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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 19 records

Performance Evaluation of an Offshore Wave Measurement Buoy in Monochromatic Waves

The accurate measurement of waves underpins marine energy resource characterization, device design, and project development. Datawell wave buoys are widely deployed and have long served as a trusted standard for wave measurements. We quantify the measurement performance, including wave elevation and energy flux estimation, of a Datawell DWR-MkIII buoy using prescribed monochromatic heave motions on a large-amplitude six-degree-of-freedom motion platform at the National Laboratory of the Rockies, assuming the buoy behaves as an ideal wave follower. Commanded motions were validated with an optical motion tracking system while buoy elevation and raw acceleration were recorded. Wave elevations were propagated to wave energy flux estimation using four methods, including one frequency-domain method and three time-domain methods. The Bayesian optimization was applied for design of experiments, and records from three test sites were also applied and evaluated in the present study. Results show two error regions within the nominal period range of 1.6 s to 30 s. For wave periods between 5 s and 25 s, the buoy provides accurate wave height measurements. For short periods less than 5 s, the 1.28 Hz sampling frequency induces sub-Nyquist artifacts that bias elevation and can drive maximum energy flux estimation errors above 100%. For long periods exceeding 25 s, the buoy reported elevation is underpredicted with error depending on period but relatively independent of wave height, with maximum wave height and wave energy flux errors reaching 64% and 87%, respectively. Furthermore, analysis of three field-derived cases shows that frequency-domain estimates at 1.28 Hz agree within 2% of the corresponding 100 Hz estimates, while larger method-dependent differences are observed for the Hilbert method.

16 TIDAL AND WAVE POWER↗

Quasiparticle spectroscopy in tantalum films with different Ta/sapphire interfaces

One of the crucial aspects of current research in quantum information science is the identification and control of loss mechanisms in superconducting (SC) circuits. Although microwave measurements directly quantify device performance, additional techniques that probe quasiparticle excitations in SC films are needed to understand the microscopic mechanisms underlying dissipation and decoherence. Here, we present results from quasiparticle spectroscopy of Ta/sapphire films by measuring the Meissner-state magnetic susceptibility using a precision frequency-domain resonator specifically designed for thin films. We find direct evidence for additional low-energy excitations in samples with lower internal quality factors. These excitations are consistent with deep subgap states due to two-level systems, Yu–Shiba–Rusinov states near the gap edge, and perhaps other pair-breaking mechanisms. The developed non-destructive frequency-domain quasiparticle spectroscopy is a valuable addition to the quantum materials toolbox.

metal/substrate interlayer↗

Quasiparticle spectroscopy in tantalum films with different Ta/sapphire interfaces

One of the crucial aspects of current research in quantum information science is the identification and control of loss mechanisms in superconducting circuits. Although microwave measurements directly quantify device performance, additional techniques that probe quasiparticle excitations in superconducting films are needed to understand the microscopic mechanisms underlying dissipation and decoherence. Here, we present results from quasiparticle spectroscopy of Ta/sapphire films by measuring the Meissner-state magnetic susceptibility using a precision frequency-domain resonator specifically designed for thin films. We find direct evidence for additional low-energy excitations in samples with lower internal quality factors. These excitations are consistent with deep subgap states due to two-level systems, Yu-Shiba-Rusinov states near the gap edge, and perhaps other pair-breaking mechanisms. The developed non-destructive frequency-domain quasiparticle spectroscopy is a valuable addition to the quantum materials toolbox.

Moirangthem, Bicky Singh [Ames Lab; Iowa State U.]↗

Quasiparticle spectroscopy in tantalum films with different Ta/sapphire interfaces

One of the crucial aspects of current research in quantum information science is the identification and control of loss mechanisms in superconducting circuits. Although microwave measurements directly quantify device performance, additional techniques that probe quasiparticle excitations in superconducting films are needed to understand the microscopic mechanisms underlying dissipation and decoherence. Here, we present results from quasiparticle spectroscopy of Ta/sapphire films by measuring the Meissner-state magnetic susceptibility using a precision frequency-domain resonator specifically designed for thin films. We find direct evidence for additional low-energy excitations in samples with lower internal quality factors. These excitations are consistent with deep subgap states due to two-level systems, Yu-Shiba-Rusinov states near the gap edge, and perhaps other pair-breaking mechanisms. The developed non-destructive frequency-domain quasiparticle spectroscopy is a valuable addition to the quantum materials toolbox.

Moirangthem, Bicky Singh [Ames Lab; Iowa State U.]↗

Quantifying System Strength From Grid-Forming Resources Using Frequency Scan Approach: Preprint

Current industry practices for quantifying the system strength contribution from grid-forming (GFM) resources to ensure stability of power systems dominated by inverter-based resources (IBRs) are primarily based on iterative electromagnetic transient (EMT) time-domain simulation studies. While feasible, these approaches are resource-intensive, lack scalability and intuition, and might not evaluate the system strength contribution over the entire frequency range of interest. This paper introduces a novel, frequency-domain approach to quantify system strength support provided by a GFM resource using frequency scans. The proposed method uses transfer functions from the grid voltage magnitude (V) and phase (?), respectively, to the reactive (Q) and active power (P) output of a GFM resource for quantifying its contribution to system strength. These transfer functions provide a direct measure of the ability of a GFM resource to behave as a stiff voltage source behind a reactance over a specified frequency range, enabling robust quantification of its system strength contribution. The key innovation of this work is the development of a frequency domain system strength metric called the dynamic short-circuit ratio (dSCR) that is suitable for IBR-dominated power systems and is directly related with the familiar short circuit ratio (SCR) metric. The new metric, dSCR, enables the assessment of system strength contributions from both synchronous machines and converter-based GFM resources using a unified benchmark, which is not possible with the traditional SCR metric. The paper also demonstrates how impedance scans could identify if an unstable condition observed during weak grid conditions is a result of the lack active or reactive power support or both. By leveraging the proposed frequency-domain dSCR metric for quantifying system strength contribution from GFM IBRs, the paper demonstrates targeted mitigation strategies for weak grid instabilities without resorting to repeated, time-consuming time-domain simulations. The result is a scalable and efficient approach to remediate stability challenges in power systems with high shares of IBRs and accelerating the integration of GFM technologies for system strength support in power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Deep learning for time series forecasting: a survey of recent advances

Time series forecasting plays a critical role in numerous real-world applications, such as finance, healthcare, transportation, and scientific computing. In recent years, deep learning has become a powerful tool for modeling complex temporal patterns and improving forecasting accuracy. This survey provides an overview of recent deep learning approaches for time series forecasting, involving various architectures including RNNs, CNNs, GNNs, transformers, large language models, MLP-based models, and diffusion models. We first identify key challenges in the field, such as temporal dependency, efficiency, and cross-variable dependency, which drive the development of forecasting techniques. Then, the general advantages and limitations of each architecture are discussed to contextualize their adaptation in time series forecasting. Furthermore, we highlight promising design trends like multi-scale modeling, decomposition, and frequency-domain techniques, which are shaping the future of the field. This paper serves as a compact reference for researchers and practitioners seeking to understand the current landscape and future trajectory of deep learning in time series forecasting.

97 MATHEMATICS AND COMPUTING↗

Simulation of electron Bernstein waves using FullWave with a 2D non-local hot plasma model

Hot plasma wave simulation capability is expanded in the FullWave code by updating the hybrid iterative solver in the code with a semi-implicit time stepping method. The new approach is used to simulate Electron Bernstein Wave (EBW) heating in over-dense spherical tokamak plasmas. The code’s hybrid iterative solver circumvents the prohibitive memory cost of direct methods by combining a time evolution of Maxwell’s equations with frequency-domain relaxation, while the conductivity kernel, calculated via 3D particle tracking, captures the essential non-local wave–particle interactions. One-dimensional EBW simulations verify the algorithm’s accuracy by demonstrating mode conversion from X-mode wave to EBW at the upper hybrid resonance and a strong cyclotron damping near the plasma core. Two-dimensional simulation reproduces the predicted short EBW wavelength and quantitatively matches the hot-plasma dispersion relation. This study demonstrates the fidelity of the hybrid solver for the electron cyclotron frequency range.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparative Evaluation of Spectral Methods for Robust Reactor Noise Estimation

Reactor noise analysis provides a noninvasive means to determine neutron kinetic parameters from stochastic fluctuations in detector signals. However, standard cross-power spectral density (CPSD) analyses can be sensitive to numerical processing choices, which may introduce processing-dependent systematic shifts in estimates of the prompt neutron decay constant (α) and limit reproducibility. This study uses a hybrid multitaper–Welch spectral estimator to analyze subcritical noise measurements from a fast-spectrum critical assembly. The decay constant α was extracted using three frequency-domain methods: the CPSD, the magnitude-squared coherence (MSC), and the generalized magnitude-squared coherence (GMSC). These coherence-based estimators normalize detector auto-spectral structure and are expected to reduce the sensitivity of fitted α values to processing parameters. A Sobol global sensitivity analysis identified which numerical inputs most strongly influence the fitted values of α. All estimators produced a linear dependence of α on inverse count rate, with delayed-critical extrapolations near 1.7 × 10 4 s −1 , in agreement within 8% of MCNP6.3 KOPTS benchmark calculations. Sensitivity results show that while the CPSD depends on both time-bin width and taper selection, the MSC and GMSC are dominated by time-bin width alone, indicating reduced parameter coupling and greater robustness to processing variability. These findings demonstrate the feasibility and practical value of coherence-based spectral estimators for extracting α from reactor noise and support their broader application to multi-detector and irregular datasets in subcritical system characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High-bandwidth frequency domain multiplexed readout of transition-edge sensors for neutrinoless double beta decay searches

The next-generation of cryogenic neutrinoless double-beta decay experiments require increasingly fast readout in order to improve background discrimination. These experiments, operated as cryogenic calorimeters at ∼ 10 mK, are usually read out by high-impedance neutron transmutation doped (NTD) thermistors, which provide good energy resolution, but are limited by ∼ 1 ms response times. Superconducting detectors, such as transition-edge sensors (TESs) with a time resolution of ∼ 100 μs, offer superior timing performance over NTD semiconductor bolometers. To make this technology viable for an application to a thousand or more channels, multiplexed readout is necessary in order to minimize the thermal load and radioactive contamination induced by the readout. Frequency-domain multiplexing readout (fMUX) for TESs, previously developed at Berkeley Lab and McGill University, is currently in use for mm-wave telescopes with detector sampling rates in the order of 100 Hz. We demonstrate a new readout system, based on the McGill/Berkeley digital fMux readout, to satisfy the higher bandwidth and noise requirements of the next generation of TES-instrumented cryogenic calorimeters. Each multiplexing readout module comprises 10 superconducting resonators in the 1–5 MHz range and a DC superconducting quantum interference device (DC-SQUID), interfaced to high-speed field programmable gate array (FPGA)-based electronics for digital signal processing and low-latency SQUID feedback. The new readout samples detectors at 156 kHz, three orders of magnitude faster than its cosmology-oriented predecessor, and demonstrates a stable feedback bandwidth of 3 kHz in a real TES-based system.

47 OTHER INSTRUMENTATION↗

Eliminating beam-induced depolarizing effects in the hydrogen jet target for high-precision proton beam polarimetry at the electron-ion collider

We analyze beam-induced depolarizing effects in the hydrogen jet target (HJET) at the relativistic heavy ion collider (RHIC), which has been used for absolute hadron beam polarimetry and shall be employed at the electron-ion collider (EIC). The EIC’s higher bunch repetition frequencies and shorter bunch durations shift beam harmonics to frequencies that can resonantly drive hyperfine transitions in hydrogen, threatening to depolarize the target atoms. Using frequency-domain analysis of beam harmonics and hyperfine transition frequencies, we establish a photon emission threshold above which beam-induced fields are too weak to cause significant depolarization. For EIC injection (23.5 GeV) and flattop (275 GeV), beam-induced depolarization through the bunch structure renders operation at the current RHIC magnetic guide field at the target (𝐵 0 =120⁢ mT) untenable. Increasing the magnetic guide field at the target to 𝐵 0 ≈ 400⁢ mT moves all hyperfine transition frequencies to at least 3 times the cutoff frequency, ensuring reliable absolute beam polarimetry with the required 1% precision at the EIC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes

The design of materials for electrochemical energy conversion is complicated by a vast search space of candidate materials and multifaceted property requirements: multicarrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Although self-driving laboratories are rapidly rising to address such material optimization problems, the required infrastructure for integrated, large-scale robotic facilities can be cost-prohibitive. Here we develop and evaluate a closed-loop measurement system for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers, building on top of an existing benchtop instrument and integrating techniques for rapid impedance measurement and automated analysis. This system exemplifies a “minimum viable” self-driving implementation that can deliver substantial benefits with relatively simple infrastructure. Combinatorial thin-film microelectrode libraries are characterized with a recently developed joint time-domain and frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed an active learning and Bayesian optimization process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces the screening time by tenfold with optimized experimental sequences. We apply this system to Ba⁡(Co,Fe,Zr,Y)⁢O 3−𝛿 combinatorial libraries and evaluate its effectiveness for learning material property trends and optimizing expensive-to-evaluate properties such as activation energy. This offers insights into key methodological aspects of practical autonomous experimentation, including surrogate model validation, cost-aware acquisition functions, and high-throughput data interpretation. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight real-world experimental challenges of thin-film degradation and numerical instability in surrogate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis and Overview of Hybrid Wired and Wireless Bi-Directional EV Charger Systems

Here, this paper analyzes and overviews hybrid wired and wireless bi-directional Electric Vehicle (EV) charging systems with a primary focus on resonant compensation methods that enable a unified power conversion architecture. Four compensation configurations based on series–series and LCC–LCC resonant networks are systematically evaluated for both wired transformer-based and wireless coupler-based operation. The analysis examines how coupling conditions, resonant component selection, and auxiliary compensation tuning influence voltage gain characteristics, resonant tank current magnitude and phase, and operating frequency requirements. Normalized frequency-domain results are presented to directly compare reactive current behavior and voltage regulation capability under wired and wireless operating conditions. A 60 kW bi-directional charger case study is used to demonstrate the feasibility of retaining a common hardware platform while accommodating distinct coupling scenarios through compensation tuning rather than structural modification. The presented results provide design-oriented insights into resonant network selection and compensation strategies for scalable and flexible hybrid EV charging systems.

Hybrid↗

Comparative Analysis of Pendulum and Flywheel Power Take-Off Mechanisms for Wave Energy Conversion

Here, this study compares three power-take-off (PTO) mechanisms for wave energy converters—a flywheel -type pitch resonator and two pendulum variants (normal and inverted)—all designed to fit within a fixed envelope. Performance is assessed via linear frequency-domain models and bi-conjugate impedance matching under a representative sea state. The inverted-pendulum PTO achieves 27.9% of the incident wave energy, versus 16.5% for the normal pendulum and 4.2% for the flywheel—that is, 6.6 × and 3.9 × improvements, respectively. These gains arise because pendulum-based systems generate higher torque for a given buoy motion and maintain impedance matching across a wider frequency band. Parametric studies of mass, pendulum arm length, spring stiffness, generator friction, and motor constant quantify the impact of key design choices on power output. By locating the pendulum pivot near the buoy's center of gravity and positioning the center of rotation below the COG, surge–pitch coupling is improved and energy transfer is further boosted.

Keow, Alicia Li Jen [Sandia National Laboratories ↗

Leveraging generative artificial intelligence to bridge domain gaps in wind turbine research

A central challenge in wind turbine health monitoring is the scarcity of real-world data due to limited instrumentation, leading researchers to rely on simulation models that often suffer from reduced fidelity. However, even within simulation environments, discrepancies arise because of modeling assumptions, and configuration fidelities, creating domain gaps that limit the transferability of learned representations. Here, to investigate domain translation under controlled conditions, this project explores the use of generative artificial intelligence, specifically cycle-consistent generative adversarial networks (CGANs), to bridge the gap between OpenFAST simulation models representing 1.5 MW and 5 MW wind turbines. A physics-informed CGAN architecture is introduced, where a simplified turbine tower dynamics model is incorporated into the training loss to ensure physically consistent outputs. Quantitative results showed moderate to high agreement in frequency-domain features. Incorporating the physics-informed loss function improved the R 2 values by 30%, reduced the RMSE from 1.39 to 1.1 m/s 2 , and reduced training time by 82%. Furthermore, under increased turbulence intensity (IEC Category A), the RMSE remained stable at approximately 1.1 m/s 2 . While the present study is entirely simulation-based, it establishes a pipeline for evaluating physics-informed generative domain translation, which may serve as a foundation for future simulation-to-reality validation studies.

17 WIND ENERGY↗

Measuring orbit responses with oscillating trajectories in the Fermilab Linac

Recording changes in beam transverse positions and longitudinal phase reported by Beam Position Monitors (BPMs) in response to a beam deflection by an upstream dipole corrector or RF cavity phase (orbit response) is a powerful tool for analysis of accelerator optics and assisting with machine tuning. In Fermilab Linac, orbit responses were recorded by oscillating the corrector currents and cavity phases in a sinusoidal manner parasitically during regular operation, simultaneously oscillating up to 19 correctors and 7 cavities at distinct frequencies, providing faster, drift-resistant measurements through frequency-domain analysis. This report describes the technique, including error estimations and consistency checks and shows examples of the measurements.

Shemyakin, Alexander [Fermilab] (ORCID:00000001501↗

UNIFI Specifications for GFM IBRs (V3) and Transitioning to an IEEE Standard [Slides]

This presentation describes version 3 of the grid-forming (GFM) specifications for inverter-based resources developed by the UNIFI (Uniform Interoperability for Grid-Forming Inverters) Consortium. It summarizes the requirements for GFM inverters, the four categories of GFM capability, and the tests designed to assess GFM capability. The tests including time-domain tests similar to those in use by some industry entities and frequency-domain tests that are largely new. This presentation also describes ongoing efforts to use the UNIFI GFM specifications as the starting point for a new IEEE standard called IEEE P2800.1.

14 SOLAR ENERGY↗

Dynamic Multipoles in the RCS

The Rapid Cycling Synchrotron (RCS) of the Electron--Ion Collider (EIC) will accelerate polarized electrons up to 18 GeV at a repetition rate of 1 Hz. Dynamic multipoles driven by eddy currents in the vacuum chamber can affect beam dynamics and polarization preservation during the energy ramp. Building on the analytical treatment of S.Y. Lee for a ramped normal-conducting dipole magnet, we use conformal transformations to derive compact expressions for dynamic multipoles in higher-order ramped magnets with circular beam pipes. We further derive analytical frequency-domain transfer functions for both self-response and cross-response multipoles, providing compact dynamical models for their evolution during arbitrary ramp waveforms. The resulting analytical predictions are benchmarked against finite-element simulations, including the effects of practical pole geometry and beam-pipe misalignment. Finally, the expected dynamic multipoles in the RCS magnets are estimated and their implications for beam dynamics and polarization preservation are discussed.

43 PARTICLE ACCELERATORS↗

Data Driven Correlated Noise Simulation for the ICEBERG LArTPC

Accurate electronic-noise simulation is essential for low-energy physics in liquid-argon TPCs. More realistic noise modeling allows us to better tune reconstruction algorithms and more reliably assess and optimize signal-detection thresholds. We present a data-driven noise simulation framework developed for the ICEBERG test stand for DUNE that generates synthetic noise waveforms that reproduce both (i) the measured per-channel magnitude of the Fast Fourier Transform (FFT) and (ii) frequency-dependent channel-to-channel correlations observed in ICEBERG noise data. Using a dedicated noise-only dataset, we build a compact noise model containing per-channel FFT-magnitude targets together with a small set of band-wise cross-wire color matrices. White noise is generated in the frequency domain by drawing circular-symmetric complex Gaussian coefficients with random phases and scaling them to match the measured FFT-magnitude targets, and cross-wire correlations are subsequently imposed using the stored color matrices. The model and algorithm were integrated into the LArSoft + Wire-Cell Toolkit simulation chain and validated by comparing waveform structure, frequency-domain spectra, and band-limited correlation matrices from simulated noise and ICEBERG data. This approach can be extended to other LArTPC operating conditions.

Ghosh, Avik [Iowa State U.]↗