Turbulent Wake Research Articles

Nonlinear feedback control of bimodality in the wake of a three-dimensional bluff body

The turbulent wake behind a square-back Ahmed body in close proximity to the ground exhibits bimodal switching. This manifests as the center of the wake randomly switching side-to-side between one of two asymmetric positions. This work is the first attempt to employ nonlinear model-based feedback control to suppress this wake bimodality. High fidelity simulations are used to develop and implement the control strategy and investigate the resulting effect on the wake and aerodynamic drag.

Coupled BEM and two-phase mixture model for surrounding flow of horizontal axial turbine over sediment seabed

Horizontal axial turbine (HAT) is widely used to extract kinetic energy from tidal current. The power absorption of HAT is largely decided by the surrounding flow. A two-phase, sediment-laden mixture model is coupled with the blade element momentum method (BEM) for the impact of HAT on surrounding flow over sediment seabed. The mixture model incorporates theoretical relative velocity, turbulence enhancement from particle wake flow and turbulence damping from high concentration sediment. A blade-induced turbulence (BIT) term is introduced into the mixture model to represent the turbulence production at blade edge. The computed velocity and turbulence are improved by the BIT term in the wake region of HAT. Three turbine hub heights are adopted to investigate the impact of the turbine on sediment seabed and the surrounding flow. Results show that with low turbine hub height, long wake region is generated after the turbine, force exerted on the turbine is asymmetric vertically and thrust and power coefficients decrease. The pattern of bed shear stress is highly dependent on the turbine hub height. The bed shear stress is enhanced under the turbine and strong scour and sediment transport tend to occur on the sediment seabed with low turbine hub height.

Turbulent planar wakes of viscoelastic fluids analysed by direct numerical simulations

Direct numerical simulations employing the finitely extensible nonlinear elastic constitutive model closed with Peterlin's approximation (FENE-P) are used to investigate the far-field region of turbulent planar wakes of viscoelastic fluids and to develop the theory describing these flows. The theoretical results display excellent agreement with the simulations and provide new scaling laws for the evolution of the shear layer thickness $\delta (x) \sim x^{1/2}$ , mean velocity deficit ${\rm \Delta} U(x) \sim x^{-1/2}$ and, for very high Deborah numbers, of the maximum polymer shear stresses $\sigma ^{[p]}_c(x) \sim x^{-2}$ and averaged polymer chain extension $\textrm {tr}(\bar {C}(x) - \boldsymbol{\mathsf{I}}) \sim x^{-2}$ , where $x$ is the streamwise distance from the solid body generating the wake. The theory is able to show the existence of self-similarity for the profiles of mean velocity, mean polymer shear stress, averaged polymer chain extension and the conditions for similarity of the turbulent shear stress, and is very well supported by the numerical simulations. Similarly to the case of viscoelastic turbulent planar jets (Guimarães et al., J. Fluid Mech., vol. 899, 2020, p. A11), when the inlet Weissenberg and Deborah numbers are sufficiently large, turbulent viscoelastic wakes exhibit a considerable reduction of the spreading rate and of the normalised Reynolds stresses. However, for very large downstream locations the turbulent viscoelastic wake recovers the classical evolution laws observed for Newtonian turbulent planar wakes.

A study on measuring wind turbine wake based on UAV anemometry system

Unmanned aerial vehicle (UAV) wind measurement is a newly developed wind measurement method that can improve the efficiency of conventional wind measurements. A method for measuring the wake characteristics of wind turbines based on UAV is proposed. The research results show that when the downstream distance was 1D, the wake wind speed and turbulence intensity at the hub height are about 60–70% and 130–150% of the incoming flow, respectively. When the downstream distance was 10D, the wake wind speed and turbulence intensity at the hub height gradually recovered to about 90% and 110% of the incoming flow, respectively, and the wake width in the area was about 2.5 times the diameter of the turbine. The wind speed measured by UAV was in good agreement with that predicted by the AV model and the 3DJG model, indicating that the Gaussian-shape curve could better describe the wake wind speed distribution. The UAV anemometry system provides a new research approach for wind turbine wake wind field measurement and the assessment of in-service wind farm resources. Moreover, the results from this study provide a reference for the determination of wind turbine wake, generation power prediction, and structure design.

Characteristics and modelling of wake for aligned multiple turbines based on numerical simulation

Wind energy has become one of the most commercially prospective renewable energies. However, the wake effect of wind turbine can reduce the power generation efficiency and increase the fatigue loading of downstream turbines. Hence, the wake effect study has attracted increasing interests. Compared with the extensive study on the single turbine wake, that on the superposition effect of multiple turbine (multi-turbine) wakes is limited. In this study, the characteristics of the wake velocity and turbulence intensity are studied and the exponential superposition model is proposed for the aligned multi-turbine wakes. Firstly, Simulator for Offshore Wind Farm Applications (SOWFA), a high-fidelity simulator for the interaction between wind turbine dynamics and the flow in a wind farm, is used to analyze the distribution of aligned multi-turbine wakes. It is observed that wakes reach the steady state from second turbine in the aligned turbines. Then influences of different factors on the accuracy of existing superposition models are studied. It is found spacing has significant effect on the performance of superposition models. Furthermore, the exponential superposition model with higher applicability is proposed for the wake velocity and turbulence intensity. Finally, this model is validated by the benchmark data of real wind farms.

Direct numerical simulation of the turbulent kinetic energy and energy dissipation rate in a cylinder wake

AbstractThe turbulent kinetic energy and energy dissipation rate in the wake of a circular cylinder are examined at a Reynolds number of 1000. The turbulence characteristics are quantified using direct numerical simulation, which provides a comprehensive dataset that is almost impossible to acquire from physical experiments. The energy dissipation rate is decomposed into the components due to the mean flow, the coherent primary vortices and the remainder. It is found that the remainder component, which develops only in a three-dimensional turbulent wake and resides mainly in the regions of vortices, accounts for 95 % and 97 % of the total dissipation rate for 10 and 20 cylinder diameters downstream of the cylinder, respectively (while the remainder accounts for 62 % and 83 % of the total turbulent kinetic energy). Based on the remainder component, the validity of local isotropy, local axisymmetry, local homogeneity and homogeneity in they–zplane for the turbulent dissipation in the wake is examined. The analysis reveals that the turbulent dissipation is largely locally homogeneous, but not locally isotropic or axisymmetric, even after the annihilation of the primary vortex street. In addition, the performances of the four corresponding surrogates to the true dissipation rate are evaluated. Owing to the general validity of local homogeneity, the surrogates of local homogeneity and homogeneity in they–zplane perform well. Although local axisymmetry does not hold, the corresponding surrogate performs well, because errors from different terms largely cancel out. However, the surrogate of local isotropy generally underestimates the true dissipation rate.

Measurements of Turbulence Generated by Wake Eddies Near a Steep Headland

AbstractTidal and low‐frequency flows interact with abrupt topographic features, giving rise to a variety of small‐scale phenomena including lee waves, vortical motions and turbulence. With the goal of identifying the processes that transfer momentum and energy between the larger‐scale and smaller‐scale flows, detailed tidally‐resolving shipboard surveys were conducted near a sharp and steep headland north of Velasco Reef, Palau, in the Western Pacific. We present velocity, microstructure and rapid‐cycling conductivity and temperature measurements, contextualized with a nearby 10‐month moored record, to examine wake and vortex structures. Observed flow near Velasco Reef was layered and multi‐directional in depth such that the “downstream” side of the headland depended on depth. Downstream of the headland, during a period where mean flow dominated over the tide in the top 100 m of the water column, turbulent kinetic energy dissipation rates were enhanced by up to three orders of magnitude relative to those upstream. During a period dominated by tides, the flow reversed periodically and wake eddies were associated with turbulent dissipation rates up to . Turbulent dissipation rates in the wake increased with inverse Richardson number for both tidal and mean flows past the headland, and were larger for stronger vorticity flows. Our analysis suggests that the eddies themselves lead to shear instabilities and subsequent turbulence, either through tilting or their limited vertical extent. We associate the enhanced downstream dissipation with a combination of breaking internal tides and either these eddy processes or a multi‐scaled turbulent wake.

Data-driven quantification of model-form uncertainty in Reynolds-averaged simulations of wind farms

Computational fluid dynamics using the Reynolds-averaged Navier–Stokes (RANS) remains the most cost-effective approach to study wake flows and power losses in wind farms. The underlying assumptions associated with turbulence closures are the biggest sources of errors and uncertainties in the model predictions. This work aims to quantify model-form uncertainties in RANS simulations of wind farms at high Reynolds numbers under neutrally stratified conditions by perturbing the Reynolds stress tensor through a data-driven machine-learning technique. To this end, a two-step feature-selection method is applied to determine key features of the model. Then, the extreme gradient boosting algorithm is validated and employed to predict the perturbation amount and direction of the modeled Reynolds stress toward the limiting states of turbulence on the barycentric map. This procedure leads to a more accurate representation of the Reynolds stress anisotropy. The data-driven model is trained on high-fidelity data obtained from large-eddy simulation of a specific wind farm, and it is tested on two other (unseen) wind farms with distinct layouts to analyze its performance in cases with different turbine spacing and partial wake. The results indicate that, unlike the data-free approach in which a uniform and constant perturbation amount is applied to the entire computational domain, the proposed framework yields an optimal estimation of the uncertainty bounds for the RANS-predicted quantities of interest, including the wake velocity, turbulence intensity, and power losses in wind farms.

Zonal Detached Eddy Simulation of the Fan-Outlet Guide Vanes Stage of a Turbofan Engine: Part I—Methodology, Numerical Setup, and Aerodynamic Analysis

Abstract This article deals with the zonal detached eddy simulation of the fan module of a modern turbofan engine for the prediction of the broadband noise due to the interaction of the fan turbulent wakes with the stationary outlet guide vanes. The simulation relies on a hybrid RANS/LES approach with a zonal strategy: the core airflow is treated in RANS, while the bypass airflow is solved with the hybrid approach. The simulation was performed during four revolutions, and statistical convergence was reached. Inspections of the flowfields highlight a consistent behavior of the shielding function (border between RANS and LES solving areas) around the blade walls and at the trailing edge for a such complex flow. The fan module was tested in the AneCom facility in which hot wire measurements were made in-between the fan and the outlet guide vanes. The numerical results are compared to this large dataset of measurements. The flow maps are well retrieved by the simulation for both the time-averaged and the turbulent quantities. Comparison of radial profiles shows an excellent agreement for the three root-mean-square (RMS) components of the velocities between zonal detached eddy simulation (ZDES) and the measurements, particularly in the tip gap flow area, in which RANS results do not reproduce correctly the flow quantities. The wake shape, a key feature in the mechanism of generation of rotor–stator interaction noise), is quite well predicted by the ZDES simulation. These numerical results demonstrate the maturity of the approach for the simulation of complex turbomachinery flows.

Effectiveness of data-driven wind turbine wake models developed by machine/deep learning with spatial-segmentation technique

In this paper, the effectiveness of three machine/deep learning algorithms, namely, the artificial neural network (ANN), convolutional neural network (CNN) and U-shape neural network (Unet), in constructing wind turbine wake modeling is investigated. In order to enhance the performance of different neural networks, the spatial-segmentation technique for wake flow field is adopted which aims to divide the original wake field configuration (4D × 50D, D is the rotor diameter) into several small pieces (each with 4D × 6.25D). This is followed by separately training the subdivided small piece of wake flow fields and the resultant sub-models are consolidated to predict the whole wake flow field. Both wake velocity field and turbulence intensity field are predicted by the wake model to facilitate its applications to alleviate both wind turbine power losses and fatigue loads caused by wake interactions. Through comparative study, it is found that by using the spatial-segmentation technique it can significantly reduce the prediction error of the wake velocity but not for the prediction of turbulence intensity. Among the three selected network structures, ANN has the best prediction performance yielding the wake model with the maximum error of 11.6 % near to the rotor place, while for other regions it is generally below 8 %. By dividing the wake flow field into pieces, the maximum error located right behind the rotor reduces to 7.2 % with others less than 6 %. Through further repetitive training analysis, it proves a better and robust wake model can be achieved by ANN with the spatial segmentation. In comparison, the prediction error of turbulence intensity field is higher, but still fairly accurate for the far wake prediction with the error less than 5 %.

Characterization Of Shock Buffet On A Supercritical 2D Airfoil In Transonic Flow

The transonic flow over the supercritical OAT15A airfoil is investigated experimentally. Using time-resolved focusing schlieren sequences, we extracted the temporal evolution of the chordwise shock location for a wide range of combinations of Mach number and angle of attack. Based on this data, we identified the conditions of pre-buffet, buffet onset, fully-established buffet, and buffet-offset behavior. Key parameters characterizing most pronounced buffet behavior are presented and quantified in terms of the shock amplitude, its variation over multiple buffet cycles, and the associated frequency of the periodic shock oscillation. Fully-established buffet is identified at a Mach number of 0.72 and angle of attack of 5 deg. It is demonstrated that these operating conditions are characterized by a quasi-sinusoidal shock oscillation at a distinct frequency of 113 Hz, in good agreement with previous studies. This analysis reveals that the harmonic shock oscillation spanning a range of about 16.5% of the airfoil chord is accompanied by a coupled large-scale variation of the global flow topology. Both instantaneous and mean velocity components in the chordwise and vertical directions are discussed for representative phases of the buffet cycle. Instantaneous vector fields of both components provide insight into the flow organization throughout the buffet cycle and allow to identify the streamwise distance traveled by the shock wave within a full cycle. We can thus precisely capture the state of the shock wave and quantify the evolution of the shock-induced separation and the size of the turbulent wake. Severe variations of the flow topology are induced by the large-scale upstream and downstream shock displacement. The results show that incidents of massive flow separation are observed for shock positions being close to the upstream limit, and more general, that the wake influence is more pronounced when induced by an upstream traveling shock wave. Phase-averaged velocity profiles at significant locations along the airfoil suction side complement this analysis. Characteristic sets of velocity profiles are discussed in detail that allow to uniquely describe the development of the flow in each phase of the buffet cycle. Detailed contours and profiles of both velocity and Reynolds shear stress contributions across the wake region highlight the strong downstream influence the shock-induced turbulent wake. Phases of severe flow separation result in reverse flow persisting until the trailing edge which further substantiates the induced momentum deficit.

Proper Orthogonal Decomposition Method for the Prediction of Fan Broadband Interaction Noise

The turbulent wake generated by a rotor interacting with outlet guide vanes (OGVs) is one of the dominant broadband noise sources in a turbofan engine. An accurate representation of the rotor wake turbulence is therefore important for the reliable prediction of the rotor–OGV interaction noise. This paper presents a turbulence synthesis method based on a spectral proper orthogonal decomposition (POD) representation of the turbulent wake that aims to reproduce the desired velocity cross-spectrum along the OGV leading edges where noise is emitted due to turbulence–OGV interaction. The method is first developed in the frequency domain based on a superposition of vortical modes with the appropriate amplitudes. Fourier modes and POD modes are proposed to represent the two-point velocity spectrum. The POD modes will be shown to be highly efficient in reconstructing the flowfield near the tip region where a large-scale coherent structure is present. An extension of the POD synthetic turbulence method to the time domain is also presented by means of a white noise filtering technique to allow the generation of time-varying velocity signals with the desired cross-spectral characteristics. The results show that both the one- and two-point statistics can be closely reproduced. The proposed frequency-domain POD synthetic turbulence method for fan broadband noise prediction for a realistic fan–OGV configuration is illustrated by the use of a frequency-domain linearized Navier–Stokes solver to predict the sound power radiation due to each vortical mode. Overall sound power levels at a number of discrete frequencies are predicted and compared against measured noise data. Agreement is found to be within the uncertainty of the noise sound power measurement.

하이브리드 난류 모델을 이용한 전류고정덕트 후류의 고정도 수치 해석

A hybrid turbulence model has developed by combining a sub-grid scale model using dynamic k equation in LES with k-ω SST model of RANS equation. To ascertain potential applicability of the hybrid turbulence model, fully developed turbulent channel flows at ReSUBτ/SUB=180 have been simulated of which computational domain has a top wall with coarse cells and a bottom wall with fine cells. The streamwise mean velocity and turbulent intensity profiles showed a good agreement with DNS data when using the hybrid model rather than using a single model in k-ω SST or dynamic k equation models. Computational simulations of turbulent flows around KVLCC2 with a pre-swirl duct have been mainly performed using the hybrid turbulence model. Compared to the results obtained from RANS simulation with k-ω SST model as well as LES with dynamic k equation SGS model, turbulent wakes of the duct in the present simulation using the hybrid turbulence model were very similar to that of LES. Also, the resistances acting on hull, rudder and duct in hybrid turbulence model were similar to those in RANS simulation whereas the viscous forces acting on the hull in LES had a significant error due to coarse cells inappropriate to the sub-grid scale model.

Identification of Aircraft Wake Vortex Based on VGGNet

The exploration of information for aircraft wake vortex enables us to obtain new knowledge of wake turbulence separation standards. Traditional manual methods cannot work satisfactorily for the identification of great number of wake vortex data with high accuracy. Fortunately, the LiDAR intensity data can be explained by integrating LiDAR products with the strategies of computer vision. To overcome the limitation of traditional manual methods, this paper is aimed at developing an automatic method to identify a given set of wake vortices from various aircrafts. The main innovation works are outlined as follows. (1) From the wake vortex data that consists of various aircrafts measured by Wind3D 6000 LiDAR, a grayscale dataset of wake flow is constructed to boost the deep learning model for identifying aircraft wake vortex. (2) Following this, we propose a new method for the identification of aircraft wake vortex by modifying the VGG16 network, providing binary classifications of uncertain behavior patterns for wake vortices. To evaluate the proposed identification model, performance evaluation was conducted on our dataset, where experimental results revealed the values of 0.984, 0.951, 0.959, and 0.955 in terms of accuracy, precision, recall, and F1-score, respectively.

Very-large-scale motions in the turbulent cylinder wake

This work studied the very-large-scale motions (VLSMs), which were first observed in wall-bounded flows, in a turbulent cylinder near wake using two experimental datasets from Chen et al. [“Three-dimensional vorticity, momentum and heat transport in a turbulent cylinder wake,” J. Fluid Mech. 809, 135–167 (2016)] and Tang et al. [“Secondary vortex street in the intermediate wake of a circular cylinder,” Exp. Fluids 59, 119 (2018)]. It is found that the premultiplied spectra of both the streamwise velocity and temperature fluctuations measured with hot and cold wires by Chen et al. [“Three-dimensional vorticity, momentum and heat transport in a turbulent cylinder wake,” J. Fluid Mech. 809, 135–167 (2016)] display a peak at a low wavenumber corresponding to a frequency of about 1/4 of that of the Kármán vortices in the flow. A proper orthogonal decomposition method was utilized to decompose the velocity field measured with particle image velocimetry by Tang et al. [“Secondary vortex street in the intermediate wake of a circular cylinder,” Exp. Fluids 59, 119 (2018)] into modes with different frequencies. A prolonged coherent structure with a wavelength of about four times the Kármán vortices is observed in the visualization of the energetic velocity modes with the same frequency of the spectral peak, which is consistent with the spectral data and confirms the existence of VLSMs in the wake.

Investigation of the wake flow of a simplified heavy vehicle with different aspect ratios

This study numerically investigates the effects of aspect ratios on the wake flow of a simplified ground transportation system (GTS) model using improved delayed detached-eddy simulation (IDDES) at a Reynolds number of 2.7 × 104. The aspect ratio Ra* ∈ [1.0, 2.0] is defined as the ratio of the height (H, variable) to the width (W, constant) of the GTS. The primary purpose of this work is to identify the relationship between the aspect ratio and the wake flow topology. The accuracy of the IDDES method has been validated by comparing the recirculation bubble configuration, vortex core position, velocity profiles, and aerodynamic drag of the baseline model (Ra* = 1.41) with those obtained from the previous large-eddy simulation study and the wind tunnel experiment. The results show that three typical flow states are observed in the near-wake region for various aspect-ratio cases. The aerodynamic drag increases by 4.60% and 2.06% for the aspect-ratio value equal to Ra* = 2.0 and Ra* = 1.8 (flow state II) and reduces by 6.75%, 7.37%, and 7.98% for the models with the aspect-ratio value of Ra* = 1.15, Ra* = 1.05, and Ra* = 1.0 (flow state III) compared to the aerodynamic drag of the baseline model with the aspect-ratio value of Ra* = 1.41 (flow state I). The dominant shedding frequency of the turbulent wake flow is identical for the aspect-ratio cases when the corresponding wake topology stays in the same flow state. The flow state acts as the substantial factor, which has an essential influence on the GTS's wake flow and its inducing aerodynamic response.

Scaling patch analysis of planar turbulent wakes

A scaling patch approach is used to investigate the proper scales in planar turbulent wakes. A proper scale for the mean axial flow is the well-known maximum velocity deficit Uref=U∞−Uctr, where U∞ is the free stream velocity and Uctr is the mean axial velocity at the wake centerline. From an admissible scaling of the mean continuity equation, a proper scale for the mean transverse flow is found as Vref=(dδ/dx)Uref, where dδ/dx is the growth rate of the wake width. From an admissible scaling of the mean momentum equation, a proper scale for the kinematic Reynolds shear stress is found as Ruv,ref=U∞Vref, which is a mixed scale of the free stream velocity and the mean transverse flow scale. Expressions are derived for the scaled mean transverse velocity and Reynolds shear stress in the far field of planar turbulent wakes. Using a Gaussian function for the mean axial velocity deficit, approximate functions for the scaled mean transverse velocity and Reynolds shear stress are developed and found to agree well with experimental and simulation data. This work reveals that the mean transverse flow, despite its small magnitude, plays an important role in the scaling and understanding of the planar turbulent wake.

Novel scaling laws in the nonequilibrium turbulent wake of a rotor and a fractal plate

This paper describes an experimental study in which a novel nonequilibrium self-similarity/self-preservation region is found to exist in the wakes of both a rotor and a fractal plate. In this novel nonequilibrium self-similarity region, the ratio of the mean flow length scale to the turbulence length scale and the ratio of the mean flow velocity scale to the turbulence velocity scale are not constant in the streamwise direction. However, in this region, the ratio of the mean flow time scale to the turbulence time scale is approximately constant in the streamwise direction. Using the simplified Reynolds-averaged equation of motion, new scaling laws are derived for this novel nonequilibrium self-similarity region, and these are confirmed by experimental measurements. Significant differences are observed between the rotor wake and fractal plate wake. The rotor wake reaches a self-similarity state much earlier than the fractal plate wake. A transition in the self-similarity state and scaling laws is found to occur in the rotor wake within the measurement region considered in the present study (3D–20D, where D is the effective diameter of the wake generator).

Quadratic approximation manifold for mitigating the Kolmogorov barrier in nonlinear projection-based model order reduction

A quadratic approximation manifold is presented for performing nonlinear, projection-based, model order reduction (PMOR). It constitutes a departure from the traditional affine subspace approximation that is aimed at mitigating the Kolmogorov barrier for nonlinear PMOR, particularly for convection-dominated transport problems. It builds on the data-driven approach underlying the traditional construction of projection-based reduced-order models (PROMs); is application-independent; is linearization-free; and therefore is robust for highly nonlinear problems. Most importantly, this approximation leads to quadratic PROMs that deliver the same accuracy as their traditional counterparts using however a much smaller dimension – typically, n2∼n1, where n2 and n1 denote the dimensions of the quadratic and traditional PROMs, respectively. The computational advantages of the proposed high-order approach to nonlinear PMOR over the traditional approach are highlighted for the detached-eddy simulation-based prediction of the Ahmed body turbulent wake flow, which is a popular CFD benchmark problem in the automotive industry. For a fixed accuracy level, these advantages include: a reduction of the total offline computational cost by a factor greater than five; a reduction of its online wall clock time by a factor greater than 32; and a reduction of the wall clock time of the underlying high-dimensional model by a factor greater than two orders of magnitude.

Wind Turbine Systematic Wake to Wake Analysis: Quantification of Turbulence and Statistical Analysis for Optimal Wind Farm Design

Through this work, we have analyzed wake to wake interactions between horizontal axis wind turbines located in line to each other. We have quantified wake interactions based on hot wire anemometric data and statistical correlations using a model wind farm fabricated inside a wind tunnel. The results of these measurements show that a high level of turbulent kinetic energy is generated at the region of intersection between rotor and stator wakes. Numerical models of wake interactions of wind turbines under varying turbulent inflow conditions using the actuator line technique and EllipSys3D Navier-Stokes solver were carried out to resolve dynamics of wake interactions. Our results showed good agreement with field measurements of wake deficit and turbulence intensity for inline and eccentric turbine arrangements.