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In response to invitation to participate in the Valahia, Romania 2023 Full Field Exercise in October, 2023, host country is requesting exercise objectives and resource needs from the US Aerial Measuring System participants. This document is to illustrate to the IAEA 3rd Consultancy Workshop meeting on Marc 6-7, 2023 (virtually) what will be expected from AMS at the exercise.
Presentation for joint US-UK meeting to discuss future research for single-cycle used nuclear reprocessing flowsheets.
The National Renewable Energy Laboratory (NREL) is a Department of Energy (DOE) national laboratory focused on renewable energy and energy efficiency. NREL has evaluated alternative fuel and advanced propulsion transit buses for DOE and the U.S. Department of Transportation's Federal Transit Administration (FTA). These evaluations are focused on determining the status of fuel cell systems and the corresponding infrastructure in transit applications to help DOE and FTA assess the progress toward technology readiness. For the last 19 years NREL has evaluated FCEBs in service around the United States and in Canada. The results of these evaluations have been published in numerous reports that compare FCEB performance to conventional technology as well as document the implementation experience and lessons learned by the transit agencies and their demonstration teams. Currently, 70 fuel cell buses are in active service in the US and 66 FCEBs are in development. NREL is evaluating a subset of the active FCEBs that includes three transit agencies demonstrating 25 fuel cell electric buses in California. One bus has exceeded 35,000 hours in service and 12 have exceeded 25,000 hours. Fuel economy for the current generation of FCEBs has improved 35% over the previous generation and is double that of conventional buses. Maintenance cost for FCEBs is equivalent to diesel and BEBs. The most up-to-date performance results will be presented, including fuel economy, availability, reliability, and operational costs.
Presentation of TRISO Fuel Development and Qualification in the US. Including Status of HTGR and TRISO Technology Circa 2000, Advanced Gas Reactor focus on licensing and domestic TRISO fuel fabrication capabilities. Irradiation experiments discussed include AGR-1, AGR-2, AGR-5/6/7, and AGR-3/4. Results, of tests and Kernel and coating behaviors during irradiation, Fission product release from UCO Fuel Compacts, study of failed particles, safety and accident performance summaries, and Parfume modeling and capabilities.
The United States generates the most plastic waste of any country. Along with that GHG emissions from the global plastic economy are expected to increase to 15% of the global carbon budget by 2050. It is imperative that plastic recycling is made a reality to reduce both plastic pollution in the environment and GHG emissions. A portfolio of end-of-life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different utility and lifetime. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. The novel analysis framework, Plastic Parallel Pathways Platform (4P) has been equipped with consequential life cycle assessment, techno-economic analysis, and a plastic circularity indicator to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) down-cycling to lower-quality resin, closed-loop recycling to food-grade PET bottles, up-cycling to fiber-reinforced plastic (FRP), and conversion to non-plastic products (electricity, oil) on a United States economy-wide basis. Integrating system dynamics into this robust plastics model that already incorporates techno-economics, circularity, and environmental impacts will enable identification of key bottlenecks between manufacturers, waste sorters, and reclaimers that currently prevent rapid decarbonization of the plastics economy. System dynamics (SD) explore the evolution of activities and technologies based on changed macro parameters such as plastic demand and supply, market shifts, and cross-sectoral interactions. This project particularly aims to explore the interplay between, waste collection, plastic waste sorting, recycling, and manufacturing, as well as the effect of plastic bale quality and plastic reuse initiatives on the surrounding process stages. This functionality will facilitate combinatory analysis in which a portfolio of end-of-life pathways are assessed simultaneously, with the exact makeup of that portfolio affected by parameters such as technology scales, resource constraints, and waste mitigation efforts. Integrating SD with the 4P framework enables analyzing the effect of increased revenue and reinvestment into improving process efficiencies, sorting and collection quantities. Through that, market effects of increased recycled resin availability can be studied for the plastics systems model for the US. The results will help identify technical or economic bottlenecks that currently limit efforts to decarbonize the U.S. plastics economy.
This panel focused on the technical, institutional and broader political issues associated with advancing a US HLW Repository program including programmatic, regulatory, legislative and funding challenges. Panelist with presentations: WM 2020 HLW Repository Status and Next Steps (Leo Blundo)
This panel focused on the interaction and collaboration between US Department of Energy's Office of Environmental Management (DOE EM) and National Nuclear Security Administration (NNSA) offices and sites. Panelists with presentations: NNSA and DOE EM Collaboration on Facility Disposition (Deborah Couchman-Griswold); DOE EM and NNSA D and D Collaboration at the Y-12 National Security Complex (Diane McDaniel); Working Together to Achieve Environmental Cleanup Success in Oak Ridge (Laura Wilkerson, James Daffron); DOE-EM - NNSA (Rick Demmer)
ASME Section III, Division 5 Introduction High Temperature Alloys, Weld Materials and Bolting Design Parameters Required for Design Evaluations Data Requirements for New Materials US DOE High Temperature Materials R&D Program
Jezebel (operated from 1954-1977) has been the primary experiment for fast 239 Pu nuclear data validation for the last 70 years. Validation has included not only k eff , but also spectral indicies, Rossi-α, reactivity coefficients, and neutron leakage spectra. While this has been incredibly valuable to the community, there are three major issues. The first issue is that documentation on many of these experiments were lacking, leading to large uncertainties or (even worse) incorrect assumptions. The second issue is that while there have been many advances in research, there is no way to test those new advances today. The last issue is that since the assembly only operated for 23 years (and at time when 30 other critical assemblies were operating at the same facility and nuclear weapons testing was occurring), there were limited opportunities to observe how any system parameters changed as a function of time. Note that this work is not suggesting that a "Jezebel re placement" used for a limited experiment campaign would have great value. A new enduring (100 year target) plutonium (Pu) assembly with simple geometry and low uncertainties, however, would be extremely valuable. Such a capability would have a transformative impact on many research areas including nuclear data validation, analytical methods validation, dosimetry, reactor kinetics, and materials. The need for a new plutonium assembly is not new: it has been in the DOE Nuclear Criticality Safety Program (NCSP) Mission and Vision for over 10 years and was also the top priority established at the 2022 National Criticality Experiments Research Center (NCERC) Futures meeting. This work will discuss how such a new capability would help ensure that the US retains international leadership in plutonium research. Last, a brief overview of Lilith, a project aimed to design a new enduring plutonium assembly for operation at the NCERC will be given.
A just energy transition is an imperative of the Biden-Harris Administration, emphasizing the equitable distribution of benefits through energy-efficient and decarbonizing household technologies. Understanding the factors that increase a household's willingness to adopt these technologies helps policymakers implement more targeted and effective approaches. Our research addresses this by blending 550,000 housing stock types and energy simulation data with a nationally representative survey on residential technology adoption and decision-making (n=10,000). We identify energy equity gaps across tenure and income, highlighting disparities in energy burdens and insecurity. Findings show that households with prior modification experience are more willing to renovate, suggesting that small-scale retrofit programs could foster greater willingness. Energy secure but burdened homeowners are least willing to modify, highlighting the need to consider energy bill perceptions in policy design. Nearly half of US households that are energy burdened also face energy insecurity, with a significant gap in assistance for low-income households. We emphasize the need to understand household perceptions to improve policy. This research underscores the importance of understanding household behaviors to improve policy effectiveness, offering actionable insights for policymakers to promote equitable housing upgrades and advance a decarbonized future.
The adoption of new technology for electric vehicles (EV) and mobility applications can bring underappreciated vulnerabilities to the power grid. One area of potential fraud and adversarial influence is through the business ecosystem of startups that own and deploy EV technology. Yet, there are no models or analyses that map the network of organizations and people that have direct and indirect influence over technologies currently deployed in the grid. To fill this gap, we develop a multilayer network model to measure direct and indirect influence on EV charging stations. First, we create and adversarial socio-technical network (ASTN) model via a data fusion pipeline for different US regions of interest (ROI). Then, we develop an integrated ASTN for Chicago, Los Angeles, New York, and Philadelphia. We rank EV charging companies direct influence within each geographic region as well as indirect influence via social network analysis. While some companies have strong direct and indirect influence (i.e., ChargePoint) others show a mismatch between their influence over charging stations and their position within the social network. For example, Tesla has strong direct influence on stations and weak indirect influence over competitors. In contrast, 7Charge has weak direct influence over stations, but strong indirect influence over competitors.
On July 4, 2012, scientists at CERN announced the discovery of an essential part of the Standard Model of particle physics: the Higgs boson. The search for the Higgs at experiments at the Large Hadron Collider was an international effort involving thousands of people, with physicists and engineers from US institutions playing a significant role throughout.
Currently, there is no U.S. Environmental Protection Agency (EPA) guidance on correlating soil or groundwater levels of radon with indoor radon concentrations at Superfund sites. EPA is developing the Radon Vapor Intrusion Level Calculator (RVISL) Calculator which is an online tool. The RVISL calculator: (1) lists three radon isotopes (Rn-219, Rn-220 and Rn-222) known to pose a potential cancer risk through the inhalation pathway; (2) provides generally recommended risk and Applicable or Relevant and Appropriate Requirements (ARAR) based preliminary remediation goals (PRG) for groundwater, soil gas (exterior to buildings and sub-slab) and indoor air for default target risk and ARAR based levels and exposure scenarios; and (3) allows calculation of site-specific PRGs based on user-defined target risk and ARAR based levels and exposure scenarios. EPA developed the RVISL calculator to help risk assessors, remedial project managers, and others involved with risk assessment and decision making at radioactively contaminated sites. (authors)
The U.S. Environmental Protection Agency (EPA) Superfund remedial program is finishing up a significant number of revisions to its guidance for the risk assessment process at radioactively contaminated Superfund sites. The six Preliminary Remediation Goal (PRG) and Dose Compliance Concentration (DCC) internet-based calculators for radiation risk and dose assessment at Superfund sites are being reformatted to match the chemical calculators and improve the user experience, revised to add a new peak risk and dose output option, and to add some adjustment options for external exposure. A new Radon Vapor Intrusion Screening Level (RVISL) calculator is expected to be finished in 2020, will be similar to the Vapor Intrusion Screening Level (VISL) for chemical calculator that was finished in 2018. (authors)
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Crop planting dates are a dynamic feature of agricultural systems that respond to short- and long-term climate signals, crop and cultivar selection, and technology changes. Planting date records are essential for yield gap analyses, accurate crop modeling, and tracking farmer adaptations to weather and climate change. Although planting dates have high variation at local scales due to heterogeneity in farm resources and decision-making, available long-term data on planting dates is largely restricted to aggregated regional statistics or, at best, satellite-derived datasets with limited spatiotemporal extent and at resolutions unable to distinguish individual fields (> 250 m). Here, we generated retrospective annual field-scale (30 m) planting date maps for both maize and soybeans spanning 2000-2020 across a 12 state region in the United States Corn Belt based on Landsat satellite data and a large ground sample of over 28,000 maize and soybean fields. Using training data from 2015-2020 for model selection, we found that planting date predictions improved with harmonic regression of Landsat data and additional annual weather covariates. The preferred random forests model approximately doubled performance compared to a null model based on state median planting dates, capturing 47% of field-level variation for maize (mean absolute error, MAE = 7.4 days) and 44% for soybeans (MAE = 7.5 days) against held-out ground truth test data for 2008-2014. We also evaluated the full 2000-2020 dataset with state agricultural statistics, finding strong agreement with median planting dates for maize (R 2 = 0.76, MAE = 4.4 days) and slightly lower agreement for soybeans (R 2 = 0.65, MAE = 5.4 days) when aggregated to the state level. We then used this new dataset to analyze environmental determinants of planting dates at a finer-scale than previously possible, controlling for unobserved variation at the sub-state district level. We found that during 2000-2020, each standard deviation increase in rainfall delayed planting by ~ 2.5 days, and fields with higher soil productivity ratings tended to be planted earlier. We did not find meaningful trends over the last two decades in planting dates for maize or soybeans, in contrast to trends towards earlier planting dates late last century and predicted for this period in climate adaptation studies. We hypothesize increases in early season rainfall may have inhibited these shifts towards earlier planting. Remotely sensed planting dates will be a useful tool for yield gap analyses, crop simulation modeling, and ongoing assessment of climate adaptation.
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