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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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Vendor Irradiation Capsule (VIC) update and summary. Includes what the VIC is, why it is needed, options, how data will be used, and what is concluded from using VIC. Also discusses realistic irradiation timelines, available MTRs and realisitic irradiation positions, disassembly and PIE timelines, processes and conclusions.
This presentation provides an update on the Utilization of Nuclear Energy for Hydrogen Production in the United States. This work will be presented at the 78th Meeting of the Committee for Technical and Economic Studies on Nuclear Energy Development and the Fuel Cycle (NDC), OECD Nuclear Energy Agency, in Paris, France. The presentation will be delivered on 13 September 2023.
This poster presents updated capabilities within the FOQUS Toolset, covering core features as well as project-based applications. Specifically, the poster highlights advancements in FOQUS integration with cloud-based clients, plugin support for machine learning tools and external simulations, sequential design of experiments, and advanced support for dynamic process models. The applications demonstrate the breadth of FOQUS predictive capabilities for chemical, energy and economic system analysis.
Description of NETL CO2U LCA Guidance Toolkit that includes goals, key points, overview of addenda and toolkit utilities and highlights of recent updates.
The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has implemented data standards and automated data pipelines for the following data types: 1) drilling data, 2) geospatial datasets, and 3) DAS data. An additional data pipeline is proposed for stimulation data. These data standards and pipelines are intended to improve the real-world applicability of geothermal machine learning outputs through improving the quality of data. More specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, allowing more time to be spent on actual research. By automating this process, the burden of standardization is taken off of the user, overall increasing the availability of standardized data. This paper provides an update on the GDR's transition toward data standardization through automated data pipelines and calls for feedback from the community on how we can improve this process.
The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has implemented data standards and automated data pipelines for the following data types: 1) drilling data, 2) geospatial datasets, and 3) DAS data. An additional data pipeline is proposed for stimulation data. These data standards and pipelines are intended to improve the real-world applicability of geothermal machine learning outputs through improving the quality of data. More specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, allowing more time to be spent on actual research. By automating this process, the burden of standardization is taken off of the user, overall increasing the availability of standardized data. This paper provides an update on the GDR's transition toward data standardization through automated data pipelines and calls for feedback from the community on how we can improve this process.
The High Flux Isotope Reactor (HFIR) provides one of the world’s highest steady-state neutron fluxes in the world for neutron scattering experiments focused on impactful scientific discovery, as well as materials irradiation studies and production of medical, industrial, and research isotopes. Efforts are ongoing to convert HFIR from high-enriched uranium (HEU) to low-enriched uranium (LEU) fuel while maintaining or enhancing current performance and safety margin, thus sustaining HFIR’s mission portfolio and reactor-based neutron science leadership. This paper presents a status update on the HFIR fuel conversion efforts.
The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has implemented or is currently implementing data standards and automated data pipelines for the following geothermal data types: 1) drilling data, 2) geospatial datasets, and 3) Distributed Acoustic Sensing (DAS) data. These data standards and pipelines are intended to improve the real-world applicability of geothermal machine learning outputs through improving the quality of data. More specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, allowing more time to be spent on actual research. By automating this process, the burden of standardization is taken off of the user, overall increasing the availability of standardized data. This paper provides an update on the GDR's transition toward data standardization through automated data pipelines and calls for feedback from the community on how the GDR team can improve this process.
A recent Special Issue of the Energies Journal on Deep Borehole Disposal of Nuclear Waste has delivered a timely update on the science and technology of borehole disposal and the types of radioactive wastes it could potentially accommodate. The Special Issue papers discuss (i) circumstances under which a national waste management programme might wish to consider deep borehole disposal [1], (ii) a status report of deep borehole disposal options in Germany [2], (iii) the use of deep horizontal drill-holes in sedimentary, metamorphic or igneous rocks for disposal of spent nuclear fuel and high-level radioactive waste [3], (iv) the analysis of corrosion performance of engineered barrier systems [4], (v) a review of the potential cementing systems suitable for deep borehole disposal [5], (vi) the thermal evolution around heat-generating waste for a wide range of material properties and disposal configurations [6], (vii) a geochemical analysis of deep brines focussed on fluid-rock interactions [7], (viii) post-closure performance assessment calculations for deep borehole disposal of Cs/Sr capsules [8], and (ix) an example safety case for deep borehole disposal of nuclear wastes [9]. This paper provides an overview of the main findings from these publications and highlights some of the technological and scientific challenges that need to be overcome when developing a deep borehole disposal concept. (authors)
The New York State Energy Research and Development Authority (NYSERDA) is the owner of the Western New York Nuclear Service Center (WNYNSC), a 1,351-ha site located approximately 48 km south of Buffalo, New York. In 1962, Nuclear Fuel Services, Inc. (NFS) entered into agreements with the Atomic Energy Commission and New York State to construct the first commercial reprocessing plant of nuclear fuel in the United States at the WNYNSC. NFS built and operated the spent fuel reprocessing plant and waste disposal facilities, processing 640 Mg (640 metric tons) of spent nuclear fuel from 1966 to 1972 under an Atomic Energy Commission license. Nuclear fuel reprocessing operations halted in 1972 and never restarted, leaving behind radioactive and chemical wastes. The U.S. Department of Energy (DOE) was required to complete certain waste management activities under the West Valley Demonstration Project (WVDP) Act of 1980 including decommissioning of WVDP facilities. As collaborating agencies, NYSERDA and the DOE are tasked with making decisions about decommissioning and risk reduction for the West Valley Site. Neptune and Company, Inc. (Neptune) was contracted to develop a probabilistic performance assessment (PPA) model to assist the agencies in their decision making process for decommissioning the WVDP and WNYNSC. One important tool that is needed in order to inform the decision-making process is a science-based model of the West Valley Site that evaluates potential future consequences for human health and the environment. This forms the core of the spatial domain of the West Valley PPA Model. The PPA Model, developed using the GoldSim system modeling software, is a tool intended to provide support for decision making that evaluates uncertainty, in a manner that is transparent, defensible, and robust. The PPA Model includes contaminant transport and health effects components, and is organized around geographically-grouped contaminated facilities. These include the waste disposal areas licensed by the U.S. Nuclear Regulatory Commission and the State of New York, a waste tank farm for storage of high level radioactive waste resulting from reprocessing operations, and several areas contaminated with radioactive and chemical constituents. The PPA Model evaluates contaminant transport from these sources to points of exposure across the site and into receiving surface waters and sediments. Hypothetical people and wildlife could be exposed to contamination at these locations, and the effects of these exposures are evaluated. Contaminant transport processes to be evaluated in the PPA Model include groundwater and surface water transport, contaminant translocation by plants and animals, diffusion, and erosion. The evaluation of exposures to people in this preliminary model is limited to a resident farmer scenario, and ecological assessment is performed at the level of a screening analysis. The results of these preliminary evaluations inform future model developments. PPA Model results are subjected to sensitivity analysis in order to determine those pathways and parameters that are most significant in influencing the results. This information allows analysts and decision makers to focus on those aspects of Site behavior and processes. With this information, the decision makers can drive informed, defensible decisions regarding decommissioning of the Site. This paper includes an update of the information presented at WM2019 [1]. (authors)
Update given to Westinghouse on Sockeye progress for May-August.
PV Life Cycle Assessment (LCA) is a structured, comprehensive method of quantifying and assessing material and energy flows and their associated emissions from manufacturing, transport, installation, use and end of life. This is the second version of this Fact Sheet, published in 2022 based on the 2021 update of the LCA database.
Update on R&D progress DOE for High Temperature Materials presented for GIF VHTR Materials PMB Meeting Manchester for DOE.
Type 304H and 316H stainless steels are codified in the ASME Boiler and Pressure Vessel Code for Section III, Division 5, Class A construction for up to 1500F (816C) and 300,000 hours. Extension of the design lifetimes to 500,000 hours has been undertaken by various research projects and by the ASME Section III, Division 5 Code Committees. Due to a long-standing issue related to non-classical creep behavior on the use of the time to the onset of tertiary creep as one of the time-dependent allowable stress criteria, little progress was made in the extension of the time-dependent allowable stresses for Type 304H and 316H stainless steels. A recent effort by Dabrow and Nestell (Impact of Tertiary Creep on Time Dependent Allowable Stresses for Type 304H and 316H Stainless Steels, Report 0300-0003-RPT-001, MPR Associates, Alexandria, VA, 2020) has provided a rational method for the treatment of the highly variable data for the time to onset of tertiary creep. In this paper, the background formulas for determining the time-dependent allowable stress values of Type 304H and 316H stainless steels, as assembled from relevant project work, are presented. These updates and extensions are being recommended to the ASME Code committees for approval, and are subject to change upon feedback from ASME Section III Code committees.
Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation and storage technologies: land-based wind, offshore wind, distributed wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, commercial battery storage, residential battery storage, pumped storage hydropower, nuclear, coal, and natural gas. EIA data for conventional biopower are included for reference. This webinar presentation introduces the 2024 update to the ATB Electricity data and documentation.
Overview of current ART-GCR Data, including fuel fabrication, irradiation monitoring, fuel and graphite, post-irradiation examination, graphite characterization, high temperature metals mechanical tests, methods validation data (including: HTTR, NSTF, and HTTF), addition of AGR fuel data, other GCR and related data, updated high temperature metals, ongoing and upcoming work, users guide, and the link to those interested in access to NDMAS.
Fuel performance modeling status update and potential model improvements overview of TRISO fuel performance modeling codes PARFUME/BISON, AGR experiment support, potential modeling improvements, BISON smeared cracking model, BISON fission product source term, and AGR-3/4 reirradiation heating test.
This presentation discusses recent and future Home Energy Professional credential and resource updates at the National Renewable Energy Laboratory in support to the U.S Department of Energy's Weatherization Assistance Program (WAP). It will provide an in-depth overview of planned improvements to the EA and QCI certification schemes.