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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 OSTI2024

Justice Underpinning Science and Technology Research (JUST-R) Offline Tool: A Tool for Guiding Researchers in Addressing Energy Justice Considerations in Early-Stage Research

The Justice Underpinning Science and Technology Research (JUST-R) Metrics Framework is a set of metrics for assessing the energy justice implications of technologies that are currently under research and development (R&D). The JUST-R Metrics Framework guides researchers through an analysis of the many facets of their research processes, from material inputs to knowledge sources, that may contribute to energy injustice both during the research period and when the technology is scaled. This JUST-R Offline Tool consists of an Excel file and PDF guide to aid researchers, engineers, and project managers in their application of the JUST-R Metrics Framework. This tool enables researchers to 1) evaluate the baseline energy justice implications of their research; 2) develop justice-oriented changes to the research process; and 3) track the implementation of proposed changes. The metrics included in the framework are sorted into five aspects of research: Team Dynamics, Sources & Inputs, Processes & Protocols, Waste & Hazards, and Results & Dissemination. The JUST-R Tool can be found here: https://www.nrel.gov/analysis/just-r.html.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Rules and Tools Crosswalk: A Compendium of Computational Tools to Support Geologic Carbon Storage Environmentally Protective UIC Class VI Permitting

This report identifies computational tools useful for addressing aspects of the dedicated carbon storage (Class VI) well permit application under the U. S. Environmental Protection Agency’s (EPA) Underground Injection Control (UIC) Program. The survey was conducted by researchers of the National Energy Technology Laboratory’s (NETL) Research and Innovation Center in collaboration with representatives of the U.S. EPA, Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), Pacific Northwest National Laboratory (PNNL), and the four Regional Initiatives to Accelerate Carbon Capture, Utilization, and Storage: Carbon Utilization and Storage Partnership of the Western United States (CUSP), Plains CO 2 Reduction Partnership Initiative to Accelerate Carbon Capture, Utilization, and Storage Deployment (PCOR Partnership), Midwest Regional Carbon Initiative (MRCI), and the Southeast Regional Carbon Utilization and Storage Partnership (SECARB-USA). A total of 59 tools were identified through the elicitation for this report. It is intended to serve as a reference that can be used by geologic carbon storage stakeholders to identify computational tools that may be used to develop Class VI permit applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Challenges of NDE Simulation Tool Challenges of NDE Simulation Tool

Realistic nondestructive evaluation (NDE) simulation tools enable inspection optimization and predictions of inspectability for new aerospace materials and designs. NDE simulation tools may someday aid in the design and certification of advanced aerospace components; potentially shortening the time from material development to implementation by industry and government. Furthermore, modeling and simulation are expected to play a significant future role in validating the capabilities and limitations of guided wave based structural health monitoring (SHM) systems. The current state-of-the-art in ultrasonic NDE/SHM simulation cannot rapidly simulate damage detection techniques for large scale, complex geometry composite components/vehicles with realistic damage types. This paper discusses some of the challenges of model development and validation for composites, such as the level of realism and scale of simulation needed for NASA' applications. Ongoing model development work is described along with examples of model validation studies. The paper will also discuss examples of the use of simulation tools at NASA to develop new damage characterization methods, and associated challenges of validating those methods.

Leckey, Cara A. C.↗
DOE OSTI2022

Federal Automotive Statistical Tool: FY 2022 Data Call Status & Review Tools [Slides]

This presentation presents an overview of current federal vehicle fleet current data collection efforts covering required information submissions about the motor vehicles, fueling centers, and electric vehicle supply equipment (EVSE) inventory through the Federal Automotive Statistical Tool (FAST). The presentation also provides an overview of the capabilities within FAST to assist federal agency users with reviewing and improving the quality of their fleet data submissions. This presentation is intended for delivery via WebEx at the November 9, 2022 meeting of the DOE-sponsored INTERFUEL working group. FAST is a web-based information management tool developed by INL and funded by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Computing tools for effective field theories: SMEFT-Tools 2022 Workshop Report, 14–16th September 2022, Zürich

Abstract In recent years, theoretical and phenomenological studies with effective field theories have become a trending and prolific line of research in the field of high-energy physics. In order to discuss present and future prospects concerning automated tools in this field, the SMEFT-Tools 2022 workshop was held at the University of Zurich from 14th–16th September 2022. The current document collects and summarizes the content of this workshop.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Justice 40 Tool (J40 Tool) v1.0

The Justice 40 tool provides a quantitative framework to support decision-making around equitable energy interventions at the community level. The tool calculates the optimal portfolio of policy interventions that explicitly mitigates energy insecurity of an eligible population, by reducing its disproportionate energy burden. The place-based analysis assumes a spatial census tract-level resolution and distinguishes different sociodemographic groups within each tract. Instead of focusing on a specific technology, the underlying J40 model captures the combined effect of a set of policy interventions, currently including weatherization, rooftop solar, community solar and community wind. For each tract, the model chooses the optimal (least cost) combination of interventions to address the disproportionate burden, considering the specific population demographics and techno-economic potentials of technologies. Mathematically, this problem is formalized as an optimization model and formulated as a linear program.

Heleno, Miguel↗
NASA NTRS1998

Data Mining and Optimization Tools for Developing Engine Parameters Tools

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy datasets. From the study and discussion with NASA LERC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.

Dhawan, Atam P.↗
NASA NTRS1998

Data Mining and Optimization Tools for Developing Engine Parameters Tools

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

Dhawan, Atam P.↗
DOE OSTI2023

Azure Data Tools (FKA: OEDI (Open Energy Data Initiative) Data Access Tools) [SWR-23-92]

The Open Energy Data Initiative (OEDI) provides a number of tools to enable the use of the open data published through this initiative. The source is largely written in Python, including Jupyter notebooks. The Open Energy Data Initiative (OEDI) is a partnership between the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE), Amazon, Microsoft, and Google to provide universal access to big data in the cloud. At the heart of OEDI is a centralized repository of high-value energy research datasets aggregated from DOE Program Offices, National Laboratories and other collaborators.

Jonathan, Weers↗
DOE OSTI2024

NEB-Tool (Multiple Non Energy Benefits Tool) [SWR-24-08]

A user friendly, graphical, open-source implementation of the multiple benefits framework to non-energy-benefits incorporating additional aspects to make the tool effective for use in the United States. The software may be distributed as web, desktop and/or mobile apps. Development is ongoing at the related JUSTIFI repository, found here: https://github.com/ORNL-AMO/JUSTIFI

Perr-Sauer, Jordan↗
DOE OSTI2022

Deployment of the HFIRCON transport and depletion tool for plutonium-238 production studies

Irradiation of {sup 237}Np-bearing targets in Oak Ridge National Laboratory's (ORNL) High Flux Isotope Reactor (HFIR) results in the efficient production of {sup 238}Pu, which, in the form of heat source PuO{sub 2}, is used as a reliable power source for deep-space and planetary NASA missions. A technology demonstration subproject was initiated at ORNL in 2011 to develop and implement the technology required to establish a {sup 238}Pu supply chain. A systematic progression of NpO{sub 2}/Al cermet (20 vol.% NpO{sub 2}) activities to date has successfully demonstrated target fabrication, irradiation, and chemical recovery processes. Recent program tasks have included the development of the HFIRCON transport and depletion tool for efficient reactor physics analyses and the evaluation of increased NpO{sub 2} loadings (i.e., beyond 20 vol.%) and NpN-based targets. This paper documents the deployment of the HFIRCON code to assess various Np concentrations in NpO{sub 2}- and NpN-based targets in HFIR's inner small vertical experiment facilities. Results indicate that {sup 238}Pu production and quality can be enhanced with increased Np loadings; however, target conversion rates are reduced. The results recorded in this paper, thermal and material balance evaluations, and testing requirement planning will be used to determine whether increased NpO{sub 2} loadings or NpN-based targets will be further considered. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1973

The remote sensing of aquatic macrophytes Part 1: Color-infrared aerial photography as a tool for identification and mapping of littoral vegetation. Part 2: Aerial photography as a quantitative tool for the investigation of aquatic ecosystems

Research was initiated to use aerial photography as an investigative tool in studies that are part of an intensive aquatic ecosystem research effort at Lake Wingra, Madison, Wisconsin. It is anticipated that photographic techniques would supply information about the growth and distribution of littoral macrophytes with efficiency and accuracy greater than conventional methods.

Gustafson, T. D.↗
NASA NTRS2017

The Profile Envision and Splicing Tool (PRESTO): Developing an Atmospheric Wind Analysis Tool for Space Launch Vehicles Using Python

Launch vehicle programs require vertically complete atmospheric profiles. Many systems at the ER to make the necessary measurements, but all have different EVR, vertical coverage, and temporal coverage. MSFC Natural Environments Branch developed a tool to create a vertically complete profile from multiple inputs using Python. Forward work: Finish Formal Testing Acceptance Testing, End-to-End Testing. Formal Release

Orcutt, John M.↗
NASA NTRS2017

The Profile Envision and Splice Tool (PRESTO): Developing an Atmospheric Wind Analysis Tool for Space Launch Vehicles Using Python

Tropospheric winds are an important driver of the design and operation of space launch vehicles. Multiple types of weather balloons and Doppler Radar Wind Profiler (DRWP) systems exist at NASA's Kennedy Space Center (KSC), co-located on the United States Air Force's (USAF) Eastern Range (ER) at the Cape Canaveral Air Force Station (CCAFS), that are capable of measuring atmospheric winds. Meteorological data gathered by these instruments are being used in the design of NASA's Space Launch System (SLS) and other space launch vehicles, and will be used during the day-of-launch (DOL) of SLS to aid in loads and trajectory analyses. For the purpose of SLS day-of-launch needs, the balloons have the altitude coverage needed, but take over an hour to reach the maximum altitude and can drift far from the vehicle's path. The DRWPs have the spatial and temporal resolutions needed, but do not provide complete altitude coverage. Therefore, the Natural Environments Branch (EV44) at Marshall Space Flight Center (MSFC) developed the Profile Envision and Splice Tool (PRESTO) to combine balloon profiles and profiles from multiple DRWPs, filter the spliced profile to a common wavelength, and allow the operator to generate output files as well as to visualize the inputs and the spliced profile for SLS DOL operations. PRESTO was developed in Python taking advantage of NumPy and SciPy for the splicing procedure, matplotlib for the visualization, and Tkinter for the execution of the graphical user interface (GUI). This paper describes in detail the Python coding implementation for the splicing, filtering, and visualization methodology used in PRESTO.

Orcutt, John M.↗