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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Cybersecurity-Tools/V2W-BERT

Software Vulnerabilities to Weakness Mapping. V2W-BERT optimizes the learnable parameters θ of Fθ in two steps. In the first step, the pre-trained BERT language model is further fine-tuned with CVE/CWE descriptions specific to cyber security. In the second step, the trained BERT model is employed in a Siamese network architecture to establish links between CVEs and CWEs. The architecture takes a specific CVE-CWE pair as input and predicts whether the CVE belongs to the CWE or not, with a confidence value. V2W-BERT includes a Mask Language Model (LM) based Reconstruction Decoder to ensure that the descriptions’ contexts are not changed too much during the training process.

Halappanavar,, Mahantesh↗
DOE OSTI2024

Machine learning tools for epigenetics

The software provides machine learning analysis and visualization to detect patterns in epigenetic data, including conventional machine learning and statistical methods, and open-source packages like pyBigWig (https://github.com/deeptools/pyBigWig) for data processing. The software is written in python, it uses some python libraries.

Kim, Anastasiia↗
DOE OSTI2024

Vidyut3d: A Non-Equilibrium Plasma Modeling Tool [SWR-24-101]

Vidyut3d is a massively-parallel plasma-fluid solver for low-temperature plasmas (LTPs) that supports both local field (LFA) and local mean energy (LMEA) approximations, as well as complex gas and surface-phase chemistry. The solver supports 2D and 3D domains, and uses AMReX's adaptive mesh refinement capabilities to increase the grid resolution around complex structures (e.g. streamer heads and sheaths) while maintaining a tractable problem size. Vidyut specializes in simulating various types of gas-phase discharges, as well as plasma/surface interactions and surface chemistry (e.g. for plasma-mediated catalysis applications). The solver also supports hybrid CPU/GPU parallelization strategies, and has demonstrated excellent scaling on various HPC architectures for problem sizes consisting of O(100 M) control volumes.

Sitaraman, Hariswaran↗
DOE OSTI2024

PNNL-CIM-Tools/EASY-CIM

Extracting Attributes in a Simple DictionarY of CIM (EASY-CIM) is a python library to reduce the time and burden of model queries using simplified data representations of CIM power system models.

Anderson, Alex↗
DOE OSTI2025

Open-Source Ambient-Signal-Based Inertia Monitoring Tool for Power systems [SWR-25-59]

This script, developed by NREL, implements an inertia estimation algorithm using a sliding window approach. The inertia (H) is estimated based on frequency deviations and active power deviations, utilizing the swing equation from power system dynamics. An example application is provided using the WECC 240-bus system.

Peng, Jiangkai [National Renewable Energy Laborato↗
DOE OSTI2025

Blue Keanu: A Scientific Visualization Tool For Network Data

This software allows the user to visualize complex PCAP-ng files captured from network capture software such as Wireshark. The visualization runs in a GUI window that can be zoomed or moved to areas of interest in a waterfall type display. The user then can see an area of interest that looks different than the typical traffic visually, such as a human interaction or non-repetitive area of data. The program will tell the user the packet number and byte offset of interest for fast analysis of discrete atomic or non-random events. This is particularly useful for visualization of unknown binary format data, such as in PLC or SCADA protocols that may have human or other non-repetitive activity for further analysis, reverse engineering, or fast forensic analysis.

Durller, MichaelGeorge↗
DOE OSTI2025

reVReports (Renewable Energy Potential(V) Reports Tool) [SWR-25-29]

The purpose of this library is to make it very simple to create standard, report-quality graphics that summarize the key results from multiple scenarios of reV supply curves. Refer to the Usage for documentation of how to use the library.

Gleason, Mike [Root Geospatial, LLC]↗
DOE OSTI2025

OPET Firmware (Open PV Electrical Tool Firmware) [SWR-25-43]

The main application of OPET is long term performance measurements of PV devices in field or under controlled environmental conditions. This repository contains everything relating to the firmware of the OPET device including source code. If you are looking for the hardware or control software repositories, links are below: https://github.com/NREL/opet-hardware https://github.com/NREL/opet-control

McDanold, Byron [National Renewable Energy Laborat↗
DOE OSTI2025

Cyber Informed Engineering Cie Analysis Tool

Main Benefits: • Collaborate on assessment via the web and access and share assessments on your mobile device. • Helps you maximize your cybersecurity investment and resources • Saves you significant time and money by eliminating the requirement to research each government and industry standard in order to understand your cybersecurity posture • Contains easy to follow, step by step instructions to guide you through the process of identifying the cybersecurity posture of your organization • Provides a place to begin with cybersecurity improvement and a way to prioritize your tasks and budgets. • Covers all major cyber relevant topic areas for a comprehensive assessment of your organization’s cybersecurity posture. • Dives deep into the details of each topic area. • Contributes to the organization's risk management and decision-making process • Highlights vulnerabilities and gaps in your organization's IT and control systems. • Raises awareness and facilitates discussion on cybersecurity within your organization • Educates the controls system community on cyber security.

Hansen, Barry [Idaho National Laboratory (INL), Id↗
DOE OSTI2025

Radsource Mr: Mixed Reality Planning Tool For Radioactive Recovery

The RadSource MR system leverages Meta Quest 3's advanced mixed reality capabilities to create a comprehensive spatial planning platform for end-of-life sealed radioactive source recovery operations. The application utilizes the Quest 3's high-resolution passthrough cameras and spatial mapping algorithms to generate accurate 3D environmental models. Core technical components include: (1) Real-time spatial measurement algorithms calculating distances, angles, slopes, and surface areas with sub-centimeter accuracy; (2) Virtual object placement system allowing users to position digital representations of recovery equipment (trailers, containment vessels, protective barriers) within the real environment; (3) Voice recording and annotation system for hands-free documentation in protective equipment; (4) 3D mesh capture and storage capabilities for post-operation analysis and regulatory documentation. (5) Procedure documentation is available for viewing in Mixed Reality, providing an innovative and convenient way to access the information during pre-visit and inspection activities. (6) Support for screen capture for the view for real world and virtual objects together to use it later for planning. The system integrates computer vision techniques for environmental understanding, spatial mathematics for precise measurements, and human-computer interaction principles optimized for hazardous environment operations. Data persistence allows teams to save and share planning sessions across multiple stakeholders while maintaining operational security requirements.

Khadka, Rajiv [Idaho National Laboratory (INL), Id↗
DOE OSTI2025

Machine Learning Atom Probe Tomography Tool For Automatic And Fast Clustering

The software uses a YOLO11 segmentation model trained on synthetic data to analyze APT datasets. The workflow operates as follows: 1. Data Slicing: The APT dataset is divided into multiple 2D cross-sections of a specified thickness. 2. Segmentation: The model identifies point-dense regions within each 2D slice. 3. 3D Reconstruction: Detected regions (masks) from all slices are combined and reconstructed back into the original 3D space, forming clusters. The integration with HPC resources enables the software to process large-scale APT datasets efficiently. This combination of automation and scalability reduces manual intervention, improves reproducibility, and accelerates the clustering workflow.

Tang, Yalei [Idaho National Laboratory (INL), Idah↗
DOE OSTI2025

An Open-source Llm Enhanced-tool Specialized In Helping Moose Related Problems And Tasks

MOOSEenger is an open-source, terminal-first chat application for the MOOSE ecosystem that couples specialized parsing of MOOSE documentation and “.i” input files with retrieval-augmented generation to deliver grounded answers about multiphysics modeling and workflows. It includes dedicated readers for MOOSE-style HTML and a pyhit-based parser that uses the MOOSE syntax tree to preserve block structure and attach retrieval metadata. A data-ingestion pipeline performs semantic chunking into atomic facts and stores them hierarchically in a local Chroma vector database that maintains parent–child relationships across documents; the system can ingest directories, individual files, and single-page web content, and it provides CRUD operations (insert, update, delete) to manage the corpus. At query time, relevant chunks are embedded, retrieved, and fused into the model context, with interactive features such as token streaming, persistent chat history, and dynamic RAG (retrieval triggered by user input or intermediate model output). Deployment is flexible: MOOSEenger runs with local Ollama models or remote Hugging Face/OpenAI backends—typically coordinating generation, lightweight tagging/summarization, and embeddings across three models—and it also supports a server mode and integration with the VS Code Continue interface.

Li, Mengnan [Idaho National Laboratory (INL), Idah↗
DOE OSTI2025

DEMOS (Demographic Microsimulator Tool for Longitudinal Synthetic Population) [SWR-25-135] related to NLR SWR-26-076

The Demographic Microsimulator (DEMOS) is an agent-based simulation framework used to model the evolution of population demographic characteristics and lifecycle events, such as education attainment, marital status, and other key transitions. DEMOS modules are designed to capture the interdependencies between short-term and long-term lifecycle events, which are often influential in downstream transportation and land-use modeling. A key feature of DEMOS is its ability to track changes in an agent’s demographic status from year t to year t + 1. This structure allows the model to evolve populations over any user-defined time horizon. As a result, DEMOS is well suited for analyzing medium- and long-term transportation-related decisions, including household vehicle transactions (e.g., purchasing, selling, or replacing vehicles) and work location choices. Core features of DEMOS include the modeling of more than ten lifecycle events, behaviorally realistic patterns informed by long-running panel data, explicit representation of interdependencies among lifecycle processes, and a flexible, modular simulation architecture. A technical memorandum describing DEMOS is available here. The memorandum provides an overview of the framework’s functionality, model structure, input and output data, and its applications in transportation planning and broader policy analysis contexts. Interested readers are also encouraged to consult the paper listed below for additional details on the DEMOS methodology. Sun, Bingrong, Shivam Sharda, Venu M. Garikapati, Mohamed Amine Bouzaghrane, Juan Caicedo, Srinath Ravulaparthy, Isabel Viegas de Lima, Ling Jin, C. Anna Spurlock, and Paul Waddell. "Demographic Microsimulator for Integrated Urban Systems: Adapting Panel Survey of Income Dynamics to Capture the Continuum of Life." Transportation Research Record (2025): 03611981251333339.

Sun, Bingrong [National Laboratory of the Rockies ↗
DOE OSTI2026

Cyber-informed Engineering Dashboard Tool

The CIE Engineered Controls Database is a large collection of entries and stored in a json structure which makes manual analysis of entries challenging. The dashboard provides a user with a simple interface to look through the database contents.

Lampe, BenjaminR↗
DOE OSTI2020

The ARM Data-oriented Metrics and Diagnostics Package for Climate Models - A New Tool for Evaluating Climate Models with Field Data

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program User Facility produces ground-based long-term continuous unique measurements for atmospheric state, precipitation, turbulent fluxes, radiation, aerosol, cloud and the land surface, which are collected at multiple sites. These comprehensive datasets have been widely used to calibrate climate models and are proven to be invaluable for climate model development and improvement. This article introduces an evaluation package to facilitate the use of ground-based ARM measurements in climate model evaluation. The ARM data-oriented metrics and diagnostics package (ARM-DIAGS) includes both ARM observational datasets and a Python-based analysis toolkit for computation and visualization. The observational datasets are compiled from multiple ARM data products and specifically tailored for use in climate model evaluation. In addition, ARM-DIAGS also includes simulation data from models participating the Coupled Model Inter-comparison Project (CMIP), which will allow climate-modeling groups to compare a new, candidate version of their model to existing CMIP models. The analysis toolkit is designed to make the metrics and diagnostics quickly available to the model developers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Microscale thermophoresis as a powerful tool for screening glycosyltransferases involved in cell wall biosynthesis

Background: Identification and characterization of key enzymes associated with cell wall biosynthesis and modification is fundamental to gain insights into cell wall dynamics. However, it is a challenge that activity assays of glycosyltransferases are very low throughput and acceptor substrates are generally not available. Results: We optimized and validated microscale thermophoresis (MST) to achieve high throughput screening for glycosyltransferase substrates. MST is a powerful method for the quantitative analysis of protein-ligand interactions with low sample consumption. The technique is based on the motion of molecules along local temperature gradients, measured by fluorescence changes. We expressed glycosyltransferases as YFP-fusion proteins in tobacco and optimized the MST method to allow the determination of substrate binding affinity without purification of the target protein from the cell lysate. The application of this MST method to the β-1,4-galactosyltransferase AtGALS1 validated the capability to screen both nucleotide-sugar donor substrates and acceptor substrates. We also expanded the application to members of glycosyltransferase family GT61 in sorghum for substrate screening and function prediction. Conclusions: This method is rapid and sensitive to allow determination of both donor and acceptor substrates of glycosyltransferases. MST enables high throughput screening of glycosyltransferases for likely substrates, which will narrow down their in vivo function and help to select candidates for further studies. Additionally, this method gives insight into biochemical mechanism of glycosyltransferase function.

59 BASIC BIOLOGICAL SCIENCES↗