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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Site-averaged kinetics for catalysts on amorphous supports: an importance learning algorithm

Ab initio calculations have greatly advanced our understanding of homogeneous catalysts and crystalline heterogeneous catalysts. In contrast, amorphous heterogeneous catalysts remain poorly understood. The principal difficulties include (i) the nature of the disorder is quenched and unknown; (ii) each active site has a different local environment and activity; (iii) active sites are rare, often less than ~20% of potential sites, depending on the catalyst and its preparation method. Few (if any) studies of amorphous heterogeneous catalysts have ever attempted to compute site-averaged kinetics, because the exponential dependence on variable activation energy requires an intractable number of ab initio calculations to converge. We present a new algorithm using machine learning techniques (metric learning kernel regression) and importance sampling to efficiently learn the distribution of activation energies. We demonstrate the algorithm by computing the site-averaged activity for a model amorphous catalyst with quenched disorder.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Effect of anionic surfactant concentration on the variable range hopping conduction in polypyrrole nanoparticles

The mechanism of charge transport in polypyrrole (PPy) nanoparticles prepared with different concentrations (5 to 30 mM) of anionic surfactant (sodium dodecyl sulfate) is reported. Transmission electron microscopy technique confirms the formation of PPy nanoparticles of sizes ∼52 to 28 nm under surfactant directed approach. The room temperature electrical conductivity of the prepared nanoparticles found to increase from 3 to 22 S/cm with surfactant concentration. The temperature dependent activation energy rules out the possibility of band conduction mechanism in the prepared PPy nanoparticles and thus the synthesized nanoparticles are analyzed under variable range hopping (VRH) model for conduction mechanism. The PPy nanoparticles, reduced with liquid ammonia, hold 3D VRH conduction mechanism for the charge transport. However, in the doped samples, some deviation from 3D VRH conduction behavior at higher temperatures (>150 K) has been observed. This may be attributed to the presence of anionic surfactant in these samples. The doping of anionic surfactant causes rise in conducting islands, which may lead to the change in the shape/distribution of density of states governed by Gaussian or exponential type near Fermi level.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

A spatially resolved retarding field energy analyzer design suitable for uniformity analysis across the surface of a semiconductor wafer

A novel retarding field energy analyzer design capable of measuring the spatial uniformity of the ion energy and ion flux across the surface of a semiconductor wafer is presented. The design consists of 13 individual, compact-sized, analyzers, all of which are multiplexed and controlled by a single acquisition unit. The analyzers were tested to have less than 2% variability from unit to unit due to tight manufacturing tolerances. The main sensor assembly consists of a 300 mm disk to mimic a semiconductor wafer and the plasma sampling orifices of each sensor are flush with disk surface. This device is placed directly on top of the rf biased electrode, at the wafer location, in an industrial capacitively coupled plasma reactor without the need for any modification to the electrode structure. The ion energy distribution, average ion energy, and average ion flux were measured at the 13 locations over the surface of the powered electrode to determine the degree of spatial nonuniformity. The ion energy and ion flux are shown to vary by approximately 20% and 5%, respectively, across the surface of the electrode for the range of conditions investigated in this study.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Prediction of atomization energy using graph kernel and active learning

Data-driven prediction of molecular properties presents unique challenges to the design of machine learning methods concerning data structure/dimensionality, symmetry adaption, and confidence management. In this paper, we present a kernel-based pipeline that can learn and predict the atomization energy of molecules with high accuracy. The framework employs Gaussian process regression to perform predictions based on the similarity between molecules, which is computed using the marginalized graph kernel. To apply the marginalized graph kernel, a spatial adjacency rule is first employed to convert molecules into graphs whose vertices and edges are labeled by elements and interatomic distances, respectively. We then derive formulas for the efficient evaluation of the kernel. Specific functional components for the marginalized graph kernel are proposed, while the effects of the associated hyperparameters on accuracy and predictive confidence are examined. We show that the graph kernel is particularly suitable for predicting extensive properties because its convolutional structure coincides with that of the covariance formula between sums of random variables. Using an active learning procedure, we demonstrate that the proposed method can achieve a mean absolute error of 0.62 ± 0.01 kcal/mol using as few as 2000 training samples on the QM7 dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

The surface nitrogen abundance of a massive star in relation to its oscillations, rotation, and magnetic field

We have composed a sample of 68 massive stars in our galaxy whose projected rotational velocity, effective temperature, and gravity are available from high-precision spectroscopic measurements. The additional seven observed variables considered here are their surface nitrogen abundance, rotational frequency, magnetic field strength, and the amplitude and frequency of their dominant acoustic and gravity modes of oscillation. A multiple linear regression to estimate the nitrogen abundance combined with principal component analysis, after addressing the incomplete and truncated nature of the data, reveals that the effective temperature and the frequency of the dominant acoustic oscillation mode are the only two significant predictors for the nitrogen abundance, while the projected rotational velocity and the rotational frequency have no predictive power. The dominant gravity mode and the magnetic field strength are correlated with the effective temperature but have no predictive power for the nitrogen abundance. Our findings are completely based on observations and their proper statistical treatment and call for a new strategy in evaluating the outcome of stellar evolution computations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Observational window effects on multi-object reverberation mapping

ABSTRACT Contemporary reverberation mapping campaigns are employing wide-area photometric data and high-multiplex spectroscopy to efficiently monitor hundreds of active galactic nuclei (AGNs). However, the interaction of the window function(s) imposed by the observation cadence with the reverberation lag and AGN variability time-scales (intrinsic to each source over a range of luminosities) impact our ability to recover these fundamental physical properties. Time dilation effects due to the sample source redshift distribution introduce added complexity. We present comprehensive analysis of the implications of observational cadence, seasonal gaps, and campaign baseline duration (i.e. the survey window function) for reverberation lag recovery. We find that the presence of a significant seasonal gap dominates the efficacy of any given campaign strategy for lag recovery across the parameter space, particularly for those sources with observed-frame lags above 100 d. Using the Australian Dark Energy Survey as a baseline, we consider the implications of this analysis for the 4MOST/Time-Domain Extragalactic Survey campaign providing concurrent follow-up of the Legacy Survey of Space and Time deep-drilling fields, as well as upcoming programmes. We conclude that the success of such surveys will be critically limited by the seasonal visibility of some potential field choices, but show significant improvement from extending the baseline. Optimizing the sample selection to fit the window function will improve survey efficacy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Multiwavelength analysis of Fermi -LAT blazars with high-significance periodicity: detection of a long-term rising emission in PG 1553+113

ABSTRACT Blazars display variable emission across the entire electromagnetic spectrum, with time-scales that can range from a few minutes to several years. Our recent work has shown that a sample of five blazars exhibit hints of periodicity with a global significance ${\gtrsim}2\, \sigma$ at γ-ray energies, in the range of 0.1 GeV < E < 800 GeV. In this work, we study their multiwavelength emission, covering the X-ray, ultraviolet, optical, and radio bands. We show that three of these blazars present similar periodic patterns in the optical and radio bands. Additionally, fluxes in the different bands of the five blazars are correlated, suggesting a co-spatial origin. Moreover, we detect a long-term (≈10 yr) rising trend in the light curves of PG 1553+113, and we use it to infer possible constraints on the binary black hole hypothesis.

Astronomy & Astrophysics↗
DOE OSTI2022

Magnetic damping in ferromagnetic/heavy-metal systems: The role of interfaces and the relation to proximity-induced magnetism

Damping and spin transport in spintronic multilayered systems continues to be a topic of active research. The enhancement of damping in ferromagnet (FM)/spacer layer (SL)/heavy-metal (HM) thin-film systems was studied for Co 25 Fe 75 /SL/Pt with a nonmagnetic (NM) SL of either Au or Cu with variable thickness, in order to understand the correlation with proximity-induced magnetism (PIM) in the HM. Structural, PIM and magnetic damping measurements were undertaken on the same samples. Specifically, secondary ion mass spectroscopy, element specific x-ray magnetic reflectivity and x-ray magnetic circular dichroism at the Pt and Au L 3 edges, and ferromagnetic resonance methods were used. With increasing thickness of a Cu or Au SL directly between the FM and the Pt layer, the Pt PIM and the damping both fall rapidly, with a relationship between damping and PIM that depends on the SL material. The PIM observed in the Au layer showed a complex dependence on the layer thickness, suggesting some hybridization with the Pt. The role of the number and location of interfaces on the damping was demonstrated with the addition of a SL within the Pt layer, which showed that the specific details of the NM/HM interface also affects the damping. The insertion of a Cu SL within the Pt showed a measurable increase in the overall enhancement of the damping while the insertion of a Au SL into Pt had almost no effect on the damping. Finally, together these results demonstrate the role of both PIM and of additional interfaces in the enhancement of damping in FM/HM systems, which is not fully accounted for by existing theory

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Visualization and manipulation of magnetic domains in the quasi-two-dimensional material F e 3 GeT e 2

The magnetic domains in two-dimensional layered material Fe 3 GeTe 2 are studied by using a variable-temperature scanning tunneling microscope with a magnetic tip after in situ cleaving of single crystals. A stripy domain structure is revealed in a zero-field-cooled sample below the ferromagnetic transition temperature of 205 K, which is replaced by separate double-walled domains and bubble domains when cooling the sample under a magnetic field of a ferromagnetic Ni tip. The Ni tip can further convert the double-walled domain to a bubble domain pattern as well as move the Neel-type chiral bubble in submicrometer distance. The temperature-dependent evolutions of both zero-field-cooled and field-cooled domain structures correlate well with the bulk magnetization from magnetometry measurements. Furthermore, atomic resolution scanning tunneling images and spectroscopy are acquired to understand the atomic and electronic structures of the material, which are further corroborated by first-principles calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Field testing of modular borehole monitoring with simultaneous distributed acoustic sensing and geophone vertical seismic profiles at Citronelle, Alabama: Field testing of MBM

A modular borehole monitoring concept has been implemented to provide a suite of well-based monitoring tools that can be deployed cost effectively in a flexible and robust package. The initial modular borehole monitoring system was deployed as part of a CO 2 injection test operated by the Southeast Regional Carbon Sequestration Partnership near Citronelle, Alabama. The Citronelle modular monitoring system transmits electrical power and signals, fibre-optic light pulses, and fluids between the surface and a reservoir. Additionally, a separate multi-conductor tubing-encapsulated line was used for borehole geophones, including a specialized clamp for casing clamping with tubing deployment. The deployment of geophones and fibre-optic cables allowed comparison testing of distributed acoustic sensing. We designed a large source effort (>64 sweeps per source point) to test fibre-optic vertical seismic profile and acquired data in 2013. The native measurement in the specific distributed acoustic sensing unit used (an iDAS from Silixa Ltd) is described as a localized strain rate. Following a processing flow of adaptive noise reduction and rebalancing the signal to dimensionless strain, improvement from repeated stacking of the source was observed. Conversion of the rebalanced strain signal to equivalent velocity units, via a scaling by local apparent velocity, allows quantitative comparison of distributed acoustic sensing and geophone data in units of velocity. We see a very good match of uncorrelated time series in both amplitude and phase, demonstrating that velocity-converted distributed acoustic sensing data can be analyzed equivalent to vertical geophones. We show that distributed acoustic sensing data, when averaged over an interval comparable to typical geophone spacing, can obtain signal-to-noise ratios of 18 dB to 24 dB below clamped geophones, a result that is variable with noise spectral amplitude because the noise characteristics are not identical. With vertical seismic profile processing, we demonstrate the effectiveness of downgoing deconvolution from the large spatial sampling of distributed acoustic sensing data, along with improved upgoing reflection quality. finally, we conclude that the extra source effort currently needed for tubing-deployed distributed acoustic sensing vertical seismic profile, as part of a modular monitoring system, is well compensated by the extra spatial sampling and lower deployment cost as compared with conventional borehole geophones.

58 GEOSCIENCES↗
DOE OSTI2019

The spatial scale dependence of diazotrophic and bacterial community assembly in paddy soil

Aim: The factors driving microbial community β-diversity (variation in composition) at different spatial scales yield fundamental insights into the mechanisms that maintain ecosystem biodiversity, which as yet are uncertain. In this work, we explore whether spatial scale-dependent patterns of β-diversity vary between microbial functional groups and bacterial taxa (i.e., diazotrophic and bacterial communities) across local to regional scales (from metres to hundreds of kilometres). Location: Eastern China. Time period: October and November 2015. Major taxa studied: Diazotrophic and bacterial communities. Methods: We use two complementary statistical tools to unveil biotic mechanisms (i.e., species association) underlying variation in β-diversity of diazotrophic and bacterial communities. We examined distance–decay slopes of both communities at the local (1–113 m), meso- (3.4–39 km) and regional (103–668 km) scales. We used an environmentally constrained checkerboard score and topological features of association networks as indices of species association. We then calculated contributions of species association, abiotic factors and geographical distance to explain community β-diversity. The scale-dependent distance–decay relationships were also examined in ubiquitous (high occupancy across samples) and endemic communities of diazotrophs and bacteria. Results: Diazotrophs displayed steeper distance–decay slopes than bacteria, suggesting that the β-diversity of diazotrophic communities was more variable. The distance–decay slopes were dependent on spatial scales in both communities, owing to different contributions of geographical distance, abiotic factors and species association at three spatial scales. Intriguingly, species association was greater and contributed more to community β-diversity than other forces at the local scale, implying that species association could greatly alter community structures. Main conclusions: Drivers of diazotrophic and bacterial community β-diversity depended on spatial scales, resulting in different distance–decay patterns. Moreover, this was the first study to use two methods to demonstrate that species association played important, but as yet unrecognized, roles in driving spatial scale-dependent β-diversity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

SU-E-J-261: Statistical Analysis and Chaotic Dynamics of Respiratory Signal of Patients in BodyFix

Purpose: To quantify respiratory signal of patients in BodyFix undergoing 4DCT scan with and without immobilization cover. Methods: 20 pairs of respiratory tracks recorded with RPM system during 4DCT scan were analyzed. Descriptive statistic was applied to selected parameters of exhale-inhale decomposition. Standardized signals were used with the delay method to build orbits in embedded space. Nonlinear behavior was tested with surrogate data. Sample entropy SE, Lempel-Ziv complexity LZC and the largest Lyapunov exponents LLE were compared. Results: Statistical tests show difference between scans for inspiration time and its variability, which is bigger for scans without cover. The same is for variability of the end of exhalation and inhalation. Other parameters fail to show the difference. For both scans respiratory signals show determinism and nonlinear stationarity. Statistical test on surrogate data reveals their nonlinearity. LLEs show signals chaotic nature and its correlation with breathing period and its embedding delay time. SE, LZC and LLE measure respiratory signal complexity. Nonlinear characteristics do not differ between scans. Conclusion: Contrary to expectation cover applied to patients in BodyFix appears to have limited effect on signal parameters. Analysis based on trajectories of delay vectors shows respiratory system nonlinear character and its sensitive dependence on initial conditions. Reproducibility of respiratory signal can be evaluated with measures of signal complexity and its predictability window. Longer respiratory period is conducive for signal reproducibility as shown by these gauges. Statistical independence of the exhale and inhale times is also supported by the magnitude of LLE. The nonlinear parameters seem more appropriate to gauge respiratory signal complexity since its deterministic chaotic nature. It contrasts with measures based on harmonic analysis that are blind for nonlinear features. Dynamics of breathing, so crucial for 4D-based clinical technologies, can be better controlled if nonlinear-based methodology, which reflects respiration characteristic, is applied. Funding provided by Varian Medical Systems via Investigator Initiated Research Project.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-AB-BRA-03: Backscatter Dose Factors Re-Evaluated for Inhomogeneities in the Presence of a 1.5 T Magnetic Field Using the GPUMCD Monte Carlo Algorithm

Purpose: To quantify the backscatter dose factors near the interfaces for clinically relevant high atomic number materials using GPUMCD for the Elekta MRI Linac. Methods: Backscatter dose factors (BSDF) were calculated as the ratio of the dose with and without the presence of the heterogeneity. The BSDF’s were calculated either in the absence or presence of an orthogonal 1.5 T magnetic field. Doses were scored in small voxels of side 1 mm in a water phantom with dimensions of 20×20×20 cm using GPUMCD (Elekta). The minimum uncertainty in dose calculations was kept to 0.5%. A slab of thickness 2 cm, representing the inhomogeneity, was placed inside the phantom with variable position from the surface of the phantom. The slab was filled with either bone, aluminum, titanium, stainless steel, or dental amalgam. The phantom was irradiated using particles sampled from a histogram which represented the true MRI Linac spectrum. Results: With the application of the 1.5 T magnetic field (B-On), all of the BSDF’s were reduced by at least 8% compared to the no magnetic field (B-Off) cases. For the B-Off case, the BSDF decreases exponentially with the upstream distance away from the interface. With B-On, the BSDF decreases exponentially for titanium, SS, and amalgam. However, it remains constant for Aluminum. In the case of bone, the BSDF increases up to a distance of 4 mm away from the interface in the presence of the magnetic field. Conclusion: The BSDF does not depend upon the thickness of the homogeneous material above the inhomogeneity for either the B-Off or B-On cases. For all the materials investigated, the BSDF is lower at the interface for the B-On case. The exponential fall-off of the BSDF away from the interface is not valid for all the materials when the magnetic field is turned ON. Funding support for this research was provided by Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Galvanostatic Intermittent Titration Technique Reinvented: Part I. A Critical Review

The galvanostatic intermittent titration technique (GITT), introduced in 1977 by Weppner and Huggins, provided a readily accessible means to measuring the chemical diffusion coefficient of electrochemical electrode materials. The method continues to be widely used today, but the reported diffusivity values are highly inconsistent, ranging as much as four orders of magnitude for some Li layered oxide compositions. Even qualitative trends of diffusivity are inconsistent, suggesting significant flaws in the implementation of the method. Other variants of the GITT method also suffer from similar inconsistency problems. Here we identify numerous sources of significant error including composition-dependent reaction overpotentials, mathematical flaws in the relaxation analysis methods, finite-size and non-planar geometry effects, inter-particle inhomogeneity issues, early transient effects, and surface area uncertainties. We propose a simple relaxation analysis scheme using the time variable t relax + τ - t relax , where t relax is relaxation time and τ is the galvanostatic pulse duration. We also propose to use dense diffusion-limited samples to isolate the bulk-diffusion process in the time domain. Chemical diffusivity can be extracted much more reliably with this improved implementation of the GITT method.

25 ENERGY STORAGE↗
DOE OSTI2021

Quantifying the Uncertainty of the Future Hydrological Impacts of Climate Change: Comparative Analysis of an Advanced Hierarchical Sensitivity in Humid and Semiarid Basins

Comparison and quantification of different uncertainties of future climate change involved in the modeling of a hydrological system are highly important for both hydrological modelers and policy-makers. However, few studies have accurately estimated the relative importance of different sources of uncertainty at different spatiotemporal scales. Here, a hierarchical sensitivity analysis framework (HSAF) incorporated with a variance-based global sensitivity analysis is developed to quantify the spatiotemporal contributions of different uncertainties in hydrological impacts of climate change in two different climatic (humid and semiarid) basins in China. The uncertainty sources include three emission scenarios (ESs), 20 global climate models (GCs), three hydrological models (HMs), and the associated sensitive hydrological parameters (PAs) screened and sampled by the Morris and Latin hypercube sampling methods, respectively. Further, the results indicate that the overall trend of uncertainty is PA > HM > GC > ES, but their uncertainties have discrepancies in projections of different hydrological variables. The HM uncertainty in annual and monthly discharge projections is generally larger than the PA uncertainty in the humid basin than semiarid basin. The PA has greater uncertainty in extreme hydrological event (annual peak discharge) projections than in annual discharge projections for both basins (particularly for the humid basin), but contributes larger uncertainty to annual and monthly discharge projections in the semiarid basin than humid basin. The GC contributes larger uncertainty in all the hydrological variables projections in the humid basin than semiarid basin, while the ES uncertainty is rather limited in both basins. Overall, our results suggest there is greater spatiotemporal variability of hydrological uncertainty in more arid regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Machine learning-based inversion for acoustic impedance with large synthetic training data: Workflow and data characterization

Where wells are sparse or training data are difficult to label with high-quality wireline-derived impedance logs, machine learning (ML)-based inversion of acoustic impedance typically depends on small training data sets, leading to biased prediction. We have advanced a novel workflow that applies large synthetic seismic training data to reduce facies-related bias. Using a geologically realistic model as the truth model, we randomly select sparse seed wells to perform sequential Gaussian simulation (SGS) for impedance models of the same geometry and simulate facies variability. We implement random forest regression on 30 features extracted from the synthetic volume. We observe that more seed wells tend to reduce facies-induced bias by sampling more types of facies, resulting in a better prediction. We then focus on the responses of SGS models to facies changes, the number of seed wells necessary for a useful synthetic model, and how much a synthetic model can help ML-based inversion. Here, we observe that the SGS synthetic training model outperforms well-direct training in general. For modeled clastic shore-zone systems in Miocene Gulf of Mexico, two or more seed wells are necessary for a significant reduction of root-mean-square error and outliners, and improvement of facies imaging. In a field-data test, we apply a similar workflow to quantitatively predict acoustic impedance, which is then converted to a sand-volume map at a high-frequency sequence (10–100 m), revealing detailed facies and sandstone patterns. Such results are valuable in many geologic and engineering applications, such as hydrocarbon and CO 2 reservoir prospecting, reserve estimation, simulation, etc.

3D seismic↗
DOE OSTI2021

Flooding and ecological restoration promote wetland microbial communities and soil functions on former cranberry farmland

Microbial communities are early responders to wetland degradation, and instrumental players in the reversal of this degradation. However, our understanding of soil microbial community structure and function throughout wetland development remains incomplete. We conducted a survey across cranberry farms, young retired farms, old retired farms, flooded former farms, ecologically restored former farms, and natural reference wetlands with no history of cranberry farming. We investigated the relationship between the microbial community and soil characteristics that restoration intends to maximize, such as soil organic matter, cation exchange capacity and denitrification potential. Among the five treatments considered, flooded and restored sites had the highest prokaryote and microeukaryote community similarity to natural wetlands. In contrast, young retired sites had similar communities to farms, and old retired sites failed to develop wetland microbial communities or functions. Canonical analysis of principal coordinates revealed that soil variables, in particular potassium base saturation, sodium, and denitrification potential, explained 45% of the variation in prokaryote communities and 44% of the variation in microeukaryote communities, segregating soil samples into two clouds in ordination space: farm, old retired and young retired sites on one side and restored, flooded, and natural sites on the other. Heat trees revealed possible prokaryotic ( Gemmatimonadetes ) and microeukaryotic ( Rhizaria ) indicators of wetland development, along with a drop in the dominance of Nucletmycea in restored sites, a class that includes suspected mycorrhizal symbionts of the cranberry crop. Flooded sites showed the strongest evidence of wetland development, with triple the soil organic matter accumulation, double the cation exchange capacity, and seventy times the denitrification potential compared to farms. However, given that flooding does not promote any of the watershed or habitat benefits as ecological restoration, we suggest that flooding can be used to stimulate beneficial microbial communities and soil functions during the restoration waiting period, or when restoration is not an option.

Rubin, Rachel L. (ORCID:0000000284326811)↗
DOE OSTI2020

Data for Post-Access Report: Tidal Energy Resource Characterization and Model Validation via the Assessment of Cost-effective Spatially Distributed Current Measurements from microFloat Swarms

This project evaluated how high-resolution, spatially distributed field data can be used to refine and validate site-scale hydrodynamic simulations of tidal channels. Use of such spatially-distributed field observations or site-scale hydrodynamic simulations will be needed for producing accurate predictions of tidal energy production over larger arrays of tidal turbines. The data contained in this archive includes field observations of water velocity from a series of short surveys in Agate Pass taken on August 20th, 2020 using station-keeping ADCP (acoustic doppler current profiler) measurements, drifting downward-looking ADCPs, and microFloats, gathered by researchers at APL-UW under a previous project. It also includes high-resolution hydrodynamic model runs for the site during that time generated under TEAMER support. An explanatory file (.pdf format) describes the survey and field data structure. Processed data is stored in .mat format. Survey summary: start time, number of floats, water level. microFloat data: - Cleaned data for each float in survey, - Time series of position (lat., lon.), depth (relative to surface), and horizontal velocity (u, v) Drifting ADCP data: - Cleaned data for each drifting ADCP in survey - Time series of position (lat., lon.), sample depth (relative to surface), and observed water velocity (u,v,w) Stationary ADCP data: - Cleaned data for each station-keeping data set in survey - Time series of position (lat., lon.), sample depth (relative to surface), and observed water velocity (u,v,w) FVCOM (Finite Volume Coastal Ocean Model) model outputs: Water level and velocity, as well as derived variables (e.g., power density) from the final refined model simulations for the Agate Pass subdomain. Contained in NetCDF and ASCII files for the duration of August 18th and 20th 2020 field surveys. Additional scripts for processing the data and generating the figures in the report are included.

16 TIDAL AND WAVE POWER↗