Site Constrained: Evaluation of D&D Impacts on Mission Critical Waste Management
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Marine renewable energy (MRE) harnesses ocean-based resources such as waves, tides, currents, and thermal or salinity gradients for sustainable power generation. It has the potential to complement existing renewable resources, support remote communities, and contribute to decarbonization efforts. However, understanding the hydrodynamic forces created by MRE devices and their impacts on marine life is critical for responsible deployment. Here, to address these concerns, advanced sensor devices, including the Marine Sensor Fish (MSF), Sensor Fish Mini (SF Mini), and Flexible Sensor Fish (FSF), were developed to measure interactions between aquatic organisms and MRE systems. This paper details the design, manufacturing, calibration, and field deployment of these sensor suites, highlighting their ability to capture key physical stressors such as shear forces, pressure changes, and collision impacts. The MSF successfully evaluated turbine interactions at a tidal turbine in the Salish Sea, capturing data on turbulence, collision impact, and pressure gradients. The SF Mini validated hydrodynamic conditions in scaled hydraulic models, supporting computational fluid dynamics simulations. The FSF, with its flexible silicone body, measured species-specific impacts in turbulent environments. This research demonstrates the potential of Sensor Fish technology to advance sustainable marine energy systems by reducing biological impacts and informing environmentally sustainable designs.
Significance Researchers lack the tools for quantitatively evaluating the impact of their research on technology costs, especially when those technologies comprise multiple components or when the component costs are highly uncertain. We propose a suite of tools to aid in evaluating technology platforms, setting system- and component-level research targets and identifying high-impact innovation trajectories. These tools are applicable to any technology composed of multiple components whose performance or cost will benefit from innovation, but they are especially valuable for membrane systems in which the high interdependence in components amplifies or dampens the effects of innovation in nonintuitive ways.
This study investigates the impact that operations and market strategy have on the design and value of an energy storage system on three levels of the facility: the cell level, the system level, and the project level. The study provides insights for developers, capital providers, customers and policy makers into the impact different operational strategies have on effectiveness of energy storage system in today's emerging market. Energy storage systems can be used for a variety of usage profiles, with the choice having a profound impact on their performance, lifespan, and revenue potential. Most evaluations of application stacking only look at the possible revenue potential without understanding the increased costs and potential for major damage to the cells. Evaluating the impact of operational choices is critical to understanding the risk adjusted return from energy storage project investment. This is the fifth study in the Energy Storage Financing Study series, which is designed to investigate challenges surrounding the financing of energy storage projects in the U.S., promoting greater technology and project risk transparency, reducing project transaction costs, and supporting a level playing field for innovative energy storage technologies.
Abstract. The vertical structure of clouds has a profound effect on the global energy budget, the global circulation, and the atmospheric hydrological cycle. The CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) missions have taken complementary, colocated observations of cloud vertical structure for over a decade. However, no globally gridded dataset is available to the public for the full length of this unique combined data record. Here we present the 3S-GEOPROF-COMB product (Bertrand et al. 2023, https://doi.org/10.5281/zenodo.8057791), a globally gridded (level 3S) community data product summarizing geometrical profiles (GEOPROF) of hydrometeor occurrence from combined (COMB) CloudSat and CALIPSO data. Our product is calculated from the latest release (R05) of per-orbit (level-2) combined cloud mask profiles. We process a set of cloud cover, vertical cloud fraction, and sampling variables at 2.5, 5, and 10° spatial resolutions and monthly and seasonal temporal resolutions. We address the 2011 reduction in CloudSat data collection with Daylight-Only Operations (DO-Op) mode by subsampling pre-2011 data to mimic DO-Op collection patterns, thereby allowing users to evaluate the impact of the reduced sampling on their analyses. We evaluate our data product against CloudSat-only and CALIPSO-only global-gridded data products as well as four comparable surface-based sites, underscoring the added value of the combined product. Interest in the product is anticipated for the study of cloud processes, cloud–climate interactions, and as a candidate baseline climate data record for comparison to follow-up satellite missions, among other uses.
Efficient and cost-effective operation of a nuclear power plant (NPP) is essential to ensuring long-term economical and safe operation. Multiple cost saving opportunities exist, referred to here as work reduction opportunities (WRO). These WROs reduce plant operating costs by employing various cost-effective strategies (e.g., implementation of modern technologies). Identifying and objectively screening WROs is an essential task to help reduce overall costs. However, there is no comprehensive framework for assessing WROs in the nuclear industry and evaluating their impact on plant operations. This report presents a novel framework for systematically evaluating WROs from a technical, economic, and risk perspective. As NPPs continue to add new technology and implement modernization strategies into their current processes, potential WROs are commonly identified. Although most WROs have the potential to reduce costs, not all opportunities will result in significant cost savings due to unforeseen risks, large implementation costs, or benefits that fall short of expectations. Examples of this can be the result of a technology that is not fully developed, uncertainty in the amount of cost reduction, or difficulties introducing a new process into an organization. These uncertainties can manifest several ways and can result in a WRO with limited cost savings or even a loss of investment. The framework developed emphasizes the importance of effectively screening the WROs from a holistic perspective to objectively identify inefficiencies and ensure a positive impact to the organization. This report presents the Technical, Economic, and Risk Assessment (TERA) as a key methodology for the screening and evaluation of potential WROs. The TERA framework begins with a screening phase where the process is examined through a hybrid combination of Lean Six Sigma and Integrated Operations for Nuclear (ION) guiding principles. This framework examines the current processes using the Lean Six Sigma SIPOC (Suppliers, Inputs, Process, Outputs, Consumers) methodology but retains the ION key elements of People, Technology, Process, and Governance as important factors to the nuclear decision-making process. By combining the principles of Lean Six Sigma and ION, the developed screening process is specific to the nuclear industry in that it systematically evaluates WROs in order to implement new technology that is comprehensively evaluated. The TERA begins by mapping current processes as they relate to WROs and examining the inefficiencies. Furthermore, the created process map can be used to identify and evaluate potential solutions. Using key performance indicators (KPIs), the TERA evaluates each area—technology, economics, and risk—for uncertainties and to perform cost-benefit analysis. The results of the TERA are important KPIs that allow for an evaluation of different processes and technology implementations. This assessment enables decision-makers to compare various WROs based on metrics and then make informed decisions for which opportunity to implement first. This research includes not only the creation of the TERA framework, but also the evaluation of its performance. A case study for screening potential WROs at Southern Nuclear Company is presented that utilizes the TERA methodology. Through the use of TERA, various WROs were screened, and the solutions evaluated for cost-benefit expectations. The report concludes by summarizing the overall effort and implications for utility modernization. The performance of the screening and TERA are discussed as well as the impact on the nuclear industry. The TERA process enables utilities to evaluate and inform investment decisions for WROs and mitigate any potential risks. Through this research, we provide utilities with a valuable framework to optimize operations, reduce costs, and drive continuous process improvement.
ABSTRACT We describe and test the fiducial covariance matrix model for the combined two-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) data set. Using a variety of new ansatzes for covariance modelling and testing, we validate the assumptions and approximations of this model. These include the assumption of Gaussian likelihood, the trispectrum contribution to the covariance, the impact of evaluating the model at a wrong set of parameters, the impact of masking and survey geometry, deviations from Poissonian shot noise, galaxy weighting schemes, and other sub-dominant effects. We find that our covariance model is robust and that its approximations have little impact on goodness of fit and parameter estimation. The largest impact on best-fitting figure-of-merit arises from the so-called fsky approximation for dealing with finite survey area, which on average increases the χ2 between maximum posterior model and measurement by $3.7{{\ \rm per\ cent}}$ (Δχ2 ≈ 18.9). Standard methods to go beyond this approximation fail for DES-Y3, but we derive an approximate scheme to deal with these features. For parameter estimation, our ignorance of the exact parameters at which to evaluate our covariance model causes the dominant effect. We find that it increases the scatter of maximum posterior values for Ωm and σ8 by about $3{{\ \rm per\ cent}}$ and for the dark energy equation-of-state parameter by about $5{{\ \rm per\ cent}}$.
A simplified flowsheet was developed to evaluate the impact of varied assumptions of I-129 decontamination factors on the overall I-129 material balance in the Direct Feed Low-Activity Waste (DFLAW) facility. The flowsheet allows inputs for I-129 feed and Decontamination Factors (DFs) for multiple DFLAW unit operations and provides information on I-129 partitioning to output streams. A series of 6 DFs were evaluated, including baseline DFs from a prior Waste Treatment and Immobilization Plant (WTP) study and refined values based on a Savannah River National Laboratory (SRNL) review. The Microsoft Excel flowsheet spreadsheet will be provided to WRPS to allow further evaluation of the impact of DF assumptions on output streams. The spreadsheet is not specific to iodine, the partitioning of any species can be estimated by entering the assumed DFs for each unit operation. Flowsheet outputs matched results from the prior WTP study and show that different assumptions for the DFs can greatly impact iodine partitioning to primary and secondary waste streams. Results from SRNL's baseline DF values suggest less than 50% of I-129 would be retained in glass versus the 96% when using the BNI DF values. In addition, the flowsheet demonstrated that more than 5 DFLAW operational cycles are required to achieve a steady-state of I-129 to the primary waste stream. It is not possible with the data available to determine whether the BNI approach or the approach taken in this study will be a better match for the iodine partitioning once the LAW facility begins operation.
Nanoconfined electrocatalysts demonstrate enhanced selectivity and activity owing to new phenomena emerging from chemical species confined at the interface. Creating these nanoconfined pockets at the interface is not trivial. We need highly negative potentials to create the pockets in metal/ligand catalysts like Ag-nanoparticle/ordered ligand interlayer catalysts. Lowering this activation potential can make the electrocatalysis more energy-efficient, and changes in the environment can impact this potential. We used Density Functional Theory (DFT) to evaluate the impact of ligand length and density, interfacial protons, and surface defects like Ag vacancies and Cu and Au dopants. The nanoconfined configuration is stabilized when the ligands are longer and more densely packed, leading to better agglomeration. It is also stabilized when the ligands adsorb protons and when the ligands detach from the surface easily owing to lower charge transfer. Au-doped surfaces displayed the lowest charge transfer and decreased the activation potential.
The project’s overall objective is to research, develop, and conduct a wide-scale demonstration of a utility smart charge management (SCM) system to develop optimal managed charging structures for grid value, evaluate the impact of EV charging on local distribution utility operations, and evaluate the utilities’ ability to control electronic vehicle (EV) charging load based on grid conditions. This report covers Argonne’s validation testing in the first period of the project, the objective of which was to determine the current managed charging functionality of the EVSE hardware, the network and the vehicle telematics software solution and understand gaps that need to be addressed prior to a large-scale demonstration.
MARVEL Hazards Evaluation evaluated the impacts of MARVEL operations, hazards, and postulated accidents. The hazard evaluation of MARVEL events and associated operations was performed for selection and evaluation of safety classification of systems, structures, and components (SSCs) and SSC safety functions, and for selection of design basis accidents (DBAs) applicable to the MARVEL microreactor design.
The Savannah River Site (SRS) is one of the major nuclear facilities owned by the U.S Department of Energy. During the Cold War, these facilities produced large amounts of radioactive and hazardous waste. On site, three unlined seepage basins in the F-Area received approximately 1.8 billion gallons of low-level waste containing nitric acid, radionuclides, and dissolved metals due to plutonium and tritium production operations. The acidic nature of the waste created a source of relatively mobile radionuclides below the basins. Radionuclides previously disposed of within the F-Area, including uranium isotopes (U), technetium-99 (Tc-99), and iodine-129 (I-129), are moving with groundwater towards Four Mile Branch Wetland, where they are subsequently upwelling and interacting with natural organic matter (NOM). Many environmental factors including redox conditions, porewater composition, pH, light, and temperature affect the degradation of organic matter as well as interactions with Tc-99, U, and I-129. In particular, the high concentrations of nitrate from the acidic waste may increase the formation of reactive oxygen species (ROS) that impact both degradation of NOM and behavior of contaminants. In the presence of sunlight, I-129, Tc-99, and U speciation and complexation behavior may be affected by ROS and NOM degradation products in addition to the factors generally considered in subsurface systems in the absence of light. This research aims to determine whether the interactions between radionuclides, NOM, and nitrate affect the fate of I-129, Tc-99, and U and which processes are controlling their behavior. Experiments were conducted at variable pH in the presence of NaNO{sub 3} in order to determine the impact of light and pH on NOM degradation and to evaluate the impact on the fate of contaminants of concern. Soil samples high in NOM collected from two sites in the Southeastern United States (Savannah River Site and the Everglades) were studied. Batch experiments were conducted with NOM and the following aqueous contaminants, U, I-129, Tc-99 with exposure to ultraviolet (UV) light in an environmental chamber. This study was conducted in a sterile environment in order to exclude the potential for microbial degradation of organic matter. Results indicated photodegradation of NOM and significant interaction of radionuclides with NOM. (authors)
Nonlinear acoustic methods demonstrate high sensitivity for concrete damage evaluation. Among these methods, nonlinear resonance acoustic methods have been widely used in laboratory tests on small scale test samples. In this study, a nonlinear impact-echo (IE) method for concrete damage evaluation was introduced, in which the IE frequency shift was measured at different impact force levels. The nonlinear IE test and the nonlinear impact resonance acoustic spectroscopy (NIRAS) test share similarities in the experimental setup and analysis method. However, the nonlinear IE test excites a local thickness resonance mode of a member instead of the global resonance vibration. Therefore, the analyzed mode is unaffected by member boundary conditions and is applicable to large concrete structural members. To identify the fundamental IE frequencies, multiple impacts were applied along the members. Once the fundamental IE frequencies were determined, the effectiveness of the nonlinear IE method was evaluated by testing seven concrete beam specimens with varying levels of alkali-silica reaction (ASR) damage. In conclusion, the nonlinear IE test demonstrates high sensitivity to concrete damage and allows for quantitative assessment of the damage state of concrete without a baseline measurement.
Automation and cost-saving initiatives, such as process automation with advances in artificial intelligence, are gaining traction in modernization efforts across the nuclear industry. As these innovations are increasingly adopted, it becomes crucial to evaluate their impacts comprehensively. Various technical and economic attributes, along with risk and human readiness factors, must be achieved to ensure that innovative projects enabling automation and modernization are successful. However, no systematic or integrated framework exists that allows plants to evaluate these innovative projects. To address this gap, the Technical, Economic, Risk, and Adoption (TERA) assessment offers a structured method to evaluate innovative technologies, ensuring solutions meet both operational and safety standards. The TERA framework integrates the disparate perspectives to assess modernization opportunities in nuclear operations. It combines qualitative and quantitative models to evaluate the relationship between performance and business impacts, while also enabling continuous re-evaluation during project development. This approach helps plant owners identify high-priority opportunities, optimize cost savings, and minimize risks, ensuring projects remain on track to achieve desired returns. By providing a comprehensive, systematic methodology, TERA enables informed, data-driven decisions that support successful modernization efforts, enhancing efficiency, safety, and cost savings across nuclear operations. This paper explains the TERA framework and its benefits for the nuclear industry.
The Middle Devonian Marcellus shale play has emerged as a major world-class hydrocarbon accumulation and represents one of the largest and most prolific shale plays in the world. According to many outcrop studies in the region, natural fractures are well developed in the Marcellus Shale. However, evaluating fractures in the subsurface is often a significant challenge due to a lack of sufficient data. Therefore, in the Marcellus Shale Energy and Environment Laboratory (MSEEL) consortium project, significant efforts have been made to acquire high-quality image logs in the Marcellus laterals. The project provided tremendous opportunities to characterize the natural fractures and sub-seismic faults and to evaluate their impact on well stimulation. In this study, about 70,000 ft of acquired high-resolution logging while drilling (LWD) acoustic images from five long laterals located in Monongalia County, West Virginia, were processed and interpreted. In addition, the study used high-quality micro-resistivity images from a pilot well, allowing the evaluation of natural fractures in the entire Marcellus vertical sequence. Based on the available acoustic images, the natural fractures were classified into three basic categories: high-amplitude fractures, low-amplitude fractures, and faults. Further, larger open fractures can also be determined when a low-amplitude fracture is evident on caliper images. The fractures in the Marcellus usually have a medium to high angle dip; however, multiple fracture sets in terms of strike orientation were clearly observed in all the laterals. The fracture set with a strike at NE-SW (or 60-240 deg) seems to be the predominant one in all the wells. A few other sets, including those with N-S, NWW-SEE, and E-W strikes, were also observed. Several sub-seismic faults, with mostly a low dip angle and a NE-SW strike, have also been seen in two of the laterals. The fracture density is variable across all the laterals, ranging from very low (or none) to very high (up to 5 fractures per ft). The average fracture density for all the laterals is about 1 fracture per 10 ft. In the vertical sequence, the natural fracture development showed a clear preference for shale or shaly facies over carbonate-rich or thin limestone layers. The interpreted fracture and fault data were used as input data for the stimulation design with the purpose of better understanding the fractures’ impact on well stimulation. Production data from the laterals were also used to evaluate the natural fractures’ influence on well performance. The quality image database and the consistent interpretation results for the entire project enabled a systematic approach to characterizing fractures and, more importantly, to evaluating the impact of fractures on well stimulation and production.
Here, the distorted-wave with exchange (DWE) method is employed to evaluate electron impact ionization cross sections in dense electron–ion plasmas. Bound and continuum electron wave functions are obtained from a non-relativistic average-atom code. Plots of DWE cross sections are presented for 1s electrons in Li and Be plasmas and 2p electrons in Na and Mg plasmas. For each of these elements, cross sections are evaluated at metallic density in a range of temperatures from 10 to 100 eV and at their respective melting points. Resonances in the cross sections appear near the incident energy threshold at high temperatures. The origin of these resonances is discussed. In general, the distorted wave (DW) method without exchange is found to be a good approximation to the DWE method for electron impact ionization calculations. In the resonance region, however, exchange effects are found to be very important and cannot be neglected.
Grid-interactive efficient buildings (GEBs) have been considered as an important asset to support the power grid reliability by utilizing the demand flexibility offered by GEBs. GEBs are enabled by advances in sensors and controls, and the communication between building equipment, whole buildings, and the grid. The integration of different building technologies and network-based communication system makes GEBs vulnerable to passive threats such as equipment failure and active threats such as cyber-attacks. Modeling and simulation is an effective way to evaluate the impact of threats on the system performance. This paper proposes a generic and flexible threat injection framework for commonly-used building energy simulators such as EnergyPlus and Modelica to support threat modeling and evaluation. This framework leverages functional mock-up unit (FMU) to develop a general modeling interface for threat injection and simulation. A numerical case study using Modelica as a building energy simulator is conducted to demonstrate the capability of the framework for supporting single/multiple-order threat modeling and simulation of a GEB. Four threats and their combinations are injected on a Modelica-based threat-free building energy and control system, including operating supply fan at its full speed, remotely cycling the chiller on and off, blocking the chiller from receiving the chilled water supply temperature setpoints, and hijacking the global zone air temperature setpoint. Simulation results show that the cyber-attack that leads to short-term signal blocking has small effects on the system operation due to the "self-healing" feature of the heating, ventilation, and air-conditioning (HVAC) interactive control system. The threat that takes control of resetting the global zone air temperature setpoints has the most adverse impact on the system energy use, peak power demand, thermal comfort and the provision of demand flexibility. The combination of four threats have aggregative effects on the system but the effects are less than the additive effects of the individual threat.