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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Updates to the Spatial Analysis and Decision Assistance (SADA) Freeware Tool - 16583

SADA is a collaboration between the University of Tennessee and Oak Ridge National Laboratory to present a freeware desktop application integrating environmental risk analytics, spatial modeling, and decision sciences for use at EPA, NRC, DOE, and DoD contaminated sites. The software embeds risk assessment, uncertainty modeling, and downstream decision processes within a spatial context. Updates to Version 6 will provide will include a rich GIS environment and a new 3-D visualization model which permits immersive visualization of contamination, with topology, and the built environment. The risk models presented are developed in conjunction with Superfund to implement all scenarios in their Regional Screening Levels (RSLs) and radionuclide preliminary remediation goals (PRGs). In addition, SADA will be able to ingest high resolution LandScan population data providing insights into the proximity of population to contamination. A brief overview of the progress in provided along with anticipated next steps. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Optimization and Diagnostics Code for Technological Processes: Radiochemical Production Simulator

A software-hardware complex with the possibility of simulating the functioning of technological processes with APCS in real and accelerated time is being developed as part of Project Breakthrough in order to determine the optimal operating regimes of the technological processes of the units in a closed nuclear fuel cycle. It makes possible monitoring and control functions and the visualization and archiving of the results of simulation, which makes it possible at the development stages of technologies to evaluate the degree of adherence to the requirements of the technological equipment, regulating organs and final-control mechanisms, measurement apparatus, and monitoring channels, to analyze the control and diagnostics algorithms, blocking and protection, and to make when necessary changes in the design being developed. The developed software-hardware complex is a stimulator that will make it possible not only to investigate process schemes with their corresponding algorithms but also to develop training complexes for the training and certification of service personnel.

42 ENGINEERING↗
DOE OSTI2021

VERAIO Software Management Plan

VERAIO is a set of utility codes used to provide a common set of input and outputs to the Virtual Environment for Reactor Applications (VERA). VERA is a collection of several different computer codes that all have a common input and output. This prevents the need to manage input and output from each individual code, allowing for ease of use and reducing errors associated with code operability. The VERAIO utilities include VERAIn, VERAView, and VERARun. Each of these utilities is described below. VERAIn is an input processor that reads an ASCII input file generated by users, parses the file, performs some error checking, and writes an XML file to be read by other VERA codes. The main purpose of VERAIn is to provide a common input to all of the VERA codes so users only need to learn one input. VERAIn is written in Perl and uses YAML configuration files to provide flexibility. VERAView is a graphical user interface (GUI) that reads a VERA HDF output file and allows users to visualize results. VERAView is written in Python. VERARun is a script that drives the VERA execution in a high performance computing (HPC) environment. Work performed at the code level supports the Quality Assurance Program Plan (QAPP) (VERA-QA-001), and VERA Software Quality Assurance Plan (VERA-QA-002).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Lightfall v0.0.1

Lightfall is a desktop application for synchrotron beamline instrument control, data acquisition, and live analysis at the Advanced Light Source (ALS). Built on Python and Qt, it provides a native graphical interface for operating beamline hardware, configuring and executing experimental scans, and visualizing results in real time. Key features include direct integration with EPICS control systems, a built-in electronic logbook, remote beamline access over secure tunnels, and an interprocess communication (IPC) architecture that coordinates with external analysis applications via ZMQ and EPICS process variables. This IPC approach allows Lightfall to orchestrate specialized analysis tools—including GPU-accelerated streaming correlators—without embedding them, avoiding the dependency conflicts common in monolithic scientific software platforms. Compared to prior approaches such as Xi-CAM's plugin-based architecture, Lightfall's design cleanly separates instrument control from domain-specific analysis, enabling feedback-driven acquisition where live analysis results can adjust scan parameters during an experiment. Its native Qt interface provides responsive performance for real-time data visualization that web-based alternatives struggle to match. Lightfall is designed for use by beamline scientists and staff operating synchrotron instruments at national user facilities.

Pandolfi, Ronald [Lawrence Berkeley National Labor↗
DOE OSTI2022

VERAIO Software Management Plan

VERAIO is a set of utility codes used to provide a common set of inputs and outputs to the Virtual Environment for Reactor Applications (VERA). VERA is a collection of several different computer codes that all have a common input and output. This prevents the need to manage input and output from each individual code, allowing for ease of use and reducing errors associated with code operability. The VERAIO utilities include VERAIn, VERAView, and VERARun. Each of these utilities is described below. VERAIn is an input processor that reads an ASCII input file generated by users, parses the file, performs some error checking, and writes an XML file to be read by other VERA codes. The main purpose of VERAIn is to provide a common input to all of the VERA codes, so users only need to learn one input. VERAIn is written in Perl and uses YAML configuration files to provide flexibility. VERAView is a graphical user interface (GUI) that reads a VERA hierarchical data format (HDF) output file and allows users to visualize results. VERAView is written in Python. VERARun is a script that drives the VERA execution in a high performance computing (HPC) environment. Work performed at the code level supports the quality assurance program plan (QAPP) (VERA-QA-001) and the VERA Software Quality Assurance Plan (VERA-QA-002).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Verification of Advective Bar Elements Implemented in the Aria Thermal Response Code.

A verification effort was undertaken to evaluate the implementation of the new advective bar capability in the Aria thermal response code. Several approaches to the verification process were taken : a mesh refinement study to demonstrate solution convergence in the fluid and the solid, visually examining the mapping of the advective bar element nodes to the surrounding surfaces, and a comparison of solutions produced using the advective bars for simple geometries with solutions from commercial CFD software . The mesh refinement study has shown solution convergence for simple pipe flow in both temperature and velocity . Guidelines were provided to achieve appropriate meshes between the advective bar elements and the surrounding volume. Simulations of pipe flow using advective bars elements in Aria have been compared to simulations using the commercial CFD software ANSYS Fluent (r) and provided comparable solutions in temperature and velocity supporting proper implementation of the new capability. Verification of Advective Bar Elements iv Acknowledgements A special thanks goes to Dean Dobranich for his guidance and expertise through all stages of this effort . His advice and feedback was instrumental to its completion. Thanks also goes to Sam Subia and Tolu Okusanya for helping to plan many of the verification activities performed in this document. Thank you to Sam, Justin Lamb and Victor Brunini for their assistance in resolving issues encountered with running the advective bar element model. Finally, thanks goes to Dean, Sam, and Adam Hetzler for reviewing the document and providing very valuable comments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗
DOE OSTI2016

SU-F-T-468: Efficient Scanning Data Analysis for TomoTherapy

Purpose: The standard TomoTherapy 2D scanning system requires manual analysis using spreadsheets or similar software. Manual analysis is time consuming and does not allow efficient use of the medical physicist or timely results that may indicate issues during the acquisition of data. The purpose of this study is to determine if an in-house solution can provide timely analysis of TomoTherapy scan data. Methods: A custom MATLAB program utilizing a streamlined graphical interface was developed to interpret the native scanning data acquired by the TomoTherapy Electrometer Measurement System (TEMS). The gold beam data provided by the manufacturer was used as a baseline for the acquired data. Two separate sets of scan data were used including longitudinal, transverse, and percent depth dose (PDD). The scan data were compared visually in an overlay and analytically for each beam width using the full width half max (FWHM) for longitudinal profiles and difference inside the field core for the transverse profiles as recommended by TG-148. A plot of the PDD percent error at each point along the curve was generated to show agreement. The time to analysis was measured on a laptop running an Intel i5 processor with 8GB of RAM. Results: The software program required on average less than 5 seconds to load and analyze the results. No conversion or reformatting of the data was required. This allowed real-time visualization of the comparison to the gold beam data as well as the parameters recommended by TG-148. The average percent difference was 0.3% for the longitudinal profiles and 0.1% for the transverse profiles. All PDD data was less than 1% different beyond dmax. Conclusion: We have developed a tool to analyze TomoTherapy scan data in real-time. This allows an efficient method to perform beam commissioning, annual QA, and adjust the beam parameters if necessary.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

Scalable Data Management, Analysis, and Visualization

This report is the entire final report for the SciDAC project authored by the whole team. OSU is part of the contributors to the report. This report is organized into sections and subsections, each covering an area of development and deployment of technologies applied to scientific applications of interest to the Department of Energy. Each sub-section includes: 1) a summary description of the research, development, and deployment carried out, the results and the extent to which the stated project objectives were met; 2) significant results, including major findings, developments, or conclusions; 3) products, such as publications and presentations, software developed, project website(s), technologies or techniques, inventions, awards, etc., and 4) conclusions of the projects and future directions for research, development, and deployment in this technology area.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Securing Your ICS Software with the AttackSurface Host Analyzer (AHA)

Implementing a secure development lifecycle (SDL) presents increasing challenges to software developers as they must ensure software correctly integrates both underlying operating system security features while also managing dependencies on third-party libraries or executables. There are a growing number of security functions that require a close integration between the OS security features and software builds to ensure strong protection. Furthermore, as software platforms grow in complexity, they present many opportunities for misconfigurations and inadequate defenses. This challenge is especially prevalent for industrial control systems (ICS), which oten depend on both legacy sotware platforms, or out of date operating systems. This paper presents the AttackSurface Host Analyzer (AHA) tool, which is used to assess the security of a software platform through its integration with a host operating system. The tool collects data from the various platforms running on an OS, evaluates an array of security properties, and then introduces metrics and visualizations to provide feedback on the system's attack surface based on the external interconnections and the completeness of the available security protections. The paper then explores the attack surface of a variety of industry-standard ICS platforms to provide insight into the current degree of protection enabled by them.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

P-MartCancer–Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets

P-MartCancer is a new interactive web-based software environment that enables biomedical and biological scientists to perform in-depth analyses of global proteomics data without requiring direct interaction with the data or with statistical software. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access to multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium (CPTAC) at the peptide, gene and protein levels. P-MartCancer is deployed using Azure technologies (http://pmart.labworks.org/cptac.html), the web-service is alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/) and many statistical functions can be utilized directly from an R package available on GitHub (https://github.com/pmartR).

Webb-Robertson, Bobbie-Jo M.↗
DOE OSTI2025

ViBRANT Applied as a Closed Loop Flux and Thermal Surrogate

Surrogate testing platforms provide a means to develop a target aspect of a larger system. Some systems target single aspects while others are more wholistic. ViBRANT (Visual Benign Reactor as Analog for Nuclear Testing) aims to be a wholistic system by representing the primary reactor behaviors through an accessible LED driven reactor core, photodiodes, thermocouples, and high-performance software interfaces being developed to the standards required for actual microreactor deployment such as MARVEL. With the ability to drive control drums enabled with full reactor capability (e.g. speed/angle/torque capability/limits for operation and clutch/spring scram capability), drive ViBRANT’s high fidelity 36 pin hexagon core to represent phenomena via LEDs, and capture the analog response of distributed photodiodes/thermocouples, this paper will show the system’s ability to operate in a closed-loop fashion and do well at matching reactor power/temperature distribution in an accessible reactor surrogate environment.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Visualizing Comparisons of Bill of Materials

Protecting critical infrastructure from cyber attacks, natural disasters, and other disruptions is a priority of the U.S. Government. Critical infrastructure includes providing electricity to homes and businesses, supplying natural gas for heating, and producing renewable energy sources. A loss of these services, as seen in the Solarwinds supply chain attack in 2020 , Texas snowstorm of 2021, the Colonial Pipeline cyber incident of 2021, and the Washington power substation attacks in 2022 result in high costs to consumers, disruption of everyday life, and even death. To protect the infrastructure, we first have to know what equipment we are protecting. The complexity of distributed manufacturing and development coupled with the increasing prevalence of cyber and supply chain attacks necessitates a greater understanding of the hardware and software components that comprise equipment in critical infrastructure. When a vulnerability in a single software library can have disastrous consequences, it is vital to understand critical equipment and systems at a granular level. This need has led to increased energy around the development and incorporation of bill-of-materials (BOM) into existing asset management practices to aid in mitigating, and responding to future attacks \cite{noauthor_software_nodate}. While much of the current research is devoted to creating BOMs, it is equally important to develop methodologies for leveraging BOMs to answer questions, such as: How has my software changed? Are two pieces of equipment equivalent? Does this piece of equipment that just arrived match my historical information? In this work, we demonstrate how BOMs can be represented by graph structures. We then describe how these structures can be fed into a graph comparison algorithm to produce a novel interactive visualization that allows us to not only identify differences in BOMs, but show exactly where they are in the product.

Jones, Rebecca D.↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
DOE OSTI2017

Fifteen years of the Protein Crystallography Station: The coming of age of macromolecular neutron crystallography

The Protein Crystallography Station (PCS), located at the Los Alamos Neutron Scattering Center (LANSCE), was the first macromolecular crystallography beamline to be built at a spallation neutron source. Following testing and commissioning, the PCS user program was funded by the Biology and Environmental Research program of the Department of Energy Office of Science (DOE-OBER) for 13 years (2002–2014). The PCS remained the only dedicated macromolecular neutron crystallography station in North America until the construction and commissioning of the MaNDi and IMAGINE instruments at Oak Ridge National Laboratory, which started in 2012. The instrument produced a number of research and technical outcomes that have contributed to the field, clearly demonstrating the power of neutron crystallography in helping scientists to understand enzyme reaction mechanisms, hydrogen bonding and visualization of H-atom positions, which are critical to nearly all chemical reactions. During this period, neutron crystallography became a technique that increasingly gained traction, and became more integrated into macromolecular crystallography through software developments led by investigators at the PCS. As a result, this review highlights the contributions of the PCS to macromolecular neutron crystallography, and gives an overview of the history of neutron crystallography and the development of macromolecular neutron crystallography from the 1960s to the 1990s and onwards through the 2000s.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Galen View

This is software lets one explore the data released as part of the COVID-19 Open Research Dataset Challenge. It downloads and analyzes the natural language text of the data set and then creates a 2D visualization that can be used to explore it. SAND2020-12185 M 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.

Bauer, Travis↗
DOE OSTI2022

MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]

Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.

Eseye, Abinet Tesfaye↗
DOE OSTI2019

Scalable Reasoning System (SRS)

SRS is a web-based and mobile toolkit for information visualization and collaboration. It includes server-side components in the form of web services that provide analytical functions such as data clustering and temporal analysis. The SRS client is accessed via a web browser and uses asynchronous javascript and XML (AJAX) to interact with and visualize the results of these web services. Users of SRS can query data sources that are connected to the SRS backend, and query results are presented in the form of coordinated visual displays in a web browser that depict temporal, topical, and spatial relationships in the results. SRS also includes an early stage graphical reasoning diagram interface that helps analysts express and test hypotheses. This software was developed with funding from the Science and Technology Directorate of the U.S. Department of Homeland Security.

Pike, William↗