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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

DXRD : a user-friendly suite of two- and multiple-beam dynamical X-ray diffraction programs

The DXRD program suite consisting of a series of dynamical theory programs is introduced for computing dynamical X-ray diffraction from single crystals. Its interactive graphical user interfaces (GUIs) allow general users to make complicated calculations with minimal effort. It can calculate plane-wave Darwin curves of single crystals (or multiple crystals) for both the Bragg and Laue cases, including grazing-incidence diffraction and backward diffraction (with Bragg angles approaching 90°). It is also capable of simulating rocking curves for divergent incident X-ray beams with finite bandwidths. A unique feature of DXRD is that it provides a convenient GUI-based multiple-beam diffraction program that can accurately compute arbitrary N-beam diffraction of any geometry using a universal 4N × 4N matrix method. DXRD also provides a mapping program for plotting all the multiple-beam diffraction lines (monochromator glitches) in the azimuth–energy coordinate system. All these functions make DXRD a convenient and powerful software tool for designing crystal-based synchrotron/X-ray optics (monochromators, analyzers, polarizers, phase plates etc.) and for crystal characterization, X-ray spectroscopy and X-ray diffraction teaching.

Bragg reflection↗
DOE OSTI2025

sourcePy

Pollutant source identification techniques (of which there are many variations) are either locked behind researchers writing their own code for each use case or GUI platforms that are easy to use but inflexible and opaque. The Python package sourcePy brings together many of the pollutant source identification algorithms, giving the user full control out of the box. It aims to create a platform for source identification experiments where the full analysis from beginning to end can be done in Python, with a level of specificity in design that isn't available in the GUI options. sourcePy provides users with a few key features: -A Python interface with HYSPLIT, which can be used to generate trajectories and concentration plumes -Several Python classes which standardize the preparation and processing of data related to source identification experiments -Example scripts and notebooks that allow even new python users to get started with their own experiments quickly -Visualization methods

Arseneau, Isaac [Oak Ridge National Laboratory (OR↗
DOE OSTI2025

FY25 Mid-Year Report: FNCL Enhancements Implementation

During the first half of FY25 the FNCL team has made consistent progress toward the completion of our project goals. The FNCL prototype panel design has been successfully applied to a fully instrumented 3-panel system which is actively under construction. The FNCL Demonstrator System contains solid scintillators instrumented with SiPMs, which operate on an updated CAEN digitizer, requires no high-voltage, and has a smaller overall footprint. The onboard software will include the LLNL-developed GMM-PSD signal processing. Later this year the system will be experimentally tested alongside the baseline FNCL instrument at LLNLs ISSA facility. In addition to a full systems test, the performance of a DD generator for active interrogation measurements compared to the standard AmLi source will be established for both systems. The data collected at the ISSA facility will be used to experimentally validate the FNCL-Fast Isotopic Fuel Assay’s (FIFA) capability to measure U-235 loading and to predict gadolinium poison content with passive interrogation. The FNCL-FIFA modal was benchmarked with simulation-based data and a user-friendly GUI was added earlier this year. Three separate codes have been submitted to the LLNL ESW system for review prior to their transfers. These include the Predictive Modeling Response toolkit, GMM-PSD firmware beta version, and the FNCL-FIFA analysis package with GUI and user documentation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions

Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.

25 - ENERGY STORAGE↗
DOE OSTI2025

Nanopolysaccharide Builder: A User-Friendly Tool for Atomistic Models of Polysaccharide-Based Nanostructures

Here, we introduce Nanopolysaccharide Builder (NPB), a user-friendly software tool designed to construct polysaccharide nanostructures─mainly those based on cellulose, chitin, and chitosan─using experimental data or user-defined parameters. NPB enables the generation of cellulose and chitin allomorphs with customizable biochemical topologies and also facilitates the construction of large bundles that replicate nanostructures found in biological support systems, including plant cell walls and arthropod cuticles. The software outputs atomic Cartesian coordinates in Protein Data Bank (PDB) format and also provides atom connectivity files in PSF and PARM formats, ensuring seamless integration with major molecular dynamics (MD) engines such as NAMD, CHARMM, GROMACS, AMBER, OpenMM, and LAMMPS. Built on an interactive visualization framework, NPB features a graphical user interface (GUI) and supports both macOS and Linux operating systems. By enabling detailed atomic-scale studies of polysaccharide evolution in extracellular matrices and cell walls of algae, bacteria, fungi, and plants, NPB is poised to advance AI-guided research in sustainable chemical development and biomass utilization.

Wan, Zhangmin [Univ. of British Columbia, Vancouve↗
DOE OSTI2025

A machine-learning-driven data labeling pipeline for scientific analysis in MLExchange

This study introduces a novel labeling pipeline to accelerate the labeling process of scientific data sets by using artificial intelligence (AI)-guided tagging techniques. This pipeline includes a set of interconnected web-based graphical user interfaces (GUIs), where Data Clinic and MLCoach enable the preparation of machine learning (ML) models for data reduction and classification, respectively, while Label Maker is used for label assignment. Throughout this pipeline, data can be accessed through a direct connection to a file system or through Tiled for access through Hypertext Transfer Protocol (HTTP). Our experimental results present three use cases where this labeling pipeline has been instrumental for the study of large X-ray scattering data sets in the area of pattern recognition, the remote analysis of resonant soft X-ray scattering data and the fine-tuning process of foundation models. These use cases highlight the labeling capabilities of this pipeline, including the ability to label large data sets in a short period of time, to perform remote data analysis while minimizing data movement and to enhance the fine-tuning process of complex ML models with human involvement.

Chavez, Tanny (ORCID:0000000193172896)↗
DOE OSTI2024

Spatial-Temporal PV Hosting Capacity Estimation and Evaluation

Evaluating Photovoltaic Hosting Capacity (PVHC) is an essential step in the process of integrating solar energy into power grids, particularly when focusing on the distribution network (DN) as the primary integration target. PVHC needs to be investigated, especially in cases where the grids are unbalanced, and their operational conditions vary spatially and temporally. This motivation prompted us to propose a scalable model tailored to this application. In this paper, we applied linearization to the alternating current optimal power flow (AC-OPF) and solar inverters, transforming the original problem into a mixed-integer linear programming (MILP) problem. Additionally, we accounted for the battery energy storage system (BESS) as a time-coupling factor for calculating PVHC. We then compared the PVHC results between the IEEE-13 bus and SMART-DS San Francisco (SFO) cases and discussed the extent to which BESS can enhance the PVHC of a DN. Furthermore, we designed a web-based graphical visualization for the SFO case, enabling user interaction with raw data and simulation results on a map through a graphical user interface (GUI). In summary, our results and findings provide valuable insights for future three-phase unbalanced AC-OPF PVHC practices and their visualization.

AC-optimal power flow↗
DOE OSTI2024

Hardware-in-the-Loop Testing of Wide-Area Damping Controller for Field Implementation in Large-scale Power Grid

In our previous work, an adaptive measurement-driven wide-area damping controller (WADC) for suppressing inter-area oscillations has been proposed and a hardware prototype was developed and validated through hardware-in-the-loop tests. As a continuation of the work, this paper introduces a WADC software prototype to handle the realistic challenges for field implementation in the control room of the power grid. The WADC software is developed and operated as an openPDC adapter with a graphical user interface (GUI) to monitor the WADC inputs and output, the communication delays and other variables. The software prototype has been fully tested through an enhanced hardware-in-the-loop (HIL) test setup. Its performance is verified under various realistic communication uncertainties, such as random time delays and data losses, with different communication protocols. The experiment results have proven the WADC software can deliver sufficient damping to suppress the targeted oscillation mode in handling various communication uncertainties for future field deployment.

Jia, Xinlan↗
DOE OSTI2025

Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. In preparation for VENUS, the neutron imaging beamline to be located at beam port 10, we have performed a series of experiments focused on wavelength-dependent radiography and computed tomography for a broad range of applications, from materials science to biological tissues.One of the time-of-flight (TOF) techniques that is of interest to the scientific community is the 2-dimensional mapping of phases and average crystalline plane orientation in samples both ex-situ and during applied stresses such as tensile loading and heating. This technique is known as Bragg edgeimaging and relies on the identification of changes of transmission values, fitting of the edge to measure its displacement, and thus identify the shift in lattice parameter due to stresses. One of the challenges of TOF imaging measurements is the amount of data and the inability to observe Bragg edge shifts in real time during an experiment. Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the

Bilheux, JeanChristophe [Oak Ridge National Labora↗
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

Seismic H2: Version 1.0

Seismic-H2 is an integrated software package for geological hydrogen reservoir simulation, optimization, and leakage monitoring. The package includes multiple components: (1) code used for modeling seismic wave propagation in 3D heterogeneous elastic media based on finite-difference method to support detection of geological hydrogen storage reservoir leakage; (2) 3D reservoir simulations of leaks from an underground reservoir and 3D simulations of saline aquifers and depleted gas reservoirs; (3) seismic monitoring costs of passive and active seismic monitoring required for UHS; (4) rock physics calculations and interpolations for converting the reservoir simulations from part (2) into the elastic media models in part (1); (5) pre-processing seismic data; and lastly (6), a GUI interface that combines these different components.

Creasy, Neala↗
DOE OSTI2025

Coreii - Scout

COREII Scout employs React, Vite, TypeScript, Tailwind, and Daisy UI for its graphical user interface (GUI), offering both dark and light modes. The code is modular, with components and reusable wrappers to enhance efficiency. The primary goal of COREII Scout is to aid analysts in collecting and analyzing various sources related to cyber attacks, utilizing models to automate the report writing process. It uses Named Entity Recognition (NER), a type of Natural Language Processing (NLP), to extract key entities from each source. Analysts review and classify these entities using the COREII Attack Chain Estimator (ACE), adding their comments. Ultimately, a Large Language Model (LLM) generates a detailed report with user guidance. This setup ensures a streamlined and effective approach to cyber attack analysis and reporting.

Pluth, Adam [Idaho National Laboratory (INL), Idah↗
DOE OSTI2025

otsdaq

otsdaq is a Ready-to-Use data-acquisition (DAQ) solution aimed at scaling down to test-beam, detector development, and other rapid-deployment scenarios; and scaling up through the development cycle to fullscale production and operation. otsdaq uses the artdaq DAQ framework under-the-hood, providing flexibility and scalability to meet evolving DAQ needs. otsdaq provides a library of supported front-end boards and firmware modules which implement a custom UDP protocol. Additionally, an integrated Run Control GUI and readout software are provided, preconfigured to communicate with otsdaq firmware.

Rivera, Ryan [Fermi National Accelerator Laborator↗
DOE OSTI2026

OptiMX

OptiMX is a GUI-oriented program with principal aim to be an easy to use, yet comprehensive, interactive accelerator optics design and analysis tool. It was originally developed starting in the 1990s as an MS Windows centric application using the commercial Borland OWL framework. In the spring of 2014, a decision was made to port OptiM to Qt, a modern, portable and open framework. As much as possible, the original interface was preserved.While a significant amount of refactoring was required, the underlying physics has been for the most, left unchanged. The custom plots of the original application have been replaced with functional equivalents based on a stable and well-established library (qwt). With very few minor exceptions the new refactored OptiMX should be a drop-in replacement for the original OWL version.

Lebedev, ValeriA. [Joint Inst. for Nuclear Researc↗
DOE OSTI2026

EPWgen (EPW generator) [SWR-26-017]

EPWgen fetches hourly station observations (NOAA/Meteostat), fills gaps with MERRA2 reanalysis, merges data, and writes EPW files with computed headers (HDD/CDD, ground temperatures). It also runs QC checks, supports CSV-driven batch and metered-variable exports, and provides a PyQt5 GUI with mapping and progress tracking for single/multi-year workflows.

Bianchi, Carlo [National Laboratory of the Rockies↗
DOE OSTI2026

lumicap v0.1

Automated HDR luminance imaging system designed for daylighting research and building science. It controls a fisheye-lens camera to capture time-lapse bracket sequences, merges them into calibrated HDR images, and runs a full post-processing pipeline — all unattended. Features: - Scheduled LDR bracket capture via gphoto2 - HDR merging with vignetting, ND filter, and fisheye projection corrections - Illuminance and luminance meter integration (Konica Minolta T-10A, LS-100/150) - Daylight glare probability (DGP) and solar position computation - Automated false-color rendering, JPEG thumbnails, and daily time-lapse video - CSV data logging per timestep Uses: - Long-term monitoring of daylight conditions in buildings - Glare analysis for occupant comfort research - Solar irradiance and sky luminance studies Advantages: - End-to-end automation — capture, calibration, analysis, and archiving run without manual intervention - Built on the proven Radiance toolchain, ensuring photometrically accurate HDR output - Hardware-agnostic meter support via serial auto-detection - Lightweight — no GUI overhead, deployable on a headless Raspberry Pi or similar embedded system

Wang, Taoning [Lawrence Berkeley National Laborato↗
DOE OSTI2026

pnnl/HADREC (33077-E)

This HADREC GUI is designed to visualize power system emergency control time-series data and facilitate the comparison of the newly developed meta strategy optimization algorithm-based emergency control with existing out-of-step-based emergency control approach, and a no-action case for reference.

Wang, Heng [Pacific Northwest National Laboratory ↗
DOE OSTI2026

pySimpleMask

SF-26-118 pySimpleMask is a tool for creating masks and Q-partition maps for X-ray scattering patterns, supporting SAXS, WAXS, and XPCS data reduction. It ships both a desktop GUI and a headless Python API that can drive the full pipeline from scripts.

Chu, Miaoqi [Argonne National Laboratory (ANL), Ar↗