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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 1,117 records · Page 62

IN SITU PLASMA PROCESSING OF SUPERCONDUCTING CAVITIES AT JLAB, 2023 UPDATE

Jefferson Lab has an ongoing R&D program in plasma processing which just completed a round of production processing in the CEBAF accelerator. Plasma processing is a common technique for removing hydrocarbons from surfaces, which increases the work function and reduces the secondary emission coefficient. The initial focus of the effort was processing C100 cavities by injecting RF power into the higher order mode (HOM) coupler ports. Results from processing cryomodules in the CEBAF accelerator as well as vertical test results will be present-ed. The goal of in-situ processing is to improve the operational gradients and the energy margin of the linacs. This work will describe the systems and methods used at JLAB for processing cavities using an argon-oxygen gas mixture as well as a helium-oxygen gas mixture. Before and after plasma processing results will also be presented.

Powers, Thomas↗

Surface Cloud Grid Version 2 (SFCCLDGRID2) Value-Added Product: Description of Update"

This document describes the algorithm used for the Surface Cloud Grid Value-Added Product (VAP). This VAP uses as input the 15-min. output from the Shortwave (SW) Flux Analysis VAP (see Long 2001; Long and Ackerman 2000; Long et al. 1999) from the Atmospheric Radiation Measurement (ARM) Climate Reseach Facility (ACRF) Southern Great Plains (SGP) Central Facility and extended facilities. This network of 21 sites is unevenly spaced over northern Oklahoma into southern Kansas, covering an area from 95.5° to 99.5° west longitude and 34.5° to 38.5° north latitude. For research applications such as single-column modeling, an estimate of the cloud and cloud effects distribution over this entire domain is desirable. The Surface Cloud Grid VAP applies a multi-pass weighted sum analytic approximation technique (Caracena 1987), which uses Gaussian weighting and an imposed scale length, to interpolate to a 0.25° by 0.25° lat/long grid over the SGP domain. The output, like the input, includes solar elevation angles of 10° or greater.

97 MATHEMATICS AND COMPUTING↗

Utility Sector Impacts of Reduced Electricity Demand: Updates to Methodology and Results

This report presents revisions to the methodology for estimating the utility sector impacts associated with electricity demand reductions, first published in our 2014 study. The earlier report described how to calculate utility impact factors based on data from the Energy Information Agency's Annual Energy Outlook (AEO) projections of electricity supply and demand. The 2014 methodology relied on data from the AEO Reference case, and side cases implementing demand-side policies with a substantial impact on total demand. Beginning in 2015, the AEO publication schedule was revised to limit the number of side cases published with each AEO, and no suitable demand-focused side cases have been released since 2014. Hence, this paper presents a generalization of the methodology that allows a uniform approach irrespective of the nature of the side cases published with the AEO. The impact factors we calculate represent coeffcients of variation between a unit reduction to site electricity demand and corresponding supply-side changes, including reductions to electric power generation and primary fuel consumption by fuel type, emissions of criteria pollutants (Hg, NO x and SO 2 ) and greenhouse gases (CO 2 , N 2 O and CH 4 ), and total installed capacity by plant type. The impact factors are time-dependent, and also depend on the demand sector and end use. In this report, we apply the methodology to all AEO publications from 2014-2019, and all scenarios. We quantify the variation in factors across different side cases within each AEO, and across different AEO publications, and compare this to the variation due to changes in methodology.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Organizational Conflicts of Interest Disclosure Update Statement (FY2019)

The National Technology & Engineering Solutions of Sandia, LLC (NTESS) Prime Contract department manages an organizational conflicts of interest (OCI) program that is designed to provide NTESS employees an accessible means to assist in identifying potential OCI risk and providing development support services to avoid, neutralize, or mitigate the risk. The OCI program is responsible for maintaining a regulatory infrastructure, such as corporate OCI policy and training content, to comply with NTESS's obligations set forth in prime contract clauses H-4: ORGANIZATIONAL CONFLICT OF INTEREST (OCI) — SPECIAL PROVISION and Section I Department of Energy Acquisition Regulation 952.209-72, Organizational Conflicts of Interest, Alternate I, paragraph (c)(1), Disclosure After Award. Risk identification is a key OCI program priority. Providing employees with a straight-forward, accessible and navigable mechanism to identify potential OCI risk will assist the OCI program in meeting this priority.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Safety Codes and Standards Update (Winter 2019/2020)

The goal of the DOE OE Energy Storage System Safety Roadmap is to foster confidence in the safety and reliability of energy storage systems. There are three interrelated objectives to support the realization of that goal: research, codes and standards (C/S) and communication/coordination. The objective focused on C/S is "To apply research and development to support efforts that refocused on ensuring that codes and standards are available to enable the safe implementation of energy storage systems in a comprehensive, non-discriminatory and science-based manner."

25 ENERGY STORAGE↗

Testing Update SNL (Q2 FY2020)

Two different cell constructions are currently being investigated for the LFP/Graphite system. These cells have undergone continuous cycling until the target of 1000 cycles was reached.

42 ENGINEERING↗

ECP Report: Update on Proxy Applications and Vendor Interactions

The ExaLearn miniGAN team (Ellis and Rajamanickam) have released miniGAN, a generative adversarial network(GAN) proxy application, through the ECP proxy application suite. miniGAN is the first machine learning proxy application in the suite (note: the ECP CANDLE project did previously release some benchmarks) and models the performance for training generator and discriminator networks. The GAN's generator and discriminator generate plausible 2D/3D maps and identify fake maps, respectively. miniGAN aims to be a proxy application for related applications in cosmology (CosmoFlow, ExaGAN) and wind energy (ExaWind). miniGAN has been developed so that optimized mathematical kernels (e.g., kernels provided by Kokkos Kernels) can be plugged into to the proxy application to explore potential performance improvements. miniGAN has been released as open source software and is available through the ECP proxy application website (https://proxyapps.exascaleproject.ordecp-proxy-appssuite/) and on GitHub (https://github.com/SandiaMLMiniApps/miniGAN). As part of this release, a generator is provided to generate a data set (series of images) that are inputs to the proxy application.

97 MATHEMATICS AND COMPUTING↗

Probabilistic Topography Project Update 5/20 [Slides]

Problem/Goal: Earth System Models (ESMs) do not accurately predict fire spread. There are no effects from topography/vegetation heterogeneity below the model’s scale (100-200km). Use physics based models (FIRETEC and QUICFIRE) to produce an archive of correction factors for SPITFIRE (chosen ESM). This project will: Use datasets to create PDFs of slope & aspect, vegetation distribution; Create joint distribution and sample to make new domain; Run FIRETEC & QUICFIRE on created domain, record output (area burned, intensity, etc.); and Use output to create PDF of correction factors for SPITFIRE runs.

58 GEOSCIENCES↗