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At least 19 records

Log-N/Period Power Offset Sensitivity Calculation

This study focused on the calculation of sensitivity values for Channels 4 and 5 in the Log-N/Period system at the Advanced Test Reactor (ATR). The Log-N/Period system provides an indication of reactor power generation between criticality and full power. This indication is determined by the power offset and the current produced by the detector. Sensitivity values for Channels 4 and 5 were calculated using existing equations, documents, reactor startup data.

42 - ENGINEERING

Application of Ocean Thermal Energy Conversion (OTEC) Systems for Powering Safety Monitoring Systems of Offshore Oil and Gas Operations, OESI 2.0 M-1 T-1-P1.1 – Objective 3 Report: Collocation of OTEC with Offshore Oil and Gas Activities

This report is a component of a comprehensive research initiative aimed at evaluating the technoeconomic feasibility of deploying Ocean Thermal Energy Conversion (OTEC) systems to power safety monitoring systems for offshore oil and gas operations in the Gulf of America (GOA). The overarching study has three primary objectives: summarizing existing oil and gas equipment monitoring systems, modeling OTEC as a renewable marine energy source, and exploring the collocation of OTEC power sources with offshore oil and gas activities to offset power demand. This report specifically addresses Objective 3, focusing on the integration of OTEC systems with floating oil and gas facilities.

02 PETROLEUM

Application of Ocean Thermal Energy Conversion (OTEC) Systems for Powering Safety Monitoring Systems of Offshore Oil and Gas Operations. OESI 2.0 M-1 T-1-P1.1 – Objective 1 Interim Report: Summary of Offshore Oil and Gas Well Monitoring Systems and Process Power Requirements

This report is part of a comprehensive research initiative aimed at evaluating the technoeconomic feasibility of deploying greenhouse gas (GHG) emissions monitoring systems powered by small-scale renewable energy sources on the U.S. Outer Continental Shelf (OCS). The study has three primary objectives: summarizing available GHG monitoring systems for the OCS, modeling a renewable marine energy source (specifically ocean thermal energy conversion, or OTEC), and modeling the collocation of OTEC power sources with offshore oil and gas activities to offset power demand.

02 PETROLEUM

Dissimilar metal joining of Ti-6Al-4V and Inconel 625

The dissimilar joining of Ti-6Al-4V and Inconel 625 by using a suitable interlayer shows potential design flexibility by avoiding the brittle intermetallic phases from direct welding. These phases include NiTi , NiTi 2 , and Ni 3 Ti . The objective of this work is to facilitate laser welding of Ti-6Al-4V and Inconel 625 through a vanadium interlayer to form an intermetallic free, strong, and corrosion resistant joint. Vanadium was chosen based on binary phase diagram solubilities, literature, and theoretical CalPhaD calculations in PanDat. Laser welding was systematically explored from based on beam mode, offset, power, and scan speed. Varied parameters include laser power from 325 to 650 watts, laser scan speed from 80 to 160 in/min, and beam offset up to a ¼ of the beam diameter. Parameters were chosen based on previous dissimilar joining research and those found in the literature. Metallography, including optical and scanning electron microscopy, was used to analyze the weld chemical composition, grain structure, and defects through both the fusion and heat affected zones. The results and discussion will examine the relationship between process parameters, microstructure, and observed weld defects. Our findings will not only assess the weldability of vanadium and Inconel 625 but also establish a transferable framework for studying other dissimilar material combinations, providing valuable insights for future research in this field.

36 MATERIALS SCIENCE

Utility-Scale Solar, 2024 Edition: Empirical Trends in Deployment, Technology, Cost, Performance, PPA Pricing, and Value in the United States [Slides]

Berkeley Lab’s “Utility-Scale Solar, 2024 Edition” presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC (PV plants of 5 MWAC or less, including residential rooftop systems, are covered separately in Berkeley Lab’s companion annual report, Tracking the Sun). Key findings from this year’s report include: -18.5 GWAC of new utility-scale PV capacity came online in 2023, bringing cumulative installed capacity to more than 80.2 GWAC across 47 states. Installed costs continued to fall in 2023. Relative to 2022, capacity-weighted averages decreased by 8% to -$\$1.43$/WAC (or $\$1.08$/WDC). Costs, based on a 7.1 GWAC sample of 76 plants completed in 2023, have fallen by 75% (averaging 10% annually) since 2010. Plant-level capacity factors vary widely, from 6% to 36% (on an AC basis), with a sample median of 24%. -Levelized cost of energy (LCOE) of new 2023 projects increased slightly to $\$46$/MWh prior to the application of tax credits but continued to fall to $\$31$/MWh when accounting for federal incentives. PPA prices have largely followed the decline in solar’s LCOE over time, but newly signed longer-term PPA prices have increased since 2021, to an average of $\$35$/MWh (levelized, in 2023 dollars). -Solar’s average energy and capacity value (i.e., ability to offset costs of other power generation sources) across the U.S. was $\$45$/MWh in 2023. Solar’s average market value was lowest in CAISO ($\$27$/MWh), the market with the greatest solar generation share, and highest in ERCOT ($\$67$/MWh). -Newer solar projects had greater market value in 2023 than their generation costs, yielding $\$1.1$ billion in benefits. Projects built in 2022 delivered on average $\$15$/MWh more market value than their costs in 2023. -Solar’s combined value from wholesale electricity markets, public health and climate damage reduction were greater than generation costs and incentives, yielding $\$13.7$ billion in net benefits in 2023. We estimate U.S. health benefits of $\$24$/MWh and reduced global climate damages of $\$101$/MWh. -Adding battery storage is one way to increase the value of solar. Deployment of 52 new PV+battery hybrid plants set a record with 5.3 GW installed in 2023. Our public data file tracks metadata and PPA prices from more than 100 PV+battery hybrid projects that are already online or that have secured offtake arrangements. -Looking ahead, a massive pipeline of at least 1,085 GW of solar capacity dominates the nation’s interconnection queues at the end of 2023. Nearly 571 GW, or 53%, of that total was paired with a battery – in CAISO it was a staggering 98%. Historically only 10% of the requested solar capacity is built. -For more information, and to explore related interactive data visualizations, go to utilityscalesolar.lbl.gov.

14 SOLAR ENERGY

Frequency-domain modeling of floating wind arrays with shared mooring lines

A frequency-domain model for floating wind turbine dynamics has been extended to model floating wind farms with couplings from shared mooring systems. The model, called RAFT, could previously calculate the mean offsets and wave-induced response spectra for single floating wind turbines. Now, the model supports multiple floating wind turbines, each with their own properties and responses, along with mooring lines that run directly between floating wind turbines in the array, meaning that shared mooring lines or fully suspended dynamic power cables can be included. This capability is achieved by setting up an array-level solution of the system mean offsets and assembling the full system matrices for solving the dynamic response. The quasi-static mooring model MoorPy is used to linearize the mooring system properties. To compute the floating wind turbine relative motions, phase offsets are applied to each turbine's response as a function of wave frequency based on the wavelength and relative positions in the array. These differential motions are then applied to mooring system tension Jacobians to compute the tension loads in the shared mooring lines. Overall, the capability provides a frequency-domain analog to the modeling capabilities of the floating support structure in FAST.Farm. Mean offsets and power spectral density plots of responses are compared between RAFT and FAST.Farm to verify the implementation. The results indicate good agreement within the expectations of a frequency-domain modeling approach and suggest correct implementation of the shared mooring aspects. Additionally, a unique comb-like frequency response in the shared mooring line tensions has been observed. This phenomenon has a clear physical basis and may be an important design consideration for future shared mooring systems.

17 WIND ENERGY

Biochemical Conversion of Herbaceous Biomass to Renewable Diesel: Net Greenhouse Gas and Air Pollutant Trade-offs

This study examines greenhouse gas (GHG) and criteria air pollutant (CAP) emissions trade-offs for renewable diesel across 12 scenarios, involving different biochemical conversion designs, biorefinery scales, and feedstocks. A conventional design uses lignin for on-site heat and power, which exports excess power to the grid. An alternative design exports lignin pellets, offsetting other pellet production methods but requiring grid electricity to meet biorefinery power demands. Net emissions were quantified in Iowa and Georgia, selected considering feedstock availability, coproduct displacement, and regional power grids, assuming grid-exported power avoids coal or low-carbon electricity. Results for the conventional design remained consistent across the electricity displacement scenarios. When comparing lignin utilization strategies, pelletizing lignin reduces sulfur dioxide, carbon monoxide, nitrogen oxides, and volatile organic compounds (net emissions –0.66 mg MJ –1 , 25 mg MJ –1 , 25 mg MJ –1 , 7.8 mg MJ –1 , respectively). However, lignin pelletization increases net particulate matter (fine and coarse) and ammonia (net emissions of 4.7 mg MJ –1 , 13 mg MJ –1 , and 0.26 mg MJ –1 , respectively), alongside indirect GHG emissions due to grid electricity dependence. Additionally, processing 2000 tonnes corn stover daily minimizes emissions for both designs. Only lignin pelletization with renewable electricity and additional particulate matter and ammonia controls reduces all CAP and GHG emissions simultaneously.

09 BIOMASS FUELS

A Gaussian Process-Based extended Goldak heat source model for finite element simulation of laser powder bed fusion additive manufacturing process

In this study, laser powder bed fusion (L-PBF) additive manufacturing (AM) is a key enabling technology to manufacture highly complex and integrated metallic structures. In L-PBF AM process, the melting of the metal powders and the layers underneath can be governed by either “conduction mode” or “keyhole mode”, with the keyhole mode reportedly leading to porosity and decreased strength and ductility by many studies. In part scale simulations, finite element (FE) model is often used to study the temperature distribution during printing and to predict the residual stress, where a volumetric heat flux with a Gaussian or a double ellipsoidal (Goldak) distribution is often applied as the laser heat source. However, the above heat source models can only capture the melt pool shape in the conduction mode, and fail to capture the transition to keyhole melting mode when the process parameters change. To overcome this inaccuracy, an extended Goldak heat source model is proposed by introducing a laser penetration term as a function of laser parameters obtained from a Gaussian-Process (GP) model. The model is validated by “2D pad” AlSi10Mg L-PBF experiments under a wide range of laser power, scan speed, and laser focus offset, and the results show the model successfully captures the measured melt pool shape in all conditions.

36 MATERIALS SCIENCE

Coupled modeling of wake steering and platform offsets for floating wind arrays

Wake effects are a key challenge in the design and analysis of wind farms. For floating wind farms, the platforms offset under the aerodynamic loading of the turbine and are constrained by mooring systems that can vary significantly in allowable offsets. When considering wake steering, the crosswind offset of the turbine can counteract the lateral deflection of the wake. This work presents a tool to efficiently model the coupled impacts of wake steering and platform offsets for floating wind farms. The tool relies on the frequency-domain wind farm model RAFT and the steady-state wake model FLORIS. A verification with FAST.Farm is presented, then the tool is applied to a simple two-turbine case study. A range of mooring systems with increasing platform offsets and varied yaw misalignment angles are considered while comparing the impact on turbine power. Additional sensitivities to turbine spacing and mooring system orientation are explored. The results show that there is a least-optimal watch circle width for downwind turbine power production that varies with yaw misalignment angle and turbine spacing. Additionally, the turbine offsets under yaw-misaligned conditions vary significantly depending on mooring system orientation relative to the rotor plane, which in turn impacts the optimal misalignment angle. These results highlight the importance of including floating platform offsets and mooring systems in the evaluation of wake steering strategies for floating wind arrays.

17 WIND ENERGY

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing

Challenges of standard halo models in constraining galaxy properties from cosmic infrared background anisotropies

The halo model, combined with halo occupation distribution (HOD) prescriptions, is widely used to interpret cosmic infrared background (CIB) anisotropies and extract physical information about star-forming galaxies and their connection to large-scale structures. Recent CIB-specific implementations of the halo model have adopted more physical parameterizations. However, the extent to which these models can reliably recover meaningful physical parameters remains uncertain. We assessed whether the current parameterization of CIB halo models is sufficient to recover astrophysical quantities, such as star formation efficiency, η(M h , z), and halo mass at which the peak of star formation efficiency occurs, M max , when fit to mock data. We also assessed whether discrepancies arise from assumptions about galaxy emission (the HOD ingredients) or from more fundamental components in the halo model, such as bias and matter clustering. We fit the M21 CIB HOD model, implemented within the halo model framework, to mock CIB power spectra and star formation rate density (SFRD) data generated from the SIDES-Uchuu simulation, and compared the best-fit parameters to the known simulation inputs. We then repeated the analysis using a simplified version of the simulation (SSU), explicitly designed to match the HOD assumptions. A detailed comparison of model and simulation outputs was carried out to trace the origin of observed discrepancies. While the M21 HOD model provides a good fit to the mock data, it failed to recover the intrinsic parameters accurately, particularly the halo mass at which star formation efficiency peaks. This mismatch persists even when fitting data generated with the same model assumptions. We find strong agreement (within 5%) in the emission-related components (SFRD, emissivity), but observe a scale- and redshift-dependent offset exceeding 20% in the two-halo term of the CIB power spectrum. This likely arises from limitations in the treatment of halo bias and matter clustering within the linear approximation. Additionally, incorporating scatter in the SFR–halo mass relation and the spectral energy distribution (SED) templates significantly affects the shot noise (∼50%), but has only a modest impact (less than 10%) on the clustered component. These results suggest that recovering physical parameters from CIB clustering requires improvements to the cosmological ingredients of the halo model framework, such as adopting scale-dependent halo bias and nonlinear matter power spectra in addition to careful modeling of emission physics.

cosmic background radiation

Hydrogen-Battery Hybrid Energy System on Repurposed Offshore Platforms for Efficient Clean-Energy Transition

Due to the rising global energy demand and enhanced awareness of the environmental impact of fossil fuels, the Gulf of Mexico, traditionally known for oil extraction, offers a distinct chance to repurpose the existing offshore infrastructure. With the depletion of oil reserves, it is feasible to adapt previously utilized floating platforms for extraction to generate renewable energy, specifically through wind-generated power and hydrogen production. This adaptation seeks to promote a transport system that is more ecologically friendly in the future. Offshore wind turbines serve as the main energy source, with help from battery storage and hydrogen production to enhance the overall system performance, hydrogen creation, fuel, and electricity delivery for sustainable energy production. The system is divided into two distinct cases, each evaluated for cost, performance, and feasibility, with a focus on minimizing both the Levelized Cost of Energy (LCOE) and the Levelized Cost of Hydrogen (LCOH). The first case examines the integration of offshore wind turbines with hydrogen production. Excess electricity generated by wind turbines is directed toward hydrogen production via electrolysis. The hydrogen produced can be used as fuel for vehicles or transported to the shore via pipelines. The second case investigates a technology that combines wind turbines with battery storage. The batteries possess an ability to supply electricity for a continuous duration of 4 hours maximum each day. The main objective is to reduce the LCOE by considering the battery's charging and discharging cycles, together with the uncertain attributes of wind power and battery deterioration. The produced energy can be distributed for onshore applications or utilized for the purpose of offsetting offshore loads such as subsea oil and gas production, transportation, etc. The offshore hydrogen-battery hybrid system is improved via three advanced algorithms, Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). In Case 1, PSO improves hydrogen production by efficiently managing the electrolyzer’s power consumption, decreasing production costs significantly. Particle Swarm Optimization (PSO) is applied to improve the efficiency of the electrolyzer, reducing production costs and achieving an optimized CAPEX of $240.00 million (from an initial $300.00 million) and OPEX of $9.60 million per year. This system produces 4,720,000 kg of hydrogen annually, with a Levelized Cost of Hydrogen (LCOH) of $6.40/kg and an annual profit of $9.27 million. In Case 2, GWO effectively reduces the overall energy cost by improving the charge-discharge management of batteries, which extends battery life and optimizes their use. The second case focuses on integrating battery storage, optimized using the Grey Wolf Optimizer (GWO), which enhances battery charge-discharge cycles, extending battery life and lowering costs. This system achieves an optimized CAPEX of $204.80 million (from an initial $256.00 million) and OPEX of $9.29 million per year, producing 310883.39 MWh of electricity annually at a Levelized Cost of Energy (LCOE) of $86.13/MWh, with an annual profit of $6.25 million. The implementation of a comprehensive strategy results in a substantial reduction in costs, improved energy efficiency, and a dependable supply of both electric power and hydrogen, emphasizing the benefits of converting offshore oil platforms for clean energy transition. This study explores a clean strategy to enable cost-effective repurposing of offshore O&G platforms. Both cases highlight the economic and technical feasibility of transitioning offshore oil platforms to clean energy systems, demonstrating substantial cost reductions and reliable energy and hydrogen supplies for sustainable energy production.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

FLAMINGO: combining kinetic SZ effect and galaxy–galaxy lensing measurements to gauge the impact of feedback on large-scale structure

Energetic feedback processes associated with accreting supermassive black holes can expel gas from massive haloes and significantly alter various measures of clustering on $\sim$Mpc scales, potentially biasing the values of cosmological parameters inferred from analyses of large-scale structure (LSS) if not modelled accurately. Here, we use the state-of-the-art FLAMINGO suite of cosmological hydrodynamical simulations to gauge the impact of feedback on large-scale structure by comparing to Planck + ACT stacking measurements of the kinetic Sunyaev–Zel’dovich (kSZ) effect of SDSS BOSS galaxies. We make careful like-with-like comparisons to the observations, aided by high precision KiDS and DES galaxy–galaxy lensing measurements of the BOSS galaxies to inform the selection of the simulated galaxies. In qualitative agreement with several recent studies using dark matter only simulations corrected for baryonic effects, we find that the kSZ effect measurements prefer stronger feedback than predicted by simulations which have been calibrated to reproduce the gas fractions of low redshift X-ray-selected groups and clusters. We find that the increased feedback can help to reduce the so-called $S_8$ tension between the observed and CMB-predicted clustering on small scales as probed by cosmic shear (although at the expense of agreement with the X-ray group measurements). However, the increased feedback is only marginally effective at reducing the reported offsets between the predicted and observed clustering as probed by the thermal SZ (tSZ) effect power spectrum and tSZ effect – weak lensing cross-spectrum, both of which are sensitive to higher halo masses than cosmic shear.

79 ASTRONOMY AND ASTROPHYSICS

Reconstruction of the BNB and NuMI Neutrino Bunch Structure with ICARUS

ICARUS serves as the Far Detector of the Short Baseline Neutrino (SBN) program at Fermilab, sitting on-axis on the Booster Neutrino Beam (BNB) and 6$^\circ$ off-axis from the Neutrinos at the Main Injector (NuMI) beam. Neutrinos from both beams inherit the timing sub-structure of their parent proton spills, which is in turn derived from either the Booster's or the Main Injector's synchrotron acceleration. Since neutrino propagation introduces only a constant offset, their timing structure is preserved as they travel. Identifying this structure in data represents a powerful tool for selecting neutrino events and searching for physics beyond the Standard Model (BSM). This poster presents the preliminary reconstruction of the BNB and NuMI neutrino bunch structure with ICARUS data, exploiting only the precise timing of ICARUS optical readout system to both locate and assign a time to each interaction.

43 PARTICLE ACCELERATORS

Reconstruction of the BNB and NuMI Neutrino Bunch Structure with ICARUS

ICARUS serves as the Far Detector of the Short Baseline Neutrino (SBN) program at Fermilab, sitting on-axis on the Booster Neutrino Beam (BNB) and 6$^\circ$ off-axis from the Neutrinos at the Main Injector (NuMI) beam. Neutrinos from both beams inherit the timing sub-structure of their parent proton spills, which is in turn derived from either the Booster's or the Main Injector's synchrotron acceleration. Since neutrino propagation introduces only a constant offset, their timing structure is preserved as they travel. Identifying this structure in data represents a powerful tool for selecting neutrino events and searching for physics beyond the Standard Model (BSM). This poster presents the preliminary reconstruction of the BNB and NuMI neutrino bunch structure with ICARUS data, exploiting only the precise timing of ICARUS optical readout system to both locate and assign a time to each interaction.

43 PARTICLE ACCELERATORS

Performance Characterization of InCharge™ ICE-66 V2X Bidirectional DC Fast Charger

Vehicle-to-grid (V2G) technology extends the role of Plug-in Hybrid Vehicle’s (PHEV) and Battery Electric Vehicle’s (BEV) batteries beyond transportation by enabling bidirectional power transfer between the vehicle's onboard energy storage and the utility grid. Modern battery-powered vehicles are equipped with high-capacity battery packs that remain stationary and underutilized for the majority of their operational life. A vehicle used for daily commuting may be parked and connected to charging infrastructure for 18–20 hours per day, representing a significant untapped energy resource. When considered at scale, the aggregated storage capacity of a modest fleet of 10–15 vehicles within a single parking facility can reach the MWh range, sufficient to partially offset peak demand for a mid-size commercial building or contribute meaningful ancillary services to the local grid. The ability to charge during off-peak periods when electricity prices are low and discharge during peak demand when prices are high positions EV batteries as distributed energy arbitrage assets, with the potential to offset vehicle ownership and charging costs. Beyond energy arbitrage, V2G-capable assets can provide ancillary grid services through active and reactive power injections. Active power supports grid frequency regulation, while reactive power supports local voltage regulation. Together, these capabilities establish V2G as a technically promising and economically relevant pathway toward greater integration of battery-powered vehicles into the broader energy system.

33 ADVANCED PROPULSION SYSTEMS

Filter-Banks for Ultra-Wideband Communications, Sensing, and Localization

Recently, filterbank multi-carrier spread spectrum (FBMC-SS) has been proposed as a candidate waveform for ultrawideband (UWB) communications. It has been noted that FBMCSS is a perfect match to this application, leading to a trivial method of matching to the required spectral mask at different regions of the world. FBMC-SS also allows easy rejection of high-power interfering signals that may appear over different parts of the UWB spectral band. In this paper, we concentrate on the use of staggered multitone spread spectrum (SMT-SS) for UWB communications. SMT makes use of offset QAM modulation to transmit data symbols over narrowband, overlapping subcarrier bands. This form of FBMC-SS is well-suited to UWB communications because it has good spectral efficiency and a flat power spectral density (PSD), resulting in good utilization of the UWB spectral mask. Additionally, we explore new methods for multi-coding that result in higher bit rates than previous FBMCSS systems. Moreover, we study methods for equalizing the UWB multipath channel and cancelling narrowband interference. Excellent performance of the proposed methods are substantiated by presenting simulation results.

99 - GENERAL AND MISCELLANEOUS

Floating Solar at Lima's Twin Lakes Reservoir

The City of Lima, Ohio is developing a floating photovoltaic (FPV) facility on the surface of Twin Lake Reservoir, adjacent to the City’s water treatment plant. The FPV array is designed with a capacity of 2 megawatts (MW) and will consist of approximately 3,500 solar panels spanning more than four acres of water surface. Based on regional solar conditions, the system will generate 2,000 megawatt-hours (MWh) of electricity annually. While the FPV system will interconnect to the electrical infrastructure serving the water treatment plant, power produced by the system will be net-metered through the utility grid, with energy credits applied to offset the plant’s overall electrical demand rather than directly supplying all plant loads in real time.

14 SOLAR ENERGY