CY22 Second Quarter Asbestos Report for Permit SW532
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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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The U.S. Department of Energy’s Alternative Fueling Station Locator contains information on public and private non-residential alternative fueling stations in the United States and Canada and currently tracks ethanol (E85), biodiesel, compressed natural gas, electric vehicle (EV) charging, hydrogen, liquefied natural gas, and propane stations. Of these fuels, EV charging continues to experience rapidly changing technology and growing infrastructure. This report provides a snapshot of the state of EV charging infrastructure in the United States in the second calendar quarter of 2020. Using data from the Station Locator, this report breaks down the growth of public and private charging infrastructure by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with the amount projected to meet charging demand by 2030. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape for EV charging. This is the second report in a new series. The first report for the first calendar quarter of 2020 can be found in the publication databases of the Alternative Fuels Data Center and the National Renewable Energy Laboratory.
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The U.S. Department of Energy's Alternative Fueling Station Locator contains information on public and private nonresidential alternative fueling stations in the United States and Canada and currently tracks ethanol (E85), biodiesel, compressed natural gas, electric vehicle (EV) charging, hydrogen, liquefied natural gas, and propane stations. Of these fuels, EV charging continues to experience rapidly changing technology and growing infrastructure. This report provides a snapshot of the state of EV charging infrastructure in the United States in the second calendar quarter of 2022 (Q2). Using data from the Station Locator, this report breaks down the growth of public and private charging infrastructure by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with two different 2030 infrastructure requirement scenarios. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape of EV charging infrastructure. This is the tenth report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory (NREL) publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).
The U.S. Department of Energy's (DOE's) Alternative Fueling Station Locator contains information on public and private non-residential alternative fueling stations in the United States and Canada and currently tracks ethanol (E85), biodiesel, compressed natural gas, electric vehicle (EV) charging, hydrogen, liquefied natural gas, and propane stations. Of these fuels, EV charging continues to experience rapidly changing technology and growing infrastructure. This report provides a snapshot of the state of EV charging infrastructure in the United States in the second calendar quarter of 2021 (Q2). Using data from the Station Locator, this report breaks down the growth of public and private charging infrastructure by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with the target infrastructure volume for 2030. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape for EV charging. This is the sixth report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory (NREL) publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).
Highlights and significant accomplishments of Advanced Gas Reactor (AGR) fuels development activities during January, February and March 2021
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FY21 Second Quarter Volume Report
The second quarter of the project was spent carrying out numerical experiments on a variety of test matrices, using a combination of precisions, with the intent to study the numerical properties (namely, accuracy and convergence behavior) of the Conjugate Gradient (CG) method. We summarize our findings in the remainder of the document. Other activities include attending biweekly xSDK meetings. We are also currently collaborating with Steven Thomas (NREL) on the numerical stability analysis of “low-synch” Gram-Schmidt routines, for potential application within high-performance GMRES variants. This work is in progress. The subsequent quarter will be spent delving into the numerical analysis in order to provide theoretical explanation for the behavior observed in our experiments.
Calendar Year 24 Second Quarter Asbestos Report for Permit SW532
In this Technical Report, the chemical and radionuclide contaminant results from the Second Quarter Calendar Year 2021 (CY21) sample of Tank 50 salt solution are presented in tabulated form. The information from this characterization will be used by Savannah River Remediation (SRR) for the transfer of aqueous waste from Tank 50 to the Saltstone Production Facility (SPF), where the waste will be treated and disposed in the Saltstone Disposal Facility. This Technical Report compares results, where applicable, to SPF Waste Acceptance Criteria (WAC) Limits and Targets that were established at the time the Tank 50 sample was obtained. The chemical and radionuclide contaminant results from the characterization of the Second Quarter CY21 sampling of Tank 50 were requested by SRR personnel via a Task Technical Request (TTR) and details of the testing are presented in the Savannah River National Laboratory (SRNL) Task Technical and Quality Assurance Plan (TTQAP). This Technical Report is part of Deliverable 2 relating to Task 1 from the SRR request. Data pertaining to the regulatory limits for Resource Conservation and Recovery Act (RCRA) metals per Task 2 from the SRR request, will be obtained semi-annually for the 1QCY21 and 3QCY21 Tank 50 samples.
In this Technical Report, the chemical and radionuclide contaminant results from the April 2024 Semiannual sample of the Salt Waste Processing Facility (SWPF) Decontaminated Salt Solution (DSS) salt solution are presented in tabulated form. The information from this characterization will be used by Savannah River Mission Completion (SRMC) for the transfer of aqueous waste from SWPF to the Saltstone Production Facility (SPF) where the waste will be treated and disposed in the Saltstone Disposal Facility. This Technical Report compares results, where applicable, to SPF Waste Acceptance Criteria (WAC) LIMITS and TARGETS that were established at the time the SWPF DSS sample was obtained.1 The April 2024 Semiannual sample of the SWPF DSS is a composite from the six months of SWPF processing during the First Quarter Fiscal Year 2024 (1QFY2024) and the Second Quarter Fiscal Year 2024 (2QFY2024). The following facts pertaining to the WAC are drawn from the analytical results provided in this report. WAC TARGETS and LIMITS were met for all analyzed chemical and radioactive contaminants for which the detection limits are below the WAC TARGETS and LIMITS. Nitrosamines were not detected in the SWPF DSS salt solution sample above the instrument detection limits of <1 mg/L. The minimum detection limit (<3.33E-01 pCi/mL) is reported for 94 Nb as determined from the minimum detectable activity associated with the radiochemical method used for this radionuclide. The reported detection limit is above the requested SRMC target minimum detection limit concentration. However, the minimum detection limit reported for the April 2024 semiannual SWPF DSS sample for 94 Nb is lower than the estimated detection limit of 4.38E-01 pCi/mL initially established by SRNL in 2009. Thus, per guidance from SRMC, 2 SRNL continues to achieve as low as practical detection limits for this radionuclide.
In this Technical Report, the chemical and radionuclide contaminant results from the April 2025 Semiannual sample of the Salt Waste Processing Facility (SWPF) Decontaminated Salt Solution (DSS) salt solution are presented in tabulated form. The information from this characterization will be used by Savannah River Mission Completion (SRMC) for the transfer of aqueous waste from SWPF to the Saltstone Production Facility (SPF) where the waste will be treated and disposed in the Saltstone Disposal Facility. This Technical Report compares results, where applicable, to SPF Waste Acceptance Criteria (WAC) LIMITS and TARGETS that were established at the time the SWPF DSS sample was obtained. The April 2025 Semiannual sample of the SWPF DSS is a composite from the six months of SWPF processing during the First Quarter Fiscal Year 2025 (1QFY2025) and the Second Quarter Fiscal Year 2025 (2QFY2025).
This publication includes 91 composite data products (CDPs) produced for next generation hydrogen stations, with data through the second quarter of 2021.
This publication includes 54 composite data products (CDPs) produced for next generation hydrogen stations, with data through the second quarter of 2022.
The goal of this project is to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first quarter, the project focused on collecting data, establishing a simulation workflow, and engaging industry through the creation of the Industry Advisory Board (IAB). In the second quarter, the project focused on selecting fuel pathways and powertrain technologies, setting performance targets, conducting a techno-economic analyses, and developing the simulation framework that would serve as the backbone of the future toolhead. The third quarter involved developing an industry-oriented interactive dashboard powered by a five-step sequential framework, as well as holding industry advisory board meetings as per the initial technology-to-market plan. In the remaining project quarters, the NUFRIEND dashboard were fine-tuned with the help of IAB member feedback and in-depth scenario analyses were conducted to support the techno-economic analysis of energy sources. Additionally, dashboard documentation, project insights, and open-source code on GitHub were prepared and released. Throughout the project, the team completed testing and analysis of all model components, integrated all initial test scenarios, and conducted stakeholder engagement. Lower-carbon drop-in fuels can be deployed as admixtures and are considered uniform across the network at a desired penetration rate, while hydrogen and battery-electric technology deployment poses a more complex problem as they require significant investments to be made in the siting of refueling/charging facilities and the replacement of locomotive fleets. Thus, strategies for locating and sizing refueling/charging facilities on a railroad’s network to meet their energy demands were developed to inform deployment decisions. To address this challenge, the Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework presents a five-step sequential framework to select O-D paths, locate facilities, reroute flows, size facilities, and evaluate the deployment for alternative energy sources that require locomotive powertrains to be converted and new refueling infrastructure to be deployed. The NUFRIEND Framework is an industry-oriented tool for simulating the deployment of new energy technologies across the US freight rail network. The framework provides a comprehensive network-level optimization and scenario simulation tool for decarbonizing the freight rail sector, addressing the uncertainties surrounding technological developments by supporting sensitivity analyses for different operational and technological parameters through a transparent and flexible input module. It offers practical alternatives to diesel locomotives and can be applied for any railroad considering the specific network structure and freight demand, outputting evaluation metrics for the associated emissions and costs relative to diesel operations. A number of relevant simulation scenarios were run and analyzed for key insights on the value of different alternative technologies for freight rail decarbonization. The project developments and findings have been presented at numerous conferences and events.
Mesoscale convective systems (MCSs) consist of an assembly of cumulonimbus clouds on scales of 100 km or more and produce mesoscale circulations (Houze, 2004, 2018). As the largest form of deep convective storms, MCSs contribute to 30% – 70% of annual and warm season rainfall in the U.S. and in the global tropics (Houze 2018; Stevenson & Schumacher, 2014; Feng et al., 2019; Haberlie & Ashley, 2019). Since MCSs contribute importantly to mean and extreme precipitation in the U.S. and many other regions around the world, understanding how well they are simulated by E3SM may guide future development towards more skillful modeling of convective storms and associated hydrologic impacts. The FY2020 Second Quarter Performance Metric Report documented comparisons of MCSs in the central and eastern U.S. in a high-resolution simulation produced by E3SM v1 at 25 km resolution (Caldwell et al. 2019) with observations. MCSs in the simulation occur less frequently and produce less intense precipitation, resulting in large underestimation of MCS volumetric rain-rate compared to observations. The first and third quarter performance metric report indicated that these model biases in simulating MCSs can be attributed to model limitations in parameterizing convection, clouds, and other related processes, as well as model biases in simulating the MCS large-scale environment. In the current FY2020 Fourth Quarter Performance Metric Report, we evaluate MCSs simulated in E3SM with several new developments in convection parameterizations that are being developed for its next generation. The goal is to summarize what have been improved with the new developments and highlight what need more work in the future.