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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

FAST.Farm Development and Validation of Structural Load Prediction Against Large Eddy Simulations

FAST.Farm is a mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. FAST.Farm is based on several principles of the dynamic wake meandering (DWM) model, but also addresses limitations of previous DWM implementations. Previous FAST.Farm studies have shown the similarities and differences between FAST.Farm and large eddy simulations for rigid turbine cases. The objective of this work is to quantify the ability of FAST.Farm to accurately predict turbine structural response in a small wind farm. This is done by comparing FAST.Farm structural response to SOWFA-OpenFAST results for three laterally-aligned turbines. The purpose of this study is to characterize the similarities and differences between FAST.Farm and a higher fidelity model for predicting turbine structural response in a wind farm for differing atmospheric inflows. Strong statistical agreement was found between FAST.Farm and SOWFA-OpenFAST structural response for the non-waked upstream turbine, and good agreement was found for the downstream turbines for most structural quantities. Higher differences were seen for downstream turbines with low ambient turbulence intensity or yawed turbines, suggesting areas for FAST.Farm wake dynamics modeling improvements. For all cases and turbines, small statistical differences were seen between blade deflections and bending moments, with larger differences for tower-top and tower-base bending moments. Overall, the results establish confidence for applying FAST.Farm to wind farm power and loads analyses and identify areas where further model validations and model improvements should be targeted.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2021

Mechanisms of Dynamic Near-Wake Modulation of a Utility-Scale Wind Turbine

The current study uses large eddy simulations to investigate the transient response of a utility-scale wind turbine wake to dynamic changes in atmospheric and operational conditions, as observed in previous field-scale measurements. Most wind turbine wake investigations assume quasi-steady conditions, but real wind turbines operate in a highly stochastic atmosphere, and their operation (e.g. blade pitch, yaw angle) changes constantly in response. Furthermore, dynamic control strategies have been recently proposed to optimize wind farm power generation and longevity. Therefore, improved understanding of dynamic wake behaviours is essential. First, changes in blade pitch are investigated and the wake expansion response is found to display hysteresis as a result of flow inertia. The time scales of the wake response to different pitch rates are quantified. Next, changes in wind direction with different time scales are explored. Under short time scales, the wake deflection is in the opposite direction of that observed under quasi-steady conditions. Finally, yaw changes are implemented at different rates, and the maximum inverse wake deflection and time scale are quantified, showing a clear dependence on yaw rate. To gain further physical understanding of the mechanism behind the inverse wake deflection, the streamwise vorticity in different parts of the wake is quantified. The results of this study provide guidance for the design of advanced wake flow control algorithms. The lag in wake response observed for both blade pitch and yaw changes shows that proposed dynamic control strategies must implement turbine operational changes with a time scale of the order of the rotor time scale or slower.

flow-structure interactions↗
DOE OSTI2023

Structure, Kinematics, and Observability of the Large Magellanic Cloud’s Dynamical Friction Wake in Cold versus Fuzzy Dark Matter

Abstract The Large Magellanic Cloud (LMC) will induce a dynamical friction (DF) wake on infall to the Milky Way (MW). The MW’s stellar halo will respond to the gravity of the LMC and the dark matter (DM) wake, forming a stellar counterpart to the DM wake. This provides a novel opportunity to constrain the properties of the DM particle. We present a suite of high-resolution, windtunnel-style simulations of the LMC's DF wake that compare the structure, kinematics, and stellar tracer response of the DM wake in cold DM (CDM), with and without self-gravity, versus fuzzy DM (FDM) with m a = 10 −23 eV. We conclude that the self-gravity of the DM wake cannot be ignored. Its inclusion raises the wake’s density by ∼10%, and holds the wake together over larger distances (∼50 kpc) than if self-gravity is ignored. The DM wake’s mass is comparable to the LMC’s infall mass, meaning the DM wake is a significant perturber to the dynamics of MW halo tracers. An FDM wake is more granular in structure and is ∼20% dynamically colder than a CDM wake, but with comparable density. The granularity of an FDM wake increases the stars’ kinematic response at the percent level compared to CDM, providing a possible avenue of distinguishing a CDM versus FDM wake. This underscores the need for kinematic measurements of stars in the stellar halo at distances of 70–100 kpc.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Spectral proper orthogonal decomposition of active wake mixing dynamics in a stable atmospheric boundary layer

Recent advancements in the use of active wake mixing (AWM) to reduce wake effects on downstream turbines open new avenues for increasing power generation in wind farms. However, a better understanding of the fluid dynamics underlying AWM is still needed to make wake mixing a reliable strategy for wind farm flow control. In this work, a spectral proper orthogonal decomposition (SPOD) is used to analyze the dynamics of coherent flow structures that are induced in the wake through blade pitch actuation. The data are generated using the ExaWind software suite to perform large eddy simulations of an NREL 2.8 MW turbine operating in a stable atmospheric boundary layer. SPOD tracks the modal behavior of flow structures from their generation in the turbine induction field through their growth in the near-wake region and to their subsequent evolution and energy transfers in the far wake. SPOD is shown to be a useful tool in the context of AWM because it translates the wavenumber and frequency inputs to the turbine controller to structures in the wake. A decomposition of the radial shear stress flux in the wake is also developed using SPOD to measure the contribution of coherent flow structures to mean flow turbulent entrainment and wake recovery. The effectiveness of AWM is connected to its ability to excite inherent structures in the wake of the turbine that arise using baseline controls. The effects of AWM on blade loading are also analyzed by connecting the axial force along the blade to the SPOD analysis of the turbine induction field. Lastly, the performance of different AWM strategies is demonstrated in a two-turbine array.

17 WIND ENERGY↗
NASA NTRS1994

Sensitivity of lag-damping correlations to structural and aerodynamic approximations of isolated experimental rotors in forward flight

The predictions of regressive lag-mode damping levels are correlated with the database of an isolated, soft-inplane, three-blade rotor operated untrimmed. The database was generated at the Army Aeroflightdynamics Directorate at Ames. The correlation covers a broad range of data, from near-zero thrust conditions in hover to high-thrust and highly stalled conditions in forward flight with advance ratio as high as 0.55 and shaft angle as high as 20 degrees. In the experimental rotor, the airfoil or blade portion has essentially uniform mass and stiffness distributions, but the root flexure has highly nonuniform mass and stiffness distributions. Accordingly, the structural approximations refer to four models of root-flexure-blade assembly. They range from a rigid flap-lag model to three elastic flap-lag-torsion models, which differ in modeling the root flexure. The three models of root-flexure are: three root springs in which the bending-torsion couplings are fully accounted for; a finite-length beam element with some average mass and stiffness distributions such that the fundamental frequencies match those of the experimental model; and accurate modal representation in which the actual mass and stiffness distributions of the experimental root-flexure-blade assembly are used in calculating the nonrotating mode shapes. The four models of root-flexure-blade assembly are referred to as the rigid flap-lag model, spring model, modified model and modal model. For each of these four models of the root-flexure-blade assembly, the predictions are based on the following five aerodynamic theories: ear theory, which accounts for large angle-of-attack and reverse-flow effects on lift, and has constant drag and pitching moment; quasisteady stall theory, which includes quasisteady stall lift, drag and pitching moment characteristics of the airfoil section, dynamics stall theory, which uses the ONERA dynamic stall models of lift, drag and pitching moment; dynamic wake theory, which is based on a finite-state three-dimensional wake model and includes all wake effects including both shed and trailing vorticity; and dynamics and wake theory, which combines both dynamic stall theory and dynamic wake theory and is a relatively complete aerodynamic representation.

Gaonkar, G. H.↗
NASA NTRS1975

Additional experiments with a four-bladed cyclic pitch stirring model rotor, part 2 of second yearly report

The four bladed pitch stirring rotor model was used in a rotor dynamic wake survey at zero advance ratio, covering 2 deg, 5 deg and 8 deg collective pitch settings. Dynamic wake data were taken in planes .12 and .20 radii below the rotor disk and are to be compared with analytical wake data with parameters to be identified from pitch stirring transients. The model was modified to perform such transients. The instrumentation developed for this purpose is described together with the method of data acquisition and with the test procedures. The hardware and software for several data handling systems are discussed. These systems extract from pitch stirring transients the parameters of analytical dynamic rotor wake models.

Hohenemser, K. H.↗
NASA NTRS1989

The dynamics of charged particles in the near wake of a very negatively charged body - Laboratory experiment and numerical simulation

A numerical simulation that is cylindrical in configuration space and three-dimensional in velocity space has been initiated to test a model for the near-wake dynamics of a very negatively charged body, with reference to the plasma environment around spacecraft. The simulation parameters were closely matched to those of a laboratory experiment so that the results can be compared directly. The laboratory study showed that the electrons and ions can display different temporal features in the filling-in of the wake; and that they can both be found within one body diameter of an object with a highly negative body potential. It was also found that the temperature of the electrons in the very near wake could be somewhat colder than the ambient value, suggesting the possibility of a filtering mechanism being operative there. The simulation results to date largely corroborate the density findings.

Morgan, M. Alvin↗
DOE OSTI2020

Validation of FAST.Farm Against Full-Scale Turbine SCADA Data for a Small Wind Farm

FAST.Farm is a new midfidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. FAST.Farm is based on some of the principles of the Dynamic Wake Meandering model—including passive tracer modeling of wake meandering—but addresses many of the limitations of previous Dynamic Wake Meandering (DWM) implementations. Previous FAST.Farm verification studies show the similarities and differences between FAST.Farm and large-eddy simulations for rigid and flexible turbines. In this validation study, FAST.Farm turbine responses are compared to multiturbine measurements from a subset of a full-scale wind farm. FAST.Farm predictions of turbine generator power, rotor speed, and blade pitch for five-turbine simulations are compared to supervisory control and data acquisition results. Results reveal that FAST.Farm generator power mean and standard deviation results reasonably match measured data for upstream and downstream turbines, as well as the mean rotor speed and blade pitch above rated wind speeds. However, FAST.Farm generally underpredicts the mean rotor speed and overpredicts the mean blade pitch below rated operation. These errors are likely related to inaccuracies in the generic controller simulated. Despite controller differences, FAST.Farm predicts the same overall relative rotor power trends for all waked turbines at all wind speeds.

17 WIND ENERGY↗
NASA NTRS1993

Flap-lag damping in hover and forward flight with a three-dimensional wake

Prediction of lag damping is difficult owing to the delicate balance of drag, induced drag and Coriolis forces in the in-plane direction. Moreover, induced drag is sensitive to dynamic wake, both shed and trailing components, and thus its prediction requires adequate unsteady-wake representation. Accordingly, rigid-blade flap-lag equations are coupled with a three-dimensional finite-state wake model; three isolated rotor configurations with three, four and five blades are treated over a range of thrust levels, Lock numbers, lag frequencies and advance ratios. The investigation includes convergence characteristics of damping with respect to the number of radial shape functions and harmonics of the wake model for multiblade modes of low frequency (less than 1/rev.) to high frequency (greater than 1/rev.). Predicted flap and lag damping levels are then compared with similar predictions with (1) rigid wake (no unsteady induced flow, (2) Loewy lift defficiency and (3) dynamic inflow. The coverage also includes correlations with the measured lag regressive-mode damping in hover and forward flight and comparisons with similar correlations with dynamic wake model are consistently higher than the predictions with the dynamic inflow model; even for the low frequency lag regressive mode, the number of wake harmonics should at least be equal to twice the number of blades.

Manjunath, A. R.↗
DOE OSTI2023

Comparison of three DWM-based wake models at above-rated wind speeds

In this study we investigate three mid-fidelity wind turbine wake models based on the dynamic wake meandering (DWM) model principle, and compare their performance with a reference dataset, produced with large-eddy simulations using the actuator line model. The models are compared with respect to flow field, power, and loads on a row of four 5MW reference turbines experiencing above-rated wind conditions. In general, the DWM models show fairly good agreement with large-eddy simulation for the time-averaged flow fields, blade forces and power, with increasing differences along the turbine row. Also when comparing fatigue loads of blade root moments, the differences between the models increase further into the row, with deviations up to 25 % of the reference case. However, while the development in blade root moment fatigue along the turbine row is predominantly driven by the energy content at the frequency corresponding to the turbine's rotational period (1 P ) for the DWM models, the large-eddy simulation results suggest that the key drivers for the blade root and tower loads are the increase in meandering and energy at higher frequencies (> 1 P ) deeper into the turbine row. For the tower loads, the DWM models highly underestimate the fatigue for the waked turbines. From these results, we suggest priorities for future model developments so that robust model implementations can be used in wind farm design and operation.

17 WIND ENERGY↗
DOE OSTI2025

Modeling and Analysis of Wind Turbine Wake Vortex Evolution Due to Time-Constant Spatial Variations in Atmospheric Flow

Modern utility-scale wind turbines are evolving toward larger, lighter, and more flexible designs to meet the growing demand for renewable energy while minimizing logistical costs. However, these advancements in lightweight design result in heightened aeroelastic sensitivity, leading to complex interactions which affect the rotor’s capacity to withstand aerodynamic loading and the cascading effects that manifest in the wake’s vortex-structure evolution under variable atmospheric conditions. In this paper, we analyze the influence of stream-wise fluctuating atmospheric flow conditions on wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex–wake interactions for a range of conditions with spatially variant atmospheric flow. CODEF solutions for turbine operation in wind conditions featuring only one parameter fluctuation are compared to wind conditions with several wind parameter variations in combination. By isolating individual inflow variations and comparing them to multi-parameter scenarios, we determine the contributions of each atmospheric factor to rotor dynamics, wake evolution, and downstream wind farm interactions. The purpose of this paper is to analyze the effects of spatial variations in atmospheric flow on the topological evolution of wind turbine vortex wakes, which constitutes a gap in the current understanding of wind turbine wake dynamics. The insights gained from this study are particularly valuable for the development of wind farm control strategies aimed at mitigating the adverse effects of wake interactions, enhancing energy capture, and improving the overall stability of wind farm operations. With these insights, we aim to contribute to the development of modeling and simulation tools to optimize utility-scale wind power plants operating in diverse atmospheric environments.

Farrell, Alayna (ORCID:000000023555720X)↗
DOE OSTI2022

Magnetic excitations, nonclassicality, and quantum wake spin dynamics in the Hubbard chain

Recent work has demonstrated that quantum Fisher information (QFI), a witness of multipartite entanglement, and magnetic Van Hove correlations G(r,t), a probe of local real-space real-time spin dynamics, can be successfully extracted from inelastic neutron scattering on spin systems through accurate measurements of the dynamical spin structure factor S(k,ω). In this work, we apply theoretically these ideas to the half-filled Hubbard chain with nearest-neighbor hopping, away from the strong-coupling limit. This model has nontrivial redistribution of spectral weight in S(k,ω) going from the noninteracting limit (U = 0) to strong coupling (U→∞), where it reduces to the Heisenberg quantum spin chain. We use the density matrix renormalization group to find S(k,ω), from which QFI is then calculated. We find that QFI grows with U. With realistic energy resolution it becomes capable of witnessing bipartite entanglement above U=2.5 (in units of the hopping), where it also changes slope. This point is also proximate to slope changes of the bandwidth W(U) and the half-chain von Neumann entanglement entropy. We compute G(r,t) by Fourier transforming S(k,ω). The results indicate a crossover in the short-time short-distance dynamics at low U characterized by ferromagnetic light-cone wavefronts, to a Heisenberg-type behavior at large U featuring antiferromagnetic light cones and spatially period-doubled antiferromagnetism. We find this crossover has largely been completed by U=3. Our results thus provide evidence that, in several aspects, the strong-coupling limit of the Hubbard chain is reached qualitatively already at a relatively modest interaction strength. We discuss experimental candidates for observing the G(r,t) dynamics found at low U.

1-dimensional systems↗
NASA NTRS1981

Dynamics of wakes downstream of wind turbine towers

The near field wakes downstream of circular cylinders and of 12 sided cylinders were surveyed in a wind tunnel. Local velocity and velocity deficit diagrams are presented. The variation of turbulence in the wake was surveyed and the frequency of the periodic component of wake motion was determined. Differences between wakes of circular cylinders and of 12 sided cylinders are discussed. Also effects of strakes, orientation of the 12 sided cylinders, and rounding of the corners are noted.

Snyder, M. H.↗
NASA NTRS1996

Predictions of Control Inputs, Periodic Responses and Damping Levels of an Isolated Experimental Rotor in Trimmed Flight

Since the early 1990s the Aeroflightdynamics Directorate at the Ames Research Center has been conducting tests on isolated hingeless rotors in hover and forward flight. The primary objective is to generate a database on aeroelastic stability in trimmed flight for torsionally soft rotors at realistic tip speeds. The rotor test model has four soft inplane blades of NACA 0012 airfoil section with low torsional stiffness. The collective pitch and shaft tilt are set prior to each test run, and then the rotor is trimmed in the following sense: the longitudinal and lateral cyclic pitch controls are adjusted through a swashplate to minimize the 1/rev flapping moment at the 12 percent radial station. In hover, the database comprises lag regressive-mode damping with pitch variations. In forward flight the database comprises cyclic pitch controls, root flap moment and lag regressive-mode damping with advance ratio, shaft angle and pitch variations. This report presents the predictions and their correlation with the database. A modal analysis is used, in which nonrotating modes in flap bending, lag bending and torsion are computed from the measured blade mass and stiffness distributions. The airfoil aerodynamics is represented by the ONERA dynamic stall models of lift, drag and pitching moment, and the wake dynamics is represented by a state-space wake model. The trim analysis of finding, the cyclic controls and the corresponding, periodic responses is based on periodic shooting with damped Newton iteration; the Floquet transition matrix (FTM) comes out as a byproduct. The stabillty analysis of finding the frequencies and damping levels is based on the eigenvalue-eigenvector analysis of the FTM. All the structural and aerodynamic states are included from modeling to trim analysis. A major finding is that dynamic wake dramatically improves the correlation for the lateral cyclic pitch control. Overall, the correlation is fairly good.

Gaonkar, G. H.↗