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At least 937 records · Page 52

Downstream Separation of Formic Acid with Anion-Exchange Resin from Electrocatalytic Carbon Dioxide (CO 2 ) Conversion: Adsorption, Kinetics, and Equilibrium Modeling

The electrocatalytic carbon dioxide reduction reaction (CO 2 RR) that produces liquid formic acid (FA) is one potential route to minimize the CO 2 concentration in the atmosphere by utilizing CO 2 as a feedstock. However, one of the main disadvantages of this route is the high energy demand required for purification through conventional distillation. This method of purification has been shown to result in a large carbon footprint in life-cycle analysis (LCA). Therefore, finding an alternative purification technique that can integrate with an electrochemical CO 2 RR process with the potential to lower the carbon footprint would be of great interest. Under the experimental conditions of the CO 2 RR, FA remains in its basic form as the formate anion in the catholyte. Anion exchange resins with their basic properties can separate the formate anion from the catholyte mixture as an alternative to energy intensive distillation. In this work, three anion exchange resins with increasing basicity order: Amberlite IRA-96 < Amberlite IRA-910 < Ambersep 900 are tested to separate FA in the presence of aqueous solution of potassium bicarbonate catholyte with varying levels of resin and FA. Kinetics and equilibrium studies data for the FA adsorption are interpreted using several kinetics and isotherm models. The kinetics data fit well with a pseudo-first-order model at high initial FA concentrations and a pseudo-second-order model at low initial FA concentrations. The experimental data can be best explained with the Freundlich isotherm model. The fitted results show that strongly basic Ambersep 900 is more effective at separating FA, with a maximum adsorption capacity of 336.7 mg/g compared to Amberlite IRA-96 (275.2 mg/g) and Amberlite IRA-910 (209.2 mg/g) in neutral water. However, weakly basic Amberlite IRA-96 (110.8 mg/g) can separate FA more efficiently from potassium bicarbonate catholyte than Amberlite IRA-910 (99.9 mg/g) and Ambersep 900 (40.0 mg/g). As a result, competitive adsorption occurs in the presence of potassium bicarbonate catholyte, but the formic acid adsorption capacity is still sufficient for adequate separation.

20 FOSSIL-FUELED POWER PLANTS↗

Evolution of the ATLAS TDAQ online software framework towards Phase-II upgrade: Use of Kubernetes as an orchestrator of the ATLAS Event Filter computing farm

The ATLAS experiment at the LHC at CERN continuously evolves its TDAQ system to meet the challenges of new physics goals and technological advancements. As ATLAS prepares for the Phase-II Run 4 of the LHC, significant enhancements in the TDAQ Controls and Configuration (TDAQ-CC) tools have been designed to ensure efficient data collection, processing, and management. This abstract presents the evolution of ATLAS TDAQ-CC system leading up to Phase-II Run 4. As part of the evolution towards Phase-II, Kubernetes has been chosen to orchestrate the Event Filter (EF) farm. By leveraging Kubernetes, ATLAS can dynamically allocate computing resources, scale processing capacity in response to changing data taking conditions and ensure high availability of data processing services. The integration of the Kubernetes with the TDAQ Run Control framework enables perfect synchronisation between the experiment’s data acquisition components and the computing infrastructure. We will discuss the architectural considerations and implementation challenges involved in Kubernetes integration with the ATLAS TDAQ-CC system. We will highlight the benefits of using Kubernetes as an EF farm orchestrator, including improved resource utilization, enhanced fault tolerance, and simplified deployment and management of data processing workflows. In addition, we will report on the extensive testing of Kubernetes that was conducted using a farm of 2500 servers within the experiment data taking environment, demonstrating its scalability and robustness in handling the demands of the ATLAS TDAQ system for Phase-II. The adoption of Kubernetes represents a significant step forward in the evolution of ATLAS TDAQ-CC system, aligning with industry best practices in container orchestration.

Corso Radu, Alina [Univ. of California, Irvine, CA↗

Safeguards by Design Table Top Exercises Final Report (FY 2023)

This University Engagement project challenged engineering students at universities, that do not have bachelor’s degree programs in nuclear engineering but do have research reactors and some nuclear engineering coursework, to develop capacity in Safeguards by Design concepts through the application of Tabletop Exercises. This University Engagement project was part of the U. S. Department of Energy’s (DOE) National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation, Office of International Nuclear Safeguards, Next Generation Safeguards Initiative (NGSI), Human Capital Development (HCD): University Engagement Program. This program exposed university students with Mechanical Engineering majors and Nuclear Engineering minors to the concepts of international nuclear safeguards. In FY22, three teams at the University of Rhode Island and two teams at the University of Texas Austin participated in researching, designing, building, and testing projects to support international nuclear safeguards measurements or verification. The projects involved engaging in activities at the university’s research reactors. All the projects engaged students with prototyping a design and/or tool for application at the Universities’ reactor. However, for FY23, the direction of the HCD project had changed to implementing a Tabletop Exercise in Safeguards by Design (SBD). A Tabletop Exercise was not executed during FY23, but relationships with both Universities was maintained and how to integrate the exercise into the curriculum of both programs was determined.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Accelerated computation of lattice thermal conductivity using neural network interatomic potentials

We report with the development of the density functional theory (DFT) and ever-increasing computational capacity, an accurate prediction of lattice thermal conductivity based on the Boltzmann transport theory becomes computationally feasible, contributing to a fundamental understanding of thermal conductivity as well as a choice of the optimal materials for specific applications. However, steep costs in evaluating third-order force constants limit the theoretical investigation to crystals with high symmetry and few atoms in the unit cell. Currently, machine learning potentials are garnering attention as a computationally efficient high-fidelity model of DFT, and several studies have demonstrated that the lattice thermal conductivity could be computed accurately via the machine learning potentials. However, test materials were mostly crystals with high symmetries, and the applicability of machine learning potentials to a wide range of materials has yet to be demonstrated. Furthermore, establishing a standard training set that provides consistent accuracy and computational efficiencies across a wide range of materials would be useful. To address these issues, herein we compute lattice thermal conductivities at 300 K using neural network interatomic potentials. As test materials, we select 25 materials with diverse symmetries and a wide range of lattice thermal conductivities between 10 -1 and 10 3 Wm -1 K -1 . Among various choices of training sets, we find that molecular dynamics trajectories at 50–700 K consistently provide results at par with DFT for the test materials. In contrast to pure DFT approaches, the computational cost in the present approach is uniform over the test materials, yielding a speed gain of 2–10 folds. When a smaller reduced training set is used, the relative efficiency increases by up to ~50 folds without sacrificing accuracy significantly. The current work will broaden the application scope of machine learning potentials by establishing a robust framework for accurately computing lattice thermal conductivity with machine learning potentials.

36 MATERIALS SCIENCE↗

Secondary Frequency Regulation from Variable Generation through Uncertainty Decomposition: An Economic and Reliability Perspective

The rapid integration of variable generation (VG), such as photovoltaics (PV), necessitates an increase in the secondary frequency regulation (SFR) to handle the system intra-dispatch interval imbalance because of VG's variation. Although PV has the control capability to provide SFR, the main challenge is in guaranteeing the delivery of PV's energy and SFRs capacities in the automatic generation control (AGC) within each dispatch interval considering its uncertainty. This paper proposes a deliverable VG SFR provision model with endogenous VG's power uncertainty decomposition. First, the uncertainty of VG is decomposed using distributionally robust chance constraints through which the deliverable SFR provision is guaranteed. Next, the intra-interval frequency response of PV's SFR is validated with a user defined AGC model including the PV power plant. Finally, the economic benefits and the reliability improvements such as the frequency deviation reduction with PV providing SFRcan be integrated and evaluated. The proposed model is tested in a modified 18-bus system and in the Western Electricity Coordinating Council test system. Results demonstrate that with the deliverable SFR from PV, the system cost and the frequency reliability can be improved simultaneously. PV's SFR performance can be guaranteed with the proposed model.

14 SOLAR ENERGY↗

A Rechargeable Carbon-Oxygen Battery for Efficient, Low-Cost Energy Storage

As part of the Cyclotron Road program, Noon Energy Inc investigated the feasibility of a new class of rechargeable flow battery for long-duration energy storage at the 100+ hour storage capacities needed to make intermittent solar/wind power available 24/7 year-round. Whereas conventional batteries store energy in relatively expensive metals like cobalt, lithium, and vanadium, the new battery stores energy in abundant, ultra-low-cost carbon and oxygen, storage media that cost well below $1 per kWh capacity (less than the cost of their containers). It also can operate with a high roundtrip energy efficiency of ~80% and has 10x higher energy density than conventional aqueous flow batteries, even higher than lithium ion batteries at system level. These properties make it suitable for a variety of potential stationary energy storage applications as well as for electric transportation vehicles (long-haul marine shipping and trucking), so determining the best product-market fit and market entry was a key outcome of Noon’s Cyclotron Road fellowship. Noon had demonstrated initial materials development and proof-of-principle testing before the fellowship. Overall, within the fellowship Noon carried out key initial technology development in market applications, system design, risk assessment and prototyping.

25 ENERGY STORAGE↗

Performance Testing of the 4kW ESR 2 Refrigerator at JLab

Abstract The End Station Refrigerator 2 (ESR2), a refurbished cryoplant, will replace the ESR1. ESR2 is comprised of the cold box and compressors from the Superconducting Super Collider’s 4 kW, 4.5 K ASST-A plant. It also features a new 10 kL liquid helium dewar, a cryogenic distribution system and new control and utility systems. This plant was reconfigured to provide a cold helium supply at 15 K, 12 K, and 8 K for the experimental hall’s hydrogen targets. The most significant load will be during the MOLLER experiment, which will see a total hydrogen target load of 5 kW at 15 K. This paper details the commissioning results of the 4.5 K refrigeration system in various modes (maximum refrigeration, maximum liquefaction, and a 50/50 mix) at both 100 % and 50 % capacity. We will also evaluate the performance with an expected MOLLER load. Current performance will be compared with the historical commissioning data from the ASST-A plant.

Perry, C. [Cryogenics Department, Thomas Jefferson↗

Paleotribological models using preserved fossil tissue properties reveal functional significance of Eurasian mammoth dental evolution

Eurasian mammoths (Mammuthus) underwent substantial modifications in molar morphology as later-diverging species evolved progressively thinner enamel and increased enamel crest complexity. These features have been hypothesized to reduce whole-tooth wear and extend dental longevity as increasingly graze-dominated diets evolved within the lineage. This hypothesis has yet to be directly tested. Here, in this study, we developed an in-silico wear model using experimentally derived wear rates from fossil and extant proboscidean dental tissues. The models revealed that shifts in tissue topology do not affect whole-tooth wear rate, as inverse trends in lamellar frequency and enamel thickness preserve a consistent surface enamel area fraction; the determining factor of wear. Rather, topological shifts produce a wear-emergent secondary occlusal surface with greater numbers of triturating crests that create a regular, low-relief, file-like shearing pavement. These changes in occlusal architecture likely directly impacted the mastication capacity of Mammuthus dentitions, facilitating their dietary expansion to incorporate fibrous, lower-nutrient graze.

Dental wear↗

Highly Reversible Plating/Stripping of Porous Zinc Anodes for Multivalent Zinc Batteries

Zinc continues to garner immense interest due to its versatility as an anode material in several configurations utilizing either alkaline or mild-pH electrolytes. Current research on using mild-pH electrolytes has improved the rechargeability aspect of Zn-based batteries since Zn2+ is solely utilized for plating/stripping of Zn. Several studies have incorporated Zn metal foils, yet, dramatic improvements can be achieved by expressing Zn as a porous structure. Herein, we use a quasi-pulsed electrodeposition process to prepare a conformal Zn coating onto 3D porous copper foam. By tuning the electrodeposition parameters, we achieved an optimal Zn coating that undergoes reversible plating/stripping when tested in symmetric Zn cells, which supported a low overpotential of ~60 mV for up to 100 cycles. We further investigated changes in the surface morphology by studying the Zn surface of both foil and 3D structure using scanning electron microscopy and X-ray micro-computed tomography. Both techniques showed that the Zn foil undergoes dramatic alterations at the surface, which results in inhomogeneous deposition of Zn, whereas the 3D form exhibited minimal changes. Lastly, we paired both Zn foil and 3D Zn with vanadium oxide and demonstrated that the porous structure supports high rate capability and high specific capacity.

25 ENERGY STORAGE↗

DOE Cold Climate Heat Pump Challenge: Development, Metrics, and Early Field Observations

Space heating in residential buildings is a major contributor of Greenhouse Gas (GHG) emissions in the United States. New, advanced electric heat pumps are poised to provide a low carbon alternative to traditional fossil-based heating, especially in colder climates. Widespread deployment of cold climate heat pumps could help address the significant portion of building emissions and primary energy used in American households, but these gains will require broader acceptance from consumers and decision makers. As part of the “Energy, Emissions, and Equity” (E3) initiative, the U.S. Department of Energy launched the Cold Climate Heat Pump Challenge (CCHP) in 2021 to accelerate the deployment of the next generation of air source heat pumps. The Challenge is currently focused on residential, centrally ducted, electric heat pumps, with a nominal cooling capacity greater than or equal to 24,000 Btu/h (2 tons) and less than or equal to 65,000 Btu/h (5 tons). The Challenge specifications represent a best-in-class heat pump product that provides high-efficiency heating performance in cold climates, employs environmentally friendly low-Global Warming Potential (GWP) refrigerants, and is designed to be grid interactive. Spearheaded by DOE in partnership with the US Environmental Protection Agency (EPA) and Natural Resources Canada (NRCan), the CCHP Challenge brings together numerous major heat pump manufacturers and key stakeholders including utilities and state agencies across the country. In addition to performance testing in a laboratory environment, a key component of this research is evaluating the in-field performance of the prototype heat pumps developed as part of the Challenge. This paper will discuss the development of the CCHP Challenge, key performance specifications, and the energy and non-energy metrics that will be evaluated through the field study. The types of data that are being collected from the units installed in homes across North America as part of the field validation will be described, including details about the sensors and data acquisition system. Data cleaning and analysis methodologies will be discussed, along with early observations from the winter 2022-2023, spring and summer performance periods, and an assessment of non-energy metrics through pre- and post-installation homeowner surveys. Challenges uncovered and lessons learned throughout the process will also be discussed. Finally, the paper will discuss next steps for the second winter assessment period, areas needing additional research, and potential applications of the data collected and analyzed through this work.

Mendon, Vrushali V.↗

High-Frequency Signature-Based Fault Detection for Future MV Distribution Grids: Preprint

Increased deployment of Distributed Energy Resources (DERs) and microgrids are significantly changing the operation of distribution grid. Increasing penetration of power electronics based DERs also raise several operational problems such as protection coordination issues, voltage raise, recloser synchronization, stability, and frequency control. Legacy systems are designed for unidirectional power flow. Bidirectional power flows, and varying short circuit levels are some of the major challenges in implementing these legacy protection schemes for future power grid with high penetration of power electronics based DERs. Inverter based DER’s can contribute to a maximum of 2 p.u. fault current. Interconnection standards might require even lower fault current contribution. If these protection related challenges are not addressed, it will result in limiting the penetration of DERs in distribution feeders. In this paper, the feasibility of high frequency signature generated by transients is evaluated to identify and locate faults in a distribution system. The paper will discuss the need for an accurate line modeling approach to accurately capture the high frequency signatures. These high frequency signatures are naturally occurring electromagnetic transients for events such as switching events in the network, faults events, etc. This is different than that implemented in transmission systems as the proposed approach utilizes advanced signal processing techniques to retrieve valuable information from the high frequency signatures generated during faults and does not just rely on time delay measurements between reflections of the high frequency signals. In the full paper, information of a modified IEEE distribution feeder test system to accurately model the high frequency signatures will be provided. The distribution lines will be modeled using universal line modeling (ULM) technique in an electromagnetic transients program (EMTP) modeling platform. Different test cases will be simulated and these test cases will include different fault types, multiple fault locations, capacitor bank switching, etc. The feeder system modeled for these simulations will also include power electronics based DERs. Additionally, experimental results demonstrating the high frequency signatures generated due to a transient event in a medium voltage (13.8 kV) distribution line will also be presented in the full paper. Furthermore, the analysis combined with simulation and experimental results in the full paper will help demonstrate the feasibility and efficacy of the proposed protection scheme. The developed protection scheme will not just help solve problems generated by bidirectional current flow, varying short-circuit current capacity, but also help in proliferation of DERs in distribution systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Cold Climate Integrated Heat Pump with Energy Storage for Grid-Responsive Control

An air-source integrated heat pump (ASIHP) is a multifunctional unit, capable of space cooling, space heating, and water heating. We developed a packaged cold climate ASIHP, using a multi-stage compressor, capable of working down to -25°C, and providing 100% rated capacity down to -15°C with a heating COP > 2.2. An innovative system configuration and related controls were developed to solve charge balance in the integrated heat pump, smooth charge migration, and mode transition among multiple working modes. Extensive laboratory investigations for individual modes were performed to verify the performance. Its integrated heating capability provides speedy water heating to meet domestic hot water use and store heating energy in a phase change material ceiling/panel. The heating energy storage can be used to shift the load when the electricity price is high. Based on the performance data and a calibrated model from the laboratory testing, we conducted building energy simulations driven by a model predictive control, using EnergyPlus in one U.S. cold climate zone to investigate the grid-responsive control strategy and estimate the utility cost reduction potential.

Shen, Bo↗

Insights into the Effect of Heat Treatment and Carbon Coating on the Electrochemical Behaviors of SiO Anodes for Li-Ion Batteries

The use of SiO as an anode material has attracted significant interest due to its high capacity and long cycling life. Many promising approaches, including structural design and carbon coating at high temperatures, effectively improve its intrinsic low electrical conductivity and poor Coulombic efficiency. However, the “heat treatment process-composition and microstructure-electrochemical properties” relationship of the SiO anode is not fundamentally understood. Here the structure and composition evolution in amorphous SiO and graphene-coated SiO is investigated using different heat-treatment conditions. X-ray absorption near-edge structure techniques are also employed to analyze the surface and bulk composition change during the initial lithiation process, supplemented by physical or chemical characterization and electrochemical testing. Here results reveal the structural transition of SiO during heat treatment, from amorphous to disproportionated hierarchical structure, where the as-formed dielectric exterior SiO 2 shell and interior SiO 2 matrix severely polarizes electrodes, hindering the lithiation process. Carbon coating on SiO effectively restricts the growth of the SiO 2 shell and facilitates charge transfer, leading to improved electrochemical performance. A schematic model is proposed to reveal the relationship between the treatments, the resultant structural evolutions, and corresponding electrochemical behaviors.

36 MATERIALS SCIENCE↗

High-Temperature Active Magnetic Bearing Development for Supercritical CO 2 Machinery Applications

Hermetic machinery utilizing gas bearings for MW-scale supercritical CO 2 (sCO 2 ) machinery applications can have significantly lower power loss and enable improved cycle efficiency compared to conventional machinery with oil-lubricated bearings. Active magnetic bearings (AMBs) are another option anticipated to have similar power loss and load capacity to gas bearings as well as offering larger mechanical tolerances, the ability to tune properties, and high reliability due to lack of mechanical wear. AMBs also have proven commercial experience at MW-scale, though environments for high-temperature sCO 2 power cycle machinery conditions are novel. Besides the potential impact of AMBs for sCO 2 turbomachinery, the technology also offers promising benefits for steam and gas turbines for power generation, compressors and expanders for industrial heat and power, and in other oil and gas and space applications. The goals of this project were to conceptual design an AMB and perform material testing. Conceptual designs for radial and thrust AMBs were produced based on a hermetically-sealed sCO 2 machinery waste-heat recovery (WHR) application for sizing and loads, and choosing a target design temperature of 540°C useful for high-temperature sCO 2 turbines for concentrating solar power (CSP) applications. Conceptual designs were initially developed for multiple radial and thrust AMBs with spreadsheet-based calculations before selecting one of each to develop further using higher-fidelity design methods for magnetic and structural performance. It was found that the radial AMB at 540°C was feasible, but the thrust AMB needed to be limited to 315°C for high-speed operation. The decision for a reduced-temperature thrust AMB was the result of several significant conclusions: 1) Hiperco 50A, originally chosen for good magnetic performance at high temperature, had insufficient strength for high-speed operation, so it was replaced with 17-4 PH. 2) The reduced magnetic performance from 17-4 PH yielded a larger bearing size, reducing the strength margin. 3) This ultimately led to a creative design implementing a more-compact E-core topology, compared to the original (conventional) C-core, and an integral shaft-disk with Hirth joint connection. These conceptual designs are unique for the size and temperature in CO 2 , relevant for MW-scale CSP applications. Long term, high temperature test data was generated for several materials, filling a void in the current body of literature. Corrosion and magnetic performance measurements were produced for PM materials (Alnico 5-7C, Alnico 9C, and SmCo) with and without nickel-coating for environments of high-temperature CO 2 up to 550°C at atmospheric pressure and 450°C at 103 bar for up to 6,000 hours. Corrosion measurements were also produced for Hiperco 50, a SM material relevant for AMB laminations, with and without C5 coating. Comparisons were also made for 450°C and 550°C, atmospheric pressure air exposures up to 5,000 hours. Results generally show that coatings can be effective at improving oxidation resistance of the bare materials, and Alnicos generally outperformed SmCo after high-temperature exposure. In addition to technical feasibility demonstrated by the design, economic feasibility was demonstrated by updating the TEA from the reference machine, re-evaluating it with CAPEX and OPEX to reflect estimated changes from process-lubricated bearings to AMBs. AMBs were shown to be comparable in performance to process-lubricated bearings, still showing a notable improvement over conventional machinery architecture with oil-lubricated bearings.

42 ENGINEERING↗

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS): Task 6.0 Deliverable – CarbonSAFE Phase III Readiness

The OASIS CarbonSAFE Phase II Project OASIS (Optimizing Alabama’s CO 2 Storage in Shelby County) is a geologic and reservoir characterization study designed to evaluate deep saline formations for potential long-term carbon dioxide (CO 2 ) storage in central Alabama near the National Carbon Capture Center (NCCC) and Alabama Power’s Plant Gaston. The project centers on understanding the potential of the Cambro-Ordovician Knox Group and underlying strata such as the Conasauga and Rome Formations for geologic storage of CO 2 . These formations were investigated as part of SECARB-USA (DE-FE0031830) and Project OASIS through the drilling of two stratigraphic test wells to obtain electronic well logs, core, and sidewall core plugs. These data provide direct measurements of porosity, permeability, and lithologic variability critical for reservoir characterization. Complementing the well program, a limited 2D seismic survey was conducted to help select the site for Westover #2 as part of SECARB-USA (DE-FE0031830), and a more regional Seismic Exchange (SEI) seismic survey was licensed and interpreted to define structural and stratigraphic frameworks in a new Static Earth Model (SEM), map reservoir continuity, and to identify potential sealing intervals. Integrated with geologic and reservoir modeling, these datasets form the basis for evaluating storage capacity, injectivity, and containment. While this document endeavors to provide readers with a high-level overview of Project OASIS activities and its suitability for subsequent CarbonSAFE Phases, such as a Phase III effort. Other project deliverables and milestones will provide more details on individual subjects.

20 FOSSIL-FUELED POWER PLANTS↗

Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets

This dataset contains turbine- and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in Steady State (FLORIS) model, version 2.3.0. The 252,500 cases include 500 unique wind plants generated randomly by a specialized Plant Layout Generator (PLayGen) that samples randomized realizations of wind plant layouts from one of four canonical configurations: (i) cluster, (ii) single string, (iii) multiple string, (iv) parallel string. Other wind plant layout parameters were also randomly sampled, including the number of turbines (25-200) and the mean turbine spacing (3D-10D, where D denotes the turbine rotor diameter). For each layout, 500 different sets of atmospheric conditions were randomly sampled. These include wind speed in 0-25 m/s, wind direction in 0 deg.-360 deg., and turbulence intensity chosen from low (6%), medium (8%), and high (10%). For each atmospheric inflow scenario, the individual turbine yaw angles were randomly sampled from a one-sided truncated Gaussian on the interval 0 deg.-30 deg. oriented relative to wind inflow direction. This random data is supplemented with a collection of yaw-optimized samples where FLORIS was used to determine turbine yaw angles that maximize power production for the entire plant. To generate this data, a subset of cases were selected (50 atmospheric conditions from 50 layouts each for a total of additional 2,500 cases) for which FLORIS was re-run with wake steering control optimization. The IEA onshore reference turbine, which has a 130 m rotor diameter, a 110 m hub height, and a rated power capacity of 3.4 MW was used as the turbine for all simulations. The simulations were performed using NREL's Eagle high performance computing system in February 2021 as part of the Spatial Analysis for Wind Technology Development project funded by the U.S. Department of Energy Wind Energy Technologies Office. The data was collected, reformatted, and preprocessed for this OEDI submission in May 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub repository under explore_wind_plant_data_h5.ipynb.

AI↗

The Role of Electrolyte Composition in Enabling Li Metal‐Iron Fluoride Full‐Cell Batteries

Abstract FeF 3 conversion cathodes, paired with Li metal, are promising for use in next‐generation secondary batteries and offer a remarkable theoretical energy density of 1947 Wh kg −1 compared to 690 Wh kg −1 for LiNi 0.5 Mn 1.5 O 4 ; however, many successful studies on FeF 3 cathodes are performed in cells with a large (>90‐fold) excess of Li that disguises the effects of tested variables on the anode and decreases the practical energy density of the battery. Herein, it is demonstrated that for full‐cell compatibility, the electrolyte must produce both a protective solid‐electrolyte interphase and cathode‐electrolyte interphase and that an electrolyte composed of 1:1.3:3 (m/m) LiFSI, 1,2‐dimethoxyethane, and 1,1,2,2‐tetrafluoroethyl‐2,2,3,3‐tetrafluoropropyl ether fulfills both these requirements. This work demonstrates the importance of verifying electrode level solutions on the full‐cell level when developing new battery chemistries and represents the first full cell demonstration of a Li/FeF 3 cell, with both limited Li and high capacity FeF 3 utilization.

25 ENERGY STORAGE↗

Effects of surface runoff and infiltration partition methods on hydrological modeling: A comparison of four schemes in two watersheds in the Northeastern US

The ratio according to which the precipitation/snowmelt is divided into surface and subsurface water is of primary importance to watershed scale hydrological modeling. The present study compared four different surface runoff and infiltration partition methods in the Richards-equation-based SWAT model (RSWAT), i.e., daily curve number method (DC-RSWAT), hourly curve number method (HC-RSWAT), Green-Ampt method (GA-RSWAT), and effective infiltration capacity method (EIC-RSWAT). These four versions of RSWAT and a daily-curve-number-based SWAT (DC-SWAT) were used to simulate daily flow rate (from 2001 to 2015) at the outlets of the Tuckahoe Creek Watershed (TCW) and Greensboro Watershed (GW) of the Chesapeake Bay in Maryland. Parameter sensitivity analysis, calibration, and prediction uncertainty analysis were conducted. The results indicate that surface runoff and infiltration partition methods have pronounced impacts on model performance. Comparative analysis showed that DC-RSWAT outperformed other versions of RSWAT for both calibration (from 2001 to2007) and validation (from 2008 to 2015) periods in the two test watersheds. In general, DC-RSWAT achieved more accurate deterministic flow simulation and reliable uncertainty estimation than other versions. As such, daily-curve-number method is recommended for surface runoff and infiltration partition in RSWAT for simulating stream flow.

hydrology, modeling, streamflow↗