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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 253 records · Page 14

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.↗

Livermore Computing User and System Scripts

LCUSS is a collection of scripts used to improve productivity on HPC systems for both administrators and general users. It will include general scripts for user management, scripts for helping users interact with LC resource management software (e.g. SLURM and Flux), and scripts to automate common user command-line tasks on LC and other HPC machines. These scripts are intended to be made available to all LC users. Hosting them on GitHub will allow LC staff, users, and collaborators to work on them together.

Long, Jeffery↗

Drishti v0.3

Drishti is a command-line tool to guide end-users in optimizing I/O in their applications by detecting typical I/O performance pitfalls and providing a set of recommendations.

Bez, Jean Luca↗

Julienne v1.0.0

Julienne is a compiler-portable unit-testing framework for Fortran software projects, including those that use the parallel/accelerator-programming features of Fortran 2023. Julienne achieves portability across compilers through minimalism and isolation. The minimal design ensures that Julienne uses only features supported by the majority of Fortran compilers. The isolation through zero dependencies ensures that no other projects block Julienne from building with a particular compiler. Julienne also contains with additional services that support its unit-testing code. These include functions for manipulating strings, command lines and input/output format strings; and a user-defined collective subroutine for verifying that all processes pass a test in parallel testing. Julienne's name derives from the term for vegetables sliced into thin strings: julienne vegetables. Julienne captures the authors' most frequently used thin slice of the Veggies and Sourcery software repositories while avoiding certain compiler limitations of the those two packages.

Rouson, Damian↗

BiG-SLiCE 2 v1.0.0

BiG-SLiCE was originally an open source Python-based command line bioinformatics software that offers a highly scalable clustering analysis on biosynthetic gene clusters (BGC) data. It allows a simultaneous analysis of millions of BGCs, exceeding the capability of other existing tools (around one hundred thousands). As a tradeoff, the clustering accuracy is relatively lower and sometimes fall short in corner cases and specific BGC classes such as the RiPPs (Ribosomally-translated, Post-translationally modified Peptides). In BiG-SLiCE V2 (developed in LBNL), the clustering algorithm has been significantly improved to deliver a much accurate result even for RiPPs and other previous corner case classes. Moreover, the speed of the overall pipeline has been improved by 50-100%. Finally, additional features were implemented to support downstream analyses of BiG-SLiCE results, such as customized tabular (TSV/CSV) and columnar (Parquet) outputs.

Kautsar, Satria↗

BaseBuddy v1

The software "BaseBuddy" (basebuddy.lbl.gov) is a user-friendly web app designed for codon optimization of heterologous genes. Codon optimization is a widely used technique to enhance the expression levels of non-native genes. Our app is built on the DNA Chisel Python library (Zulkower and Rosser, 2020), which offers highly customizable and transparent gene optimization. Unlike DNA Chisel, which is a command-line interface software with numerous optional functions, our web app simplifies the process for users. Additionally, while DNA Chisel relies on the outdated Kazusa codon usage database, our app introduces the option to utilize the most recent version of the CoCoPUTs database (Athey et al., 2017). By incorporating CoCoPUTs, we also expand the range of target organisms and maintain up-to-date sequencing data for more accurate codon optimization results.

Schmidt, Matthias↗

Mesh Computing Remote Automatic Workflow

The software suite uses a microservice architecture using Docker and `docker-compose`. The microservices are as follows: 1. User interface. This interface is written in JavaScript using the Svelte framework. It exposes form elements and a 3D visualizer to prompt the user through the definition of microstructure parameters, and setting parameters for mesh generation and refinement. 2. Mesh generator. This is a container running the Python package for DREAM3D to generate a voxelized mesh that represents a microstructure defined by the user in the interface. 3. Cubit runner. This is a secure shell protocol tool that makes the submitting the DREAM mesh to an HPC instance and starts to run Cubit shell commands to smooth the grain boundaries with its `sculpt` library, applies user-defined boundary node sets, and bundles and returns the simulation-ready meshes and input files as a zipped directory.

Harris, BrennanKay↗

Conversion Helper 4 Easy Serialization Of Exi (ch4ese)

CH4ESE is an EXI conversion tool developed in Python3 that utilizes the open-source EXIficient implementation of the W3C EXI format specification. CH4ESE can be used to translate to and from EXI format using the command line with input data or using the web server for live-translation.

Rohde, KennethW [Idaho National Laboratory (INL), ↗

EyeON

EyeON: Eye on Operational technology Software Supply Chain attacks have risen drastically over the past few years, none more well-known and impactful than the SolarWinds compromise. Criminal organizations inserted an attack vector into a specific version of the source code, giving themselves an air of credibility. Once news broke on SolarWinds, identifying compromised sites was very difficult, even knowing the culprit update. Software Bills of Materials (SBOM) have been touted as the solution to reclaiming control of your software supply chain. Deployment of SBOMs has been slow, however, due to conflicting standards, opaque storage requirements, and vendor adoption. Additionally, the path from obtaining an SBOM and securing your supply chain is unclear; how can an SBOM library be leveraged to provide insight to your attack surface? The EyeON tool, sponsored by Department of Energy Cybersecurity, Energy Security, and Emergency Response (DoE CESER), aims to address these gaps by providing an encapsulated solution to tracking which updates have been installed in an enterprise, and alerting system administrators to vulnerabilities as they become known. Similar to a virus scanner, EyeON is a command line tool to parse either a single file, nested directory structure, or filesystem. It collects data such as signature (hashes), version information, VirusTotal tags, compiler, compilation date, and code signing information. Users will anonymously submit scan data periodically to DoE CESER, who will then compile a database of known software products employed by Critical Infrastructure and broadcast alerts based on discovered flaws as they arise.

Tenzing, Wangmo↗

Datum: A Scientific Metadata Catalog

The data catalog market is currently flooded with a myriad of different products, but none serve the scientific community well. There are cloud-native tools like Databricks, Snowflake,to on-premise solutions like Collibra and Datahub. The common failing of all these tools however, is their inability to serve the scientific data community directly. Most catalogs are targeted towards financial, health, or user data - not sensor or scientific domain data. They also prioritize integrations that often don’t exist or are just starting to be used in the scientific realm - all while ignoring common scientific tools and file types. Datum is a catalog which targets the scientific data directly, including the tools and networks in which those tools are used. We work with the producers and consumers of the data where they are, targeting cloud and on-premise with a focus on classified networks. Datum is an Erlang/Elixir application. Technical Features Note: The features listed below are still under development and may change, slightly, upon final delivery of the product. File Formats - Datum has the ability to read additional metadata and provides processing pipelines for the following file formats: Plain Text, PDF, LaTeX, HTML, Open Document Format (.odt), XML, CSV/TSV (and other standard delimiters), OpenDocument Database and Spreadsheets, Geo-Referenced TIFF, Common Data Format, HDF/HDF5, LabView TDMS, Excel, DeltaTables, Parquet, Apache Iceberg, Apache Hudi and many others. Metadata Collection - Scanners for the local and networked file systems and cloud storage providers. Network integration with common databases such as MSSQL and MySQL. User Plugin System - Users are able to provide either file processing, metadata extraction, or sampling plugins in the programming language of their choice. Authentication/Authorization -: OIDC integration, SCIM provisioning and EntraID integration out of the box. Full user and group management system with a “least privilege” operating mode. Governance - Customizable data governance platform; dictate and enforce required metadata, enforce data embargos, and enforce user agreements and NDAs before data access. Ability to create health checks on data, rejecting abandoned or poorly curated data and automatically removing it from the search index. Ability for users to submit corrections. Search - Semantic search is a first class citizen. No licenses to expensive, external software required. Integrated use of vectors and vector-based search allows for AI agent integration at all levels of operation. Metadata Model - Display and control data’s lineage and connections to other data and data directories. Data is modeled after a filesystem - an organization instantly recognizable and navigable by most any user. CLI and SDK - Ships with a Command Line Interface (CLI) tool and with a fully-featured Python SDK. This allows for rapid and programmatic use of Datum by every level of user. Minimal Infrastructure - Datum ships as a single executable file and can be run on any operating system and most CPU architectures. Datum has no reliance on external databases, search indexing tools, or other outside services - and it runs equally well on edge computing devices, cloud services, or in a clustered HPC environment.

darrington, john↗

DER Cybersecurity Detection and Response Suite

SAND2024-08475O The Distributed Energy Resource (DER) Cybersecurity Detection and Response Suite is a solution for distributed energy resource (DER) systems. The DER Security Orchestration, Automation, and Response (SOAR) solution that uses alerts from signature- and behavior-based Intrusion Detection Systems are intended to be deployed as bump-in-the-wire (BITW) devices in front of DER equipment. The fielded application would use multiple intrusion detection systems that report data to SOAR to respond to cyberattacks. The suite consists of two software components: • The proactive intrusion detection and mitigation system (PIDMS) secures grid-edge photovoltaic smart inverters and other equipment in distributed energy resource systems. It is a distributed BITW solution; cyber and physical data are automatically processed using network inspection tools and custom machine learning algorithms to detect abnormal events and correlate cyber-physical events. • The Security Orchestration, Automation, and Response for Distributed Energy Resources (SOAR4DER) application ingests data from several intrusion detection systems to quickly block attacks and revert DER systems to good states. Using a collection of intrusion detection system technologies on a BITW device, it incorporates physical and cyber data to detect abnormal and potential malicious behaviors. Multiple SOAR playbooks then use the intrusion detection system data streams to automatically defend the system. SOAR4DER system testing showed detection and response times under 30 seconds for all adversary reconnaissance, denial-of-service attacks, malicious Modbus commands, brute-force logins, and machine-in-the-middle attacks. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Johnson, Jay↗

Machine Learning Automation Pipeline

Machine Learning Automation Pipeline (MLAP) is a package to perform machine learning (ML) analysis in a step by step manner, starting with data extraction until analysis and prediction. The scripts provide the users option to chose an action such as "Extract", "Prep", and "Train" and numerous cases can be launched with just a single command. The inputs for each case are provided using a JSON file. The simulation results of several cases can be assessed using an automated process and analyzed for various metrics pertinent to ML analysis.

Jha, Pankaj↗

Web Based Beamline Control System (Bluesky Web) v0.1.0

Bluesky Web is a web based interface that provides beam line controls to the end user. It allows users to issue commands to various physical devices at a beam line end station like motors and cameras. It utilizes an open source Python library (Bluesky) as the controller. It uses Bluesky to also allow for running "plans" or a sequence of device operations that can be used when running an experiment. This program is different from other controls technologies because it is intended to be open source and can be accessed from a web browser, as opposed to other paid software that is run as a stand-alone application on a computer.

De Leon, Seij↗

Microreactor Optimization Using Simulation And Economics (mouse)

Microreactor Optimization Using Simulation and Economics (MOUSE) is a tool that integrates both nuclear microreactor design and reactor economics to provide comprehensive evaluations and optimizations. This tool enables stakeholders to explore the interplay between technical and economic variables, guiding them towards effective and competitive microreactor solutions. For the reactor core simulations, MOUSE leverages the OpenMC Monte Carlo Particle Transport Code to perform detailed core simulations for various microreactor designs. The included OpenMC models are 2D core designs of a Liquid Metal Thermal Microreactor (LMTR), a Gas-Cooled TRISO-Fueled Microreactor (GCMR), and a Heat Pipe Microreactor. Beyond core design, MOUSE includes simplified calculations for: - Calculating the masses of heat exchangers within the system. - Mechanical power of pumps. - Estimating the area occupied by various buildings within the nuclear plant. For the economic analysis, MOUSE provides detailed bottom-up cost estimates, encompassing a wide range of costs including preconstruction costs, direct costs, indirect costs, training costs, financial costs, operation & maintenance (O&M) costs, and fuel costs. These cost estimations are developed using data from the MARVEL project and additional literature sources, enabling the calculation of total capital costs and levelized cost of energy for both first-of-a-kind and nth-of-a-kind microreactors. MOUSE also enables analysis of the cost drivers and competitiveness in the electricity market. MOUSE allows users to modify a wide array of technical and economic parameters to evaluate different scenarios and their impacts. Examples of these parameters include: Fuels, coolants, or reflector materials Enrichment levels Control drum materials and geometry Fuel pin geometry and materials Moderator pin geometry and materials Reactor core and reflector dimensions Packing factor for the TRISO particles Nuclear reactor power and reactor burnup Number of sensors Shielding thickness Reactor vessel and guard vessel dimensions Operational staff requirements Number of emergency shutdowns Levelization period Interest rate Construction duration Since MOUSE is powered by the WATTS toolkit, it supports optimization studies, parametric analyses, and uncertainty calculations/propagation. The optimization techniques enable users to identify optimal design and economic configurations. The parametric analysis tools allow users to explore the sensitivity of various parameters, while uncertainty propagation helps quantify the impact of uncertainties on overall performance and cost. User Interface and Workflow: Currently, MOUSE is a command-line-based tool. Users can input various reactor design or economic parameters, modify the designs, run simulations, and visualize results through comprehensive data visualization and reporting capabilities. The typical workflow involves setting up the reactor model, defining economic parameters, running simulations, and analyzing the results to make informed decisions. By combining advanced design calculations with detailed economic modeling, MOUSE provides a robust framework for optimizing nuclear microreactor technologies, enhancing their competitiveness, and guiding stakeholders towards innovative and cost-effective solutions.

Hanna, Botros [Idaho National Laboratory (INL), Id↗

PyTrac

SAND2025-00635O PyTrac is a software tool that analyzes and visualizes PTRAC event files generated by MCNP 6.3. It converts these files into a graph network that makes it easier to interpret individual histories. The software includes command line tools for viewing the graph data structure in both 2D and 3D formats. PyTrac also integrates with MCNP to run simulations and manage data files. This provides a streamlined approach to analyzing and understanding the complex data generated by MCNP simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Nowack, Aaron [Sandia National Lab. (SNL-CA), Live↗