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At least 1,225 records · Page 68

Criticality Consideration for Geologic Disposal of DOE-Owned Spent Nuclear Fuels - 20255

Decisions must be made relative to packaging spent nuclear fuel (SNF) for storage, transportation, and eventual disposal. This paper evaluates potential criticality-related loading and packaging considerations for Department of Energy (DOE)-owned SNF that could be impacted favorably or unfavorably by disposal uncertainties and proposes approaches to minimize such impacts. Using Al-Based SNF as an example and drawing on analyses performed in support of the Yucca Mountain Repository License Application (LA), this paper explores the role of natural barriers, engineered barriers, and waste form characteristics relative to reducing the potential for postclosure criticality. Several parameters important to postclosure criticality are considered in order to determine which are useful discriminators to support packaging decisions. Using these parameters, a qualitative assessment is performed relative to three options for managing DOE-owned SNFs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

BI-LEVEL OPTIMIZATION FOR ELECTRICITY TRANSACTION IN SMART COMMUNITY WITH MODULAR PUMP HYDRO STORAGE

Grid integration of the increasing distributed energy resources could be challenging in terms of new infrastructure investment, power grid stability, etc. To resolve more renewables locally and reduce the need for extensive electricity transmission, a community energy transaction market is assumed with market operator as the leader whose responsibility is to generate local energy prices and clear the energy transaction payment among the prosumers (followers). The leader and multi-followers have competitive objectives of revenue maximization and operational cost minimization. This non-cooperative leader-follower (Stackelberg) game is formulated using a bi-level optimization framework, where a novel modular pump hydro storage technology (GLIDES system) is set as an upper level market operator, and the lower level prosumers are nearby commercial buildings. The best responses of the lower level model could be derived by necessary optimality conditions, and thus the bi-level model could be transformed into single level optimization model via replacing the lower level model by its Karush-Kuhn-Tucker (KKT) necessary conditions. Several experiments have been designed to compare the local energy transaction behavior and profit distribution with the different demand response levels and different local price structures. The experimental results indicate that the lower level prosumers could benefit the most when local buying and selling prices are equal, while maximum revenue potential for the upper level agent could be reached with non-equal trading prices.

Chen, Yang↗

Implementation and optimization of the PTOLEMY transverse drift electromagnetic filter

The PTOLEMY transverse drift filter is a new concept to enable precision analysis of the energy spectrum of electrons near the tritium β-decay endpoint. Here, we detail the implementation and optimization methods for successful operation of the filter for electrons with a known pitch angle. We present the first demonstrator that produces the required magnetic field properties with an iron return-flux magnet. Two methods for the setting of filter electrode voltages are detailed. The challenges of low-energy electron transport in cases of low field are discussed, such as the growth of the cyclotron radius with decreasing magnetic field, which puts a ceiling on filter performance relative to fixed filter dimensions. Additionally, low pitch angle trajectories are dominated by motion parallel to the magnetic field lines and introduce non-adiabatic conditions and curvature drift. To minimize these effects and maximize electron acceptance into the filter, we present a three-potential-well design to simultaneously drain the parallel and transverse kinetic energies throughout the length of the filter. These optimizations are shown, in simulation, to achieve low-energy electron transport from a 1 T iron core (or 3 T superconducting) starting field with initial kinetic energy of 18.6 keV drained to < 10 eV (< 1 eV) in about 80 cm. This result for low field operation paves the way for the first demonstrator of the PTOLEMY spectrometer for measurement of electrons near the tritium endpoint to be constructed at the Gran Sasso National Laboratory (LNGS) in Italy.

47 OTHER INSTRUMENTATION↗

Local Cation-Ordered Superlattice Stabilizing Ni-Rich Single-Crystalline Cathodes

Ni-rich single-crystalline cathodes are pivotal for advancing lithium-ion battery technology due to their high energy density and mechanical stability. However, Ni-rich single-crystalline particles face intrinsic structural heterogeneity due to excessively high sintering temperature required to shape micron-sized morphologies─typically over 150 °C above the polycrystalline optimum, leading to rapid electrochemical decay and unsatisfied rate performance that hinder their practical application. Here, in this work, we propose a lithium-deficient presintering strategy to synthesize cation-ordered single-crystalline LiNi 0.83 Co 0.12 Mn 0.05 O 2 (S-NCM83), effectively minimizing lattice chemical heterogeneity and defect formation. The resulting cation-ordered percolation network enhances the structural stability of the bulk, reduces the energy barrier for Li + migration, and stabilizes Li + diffusion pathways. Consequently, S-NCM83 demonstrates significantly improved cycling stability across various operating temperatures and achieves exceptional rate performance, delivering 206 mAh g –1 at 0.1 C and 170 mAh g –1 at 5 C, without requiring surface coatings or doping. This work introduces a universal strategy to address the long-standing structural instability issues in single-crystalline cathodes, paving the way for simplified and scalable approaches to long-life and high-energy lithium-ion batteries.

36 MATERIALS SCIENCE↗

Real-time hybrid controls of energy storage and load shedding for integrated power and energy systems of ships

This paper presents an original energy management methodology to enhance the resilience of ship power systems. The integration of various energy storage systems (ESS), including battery energy storage systems (BESS) and super-capacitor energy storage systems (SCESS), in modern ship power systems poses challenges in designing an efficient energy management system (EMS). The EMS proposed in this paper aims to achieve multiple objectives. The primary objective is to minimize shed loads, while the secondary objective is to effectively manage different types of ESS. Considering the diverse ramp-rate characteristics of generators, SCESS, and BESS, the proposed EMS exploits these differences to determine an optimal long-term schedule for minimizing shed loads. Furthermore, the proposed EMS balances the state-of-charge (SoC) of ESS and prioritizes the SCESS’s SoC levels to ensure the efficient operation of BESS and SCESS. For better computational efficiency, we introduce the receding horizon optimization method, enabling real-time EMS implementation. Further, a comparison with the fixed horizon optimization (FHO) validates its effectiveness. Simulation studies and results demonstrate that the proposed EMS efficiently manages generators, BESS, and SCESS, ensuring system resilience under generation shortages. Additionally, the proposed methodology significantly reduces the computational burden compared to the FHO technique while maintaining acceptable resilience performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Bifacial all-perovskite tandem solar cells

The efficiency of all-perovskite tandem devices falls far below theoretical efficiency limits, mainly because a widening bandgap fails to increase open-circuit voltage. We report on a bifacial all-perovskite tandem structures with an equivalent efficiency of 29.3% under back-to-front irradiance ratio of 30. This increases energy yield and reduces the required bandgap of a wide-bandgap cell. Open-circuit voltage deficit is therefore minimized, although its performance under only front irradiance is not ideal. The bifacial device needs a sputtered rear transparent electrode, which could reduce photon path length and deteriorate stability of Pb-Sn perovskites. Embedding a light-scattering micrometer-sized particle layer into perovskite to trap light, effectively increases absorptance by 5 to 15% in the infrared region. Using a nonacidic hole transport layer markedly stabilizes the hole-extraction interface by avoiding proton-accelerated formation of iodine. These two strategies together increase efficiency of semitransparent Pb-Sn cells from 15.6 to 19.4%, enabling fabrication of efficient bifacial all-perovskite tandem devices.

14 SOLAR ENERGY↗

Impact of a dynamic grid mix and climate on operational carbon emissions modeling for different building typologies and climate zones

Calculating operational carbon emissions through a building’s lifecycle is complex due to the dynamic nature of influencing factors such as climate and energy grid mix. This paper introduces a novel methodology for modeling 30-year operational carbon impacts of buildings and applies this method to mid-rise office and residential typologies across various US climate zones. The method accounts for these temporal variabilities using new and scarcely cited data sources. Key findings indicate that future changes in the climate, while impactful, play a relatively modest role in operational carbon emissions compared to significant reductions with modeling scenarios using the projected decarbonization of the electricity grid. Here, the study also finds that using annual, month-hourly, or hourly grid emission factors have a minimal impact on carbon accounting, except in certain climates and program types where emission patterns do not align with a building’s energy consumption. Warmer climates like Miami, Florida and Tucson, Arizona, which rely heavily on cooling, demonstrate larger variations in carbon emissions when using higher temporal resolution emission factors. Ultimately, this study underscores the critical role of grid decarbonization in reducing long-term emissions and the importance of incorporating this variable in life cycle assessment (LCA) modeling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Grid Architecture Mapping to Understand Transformation (GAMUT): Concept Definition

The electric power system is undergoing significant transformation driven by changes in the generation mix, increasing reliance on information and communication technologies, evolving customer expectations, and a dynamic cyber-physical environment. To address these challenges, substantial investments will be made over the next decade to create a flexible, affordable, secure, reliable, and resilient electric system. In response, the U.S. Department of Energy's Office of Electricity is developing knowledge management tools aimed at systematically documenting technology pilots and demonstration projects. This initiative seeks to improve understanding of operating contexts, planning steps, and integration requirements for innovative grid technologies. The Department of Energy project leverages Grid Architecture principles to collect and organize insights into the interdependencies, requirements, and capabilities of various grid solutions. By employing a systematic approach, the project aims to perform a feasibility study for the development of a software tool that will support stakeholders, including regulators, transmission and distribution system operators, distributed energy resources aggregators, and technology providers. By offering a systematic, software-based framework to document technologies, understand their benefits and impacts, and inform deployment strategies, the proposed Grid Architecture Mapping to Understand Transformation (GAMUT) Tool is intended to reduce costs, enhance decision-making, and facilitate scaling and effective deployment of new technologies. The feasibility study will evaluate the technical and financial viability of the GAMUT Tool, identifying stakeholder needs and assessing risks and mitigation strategies. Ultimately, the GAMUT team aims to develop an initial minimal viable product, followed by staged improvements, to aid in the modernization of the electric grid, contributing to a more sustainable and resilient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Uniform Methods Project: Smart Thermostat Evaluation Protocol

A smart thermostat is an internet-connected device that controls home heating, ventilation, and air-conditioning (HVAC) equipment and can automatically adjust temperature set points to optimize performance and achieve energy savings. Smart thermostat features often include two way communication, occupancy detection (such as geofencing and occupancy sensors), schedule learning, and seasonal optimization algorithms. Smart thermostats can control most conventional HVAC systems, including central air conditioners, heat pumps, and forced air furnaces. Several types of residential utility programs offer smart thermostats as replacements measures. Working with smart thermostat vendors, utilities can offer separate optimization programs to produce energy savings beyond those achieved by installing a smart thermostat. From an evaluation perspective, smart thermostat programs have several noteworthy features. First, the energy savings from a smart thermostat may change over the life of the device. As a smart thermostat is connected to the internet, original equipment manufacturers can update the thermostat software to improve the thermostat's energy efficiency. Likewise, users can adjust the thermostat settings and schedules over time in response to changes in weather, thermal comfort, energy prices, or preferences for energy efficiency. Additionally, many thermostat manufacturers offer seasonal optimization programs that recommend changes or make minor, automated adjustments to the thermostat settings to improve energy efficiency. These opt-in programs are now standard offerings for many smart thermostat manufacturers and provided at no additional cost to users. The potential for software updates and continuous optimization and the evolving nature of user interactions mean future energy savings may differ from first-year savings and the energy savings of smart thermostats may need to be evaluated more than once. Second, smart thermostats often have small unit energy savings relative to a home's total energy consumption, especially in comparison to whole- home retrofit programs. This can make it difficult to detect the smart thermostat savings in billing or advanced metering infrastructure (AMI) meter consumption data. For example, as cooling loads in many regions average about 20% of annual electricity consumption, smart thermostat savings of 10% of cooling energy use would equate to a 2% reduction in home electricity consumption. Evaluators should use regression analysis of whole-home billing consumption or advanced metering infrastructure (AMI) meter consumption data to evaluate smart thermostat savings because, as explained at greater length below , these data are usually available to evaluators and regression can control for the impacts of weather and other potentially confounding factors on a home's energy consumption. Finally, as with other energy efficiency programs, participation in smart thermostat programs is self-selective. As discussed at greater length below , smart thermostat participants tend to be, among other things, younger, higher-income, and more likely to adopt electric vehicles (EVs) and internet connected devices than nonparticipants. These differences are often unobservable to the evaluator and correlated with a home's energy consumption, creating the potential for bias in estimating savings. Due to the small unit savings of thermostats, errors and biases from self-selection that may not be very consequential when evaluating a whole- home retrofits (e.g., ±2% of home electricity consumption) can have a major impact when evaluating the savings and cost-effectiveness of smart thermostat programs. A percentage point change in the estimated savings could affect the cost-effectiveness of a program. This means it is important for evaluators to assess and to minimize the potential for error from selection bias in estimating smart thermostat program savings. The Uniform Methods Project provides model protocols for determining energy savings and demand reductions that result from specific energy efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol ; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The UMP protocols can be used by utilities, program administrators, public utility commissions, evaluators, and other stakeholders for both program planning and evaluation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Universal Utility Data Exchange (UUDEX): Information Exchange Models for Solar DER (Rev. 1)

This report describes how the Universal Utility Data Exchange (UUDEX) can encapsulate and exchange information about distributed energy resources (DER) within UUDEX-formatted JSON documents. It proposes to use the existing extensible markup language (XML) information exchange format described in IEEE Std 2030.5, IEEE Standard for Smart Energy Profile Application Protocol but not other information exchange provisions of IEEE 2030.5, rather, relying on equivalent mechanisms in UUDEX. This will allow adoption of the UUDEX exchanges with minimal changes to the structure of the information exchanged and will not require a modification to the UUDEX documentation if IEEE 2030.5 makes changes to the information models.

14 SOLAR ENERGY↗

Influence of Nanoconfinement and Elevated Temperatures on Geocolloid-Facilitated Transport of Energy related Contaminants

Fossil fuels obtained using hydraulic fracturing and nuclear energy are deemed crucial for meeting the current and future energy demands of the United States. The utilization of these resources, especially fossil fuels from hydraulic fracturing, has increased rapidly within the last decade. However, with the increasing levels of hydraulic fracturing activities, the occurrence and fate of chemicals used in these processes in the geosystem, as well as the potential consequences of their interactions with environment and geosystems (e.g. mineral-based geocolloids and geosurfaces), have been increasingly recognized as issues warranting consideration owing to the toxic nature of these chemicals. Scientific results originated from this project has brought better understandings on how such contaminants can preferentially or adversely interact with geosystems and how geocolloids can facilitate their transport by realistically mimicking geological conditions and environments in the laboratory level for the first time. Based on such knowledge, it may eventually lead to the development of mitigation strategies for reducing and minimizing the transport and wide distribution of contaminants and pollutants. This aspect is important for the society to ensure that energy-related contaminants do not find their way to waterbodies that are used as drinking water or irrigation. The project is also anticipated to increase public awareness about potential adverse effects of energy systems on the geosphere and environment and may motivate society to consider better mitigation strategies to prevent such occurrences.

(Nano)Confinement↗

Anomaly Detection and Mitigation for Dynamic Frequency Regulation in Hydropower-Battery Systems

Hydropower operators and energy storage providers are increasingly interested in participating in frequency regulation services, driven by the incentives offered by independent system operators, such as the PJM Interconnection. This transition, however, unfolds against the backdrop of a modernizing and rapidly digitizing power grid, exposing the integrated legacy infrastructure to a multitude of cybersecurity threats. This work presents an approach for developing an anomaly detection and mitigation system to address cybersecurity challenges during the participation of a hydropower-integrated battery energy storage system (BESS) in a frequency regulation market. The applied anomaly detector utilizes machine learning algorithms to provide detailed classification of cyber-physical events. Later, the applied mitigation system triggers predefined corrective actions to minimize the impact of data integrity attacks on the regulation market and system stability. We evaluated the proposed approach on a hydropower-integrated BESS topology, specifically analyzing the slow regulation signal (Reg A) coming from the PJM market. Our simulation results demonstrate that the proposed approach performs well in detecting data integrity attacks within the allocated time frame and also minimizes the system's transient instability during the participation of hydropower and BESS in the regulation market.

battery energy storage system↗

Cross-beam energy transfer in direct-drive ICF. II. Theory and simulation of mitigation through increased laser bandwidth

The response of the cross-beam energy transfer instability (CBET) to laser bandwidth is investigated through a combination of theory and simulation. Existing linear theory is generalized to treat broadband lasers, demonstrating that CBET is most effectively suppressed when the bandwidth exceeds the ion-acoustic wave (IAW) frequency. It is shown that for such bandwidths, reverse (seed to pump) transfer becomes possible, which reduces the net energy transfer rapidly as bandwidth is increased. The CBET gain exponent in this regime scales with bandwidth (Δω) as Δω−3 for Gaussian or Lorentzian laser spectra with different scalings possible for other spectra. Comparison of our theory with linearized fluid and particle-in-cell simulations, performed with the laser-plasma simulation environment (LPSE) and vector particle in cell (VPIC) codes, respectively, finds that the model is accurate in the absence of nonlinear processes. However, linear analysis also finds that the IAW energy density scales as Δω−1, implying that nonlinear effects may be more difficult to control than the CBET scaling would suggest. Indeed, nonlinear effects are found to be present in VPIC simulations with high-intensity lasers, despite minimal apparent CBET. Nonlinear processes in the VPIC cases include particle trapping, the two-ion wave decay, and ion wave self-focusing. In some high intensity VPIC cases, these effects lead to net energy transfer from seed to pump and increases to backscatter stimulated Brillouin scattering reflectivities. Finally, for a given bandwidth, we show that improved control of nonlinear processes can be achieved via smoothing by spectral dispersion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Investigation of defects in melt and solution grown perovskite CsPbBr 3 single crystals

Recently, there has been considerable interest in x-ray and gamma ray detectors with large volume and high energy resolution that operate at room temperature. To improve detector energy resolution, the carrier mobility-lifetime product needs to be increased, and the electronic trap state concentration needs to be minimized. Defect concentrations in the part per billion range can alter the charge transport and carrier recombination lifetime. In this work, thermally stimulated current spectroscopy measurements were systematically carried out in bulk halide perovskite single crystals of CsPbBr 3 over a temperature range of 80–320 K. The origins and trap parameters of CsPbBr 3 crystals from the solution growth and melt growth procedures were determined and compared. Trap concentrations were ranged from 1 × 10 11 to 1 × 10 16 cm –3 . Appreciable detector performance was observed for CsPbBr3 crystals with trap concentrations less than 1 × 10 14 cm –3 . The comparison of spectral responses of crystal samples grown using two different methods shows that, after purification, solution-grown crystals are comparable to melt-grown crystals in terms of low defect concentration and improved detector performance. Finally, for an improved mobility-lifetime product and enhanced spectral response to high energy radiation from fissile materials, trap states in either type of a crystal ingot must be reduced closer to 10 11 cm –3 .

36 MATERIALS SCIENCE↗

Privacy-Preserving Control of Partitioned Energy Resources

Distributed energy resources are an increasingly important part of the electric grid. We examine the problem of partitioning a distributed energy resource among many users while providing privacy to them. In this model, clients can send requests to a server, the server can verify that the requests are valid and aggregate them, but it cannot see the actual values in the requests. Without privacy, each user is forced to reveal their daily schedule or energy use. Energy resources add a novel challenge that prior systems do not address: they require verifying limits on private power (a rate over time) and energy (a sum) values. Furthermore, the cryptographic mechanisms must run on embedded energy control systems. We describe Weft, a novel cryptographic system that verifies both power (rate) and energy (integral) constraints on private client values and aggregates them. The key insight behind the approach is to rely on additively homomorphic secret shares, which allows servers to compute sums from rates. We present 3 cryptographic proof systems with different system trade-off for embedded systems: bit-splitting proofs minimize memory use, sorting proofs minimize computation, and commitment proofs minimize network communication. Using bit-splitting proofs, it takes an IoT client using a CortexM microcontroller 4 minutes of compute time to privately control its share of an energy resource for a day at 20s granularity.

Laufer, Evan↗

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. In this study, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model Based Validation of Intelligent Powertrain Strategies for Connected and Automated Vehicles

Systems incorporating Vehicle to Everything (V2X) and conventional cellular based communication in vehicles can significantly help improve energy consumption via a combination of intelligent powertrain control strategies, smarter routing algorithms and driving in such a way as to minimize fuel economy and the emission of carbon dioxide, known as "eco-driving." In projects led by the Southwest Research Institute (SwRI), large-scale traffic simulations are created to model real-world scenarios with dynamic behavior that is reactive to imposed changes. Coupled with high fidelity powertrain models, the closed loop framework enables research and development of such Connected and Automated Vehicle (CAV) enabled technologies at scale. This paper will discuss a traffic system simulation environment that was built based on the High Street urban corridor in Columbus, Ohio. Eco-driving strategies were tested at scale on a variety of powertrain platforms – internal combustion engines, hybrid electric and fully electric vehicles. Furthermore, the paper will focus on hybrid electric powertrain modeling along with details on how the powertrain model was leveraged to develop a sophisticated clustering scheme to help down-select speed traces from large scale simulation studies for validation on vehicle dynamometer. Nominal energy consumption improvement around 12% was observed with good match between simulation studies and vehicle testing.

33 ADVANCED PROPULSION SYSTEMS↗

First-principles theory of the Dirac semimetal Cd 3 As 2 under Zeeman magnetic field

Time-reversal broken Weyl semimetals have attracted much attention recently, but certain aspects of their behavior, including the evolution of their Fermi surface topology and anomalous Hall conductivity with Fermi-level position, have remained underexplored. A promising route to obtain such materials may be to start with a nonmagnetic Dirac semimetal and break time-reversal symmetry via magnetic doping or magnetic proximity. Here we explore this scenario in the case of the Dirac semimetal Cd 3 As 2 , based on first-principles density-functional calculations and subsequent low-energy modeling of Cd 3 As 2 in the presence of a Zeeman field applied along the symmetry axis. We clarify how each four-fold degenerate Dirac node splits into four Weyl nodes, two with chirality ±1 and two higher-order nodes with chirality ±2. Using a minimal k · p model Hamiltonian whose parameters are fit to the first-principles calculations, we detail the evolution of the Fermi surfaces and their Chern numbers as the Fermi energy is scanned across the region of the Weyl nodes at fixed Zeeman field. We also compute the intrinsic anomalous Hall conductivity as a function of Fermi-level position, finding a characteristic inverted-dome structure. Cd 3 As 2 is especially well suited to such a study because of its high mobility, but the qualitative behavior revealed here should be applicable to other Dirac semimetals as well.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗