arXiv subjects

Charles Meneveau

Publications and source records attributed to Charles Meneveau.

At least 19 recordsLinked to original sources

arXiv2026

Actuator Disk Models reproduce Actuator Line Model power and thrust fluctuation statistics in wind farm simulations

Actuator-disk models (ADM) are widely used in wind-farm simulations, but their accuracy in reproducing power and thrust temporal fluctuation statistics has not yet been compared to the more accurate and detailed predictions of actuator-line models (ALM). This work provides a detailed comparison of such model predictions under three distinct atmospheric conditions. Data is obtained from a database (JHTDB-Wind) containing actuator-line turbine-response and time-resolved flow field data from a large-eddy simulation of a small windfarm operating over a full diurnal cycle. Power and thrust time series corresponding to ADM are constructed from disk-averaged velocity signals and compared with the corresponding more detailed actuator-line signals over three temporal windows within the diurnal cycle. The analysis compares time series, power spectral densities, and both the fluctuation and increment probability density distributions. The results show that the ADM time-series capture the dominant temporal, spectral, and statistical features of the ALM values at resolved and disk-averaged flow-field time scales, i.e. slower than the rotor frequency. Effects of temporal filtering that are often applied to ADM inputs are examined. Overall, the results provide strong support for the use of ADM for predicting power and thrust fluctuation statistics in wind-farm simulations.

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arXiv2026

Wind farms as sensor arrays of turbulent boundary layer spatio-temporal flow structure

Temporal fluctuations of wind farm-generated power arise from the interaction between atmospheric turbulence, turbine properties, and wind-farm layout. However, accurately characterizing these fluctuations remains an open challenge. We here present and extend an analytical framework to predict the temporal spectrum of wind farm power-fluctuations, and compare its predictions with detailed large-eddy-simulations (LES) of a wind farm operating within a conventionally neutral boundary layer. The modeling framework assembles several established concepts from turbulent boundary layer physics: a spatio-temporal turbulence spectral model accounting for mean advection and assuming random sweeping by large eddies, a top-down wind farm model of a fully developed wind turbine array boundary layer flow providing the required mean-flow and turbulence scales, and a spatial sampling kernel representing turbine positions and finite rotor size. The latter is extended to three dimensions to represent filtering of spatial fluctuations of turbulence along the vertical direction. Using only atmospheric, turbine, and layout parameters, the model predictions are evaluated against an extensive LES database of a large wind farm on flat terrain. The model accurately predicts the aggregate power frequency spectrum, including peaks associated with advection between turbine rows, the decay of inertial-range turbulence fluctuations due to rotor averaging, and spectra of aggregate power signals from various arrangements of groups of turbines within the array (e.g. staggered or random subsets). The ability to predict wind power fluctuation spectra from fundamental fluid dynamics and existing boundary layer turbulence models could help improve wind farm grid integration.

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arXiv2026

Data-driven impeller model for efficient large eddy simulations of metastable von Kármán flows

The von Kármán turbulent swirling flow exhibits intriguing large-scale metastable dynamics, including low-frequency state switching. The study of state switching demands long-duration high-fidelity simulations at high Reynolds numbers that capture the flow generated by the impellers. Blade-resolved Large Eddy Simulations (LES) are computationally prohibitive, limiting access to these slow dynamics. Here, we develop a model for the action of the impellers on the flow using experimental data from Particle Image Velocimetry (PIV) and torque measurements of the von Kármán flow. The impeller-region velocity is parametrized via B-splines and coupled to the LES through momentum forcing. An initial set of B-spline coefficients is inferred using the Optimizing a DIscrete Loss (ODIL) framework constrained by the Reynolds-Averaged Navier--Stokes (RANS) equations, PIV measurements in the optically accessible portion of the device, and impeller torque measurements. The coefficients are then refined by the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), which minimizes the discrepancy between the LES time-averaged velocity and torque and their experimental counterparts. Using the data-driven impeller model, we perform long-duration LES of the von Kármán flow. We find that the simulation reproduces the mean flow in the bulk and displays metastable state-switching dynamics. We further show that these metastable states are not axisymmetric and consist of an alternating four-cell flow pattern that slowly rotates around the axis of the cylindrical vessel. The proposed approach provides a practical and computationally efficient route to investigating large-scale dynamics in impeller-driven turbulent flows.

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arXiv2026

The multifractal nature of turbulent energy dissipation

The intermittency of the rate of turbulent energy dissipation $ε$ is investigated experimentally, with special emphasis on its scale-similar facets. This is done using a general formulation in terms of multifractals, and by interpreting measurements in that light. The concept of multiplicative processes in turbulence is (heuristically) shown to lead to multifractal distributions, whose formalism is described in some detail. To prepare proper ground for the interpretation of experimental results, a variety of cascade models is reviewed and their physical contents are analysed qualitatively. Point-probe measurements of $ε$ are made in several laboratory flows and in the atmospheric surface layer, using Taylor's frozen-flow hypothesis. The multifractal spectrum $f(α)$ of $ε$ is measured using different averaging techniques, and the results are shown to be in essential agreement among themselves and with our earlier ones. Also, long data sets obtained in two laboratory flows are used to obtain the latent part of the $f(α)$ curve, confirming Mandelbrot's idea that it can in principle be obtained from linear cuts through a three-dimensional distribution. The tails of distributions of box-averaged dissipation are found to be of the square-root exponential type, and the implications of this finding for the $f(α)$ distribution are discussed. A comparison of the results to a variety of cascade models shows that binomial models give the simplest possible mechanism that reproduces most of the observations. Generalizations to multinomial models are discussed.

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arXiv2026

Generalised actuator disk theory: wake development with turbulent entrainment

Classical actuator disk theory, developed more than a century ago, provides an idealised description of turbine rotor performance. It treats a rotor as an infinitesimally-thin permeable disk and applies the governing flow equations over a streamtube encompassing the disk. A well-known limitation of the theory is its assumption of ideal flow downstream of the disk, which restricts its applicability to short downwind distances before turbulence and mixing processes governing the wake evolution take hold. The classical theory also leads to unphysical predictions of thrust and power coefficients for highly-loaded rotors. Turbulent axisymmetric wakes, by contrast, represent an extensively-studied canonical free shear flow with much of the progress and its applications to wind turbines limited to the far-wake dynamics. In this work, we introduce a generalised actuator disk theory based on a hybrid stream-tube and wake control volume, that seamlessly integrates classical actuator disk analysis with wake turbulence modelling at arbitrary distances from the rotor. The resulting model, while still idealised, can be used to predict variations in velocity, pressure, and cross-sectional flow area as function of position, both upstream and downstream of the rotor disk. Furthermore, by accounting for turbulent entrainment in the wake development, it provides more realistic predictions of thrust and power coefficients for highly-loaded disks.

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arXiv2025

Wind Farm Dynamics over a Diurnal Cycle: Analysis of a Comprehensive Large Eddy Simulation, Web-Services Accessible Dataset

The atmospheric boundary layer undergoes significant changes throughout a diurnal cycle, affecting wind turbine performance and wakes in wind farms. Wind farm Large Eddy Simulations (LES) under such conditions provide rich datasets to study the underlying dynamics and identify important trends. Here, we describe a comprehensive open dataset generated using LES of an 8-turbine wind farm consisting of four rows of two turbines. To avoid specifying either prescribed surface temperature or heat flux, a local 1D soil heat conduction model is used with time-periodic solar surface heating, coupled to LES. After several days of low-resolution LES, an approximately time periodic behavior is achieved, after which high-resolution LES is continued during a 24-hour period. Analysis of the LES data reveals that wind turbine wakes have a significant impact on the temperature field and spatial surface heat flux patterns and exhibiting increased surface temperature behind the wind farm at night under the specific conditions of the simulation (dry unvegetated soil, clear sky). We observe that for a few morning hours the first row of wind turbines generates less power compared to the last row. Detailed analyses of the data using innovative web-services facilitated data access tools reveal that during the morning transition, the presence of a low-level jet and the wind farm blockage effect combine to cause cooling and a reduction in wind speed at hub height upstream of the wind farm. In addition, larger turbulence levels exist downstream in the wind farm, explaining the larger power production of downstream turbines.

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arXiv2025

Surface Wave-Aerodynamic Roughness Length Model for Air-Sea Interactions

A new model to evaluate the equivalent hydrodynamic length or surface roughness, z0, of ocean waves is developed and tested. The proposed Surface Wave-Aerodynamic Roughness Length (SWARL) model requires maps of the wave surface height at consecutive times and the air flow characteristic Reynolds number as inputs. Pressure drag is accounted for by approximating the relative velocity in a frame moving with the local wave phase-speed assuming ideal inviscid ramp flow (Ayala et al. 2024). Drag from viscous and unresolved ripples is modeled using the standard equilibrium model. The SWARL model is tested using over 300 datasets for monochromatic and broad-spectrum wave surfaces. The model-predicted z0 and drag coefficients are compared to measured values, as well as commonly used wave parametrization methods found in the literature. For datasets with well-characterized surfaces, the proposed model shows significantly better agreement with data compared to prior models. For data that did not include a full characterization of the wave fields (typically field data), the model yields predictions with accuracy similar to prior models. Results highlight that including detailed flow physics and extensive wave-field characterization in the modeling of z0 can provide significant improvements in roughness-length based modeling of air-sea interactions.

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arXiv2025

Lagrangian Finite-Time Fluctuation Relation in isotropic turbulence

The entropy generation rate in turbulence can be defined using the energy cascade rate as described in the scale-integrated Kolmogorov-Hill equation at a specified length scale. The fluctuation relation (FR) from non-equilibrium thermodynamics, which predicts exponential behaviour of the ratio of probability densities for positive and negative entropy production rates, was confirmed in prior work \citep{yao2023entropy}, but under certain limiting assumptions. We here examine the applicability of FR to isotropic turbulence under less stringent assumptions by analyzing entropy generation rates averaged over intervals ranging from one to several eddy turnover times. Based on time-resolved data at a Taylor-scale based Reynolds number $Re_λ= 433$, we find that the FR is valid in the sense that very close to exponential behaviour of probability ratios of positive and negative entropy generation (forward and inverse cascade of energy) is observed. Interestingly, finite-time averaging yields FR-consistent results only within a Lagrangian framework, along fluid trajectories using filtered convective velocities. In contrast, the FR does not hold with time-averaging at fixed (Eulerian) positions. Results provide evidence that the definition of entropy generation based on the scale-integrated Kolmogorov-Hill equation describes turbulent cascade processes that exhibit properties predicted by non-equilibrium thermodynamics.

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arXiv2024

An extended analytical wake model and applications to yawed wind turbines in atmospheric boundary layers with different levels of stratification and veer

Analytical wake models provide a computationally efficient means to predict velocity distributions in wind turbine wakes in the atmospheric boundary layer (ABL). Most existing models are developed for neutral atmospheric conditions and correspondingly neglect the effects of buoyancy and Coriolis forces that lead to veer, i.e. changes in the wind direction with height. Both veer and changes in thermal stratification lead to lateral shearing of the wake behind a wind turbine, which affects the power output of downstream turbines. Here we develop an analytical engineering wake model for a wind turbine in yaw in ABL flows including Coriolis and thermal stratification effects. The model combines the new analytical representation of ABL vertical structure based on coupling Ekman and surface layer descriptions (Narasimhan, Gayme, and Meneveau, 2024a) with the vortex sheet-based wake model for yawed turbines (Bastankhah et al., 2022), as well as a new method to predict the wake expansion rate based on the Townsend-Perry logarithmic scaling of streamwise velocity variance. The proposed wake model's predictions show good agreement with Large Eddy Simulation (LES) results, capturing the effects of wind veer and yawing including the curled and sheared wake structures across various states of the ABL, ranging from neutrally to strongly stably stratified atmospheric conditions. The model significantly improves power loss predictions from wake interactions, especially in strongly stably stratified conditions where wind veer effects dominate.

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arXiv2024

A Moving Surface Drag Model for LES of Wind over Waves

Numerical prediction of the interactions between wind and ocean waves is essential for climate modeling and a wide range of offshore operations. Large Eddy Simulation (LES) of the marine atmospheric boundary layer is a practical numerical predictive tool but requires parameterization of surface fluxes at the air-water interface. Current momentum flux parameterizations primarily use wave-phase adapting computational grids, incurring high computational costs, or use an equilibrium model based on Monin-Obukhov similarity theory for rough surfaces that cannot resolve wave phase information. To include wave phase-resolving physics at a cost similar to the equilibrium model, the Moving Surface Drag (MOSD) model is introduced. It assumes ideal airflow over locally piece-wise planar representations of moving water wave surfaces. Horizontally unresolved interactions are still modeled using the equilibrium model. Validation against experimental and numerical datasets with known monochromatic waves demonstrates the robustness and accuracy of the model in representing wave-induced impacts on mean velocity and Reynolds stress profiles. The model is formulated to be applicable to a broad range of wave fields and its ability to represent cross-swell and multiple wavelength cases is illustrated. Additionally, the model is applied to LES of a laboratory-scale fixed-bottom offshore wind turbine model, and the results are compared with wind tunnel experimental data. The LES with the MOSD model shows good agreement in wind-wave-wake interactions and phase-dependent physics at a low computational cost. The model's simplicity and minimal computational needs make it valuable for studying turbulent atmospheric-scale flows over the sea, particularly in offshore wind energy research.

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arXiv2024

The wind-shade roughness model for turbulent wall-bounded flows

To aid in prediction of turbulent boundary layer flows over rough surfaces, a new model is proposed to estimate hydrodynamic roughness based solely on geometric surface information. The model is based on a fluid-mechanics motivated geometric parameter called the wind-shade factor. Sheltering is included using a rapid algorithm adapted from the landscape shadow literature, while local pressure drag is estimated using a piecewise potential flow approximation. Similarly to evaluating traditional surface parameters such as skewness or average slope magnitude, the wind-shade factor is purely geometric and can be evaluated efficiently from knowing the surface elevation map and the mean flow direction. The wind-shade roughness model is applied to over 100 different surfaces available in a public roughness database and some others, and the predicted sandgrain-roughness heights are compared to measured values. Effects of various model ingredients are analyzed, and transitionally rough surfaces are treated by adding a term representing the viscous stress component.

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arXiv2023

Vortices within vortices: hierarchical nature of vortex tubes in turbulence

The JHU turbulence database [1] can be used with a state of the art visualisation tool [2] to generate high quality fluid dynamics videos. In this work we investigate the classical idea that smaller structures in turbulent flows, while engaged in their own internal dynamics, are advected by the larger structures. They are not advected undistorted, however. We see instead that the small scale structures are sheared and twisted by the larger scales. This illuminates the basic mechanisms of the turbulent cascade.

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arXiv2023

Lagrangian modeling of a non-homogeneous turbulent shear flow: Molding homogeneous and isotropic trajectories into a jet

Turbulence is prevalent in nature and industry, from large-scale wave dynamics to small-scale combustion nozzle sprays. In addition to the multi-scale nonlinear complexity and both randomness and coherent structures in its dynamics, practical turbulence is often non-homogeneous and anisotropic, leading to great modeling challenges. In this letter, an efficient model is proposed to predict turbulent jet statistics with high accuracy. The model leverages detailed knowledge of readily available velocity signals from idealized homogeneous turbulence and transforms them into Lagrangian trajectories of a turbulent jet. The resulting spatio-temporal statistics are compared against experimental jet data showing remarkable agreement at all scales. In particular the intermittency phenomenon is accurately mapped by the model to this inhomogeneous situation, as observed by higher-order moments and velocity increment probability density functions. Crucial to the advancement of turbulence modeling, the transformation is simple to implement, with possible extensions to other inhomogeneous flows such as wind turbine wakes and canopy flows, to name a few.

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arXiv2023

Vorticity cascade and turbulent drag in wall-bounded flows: plane Poiseuille flow

Drag for wall-bounded flows is directly related to flux of spanwise vorticity outward from the wall. In turbulent flows a key contribution arises from cross-stream "vorticity cascade" by nonlinear advection and stretching of vorticity. We study this process using numerical simulation data of turbulent channel flow at $Re_τ=1000$. The net transfer from the wall of fresh spanwise vorticity created by downstream pressure drop is due to two large opposing fluxes, one which is "down-gradient" or outward from the wall, where most vorticity concentrates, and the other which is "up-gradient" or toward the wall and acting against strong viscous diffusion in the near-wall region. We present evidence that the up-gradient transport occurs by a mechanism of correlated inflow and spanwise vortex stretching that was proposed by Lighthill. This mechanism is essentially Lagrangian, but we explicate its relation to the Eulerian anti-symmetric vorticity flux tensor. As evidence for the mechanism we study (i) statistical correlations of the wall-normal velocity and of wall-normal flux of spanwise vorticity, (ii) vorticity flux cospectra that identify eddies involved in nonlinear vorticity transport in the two opposing directions, and (iii) visualizations of coherent vortex structures which contribute dominantly to the transport. The "D-type" vortices contributing dominantly to down-gradient transport in the log-layer are found to be attached, hairpin-type vortices. However, the "U-type" vortices contributing dominantly to up-gradient transport are detached, wall-parallel, pancake-shaped vortices with strong spanwise vorticity, as expected by Lighthill's mechanism. We discuss modifications to the attached eddy model and implications for turbulent drag reduction.

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arXiv2023

Analytical model coupling Ekman and surface layer structure in atmospheric boundary layer flows

We introduce an analytical model that describes the vertical structure of Ekman boundary layer flows coupled to the Monin-Obukhov Similarity Theory (MOST) surface layer representation, which is valid for conventionally neutral (CNBL) and stable (SBL) atmospheric conditions. The model is based on a self-similar total stress distribution for both CNBL and SBL flows that merges the classic 3/2 power law profile with a MOST-consistent stress profile in the surface layer. The velocity profiles are then obtained from the Ekman momentum balance equation. The same stress model is used to derive a new self-consistent Geostrophic Drag Law (GDL). We determine the ABL depth (h) using an equilibrium boundary layer height model and parameterize the surface heat flux for quasi-steady SBL flows as a function of a prescribed surface temperature cooling rate. The ABL height and GDL equations can then be solved together to obtain the friction velocity and the cross-isobaric angle as a function of known input parameters such as the Geostrophic wind velocity magnitude and surface roughness. We show that the model predictions agree well with predictions from the literature and newly generated Large Eddy Simulation (LES). These results indicate that the proposed model provides an efficient and reasonably accurate self-consistent approach for predicting the mean wind velocity distribution in CNBL and SBL flows.

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arXiv2023

Folding dynamics and its intermittency in turbulence

Fluid elements deform in turbulence by stretching and folding. In this work, by projecting the material deformation tensor onto the largest stretching direction, the dynamics of folding is depicted through the evolution of the material curvature. Results from direct numerical simulation (DNS) show that the curvature growth exhibits two regimes, first a linear stage dominated by folding fluid elements through a persistent velocity Hessian which then transitions to an exponential growth driven by the stretching of already strongly bent fluid elements. This transition leads to strong curvature intermittency at later stages, which can be explained by a proposed curvature-evolution model. The link between velocity Hessian to folding provides a new way to understand the crucial steps in energy cascade and mixing in turbulence beyond the classical linear description.

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arXiv2022

Effects of wind veer on a yawed wind turbine wake in atmospheric boundary layer flow

Large Eddy Simulations (LES) are used to study the effects of veer (the height-dependent lateral deflection of wind velocity due to Coriolis acceleration) on the evolution of wind turbine wakes. Specifically, this work focuses on turbines that are yawed with respect to the mean incoming wind velocity, which produces laterally deflected wakes that have a curled (crescent-shaped) structure. These effects can be attributed to the introduction of streamwise mean vorticity and the formation of a Counter-rotating Vortex Pair (CVP) on the top and bottom of the wake. In a Truly Neutral Boundary Layer (TNBL) in which wind veer effects are absent, these effects can be captured well with existing analytical wake models (Bastankhah et al. J. Fluid Mech. (2022), 933, A2). However, in the more realistic case of atmospheric boundary layers subjected to Coriolis acceleration, existing models need to be re-examined and generalized to include the effects of wind veer. To this end, the flow in a Conventionally Neutral Atmospheric Boundary Layer (CNBL) interacting with a yawed wind turbine is investigated in this study. Results indicate that in the presence of veer the CVP's top and bottom vortices exhibit considerable asymmetry. However, upon removing the veer component of vorticity, the resulting distribution is much more symmetric and agrees well with that observed in a TNBL. These results are used to develop a simple correction to predict the mean velocity distribution in the wake of a yawing turbine in a CNBL using analytical models. The correction includes the veer-induced sideways wake deformation, as proposed by Abkar et al. (Energies (2018), 11(7), 1838). The resulting model predictions are compared to mean velocity distributions from the LES and good agreement is obtained.

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arXiv2022

Reconstructing velocity and pressure from sparse noisy particle tracks using Physics-Informed Neural Networks

Volume-resolving imaging techniques are rapidly advancing progress in experimental fluid mechanics. However, reconstructing the full and structured Eulerian velocity and pressure fields from sparse and noisy particle tracks obtained experimentally remains a significant challenge. We introduce a new method for this reconstruction, based on Physics-Informed Neural Networks (PINNs). The method uses a Neural Network regularized by the Navier-Stokes equations to interpolate the velocity data and simultaneously determine the pressure field. We compare this approach to the state-of-the-art Constrained Cost Minimization method [1]. Using data from direct numerical simulations and various types of synthetically generated particle tracks, we show that PINNs are able to accurately reconstruct both velocity and pressure even in regions with low particle density and small accelerations. PINNs are also robust against increasing the distance between particles and the noise in the measurements, when studied under synthetic and experimental conditions.

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