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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

The evolution of the power system to the reliable, effi- cient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of re- newable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distri- bution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for co- optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this frame- work, microgrids encompass consumers, distributed renewables and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the devel- opment of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic op- timization, including decomposition and stochastic dual dynamic programming.

14 SOLAR ENERGY↗
DOE OSTI2016

Mean field dynamics of networks of delay-coupled noisy excitable units

We use the mean-field approach to analyze the collective dynamics in macroscopic networks of stochastic Fitzhugh-Nagumo units with delayed couplings. The conditions for validity of the two main approximations behind the model, called the Gaussian approximation and the Quasi-independence approximation, are examined. It is shown that the dynamics of the mean-field model may indicate in a self-consistent fashion the parameter domains where the Quasi-independence approximation fails. Apart from a network of globally coupled units, we also consider the paradigmatic setup of two interacting assemblies to demonstrate how our framework may be extended to hierarchical and modular networks. In both cases, the mean-field model can be used to qualitatively analyze the stability of the system, as well as the scenarios for the onset and the suppression of the collective mode. In quantitative terms, the mean-field model is capable of predicting the average oscillation frequency corresponding to the global variables of the exact system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Synchronization in Complex Oscillator Networks and Smart Grids

The emergence of synchronization in a network of coupled oscillators is a fascinating topic in various scientific disciplines. A coupled oscillator network is characterized by a population of heterogeneous oscillators and a graph describing the interaction among them. It is known that a strongly coupled and sufficiently homogeneous network synchronizes, but the exact threshold from incoherence to synchrony is unknown. Here we present a novel, concise, and closed-form condition for synchronization of the fully nonlinear, non-equilibrium, and dynamic network. Our synchronization condition can be stated elegantly in terms of the network topology and parameters, or equivalently in terms of an intuitive, linear, and static auxiliary system. Our results significantly improve upon the existing conditions advocated thus far, they are provably exact for various interesting network topologies and parameters, they are statistically correct for almost all networks, and they can be applied equally to synchronization phenomena arising in physics and biology as well as in engineered oscillator networks such as electric power networks. We illustrate the validity, the accuracy, and the practical applicability of our results in complex networks scenarios and in smart grid applications.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Man-machine cooperation in advanced teleoperation

Teleoperation experiments at JPL have shown that advanced features in a telerobotic system are a necessary condition for good results, but that they are not sufficient to assure consistently good performance by the operators. Two or three operators are normally used during training and experiments to maintain the desired performance. An alternative to this multi-operator control station is a man-machine interface embedding computer programs that can perform some of the operator's functions. In this paper we present our first experiments with these concepts, in which we focused on the areas of real-time task monitoring and interactive path planning. In the first case, when performing a known task, the operator has an automatic aid for setting control parameters and camera views. In the second case, an interactive path planner will rank different path alternatives so that the operator will make the correct control decision. The monitoring function has been implemented with a neural network doing the real-time task segmentation. The interactive path planner was implemented for redundant manipulators to specify arm configurations across the desired path and satisfy geometric, task, and performance constraints.

Fiorini, Paolo↗
DOE OSTI2025

Real-World Cyber Security Demonstration for Networked Electric Drives

In this article, we present the design and implementation of a cyber-physical security testbed for networked electric drive systems, aimed at conducting real-world security demonstrations. To our knowledge, this is one of the first security testbeds for networked electric drives, seamlessly integrating the domains of power electronics and computer science, and cybersecurity. By doing so, the testbed offers a comprehensive platform to explore and understand the intricate and often complex interactions between cyber and physical systems. The core of our testbed consists of four electric machine drives, meticulously configured to emulate small-scale but realistic information technology (IT) and operational technology (OT) networks. This setup both provides a controlled environment for simulating a wide array of cyber-attacks, and mirrors potential real-world attack scenarios with a high degree of fidelity. The testbed serves as an invaluable resource for the study of cyber-physical security, offering a practical and dynamic platform for testing and validating cybersecurity measures in the context of networked electric drive systems. As a concrete example of the testbed's capabilities, we have developed and implemented a Python-based script designed to execute step-stone attacks over a wireless local area network (WLAN). This script leverages a sequence of target IP addresses, simulating a real-world attack vector that could be exploited by adversaries. To counteract such threats, we demonstrate the efficacy of our developed cyber-attack detection algorithms, which are integral to our testbed's security framework. Furthermore, the testbed incorporates a real-time visualization system using InfluxDB and Grafana, providing a dynamic and interactive representation of networked electric drives and their associated security monitoring mechanisms. This visualization component not only enhances the testbed's usability but also offers insightful, real-time data for researchers and practitioners, thereby facilitating a deeper understanding of cyber-physical security dynamics in networked electric drive systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

ChatGrid: Power Grid Visualization Empowered by Large Language Model

This paper presents a novel open framework, ChatGrid, for easy, intuitive, and interactive geospatial visualization of large-scale transmission networks. ChatGrid uses state-of-the-art techniques for geospatial visualization of large networks including 2.5D views, animated flows, hierarchical and level-based filtering, and aggregation to provide visual information in an easy, cognitive manner. The highlight of ChatGrid is a natural language query based interface powered by large language model (ChatGPT) that offers an enhanced interactive experience whereby the user asks a question and ChatGrid provides the information both in text and visual. We discuss the architecture, implementation, design decisions, and usage of large language model for ChatGrid.

Jin, Sichen↗
DOE OSTI2017

Software-defined Quantum Networking Ecosystem

The software enables a user to perform modeling and simulation of software-defined quantum networks. The software addresses the problem of how to synchronize transmission of quantum and classical signals through multi-node networks and to demonstrate quantum information protocols such as quantum teleportation. The software approaches this problem by generating a graphical model of the underlying network and attributing properties to each node and link in the graph. The graphical model is then simulated using a combination of discrete-event simulators to calculate the expected state of each node and link in the graph at a future time. A user interacts with the software by providing an initial network model and instantiating methods for the nodes to transmit information with each other. This includes writing application scripts in python that make use of the software library interfaces. A user then initiates the application scripts, which invokes the software simulation. The user then uses the built-in diagnostic tools to query the state of the simulation and to collect statistics on synchronization.

Humble, Travis S.↗
NASA NTRS2018

Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia From Aerosol Robotic Network and Satellite Remote Sensing

Analysis of Sun photometer measured and satellite retrieved aerosol optical depth (AOD) datahas shown that major aerosol pollution events with very highfine mode AOD (>1.0 in midvisible) in theChina/Korea/Japan region are often observed to be associated with significant cloud cover. This makesremote sensing of these events difficult even for high temporal resolution Sun photometer measurements.Possible physical mechanisms for these events that have high AOD include a combination of aerosolhumidification, cloud processing, and meteorological covariation with atmospheric stability andconvergence. The new development of Aerosol Robotic Network Version 3 Level 2 AOD with improved cloudscreening algorithms now allow for unprecedented ability to monitor these extremefine mode pollutionevents. Further, the spectral deconvolution algorithm (SDA) applied to Level 1 data (L1; no cloud screening)provides an even more comprehensive assessment offine mode AOD than L2 in current and previous dataversions. Studying the 2012 winter-summer period, comparisons of Aerosol Robotic Network L1 SDA dailyaveragefine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer satellite remotesensing of AOD often did not retrieve and/or identify some of the highestfine mode AOD events in thisregion. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDAfinemode AOD was significantly higher in magnitude, particularly for the highest AOD events that were oftenassociated with significant cloudiness.

Eck, T. F.↗
DOE OSTI2025

Accuracy and capacity of modern Hopfield networks with synaptic noise.

We study the retrieval accuracy and capacity of modern Hopfield networks of with two-state (Ising) spins interacting via modified Hebbian 𝑛 -spin interactions. In particular, we consider systems where the interactions deviate from the Hebb rule through additive or multiplicative noise or through clipping or deleting interactions. We find that the capacity scales as 𝑁𝑛−1 with the number of spins 𝑁 in all cases, but with a prefactor reduced compared to the Hebbian case. For 𝑛=2 our results agree with the previously known results for the conventional 𝑛=2 Hopfield network.

Bhattacharjee, Sharba↗
NASA NTRS2015

Optical Meteor Systems Used by the NASA Meteoroid Environment Office

The NASA Meteoroid Environment Office (MEO) uses two main meteor camera networks to characterize the meteoroid environment: an all sky system and a wide field system to study cm and mm size meteors respectively. The NASA All Sky Fireball Network consists of fifteen meteor video cameras in the United States, with plans to expand to eighteen cameras by the end of 2015. The camera design and All-Sky Guided and Real-time Detection (ASGARD) meteor detection software [1, 2] were adopted from the University of Western Ontario's Southern Ontario Meteor Network (SOMN). After seven years of operation, the network has detected over 12,000 multi-station meteors, including meteors from at least 53 different meteor showers. The network is used for speed distribution determination, characterization of meteor showers and sporadic sources, and for informing the public on bright meteor events. The NASA Wide Field Meteor Network was established in December of 2012 with two cameras and expanded to eight cameras in December of 2014. The two camera configuration saw 5470 meteors over two years of operation with two cameras, and has detected 3423 meteors in the first five months of operation (Dec 12, 2014 - May 12, 2015) with eight cameras. We expect to see over 10,000 meteors per year with the expanded system. The cameras have a 20 degree field of view and an approximate limiting meteor magnitude of +5. The network's primary goal is determining the nightly shower and sporadic meteor fluxes. Both camera networks function almost fully autonomously with little human interaction required for upkeep and analysis. The cameras send their data to a central server for storage and automatic analysis. Every morning the servers automatically generates an e-mail and web page containing an analysis of the previous night's events. The current status of the networks will be described, alongside with preliminary results. In addition, future projects, CCD photometry and broadband meteor color camera system, will be discussed.

Kingery, A. M.↗
DOE OSTI2023

A Reversed Impedance-Based Stability Criterion for IBR Grids

The existing impedance-based stability criterion is effective for analyzing local control interactions; however, it is difficult to scale the existing criterion to analyze wide-area control interactions among numerous IBRs through a complex power system network. The scaled version of the existing criterion requires the impedance response of each IBR in the system as well as of the network looking from all the IBRs. It is quite challenging to obtain all these impedance responses because of the computational effort and the requirement of separately scanning the impedance of the network and the IBRs. We propose a reversed criterion for the impedance-based stability analysis to address these problems. In contrast to the existing criterion, the reversed criterion analyzes the stability of a power system when an IBR is disconnected from the system. The reversed criterion estimates the impact of an IBR on the frequency and damping of power system oscillation modes using the impedance scans of only the IBR and the grid at its terminal. It can be sequentially applied at different IBRs to evaluate their impact on the power system stability. In addition to scalability, the reversed criterion gives flexibility to focus only on a few selected IBRs, depending on their rating, the magnitude of oscillations observed at their terminals, and the vendor support available for implementing stabilizing control system updates. The reversed criterion is demonstrated on a 14-bus power system with 100% IBRs.

control interactions↗
DOE OSTI2021

Subsurface Characterization of Hydraulic Fracture Test Site-2 (HFTS-2), Delaware Basin

Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp Formation of the Permian (Delaware) Basin. This paper focuses on integration, advanced geological characterization, and 3D subsurface modeling of the comprehensive HFTS-2 dataset. The study showcases a multidisciplinary reservoir characterization approach that incorporates geology, petrophysics, geochemistry, geomechanics, microseismic, and subsurface engineering analysis. Subsurface characterization of organic-rich mudstone formations requires understanding complex hydraulic fracture network growth in relation to inherent lithology, geomechanical properties, and interaction with pre-existing natural fractures. This paper presents a characterization workflow incorporating pre- and post-stimulation subsurface data, unique to the HFTS-2 dataset. The study integrated: (1) rock properties from logs, cores, and thin sections; (2) natural and hydraulic fracture descriptions from cores and image logs; (3) local and regional stresses; (4) geomechanics; (5) microseismic; (6) fiber optic (FO) and bottomhole pressure gauge (BHPG) response; and (7) produced fluids analysis. During a stimulation treatment, creation of the stimulated rock volume (SRV) is influenced by several subsurface factors. Key contributing factors include structural context, stress conditions, lithology, facies architecture, pre-existing natural fractures, and geomechanical properties. The HFTS-2 subsurface data integration indicates that the SRV is comprised of a complex juxtaposition of hydraulic fracture swarms, as evidenced by image logs analysis, core description, and microseismic monitoring. The HFTS-2 microseismic event density was used to generate 3D heat maps that serve as a representative SRV footprint, corroborated by secondary datasets. These maps were further integrated with petrophysical and geomechanical characteristics, as well as responses from FO and BHPG, to estimate the lateral and vertical dimensions of the effective fractures. The geological characterization for the HFTS-2 dataset combined with 3D modeling for petrophysical and geomechanical properties provides a strong foundation for subsurface simulation and optimization studies. Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S005R001/2477501/urtec-2021-5243-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5243 The workflow improved our understanding of HFTS-2 hydraulic fracture propagation and characteristics in relation to offset pressure depletion and interaction with pre-existing natural fractures. Analysis showed that fracture geometry varies by stage and by well, and a complex fracture network is generated with varying fracture density. The multidisciplinary workflow presented herein for integration and characterization serves as a foundation to evaluate completion efficiency and estimate areal and vertical stimulation and depletion extent for the project. Furthermore, the workflow and learnings can also be transferred to other unconventional plays.

58 GEOSCIENCES↗
DOE OSTI2021

Condensed Phase Water Molecular Multipole Moments from Deep Neural Network Models Trained on Ab Initio Simulation Data

Ionic solvation phenomena in liquids involve intense interactions in the inner solvation shell. For interactions beyond the first shell, the ion–solvent interaction energies result from the sum of many smaller-magnitude contributions that can still include polarization effects. Deep neural network (DNN) methods have recently found wide application in developing efficient molecular models that maintain near-quantum accuracy. In this work, we extend the DeePMD-kit code to produce accurate molecular multipole moments in the bulk and near interfaces. The new method is validated by comparing the DNN moments with those generated by ab initio simulations. The moments are used to compute the electrostatic potential at the center of a molecular-sized hydrophobic cavity in water. The results show that the fields produced by the DNN models are in quantitative agreement with the AIMD-derived values. These efficient methods will open the door to more accurate solvation models for large solutes such as proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Electronic, structural and magnetic studies of niobium borides of group 8 transition metals, Nb{sub 2}MB{sub 2} (M=Fe, Ru, Os) from first principles calculations

The Nb{sub 2}FeB{sub 2} phase (U{sub 3}Si{sub 2}-type, space group P4/mbm, no. 127) is known for almost 50 years, but until now its magnetic properties have not been investigated. While the synthesis of Nb{sub 2}OsB{sub 2} (space group P4/mnc, no. 128, a twofold superstructure of U{sub 3}Si{sub 2}-type) with distorted Nb-layers and Os{sub 2}-dumbbells was recently achieved, “Nb{sub 2}RuB{sub 2}” is still not synthesized and its crystal structure is yet to be revealed. Our first principles density functional theory (DFT) calculations have confirmed not only the experimental structures of Nb{sub 2}FeB{sub 2} and Nb{sub 2}OsB{sub 2}, but also predict “Nb{sub 2}RuB{sub 2}” to crystalize with the Nb{sub 2}OsB{sub 2} structure type. According to chemical bonding analysis, the homoatomic B–B interactions are optimized and very strong, but relatively strong heteroatomic M–B, B–Nb and M–Nb bonds (M=Fe, Ru, Os) are also found. These interactions, which together build a three-dimensional network, are mainly responsible for the structural stability of these ternary borides. The density-of-states at the Fermi level predicts metallic behavior, as expected, from metal-rich borides. Analysis of possible magnetic structures concluded preferred antiferromagnetic ordering for Nb{sub 2}FeB{sub 2}, originating from ferromagnetic interactions within iron chains and antiferromagnetic exchange interactions between them. -- Graphical abstract: Nb{sub 2}FeB{sub 2} (U{sub 3}Si{sub 2} structure type, space group P4/mbm, no. 127) is predicted to order antiferromagnetically, due to the presence of iron chains which show ferromagnetic interactions in the chains and antiferromagnetic interactions between them. “Nb{sub 2}RuB{sub 2}” is predicted to crystallize with the recently discovered Nb{sub 2}OsB{sub 2} twofold superstructure (space group P4/mnc, no. 128) of U{sub 3}Si{sub 2} structure type. The building of ruthenium dumbbells instead of chains along [001] is found to be responsible for the stabilization of this superstructure. Highlights: • Nb{sub 2}FeB{sub 2} is predicted to order antiferromagnetically. • Ferromagnetic interactions found in iron chains and antiferromagnetic ones between them. • Unknown “Nb{sub 2}RuB{sub 2}” predicted to crystallize with a twofold U{sub 3}Si{sub 2} superstructure. • Puckering of Nb-layer and Ru-dumbbell formation responsible for superstructure occurrence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Tyrosine B10 triggers a heme propionate hydrogen bonding network loop with glutamine E7 moiety

Highlights: Black-Right-Pointing-Pointer H-bonding network loop by PheB10Tyr mutation is proposed. Black-Right-Pointing-Pointer The propionate group H-bonding network restricted the flexibility of the heme. Black-Right-Pointing-Pointer The hydrogen bonding interaction modulates the electron density of the iron. Black-Right-Pointing-Pointer Propionate H-bonding network loop explains the heme-ligand stabilization. -- Abstract: Propionates, as peripheral groups of the heme active center in hemeproteins have been described to contribute in the modulation of heme reactivity and ligand selection. These electronic characteristics prompted the question of whether the presence of hydrogen bonding networks between propionates and distal amino acids present in the heme ligand moiety can modulate physiological relevant events, like ligand binding association and dissociation activities. Here, the role of these networks was evaluated by NMR spectroscopy using the hemoglobin I PheB10Tyr mutant from Lucina pectinata as model for TyrB10 and GlnE7 hemeproteins. {sup 1}H-NMR results for the rHbICN PheB10Tyr derivative showed chemical shifts of TyrB10 OH{eta} at 31.00 ppm, GlnE7 N{sub {epsilon}1}H/N{sub {epsilon}2}H at 10.66 ppm/-3.27 ppm, and PheE11 C{sub {delta}}H at 11.75 ppm, indicating the presence of a crowded, collapsed, and constrained distal pocket. Strong dipolar contacts and inter-residues crosspeaks between GlnE7/6-propionate group, GlnE7/TyrB10 and TyrB10/CN suggest that this hydrogen bonding network loop between GlnE7, TyrB10, 6-propionate group, and the heme ligand contribute significantly to the modulation of the heme iron electron density as well as the ligand stabilization mechanism. Therefore, the network loop presented here support the fact that the electron withdrawing character of the hydrogen bonding is controlled by the interaction of the propionates and the nearby electronic environments contributing to the modulation of the heme electron density state. Thus, we hypothesize that in hemeproteins with similar electrostatic environment the flexibility of the heme-6-propionate promotes a hydrogen bonding network loop between the 6-propionate, the heme ligand and nearby amino acids, tailoring in this way the electron density in the heme-ligand moiety.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Crystal structure and catalytic properties of three inorganic–organic hybrid constructed from heteropolymolybdate and aminopyridine

Three new organic–inorganic hybrid compounds (2-C{sub 5}H{sub 7}N{sub 2}){sub 3}·(SiMo{sub 12}O{sub 40})·(C{sub 4}H{sub 8}N{sub 4}){sub 0.5}·(C{sub 5}H{sub 6}N{sub 2}){sub 2}·(H{sub 2}O){sub 2} (1), (3-C{sub 5}H{sub 7}N{sub 2}){sub 8}·(SiMo{sub 12}O{sub 40}){sub 2}·(C{sub 5}H{sub 7}N{sub 3}){sub 2}·(H{sub 8}O{sub 4})·(H{sub 2}O){sub 8} (2) and (4-C{sub 5}H{sub 7}N{sub 2}){sub 6}·(SiMo{sub 12}O{sub 40}) (3) composed the heteropolymolybdate α-H{sub 4}SiMo{sub 12}O{sub 40} and the organic substrate 2/3/4-aminopyridine have been hydrothermally synthesized and characterized by routine methods. Compounds 1 and 2 exhibit a three-dimensional supramolecular network via hydrogen bond and π–π stacking interactions. Compound 2 contains a tetramolecular water cluster which consists of four water molecules connected by hydrogen bonds. These compounds exhibit good thermal stability and photoluminescent phenomena. Compounds 1 and 3 are active for catalytic oxidation of methanol in a continuous-flow fixed-bed micro-reactor, when the initial concentration of methanol is 2.75 g m{sup −3} in air and flow rate is 10 mL min{sup −1} at 150 °C, corresponding to the elimination rate of methanol i.e. 87.7% and 76.8%, respectively. - Three new Keggin type inorganic–organic hybrid frameworks were synthesized. Compounds exhibit an extended three-dimensional supramolecular network. Compounds 1 and 3 have better catalytic activity for eliminating methanol. Highlights: ► Three 3-D Keggin inorganic–organic hybrid frameworks were synthesized. ► The π–π stacking interactions are existed in Compounds 1 and 2. ► Compound 2 contains a tetramolecular water cluster connected by hydrogen bond. ► Compounds 1 and 3 are active in the catalytic oxidation of methanol into CO{sub 2} and H{sub 2}O.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗