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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 649 records · Page 36
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 OSTI2015

Development of Improved Graphical Displays for an Advanced Outage Control Center, Employing Human Factors Principles for Outage Schedule Management

The long-term viability of existing nuclear power plants in the United States (U.S.) is dependent upon a number of factors, including maintaining high capacity factors, maintaining nuclear safety, and reducing operating costs, particularly those associated with refueling outages. Refueling outages typically take 20-30 days, and for existing light water NPPs in the U.S., the reactor cannot be in operation during the outage. Furthermore, given that many NPPs generate between $1-1.5 million/day in revenue when in operation, there is considerable interest in shortening the length of refueling outages. Yet refueling outages are highly complex operations, involving multiple concurrent and dependent activities that are somewhat challenging to coordinate; therefore, finding ways to improve refueling outage performance, while maintaining nuclear safety has proven to be difficult. The Advanced Outage Control Center (AOCC) project is a research and development (R&D) demonstration activity under the LWRS Program. LWRS is an R&D program that works closely with industry R&D programs to establish technical foundations for the licensing and managing of long-term, safe, and economical operation of current fleet of NPPs. As such, the LWRS Advanced Outage Control Center project has the goal of improving the management of commercial NPP refueling outages. To accomplish this goal, INL is developing an advanced outage control center (OCC) that is specifically designed to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. The overall focus is on developing an AOCC with the following capabilities that enables plant and OCC staff to; Collaborate in real-time to address emergent issues; Effectively communicate outage status to all workers involved in the outage; Effectively communicate discovered conditions in the field to the OCC; Provide real-time work status; Provide automatic pending support notifications; Provide real-time requirements monitoring; Maximize their collective situational awareness to improve decision-making; and Leverage macro data to better support resource allocation. INL has partnered with several commercial NPP utilities to develop a number of advanced outage management technologies. These outage management technologies have focused on both collaborative technologies for control centers and developing mobile technologies for NPP field workers. This report describes recent efforts made in developing a suite of outage technologies to support more effective schedule management. Currently, a master outage schedule is created months in advance using the plant’s existing scheduling software (e.g., Primavera P6). Typically, during the outage, the latest version of the schedule is printed at the beginning of each shift. INL and its partners are developing technologies that will have capabilities such as Automatic Schedule Updating, Automatic Pending Support Notifications, and the ability to allocate and schedule outage support task resources on a sub-hour basis (e.g., outage Micro-Scheduling). The remaining sections of this report describe in more detail the scheduling challenges that occur during outages, how the outage scheduling technologies INL is developing helps address those challenges, and the latest developments on this task (e.g., work accomplished to date and the path forward)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2012

Low Lunar Orbit Design via Graphical Manipulation of Eccentricity Vector Evolution

Low lunar orbits, such as those used by GRAIL and LRO, experience predictable variations in the evolution of their eccentricity vectors. These variations are nearly invariant with respect to the initial eccentricity and argument of periapse and change only in the details with respect to the initial semi-major axis. These properties suggest that manipulating the eccentricity vector evolution directly can give insight into orbit maintenance designs and can reduce the number of propagations required. A trio of techniques for determining the desired maneuvers is presented in the context of the GRAIL extended mission.

techniques↗
DOE OSTI2017

Brookhaven Lab Hosts Hackathon Focused on Graphics Processing Units (GPUs)

For five days in June 2017, Brookhaven Lab’s Computational Science Initiative hosted “Brookathon”—a programming workshop where teams of researchers, students, and software developers worked with mentors to accelerate scientific applications on GPUs for high-performance computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

From graphical to model-based distillation column design: A McCabe-Thiele-inspired mathematical programming approach

We propose a mixed-integer nonlinear programming (MINLP) model for simple and complex distillation column design and optimization. The model is based upon the concepts and equations underpinning the McCabe-Thiele method. Generalizing this method, we introduce material balances at various locations of the column and employ binary variables to determine the optimal number of trays and optimal feed locations. We model the vapor–liquid equilibrium using continuous piecewise linear approximating functions. The model is extended to account for multicomponent mixtures and non-constant-molar overflow. We also discuss how to estimate the minimum number of trays and the minimum reflux ratio.

42 ENGINEERING↗
DOE OSTI2016

iMatTOUGH: An open-source Matlab-based graphical user interface for pre- and post-processing of TOUGH2 and iTOUGH2 models

TOUGH2 and iTOUGH2 are powerful models that simulate the heat and fluid flows in porous and fracture media, and perform parameter estimation, sensitivity analysis and uncertainty propagation analysis. However, setting up the input files is not only tedious, but error prone, and processing output files is time consuming. Here, we present an open source Matlab-based tool (iMatTOUGH) that supports the generation of all necessary inputs for both TOUGH2 and iTOUGH2 and visualize their outputs. The tool links the inputs of TOUGH2 and iTOUGH2, making sure the two input files are consistent. It supports the generation of rectangular computational mesh, i.e., it automatically generates the elements and connections as well as their properties as required by TOUGH2. The tool also allows the specification of initial and time-dependent boundary conditions for better subsurface heat and water flow simulations. The effectiveness of the tool is illustrated by an example that uses TOUGH2 and iTOUGH2 to estimate soil hydrological and thermal properties from soil temperature data and simulate the heat and water flows at the Rifle site in Colorado.

58 GEOSCIENCES↗