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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Testing the thermal Sunyaev-Zel’dovich power spectrum of a halo model using hydrodynamical simulations

Statistical properties of large-scale cosmological structures serve as powerful tools for constraining the cosmological properties of our Universe. Tracing the gas pressure, the thermal Sunyaev-Zel’dovich (tSZ) effect is a biased probe of mass distribution and, hence, can be used to test the physics of feedback or cosmological models. Therefore, it is crucial to develop robust modelling of hot gas pressure for applications to tSZ surveys. Since gas collapses into bound structures, it is expected that most of the tSZ signal is within halos produced by cosmic accretion shocks. Hence, simple empirical halo models can be used to predict the tSZ power spectra. In this study, we employed the HMx halo model to compare the tSZ power spectra with those of several hydrodynamical simulations: the Horizon suite and the Magneticum simulation. We examine various contributions to the tSZ power spectrum across different redshifts, including the one- and two-halo term decomposition, the amount of bound gas, the importance of different masses, and the electron pressure profiles. Our comparison of the tSZ power spectrum reveals discrepancies between the halo model and cosmological simulations that increase with redshift. We find a 20% to 50% difference between the measured and predicted tSZ angular power spectrum over the multipole range ℓ = 10 3 − 10 4 . Our analysis reveals that these differences are driven by the excess of power in the predicted two-halo term at low k and in the one-halo term at high k . At higher redshifts ( z ∼ 3), simulations indicate that more power comes from outside the virial radius than from inside, suggesting a limitation in the applicability of the halo model. We also observe differences in the pressure profiles, despite the fair level of agreement on the tSZ power spectrum at low redshift with the default calibration of the halo model. In conclusion, our study suggests that the properties of the halo model need to be carefully controlled against real or mock data to be proven useful for cosmological purposes.

Ayçoberry, Emma (ORCID:0000000292351195)↗
DOE OSTI2023

TEAMER: Supporting model output files for Environmental Compliance Framework for Floating Tidal Turbines, Cook Inlet, AK

Orbital Marine Power (Orbital) is seeking to deploy their floating tidal technology in US waters and has considered the possibility of deploying in temperate waters including the Pacific Northwest (PNW) and the Western Passage, Maine. It has become apparent that some of the most promising tidal sites in the US are located in high latitudes, within the State of Alaska. Within the state, the most likely sites for grid-scale tidal energy are in Cook Inlet, with the largest city (Anchorage) located on the shores, ready and able to absorb the electrical output of a commercial scale tidal development. Through the TEAMER project, Pacific Northwest National Laboratory (PNNL) developed a framework to select environmentally compliant sites partially based on hydrodynamic model output. This uploaded dataset summarizes the key hydrodynamic model output files discussed in the TEAMER project report. Please unzip the file to see actual data files and the ReadMe file. This project is part of the TEAMER RFTS 4 (request for technical support) program.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Characterizing in-stream turbulent flow for tidal energy converter siting in Cook Inlet, Alaska

Cook Inlet in Alaska is the most promising location for tidal energy development in the U.S. due to its significant tidal range of approximately 10 meters and high volume flux. The inlet's unique geometry and flow characteristics make it the most energetic tidal stream in the nation, with GW-scale potential energy capacity. With the growing interest in tidal energy converter (TEC) deployment in this area, we implemented a regional-scale, 3D hydrodynamic modeling framework to predict tidal current and turbulence characteristics that can assist TEC designers and project managers. We validated the model results extensively using various datasets collected with bottom-mounted acoustic Doppler current profilers and velocimeters. The comparison between the model outputs and observational data highlighted the effectiveness of the 3D FVCOM model and the Mellor-Yamada Level 2.5 Turbulence Model in accurately assessing macro-scale kinetic energy, turbulence intensity, and the production and dissipation rates at a prospective TEC site. Using two months of model simulation data, we examined the channel cross-section for TEC deployment, focusing on undisturbed power density and macro-scale turbulent properties. Further, our findings indicate that understanding the turbulence characteristics and flow properties can enhance Stage I/II resource characterization by identifying optimal locations for TECs and their layouts within the channel. Furthermore, we demonstrated that TEC designers can utilize macro-scale turbulence data from 3D coastal models as boundary conditions for other turbulence models, allowing for a more detailed resolution of the turbulence structure at TEC siting locations. Ultimately, this work emphasizes the importance of estimating flow and turbulence conditions in energetic systems to understand turbulent sites better and improve resource characterization.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Modeling the hydrodynamic impact on the tool influence function during hemispherical subaperture optical polishing

To fabricate high-precision and accurate optics relative to the optical design surface, a high level of deterministic control of material removal (i.e., the tool influence function, TIF) during subaperture tool polishing is required. In this study, a detailed analysis of the pressure distribution, which is a key component of the TIF, has been performed using finite element analysis to couple together solid mechanics and fluid dynamics. Modeling experimental parameters of recently published work reveals that, when considering tool deformation, which in turn influences the fluid film thickness between the tool and workpiece, the effective pressure profile has a flat-top distribution. This flat-top pressure profile differs from the parabolic pressure distributions predicted by Hertzian mechanics. Furthermore, the shear contribution is shown here to be a key contributor to material removal, inducing the removal at the periphery of the contact edge and even outside the generally accepted contact area. Finally, the simulated fluid velocities provide evidence of mixed-mode contact polishing, supporting recent experimental findings that also suggest that onset of hydroplaning contributions lead to material removal drop-off.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Review of TEAMER Awards for WEC-Sim Support: Preprint

Testing Expertise and Access for Marine Energy Research (TEAMER) is a U.S. Department of Energy Water Power Technologies Office sponsored program, overseen by the Pacific Ocean Energy Trust, which aims to advance the state of marine energy technologies. The program connects technology developers with experts at U.S. facilities, including numerical modeling and analysis facilities, like WEC-Sim. The WEC-Sim facility is supported by the WEC-Sim development team at Sandia National Laboratories and the National Renewable Energy Laboratory. WEC-Sim (Wave Energy Converter SIMulator) is an open-source software for simulating wave energy converters. WEC-Sim can model the multi-body dynamics of devices comprised of bodies, joints, power take-off systems, and mooring systems. Since TEAMER's first round of support in 2020, there have been eighteen TEAMER awards focused on numerical model development in WEC-Sim. TEAMER awards for WEC-Sim support have modeled a wide range of wave energy converter archetypes, including point absorbers, attenuators, oscillating water columns, and many other novel architectures. A wide variety of studies have been conducted, leading to important insights for TEAMER partners and software improvements for WECSim. This article highlights several successful WEC-Sim TEAMER awards. The awards described herein include TEAMER recipients Ocean Motion Technologies, AquaHarmonics, iProTech, East Carolina University, Virginia Tech, Maiden Wave Energy, and the University of Massachusetts Dartmouth. The awards of these seven partners contain a wide range of investigations and cover the creation of baseline hydrodynamic models, PTO modeling, geometry optimization in both boundary element methods and WECSim, and model tuning and validation.

industry support↗
DOE OSTI2022

San Juan Islands Tidal Energy Characterization

The San Juan Islands are an archipelago with multiple tidal channels that produce strong tidal currents that could be harnessed for electricity generation. At present, there is limited electrical generation on the islands, with power primarily provided by a subsea cable connection with the mainland. As part of the C-MIST program, NOAA's CO-OPS program collected ADCP data at 46 stations in the San Juan Islands and adjacent waterways, from April to August of 2017. PNNL has recently developed a 3-D tidal hydrodynamic model for tidal energy resource characterization and assessment in the Salish Sea (Yang et al. 2021). Several tidal channels in the San Juan Islands were identified as top hotspots for potential tidal energy extraction. However, due to the complex geometry and inter-connected waterways, tidal currents around San Juan Islands also exhibit strong spatial and temporal asymmetry. Therefore, it is important to analyze the NOAA ADCP data to define metrics relevant to tidal energy, and further refine PNNL's tidal hydrodynamic model to accurately simulate currents in small tidal channels and account for sharp bathymetry gradients. The outcome of this technical assistance will allow developers to identify the promising opportunities for tidal energy in the San Juan Islands.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Tidal energy resource characterization measurements at Cook Inlet’s East Foreland: Velocity and turbulence

To characterize tidal current and turbulence at a top tidal energy site off the East Foreland in Cook Inlet, Alaska, United States, three moorings were deployed for two months between July and August 2021, and a transect survey was conducted over the course of two tidal cycles at the end of the deployment period. Measurements of velocity and turbulence were then analyzed to better understand the site's hydrodynamics and power potential. Analysis reveals that swift, north-flowing flood currents peak at 4~m/s, while south-flowing ebb currents reach just over 3~m/s. Turbulence intensity ranges from 23\% at the seafloor to 8\% near the surface, and the presence of the foreland creates more intense turbulence near-shore during ebb tide than flood. Power availability at the site could be as high as 720~MW, or 13~kW/m$^2$, though the energy available to a marine energy device will be smaller than this estimate because of water-to-wire efficiency and wake losses. The results from this measurement campaign will inform the validation of a high-resolution tidal hydrodynamic model, as well as early tidal energy projects that are beginning to move beyond the prototyping and demonstration stages to full-scale deployments.

McVey, James R.↗
DOE OSTI2022

Modeled Hourly Tidal Current Velocities, Directions, and Heights from May 1 - September 1, 2005 at Two Points Near East Forelands and Tyonek in Cook Inlet, Alaska

This dataset includes modeled tidal current velocities, direction and depth at two locations in East and North Forelands (60.716, -151.434 and 61.024, -151.157) near Nikiski and Tyonek, respectively, in Cook Inlet, Alaska. Data from two grid cells were provided by the Pacific Northwest National Laboratory based on a tidal hydrodynamic model that characterized the tidal stream resources in Cook Inlet for a period from May 1 to September 1, 2005 (Wang and Yang 2020). The model grid size had a horizontal spatial resolution of 100 m at East Forelands and 200 m at Tyonek; mean sea level (MSL) depth was 47.9 m and 23.7 m at each respective site, and there were 10 depth bins that ranged in size with the tide from 4.3-5.2 m and 1.9-2.8 m, respectively (Wang and Yang 2020).

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Climate-extreme modeling framework for sustainable flood management in the Arabian Peninsula

Evaluating extreme precipitation events (EPEs) is essential for building climate-resilient water management strategies, but it remains a major challenge in ungauged basins. Using the 26,070 km 2 Wadi al-Rummah basin in central Saudi Arabia as a case study, we developed an alternative, reliable, cost-effective satellite-based framework that combines empirically derived EPE thresholds, imagery-calibrated 2D hydrodynamic modeling, GRACE water-storage diagnostics, and bias-corrected CMIP6 projections to assess flood hazards and recharge potential under current and future climate scenarios in ungauged basins. The integrated approach and the resulting findings followed four key steps: (1) Identified a 22.5 mm EPE threshold, the 80th percentile of 3-day GPM/IMERG rainfall (2000–2024), aligned with flood-triggering events (Nov 2018: 23–28 mm; Apr, 2023: 42 mm); (2) Developed and calibrated a RiverFlow2D model using Sentinel-2 and PlanetScope imagery for the November 2018 flood, accurately reproducing flood depth and extent (RMSE ≤0.31 m; fuzzy-Dice ≥0.91), and estimating runoff (41 %), infiltration (25 %), and evaporation (34 %); (3) Independently validated the model with the April 2023 event (RMSE ≤0.35 m; fuzzy-Dice ≥0.86); (4) Conducted climate projections (2025–2100) from five bias-corrected NEX-GDDP CMIP6 models that revealed a 34 % increase in EPE intensity under SSP2-4.5 and 48 % under SSP5-8.5 scenarios, relative to 20th-century baselines. Our findings indicate that while intensifying extremes in the 21st century increase flood risk, the results highlight the potential for episodic recharge if effective retention strategies are employed, and offer a transferable model for climate-informed planning in data-scarce arid regions.

CMIP6↗
DOE OSTI2023

Co-Extrusion of Dissimilar Aluminum Alloys via Shear-Assisted Processing and Extrusion

Bimetallic tubes are used when a component requires more than one performance requirement, for instance, strength/creep resistance and oxidation/corrosion resistance. Shear-assisted processing and extrusion (ShAPE) can be used to fabricate extrudates that are comparable or superior in performance relative to conventionally manufactured extrudates. For the first time, ShAPE has been successfully employed in producing bimetallic Al tubing consisting of 6061 and 7075 Al alloys. Both light and electron microscopy techniques were used to investigate the integrity of the tubes, especially the interface between the core and cladding of the bimetallic tubes. Void-free bimetallic tubes were produced using ShAPE. Quantification of tube integrity was carried out with tensile testing under as-extruded and post-aged conditions. All the bimetallic tubes in the as-extruded samples exhibited uniform elongation above 5% with good tensile strength. Key insights such as material flow during bimetallic tube extrusion were obtained from the characterization of remnant billet and simulation results from a smoothed particle hydrodynamics model.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The transport dynamics of tens of micrometer-sized water droplets in RF atmospheric pressure glow discharges

Abstract Charging of particles having diameters of tens of microns has been extensively studied at atmospheric pressure in the context of, for example, electrostatic precipitators where the focus was on unipolar charging. The ambipolar charging of particles in atmospheric pressure plasmas, and of droplets in particular, has received less attention. The plasma activation of droplets is of interest for water purification, fertilizer production and materials synthesis, all of which depend on the transport of the droplets through the plasma, which in turn depends on their charging. In this paper, we report on the transport dynamics of water droplets, tens of microns in diameter, carried by the gas flow through an atmospheric pressure radiofrequency glow discharge sustained in helium. The droplets pass through the plasma with minimal evaporation and without reaching the Rayleigh limit. The droplet trajectory in the presence and absence of the plasma provides insights on the forces acting on the droplet. The measurements were analyzed using results from a three-dimensional fluid model and a two-dimensional plasma hydrodynamics model. We found that the transport dynamics as the droplet enters and leaves the plasma are due to differential charging of the droplet in the plasma gradients of the bounding sheaths to the plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

TEAMER: Numerical Modeling and Optimization of the iProTech Pitching Inertial Pump (PIP) Wave Energy Converter (WEC)

This project focused on developing an automated workflow to evaluate and optimize the iProTech Pitching Inertial Pump (PIP) wave energy converter (WEC) using open-source Python packages and the MATLAB/Simulink tool, WEC-Sim. The process involved parameterizing key design variables, running time-domain simulations, and performing sensitivity analyses to determine their impact on power output. The workflow, designed for the PIP device, is generalized and can be extended to optimize other WECs that can be simulated in WEC-Sim. This work establishes a foundation for future time-domain-based WEC design optimizations. Included in this submission are all figures from the final report and the model inputs required to generate them. This includes Python scripts with inputs that produce the meshes, boundary element method (BEM) models, hydrodynamic coefficients, and the WEC-Sim models used for time-domain analyses. Although data for every single run is not included to save space, all of it can be reproduced using the provided models. Detailed instructions for setting up the environment and running the codes are also included.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Impact of Limited Degree of Freedom Drag Coefficients on a Floating Offshore Wind Turbine Simulation

The worldwide effort to design and commission floating offshore wind turbines (FOWT) is motivating the need for reliable numerical models that adequately represent their physical behavior under realistic sea states. However, properly representing the hydrodynamic quadratic damping for FOWT remains uncertain, because of its dependency on the choice of drag coefficients (dimensionless or not). It is hypothesized that the limited degree of freedom (DoF) drag coefficient formulation that uses only translational drag coefficients causes mischaracterization of the rotational DoF drag, leading to underestimation of FOWT global loads, such as tower base fore-aft shear. To address these hydrodynamic modeling uncertainties, different quadratic drag models implemented in the open-source mid-fidelity simulation tool, OpenFAST, were investigated and compared with the experimental data from the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project. The tower base fore-aft shear and up-wave mooring line tension were compared under an irregular wave loading condition to demonstrate the effects of the different damping models. Two types of hydrodynamic quadratic drag formulations were considered: (1) member-based dimensionless drag coefficients applied only at the translational DoF (namely limited-DoF drag model) and (2) quadratic drag matrix model (in dimensional form). Based on the results, the former consistently underestimated the 95th percentile peak loads and spectral responses when compared to the OC5 experimental data. In contrast, the drag matrix models reduced errors in estimates of the tower base shear peak load by 7–10% compared to the limited-DoF drag model. The underestimation in the tower base fore-aft shear was thus inferred be related to mischaracterization of the rotational pitch drag and the heave motion/drag by the limited-DoF model.

17 WIND ENERGY↗
DOE OSTI2025

Optimal Uses of Magnetic Fields for Indirect-Drive Inertial Fusion

This project explored how applied magnetic fields can improve inertial confinement fusion (ICF), specifically the indirect-drive approach that uses a hohlraum. This has been proposed for several decades as potentially beneficial, due to thermal insulation (reduced losses) from the imploded hotspot. We performed the most advanced radiation-magneto-hydrodynamic modeling to date of magnetized ICF designs in the ignition regime. We found that adding technologically feasible fields up to 60 – 70 Tesla could increase the fusion yield of current igniting designs for the National Ignition Facility (NIF) by up to 8x. Also, simulations show that in certain cases relatively small fields of 3 – 5 Tesla could double the yield, and be implemented at much lower cost. Early work on re-optimizing NIF designs with magnetic fields, namely by using a thicker ablator with more mass remaining, could increase the yield of a sub-ignition target by 18x and bring it into the ignition regime. A separate benefit of magnetization besides reduced thermal loss is reduced hydrodynamic instability. Modeling work under this project shows this could be significant, though early experiments at NIF and the Omega Laser proved inconclusive. We designed and proposed an improved NIF experiment on magnetized mix, based on a large-amplitude imposed perturbation. The project also supported basic physics research into magnetized laser-plasma interactions, namely cross-beam energy transfer, both with experiments at Omega and theory / modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A hybrid CNN-LSTM surrogate model for hyper-resolution spatiotemporal flood forecasting in Norfolk, Virginia

Study region: Norfolk, Virginia, United States Study focus: Accurate and timely flood forecasting is essential for enhancing resilience in coastal urban areas in the context of increasing frequency and intensity of rainfall, sea level rise and urbanization. This study presents a hybrid deep learning-based surrogate model that integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to enable real-time spatiotemporal flood forecasting. The model leverages CNN to capture spatial features from inputs such as elevation and Topographic Wetness Index (TWI), while LSTM processes time-series inputs of rainfall and tide data to capture temporal features. New hydrologic insights for the region: The hybrid CNN-LSTM model was trained using the physics-based hydrodynamic model simulations obtained from the Two-dimensional Unsteady FLOW (TUFLOW) model for Norfolk, Virginia, and achieved high predictive accuracy across diverse flood-prone areas. The reduced computational time from four to six hours using TUFLOW to 3.2 min per event using CNN-LSTM enables rapid flood inundation mapping and early warning applications. The model effectively captured both spatial flood extents and their temporal evolution across different flooding scenarios, providing forecasts at a 2.5-m spatial resolution and 15-min temporal resolution and a one-hour-ahead prediction horizon. While challenges remain in terms of transferability to new regions and real-time data assimilation, this approach demonstrates strong potential for supporting operational flood risk management in coastal urban environments.

Coastal urban flooding↗
DOE OSTI2026

Development of an ab initio learned model of electron deposition range in deuterium-tritium plasmas through time-dependent density functional theory calculations and machine learning

Accurate hydrodynamic modeling for laser-direct-drive (LDD) inertial-confinement-fusion (ICF) relies on precise calculations of the electron thermal conduction in all target materials. The nonlocal stopping range of electrons in ICF plasmas directly influences thermal conduction; yet, no first principles model exists for the electron mean free path in the conduction-zone regime. This work utilized time-dependent stochastic density-functional theory (TD-sDFT) to calculate the electron stopping power in deuterium-tritium (DT) plasmas at (ρ, T) conditions relevant to the conduction zone and the compressed shell in ICF. Using a combination of our TD-sDFT data and already established analytical models, we developed and trained an artificial neural network to create a global model for the nonlocal electron deposition range, λ E . We compared our machine-learning (ML) based model for λ E to the currently-used modified-Lee-More model in LDD radiation-hydrodynamic codes, such as lilac, and saw an overall decrease in the deposition range. To understand the effects of λ E on LDD ICF implosion dynamics, we implemented the ML-based model into lilac; specifically, we looked at designs consistent with a current experiment on the OMEGA laser and for a newly designed LDD-ICF target for the future OMEGA-Next facility. In both cases, we saw an overall drop in predicted ablation pressure, peak areal density, and neutron yield due to the reduced thermal conduction (smaller λ E ) in DT plasmas. Comparisons with the experiment on OMEGA are also made.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗