkit for advancing air quality monitoring and forecasting decisions in the HKH region. The toolkit includes new generation satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI), Geostationary Environment Monitoring Spectrometer (GEMS), and Advanced Meteorological Imager, which provide high spatiotemporal information on NO2, HCHO, SO2, O3, and aerosol optical depth (AOD). Particulate matter with diameters less than 2.5 micrometers (PM2.5) are derived from the satellite-retrieved AOD using ground-based observations and forecast model data. The satellite observations are also used to initialize and constrain forecast model systems designed for the HKH region. This talk will highlight the performance of the air quality toolkit for enhancing decision-making processes during exceptional air quality events in the region. Note: Presentation includes additional attachment of full presentation with sound and animation (best when viewed as slide show) with runtime of 15 min 32 secs
Semantic networks of frames are commonly used as a method of reasoning in many problems. In most of these applications the semantic network exists as a single entity in a single process environment. Advances in workstation hardware provide support for more sophisticated applications involving multiple processes, interacting in a distributed environment. In these applications the semantic network may well be distributed over several concurrently executing tasks. This paper describes the design and implementation of a frame based, distributed semantic network in which frames are accessed both through C Language Integrated Production System (CLIPS) expert systems and procedural C++ language programs. The application area is a knowledge based, cooperative decision making model utilizing both rule based and procedural experts.
This research project, entitled Wellbore Leakage Mitigation using Advanced Mineral Precipitation Strategies, was directed toward advancing mineral precipitation technologies to seal wellbore leaks and other potential carbon dioxide (CO 2 ) leakage pathways, including compromised wellbore cement and fracture networks of varying geometries throughout the wellbore and surrounding formation. The advanced mineral sealing techniques were evaluated in the laboratory and the field to expand the range of temperature, pressure, and chemical conditions where mineral precipitation could be used. Rates of enzymatically or thermally induced calcium carbonate precipitation (EICP, TICP) were determined as well as rates of enzyme inactivation at elevated temperatures (>60 °C). Immobilization was shown to enhance the thermal stability of urease enzyme and provide protection from inhibition in low pH conditions. Mineral seals promoted by EICP and TICP were used to seal fractured composite (cement/sandstone) and shale cores in high pressure reactors operated at temperatures greater than 55 °C and 130 °C, respectively. A computational model was updated to model processes of EICP and TICP. The work resulted in a successful field test, which showed that EICP in the presence of low pH fluids (CO 2 -impacted brine) could promote permeability reduction and seal a channel in the near-wellbore environment.