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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 451 records · Page 25

Clippy

Clippy (CLI + PYthon) is a Python language interface to HPC resources. Precompiled binaries that execute on HPC systems are exposed as methods to a dynamically-created Clippy Python object, where they present a familiar interface to researchers, data scientists, and others. Clippy allows these users to interact with HPC resources in an easy, straightforward environment - at the REPL, for example, or within a notebook - without the need to learn complex HPC behavior and arcane job submission commands.

Bromberger, SethA.↗

Multi-genome Phage Annotation Toolkit and Evaluator

Summary: To address the need for improved tools for annotation and comparative genomics of bacteriophage genomes, we developed multiPhATE2. As an extension of the multiPhATE code, multiPhATE2 includes comparative genomics codes for gene matching among sets of input bacteriophage genomes, and scales well to large input data sets due to incorporation of multiprocessing in the functional annotation and comparative genomics subsystems. Furthermore, additional search algorithms and databases have been added to the functional annotation subsystem. MultiPhATE2 was implemented in Python 3.7, and runs as a command-line code under Linux or MAC-OS.

Kimbrel, JeffreyA.↗

AutoBEM-DynamicArchetypes

Automatic Building Energy Modeling (AutoBEM, https://bit.ly/AutoBEM) has been used to create an OpenStudio and EnergyPlus building energy model of 122.9 million U.S. buildings (https://bit.ly/ModelAmerica). Simulating and analyzing a model of every building for large areas (e.g. cities) is often not feasible. This dynamic archetyping capability uses a representative building and calculates a floor-space multiplier that allows millions of buildings to be represented by less than 100 buildings. This script (WRF_Archetypes_Parallel.py) calculates these building archetypes for each of the grid cells from a Weather Research and Forecasting (WRF) model in a parallel fashion. The script works by looping through each of the grid cells in the shapefile in parallel, spatially joining the building metadata table to each grid cell, aggregating relevant archetypes and calculating necessary statistics related to area and number of buildings in each cell. The output is a table (.csv) in which each row is an archetype building with properties about that building as well as statistics that relate that building to the total cell (such as an area multiplier). The following inputs are required: WRF zone shapefile (.shp) (wrf-grids-origin_Vegas_Select_100.geojson) The projection of the shapefile ("EPSG:XXXX") Input table containing building metadata for area corresponding to shapefile (.csv) (https://zenodo.org/record/4552901#.YZQEotDMJPY - ClarkCounty2.csv) The number of cores that will be parallelized (integer) The output file name for the archetype table (.csv) Sample command line inputs: python3 ~/WRF_Archetypes_Parallel.py -i ~/wrf-grids-origin_Vegas_Select_100.geojson -c ~/ClarkCounty2.csv -o ~/OutputArchetypes.csv -j 72 -e EPSG:4326 Using Geopandas Version 0.9.0

Bass, Brett (0000000240988434)↗

CMEC Module Manager

The CMEC module manager package is designed install and update CMEC modules (https://cmec.llnl.gov/). CMEC modules are independent climate model analysis packages. Individual scripts are provided in the module manager that outline the installation process for each module in a robust way, and a wrapper python script is provided that lets users install a chosen CMEC package with a single command.

Ordonez, AnaC↗

s3-browser

Web application that interacts with the Amazon AWS S3 REST API to allow users to manage files and buckets without having to use the aws command line application.

Chu, Vincent↗

dkainer/RWRtoolkit

a set of command-line and R tools for performing Random-walk with Restart analyses on multiplex networks in any species

Kainer, David↗

pysmurf

The python control software for SMuRF. Includes scripts to do low level commands as well as higher level analysis.

Henderson, Shawn↗

Streaming Analytics and Data Engineering

SADE is a software package for rapidly assembling analytic pipelines to manipulate data. The packages consists of the engine that manages the data and coordinates the movement of data between the tasks performing a function, a set of core libraries consisting of plugins that perform common tasks, and a framework to extend the system supporting the development of new plugins. Currently through configuration files, a pipeline can be defined that maps the routing of data through a series of plugins. Pipelines can be run in a batch mode or can process streaming data; they can be executed from the command line or run through a Windows background service. There currently exists over a hundred plugins, over fifty pipeline configurations, and the software is now being used by about a half-dozen projects.

Source record↗

WORM (Write One, Read Many)

WORM (Write One, Run Many) is an easy to use, cross platform, embedded and extensible, functional programming language designed to facilitate the creation of input-decks for computer codes that use standard ASCII text files for input. WORM makes it easy to create generic (yet, complex and powerful) reusable models. Additionally its nature allows for complex calculations and routines to be coded once and easily reused, further simplifying the creation of input decks. WORM (Write One, Run Many) is a powerful and versatile tool designed to improve the efficiency of today’s criticality safety analyst by allowing: + input decks for parametric studies to be created quickly and easily, + calculations and variables to be imbedded into any input deck, thus allowing for meaningful parameter specifications, + problems to be specified using any combination of units, and + complex mathematically defined models to be created. A very simple syntax is employed, and therefore the WORM is easy to learn. A WORM model is essentially a standard input deck with some of its numerical values replaced by WORM code. WORM code may include and evaluate the following mathematical operators and functions: addition, subtraction, multiplication, division, exponentiation, modulus, sine, cosine, tangent, arcsine, arccosine, arctangent, the natural logarithm, logarithm base 10, integer truncation, absolute value, and random number. Several common constants, e.g., pi, e, and Avogadros’s Number (both as 6.022e23 and 0.6022), are predefined in WORM. Additionally, many unit conversion factors are also predefined: millimeters, meters, inches, feet, yards, and mils to centimeters; kilograms, pounds, and ounces to grams; liters, milliliters, gallons, and fluid ounces to cubic centimeters; and angular degrees to radians. For parametric studies, WORM supports various shorthand list specifications: the explicit step size, linear interpolation, and logarithmic interpolation. The list notation sequentially assigns multiple values to a name. WORM creates an input deck for each value of the name. If multiple lists are used, WORM steps through each list individually, i.e., WORM creates input decks corresponding to each and every permutation of the list values. Additionally, a library of standard material definitions and Perl subroutines are included. Any one of these files can be incorporated into the subject model with a simple WORM read command. WORM is completely written in Perl, the Practical Extraction and Reporting Language. Perl is one of the most portable programming languages available today. As such, the WORM works on practically any computer platform.

Sartor, Raymond↗

TOMOCUPY

ANL REFERENCE SF-22-102 DESCRIPTION: Tomocupy is a Python package and a command-line interface for GPU reconstruction of tomographic/laminographic data in 16-bit and 32-bit precision. It implements an efficient data processing conveyor allowing to overlap all data transfers with computations. First, independent Python threads are started for reading data chunks from the hard disk into a Python data queue and for writing reconstructed chunks from the Python queue to the hard disk. Second, CPU-GPU data transfers are overlapped with GPU computations by using CUDA streams.

NIKITIN, VIKTOR↗

High Performance Computing Innovation Center Open Source Developer Tools

The High Performance Computing Innovation Center (HPCIC) aims to ease the transition for developers to use open source software provided by the lab. HPCIC Developer Tools is a collection of software, containers, cloud configurations, and associated documentation that make it easy to deploy tutorials or small apps to demonstrate lab-developed software. For example, building a tutorial container that includes lab software and interactive interfaces; a command line or web-based tool that accepts user preferences for the tutorial; supporting tools and software development kits (SDKs) for developer interactions or productivity in different languages embraced by the larger developer community such as Go, Rust, and Python; and automation in version control to support continued update of software and associated resources. These tools are best developed in an open source environment such as GitHub, not only to champion the lab's open source software, but for purposes of branding and demonstrating the lab's leadership in open source. Such an effort that brings in more developers to use and contribute to lab software can further improve the quality of the software, and developer experience at the lab.

Beckingsale, DavidA↗

Master State Distributed Estimator (masde)

The MSE technology provides a distributed state estimation scheme for power utilities by making it a real time dynamic system, versus the static snapshot method used today. This will allow utilities to verify power grid readings and identify false data on the communication network. The prevailing method of estimation takes all the data from the system into a single load flow equation at the utilities command center. This becomes a large algorithm that is very time consuming to solve, providing the engineers only snap shots of the system. The MFD distributes an algorithm to devises that are already installed at various locations on the power grid. This allows for much faster computer times because the algorithms contain magnitudes less data. When each distributed estimator completes its calculation, it sends the results back to the master device to check against all other distributed estimators.

Reen, DylanW.↗

UEDGE toolbox

The UEDGE Toolbox supplies an object-based interface and a wide array of tools used for running and analyzing UEDGE simulations. The toolbox provides routines for setting up UEDGE cases using YAML input files, shorthand commands for restoring converged solutions, as well as plotting profiles and surface plots of any of the parameters in UEDGE. Furthermore, the toolbox provides the necessary objects for compiling and analyzing parameter scans consisiting of several UEDGE simulations.

Holm, AndreasM↗

CMEC driver

CMEC driver is a command line tool that runs earth system evaluation modules.

Ordonez, AnaC.↗

Elastic Stacker

Stacker is a library and command-line tool for interacting with components of the Elastic Stack remotely using their APIs. For example, Stacker allows the user to persist API resources to disk and re-create them using the same APIs, potentially allowing configuration to be kept in sync across multiple Elastic Stack instances.

Taliaferro, JamesP.↗

CmdWebCtrl

CmdWebCtrl is a utility that runs a given command and provides a simple web interface for viewing anything it outputs to the console, along with providing some simple controls for restarting it.

Mast, RyanA↗

Spawn v.0.5.0 Released 12.15.2023 [SWR-SWR-20-10]

Spawn is a software package for performing co-simulations involving NREL's EnergyPlus™ tool and Modelica. This package bundles the following items in one self-contained package. 1. A method for connecting EnergyPlus models to Modelica 2. A Modelica compiler toolchain for compiling and running Modelica models 3. Modelica libraries and content, including the Modelica Buildings Library (MBL) and the Modelica Standard Library. The Spawn installation package is fully self-contained, and there are no external third-party dependencies. Together the capabilities in this package provide a single integrated environment for performing hybrid Modelica and EnergyPlus simulations. The primary entry point is the Spawn command line interface.

Li, Yanfei↗

pnnl/pyraabe

Automated Raabe table generationPyRaabe is a Python package to automate Raabe table -- a graph representation of airway geometry -- generation from a triangulated surface of an airway geometry. With a single command, it extracts a centerline from an input 3D surface mesh and subsequently computes the relevant attributes for the Raabe table, including length, diameter, bifurcation angle, and gravity angle. These can be used to inform downstream models, such as the Multiple-Path Particle Dosimetry (MPPD) model.

Colby, Sean M.↗