ISO 15118 Node-Red Dashboard
This is a graphical user interface (GUI) that can be deployed in a Node-RED environment and be configured to provide monitoring and control of an ISO 15118 EV Charger (DC or AC).
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This is a graphical user interface (GUI) that can be deployed in a Node-RED environment and be configured to provide monitoring and control of an ISO 15118 EV Charger (DC or AC).
The M-node Polarization Control program interfaces with electronic polarization controllers and polarimeters to adjust and compensate for the polarization drift of light within optical fiber. The code implements a gradient ascent control loop to calibrate to a desired state of polarization. A key advantage of this program is that it provides a TCP socket interface that allows external clients to drive the calibration routines.
This dataset contains hourly snapshot data from each of the 5 login nodes of the Summit supercomputer at Oak Ridge Leadership Computing Facility (OLCF) over a period of 2 years, starting January 2020 and ending after December 2021. The snapshots include lists of currently logged-in users, CPU and memory usage, status of users' batch jobs, and disk usage statistics. Usernames, project identifiers, and file paths have been pseudonymized in order to allow studies of user behavior without divulging Personally Identifiable Information (PII).
Compatibility with existing classical network infrastructure offers a scalable path towards deploying large-scale quantum networks. Here, we demonstrate O-band polarization-encoded quantum entanglement distribution over an installed 24.4-km fiber while coexisting with a state-of-the-art fully loaded C-band classical communications line system and a picosecond-level precision L-band synchronization signal. The classical system carries two 800-Gbps channels while the remainder of the C-band is filled with amplified spontaneous emission, as is standard for such state-of-the-art communications systems. We examine the spontaneous Raman scattering spectrum generated from this broadband C-band light and offer insights into wavelength allocation for O-band quantum channels. Optimal wavelength selection and narrow filtering enable well-preserved Bell state fidelity when coexisting with 21.4-dBm aggregate launch power across the C-band suitable for 36-Tbps transmission. To the best of our knowledge, this is the first implementation of entanglement-based quantum communications between two remote nodes coexisting with independent classical communications traffic. We demonstrate coexistence of quantum entanglement with ultra-high power levels and record classical bandwidth, offering promise for real-world entanglement-based networking integrated within high-capacity communications infrastructure.
Our goal is to report on the basic performance of PETSc vector operations on a single node of the Oak Ridge Leadership Facility System Summit. We describe the Summit system and present data collected from several vector operations. Limited analysis is also presented.
This presentation will be presented at the NNSS FY 2020 SDRD Annual (Webex) Meeting scheduled for September 23–24, 2020. Phenomenology and Node-Level Processing of MASINT Sensor Data across Distributed Sensor Networks STL-016-19, Year 2
As part of the project “Designing Resilient Communities (DRC): A Consequence-Based Approach for Grid Investment,” funded by the United States (US) Department of Energy’s (DOE) Grid Modernization Laboratory Consortium (GMLC), Sandia National Laboratories (Sandia) is partnering with a variety of government, industry, and university participants to develop and test a framework for community resilience planning focused on modernization of the electric grid. This report provides a summary of the section of the project focused on hardware demonstration of “resilience nodes” concept.
Sampling is an important step in the machine learning process because it prioritizes samples that help the model best summarize the important concepts required for the task at hand. The process of determining the best sampling method has been rarely studied in the context of graph neural networks. In this paper, we evaluate multiple sampling methods (i.e., ascending and descending) that sample based off different definitions of centrality (i.e., Voterank, Pagerank, degree) to observe its relation with network topology. We find that no sampling method is superior across all network topologies. Additionally, we find situations where ascending sampling provides better classification scores, showing the strength of weak ties. Two strategies are then created to predict the best sampling method, one that observes the homogeneous connectivity of the nodes, and one that observes the network topology. In both methods, we are able to evaluate the best sampling direction consistently.
Abstract. We developed a low-cost methane sensing node incorporating two metal oxide (MOx) sensors (Figaro Engineering TGS2611-E00 and TGS2600), humidity and temperature sensing, data storage, and telemetry. We deployed the prototype sensor alongside a reference methane analyzer at two sites: one outdoors and one indoors. We collected data at each site for several months across a range of environmental conditions (particularly temperature and humidity) and methane levels. We explored calibration models to investigate the performance of our system and its suitability for methane background monitoring and enhancement detection, first selecting a linear regression to fit a sensor baseline response and then fitting methane response by the sensor deviation from baseline. We achieved moderate accuracy in a 2 to 10 ppm methane range compared to data from the reference analyzer (RMSE < 0.6 ppm), but we found that the sensor response varied over time, possibly as a result of changes in non-targeted gas concentrations. We suggest that this cross sensitivity may be responsible for mixed results in previous studies. We discuss the implications of our results for the use of these and similar inexpensive MOx sensors for methane monitoring in the 2 to 10 ppm range.
Aviation is experiencing an influx of electrified aircraft in the advanced air mobility (AAM) space. The goal of Airports as Energy Nodes (ÆNodes) is to evaluate the impact of AAM and other advanced aircraft adoption growth on the electrical system of existing small to medium hub regional airports to better prepare them for the future while also enhancing resiliency and helping surrounding communities. AAM small passenger air service encompasses vertical takeoff and landing (VTOL), general aviation (GA) and flight training, and nine to thirty passenger conventional aircraft for regional air mobility (RAM) applications all of which include electrical, hybrid, or hydrogen powered varieties. Some challenges that ÆNodes is trying to address include how to utilize existing airport infrastructure to meet the energy needs of AAM growth in a way that is robust to aid in the growth of AAM while also leveraging any airport-hosted energy assets for the surrounding community in emergency situations.
Changes in lymph nodes of dogs following space flight
Stiffness matrices bandwidth minimization by automatic node relabeling in equilibrium problems of lumper-parameter systems
Node regression of Mercury orbit due to solar quadrupole moment, discussing regression rate values
Number of trees with arbitrary number of terminal nodes
Automated Sneak Program /ASP/ to generate diode, load, and special node reports which aid in drawing of circuitry paths for sneak circuit analysis of Apollo spacecraft
Method provides approach to automatic node relabeling that is consistent with requirements of wavefront concept. Specific applications are in analysis of aircraft, building structures, radar and surveillance structures, bridges, etc., or any other structure that is studied with aid of large and complex analytical model. Minimum growth sequencing is effective, rapid, and capable of producing economies.
The verification of the nodal averaging method for generating automated finite triangular element grids was demonstrated. This was accomplished with a six node averaging program (SNAP) which was placed on an IBM 2250 vector graphics scope terminal. The advantage of this method is that it is unnecessary to program time consuming geometric division and transition algorithms.