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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 55 records · Page 3

Resultant Cutting Trajectories on Machine Tools with Raster Tool Motion

The formation of the resultant raster trajectories in machine tools are established on the basis of Lissajous figures, taking account of additional workpiece motion for finishing purposes. Kinematic and geometric formulas are obtained for the relative tool and workpiece trajectory with strict kinematic coupling. These formulas are required in practice for abrasive lapping. They permit control of the resultant abrasive-cutting trajectory in finishing the precision planes of the workpiece.

42 ENGINEERING↗

Deep learning: Extrapolation tool for ab initio nuclear theory

Ab initio approaches in nuclear theory, such as the no-core shell model (NCSM), have been developed for approximately solving finite nuclei with realistic strong interactions. The NCSM and other approaches require an extrapolation of the results obtained in a finite basis space to the infinite basis space limit and assessment of the uncertainty of those extrapolations. Each observable requires a separate extrapolation and many observables have no proven extrapolation method. Herein, we propose a feed-forward artificial neural network (ANN) method as an extrapolation tool to obtain the ground-state energy and the ground-state point-proton root-mean-square (rms) radius along with their extrapolation uncertainties. The designed ANNs are sufficient to produce results for these two very different observables in 6 Li from the ab initio NCSM results in small basis spaces that satisfy the following theoretical physics condition: independence of basis space parameters in the limit of extremely large matrices. Comparisons of the ANN findings with other extrapolation methods are also provided.

6Li↗

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↗

Fluorescent Amplification of Next Generation Sequencing Libraries Tools (FA-NGS tools) v1

This is a software utility for calculating pooling volumes and graphing quality control data of next generation sequencing libraries amplified with fluorescent intercalating agents and monitored by real-time quantitative PCR (qPCR). The tool is used to calculate pooling volumes of individual next generation sequencing libraries based on experimentally determined fluorescence values. To do this, fluorescent values are used as a proxy for relative concentration to determine the ratio of transfer volumes. The output is a "transfer file" that specifies the transfer volume and destination well of a given library. The tool can also be used to assess the quality of individual next generation sequencing libraries by melting curve analysis. The output are small-multiples graphs of the melting curves of individual sequencing libraries according to the specified plate layout.

Garber, Megan↗

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↗

Spatial Environmental Assessment Tool (SEAT): A Modeling Tool to Evaluate Potential Environmental Risks Associated with Wave Energy Converter Deployments

Wave energy converter (WEC) arrays deployed in coastal regions may create physical disturbances, potentially resulting in environmental stresses. Presently, limited information is available on the nature of these physical disturbance or the resultant effects. A quantitative Spatial Environmental Assessment Tool (SEAT) for evaluating the potential effects of wave energy converter (WEC) arrays on nearshore hydrodynamics and sediment transport is presented for the central Oregon coast (USA) through coupled numerical model simulations of an array of WECs. Derived climatological wave conditions were used as inputs to the model to allow for the calculation of risk metrics associated with various hydrodynamic and sediment transport variables such as maximum shear stress, bottom velocity, and change in bed elevation. The risk maps provided simple, quantitative, and spatially-resolved means of evaluating physical changes in the vicinity of a hypothetical WEC array in response to varying wave conditions. The near-field risk of sediment mobility was determined to be moderate in the lee of the densely spaced array, where the potential for increased sediment deposition could result in benthic habitat alteration. Modifications to the nearshore sediment deposition and erosion patterns were observed near headlands and topographic features, which could have implications for littoral sediment transport. The results illustrate the benefits of a risk evaluation tool for facilitating coastal resource management at early market marine renewable energy sites.

Jones, Craig↗

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.↗

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.↗

The FLOod Probability Interpolation Tool (FLOPIT): A Simple Tool to Improve Spatial Flood Probability Quantification and Communication

Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate, flood-proofing a house, or managing floodplain development. Current flood probability maps typically use flood zones (for example the 1 in 100 or 1 in 500-year flood zones) to communicate flooding probabilities. However, this choice of communication format can miss important details and lead to biased risk assessments. Here we develop, test, and demonstrate the FLOod Probability Interpolation Tool (FLOPIT). FLOPIT interpolates flood probabilities between water surface elevation to produce continuous flood-probability maps. FLOPIT uses water surface elevation inundation maps for at least two return periods and creates Annual Exceedance Probability (AEP) as well as inundation maps for new return levels. Potential advantages of FLOPIT include being open-source, relatively easy to implement, capable of creating inundation maps from agencies other than FEMA, and applicable to locations where FEMA published flood inundation maps but not flood probability. Using publicly available data from the Federal Emergency Management Agency (FEMA) flood risk databases as well as state and national datasets, we produce continuous flood-probability maps at three example locations in the United States: Houston (TX), Muncy (PA), and Selinsgrove (PA). We find that the discrete flood zones generally communicate substantially lower flood probabilities than the continuous estimates.

54 ENVIRONMENTAL SCIENCES↗

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↗

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↗

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↗

Development of Fleet Energy Savings Evaluation Tools for Smart Mobility: Smart Vehicle Energy Technology (SVET) Model for Passenger Fleets and Freight Fleet Level Energy Estimation Tool (FFLEET) for Freight Fleets

As part of the U.S. Department of Energy’s (DOE) Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Initiative, the Oak Ridge National Laboratory (ORNL) led a study to develop web-based tools intended to enable vehicle fleet operators, including both passenger and freight fleets, to quantify the energy savings achievable by implementing advanced transportation technologies. By developing a profile of a fleet’s existing vehicle inventory and providing data about how and where the vehicles are driven, fuel consumption can be calculated for the entire fleet and users can perform “what if” scenarios to evaluate the energy savings that can be realized when replacing existing vehicles and implementing new technologies.

33 ADVANCED PROPULSION SYSTEMS↗