Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “interconnected network”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30

Real Space Imaging of Field-Driven Decision-Making in Nanomagnetic Galton Boards

A possible spintronic route to hardware implementation for decision-making involves injecting a domain wall into a bifurcated magnetic nanostrip resembling a Y-shaped junction. A decision is made when the domain wall chooses a particular path through the bifurcation. Recently, it was shown that a structure like a nanomagnetic Galton board, which is essentially an array of interconnected Y-shaped junctions, produces outcomes that are stochastic and therefore relevant to artificial neural networks. However, the exact mechanism leading to the robust nature of randomness is unknown. Here, in this study, we directly image the decision-making process in nanomagnetic Galton boards using Lorentz transmission electron microscopy. We identify that the stochasticity in nanomagnetic Galton boards arises as a culmination of (1) the topology of the injected domain wall, (2) dissimilarly sized vertices, and (3) the strength of the applied field. Our results pave the way to a detailed understanding of stochasticity in nanomagnetic networks.

lorentz microscopy↗

Resonant metasurface‐enabled quantum light sources for single‐photon emission and entangled photon‐pair generation

Light encodes information in multiple degrees of freedom (e.g., frequency, amplitude, and phase), enabling high‐speed, high‐bandwidth communication through fiber optics. Unlike classical light, quantum light (single or entangled photons) can transmit quantum states over long distances without loss of coherence, thereby coherently interconnecting quantum nodes for distributed quantum entanglement. Quantum light sources are critical for developing scalable quantum networks aimed at distributed quantum computing, quantum teleportation, and secure quantum communications. However, existing quantum light sources suffer from limited integrability, insufficient spectral and spatial tunability, and inefficiencies in achieving mass‐produced, deterministic, on‐demand quantum light generation. These limitations significantly hinder progress toward direct, on‐chip integration with quantum processing units and detectors – an essential step toward scalable quantum networks. Resonant metasurfaces that leverage photonic modes – such as Mie resonances, guided‐mode resonances, or symmetry‐protected bound states in the continuum – offer strong spatial and temporal confinement of electromagnetic fields, characterized by high quality factors and small mode volumes. These metasurfaces greatly enhance linear and nonlinear light‐matter interactions, making them ideal for efficient on‐chip quantum light generation and manipulation. Here, we describe recent advances in nanoscale quantum light sources and quantum photonic state manipulation enabled by resonant metasurfaces. We also provide an outlook on next‐generation miniaturized quantum light sources achievable through materials innovations in quantum emitters, the co‐design of resonant metasurfaces, and ultimately, the heterogeneous integration of emerging layered van der Waals materials with resonant metasurfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

New evidence for global tectonic zones on Venus

Venera 15 and 16 spacecraft images show clear evidence of major crustal disruptions on Venus which have been interpreted to indicate crustal divergence. Complementary to the divergent zones are mountain belts that border the continent-like high terrains. The requisite transcurrent motions appear to be manifested as diffuse shear zones. The rift zones form an interconnected transpolar system which ties in with previously recognized equatorial disruption zones, suggesting a global tectonic network. Several independent lines of evidence suggest that the tectonism may be geologically young.

Kozak, Richard C.↗

Optoelectronic Integrated Circuits For Neural Networks

Many threshold devices placed on single substrate. Integrated circuits containing optoelectronic threshold elements developed for use as planar arrays of artificial neurons in research on neural-network computers. Mounted with volume holograms recorded in photorefractive crystals serving as dense arrays of variable interconnections between neurons.

Psaltis, D.↗

Networking and AI systems: Requirements and benefits

The price performance benefits of network systems is well documented. The ability to share expensive resources sold timesharing for mainframes, department clusters of minicomputers, and now local area networks of workstations and servers. In the process, other fundamental system requirements emerged. These have now been generalized with open system requirements for hardware, software, applications and tools. The ability to interconnect a variety of vendor products has led to a specification of interfaces that allow new techniques to extend existing systems for new and exciting applications. As an example of the message passing system, local area networks provide a testbed for many of the issues addressed by future concurrent architectures: synchronization, load balancing, fault tolerance and scalability. Gold Hill has been working with a number of vendors on distributed architectures that range from a network of workstations to a hypercube of microprocessors with distributed memory. Results from early applications are promising both for performance and scalability.

Source record↗

Computational chaos in massively parallel neural networks

A fundamental issue which directly impacts the scalability of current theoretical neural network models to massively parallel embodiments, in both software as well as hardware, is the inherent and unavoidable concurrent asynchronicity of emerging fine-grained computational ensembles and the possible emergence of chaotic manifestations. Previous analyses attributed dynamical instability to the topology of the interconnection matrix, to parasitic components or to propagation delays. However, researchers have observed the existence of emergent computational chaos in a concurrently asynchronous framework, independent of the network topology. Researcher present a methodology enabling the effective asynchronous operation of large-scale neural networks. Necessary and sufficient conditions guaranteeing concurrent asynchronous convergence are established in terms of contracting operators. Lyapunov exponents are computed formally to characterize the underlying nonlinear dynamics. Simulation results are presented to illustrate network convergence to the correct results, even in the presence of large delays.

Barhen, Jacob↗

ESnet Requirements Review Program Through the IRI Lens: A Meta-Analysis of Workflow Patterns Across DOE Office of Science Programs (Final Report)

The Department of Energy (DOE) ensures America’s security and prosperity by addressing its energy, environmental, and nuclear challenges through transformative science and technology solutions. The DOE’s Office of Science (SC) delivers groundbreaking scientific discoveries and major scientific tools that transform our understanding of nature and advance the energy, economic, and national security of the United States. The SC’s programs advance DOE mission science across a wide range of disciplines and have developed the research infrastructure needed to remain at the forefront of scientific discovery. The DOE SC’s world-class research infrastructure — exemplified by the 28 SC scientific user facilities — provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance core DOE mission science for its sponsor SC program and to stimulate a rich discovery and innovation ecosystem. Research communities gather and flourish around each user facility, bringing together diverse perspectives. A hallmark of many facilities is the large population of students, postdoctoral researchers, and early-career scientists who contribute as full-fledged users. These facility staff and users collaborate over years to devise new approaches to utilizing the user facility’s core capabilities. The history of the SC user facilities has many examples of wildly inventive researchers challenging operational orthodoxy to pioneer new vistas of discovery; for example, the use of the synchrotron X-ray light sources for study of proteins and other large biological molecules. This continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress. Within this research ecosystem, the high-performance computing (HPC) and networking user facilities stewarded by SC’s Advanced Scientific Computing Research (ASCR) program play a dynamic cross-cutting role, enabling complex workflows demanding high performance data, networking, and computing solutions. The DOE SC’s three HPC user facilities and the Energy Sciences Network (ESnet) high-performance research network serve all of the SC’s programs as well as the global research community. Argonne Leadership Computing Facility (ALCF), the National Energy Research Scientific Computing Center (NERSC), and Oak Ridge Leadership Computing Facility (OLCF) conceive, build, and provide access to a range of supercomputing, advanced computing, and large-scale data-infrastructure platforms, while ESnet interconnects DOE SC research infrastructure and enables seamless exchange of scientific data. All four facilities operate testbeds to expand the frontiers of computing and networking research. Together, the ASCR facilities enterprise seeks to understand and meet the needs and requirements across SC and DOE domain science programs and priority efforts, highlighted by the formal requirements reviews (RRs) methodology. In recent years, the research communities around the SC user facilities have begun experimenting with and demanding solutions integrated with HPC and data infrastructure. This rise of integrated-science approaches is documented in many community and high-level government reports. At the dawn of the era of exascale science and the acceleration of artificial intelligence (AI) innovation, there is a broad need for integrated computational, data, and networking solutions. In response to these drivers, DOE has developed a vision for an Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation.

42 ENGINEERING↗

Machine learning unifies flexibility and efficiency of spinodal structure generation for stochastic biomaterial design

Abstract Porous biomaterials design for bone repair is still largely limited to regular structures (e.g. rod-based lattices), due to their easy parameterization and high controllability. The capability of designing stochastic structure can redefine the boundary of our explorable structure–property space for synthesizing next-generation biomaterials. We hereby propose a convolutional neural network (CNN) approach for efficient generation and design of spinodal structure—an intriguing structure with stochastic yet interconnected, smooth, and constant pore channel conducive to bio-transport. Our CNN-based approach simultaneously possesses the tremendous flexibility of physics-based model in generating various spinodal structures (e.g. periodic, anisotropic, gradient, and arbitrarily large ones) and comparable computational efficiency to mathematical approximation model. We thus successfully design spinodal bone structures with target anisotropic elasticity via high-throughput screening, and directly generate large spinodal orthopedic implants with desired gradient porosity. This work significantly advances stochastic biomaterials development by offering an optimal solution to spinodal structure generation and design.

59 BASIC BIOLOGICAL SCIENCES↗

Packet router with virtual channel hop buffer control

An integrated circuit includes a network on chip (NOC) that includes a plurality of processing elements and a plurality of NOC nodes, interconnected to the plurality of processing elements. The integrated circuit includes logic that is configured to: increment by one, a virtual channel identifier to produce an incremented destination VC identifier, the virtual channel (VC) identifier associated with at least portion of a packet stored in at least one virtual channel buffer; determine that a destination virtual channel buffer corresponding to the incremented destination VC identifier in a destination NOC node in the NOC is available to store the portion of the packet; and in response to the determination, send the portion of the packet and the incremented destination VC identifier to the destination NOC node.

97 MATHEMATICS AND COMPUTING↗

Large-scale effects of supernova remnants on the Galaxy - Generation and maintenance of a hot network of tunnels

It is found that a supernova rate on the order of 1 per 50 years in the gaseous disk of our Galaxy is sufficient to generate and maintain throughout the interstellar medium a mesh of interconnected tunnels containing very low-density gas. This tunnel system would have a density of approximately 0.01 per cu cm, a temperature of about 1,000,000 K, very low magnetic field strength, tunnel radii of about 10 pc, and would occupy roughly half the interstellar volume. Such a tunnel network may already have been observed in soft X-ray emission, in ultraviolet absorption of O VI against background stars, in the seemingly chaotic distribution of local H I, and in the stringy appearance of velocity-correlated large-scale H I features.

Cox, D. P.↗

Characterization of Extremes and Compound Impacts: Applications of Machine Learning and Interpretable Neural Networks

Focal Area: This white paper responds to Focal area III by exploring data fusion, learning and explainable AI methods in characterizing hydrological extremes and interconnections. It also addresses Focal area II by using probabilistic AI and ensemble ML for predicting extremes and compound extremes. Science Challenge: A key question associated with the integrated water (or hydrological) cycle grand challenge in the Earth and Environmental Systems Sciences Division (EESSD) strategic plan, is how the frequency and intensity of hydrological events will change. Prediction of the tail behavior (extremes) of the hydrological cycle is especially challenging, because of their stochasticity and low probability. These extreme events and their compound impacts have significant societal and economic consequences. It is anticipated for the next-generation Earth System models (ESMs), that model predictability of the water cycle will improve with increased resolution (e.g., regionally refined E3SM), advanced software and computational architectures, and improved model physics based on the data from ARM measurements and high-fidelity models. However, the challenges for predictability of low-probability high-impact extreme events will unlikely be alleviated with conventional modeling and data-driven approaches, as ESMs are calibrated largely for capturing the high-frequency mean climate states. Recent AI and ML applications have shown great potential in quantifying well-defined climate extremes (e.g., supervised learning of tropical cyclones/atmospheric rivers by ClimateNet1) but few efforts are dedicated to compound events, extreme drivers and uncertainty estimation. We envision the opportunity to develop and apply ML and interpretable AI methods extended on the existing efforts, specifically, for: (1) identification of compound extremes, (2) diagnosing drivers of extremes, (3) bias correction in extreme predictions and (4) probabilistic modeling of extremes.

54 ENVIRONMENTAL SCIENCES↗

Testing interconnected VLSI circuits in the Big Viterbi Decoder

The Big Viterbi Decoder (BVD) is a powerful error-correcting hardware device for the Deep Space Network (DSN), in support of the Galileo and Comet Rendezvous Asteroid Flyby (CRAF)/Cassini Missions. Recently, a prototype was completed and run successfully at 400,000 or more decoded bits per second. This prototype is a complex digital system whose core arithmetic unit consists of 256 identical very large scale integration (VLSI) gate-array chips, 16 on each of 16 identical boards which are connected through a 28-layer, printed-circuit backplane using 4416 wires. Special techniques were developed for debugging, testing, and locating faults inside individual chips, on boards, and within the entire decoder. The methods are based upon hierarchical structure in the decoder, and require that chips or boards be wired themselves as Viterbi decoders. The basic procedure consists of sending a small set of known, very noisy channel symbols through a decoder, and matching observables against values computed by a software simulation. Also, tests were devised for finding open and short-circuited wires which connect VLSI chips on the boards and through the backplane.

Onyszchuk, I. M.↗

High-fidelity remote entanglement of trapped atoms mediated by time-bin photons

Abstract Photonic interconnects between quantum processing nodes are likely the only way to achieve large-scale quantum computers and networks. The bottleneck in such an architecture is the interface between well-isolated quantum memories and flying photons. We establish high-fidelity entanglement between remotely separated trapped atomic qubit memories, mediated by photonic qubits stored in the timing of their pulses. Such time-bin encoding removes sensitivity to polarization errors, enables long-distance quantum communication, and is extensible to quantum memories with more than two states. Using a measurement-based error detection process and suppressing a fundamental source of error due to atomic recoil, we achieve an entanglement fidelity of 97% and show that fundamental limits due to atomic recoil still allow fidelities in excess of 99.9%.

Science & Technology - Other Topics↗

Measurement-Based Approach for Inertia-Trend Analysis of the US Western Interconnection

Rising deployment of inverter-based resources (IBRs), characterized by a lack of rotating mass, is decreasing the total inertia of the system. This can lead to an increased Rate of Change of Frequency (RoCoF) during the disturbance and false activation of protective devices. There is a need to assess the inertia over the past decade amidst the evolving landscape of renewable energy sources to develop strategies for integrating energy storage, enhancing resilience measures, and ensuring the stable and reliable operation of the grid. Therefore, a realistic assessment of the inertia trend using a measurement-based approach that addresses the limitations of existing models is proposed. An inertia study of the Western Interconnection in the United States is performed utilizing the data from 2013 to 2022, obtained from FNET/ GridEye network. The three-second RoCoF time window is chosen for the study as it showed an optimum balance between a strong correlation with the power imbalance (ΔP) and minimum inclusion of primary response from governor. The obtained inertia trend result shows a small percentage declination of inertia over the decade. By examining the result alongside a generation mix graph, insights are gained into the dynamic interplay between shifting energy landscape and system inertia.

Dulal, Saurav↗

OSI in the NASA science internet: An analysis

The Open Systems Interconnection (OSI) protocol suite is a result of a world-wide effort to develop international standards for networking. OSI is formalized through the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). The goal of OSI is to provide interoperability between network products without relying on one particular vendor, and to do so on a multinational basis. The National Institute for Standards and Technology (NIST) has developed a Government OSI Profile (GOSIP) that specified a subset of the OSI protocols as a Federal Information Processing Standard (FIPS 146). GOSIP compatibility has been adopted as the direction for all U.S. government networks. OSI is extremely diverse, and therefore adherence to a profile will facilitate interoperability within OSI networks. All major computer vendors have indicated current or future support of GOSIP-compliant OSI protocols in their products. The NASA Science Internet (NSI) is an operational network, serving user requirements under NASA's Office of Space Science and Applications. NSI consists of the Space Physics Analysis Network (SPAN) that uses the DECnet protocols and the NASA Science Network (NSN) that uses TCP/IP protocols. The NSI Project Office is currently working on an OSI integration analysis and strategy. A long-term goal is to integrate SPAN and NSN into one unified network service, using a full OSI protocol suite, which will support the OSSA user community.

Nitzan, Rebecca↗

Data distribution satellite

The Data Distribution Satellite (DDS), operating in conjunction with the planned space network, the National Research and Education Network and its commercial derivatives, would play a key role in networking the emerging supercomputing facilities, national archives, academic, industrial, and government institutions. Centrally located over the United States in geostationary orbit, DDS would carry sophisticated on-board switching and make use of advanced antennas to provide an array of special services. Institutions needing continuous high data rate service would be networked together by use of a microwave switching matrix and electronically steered hopping beams. Simultaneously, DDS would use other beams and on board processing to interconnect other institutions with lesser, low rate, intermittent needs. Dedicated links to White Sands and other facilities would enable direct access to space payloads and sensor data. Intersatellite links to a second generation ATDRS, called Advanced Space Data Acquisition and Communications System (ASDACS), would eliminate one satellite hop and enhance controllability of experimental payloads by reducing path delay. Similarly, direct access would be available to the supercomputing facilities and national data archives. Economies with DDS would be derived from its ability to switch high rate facilities amongst users needed. At the same time, having a CONUS view, DDS would interconnect with any institution regardless of how remote. Whether one needed high rate service or low rate service would be immaterial. With the capability to assign resources on demand, DDS will need only carry a portion of the resources needed if dedicated facilities were used. Efficiently switching resources to users as needed, DDS would become a very feasible spacecraft, even though it would tie together the space network, the terrestrial network, remote sites, 1000's of small users, and those few who need very large data links intermittently.

Stevens, Grady H.↗

Establishing Co‐Continuous Network of Conjugated Polymers and Elastomers for High‐Performance Polymer Solar Cells with Extreme Stretchability

High power conversion efficiency (PCE) and mechanical robustness are prerequisites for wearable applications of organic solar cells (OSCs). However, stretchability of present active systems (i.e., crack-onset strain (COS) < 30%) should be improved. While introducing elastomers into active systems is considered a simple method for improving stretchability, the inclusion of elastomers typically results in a decrease in PCE of the OSC with a limited enhancement in the stretchability due to lack of interconnected electrical and mechanical pathways. In this study, it is developed efficient and intrinsically stretchable (IS)-OSCs with exceptional mechanical robustness, by constructing co-continuous networks of conjugated polymers (D18) and elastomers (SEBS) within active layers. It is demonstrated that the blend film with a specific ratio (40:60 w/w) of D18:SEBS is crucial for forming co-continuous structures, establishing well-connected mechanical and electrical channels. Consequently, D18 0.4 :SEBS 0.6 /L8-BO OSCs achieve 16-times higher stretchability (COS = 126%) than the OSCs based on D18/L8-BO (COS = 8%), while achieving 4-times higher PCE (12.13%) compared to the OSCs based on SEBS-rich active layers (D18 0.2 :SEBS 0.8 /L8-BO, PCE = 3.15%). Furthermore, D18 0.4 :SEBS 0.6 -based IS-OSCs preserve 86 and 90% of original PCEs at 50% strain and after 200 stretching/releasing cycles with 15% strain, respectively, demonstrating the highest mechanical robustness among reported IS-OSCs.

14 SOLAR ENERGY↗