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Results for “network flow”

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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids

Power distribution grids are structurally operated radially, such that energized lines form a collection of trees with a substation at the root of each tree. The operational topology may change from time to time, however tracking these changes, even though important for the distribution grid operation and control, is hindered by limited real-time monitoring. This work develops a learning framework to reconstruct the radial operational structure of the distribution grid from synchronized voltage measurements. To detect operational lines our learning algorithm uses conditional independence tests for continuous random variables that is applicable to a wide class of probability distributions and Gaussian injections in particular. Furthermore, our algorithm applies to the practical case of unbalanced three-phase power flow. The performance is validated on AC power flow simulations over three phase IEEE distribution grid test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

System Impact Study of the Eastern Grid of Sumba Island, Indonesia: Steady-State and Dynamic System Modeling for the Integration of One and Two 850-kW Wind Turbine Generators

The goal of this project was to study the impact of integrating one and two 850-kW wind turbine generators into the eastern power system network of Sumba Island, Indonesia. A model was created for the 20-kV distribution network as it existed in the first quarter of 2015 with a peak load of 5.682 MW. Detailed data were collected for each element of the network. Load flow, short-circuit, and transient analyses were performed using DIgSILENT PowerFactory 15.2.1.

17 WIND ENERGY↗
DOE OSTI2016

Shared Freight Transportation and Energy Commodities Phase One: Coal, Crude Petroleum, & Natural Gas Flows

The Freight Analysis Framework (FAF) integrates data from a variety of sources to create a comprehensive picture of nationwide freight movements among states and major metropolitan areas for all modes of transportation. It provides a national picture of current freight flows to, from, and within the United States, assigns selected flows to the transportation network, and projects freight flow patterns into the future. The latest release of FAF is known as FAF4 with a base year of 2012. The FAF4 origin-destination-commodity-mode (ODCM) matrix is provided at national, state, major metropolitan areas, and major gateways with significant freight activities (e.g., El Paso, Texas). The U.S. Department of Energy (DOE) is interested in using FAF4 database for its strategic planning and policy analysis, particularly in association with the transportation of energy commodities. However, the geographic specification that DOE requires is a county-level ODCM matrix. Unfortunately, the geographic regions in the FAF4 database were not available at the DOE desired detail. Due to this limitation, DOE tasked Oak Ridge National Laboratory (ORNL) to assist in generating estimates of county-level flows for selected energy commodities by mode of transportation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Visualization and Analytics of Distribution Systems with Deep Penetration of Distributed Energy Resources (VADER)

In its current state, the distribution system is incapable of handling small to moderate amounts of photovoltaic (PV) penetration. This is because it was initially designed for handling passive loads which, at the level of a substation, have low variability and are forecastable with high accuracy. It has been an open loop system with little monitoring and control. With the addition of PV energy sources, the overall scenario will change dramatically due to (1) two way power flow on network; and (2) high aggregate variability. Additionally, changes on the consumption side lead to a number of smart loads, Electric Vehicles (EVs), and Demand Response. These fundamental changes in the characteristics of the generation and consumption of power will lead to a number of practical engineering problems which must be overcome to allow increased penetration of Distributed PV. Solving the unique engineering challenges which arise at moderate levels of PV penetration requires closed loop integration of data from (1) PV sources; (2) customer load data from smart meters; (3) EV charging data; and (4) local and line mounted precision instruments. These data are not traditionally used by utilities in operations since they are ”non-SCADA” and the current grid does not require such levels of control. To integrate this data and provide real time intelligence from these non-SCADA data, we created the Visualization and Analytics of Distribution Systems with Deep Penetration of Distributed Energy Resources (VADER) platform. VADER is a collection of analytics enabled by integration of massive and heterogeneous data streams for granular real-time monitoring, visualization and control of Distributed Energy Resources (DER) in distribution networks. VADER analytics enable utilities to have greater visibility into distributed energy resources. We built several batch- and stream-analytics in VADER which help operators better understand the impact of distributed energy resources on the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Nonperturbative Exploration of Near-Conformal Dynamics

This project had three major goals: Explore qheories of composite dark matter and composite Higgs bosons through the work of the Lattice Strong Dynamics (LSD) collaboration.; Extend lattice gauge theories to curved manifolds through the work of the Quantum Finite Elements (QFE) collaboration.; Explore normalizing flow neural networks for producing ensembles of lattice gauge theory configurations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Toward Smart, Automated Junctional Tourniquets—AI Models to Interpret Vessel Occlusion at Physiological Pressure Points

Hemorrhage is the leading cause of preventable death in both civilian and military medicine. Junctional hemorrhages are especially difficult to manage since traditional tourniquet placement is often not possible. Ultrasound can be used to visualize and guide the caretaker to apply pressure at physiological pressure points to stop hemorrhage. However, this process is technically challenging, requiring the vessel to be properly positioned over rigid boney surfaces and applying sufficient pressure to maintain proper occlusion. As a first step toward automating this life-saving intervention, we demonstrate an artificial intelligence algorithm that classifies a vessel as patent or occluded, which can guide a user to apply the appropriate pressure required to stop flow. Neural network models were trained using images captured from a custom tissue-mimicking phantom and an ex vivo swine model of the inguinal region, as pressure was applied using an ultrasound probe with and without color Doppler overlays. Using these images, we developed an image classification algorithm suitable for the determination of patency or occlusion in an ultrasound image containing color Doppler overlay. Separate AI models for both test platforms were able to accurately detect occlusion status in test-image sets to more than 93% accuracy. In conclusion, this methodology can be utilized for guiding and monitoring proper vessel occlusion, which, when combined with automated actuation and other AI models, can allow for automated junctional tourniquet application.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2004

Metal-Silicate Segregation in Deforming Dunitic Rocks: Applications to Core Formation in Europa and Ganymede

Core formation is an important event in the evolution of a planetary body, affecting both the geochemical and geophysical properties of the body. Metal-silicate segregation could have proceeded either by settling of liquid metal through a magma ocean or by percolation of liquid metal through a solid silicate mantle. Percolation of metallic melt had previously been excluded as a viable segregation mechanism because metallic melts do not form an interconnected network under hydrostatic conditions, except at high melt fraction (>5 vol%), due to the high dihedral angle between metals and silicates (>60 ). Without an interconnected network, porous flow of metallic melt is impossible, leaving the magma ocean scenario as the only mechanism to form the core. Moment-of-inertia measurements of Europa and Ganymede from the Galileo probe indicate that they are differentiated. This evidence suggests that a method for segregating metals and silicates at temperatures low enough to retain volatile compounds must exist. We have investigated the effect of deformation on the distribution of metallic melts in silicates. We have deformed samples of olivine + 5-9 vol% Fe-S to strains of 2.5 in simple shear and find that the metallic melt segregates into melt-rich planes oriented at 20 to the shear plane. These metallic melt-rich bands are similar in structure to the silicate melt-rich bands reported by Holtzman, indicating that deformation can interconnect isolated metallic melt pockets and allow porous flow of non-wetting melts. Such a core formation process could have occurred in the jovian satellites.

Hustoft, J. W.↗
DOE OSTI2017

Modeling Road Vulnerability to Snow Using Mixed Integer Optimization

As the number and severity of snowfall events continue to grow, the need to intelligently direct road maintenance during these snowfall events will also grow. In several locations, local governments lack the resources to completely treat all roadways during snow events. Furthermore, some governments utilize only traffic data to determine which roads should be treated. As a result, many schools, businesses, and government offices must be unnecessarily closed, which directly impacts the social, educational, and economic well-being of citizens and institutions. In this work, we propose a mixed integer programming formulation to optimally allocate resources to manage snowfall on roads using meteorological, geographical, and environmental parameters. Additionally, we evaluate the impacts of an increase in budget for winter road maintenance on snow control resources.

Mixed integer optimization↗
DOE OSTI2015

Three‐phase probabilistic load flow in radial and meshed distribution networks

With the introduction of higher levels of renewables and demand response programs, traditional deterministic power system tools fall short of expectations. Probabilistic load flow (PLF) takes into account the inconsistency or the unknown loads, and generation in the fundamental load flow analysis. This study proposes a PLF solution for both balanced and unbalanced, radial and weakly meshed networks without explicitly using the Y ‐bus matrix. It allows for discrete probability density functions as input variables without having to assume a predefined distribution. The nodal voltages and the power flows can be calculated independently from one another. The proposed method is applied to the IEEE 123 Node Test Feeder and the IEEE 13 Node Test Feeder in both its original radial configuration and a modified mesh configuration, including a load replaced with a wind turbine. The results are validated by comparison of the proposed method's solutions to those obtained using cumulants and Monte Carlo simulation. The proposed PLF method provides an accurate and practical way for finding the solution to stochastic problems occurring in power distribution systems allowing for real‐system data to be analysed.

Melhorn, Alexander C.↗
NASA NTRS1994

Towards a Comprehensive Computational Simulation System for Turbomachinery

The objective of this work is to develop algorithms associated with a comprehensive computational simulation system for turbomachinery flow fields. This development is accomplished in a modular fashion. These modules includes grid generation, visualization, network, simulation, toolbox, and flow modules. An interactive grid generation module is customized to facilitate the grid generation process associated with complicated turbomachinery configurations. With its user-friendly graphical user interface, the user may interactively manipulate the default settings to obtain a quality grid within a fraction of time that is usually required for building a grid about the same geometry with a general-purpose grid generation code. Non-Uniform Rational B-Spline formulations are utilized in the algorithm to maintain geometry fidelity while redistributing grid points on the solid surfaces. Bezier curve formulation is used to allow interactive construction of inner boundaries. It is also utilized to allow interactive point distribution. Cascade surfaces are transformed from three-dimensional surfaces of revolution into two-dimensional parametric planes for easy manipulation. Such a transformation allows these manipulated plane grids to be mapped to surfaces of revolution by any generatrix definition. A sophisticated visualization module is developed to al-low visualization for both grid and flow solution, steady or unsteady. A network module is built to allow data transferring in the heterogeneous environment. A flow module is integrated into this system, using an existing turbomachinery flow code. A simulation module is developed to combine the network, flow, and visualization module to achieve near real-time flow simulation about turbomachinery geometries. A toolbox module is developed to support the overall task. A batch version of the grid generation module is developed to allow portability and has been extended to allow dynamic grid generation for pitch changing turbomachinery configurations. Various applications with different characteristics are presented to demonstrate the success of this system.

Shih, Ming-Hsin↗