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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Grid Architecture Mapping to Understand Transformation (GAMUT): Concept Definition

The electric power system is undergoing significant transformation driven by changes in the generation mix, increasing reliance on information and communication technologies, evolving customer expectations, and a dynamic cyber-physical environment. To address these challenges, substantial investments will be made over the next decade to create a flexible, affordable, secure, reliable, and resilient electric system. In response, the U.S. Department of Energy's Office of Electricity is developing knowledge management tools aimed at systematically documenting technology pilots and demonstration projects. This initiative seeks to improve understanding of operating contexts, planning steps, and integration requirements for innovative grid technologies. The Department of Energy project leverages Grid Architecture principles to collect and organize insights into the interdependencies, requirements, and capabilities of various grid solutions. By employing a systematic approach, the project aims to perform a feasibility study for the development of a software tool that will support stakeholders, including regulators, transmission and distribution system operators, distributed energy resources aggregators, and technology providers. By offering a systematic, software-based framework to document technologies, understand their benefits and impacts, and inform deployment strategies, the proposed Grid Architecture Mapping to Understand Transformation (GAMUT) Tool is intended to reduce costs, enhance decision-making, and facilitate scaling and effective deployment of new technologies. The feasibility study will evaluate the technical and financial viability of the GAMUT Tool, identifying stakeholder needs and assessing risks and mitigation strategies. Ultimately, the GAMUT team aims to develop an initial minimal viable product, followed by staged improvements, to aid in the modernization of the electric grid, contributing to a more sustainable and resilient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

SU-C-202-03: A Tool for Automatic Calculation of Delivered Dose Variation for Off-Line Adaptive Therapy Using Cone Beam CT

Purpose: Monitoring the delivered dose is an important task for the adaptive radiotherapy (ART) and for determining time to re-plan. A software tool which enables automatic delivered dose calculation using cone-beam CT (CBCT) has been developed and tested. Methods: The tool consists of four components: a CBCT Colleting Module (CCM), a Plan Registration Moduel (PRM), a Dose Calculation Module (DCM), and an Evaluation and Action Module (EAM). The CCM is triggered periodically (e.g. every 1:00 AM) to search for newly acquired CBCTs of patients of interest and then export the DICOM files of the images and related registrations defined in ARIA followed by triggering the PRM. The PRM imports the DICOM images and registrations, links the CBCTs to the related treatment plan of the patient in the planning system (RayStation V4.5, RaySearch, Stockholm, Sweden). A pre-determined CT-to-density table is automatically generated for dose calculation. Current version of the DCM uses a rigid registration which regards the treatment isocenter of the CBCT to be the isocenter of the treatment plan. Then it starts the dose calculation automatically. The AEM evaluates the plan using pre-determined plan evaluation parameters: PTV dose-volume metrics and critical organ doses. The tool has been tested for 10 patients. Results: Automatic plans are generated and saved in the order of the treatment dates of the Adaptive Planning module of the RayStation planning system, without any manual intervention. Once the CTV dose deviates more than 3%, both email and page alerts are sent to the physician and the physicist of the patient so that one can look the case closely. Conclusion: The tool is capable to perform automatic dose tracking and to alert clinicians when an action is needed. It is clinically useful for off-line adaptive therapy to catch any gross error. Practical way of determining alarming level for OAR is under development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Center for Efficient Exascale Discretizations Software Suite

The CEED Software suite is a collection of generally applicable software tools focusing on the following computational motives: PDE discretizations on unstructured meshes, high-order finite element and spectral element methods and unstructured adaptive mesh refinement. All of this software is being developed as part of CEED, a co-design Center for Efficient Exascale Discretizations, within DOE's Exascale Computing Project (ECP) program.

Kolev, Tzanio↗
DOE OSTI2020

Neurodata Extensions Catalog (NDX Catalog) v1.0.0

The Neurodata Extensions Catalog (NDX Catalog) is a novel web archive and associated software tools that enable users to easily create, search for, test, review, and install extensions to the Neurodata Without Borders (NWB) data standard for neurophysiology. The Catalog consists of several software repositories that can be found at https://github.com/nwb-extensions.

Tritt, Andrew↗
DOE OSTI2021

Sensitivity Analysis of MFiX-PIC Parameters Using Nodeworks, PSUADE, and DAKOTA

The study presented in this report was aimed to demonstrate UQ analysis performed not only with Nodeworks, but also two other well-established UQ software tools from the U.S. DOE’s National Laboratories (PSUADE from Lawrence Livermore National Laboratory and DAKOTA from Sandia National Laboratory). It is important to emphasize that the motivation of this study was not to determine the best UQ software, but to verify if the global sensitivity analyses from the end-to-end workflow in Nodeworks are consistent with the results of other two UQ software. The components of Nodeworks from Python’s ecosystem have been tested as standalone libraries. However, an assessment study for the complete workflow targeting a specific UQ analysis has not been performed for Nodeworks. Hence, this study is expected to serve as an equivalent of solution verification for Nodeworks using other established UQ tools as reference solution. For this purpose, three distinct flow configurations (i.e., settling bed, bubbling fluidized, and circulating fluidized bed) have been used as representative multiphase flow problems of interest. The results of the systematic simulation campaigns performed in an earlier study using the particle-in-cell (PIC) approach in the Multiphase Flow with Interphase eXchanges (MFIX) suite of solvers (i.e., MFiX-PIC) was utilized. The same set of tabulated results was provided as input to the different UQ software for global sensitivity analysis. Results for the three cases indicate that based on the Sobol’ Sensitivity Indices method the order of importance ranking determined by Nodeworks for the Sobol’ Total Sensitivity Indices is consistent with PSUADE and DAKOTA in each case for the five model parameters considered. The input files for Nodeworks for the three cases are also shared through NETL’s Gitlab repository for the reader interested in reproducibility and further analysis (See Section 1.2).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

NeuroFEM

SAND2025-00525O NeuroFEM is a software tool that demonstrates a neuromorphic algorithm for solving finite element problems. It sets up a 2D finite element problem for the Poisson equation on a disk, constructs synaptic matrices, and simulates neural dynamics to solve the resulting sparse linear system. The software illustrates how the algorithm converges to the solution and plots the results, showcasing a neuromorphic counterpart to traditional methods like Conjugate Gradient or GMRES. This tool is designed to highlight the potential of neuromorphic algorithms for solving sparse linear systems, which are prevalent in various computational applications. 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.

SciDAC↗
DOE OSTI2016

Economic Analysis of Complex Nuclear Fuel Cycles with NE-COST

The purpose of this work is to present a new methodology, and associated computational tools, developed within the U.S. Department of Energy (U.S. DOE) Fuel Cycle Option Campaign to quantify the economic performance of complex nuclear fuel cycles. The levelized electricity cost at the busbar is generally chosen to quantify and compare the economic performance of different baseload generating technologies, including of nuclear: it is the cost of electricity which renders the risk-adjusted discounted net present value of the investment cash flow equal to zero. The work presented here is focused on the calculation of the levelized cost of electricity of fuel cycles at mass balance equilibrium, which is termed LCAE (Levelized Cost of Electricity at Equilibrium). To alleviate the computational issues associated with the calculation of the LCAE for complex fuel cycles, a novel approach has been developed, which has been called the “island approach” because of its logical structure: a generic complex fuel cycle is subdivided into subsets of fuel cycle facilities, called islands, each containing one and only one type of reactor or blanket and an arbitrary number of fuel cycle facilities. A nuclear economic software tool, NE-COST, written in the commercial programming software MATLAB®, has been developed to calculate the LCAE of complex fuel cycles with the “island” computational approach. NE-COST has also been developed with the capability to handle uncertainty: the input parameters (both unit costs and fuel cycle characteristics) can have uncertainty distributions associated with them, and the output can be computed in terms of probability density functions of the LCAE. In this paper NE-COST will be used to quantify, as examples, the economic performance of (1) current Light Water Reactors (LWR) once-through systems; (2) continuous plutonium recycling in Fast Reactors (FR) with driver and blanket; (3) Recycling of plutonium bred in FR into LWR. For each fuel cycle, the contributions to the total LCAE of the main cost components will be identified.

Fuel Cycles↗
DOE OSTI2015

ProDeGe: A Computational Protocol for fully Automated Decontamination of Genomic Data

The Single Cell Data Decontamination Pipeline is a fully-automated software tool which classifies unscreened contigs from single cell datasets through a combination of homology and feature-based methodologies using the organism's nucleotide sequences and known NCBI taxonomony. The software is freely available to download and install, and can be run on any system.

Andersen, Evan↗
DOE OSTI2019

Municipal Portfolio Performance and Policy Opportunities

A wide range of policy tools are in place to enhance energy efficiency in the built environment. However, the lion’s share of today’s energy savings opportunities have to do with energy consumption in existing buildings currently in operation. Many of the policy tools in play, including energy codes, have little to no effect on these existing buildings. New tools and resources are needed to bring existing buildings up to higher levels of energy performance. This project was focused on building a replicable framework, complete with open-source software tools and resources, to empower cities around the country to significantly enhance the energy performance of their own existing buildings and identify opportunities for future improvements. These issues were addressed through the evaluation of the performance of the municipal building stock and policy environments of four mid-size cities: Eugene, Oregon; Providence, Rhode Island; Grand Rapids, Michigan; and Tacoma, Washington. The project team worked closely with these cities to help city staff lead by example and create actionable, implementation-focused strategic energy plans for their own municipal building portfolios and to evaluate and improve city policies. A major focus throughout has been replicability and knowledge transfer (“teaching them to fish” rather than doing the work for the city).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Evaluation and Suitability of Using SERI QC Software for Estimating Measurement Uncertainty

SERI QC is a robust solar data quality assessment software tool that has been in continuous use for more than three decades. This report (the first of six in the Data Quality and Uncertainty Integration project) reviews and evaluates the software to determine its suitability for determining the estimated expanded measurement uncertainty of solar measurement data by including operational factors. Using redundancy incorporated in three-component (global, direct, diffuse) solar measurements, SERI QC can quantify the standard uncertainty estimates for estimating uncertainty. With minor modifications, SERI QC will provide an operational uncertainty to be used in conjunction with the National Renewable Energy Laboratory method for instrument uncertainty to provide an integrated estimate of solar measurement data sets. These modifications will capitalize on SERI QC's evaluation of data quality, including data input validation and a variety of built-in solar routines, and will further develop the utility of the software.

14 SOLAR ENERGY↗
DOE OSTI2024

CALMS: CONTEXT-AWARE LANGUAGE MODEL FOR SCIENCE

Context-Aware Language Model for Science (CALMS) is designed to assist scientists with instrument operations and complex experimentation. CALMS consists of a large-language model (LLM) augmented with context and tool use abilities. With the ability to retrieve relevant information from facility documentation, CALMS can answer simple questions on scientific capabilities and other operational procedures. With the ability to interface with software tools and experimental hardware, CALMS can operate scientific instruments in a conversational manner.

CHERUKARA, MATTHEW↗
DOE OSTI2022

Snowmass Computational Frontier: Topical Group Report on Experimental Algorithm Parallelization

The substantial increase in data volume and complexity expected from future experiments will require significant investment to prepare experimental algorithms. These algorithms include physics object reconstruction, calibrations, and processing of observational data. In addition, the changing computing architecture landscape, which will be primarily composed of heterogeneous resources, will continue to pose major challenges with regard to algorithmic migration. Portable tools need to be developed that can be shared among the frontiers (e.g., for code execution on different platforms) and opportunities, such as forums or cross-experimental working groups, need to be provided where experiences and lessons learned can be shared between experiments and frontiers. At the same time, individual experiments also need to invest considerable resources to develop algorithms unique to their needs (e.g., for facilities dedicated to the experiment), and ensure that their specific algorithms will be able to efficiently exploit external heterogeneous computing facilities. Common software tools represent a cost-effective solution, providing ready-to-use software solutions as well as a platform for R&D work. These are particularly important for small experiments which typically do not have dedicated resources needed to face the challenges imposed by the evolving computing technologies. Workforce development is a key concern across frontiers and experiments, and additional support is needed to provide career opportunities for researchers working in the field of experimental algorithm development. Finally, cross-discipline collaborations going beyond high-energy physics are a key ingredient to address the challenges ahead and more support for such collaborations needs to be created. This report targets future experiments, observations and experimental algorithm development for the next 10-15 years.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

SU-E-T-407: Evaluation of Four Commercial Dosimetry Systems for Routine Patient-Specific Tomotherapy Delivery Quality Assurance

Purpose: The purpose of this project was to evaluate the performance of four commercially available dosimetry systems for Tomotherapy delivery quality assurance (DQA). Methods: Eight clinical patient plans were chosen to represent a range of treatment sites and typical clinical plans. Four DQA plans for each patient plan were created using the TomoTherapy DQA Station (Hi-Art version 4.2.1) on CT images of the ScandiDose Delta4, IBA MatriXX Evolution, PTW Octavius 4D and Sun Nuclear ArcCHECK phantoms. Each detector was calibrated following the manufacture-provided procedure. No angular response correction was applied. All DQA plans for each detector were delivered on the Tomotherapy Hi-Art unit in a single measurement session but on different days. The measured results were loaded into the vendor supplied software for each QA system for comparison with the TPS-calculated dose. The Gamma index was calculated using 3%/3mm, 2%/2mm with 10% dose threshold of maximum TPS calculated dose. Results: Four detector systems showed comparable gamma pass rates for 3%/3m, which is recommended by AAPM TG119 and commonly used within the radiotherapy community. The averaged pass rates ± standard deviation for all DQA plans were (98.35±1.97)% for ArcCHECK, (99.9%±0.87)% for Matrix, (98.5%±5.09)% for Octavius 4D, (98.7%±1.27)% for Delata4. The rank of the gamma pass rate for individual plans was consistent between detectors. Using 2%/2mm Gamma criteria for analysis, the Gamma pass rate decreased on average by 9%, 8%, 6.6% and 5% respectively. Profile and Gamma failure map analysis using the software tools from each dosimetry system indicated that decreased passing rate is mainly due to the threading effect of Tomo plan. Conclusion: Despite the variation in detector type and resolution, phantom geometry and software implementation, the four systems demonstrated similar dosimetric performance, with the rank of the gamma pass rate consistent for the plans considered.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A Refined Method to Translate Solar Data Quality Assessment Flags to Estimated Measurement Uncertainty

Integrating solar resource uncertainties due to radiometer measurement performance and operational data quality assessment can provide improved estimates of economic bankability, system design performance, and compliance of solar energy conversion systems. Estimating radiometer measurement uncertainty is an established procedure consistent with recognized best practices and international guidelines. SERI QC is a robust solar data quality assessment software tool that has been in continuous use for more than three decades. This report, the fourth of six for the Data Quality and Uncertainty Integration Project, presents a refined algorithm description for software to translate solar resource data quality assessment results into estimated uncertainty values in a Solar Resource Operational Uncertainty Integrator (SROUI) application. This algorithm requires three-component solar irradiance measurements - global horizontal irradiance, direct normal irradiance, and diffuse horizontal irradiance - collected at 1- to 60-minute intervals, as described in the previous deliverables. The development of this report as Deliverable 6.4 was an iterative process that included reviews and feedback from the project team on initial drafts designed to refine how the new software could best support determining solar resource data uncertainty. The results of this effort will contribute to the final software system development by National Renewable Energy Laboratory staff.

14 SOLAR ENERGY↗
DOE OSTI2022

Optical emissivity dataset of multi-material heterogeneous designs generated with automated figure extraction

Optical device design is typically an iterative optimization process based on a good initial guess from prior reports. Optical properties databases are useful in this process but difficult to compile because their parsing requires finding relevant papers and manually converting graphical emissivity curves to data tables. Here, we present two contributions: one is a dataset of thermal emissivity records with design-related parameters, and the other is a software tool for automated colored curve data extraction from scientific plots. We manually collected 64 papers with 176 figures reporting thermal emissivity and automatically retrieved 153 colored curve data records. The automated figure analysis software pipeline uses Faster R-CNN for axes and legend object detection, EasyOCR for axes numbering recognition, and k-means clustering for colored curve retrieval. Additionally, we manually extracted geometry, materials, and method information from the text to add necessary metadata to each emissivity curve. Finally, we analyzed the dataset to determine the dominant classes of emissivity curves and determine the underlying design parameters leading to a type of emissivity profile.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Technical Report

MEST has developed Materials Navigator, a machine-learning software tool, to extract/combine data from disparate sources of materials information, which can be used to make suggestions for new directions of search and discovery of materials. The goal is to create a flexible software which can help materials science researchers quickly focus on a small group of promising materials and conduct fewer and less expensive experiments for maximum impact. Materials domains of interest for the Materials Navigator include solid state electrolytes for batteries, materials for fuel cells, photovoltaics, caloric cooling materials, and permanent magnets. Our solution is useful to materials researchers in academics and industry. To date, the MEST team has already developed a prototype of the Materials Navigator, which can be used to visualize a large number of materials compounds in their “descriptor space” where materials properties are encoded in machine learning based quantities. We have used Materials Navigator to make a list of potential new materials for batteries. It has also led to the experimental discovery of a new tantalum oxide superconductor.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Recent improvements to software used for optimization of SRF linacs

This work describes a software tool that allows one to vary parameters and understand the effects on the optimized costs of construction plus 10 year operations of an SRF linac, where operation costs includes the cost of the electrical utilities but not the labor or other costs. The program includes estimates for the associated cryogenic facility, and controls hardware. The software interface provides the ability to vary the cost of the different aspects of the machine as well as to change the cryomodule and cavity types. Additionally, this work will describe the recent improvements to the software that allow one to estimate the costs of energy-recovery based linacs and to enter arbitrary values of the low field Q0 and Q0 slope. The initial goal when developing the software was to convert a spreadsheet format to a graphical interface and to allow the ability to sweep different parameter sets. The tools also allow one to compare the cost of the different facets of the machine design and operations so as to better understand tradeoffs. An example of how it was used to independently investigate cost optimization tradeoffs for the LCLS-II linac will also be presented.

Powers, Tom J.↗
DOE OSTI2015

SU-E-J-92: Validating Dose Uncertainty Estimates Produced by AUTODIRECT, An Automated Program to Evaluate Deformable Image Registration Accuracy

Purpose: Deformable image registration (DIR) is a powerful tool with the potential to deformably map dose from one computed-tomography (CT) image to another. Errors in the DIR, however, will produce errors in the transferred dose distribution. We have proposed a software tool, called AUTODIRECT (automated DIR evaluation of confidence tool), which predicts voxel-specific dose mapping errors on a patient-by-patient basis. This work validates the effectiveness of AUTODIRECT to predict dose mapping errors with virtual and physical phantom datasets. Methods: AUTODIRECT requires 4 inputs: moving and fixed CT images and two noise scans of a water phantom (for noise characterization). Then, AUTODIRECT uses algorithms to generate test deformations and applies them to the moving and fixed images (along with processing) to digitally create sets of test images, with known ground-truth deformations that are similar to the actual one. The clinical DIR algorithm is then applied to these test image sets (currently 4) . From these tests, AUTODIRECT generates spatial and dose uncertainty estimates for each image voxel based on a Student’s t distribution. This work compares these uncertainty estimates to the actual errors made by the Velocity Deformable Multi Pass algorithm on 11 virtual and 1 physical phantom datasets. Results: For 11 of the 12 tests, the predicted dose error distributions from AUTODIRECT are well matched to the actual error distributions within 1–6% for 10 virtual phantoms, and 9% for the physical phantom. For one of the cases though, the predictions underestimated the errors in the tail of the distribution. Conclusion: Overall, the AUTODIRECT algorithm performed well on the 12 phantom cases for Velocity and was shown to generate accurate estimates of dose warping uncertainty. AUTODIRECT is able to automatically generate patient-, organ- , and voxel-specific DIR uncertainty estimates. This ability would be useful for patient-specific DIR quality assurance.

60 APPLIED LIFE SCIENCES↗