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DOE OSTI2024

Offshore wind and wave energy can reduce total installed capacity required in zero-emissions grids

Abstract As the world races to decarbonize power systems to mitigate climate change, the body of research analyzing paths to zero emissions electricity grids has substantially grown. Although studies typically include commercially available technologies, few of them consider offshore wind and wave energy as contenders in future zero-emissions grids. Here, we model with high geographic resolution both offshore wind and wave energy as independent technologies with the possibility of collocation in a power system capacity expansion model of the Western Interconnection with zero emissions by 2050. In this work, we identify cost targets for offshore wind and wave energy to become cost effective, calculate a 17% reduction in total installed capacity by 2050 when offshore wind and wave energy are fully deployed, and show how curtailment, generation, and transmission change as offshore wind and wave energy deployment increase.

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

Virtual tower measurements during the American WAKE ExperimeNt (AWAKEN)

Dual-Doppler lidar measurements were made during the American WAKE ExperimeNt to provide height-resolved measurements of wind speed and direction at multiple locations immediately south of the leading row turbines in the King Plains wind farm in Oklahoma. These so-called virtual tower measurements were performed to characterize the inflow into the wind farm and to assess possible upwind blockage effects due to the collective action of the wind farm. The campaign was conducted from 12 November 2022 to 17 October 2023, during which time 14 unique virtual tower locations were sampled with heights ranging from 240 to 490 m AGL. The wind retrieval algorithm provided estimates of the horizontal winds and their uncertainties with a vertical resolution of about 10 m, while also accounting for the tilt of the lidar platform. The virtual tower results are compared to collocated lidar wind profiling data at the A1 site, which was located roughly 2.4 rotor diameters south of the nearest turbine. The wind speed difference between the wind profiler and the virtual tower was found to be quite sensitive to atmospheric stability and wind direction below 250 m AGL. The largest differences were observed for inflow under stable conditions, where the profiler wind speeds were observed to be about 22% lower than the virtual tower near hub height. These results suggest that there are persistent horizontal gradients in the flow upwind of the wind farm which result in biased estimates using standard ground-based lidar wind profiling methods.

17 WIND ENERGY↗

DOE OSTI2025

SPIKANs: separable physics-informed Kolmogorov–Arnold networks

Physics-Informed Neural Networks (PINNs) have emerged as a promising method for solving partial differential equations (PDEs) in scientific computing. While PINNs typically use multilayer perceptrons (MLPs) as their underlying architecture, recent advancements have explored alternative neural network structures. One such innovation is the Kolmogorov–Arnold Network (KAN), which has demonstrated benefits over traditional MLPs, including faster neural scaling and better interpretability. The application of KANs to physics-informed learning has led to the development of Physics-Informed KANs (PIKANs), enabling the use of KANs to solve PDEs. However, despite their advantages, KANs often suffer from slower training speeds, particularly in higher-dimensional problems where the number of collocation points grows exponentially with the dimensionality of the system. To address this challenge, we introduce Separable Physics-Informed Kolmogorov–Arnold Networks (SPIKANs). This novel architecture applies the principle of separation of variables to PIKANs, decomposing the problem such that each dimension is handled by an individual KAN. This approach drastically reduces the computational complexity of training without sacrificing accuracy, facilitating their application to higher-dimensional PDEs. Through a series of benchmark problems, we demonstrate the effectiveness of SPIKANs, showcasing their superior scalability and performance compared to PIKANs and highlighting their potential for solving complex, high-dimensional PDEs in scientific computing.

Kolmogorov-Arnold networks↗

DOE OSTI2024

IEEE LDAV 2024 Preface

Join us here for the 14th IEEE Symposium on Large Data Analysis and Visualization (IEEE LDAV) on Sunday, October 13th 2024 collocated with IEEE VIS 2024 in St. Pete Beach, Florida, USA.

Beyer, Johanna↗

DOE OSTI2024

S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models

While projection-based reduced order models can reduce the dimension of full order solutions, the resulting reduced models may still contain terms that scale with the full order dimension. Hyper-reduction techniques are sampling-based methods that further reduce this computational complexity by approximating such terms with a much smaller dimension. The goal of this work is to introduce the points selection algorithm developed by Shin and Xiu as a hyper-reduction method. The selection algorithm was originally proposed as a stochastic collocation method for uncertainty quantification. Since the algorithm aims at maximizing a quantity $\mathcal{S}$ that measures both the column orthogonality and the determinant, we refer to the algorithm as S-OPT. Numerical examples are provided to demonstrate the performance of S-OPT and to compare its performance with a gappy proper orthogonal decomposition (POD) algorithm. Here, we found that using the S-OPT algorithm is shown to predict the full order solutions with higher accuracy than gappy POD especially when the number of sampling points is small, although we note that S-OPT shows slow asymptotic convergence with respect to the number of samples for some applications, e.g., Lagrangian hydrodynamics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Estimating Ice Water Content for Winter Storms from Millimeter-Wavelength Radar Measurements Using a Synthesis of Polarimetric and Dual-Frequency Radar Observations

The potential of millimeter-wavelength radar-based ice water content (IWC) estimation is demonstrated using a Ka-band Scanning Polarimetric Radar (KASPR) for the U.S. northeast coast winter storms. Two IWC relations for Ka-band polarimetric radar measurements are proposed: one that uses a combination of the radar reflectivity Z and the estimated total number concentration of snow particles N t and the other based on the joint use of Z, specific differential phase K DP , and the degree of riming f rim . A key element of the algorithms is to obtain the “Rayleigh-equivalent” value of Z measured at the Ka band, i.e., the corresponding Z at a longer radar wavelength for which Rayleigh scattering takes place. This is achieved via polarimetric retrieval of the mean volume diameter D m and incorporating the relationship between the dual-wavelength ratio DWR S/Ka and D m . Those techniques allow for retrievals from single millimeter-wavelength radar measurements and do not necessarily require the dual-wavelength ratio (DWR) measurements, if the DWR–D m relation and Rayleigh assumption for Ka-band K DP are valid. Comparison between the quasivertical profile product obtained from KASPR and the columnar vertical profile product generated from the nearby WSR-88D S-band radar measurements demonstrates that the DWR S/Ka can be estimated from the two close radars without the need for collocated radar beams and synchronized antenna scanning and can be used for determining the Rayleigh-equivalent value of Z. As a result, the performance of the suggested techniques is evaluated for seven winter storms using surface disdrometer and snow accumulation measurements.

Cloud retrieval↗

DOE OSTI2024

Monitoring of ground water table depth and soil moisture at the Point Reyes field site

Ground water table (GWT) depth and soil moisture (SM) have been monitored at several locations at the Point Reyes field site (Californian coastal grassland) from 2021 to 2024. Monitoring is still on-going and data may be added to this archive at later time. The SM data have been acquired using Teros 12 Meter soil moisture sensors placed at 10, 30, 60 and 90 cm depth at 5 locations along a small hillslope. These sensors also collect soil temperature and bulk conductance. In addition, some collocated sensors provide pore pressure and Photochemical Reflectance Index (PRI). The GWT depth has been inferred from various type of Onset pressure transducers. The pressure measurements have been corrected for atmospheric pressure variations and sensor position relative to the ground surface to infer GWT depth, as well as with RTK GPS data to infer GWT elevation. The GWT data have been acquired at 5 distinct locations from 2020 to 2024 with the sensors placed at about 4 m depth. In addition, GWT data has been acquired for the 2023-2024 period with sensors located in 1 m deep shallow wells installed near each deeper well. This data is intended to evaluate possibly different dynamic in shallow (perched) and deep aquifer. The datasets are all provided in csv format. Please note that the interpretation of the GWT data needs to be done with consideration of environmental and well characteristics at the site and uncertainty in various variables. For more information on GWT and SM data, please contact the author.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

AmeriFlux FLUXNET-1F US-xTL NEON Toolik (TOOL)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xTL NEON Toolik (TOOL). This is the FLUXNET version of the carbon flux data for the site US-xTL NEON Toolik (TOOL) produced by applying the standard ONEFlux (1F) software. Site Description - The Toolik field site is located in a remote wilderness area at the Toolik Field Station which is on land managed by the Bureau of Land Management. The area is underlain by continuous permafrost, which exerts a major influence on hydrology and the distribution, structure, and function of terrestrial and aquatic ecosystems. Because of its location between the Brooks Range and the coastal plain, the vegetation and soils at TOOL are representative of much of the Alaskan foothills tundra. This terrestrial field site is collocated with NEON’s Toolik Lake aquatic site. The closest city, Fairbanks, Alaska is 400 miles away. The Dalton Highway (also known as the Haul Road or Pipeline Road), which traverses the middle of the state from Fairbanks to Prudhoe Bay, provides access to the area.

Network), NEON (National Ecological Observatory↗

DOE OSTI2025

Effect of Time Window and Spectral Measurement Options on Empirical Green’s Function Analysis Using DAS Array and Seismic Stations

The recorded seismic waveform is a convolution of event source term, path term, and station term. Removing high-frequency attenuation due to path effect is a challenging problem. Empirical Green’s function (EGF) method uses nearly collocated small earthquakes to correct the path and station terms for larger events recorded at the same station. However, this method is subject to variability due to many factors. Here, we focus on three events that were well recorded by the seismic network and a rapid response distributed acoustic sensing (DAS) array. Using a suite of high-quality EGF events, we assess the influence of time window, spectral measurement options, and types of data on the spectral ratio and relative source time function (RSTF) results. Increased number of tapers (from 2 to 16) tends to increase the measured corner frequency and reduce the source complexity. Extended long time window (e.g., 30 s) tends to produce larger variability of corner frequency. The multitaper algorithm that simultaneously optimizes both target and EGF spectra produces the most stable corner-frequency measurements. The stacked spectral ratio and RSTF from the DAS array are more stable than two nearby seismic stations, and are comparable to stacked results from the seismic network, suggesting that DAS array has strong potential in source characterization.

58 GEOSCIENCES↗

DOE OSTI2025

Detection of a Space Capsule Entering Earth’s Atmosphere with Distributed Acoustic Sensing (DAS)

On 24 September 2023, the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer sample return capsule (SRC) entered Earth’s atmosphere after successfully collecting samples from an asteroid. The known trajectory and timing of this return provided a rare opportunity to strategically instrument sites to record geophysical signals produced by the capsule because it travelled at hypersonic speeds through the atmosphere. For this work, we deployed two distributed acoustic sensing (DAS) interrogators to sample over 12 km of surface-draped fiber-optic cables, as well as six collocated seismometer-infrasound sensor pairs, spread across two sites near Eureka, Nevada. This campaign-style rapid deployment is the first reported recording of an SRC re-entry with any distributed fiber-optic sensing technology. The DAS interrogators recorded an impulsive arrival with an extended coda which had features that were similar to recordings from both the seismometers and infrasound sensors. While the signal-to-noise ratio of the DAS data was lower than the seismic-infrasound data, the extremely dense spacing of fiber-optic sensors allowed for more phases to be clearly distinguished and the visualization of the continuous transformation of the wavefront as it impacted the ground. Unexpectedly, the DAS recordings contain less low-frequency content than is present in both the seismic and infrasound data. The deployment conditions strongly affected the recorded DAS data; in particular, we observed that fiber selection and placement exert strong controls on data quality.

58 GEOSCIENCES↗

DOE OSTI2025

Rapid and Temporary Deployment of Fiber-Optic Arrays to Measure Surface Chemical Explosion Series with Distributed Acoustic Sensing

Rapid and temporary distributed acoustic sensing (DAS) deployments are crucial for accurately capturing the seismic wavefield following major events, such as earthquakes, or in anticipation of known events of interest, such as chemical explosions. We provide an overview of two DAS campaigns conducted in May and October 2024 to record the seismoacoustic waves generated by two series of surface chemical explosions in New Mexico, United States, involving 1- and 10-ton trinitrotoluene-equivalent charges. In both campaigns, we deployed approximately 2 km of fiber-optic cables in a dry riverbed, about 12 km east of the explosion sites. For the October campaign, seven geophones and two anemometers were collocated with the fiber. We describe the field deployments and present preliminary results from the recorded signals. Specifically, we cross analyze the data recorded in May and October, validate the DAS data with geophone measurements, and highlight the benefits of burying fibers to reduce wind noise and improve signal-to-noise ratios. This study demonstrates the potential of DAS to record the seismoacoustic waves generated by surface chemical explosions of varying sizes at distances of approximately 10 km from the source.

58 GEOSCIENCES↗

DOE OSTI2025

Surface Energy Balance System (SEBS) Instrument Handbook

A Surface Energy Balance System (SEBS) has been installed collocated with each deployed ECOR system at the Southern Great Plains (SGP), North Slope of Alaska (NSA), Tropical Western Pacific (TWP), ARM Mobile Facility 1 (AMF1), and ARM Mobile Facility 2 (AMF2). The surface energy balance system consists of upwelling and downwelling solar and infrared radiometers within one net radiometer, a wetness sensor, and soil measurements. The SEBS measurements allow the comparison of ECOR sensible and latent heat fluxes with the energy balance determined from the SEBS and provide information on wetting of the sensors for data quality purposes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Eddy Correlation Flux Measurement System (ECOR) Instrument Handbook

The eddy correlation (ECOR) flux measurement system provides in situ, half-hour measurements of the surface turbulent fluxes of momentum, sensible heat, latent heat, and carbon dioxide (CO 2 ) (and methane at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s North Slope of Alaska central facility [NSA Barrow], and at the ARM Mobile Facility (AMF) deployment at Oliktok Point). The fluxes are obtained with the eddy covariance technique, which involves correlation of the vertical wind component with the horizontal wind component, the air temperature, the water vapor density, and the CO 2 concentration. The instruments used are: a fast-response, three-dimensional (3D) wind sensor (sonic anemometer) to obtain the orthogonal wind components and the speed of sound (SOS) (used to derive the air temperature), an open-path infrared gas analyzer (IRGA) to obtain the water vapor density and the CO 2 concentration, and an open-path infrared gas analyzer (IRGA) to obtain methane density and methane flux at NSA Barrow and at the AMF deployment at Oliktok Point. The ECOR systems are deployed at the locations where other methods for surface flux measurements (e.g., energy balance Bowen ratio [EBBR] systems) are difficult to employ, primarily at the north edge of a field of crops. A surface energy balance system (SEBS) has been installed collocated with each deployed ECOR system in SGP, NSA, Tropical Western Pacific (TWP), and each of three ARM Mobile Facilities. The surface energy balance system consists of upwelling and downwelling solar and infrared radiometers within one net radiometer, a wetness sensor, and soil measurements. Finally, the SEBS measurements allow the comparison of ECOR sensible and latent heat fluxes with the energy balance determined from the SEBS and provide information on wetting of the sensors for data quality purposes.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Efficient Scalable Contact Network Generation from Population Data

Modeling the contacts among a population is critical to understanding the dynamics of a disease outbreak. Contact networks, where nodes are individuals and edges are contacts among them, are used to represent these complex individual-level interactions. In this work, we are given the daily activity schedules of an urban population that represent the activity location and time of individuals in a population during a single twenty four hour period over multiple days. Using collocation to determine contact between individuals, our goal is to extract hourly contact networks from large-scale activity data. We improve upon the existing adjacency matrix-based method by implementing our custom sparse matrix multiplication algorithm. Starting with a Python implementation, we achieve a 1600x speed up in the computation with a fast custom designed sparse matrix multiplier algorithm implemented in the C++ language. This work is central to future parallel designs of the problem.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Advanced Precipitation and Boundary Layer Data Products Derived from ARM Radar Wind Profilers

This research project was successful in delivering on four main objectives. First, software was developed to accurately calculate 915-MHz radar wind profiler (RWP) spectrum moments from the recorded Doppler velocity power spectra. Second, software was developed to calibrate the RWP reflectivity factor using collocated surface disdrometer observations. Third, the Python processing code was documented and given to the ARM Infrastructure to produce ARM ‘b level’ calibrated RWP products. Fourth, calibrated RWP products were uploaded to the ARM Archive as PI Products for 10 years of SGP RWP observations and for GoAmazon and TRACER field campaign RWP observations. In addition to working with RWP observations, this research project also worked with KAZR observations to distinguish insects from boundary layer clouds to help improve the ARSCL cloud mask product. The PI worked with senior and early career ARM funded scientists at BNL exploring how to include calibrated RWP moments into future versions of the ARSCL product.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Implications of Aerosol Physicochemical Properties Including Ice Nucleation at ARM Mega Sites for Improved Understanding of Microphysical Atmospheric Cloud Processes (Final Technical Report)

Continuous, long-term measurements of atmospheric ice-nucleating particles (INPs) that influence clouds and precipitation were conducted to investigate the abundance and variability of ground-level INPs across the world. Three field campaigns were organized by the DOE Atmospheric Radiation Measurement (ARM) program, including Examining INP from Southern Great Plains (ExINP-SGP, 2019), Examining INP from Eastern North Atlantic (ExINP-ENA, 2020 – 2021), and Examining INP from North Slope of Alaska (ExINP-NSA, 2021 – 2024). Additional small-scale supporting field experiments were performed in 2019 and 2021 to collect airborne particulate matter at SGP for complementary laboratory characterization of the particles’ physical and chemical properties [Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY), 2019; ExINP-SGP II, 2021]. In these studies, the PI’s team measured INP concentration with both real-time and laboratory measurements in a wide range of freezing temperatures ($T$ from 0 °C to about –30 °C). This project elucidated spatial variability and seasonality in the abundance of immersion mode active INPs across three ARM sites using a single instrument, a Portable Ice Nucleation Experiment (PINE) chamber version 03 (PINE-03 hereafter). Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient INP abundance, air mass origin region, and meteorological variability. Our findings suggest very high freezing efficiency of INPs at the NSA site across the measured temperatures (ice nucleation active surface site density, $n_s(T)$, $\approx 2 \times 10^{8} - 10^{10}$ m -2 for from –16 to –31 °C), which is a factor of 10 – 1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in autumn using the same instrument; surprisingly high INP abundance ($\ge 1 \text{ L}^{-1}$ at –25 °C) for the examined temperatures throughout the year that PINE-03 did not measure at other sites; and high INP concentration in spring, possibly related to arctic haze episodes.

58 GEOSCIENCES↗

DOE OSTI2025

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↗

DOE OSTI2025

Regulatory Considerations for Domestic Reprocessing Facility Physical Security

U.S. advanced non-light-water reactor vendors may pursue collocated on-site reprocessing activities. Therefore, these facilities are likely to possess formula quantities, or Category I quantities, of special nuclear material (SNM) during normal operations. The U.S. Nuclear Regulatory Commission (U.S. NRC) has yet to formally establish a regulatory framework for commercial reprocessing. While Category I requirements would explicitly not apply in this circumstance under current regulatory requirements, regulatory certainty does not exist. A novel framework should be developed to ensure public health and safety while also risk-informing the physical security requirements. This report reviews the relevant background of related rulemaking activities and proposes risk-informed physical protection requirements to satisfy these objectives. Insights from NRC security-related rulemaking activities provide a substantial technical basis to approach potential establishment of physical security requirements for reprocessing facilities. If a licensee can provide justification that the material satisfies a sufficient self-protecting radiation dose threshold, the material may not be subject to theft or diversion requirements and only potential sabotage requirements would apply. Furthermore, if the material can be justified to be moderately dilute, a set of risk-informed requirements could provide adequate protection of public health and safety. A revised performance objective for prevention of theft of moderately dilute Category I SNM may be detection to allow prompt recovery by a local law enforcement agency. However, a significant caveat to the proposed categorization scheme is the unknown integration of radiological sabotage with requirements for the protection against theft. Future licensees should consult with the NRC regarding treatment of this regulatory topic. Additionally, the self-protecting radiation dose threshold (either the existing or a proposed future threshold) would need to be considered. An integrated approach may apply graded potential requirements for protection against the design basis threat of radiological sabotage currently applicable to commercial nuclear power plants and Category I SNM facilities defined within 10 CFR 73.1(a).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗