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Raw ADCP (Acoustic Doppler Current Profiler) datasets from acoustic interference surveys with a TRDI Workhorse 300, a Nortek Signature500 and two Signature1000 instruments from August 2020. One Signature 1000 ADCP was deployed for 13 days on a bottom lander in Sequim Bay Inlet, WA. Data from the other three instruments were taken from a survey vessel running transects above the deployed lander.
Monitoring marine contamination by floating litter can be particularly challenging since debris are continuously moving over a large spatial extent pushed by currents, waves, and winds. Floating litter contamination have mostly relied on opportunistic surveys from vessels, modeling and, more recently, remote sensing with spectral analysis. This study explores how a low-cost commercial unmanned aircraft system equipped with a high-resolution RGB camera can be used as an alternative to conduct floating litter surveys in coastal waters or from vessels. The study compares different processing and analytical strategies and discusses operational constraints. Collected UAS images were analyzed using three different approaches: (i) manual counting (MC), using visual inspection and image annotation with object counts as a baseline; (ii) pixel-based detection, an automated color analysis process to assess overall contamination; and (iii) machine learning (ML), automated object detection and identification using state-of-the-art convolutional neural network (CNNs). Our findings illustrate that MC still remains the most precise method for classifying different floating objects. ML still has a heterogeneous performance in correctly identifying different classes of floating litter; however, it demonstrates promising results in detecting floating items, which can be leveraged to scale up monitoring efforts and be used in automated analysis of large sets of imagery to assess relative floating litter contamination.
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For the Hi-Lumi LHC Upgrade (HL-LHC) new high field and large-aperture quadrupole magnets for the low-beta inner triplets (Q1, Q2, Q3) are being built. These new quadrupole magnets are based on Nb3Sn superconducting technology. As part of the US-HiLumi Accelerator Upgrade Project (AUP) ten Cryostat Assemblies (LQXFA) for Q1 and Q3 replacement will be built, tested and delivered to CERN. The first of the LQXFA was assembled and tested at Fermi National Accelerator Laboratory (FNAL) during the fall of 2022 and spring 2023. We will present the integration work of the Cold Mass assembly into the Cryostat Kit provided by CERN. Each Cold Mass contains two trained MQXFA magnets of ~ 5 m length installed in a stainless-steel helium pressure vessel. The Cold Mass will be surrounded by cryostat shields, piping, and vacuum vessel. We will discuss the metrology survey results and present the LQXFA measurements prior testing at the Fermilab Magnet Test facility and lessons learned.
The U.S. Army Corps of Engineers (USACE) with its prime contractor, Aptim Federal Services, LLC (APTIM), recycled 5,260 metric tons (11.6 million pounds) of material from Sturgis Barge (Sturgis) during the Decommissioning and Dismantlement of the MH-1A nuclear power reactor. The overall objective of the project was to reduce residual radioactivity associated with MH-1A to levels that permitted release of Sturgis for dismantlement and termination of the Army Reactor Office permit. By effectively applying waste hierarchy's three Rs - reduce, reuse and recycle - the Sturgis project not only minimized the amount of waste that required disposal at landfills, but also reduced the potential for long-term environmental liability emanating from these landfills. The project team completed the physical decommissioning efforts in June 2018 in Galveston, TX. In September 2018, radiological surveys were completed to demonstrate the vessel could be released for shipbreaking. Sturgis was towed from Galveston, TX to Brownsville, TX in late September 2018. Shipbreaking, dismantlement and recycling efforts began in early October 2018 and were completed on 15 March 2019. As part of the decommissioning effort in Galveston, the team shipped 69 shipments (860 metric tons) of low-level radioactive waste and radioactive components to the Waste Control Specialist (WCS) facility in Andrews TX for disposal. Certain radioactive components had to be transferred to the Department of Energy prior to placing the materials into the Federal Waste Facility located within WCS. However, most of the radioactive waste was characterized, profiled, approved and managed under the WCS permitted radioactive waste exemption process authorized and implemented by the Texas Commission on Environmental Quality (TCEQ) and the Radioactive Materials Division. This allows LLRW and LLMW to be shipped as regulated waste and then upon receipt at WCS through satisfying the relevant waste acceptance criteria the waste is exempted and placed into the WCS RCRA permitted cell. An additional 35 shipments (544 metric ton) of contaminated hazardous waste water were transported to U.S. Ecology in Robstown, TX for treatment/disposal. An additional 36 shipments (500 metric tons) of non-hazardous wastewater was sent to Republic Waste Services' facility in Fresno, TX. The disposal of these materials required close coordination with State of Texas regulators. During decommissioning, the project team recycled approximately 270 metric tons (600,000 pounds) of lead and steel. As part of the dismantlement in Brownsville, TX the team recycled approximately 5,000 metric tons (11 million pounds) of ferrous and non-ferrous material, limiting our disposal requirements to about 180 metric tons (400,000 pounds) of material (<4% from entire shipbreaking activity). Although the primary hazard being mitigated by this project was radiological, recycling was always a priority for the project. The team strived to achieve sustainability goals as we implemented this one of a kind project. Scrap metal recycling has a large positive impact on the environment and can also favorably impact project disposal costs. Steel is among the most recycled material in the world. Nearly 40% of the world's steel production is made from scrap. Recycling steel also requires 75% less energy than producing it from raw materials. By using recycled steel rather than virgin materials, 2.33 kg of carbon emissions are eliminated per kg of steel [1]. The project recycled more than 4,500 metric tons (10 million pounds) of steel, which eliminated about 10,400 metric tons (23 million pounds) of CO{sub 2}. By implementing a recycling initiative for the Sturgis project, the team was able to realize cost avoidance for disposal of scrap, cost savings from the metals recycled, plus the project provided benefits to the environment through our recycling efforts. Once the dismantlement was complete, the team prepared a detailed decommissioning closure report, which allowed for the termination of the Army Reactor Decommissioning Permit. While it not only reduced any potential long-term environmental liability, this project to decommission and dismantle a floating nuclear power plant is truly unprecedented - it is a prime example of the USACE mission which is: 'Engineering solutions for the Nation's toughest challenges'. This unique, one of a kind, historical power plant was never designed to be taken apart, and the available information about its construction was lacking in many details. The hazards that required mitigation dictated a painstaking and deliberate process in order to avoid any release to the environment and the community, and to protect the health and safety of the workers involved while keeping the waste hierarchy's three R's - reduce, reuse and recycle at the forefront. (authors)
Marine Spatial Planning (MSP) provides a process that uses spatial data and models to evaluate environmental, social, economic, cultural, and management trade-offs when siting (i.e., strategically locating) ocean industries. Aquaculture is the fastest-growing food sector in the world. The United States (U.S.) has substantial opportunity for offshore aquaculture development given the size of its exclusive economic zone, habitat diversity, and variety of candidate species for cultivation. However, promising aquaculture areas overlap many protected species habitats. Aquaculture siting surveys, construction, operations, and decommissioning can alter protected species habitat and behavior. Additionally, aquaculture-associated vessel activity, underwater noise, and physical interactions between protected species and farms can increase the risk of injury and mortality. In 2020, the U.S. Gulf of Mexico was identified as one of the first regions to be evaluated for offshore aquaculture opportunities as directed by a Presidential Executive Order. We developed a transparent and repeatable method to identify aquaculture opportunity areas (AOAs) with the least conflict with protected species. First, we developed a generalized scoring approach for protected species that captures their vulnerability to adverse effects from anthropogenic activities using conservation status and demographic information. Next, we applied this approach to data layers for eight species listed under the Endangered Species Act, including five species of sea turtles, Rice’s whale, smalltooth sawfish, and giant manta ray. Next, we evaluated four methods for mathematically combining scores (i.e., Arithmetic mean, Geometric mean, Product, Lowest Scoring layer) to generate a combined protected species data layer. The Product approach provided the most logical ordering of, and the greatest contrast in, site suitability scores. Finally, we integrated the combined protected species data layer into a multi-criteria decision-making modeling framework for MSP. This process identified AOAs with reduced potential for protected species conflict. These modeling methods are transferable to other regions, to other sensitive or protected species, and for spatial planning for other ocean-uses.
Tritium collection efficiency varies as a function of smear media. The use of porous smear materials leads to an increase in the measured tritium activity as a function of time when the measurement is performed with liquid scintillation counters. Operational inclusion of the efficiency differences and the time dependence of the tritium smear activity is necessary to preclude inadvertently releasing materials or areas. Thomas Jefferson National Laboratory Radiological Control Department identified a contaminated stainless steel containment vessel that previously housed a target containing more than 37 TBq of tritium. The item was systematically sectioned and surveyed to compare three smear types: water-wetted cotton swabs, water-wetted paper smears, and ethanol-wetted Styrofoam wipes (NUC-Wipes™). The total activity of each section was determined using repeated decontamination. The time dependence of the measured activity was also studied. The measured activity of both paper smears and cotton swabs showed significant time dependence. The cotton swabs also showed significantly reduced collection efficiency. Given the widespread use of both of these media in routine contamination surveys, site operational limits were derived using fitted curves for time dependence and average efficiency results. In conclusion, the use of these more restrictive limits allows for rapid measurement of tritium smears while ensuring regulatory compliance.
Acoustic data and metadata from Drifting Acoustic Instrumentation SYstem (DAISY) testing in Agate Pass (separating the north end of Bainbridge Island and the Kitsap Peninsula in Puget Sound), WA in April 2022. The goal was to characterize radiated noise from a cross-flow turbine deployed from a moored vessel. As discussed in the accompanying report, sound produced by the turbine was below the ambient nose floor at the surveyed ranges.
In 2018, nuclear energy generated 55% of United States’ and one third of the world’s carbon free electricity, making nuclear energy a key tool in efforts to mitigate climate change before 2050. However, the current nuclear technology, light water reactors (LWRs), is limited to 300°C, so it cannot be used to decarbonize industrial process heat which accounts for 12% of US greenhouse gas emissions. High temperature gas reactors (HTGRs) can meet the high temperature demand with carbon free nuclear heat. The estimated cost of HTGRs, such as the Next Generation Nuclear Plant (NGNP), are even higher than state-of-the-art LWRs. In this paper, we expanded our nuclear cost estimating tool to include HTGRs and find that the NGNP overnight capital costs were 32% higher than an advanced LWR per unit capacity. The higher cost will naturally result in larger risk to cost overrun as recently experienced by larger LWRs in western nations. With a design-to-build mindset to minimize cost and construction risk, we introduce the horizontal, compact HTGR (HC-HTGR). The reactor core and steam generator are mounted horizontally on rails and in-line with one another, decreasing the size of the reactor building relative to the power capacity four times when compared to traditional HTGRs. The HC-HTGR reduced overnight civil structure costs by 42%, indirect costs by 38%, and total capital costs by 20% from NGNP. We discussed the required engineering of new systems for the HC-HTGR including vessel supports, the reactor cavity cooling system, and steam generator design. Finally, we estimated the fuel and operations costs of the HC-HTGR, and a survey of low-carbon industrial process heat technology showed the HC-HTGR can deliver a highly competitive levelized cost of heat in the range of $6.13–12.48/GJ.
Several net-zero scenario evaluations predict a rapid ramp up of nuclear energy in the coming decades. If this materializes, it will most likely strain the supply chains associated with the potential advanced reactor concepts awaiting deployment. To help assess the current and potential capacities of the various advanced reactor supply chains, the Gateway for Accelerated Innovation in Nuclear (GAIN) conducted a survey of companies able to produce components for advanced reactors in the near future (namely for sodium, gas-cooled, and molten salt reactors). Using an aggressive nuclear deployment scenario, the objective was to assess the ability of the various supply chains to meet the considerable demand projections for certain key components (vessels, heat exchangers, pumps, graphite, and sensors) and identify potential challenges. While individual companies were unable to meet the most optimistic nuclear deployment rate projections, it was found that on aggregate, a United States-based supply chain projected that expansion could be ramped up to meet a larger future demand of these components. However, meeting projected demand for several more complex items (namely gas or salt heat exchangers) was found to be more challenging. Deploying new reactors at scale necessitates the production of more and more supply chain components, requiring a ramp up in production. Supply chain companies were surveyed, and respondents appeared less able to meet short term demand (next year) versus longer-term demand projections (5 and 10 years). This reflects the need to obtain orders with adequate lead times (can range from 3 to 30 months). Future demand will need to be met by expanding existing capacity. These expansions will require suppliers to raise capital or secure other types of support (federal loans or grants) to invest in facilities, equipment, and workforce. Individual suppliers indicated financial investments could be in the range of $\$ $100 million to $\$ $1 billion for their own facilities (depending on the type of facility). The biggest risk, according to respondents, related to general uncertainties surrounding the future nuclear industry and whether the potential demand projections will materialize into real demand that is actionable from a business perspective. Businesses do not seem willing to take investments risks without clear orders. If businesses are not able to invest to expand the supply, it will either delay the deployment of advanced nuclear technology, or the supply chain will be met by suppliers outside of the United States. This report only focuses on the domestic supply chain’s ability to meet the various projections stipulated here for the specific assessed components (vessels, heat exchangers, pumps, graphite, and sensors). The report does not cover all reactor designs or all components that may ultimately be needed for any one reactor design. It also does not address whether any specific aspect of the supply chain will be cost competitive in the global market, nor how potential state-backed entities could affect the expansion of a United States-based supply chain. The largest challenges in ramping up capacity among respondents appear to be workforce related. This includes workforce availability, experience, training, and turnover. In addition to facility investment, suppliers will also need to invest heavily in long-term workforce training to meet production goals. This issue is not nuclear-specific, and the expansion of any supply chain will likely face similar challenges. While suppliers evaluated expected normal business demand from other markets outside of nuclear, it is possible that other market segments could expand more than predicted and compete for the same suppliers. One potential market that may compete for the same supplier resources is the United States military, as many of these suppliers support both the commercial nuclear sector as well as the Navy with reactors and components. In summary, suppliers in the United States believe that there is a way to increase production in order to begin meeting the demand which will exist for advanced reactors—as long as appropriate investments can be made in the supply chain in an appropriate timeframe. Based on the capacity projections and lead times, investment will be needed to meet the 5-year and 10-year production targets. Therefore, if significant nuclear deployment is to occur in the 2030s, investment and ramp up of the advanced nuclear supply chain will need to begin in the near future for the United States to successfully deploy these advanced reactors with domestic supply chains.
This report surveys current creep-fatigue design and fitness-for-service assessment procedures, with a particular focus on environmental effects and creep-fatigue cracking near weldments. Included in this assessment are the American Society of Mechanical Engineers Boiler and Pressure Vessel Code Section III, Division 5, the British R5 standard, the French RCC-MRx design code, the ITER Structural Design Criteria, and the API-579/ASME FFS-1 fitness-for-service rules for petrochemical components. The focus of this review is to identify gaps in the available methods that could prevent regulators from evaluating future high temperature reactor designs. The report makes recommendations, where appropriate, on actions that could be taken to fill these gaps by either providing adequate assessment procedures for creep-fatigue damage in harsh environments or by evaluating strategies vendors could use to mitigate regulatory concerns with creep-fatigue damage in high temperature reactor components.
Mononuclear Fe ions ligated by nitrogen (FeN x ) dispersed on nitrogen-doped carbon (Fe-N-C) serve as active centers for electrocatalytic O 2 reduction and thermocatalytic aerobic oxidations. Despite their promise as replacements for precious metals in a variety of practical applications, such as fuel cells, the discovery of new Fe-N-C catalysts has relied primarily on empirical approaches. In this context, the development of quantitative structure–reactivity relationships and benchmarking of catalysts prepared by different synthetic routes and by different laboratories would be facilitated by the broader adoption of methods to quantify atomically dispersed FeN x active centers. In the present study, we develop a kinetic probe reaction method that uses the aerobic oxidation of a model hydroquinone substrate to quantify the density of FeN x centers in Fe- N-C catalysts. The kinetic method is compared with low-temperature Mössbauer spectroscopy, CO pulse chemisorption, and electrochemical reductive stripping of NO derived from NO 2 – on a suite of Fe-N-C catalysts prepared by diverse routes and featuring either the exclusive presence of Fe as FeN x sites or the coexistence of aggregated Fe species in addition to FeN x . The FeN x site densities derived from the kinetic method correlate well with those obtained from CO pulse chemisorption and Mössbauer spectroscopy. The broad survey of Fe-N-C materials also reveals the presence of outliers and challenges associated with each site quantification approach. Furthermore, the kinetic method developed here does not require pretreatments that may alter active-site distributions nor specialized equipment beyond reaction vessels and analytical instrumentation (e.g., NMR).
This is the Phase 3 Report for the ‘Deepwater Methane Hydrate Characterization and Scientific Assessment or Genesis of Methane Hydrates in the Gulf of Mexico (GOM2)’ research project (DOE Award No. DE-FE0023919). The report summarizes activities from January 16, 2018 to September 30, 2019. The project is led by the University of Texas at Austin (UT). The objective is to gain insight into the nature, formation, occurrence and physical properties of methane hydrate-bearing sediments for the purpose of methane hydrate resource appraisal through the planning and execution of drilling, coring, logging, testing and analytical activities that assess the geologic occurrence, regional context, and characteristics of marine methane hydrate deposits in the Gulf of Mexico outer continental shelf (OCS). We determined that it would not be possible to pursue the project with the International Ocean Discovery Program (IODP) and then developed a revised science and operations plan to maximize the science using a commercial vessel within the budget that is available. We improved the scientific capability of the UT pressure core center by adding the ability to X-ray pressure cores, and the ability to cut and store multiple core samples for experimental analysis. We transferred pressure cores to peer institutions, including the National Energy Technology Lab (NETL) the United States Geological Survey (USGS Woods Hole). We made advances in understanding the composition and source of gasses locked in the methane hydrate from Green Canyon 955 (GC-955). We developed approaches to determine the in-situ salinity of hydrate-bearing samples, revealing that the in situ salinity of the GC 955 reservoir is just above that of seawater. We determined that the GC-955 hydrate reservoir is composed of sandy silt with a high concentration of hydrate interbedded with clayey silt with no hydrate present. We determined that some or all of the intervals bounding the hydrate reservoir are composed of material similar to the reservoir (sandy silt with hydrate and clayey silt with no hydrate), but with a lower net to gross. We determined that the reservoir effective permeability at a hydrate saturation of ~80-90 % is ~0.1 mD (or 1.0×10-16 m2) to ~0.5 mD (or 5.0×10-16 m2) and the intrinsic permeability is ~12 mD (or 1.2×10-14 m2). The GC-955 reservoir in-situ porosity of sandy silt is 0.38 to 0.40 and is largely independent of effective stress, and that the porosity of clayey silt is 0.33 at an in situ effective stress of 3.8 MPa to ~0.37 at zero effective stress. We developed a systematic, repeatable approach to studying hydrate reservoir properties by reconstituting individual lithofacies from dissociated pressure cores. We determined index properties of GC-955 reservoir, including liquid limit and plasticity, porosity, capillary behavior, and particle size distribution. We developed a more robust pressure coring technology. We finalized and published the UT-GOM2-1 Expedition Volume and we finalized a dedicated volume on the UT-GOM2-1 expedition that will be published in the American Association of Petroleum Geologists Bulletin (AAPG) in spring 2020.
This report describes the Offshore Renewables Balance-of-system Installation Tool ("ORBIT"), a new model developed by the National Renewable Energy Laboratory (NREL) to evaluate the balance-of-system (BOS) costs associated with offshore wind projects. In the context of wind energy projects BOS costs encompass all expenses required to construct a project other than the capital expenditures (CapEx) of the turbines and towers, including the procurement costs for all other components (such as substructures, cables, and electrical infrastructure), offshore and land-based construction costs, port costs, site surveying fees, permitting fees, and leasing fees are all categorized as BOS costs. BOS costs significantly contribute to the levelized cost of energy (LCOE) for offshore wind, typically comprising over 50\% of the CapEx for a fixed-bottom offshore wind project and 60\% for a floating project. In addition, technology solutions and installation methods vary drastically between projects as they are impacted by factors such as vessel availability, geographic considerations and site geotechnical conditions. These effects require a model with appropriate fidelity to understand how these costs scale as turbine rating increases and the offshore wind supply chain, particularly offshore construction vessels, is expanded. For offshore wind, cost savings attributed to increased turbine rating are primarily realized through BOS procurement and project installation as fewer substructures and less cable are required. BOS costs represent both a modeling challenge, as well as an opportunity, for project developers to optimize solutions to reduce costs. It is critical to understand how these costs are affected by novel technologies, innovative installation processes, and operational constraints in order identify meaningful cost reductions for offshore wind energy.
Recombinant protein production (RPP) is central to biotechnology, where recombinant proteins are used as either end products or catalysts in the synthesis of chemicals, fuels, and materials. Among the major cost drivers, culture medium plays a pivotal role in determining protein yield and quality. This review presents a comprehensive perspective on the critical stages of “smart” culture medium optimization: planning, screening, modeling, optimization, and validation. In the planning stage, we examine the nutritional and energetic roles of medium components, including carbon, nitrogen, amino acids, salts, and trace metals, and their impacts on culture parameters such as pH, oxidative state, and osmolality. We highlight the variability in trace metal content due to water sources, culture vessels, and raw materials, which can substantially influence RPP. The screening stage covers Design of Experiments (DoE) approaches, assessing their theoretical basis, implementation, and limitations. For modeling, we describe methods that integrate experimental data to develop predictive models for smart medium formulation. Model-based optimization strategies can then be employed to select optimal media compositions for a given application. The validation stage aims to evaluate model predictions and provide feedback for model training and refinement. Finally, we survey mechanistic and artificial intelligence/machine learning (AI/ML)-driven models as integrated, transformational tools for predictive modeling of bioprocess conditions, nutrient availability, cellular metabolism, and protein quality, with the goal of optimizing culture media to enhance protein yields while reducing costs and environmental impact. We conclude by addressing the challenges of translating laboratory-scale medium optimization to industrial-scale settings and exploring future AI/ML-driven approaches that may overcome current bottlenecks and accelerate medium design for RPP. Overall, this review provides a unified framework for advancing smart medium design in RPP.
Recent years have seen a substantial increase in the application of machine learning (ML) for automated analysis of nondestructive examination (NDE) data. One of the applications of interest is the use of ML for the analysis of data from in-service inspection of welds in nuclear power and other industries. These types of inspections are performed in accordance with criteria described in the ASME Boiler and Pressure Vessel Code and require the use of reliable NDE techniques. The rapid growth in ML methods and the diversity of possible approaches indicate a need to assess the current capabilities of ML and automated data analysis for NDE and identify any gaps or shortcomings in current ML technologies as applied to the automated analysis of NDE data. In particular, there is a need to determine the impact of ML on the NDE reliability. This paper discusses the findings from a literature survey on the current state of ML for the automated analysis of data from ultrasonic NDE of weld flaws. It discusses an overview of ultrasonic NDE as used for weld inspections in nuclear power and other industries. Herein, data sets and ML models used in the literature are summarized, along with a generally applicable workflow for ML. Findings on the capabilities, limitations and potential gaps in feature selection, data selection, and ML model optimization are discussed. The paper identified several needs for quantifying and validating the performance of ML methods for ultrasonic NDE, including the need for common data sets.
This report summarizes an investigation of utilizing a Piezoelectric coating on fiber optics to monitor electric fields. The application of interest was monitoring the electric field emitted from a borehole casing being used an an Electromagnetic source in geophysical monitoring. Testing consists of using a water filled vessel with plate electrodes on opposing sides to generate electric fields while lowering a custom designed sensor into the water. The results are compared to what is conventionally available via simulations.
This report completes work on a universal high temperature constitutive model suitable for use with the ASME Boiler & Pressure Vessel Code Section III, Division 5 rules for the design by inelastic analysis of Class A nuclear reactor components. The goals of this work are to provide a simple model form that adequately captures the high temperature response of materials and can be applied to any future Code material. Additionally, the report describes an automated process for calibrating a model against test data. The idea is to simplify the effort required to generate a constitutive model for an arbitrary material, provided test data is available. This will accelerate the process of qualifying new Code materials in the future. In addition, the report provides calibrated models and detailed validation comparisons to test data for five currently-qualified or soon-to-be qualified materials: 316H, Grade 91, Alloy 800H, Alloy 617, and Alloy 709. The report surveys the available data for the remaining two ASME Class Materials --- 2.25Cr-1Mo and 304H --- concluding that there is enough data data to generate a model for 2.25Cr-1Mo steel provided some additional sources of non-public data can be included in the test database, but that a dedicated cyclic test campaign would be needed for 304H. Supplemental material includes the full text of an ASME Code change proposal to incorporate the models for the four currently-qualified Class A material, detailed validation comparisons to test data for the five material models, and input files for reference implementations of the constitutive models in the NEML and NEML2 modeling frameworks.