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At least 37 records · Page 2

Distribution System Congestion Management - A Survey of Reliable Integration for Aggregated Resources and Microgrids

Rising penetration of consumer-owned Distribution Grid Resources (DGRs), increasingly managed by third party aggregators and enrolled in grid services and wholesale market programs, can create localized congestion in distribution networks. Managing these constraints is challenging due to a persistent coordination and information gap: utilities are accountable for reliability and have network topology and state visibility, while aggregators control the DGR capability needed to relieve congestion. This survey synthesizes congestion management solutions for distribution systems with high DGR penetration, covering both market-based mechanisms (distribution level markets, locational pricing, flexibility auctions) and non-market-based solutions (network reconfiguration, direct DGR control, demand response, curtailment, etc.). The literature is organized across three decision horizons: long term planning, operational planning, and real-time operation. Special attention is devoted to emerging distribution system operator architectures and coordination frameworks spanning transmission system operators, aggregators, and microgrids. Drawing on recent case studies and implementations, we distill best practices, identify key technical and economic barriers, and outline research directions. The evidence points to a shift toward integrated congestion management that combines market signals with technical controls, enabled by improved monitoring, forecasting, and closed loop control capabilities.

Active Distribution Networks (ADN)

Bond-centric modular design of protein assemblies

Directional interactions that generate regular coordination geometries are a powerful means of guiding molecular and colloidal self-assembly, but implementing such high-level interactions with proteins remains challenging due to their complex shapes and intricate interface properties. Here we describe a modular approach to protein nanomaterial design inspired by the rich chemical diversity that can be generated from the small number of atomic valencies. We design protein building blocks using deep learning-based generative tools, incorporating regular coordination geometries and tailorable bonding interactions that enable the assembly of diverse closed and open architectures guided by simple geometric principles. Experimental characterization confirms the successful formation of more than 20 multicomponent polyhedral protein cages, two-dimensional arrays and three-dimensional protein lattices, with a high (10%–50%) success rate and electron microscopy data closely matching the corresponding design models. Due to modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable networks for designer nanomaterials.

Biomaterials – proteins

Enhancing Power Distribution System Resilience with Fusion-GNN: A Dynamic Graph Representation Learning Approach

This paper explores the applications of Fusion Graph Neural Network (FuGNN) on power distribution systems. FuGNN effectively models dynamic networks with evolving topology and features. Applied to power system network reconfiguration, FuGNN demonstrates its feasibility in optimizing switch configurations to minimize unserved loads and operational costs during extreme events. Additionally, FuGNN supports various downstream tasks, such as node feature prediction, further enhancing its versatility and applicability in power system resilience.

Liu, Boming

ARM-IRL: Adaptive Resilience Metric Quantification Using Inverse Reinforcement Learning

The resilience of safety-critical systems is gaining importance due to the rise in cyber and physical threats, especially within critical infrastructure. Traditional static resilience metrics may not capture dynamic system states, leading to inaccurate assessments and ineffective responses to cyber threats. This work aims to develop a data-driven, adaptive method for resilience metric learning. We propose a data-driven approach using inverse reinforcement learning (IRL) to learn a single, adaptive resilience metric. The method infers a reward function from expert control actions. Unlike previous approaches using static weights or fuzzy logic, this work applies adversarial inverse reinforcement learning (AIRL), training a generator and discriminator in parallel to learn the reward structure and derive an optimal policy. The proposed approach is evaluated on multiple scenarios: optimal communication network rerouting, power distribution network reconfiguration, and cyber–physical restoration of critical loads using the IEEE 123-bus system. The adaptive, learned resilience metric enables faster critical load restoration in comparison to conventional RL approaches.

97 MATHEMATICS AND COMPUTING

High-Efficiency K-Band Space Traveling-Wave Tube Amplifier for Near-Earth High Data Rate Communications

The RF performance of a new K-Band helix conduction cooled traveling-wave tube amplifier (TWTA) is presented in this paper. A total of three such units were manufactured, tested and delivered. The first unit is currently flying onboard NASA s Lunar Reconnaissance Orbiter (LRO) spacecraft and has flawlessly completed over 2000 orbits around the Moon. The second unit is a proto-flight model. The third unit will fly onboard NASA s International Space Station (ISS) as a very compact and lightweight transmitter package for the Communications, Navigation and Networking Reconfigurable Testbed (CoNNeCT), which is scheduled for launch in 2011. These TWTAs were characterized over the frequencies 25.5 to 25.8 GHz. The saturated RF output power is >40 W and the saturated RF gain is >46 dB. The saturated AM-to- PM conversion is 3.5 /dB and the small signal gain ripple is 0.46 dB peak-to-peak. The overall efficiency of the TWTA, including that of the electronic power conditioner (EPC) is as high as 45 percent.

Simons, Rainee N.

High-Efficiency K-Band Space Traveling-Wave Tube Amplifier for Near-Earth High Data Rate Communications

The RF performance of a new K-Band helix conduction cooled traveling-wave tube amplifier (TWTA), is presented in this paper. A total of three such units were manufactured, tested and delivered. The first unit is currently flying onboard NASA's Lunar Reconnaissance Orbiter (LRO) spacecraft and has flawlessly completed over 2000 orbits around the Moon. The second unit is a proto-flight model. The third unit will fly onboard NASA's International Space Station (ISS) as a very compact and lightweight transmitter package for the Communications, Navigation and Networking Reconfigurable Testbed (CoNNeCT), which is scheduled for launch in 2011. These TWTAs were characterized over the frequencies 25.5 to 25.8 GHz. The saturated RF output power is greater than 40 W and the saturated RF gain is greater than 46 dB. The saturated AM-to-PM conversion is 3.5 /dB and the small signal gain ripple is 0.46 dB peak-to-peak. The overall efficiency of the TWTA, including that of the electronic power conditioner (EPC) is as high as 45%.

Simons, Rainee N.

Whispering-Gallery-Mode Tunable Narrow-Band-Pass Filter

An experimental tunable, narrow-band-pass electro-optical filter is based on a whispering-gallery resonator. This device is a prototype of tunable filters needed for the further development of reconfigurable networking wavelength-division multiplexers and communication systems that utilize radio-frequency (more specifically, microwave) subcarrier signals on optical carrier signals. The characteristics of whispering-gallery resonators that make them attractive for such applications include high tuning speed, compactness, wide tuning range, low power consumption, and compatibility with single-mode optical fibers. In addition, relative to Fabry-Perot resonators, these devices offer advantages of greater robustness and lower cost. As described in several prior NASA Tech Briefs articles, a whispering-gallery resonator is a spheroidal, disk-like, or toroidal body made of a highly transparent material. It is so named because it is designed to exploit whispering-gallery electromagnetic modes, which are waveguide modes that propagate circumferentially and are concentrated in a narrow toroidal region centered on the equatorial plane and located near the outermost edge. The experimental whispering-gallery tunable filter (see figure) is made from a disk of Z-cut LiNbO3 of 4.8-mm diameter and 0.17-mm thickness. The perimeter of the disk is rounded to a radius of curvature of 100 m. Metal coats on the flat faces of the disk serve as electrodes for exploiting the electro-optical effect in LiNbO3 for tuning. There is no metal coat on the rounded perimeter region, where the whispering-gallery modes propagate. Light is coupled from an input optical fiber into the whispering-gallery modes by means of a diamond prism. Another diamond prism is used to couple light from the whispering-gallery modes to an output optical fiber. This device is designed and operated to exploit transverse magnetic (TM) whispering- gallery modes, rather than transverse electric (TE) modes because the resonance quality factors (Q values) of the TM modes are higher. If Q values were not of major concern, it would be better to use the TE modes because the electro-optical shifts of the TE modes are 3 times those of the TM modes.

Savchenkov, Anatoliy

Test Waveform Applications for JPL STRS Operating Environment

This software demonstrates use of the JPL Space Telecommunications Radio System (STRS) Operating Environment (OE), tests APIs (application programming interfaces) presented by JPL STRS OE, and allows for basic testing of the underlying hardware platform. This software uses the JPL STRS Operating Environment ["JPL Space Tele com - munications Rad io System Operating Environment,"(NPO-4776) NASA Tech Briefs, commercial edition, Vol. 37, No. 1 (January 2013), p. 47] to interact with the JPL-SDR Software Defined Radio developed for the CoNNeCT (COmmunications, Navigation, and Networking rEconfigurable Testbed) Project as part of the SCaN Testbed installed on the International Space Station (ISS). These are the first applications that are compliant with the new NASA STRS Architecture Standard. Several example waveform applications are provided to demonstrate use of the JPL STRS OE for the JPL-SDR platform used for the CoNNeCT Project. The waveforms provide a simple digitizer and playback capability for the SBand RF slice, and a simple digitizer for the GPS slice [CoNNeCT Global Positioning System RF Module, (NPO-47764) NASA Tech Briefs, commercial edition, Vol. 36, No. 3 (March 2012), p. 36]. These waveforms may be used for hardware test, as well as for on-orbit or laboratory checkout. Additional example waveforms implement SpaceWire and timer modules, which can be used for time transfer and demonstration of communication between the two Xilinx FPGAs in the JPLSDR. The waveforms are also compatible with ground-based use of the JPL STRS OE on radio breadboards and Linux.

Lux, James P.

Combining System Safety and Reliability to Ensure NASA CoNNeCT's Success

Hazard Analysis, Failure Modes and Effects Analysis (FMEA), the Limited-Life Items List (LLIL), and the Single Point Failure (SPF) List were applied by System Safety and Reliability engineers on NASA's Communications, Navigation, and Networking reConfigurable Testbed (CoNNeCT) Project. The integrated approach involving cross reviews of these reports by System Safety, Reliability, and Design engineers resulted in the mitigation of all identified hazards. The outcome was that the system met all the safety requirements it was required to meet.

Havenhill, Maria

Reconfigurable optical interconnection network for multimode optical fiber sensor arrays

A single-source, single-detector architecture has been developed to implement a reconfigurable optical interconnection network multimode optical fiber sensor arrays. The network was realized by integrating LiNbO3 electrooptic (EO) gratings working at the Raman Na regime and a massive fan-out waveguide hologram (WH) working at the Bragg regime onto a multimode glass waveguide. The glass waveguide utilized the whole substrate as a guiding medium. A 1-to-59 massive waveguide fan-out was demonstrated using a WH operating at 514 nm. Measured diffraction efficiency of 59 percent was experimentally confirmed. Reconfigurability of the interconnection was carried out by generating an EO grating through an externally applied electric field. Unlike conventional single-mode integrated optical devices, the guided mode demonstrated has an azimuthal symmetry in mode profile which is the same as that of a fiber mode.

Chen, R. T.

SPARTAN (Scalable Probabilistic Application Reconfigurable Tensor Autonomous Network)

The technical founder of Ludwig Computing Inc has been competitively selected for support by Cyclotron Road, a U.S. Department of Energy (DOE) Advanced Manufacturing Office (AMO) Lab-Embedded Entrepreneurship Program (LEEP) through an approved merit review process. Ludwig Computing Inc, supported by the U.S. Department of Energy's Advanced Manufacturing Office through the Cyclotron Road program, has investigated the advantages of probabilistic computing for real-world compute-intensive applications. This research adds to the understanding of alternative computing paradigms by exploring a unique hardware-software co-design that integrates quantum computing methods with nature-inspired problem-solving techniques. The project's focus on areas such as combinatorial optimization, graph analytics, and machine learning demonstrates the potential for significant advancements in computational efficiency and performance. By harnessing natural randomness to streamline large circuits into fewer devices, Ludwig's approach enables massive parallelism, potentially offering higher throughput, speed, and energy efficiency compared to conventional hardware solutions. This work benefits the public by paving the way for more efficient computing solutions that could address complex real-world problems while potentially reducing energy consumption in data-intensive industries.

97 MATHEMATICS AND COMPUTING

Reconfigurable modular computer networks for spacecraft on-board processing

The core electronics subsystems on unmanned spacecraft, which have been sent over the last 20 years to investigate the moon, Mars, Venus, and Mercury, have progressed through an evolution from simple fixed controllers and analog computers in the 1960's to general-purpose digital computers in current designs. This evolution is now moving in the direction of distributed computer networks. Current Voyager spacecraft already use three on-board computers. One is used to store commands and provide overall spacecraft management. Another is used for instrument control and telemetry collection, and the third computer is used for attitude control and scientific instrument pointing. An examination of the control logic in the instruments shows that, for many, it is cost-effective to replace the sequencing logic with a microcomputer. The Unified Data System architecture considered consists of a set of standard microcomputers connected by several redundant buses. A typical self-checking computer module will contain 23 RAMs, two microprocessors, one memory interface, three bus interfaces, and one core building block.

Rennels, D. A.

Reconfigurations in Brain Networks Upon Awakening From Slow Wave Sleep: Interventions and Implications in Neural Communication

Sleep inertia is the brief period of impaired alertness and performance experienced immediately after waking. Little is known about the neural mechanisms underlying this phenomenon. A better understanding of the neural processes during sleep inertia may offer insight into the awakening process. We observed brain activity every 15 min for 1 hr following abrupt awakening from slow wave sleep during the biological night. Using 32-channel electroencephalography, a network science approach, and a within-subject design, we evaluated power, clustering coefficient, and path length across frequency bands under both a control and a polychromatic short-wavelength-enriched light intervention condition. We found that under control conditions, the awakening brain is typified by an immediate reduction in global theta, alpha, and beta power. Simultaneously, we observed a decrease in the clustering coefficient and an increase in path length within the delta band. Exposure to light immediately after awakening ameliorated changes in clustering. Our results suggest that long-range network communication within the brain is crucial to the awakening process and that the brain may prioritize these long-range connections during this transitional state. Our study highlights a novel neurophysiological signature of the awakening brain and provides a potential mechanism by which light improves performance after waking.

EEG

Characterization of robotics parallel algorithms and mapping onto a reconfigurable SIMD machine

The kinematics, dynamics, Jacobian, and their corresponding inverse computations are six essential problems in the control of robot manipulators. Efficient parallel algorithms for these computations are discussed and analyzed. Their characteristics are identified and a scheme on the mapping of these algorithms to a reconfigurable parallel architecture is presented. Based on the characteristics including type of parallelism, degree of parallelism, uniformity of the operations, fundamental operations, data dependencies, and communication requirement, it is shown that most of the algorithms for robotic computations possess highly regular properties and some common structures, especially the linear recursive structure. Moreover, they are well-suited to be implemented on a single-instruction-stream multiple-data-stream (SIMD) computer with reconfigurable interconnection network. The model of a reconfigurable dual network SIMD machine with internal direct feedback is introduced. A systematic procedure internal direct feedback is introduced. A systematic procedure to map these computations to the proposed machine is presented. A new scheduling problem for SIMD machines is investigated and a heuristic algorithm, called neighborhood scheduling, that reorders the processing sequence of subtasks to reduce the communication time is described. Mapping results of a benchmark algorithm are illustrated and discussed.

Lee, C. S. G.

Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

Burken, John J.

Automatic protection switching in an entanglement-based quantum network

We demonstrate multihop two-qubit entanglement distribution in a reconfigurable quantum network over deployed fiber. Using quantum-compatible software-defined networking, we distribute entanglement across six nodes in three buildings, with adaptive link recovery mitigating transmission disruptions.

Alshowkan, Muneer [ORNL] (ORCID:0000000264293450)

Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft

Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.

Burken, John J.