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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Experimental Validation of Models of a Hull-Based Tuned Mass Damper System for a Semisubmersible Floating Offshore Wind Turbine Platform

Floating offshore wind turbine designs can be further optimized if the controller and remaining systems are designed together, known as control co-design. To effectively perform control co-design, modeling tools predicting the influence of the control systems on the response of a system must be validated. This article presents an experimental validation that utilizes a scale model of a semisubmersible platform for an offshore wind turbine that is fitted with adjustable tuned mass dampers. These dampers can be tuned to attenuate either the hull-pitch resonance or the tower-bending resonance. The data from the experiment are used to validate state-of-the-art modeling tools. It is shown that the models capture the overall effects of the tuned mass dampers; however, some models overpredict the reduction in platform pitch motion when the dampers are tuned to the pitch resonance. The relative reduction in the tower-base bending moment is more consistently captured by the models when the dampers are tuned to the tower-bending resonance. However, there are significant differences in the absolute level of tower-base bending moment between the models and the experiment. Much of the differences observed are a consequence of the challenge with accurately predicting the baseline platform resonance motion and the tower-bending moment, which should be addressed in future modeling efforts.

17 WIND ENERGY↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Ced Cedar Bridge

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ced Cedar Bridge. This is the FLUXNET version of the carbon flux data for the site US-Ced Cedar Bridge produced by applying the standard ONEFlux (1F) software. Site Description - Wildfires and prescribed fires are a common occurrence in the NJ Pinelands. Prior to a 1995 nonstand replacing wildfire, the stand was last burned in the very large wildfire in 1963. Plow lines were installed for fire control in December of 2007, followed by a prescribed burns in 2008 and 2013, conducted by the New Jersey Forest Fire Service. Pine looper defoliated the stand in 1998, and Gypsy moth defoliated the understory and deciduos oaks in 2007. Pitch Pines are largely unaffected by defoliation by Gypsy moth.

Skowronski, Nicholas S.↗
DOE OSTI2022

Reversible electron spirals by chirped attopulses at zero time delay

A class of linear, spiral phenomena is discovered in the photoelectron momentum distribution when studying photoionization of S -state atoms by a pair of linearly chirped, oppositely circularly polarized attosecond pulses eventually delayed in time by $\tau$. This controllable effect, dubbed. reversible electron spirals because of its energy-dependent sense of rotation, is identified and can be isolated in the absence of time delay for the case of opposite chirp rates. Further, the astrophysical concept of spiral arm pitch angle is borrowed to gain a better insight into the energy dependence of the reversible spiral rotation, to determine the attochirp as well as the binding energy characteristic of an atomic target. Our results indicate potential applications in attochirpmetry and polarimetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Augmented Kalman filter with a reduced mechanical model to estimate tower loads on a land-based wind turbine: a step towards digital-twin simulations

This article presents an application of the Kalman filtering technique to estimate loads on a wind turbine. The approach combines a mechanical model and a set of measurements to estimate signals that are not available in the measurements, such as wind speed, thrust, tower position, and tower loads. The model is severalfold faster than real time and is intended to be run online, for instance, to evaluate real-time fatigue life consumption of a field turbine using a digital twin, perform condition monitoring, or assess loads for dedicated control strategies. The mechanical model is built using a Rayleigh–Ritz approach and a set of joint coordinates. We present a general method and illustrate it using a 2-degrees-of-freedom (DOF) model of a wind turbine and using rotor speed, generator torque, pitch, and tower-top acceleration as measurement signals. The different components of the model are tested individually. The overall method is evaluated by computing the errors in estimated tower-bottom-equivalent moment from a set of simulations. From this preliminary study, it appears that the tower-bottom-equivalent moment is obtained with about 10 % accuracy. The limitation of the model and the required steps forward are discussed.

17 WIND ENERGY↗
DOE OSTI2020

A digital twin based on OpenFAST linearizations for real-time load and fatigue estimation of land-based turbines

Monitoring a wind turbine requires intensive instrumentation, which would be too cost-prohibitive to deploy to an entire wind plant. This work presents a technique that uses readily available measurements to estimate signals that would otherwise require additional instrumentation. This study presents a digital twin concept with a focus on estimating wind speed, thrust, torque, tower-top position, and loads in the tower using supervisory control and data acquisition (SCADA) measurements. The model combines a linear state-space model obtained using OpenFAST linearizations, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The measurements are: top acceleration, generator torque, pitch, and rotational speed. The article extends previous work that derived the linear state-space model using a different method. The new implementation, based on OpenFAST linearization capability, allows for a systematic extension of the method to more states, inputs, outputs, and to the offshore environment. Results from the two methods are compared, and the validation is made with additional measurements using the GE 1.5-MW turbine located at the National Renewable Energy Laboratory test site. Real-time damage equivalent loads of the tower bottom moment are estimated with an average accuracy of approximately 10%. Overall, the results from this proof of concept are encouraging, and further application of the model will be considered.

17 WIND ENERGY↗
DOE OSTI2023

Reactor physics characterization of triply periodic minimal surface-based nuclear fuel lattices

Triply periodic minimal surface (TPMS) lattices are receiving substantial attention in numerous engineering fields due to their impressive topology-driven physical characteristics. TPMS lattices are periodic structures of two distinct intertwined volume domains separated by an area-minimizing surface or wall. TPMS lattices have been observed in nature, such as biological membranes, skeletons, block copolymers, sea urchins, butterfly wings, and equipotential surfaces in crystals. Intriguingly, the topology of TPMS lattices can be easily parametrized via level-set equations and thus are heavily numerically and experimentally studied. Here, a significant research effort is currently applying TPMS lattices for heat exchangers and sinks. This paper extends TPMS lattice applications to nuclear reactor fuel designs, with a focus on identifying relevant TPMS geometric parameters controlling neutronics characteristics, such as reactivity, neutron spectrum, and heat removal properties. We found that fuel surface-area-to-volume ratios for TPMS lattices can be two orders of magnitude larger than current cylindrical fuel rods. Further, the selected TPMS lattice and its implicit equation, the unit cell pitch, wall thickness, and structure porosity are design parameters enabling neutronics optimization for both thermal and fast spectrum configurations, paving the way for exceptionally compact and dense nuclear core concepts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

The competing effects of wave amplitude and collisions on multi-ion species suppression of stimulated Brillouin scattering in inertial confinement fusion Hohlraums

Reduction in stimulated Brillouin scattering (SBS) from National Ignition Facility Hohlraums has been predicted through the use of multi-ion species materials on Hohlraum walls. This approach to controlling SBS is based upon introducing a lighter ion species to the heavier ion species Hohlraum wall in order to greatly increase the ion Landau damping of ion acoustic waves (IAWs). In a collisionless plasma, if the IAWs driven by SBS reach sufficient amplitudes, this increased damping is reduced or even eliminated by ion trapping in the IAWs. Here, the nonlinear behavior of IAWs is simulated with a multi-ion species Vlasov code, including interspecies ion–ion collisions, self-collisions, and electron–ion pitch-angle collisions. The effect of collisions on the trapping of ions and electrons in a large-amplitude IAW is studied in a regime of relevance to current Inertial Confinement Fusion experiments. Our simulations show that collisions can scatter trapped particles out of resonance with the IAW, suppressing trapping and helping to maintain an effective Landau damping of the IAW. The IAW amplitude required to trap particles in the presence of strong collisions is estimated analytically. These estimates are tested for strongly damped IAWs in tantalum oxide and pure helium plasmas. Here our simulations show that, above a threshold amplitude, the damping is reduced by an amount inversely proportional to the wave amplitude. Thus, the success of controlling SBS using a multispecies plasma may depend sensitively on laser power and pulse length.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Ion transport on phased radiofrequency carpets in xenon gas

We present the design and performance of a four-phased radiofrequency (RF) carpet system for ion transport between 200–600 mbar, significantly higher than previously demonstrated RF carpet applications. The RF carpet, designed with a 160 μm pitch, is applied to the lateral collection of ions in xenon at pressures up to 600 mbar. We demonstrate transport efficiency of caesium ions across varying pressures, and compare with microscopic simulations made in the SIMION package. The novel use of an N-phased RF carpet can achieve ion levitation and controlled lateral motion in a denser environment than is typical for RF ion transport in gases. This feature makes such carpets strong candidates for ion transport to single ion sensors envisaged for future neutrinoless double-beta decay experiments in xenon gas.

ion transport↗
DOE OSTI2024

Implementation of a real-time MSE system

Motional Stark effect polarimetry is a key diagnostic for plasma fusion research since its usage on PBX-M. The MSE diagnostic measures the radial magnetic pitch angle profile in a plasma from a neutral beam by observation of Stark split D-alpha emission from atoms excited by collision with ions and electrons in the plasma. The pitch angle measurement is used with equilibrium reconstruction codes to determine the q-profile for studies of plasma stability, confinement, and transport. Historically, the algorithm was used in a post-processing fashion. The goal of our work was to apply this method in real time and pass the results to the plasma control system computer for real-time equilibrium reconstruction and control.

Instruments & Instrumentation↗
DOE OSTI2022

Ion and Electron Acceleration in Fully Kinetic Plasma Turbulence

Turbulence is often invoked to explain the origin of nonthermal particles in space and astrophysical plasmas. By means of 3D fully kinetic particle-in-cell simulations, we demonstrate that turbulence in low-β plasmas (β is the ratio of plasma pressure to magnetic pressure) accelerates ions and electrons into a nonthermal energy distribution with a power-law energy range. The ion spectrum is harder than the electron one, and both distributions get steeper for higher β. We show that the energization of electrons is accompanied by a significant energy-dependent pitch-angle anisotropy, with most electrons moving parallel to the local magnetic field, while ions stay roughly isotropic. We demonstrate that particle injection from the thermal pool occurs in regions of high current density. Parallel electric fields associated with magnetic reconnection are responsible for the initial energy gain of electrons, whereas perpendicular electric fields control the overall energization of ions. Our findings have important implications for the origin of nonthermal particles in space and astrophysical plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Effect of secondary gas-phase reactions (SGR) in pyrolysis of carbon feedstocks for anisotropic carbon materials production – 3: Modifying non-coking coal tar through co-pyrolysis of coal with linear low-density polyethylene and high-impact polystyrene

Herein, this work focuses on co-pyrolysis experiments of Utah Sufco coal with linear low-density polyethylene (LLDPE) and high-impact polystyrene (HIPS). These two plastic types have differing pyrolysis chemistries and have different hydrogen transfer behavior. Similar to earlier work in this series of papers, controlled secondary gas-phase reactions during pyrolysis were used to induce cracking and condensation reactions among the pyrolytic tar species. Co-pyrolysis tests were performed with feed plastic percentages ranging from 10-20 wt% and pyrolysis SGR temperatures ranging from 800-900°C. Analyses of the intermediate tar products showed that oxygen contents and aromaticity were substantially different, depending on the plastic, and resulting pitch softening points and mesophase contents also varied greatly depending on the starting plastic feedstock used. Most of the synergies observed in the co-pyrolysis results were negative, except for the oxygen content. Oxygen contents were higher than expected when LLDPE was used, resulting in reactive pitches with softening points > 350°C. On the other hand, oxygen contents were lower than expected when HIPS was used, resulting in less reactive pitches. Ultimately, only the HIPS/coal samples created at the SGR temperature of 900°C had reasonable softening points at or under 350°C, making them the only samples created in this work potentially suitable for mesophase pitch-based carbon fiber production. The success in creating fusible mesophase pitches from co-pyrolyzing HIPS with Utah Sufco coal is likely attributed to the fact that polystyrene is a stronger hydrogen acceptor rather than donor, which should facilitate more cracking rather than stabilizing tar oxygen functional groups, making the tar species ultimately less reactive during thermal conversion to mesophase pitch.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Interpretation of high-harmonic fast-wave propagation in the scrape-off layer of NSTX-U as a geometrically bounded-waveguide mode

This paper revisits the onset of high-harmonic fast-wave (HHFW) propagation in the scrape-off layer (SOL) plasma of the NSTX/NSTX-U spherical tokamak, motivated by past HHFW heating and current drive experiments and modelling. Previously, the fast-wave propagation in the SOL was correlated with the opening (suppression) of the fast-wave right-hand cutoff layer in front of the antenna. In this work, the SOL propagation is interpreted as a geometric waveguide mode guided by the SOL geometry, whose radial width can be comparable to the wave’s perpendicular wavelength in the HHFW regime. A two-dimensional circular model is first employed using full-wave solvers to characterise the poloidal eigenmode structures and to clarify their relationship to annulus resonance. By progressively adding a tokamak-like magnetic-field configuration, starting from a uniform axial field, the effects of magnetic-field gradients and pitch on the SOL waveguide mode are characterised. The poloidal mode numbers supported by the SOL plasma agree well with analytic estimates, indicating that an anisotropic plasma in a bounded geometry selectively supports and amplifies the resonant poloidal mode number. Additionally, two-dimensional axisymmetric NSTX-U simulations demonstrate that the SOL eigenmode features identified in the circular model persist in the experimentally relevant configurations. A control approach based on lengthening the wave perpendicular wavelength relative to the SOL width, including a higher magnetic (B)-field operation, is discussed. The analysis here shows the key role of a bounded geometry in interpreting HHFW eigenmode coupling and propagation in the NSTX-U SOL plasma.

plasma heating↗
DOE OSTI2026

Gearbox bearing crack growth prognostics and uncertainty quantification with physics-informed machine learning

This paper introduces the extreme theory of functional connections (X-TFC), a physics-informed machine learning algorithm, and tailors it to estimate the remaining useful life (RUL) of wind turbine gearbox bearings experiencing fatigue crack growth. Unlike purely data-driven methods, X-TFC embeds a physics model, based on Head's theory in this work, into its training objective. The core of X-TFC is a random-projection single-layer neural network trained via an extreme learning machine, which requires only limited damage progression data and solves for output weights with a least-squares optimization algorithm. A composite loss function balances the network's fit to observed degradation data against the residuals of the governing crack growth differential equation, ensuring the learned damage trajectory remains physically plausible. When applied to a vibration-based health-index (HI) dataset measured during the growth of a crack on the inner ring of a high-speed bearing in a wind turbine gearbox (Bechhoefer and Dubé, 2020), X-TFC achieves near-zero prediction bias. Even when trained on only the first 10 %–20 % of the damage progression data, with sufficient physics weighting its predictions remain monotonic and smooth, delivering high prognosability and trendability. To quantify the epistemic uncertainty, we employ a Monte Carlo ensemble of independently initialized X-TFC models trained on noise-perturbed data, which yields confidence intervals around each RUL estimate and captures both model-parameter and epistemic uncertainty. In addition to a vibration-based HI, we demonstrate that the proposed framework can be directly applied to a supervisory control and data acquisition (SCADA) data-based HI (Eftekhari Milani et al., 2026) measured during similar wind turbine gearbox bearing crack faults, preserving its accuracy and interpretability. This extension shows the versatility of our approach, which is applicable to bearings of multiple gearbox manufacturers, models, and ratings using only SCADA data. By integrating domain knowledge with machine learning, X-TFC offers a rapid, reliable tool for crack prognostics. Its adaptability to other bearing failure modes, such as pitch bearing ring cracks, positions X-TFC as a powerful enabler of data-driven, physics-informed asset management in the wind energy sector and beyond.

17 WIND ENERGY↗
DOE OSTI2023

Reconstruction of tokamak plasma safety factor profile using deep learning

Abstract The motional Stark effect (MSE) diagnostic has been a standard measurement for the magnetic field line pitch angle in tokamaks that are equipped with neutral beams. However, the MSE data are not always available due to experimental constraints, especially in future devices without neutral beams. Here we develop a deep-learning based model (SGTC-QR) that can reconstruct the safety factor profile without the MSE diagnostic to mimic the traditional equilibrium reconstruction with the MSE constraint. The model demonstrates promising performance, and the sub-millisecond inference time is compatible with the real-time plasma control system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Forming a database to study reversed magnetic shear from the National Spherical Torus eXperiment using machine learning

Achieving a long-lived reversed magnetic shear (RMS) target plasma in the National Spherical Torus eXperiment Upgrade will require developing various sustainment scenarios. To help with the ongoing plasma control efforts, the development of a new analysis for the motional Stark effect (MSE) diagnostic using a machine learning algorithm, namely, MSE-ML, is described. MSE-ML will be used to identify patterns during RMS discharges, some of which suffer magnetohydrodynamic (MHD) events resulting in current redistribution and monotonic q-profiles. A database consisting of q and magnetic shear profiles is being constructed primarily based on the existing National Spherical Torus eXperiment data with equilibrium reconstructions constrained by the magnetic field pitch angle profile measured using the multi-channel MSE diagnostic. An unsupervised k-means clustering of the data is developed to study the RMS formation as a function of time. The initial clustering from the q-profiles shows significant differences in both amplitude and the duration of the RMS period. As a goal, the clustering results that detect and distinguish shots with substantial and sustained RMS are to be used as a preprocessing step in a supervised algorithm to identify the underlying conditions that lead to long-lasting improved confinement with RMS. Another aim of the MSE-ML study is to identify precursors of RMS-destroying MHD events in either derived data such as the q-profile or directly measured data such as the magnetic field pitch angle profile.

Uzun-Kaymak, I. U. (ORCID:0000000276251493)↗
DOE OSTI2024

Novel plasma actuator for mitigation of dynamic stall

A novel plasma actuator, the Linear Counter-flow using a Point Embedded Electrode (LCPEE), is developed for the prevention of dynamic stall for a sinusoidal pitching movement between α = 4° and α = 18°. The LCPEE is implemented on a NACA0012 airfoil and tested at a Reynolds Number of Re c = 2 × 105 and reduced frequency of k = π/16. Prior investigations using a standard linear actuator showed that the exposed electrode introduced perturbations passively which delayed dynamic stall when the actuator was off. For the LCPEE actuator, when turned off, there is least passive delay. When the LCPEE is turned on at St f = 50, the dynamic stall is prevented for the sinusoidal pitching motion of the airfoil. The LCPEE actuator is also tested for the same sinusoidal motion between α = 6° and α = 20°. Four cases are considered for the higher α range of motion: actuator off, actuator on at St f = 50 with a sinusoidal input waveform, actuator on at St f = 50 with a triangular input waveform, and actuator on at Stf = 100 with a sinusoidal input waveform. Specifically for the last case, experiment shows no flow reversal demonstrating the efficacy of LCPEE in controlling the dynamic stall. The effects of LCPEE on the flow energy distribution have also been studied by using proper orthogonal decomposition (POD) method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Disruption Prediction and Avoidance in High Beta Long Pulse KSTAR Plasmas

This research is a concentrated and coordinated experimental and physics analysis program by a small U.S. team, focused on the topical area of “Long Pulse Control” as stated in the proposal solicitation. The overall goal of the research is to produce world-class analysis regarding forecasting and avoidance of disruptions in a long-pulse, superconducting tokamak at high stability parameters (e.g. normalized beta) with direct, quantifiable figures of merit (i.e. plasma disruption rate - “disruptivity”) and its reduction based on improved stability physics and control. The research targets the backbone of the problem – the basic, main issues – to produce this quantitative analysis by: (1) Creating and applying a new physics-based paradigm to understand how to eliminate disruptions: disruption event characterization, and event chain analysis – a direct manifestation of the approach suggested in the DOE Transients Report, (2) Ensuring that the components required to produce high-quality measurements and analysis needed for disruption event characterization for the tokamak in question (here, KSTAR) exist (e.g. pressure profile peaking, high-accuracy pitch angle data, compensated low frequency toroidal mode number n = 1 mode measurement) to create a primarily physics-based disruption forecasting capability, and (3) Addressing disruption avoidance for the first time in KSTAR by attacking primary disruption ‘event chains’, utilizing the most important associated plasma measurements (dynamic n = 1 field). The focus of this work will be avoidance of macroscopic instabilities, especially global modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Camera / Raw Data

The SUMR-D CART2 turbine data are recorded by the CART2 wind turbine's supervisory control and data acquisition (SCADA) system for the Advanced Research Projects Agency–Energy (ARPA-E) SUMR-D project located at the National Renewable Energy Laboratory (NREL) Flatirons Campus. For the project, the CART2 wind turbine was outfitted with a highly flexible rotor specifically designed and constructed for the project. More details about the project can be found here: https://sumrwind.com/. The data contain video data of the wind turbine blades during operation as well as while parked. Since the blades had a coning angle, the blades are only in frame of the video camera when the blades are in a pitched to run configuration.

17 WIND ENERGY↗