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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 415 records · Page 23

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Design and simulation of the snowflake divertor control for NSTX-U

This paper presents the development of a physics-based multiple-input-multiple-output algorithm for real-time feedback control of snowflake divertor (SFD) configurations on the National Spherical Torus eXperiment Upgrade (NSTX-U). A model of the SFD configuration response to applied voltages on the divertor control coils is first derived and then used, in conjunction with multivariable control synthesis techniques, to design an optimal state feedback controller for the configuration. To demonstrate the capabilities of the controller, a nonlinear simulator for axisymmetric shape control was developed for NSTX-U which simultaneously evolves the currents in poloidal field coils based upon a set of feedback-computed voltage commands, calculates the induced currents in passive conducting structures, and updates the plasma equilibrium by solving the free-boundary Grad-Shafranov problem. Closed-loop simulations demonstrate that the algorithm enables controlled operations in a variety of SFD configurations and provides capabilities for accurate tracking of time-dependent target trajectories for the divertor geometry. In particular, simulation results suggest that a time-varying controller which can properly account for the evolving SFD dynamical response is not only desirable but necessary for achieving acceptable control performance. The algorithm presented in this paper has been implemented in the NSTX-U Plasma Control System in preparation for future control and divertor physics experiments.

snowflake divertor, MIMO feedback control, nonline↗

DOE OSTI2014

CyPhyTown

A series of software programs that enables students to progress from completely unsecured control of devices to control that protects network commands with authentication, integrity and confidentiality. The working example provided is for turning LED lights on and off on a Raspberry Pi computer.

Source record↗

DOE OSTI2016

Response Surface Modeling Tool Suite, Version 1.x

The Response Surface Modeling (RSM) Tool Suite is a collection of three codes used to generate an empirical interpolation function for a collection of drag coefficient calculations computed with Test Particle Monte Carlo (TPMC) simulations. The first code, "Automated RSM", automates the generation of a drag coefficient RSM for a particular object to a single command. "Automated RSM" first creates a Latin Hypercube Sample (LHS) of 1,000 ensemble members to explore the global parameter space. For each ensemble member, a TPMC simulation is performed and the object drag coefficient is computed. In the next step of the "Automated RSM" code, a Gaussian process is used to fit the TPMC simulations. In the final step, Markov Chain Monte Carlo (MCMC) is used to evaluate the non-analytic probability distribution function from the Gaussian process. The second code, "RSM Area", creates a look-up table for the projected area of the object based on input limits on the minimum and maximum allowed pitch and yaw angles and pitch and yaw angle intervals. The projected area from the look-up table is used to compute the ballistic coefficient of the object based on its pitch and yaw angle. An accurate ballistic coefficient is crucial in accurately computing the drag on an object. The third code, "RSM Cd", uses the RSM generated by the "Automated RSM" code and the projected area look-up table generated by the "RSM Area" code to accurately compute the drag coefficient and ballistic coefficient of the object. The user can modify the object velocity, object surface temperature, the translational temperature of the gas, the species concentrations of the gas, and the pitch and yaw angles of the object. Together, these codes allow for the accurate derivation of an object's drag coefficient and ballistic coefficient under any conditions with only knowledge of the object's geometry and mass.

Walker, Andrew↗

DOE OSTI2016

rsed

"rsed" is an R package that contains tools for stream editing: manipulating text files by making insertions, replacements, deletions, substitutions, or commenting. It hails from the powerful Unix command, "sed". While the "rsed" package is not nearly as powerful as "see", it is much simpler to use. R programmers often write scripts that may require simple manipulation of text files. "rsed" addresses that need.

Source record↗

DOE OSTI2016

Contact Control, Version 1

The contact control code is a generalized force control scheme meant to interface with a robotic arm being controlled using the Robot Operating System (ROS). The code allows the user to specify a control scheme for each control dimension in a way that many different control task controllers could be built from the same generalized controller. The input to the code includes maximum velocity, maximum force, maximum displacement, and a control law assigned to each direction and the output is a 6 degree of freedom velocity command that is sent to the robot controller.

von Sternberg, Alex↗

DOE OSTI2016

Mcqueuer

Mcqueuer is a simple tool that allows anyone from researchers to experienced developers to create multi-node/multi-core jobs by simply creating a file with a list of commands. Users simply combine tasks, which would otherwise each be their own job on the cluster, into a single file that is given to Mcqueuer. Mcqueuer then does the heavy lifting required to process the tasks in parallel in a single multi-node job. In addition, Mcqueuer provides load-balancing, which frees the user from having to worry about complex memory and CPU considerations, and instead focus on the processing itself.

Source record↗

DOE OSTI2016

PcapDB: Search Optimized Packet Capture, Version 0.1.0.0

PcapDB is a packet capture system designed to optimize the captured data for fast search in the typical (network incident response) use case. The technology involved in this software has been submitted via the IDEAS system and has been filed as a provisional patent. It includes the following primary components: capture: The capture component utilizes existing capture libraries to retrieve packets from network interfaces. Once retrieved the packets are passed to additional threads for sorting into flows and indexing. The sorted flows and indexes are passed to other threads so that they can be written to disk. These components are written in the C programming language. search: The search components provide a means to find relevant flows and the associated packets. A search query is parsed and represented as a search tree. Various search commands, written in C, are then used resolve this tree into a set of search results. The tree generation and search execution management components are written in python. interface: The PcapDB web interface is written in Python on the Django framework. It provides a series of pages, API's, and asynchronous tasks that allow the user to manage the capture system, perform searches, and retrieve results. Web page components are written in HTML,CSS and Javascript.

Ferrell, Paul↗

DOE OSTI2017

Futility

The Futility package contains the following: 1) Definition of the size of integers and real numbers; 2) A generic Unit test harness; 3) Definitions for some basic extensions to the Fortran language: arbitrary length strings, a parameter list construct, exception handlers, command line processor, timers; 4) Geometry definitions: point, line, plane, box, cylinder, polyhedron; 5) File wrapper functions: standard Fortran input/output files, Fortran binary files, HDF5 files; 6) Parallel wrapper functions: MPI, and Open MP abstraction layers, partitioning algorithms; 7) Math utilities: BLAS, Matrix and Vector definitions, Linear Solver methods and wrappers for other TPLs (PETSC, MKL, etc), preconditioner classes; 8) Misc: random number generator, water saturation properties, sorting algorithms.

Collins, BenjaminS.↗

DOE OSTI2014

Avalaunch

Avalaunch implements a tree-based process launcher. It first bootstraps itself on to a set of compute nodes by launching children processes, which immediately connect back to the parent process to acquire info needed t launch their own children. Once the tree is established, user processes are started by broadcasting commands and application binaries through the tree. All communication flows over high-performance network protocols via spawnnet. The goal is to start MPI jobs having hundreds of thousands of processes within seconds.

Moody, A.T.↗

DOE OSTI2014

Dimensionality Reduction Library v 0.2

Dimensionality Reduction Library is a C++ library for dimensionality reduction. In the context of this library, dimensionality reduction is considered to consist of 1)estimation of the intrinsic dimensionality using sampled data, 2) Finding maps that reduce the dimensionality of data (forward map) or increase the dimensionality of data (reverse map) and 3) mapping arbitray coordinates to high and low dimensionalities. The library is intended to provide a consistent interface to multiple dimensionality reduction algorithms with an efficient C++ interface that runs efficiently on multicore architectures. A few routines have been optimized with an option for GPU acceleration or distributed computation. Currently the library offers intrinsic dimensionality estimation using point-PCA reconstruction error and/ residual variance. The following dimensionality reduction methods have been implemented: Principal Component Analysis Multidimensional Scaling Locally Linear Embedding IsoMap Autoencoder Neutral Networks An executable is also supplied that can be built to allow for command-line access to the library routines. A description for an application of the library for molecular structure analysis has been published.

BROWN, WILLIAM↗

DOE OSTI2014

GridPV Toolbox

Matlab Toolbox for simulating the impact of solar energy on the distribution grid. The majority of the functions are useful for interfacing OpenDSS and MATLAB, and they are of generic use for commanding OpenDSS from MATLAB and retrieving GridPV Toolbox information from simulations. A set of functions is also included for modeling PV plant output and setting up the PV plant in the OpenDSS simulation. The toolbox contains functions for modeling the OpenDSS distribution feeder on satellite images with GPS coordinates. Finally, example simulations functions are included to show potential uses of the toolbox functions.

Broderick, Robert↗

DOE OSTI2014

Codevision 0.x

CodeVision (formerly MassAV) is a malware analysis workflow system and repository. It began as a simple tool for analyzing a large malware corpus using multiple COTS antivirus engines in parallel. It has since evolved into a unified interface for collecting, storing and analyzing malicious executable code using a variety of COTS and GOTS backends. Not only can CodeVision receive samples from users via its command-line and web interfaces, but it can also operate on continuous network data feeds (e.g., perimeter e-mail attachments, HTTP downloads). The modular analysis framework and simple API give developers the ability to integrate custom and off-the-shelf analysis tools with ease. The system manages scheduling and dependencies, allowing modules to be chained together into analysis-driven workflows. The system is designed as a distributed, load-balanced web service, an architecture that allows it to scale horizontally by adding additional nodes.

Anderson, Blake↗

DOE OSTI2018

Swiftbat Python Library

Swiftbat is a set of Python library routines and command-line utilities that have been developed for the purpose of retrieving, analyzing, and displaying data from NASA's Swift spacecraft, especially the data from the Swift Burst Alert Telescope (BAT).

Palmer, David↗

DOE OSTI2017

Thermochimica

Thermochimica is a software library that determines a unique combination of phases and their compositions at thermochemical equilibrium. Thermochimica can be used for stand-alone calculations or it can be directly coupled to other codes. This release of the software does not have a graphical user interface (GUI) and it can be executed from the command line or from an Application Programming Interface (API). Also, it is not intended for thermodynamic model development or for constructing phase diagrams. The main purpose of the software is to be directly coupled with a multi-physics code to provide material properties and boundary conditions for various physical phenomena. Significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. Various useful parameters can be provided as output from Thermochimica, such as: determination of which phases are stable at equilibrium, the mass of solution species and phases at equilibrium, mole fractions of solution phase constituents, thermochemical activities (which are related to partial pressures for gaseous species), chemical potentials of solution species and phases, and integral Gibbs energy (referenced relative to standard state). The overall goal is to provide an open source computational tool to enhance the predictive capability of multi-physics codes without significantly impeding computational performance.

Simunovic, Srdjan↗

DOE OSTI2018

Peptide Fragmentation Modeller

The Peptide Fragmentation Modeller is a command-line utility reads that reads in a text file of peptide sequences and generates the theoretical fragmentation pattern for each, outputting the results in a single concatenated DTA file, or in separate .Dta files. The ion intensity values are not predicted values; instead, b, c, y, and z ions are assigned an intensity of 100; while a ions and neutral loss ions receive an intensity of 20.

Monroe, Matthew↗

DOE OSTI2018

STOMP-W

Fortran 90 source code, example problems, and output conversion scripts for the STOMP-W simulator. STOMP-W is a numerical simulator written in Fortran 90 for solving problems involving fluid flow and solute/species transport in variably saturated geologic media. The zipped file contains five directories: 1) src (the source code), 2) scripts (output conversion scripts written in perl, 3) prb-w-1 (example problem 1), 4) prb-w-2 (example problem 2), and 5) prb-w-3 (example problem 3). After downloading and unzipping the file, the user must create an executable from the files stored in the src directory. Generic instructions for compiling the source code is shown below as a UNIX/Linux command line, with f90 representing the user's Fortran 90 compiler.

White, Mark↗

DOE OSTI2018

Stack Trace Analysis Tool (STAT)

STAT is a light weight debugging tool that gathers and merges stack traces from all of the processes in a parallel application. STAT uses the MRNet tree based overlay network to broadcast commands from the tool front-end to the STAT daemons and for the front-end to gather the traces from the STAT daemons. As the traces propagate through the MRNet network tree, they are merged across all tasks to fonn a single call prefix tree. The call prefix tree can be examined to identify tuks with similar function call patterns and to delineate a small set of equivalence classes. A representative task from each of these classes can then be fed into a full feature debugger like TotalView for root cause analysis.

ECP↗

DOE OSTI2018

BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) [SWR 18-23]

Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. https://www.nrel.gov/docs/legosti/old/6231.pdf For EnergyPlus® and OpenStudio®, generation of test cases, simulation, and reporting has been a manual or partially automated process that typically took a number of months after a new version of EnergyPlus came out. Building Energy Simulation Test - Generation Simulation and Reporting (BESTEST-GSR) was developed to fully automate this process so it is less error-prone, less time-consuming, and can be quickly run on request for any development branch of EnergyPlus and OpenStudio. The initial use case is to directly support OpenStudio and EnergyPlus development, but the software is configured to support use by external software developers that build tools on top of EnergyPlus and/or OpenStudio. Tools built on top of OpenStudio can leverage the test generation, simulation, and reporting, while tools built on EnergyPlus can leverage the test simulation and reporting. The model generation is accomplished by running OpenStudio measures for envelope, heating, or cooling test cases. At this stage the specified weather file required for a specific test case is assigned to the model. Simulation is enabled using the OpenStudio Command Line Interface (CLI) to run a series of OpenStudio and Reporting measures to a specified seed model. The specified workflow is defined with an OpenStudio OSW file. The first measure generates the test case model, while the second measure is a reporting measure that runs after the simulation to collect necessary simulation results from the EnergyPlus SQL file. The Reporting stage gathers data from individual OpenStudio OSW files and populates a series of BESTEST Microsoft Excel spreadsheets. BESTEST-GSR also gathers zip files from individual simulations for diagnostic purposes.

Goldwasser, David↗